{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime as dt\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.pyplot as ticker\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#지수표현식 없애기 \n",
    "pd.options.display.float_format = '{:.5f}'.format\n",
    "\n",
    "#되돌리기\n",
    "#pd.reset_option('display.float_format')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 한글 깨짐 해결\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.family'] ='Malgun Gothic'\n",
    "plt.rcParams['axes.unicode_minus'] =False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # 리샘플링\n",
    "# import pandas as pd\n",
    "\n",
    "# # 예시 데이터 로드 (실제 데이터 파일로 대체)\n",
    "# # df = pd.read_csv('your_data.csv')\n",
    "\n",
    "# # 대여월별로 그룹화하여 샘플링 비율 설정\n",
    "# sampling_ratio = 0.1  # 10% 비율로 샘플링\n",
    "\n",
    "# # 각 월별로 샘플링\n",
    "# sampled_df = df.groupby('대여월').apply(lambda x: x.sample(frac=sampling_ratio)).reset_index(drop=True)\n",
    "\n",
    "# # 결과 확인\n",
    "# print(sampled_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 0. 데이터 가져오기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_in = pd.read_csv('./따릉이 대여이력 정보/서울특별시 공공자전거 대여이력 정보_23하반기(전처리완_내).csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대여 대여소번호</th>\n",
       "      <th>대여 대여소명</th>\n",
       "      <th>반납대여소번호</th>\n",
       "      <th>반납대여소명</th>\n",
       "      <th>이용시간(분)</th>\n",
       "      <th>이용거리(M)</th>\n",
       "      <th>생년</th>\n",
       "      <th>성별</th>\n",
       "      <th>이용자종류</th>\n",
       "      <th>대여대여소ID</th>\n",
       "      <th>반납대여소ID</th>\n",
       "      <th>대여날짜</th>\n",
       "      <th>반납날짜</th>\n",
       "      <th>대여시간</th>\n",
       "      <th>반납시간</th>\n",
       "      <th>대여일자</th>\n",
       "      <th>대여요일</th>\n",
       "      <th>연령대</th>\n",
       "      <th>대여월</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2191</td>\n",
       "      <td>대학동주민센터</td>\n",
       "      <td>2183</td>\n",
       "      <td>동방1교</td>\n",
       "      <td>1</td>\n",
       "      <td>318.46000</td>\n",
       "      <td>1955</td>\n",
       "      <td>M</td>\n",
       "      <td>내국인</td>\n",
       "      <td>ST-2375</td>\n",
       "      <td>ST-1678</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Friday</td>\n",
       "      <td>60대</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   대여 대여소번호  대여 대여소명  반납대여소번호 반납대여소명  이용시간(분)   이용거리(M)    생년 성별 이용자종류  \\\n",
       "0      2191  대학동주민센터     2183   동방1교        1 318.46000  1955  M   내국인   \n",
       "\n",
       "   대여대여소ID  반납대여소ID        대여날짜        반납날짜  대여시간  반납시간  대여일자    대여요일  연령대  \\\n",
       "0  ST-2375  ST-1678  2023-12-01  2023-12-01     0     0     1  Friday  60대   \n",
       "\n",
       "   대여월  \n",
       "0   12  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 12334954 entries, 0 to 12334953\n",
      "Data columns (total 19 columns):\n",
      " #   Column    Non-Null Count     Dtype  \n",
      "---  ------    --------------     -----  \n",
      " 0   대여 대여소번호  12334954 non-null  int64  \n",
      " 1   대여 대여소명   12334954 non-null  object \n",
      " 2   반납대여소번호   12334954 non-null  int64  \n",
      " 3   반납대여소명    12334954 non-null  object \n",
      " 4   이용시간(분)   12334954 non-null  int64  \n",
      " 5   이용거리(M)   12334954 non-null  float64\n",
      " 6   생년        12334954 non-null  int64  \n",
      " 7   성별        12334954 non-null  object \n",
      " 8   이용자종류     12334954 non-null  object \n",
      " 9   대여대여소ID   12334954 non-null  object \n",
      " 10  반납대여소ID   12334954 non-null  object \n",
      " 11  대여날짜      12334954 non-null  object \n",
      " 12  반납날짜      12334954 non-null  object \n",
      " 13  대여시간      12334954 non-null  int64  \n",
      " 14  반납시간      12334954 non-null  int64  \n",
      " 15  대여일자      12334954 non-null  int64  \n",
      " 16  대여요일      12334954 non-null  object \n",
      " 17  연령대       12334954 non-null  object \n",
      " 18  대여월       12334954 non-null  int64  \n",
      "dtypes: float64(1), int64(8), object(10)\n",
      "memory usage: 1.7+ GB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "display(df_in.head(1))\n",
    "print(df_in.info(show_counts=True))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. 모델링 적용 전 전처리"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- df_in 필요없는 컬럼 1차 drop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대여 대여소번호</th>\n",
       "      <th>대여 대여소명</th>\n",
       "      <th>반납대여소번호</th>\n",
       "      <th>반납대여소명</th>\n",
       "      <th>이용시간(분)</th>\n",
       "      <th>이용거리(M)</th>\n",
       "      <th>생년</th>\n",
       "      <th>성별</th>\n",
       "      <th>이용자종류</th>\n",
       "      <th>대여대여소ID</th>\n",
       "      <th>반납대여소ID</th>\n",
       "      <th>대여날짜</th>\n",
       "      <th>반납날짜</th>\n",
       "      <th>대여시간</th>\n",
       "      <th>반납시간</th>\n",
       "      <th>대여일자</th>\n",
       "      <th>대여요일</th>\n",
       "      <th>연령대</th>\n",
       "      <th>대여월</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2191</td>\n",
       "      <td>대학동주민센터</td>\n",
       "      <td>2183</td>\n",
       "      <td>동방1교</td>\n",
       "      <td>1</td>\n",
       "      <td>318.46000</td>\n",
       "      <td>1955</td>\n",
       "      <td>M</td>\n",
       "      <td>내국인</td>\n",
       "      <td>ST-2375</td>\n",
       "      <td>ST-1678</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Friday</td>\n",
       "      <td>60대</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   대여 대여소번호  대여 대여소명  반납대여소번호 반납대여소명  이용시간(분)   이용거리(M)    생년 성별 이용자종류  \\\n",
       "0      2191  대학동주민센터     2183   동방1교        1 318.46000  1955  M   내국인   \n",
       "\n",
       "   대여대여소ID  반납대여소ID        대여날짜        반납날짜  대여시간  반납시간  대여일자    대여요일  연령대  \\\n",
       "0  ST-2375  ST-1678  2023-12-01  2023-12-01     0     0     1  Friday  60대   \n",
       "\n",
       "   대여월  \n",
       "0   12  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_in.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_in = df_in.drop(columns=['대여 대여소번호', '반납대여소번호', '대여 대여소명', '반납대여소명', '이용자종류'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>이용시간(분)</th>\n",
       "      <th>이용거리(M)</th>\n",
       "      <th>생년</th>\n",
       "      <th>성별</th>\n",
       "      <th>대여대여소ID</th>\n",
       "      <th>반납대여소ID</th>\n",
       "      <th>대여날짜</th>\n",
       "      <th>반납날짜</th>\n",
       "      <th>대여시간</th>\n",
       "      <th>반납시간</th>\n",
       "      <th>대여일자</th>\n",
       "      <th>대여요일</th>\n",
       "      <th>연령대</th>\n",
       "      <th>대여월</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>318.46000</td>\n",
       "      <td>1955</td>\n",
       "      <td>M</td>\n",
       "      <td>ST-2375</td>\n",
       "      <td>ST-1678</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>2023-12-01</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Friday</td>\n",
       "      <td>60대</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   이용시간(분)   이용거리(M)    생년 성별  대여대여소ID  반납대여소ID        대여날짜        반납날짜  대여시간  \\\n",
       "0        1 318.46000  1955  M  ST-2375  ST-1678  2023-12-01  2023-12-01     0   \n",
       "\n",
       "   반납시간  대여일자    대여요일  연령대  대여월  \n",
       "0     0     1  Friday  60대   12  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_in.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (1) 데이터 층화추출 (샘플링)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import pandas as pd\n",
    "# from sklearn.model_selection import StratifiedShuffleSplit\n",
    "\n",
    "# # 층화 추출\n",
    "# split = StratifiedShuffleSplit(n_splits=1, test_size=0.3, random_state=42)\n",
    "\n",
    "# # 연령대, 성별, 대여월을 기준으로 층화 추출\n",
    "# for train_index, test_index in split.split(df_in, df_in[['연령대', '성별', '대여월']]):\n",
    "#     stratified_sample = df_in.iloc[test_index]\n",
    "    \n",
    "# # 추출된 데이터 확인\n",
    "# print(stratified_sample.head())\n",
    "\n",
    "# # 결과를 파일로 저장 \n",
    "# stratified_sample.to_csv('./서울시 따릉이 내국인 데이터(층화추출1).csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         이용시간(분)    이용거리(M)    생년 성별  대여대여소ID  반납대여소ID        대여날짜  \\\n",
      "763943         6 1045.13000  1980  M  ST-1376  ST-2190  2023-12-13   \n",
      "506950         8 1599.36000  1995  M  ST-1337  ST-2379  2023-12-08   \n",
      "3342117       55 3131.66000  1971  F  ST-2800   ST-300  2023-11-27   \n",
      "5664292       17 3126.48000  1988  F   ST-493  ST-1086  2023-10-20   \n",
      "716201         4  794.69000  1998  M   ST-914  ST-2835  2023-12-12   \n",
      "\n",
      "               반납날짜  대여시간  반납시간  대여일자       대여요일  연령대  대여월  \n",
      "763943   2023-12-13    14    14    13  Wednesday  40대   12  \n",
      "506950   2023-12-08    20    20     8     Friday  20대   12  \n",
      "3342117  2023-11-27    14    15    27     Monday  50대   11  \n",
      "5664292  2023-10-20     8     8    20     Friday  30대   10  \n",
      "716201   2023-12-12    20    20    12    Tuesday  20대   12  \n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# train_test_split 층화 추출\n",
    "_, stratified_sample = train_test_split(df_in, test_size=0.5, stratify=df_in[['연령대', '성별', '대여월']], random_state=42)\n",
    "\n",
    "# 추출된 데이터 확인\n",
    "print(stratified_sample.head())\n",
    "\n",
    "# 결과를 파일로 저장 \n",
    "stratified_sample.to_csv('./서울시 따릉이 내국인 데이터(층화추출1).csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- df_ins : 층화추출 샘플링된 데이터 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_ins = pd.read_csv('./서울시 따릉이 내국인 데이터(층화추출1).csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>이용시간(분)</th>\n",
       "      <th>이용거리(M)</th>\n",
       "      <th>생년</th>\n",
       "      <th>성별</th>\n",
       "      <th>대여대여소ID</th>\n",
       "      <th>반납대여소ID</th>\n",
       "      <th>대여날짜</th>\n",
       "      <th>반납날짜</th>\n",
       "      <th>대여시간</th>\n",
       "      <th>반납시간</th>\n",
       "      <th>대여일자</th>\n",
       "      <th>대여요일</th>\n",
       "      <th>연령대</th>\n",
       "      <th>대여월</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>1045.13000</td>\n",
       "      <td>1980</td>\n",
       "      <td>M</td>\n",
       "      <td>ST-1376</td>\n",
       "      <td>ST-2190</td>\n",
       "      <td>2023-12-13</td>\n",
       "      <td>2023-12-13</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>13</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>40대</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   이용시간(분)    이용거리(M)    생년 성별  대여대여소ID  반납대여소ID        대여날짜        반납날짜  \\\n",
       "0        6 1045.13000  1980  M  ST-1376  ST-2190  2023-12-13  2023-12-13   \n",
       "\n",
       "   대여시간  반납시간  대여일자       대여요일  연령대  대여월  \n",
       "0    14    14    13  Wednesday  40대   12  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ins.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### (2) 따릉이대여소 마스터 정보 + df_in 조인\n",
    "- ll_join : '따릉이 마스터 정보' 전처리 완료한 데이터"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "ll_join = pd.read_csv('./서울시 따릉이대여소 마스터 정보(전처리).csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대여소_ID</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "      <th>구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ST-999</td>\n",
       "      <td>37.5334</td>\n",
       "      <td>126.8765</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   대여소_ID       위도        경도    구\n",
       "0  ST-999  37.5334  126.8765  양천구"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ll_join.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 대여대여소ID 기준 merge\n",
    "df_ins = pd.merge(df_ins, ll_join, how='left', left_on='대여대여소ID', right_on='대여소_ID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 반납대여소ID 기준 merge\n",
    "df_ins = pd.merge(df_ins, ll_join, how='left', left_on='반납대여소ID', right_on='대여소_ID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
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       "      <th>이용시간(분)</th>\n",
       "      <th>이용거리(M)</th>\n",
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       "      <th>대여날짜</th>\n",
       "      <th>반납날짜</th>\n",
       "      <th>대여시간</th>\n",
       "      <th>반납시간</th>\n",
       "      <th>...</th>\n",
       "      <th>연령대</th>\n",
       "      <th>대여월</th>\n",
       "      <th>대여소_ID_x</th>\n",
       "      <th>위도_x</th>\n",
       "      <th>경도_x</th>\n",
       "      <th>구_x</th>\n",
       "      <th>대여소_ID_y</th>\n",
       "      <th>위도_y</th>\n",
       "      <th>경도_y</th>\n",
       "      <th>구_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>1045.13000</td>\n",
       "      <td>1980</td>\n",
       "      <td>M</td>\n",
       "      <td>ST-1376</td>\n",
       "      <td>ST-2190</td>\n",
       "      <td>2023-12-13</td>\n",
       "      <td>2023-12-13</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>...</td>\n",
       "      <td>40대</td>\n",
       "      <td>12</td>\n",
       "      <td>ST-1376</td>\n",
       "      <td>37.54446</td>\n",
       "      <td>126.97239</td>\n",
       "      <td>용산구</td>\n",
       "      <td>ST-2190</td>\n",
       "      <td>37.55155</td>\n",
       "      <td>126.97686</td>\n",
       "      <td>용산구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   이용시간(분)    이용거리(M)    생년 성별  대여대여소ID  반납대여소ID        대여날짜        반납날짜  \\\n",
       "0        6 1045.13000  1980  M  ST-1376  ST-2190  2023-12-13  2023-12-13   \n",
       "\n",
       "   대여시간  반납시간  ...  연령대 대여월 대여소_ID_x     위도_x      경도_x  구_x  대여소_ID_y  \\\n",
       "0    14    14  ...  40대  12  ST-1376 37.54446 126.97239  용산구   ST-2190   \n",
       "\n",
       "      위도_y      경도_y  구_y  \n",
       "0 37.55155 126.97686  용산구  \n",
       "\n",
       "[1 rows x 22 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ins.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 필요없는 컬럼 drop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_ins = df_ins.drop(columns=['대여소_ID_y'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "      <th>대여시간</th>\n",
       "      <th>반납시간</th>\n",
       "      <th>...</th>\n",
       "      <th>대여요일</th>\n",
       "      <th>연령대</th>\n",
       "      <th>대여월</th>\n",
       "      <th>대여소_ID_x</th>\n",
       "      <th>위도_x</th>\n",
       "      <th>경도_x</th>\n",
       "      <th>구_x</th>\n",
       "      <th>위도_y</th>\n",
       "      <th>경도_y</th>\n",
       "      <th>구_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>1045.13000</td>\n",
       "      <td>1980</td>\n",
       "      <td>M</td>\n",
       "      <td>ST-1376</td>\n",
       "      <td>ST-2190</td>\n",
       "      <td>2023-12-13</td>\n",
       "      <td>2023-12-13</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>...</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>40대</td>\n",
       "      <td>12</td>\n",
       "      <td>ST-1376</td>\n",
       "      <td>37.54446</td>\n",
       "      <td>126.97239</td>\n",
       "      <td>용산구</td>\n",
       "      <td>37.55155</td>\n",
       "      <td>126.97686</td>\n",
       "      <td>용산구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   이용시간(분)    이용거리(M)    생년 성별  대여대여소ID  반납대여소ID        대여날짜        반납날짜  \\\n",
       "0        6 1045.13000  1980  M  ST-1376  ST-2190  2023-12-13  2023-12-13   \n",
       "\n",
       "   대여시간  반납시간  ...       대여요일  연령대 대여월  대여소_ID_x     위도_x      경도_x  구_x  \\\n",
       "0    14    14  ...  Wednesday  40대  12   ST-1376 37.54446 126.97239  용산구   \n",
       "\n",
       "      위도_y      경도_y  구_y  \n",
       "0 37.55155 126.97686  용산구  \n",
       "\n",
       "[1 rows x 21 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ins.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_ins.columns = ['이용시간(분)', '이용거리(M)', '생년', '성별', '대여대여소ID', '반납대여소ID', '대여날짜', '반납날짜', '대여시간', '반납시간', '대여일자', '대여요일', '연령대','대여월', '대여소ID', '대여위도', '대여경도', '대여구', '반납위도', '반납경도', '반납구']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "      <th>대여날짜</th>\n",
       "      <th>반납날짜</th>\n",
       "      <th>대여시간</th>\n",
       "      <th>반납시간</th>\n",
       "      <th>...</th>\n",
       "      <th>대여요일</th>\n",
       "      <th>연령대</th>\n",
       "      <th>대여월</th>\n",
       "      <th>대여소ID</th>\n",
       "      <th>대여위도</th>\n",
       "      <th>대여경도</th>\n",
       "      <th>대여구</th>\n",
       "      <th>반납위도</th>\n",
       "      <th>반납경도</th>\n",
       "      <th>반납구</th>\n",
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       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>1045.13000</td>\n",
       "      <td>1980</td>\n",
       "      <td>M</td>\n",
       "      <td>ST-1376</td>\n",
       "      <td>ST-2190</td>\n",
       "      <td>2023-12-13</td>\n",
       "      <td>2023-12-13</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>...</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>40대</td>\n",
       "      <td>12</td>\n",
       "      <td>ST-1376</td>\n",
       "      <td>37.54446</td>\n",
       "      <td>126.97239</td>\n",
       "      <td>용산구</td>\n",
       "      <td>37.55155</td>\n",
       "      <td>126.97686</td>\n",
       "      <td>용산구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   이용시간(분)    이용거리(M)    생년 성별  대여대여소ID  반납대여소ID        대여날짜        반납날짜  \\\n",
       "0        6 1045.13000  1980  M  ST-1376  ST-2190  2023-12-13  2023-12-13   \n",
       "\n",
       "   대여시간  반납시간  ...       대여요일  연령대 대여월    대여소ID     대여위도      대여경도  대여구  \\\n",
       "0    14    14  ...  Wednesday  40대  12  ST-1376 37.54446 126.97239  용산구   \n",
       "\n",
       "      반납위도      반납경도  반납구  \n",
       "0 37.55155 126.97686  용산구  \n",
       "\n",
       "[1 rows x 21 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ins.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# csv 파일로 저장\n",
    "#df_ins.to_csv('서울시 따릉이 내국인 데이터(층화1, 마스터조인).csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 파일 저장 확인\n",
    "df_ins = pd.read_csv('./서울시 따릉이 내국인 데이터(층화1, 마스터조인).csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>성별</th>\n",
       "      <th>대여대여소ID</th>\n",
       "      <th>반납대여소ID</th>\n",
       "      <th>대여날짜</th>\n",
       "      <th>반납날짜</th>\n",
       "      <th>대여시간</th>\n",
       "      <th>반납시간</th>\n",
       "      <th>...</th>\n",
       "      <th>대여요일</th>\n",
       "      <th>연령대</th>\n",
       "      <th>대여월</th>\n",
       "      <th>대여소ID</th>\n",
       "      <th>대여위도</th>\n",
       "      <th>대여경도</th>\n",
       "      <th>대여구</th>\n",
       "      <th>반납위도</th>\n",
       "      <th>반납경도</th>\n",
       "      <th>반납구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>1045.13000</td>\n",
       "      <td>1980</td>\n",
       "      <td>M</td>\n",
       "      <td>ST-1376</td>\n",
       "      <td>ST-2190</td>\n",
       "      <td>2023-12-13</td>\n",
       "      <td>2023-12-13</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>...</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>40대</td>\n",
       "      <td>12</td>\n",
       "      <td>ST-1376</td>\n",
       "      <td>37.54446</td>\n",
       "      <td>126.97239</td>\n",
       "      <td>용산구</td>\n",
       "      <td>37.55155</td>\n",
       "      <td>126.97686</td>\n",
       "      <td>용산구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   이용시간(분)    이용거리(M)    생년 성별  대여대여소ID  반납대여소ID        대여날짜        반납날짜  \\\n",
       "0        6 1045.13000  1980  M  ST-1376  ST-2190  2023-12-13  2023-12-13   \n",
       "\n",
       "   대여시간  반납시간  ...       대여요일  연령대 대여월    대여소ID     대여위도      대여경도  대여구  \\\n",
       "0    14    14  ...  Wednesday  40대  12  ST-1376 37.54446 126.97239  용산구   \n",
       "\n",
       "      반납위도      반납경도  반납구  \n",
       "0 37.55155 126.97686  용산구  \n",
       "\n",
       "[1 rows x 21 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ins.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (3) 전처리\n",
    "- (연령대) 10대, 20대 이런 데이터 >> 10, 20 이렇게 바꾸기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# '기타'를 0으로 치환\n",
    "df_ins['연령대'] = df_ins['연령대'].replace('기타', '0')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>이용시간(분)</th>\n",
       "      <th>이용거리(M)</th>\n",
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       "      <th>성별</th>\n",
       "      <th>대여대여소ID</th>\n",
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       "      <th>반납날짜</th>\n",
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       "      <th>대여월</th>\n",
       "      <th>대여위도</th>\n",
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       "      <td>6</td>\n",
       "      <td>1045.13000</td>\n",
       "      <td>1980</td>\n",
       "      <td>M</td>\n",
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       "      <td>2023-12-13</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>13</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>40</td>\n",
       "      <td>12</td>\n",
       "      <td>37.54446</td>\n",
       "      <td>126.97239</td>\n",
       "      <td>용산구</td>\n",
       "      <td>37.55155</td>\n",
       "      <td>126.97686</td>\n",
       "      <td>용산구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   이용시간(분)    이용거리(M)    생년 성별  대여대여소ID  반납대여소ID        대여날짜        반납날짜  \\\n",
       "0        6 1045.13000  1980  M  ST-1376  ST-2190  2023-12-13  2023-12-13   \n",
       "\n",
       "   대여시간  반납시간  대여일자       대여요일  연령대  대여월     대여위도      대여경도  대여구     반납위도  \\\n",
       "0    14    14    13  Wednesday   40   12 37.54446 126.97239  용산구 37.55155   \n",
       "\n",
       "       반납경도  반납구  \n",
       "0 126.97686  용산구  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ins.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 성별 더미변수화"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 성별 더미변수화\n",
    "df_ins = pd.get_dummies(df_ins, columns=['성별'], prefix='성별', drop_first=True)\n",
    "# True/False를 0/1로 변환\n",
    "df_ins['성별_M'] = df_ins['성별_M'].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "      <th>이용시간(분)</th>\n",
       "      <th>이용거리(M)</th>\n",
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       "      <th>대여시간</th>\n",
       "      <th>반납시간</th>\n",
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       "      <th>연령대</th>\n",
       "      <th>대여월</th>\n",
       "      <th>대여위도</th>\n",
       "      <th>대여경도</th>\n",
       "      <th>대여구</th>\n",
       "      <th>반납위도</th>\n",
       "      <th>반납경도</th>\n",
       "      <th>반납구</th>\n",
       "      <th>성별_M</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
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       "      <td>14</td>\n",
       "      <td>13</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>40</td>\n",
       "      <td>12</td>\n",
       "      <td>37.54446</td>\n",
       "      <td>126.97239</td>\n",
       "      <td>용산구</td>\n",
       "      <td>37.55155</td>\n",
       "      <td>126.97686</td>\n",
       "      <td>용산구</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   이용시간(분)    이용거리(M)    생년  대여대여소ID  반납대여소ID        대여날짜        반납날짜  대여시간  \\\n",
       "0        6 1045.13000  1980  ST-1376  ST-2190  2023-12-13  2023-12-13    14   \n",
       "\n",
       "   반납시간  대여일자       대여요일  연령대  대여월     대여위도      대여경도  대여구     반납위도      반납경도  \\\n",
       "0    14    13  Wednesday   40   12 37.54446 126.97239  용산구 37.55155 126.97686   \n",
       "\n",
       "   반납구  성별_M  \n",
       "0  용산구     1  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ins.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 대여시간, 반납시간 0 >> 24로 바꾸기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_ins.loc[df_ins['대여시간'] == 0, '대여시간'] = 24\n",
    "df_ins.loc[df_ins['반납시간'] == 0, '반납시간'] = 24"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "      <th>대여위도</th>\n",
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       "      <th>대여구</th>\n",
       "      <th>반납위도</th>\n",
       "      <th>반납경도</th>\n",
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       "      <th>0</th>\n",
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       "      <td>37.54446</td>\n",
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       "      <td>37.55155</td>\n",
       "      <td>126.97686</td>\n",
       "      <td>용산구</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   이용시간(분)  이용거리(M)    생년  대여대여소ID  반납대여소ID        대여날짜        반납날짜  대여시간  \\\n",
       "0        6  1045.13  1980  ST-1376  ST-2190  2023-12-13  2023-12-13    14   \n",
       "\n",
       "   반납시간  대여일자       대여요일  연령대  대여월      대여위도       대여경도  대여구      반납위도  \\\n",
       "0    14    13  Wednesday   40   12  37.54446  126.97239  용산구  37.55155   \n",
       "\n",
       "        반납경도  반납구  성별_M  \n",
       "0  126.97686  용산구     1  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ins.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (4) 대여구, 반납구 간단 EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='count', ylabel='대여구'>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tmp = df_ins.groupby('대여구')['대여구'].value_counts().reset_index().sort_values(by='count', ascending=False)\n",
    "sns.barplot(data=tmp, y='대여구', x='count', color='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='count', ylabel='반납구'>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tmp2 = df_ins.groupby('반납구')['반납구'].value_counts().reset_index().sort_values(by='count', ascending=False)\n",
    "sns.barplot(data=tmp2, y='반납구', x='count', color='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (5) 대여구, 반납구 전처리"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1_ins = df_ins.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 대여구의 강남구와 반납구의 강남구가 동일한 숫자로 라벨링 되도록 학습\n",
    "import pandas as pd\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "# LabelEncoder 생성 및 학습\n",
    "le = LabelEncoder()\n",
    "combined_values = pd.concat([df1_ins['대여구'], df1_ins['반납구']])\n",
    "le.fit(combined_values)\n",
    "\n",
    "# 대여구와 반납구 컬럼 변환\n",
    "df1_ins['대여구_e'] = le.transform(df1_ins['대여구'])\n",
    "df1_ins['반납구_e'] = le.transform(df1_ins['반납구'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>이용시간(분)</th>\n",
       "      <th>이용거리(M)</th>\n",
       "      <th>생년</th>\n",
       "      <th>대여대여소ID</th>\n",
       "      <th>반납대여소ID</th>\n",
       "      <th>대여날짜</th>\n",
       "      <th>반납날짜</th>\n",
       "      <th>대여시간</th>\n",
       "      <th>반납시간</th>\n",
       "      <th>대여일자</th>\n",
       "      <th>...</th>\n",
       "      <th>대여월</th>\n",
       "      <th>대여위도</th>\n",
       "      <th>대여경도</th>\n",
       "      <th>대여구</th>\n",
       "      <th>반납위도</th>\n",
       "      <th>반납경도</th>\n",
       "      <th>반납구</th>\n",
       "      <th>성별_M</th>\n",
       "      <th>대여구_e</th>\n",
       "      <th>반납구_e</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>1045.13</td>\n",
       "      <td>1980</td>\n",
       "      <td>ST-1376</td>\n",
       "      <td>ST-2190</td>\n",
       "      <td>2023-12-13</td>\n",
       "      <td>2023-12-13</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>13</td>\n",
       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>37.54446</td>\n",
       "      <td>126.97239</td>\n",
       "      <td>용산구</td>\n",
       "      <td>37.55155</td>\n",
       "      <td>126.97686</td>\n",
       "      <td>용산구</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   이용시간(분)  이용거리(M)    생년  대여대여소ID  반납대여소ID        대여날짜        반납날짜  대여시간  \\\n",
       "0        6  1045.13  1980  ST-1376  ST-2190  2023-12-13  2023-12-13    14   \n",
       "\n",
       "   반납시간  대여일자  ... 대여월      대여위도       대여경도  대여구      반납위도       반납경도  반납구  \\\n",
       "0    14    13  ...  12  37.54446  126.97239  용산구  37.55155  126.97686  용산구   \n",
       "\n",
       "   성별_M 대여구_e  반납구_e  \n",
       "0     1    20     20  \n",
       "\n",
       "[1 rows x 22 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 결과 출력\n",
    "df1_ins.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- null값 제거"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# null값이 있어서 dropna 해줌\n",
    "df1_ins = df1_ins.dropna(subset=['대여구', '반납구', '대여구_e', '반납구_e'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 각 구에 부여된 label 확인"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대여구</th>\n",
       "      <th>대여구_encoded</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>강남구</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>강동구</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>강북구</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>강서구</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>관악구</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>광진구</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>구로구</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>금천구</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>노원구</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>도봉구</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>동대문구</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>동작구</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>마포구</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>서대문구</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>서초구</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>성동구</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>성북구</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>송파구</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>양천구</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>영등포구</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>용산구</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>은평구</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>종로구</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>중구</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>중랑구</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      대여구  대여구_encoded\n",
       "6     강남구            0\n",
       "3     강동구            1\n",
       "65    강북구            2\n",
       "16    강서구            3\n",
       "1     관악구            4\n",
       "7     광진구            5\n",
       "14    구로구            6\n",
       "36    금천구            7\n",
       "4     노원구            8\n",
       "118   도봉구            9\n",
       "15   동대문구           10\n",
       "17    동작구           11\n",
       "21    마포구           12\n",
       "9    서대문구           13\n",
       "53    서초구           14\n",
       "88    성동구           15\n",
       "10    성북구           16\n",
       "11    송파구           17\n",
       "8     양천구           18\n",
       "2    영등포구           19\n",
       "0     용산구           20\n",
       "39    은평구           21\n",
       "12    종로구           22\n",
       "78     중구           23\n",
       "38    중랑구           24"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 각 구에 어떤 lebel이 붙었는지 확인\n",
    "df1_ins[['대여구', '대여구_e']].drop_duplicates().sort_values(by='대여구_e')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 대여구, 반납구 컬럼은 지우기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1_ins = df1_ins.drop(columns=['대여구', '반납구'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>이용시간(분)</th>\n",
       "      <th>이용거리(M)</th>\n",
       "      <th>생년</th>\n",
       "      <th>대여대여소ID</th>\n",
       "      <th>반납대여소ID</th>\n",
       "      <th>대여날짜</th>\n",
       "      <th>반납날짜</th>\n",
       "      <th>대여시간</th>\n",
       "      <th>반납시간</th>\n",
       "      <th>대여일자</th>\n",
       "      <th>대여요일</th>\n",
       "      <th>연령대</th>\n",
       "      <th>대여월</th>\n",
       "      <th>대여위도</th>\n",
       "      <th>대여경도</th>\n",
       "      <th>반납위도</th>\n",
       "      <th>반납경도</th>\n",
       "      <th>성별_M</th>\n",
       "      <th>대여구_e</th>\n",
       "      <th>반납구_e</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>1045.13</td>\n",
       "      <td>1980</td>\n",
       "      <td>ST-1376</td>\n",
       "      <td>ST-2190</td>\n",
       "      <td>2023-12-13</td>\n",
       "      <td>2023-12-13</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>13</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>40</td>\n",
       "      <td>12</td>\n",
       "      <td>37.54446</td>\n",
       "      <td>126.97239</td>\n",
       "      <td>37.55155</td>\n",
       "      <td>126.97686</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   이용시간(분)  이용거리(M)    생년  대여대여소ID  반납대여소ID        대여날짜        반납날짜  대여시간  \\\n",
       "0        6  1045.13  1980  ST-1376  ST-2190  2023-12-13  2023-12-13    14   \n",
       "\n",
       "   반납시간  대여일자       대여요일  연령대  대여월      대여위도       대여경도      반납위도       반납경도  \\\n",
       "0    14    13  Wednesday   40   12  37.54446  126.97239  37.55155  126.97686   \n",
       "\n",
       "   성별_M  대여구_e  반납구_e  \n",
       "0     1     20     20  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_ins.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df1_ins.to_csv('./(모델링_내2) 따릉이 대여이력(23.08~12).csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1_ins = pd.read_csv('./(모델링_내2) 따릉이 대여이력(23.08~12).csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. 특성 추출"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "일 평균 방문 고객 수   \n",
    "남성 방문고객 비율   \n",
    "남성 대비 여성 방문고객 비율  \n",
    "주말-주중 일평균 방문고객 비율  \n",
    "점심시간 이후 방문고객 비율  \n",
    "새벽 방문고객 비율   \n",
    "주중 청년고객 비율  \n",
    "주말 청년고객 비율  \n",
    "주중 장년고객 비율   \n",
    "주말 장년고객 비율    \n",
    "주중 출근시간대 방문고객 비율\n",
    "주중 퇴근시간대 방문고객 비율  \n",
    "주중 해당 대여구 고객 비율  \n",
    "주말 해당 대여구 고객 비율\n",
    "주중 해당 반납구 고객 비율  \n",
    "주말 해당 반납구 고객 비율\n",
    "대여소별 평균 연령대  \n",
    "청년고객 비율  \n",
    "장년고객 비율  \n",
    "특정 시간대의 대여 횟수  \n",
    "특정 요일의 대여 횟수  \n",
    "평균 이동거리\n",
    "평균 이동시간  \n",
    "주중 평균 체류시간 대비 야간 체류시간 비  \n",
    "주말 평균 체류시간 대비 야간 체류시간 비  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 1트"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import pandas as pd\n",
    "# from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "# df1_ins['대여일자'] = pd.to_datetime(df1_ins['대여일자'])\n",
    "\n",
    "# # 주중/주말 구분\n",
    "# df1_ins['주말여부'] = df1_ins['대여요일'].isin(['Saturday', 'Sunday'])\n",
    "\n",
    "# # 시간대 구분\n",
    "# df1_ins['점심시간'] = (df1_ins['대여시간'] >= 12) & (df1_ins['대여시간'] < 14)\n",
    "# df1_ins['새벽시간'] = (df1_ins['대여시간'] >= 0) & (df1_ins['대여시간'] < 6)\n",
    "# df1_ins['출근시간'] = (df1_ins['대여시간'] >= 7) & (df1_ins['대여시간'] < 9)\n",
    "# df1_ins['퇴근시간'] = (df1_ins['대여시간'] >= 17) & (df1_ins['대여시간'] < 19)\n",
    "# df1_ins['야간시간'] = (df1_ins['대여시간'] >= 19) & (df1_ins['대여시간'] < 24)\n",
    "\n",
    "# # 대여대여소ID 기준 그룹화하여 통계 피처 생성\n",
    "# grouped = df1_ins.groupby('대여대여소ID').agg({\n",
    "#     '대여일자': 'count',  # 총 대여 횟수\n",
    "#     '성별_M': 'mean',  # 남성 방문고객 비율\n",
    "#     '이용시간(분)': ['mean', 'std'],  # 평균 이용시간 및 표준편차\n",
    "#     '이용거리(M)': ['mean', 'std'],  # 평균 이용거리 및 표준편차\n",
    "#     '주말여부': 'mean',  # 주말 대여 비율\n",
    "#     '점심시간': 'mean',  # 점심시간 대여 비율\n",
    "#     '새벽시간': 'mean',  # 새벽 대여 비율\n",
    "#     '출근시간': 'mean',  # 출근 시간대 대여 비율\n",
    "#     '퇴근시간': 'mean',  # 퇴근 시간대 대여 비율\n",
    "#     '야간시간': 'mean'  # 야간 대여 비율\n",
    "# }).reset_index()\n",
    "\n",
    "# # 컬럼 이름 변경\n",
    "# grouped.columns = [\n",
    "#     '대여대여소ID', '총대여횟수', '남성고객비율', '평균이용시간', '이용시간표준편차',\n",
    "#     '평균이용거리', '이용거리표준편차', '주말대여비율', '점심시간대여비율',\n",
    "#     '새벽대여비율', '출근시간대여비율', '퇴근시간대여비율', '야간대여비율'\n",
    "# ]\n",
    "\n",
    "# # 주중/주말 연령대별 고객 비율 계산 함수\n",
    "# def calculate_ratios(df):\n",
    "#     weekday_data = df[~df['주말여부']]\n",
    "#     weekend_data = df[df['주말여부']]\n",
    "    \n",
    "#     ratios = {\n",
    "#         '주중청소년고객비율': (weekday_data['연령대'] == 10).mean(),\n",
    "#         '주말청소년고객비율': (weekend_data['연령대'] == 10).mean(),\n",
    "#         '주중청년고객비율': ((weekday_data['연령대'] == 20) | (weekday_data['연령대'] == 30)).mean(),\n",
    "#         '주말청년고객비율': ((weekend_data['연령대'] == 20) | (weekend_data['연령대'] == 30)).mean(),\n",
    "#         '주중장년고객비율': ((weekday_data['연령대'] == 40) | (weekday_data['연령대'] == 50)).mean(),\n",
    "#         '주말장년고객비율': ((weekend_data['연령대'] == 40) | (weekend_data['연령대'] == 50)).mean(),\n",
    "#         '주중노인고객비율': ((weekday_data['연령대'] == 60) | (weekday_data['연령대'] == 70)).mean(),\n",
    "#         '주말노인고객비율': ((weekend_data['연령대'] == 60) | (weekend_data['연령대'] == 70)).mean()\n",
    "#     }\n",
    "#     return pd.Series(ratios)\n",
    "\n",
    "# # 그룹화하여 추가 피처 계산\n",
    "# additional_features = df1_ins.groupby('대여대여소ID').apply(calculate_ratios).reset_index()\n",
    "# grouped = pd.merge(grouped, additional_features, on='대여대여소ID')\n",
    "\n",
    "# print(grouped)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 2트(오후시간대 포함)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      대여대여소ID  총대여횟수    남성고객비율     평균이용시간       평균이용거리    주말대여비율    점심대여비율  \\\n",
      "0       ST-10   2764  0.641823  30.027135  2896.118784  0.308249  0.099855   \n",
      "1     ST-1000   3074  0.625895  19.268705  2427.495573  0.265777  0.093689   \n",
      "2     ST-1002   5895  0.658863  20.319932  2289.621218  0.298049  0.087532   \n",
      "3     ST-1003   1914  0.641066  17.774817  2121.170564  0.269592  0.096134   \n",
      "4     ST-1004   1543  0.736876  15.806870  1868.960045  0.288399  0.088788   \n",
      "...       ...    ...       ...        ...          ...       ...       ...   \n",
      "2748   ST-993   2288  0.677885  18.303759  1884.028086  0.255682  0.092220   \n",
      "2749   ST-994   4450  0.640225  20.783820  2037.581463  0.224045  0.087865   \n",
      "2750   ST-995    467  0.698073  18.715203  2259.101649  0.241970  0.100642   \n",
      "2751   ST-996   1075  0.709767  20.463256  1966.129544  0.279070  0.083721   \n",
      "2752   ST-997   6979  0.640923  18.015618  1877.363578  0.252472  0.082533   \n",
      "\n",
      "        오후대여비율    새벽대여비율  출근시간대여비율  퇴근시간대여비율    야간대여비율  주중청소년고객비율  주말청소년고객비율  \\\n",
      "0     0.345514  0.099493  0.045224  0.184877  0.295224   0.020397   0.042254   \n",
      "1     0.317502  0.036760  0.307417  0.155172  0.145413   0.266726   0.226438   \n",
      "2     0.333673  0.013740  0.079389  0.233927  0.318405   0.178105   0.269209   \n",
      "3     0.312435  0.060084  0.142111  0.166667  0.286311   0.129471   0.129845   \n",
      "4     0.303305  0.038885  0.263772  0.149060  0.207388   0.495446   0.400000   \n",
      "...        ...       ...       ...       ...       ...        ...        ...   \n",
      "2748  0.335227  0.042832  0.194493  0.152535  0.208479   0.134469   0.174359   \n",
      "2749  0.310337  0.014607  0.076854  0.276854  0.293708   0.063713   0.149448   \n",
      "2750  0.357602  0.008565  0.233405  0.175589  0.211991   0.093220   0.132743   \n",
      "2751  0.324651  0.097674  0.042791  0.236279  0.247442   0.117419   0.126667   \n",
      "2752  0.346611  0.028084  0.260496  0.156183  0.178106   0.278896   0.267310   \n",
      "\n",
      "      주중청년고객비율  주말청년고객비율  주중장년고객비율  주말장년고객비율  주중노인고객비율  주말노인고객비율  \n",
      "0     0.770397  0.803991  0.191423  0.142019  0.017782  0.011737  \n",
      "1     0.330970  0.432069  0.364643  0.291310  0.037661  0.048960  \n",
      "2     0.431851  0.402390  0.346786  0.308480  0.040841  0.018782  \n",
      "3     0.532904  0.476744  0.304006  0.331395  0.032904  0.062016  \n",
      "4     0.262295  0.303371  0.218579  0.265169  0.023679  0.031461  \n",
      "...        ...       ...       ...       ...       ...       ...  \n",
      "2748  0.494422  0.521368  0.328244  0.251282  0.042866  0.052991  \n",
      "2749  0.519548  0.535607  0.387200  0.292879  0.029540  0.022066  \n",
      "2750  0.437853  0.486726  0.392655  0.300885  0.076271  0.079646  \n",
      "2751  0.540645  0.570000  0.269677  0.256667  0.072258  0.046667  \n",
      "2752  0.338700  0.360953  0.345793  0.319523  0.033736  0.048241  \n",
      "\n",
      "[2753 rows x 20 columns]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\LG\\AppData\\Local\\Temp\\ipykernel_9436\\3418061814.py:57: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n",
      "  additional_features = df1_ins.groupby('대여대여소ID').apply(calculate_ratios).reset_index()\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "df1_ins['대여일자'] = pd.to_datetime(df1_ins['대여일자'])\n",
    "\n",
    "# 주중/주말 구분\n",
    "df1_ins['주말여부'] = df1_ins['대여요일'].isin(['Saturday', 'Sunday'])\n",
    "\n",
    "# 시간대 구분\n",
    "df1_ins['새벽시간'] = (df1_ins['대여시간'] >= 0) & (df1_ins['대여시간'] < 6)\n",
    "df1_ins['출근시간'] = (df1_ins['대여시간'] >= 7) & (df1_ins['대여시간'] < 10)\n",
    "df1_ins['오전시간'] = (df1_ins['대여시간'] >= 10) & (df1_ins['대여시간'] < 12)\n",
    "df1_ins['점심시간'] = (df1_ins['대여시간'] >= 12) & (df1_ins['대여시간'] < 14)\n",
    "df1_ins['오후시간'] = (df1_ins['대여시간'] >= 14) & (df1_ins['대여시간'] < 17)\n",
    "df1_ins['퇴근시간'] = (df1_ins['대여시간'] >= 17) & (df1_ins['대여시간'] < 19)\n",
    "df1_ins['야간시간'] = (df1_ins['대여시간'] >= 19) & (df1_ins['대여시간'] < 24)\n",
    "\n",
    "# 대여대여소ID 기준 그룹화하여 통계 피처 생성\n",
    "grouped = df1_ins.groupby('대여대여소ID').agg({\n",
    "    '대여일자': 'count',  # 총 대여 횟수\n",
    "    '성별_M': 'mean',  # 남성 방문고객 비율\n",
    "    '이용시간(분)': 'mean',  # 평균 이용시간\n",
    "    '이용거리(M)' : 'mean', # 평균 이용거리\n",
    "    '주말여부': 'mean',  # 주말 대여 비율\n",
    "    '새벽시간': 'mean',  # 새벽 대여 비율\n",
    "    '출근시간': 'mean',  # 출근 시간대 대여 비율\n",
    "    '오전시간': 'mean',  # 오전 대여 비율\n",
    "    '점심시간': 'mean',  # 점심시간 대여 비율\n",
    "    '오후시간': 'mean', # 오후시간 대여 비율\n",
    "    '퇴근시간': 'mean',  # 퇴근 시간대 대여 비율\n",
    "    '야간시간': 'mean',  # 야간 대여 비율\n",
    "}).reset_index()\n",
    "\n",
    "# 컬럼 이름 변경\n",
    "grouped.columns = [\n",
    "    '대여대여소ID', '총대여횟수', '남성고객비율', '평균이용시간', '평균이용거리',\n",
    "    '주말대여비율', '새벽대여비율', '출근시간대여비율', '오전대여비율', '점심대여비율', '오후대여비율',\n",
    "    '퇴근시간대여비율', '야간대여비율'\n",
    "]\n",
    "\n",
    "# 주중/주말 연령대별 고객 비율 계산 함수\n",
    "def calculate_ratios(df):\n",
    "    weekday_data = df[~df['주말여부']]\n",
    "    weekend_data = df[df['주말여부']]\n",
    "    \n",
    "    ratios = {\n",
    "        '주중청소년고객비율': (weekday_data['연령대'] == 10).mean(),\n",
    "        '주말청소년고객비율': (weekend_data['연령대'] == 10).mean(),\n",
    "        '주중청년고객비율': ((weekday_data['연령대'] == 20) | (weekday_data['연령대'] == 30)).mean(),\n",
    "        '주말청년고객비율': ((weekend_data['연령대'] == 20) | (weekend_data['연령대'] == 30)).mean(),\n",
    "        '주중장년고객비율': ((weekday_data['연령대'] == 40) | (weekday_data['연령대'] == 50)).mean(),\n",
    "        '주말장년고객비율': ((weekend_data['연령대'] == 40) | (weekend_data['연령대'] == 50)).mean(),\n",
    "        '주중노인고객비율': ((weekday_data['연령대'] == 60) | (weekday_data['연령대'] == 70)).mean(),\n",
    "        '주말노인고객비율': ((weekend_data['연령대'] == 60) | (weekend_data['연령대'] == 70)).mean()\n",
    "    }\n",
    "    return pd.Series(ratios)\n",
    "\n",
    "# 그룹화하여 추가 피처 계산\n",
    "additional_features = df1_ins.groupby('대여대여소ID').apply(calculate_ratios).reset_index()\n",
    "grouped = pd.merge(grouped, additional_features, on='대여대여소ID')\n",
    "\n",
    "print(grouped)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. k-means 군집분석"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "grouped = grouped.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 2752 entries, 0 to 2752\n",
      "Data columns (total 20 columns):\n",
      " #   Column     Non-Null Count  Dtype  \n",
      "---  ------     --------------  -----  \n",
      " 0   대여대여소ID    2752 non-null   object \n",
      " 1   총대여횟수      2752 non-null   int64  \n",
      " 2   남성고객비율     2752 non-null   float64\n",
      " 3   평균이용시간     2752 non-null   float64\n",
      " 4   평균이용거리     2752 non-null   float64\n",
      " 5   주말대여비율     2752 non-null   float64\n",
      " 6   점심시간대여비율   2752 non-null   float64\n",
      " 7   오후시간대여비율   2752 non-null   float64\n",
      " 8   새벽대여비율     2752 non-null   float64\n",
      " 9   출근시간대여비율   2752 non-null   float64\n",
      " 10  퇴근시간대여비율   2752 non-null   float64\n",
      " 11  야간대여비율     2752 non-null   float64\n",
      " 12  주중청소년고객비율  2752 non-null   float64\n",
      " 13  주말청소년고객비율  2752 non-null   float64\n",
      " 14  주중청년고객비율   2752 non-null   float64\n",
      " 15  주말청년고객비율   2752 non-null   float64\n",
      " 16  주중장년고객비율   2752 non-null   float64\n",
      " 17  주말장년고객비율   2752 non-null   float64\n",
      " 18  주중노인고객비율   2752 non-null   float64\n",
      " 19  주말노인고객비율   2752 non-null   float64\n",
      "dtypes: float64(18), int64(1), object(1)\n",
      "memory usage: 451.5+ KB\n"
     ]
    }
   ],
   "source": [
    "grouped.info(show_counts=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (1) 최적의 k찾기\n",
    "- Elbow method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "\n",
    "# # 군집분석에 사용할 피처 선택\n",
    "# features = grouped.drop(columns=['대여대여소ID'])\n",
    "\n",
    "sum_of_squared_distances = []\n",
    "K = range(1, 15)\n",
    "for k in K:\n",
    "    km = KMeans(n_clusters = k)\n",
    "    km = km.fit(features)\n",
    "    sum_of_squared_distances.append(km.inertia_)\n",
    "    \n",
    "# 시각화\n",
    "\n",
    "plt.plot(K, sum_of_squared_distances, 'bx-')\n",
    "plt.xlabel('k')\n",
    "plt.ylabel('Sum_of_squared_distances')\n",
    "plt.title('Elbow Method For Optimal k')\n",
    "plt.axvline(2,c= 'r',alpha =0.4)\n",
    "plt.axvline(3,c= 'r',alpha =0.4)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- silhouette_score(실루엣점수)  \n",
    ": 각 군집간의 거리가 얼마나 효율적으로 분리되어 있는지 (효율적으로 잘 분리 = 다른 군집과의 거리는 멀고, 동일 군집과의 데이터는 서로 가까운 것)  \n",
    ": [-1, 1] 1에 가까울수록 좋음 (= 근처 군집과 멀리 떨어져 있다는 의미), 0에 가까울수록 근처 군집과 가까움"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "k : 2 score : 0.5267140683914692\n",
      "k : 3 score : 0.3756956801412976\n",
      "k : 4 score : 0.39494375568362877\n",
      "k : 5 score : 0.3868903067278828\n",
      "k : 6 score : 0.34879216549652525\n",
      "k : 7 score : 0.3462125430789088\n",
      "k : 8 score : 0.34562471777055176\n",
      "k : 9 score : 0.3191814485016946\n",
      "k : 10 score : 0.3126998522523432\n",
      "k : 11 score : 0.30574665895883596\n",
      "k : 12 score : 0.29962811791445\n",
      "k : 13 score : 0.2995635477197215\n",
      "best n : 2 best score : 0.5267140683914692\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import silhouette_score\n",
    "k_range = range(2,14)\n",
    "\n",
    "best_n = -1\n",
    "best_silhouette_score = -1\n",
    "\n",
    "for k in k_range:\n",
    "\n",
    "  kmeans = KMeans(n_clusters=k, random_state=200)\n",
    "  kmeans.fit(features)\n",
    "  clusters = kmeans.predict(features)\n",
    "\n",
    "  score = silhouette_score(features, clusters)\n",
    "  print('k :',  k, 'score :', score)\n",
    "\n",
    "  if score > best_silhouette_score:\n",
    "    best_n = k\n",
    "    best_silhouette_score = score\n",
    "\n",
    "print('best n :', best_n, 'best score :', best_silhouette_score )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (2) k-means 군집분석"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      대여대여소ID  총대여횟수    남성고객비율     평균이용시간       평균이용거리    주말대여비율    점심대여비율  \\\n",
      "0       ST-10   2764  0.641823  30.027135  2896.118784  0.308249  0.099855   \n",
      "1     ST-1000   3074  0.625895  19.268705  2427.495573  0.265777  0.093689   \n",
      "2     ST-1002   5895  0.658863  20.319932  2289.621218  0.298049  0.087532   \n",
      "3     ST-1003   1914  0.641066  17.774817  2121.170564  0.269592  0.096134   \n",
      "4     ST-1004   1543  0.736876  15.806870  1868.960045  0.288399  0.088788   \n",
      "...       ...    ...       ...        ...          ...       ...       ...   \n",
      "2748   ST-993   2288  0.677885  18.303759  1884.028086  0.255682  0.092220   \n",
      "2749   ST-994   4450  0.640225  20.783820  2037.581463  0.224045  0.087865   \n",
      "2750   ST-995    467  0.698073  18.715203  2259.101649  0.241970  0.100642   \n",
      "2751   ST-996   1075  0.709767  20.463256  1966.129544  0.279070  0.083721   \n",
      "2752   ST-997   6979  0.640923  18.015618  1877.363578  0.252472  0.082533   \n",
      "\n",
      "        오후대여비율    새벽대여비율  출근시간대여비율  ...  주말청소년고객비율  주중청년고객비율  주말청년고객비율  \\\n",
      "0     0.345514  0.099493  0.045224  ...   0.042254  0.770397  0.803991   \n",
      "1     0.317502  0.036760  0.307417  ...   0.226438  0.330970  0.432069   \n",
      "2     0.333673  0.013740  0.079389  ...   0.269209  0.431851  0.402390   \n",
      "3     0.312435  0.060084  0.142111  ...   0.129845  0.532904  0.476744   \n",
      "4     0.303305  0.038885  0.263772  ...   0.400000  0.262295  0.303371   \n",
      "...        ...       ...       ...  ...        ...       ...       ...   \n",
      "2748  0.335227  0.042832  0.194493  ...   0.174359  0.494422  0.521368   \n",
      "2749  0.310337  0.014607  0.076854  ...   0.149448  0.519548  0.535607   \n",
      "2750  0.357602  0.008565  0.233405  ...   0.132743  0.437853  0.486726   \n",
      "2751  0.324651  0.097674  0.042791  ...   0.126667  0.540645  0.570000   \n",
      "2752  0.346611  0.028084  0.260496  ...   0.267310  0.338700  0.360953   \n",
      "\n",
      "      주중장년고객비율  주말장년고객비율  주중노인고객비율  주말노인고객비율  군집      PCA1      PCA2  \n",
      "0     0.191423  0.142019  0.017782  0.011737   0 -3.544605  1.905490  \n",
      "1     0.364643  0.291310  0.037661  0.048960   3  2.763782 -2.846314  \n",
      "2     0.346786  0.308480  0.040841  0.018782   3  1.055730 -1.559605  \n",
      "3     0.304006  0.331395  0.032904  0.062016   3  0.610829 -0.970262  \n",
      "4     0.218579  0.265169  0.023679  0.031461   3  3.512032 -5.871770  \n",
      "...        ...       ...       ...       ...  ..       ...       ...  \n",
      "2748  0.328244  0.251282  0.042866  0.052991   3  0.847214 -1.745630  \n",
      "2749  0.387200  0.292879  0.029540  0.022066   1 -0.283354 -0.317513  \n",
      "2750  0.392655  0.300885  0.076271  0.079646   3  2.111148 -0.684499  \n",
      "2751  0.269677  0.256667  0.072258  0.046667   0  0.025039 -0.193708  \n",
      "2752  0.345793  0.319523  0.033736  0.048241   3  2.574257 -3.698193  \n",
      "\n",
      "[2752 rows x 23 columns]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.decomposition import PCA\n",
    "\n",
    "# 군집분석에 사용할 피처 선택\n",
    "features = grouped.drop(columns=['대여대여소ID'])\n",
    "\n",
    "# 표준화\n",
    "scaler = StandardScaler()\n",
    "scaled_features = scaler.fit_transform(features)\n",
    "\n",
    "# K-means 군집분석\n",
    "kmeans = KMeans(n_clusters=4, random_state=42)\n",
    "grouped['군집'] = kmeans.fit_predict(scaled_features)\n",
    "\n",
    "# PCA 적용\n",
    "pca = PCA(n_components=2)\n",
    "pca_features = pca.fit_transform(scaled_features)\n",
    "\n",
    "# PCA 결과를 데이터프레임에 추가\n",
    "grouped['PCA1'] = pca_features[:, 0]\n",
    "grouped['PCA2'] = pca_features[:, 1]\n",
    "\n",
    "# 결과 출력\n",
    "print(grouped)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 군집 시각화\n",
    "plt.figure(figsize=(10, 7))\n",
    "plt.scatter(grouped['PCA1'], grouped['PCA2'], c=grouped['군집'], cmap='viridis')\n",
    "plt.xlabel('PCA1')\n",
    "plt.ylabel('PCA2')\n",
    "plt.title('대여소 군집 결과 (PCA)')\n",
    "plt.colorbar(label='군집')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- k=2,3,4일 때의 군집 시각화"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 2일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
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       "      <th id=\"T_759f0_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_759f0_level0_col1\" class=\"col_heading level0 col1\" >남성고객비율</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
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       "      <td id=\"T_759f0_row0_col16\" class=\"data row0 col16\" >0.226184</td>\n",
       "      <td id=\"T_759f0_row0_col17\" class=\"data row0 col17\" >0.042391</td>\n",
       "      <td id=\"T_759f0_row0_col18\" class=\"data row0 col18\" >0.038040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_759f0_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_759f0_row1_col0\" class=\"data row1 col0\" >1703.608481</td>\n",
       "      <td id=\"T_759f0_row1_col1\" class=\"data row1 col1\" >0.657364</td>\n",
       "      <td id=\"T_759f0_row1_col2\" class=\"data row1 col2\" >21.406674</td>\n",
       "      <td id=\"T_759f0_row1_col3\" class=\"data row1 col3\" >2514.513628</td>\n",
       "      <td id=\"T_759f0_row1_col4\" class=\"data row1 col4\" >0.249643</td>\n",
       "      <td id=\"T_759f0_row1_col5\" class=\"data row1 col5\" >0.086861</td>\n",
       "      <td id=\"T_759f0_row1_col6\" class=\"data row1 col6\" >0.333203</td>\n",
       "      <td id=\"T_759f0_row1_col7\" class=\"data row1 col7\" >0.051180</td>\n",
       "      <td id=\"T_759f0_row1_col8\" class=\"data row1 col8\" >0.182996</td>\n",
       "      <td id=\"T_759f0_row1_col9\" class=\"data row1 col9\" >0.163784</td>\n",
       "      <td id=\"T_759f0_row1_col10\" class=\"data row1 col10\" >0.220927</td>\n",
       "      <td id=\"T_759f0_row1_col11\" class=\"data row1 col11\" >0.093904</td>\n",
       "      <td id=\"T_759f0_row1_col12\" class=\"data row1 col12\" >0.100016</td>\n",
       "      <td id=\"T_759f0_row1_col13\" class=\"data row1 col13\" >0.472638</td>\n",
       "      <td id=\"T_759f0_row1_col14\" class=\"data row1 col14\" >0.494725</td>\n",
       "      <td id=\"T_759f0_row1_col15\" class=\"data row1 col15\" >0.362727</td>\n",
       "      <td id=\"T_759f0_row1_col16\" class=\"data row1 col16\" >0.337462</td>\n",
       "      <td id=\"T_759f0_row1_col17\" class=\"data row1 col17\" >0.069840</td>\n",
       "      <td id=\"T_759f0_row1_col18\" class=\"data row1 col18\" >0.066780</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x14acbc41610>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 3일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
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       "#T_5c675_row0_col1, #T_5c675_row0_col4, #T_5c675_row0_col6, #T_5c675_row0_col8, #T_5c675_row0_col11, #T_5c675_row0_col12, #T_5c675_row0_col15, #T_5c675_row0_col16, #T_5c675_row0_col17, #T_5c675_row0_col18, #T_5c675_row1_col0, #T_5c675_row1_col7, #T_5c675_row1_col10, #T_5c675_row2_col2, #T_5c675_row2_col3, #T_5c675_row2_col5, #T_5c675_row2_col9, #T_5c675_row2_col13, #T_5c675_row2_col14 {\n",
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       "<table id=\"T_5c675\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_5c675_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_5c675_level0_col1\" class=\"col_heading level0 col1\" >남성고객비율</th>\n",
       "      <th id=\"T_5c675_level0_col2\" class=\"col_heading level0 col2\" >평균이용시간</th>\n",
       "      <th id=\"T_5c675_level0_col3\" class=\"col_heading level0 col3\" >평균이용거리</th>\n",
       "      <th id=\"T_5c675_level0_col4\" class=\"col_heading level0 col4\" >주말대여비율</th>\n",
       "      <th id=\"T_5c675_level0_col5\" class=\"col_heading level0 col5\" >점심대여비율</th>\n",
       "      <th id=\"T_5c675_level0_col6\" class=\"col_heading level0 col6\" >오후대여비율</th>\n",
       "      <th id=\"T_5c675_level0_col7\" class=\"col_heading level0 col7\" >새벽대여비율</th>\n",
       "      <th id=\"T_5c675_level0_col8\" class=\"col_heading level0 col8\" >출근시간대여비율</th>\n",
       "      <th id=\"T_5c675_level0_col9\" class=\"col_heading level0 col9\" >퇴근시간대여비율</th>\n",
       "      <th id=\"T_5c675_level0_col10\" class=\"col_heading level0 col10\" >야간대여비율</th>\n",
       "      <th id=\"T_5c675_level0_col11\" class=\"col_heading level0 col11\" >주중청소년고객비율</th>\n",
       "      <th id=\"T_5c675_level0_col12\" class=\"col_heading level0 col12\" >주말청소년고객비율</th>\n",
       "      <th id=\"T_5c675_level0_col13\" class=\"col_heading level0 col13\" >주중청년고객비율</th>\n",
       "      <th id=\"T_5c675_level0_col14\" class=\"col_heading level0 col14\" >주말청년고객비율</th>\n",
       "      <th id=\"T_5c675_level0_col15\" class=\"col_heading level0 col15\" >주중장년고객비율</th>\n",
       "      <th id=\"T_5c675_level0_col16\" class=\"col_heading level0 col16\" >주말장년고객비율</th>\n",
       "      <th id=\"T_5c675_level0_col17\" class=\"col_heading level0 col17\" >주중노인고객비율</th>\n",
       "      <th id=\"T_5c675_level0_col18\" class=\"col_heading level0 col18\" >주말노인고객비율</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
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       "      <td id=\"T_5c675_row0_col2\" class=\"data row0 col2\" >20.316108</td>\n",
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       "      <td id=\"T_5c675_row0_col4\" class=\"data row0 col4\" >0.243991</td>\n",
       "      <td id=\"T_5c675_row0_col5\" class=\"data row0 col5\" >0.084316</td>\n",
       "      <td id=\"T_5c675_row0_col6\" class=\"data row0 col6\" >0.308865</td>\n",
       "      <td id=\"T_5c675_row0_col7\" class=\"data row0 col7\" >0.053617</td>\n",
       "      <td id=\"T_5c675_row0_col8\" class=\"data row0 col8\" >0.155933</td>\n",
       "      <td id=\"T_5c675_row0_col9\" class=\"data row0 col9\" >0.173947</td>\n",
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       "      <td id=\"T_5c675_row0_col12\" class=\"data row0 col12\" >0.049915</td>\n",
       "      <td id=\"T_5c675_row0_col13\" class=\"data row0 col13\" >0.661300</td>\n",
       "      <td id=\"T_5c675_row0_col14\" class=\"data row0 col14\" >0.690685</td>\n",
       "      <td id=\"T_5c675_row0_col15\" class=\"data row0 col15\" >0.255367</td>\n",
       "      <td id=\"T_5c675_row0_col16\" class=\"data row0 col16\" >0.221454</td>\n",
       "      <td id=\"T_5c675_row0_col17\" class=\"data row0 col17\" >0.041388</td>\n",
       "      <td id=\"T_5c675_row0_col18\" class=\"data row0 col18\" >0.037557</td>\n",
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       "    <tr>\n",
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       "      <td id=\"T_5c675_row1_col1\" class=\"data row1 col1\" >0.655373</td>\n",
       "      <td id=\"T_5c675_row1_col2\" class=\"data row1 col2\" >23.951638</td>\n",
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       "      <td id=\"T_5c675_row1_col4\" class=\"data row1 col4\" >0.248415</td>\n",
       "      <td id=\"T_5c675_row1_col5\" class=\"data row1 col5\" >0.090221</td>\n",
       "      <td id=\"T_5c675_row1_col6\" class=\"data row1 col6\" >0.340935</td>\n",
       "      <td id=\"T_5c675_row1_col7\" class=\"data row1 col7\" >0.048849</td>\n",
       "      <td id=\"T_5c675_row1_col8\" class=\"data row1 col8\" >0.166816</td>\n",
       "      <td id=\"T_5c675_row1_col9\" class=\"data row1 col9\" >0.182580</td>\n",
       "      <td id=\"T_5c675_row1_col10\" class=\"data row1 col10\" >0.217125</td>\n",
       "      <td id=\"T_5c675_row1_col11\" class=\"data row1 col11\" >0.043803</td>\n",
       "      <td id=\"T_5c675_row1_col12\" class=\"data row1 col12\" >0.054675</td>\n",
       "      <td id=\"T_5c675_row1_col13\" class=\"data row1 col13\" >0.498559</td>\n",
       "      <td id=\"T_5c675_row1_col14\" class=\"data row1 col14\" >0.523787</td>\n",
       "      <td id=\"T_5c675_row1_col15\" class=\"data row1 col15\" >0.380076</td>\n",
       "      <td id=\"T_5c675_row1_col16\" class=\"data row1 col16\" >0.348232</td>\n",
       "      <td id=\"T_5c675_row1_col17\" class=\"data row1 col17\" >0.076591</td>\n",
       "      <td id=\"T_5c675_row1_col18\" class=\"data row1 col18\" >0.072317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_5c675_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "      <td id=\"T_5c675_row2_col0\" class=\"data row2 col0\" >2358.428571</td>\n",
       "      <td id=\"T_5c675_row2_col1\" class=\"data row2 col1\" >0.659102</td>\n",
       "      <td id=\"T_5c675_row2_col2\" class=\"data row2 col2\" >17.865619</td>\n",
       "      <td id=\"T_5c675_row2_col3\" class=\"data row2 col3\" >2064.412353</td>\n",
       "      <td id=\"T_5c675_row2_col4\" class=\"data row2 col4\" >0.248751</td>\n",
       "      <td id=\"T_5c675_row2_col5\" class=\"data row2 col5\" >0.081228</td>\n",
       "      <td id=\"T_5c675_row2_col6\" class=\"data row2 col6\" >0.322852</td>\n",
       "      <td id=\"T_5c675_row2_col7\" class=\"data row2 col7\" >0.051932</td>\n",
       "      <td id=\"T_5c675_row2_col8\" class=\"data row2 col8\" >0.191878</td>\n",
       "      <td id=\"T_5c675_row2_col9\" class=\"data row2 col9\" >0.145024</td>\n",
       "      <td id=\"T_5c675_row2_col10\" class=\"data row2 col10\" >0.236744</td>\n",
       "      <td id=\"T_5c675_row2_col11\" class=\"data row2 col11\" >0.188600</td>\n",
       "      <td id=\"T_5c675_row2_col12\" class=\"data row2 col12\" >0.186102</td>\n",
       "      <td id=\"T_5c675_row2_col13\" class=\"data row2 col13\" >0.447550</td>\n",
       "      <td id=\"T_5c675_row2_col14\" class=\"data row2 col14\" >0.472927</td>\n",
       "      <td id=\"T_5c675_row2_col15\" class=\"data row2 col15\" >0.313483</td>\n",
       "      <td id=\"T_5c675_row2_col16\" class=\"data row2 col16\" >0.292542</td>\n",
       "      <td id=\"T_5c675_row2_col17\" class=\"data row2 col17\" >0.049586</td>\n",
       "      <td id=\"T_5c675_row2_col18\" class=\"data row2 col18\" >0.047502</td>\n",
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       "  </tbody>\n",
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      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x14aa9064b90>"
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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 4일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<table id=\"T_c0d10\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_c0d10_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_c0d10_level0_col1\" class=\"col_heading level0 col1\" >남성고객비율</th>\n",
       "      <th id=\"T_c0d10_level0_col2\" class=\"col_heading level0 col2\" >평균이용시간</th>\n",
       "      <th id=\"T_c0d10_level0_col3\" class=\"col_heading level0 col3\" >평균이용거리</th>\n",
       "      <th id=\"T_c0d10_level0_col4\" class=\"col_heading level0 col4\" >주말대여비율</th>\n",
       "      <th id=\"T_c0d10_level0_col5\" class=\"col_heading level0 col5\" >점심대여비율</th>\n",
       "      <th id=\"T_c0d10_level0_col6\" class=\"col_heading level0 col6\" >오후대여비율</th>\n",
       "      <th id=\"T_c0d10_level0_col7\" class=\"col_heading level0 col7\" >새벽대여비율</th>\n",
       "      <th id=\"T_c0d10_level0_col8\" class=\"col_heading level0 col8\" >출근시간대여비율</th>\n",
       "      <th id=\"T_c0d10_level0_col9\" class=\"col_heading level0 col9\" >퇴근시간대여비율</th>\n",
       "      <th id=\"T_c0d10_level0_col10\" class=\"col_heading level0 col10\" >야간대여비율</th>\n",
       "      <th id=\"T_c0d10_level0_col11\" class=\"col_heading level0 col11\" >주중청소년고객비율</th>\n",
       "      <th id=\"T_c0d10_level0_col12\" class=\"col_heading level0 col12\" >주말청소년고객비율</th>\n",
       "      <th id=\"T_c0d10_level0_col13\" class=\"col_heading level0 col13\" >주중청년고객비율</th>\n",
       "      <th id=\"T_c0d10_level0_col14\" class=\"col_heading level0 col14\" >주말청년고객비율</th>\n",
       "      <th id=\"T_c0d10_level0_col15\" class=\"col_heading level0 col15\" >주중장년고객비율</th>\n",
       "      <th id=\"T_c0d10_level0_col16\" class=\"col_heading level0 col16\" >주말장년고객비율</th>\n",
       "      <th id=\"T_c0d10_level0_col17\" class=\"col_heading level0 col17\" >주중노인고객비율</th>\n",
       "      <th id=\"T_c0d10_level0_col18\" class=\"col_heading level0 col18\" >주말노인고객비율</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "      <th class=\"blank col8\" >&nbsp;</th>\n",
       "      <th class=\"blank col9\" >&nbsp;</th>\n",
       "      <th class=\"blank col10\" >&nbsp;</th>\n",
       "      <th class=\"blank col11\" >&nbsp;</th>\n",
       "      <th class=\"blank col12\" >&nbsp;</th>\n",
       "      <th class=\"blank col13\" >&nbsp;</th>\n",
       "      <th class=\"blank col14\" >&nbsp;</th>\n",
       "      <th class=\"blank col15\" >&nbsp;</th>\n",
       "      <th class=\"blank col16\" >&nbsp;</th>\n",
       "      <th class=\"blank col17\" >&nbsp;</th>\n",
       "      <th class=\"blank col18\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_c0d10_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_c0d10_row0_col0\" class=\"data row0 col0\" >2956.326255</td>\n",
       "      <td id=\"T_c0d10_row0_col1\" class=\"data row0 col1\" >0.626451</td>\n",
       "      <td id=\"T_c0d10_row0_col2\" class=\"data row0 col2\" >20.331008</td>\n",
       "      <td id=\"T_c0d10_row0_col3\" class=\"data row0 col3\" >2272.635104</td>\n",
       "      <td id=\"T_c0d10_row0_col4\" class=\"data row0 col4\" >0.252940</td>\n",
       "      <td id=\"T_c0d10_row0_col5\" class=\"data row0 col5\" >0.083725</td>\n",
       "      <td id=\"T_c0d10_row0_col6\" class=\"data row0 col6\" >0.305573</td>\n",
       "      <td id=\"T_c0d10_row0_col7\" class=\"data row0 col7\" >0.056464</td>\n",
       "      <td id=\"T_c0d10_row0_col8\" class=\"data row0 col8\" >0.158887</td>\n",
       "      <td id=\"T_c0d10_row0_col9\" class=\"data row0 col9\" >0.162416</td>\n",
       "      <td id=\"T_c0d10_row0_col10\" class=\"data row0 col10\" >0.269436</td>\n",
       "      <td id=\"T_c0d10_row0_col11\" class=\"data row0 col11\" >0.043643</td>\n",
       "      <td id=\"T_c0d10_row0_col12\" class=\"data row0 col12\" >0.051528</td>\n",
       "      <td id=\"T_c0d10_row0_col13\" class=\"data row0 col13\" >0.665818</td>\n",
       "      <td id=\"T_c0d10_row0_col14\" class=\"data row0 col14\" >0.693225</td>\n",
       "      <td id=\"T_c0d10_row0_col15\" class=\"data row0 col15\" >0.248226</td>\n",
       "      <td id=\"T_c0d10_row0_col16\" class=\"data row0 col16\" >0.217179</td>\n",
       "      <td id=\"T_c0d10_row0_col17\" class=\"data row0 col17\" >0.041859</td>\n",
       "      <td id=\"T_c0d10_row0_col18\" class=\"data row0 col18\" >0.037667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c0d10_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_c0d10_row1_col0\" class=\"data row1 col0\" >1803.287257</td>\n",
       "      <td id=\"T_c0d10_row1_col1\" class=\"data row1 col1\" >0.681573</td>\n",
       "      <td id=\"T_c0d10_row1_col2\" class=\"data row1 col2\" >20.988724</td>\n",
       "      <td id=\"T_c0d10_row1_col3\" class=\"data row1 col3\" >2330.368143</td>\n",
       "      <td id=\"T_c0d10_row1_col4\" class=\"data row1 col4\" >0.183735</td>\n",
       "      <td id=\"T_c0d10_row1_col5\" class=\"data row1 col5\" >0.098823</td>\n",
       "      <td id=\"T_c0d10_row1_col6\" class=\"data row1 col6\" >0.365492</td>\n",
       "      <td id=\"T_c0d10_row1_col7\" class=\"data row1 col7\" >0.026708</td>\n",
       "      <td id=\"T_c0d10_row1_col8\" class=\"data row1 col8\" >0.141667</td>\n",
       "      <td id=\"T_c0d10_row1_col9\" class=\"data row1 col9\" >0.250766</td>\n",
       "      <td id=\"T_c0d10_row1_col10\" class=\"data row1 col10\" >0.187827</td>\n",
       "      <td id=\"T_c0d10_row1_col11\" class=\"data row1 col11\" >0.026499</td>\n",
       "      <td id=\"T_c0d10_row1_col12\" class=\"data row1 col12\" >0.040000</td>\n",
       "      <td id=\"T_c0d10_row1_col13\" class=\"data row1 col13\" >0.557351</td>\n",
       "      <td id=\"T_c0d10_row1_col14\" class=\"data row1 col14\" >0.603960</td>\n",
       "      <td id=\"T_c0d10_row1_col15\" class=\"data row1 col15\" >0.365510</td>\n",
       "      <td id=\"T_c0d10_row1_col16\" class=\"data row1 col16\" >0.309245</td>\n",
       "      <td id=\"T_c0d10_row1_col17\" class=\"data row1 col17\" >0.049869</td>\n",
       "      <td id=\"T_c0d10_row1_col18\" class=\"data row1 col18\" >0.046337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c0d10_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "      <td id=\"T_c0d10_row2_col0\" class=\"data row2 col0\" >1428.899244</td>\n",
       "      <td id=\"T_c0d10_row2_col1\" class=\"data row2 col1\" >0.644271</td>\n",
       "      <td id=\"T_c0d10_row2_col2\" class=\"data row2 col2\" >24.798178</td>\n",
       "      <td id=\"T_c0d10_row2_col3\" class=\"data row2 col3\" >3010.576078</td>\n",
       "      <td id=\"T_c0d10_row2_col4\" class=\"data row2 col4\" >0.274155</td>\n",
       "      <td id=\"T_c0d10_row2_col5\" class=\"data row2 col5\" >0.083391</td>\n",
       "      <td id=\"T_c0d10_row2_col6\" class=\"data row2 col6\" >0.320851</td>\n",
       "      <td id=\"T_c0d10_row2_col7\" class=\"data row2 col7\" >0.061413</td>\n",
       "      <td id=\"T_c0d10_row2_col8\" class=\"data row2 col8\" >0.176385</td>\n",
       "      <td id=\"T_c0d10_row2_col9\" class=\"data row2 col9\" >0.154797</td>\n",
       "      <td id=\"T_c0d10_row2_col10\" class=\"data row2 col10\" >0.234832</td>\n",
       "      <td id=\"T_c0d10_row2_col11\" class=\"data row2 col11\" >0.054736</td>\n",
       "      <td id=\"T_c0d10_row2_col12\" class=\"data row2 col12\" >0.064375</td>\n",
       "      <td id=\"T_c0d10_row2_col13\" class=\"data row2 col13\" >0.487908</td>\n",
       "      <td id=\"T_c0d10_row2_col14\" class=\"data row2 col14\" >0.503194</td>\n",
       "      <td id=\"T_c0d10_row2_col15\" class=\"data row2 col15\" >0.371744</td>\n",
       "      <td id=\"T_c0d10_row2_col16\" class=\"data row2 col16\" >0.350849</td>\n",
       "      <td id=\"T_c0d10_row2_col17\" class=\"data row2 col17\" >0.084604</td>\n",
       "      <td id=\"T_c0d10_row2_col18\" class=\"data row2 col18\" >0.080383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_c0d10_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "      <td id=\"T_c0d10_row3_col0\" class=\"data row3 col0\" >2468.873638</td>\n",
       "      <td id=\"T_c0d10_row3_col1\" class=\"data row3 col1\" >0.655936</td>\n",
       "      <td id=\"T_c0d10_row3_col2\" class=\"data row3 col2\" >17.640643</td>\n",
       "      <td id=\"T_c0d10_row3_col3\" class=\"data row3 col3\" >2022.297376</td>\n",
       "      <td id=\"T_c0d10_row3_col4\" class=\"data row3 col4\" >0.247822</td>\n",
       "      <td id=\"T_c0d10_row3_col5\" class=\"data row3 col5\" >0.082986</td>\n",
       "      <td id=\"T_c0d10_row3_col6\" class=\"data row3 col6\" >0.328065</td>\n",
       "      <td id=\"T_c0d10_row3_col7\" class=\"data row3 col7\" >0.047950</td>\n",
       "      <td id=\"T_c0d10_row3_col8\" class=\"data row3 col8\" >0.192472</td>\n",
       "      <td id=\"T_c0d10_row3_col9\" class=\"data row3 col9\" >0.144345</td>\n",
       "      <td id=\"T_c0d10_row3_col10\" class=\"data row3 col10\" >0.236745</td>\n",
       "      <td id=\"T_c0d10_row3_col11\" class=\"data row3 col11\" >0.193449</td>\n",
       "      <td id=\"T_c0d10_row3_col12\" class=\"data row3 col12\" >0.189779</td>\n",
       "      <td id=\"T_c0d10_row3_col13\" class=\"data row3 col13\" >0.446495</td>\n",
       "      <td id=\"T_c0d10_row3_col14\" class=\"data row3 col14\" >0.473367</td>\n",
       "      <td id=\"T_c0d10_row3_col15\" class=\"data row3 col15\" >0.311623</td>\n",
       "      <td id=\"T_c0d10_row3_col16\" class=\"data row3 col16\" >0.290119</td>\n",
       "      <td id=\"T_c0d10_row3_col17\" class=\"data row3 col17\" >0.047648</td>\n",
       "      <td id=\"T_c0d10_row3_col18\" class=\"data row3 col18\" >0.045865</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x14aa8c85490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 2일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   0\n",
      "1     ST-1000   1\n",
      "2     ST-1002   1\n",
      "3     ST-1003   1\n",
      "4     ST-1004   1\n",
      "...       ...  ..\n",
      "2748   ST-993   1\n",
      "2749   ST-994   0\n",
      "2750   ST-995   1\n",
      "2751   ST-996   1\n",
      "2752   ST-997   1\n",
      "\n",
      "[2752 rows x 2 columns]\n",
      "n_clusters = 3일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   0\n",
      "1     ST-1000   2\n",
      "2     ST-1002   2\n",
      "3     ST-1003   2\n",
      "4     ST-1004   2\n",
      "...       ...  ..\n",
      "2748   ST-993   2\n",
      "2749   ST-994   0\n",
      "2750   ST-995   1\n",
      "2751   ST-996   0\n",
      "2752   ST-997   2\n",
      "\n",
      "[2752 rows x 2 columns]\n",
      "n_clusters = 4일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   0\n",
      "1     ST-1000   3\n",
      "2     ST-1002   3\n",
      "3     ST-1003   3\n",
      "4     ST-1004   3\n",
      "...       ...  ..\n",
      "2748   ST-993   3\n",
      "2749   ST-994   1\n",
      "2750   ST-995   3\n",
      "2751   ST-996   0\n",
      "2752   ST-997   3\n",
      "\n",
      "[2752 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "# 변수 초기화\n",
    "cluster_results = {}\n",
    "\n",
    "# n_clusters 값을 2, 3, 4로 설정하여 K-means 군집분석 및 시각화\n",
    "for n_clusters in [2, 3, 4]:\n",
    "    # K-means 군집분석\n",
    "    kmeans = KMeans(n_clusters=n_clusters, random_state=42)\n",
    "    grouped['군집'] = kmeans.fit_predict(scaled_features)\n",
    "\n",
    "    # PCA 적용\n",
    "    pca = PCA(n_components=2)\n",
    "    pca_features = pca.fit_transform(scaled_features)\n",
    "\n",
    "    # PCA 결과를 데이터프레임에 추가\n",
    "    grouped['PCA1'] = pca_features[:, 0]\n",
    "    grouped['PCA2'] = pca_features[:, 1]\n",
    "\n",
    "    # 군집 시각화\n",
    "    plt.figure(figsize=(10, 7))\n",
    "    plt.scatter(grouped['PCA1'], grouped['PCA2'], c=grouped['군집'], cmap='viridis')\n",
    "    plt.xlabel('PCA1')\n",
    "    plt.ylabel('PCA2')\n",
    "    plt.title(f'대여소 군집 결과 (PCA, n_clusters={n_clusters})')\n",
    "    plt.colorbar(label='군집')\n",
    "    plt.show()\n",
    "    \n",
    "    # 각 군집의 평균 값 계산 (대여대여소ID 제외)\n",
    "    grouped_means = grouped.drop(columns=['대여대여소ID', 'PCA1', 'PCA2']).groupby('군집').mean()\n",
    "\n",
    "    # # 컬럼 별로 가장 높은 값을 가진 군집의 셀에 파란색 배경 추가\n",
    "    # def highlight_max(s):\n",
    "    #     is_max = s == s.max()\n",
    "    #     return ['background-color: #ccffcc' if v else '' for v in is_max]\n",
    "\n",
    "    # styled_means = grouped_means.style.apply(highlight_max)\n",
    "    \n",
    "    # 컬럼 별로 가장 높은 값을 가진 군집의 셀에 연한 초록색 배경 추가\n",
    "    def highlight_max(s):\n",
    "        is_max = s == s.max()\n",
    "        return ['background-color: #ccffcc' if v else '' for v in is_max]\n",
    "\n",
    "    # 컬럼 별로 가장 낮은 값을 가진 군집의 셀에 연한 노랑색 배경 추가\n",
    "    def highlight_min(s):\n",
    "        is_min = s == s.min()\n",
    "        return ['background-color: #fffff0' if v else '' for v in is_min]\n",
    "\n",
    "    styled_means = grouped_means.style.apply(highlight_max).apply(highlight_min)\n",
    "\n",
    "    \n",
    "    # 결과 출력\n",
    "    print(f\"n_clusters = {n_clusters}일 때 각 군집의 평균 값:\")\n",
    "    display(styled_means)\n",
    "    \n",
    "    # 각 대여소가 속한 군집 저장\n",
    "    cluster_results[f'cluster_{n_clusters}'] = grouped[['대여대여소ID', '군집']].copy()\n",
    "\n",
    "# 결과 데이터프레임 확인\n",
    "df_ins_2 = cluster_results['cluster_2']\n",
    "df_ins_3 = cluster_results['cluster_3']\n",
    "df_ins_4 = cluster_results['cluster_4']\n",
    "\n",
    "print(\"n_clusters = 2일 때 각 대여소가 속한 군집:\")\n",
    "print(df_ins_2)\n",
    "\n",
    "print(\"n_clusters = 3일 때 각 대여소가 속한 군집:\")\n",
    "print(df_ins_3)\n",
    "\n",
    "print(\"n_clusters = 4일 때 각 대여소가 속한 군집:\")\n",
    "print(df_ins_4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대여소ID</th>\n",
       "      <th>k=2</th>\n",
       "      <th>k=3</th>\n",
       "      <th>k=4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ST-10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ST-1000</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ST-1002</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ST-1003</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ST-1004</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     대여소ID  k=2  k=3  k=4\n",
       "0    ST-10    0    0    0\n",
       "1  ST-1000    1    2    3\n",
       "2  ST-1002    1    2    3\n",
       "3  ST-1003    1    2    3\n",
       "4  ST-1004    1    2    3"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_df = df_ins_2.merge(df_ins_3, on='대여대여소ID', suffixes=('_2', '_3')).merge(df_ins_4, on='대여대여소ID')\n",
    "merged_df.columns = ['대여소ID', 'k=2', 'k=3', 'k=4']\n",
    "merged_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "#merged_df.to_csv('./(군집결과) 서울시 따릉이 대여소 별 군집.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (3) k=2, 3 데이터 결과 >> ll_join (서울시 따릉이 마스터 정보)와 위도, 경도 조인하기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- k=2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "in_k_2 = pd.merge(df_ins_2, ll_join, how='left', left_on='대여대여소ID', right_on='대여소_ID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "in_k_2 = in_k_2.drop(columns=['대여소_ID'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대여대여소ID</th>\n",
       "      <th>군집</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "      <th>구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>ST-10</td>\n",
       "      <td>0</td>\n",
       "      <td>37.55275</td>\n",
       "      <td>126.91862</td>\n",
       "      <td>마포구</td>\n",
       "    </tr>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  대여대여소ID  군집        위도         경도    구\n",
       "0   ST-10   0  37.55275  126.91862  마포구"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in_k_2.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대여소ID</th>\n",
       "      <th>군집</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "      <th>구</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>ST-10</td>\n",
       "      <td>0</td>\n",
       "      <td>37.55275</td>\n",
       "      <td>126.91862</td>\n",
       "      <td>마포구</td>\n",
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       "  </tbody>\n",
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       "</div>"
      ],
      "text/plain": [
       "   대여소ID  군집        위도         경도    구\n",
       "0  ST-10   0  37.55275  126.91862  마포구"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in_k_2.columns = ['대여소ID', '군집', '위도', '경도', '구']\n",
    "in_k_2.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>2</th>\n",
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       "      <td>65</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>성동구</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>강남구</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
       "      <td>용산구</td>\n",
       "      <td>59</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>금천구</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0</td>\n",
       "      <td>동대문구</td>\n",
       "      <td>52</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0</td>\n",
       "      <td>동작구</td>\n",
       "      <td>51</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
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       "      <td>50</td>\n",
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       "      <th>13</th>\n",
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       "      <td>종로구</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0</td>\n",
       "      <td>중구</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0</td>\n",
       "      <td>노원구</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0</td>\n",
       "      <td>중랑구</td>\n",
       "      <td>45</td>\n",
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       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>구로구</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0</td>\n",
       "      <td>서초구</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>성북구</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0</td>\n",
       "      <td>서대문구</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0</td>\n",
       "      <td>은평구</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
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       "      <th>23</th>\n",
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       "      <td>도봉구</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0</td>\n",
       "      <td>양천구</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
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       "      <td>113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1</td>\n",
       "      <td>서초구</td>\n",
       "      <td>102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1</td>\n",
       "      <td>강서구</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1</td>\n",
       "      <td>송파구</td>\n",
       "      <td>99</td>\n",
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       "    <tr>\n",
       "      <th>29</th>\n",
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       "      <td>노원구</td>\n",
       "      <td>97</td>\n",
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       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>1</td>\n",
       "      <td>양천구</td>\n",
       "      <td>92</td>\n",
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       "      <th>31</th>\n",
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       "      <td>74</td>\n",
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       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>1</td>\n",
       "      <td>강동구</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>1</td>\n",
       "      <td>은평구</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>1</td>\n",
       "      <td>영등포구</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>1</td>\n",
       "      <td>도봉구</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>1</td>\n",
       "      <td>종로구</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>1</td>\n",
       "      <td>중랑구</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>1</td>\n",
       "      <td>성북구</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>1</td>\n",
       "      <td>서대문구</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>1</td>\n",
       "      <td>중구</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>1</td>\n",
       "      <td>강북구</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>1</td>\n",
       "      <td>마포구</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>1</td>\n",
       "      <td>용산구</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>1</td>\n",
       "      <td>동대문구</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>1</td>\n",
       "      <td>성동구</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>1</td>\n",
       "      <td>금천구</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>1</td>\n",
       "      <td>동작구</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>1</td>\n",
       "      <td>광진구</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>1</td>\n",
       "      <td>관악구</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    군집     구  count\n",
       "0    0   송파구    115\n",
       "1    0  영등포구     95\n",
       "2    0   강서구     92\n",
       "3    0   마포구     84\n",
       "4    0   광진구     70\n",
       "5    0   관악구     65\n",
       "6    0   성동구     64\n",
       "7    0   강남구     60\n",
       "8    0   용산구     59\n",
       "9    0   금천구     53\n",
       "10   0  동대문구     52\n",
       "11   0   동작구     51\n",
       "12   0   강동구     50\n",
       "13   0   종로구     50\n",
       "14   0    중구     47\n",
       "15   0   노원구     46\n",
       "16   0   중랑구     45\n",
       "17   0   구로구     41\n",
       "18   0   서초구     40\n",
       "19   0   성북구     37\n",
       "20   0  서대문구     36\n",
       "21   0   은평구     31\n",
       "22   0   강북구     19\n",
       "23   0   도봉구     18\n",
       "24   0   양천구     17\n",
       "25   1   강남구    113\n",
       "26   1   서초구    102\n",
       "27   1   강서구    100\n",
       "28   1   송파구     99\n",
       "29   1   노원구     97\n",
       "30   1   양천구     92\n",
       "31   1   구로구     74\n",
       "32   1   강동구     70\n",
       "33   1   은평구     69\n",
       "34   1  영등포구     61\n",
       "35   1   도봉구     59\n",
       "36   1   종로구     53\n",
       "37   1   중랑구     50\n",
       "38   1   성북구     45\n",
       "39   1  서대문구     44\n",
       "40   1    중구     42\n",
       "41   1   강북구     41\n",
       "42   1   마포구     39\n",
       "43   1   용산구     33\n",
       "44   1  동대문구     32\n",
       "45   1   성동구     29\n",
       "46   1   금천구     23\n",
       "47   1   동작구     23\n",
       "48   1   광진구     16\n",
       "49   1   관악구      9"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in_k_2.groupby('군집')['구'].value_counts().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>구</th>\n",
       "      <th>군집</th>\n",
       "      <th>count</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>113</td>\n",
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       "      <td>60</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>강동구</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>41</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>강북구</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>강서구</td>\n",
       "      <td>1</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>강서구</td>\n",
       "      <td>0</td>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>관악구</td>\n",
       "      <td>0</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>관악구</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>광진구</td>\n",
       "      <td>0</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>광진구</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>구로구</td>\n",
       "      <td>1</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>구로구</td>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>금천구</td>\n",
       "      <td>0</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>금천구</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>노원구</td>\n",
       "      <td>1</td>\n",
       "      <td>97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>노원구</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>도봉구</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>도봉구</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>동대문구</td>\n",
       "      <td>0</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>동대문구</td>\n",
       "      <td>1</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>동작구</td>\n",
       "      <td>0</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>동작구</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>마포구</td>\n",
       "      <td>0</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>마포구</td>\n",
       "      <td>1</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>서대문구</td>\n",
       "      <td>1</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>서대문구</td>\n",
       "      <td>0</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>서초구</td>\n",
       "      <td>1</td>\n",
       "      <td>102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>서초구</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>성동구</td>\n",
       "      <td>0</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>성동구</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>성북구</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>성북구</td>\n",
       "      <td>0</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>송파구</td>\n",
       "      <td>0</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>송파구</td>\n",
       "      <td>1</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>양천구</td>\n",
       "      <td>1</td>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>양천구</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>영등포구</td>\n",
       "      <td>0</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>영등포구</td>\n",
       "      <td>1</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>용산구</td>\n",
       "      <td>0</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>용산구</td>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>은평구</td>\n",
       "      <td>1</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>은평구</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>종로구</td>\n",
       "      <td>1</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>종로구</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>중구</td>\n",
       "      <td>0</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>중구</td>\n",
       "      <td>1</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>중랑구</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>중랑구</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       구  군집  count\n",
       "0    강남구   1    113\n",
       "1    강남구   0     60\n",
       "2    강동구   1     70\n",
       "3    강동구   0     50\n",
       "4    강북구   1     41\n",
       "5    강북구   0     19\n",
       "6    강서구   1    100\n",
       "7    강서구   0     92\n",
       "8    관악구   0     65\n",
       "9    관악구   1      9\n",
       "10   광진구   0     70\n",
       "11   광진구   1     16\n",
       "12   구로구   1     74\n",
       "13   구로구   0     41\n",
       "14   금천구   0     53\n",
       "15   금천구   1     23\n",
       "16   노원구   1     97\n",
       "17   노원구   0     46\n",
       "18   도봉구   1     59\n",
       "19   도봉구   0     18\n",
       "20  동대문구   0     52\n",
       "21  동대문구   1     32\n",
       "22   동작구   0     51\n",
       "23   동작구   1     23\n",
       "24   마포구   0     84\n",
       "25   마포구   1     39\n",
       "26  서대문구   1     44\n",
       "27  서대문구   0     36\n",
       "28   서초구   1    102\n",
       "29   서초구   0     40\n",
       "30   성동구   0     64\n",
       "31   성동구   1     29\n",
       "32   성북구   1     45\n",
       "33   성북구   0     37\n",
       "34   송파구   0    115\n",
       "35   송파구   1     99\n",
       "36   양천구   1     92\n",
       "37   양천구   0     17\n",
       "38  영등포구   0     95\n",
       "39  영등포구   1     61\n",
       "40   용산구   0     59\n",
       "41   용산구   1     33\n",
       "42   은평구   1     69\n",
       "43   은평구   0     31\n",
       "44   종로구   1     53\n",
       "45   종로구   0     50\n",
       "46    중구   0     47\n",
       "47    중구   1     42\n",
       "48   중랑구   1     50\n",
       "49   중랑구   0     45"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in_k_2.groupby('구')['군집'].value_counts().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "#in_k_2.to_csv('./(군집_내국인_k=2) 서울시 따릉이 대여소 별 군집결과_마스터 조인.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- k=3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "in_k_3 = pd.merge(df_ins_3, ll_join, how='left', left_on='대여대여소ID', right_on='대여소_ID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "in_k_3 = in_k_3.drop(columns=['대여소_ID'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대여소ID</th>\n",
       "      <th>군집</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "      <th>구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ST-10</td>\n",
       "      <td>0</td>\n",
       "      <td>37.55275</td>\n",
       "      <td>126.91862</td>\n",
       "      <td>마포구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   대여소ID  군집        위도         경도    구\n",
       "0  ST-10   0  37.55275  126.91862  마포구"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in_k_3.columns = ['대여소ID', '군집', '위도', '경도', '구']\n",
    "in_k_3.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "#in_k_3.to_csv('./(군집_내국인_k=3) 서울시 따릉이 대여소 별 군집결과_마스터 조인.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>군집</th>\n",
       "      <th>구</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>송파구</td>\n",
       "      <td>109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>강서구</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>영등포구</td>\n",
       "      <td>86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>마포구</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>광진구</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>관악구</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>성동구</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>강동구</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
       "      <td>용산구</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>금천구</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0</td>\n",
       "      <td>동대문구</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0</td>\n",
       "      <td>동작구</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0</td>\n",
       "      <td>노원구</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "      <td>구로구</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0</td>\n",
       "      <td>종로구</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0</td>\n",
       "      <td>성북구</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0</td>\n",
       "      <td>중랑구</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>강남구</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0</td>\n",
       "      <td>서대문구</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>은평구</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0</td>\n",
       "      <td>중구</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0</td>\n",
       "      <td>서초구</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0</td>\n",
       "      <td>강북구</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0</td>\n",
       "      <td>도봉구</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0</td>\n",
       "      <td>양천구</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1</td>\n",
       "      <td>강남구</td>\n",
       "      <td>134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1</td>\n",
       "      <td>서초구</td>\n",
       "      <td>111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1</td>\n",
       "      <td>송파구</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1</td>\n",
       "      <td>종로구</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1</td>\n",
       "      <td>중구</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>1</td>\n",
       "      <td>영등포구</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>1</td>\n",
       "      <td>노원구</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>1</td>\n",
       "      <td>은평구</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>1</td>\n",
       "      <td>도봉구</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>1</td>\n",
       "      <td>서대문구</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>1</td>\n",
       "      <td>용산구</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>1</td>\n",
       "      <td>강북구</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>1</td>\n",
       "      <td>마포구</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>1</td>\n",
       "      <td>강서구</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>1</td>\n",
       "      <td>강동구</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>1</td>\n",
       "      <td>성북구</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>1</td>\n",
       "      <td>성동구</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>1</td>\n",
       "      <td>금천구</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>1</td>\n",
       "      <td>구로구</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>1</td>\n",
       "      <td>동대문구</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>1</td>\n",
       "      <td>동작구</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>1</td>\n",
       "      <td>중랑구</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>1</td>\n",
       "      <td>관악구</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>1</td>\n",
       "      <td>광진구</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>1</td>\n",
       "      <td>양천구</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2</td>\n",
       "      <td>양천구</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>2</td>\n",
       "      <td>강서구</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2</td>\n",
       "      <td>노원구</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>2</td>\n",
       "      <td>구로구</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>2</td>\n",
       "      <td>중랑구</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>2</td>\n",
       "      <td>강동구</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>2</td>\n",
       "      <td>영등포구</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>2</td>\n",
       "      <td>도봉구</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>2</td>\n",
       "      <td>은평구</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>2</td>\n",
       "      <td>동대문구</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>2</td>\n",
       "      <td>송파구</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>2</td>\n",
       "      <td>성북구</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>2</td>\n",
       "      <td>광진구</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>2</td>\n",
       "      <td>마포구</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>2</td>\n",
       "      <td>동작구</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>2</td>\n",
       "      <td>강남구</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2</td>\n",
       "      <td>관악구</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>2</td>\n",
       "      <td>성동구</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2</td>\n",
       "      <td>강북구</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>2</td>\n",
       "      <td>금천구</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2</td>\n",
       "      <td>서대문구</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>2</td>\n",
       "      <td>서초구</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>2</td>\n",
       "      <td>종로구</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>2</td>\n",
       "      <td>용산구</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    군집     구  count\n",
       "0    0   송파구    109\n",
       "1    0   강서구     90\n",
       "2    0  영등포구     86\n",
       "3    0   마포구     76\n",
       "4    0   광진구     69\n",
       "5    0   관악구     60\n",
       "6    0   성동구     60\n",
       "7    0   강동구     49\n",
       "8    0   용산구     48\n",
       "9    0   금천구     47\n",
       "10   0  동대문구     47\n",
       "11   0   동작구     47\n",
       "12   0   노원구     43\n",
       "13   0   구로구     40\n",
       "14   0   종로구     40\n",
       "15   0   성북구     37\n",
       "16   0   중랑구     35\n",
       "17   0   강남구     34\n",
       "18   0  서대문구     34\n",
       "19   0   은평구     34\n",
       "20   0    중구     32\n",
       "21   0   서초구     29\n",
       "22   0   강북구     17\n",
       "23   0   도봉구     15\n",
       "24   0   양천구     11\n",
       "25   1   강남구    134\n",
       "26   1   서초구    111\n",
       "27   1   송파구     89\n",
       "28   1   종로구     61\n",
       "29   1    중구     57\n",
       "30   1  영등포구     49\n",
       "31   1   노원구     48\n",
       "32   1   은평구     48\n",
       "33   1   도봉구     44\n",
       "34   1  서대문구     44\n",
       "35   1   용산구     43\n",
       "36   1   강북구     39\n",
       "37   1   마포구     39\n",
       "38   1   강서구     35\n",
       "39   1   강동구     34\n",
       "40   1   성북구     34\n",
       "41   1   성동구     28\n",
       "42   1   금천구     27\n",
       "43   1   구로구     25\n",
       "44   1  동대문구     21\n",
       "45   1   동작구     21\n",
       "46   1   중랑구     13\n",
       "47   1   관악구      9\n",
       "48   1   광진구      8\n",
       "49   1   양천구      5\n",
       "50   2   양천구     93\n",
       "51   2   강서구     67\n",
       "52   2   노원구     52\n",
       "53   2   구로구     50\n",
       "54   2   중랑구     47\n",
       "55   2   강동구     37\n",
       "56   2  영등포구     21\n",
       "57   2   도봉구     18\n",
       "58   2   은평구     18\n",
       "59   2  동대문구     16\n",
       "60   2   송파구     16\n",
       "61   2   성북구     11\n",
       "62   2   광진구      9\n",
       "63   2   마포구      8\n",
       "64   2   동작구      6\n",
       "65   2   강남구      5\n",
       "66   2   관악구      5\n",
       "67   2   성동구      5\n",
       "68   2   강북구      4\n",
       "69   2   금천구      2\n",
       "70   2  서대문구      2\n",
       "71   2   서초구      2\n",
       "72   2   종로구      2\n",
       "73   2   용산구      1"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('display.max_rows', None)\n",
    "in_k_3.groupby('군집')['구'].value_counts().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>구</th>\n",
       "      <th>군집</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>강남구</td>\n",
       "      <td>1</td>\n",
       "      <td>134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>강남구</td>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>강남구</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>강동구</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>강동구</td>\n",
       "      <td>2</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>중구</td>\n",
       "      <td>1</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>중구</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>중랑구</td>\n",
       "      <td>2</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>중랑구</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>중랑구</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>74 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      구  군집  count\n",
       "0   강남구   1    134\n",
       "1   강남구   0     34\n",
       "2   강남구   2      5\n",
       "3   강동구   0     49\n",
       "4   강동구   2     37\n",
       "..  ...  ..    ...\n",
       "69   중구   1     57\n",
       "70   중구   0     32\n",
       "71  중랑구   2     47\n",
       "72  중랑구   0     35\n",
       "73  중랑구   1     13\n",
       "\n",
       "[74 rows x 3 columns]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in_k_3.groupby('구')['군집'].value_counts().reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. DB Scan 군집분석"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\LG\\AppData\\Local\\Temp\\ipykernel_2632\\1893907878.py:62: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n",
      "  additional_features = df1_ins.groupby('대여대여소ID').apply(calculate_ratios).reset_index()\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DBSCAN을 사용한 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_ab298_row0_col0, #T_ab298_row0_col1, #T_ab298_row0_col2, #T_ab298_row0_col3, #T_ab298_row0_col4, #T_ab298_row0_col5, #T_ab298_row0_col6, #T_ab298_row0_col7, #T_ab298_row0_col8, #T_ab298_row0_col9, #T_ab298_row0_col10, #T_ab298_row0_col11, #T_ab298_row0_col12, #T_ab298_row0_col13, #T_ab298_row0_col14, #T_ab298_row0_col15, #T_ab298_row0_col16, #T_ab298_row0_col17, #T_ab298_row0_col18, #T_ab298_row0_col19 {\n",
       "  background-color: #ccffcc;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_ab298\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_ab298_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_ab298_level0_col1\" class=\"col_heading level0 col1\" >남성고객비율</th>\n",
       "      <th id=\"T_ab298_level0_col2\" class=\"col_heading level0 col2\" >평균이용시간</th>\n",
       "      <th id=\"T_ab298_level0_col3\" class=\"col_heading level0 col3\" >이용시간표준편차</th>\n",
       "      <th id=\"T_ab298_level0_col4\" class=\"col_heading level0 col4\" >평균이용거리</th>\n",
       "      <th id=\"T_ab298_level0_col5\" class=\"col_heading level0 col5\" >이용거리표준편차</th>\n",
       "      <th id=\"T_ab298_level0_col6\" class=\"col_heading level0 col6\" >주말대여비율</th>\n",
       "      <th id=\"T_ab298_level0_col7\" class=\"col_heading level0 col7\" >점심시간대여비율</th>\n",
       "      <th id=\"T_ab298_level0_col8\" class=\"col_heading level0 col8\" >새벽대여비율</th>\n",
       "      <th id=\"T_ab298_level0_col9\" class=\"col_heading level0 col9\" >출근시간대여비율</th>\n",
       "      <th id=\"T_ab298_level0_col10\" class=\"col_heading level0 col10\" >퇴근시간대여비율</th>\n",
       "      <th id=\"T_ab298_level0_col11\" class=\"col_heading level0 col11\" >야간대여비율</th>\n",
       "      <th id=\"T_ab298_level0_col12\" class=\"col_heading level0 col12\" >주중청소년고객비율</th>\n",
       "      <th id=\"T_ab298_level0_col13\" class=\"col_heading level0 col13\" >주말청소년고객비율</th>\n",
       "      <th id=\"T_ab298_level0_col14\" class=\"col_heading level0 col14\" >주중청년고객비율</th>\n",
       "      <th id=\"T_ab298_level0_col15\" class=\"col_heading level0 col15\" >주말청년고객비율</th>\n",
       "      <th id=\"T_ab298_level0_col16\" class=\"col_heading level0 col16\" >주중장년고객비율</th>\n",
       "      <th id=\"T_ab298_level0_col17\" class=\"col_heading level0 col17\" >주말장년고객비율</th>\n",
       "      <th id=\"T_ab298_level0_col18\" class=\"col_heading level0 col18\" >주중노인고객비율</th>\n",
       "      <th id=\"T_ab298_level0_col19\" class=\"col_heading level0 col19\" >주말노인고객비율</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "      <th class=\"blank col8\" >&nbsp;</th>\n",
       "      <th class=\"blank col9\" >&nbsp;</th>\n",
       "      <th class=\"blank col10\" >&nbsp;</th>\n",
       "      <th class=\"blank col11\" >&nbsp;</th>\n",
       "      <th class=\"blank col12\" >&nbsp;</th>\n",
       "      <th class=\"blank col13\" >&nbsp;</th>\n",
       "      <th class=\"blank col14\" >&nbsp;</th>\n",
       "      <th class=\"blank col15\" >&nbsp;</th>\n",
       "      <th class=\"blank col16\" >&nbsp;</th>\n",
       "      <th class=\"blank col17\" >&nbsp;</th>\n",
       "      <th class=\"blank col18\" >&nbsp;</th>\n",
       "      <th class=\"blank col19\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_ab298_level0_row0\" class=\"row_heading level0 row0\" >-1</th>\n",
       "      <td id=\"T_ab298_row0_col0\" class=\"data row0 col0\" >2240.347020</td>\n",
       "      <td id=\"T_ab298_row0_col1\" class=\"data row0 col1\" >0.645784</td>\n",
       "      <td id=\"T_ab298_row0_col2\" class=\"data row0 col2\" >21.281799</td>\n",
       "      <td id=\"T_ab298_row0_col3\" class=\"data row0 col3\" >25.961260</td>\n",
       "      <td id=\"T_ab298_row0_col4\" class=\"data row0 col4\" >2453.503750</td>\n",
       "      <td id=\"T_ab298_row0_col5\" class=\"data row0 col5\" >2752.757293</td>\n",
       "      <td id=\"T_ab298_row0_col6\" class=\"data row0 col6\" >0.246564</td>\n",
       "      <td id=\"T_ab298_row0_col7\" class=\"data row0 col7\" >0.086045</td>\n",
       "      <td id=\"T_ab298_row0_col8\" class=\"data row0 col8\" >0.051466</td>\n",
       "      <td id=\"T_ab298_row0_col9\" class=\"data row0 col9\" >0.123113</td>\n",
       "      <td id=\"T_ab298_row0_col10\" class=\"data row0 col10\" >0.172068</td>\n",
       "      <td id=\"T_ab298_row0_col11\" class=\"data row0 col11\" >0.240269</td>\n",
       "      <td id=\"T_ab298_row0_col12\" class=\"data row0 col12\" >0.068945</td>\n",
       "      <td id=\"T_ab298_row0_col13\" class=\"data row0 col13\" >0.076354</td>\n",
       "      <td id=\"T_ab298_row0_col14\" class=\"data row0 col14\" >0.559659</td>\n",
       "      <td id=\"T_ab298_row0_col15\" class=\"data row0 col15\" >0.586710</td>\n",
       "      <td id=\"T_ab298_row0_col16\" class=\"data row0 col16\" >0.314169</td>\n",
       "      <td id=\"T_ab298_row0_col17\" class=\"data row0 col17\" >0.283400</td>\n",
       "      <td id=\"T_ab298_row0_col18\" class=\"data row0 col18\" >0.056505</td>\n",
       "      <td id=\"T_ab298_row0_col19\" class=\"data row0 col19\" >0.052817</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x23480352390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.cluster import DBSCAN\n",
    "from sklearn.decomposition import PCA\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 데이터 준비 및 전처리\n",
    "df1_ins['대여일자'] = pd.to_datetime(df1_ins['대여일자'])\n",
    "\n",
    "# 주중/주말 구분\n",
    "df1_ins['주말여부'] = df1_ins['대여요일'].isin(['Saturday', 'Sunday'])\n",
    "\n",
    "# 시간대 구분\n",
    "df1_ins['점심시간'] = (df1_ins['대여시간'] >= 12) & (df1_ins['대여시간'] < 14)\n",
    "df1_ins['새벽시간'] = (df1_ins['대여시간'] >= 0) & (df1_ins['대여시간'] < 6)\n",
    "df1_ins['출근시간'] = (df1_ins['대여시간'] >= 7) & (df1_ins['대여시간'] < 9)\n",
    "df1_ins['퇴근시간'] = (df1_ins['대여시간'] >= 17) & (df1_ins['대여시간'] < 19)\n",
    "df1_ins['야간시간'] = (df1_ins['대여시간'] >= 19) & (df1_ins['대여시간'] < 24)\n",
    "\n",
    "# 대여대여소ID 기준 그룹화하여 통계 피처 생성\n",
    "grouped = df1_ins.groupby('대여대여소ID').agg({\n",
    "    '대여일자': 'count',  # 총 대여 횟수\n",
    "    '성별_M': 'mean',  # 남성 방문고객 비율\n",
    "    '이용시간(분)': ['mean', 'std'],  # 평균 이용시간 및 표준편차\n",
    "    '이용거리(M)': ['mean', 'std'],  # 평균 이용거리 및 표준편차\n",
    "    '주말여부': 'mean',  # 주말 대여 비율\n",
    "    '점심시간': 'mean',  # 점심시간 대여 비율\n",
    "    '새벽시간': 'mean',  # 새벽 대여 비율\n",
    "    '출근시간': 'mean',  # 출근 시간대 대여 비율\n",
    "    '퇴근시간': 'mean',  # 퇴근 시간대 대여 비율\n",
    "    '야간시간': 'mean'  # 야간 대여 비율\n",
    "}).reset_index()\n",
    "\n",
    "# 컬럼 이름 변경\n",
    "grouped.columns = [\n",
    "    '대여대여소ID', '총대여횟수', '남성고객비율', '평균이용시간', '이용시간표준편차',\n",
    "    '평균이용거리', '이용거리표준편차', '주말대여비율', '점심시간대여비율',\n",
    "    '새벽대여비율', '출근시간대여비율', '퇴근시간대여비율', '야간대여비율'\n",
    "]\n",
    "\n",
    "# 주중/주말 연령대별 고객 비율 계산 함수\n",
    "def calculate_ratios(df):\n",
    "    weekday_data = df[~df['주말여부']]\n",
    "    weekend_data = df[df['주말여부']]\n",
    "    \n",
    "    ratios = {\n",
    "        '주중청소년고객비율': (weekday_data['연령대'] == 10).mean(),\n",
    "        '주말청소년고객비율': (weekend_data['연령대'] == 10).mean(),\n",
    "        '주중청년고객비율': ((weekday_data['연령대'] == 20) | (weekday_data['연령대'] == 30)).mean(),\n",
    "        '주말청년고객비율': ((weekend_data['연령대'] == 20) | (weekend_data['연령대'] == 30)).mean(),\n",
    "        '주중장년고객비율': ((weekday_data['연령대'] == 40) | (weekday_data['연령대'] == 50)).mean(),\n",
    "        '주말장년고객비율': ((weekend_data['연령대'] == 40) | (weekend_data['연령대'] == 50)).mean(),\n",
    "        '주중노인고객비율': ((weekday_data['연령대'] == 60) | (weekday_data['연령대'] == 70)).mean(),\n",
    "        '주말노인고객비율': ((weekend_data['연령대'] == 60) | (weekend_data['연령대'] == 70)).mean()\n",
    "    }\n",
    "    return pd.Series(ratios)\n",
    "\n",
    "# 그룹화하여 추가 피처 계산\n",
    "additional_features = df1_ins.groupby('대여대여소ID').apply(calculate_ratios).reset_index()\n",
    "grouped = pd.merge(grouped, additional_features, on='대여대여소ID')\n",
    "\n",
    "# null 값 제거\n",
    "grouped = grouped.dropna()\n",
    "\n",
    "# 군집분석에 사용할 피처 선택\n",
    "features = grouped.drop(columns=['대여대여소ID'])\n",
    "\n",
    "# 표준화\n",
    "scaler = StandardScaler()\n",
    "scaled_features = scaler.fit_transform(features)\n",
    "\n",
    "# DBSCAN 군집분석 >> eps, min_samples 값 조정 필요!\n",
    "dbscan = DBSCAN(eps=0.7, min_samples=3)\n",
    "grouped['군집'] = dbscan.fit_predict(scaled_features)\n",
    "\n",
    "# PCA 적용\n",
    "pca = PCA(n_components=2)\n",
    "pca_features = pca.fit_transform(scaled_features)\n",
    "\n",
    "# PCA 결과를 데이터프레임에 추가\n",
    "grouped['PCA1'] = pca_features[:, 0]\n",
    "grouped['PCA2'] = pca_features[:, 1]\n",
    "\n",
    "# 군집 시각화\n",
    "plt.figure(figsize=(10, 7))\n",
    "plt.scatter(grouped['PCA1'], grouped['PCA2'], c=grouped['군집'], cmap='viridis')\n",
    "plt.xlabel('PCA1')\n",
    "plt.ylabel('PCA2')\n",
    "plt.title('대여소 군집 결과 (PCA, DBSCAN)')\n",
    "plt.colorbar(label='군집')\n",
    "plt.show()\n",
    "\n",
    "# 각 군집의 평균 값 계산 (대여대여소ID, PCA1, PCA2 제외)\n",
    "grouped_means = grouped.drop(columns=['대여대여소ID', 'PCA1', 'PCA2']).groupby('군집').mean()\n",
    "\n",
    "# 컬럼 별로 가장 높은 값을 가진 군집의 셀에 연한 초록색 배경 추가\n",
    "def highlight_max(s):\n",
    "    is_max = s == s.max()\n",
    "    return ['background-color: #ccffcc' if v else '' for v in is_max]\n",
    "\n",
    "styled_means = grouped_means.style.apply(highlight_max)\n",
    "\n",
    "# 결과 출력\n",
    "print(\"DBSCAN을 사용한 각 군집의 평균 값:\")\n",
    "display(styled_means)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5. k-means 보완"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- (1) 비율..이라고 해놓고 mean을 구해놓은 건에 대하여.. 새로고침\n",
    "- (1-1) 청년1,2 분류하기 이전"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\LG\\AppData\\Local\\Temp\\ipykernel_9436\\3874928948.py:65: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n",
      "  additional_features = df1_ins.groupby('대여대여소ID').apply(calculate_ratios).reset_index()\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      대여대여소ID  총대여횟수    남성고객비율     평균이용시간       평균이용거리    주말대여비율    새벽대여비율  \\\n",
      "0       ST-10   2764  0.641823  30.027135  2896.118784  0.308249  0.099493   \n",
      "1     ST-1000   3074  0.625895  19.268705  2427.495573  0.265777  0.036760   \n",
      "2     ST-1002   5895  0.658863  20.319932  2289.621218  0.298049  0.013740   \n",
      "3     ST-1003   1914  0.641066  17.774817  2121.170564  0.269592  0.060084   \n",
      "4     ST-1004   1543  0.736876  15.806870  1868.960045  0.288399  0.038885   \n",
      "5     ST-1005   5385  0.666295  16.411513  2028.707627  0.268152  0.043825   \n",
      "6     ST-1006   5129  0.584909  17.895301  2063.188239  0.254046  0.037044   \n",
      "7     ST-1007   1738  0.702532  19.873418  2323.346559  0.242232  0.107020   \n",
      "8     ST-1008   1562  0.620999  17.128681  2057.830787  0.255442  0.090909   \n",
      "9     ST-1010   2686  0.615041  17.107967  2060.121754  0.237156  0.084885   \n",
      "10    ST-1011   1591  0.698931  17.680075  2151.094519  0.241986  0.108737   \n",
      "11    ST-1012    781  0.580026  20.120359  2546.327324  0.199744  0.079385   \n",
      "12    ST-1013   1839  0.652529  17.926047  2100.868532  0.268080  0.079391   \n",
      "13    ST-1014   2110  0.757346  16.622749  1976.020043  0.174408  0.092891   \n",
      "14    ST-1015   5449  0.664342  15.335474  2033.100934  0.209029  0.027528   \n",
      "15    ST-1016    903  0.700997  17.579181  1963.192946  0.294574  0.058693   \n",
      "16    ST-1017   7777  0.607818  18.608332  1880.443046  0.308474  0.023531   \n",
      "17    ST-1018   4722  0.603558  20.476493  1754.971576  0.305167  0.027319   \n",
      "18    ST-1019   1251  0.494804  20.408473  2096.043909  0.302158  0.011191   \n",
      "19     ST-102   4542  0.589828  17.608983  1861.184447  0.275429  0.064069   \n",
      "20    ST-1020    459  0.612200  22.507625  2352.459869  0.274510  0.069717   \n",
      "21    ST-1023    215  0.623256  33.083721  4119.819721  0.446512  0.083721   \n",
      "22    ST-1024    296  0.652027  32.084459  3604.316115  0.368243  0.084459   \n",
      "23    ST-1025   1384  0.627168  17.930636  1936.868772  0.242775  0.055636   \n",
      "24    ST-1027   1048  0.743321  23.715649  1857.247023  0.295802  0.030534   \n",
      "25    ST-1028    694  0.550432  15.579251  1840.226585  0.266571  0.017291   \n",
      "26    ST-1029   2207  0.687812  18.700498  1917.995179  0.168101  0.023561   \n",
      "27     ST-103   1518  0.517128  19.182477  2629.554190  0.183794  0.050066   \n",
      "28    ST-1031    232  0.801724  11.461207  1623.920603  0.228448  0.116379   \n",
      "29    ST-1032   1256  0.703025  18.134554  2114.573957  0.261943  0.058121   \n",
      "30    ST-1033    723  0.623790  20.230982  2706.198396  0.246196  0.059474   \n",
      "31    ST-1034   1364  0.689150  16.321848  1968.103387  0.176686  0.016129   \n",
      "32    ST-1035   2169  0.626095  20.044260  2067.914786  0.268326  0.067312   \n",
      "33    ST-1036   2533  0.527438  22.032373  2410.296368  0.260561  0.037505   \n",
      "34    ST-1038    535  0.485981  12.620561  1467.208785  0.321495  0.057944   \n",
      "35    ST-1039    722  0.595568  15.493075  1939.576205  0.289474  0.055402   \n",
      "36    ST-1040   3813  0.683714  19.521637  2057.314377  0.127459  0.012064   \n",
      "37    ST-1041   5801  0.552491  22.614722  2040.038411  0.232201  0.036545   \n",
      "38    ST-1042   1416  0.715395  21.580508  2413.034562  0.170198  0.033898   \n",
      "39    ST-1044   1709  0.760094  18.361615  1864.995810  0.235225  0.037449   \n",
      "40    ST-1045   3053  0.633803  19.516869  1738.346931  0.252211  0.081559   \n",
      "41    ST-1046   5133  0.624196  19.441457  1859.437278  0.287746  0.055913   \n",
      "42    ST-1047   2301  0.520643  19.689266  2051.637631  0.276836  0.057366   \n",
      "43    ST-1048    947  0.658923  26.570222  3142.622027  0.261880  0.025343   \n",
      "44    ST-1049    679  0.678940  24.058910  3097.871149  0.225331  0.013255   \n",
      "45     ST-105   3583  0.583031  19.155735  1876.295093  0.205694  0.010047   \n",
      "46    ST-1050   1928  0.688797  17.575726  1997.172951  0.277490  0.066390   \n",
      "47    ST-1051    740  0.651351  23.005405  2353.244797  0.286486  0.040541   \n",
      "48    ST-1053   2131  0.696856  17.221492  1859.324298  0.324730  0.040357   \n",
      "49    ST-1054    497  0.501006  21.289738  2526.898672  0.273642  0.042254   \n",
      "50    ST-1055    554  0.575812  31.705776  2636.074639  0.272563  0.043321   \n",
      "51    ST-1056    310  0.606452  13.954839  1644.136226  0.274194  0.009677   \n",
      "52    ST-1058    886  0.628668  19.101580  1991.193352  0.261851  0.059819   \n",
      "53    ST-1059   1116  0.499104  19.947133  2235.886711  0.238351  0.034946   \n",
      "54     ST-106    334  0.631737  28.317365  2695.232695  0.176647  0.053892   \n",
      "55    ST-1061   7048  0.624858  21.274262  2094.012518  0.284620  0.064983   \n",
      "56    ST-1062   5361  0.653236  14.421004  1713.027691  0.237456  0.059690   \n",
      "57    ST-1063   6162  0.623337   8.630477   932.610446  0.160662  0.004869   \n",
      "58    ST-1064   8078  0.515227  10.692622  1166.555553  0.192251  0.012998   \n",
      "59    ST-1065  15049  0.626620  14.625689  1632.228739  0.241810  0.051764   \n",
      "60    ST-1067   4359  0.664373  17.231705  2208.648892  0.207616  0.021794   \n",
      "61    ST-1069   5338  0.617647  16.973586  2134.785384  0.196328  0.048707   \n",
      "62     ST-107   1713  0.521308  42.304729  4551.956287  0.413310  0.042615   \n",
      "63    ST-1070   4624  0.544983  21.247837  1899.899862  0.286332  0.033521   \n",
      "64    ST-1072   1254  0.578947  18.772727  2016.758676  0.228868  0.034290   \n",
      "65    ST-1075   1260  0.655556  16.850794  1861.088111  0.290476  0.053968   \n",
      "66    ST-1076   1892  0.618922  15.489429  1704.607077  0.173890  0.011628   \n",
      "67    ST-1077    804  0.717662  18.808458  2206.681381  0.304726  0.087065   \n",
      "68    ST-1078   2969  0.574267  20.889862  2307.792179  0.248905  0.049848   \n",
      "69    ST-1079   2445  0.567280  19.366871  2276.790524  0.230266  0.053988   \n",
      "70     ST-108   2780  0.572302  31.375540  2990.469169  0.266187  0.010791   \n",
      "71    ST-1081   4088  0.568982  19.916585  1978.505729  0.270548  0.048679   \n",
      "72    ST-1082    611  0.680851  15.851064  2406.016628  0.220949  0.067103   \n",
      "73    ST-1083   6365  0.527730  18.722074  1953.921962  0.245719  0.025609   \n",
      "74    ST-1084   1829  0.607983  18.451066  1992.090252  0.200656  0.049754   \n",
      "75    ST-1085   1365  0.561905  22.117949  2462.271436  0.241026  0.046154   \n",
      "76    ST-1086   2299  0.512832  26.902131  2449.067843  0.308395  0.006960   \n",
      "77    ST-1087   3519  0.509236  32.593635  2951.444899  0.435635  0.017903   \n",
      "78    ST-1088   3032  0.604222  21.590369  2052.265792  0.294525  0.043536   \n",
      "79    ST-1089   1593  0.662272  25.385436  2514.144903  0.302574  0.006277   \n",
      "80     ST-109   4482  0.525212  27.005355  3074.579643  0.268853  0.021419   \n",
      "81    ST-1092   2480  0.468548  18.181452  1698.632286  0.222984  0.040323   \n",
      "82    ST-1093   3942  0.628615  16.402588  1795.793983  0.240487  0.104515   \n",
      "83    ST-1095   2124  0.581450  25.928908  3289.557392  0.253766  0.055556   \n",
      "84    ST-1096    375  0.680000  24.805333  3089.876640  0.253333  0.125333   \n",
      "85    ST-1097   3134  0.621889  16.756860  1914.754968  0.261008  0.099553   \n",
      "86    ST-1098   4769  0.664290  19.116377  2158.201958  0.250367  0.070455   \n",
      "87    ST-1099   3097  0.570552  19.387149  2055.147514  0.315144  0.091702   \n",
      "88      ST-11   2337  0.621309  32.154044  3731.511819  0.307659  0.109970   \n",
      "89     ST-110   2656  0.627259  19.899849  2112.669326  0.269202  0.031250   \n",
      "90    ST-1100   1388  0.596542  22.574207  2244.815202  0.300432  0.120317   \n",
      "91    ST-1101   1264  0.673259  22.055380  2254.576661  0.268196  0.060918   \n",
      "92    ST-1102    998  0.791583  18.692385  2056.407926  0.207415  0.077154   \n",
      "93    ST-1103   2922  0.592745  25.811431  2519.954418  0.254620  0.079055   \n",
      "94    ST-1104   2712  0.610988  20.172198  2169.339889  0.277286  0.077434   \n",
      "95    ST-1105   4187  0.647003  19.841414  2160.874275  0.266062  0.101027   \n",
      "96    ST-1106   1396  0.722063  26.028653  3239.239900  0.267192  0.098138   \n",
      "97    ST-1107   1774  0.607103  22.138670  2681.525846  0.256483  0.062007   \n",
      "98    ST-1109   3760  0.682447  21.211170  2271.967191  0.277394  0.094415   \n",
      "99     ST-111   2459  0.581537  23.303782  2087.445868  0.181781  0.026434   \n",
      "100   ST-1110   1239  0.598063  20.874092  2134.039266  0.248588  0.071025   \n",
      "101   ST-1111   3851  0.622695  22.389509  3008.212885  0.257595  0.064139   \n",
      "102   ST-1114    786  0.678117  29.972010  4532.624148  0.212468  0.076336   \n",
      "103   ST-1118   6699  0.577400  20.352590  2371.064750  0.293327  0.056874   \n",
      "104   ST-1119   1930  0.606218  17.773057  1920.393715  0.287565  0.058549   \n",
      "105    ST-112   5164  0.600310  18.300542  1795.162949  0.184934  0.047637   \n",
      "106   ST-1120    695  0.558273  19.420144  2243.307482  0.299281  0.057554   \n",
      "107   ST-1121   8873  0.662910  19.400654  1944.299549  0.283782  0.055336   \n",
      "108   ST-1122   1379  0.604061  18.316171  2346.212088  0.282814  0.070341   \n",
      "109   ST-1123   5187  0.581646  19.331791  2287.494157  0.228649  0.040679   \n",
      "110   ST-1124   3534  0.597906  17.070741  1789.777295  0.292020  0.062535   \n",
      "111   ST-1125   3223  0.610922  23.040335  2499.410323  0.155445  0.020168   \n",
      "112   ST-1127   1694  0.533058  15.701299  1846.908601  0.284534  0.030697   \n",
      "113   ST-1128    959  0.637122  14.968717  1698.702669  0.246090  0.023983   \n",
      "114   ST-1129    800  0.666250  19.033750  2646.654437  0.277500  0.101250   \n",
      "115    ST-113   1121  0.536128  25.518287  3074.595558  0.272971  0.033898   \n",
      "116   ST-1130    464  0.566810  16.474138  1861.273556  0.256466  0.019397   \n",
      "117   ST-1131   1513  0.608063  28.517515  2966.239861  0.302049  0.028420   \n",
      "118   ST-1132   1671  0.508079  22.239378  2535.781149  0.290245  0.027528   \n",
      "119   ST-1133    555  0.542342  21.657658  2220.882541  0.236036  0.054054   \n",
      "120   ST-1135   1530  0.607190  20.215686  2232.636170  0.257516  0.081046   \n",
      "121   ST-1136   2860  0.555594  28.894406  4115.404559  0.290559  0.027273   \n",
      "122   ST-1137   6355  0.669394  17.154524  1561.205791  0.259953  0.053186   \n",
      "123    ST-114   2822  0.619064  20.434444  2025.994784  0.255493  0.047838   \n",
      "124   ST-1140   1510  0.675497  16.352318  1770.802742  0.141722  0.039735   \n",
      "125   ST-1141   1141  0.663453  11.937774  1447.839833  0.127082  0.005259   \n",
      "126   ST-1142   3221  0.737349  12.432474  1415.808476  0.189382  0.062093   \n",
      "127   ST-1143    427  0.796253  14.297424  1875.409906  0.252927  0.199063   \n",
      "128   ST-1144    769  0.669701  16.396619  1761.320494  0.223667  0.057217   \n",
      "129   ST-1146   1146  0.586387  14.601222  2028.565314  0.189354  0.032286   \n",
      "130   ST-1147   1388  0.540346  14.694524  1852.000829  0.204611  0.011527   \n",
      "131   ST-1148    437  0.601831  29.151030  3356.255675  0.244851  0.034325   \n",
      "132   ST-1149   3183  0.632108  13.736726  1720.410474  0.085140  0.017279   \n",
      "133   ST-1150   3718  0.710059  26.958042  3292.252367  0.316030  0.077999   \n",
      "134   ST-1151   2396  0.596828  22.177379  2515.873222  0.240818  0.030467   \n",
      "135   ST-1152   2771  0.704439  21.083003  2430.353685  0.239986  0.052328   \n",
      "136   ST-1153    112  0.571429  24.401786  2890.046429  0.294643  0.089286   \n",
      "137   ST-1154    621  0.602254  16.380032  1964.016023  0.251208  0.127214   \n",
      "138   ST-1156    589  0.516129  19.921902  2053.219525  0.312394  0.057725   \n",
      "139   ST-1158   1327  0.675207  28.834213  2710.231010  0.238131  0.027129   \n",
      "140    ST-116   1936  0.676653  17.768079  1779.244540  0.180785  0.011364   \n",
      "141   ST-1160   1882  0.665250  22.785866  2588.801913  0.231668  0.081296   \n",
      "142   ST-1161    598  0.561873  26.498328  2801.054465  0.188963  0.070234   \n",
      "143   ST-1162    596  0.498322  25.879195  3209.117819  0.285235  0.016779   \n",
      "144   ST-1163   1371  0.641867  26.277899  2767.285988  0.212254  0.037199   \n",
      "145   ST-1164    855  0.683041  28.208187  3441.749427  0.188304  0.036257   \n",
      "146   ST-1165   1187  0.605729  22.728728  2622.783454  0.224094  0.021061   \n",
      "147   ST-1166   2552  0.661050  17.622649  2016.343523  0.153213  0.016066   \n",
      "148   ST-1167    143  0.587413  24.790210  3067.858531  0.181818  0.006993   \n",
      "149   ST-1168   1576  0.592005  28.174492  3581.595057  0.274112  0.030457   \n",
      "150   ST-1169   1786  0.643337  29.842105  3990.740817  0.236282  0.049272   \n",
      "151    ST-117   1803  0.680532  20.404881  2068.360238  0.246811  0.031059   \n",
      "152   ST-1171   1445  0.632526  33.070588  3513.469488  0.274048  0.089273   \n",
      "153   ST-1172    613  0.727569  26.061990  2989.834095  0.230016  0.117455   \n",
      "154   ST-1173    879  0.642776  23.769056  3101.743003  0.167235  0.084187   \n",
      "155   ST-1174   1258  0.674086  36.511924  4270.344086  0.248808  0.124006   \n",
      "156   ST-1177    890  0.621348  18.125843  2066.816798  0.238202  0.056180   \n",
      "157   ST-1178   2300  0.721739  27.421304  2813.762561  0.184348  0.051304   \n",
      "158   ST-1179    734  0.675749  24.465940  2395.337357  0.277929  0.039510   \n",
      "159    ST-118   4253  0.613684  20.500353  2071.649979  0.252998  0.023748   \n",
      "160   ST-1180    677  0.608567  22.849335  2786.622762  0.209749  0.048744   \n",
      "161   ST-1181   1731  0.616407  29.139804  3354.262282  0.279607  0.030040   \n",
      "162   ST-1182   1248  0.706731  25.733173  3325.230986  0.281250  0.041667   \n",
      "163   ST-1184   2171  0.654998  21.248733  2658.103620  0.210502  0.021649   \n",
      "164   ST-1185    752  0.679521  17.087766  2583.411396  0.252660  0.018617   \n",
      "165   ST-1186   4579  0.716095  23.215768  3107.442804  0.231492  0.032103   \n",
      "166   ST-1188    359  0.635097  19.835655  2459.245125  0.295265  0.083565   \n",
      "167   ST-1189    631  0.477021  25.177496  3158.183170  0.213946  0.020602   \n",
      "168    ST-119   4872  0.668309  19.033662  1773.091121  0.146141  0.015599   \n",
      "169   ST-1190   1858  0.514532  20.266416  2292.608326  0.268568  0.052207   \n",
      "170   ST-1191   3680  0.567120  22.569565  2370.896601  0.247011  0.076902   \n",
      "171   ST-1192   2012  0.546720  13.868290  1704.157043  0.225149  0.046720   \n",
      "172   ST-1193   1433  0.576413  17.553385  1860.902742  0.249128  0.060014   \n",
      "173   ST-1194   5972  0.589920  16.874749  1708.040198  0.250000  0.058272   \n",
      "174   ST-1195   6198  0.630042  37.381736  5622.197331  0.321071  0.030494   \n",
      "175   ST-1197   4227  0.606104  15.951975  1711.975117  0.252188  0.028152   \n",
      "176   ST-1198   5204  0.586472  17.559185  2031.106412  0.239239  0.076480   \n",
      "177   ST-1199   3320  0.475000  44.250602  3691.817789  0.475301  0.010542   \n",
      "178     ST-12   1682  0.530321  21.862069  2252.724174  0.233056  0.076694   \n",
      "179   ST-1200   2372  0.600337  21.911889  2964.714427  0.273187  0.064503   \n",
      "180   ST-1201   3274  0.604459  23.789554  2955.940031  0.295052  0.078497   \n",
      "181   ST-1202   2692  0.578380  18.307207  2189.489060  0.249257  0.033804   \n",
      "182   ST-1203   1945  0.624679  20.215938  2335.302329  0.258098  0.103342   \n",
      "183   ST-1204   1385  0.691697  19.203610  2466.583365  0.233213  0.037545   \n",
      "184   ST-1206    369  0.772358  17.653117  2051.293198  0.252033  0.043360   \n",
      "185   ST-1207   1343  0.690990  15.015637  1698.292144  0.283693  0.050633   \n",
      "186   ST-1208    792  0.734848  20.229798  2402.817917  0.268939  0.068182   \n",
      "187    ST-121   3943  0.700228  22.020289  2238.113759  0.139234  0.014202   \n",
      "188   ST-1210   1281  0.721311  17.760343  2066.324660  0.298985  0.093677   \n",
      "189   ST-1211    654  0.706422  21.755352  2087.114343  0.235474  0.076453   \n",
      "190   ST-1212    878  0.691344  17.717540  1863.238235  0.243736  0.058087   \n",
      "191   ST-1213   1340  0.614925  22.971642  3251.619866  0.294030  0.068657   \n",
      "192   ST-1215   3535  0.679208  18.200566  2125.594690  0.228289  0.077511   \n",
      "193   ST-1216    305  0.511475  18.832787  2347.881738  0.229508  0.019672   \n",
      "194   ST-1217    387  0.764858  19.488372  3050.785168  0.284238  0.227390   \n",
      "195   ST-1218   2400  0.750000  18.035833  2108.616071  0.230000  0.037917   \n",
      "196   ST-1219   3399  0.745513  16.415711  2216.939503  0.210062  0.025596   \n",
      "197   ST-1220   3105  0.653462  20.847343  2488.483961  0.242512  0.047665   \n",
      "198   ST-1221   2740  0.632482  21.060584  2270.747602  0.219343  0.017153   \n",
      "199   ST-1222   2207  0.645220  17.060716  2090.559470  0.257363  0.070684   \n",
      "200   ST-1223   9854  0.660645  17.839761  2218.154577  0.240714  0.006393   \n",
      "201   ST-1224   2682  0.721849  17.469053  1789.674579  0.113721  0.022744   \n",
      "202   ST-1226   4011  0.674894  17.730491  2153.198018  0.228621  0.032660   \n",
      "203   ST-1227   1968  0.671748  19.765244  2358.961214  0.300813  0.033028   \n",
      "204   ST-1228   3219  0.684685  19.341410  2672.177335  0.223983  0.036968   \n",
      "205   ST-1229    922  0.584599  18.155098  2138.218297  0.224512  0.023861   \n",
      "206    ST-123   1888  0.704979  20.916314  2120.844815  0.181144  0.033898   \n",
      "207   ST-1230    753  0.772908  14.455511  1863.088486  0.278884  0.126162   \n",
      "208   ST-1231    336  0.755952  24.416667  3187.396071  0.211310  0.032738   \n",
      "209   ST-1233    395  0.741772  17.584810  2418.080101  0.202532  0.144304   \n",
      "210   ST-1235    905  0.648619  14.138122  1688.768287  0.248619  0.056354   \n",
      "211   ST-1236   2559  0.691286  19.160610  2268.380145  0.257913  0.062134   \n",
      "212   ST-1237   2810  0.692527  20.400000  2320.948915  0.245552  0.028470   \n",
      "213   ST-1238   1241  0.780822  21.576954  2057.391958  0.198227  0.089444   \n",
      "214   ST-1239   3639  0.744985  10.508656  1412.256980  0.194559  0.023083   \n",
      "215    ST-124   4710  0.754565  17.878344  1825.415115  0.101699  0.014013   \n",
      "216   ST-1241    518  0.669884  17.835907  2107.448861  0.191120  0.077220   \n",
      "217   ST-1243   1314  0.700152  18.422374  2737.817884  0.226788  0.037291   \n",
      "218   ST-1245    642  0.730530  24.130841  2678.868551  0.221184  0.077882   \n",
      "219   ST-1246    861  0.695703  24.782811  3193.397085  0.239257  0.078978   \n",
      "220   ST-1247    828  0.731884  26.368357  2320.820942  0.229469  0.055556   \n",
      "221   ST-1248    456  0.758772  34.570175  3331.034978  0.280702  0.140351   \n",
      "222   ST-1249   7275  0.614983  16.725361  1723.481446  0.244536  0.035739   \n",
      "223    ST-125   1124  0.702847  20.552491  2095.903665  0.128114  0.016904   \n",
      "224   ST-1250   1268  0.692429  17.152208  1908.498265  0.167192  0.016562   \n",
      "225   ST-1251  10339  0.600445  15.080472  1708.168325  0.227391  0.031531   \n",
      "226   ST-1252    868  0.697005  14.366359  1630.874735  0.167051  0.014977   \n",
      "227   ST-1253   5341  0.587530  10.330462  1153.954020  0.243587  0.018536   \n",
      "228   ST-1254   5645  0.663419  13.166342  1360.599708  0.246590  0.038441   \n",
      "229   ST-1259   3520  0.595739  19.021591  2167.140506  0.251705  0.116477   \n",
      "230    ST-126   2621  0.682564  22.457459  2686.550149  0.156429  0.008775   \n",
      "231   ST-1260    487  0.591376  22.607803  2691.566756  0.277207  0.092402   \n",
      "232   ST-1262    972  0.580247  22.306584  2550.786739  0.280864  0.104938   \n",
      "233   ST-1263   8477  0.608116  17.234281  1957.062178  0.239589  0.036923   \n",
      "234   ST-1264   2366  0.618343  18.035926  1931.783178  0.278107  0.095097   \n",
      "235   ST-1265   2123  0.658031  17.389543  1897.454249  0.276496  0.081959   \n",
      "236   ST-1266   3271  0.613574  26.042189  3045.158423  0.262611  0.075206   \n",
      "237   ST-1267    823  0.732685  25.334143  3291.074070  0.330498  0.021871   \n",
      "238   ST-1268   5680  0.648944  22.920775  2586.963039  0.271127  0.061444   \n",
      "239   ST-1269   1294  0.680835  21.035549  2409.153532  0.271252  0.097372   \n",
      "240   ST-1270   2810  0.674377  23.136299  2382.512527  0.259786  0.165480   \n",
      "241   ST-1271   1509  0.611001  16.195494  1812.585898  0.259775  0.046388   \n",
      "242   ST-1273   1578  0.700887  20.761090  2383.951248  0.274398  0.130545   \n",
      "243   ST-1274   2592  0.693673  19.795910  2167.221848  0.205247  0.042824   \n",
      "244   ST-1275   6477  0.659565  17.482631  2028.586647  0.262930  0.036128   \n",
      "245   ST-1276   1031  0.699321  17.540252  2021.299767  0.133851  0.059166   \n",
      "246   ST-1277    604  0.791391  17.706954  2013.560679  0.125828  0.051325   \n",
      "247   ST-1278   3016  0.598143  21.468170  2484.282321  0.264589  0.042772   \n",
      "248   ST-1279   4788  0.586884  22.746867  2429.207957  0.306182  0.047410   \n",
      "249   ST-1280   5537  0.704714  18.108904  2364.417347  0.206791  0.047499   \n",
      "250   ST-1281    447  0.619687  21.192394  2309.931320  0.328859  0.078300   \n",
      "251   ST-1282   2801  0.704034  16.544805  1987.019704  0.278829  0.034273   \n",
      "252   ST-1283   1471  0.683889  17.583277  2394.721224  0.247451  0.062542   \n",
      "253   ST-1284   2957  0.609063  16.998647  1973.534954  0.236388  0.041934   \n",
      "254   ST-1285   5032  0.633545  17.540143  1942.812077  0.273450  0.026033   \n",
      "255   ST-1286   3981  0.604873  17.695303  1831.609256  0.237378  0.065059   \n",
      "256   ST-1287   2751  0.589967  18.338059  2054.048437  0.200654  0.062886   \n",
      "257   ST-1288   1421  0.660099  21.714989  2657.699254  0.182266  0.026742   \n",
      "258   ST-1289   1285  0.559533  20.403891  2959.139650  0.282490  0.075486   \n",
      "259   ST-1291   5204  0.590892  22.616641  2435.647936  0.235780  0.030553   \n",
      "260   ST-1292   1484  0.508760  20.487197  2343.366301  0.211590  0.012129   \n",
      "261   ST-1293    800  0.671250  22.402500  2740.620388  0.292500  0.030000   \n",
      "262   ST-1295   1194  0.757956  17.494975  2109.565251  0.214405  0.091290   \n",
      "263   ST-1296   1840  0.647283  18.636957  2146.651793  0.275543  0.067391   \n",
      "264   ST-1297   1034  0.470986  23.968085  2967.246025  0.266925  0.037718   \n",
      "265   ST-1298   2042  0.663075  17.331048  1911.393624  0.248776  0.049951   \n",
      "266   ST-1299   1967  0.679207  22.095577  2002.349654  0.217082  0.048805   \n",
      "267    ST-130   1754  0.596351  24.425314  1994.376591  0.316420  0.006271   \n",
      "268   ST-1300   5705  0.622086  20.882033  2101.468924  0.242594  0.045223   \n",
      "269   ST-1302   2381  0.591348  24.032759  3176.374481  0.298614  0.097438   \n",
      "270   ST-1305   2799  0.732404  25.994284  2432.848146  0.195784  0.041086   \n",
      "271   ST-1306    871  0.644087  21.861079  2295.644179  0.211251  0.017222   \n",
      "272   ST-1307    678  0.626844  21.749263  2124.992389  0.219764  0.081121   \n",
      "273   ST-1309    456  0.631579  14.092105  1586.872763  0.212719  0.105263   \n",
      "274   ST-1310    312  0.727564  15.548077  2193.217212  0.205128  0.041667   \n",
      "275   ST-1311    630  0.593651  31.476190  4191.489159  0.279365  0.025397   \n",
      "276   ST-1312     38  0.631579  23.157895  2874.690789  0.289474  0.368421   \n",
      "277   ST-1313     67  0.716418  19.910448  2530.448358  0.223881  0.044776   \n",
      "278   ST-1314     72  0.583333  20.208333  2892.218750  0.180556  0.055556   \n",
      "279   ST-1315    163  0.840491  20.588957  2854.023681  0.202454  0.079755   \n",
      "280   ST-1317   4109  0.676077  19.337065  1955.076554  0.192748  0.039912   \n",
      "281    ST-132   3646  0.675535  19.889468  2008.315277  0.166758  0.023039   \n",
      "282   ST-1320   5248  0.657774  17.972942  1895.629057  0.232279  0.049543   \n",
      "283   ST-1321   2953  0.650525  20.554690  2451.277199  0.241111  0.053166   \n",
      "284   ST-1323   4615  0.669122  21.230553  2780.322141  0.268256  0.058722   \n",
      "285   ST-1324    521  0.856046  19.107486  1966.127678  0.119002  0.001919   \n",
      "286   ST-1325   1791  0.667783  20.907314  2292.379162  0.282524  0.065885   \n",
      "287   ST-1326   3404  0.600470  29.553760  3910.293364  0.330787  0.052585   \n",
      "288   ST-1327    679  0.686303  16.888071  2512.480619  0.300442  0.011782   \n",
      "289   ST-1328    268  0.649254  27.884328  2511.765112  0.365672  0.067164   \n",
      "290   ST-1329   1330  0.689474  15.939098  1678.546639  0.300752  0.075940   \n",
      "291   ST-1331   3960  0.534091  20.636111  2422.702646  0.241414  0.059091   \n",
      "292   ST-1332   2500  0.601200  15.194000  1751.533792  0.266400  0.035600   \n",
      "293   ST-1333   3705  0.663428  20.746559  2711.901120  0.205938  0.024291   \n",
      "294   ST-1334   4037  0.609116  24.087689  3349.411573  0.286847  0.054991   \n",
      "295   ST-1335   4500  0.602889  30.842667  3932.837776  0.308222  0.035333   \n",
      "296   ST-1337   2830  0.616608  20.629682  2305.669438  0.281979  0.068198   \n",
      "297   ST-1338   2126  0.706021  12.733772  1309.973579  0.225776  0.025870   \n",
      "298   ST-1339   1940  0.622680  28.392784  3183.315773  0.258763  0.028866   \n",
      "299    ST-134   1696  0.714033  22.360849  2240.543101  0.149764  0.014151   \n",
      "300   ST-1341   3038  0.656682  20.232719  1973.239477  0.236011  0.048387   \n",
      "301   ST-1342   2628  0.671994  16.487062  1734.887272  0.230974  0.037671   \n",
      "302   ST-1343   1605  0.572586  37.996262  5459.141813  0.332710  0.024299   \n",
      "303   ST-1344   2407  0.517657  43.778563  6369.290320  0.311591  0.053594   \n",
      "304   ST-1345    288  0.704861  21.208333  2396.757187  0.267361  0.027778   \n",
      "305   ST-1346   1723  0.668021  16.041788  1794.380424  0.247243  0.121300   \n",
      "306   ST-1347   4850  0.587835  24.850309  3504.064728  0.306804  0.064330   \n",
      "307   ST-1348    464  0.691810  15.903017  1581.889741  0.140086  0.008621   \n",
      "308   ST-1349   2860  0.529720  23.475874  3100.380535  0.294755  0.021329   \n",
      "309   ST-1350   2569  0.572207  22.599455  2965.164173  0.195018  0.016738   \n",
      "310   ST-1351   7698  0.598467  16.427903  1637.772616  0.242660  0.034295   \n",
      "311   ST-1352   6979  0.538616  11.373406  1278.228647  0.244304  0.023212   \n",
      "312   ST-1353   2779  0.620727  16.497661  1924.495707  0.263044  0.066931   \n",
      "313   ST-1355     63  0.777778  18.444444  2183.338095  0.412698  0.079365   \n",
      "314   ST-1356    922  0.599783  17.595445  1919.295586  0.164859  0.016269   \n",
      "315   ST-1357   3519  0.577721  23.651890  3128.517096  0.287582  0.042626   \n",
      "316    ST-136   2228  0.738330  26.028725  2517.103658  0.127469  0.010323   \n",
      "317   ST-1360   1485  0.690909  19.783165  2239.239044  0.186532  0.030303   \n",
      "318   ST-1361   2827  0.711709  22.063672  2360.300141  0.205164  0.042448   \n",
      "319   ST-1364   3065  0.578140  18.622186  2491.834225  0.236542  0.063622   \n",
      "320   ST-1365    904  0.675885  24.949115  2822.665022  0.243363  0.087389   \n",
      "321   ST-1366    575  0.624348  26.446957  2885.239357  0.234783  0.043478   \n",
      "322   ST-1367   1114  0.642729  23.125673  2655.024336  0.261221  0.011670   \n",
      "323    ST-137   1784  0.693946  28.883408  2565.823027  0.197870  0.029709   \n",
      "324   ST-1370    130  0.761538  19.415385  1784.324538  0.207692  0.069231   \n",
      "325   ST-1371   1085  0.546544  19.903226  1975.707097  0.261751  0.047005   \n",
      "326   ST-1372   4204  0.529020  25.097764  2334.431665  0.155804  0.021646   \n",
      "327   ST-1373   1963  0.724911  17.431482  1952.360092  0.149771  0.013245   \n",
      "328   ST-1374   2125  0.693176  16.478588  1968.286800  0.256000  0.051294   \n",
      "329   ST-1375   4463  0.613713  15.644858  1780.828949  0.242214  0.040332   \n",
      "330   ST-1376   3018  0.730948  20.933400  2271.121471  0.233930  0.062624   \n",
      "331   ST-1378   5462  0.598316  16.400220  1764.259226  0.228671  0.056573   \n",
      "332   ST-1379    604  0.658940  20.221854  2128.184189  0.283113  0.100993   \n",
      "333    ST-138    779  0.722721  23.955071  2276.525366  0.256739  0.005135   \n",
      "334   ST-1380   2410  0.719917  18.849378  2027.571905  0.283402  0.097925   \n",
      "335   ST-1381   1066  0.647280  17.814259  1959.002129  0.228893  0.074109   \n",
      "336   ST-1383    517  0.787234  23.667311  2924.624178  0.324952  0.147002   \n",
      "337   ST-1384   1151  0.735013  21.944396  2732.575352  0.294526  0.129453   \n",
      "338   ST-1386   1089  0.748393  20.852158  2583.808613  0.236915  0.132231   \n",
      "339   ST-1387   1016  0.635827  26.195866  3782.419400  0.355315  0.039370   \n",
      "340   ST-1388    420  0.490476  24.428571  2774.399286  0.292857  0.085714   \n",
      "341   ST-1389   1322  0.528744  24.670953  2591.711641  0.278366  0.048411   \n",
      "342   ST-1390   1863  0.645196  19.319914  1859.588164  0.272678  0.069780   \n",
      "343   ST-1391    384  0.750000  20.739583  1875.521979  0.281250  0.062500   \n",
      "344   ST-1392    629  0.775835  22.745628  2508.010731  0.278219  0.087440   \n",
      "345   ST-1394    705  0.529078  22.774468  1974.998071  0.164539  0.024113   \n",
      "346   ST-1395    791  0.725664  24.958281  3562.536296  0.173198  0.069532   \n",
      "347   ST-1396    166  0.680723  26.000000  4033.812892  0.144578  0.030120   \n",
      "348   ST-1397   2573  0.643995  19.718228  2266.619254  0.248348  0.035756   \n",
      "349   ST-1398   1668  0.686451  17.715228  2081.343016  0.288969  0.067746   \n",
      "350    ST-140   1530  0.694771  26.747059  2799.329039  0.220915  0.023529   \n",
      "351   ST-1400   2045  0.668949  20.725672  2522.151267  0.243521  0.037164   \n",
      "352   ST-1402   2665  0.560225  13.079925  1451.030589  0.228893  0.045403   \n",
      "353   ST-1403   6092  0.759849  17.309258  2298.317896  0.134110  0.013296   \n",
      "354   ST-1404   1186  0.684654  21.913153  2509.551492  0.206577  0.035413   \n",
      "355   ST-1406   1301  0.622598  21.936972  2135.224504  0.194466  0.025365   \n",
      "356   ST-1407   1341  0.673378  20.136465  2514.481186  0.281133  0.126025   \n",
      "357   ST-1408   1304  0.619632  24.750767  2839.603811  0.256902  0.053681   \n",
      "358   ST-1409   3531  0.631266  23.237893  2376.456389  0.226848  0.043047   \n",
      "359   ST-1410    484  0.652893  17.514463  2362.497087  0.233471  0.035124   \n",
      "360   ST-1411    789  0.628644  24.456274  2730.265944  0.254753  0.051965   \n",
      "361   ST-1413   2783  0.608696  24.053899  3064.106213  0.255839  0.061085   \n",
      "362   ST-1414    288  0.565972  19.899306  1998.548056  0.236111  0.065972   \n",
      "363   ST-1416    793  0.727617  20.071879  2321.972963  0.245902  0.056747   \n",
      "364   ST-1417   1709  0.609128  20.459333  2602.000690  0.301931  0.067876   \n",
      "365   ST-1418    730  0.682192  21.272603  2260.299849  0.264384  0.057534   \n",
      "366   ST-1419   1705  0.608798  17.935484  1995.773977  0.284457  0.076246   \n",
      "367    ST-142   2648  0.694864  19.780211  2082.671507  0.177870  0.014728   \n",
      "368   ST-1420   7596  0.611901  16.560953  1704.521496  0.251053  0.057662   \n",
      "369   ST-1421   2297  0.688724  22.854593  2792.127423  0.263822  0.041794   \n",
      "370   ST-1422    979  0.595506  23.249234  2491.592594  0.260470  0.013279   \n",
      "371   ST-1423   1115  0.707623  21.213453  2436.637166  0.247534  0.097758   \n",
      "372   ST-1424   1733  0.620889  16.112522  2108.564686  0.227351  0.065782   \n",
      "373   ST-1425   2743  0.607364  16.605177  2080.454287  0.260299  0.045935   \n",
      "374   ST-1426   1017  0.652901  22.127827  2076.725644  0.278269  0.036382   \n",
      "375   ST-1427   1075  0.571163  19.080930  2290.061172  0.275349  0.120000   \n",
      "376   ST-1428    253  0.671937  16.158103  1503.812016  0.177866  0.031621   \n",
      "377   ST-1429   2166  0.706371  14.831025  1353.293717  0.088181  0.006002   \n",
      "378    ST-143   2524  0.702060  19.233756  1863.164699  0.226228  0.041997   \n",
      "379   ST-1432    881  0.643587  21.414302  2330.577639  0.271283  0.040863   \n",
      "380   ST-1433    954  0.697065  23.349057  2759.556268  0.237945  0.035639   \n",
      "381   ST-1434    471  0.675159  18.594480  2335.212548  0.195329  0.040340   \n",
      "382   ST-1435   2786  0.689519  22.298995  2387.098945  0.243001  0.028356   \n",
      "383   ST-1436   1452  0.729339  16.384298  2132.200888  0.226584  0.049587   \n",
      "384   ST-1437   1143  0.687664  33.789151  2103.086789  0.164479  0.021872   \n",
      "385   ST-1438    258  0.790698  17.724806  1974.424341  0.267442  0.077519   \n",
      "386   ST-1439   1478  0.627199  21.067659  2067.325318  0.232070  0.046008   \n",
      "387    ST-144   1502  0.685752  21.533955  2298.822144  0.256991  0.059920   \n",
      "388   ST-1440   6123  0.599869  20.466765  2479.503092  0.251184  0.125102   \n",
      "389   ST-1441   1527  0.602489  34.693517  5136.122207  0.281598  0.056974   \n",
      "390   ST-1442    748  0.624332  23.627005  2255.384933  0.272727  0.048128   \n",
      "391   ST-1443   3662  0.661114  25.641453  3359.152414  0.230475  0.029219   \n",
      "392   ST-1445    644  0.658385  25.319876  3284.745543  0.324534  0.059006   \n",
      "393   ST-1446   1929  0.641783  26.455677  3190.137963  0.288751  0.062208   \n",
      "394   ST-1447   1446  0.719225  25.515906  3527.408492  0.230290  0.024205   \n",
      "395   ST-1449   1371  0.725018  18.940190  1972.387987  0.286652  0.084610   \n",
      "396    ST-145   2705  0.618484  23.089464  2453.782717  0.217745  0.029205   \n",
      "397   ST-1451   4201  0.632468  15.884551  1876.712461  0.274935  0.064032   \n",
      "398   ST-1452    466  0.759657  24.223176  3104.603498  0.315451  0.128755   \n",
      "399   ST-1454   2673  0.653947  18.964834  2165.549031  0.254770  0.069211   \n",
      "400   ST-1455   3620  0.634254  17.063536  2127.608633  0.268508  0.051657   \n",
      "401   ST-1456   1457  0.610158  16.322581  2136.428332  0.297186  0.083734   \n",
      "402   ST-1457    496  0.659274  16.495968  2063.609577  0.270161  0.026210   \n",
      "403   ST-1458    486  0.508230  22.269547  2714.107593  0.255144  0.043210   \n",
      "404   ST-1459    793  0.558638  15.279950  1582.625687  0.242119  0.045397   \n",
      "405   ST-1460   1586  0.505044  23.930643  2572.765530  0.253468  0.031526   \n",
      "406   ST-1461   1775  0.680563  19.233239  2291.835758  0.328451  0.079437   \n",
      "407   ST-1462    422  0.703791  22.824645  3045.942275  0.286730  0.059242   \n",
      "408   ST-1463    432  0.712963  26.391204  3101.123264  0.319444  0.034722   \n",
      "409   ST-1464   1203  0.698254  20.424771  2084.982984  0.253533  0.087282   \n",
      "410   ST-1465   1288  0.670807  19.329969  2189.206421  0.268634  0.104814   \n",
      "411   ST-1466   1262  0.636292  19.492868  2267.597750  0.272583  0.061807   \n",
      "412   ST-1467   1681  0.619274  22.016062  2259.358084  0.277216  0.080309   \n",
      "413   ST-1468    987  0.643364  18.950355  2025.831692  0.279635  0.030395   \n",
      "414   ST-1469   2903  0.661385  23.137788  2993.475529  0.263865  0.092663   \n",
      "415    ST-147   1492  0.745308  21.769437  2254.640402  0.101877  0.012064   \n",
      "416   ST-1470   2603  0.586631  19.141375  2304.255367  0.229351  0.044948   \n",
      "417   ST-1473   3617  0.647774  18.060547  2095.902275  0.223666  0.067736   \n",
      "418   ST-1474   6540  0.608869  19.198624  2219.610318  0.257492  0.080734   \n",
      "419   ST-1475   2566  0.723694  16.909587  2107.142966  0.249415  0.043648   \n",
      "420   ST-1476   2978  0.607790  20.703828  2355.010850  0.279046  0.084956   \n",
      "421   ST-1479   2221  0.665916  16.016659  1789.040941  0.263845  0.058532   \n",
      "422    ST-148   1278  0.691706  21.061033  2090.425430  0.139280  0.015649   \n",
      "423   ST-1480    454  0.640969  33.605727  3917.254251  0.363436  0.158590   \n",
      "424   ST-1481   1256  0.717357  13.144904  1586.657707  0.203822  0.050159   \n",
      "425   ST-1482   2576  0.668090  20.633540  2174.235524  0.277950  0.075311   \n",
      "426   ST-1483   1840  0.640761  17.257065  1838.703701  0.325543  0.059783   \n",
      "427   ST-1484   1490  0.647651  19.052349  1865.010188  0.308054  0.052349   \n",
      "428   ST-1485    690  0.672464  16.456522  1809.317406  0.255072  0.127536   \n",
      "429   ST-1486    804  0.741294  16.324627  2002.640386  0.264925  0.048507   \n",
      "430   ST-1487    324  0.592593  28.320988  1917.918951  0.416667  0.012346   \n",
      "431   ST-1488    593  0.590219  24.229342  2478.521197  0.295110  0.065767   \n",
      "432   ST-1489    184  0.771739  10.510870  1547.943424  0.309783  0.021739   \n",
      "433   ST-1490    250  0.864000  19.116000  1894.943640  0.216000  0.016000   \n",
      "434   ST-1491   1889  0.686077  28.459502  3366.321662  0.257808  0.093700   \n",
      "435   ST-1492   1354  0.618907  17.111521  2009.865251  0.256278  0.077548   \n",
      "436   ST-1493    646  0.551084  18.291022  2224.518483  0.258514  0.043344   \n",
      "437   ST-1494    613  0.574225  22.481240  2033.812953  0.243067  0.029364   \n",
      "438   ST-1495   3649  0.640723  16.308304  1664.609830  0.325295  0.031790   \n",
      "439   ST-1496   5700  0.624737  19.376140  1858.026212  0.270175  0.034561   \n",
      "440   ST-1497   2642  0.627555  20.580999  2328.944557  0.309235  0.035958   \n",
      "441   ST-1498   1296  0.747685  18.910494  2179.929182  0.243827  0.035494   \n",
      "442   ST-1499   2240  0.669643  15.928571  1822.587960  0.307143  0.038393   \n",
      "443     ST-15   1310  0.607634  32.538931  3909.020870  0.356489  0.083206   \n",
      "444    ST-150   2643  0.692773  21.087779  1979.798131  0.204313  0.050322   \n",
      "445   ST-1500   1559  0.684413  18.201411  2388.473085  0.268121  0.035920   \n",
      "446   ST-1501   1024  0.710938  20.549805  2456.970361  0.234375  0.058594   \n",
      "447   ST-1503    941  0.646121  28.676939  3351.104176  0.293305  0.049947   \n",
      "448   ST-1504   2363  0.632670  15.487093  1584.178963  0.292848  0.033009   \n",
      "449   ST-1506   4664  0.746355  15.362350  1851.739981  0.207333  0.026587   \n",
      "450   ST-1507   1553  0.637476  20.657437  2338.256291  0.251127  0.043786   \n",
      "451   ST-1508   1884  0.613057  18.980361  2157.403546  0.274416  0.054140   \n",
      "452   ST-1509   3098  0.602324  19.522918  2299.129383  0.224015  0.039380   \n",
      "453    ST-151   1883  0.711099  22.121083  2116.130765  0.178439  0.044610   \n",
      "454   ST-1510   5427  0.573429  14.674774  1670.178006  0.248756  0.077575   \n",
      "455   ST-1511   2530  0.526877  14.052964  1689.767941  0.202372  0.019368   \n",
      "456   ST-1512   2492  0.640449  15.240770  1788.166481  0.204254  0.035714   \n",
      "457   ST-1514   3698  0.558951  13.453759  1586.976677  0.198486  0.029475   \n",
      "458   ST-1515   1962  0.765545  17.408767  1881.692176  0.226300  0.069827   \n",
      "459   ST-1517   4831  0.566342  12.499897  1336.801898  0.204513  0.034775   \n",
      "460   ST-1518    586  0.747440  16.428328  2091.578038  0.075085  0.129693   \n",
      "461   ST-1519   5450  0.521651  15.226789  1687.829602  0.185505  0.027890   \n",
      "462    ST-152   2205  0.700680  22.883900  2208.688830  0.176871  0.039456   \n",
      "463   ST-1520   1029  0.844509  17.190476  2125.123936  0.201166  0.011662   \n",
      "464   ST-1521   6133  0.618621  24.026904  2835.957062  0.131420  0.019892   \n",
      "465   ST-1522   1790  0.702793  30.896089  4744.812374  0.259218  0.061453   \n",
      "466   ST-1523   3587  0.630332  19.454419  2509.098893  0.240591  0.039866   \n",
      "467   ST-1526   2539  0.671524  19.967704  2419.519527  0.287121  0.108704   \n",
      "468   ST-1527   1030  0.737864  13.007767  1699.012427  0.262136  0.061165   \n",
      "469   ST-1528   1119  0.594281  12.932082  1457.884799  0.241287  0.029491   \n",
      "470   ST-1529   3022  0.632694  15.536400  1841.047310  0.259431  0.041363   \n",
      "471    ST-153   1433  0.590370  15.294487  1704.947202  0.240754  0.030007   \n",
      "472   ST-1531   3578  0.628843  30.631079  4641.282714  0.264952  0.014254   \n",
      "473   ST-1534    892  0.617713  15.687220  1726.617096  0.201794  0.033632   \n",
      "474   ST-1535   1395  0.718996  14.281720  1760.615297  0.179928  0.030108   \n",
      "475   ST-1536    426  0.875587  27.903756  3268.893685  0.218310  0.140845   \n",
      "476   ST-1537   1393  0.712132  21.316583  2222.789462  0.290022  0.027997   \n",
      "477   ST-1538    432  0.650463  18.546296  2248.209954  0.215278  0.023148   \n",
      "478   ST-1539   4567  0.683819  16.469017  1673.869170  0.241953  0.051675   \n",
      "479    ST-154   1144  0.647727  21.826923  1817.262107  0.186189  0.040210   \n",
      "480   ST-1540   1833  0.708129  24.107474  3027.695565  0.279324  0.043099   \n",
      "481   ST-1541   1693  0.593030  22.531010  2122.913503  0.239811  0.089191   \n",
      "482   ST-1542   1756  0.625285  17.463554  2065.794072  0.261959  0.044419   \n",
      "483   ST-1543   3156  0.629278  23.288023  2638.843565  0.284537  0.046895   \n",
      "484   ST-1544    188  0.734043  15.909574  1662.686649  0.196809  0.058511   \n",
      "485   ST-1545   2644  0.704614  27.965204  3693.916161  0.308623  0.048033   \n",
      "486   ST-1546  12473  0.650766  20.811272  2362.459600  0.266255  0.031187   \n",
      "487   ST-1547    785  0.751592  19.871338  2834.606115  0.273885  0.026752   \n",
      "488   ST-1548   2238  0.577748  18.104111  2005.052927  0.279714  0.075961   \n",
      "489    ST-155   2287  0.682991  25.048972  1699.258312  0.184521  0.027984   \n",
      "490   ST-1552    734  0.574932  21.408719  3091.584959  0.258856  0.046322   \n",
      "491   ST-1553    918  0.659041  22.610022  2468.615991  0.242919  0.035948   \n",
      "492   ST-1554   1738  0.653049  21.569620  2727.064350  0.205984  0.060990   \n",
      "493   ST-1555   1704  0.666667  27.110915  3203.208844  0.289319  0.091549   \n",
      "494   ST-1556   2954  0.728165  29.866283  2501.315105  0.186527  0.037576   \n",
      "495   ST-1557    168  0.750000  20.440476  2079.906607  0.363095  0.053571   \n",
      "496   ST-1559   1548  0.678941  23.485788  2682.896977  0.288760  0.096899   \n",
      "497    ST-156   2676  0.618087  15.628550  1786.628479  0.255605  0.106502   \n",
      "498   ST-1560    558  0.693548  21.322581  2633.222061  0.267025  0.145161   \n",
      "499   ST-1561     18  0.611111  16.055556  2419.310000  0.277778  0.055556   \n",
      "500   ST-1562    194  0.577320  13.118557  2031.338351  0.319588  0.067010   \n",
      "501   ST-1563    161  0.633540  18.639752  2243.300745  0.204969  0.062112   \n",
      "502   ST-1564   1529  0.738391  17.488555  2191.978855  0.221060  0.047744   \n",
      "503   ST-1565     84  0.809524  18.702381  1640.210595  0.297619  0.035714   \n",
      "504   ST-1566    716  0.548883  32.877095  4407.557346  0.349162  0.048883   \n",
      "505   ST-1568    552  0.606884  20.117754  2321.453080  0.173913  0.061594   \n",
      "506    ST-157   2649  0.658362  17.579464  1625.972118  0.219706  0.035485   \n",
      "507   ST-1571    583  0.668954  22.600343  2765.943345  0.255575  0.073756   \n",
      "508   ST-1573   1957  0.599898  23.968830  2844.648406  0.302504  0.055697   \n",
      "509   ST-1574   2930  0.644027  25.418089  3326.482495  0.282935  0.049147   \n",
      "510   ST-1575   1745  0.677937  21.413754  2769.878229  0.173066  0.021203   \n",
      "511   ST-1576    539  0.643785  29.912801  3540.165269  0.205937  0.070501   \n",
      "512   ST-1577   2472  0.745550  26.324838  2737.286076  0.215210  0.082120   \n",
      "513   ST-1578   1305  0.523372  17.876628  1994.663732  0.215326  0.032184   \n",
      "514   ST-1579   1223  0.556827  24.107931  2922.702600  0.273917  0.080948   \n",
      "515    ST-158   4475  0.584358  17.521341  1886.590561  0.238436  0.046927   \n",
      "516   ST-1580   2619  0.630011  18.561665  1957.901260  0.126766  0.010691   \n",
      "517   ST-1582   4877  0.517736  18.645274  1804.747564  0.277220  0.048595   \n",
      "518   ST-1584   7238  0.559409  24.509533  2567.870771  0.262503  0.017823   \n",
      "519   ST-1585   1412  0.521246  18.480878  1883.675581  0.303116  0.027620   \n",
      "520   ST-1586   5284  0.517033  21.183952  2080.342916  0.323808  0.027631   \n",
      "521   ST-1588    934  0.664882  19.458244  2157.557966  0.239829  0.036403   \n",
      "522   ST-1589   1223  0.689289  23.053148  2773.370760  0.254293  0.088307   \n",
      "523    ST-159   2064  0.722384  17.139050  1629.944767  0.194767  0.053779   \n",
      "524   ST-1590   3981  0.548857  18.360211  1890.275931  0.307209  0.047224   \n",
      "525   ST-1592   1543  0.544394  17.619572  1797.499119  0.252106  0.029812   \n",
      "526   ST-1593     32  0.687500  15.781250  1759.193438  0.093750  0.000000   \n",
      "527   ST-1594    611  0.649755  24.386252  2407.164632  0.207856  0.022913   \n",
      "528   ST-1595    597  0.730318  22.189280  2060.479129  0.276382  0.020101   \n",
      "529   ST-1597    719  0.520167  25.235049  2604.455577  0.233658  0.027816   \n",
      "530   ST-1598   1220  0.476230  25.353279  2087.593377  0.187705  0.013115   \n",
      "531   ST-1599   1136  0.588028  34.081866  4353.406664  0.262324  0.062500   \n",
      "532     ST-16   2177  0.654111  29.108865  3211.692393  0.300873  0.106109   \n",
      "533    ST-160   2962  0.773464  13.380824  1561.779483  0.211681  0.055706   \n",
      "534   ST-1601     29  0.793103  19.827586  2113.989310  0.344828  0.034483   \n",
      "535   ST-1602   2241  0.573405  32.231593  4282.160986  0.328425  0.012941   \n",
      "536   ST-1603   1423  0.567112  21.819396  2190.852741  0.309909  0.028812   \n",
      "537   ST-1605   1554  0.694981  26.828185  1955.664028  0.182754  0.055985   \n",
      "538   ST-1606   2396  0.689900  21.233723  1960.016461  0.222871  0.043406   \n",
      "539   ST-1607   2137  0.722040  21.653720  2168.513800  0.212447  0.066448   \n",
      "540   ST-1608   2022  0.795747  26.306627  2317.727186  0.138477  0.030168   \n",
      "541   ST-1609   3149  0.610035  17.224198  1749.736729  0.264846  0.115275   \n",
      "542    ST-161   2356  0.685908  19.126061  1655.901689  0.109932  0.009762   \n",
      "543   ST-1610   2047  0.691744  22.141182  1715.526009  0.158769  0.029800   \n",
      "544   ST-1611   5060  0.645455  22.530040  2595.783818  0.210079  0.015415   \n",
      "545   ST-1615    888  0.759009  21.171171  2315.466351  0.197072  0.021396   \n",
      "546   ST-1616    496  0.820565  12.116935  1523.419819  0.235887  0.151210   \n",
      "547   ST-1617    430  0.732558  24.253488  3014.471442  0.281395  0.113953   \n",
      "548   ST-1618    337  0.786350  15.139466  1717.745846  0.186944  0.020772   \n",
      "549   ST-1619   1619  0.661519  19.032736  2005.069981  0.169858  0.016059   \n",
      "550    ST-162   1793  0.546570  23.446737  2740.357373  0.186838  0.153374   \n",
      "551   ST-1620   1613  0.685679  17.970862  1884.998624  0.262864  0.073156   \n",
      "552   ST-1621   1856  0.719289  17.592134  1831.468761  0.265625  0.055496   \n",
      "553   ST-1622    415  0.650602  14.932530  1730.639518  0.200000  0.055422   \n",
      "554   ST-1623    476  0.670168  19.716387  2370.267164  0.241597  0.039916   \n",
      "555   ST-1625   2256  0.650709  23.867465  3272.387057  0.185727  0.037677   \n",
      "556   ST-1626   2221  0.579018  19.915353  2147.835083  0.253940  0.095002   \n",
      "557   ST-1627   2167  0.674665  22.097831  2425.090891  0.273650  0.030457   \n",
      "558   ST-1628   1739  0.718804  21.728005  2061.639500  0.265095  0.024152   \n",
      "559   ST-1629   3307  0.631993  20.985183  2296.233632  0.255519  0.055942   \n",
      "560    ST-163   1338  0.573244  21.266816  2272.825800  0.182362  0.136024   \n",
      "561   ST-1631   4650  0.676344  17.712258  1789.562563  0.239355  0.044516   \n",
      "562   ST-1632   3594  0.635225  20.978019  2153.887835  0.259599  0.047579   \n",
      "563   ST-1634    587  0.717206  18.574106  2371.547070  0.258944  0.027257   \n",
      "564   ST-1636   2226  0.718329  18.991914  2021.937260  0.212489  0.048967   \n",
      "565   ST-1637   1180  0.615254  24.194068  2628.422746  0.217797  0.035593   \n",
      "566   ST-1638   1962  0.605505  21.477574  2678.069144  0.280326  0.086646   \n",
      "567   ST-1639   3074  0.596291  18.030904  1796.300966  0.231620  0.022446   \n",
      "568   ST-1640   3338  0.645596  18.789694  1895.636660  0.261534  0.051228   \n",
      "569   ST-1641   2692  0.554978  19.563522  2288.620297  0.218053  0.055349   \n",
      "570   ST-1642   2496  0.625000  19.624599  2130.037640  0.282853  0.048478   \n",
      "571   ST-1645   5589  0.673287  12.750760  1583.841059  0.224369  0.048667   \n",
      "572   ST-1646   2574  0.546620  18.627428  1908.016554  0.210179  0.038462   \n",
      "573   ST-1647   2271  0.730956  14.448701  1621.221907  0.221929  0.051959   \n",
      "574   ST-1648    471  0.721868  51.276008  8261.555180  0.282378  0.114650   \n",
      "575   ST-1649   5807  0.663682  22.500258  2271.300580  0.258826  0.043396   \n",
      "576    ST-165   1231  0.667750  22.480097  2256.988424  0.285134  0.071487   \n",
      "577   ST-1650   3937  0.590551  17.878334  1902.934681  0.301753  0.028194   \n",
      "578   ST-1651   1503  0.675981  19.433799  1966.043859  0.208916  0.015968   \n",
      "579   ST-1652   2151  0.598791  22.474663  2147.385281  0.245467  0.093445   \n",
      "580   ST-1653   4103  0.584938  20.371436  1989.668428  0.271265  0.045820   \n",
      "581   ST-1654   2143  0.650023  25.215586  3268.018493  0.232851  0.053196   \n",
      "582   ST-1655   1464  0.600410  18.898224  2046.986291  0.140710  0.015027   \n",
      "583   ST-1656   2139  0.723703  25.622253  3452.769612  0.198223  0.048621   \n",
      "584   ST-1657   3699  0.539335  22.866450  2269.685566  0.284942  0.020276   \n",
      "585   ST-1659     13  0.769231  14.692308  2360.027692  0.000000  0.000000   \n",
      "586   ST-1660  11292  0.544545  20.938452  2119.424064  0.289940  0.030730   \n",
      "587   ST-1661   9083  0.557635  23.085324  2223.572327  0.277441  0.073214   \n",
      "588   ST-1663   4092  0.578690  16.445748  1837.112454  0.273705  0.064272   \n",
      "589   ST-1664   1217  0.608874  18.202958  2397.931142  0.267872  0.045193   \n",
      "590   ST-1665    752  0.652926  20.902926  2151.207606  0.239362  0.061170   \n",
      "591   ST-1667   1007  0.713009  25.812314  3369.454330  0.253227  0.117180   \n",
      "592   ST-1668   2808  0.660256  20.125712  2056.276595  0.184117  0.021011   \n",
      "593   ST-1669    964  0.784232  17.475104  2104.868869  0.268672  0.041494   \n",
      "594    ST-167   1391  0.655643  22.926671  2196.220036  0.204889  0.079080   \n",
      "595   ST-1670    506  0.701581  22.308300  2596.475791  0.227273  0.043478   \n",
      "596   ST-1671   2759  0.644799  20.355201  2624.158728  0.252265  0.032621   \n",
      "597   ST-1672   3460  0.634393  15.373699  1819.982668  0.256647  0.055202   \n",
      "598   ST-1674    888  0.748874  14.097973  1881.291802  0.204955  0.018018   \n",
      "599   ST-1675   1244  0.622186  19.569132  2008.396889  0.275723  0.031350   \n",
      "600   ST-1676   1934  0.695450  13.103930  1671.157332  0.215615  0.059979   \n",
      "601   ST-1677   2099  0.660791  19.974750  1850.030186  0.204859  0.060981   \n",
      "602   ST-1678   4770  0.697694  32.426415  5389.662260  0.305031  0.073585   \n",
      "603   ST-1679   1696  0.698113  24.468160  2293.606963  0.225825  0.063679   \n",
      "604    ST-168    535  0.781308  17.614953  2097.427850  0.256075  0.028037   \n",
      "605   ST-1680   1215  0.725103  24.670782  2473.126831  0.181893  0.057613   \n",
      "606   ST-1681  10071  0.557740  22.998511  2178.818385  0.272068  0.014696   \n",
      "607   ST-1682    365  0.753425  15.024658  1823.345096  0.068493  0.008219   \n",
      "608   ST-1684   4218  0.589616  16.711475  1618.327812  0.247511  0.038644   \n",
      "609   ST-1685     81  0.654321  29.259259  4336.256543  0.358025  0.049383   \n",
      "610   ST-1686    343  0.795918  42.758017  7217.325977  0.370262  0.113703   \n",
      "611   ST-1687   5764  0.517523  18.125434  2003.268878  0.235080  0.015788   \n",
      "612   ST-1688   5233  0.572521  13.284540  1488.493675  0.174661  0.033633   \n",
      "613   ST-1689   6034  0.598111  11.846205  1363.082116  0.243785  0.028339   \n",
      "614    ST-169   1618  0.624845  26.070457  2293.469567  0.276267  0.016069   \n",
      "615   ST-1690   2372  0.542159  21.483137  2281.221602  0.293002  0.094013   \n",
      "616   ST-1691   2034  0.702065  19.236971  1997.127984  0.264012  0.033923   \n",
      "617   ST-1692   2434  0.515201  24.509449  3154.399864  0.280608  0.022186   \n",
      "618   ST-1694   3159  0.616967  17.898386  1829.373916  0.257360  0.042418   \n",
      "619   ST-1695    670  0.870149  29.159701  3487.242672  0.241791  0.053731   \n",
      "620   ST-1696   1197  0.621554  27.482038  3535.977059  0.327485  0.043442   \n",
      "621   ST-1697   2232  0.675627  18.584229  1875.364987  0.241039  0.061828   \n",
      "622   ST-1698   4251  0.590685  16.868031  1626.795032  0.205599  0.043049   \n",
      "623   ST-1699   4907  0.665376  20.192582  2440.955490  0.154066  0.022621   \n",
      "624     ST-17   5356  0.587752  30.809933  4670.904268  0.270538  0.046677   \n",
      "625    ST-170   2000  0.640000  17.920000  1958.021840  0.247000  0.052500   \n",
      "626   ST-1700   2087  0.748443  15.275994  1744.320968  0.284140  0.112602   \n",
      "627   ST-1701   6482  0.601820  20.977168  2279.223537  0.266584  0.024684   \n",
      "628   ST-1702    425  0.788235  20.192941  2641.382894  0.249412  0.103529   \n",
      "629   ST-1703   1071  0.618114  22.428571  2261.249879  0.290383  0.020542   \n",
      "630   ST-1704   1676  0.650955  20.504177  2461.501265  0.199881  0.036396   \n",
      "631   ST-1705   3487  0.564095  36.377115  4370.783900  0.396616  0.026097   \n",
      "632   ST-1706    852  0.519953  18.293427  1924.203603  0.199531  0.093897   \n",
      "633   ST-1707   4343  0.614322  16.772277  1845.956424  0.145752  0.034999   \n",
      "634   ST-1708    793  0.738966  15.040353  1738.665195  0.153846  0.020177   \n",
      "635   ST-1709   4786  0.720852   8.542624  1028.617413  0.139574  0.016715   \n",
      "636    ST-171   3128  0.599425  15.211957  1561.483654  0.195332  0.040601   \n",
      "637   ST-1710   4308  0.516017  11.089833  1164.342326  0.235144  0.022284   \n",
      "638   ST-1712   3597  0.631081  13.097859  1433.983272  0.059772  0.003336   \n",
      "639   ST-1713   1066  0.770169  12.103189  1385.531379  0.184803  0.002814   \n",
      "640   ST-1714   4381  0.637069  15.241726  1783.109123  0.255878  0.110934   \n",
      "641   ST-1715   2751  0.778626  10.420211  1297.102690  0.122864  0.009088   \n",
      "642   ST-1716    759  0.517787  19.952569  2400.307747  0.229249  0.076416   \n",
      "643   ST-1717    678  0.594395  19.452802  2040.906490  0.274336  0.070796   \n",
      "644   ST-1718  16166  0.641532   9.105159  1109.351895  0.139614  0.003278   \n",
      "645   ST-1719   4587  0.498147  29.816874  2676.125284  0.366470  0.032483   \n",
      "646    ST-172   2318  0.623382  18.088438  1772.578292  0.219586  0.036238   \n",
      "647   ST-1720   9916  0.540440  27.827350  2360.822824  0.317769  0.007463   \n",
      "648   ST-1721   1786  0.694289  16.158455  2149.573964  0.273236  0.111422   \n",
      "649   ST-1722   4816  0.621055  14.739826  1798.485384  0.259136  0.057309   \n",
      "650   ST-1723   2316  0.634283  21.588946  2691.882219  0.222366  0.047496   \n",
      "651   ST-1724    689  0.799710  17.116110  2115.689492  0.280116  0.085631   \n",
      "652   ST-1725    992  0.574597  33.180444  2410.136351  0.466734  0.049395   \n",
      "653   ST-1726   3750  0.528533  19.964000  2472.676325  0.244267  0.067467   \n",
      "654   ST-1727   3354  0.573643  15.717949  1464.714517  0.190519  0.033989   \n",
      "655   ST-1728   2793  0.530254  21.279628  2065.952359  0.277121  0.041532   \n",
      "656   ST-1729   3450  0.586377  19.857391  1969.630038  0.252754  0.062899   \n",
      "657    ST-173   2296  0.652439  15.859321  1835.568362  0.253049  0.076220   \n",
      "658   ST-1730   8582  0.550454  21.548823  2192.495311  0.277441  0.058378   \n",
      "659   ST-1731  10241  0.643101  19.705693  2120.509662  0.295870  0.029685   \n",
      "660   ST-1732   1123  0.809439  20.652716  2687.114853  0.241318  0.054319   \n",
      "661   ST-1733   2531  0.682339  24.925326  3335.742940  0.310549  0.041486   \n",
      "662   ST-1734   1114  0.683124  22.552065  3251.728941  0.055655  0.015260   \n",
      "663   ST-1735    462  0.729437  19.997835  2521.165563  0.168831  0.025974   \n",
      "664   ST-1736   1837  0.630920  30.802395  4459.551889  0.281437  0.026674   \n",
      "665   ST-1739   1490  0.642282  24.095973  2497.648597  0.270470  0.056376   \n",
      "666    ST-174   2769  0.554352  16.014807  1554.225641  0.201878  0.042615   \n",
      "667   ST-1740    853  0.631887  19.119578  2050.252931  0.248535  0.041032   \n",
      "668   ST-1742   1007  0.722939  11.515392  1569.647805  0.243297  0.067527   \n",
      "669   ST-1745    497  0.756539  17.004024  1874.259698  0.066398  0.016097   \n",
      "670   ST-1746    325  0.676923  27.415385  2470.350554  0.144615  0.033846   \n",
      "671    ST-175   6998  0.634610  19.439697  1999.793427  0.249929  0.085739   \n",
      "672   ST-1752    161  0.732919  25.608696  3959.068199  0.254658  0.062112   \n",
      "673   ST-1753   3611  0.661313  21.806702  2812.012251  0.119081  0.016616   \n",
      "674   ST-1754   1704  0.605634  38.442488  4686.271138  0.493545  0.012324   \n",
      "675   ST-1756   1813  0.643133  24.715389  2307.820745  0.212355  0.052951   \n",
      "676   ST-1757   1268  0.783123  26.511830  3382.813667  0.284700  0.073344   \n",
      "677   ST-1758   1012  0.740119  22.595850  1720.262045  0.169960  0.020751   \n",
      "678   ST-1759    226  0.725664  23.411504  2937.185752  0.247788  0.000000   \n",
      "679    ST-176   4311  0.563210  24.700997  2415.736736  0.273950  0.046625   \n",
      "680   ST-1760    666  0.713213  20.067568  1655.334820  0.147147  0.043544   \n",
      "681   ST-1761   1192  0.666107  17.332215  1697.273901  0.109899  0.015101   \n",
      "682   ST-1762   1319  0.763457  35.981046  2383.665686  0.304018  0.119788   \n",
      "683   ST-1763    599  0.604341  19.447412  2061.077245  0.293823  0.016694   \n",
      "684   ST-1764    664  0.655120  17.602410  1925.341852  0.275602  0.003012   \n",
      "685   ST-1765    297  0.683502  23.010101  2344.631717  0.262626  0.057239   \n",
      "686   ST-1766    875  0.544000  19.939429  2103.495817  0.241143  0.032000   \n",
      "687   ST-1767   1232  0.613636  19.343344  2018.344935  0.291396  0.017045   \n",
      "688   ST-1768    674  0.716617  13.954006  1666.815134  0.218101  0.017804   \n",
      "689   ST-1769    303  0.722772  15.429043  1659.810561  0.135314  0.059406   \n",
      "690    ST-177   2957  0.677038  16.171796  1841.001245  0.267163  0.095367   \n",
      "691   ST-1771   3095  0.712116  24.294023  2301.850126  0.120517  0.009370   \n",
      "692   ST-1772    965  0.751295  24.070466  2461.849389  0.124352  0.036269   \n",
      "693   ST-1773    781  0.723431  22.428937  2636.628668  0.137004  0.010243   \n",
      "694   ST-1774    890  0.760674  24.649438  2792.408393  0.185393  0.039326   \n",
      "695   ST-1775    476  0.670168  25.792017  2517.339916  0.296218  0.073529   \n",
      "696   ST-1776    523  0.661568  28.072658  2595.778929  0.183556  0.043977   \n",
      "697   ST-1777   1074  0.671322  26.025140  2273.035400  0.157356  0.038175   \n",
      "698   ST-1778   1749  0.672956  28.576901  2709.825923  0.092053  0.012007   \n",
      "699   ST-1779   3949  0.696632  20.932135  2122.351464  0.187642  0.027349   \n",
      "700    ST-178   1130  0.600000  15.808850  2256.193239  0.222124  0.114159   \n",
      "701   ST-1780   4095  0.644933  23.576557  2376.664752  0.242979  0.083272   \n",
      "702   ST-1781   2639  0.681319  23.093975  2333.197363  0.115195  0.255400   \n",
      "703   ST-1782   1982  0.616044  23.858224  1913.620131  0.226034  0.113522   \n",
      "704   ST-1783   1116  0.582437  17.559140  1967.401703  0.259857  0.030466   \n",
      "705   ST-1785    897  0.647715  21.268673  2450.892664  0.284281  0.033445   \n",
      "706   ST-1786    837  0.755078  21.738351  2635.010311  0.231780  0.145759   \n",
      "707   ST-1787   3544  0.589729  20.717269  2068.770302  0.151806  0.151806   \n",
      "708   ST-1789    572  0.746503  23.277972  2410.395752  0.234266  0.062937   \n",
      "709   ST-1790    174  0.706897  26.212644  2741.949080  0.333333  0.017241   \n",
      "710   ST-1791   1962  0.763507  26.352192  3026.327712  0.163099  0.024465   \n",
      "711   ST-1793   5515  0.586401  20.914959  2104.415113  0.241160  0.047507   \n",
      "712   ST-1794   1644  0.621655  27.482968  3892.706283  0.304136  0.131995   \n",
      "713   ST-1795    576  0.491319  20.043403  2548.919444  0.218750  0.052083   \n",
      "714   ST-1796   2253  0.623613  23.577896  2752.941709  0.268087  0.035064   \n",
      "715   ST-1797   1333  0.591898  31.423106  3531.981118  0.315829  0.024006   \n",
      "716   ST-1798    379  0.717678  22.738786  2419.042639  0.192612  0.068602   \n",
      "717   ST-1799   1061  0.737041  13.758718  1481.332639  0.180961  0.057493   \n",
      "718     ST-18   9024  0.613697  20.625997  2036.678551  0.242797  0.031472   \n",
      "719    ST-180   2474  0.772433  17.205740  2240.497344  0.202102  0.045675   \n",
      "720   ST-1801    289  0.692042  16.968858  1596.481315  0.110727  0.038062   \n",
      "721   ST-1802   1551  0.692456  18.714378  1887.234333  0.254674  0.043843   \n",
      "722   ST-1804   2827  0.599929  22.304209  2029.233113  0.275911  0.015210   \n",
      "723   ST-1805   2483  0.708820  22.540475  2197.345473  0.143375  0.021345   \n",
      "724   ST-1807   4602  0.641243  20.839635  1842.266777  0.187744  0.029987   \n",
      "725   ST-1808   2069  0.679555  23.653939  1762.626974  0.163847  0.054132   \n",
      "726   ST-1809   1414  0.737624  20.959689  2067.924682  0.181754  0.045262   \n",
      "727    ST-181   3874  0.672173  27.621838  2862.061902  0.150232  0.006970   \n",
      "728   ST-1810   4725  0.647831  23.228571  1570.059010  0.120212  0.024127   \n",
      "729   ST-1811   2707  0.688216  21.273735  1953.884584  0.236424  0.037680   \n",
      "730   ST-1812   4011  0.713787  21.442284  2081.674717  0.239342  0.110945   \n",
      "731   ST-1813   4228  0.618732  20.627010  2227.579948  0.195601  0.181646   \n",
      "732   ST-1814   2047  0.622374  15.324866  1725.718661  0.249634  0.087934   \n",
      "733   ST-1815    354  0.559322  13.166667  1657.042175  0.276836  0.064972   \n",
      "734   ST-1816    976  0.598361  16.760246  1906.950123  0.262295  0.031762   \n",
      "735   ST-1817   2637  0.599545  16.459992  1915.549609  0.273417  0.083807   \n",
      "736   ST-1818   4735  0.648574  16.013939  1708.652729  0.239704  0.059345   \n",
      "737   ST-1819   3781  0.687913  16.819889  1861.882568  0.233272  0.078286   \n",
      "738    ST-182    318  0.672956  16.292453  1948.654088  0.075472  0.003145   \n",
      "739   ST-1820   1935  0.649096  14.032558  1465.969597  0.188630  0.025840   \n",
      "740   ST-1822   1477  0.691943  19.464455  1955.923866  0.258632  0.060934   \n",
      "741   ST-1823    559  0.747764  17.937388  2353.372558  0.241503  0.067979   \n",
      "742   ST-1824    434  0.778802  19.758065  2720.934516  0.202765  0.057604   \n",
      "743   ST-1825    381  0.551181  26.461942  3626.932966  0.317585  0.125984   \n",
      "744   ST-1826    324  0.626543  28.925926  4444.267747  0.259259  0.101852   \n",
      "745   ST-1827    270  0.807407  20.800000  3301.224296  0.262963  0.059259   \n",
      "746   ST-1828    468  0.801282  25.215812  3483.992585  0.226496  0.083333   \n",
      "747   ST-1829   2550  0.656078  23.681176  2125.039541  0.226275  0.056471   \n",
      "748    ST-183   2001  0.642679  16.897551  2173.969875  0.216892  0.066467   \n",
      "749   ST-1830    909  0.570957  17.848185  2095.694136  0.251925  0.011001   \n",
      "750   ST-1831   1217  0.619556  24.914544  2161.786393  0.251438  0.014790   \n",
      "751   ST-1832    355  0.642254  21.261972  2273.672592  0.326761  0.042254   \n",
      "752   ST-1833   3965  0.626986  19.307945  1779.291037  0.307188  0.013115   \n",
      "753   ST-1834   1485  0.668013  17.797980  1895.345118  0.277441  0.050505   \n",
      "754   ST-1835   2299  0.650283  18.468465  2086.500583  0.270117  0.097869   \n",
      "755   ST-1836   3039  0.642646  16.855874  1718.679480  0.268838  0.055281   \n",
      "756   ST-1837   3108  0.641570  19.254183  1825.520042  0.283784  0.063707   \n",
      "757   ST-1838   3527  0.596824  19.626878  1965.783538  0.257443  0.050468   \n",
      "758   ST-1839   5533  0.611965  18.037412  1908.695684  0.296584  0.029098   \n",
      "759   ST-1840    638  0.653605  22.816614  2532.493856  0.231975  0.020376   \n",
      "760   ST-1841   2138  0.611787  18.593545  1911.447035  0.252105  0.081384   \n",
      "761   ST-1842   2436  0.554187  21.809113  1978.243842  0.320197  0.064860   \n",
      "762   ST-1843    374  0.729947  28.122995  2253.038342  0.173797  0.002674   \n",
      "763   ST-1844   1272  0.724057  17.286950  1869.353160  0.204403  0.029874   \n",
      "764   ST-1845   1843  0.621270  17.308736  1936.823673  0.274552  0.024959   \n",
      "765   ST-1846   1126  0.641208  18.436057  1934.827229  0.283304  0.053286   \n",
      "766   ST-1848   2753  0.494007  19.378496  1956.504442  0.255358  0.046131   \n",
      "767   ST-1849    265  0.811321  19.750943  2709.136491  0.362264  0.116981   \n",
      "768    ST-185   4634  0.746871  23.887786  2365.051821  0.121925  0.010142   \n",
      "769   ST-1850   3660  0.622678  20.154372  1996.490096  0.223770  0.026776   \n",
      "770   ST-1851   4679  0.589015  20.670015  1950.314016  0.265869  0.041034   \n",
      "771   ST-1852    989  0.568251  22.243680  3087.207998  0.271992  0.019211   \n",
      "772   ST-1853   1294  0.570325  21.314529  2242.497125  0.205564  0.038640   \n",
      "773   ST-1854   1563  0.638516  16.886756  2071.269923  0.273832  0.075496   \n",
      "774   ST-1855   4636  0.611950  18.523512  2020.688156  0.198231  0.067515   \n",
      "775   ST-1857   3349  0.618991  19.668558  2174.830690  0.260675  0.048373   \n",
      "776   ST-1858   1229  0.567941  20.738812  2535.019292  0.216436  0.028478   \n",
      "777   ST-1859   4630  0.561987  19.511879  1918.524592  0.270410  0.051188   \n",
      "778    ST-186   1207  0.603977  24.584921  2431.686744  0.238608  0.033140   \n",
      "779   ST-1860   1753  0.556189  20.934398  2412.973360  0.313748  0.062750   \n",
      "780   ST-1861   1435  0.579094  22.131010  2397.143345  0.255052  0.041115   \n",
      "781   ST-1862   4472  0.537567  20.655859  2103.543055  0.286002  0.025492   \n",
      "782   ST-1864   4527  0.595538  25.865474  2470.937055  0.270157  0.047935   \n",
      "783   ST-1866   5991  0.551828  18.086129  1708.628793  0.246370  0.034552   \n",
      "784   ST-1867   5634  0.495918  20.021654  1923.224226  0.267306  0.044018   \n",
      "785   ST-1868   5115  0.539198  17.219746  1841.283425  0.256500  0.013490   \n",
      "786   ST-1869   2082  0.688280  21.564361  2897.026278  0.267531  0.031700   \n",
      "787    ST-187   1226  0.687602  24.253670  2894.554307  0.278140  0.165579   \n",
      "788   ST-1870    564  0.535461  19.613475  1943.539911  0.237589  0.072695   \n",
      "789   ST-1871    863  0.589803  19.137891  2372.205527  0.231750  0.038239   \n",
      "790   ST-1872   2432  0.611020  20.638158  2364.989359  0.221217  0.041530   \n",
      "791   ST-1873   1623  0.589649  20.364140  2609.527646  0.258780  0.047443   \n",
      "792   ST-1874   2283  0.611038  19.515550  2218.534196  0.311432  0.043802   \n",
      "793   ST-1875   1023  0.581623  19.146628  2401.326706  0.291300  0.056696   \n",
      "794   ST-1876    928  0.613147  19.459052  2222.940366  0.233836  0.068966   \n",
      "795   ST-1877   1212  0.400165  16.344884  1732.043853  0.287954  0.058581   \n",
      "796   ST-1878   1996  0.558116  17.774549  2199.888918  0.184870  0.027054   \n",
      "797   ST-1879   1846  0.601842  29.236728  3420.972259  0.282774  0.028711   \n",
      "798   ST-1880   2674  0.596485  21.231114  2538.847191  0.190352  0.028796   \n",
      "799   ST-1881   1795  0.604457  23.910306  2412.432763  0.288579  0.038997   \n",
      "800   ST-1882    992  0.684476  22.787298  2407.596250  0.207661  0.029234   \n",
      "801   ST-1883    468  0.771368  21.467949  2242.314380  0.224359  0.061966   \n",
      "802   ST-1884   1252  0.719649  33.571885  4590.354944  0.222843  0.014377   \n",
      "803   ST-1885   1215  0.688066  30.871605  4130.246272  0.260905  0.032099   \n",
      "804   ST-1886   1270  0.584252  25.374016  2897.046669  0.279528  0.018898   \n",
      "805   ST-1887   1389  0.716343  31.657307  3206.975018  0.264939  0.059755   \n",
      "806   ST-1888   1125  0.598222  19.904889  2376.606418  0.258667  0.042667   \n",
      "807   ST-1889   2329  0.692572  24.136110  2608.871370  0.284242  0.050666   \n",
      "808    ST-189   3063  0.643160  21.620307  2225.643950  0.207966  0.083905   \n",
      "809   ST-1891    306  0.627451  24.137255  3081.332157  0.290850  0.091503   \n",
      "810   ST-1892    942  0.632696  14.358811  1798.524257  0.183652  0.057325   \n",
      "811   ST-1893    981  0.725790  22.308869  2356.499001  0.217125  0.042813   \n",
      "812   ST-1894    701  0.690442  24.844508  2875.661469  0.315264  0.057061   \n",
      "813   ST-1895   1520  0.636842  32.076316  3960.471816  0.288158  0.086184   \n",
      "814   ST-1896   1532  0.755222  20.081593  2163.850796  0.178198  0.031332   \n",
      "815   ST-1897   2674  0.599850  23.910247  2770.847266  0.272625  0.040763   \n",
      "816   ST-1899   1214  0.627677  18.393740  1732.289152  0.274300  0.066722   \n",
      "817     ST-19   1153  0.683435  22.013010  2289.105794  0.260191  0.054640   \n",
      "818   ST-1900   1902  0.655626  26.894848  2925.427639  0.241325  0.046267   \n",
      "819   ST-1901    729  0.633745  23.921811  3492.660329  0.234568  0.013717   \n",
      "820   ST-1902    774  0.630491  22.852713  2430.150969  0.211886  0.036176   \n",
      "821   ST-1903   1077  0.695450  23.349118  2324.453110  0.202414  0.025998   \n",
      "822   ST-1904    346  0.624277  23.205202  2379.722168  0.231214  0.034682   \n",
      "823   ST-1905    759  0.718050  21.387352  2101.725652  0.226614  0.096179   \n",
      "824   ST-1906   1040  0.700000  19.604808  2058.992644  0.214423  0.071154   \n",
      "825   ST-1908   1931  0.633351  23.206629  2952.844055  0.332988  0.019679   \n",
      "826   ST-1909   1461  0.663244  23.224504  2856.361410  0.279261  0.045175   \n",
      "827   ST-1910   5270  0.610436  43.303416  5086.964459  0.361101  0.053131   \n",
      "828   ST-1912    343  0.583090  48.728863  5337.886822  0.399417  0.052478   \n",
      "829   ST-1913   1212  0.660066  24.425743  2794.949521  0.216997  0.022277   \n",
      "830   ST-1914   1371  0.574763  24.107221  2505.618009  0.246535  0.037929   \n",
      "831   ST-1915   2122  0.622526  27.409048  3076.426541  0.262488  0.042413   \n",
      "832   ST-1916   2163  0.562644  21.424873  2341.331711  0.226537  0.062876   \n",
      "833   ST-1917    528  0.573864  19.996212  3138.064867  0.232955  0.011364   \n",
      "834   ST-1918    386  0.585492  26.220207  3501.617332  0.297927  0.012953   \n",
      "835   ST-1920    730  0.584932  28.413699  2814.526548  0.324658  0.060274   \n",
      "836   ST-1921    289  0.633218  26.044983  2092.750796  0.193772  0.010381   \n",
      "837   ST-1922   1581  0.650854  18.523087  2081.709500  0.225806  0.036053   \n",
      "838   ST-1923   1990  0.656784  32.147739  3863.561724  0.330653  0.035176   \n",
      "839   ST-1924   1845  0.664499  20.508401  2309.312770  0.259079  0.067209   \n",
      "840   ST-1925    177  0.672316  28.694915  6313.712712  0.395480  0.033898   \n",
      "841   ST-1926   1666  0.701681  30.877551  3429.466801  0.236495  0.097239   \n",
      "842   ST-1929    697  0.658537  24.253945  3356.538364  0.246772  0.004304   \n",
      "843   ST-1932    283  0.752650  37.568905  5480.984876  0.402827  0.183746   \n",
      "844   ST-1933   1698  0.598351  15.154299  1895.483757  0.191991  0.027680   \n",
      "845   ST-1934    741  0.584345  18.089069  2273.881768  0.224022  0.056680   \n",
      "846   ST-1935    630  0.663492  17.896825  1895.165111  0.226984  0.066667   \n",
      "847   ST-1936    608  0.601974  20.129934  1995.216316  0.233553  0.008224   \n",
      "848   ST-1937    263  0.695817  31.403042  4090.851901  0.254753  0.030418   \n",
      "849   ST-1938   9695  0.682414  13.419288  1654.419759  0.145539  0.019701   \n",
      "850   ST-1939    653  0.581930  17.702910  2340.693890  0.150077  0.038285   \n",
      "851    ST-194   1648  0.749393  23.668689  2763.950364  0.221481  0.037015   \n",
      "852   ST-1940   1592  0.555905  15.250000  1757.726193  0.199749  0.013819   \n",
      "853   ST-1941   1366  0.703514  17.407760  2001.402840  0.230600  0.053441   \n",
      "854   ST-1944    484  0.469008  33.985537  4226.357128  0.373967  0.045455   \n",
      "855   ST-1945    242  0.475207  21.921488  2579.710826  0.276860  0.024793   \n",
      "856   ST-1946    268  0.753731  16.891791  2375.353955  0.235075  0.033582   \n",
      "857   ST-1947    376  0.670213  30.231383  3083.885399  0.305851  0.045213   \n",
      "858   ST-1948    371  0.547170  23.272237  2313.573854  0.326146  0.048518   \n",
      "859   ST-1949    224  0.531250  33.339286  3756.484643  0.330357  0.031250   \n",
      "860    ST-195   2512  0.630573  20.974124  2259.965199  0.164013  0.028662   \n",
      "861   ST-1950    189  0.455026  34.566138  3232.768836  0.269841  0.026455   \n",
      "862   ST-1952    839  0.610250  20.545888  2365.124720  0.277712  0.053635   \n",
      "863   ST-1953    205  0.556098  22.692683  2022.618244  0.234146  0.034146   \n",
      "864   ST-1954    531  0.572505  20.212806  2489.600471  0.269303  0.050847   \n",
      "865   ST-1955    802  0.705736  25.648379  3728.153155  0.269327  0.053616   \n",
      "866   ST-1956    177  0.559322  20.497175  2310.235593  0.293785  0.045198   \n",
      "867   ST-1957    722  0.666205  13.883657  1884.164349  0.290859  0.052632   \n",
      "868   ST-1958    692  0.539017  11.942197  1418.657962  0.219653  0.030347   \n",
      "869   ST-1959   1646  0.730863  14.243013  1934.542600  0.194411  0.074727   \n",
      "870    ST-196    402  0.689055  21.798507  2322.119005  0.261194  0.062189   \n",
      "871   ST-1960   1345  0.532342  21.214126  2501.738171  0.208178  0.087732   \n",
      "872   ST-1961   2538  0.561466  20.324271  2522.204007  0.223798  0.044917   \n",
      "873   ST-1962    890  0.550562  18.933708  2012.662427  0.295506  0.040449   \n",
      "874   ST-1963   1699  0.714538  14.738081  1917.344008  0.085933  0.023543   \n",
      "875   ST-1964   5777  0.638567  20.943569  2513.869060  0.249611  0.023195   \n",
      "876   ST-1965    515  0.675728  18.889320  2179.231223  0.244660  0.091262   \n",
      "877   ST-1966   1159  0.767903  15.244176  1923.154107  0.213115  0.051769   \n",
      "878   ST-1967    597  0.780570  18.973199  2051.164188  0.268007  0.041876   \n",
      "879   ST-1968   4463  0.601837  18.257226  1674.590509  0.249384  0.028232   \n",
      "880   ST-1969    345  0.727536  21.852174  2903.955855  0.226087  0.023188   \n",
      "881    ST-197    893  0.696529  21.595745  2629.767828  0.245241  0.122060   \n",
      "882   ST-1970   1273  0.695994  23.794973  2901.196457  0.191673  0.008641   \n",
      "883   ST-1971   1102  0.570780  42.229583  5063.853131  0.450998  0.030853   \n",
      "884   ST-1972   2795  0.610733  17.246154  1815.588004  0.152773  0.023971   \n",
      "885   ST-1973   5166  0.626984  18.347464  1751.118024  0.257646  0.033101   \n",
      "886   ST-1974   2118  0.643532  16.024551  1890.623810  0.228517  0.016525   \n",
      "887   ST-1975   1765  0.692918  15.843059  1931.450935  0.242493  0.111615   \n",
      "888   ST-1976   3634  0.572097  25.069070  3456.730281  0.275729  0.015960   \n",
      "889   ST-1977   2576  0.581134  18.458463  1868.100004  0.218556  0.036491   \n",
      "890   ST-1978   1770  0.598305  14.767797  1648.456119  0.180226  0.031638   \n",
      "891    ST-198   6663  0.610686  21.328981  2231.283549  0.240282  0.092751   \n",
      "892   ST-1982   1196  0.736622  22.983278  2346.888085  0.250836  0.077759   \n",
      "893   ST-1983   3995  0.709136  18.493867  1664.504618  0.238048  0.050313   \n",
      "894   ST-1985   2955  0.578003  15.424365  1970.135127  0.304230  0.077496   \n",
      "895   ST-1986   2470  0.651822  21.799595  2379.614785  0.241700  0.025911   \n",
      "896    ST-199    547  0.698355  16.791590  1812.702322  0.180987  0.034735   \n",
      "897   ST-1990   5757  0.691506  14.520757  1713.893550  0.254473  0.033003   \n",
      "898   ST-1991   2326  0.703783  18.588564  2025.904991  0.252365  0.067498   \n",
      "899   ST-1992   1548  0.594315  18.885659  1843.294722  0.233204  0.023256   \n",
      "900   ST-1993   1255  0.644622  13.113147  1713.909203  0.256574  0.026295   \n",
      "901   ST-1994   4434  0.649075  19.504511  2087.644215  0.294768  0.058412   \n",
      "902   ST-1995   9535  0.585107  19.358364  2009.728489  0.320294  0.013844   \n",
      "903   ST-1996   9207  0.576518  15.980558  1702.772546  0.207451  0.034973   \n",
      "904   ST-1997   4799  0.568869  17.484268  1792.044357  0.271098  0.032924   \n",
      "905   ST-1999   2240  0.674107  22.410268  2837.554464  0.267411  0.061607   \n",
      "906     ST-20   3818  0.619958  28.036145  2733.848816  0.276061  0.065217   \n",
      "907    ST-200   1288  0.665373  16.082298  1981.914907  0.247671  0.062112   \n",
      "908   ST-2000   1178  0.651104  19.848896  2208.951486  0.240238  0.057725   \n",
      "909   ST-2001   1800  0.663333  17.758889  2127.049017  0.266111  0.072778   \n",
      "910   ST-2002   1066  0.680113  18.405253  2359.538058  0.258912  0.045966   \n",
      "911   ST-2003   2604  0.698541  21.271505  2347.393038  0.240783  0.084869   \n",
      "912   ST-2005   6754  0.705804  17.607048  1967.746768  0.270358  0.044862   \n",
      "913   ST-2006   4509  0.660457  36.330894  4916.656999  0.315591  0.016855   \n",
      "914   ST-2007   7452  0.713500  16.554214  1906.931373  0.271202  0.047772   \n",
      "915   ST-2008   1995  0.675188  15.300752  1788.115885  0.225063  0.052632   \n",
      "916    ST-201   2149  0.705444  23.653327  2637.541661  0.231270  0.048395   \n",
      "917   ST-2011  10530  0.581576  18.868091  1763.802706  0.221368  0.010731   \n",
      "918   ST-2012   4373  0.632518  15.559113  1603.798573  0.276927  0.018980   \n",
      "919   ST-2013   6231  0.563312  16.023913  2023.082022  0.246188  0.047344   \n",
      "920   ST-2014   5115  0.692864  13.209775  1470.497939  0.212512  0.011339   \n",
      "921   ST-2016   5634  0.545438  17.760383  1801.457614  0.283990  0.020057   \n",
      "922   ST-2017   9579  0.592859  18.903330  1892.248693  0.294498  0.019835   \n",
      "923   ST-2018   2049  0.644217  21.414348  2381.985129  0.251830  0.041484   \n",
      "924   ST-2019    337  0.637982  24.572700  3363.987003  0.225519  0.133531   \n",
      "925    ST-202   4911  0.656893  28.279984  3287.618131  0.242110  0.056404   \n",
      "926   ST-2020   5575  0.559283  15.836054  1689.926002  0.230314  0.019013   \n",
      "927   ST-2022   2150  0.687442  17.090233  1910.028795  0.268837  0.048837   \n",
      "928   ST-2023   4046  0.615670  16.933515  2141.911537  0.257538  0.034602   \n",
      "929   ST-2024   6430  0.600311  18.974650  2152.827193  0.225505  0.023017   \n",
      "930   ST-2025   2231  0.690273  33.865531  4172.992394  0.332586  0.039444   \n",
      "931   ST-2026   2212  0.603978  17.022152  2327.327970  0.225588  0.057866   \n",
      "932   ST-2027   2757  0.627494  19.099383  2044.999692  0.234675  0.079797   \n",
      "933   ST-2028   1538  0.549415  18.956437  1853.666151  0.306892  0.088427   \n",
      "934   ST-2029   4025  0.663106  18.534907  2191.725516  0.233789  0.057391   \n",
      "935    ST-203   2150  0.634884  20.960465  2521.151619  0.205581  0.051163   \n",
      "936   ST-2031  25287  0.606557  12.126785  1454.068516  0.204097  0.017044   \n",
      "937   ST-2032    963  0.602285  13.563863  1851.617767  0.077882  0.015576   \n",
      "938   ST-2033   7291  0.682622  14.264847  1677.565533  0.115073  0.013716   \n",
      "939   ST-2034   3575  0.560559  12.180699  1295.507751  0.199161  0.025734   \n",
      "940   ST-2035   6279  0.623985  13.093805  1510.327960  0.139672  0.010033   \n",
      "941   ST-2036   5658  0.575999  11.479321  1333.394919  0.194768  0.031813   \n",
      "942   ST-2037   9143  0.598053  12.301323  1428.890733  0.196325  0.053155   \n",
      "943   ST-2039   5949  0.595394  19.146411  1834.825204  0.294503  0.022189   \n",
      "944    ST-204   4813  0.627675  32.285685  4448.960810  0.279867  0.052150   \n",
      "945   ST-2040   5689  0.563016  13.881174  1528.576302  0.194059  0.055897   \n",
      "946   ST-2041   3256  0.629607  12.604423  1608.363342  0.150184  0.018120   \n",
      "947   ST-2042   2226  0.582210  19.252022  2188.989699  0.274933  0.007637   \n",
      "948   ST-2044   3914  0.725345  14.291518  1760.544990  0.083291  0.003066   \n",
      "949   ST-2045  16551  0.645701  11.774273  1482.050099  0.184218  0.008096   \n",
      "950   ST-2046   3467  0.546870  16.844246  2173.991731  0.145659  0.035189   \n",
      "951   ST-2047   4753  0.584473  14.774669  1698.869971  0.238797  0.060383   \n",
      "952   ST-2048   2341  0.630073  13.062367  1468.742268  0.141820  0.016232   \n",
      "953   ST-2049   3258  0.561387  10.891344  1212.778186  0.234807  0.059239   \n",
      "954    ST-205   4906  0.629433  31.063596  4210.711724  0.264370  0.043416   \n",
      "955   ST-2050   6779  0.604661  10.465260  1219.470230  0.249889  0.032306   \n",
      "956   ST-2052   4125  0.674424  11.996848  1216.325234  0.176970  0.002909   \n",
      "957   ST-2054   3312  0.700785  24.079106  2465.378385  0.252114  0.114734   \n",
      "958   ST-2056   6541  0.577740  14.274882  1458.540501  0.224125  0.042043   \n",
      "959   ST-2057   3857  0.555095  14.880736  1885.245891  0.120041  0.005445   \n",
      "960   ST-2058   3398  0.587404  14.596822  1675.033420  0.220129  0.040024   \n",
      "961   ST-2059   4011  0.514086  18.180504  1526.470633  0.124657  0.011967   \n",
      "962    ST-206   2467  0.674503  30.789218  4101.896534  0.272396  0.039724   \n",
      "963   ST-2062   1273  0.606441  17.452474  2276.252569  0.319717  0.080911   \n",
      "964   ST-2063   2479  0.692618  17.959258  2078.240694  0.266236  0.058895   \n",
      "965   ST-2067   2566  0.687062  15.356976  1865.871617  0.261107  0.030787   \n",
      "966   ST-2068   2134  0.709934  15.212277  1795.496256  0.247423  0.038425   \n",
      "967   ST-2069    986  0.741379  25.693712  2758.414929  0.284990  0.029412   \n",
      "968    ST-207   2500  0.676400  24.778000  3139.237472  0.263600  0.069600   \n",
      "969   ST-2070   2279  0.691970  17.826240  2095.491444  0.285652  0.042124   \n",
      "970   ST-2073    688  0.697674  12.497093  1723.464230  0.154070  0.021802   \n",
      "971   ST-2074   3604  0.708935  18.604606  2335.837112  0.232242  0.065483   \n",
      "972   ST-2075   2840  0.645070  22.114437  2544.336623  0.265845  0.070775   \n",
      "973   ST-2076   3871  0.649186  19.588220  2193.463043  0.266856  0.075174   \n",
      "974   ST-2077   2103  0.685212  23.712316  2845.098317  0.284831  0.038516   \n",
      "975   ST-2078   2570  0.687938  17.857198  1968.982961  0.269261  0.031907   \n",
      "976   ST-2079   3379  0.593963  25.547203  3417.656961  0.275821  0.047647   \n",
      "977   ST-2080   1838  0.789989  18.559304  1730.001578  0.101197  0.022307   \n",
      "978   ST-2081   6210  0.610467  15.128986  1457.336026  0.201127  0.031401   \n",
      "979   ST-2083   1964  0.698574  24.744399  3520.842770  0.219450  0.041242   \n",
      "980   ST-2085   5488  0.569242  22.785714  2273.143639  0.321793  0.030430   \n",
      "981   ST-2086   1708  0.566745  17.322014  2162.590498  0.298595  0.071429   \n",
      "982   ST-2087   3715  0.610767  15.288022  1773.520272  0.253836  0.023957   \n",
      "983   ST-2088   2015  0.593548  19.700248  2264.818591  0.248139  0.075931   \n",
      "984   ST-2089   3669  0.553829  18.535841  1915.768607  0.276370  0.017171   \n",
      "985   ST-2093    927  0.633225  17.720604  1854.979159  0.238403  0.108954   \n",
      "986   ST-2094   2277  0.662714  20.902942  2315.469868  0.262187  0.088274   \n",
      "987   ST-2095   1396  0.538682  31.261461  5175.177500  0.344556  0.026504   \n",
      "988   ST-2096   1428  0.693277  21.476190  2001.335399  0.268908  0.082633   \n",
      "989   ST-2097   1556  0.694730  14.933162  1520.174049  0.292416  0.056555   \n",
      "990   ST-2099   1478  0.608254  20.698241  2528.969885  0.272666  0.093369   \n",
      "991     ST-21   2813  0.625311  33.667970  4578.947256  0.297903  0.037327   \n",
      "992    ST-210   3520  0.496307  21.672159  2469.152148  0.232386  0.041193   \n",
      "993   ST-2101    519  0.687861  20.339114  2160.317091  0.240848  0.080925   \n",
      "994   ST-2102    926  0.622030  25.568035  3444.639719  0.279698  0.055076   \n",
      "995   ST-2103   1124  0.577402  23.670819  3153.171059  0.288256  0.053381   \n",
      "996   ST-2104   1122  0.603387  19.565954  2536.130954  0.215686  0.059715   \n",
      "997   ST-2106    515  0.617476  24.893204  2887.677223  0.248544  0.128155   \n",
      "998   ST-2107   2696  0.657270  15.149110  1721.722804  0.280786  0.075668   \n",
      "999    ST-211   4643  0.554168  24.890373  2582.805585  0.313806  0.061813   \n",
      "1000  ST-2110   1967  0.619217  17.690391  2031.987712  0.284698  0.070666   \n",
      "1001  ST-2112   2371  0.600590  19.749473  2371.544863  0.263602  0.069591   \n",
      "1002  ST-2113    832  0.722356  22.358173  2808.410276  0.310096  0.106971   \n",
      "1003  ST-2115   1421  0.600281  23.482759  3092.337002  0.212526  0.017593   \n",
      "1004  ST-2116   1055  0.721327  18.292891  2107.260502  0.274882  0.131754   \n",
      "1005  ST-2117   1112  0.541367  16.102518  1813.930441  0.298561  0.095324   \n",
      "1006  ST-2119    826  0.682809  17.462470  2091.817651  0.283293  0.094431   \n",
      "1007   ST-212   2307  0.562635  18.137408  2296.654395  0.209363  0.015171   \n",
      "1008  ST-2120   1364  0.651026  18.085777  1903.138541  0.282991  0.064516   \n",
      "1009  ST-2123    250  0.928000  17.756000  2417.816320  0.204000  0.156000   \n",
      "1010  ST-2124   1024  0.631836  22.218750  2438.803623  0.320312  0.047852   \n",
      "1011  ST-2125   2468  0.639384  20.320502  2154.857378  0.291734  0.047002   \n",
      "1012  ST-2126   1126  0.681172  21.631439  2534.514893  0.300178  0.095915   \n",
      "1013  ST-2127    820  0.671951  18.563415  2346.099024  0.265854  0.073171   \n",
      "1014  ST-2129   1813  0.597904  25.027027  3340.101291  0.256481  0.037507   \n",
      "1015   ST-213   1466  0.663029  22.633697  2376.557619  0.189632  0.033424   \n",
      "1016  ST-2130    584  0.592466  25.647260  3078.640771  0.277397  0.065068   \n",
      "1017  ST-2132   1544  0.652202  22.189119  2114.754935  0.248705  0.108808   \n",
      "1018  ST-2133   2368  0.531672  22.788429  2581.905916  0.251267  0.049409   \n",
      "1019  ST-2134   2274  0.587951  24.111258  2442.706429  0.256376  0.094987   \n",
      "1020  ST-2137   5222  0.625048  19.696859  2110.787080  0.263692  0.059364   \n",
      "1021   ST-214   3082  0.705386  19.549319  2307.256330  0.256652  0.042180   \n",
      "1022  ST-2146   3680  0.629076  26.503261  3283.935283  0.252989  0.053261   \n",
      "1023  ST-2147   2775  0.546306  14.475676  1641.981186  0.197838  0.026306   \n",
      "1024  ST-2148    677  0.519941  15.319055  1695.329099  0.245199  0.044313   \n",
      "1025  ST-2149   2868  0.713040  17.404812  1862.806151  0.194909  0.013250   \n",
      "1026  ST-2150    708  0.594633  27.242938  3425.970890  0.248588  0.048023   \n",
      "1027  ST-2152   2845  0.626362  24.589104  2338.622506  0.260105  0.043234   \n",
      "1028  ST-2153    675  0.598519  24.480000  2379.984830  0.217778  0.011852   \n",
      "1029  ST-2154   1976  0.663968  28.977733  3494.581857  0.233300  0.031377   \n",
      "1030  ST-2156   4510  0.561197  27.121729  2712.114450  0.299335  0.050998   \n",
      "1031  ST-2157   4468  0.510743  20.228290  2129.523648  0.282005  0.038272   \n",
      "1032   ST-216    562  0.501779  19.117438  1986.215552  0.249110  0.039146   \n",
      "1033  ST-2160   5061  0.475203  23.165580  2548.429591  0.283936  0.030429   \n",
      "1034  ST-2161    127  0.874016  17.740157  2122.412677  0.220472  0.086614   \n",
      "1035  ST-2163    419  0.513126  22.319809  2126.433652  0.128878  0.000000   \n",
      "1036  ST-2164   1146  0.510471  17.898778  2249.902801  0.118674  0.032286   \n",
      "1037  ST-2165   1260  0.653175  19.609524  2373.596484  0.163492  0.034921   \n",
      "1038  ST-2166   1349  0.616012  14.088955  1853.532958  0.139362  0.022239   \n",
      "1039  ST-2167   3163  0.560228  22.968701  2309.257822  0.278849  0.061018   \n",
      "1040  ST-2168   6634  0.574917  22.130389  2265.089563  0.274646  0.035574   \n",
      "1041   ST-217    975  0.668718  21.607179  3286.746759  0.205128  0.060513   \n",
      "1042  ST-2172    686  0.728863  22.097668  2478.399125  0.241983  0.078717   \n",
      "1043  ST-2173   2271  0.603258  20.774108  2298.860255  0.300749  0.062087   \n",
      "1044  ST-2174    918  0.623094  21.199346  2004.224357  0.255991  0.032680   \n",
      "1045  ST-2175    644  0.590062  18.990683  2180.350311  0.267081  0.038820   \n",
      "1046  ST-2176   1655  0.668278  30.551662  4197.993106  0.311782  0.034441   \n",
      "1047  ST-2177   6753  0.632460  25.365023  3101.599542  0.324448  0.026803   \n",
      "1048  ST-2178    226  0.615044  28.495575  2942.149071  0.362832  0.035398   \n",
      "1049  ST-2179    325  0.566154  23.704615  2604.112277  0.344615  0.021538   \n",
      "1050   ST-218    513  0.656920  23.389864  2954.132982  0.237817  0.058480   \n",
      "1051  ST-2181    405  0.627160  23.780247  2949.299704  0.325926  0.101235   \n",
      "1052  ST-2182    435  0.625287  20.754023  2823.031103  0.351724  0.091954   \n",
      "1053  ST-2183    218  0.697248  26.701835  3117.142569  0.412844  0.036697   \n",
      "1054  ST-2184   2411  0.598092  33.449606  4003.722207  0.331398  0.040647   \n",
      "1055  ST-2187    715  0.502098  24.186014  2519.023748  0.351049  0.009790   \n",
      "1056  ST-2188   1339  0.645258  34.416729  5119.742532  0.221060  0.091860   \n",
      "1057  ST-2189    104  0.769231  19.807692  2903.680192  0.346154  0.038462   \n",
      "1058   ST-219   1223  0.461161  15.459526  2077.285863  0.195421  0.045789   \n",
      "1059  ST-2190    896  0.664062  18.828125  2336.337333  0.294643  0.078125   \n",
      "1060  ST-2191    562  0.681495  24.943060  2979.929270  0.266904  0.042705   \n",
      "1061  ST-2194    591  0.659898  24.177665  2796.346007  0.267343  0.081218   \n",
      "1062  ST-2195   1340  0.619403  29.764925  4064.380209  0.273881  0.093284   \n",
      "1063  ST-2196    523  0.720841  24.931166  3211.027266  0.340344  0.068834   \n",
      "1064  ST-2198    494  0.795547  16.356275  1958.302085  0.224696  0.018219   \n",
      "1065  ST-2199   1380  0.657971  23.835507  2730.408449  0.297826  0.073188   \n",
      "1066    ST-22    658  0.544073  22.231003  2743.668511  0.290274  0.054711   \n",
      "1067   ST-220    959  0.711157  22.032325  2930.345172  0.206465  0.065693   \n",
      "1068  ST-2200   1506  0.593625  17.671979  1884.179754  0.260956  0.090969   \n",
      "1069  ST-2201   1215  0.657613  23.575309  2306.903292  0.253498  0.059259   \n",
      "1070  ST-2202    438  0.356164  15.497717  1811.235046  0.203196  0.022831   \n",
      "1071  ST-2204   3504  0.583904  22.500000  2583.255197  0.253425  0.051084   \n",
      "1072  ST-2205   2188  0.595978  20.436015  2383.086490  0.276508  0.035192   \n",
      "1073  ST-2206   2167  0.646516  18.476234  2071.227300  0.251038  0.045224   \n",
      "1074  ST-2207   1191  0.637280  17.953820  2439.756725  0.245172  0.079765   \n",
      "1075  ST-2208   1770  0.694350  25.862712  2653.456418  0.270621  0.034463   \n",
      "1076   ST-221    701  0.611983  17.609130  2122.581056  0.255350  0.031384   \n",
      "1077  ST-2210   1990  0.502010  29.490452  3489.078337  0.284422  0.024623   \n",
      "1078  ST-2211    385  0.651948  21.449351  2846.234286  0.275325  0.041558   \n",
      "1079  ST-2212   1090  0.628440  23.755963  3265.876596  0.263303  0.033945   \n",
      "1080  ST-2213   2038  0.575074  29.739941  3635.382522  0.289990  0.042689   \n",
      "1081  ST-2214   1105  0.780995  19.080543  2442.374950  0.223529  0.052489   \n",
      "1082  ST-2215   1319  0.585292  23.868840  2600.760576  0.278241  0.041698   \n",
      "1083  ST-2216   1552  0.564433  24.293170  3000.615702  0.288660  0.036082   \n",
      "1084  ST-2217   1351  0.540340  31.843819  4470.352798  0.259067  0.045152   \n",
      "1085  ST-2219    703  0.741110  20.405405  2480.288706  0.284495  0.025605   \n",
      "1086   ST-222   2181  0.665291  21.289317  2366.908647  0.269601  0.023384   \n",
      "1087  ST-2221    317  0.810726  13.126183  1811.716530  0.252366  0.041009   \n",
      "1088  ST-2222   3017  0.556845  24.618827  3459.005111  0.224727  0.067285   \n",
      "1089  ST-2223   3442  0.640616  29.009006  3971.692644  0.274550  0.081639   \n",
      "1090  ST-2225   2817  0.601349  21.318779  2550.141899  0.256301  0.081292   \n",
      "1091  ST-2226   2586  0.664346  21.197989  2284.853855  0.242073  0.061098   \n",
      "1092  ST-2227    925  0.695135  26.280000  2943.539286  0.300541  0.121081   \n",
      "1093  ST-2229   1235  0.614575  17.590283  2102.311360  0.239676  0.055061   \n",
      "1094   ST-223   2687  0.643096  21.963900  2672.047722  0.263119  0.043543   \n",
      "1095  ST-2231   2966  0.610249  23.129130  2438.933001  0.246123  0.066757   \n",
      "1096  ST-2232    965  0.694301  15.711917  2052.679016  0.207254  0.074611   \n",
      "1097  ST-2233    453  0.600442  19.203091  2187.849934  0.211921  0.041943   \n",
      "1098  ST-2234    503  0.687873  16.153082  2109.486382  0.268390  0.091451   \n",
      "1099  ST-2235   1296  0.617284  19.057099  2124.023418  0.282407  0.091049   \n",
      "1100  ST-2236   1616  0.659653  22.197401  3098.911293  0.274752  0.043936   \n",
      "1101  ST-2237   2234  0.743062  22.376007  2918.388201  0.282005  0.047449   \n",
      "1102  ST-2239    633  0.538705  32.890995  4379.556651  0.380727  0.033175   \n",
      "1103   ST-224    867  0.716263  19.463668  2487.230588  0.292964  0.032295   \n",
      "1104  ST-2240   4920  0.521545  34.229065  4059.991724  0.436382  0.020528   \n",
      "1105  ST-2241    411  0.625304  17.119221  2432.028248  0.255474  0.072993   \n",
      "1106  ST-2242    240  0.595833  15.754167  1804.030750  0.250000  0.025000   \n",
      "1107  ST-2243    953  0.674711  19.198321  2228.203221  0.206716  0.096537   \n",
      "1108  ST-2244   1160  0.652586  15.167241  1440.667759  0.252586  0.037931   \n",
      "1109  ST-2245    535  0.779439  14.330841  1833.235421  0.267290  0.028037   \n",
      "1110  ST-2246    421  0.681710  21.337292  2467.199810  0.263658  0.061758   \n",
      "1111  ST-2247   1256  0.654459  20.141720  2480.292118  0.228503  0.066083   \n",
      "1112  ST-2250   1400  0.659286  20.533571  1927.205350  0.286429  0.057143   \n",
      "1113  ST-2252   1941  0.608449  22.683153  3102.878418  0.273570  0.066976   \n",
      "1114  ST-2253   2270  0.639648  18.921145  1964.164040  0.247577  0.050220   \n",
      "1115  ST-2257   2609  0.612495  23.501342  2996.191993  0.283250  0.061709   \n",
      "1116  ST-2259    281  0.715302  28.213523  3151.388932  0.409253  0.024911   \n",
      "1117   ST-226    755  0.582781  18.173510  2473.999404  0.198675  0.039735   \n",
      "1118  ST-2260    402  0.569652  31.024876  3719.015299  0.507463  0.009950   \n",
      "1119  ST-2261    821  0.649208  18.029233  1977.779890  0.250914  0.036541   \n",
      "1120  ST-2262    585  0.611966  15.343590  1904.332769  0.299145  0.037607   \n",
      "1121  ST-2263    774  0.686047  19.196382  2054.710814  0.218346  0.034884   \n",
      "1122  ST-2264   6660  0.600751  21.809459  2425.254797  0.279279  0.040691   \n",
      "1123  ST-2265   2047  0.714704  26.056668  2688.374284  0.243283  0.062531   \n",
      "1124  ST-2266   1376  0.702035  36.739826  4110.151170  0.313953  0.036337   \n",
      "1125  ST-2267   1299  0.719784  17.532717  1920.752179  0.236336  0.041570   \n",
      "1126  ST-2268   6157  0.629852  21.574468  2286.478509  0.255969  0.062855   \n",
      "1127  ST-2269   2359  0.638406  19.851208  2413.208843  0.245443  0.045358   \n",
      "1128   ST-227   1781  0.602471  24.942729  3072.557518  0.272880  0.056148   \n",
      "1129  ST-2270   6955  0.630050  23.409346  2851.432932  0.274191  0.080086   \n",
      "1130  ST-2271   1246  0.707865  15.110754  1668.557456  0.227929  0.070626   \n",
      "1131  ST-2272   2183  0.654146  19.267980  2280.922739  0.193312  0.028859   \n",
      "1132  ST-2273   1961  0.739929  19.190209  2345.154141  0.254462  0.108108   \n",
      "1133  ST-2274   2630  0.634601  21.418251  2351.117795  0.223194  0.075285   \n",
      "1134  ST-2276   1238  0.739095  20.496769  2621.624693  0.241519  0.073506   \n",
      "1135  ST-2278   3925  0.741401  23.731465  2860.771373  0.228535  0.061656   \n",
      "1136  ST-2279    761  0.842313  16.483574  1889.721787  0.261498  0.044678   \n",
      "1137   ST-228    874  0.718535  14.633867  1636.161751  0.117849  0.025172   \n",
      "1138  ST-2280   3533  0.634305  23.075573  2591.204478  0.269459  0.071894   \n",
      "1139  ST-2281    435  0.666667  15.712644  1725.459954  0.179310  0.052874   \n",
      "1140  ST-2282   2132  0.565666  19.010788  2140.173082  0.281426  0.077861   \n",
      "1141  ST-2283   3927  0.559206  17.605042  1981.369778  0.280621  0.059078   \n",
      "1142  ST-2284    539  0.658627  30.243043  3971.471484  0.239332  0.055659   \n",
      "1143  ST-2285   1881  0.640617  18.371079  1961.754981  0.249867  0.055290   \n",
      "1144  ST-2286   1501  0.612258  17.431712  2548.345989  0.190540  0.057295   \n",
      "1145  ST-2287   1030  0.643689  19.914563  2901.193563  0.233981  0.053398   \n",
      "1146  ST-2288    400  0.722500  19.807500  3001.759750  0.277500  0.122500   \n",
      "1147  ST-2289   1600  0.700000  21.614375  2613.091031  0.275625  0.118125   \n",
      "1148  ST-2290   1720  0.642442  21.207558  2360.032105  0.241279  0.033721   \n",
      "1149  ST-2291   2001  0.586207  19.407296  2105.602529  0.252874  0.090955   \n",
      "1150  ST-2292   3226  0.636702  20.534408  2266.514141  0.243025  0.080285   \n",
      "1151  ST-2293   1976  0.692814  16.168016  1693.077318  0.232287  0.030870   \n",
      "1152  ST-2294   1951  0.697591  19.652998  2176.899103  0.253716  0.027166   \n",
      "1153  ST-2295   1444  0.565097  15.820637  1683.999301  0.206371  0.070637   \n",
      "1154  ST-2298    426  0.553991  33.152582  4077.028052  0.232394  0.035211   \n",
      "1155  ST-2299   2510  0.578486  18.224701  2039.254203  0.306375  0.041036   \n",
      "1156    ST-23   1258  0.674881  24.156598  2751.040056  0.257552  0.059618   \n",
      "1157   ST-230    664  0.715361  17.739458  2035.109669  0.186747  0.024096   \n",
      "1158  ST-2300    832  0.641827  27.305288  3386.583714  0.288462  0.070913   \n",
      "1159  ST-2301   1165  0.557940  28.858369  3725.599245  0.272103  0.051502   \n",
      "1160  ST-2302    468  0.715812  16.145299  1792.197607  0.269231  0.023504   \n",
      "1161  ST-2303    458  0.665939  27.358079  2380.193297  0.320961  0.015284   \n",
      "1162  ST-2305   2922  0.599932  16.840520  1648.014346  0.270363  0.029774   \n",
      "1163  ST-2308   8559  0.606029  16.940063  1717.364291  0.225143  0.054913   \n",
      "1164  ST-2309   6012  0.596640  20.806221  2031.610805  0.243180  0.054391   \n",
      "1165   ST-231   1747  0.527762  26.652547  3604.912433  0.269605  0.025186   \n",
      "1166  ST-2310   6861  0.567118  18.148812  1978.991073  0.221542  0.061361   \n",
      "1167  ST-2312   2656  0.580949  17.372364  1822.653980  0.252259  0.073042   \n",
      "1168  ST-2314   6094  0.603216  16.833115  1614.466426  0.251395  0.039547   \n",
      "1169  ST-2318   4454  0.607768  17.856758  2016.759874  0.234845  0.073417   \n",
      "1170   ST-232   2992  0.630348  17.032086  2046.500618  0.202206  0.023730   \n",
      "1171  ST-2320   3899  0.603745  14.199025  1541.109700  0.223647  0.028982   \n",
      "1172  ST-2321   5287  0.554190  18.354454  1859.781122  0.247210  0.058256   \n",
      "1173  ST-2325   3646  0.559792  20.464070  2612.148511  0.243829  0.062260   \n",
      "1174  ST-2326   2798  0.677984  22.496426  2982.661112  0.199428  0.017870   \n",
      "1175  ST-2327   1477  0.679756  23.142857  2828.894861  0.172647  0.030467   \n",
      "1176  ST-2329   1268  0.576498  18.394322  2039.006648  0.270505  0.059937   \n",
      "1177   ST-233   1081  0.685476  21.410731  2695.000934  0.211841  0.094357   \n",
      "1178  ST-2330   3786  0.576862  22.278922  2350.031482  0.227945  0.023772   \n",
      "1179  ST-2331   3624  0.556015  17.516556  1977.126410  0.242826  0.065397   \n",
      "1180  ST-2332   2259  0.622399  36.953962  5402.188424  0.326693  0.058876   \n",
      "1181  ST-2333    880  0.914773  18.429545  2198.458682  0.130682  0.007955   \n",
      "1182  ST-2334   1436  0.531337  48.439415  4414.882709  0.479805  0.012535   \n",
      "1183  ST-2335   1137  0.686895  20.953386  2222.685048  0.222515  0.064204   \n",
      "1184  ST-2337    668  0.687126  18.209581  2194.400943  0.200599  0.053892   \n",
      "1185  ST-2338    544  0.731618  27.194853  2661.661195  0.352941  0.141544   \n",
      "1186  ST-2339    953  0.730325  26.318993  3331.169286  0.264428  0.091291   \n",
      "1187   ST-234   1320  0.623485  30.312121  3675.914773  0.233333  0.050000   \n",
      "1188  ST-2340   1325  0.655094  16.714717  2062.863600  0.257358  0.070943   \n",
      "1189  ST-2341   5121  0.515134  31.121851  2990.719590  0.283929  0.014060   \n",
      "1190  ST-2342   3627  0.642956  22.150813  2527.791050  0.230218  0.059553   \n",
      "1191  ST-2343    603  0.568823  26.384743  3180.666517  0.270315  0.064677   \n",
      "1192   ST-235   2355  0.569851  19.266667  2349.893006  0.242463  0.067941   \n",
      "1193  ST-2350   2021  0.682335  33.248887  4778.592751  0.318654  0.046017   \n",
      "1194  ST-2351    257  0.688716  25.918288  3430.894163  0.287938  0.038911   \n",
      "1195  ST-2352    371  0.719677  24.482480  3812.960081  0.277628  0.035040   \n",
      "1196  ST-2353   2738  0.710007  19.999635  2336.162469  0.258583  0.056611   \n",
      "1197  ST-2355   1758  0.672355  16.352105  1690.865933  0.228100  0.042662   \n",
      "1198  ST-2356    795  0.805031  26.280503  3409.829585  0.272956  0.085535   \n",
      "1199  ST-2357   1398  0.665236  20.530758  2350.054034  0.299714  0.079399   \n",
      "1200  ST-2358   2492  0.705457  17.758828  1993.694350  0.228331  0.057785   \n",
      "1201  ST-2359   1616  0.732673  15.084777  1771.622228  0.250619  0.035272   \n",
      "1202   ST-236   1446  0.562241  17.329184  1987.141632  0.242739  0.040111   \n",
      "1203  ST-2361    652  0.733129  23.601227  3182.289264  0.289877  0.111963   \n",
      "1204  ST-2362   1830  0.678689  20.551913  2164.738825  0.248087  0.050273   \n",
      "1205  ST-2363   2160  0.672685  23.376389  2108.790167  0.260185  0.057407   \n",
      "1206  ST-2364   1808  0.631084  19.450774  1905.958291  0.264381  0.048673   \n",
      "1207  ST-2365    289  0.626298  19.145329  2935.358443  0.252595  0.044983   \n",
      "1208  ST-2366    297  0.636364  17.848485  2567.620269  0.289562  0.037037   \n",
      "1209  ST-2367    372  0.771505  23.134409  2817.294543  0.260753  0.045699   \n",
      "1210  ST-2368   1479  0.657201  24.062880  2734.225301  0.278567  0.094659   \n",
      "1211  ST-2369    237  0.856540  20.991561  2478.022321  0.181435  0.059072   \n",
      "1212   ST-237   2923  0.630517  22.460828  2537.345884  0.249743  0.076634   \n",
      "1213  ST-2370   1058  0.647448  19.156900  2269.243686  0.304348  0.084121   \n",
      "1214  ST-2371   2321  0.692805  17.797932  2109.156898  0.259802  0.093063   \n",
      "1215  ST-2373   2570  0.588716  17.077432  1820.598148  0.250973  0.053307   \n",
      "1216  ST-2374    947  0.661035  14.913411  1610.692978  0.269271  0.087645   \n",
      "1217  ST-2375   1523  0.799081  29.267236  3307.460657  0.283651  0.084701   \n",
      "1218  ST-2379   1597  0.617408  20.919224  2237.275861  0.289919  0.130244   \n",
      "1219   ST-238    603  0.721393  22.729685  2557.419900  0.252073  0.097844   \n",
      "1220  ST-2380   1243  0.641995  18.674980  1854.488319  0.288013  0.079646   \n",
      "1221  ST-2382   1164  0.628007  17.430412  1934.593900  0.285223  0.103952   \n",
      "1222  ST-2383    237  0.603376  19.029536  2059.049072  0.261603  0.071730   \n",
      "1223   ST-239    305  0.816393  27.150820  3493.787049  0.321311  0.163934   \n",
      "1224  ST-2390     17  0.764706  12.705882  2035.398824  0.235294  0.117647   \n",
      "1225  ST-2391     80  0.800000  23.412500  2806.458875  0.337500  0.075000   \n",
      "1226  ST-2393    602  0.794020  15.378738  2007.110365  0.252492  0.043189   \n",
      "1227  ST-2394   1754  0.597491  19.098632  1940.249036  0.209806  0.046180   \n",
      "1228  ST-2395   4191  0.593653  16.702696  1765.130188  0.261751  0.038893   \n",
      "1229  ST-2396   5977  0.593107  14.926552  1536.226441  0.234733  0.031454   \n",
      "1230  ST-2397   3900  0.649487  17.174103  1978.982541  0.245641  0.025897   \n",
      "1231  ST-2398   6979  0.625161  16.258633  1783.609039  0.267947  0.039404   \n",
      "1232    ST-24   1213  0.751855  25.986810  2193.278730  0.265458  0.043693   \n",
      "1233   ST-240    685  0.738686  26.105109  3539.098321  0.258394  0.150365   \n",
      "1234  ST-2401    813  0.709717  22.932349  3350.214453  0.261993  0.035670   \n",
      "1235  ST-2402    334  0.658683  29.772455  3811.424042  0.395210  0.014970   \n",
      "1236  ST-2403    411  0.739659  21.815085  2738.229440  0.296837  0.072993   \n",
      "1237  ST-2404   1678  0.723480  21.918355  2959.098057  0.075685  0.008939   \n",
      "1238  ST-2405   1011  0.751731  25.419387  2438.543660  0.244313  0.074184   \n",
      "1239  ST-2406   2292  0.733857  16.160122  2116.759490  0.245637  0.068063   \n",
      "1240  ST-2407   2939  0.600885  18.532154  2003.589146  0.273222  0.027220   \n",
      "1241  ST-2408   1418  0.720733  18.763752  1727.188004  0.117066  0.020451   \n",
      "1242  ST-2409   2576  0.651009  16.767857  2014.443203  0.188276  0.154115   \n",
      "1243   ST-241   2966  0.690492  24.955158  3176.864666  0.311868  0.072488   \n",
      "1244  ST-2410    265  0.709434  18.381132  2648.592604  0.218868  0.033962   \n",
      "1245  ST-2411   5716  0.526767   9.993177  1075.409888  0.193142  0.034115   \n",
      "1246  ST-2412   3210  0.636760  11.760125  1478.490779  0.182866  0.038006   \n",
      "1247  ST-2414   1584  0.688763  25.087753  3212.107563  0.260732  0.022096   \n",
      "1248  ST-2415    820  0.543902  24.262195  3287.088037  0.268293  0.024390   \n",
      "1249  ST-2416   1047  0.649475  27.265521  3941.680420  0.249284  0.051576   \n",
      "1250  ST-2417    962  0.742204  23.043659  2866.941455  0.241164  0.123701   \n",
      "1251  ST-2419   3199  0.684589  12.276649  1376.460991  0.222570  0.022194   \n",
      "1252   ST-242   1226  0.713703  18.406199  2448.230400  0.111746  0.018760   \n",
      "1253  ST-2420   4974  0.591275  30.397266  4373.513727  0.261761  0.055489   \n",
      "1254  ST-2422   2704  0.718565  25.665680  2554.970692  0.116864  0.017751   \n",
      "1255  ST-2424    542  0.623616  16.750923  1843.917362  0.226937  0.031365   \n",
      "1256  ST-2425   2053  0.665855  16.712616  2001.160146  0.265952  0.050658   \n",
      "1257  ST-2427   3140  0.693631  15.995860  1682.295994  0.214331  0.015605   \n",
      "1258  ST-2428    890  0.468539  18.069663  1612.388865  0.180899  0.004494   \n",
      "1259   ST-243   8676  0.700323  17.214269  1961.147811  0.166551  0.029161   \n",
      "1260  ST-2430    257  0.696498  28.420233  3346.990467  0.155642  0.035019   \n",
      "1261  ST-2431   3724  0.603652  22.695489  2356.483625  0.259398  0.067669   \n",
      "1262  ST-2432    466  0.753219  16.942060  1993.244936  0.201717  0.019313   \n",
      "1263  ST-2433    560  0.703571  16.666071  1880.905714  0.178571  0.025000   \n",
      "1264  ST-2434    148  0.682432  18.750000  2036.610743  0.189189  0.013514   \n",
      "1265  ST-2435   1426  0.791024  28.206171  3625.253198  0.262272  0.053296   \n",
      "1266  ST-2436    453  0.465784  17.529801  1965.878675  0.251656  0.028698   \n",
      "1267  ST-2437    987  0.728470  25.433637  3711.314559  0.170213  0.030395   \n",
      "1268  ST-2438    947  0.488912  35.294615  4246.835618  0.410771  0.025343   \n",
      "1269  ST-2439    621  0.560386  26.824477  2789.541304  0.434783  0.009662   \n",
      "1270   ST-244   2968  0.650606  21.568396  2719.113181  0.227763  0.074461   \n",
      "1271  ST-2440    330  0.512121  25.390909  2624.372364  0.312121  0.003030   \n",
      "1272  ST-2441    604  0.617550  19.584437  2278.570728  0.294702  0.039735   \n",
      "1273  ST-2442    586  0.604096  38.684300  5165.032457  0.266212  0.066553   \n",
      "1274  ST-2443    291  0.711340  32.463918  3980.226838  0.305842  0.092784   \n",
      "1275  ST-2444    132  0.606061  31.787879  4186.557803  0.340909  0.083333   \n",
      "1276  ST-2445    247  0.607287  27.558704  3362.307328  0.417004  0.064777   \n",
      "1277  ST-2446   1032  0.642442  32.384690  4407.020010  0.300388  0.077519   \n",
      "1278  ST-2447   1205  0.784232  18.784232  2357.325469  0.234025  0.037344   \n",
      "1279  ST-2448    310  0.609677  24.861290  2818.282742  0.270968  0.041935   \n",
      "1280  ST-2449   1758  0.708191  23.715586  3430.307673  0.199090  0.032992   \n",
      "1281   ST-245    892  0.582960  31.633408  4211.059854  0.254484  0.079596   \n",
      "1282  ST-2450   2184  0.616758  28.493590  3712.686314  0.298535  0.030678   \n",
      "1283  ST-2451   2213  0.740624  22.023046  2369.831333  0.277000  0.067329   \n",
      "1284  ST-2452    510  0.566667  27.001961  3482.268961  0.245098  0.070588   \n",
      "1285  ST-2453    247  0.716599  24.105263  2999.924494  0.295547  0.129555   \n",
      "1286  ST-2455    755  0.676821  17.872848  1859.252477  0.264901  0.034437   \n",
      "1287  ST-2456   1781  0.647389  29.857945  3817.759994  0.306008  0.066816   \n",
      "1288  ST-2457   1662  0.577617  19.238267  2061.811913  0.287004  0.069795   \n",
      "1289  ST-2458    707  0.570014  23.405941  2075.087115  0.203678  0.056577   \n",
      "1290  ST-2459   1781  0.642897  17.741157  2147.595081  0.250983  0.067378   \n",
      "1291   ST-246    631  0.613312  27.293185  3780.820206  0.301109  0.101426   \n",
      "1292  ST-2460    478  0.648536  27.259414  3942.718138  0.303347  0.087866   \n",
      "1293  ST-2461    474  0.727848  22.588608  2444.425211  0.293249  0.101266   \n",
      "1294  ST-2462    414  0.434783  28.630435  2583.676957  0.323671  0.028986   \n",
      "1295  ST-2463   1179  0.658185  24.458015  3505.367447  0.259542  0.061069   \n",
      "1296  ST-2464   4570  0.621225  18.061269  2088.369033  0.276149  0.030416   \n",
      "1297  ST-2465   3314  0.643331  15.818648  1708.090009  0.244116  0.089922   \n",
      "1298  ST-2466   3403  0.573905  23.677050  2486.830044  0.190420  0.029386   \n",
      "1299  ST-2467   1719  0.623618  16.308901  2037.008232  0.146597  0.030250   \n",
      "1300  ST-2468   1161  0.608958  38.943152  5383.625047  0.319552  0.043928   \n",
      "1301  ST-2469    453  0.699779  19.019868  2197.940419  0.220751  0.044150   \n",
      "1302   ST-247   1094  0.702925  19.855576  2469.837770  0.258684  0.078611   \n",
      "1303  ST-2470   1414  0.618105  20.041018  2251.559222  0.246818  0.068600   \n",
      "1304  ST-2472   2763  0.695983  21.508505  1796.489059  0.145132  0.020630   \n",
      "1305  ST-2473   2247  0.585225  22.980863  2205.610129  0.254562  0.022252   \n",
      "1306  ST-2474    886  0.718962  13.077878  1733.715485  0.124153  0.011287   \n",
      "1307  ST-2476   1116  0.600358  12.924731  1498.052715  0.174731  0.019713   \n",
      "1308  ST-2477   2917  0.553994  12.420980  1297.168639  0.253342  0.021598   \n",
      "1309  ST-2478   1383  0.654375  27.068691  3750.351171  0.282719  0.049168   \n",
      "1310  ST-2479   2064  0.609496  19.695252  2185.185528  0.218992  0.016473   \n",
      "1311   ST-248   1068  0.725655  23.556180  2834.532612  0.242509  0.096442   \n",
      "1312  ST-2480   1207  0.724109  18.072908  2210.834416  0.241094  0.093621   \n",
      "1313  ST-2481   3622  0.674213  17.953893  2133.675947  0.255660  0.059083   \n",
      "1314  ST-2482   5820  0.629725  14.154467  1356.351553  0.246392  0.051203   \n",
      "1315  ST-2483   2101  0.638267  17.190386  1732.518229  0.218943  0.032366   \n",
      "1316  ST-2484    902  0.758315  18.154102  2019.273880  0.345898  0.062084   \n",
      "1317  ST-2486   3676  0.655604  19.769859  2207.506336  0.301143  0.052503   \n",
      "1318  ST-2487   6702  0.576097  17.628469  2108.410209  0.248881  0.055804   \n",
      "1319  ST-2488    232  0.836207  27.297414  3479.536853  0.327586  0.004310   \n",
      "1320  ST-2489   2754  0.595861  16.916485  2341.536866  0.239651  0.020334   \n",
      "1321   ST-249   2315  0.698488  21.937365  2690.617654  0.262203  0.062203   \n",
      "1322  ST-2490   2677  0.703399  17.902129  2512.169395  0.259245  0.035487   \n",
      "1323  ST-2491   4822  0.579428  24.759436  3740.073801  0.279345  0.037744   \n",
      "1324  ST-2492   1223  0.586263  40.639411  6054.558144  0.366312  0.032706   \n",
      "1325  ST-2494   3621  0.625518  35.757526  5289.410851  0.334162  0.024579   \n",
      "1326  ST-2496   1665  0.637838  27.824024  3527.944078  0.298498  0.050450   \n",
      "1327  ST-2497    890  0.640449  21.883146  2827.098258  0.296629  0.024719   \n",
      "1328  ST-2498   2538  0.670213  25.959811  3561.587325  0.254531  0.052403   \n",
      "1329  ST-2499   1828  0.630744  19.987965  2319.249043  0.170678  0.028993   \n",
      "1330    ST-25   3253  0.558254  33.896711  5035.760618  0.288042  0.060252   \n",
      "1331   ST-250   1349  0.646405  22.450704  2685.646449  0.206079  0.053373   \n",
      "1332  ST-2500    405  0.708642  20.311111  2452.753407  0.296296  0.049383   \n",
      "1333  ST-2501   5008  0.650160  20.855032  2304.555865  0.260383  0.057708   \n",
      "1334  ST-2502   2352  0.687925  16.937500  1877.704345  0.286139  0.117772   \n",
      "1335  ST-2504   2175  0.671724  21.424368  2747.711508  0.229885  0.041379   \n",
      "1336  ST-2505   1363  0.660308  25.110051  2910.376456  0.267792  0.068966   \n",
      "1337  ST-2506   1717  0.577752  22.654048  2983.468957  0.243448  0.046010   \n",
      "1338  ST-2507   2879  0.547760  19.531435  2361.217385  0.209100  0.031261   \n",
      "1339  ST-2508   5129  0.597192  20.799766  2639.462921  0.230454  0.040749   \n",
      "1340  ST-2509   1880  0.673936  20.760638  2449.006362  0.259043  0.034574   \n",
      "1341   ST-251   2697  0.740452  23.214312  3080.302696  0.159436  0.024842   \n",
      "1342  ST-2511    514  0.745136  16.196498  2256.642471  0.280156  0.031128   \n",
      "1343  ST-2513   2344  0.686007  30.619881  2177.520734  0.252560  0.054181   \n",
      "1344  ST-2514    885  0.661017  22.750282  1957.144780  0.169492  0.009040   \n",
      "1345  ST-2516    729  0.624143  21.362140  2135.941139  0.193416  0.054870   \n",
      "1346  ST-2517    879  0.712173  22.037543  2447.157907  0.166098  0.030717   \n",
      "1347  ST-2518   4843  0.671485  21.135040  2247.812443  0.163329  0.010737   \n",
      "1348  ST-2519    263  0.764259  19.574144  2070.020913  0.079848  0.011407   \n",
      "1349   ST-252   2815  0.551687  28.815631  3971.528124  0.273535  0.094494   \n",
      "1350  ST-2520   1068  0.584270  24.981273  1997.477669  0.205993  0.013109   \n",
      "1351  ST-2521    990  0.695960  24.739394  2423.503929  0.221212  0.038384   \n",
      "1352  ST-2522    657  0.669711  26.171994  2626.883927  0.240487  0.021309   \n",
      "1353  ST-2523   2002  0.772727  22.429570  2217.349665  0.120380  0.018981   \n",
      "1354  ST-2525    839  0.638856  23.277712  2220.366079  0.177592  0.023838   \n",
      "1355  ST-2526    953  0.724029  23.882476  2407.505593  0.125918  0.015740   \n",
      "1356  ST-2527   2060  0.689806  24.251456  2386.037485  0.253398  0.025728   \n",
      "1357  ST-2528   1459  0.723783  23.106923  2463.715147  0.197395  0.030843   \n",
      "1358   ST-253   3989  0.583104  18.063174  2076.853928  0.259464  0.109802   \n",
      "1359  ST-2530    911  0.671789  25.601537  2973.234610  0.304061  0.058178   \n",
      "1360  ST-2531   1032  0.573643  24.921512  2226.441822  0.207364  0.053295   \n",
      "1361  ST-2532   1373  0.563001  23.148580  2190.539432  0.226511  0.036417   \n",
      "1362  ST-2533   1901  0.564966  19.730142  2500.617585  0.253551  0.053656   \n",
      "1363  ST-2534   1331  0.547708  29.096920  2973.738655  0.312547  0.080391   \n",
      "1364  ST-2535   1740  0.553448  15.424713  1836.508891  0.245402  0.098851   \n",
      "1365  ST-2536   3898  0.515393  22.961262  2408.421734  0.285531  0.007696   \n",
      "1366  ST-2537   1800  0.622222  17.425556  2109.308328  0.171111  0.037778   \n",
      "1367  ST-2538   4189  0.526617  15.208164  1510.900298  0.214610  0.035808   \n",
      "1368  ST-2539    458  0.805677  18.137555  1468.872140  0.277293  0.065502   \n",
      "1369   ST-254   2880  0.632639  26.714931  3706.021059  0.315972  0.021875   \n",
      "1370  ST-2541   2267  0.613586  13.824879  1691.921760  0.217909  0.028231   \n",
      "1371  ST-2542   2521  0.609679  15.646172  1606.575173  0.229671  0.063467   \n",
      "1372  ST-2543   1287  0.709402  16.307692  2067.492836  0.248640  0.040404   \n",
      "1373  ST-2544   2642  0.583270  13.132097  1539.349633  0.219152  0.035958   \n",
      "1374  ST-2545   2770  0.536462  21.033213  1888.185617  0.248736  0.076895   \n",
      "1375  ST-2546   3357  0.538576  19.468871  1856.582270  0.244266  0.074471   \n",
      "1376  ST-2547   1973  0.640142  18.933604  1859.694328  0.187532  0.018246   \n",
      "1377  ST-2548    193  0.772021  24.891192  2878.238187  0.181347  0.005181   \n",
      "1378  ST-2549   3573  0.586622  34.131542  5465.897084  0.301427  0.040022   \n",
      "1379   ST-255   3702  0.642896  19.913560  2314.824943  0.275527  0.015397   \n",
      "1380  ST-2550   3544  0.586061  21.083239  2603.339571  0.200056  0.025959   \n",
      "1381  ST-2551   1347  0.676318  17.858203  2030.539933  0.224944  0.060134   \n",
      "1382  ST-2552   1481  0.584065  18.789332  1740.908602  0.177583  0.012829   \n",
      "1383  ST-2553   1709  0.613224  39.889994  5961.160316  0.370392  0.033353   \n",
      "1384  ST-2555   3073  0.673609  13.352424  1752.927637  0.262284  0.091767   \n",
      "1385  ST-2556   1108  0.595668  18.081227  2142.901679  0.247292  0.071300   \n",
      "1386  ST-2557   9495  0.588310  14.751659  1786.060563  0.228331  0.072038   \n",
      "1387  ST-2558   2173  0.624482  17.244363  1840.357133  0.282559  0.046940   \n",
      "1388  ST-2559   2354  0.663976  18.975361  2215.624172  0.263806  0.065845   \n",
      "1389   ST-256   1751  0.609937  31.930326  4375.697493  0.295831  0.017704   \n",
      "1390  ST-2560   2307  0.595145  22.065020  2907.964361  0.255743  0.091894   \n",
      "1391  ST-2561    984  0.623984  24.272358  3264.739715  0.289634  0.093496   \n",
      "1392  ST-2562    374  0.780749  27.173797  3639.246524  0.149733  0.026738   \n",
      "1393  ST-2563   2829  0.590315  15.796394  1486.149268  0.158360  0.018381   \n",
      "1394  ST-2564   2721  0.716648  19.442484  2213.793444  0.276736  0.058067   \n",
      "1395  ST-2565   2399  0.675698  20.293456  1857.404060  0.196332  0.021676   \n",
      "1396  ST-2567    667  0.595202  27.547226  3305.892474  0.247376  0.044978   \n",
      "1397  ST-2568    525  0.601905  31.860952  2466.681238  0.270476  0.026667   \n",
      "1398  ST-2569   3706  0.499191  15.536967  1661.750888  0.178090  0.034808   \n",
      "1399   ST-257   3852  0.595275  18.143821  1812.164813  0.248442  0.069055   \n",
      "1400  ST-2570   1056  0.648674  26.930871  2908.955199  0.208333  0.033144   \n",
      "1401  ST-2571   4644  0.581180  24.431525  2769.003351  0.172265  0.016150   \n",
      "1402  ST-2572   2624  0.577363  23.971799  2431.974432  0.324695  0.044588   \n",
      "1403  ST-2574   7222  0.427444  20.470368  2488.133398  0.195375  0.006508   \n",
      "1404  ST-2575   1104  0.634964  19.061594  2277.894538  0.236413  0.075181   \n",
      "1405  ST-2576   1812  0.591060  20.177704  2021.867047  0.173841  0.030905   \n",
      "1406  ST-2577    413  0.581114  20.125908  2264.163923  0.266344  0.043584   \n",
      "1407  ST-2578   1211  0.596201  17.678778  1911.208860  0.255161  0.136251   \n",
      "1408  ST-2579   1318  0.512898  20.179818  2267.750303  0.234446  0.046282   \n",
      "1409   ST-258   4186  0.563306  20.604873  2419.190131  0.299331  0.031534   \n",
      "1410  ST-2580   2894  0.466137  27.050104  2510.554323  0.267104  0.024188   \n",
      "1411  ST-2581   2786  0.572146  19.236899  2141.617243  0.229002  0.071788   \n",
      "1412  ST-2583   2201  0.617901  20.054066  2516.861999  0.231713  0.065425   \n",
      "1413  ST-2584   1067  0.621368  14.308341  1872.935473  0.208997  0.044986   \n",
      "1414  ST-2585    676  0.715976  18.411243  2625.461686  0.289941  0.149408   \n",
      "1415  ST-2586    412  0.582524  18.759709  2721.978786  0.257282  0.094660   \n",
      "1416  ST-2587    743  0.654105  16.767160  1869.825949  0.243607  0.078062   \n",
      "1417  ST-2588    781  0.615877  20.098592  1905.593982  0.233035  0.038412   \n",
      "1418  ST-2589   1768  0.568439  17.910068  1956.241052  0.230769  0.049774   \n",
      "1419   ST-259   5144  0.631804  18.634526  2332.703698  0.287519  0.079899   \n",
      "1420  ST-2590    275  0.640000  16.480000  1975.326873  0.236364  0.054545   \n",
      "1421  ST-2591   1325  0.636981  27.740377  1986.492694  0.231698  0.030189   \n",
      "1422  ST-2592   5509  0.459793  27.386459  2897.938684  0.259757  0.012888   \n",
      "1423  ST-2593   3068  0.540417  37.476858  4701.100740  0.400587  0.024120   \n",
      "1424  ST-2594   3442  0.629285  25.036316  2775.664605  0.246659  0.021790   \n",
      "1425  ST-2595    939  0.658147  22.040469  1963.893525  0.271565  0.035144   \n",
      "1426  ST-2596   3668  0.586968  23.955834  2320.921150  0.254907  0.015540   \n",
      "1427  ST-2597    358  0.569832  17.067039  1727.686788  0.248603  0.030726   \n",
      "1428  ST-2598    581  0.588640  24.292599  2623.268726  0.242685  0.034423   \n",
      "1429  ST-2599   2545  0.614931  16.812967  1919.044743  0.206680  0.051473   \n",
      "1430    ST-26   1835  0.675749  20.293188  1959.740719  0.253951  0.049591   \n",
      "1431   ST-260    682  0.601173  23.482405  2730.417053  0.266862  0.029326   \n",
      "1432  ST-2600    723  0.601660  21.391425  2621.556404  0.295989  0.055325   \n",
      "1433  ST-2601   2828  0.615983  19.902051  1941.471008  0.256719  0.051980   \n",
      "1434  ST-2602   2696  0.576780  23.201780  2608.896907  0.255193  0.036350   \n",
      "1435  ST-2603    927  0.668824  16.991370  2022.999374  0.293420  0.064725   \n",
      "1436  ST-2605   2413  0.745131  20.109407  2699.596022  0.194364  0.228761   \n",
      "1437  ST-2606   2230  0.637668  18.571300  1902.804426  0.242601  0.050224   \n",
      "1438  ST-2607    899  0.684093  20.116796  2507.672992  0.273637  0.116796   \n",
      "1439  ST-2608   1327  0.488320  24.473248  2520.121025  0.333082  0.024115   \n",
      "1440  ST-2609   2769  0.555435  33.446732  4204.385367  0.333694  0.032503   \n",
      "1441   ST-261   1811  0.667587  20.410823  1911.932772  0.240751  0.041966   \n",
      "1442  ST-2610   1676  0.605012  25.026850  3317.182041  0.274463  0.074582   \n",
      "1443  ST-2611   3598  0.601167  15.171762  1595.751754  0.240689  0.072262   \n",
      "1444  ST-2613   2717  0.549135  14.727273  1566.488325  0.231873  0.094222   \n",
      "1445  ST-2614   2085  0.673861  17.762110  1951.992998  0.265707  0.102638   \n",
      "1446  ST-2615    433  0.454965  26.364896  1997.798083  0.392610  0.020785   \n",
      "1447  ST-2616    397  0.574307  17.221662  1935.179824  0.269521  0.032746   \n",
      "1448  ST-2617    828  0.611111  19.021739  1999.281389  0.270531  0.107488   \n",
      "1449  ST-2618    327  0.614679  17.623853  1821.227982  0.354740  0.051988   \n",
      "1450  ST-2619    513  0.627680  18.953216  2539.642943  0.300195  0.089669   \n",
      "1451   ST-262   6980  0.709456  22.763467  2448.189049  0.260172  0.069484   \n",
      "1452  ST-2621   1022  0.519569  25.057730  2439.972994  0.345401  0.020548   \n",
      "1453  ST-2622    183  0.672131  20.273224  3038.414645  0.316940  0.180328   \n",
      "1454  ST-2623   2156  0.656772  19.312152  1899.487727  0.210575  0.049165   \n",
      "1455  ST-2624    464  0.745690  14.172414  1716.279418  0.269397  0.077586   \n",
      "1456  ST-2625   2636  0.658953  19.040592  1915.737219  0.195372  0.069044   \n",
      "1457  ST-2626   1697  0.648203  21.289334  1925.363394  0.154390  0.059517   \n",
      "1458  ST-2627   1089  0.792470  20.723600  2420.464206  0.207530  0.021120   \n",
      "1459  ST-2628    373  0.710456  11.016086  1652.673056  0.257373  0.107239   \n",
      "1460  ST-2629   1877  0.573788  15.408631  1680.559707  0.254129  0.083644   \n",
      "1461  ST-2630   3277  0.637778  15.969179  1751.265743  0.240159  0.043332   \n",
      "1462  ST-2631    888  0.673423  17.771396  2001.859685  0.296171  0.072072   \n",
      "1463  ST-2632   1469  0.674609  17.660313  1998.624799  0.247107  0.031314   \n",
      "1464  ST-2633   2440  0.698770  18.475000  2432.857586  0.271311  0.090984   \n",
      "1465  ST-2634    868  0.707373  18.888249  2242.356509  0.289171  0.024194   \n",
      "1466  ST-2635   2708  0.546160  20.333087  2152.659790  0.267356  0.068316   \n",
      "1467  ST-2636   2948  0.564111  17.360583  1790.792534  0.278833  0.065807   \n",
      "1468  ST-2637   1453  0.622161  28.700619  3963.343765  0.167928  0.015141   \n",
      "1469  ST-2638    783  0.647510  16.151980  2160.876284  0.166028  0.021711   \n",
      "1470  ST-2639   1602  0.607990  25.393258  3241.726398  0.244694  0.053683   \n",
      "1471  ST-2641   1887  0.715951  18.926338  2387.498686  0.229465  0.101219   \n",
      "1472  ST-2642   4325  0.623121  12.482312  1545.326652  0.128786  0.022428   \n",
      "1473  ST-2643    880  0.767045  21.636364  2476.223000  0.153409  0.010227   \n",
      "1474  ST-2644    836  0.801435  22.935407  2700.677380  0.031100  0.004785   \n",
      "1475  ST-2645    775  0.827097  18.553548  1607.016581  0.089032  0.010323   \n",
      "1476  ST-2646   1104  0.746377  28.040761  2632.053451  0.150362  0.000000   \n",
      "1477  ST-2647    474  0.770042  27.755274  3275.837511  0.073840  0.000000   \n",
      "1478  ST-2648    379  0.786280  21.387863  2441.793113  0.229551  0.010554   \n",
      "1479  ST-2649   1079  0.699722  20.569972  2236.634634  0.266914  0.130677   \n",
      "1480   ST-265   2527  0.628809  24.165018  2128.824998  0.235853  0.048674   \n",
      "1481  ST-2650    454  0.764317  21.614537  3238.508392  0.310573  0.044053   \n",
      "1482  ST-2651    547  0.709324  22.363803  1852.618080  0.274223  0.073126   \n",
      "1483  ST-2652    785  0.756688  17.717197  2164.480866  0.268790  0.070064   \n",
      "1484  ST-2653   2602  0.647194  23.369331  3068.099377  0.275942  0.082629   \n",
      "1485  ST-2654   3240  0.664506  22.955247  2754.572040  0.275000  0.124074   \n",
      "1486  ST-2655   1898  0.674394  20.791359  2055.779299  0.168599  0.015806   \n",
      "1487  ST-2656    449  0.714922  27.806236  2684.847728  0.193764  0.033408   \n",
      "1488  ST-2657    373  0.817694  26.327078  2061.495845  0.168901  0.058981   \n",
      "1489  ST-2658   1124  0.597865  26.395018  3238.842082  0.243772  0.044484   \n",
      "1490  ST-2659   1603  0.628821  22.406737  2584.835608  0.258266  0.031815   \n",
      "1491   ST-266   1006  0.638171  32.691849  4260.155030  0.239563  0.021869   \n",
      "1492  ST-2661     55  0.654545  15.672727  1811.490545  0.200000  0.218182   \n",
      "1493  ST-2662    263  0.730038  15.893536  2206.533802  0.102662  0.045627   \n",
      "1494  ST-2663    744  0.516129  19.696237  1886.889059  0.262097  0.029570   \n",
      "1495  ST-2664    928  0.631466  33.688578  4602.285905  0.317888  0.037716   \n",
      "1496  ST-2665     40  0.600000  21.025000  3502.040500  0.225000  0.250000   \n",
      "1497  ST-2666    627  0.719298  25.258373  2755.779011  0.186603  0.035088   \n",
      "1498  ST-2667   1310  0.683206  24.660305  2609.810298  0.223664  0.011450   \n",
      "1499  ST-2668   2524  0.612520  21.990491  2497.849849  0.222662  0.037639   \n",
      "1500  ST-2669   1499  0.733155  23.523682  2713.062789  0.254837  0.074049   \n",
      "1501   ST-267   1313  0.694593  27.402133  2896.729223  0.246763  0.023610   \n",
      "1502  ST-2671   1252  0.725240  21.491214  2561.841166  0.151757  0.030351   \n",
      "1503  ST-2673   1405  0.503203  44.481851  5317.113680  0.258363  0.054093   \n",
      "1504  ST-2674   1013  0.628825  23.218164  2817.376071  0.198421  0.047384   \n",
      "1505  ST-2675    265  0.509434  26.320755  2711.595849  0.381132  0.033962   \n",
      "1506  ST-2676    610  0.698361  17.075410  2262.729082  0.226230  0.059016   \n",
      "1507  ST-2677    912  0.623904  21.883772  2689.591469  0.320175  0.049342   \n",
      "1508  ST-2678   2303  0.653930  21.737733  2468.958133  0.287451  0.048198   \n",
      "1509  ST-2679    760  0.598684  23.855263  2858.099566  0.211842  0.055263   \n",
      "1510   ST-268    539  0.749536  18.538033  2217.008312  0.192950  0.077922   \n",
      "1511  ST-2680    476  0.699580  31.817227  2609.949475  0.197479  0.039916   \n",
      "1512  ST-2681   1137  0.586631  20.096746  2485.116447  0.260334  0.075638   \n",
      "1513  ST-2682    346  0.693642  24.312139  3164.445318  0.222543  0.026012   \n",
      "1514  ST-2683    493  0.640974  24.833671  3088.067890  0.251521  0.030426   \n",
      "1515  ST-2684    436  0.711009  22.706422  2529.419197  0.282110  0.055046   \n",
      "1516  ST-2685    634  0.586751  27.580442  3837.063912  0.274448  0.020505   \n",
      "1517  ST-2686    393  0.562341  28.147583  3556.930458  0.274809  0.045802   \n",
      "1518  ST-2688   2676  0.527280  48.255605  7386.736839  0.355007  0.044469   \n",
      "1519  ST-2689   1829  0.749043  26.066703  2376.791110  0.202843  0.061782   \n",
      "1520   ST-269   3133  0.696776  22.628471  2664.605618  0.245452  0.038940   \n",
      "1521  ST-2690    366  0.617486  29.008197  3787.310219  0.259563  0.084699   \n",
      "1522  ST-2691    788  0.704315  21.467005  2294.747538  0.261421  0.036802   \n",
      "1523  ST-2692   2330  0.685408  13.075966  1566.157755  0.202146  0.011588   \n",
      "1524  ST-2693   3117  0.706128  22.803337  2187.447639  0.174206  0.006737   \n",
      "1525  ST-2694    477  0.635220  34.276730  4068.424088  0.299790  0.020964   \n",
      "1526  ST-2696    958  0.605428  16.938413  2027.927234  0.206681  0.058455   \n",
      "1527  ST-2697   1386  0.595960  19.011544  2372.868492  0.186147  0.039683   \n",
      "1528  ST-2698   1651  0.644458  16.387644  1644.653798  0.270139  0.030285   \n",
      "1529  ST-2699   2918  0.595956  20.030500  1808.800679  0.268677  0.062714   \n",
      "1530    ST-27    780  0.728205  17.708974  1899.399756  0.250000  0.044872   \n",
      "1531   ST-270   2419  0.693262  17.702356  1997.827313  0.260025  0.031005   \n",
      "1532  ST-2700   2284  0.563485  20.663748  2875.968778  0.278021  0.071366   \n",
      "1533  ST-2701   1820  0.654945  18.900000  2027.929610  0.253297  0.054396   \n",
      "1534  ST-2702   3754  0.666489  18.955781  2031.061185  0.234150  0.051145   \n",
      "1535  ST-2703   2497  0.599519  21.379255  2454.738638  0.259111  0.027633   \n",
      "1536  ST-2704   1236  0.627023  16.915858  2387.522654  0.204693  0.033981   \n",
      "1537  ST-2705   2095  0.726014  22.296420  2814.112382  0.217661  0.050597   \n",
      "1538  ST-2706   3321  0.587775  18.130684  1872.555185  0.261066  0.041253   \n",
      "1539  ST-2707   1405  0.617794  19.652669  2790.128014  0.269039  0.062633   \n",
      "1540  ST-2708    802  0.753117  19.345387  2415.429638  0.281796  0.036160   \n",
      "1541  ST-2709   2527  0.615354  18.856351  2171.806003  0.258013  0.049861   \n",
      "1542   ST-271   4687  0.639001  16.152123  1753.859296  0.211436  0.049712   \n",
      "1543  ST-2710   2084  0.579175  20.226967  2381.840043  0.278311  0.088292   \n",
      "1544  ST-2711   3467  0.646380  15.885203  1847.415472  0.272570  0.034900   \n",
      "1545  ST-2712    440  0.663636  18.450000  2353.583068  0.329545  0.011364   \n",
      "1546  ST-2713   1825  0.664658  21.146301  2648.600345  0.269589  0.052055   \n",
      "1547  ST-2714   2581  0.669120  19.433553  2570.508501  0.234405  0.058892   \n",
      "1548  ST-2715   1801  0.624098  30.028318  4386.218884  0.291505  0.043309   \n",
      "1549  ST-2716   2540  0.628740  15.931890  1671.645512  0.259055  0.061811   \n",
      "1550  ST-2717   1887  0.645999  17.196608  2101.963863  0.267091  0.076312   \n",
      "1551  ST-2718   8376  0.558142  21.766237  2973.559256  0.262178  0.028653   \n",
      "1552  ST-2719   2553  0.653349  15.996866  1796.957658  0.300039  0.029377   \n",
      "1553   ST-272   4717  0.659953  18.026288  1945.480278  0.225355  0.050880   \n",
      "1554  ST-2720    981  0.637105  22.602446  2480.399154  0.253823  0.014271   \n",
      "1555  ST-2722   1271  0.673485  20.576711  2740.125869  0.247836  0.112510   \n",
      "1556  ST-2723    855  0.699415  36.582456  5520.350035  0.432749  0.037427   \n",
      "1557  ST-2724   1784  0.584641  21.840247  2590.652377  0.243274  0.056614   \n",
      "1558  ST-2725    749  0.694259  18.738318  2395.470601  0.277704  0.056075   \n",
      "1559  ST-2726   5784  0.614799  19.944848  2327.084723  0.265041  0.040456   \n",
      "1560  ST-2727    300  0.623333  23.333333  2470.924833  0.356667  0.046667   \n",
      "1561  ST-2728    903  0.589147  34.349945  4150.598250  0.326689  0.028793   \n",
      "1562  ST-2729   2863  0.560950  17.641285  2128.450929  0.268949  0.039469   \n",
      "1563   ST-273   4716  0.635708  19.007846  2022.662326  0.245759  0.064673   \n",
      "1564  ST-2730   1319  0.606520  17.742987  2075.575823  0.280516  0.084913   \n",
      "1565  ST-2731   1969  0.609954  24.120874  3095.161828  0.277806  0.063992   \n",
      "1566  ST-2732   3325  0.594286  19.616842  2356.232508  0.271880  0.059850   \n",
      "1567  ST-2733   1266  0.657188  19.515798  2430.738807  0.282780  0.043444   \n",
      "1568  ST-2734    489  0.713701  18.754601  2056.986708  0.257669  0.055215   \n",
      "1569  ST-2736    725  0.693793  18.760000  1890.859945  0.227586  0.034483   \n",
      "1570  ST-2737    653  0.644717  23.886677  2773.053660  0.284839  0.052067   \n",
      "1571  ST-2738   4772  0.638516  20.510687  1885.338034  0.259011  0.050712   \n",
      "1572  ST-2739   1098  0.630237  19.305100  2059.257086  0.257741  0.054645   \n",
      "1573   ST-274   2482  0.599919  19.968171  2262.135359  0.272764  0.043916   \n",
      "1574  ST-2740   5863  0.579908  17.096708  1670.818958  0.235033  0.031895   \n",
      "1575  ST-2742   3400  0.607353  18.616176  1789.918185  0.254412  0.078235   \n",
      "1576  ST-2743    904  0.529867  32.360619  3327.443761  0.268805  0.054204   \n",
      "1577  ST-2744    816  0.674020  24.615196  3296.714375  0.193627  0.077206   \n",
      "1578  ST-2745    979  0.629213  22.309499  2628.989796  0.195097  0.043922   \n",
      "1579  ST-2746     52  0.673077  35.288462  5562.285192  0.423077  0.000000   \n",
      "1580  ST-2747   2858  0.723583  18.361791  2004.520175  0.242127  0.041638   \n",
      "1581  ST-2748   6133  0.631665  17.820153  1746.277743  0.214903  0.042231   \n",
      "1582  ST-2749   6886  0.670346  18.819344  1882.053124  0.276648  0.078856   \n",
      "1583   ST-275    509  0.726916  16.862475  2080.277132  0.241650  0.029470   \n",
      "1584  ST-2750    775  0.645161  18.087742  1946.548658  0.291613  0.037419   \n",
      "1585  ST-2751   2385  0.637317  20.050734  1890.910939  0.261635  0.106499   \n",
      "1586  ST-2752   1309  0.647823  15.284186  1895.518839  0.176471  0.026738   \n",
      "1587  ST-2753   1232  0.692370  23.688312  2578.339903  0.265422  0.085227   \n",
      "1588  ST-2754   1576  0.601523  23.381345  2838.324619  0.237310  0.019036   \n",
      "1589  ST-2756    771  0.527886  21.592737  2877.414241  0.300908  0.071336   \n",
      "1590  ST-2757   1352  0.576183  18.280325  2216.326361  0.282544  0.036982   \n",
      "1591  ST-2759   1932  0.666667  18.208592  2123.724472  0.268116  0.040890   \n",
      "1592   ST-276   2851  0.707120  22.634865  2637.401459  0.272887  0.072957   \n",
      "1593  ST-2760   6173  0.688158  16.202819  1665.448072  0.266645  0.038069   \n",
      "1594  ST-2761   6584  0.637151  19.584143  1919.330143  0.254557  0.049210   \n",
      "1595  ST-2762   2615  0.659656  20.078394  2125.092612  0.256597  0.096367   \n",
      "1596  ST-2763   1903  0.626905  16.985812  2073.841661  0.242249  0.018392   \n",
      "1597  ST-2764   5243  0.603471  16.164028  1635.121184  0.308220  0.024604   \n",
      "1598  ST-2765   6344  0.639975  15.736917  1638.878053  0.295240  0.022541   \n",
      "1599  ST-2767   2313  0.706874  18.960657  2277.883796  0.285344  0.063554   \n",
      "1600  ST-2768   1758  0.754835  19.831627  2342.307008  0.243458  0.067122   \n",
      "1601  ST-2769   1549  0.723047  14.909619  2071.410755  0.067140  0.010329   \n",
      "1602   ST-277   3991  0.628414  35.376597  4718.079386  0.329742  0.038086   \n",
      "1603  ST-2770   1913  0.742290  19.266597  2141.660387  0.252483  0.059592   \n",
      "1604  ST-2771   3017  0.737156  17.313225  2000.190792  0.261850  0.087173   \n",
      "1605  ST-2772    184  0.690217  26.695652  3163.096304  0.342391  0.027174   \n",
      "1606  ST-2773   2193  0.618331  16.305518  1828.091154  0.257182  0.031920   \n",
      "1607  ST-2774   4137  0.655789  20.585690  2200.903553  0.193619  0.013053   \n",
      "1608  ST-2775   2840  0.596831  17.459507  1872.487370  0.280634  0.038380   \n",
      "1609  ST-2776    961  0.663892  18.998959  2164.705442  0.268470  0.085328   \n",
      "1610  ST-2777   2140  0.634579  20.551402  2311.213570  0.274299  0.045794   \n",
      "1611  ST-2778   1838  0.663221  20.573449  2252.667214  0.232318  0.053863   \n",
      "1612  ST-2779    739  0.562923  33.144790  3751.736509  0.296346  0.040595   \n",
      "1613   ST-278   6301  0.589748  26.513093  2817.035182  0.262181  0.039041   \n",
      "1614  ST-2780    579  0.694301  18.091537  1951.850138  0.305699  0.031088   \n",
      "1615  ST-2781    277  0.754513  12.891697  1825.873105  0.220217  0.032491   \n",
      "1616  ST-2782   1122  0.598039  23.028520  2298.565009  0.237077  0.043672   \n",
      "1617  ST-2783    545  0.543119  20.607339  2541.043835  0.222018  0.053211   \n",
      "1618  ST-2785   1633  0.676669  20.155542  2397.718034  0.285364  0.073484   \n",
      "1619  ST-2786   2407  0.788533  15.087661  1839.033133  0.214375  0.013710   \n",
      "1620  ST-2787   2063  0.663597  23.264178  2678.568182  0.242365  0.070771   \n",
      "1621  ST-2788    683  0.715959  21.521230  2974.531772  0.243045  0.046852   \n",
      "1622  ST-2789   2929  0.616934  12.016388  1341.110959  0.246842  0.045749   \n",
      "1623   ST-279   3805  0.612089  30.445466  4002.790378  0.180552  0.032326   \n",
      "1624  ST-2790    349  0.747851  20.498567  2060.664269  0.263610  0.011461   \n",
      "1625  ST-2791   4935  0.594124  23.678825  2765.960946  0.327457  0.005066   \n",
      "1626  ST-2792   3148  0.632465  20.223952  1901.214686  0.251271  0.031766   \n",
      "1627  ST-2793   3800  0.635000  16.617632  1861.193145  0.213158  0.057368   \n",
      "1628  ST-2794   1176  0.698980  15.441327  1796.917619  0.249150  0.083333   \n",
      "1629  ST-2795    786  0.548346  17.162850  2519.944860  0.165394  0.053435   \n",
      "1630  ST-2796   5179  0.574049  19.817919  2208.383543  0.254296  0.053871   \n",
      "1631  ST-2797   5151  0.497185  22.706853  2242.166366  0.254125  0.073772   \n",
      "1632  ST-2798   1991  0.569563  16.632848  1981.505329  0.261678  0.033149   \n",
      "1633  ST-2799   3101  0.585295  36.642696  6441.358288  0.332796  0.031925   \n",
      "1634    ST-28   1966  0.730926  20.506104  2061.171623  0.212614  0.061038   \n",
      "1635   ST-280   3566  0.637970  18.654795  1648.747793  0.198822  0.031688   \n",
      "1636  ST-2800   1651  0.678982  19.932162  2110.854337  0.242883  0.058752   \n",
      "1637  ST-2801    795  0.693082  16.494340  1990.492252  0.247799  0.104403   \n",
      "1638  ST-2802    210  0.695238  18.190476  2043.491476  0.261905  0.042857   \n",
      "1639  ST-2803   1967  0.680224  17.965938  1994.120402  0.245552  0.043721   \n",
      "1640  ST-2804    904  0.595133  18.596239  2047.837865  0.285398  0.045354   \n",
      "1641  ST-2805    320  0.706250  23.175000  2174.809938  0.218750  0.212500   \n",
      "1642  ST-2806   2323  0.597934  15.994834  1558.950263  0.119673  0.012053   \n",
      "1643  ST-2807   4887  0.596685  17.583998  1738.243260  0.248619  0.072232   \n",
      "1644  ST-2808   1049  0.632031  17.938036  1857.495052  0.252622  0.120114   \n",
      "1645  ST-2809   2418  0.666667  18.992969  2116.444773  0.233251  0.064103   \n",
      "1646   ST-281   4544  0.624340  21.224912  2150.253242  0.193662  0.018486   \n",
      "1647  ST-2810   2637  0.708760  22.874099  2615.127899  0.293136  0.040576   \n",
      "1648  ST-2811   3564  0.746352  19.018238  2280.008639  0.184063  0.012626   \n",
      "1649  ST-2812   6655  0.674230  17.687904  1944.472696  0.206461  0.043276   \n",
      "1650  ST-2813   1125  0.657778  21.300444  2092.923191  0.245333  0.025778   \n",
      "1651  ST-2814   4112  0.705739  28.291586  3245.030581  0.204767  0.015321   \n",
      "1652  ST-2815   8926  0.583912  19.470087  2021.368304  0.332400  0.014004   \n",
      "1653  ST-2816   3407  0.678896  18.358673  2089.070883  0.242736  0.027884   \n",
      "1654  ST-2817   2733  0.555068  17.673985  1955.153249  0.248079  0.038419   \n",
      "1655  ST-2818   1717  0.625510  20.790332  2146.735824  0.263832  0.055911   \n",
      "1656  ST-2819   2114  0.701987  18.761116  2069.482417  0.244087  0.069063   \n",
      "1657   ST-282   1277  0.632733  18.018011  2114.973171  0.108066  0.023493   \n",
      "1658  ST-2820   7231  0.666574  17.053381  2056.945255  0.226940  0.046605   \n",
      "1659  ST-2821   1026  0.608187  16.565302  1757.458908  0.266082  0.109162   \n",
      "1660  ST-2822   7239  0.627435  17.150021  1557.012336  0.234287  0.041304   \n",
      "1661  ST-2823   4209  0.650036  20.794726  1849.843179  0.253504  0.056545   \n",
      "1662  ST-2824    813  0.639606  16.020910  1964.917626  0.261993  0.066421   \n",
      "1663  ST-2825   1892  0.716702  20.214588  2667.718832  0.281184  0.037526   \n",
      "1664  ST-2826   4485  0.593534  16.188183  1665.222381  0.247269  0.020290   \n",
      "1665  ST-2827   1031  0.677983  24.294859  3513.959593  0.281280  0.111542   \n",
      "1666  ST-2828    531  0.604520  24.621469  2691.394030  0.274953  0.065913   \n",
      "1667  ST-2829    311  0.742765  25.890675  3104.998682  0.250804  0.106109   \n",
      "1668   ST-283   1952  0.560451  16.898053  1676.858817  0.194160  0.027152   \n",
      "1669  ST-2830   1076  0.635688  20.749071  2720.197230  0.297398  0.051115   \n",
      "1670  ST-2831   2567  0.550058  12.967667  1245.229092  0.230230  0.033892   \n",
      "1671  ST-2832   3628  0.620728  11.613837  1372.992770  0.211411  0.034179   \n",
      "1672  ST-2833   5255  0.540628  18.392769  1611.828729  0.267555  0.055947   \n",
      "1673  ST-2834   1231  0.639318  28.720552  3319.962721  0.123477  0.020309   \n",
      "1674  ST-2835   4068  0.630039  18.632006  2369.563122  0.274828  0.081613   \n",
      "1675  ST-2837    866  0.703233  23.267898  2468.027021  0.249423  0.063510   \n",
      "1676  ST-2838    476  0.571429  22.310924  2504.958382  0.216387  0.048319   \n",
      "1677  ST-2839    736  0.557065  42.592391  6403.853342  0.285326  0.048913   \n",
      "1678   ST-284   1535  0.641694  18.091857  1844.791114  0.255375  0.041694   \n",
      "1679  ST-2841    483  0.631470  21.134576  2533.242650  0.265010  0.051760   \n",
      "1680  ST-2842   1722  0.646922  17.297329  1896.398891  0.278746  0.085366   \n",
      "1681  ST-2843   1915  0.615144  32.743081  5073.650016  0.253264  0.045431   \n",
      "1682  ST-2844   5470  0.618830  20.466362  2015.172547  0.271481  0.027239   \n",
      "1683  ST-2845   1745  0.731232  18.745559  2034.535054  0.139255  0.014900   \n",
      "1684  ST-2846   2326  0.600602  20.608340  2485.923633  0.253654  0.061049   \n",
      "1685  ST-2847   1046  0.589866  21.503824  2632.106759  0.179732  0.026769   \n",
      "1686  ST-2849   2025  0.739753  22.875556  2852.933817  0.259259  0.098272   \n",
      "1687   ST-285   5489  0.648023  19.166697  1995.490261  0.262889  0.038076   \n",
      "1688  ST-2850   1296  0.526235  37.451389  4821.255193  0.398148  0.028549   \n",
      "1689  ST-2851   2824  0.676346  16.710340  1796.556916  0.291431  0.067280   \n",
      "1690  ST-2852   1741  0.599081  16.035612  1631.738811  0.191844  0.034463   \n",
      "1691  ST-2853     94  0.936170  23.361702  4112.706383  0.276596  0.138298   \n",
      "1692  ST-2854   2069  0.641856  24.973900  2434.663842  0.284679  0.056066   \n",
      "1693  ST-2855   1094  0.701097  22.199269  2806.564808  0.295247  0.152651   \n",
      "1694  ST-2856    125  0.712000  18.960000  2266.800960  0.376000  0.136000   \n",
      "1695  ST-2857   3969  0.560091  13.891156  1303.764142  0.245150  0.009070   \n",
      "1696  ST-2858   3666  0.593562  10.450355  1140.285000  0.166394  0.030551   \n",
      "1697  ST-2859   1659  0.541290  19.981314  2200.134165  0.223629  0.051838   \n",
      "1698   ST-286   3618  0.692371  19.601437  2339.517778  0.263682  0.058872   \n",
      "1699  ST-2860   2614  0.662586  14.449503  1629.759881  0.253634  0.039021   \n",
      "1700  ST-2861   1610  0.564596  21.217391  2637.296453  0.336025  0.046584   \n",
      "1701  ST-2862    880  0.682955  20.363636  2201.761386  0.319318  0.069318   \n",
      "1702  ST-2865   6288  0.552004  17.431934  1743.000530  0.268607  0.068225   \n",
      "1703  ST-2866   1355  0.755720  20.415498  2581.135513  0.235424  0.071587   \n",
      "1704  ST-2867   1545  0.653074  18.938511  2049.521340  0.227184  0.014887   \n",
      "1705  ST-2868   1059  0.709160  19.293673  2406.296053  0.218130  0.089707   \n",
      "1706  ST-2869   1048  0.655534  21.560115  2507.642271  0.273855  0.060115   \n",
      "1707   ST-287   4476  0.545353  15.094951  1477.039294  0.129580  0.018097   \n",
      "1708  ST-2870   1536  0.705729  23.158854  2354.260768  0.180990  0.052083   \n",
      "1709  ST-2871   9413  0.576968  10.216615  1128.552704  0.192712  0.014448   \n",
      "1710  ST-2872    772  0.678756  20.279793  2301.078057  0.290155  0.075130   \n",
      "1711  ST-2873   2566  0.702650  22.509743  1880.915090  0.277475  0.118083   \n",
      "1712  ST-2874   1221  0.606880  23.979525  2886.062154  0.280098  0.026208   \n",
      "1713  ST-2875    402  0.646766  22.529851  2582.519478  0.296020  0.014925   \n",
      "1714  ST-2876   8298  0.512774  22.119306  2240.029638  0.282237  0.056640   \n",
      "1715  ST-2877    995  0.566834  20.927638  2102.790643  0.276382  0.040201   \n",
      "1716  ST-2878   1766  0.615515  22.273499  2339.783222  0.261042  0.066251   \n",
      "1717  ST-2879   2643  0.720772  19.764661  2402.907832  0.303065  0.094589   \n",
      "1718   ST-288   2866  0.589323  19.171319  1932.888664  0.191207  0.051989   \n",
      "1719  ST-2880    404  0.720297  27.792079  3780.901832  0.334158  0.108911   \n",
      "1720  ST-2882    869  0.714614  22.112773  2321.395374  0.247411  0.049482   \n",
      "1721  ST-2883   2907  0.664259  20.239766  2072.836106  0.239766  0.040592   \n",
      "1722  ST-2884   2874  0.605776  11.132220  1247.137032  0.188935  0.019137   \n",
      "1723  ST-2885    849  0.514723  13.930506  1508.620035  0.197880  0.027091   \n",
      "1724  ST-2886   3248  0.545874  12.847906  1432.806693  0.171798  0.018165   \n",
      "1725  ST-2887   2041  0.675159  24.803038  2759.254787  0.261146  0.048506   \n",
      "1726  ST-2888   5231  0.662015  15.651692  1631.247943  0.254062  0.051424   \n",
      "1727  ST-2889   4240  0.608019  10.663915  1216.959884  0.166981  0.010377   \n",
      "1728   ST-289   7057  0.638232  15.514241  1368.953903  0.233385  0.007085   \n",
      "1729  ST-2890   1929  0.618974  15.593572  1745.452649  0.246242  0.023328   \n",
      "1730  ST-2891   3642  0.605986  15.298462  1796.967861  0.224327  0.017298   \n",
      "1731  ST-2892   3952  0.603998  15.794787  1856.003811  0.242915  0.048836   \n",
      "1732  ST-2893    620  0.808065  19.445161  2436.167742  0.254839  0.083871   \n",
      "1733  ST-2894    922  0.552061  15.479393  2185.667267  0.214751  0.079176   \n",
      "1734  ST-2895    877  0.576967  17.192702  2405.163592  0.239453  0.044470   \n",
      "1735  ST-2896   3947  0.626298  18.188751  2095.405044  0.232328  0.055232   \n",
      "1736  ST-2897   2209  0.645541  21.383884  2627.043843  0.268900  0.046627   \n",
      "1737  ST-2898   2011  0.686226  17.208851  1794.337146  0.207360  0.031825   \n",
      "1738  ST-2899   1663  0.682502  28.754660  2664.766091  0.187011  0.016236   \n",
      "1739    ST-29    513  0.752437  19.181287  2142.428226  0.288499  0.099415   \n",
      "1740   ST-290   1672  0.714713  14.216507  1801.084629  0.239833  0.134569   \n",
      "1741  ST-2901   1460  0.579452  13.176027  1738.534562  0.265068  0.055479   \n",
      "1742  ST-2902   2868  0.653068  22.691771  2535.994836  0.264644  0.033473   \n",
      "1743  ST-2903   4041  0.566444  19.111854  2205.265006  0.269240  0.035635   \n",
      "1744  ST-2904   1475  0.543729  25.736271  3469.988041  0.246102  0.072542   \n",
      "1745  ST-2905  17620  0.493019  42.800000  5455.544369  0.413224  0.036720   \n",
      "1746  ST-2906   1475  0.591186  15.322034  1921.181593  0.279322  0.067119   \n",
      "1747  ST-2907   1254  0.624402  21.065391  2842.635845  0.299841  0.098884   \n",
      "1748  ST-2908   1406  0.660740  13.472262  1358.601679  0.204836  0.007112   \n",
      "1749  ST-2909    620  0.598387  19.058065  1848.939565  0.211290  0.014516   \n",
      "1750   ST-291   1816  0.701542  17.083150  2032.995402  0.312225  0.085352   \n",
      "1751  ST-2910    383  0.723238  19.665796  2849.391723  0.198433  0.041775   \n",
      "1752  ST-2911    171  0.543860  27.497076  3447.818246  0.239766  0.087719   \n",
      "1753  ST-2912    237  0.814346  14.713080  2085.117679  0.236287  0.177215   \n",
      "1754  ST-2913    539  0.751391  16.923933  2017.161540  0.261596  0.074212   \n",
      "1755  ST-2914   1359  0.565121  22.396615  2958.692038  0.300221  0.044150   \n",
      "1756  ST-2915   1856  0.587284  21.126616  2593.086988  0.230065  0.058190   \n",
      "1757  ST-2916   1113  0.642408  26.613657  3341.688203  0.248877  0.059299   \n",
      "1758  ST-2917    730  0.600000  18.995890  2226.916288  0.227397  0.045205   \n",
      "1759  ST-2918   2203  0.579210  20.905129  2059.733246  0.261008  0.057195   \n",
      "1760   ST-292   6099  0.608952  18.788490  1936.612625  0.219052  0.009510   \n",
      "1761  ST-2920   3541  0.639932  23.211240  2780.073318  0.216041  0.029935   \n",
      "1762  ST-2921   1562  0.585787  16.850192  1916.413355  0.263764  0.037772   \n",
      "1763  ST-2922   2171  0.569784  16.603409  1883.748881  0.281898  0.087057   \n",
      "1764  ST-2923    881  0.742338  17.195233  1958.189818  0.185017  0.037457   \n",
      "1765  ST-2924   3010  0.624585  27.426910  3593.277718  0.250831  0.051827   \n",
      "1766  ST-2925    577  0.745234  15.206239  1671.576378  0.164645  0.005199   \n",
      "1767  ST-2926    276  0.818841  20.489130  2030.990471  0.235507  0.028986   \n",
      "1768  ST-2927    428  0.785047  18.250000  2033.979042  0.140187  0.007009   \n",
      "1769  ST-2928   1267  0.595107  18.922652  1946.652084  0.219416  0.032360   \n",
      "1770  ST-2929   1071  0.850607  15.263305  1855.504818  0.119514  0.040149   \n",
      "1771   ST-293   3300  0.679394  19.615455  1857.786397  0.273030  0.043939   \n",
      "1772  ST-2931    511  0.747554  26.968689  2881.445695  0.246575  0.023483   \n",
      "1773  ST-2932   1478  0.590663  15.652233  1785.927348  0.224628  0.020974   \n",
      "1774  ST-2933    195  0.671795  20.076923  2876.921077  0.205128  0.076923   \n",
      "1775  ST-2934    452  0.674779  31.148230  2979.666150  0.272124  0.022124   \n",
      "1776  ST-2935   1725  0.698551  19.762899  2131.208609  0.264348  0.068986   \n",
      "1777  ST-2936    383  0.530026  25.255875  2384.319399  0.305483  0.083551   \n",
      "1778  ST-2937    350  0.660000  18.411429  2337.243543  0.214286  0.074286   \n",
      "1779  ST-2938    519  0.736031  21.574181  2225.026474  0.292871  0.102119   \n",
      "1780  ST-2939    198  0.681818  18.757576  2292.564141  0.348485  0.080808   \n",
      "1781   ST-294   5223  0.628757  15.123492  1481.588455  0.206012  0.028528   \n",
      "1782  ST-2940    687  0.700146  19.919942  2285.120393  0.308588  0.048035   \n",
      "1783  ST-2941    999  0.680681  18.788789  2511.330951  0.316316  0.132132   \n",
      "1784  ST-2942    694  0.693084  21.923631  2619.095115  0.121037  0.005764   \n",
      "1785  ST-2943   4194  0.593467  12.758226  1573.852442  0.211969  0.022890   \n",
      "1786  ST-2944   2518  0.655679  20.770056  2321.368666  0.248610  0.021843   \n",
      "1787  ST-2945   4210  0.661995  13.735392  1546.495135  0.152969  0.107126   \n",
      "1788  ST-2946   1366  0.669107  18.733529  2070.852921  0.254758  0.074671   \n",
      "1789  ST-2947    931  0.696026  19.717508  2616.799280  0.250269  0.021482   \n",
      "1790  ST-2948   1696  0.612618  19.038915  2297.858225  0.270637  0.160967   \n",
      "1791  ST-2949    405  0.730864  14.506173  1645.727728  0.276543  0.138272   \n",
      "1792   ST-295   9669  0.638225  18.629331  2100.989318  0.248319  0.024822   \n",
      "1793  ST-2952   1716  0.683566  15.385198  1839.448362  0.277389  0.057110   \n",
      "1794  ST-2953    747  0.689424  15.270415  1880.237122  0.262383  0.060241   \n",
      "1795  ST-2954    426  0.739437  14.687793  1549.650000  0.284038  0.070423   \n",
      "1796  ST-2955    327  0.724771  17.403670  2280.110948  0.311927  0.076453   \n",
      "1797  ST-2956    930  0.645161  15.076344  1783.130376  0.263441  0.079570   \n",
      "1798  ST-2957   1345  0.590335  20.220074  2357.732885  0.228253  0.127138   \n",
      "1799  ST-2958   3150  0.627302  23.455238  2630.773225  0.273968  0.068571   \n",
      "1800  ST-2959    909  0.690869  20.746975  2103.950121  0.272827  0.074807   \n",
      "1801   ST-296   2231  0.616316  41.630659  4706.285742  0.354101  0.013447   \n",
      "1802  ST-2960   4572  0.647638  17.332458  1806.705420  0.287620  0.023403   \n",
      "1803  ST-2961   2203  0.644122  18.072174  1890.392819  0.110304  0.002724   \n",
      "1804  ST-2962   1114  0.675045  22.464991  2105.106643  0.164273  0.024237   \n",
      "1805  ST-2964   1229  0.715216  30.931652  4489.884272  0.119609  0.025224   \n",
      "1806  ST-2965   5594  0.591705  11.943868  1336.089322  0.218091  0.046657   \n",
      "1807  ST-2966   1423  0.529164  18.966268  1817.556831  0.225580  0.056219   \n",
      "1808  ST-2967   2234  0.595792  21.888541  2682.827963  0.250671  0.060877   \n",
      "1809  ST-2969    822  0.727494  17.069343  1974.689453  0.249392  0.059611   \n",
      "1810   ST-297   2762  0.574222  48.965605  5795.921043  0.396090  0.026430   \n",
      "1811  ST-2970    152  0.789474  21.684211  1618.500461  0.243421  0.157895   \n",
      "1812  ST-2971   1111  0.594059  18.944194  2635.187102  0.258326  0.051305   \n",
      "1813  ST-2972   3867  0.615723  16.460305  2060.506002  0.104732  0.008017   \n",
      "1814  ST-2974   3712  0.639009  18.215517  1996.544704  0.207705  0.037446   \n",
      "1815  ST-2975   3191  0.612974  23.983391  2932.222883  0.285177  0.054842   \n",
      "1816  ST-2976   1230  0.586992  15.543902  1818.494163  0.279675  0.037398   \n",
      "1817  ST-2977   1775  0.579155  19.708169  2287.789854  0.242817  0.051831   \n",
      "1818  ST-2978   1445  0.686505  17.923183  2179.337543  0.251903  0.036678   \n",
      "1819  ST-2979   6001  0.512248  20.012665  2018.145131  0.250958  0.060823   \n",
      "1820   ST-298   1240  0.683871  17.554839  2095.549387  0.307258  0.080645   \n",
      "1821  ST-2980    821  0.646772  15.377588  1812.093496  0.265530  0.113276   \n",
      "1822  ST-2981   2425  0.648247  18.515464  2458.146445  0.156701  0.016082   \n",
      "1823  ST-2983    305  0.763934  15.659016  1793.634656  0.262295  0.009836   \n",
      "1824  ST-2984   2371  0.613665  23.313370  2639.982813  0.177562  0.006748   \n",
      "1825  ST-2985    527  0.702087  24.743833  3096.676926  0.227704  0.041746   \n",
      "1826  ST-2986   1450  0.604828  21.240690  2545.658531  0.257931  0.040000   \n",
      "1827  ST-2987   1307  0.637337  22.718439  2702.053573  0.266259  0.030604   \n",
      "1828  ST-2988   1899  0.584518  18.932596  1821.775255  0.261190  0.066351   \n",
      "1829  ST-2989    247  0.578947  25.773279  2019.161498  0.234818  0.020243   \n",
      "1830   ST-299   1787  0.663682  18.902630  2072.369351  0.263011  0.068830   \n",
      "1831  ST-2990    516  0.558140  22.265504  2716.523566  0.267442  0.073643   \n",
      "1832  ST-2991   3772  0.629639  19.241251  2127.034976  0.297190  0.022800   \n",
      "1833  ST-2992   2833  0.659019  17.877162  1978.886004  0.279915  0.077303   \n",
      "1834  ST-2993   5622  0.549093  12.882604  1336.636697  0.202063  0.015297   \n",
      "1835  ST-2994   2748  0.589520  16.758006  2118.854582  0.241266  0.047307   \n",
      "1836  ST-2995   1375  0.723636  20.640727  1809.214793  0.240000  0.084364   \n",
      "1837  ST-2996   2394  0.558062  14.919799  1918.611896  0.261905  0.047619   \n",
      "1838  ST-2997   1164  0.674399  20.496564  2283.308617  0.267182  0.096220   \n",
      "1839  ST-2999   1940  0.663918  24.980412  3889.767840  0.103093  0.021134   \n",
      "1840    ST-30   1729  0.659341  26.317525  2749.802140  0.271833  0.056102   \n",
      "1841   ST-300   3157  0.590751  21.692113  2044.045274  0.255306  0.060184   \n",
      "1842  ST-3002   4086  0.580029  22.410181  2257.433904  0.201175  0.029613   \n",
      "1843  ST-3003   3522  0.546281  27.543441  2413.959032  0.201874  0.014196   \n",
      "1844  ST-3004   1226  0.614192  19.460848  2367.776387  0.279772  0.047308   \n",
      "1845  ST-3005    687  0.506550  19.049491  2177.004876  0.285298  0.026201   \n",
      "1846  ST-3006   1646  0.638518  20.064399  2297.391555  0.288578  0.080194   \n",
      "1847  ST-3008   2686  0.633284  20.871929  2144.648649  0.263589  0.027923   \n",
      "1848  ST-3009    451  0.598670  15.006652  1785.797871  0.301552  0.026608   \n",
      "1849  ST-3011   2673  0.664422  17.153386  1587.470774  0.202394  0.044893   \n",
      "1850  ST-3012   2160  0.672685  15.155093  1899.406037  0.271759  0.049537   \n",
      "1851  ST-3013   3128  0.602302  19.010230  2237.828283  0.281330  0.043478   \n",
      "1852  ST-3015   4188  0.590974  19.214900  1927.149269  0.290592  0.048233   \n",
      "1853  ST-3017   2147  0.587797  36.671169  4728.489832  0.322776  0.065673   \n",
      "1854  ST-3019   1029  0.639456  28.103984  3412.491759  0.261419  0.098154   \n",
      "1855   ST-302   3013  0.732493  17.557584  1887.572808  0.235646  0.084965   \n",
      "1856  ST-3020    644  0.692547  22.608696  2999.058494  0.239130  0.035714   \n",
      "1857  ST-3021    784  0.693878  21.382653  2286.839732  0.255102  0.049745   \n",
      "1858  ST-3022     50  0.780000  21.600000  2876.861000  0.320000  0.140000   \n",
      "1859  ST-3023   1562  0.675416  16.820102  2194.233630  0.213828  0.023688   \n",
      "1860  ST-3024   1150  0.575652  16.559130  2193.040070  0.260000  0.026087   \n",
      "1861  ST-3025   1150  0.673043  20.896522  1925.642217  0.270435  0.064348   \n",
      "1862  ST-3026   2013  0.712866  15.947839  1956.232300  0.241927  0.063090   \n",
      "1863  ST-3027    462  0.800866  18.781385  1930.302208  0.212121  0.056277   \n",
      "1864  ST-3028    327  0.675841  16.620795  2001.750612  0.275229  0.051988   \n",
      "1865  ST-3029   2862  0.577918  11.923829  1388.331709  0.233054  0.034591   \n",
      "1866   ST-303   3018  0.699801  16.202121  1851.649394  0.295229  0.104374   \n",
      "1867  ST-3030   1640  0.648171  21.498780  2053.959061  0.218293  0.029878   \n",
      "1868  ST-3031   1822  0.821076  15.943469  2016.512887  0.096048  0.008782   \n",
      "1869  ST-3032   1300  0.700000  17.580769  2698.676738  0.203846  0.101538   \n",
      "1870  ST-3033   1266  0.574250  26.661137  3903.788081  0.269352  0.028436   \n",
      "1871  ST-3034    193  0.746114  21.461140  3316.145699  0.243523  0.134715   \n",
      "1872  ST-3035    999  0.795796  18.932933  2272.394885  0.224224  0.028028   \n",
      "1873  ST-3036    431  0.649652  18.013921  2723.926543  0.317865  0.051044   \n",
      "1874  ST-3037   1079  0.645042  14.943466  2037.714217  0.207600  0.065802   \n",
      "1875  ST-3038   1442  0.481276  16.498613  1394.137053  0.138696  0.027046   \n",
      "1876  ST-3039   1557  0.448940  15.991651  1310.885890  0.154785  0.041105   \n",
      "1877   ST-304   2226  0.723720  15.933064  1764.129034  0.286613  0.101527   \n",
      "1878  ST-3040   2290  0.641048  23.275546  3183.300672  0.294760  0.124891   \n",
      "1879  ST-3041    461  0.707158  13.780911  1727.218416  0.245119  0.101952   \n",
      "1880  ST-3042   2895  0.555095  27.721244  3438.870249  0.208981  0.042832   \n",
      "1881  ST-3043   4860  0.554527  16.752058  1889.194885  0.132305  0.019136   \n",
      "1882  ST-3044   3256  0.645270  16.851044  1794.350541  0.101351  0.025799   \n",
      "1883  ST-3045    103  0.825243  26.077670  2954.726602  0.398058  0.135922   \n",
      "1884  ST-3046   3559  0.626019  19.781961  2444.875780  0.235178  0.073616   \n",
      "1885  ST-3047   2287  0.608220  15.937473  1455.833533  0.197639  0.034543   \n",
      "1886  ST-3048    449  0.830735  15.579065  1901.088864  0.207127  0.086860   \n",
      "1887  ST-3049   1914  0.567398  25.563741  3334.131505  0.297283  0.026123   \n",
      "1888  ST-3050   1171  0.574722  17.560205  2303.432878  0.225448  0.023057   \n",
      "1889  ST-3051   2463  0.705644  20.121803  2403.395510  0.208283  0.059683   \n",
      "1890  ST-3052   1431  0.738644  25.338225  2284.547358  0.157932  0.060098   \n",
      "1891  ST-3053   1174  0.694208  15.028961  1833.329693  0.175468  0.051959   \n",
      "1892  ST-3054   1516  0.751319  34.164248  2659.978885  0.281003  0.015172   \n",
      "1893  ST-3055    758  0.733509  16.638522  2082.517164  0.197889  0.067282   \n",
      "1894  ST-3056   1340  0.682836  24.385075  2898.420015  0.325373  0.092537   \n",
      "1895  ST-3057    690  0.728986  24.966667  2948.899899  0.182609  0.028986   \n",
      "1896  ST-3058    938  0.609808  21.662047  2787.800640  0.254797  0.051173   \n",
      "1897  ST-3059   1368  0.547515  19.499269  2045.991703  0.258772  0.059211   \n",
      "1898   ST-306   3438  0.674229  16.177720  1690.959186  0.238511  0.009308   \n",
      "1899  ST-3060   6687  0.630627  17.428742  2015.582641  0.272619  0.085390   \n",
      "1900  ST-3061   2105  0.784798  21.586698  2222.799150  0.163895  0.014252   \n",
      "1901  ST-3062   1817  0.637865  23.062190  2222.644816  0.266924  0.075399   \n",
      "1902  ST-3063   1384  0.667630  22.343931  2785.776575  0.197254  0.018064   \n",
      "1903  ST-3064    421  0.743468  22.760095  2674.082162  0.311164  0.078385   \n",
      "1904  ST-3065    235  0.685106  25.902128  3461.003404  0.336170  0.046809   \n",
      "1905  ST-3066    702  0.631054  39.091168  4785.064117  0.227920  0.081197   \n",
      "1906  ST-3067    611  0.888707  15.252046  2296.272455  0.147300  0.000000   \n",
      "1907  ST-3068   3025  0.696529  15.563636  1944.939964  0.186116  0.030413   \n",
      "1908  ST-3069    665  0.521805  23.212030  2672.577158  0.395489  0.024060   \n",
      "1909   ST-307   5564  0.731668  21.204170  2548.480602  0.216391  0.037383   \n",
      "1910  ST-3070   4715  0.625663  19.815695  2163.766210  0.265323  0.040085   \n",
      "1911  ST-3071   1358  0.590574  20.094993  2179.232901  0.255523  0.043446   \n",
      "1912  ST-3072   7194  0.672505  27.360161  3244.522848  0.205449  0.008757   \n",
      "1913  ST-3073   2895  0.703972  27.334715  3274.869979  0.168566  0.013817   \n",
      "1914  ST-3075   1733  0.687825  21.908252  2245.351506  0.170225  0.036930   \n",
      "1915  ST-3076    621  0.706924  14.299517  1593.512061  0.247987  0.033816   \n",
      "1916  ST-3077   2630  0.673004  29.680228  3468.374692  0.191635  0.033840   \n",
      "1917  ST-3078    833  0.591837  34.420168  4251.421248  0.260504  0.057623   \n",
      "1918  ST-3079   2067  0.670537  31.834543  4165.047775  0.184325  0.022738   \n",
      "1919   ST-308   2644  0.637670  23.056354  3004.063313  0.256808  0.086611   \n",
      "1920  ST-3080   1525  0.695082  19.981639  1972.917954  0.238033  0.042623   \n",
      "1921  ST-3081    892  0.656951  26.894619  2917.552881  0.289238  0.070628   \n",
      "1922  ST-3082   1519  0.624753  17.958525  2070.433219  0.276498  0.033575   \n",
      "1923  ST-3083   1241  0.642224  36.364222  4540.252006  0.427075  0.041096   \n",
      "1924  ST-3084   5313  0.648033  15.103708  1537.413934  0.223602  0.046490   \n",
      "1925  ST-3085   2673  0.641227  17.363262  1877.376180  0.267864  0.043023   \n",
      "1926  ST-3086   2913  0.596292  34.209406  4385.633292  0.350154  0.041538   \n",
      "1927  ST-3087   2144  0.625000  20.039179  2231.319585  0.224813  0.037313   \n",
      "1928  ST-3088    429  0.671329  17.048951  1969.088368  0.153846  0.053613   \n",
      "1929  ST-3089   3007  0.632192  19.152644  2404.723469  0.255737  0.038577   \n",
      "1930   ST-309   4000  0.642250  20.062000  1991.606027  0.243250  0.055000   \n",
      "1931  ST-3090   2024  0.719368  19.767292  1866.682258  0.158103  0.008893   \n",
      "1932  ST-3091    629  0.643879  18.852146  2047.649682  0.224165  0.063593   \n",
      "1933  ST-3092   2812  0.596728  29.428876  3652.562735  0.290541  0.097084   \n",
      "1934  ST-3093    535  0.762617  27.783178  3841.510991  0.358879  0.024299   \n",
      "1935  ST-3094   8844  0.586047  15.802578  1637.426364  0.238128  0.016621   \n",
      "1936  ST-3095   3549  0.649760  25.848972  3274.229794  0.278670  0.071006   \n",
      "1937  ST-3096    584  0.613014  31.484589  3887.827295  0.234589  0.113014   \n",
      "1938  ST-3097    379  0.686016  19.881266  2446.772612  0.261214  0.073879   \n",
      "1939  ST-3098   2661  0.602405  36.738068  4611.645971  0.374295  0.030440   \n",
      "1940  ST-3099   2792  0.564828  19.458095  2170.043023  0.207020  0.066977   \n",
      "1941    ST-31   1660  0.698193  23.263855  2479.865880  0.256024  0.049398   \n",
      "1942   ST-310   3972  0.565458  15.145519  1705.963847  0.259315  0.030211   \n",
      "1943  ST-3100   2729  0.604984  17.556614  1805.942833  0.192012  0.042873   \n",
      "1944  ST-3101   1305  0.652107  21.514176  3081.650797  0.271264  0.038314   \n",
      "1945  ST-3102   2047  0.708354  17.885686  2237.093351  0.267220  0.081094   \n",
      "1946  ST-3103    425  0.625882  20.070588  2383.237624  0.207059  0.091765   \n",
      "1947  ST-3104   9028  0.623505  16.039211  1666.702926  0.244351  0.052171   \n",
      "1948  ST-3105   8041  0.589976  27.184554  3139.213789  0.279940  0.042035   \n",
      "1949  ST-3106    444  0.704955  28.939189  3679.187432  0.281532  0.159910   \n",
      "1950  ST-3107    511  0.729941  19.000000  2290.304149  0.264188  0.050881   \n",
      "1951  ST-3108    424  0.688679  26.254717  2683.176108  0.231132  0.082547   \n",
      "1952  ST-3109    771  0.701686  17.813230  2024.687938  0.195850  0.041505   \n",
      "1953   ST-311   5623  0.666192  16.178730  1637.670802  0.254846  0.021519   \n",
      "1954  ST-3110   1349  0.662713  16.991846  1736.984077  0.194959  0.046701   \n",
      "1955  ST-3111    808  0.693069  29.248762  3153.001757  0.221535  0.080446   \n",
      "1956  ST-3112   1756  0.705581  30.208428  3431.165569  0.223235  0.027335   \n",
      "1957  ST-3113   2328  0.503866  26.082045  3336.415378  0.275344  0.051546   \n",
      "1958  ST-3114   1206  0.502488  24.244610  3615.549569  0.255390  0.016584   \n",
      "1959  ST-3115    524  0.774809  23.328244  2732.603588  0.139313  0.041985   \n",
      "1960  ST-3116   3991  0.518166  22.068905  1986.874375  0.267853  0.052618   \n",
      "1961  ST-3117   1902  0.592534  22.770242  2231.810605  0.276025  0.011041   \n",
      "1962  ST-3118   1441  0.689105  23.749480  3196.247745  0.122831  0.013185   \n",
      "1963  ST-3119   2418  0.613730  20.915219  2242.936844  0.250620  0.049628   \n",
      "1964   ST-312   5295  0.546742  17.664400  1608.725890  0.227195  0.033428   \n",
      "1965  ST-3120   1977  0.561963  17.745068  2176.001912  0.163379  0.038442   \n",
      "1966  ST-3121   1619  0.592959  21.618283  2302.856597  0.242742  0.043854   \n",
      "1967  ST-3122   1690  0.737870  19.402959  2175.260953  0.248521  0.092308   \n",
      "1968  ST-3123   1405  0.756584  18.933096  1781.174093  0.279715  0.030605   \n",
      "1969  ST-3124   1963  0.671931  18.372389  2121.854249  0.064187  0.010188   \n",
      "1970  ST-3125   2334  0.614396  20.827335  2288.611632  0.259640  0.056984   \n",
      "1971  ST-3126   1047  0.756447  14.170965  1606.024365  0.288443  0.064947   \n",
      "1972  ST-3127    694  0.729107  18.416427  2596.584568  0.243516  0.020173   \n",
      "1973  ST-3128   3169  0.615021  11.622909  1332.437050  0.054276  0.002524   \n",
      "1974  ST-3129   3799  0.692287  18.395630  2385.033804  0.248223  0.028165   \n",
      "1975   ST-313   1948  0.727413  15.355236  1815.806355  0.226899  0.050308   \n",
      "1976  ST-3130   2195  0.649658  16.135763  1881.974241  0.215034  0.032346   \n",
      "1977  ST-3131   1761  0.579784  19.223169  2278.641925  0.245315  0.023850   \n",
      "1978  ST-3133    709  0.648801  19.255289  2222.352779  0.286319  0.086037   \n",
      "1979  ST-3134    565  0.688496  16.819469  2497.833027  0.269027  0.037168   \n",
      "1980  ST-3135   1328  0.658133  21.670934  2209.428652  0.276355  0.044428   \n",
      "1981  ST-3136   2058  0.656948  22.863460  2686.279140  0.171040  0.029155   \n",
      "1982  ST-3137   1367  0.622531  15.092173  2039.206598  0.115582  0.024872   \n",
      "1983  ST-3138    896  0.695312  19.822545  2294.375335  0.244420  0.040179   \n",
      "1984  ST-3139   2193  0.442772  22.493844  3021.594181  0.219790  0.013224   \n",
      "1985  ST-3140   1523  0.592252  25.806960  2634.018155  0.267892  0.058437   \n",
      "1986  ST-3141   1781  0.559798  19.684447  1876.424413  0.263335  0.039304   \n",
      "1987  ST-3142   8491  0.674243  20.457661  2478.843202  0.271935  0.056766   \n",
      "1988  ST-3143   1101  0.722071  25.585831  3167.469537  0.250681  0.057221   \n",
      "1989  ST-3144    494  0.763158  22.340081  2366.412692  0.222672  0.036437   \n",
      "1990  ST-3145   2605  0.625720  12.479846  1464.254119  0.127831  0.018810   \n",
      "1991  ST-3146   1463  0.628845  20.516063  2696.735537  0.239234  0.151059   \n",
      "1992  ST-3147   1582  0.733881  18.140329  2113.596593  0.301517  0.069532   \n",
      "1993  ST-3148   1645  0.590274  21.141033  2169.320316  0.250456  0.040729   \n",
      "1994  ST-3149   1487  0.724950  18.600538  1982.004311  0.228648  0.028245   \n",
      "1995   ST-315   7578  0.614806  16.318158  1548.708775  0.231987  0.015835   \n",
      "1996  ST-3150    401  0.593516  18.645885  2100.092918  0.234414  0.024938   \n",
      "1997  ST-3151   1131  0.549072  19.883289  2262.211733  0.282051  0.007958   \n",
      "1998  ST-3152   1173  0.590793  22.949702  2703.848338  0.252344  0.052003   \n",
      "1999  ST-3153   1846  0.567714  19.968039  2466.702324  0.260563  0.099675   \n",
      "2000  ST-3154    288  0.736111  21.187500  2313.641562  0.361111  0.072917   \n",
      "2001  ST-3155    771  0.805447  21.826200  2653.195746  0.306096  0.077821   \n",
      "2002  ST-3156    179  0.748603  16.882682  1902.766034  0.061453  0.000000   \n",
      "2003  ST-3157     42  0.642857  15.619048  2550.333810  0.142857  0.000000   \n",
      "2004  ST-3158    298  0.614094  18.530201  2600.417987  0.281879  0.033557   \n",
      "2005  ST-3159    799  0.733417  23.254068  2394.514280  0.219024  0.045056   \n",
      "2006   ST-316   1361  0.751653  13.535636  1641.712506  0.260103  0.059515   \n",
      "2007  ST-3160   2770  0.645848  30.689892  3705.476700  0.318773  0.024549   \n",
      "2008  ST-3161    443  0.735892  24.934537  2177.976998  0.209932  0.024831   \n",
      "2009  ST-3162   1959  0.541603  19.598775  2005.861685  0.244002  0.063298   \n",
      "2010  ST-3163   5433  0.676606  18.183508  2023.774152  0.251979  0.029450   \n",
      "2011  ST-3164    423  0.647754  29.846336  4214.900284  0.215130  0.044917   \n",
      "2012  ST-3165   1398  0.670959  17.708870  1916.775644  0.234621  0.047210   \n",
      "2013  ST-3166    782  0.700767  20.787724  2275.930128  0.285166  0.106138   \n",
      "2014  ST-3167   2098  0.636320  18.338894  1818.549185  0.265014  0.058627   \n",
      "2015  ST-3168   2648  0.698263  27.758686  3601.588191  0.352719  0.071752   \n",
      "2016  ST-3169   1302  0.665899  16.609063  2285.369363  0.275730  0.073733   \n",
      "2017   ST-317   1197  0.710109  17.290727  2216.047602  0.182122  0.043442   \n",
      "2018  ST-3170   1165  0.714163  20.638627  2253.507863  0.257511  0.038627   \n",
      "2019  ST-3171   2117  0.737837  20.283420  2057.309556  0.269721  0.078885   \n",
      "2020  ST-3172   1953  0.651306  17.461342  2112.706446  0.230415  0.067076   \n",
      "2021  ST-3173    562  0.692171  24.711744  2473.558559  0.270463  0.065836   \n",
      "2022  ST-3174   2154  0.606314  15.572888  1703.043055  0.194986  0.023677   \n",
      "2023  ST-3175   1963  0.539480  23.263882  3005.224824  0.306673  0.045848   \n",
      "2024  ST-3177   1942  0.660659  22.129248  2961.569238  0.193100  0.031411   \n",
      "2025  ST-3178    425  0.651765  26.484706  3116.251882  0.315294  0.025882   \n",
      "2026  ST-3179   1086  0.649171  19.481584  2440.955138  0.231123  0.063536   \n",
      "2027   ST-318   2440  0.659836  13.765984  1785.969922  0.245902  0.024180   \n",
      "2028  ST-3180    228  0.824561  17.828947  2302.454211  0.184211  0.026316   \n",
      "2029  ST-3181    111  0.594595  16.198198  2415.843694  0.261261  0.072072   \n",
      "2030  ST-3182   2263  0.683164  21.931065  2648.050486  0.171896  0.023420   \n",
      "2031  ST-3183    237  0.586498  19.008439  2167.327975  0.299578  0.156118   \n",
      "2032  ST-3184    623  0.712681  23.492777  2468.138604  0.248796  0.077047   \n",
      "2033  ST-3185   1335  0.653933  18.955805  2071.614801  0.213483  0.032959   \n",
      "2034  ST-3186   2595  0.618882  24.571484  2806.230686  0.241233  0.099037   \n",
      "2035  ST-3187   6556  0.642007  16.324893  1738.662323  0.252135  0.030049   \n",
      "2036  ST-3188   4189  0.598950  17.293626  1714.046262  0.239437  0.036286   \n",
      "2037  ST-3189   1150  0.735652  13.424348  1513.323626  0.191304  0.026087   \n",
      "2038   ST-319   1230  0.675610  17.607317  2219.532545  0.181301  0.071545   \n",
      "2039  ST-3192    357  0.641457  26.042017  3936.089384  0.210084  0.042017   \n",
      "2040  ST-3193    653  0.626340  30.381317  2421.235804  0.292496  0.041348   \n",
      "2041  ST-3194   2115  0.666667  17.167376  2102.039381  0.216548  0.062411   \n",
      "2042  ST-3195   2016  0.639385  22.791171  2793.198204  0.300595  0.017361   \n",
      "2043  ST-3196   1233  0.662612  14.595296  1599.991111  0.240065  0.047040   \n",
      "2044  ST-3197    527  0.502846  15.827324  2065.324820  0.269450  0.039848   \n",
      "2045  ST-3198   1285  0.645136  23.306615  2322.768825  0.278599  0.019455   \n",
      "2046  ST-3199   1234  0.710697  24.534846  2885.842002  0.299838  0.129660   \n",
      "2047    ST-32   3474  0.632700  21.649971  2442.094963  0.270294  0.045481   \n",
      "2048   ST-320   1675  0.576716  21.472239  2272.027994  0.203582  0.059104   \n",
      "2049  ST-3200   1358  0.735641  22.798969  2347.333306  0.232695  0.033137   \n",
      "2050  ST-3201    282  0.723404  10.627660  1745.910922  0.308511  0.124113   \n",
      "2051  ST-3202   1113  0.714286  16.357592  1784.676640  0.135669  0.023360   \n",
      "2052  ST-3203   1703  0.628303  22.688197  2540.969178  0.319436  0.026424   \n",
      "2053  ST-3204   3724  0.634801  17.891515  2120.487401  0.242481  0.044039   \n",
      "2054  ST-3205    569  0.534271  36.500879  3481.462812  0.397188  0.008787   \n",
      "2055  ST-3206    707  0.690240  22.899576  2318.269958  0.229137  0.110325   \n",
      "2056  ST-3207   1303  0.634689  23.133538  2363.040806  0.302379  0.026861   \n",
      "2057  ST-3208    552  0.623188  24.007246  2491.618152  0.244565  0.052536   \n",
      "2058  ST-3209   1356  0.679204  16.286873  1604.113695  0.281711  0.058260   \n",
      "2059   ST-321   2047  0.631656  15.842697  1962.682447  0.214460  0.036639   \n",
      "2060  ST-3210   2228  0.674596  21.806104  1879.980426  0.259874  0.046230   \n",
      "2061  ST-3211   1285  0.602335  18.639689  2744.566506  0.235019  0.075486   \n",
      "2062  ST-3212   4658  0.590382  17.962430  1650.501949  0.275440  0.043796   \n",
      "2063  ST-3213    453  0.637969  18.940397  2435.888102  0.278146  0.048565   \n",
      "2064  ST-3214   9102  0.600088  20.874094  2167.002390  0.275544  0.068996   \n",
      "2065  ST-3215   1536  0.705729  20.446615  2230.330671  0.231771  0.048828   \n",
      "2066  ST-3216     80  0.625000  30.337500  4085.455375  0.400000  0.012500   \n",
      "2067  ST-3218    884  0.645928  20.684389  2431.359152  0.280543  0.030543   \n",
      "2068  ST-3219   2810  0.694306  11.440925  1436.625470  0.210676  0.052669   \n",
      "2069   ST-322   1999  0.626313  22.514257  2707.119220  0.251126  0.072536   \n",
      "2070  ST-3220    282  0.528369  13.411348  2036.358191  0.237589  0.049645   \n",
      "2071  ST-3221   1022  0.536204  24.564579  2856.199335  0.240705  0.018591   \n",
      "2072  ST-3222    341  0.782991  19.354839  2490.006628  0.263930  0.052786   \n",
      "2073  ST-3223   1925  0.667532  13.600000  1483.723922  0.171948  0.019740   \n",
      "2074  ST-3224   1420  0.725352  15.723944  1911.433585  0.244366  0.054930   \n",
      "2075  ST-3225   4110  0.881752  10.154745  1367.625363  0.225061  0.002433   \n",
      "2076  ST-3226   4790  0.510021  16.731733  1701.199889  0.299374  0.035073   \n",
      "2077  ST-3227    686  0.816327  18.523324  2156.638032  0.278426  0.016035   \n",
      "2078  ST-3228    627  0.614035  17.208931  1863.009410  0.202552  0.014354   \n",
      "2079  ST-3230   2549  0.590035  19.790114  2244.370302  0.208709  0.051000   \n",
      "2080  ST-3232    383  0.639687  24.232376  3132.290757  0.250653  0.049608   \n",
      "2081  ST-3233   1168  0.678938  23.767123  3250.890180  0.267123  0.035103   \n",
      "2082  ST-3234    945  0.813757  24.583069  2834.934952  0.277249  0.120635   \n",
      "2083  ST-3235   4094  0.601124  16.380801  1781.202667  0.182462  0.020762   \n",
      "2084  ST-3236   1158  0.833333  13.870466  1550.786822  0.185665  0.025907   \n",
      "2085  ST-3237    627  0.663477  13.456140  1618.460877  0.245614  0.148325   \n",
      "2086  ST-3238   2789  0.745428  24.067766  2289.139387  0.283256  0.101829   \n",
      "2087  ST-3239   4868  0.687962  37.858463  4580.763164  0.276294  0.015407   \n",
      "2088   ST-324    762  0.635171  21.011811  2423.675446  0.263780  0.038058   \n",
      "2089  ST-3240   1242  0.536232  28.657810  3255.757464  0.258454  0.015298   \n",
      "2090  ST-3241   1442  0.675451  18.099168  1721.208218  0.194175  0.065881   \n",
      "2091  ST-3242   1018  0.564833  18.581532  1987.718153  0.209234  0.052063   \n",
      "2092  ST-3243    484  0.609504  26.216942  3548.227665  0.237603  0.064050   \n",
      "2093  ST-3244   1128  0.654255  19.451241  2501.656215  0.258865  0.022163   \n",
      "2094  ST-3245    495  0.632323  15.107071  1813.111232  0.280808  0.046465   \n",
      "2095  ST-3247    952  0.735294  19.456933  2144.399496  0.260504  0.107143   \n",
      "2096  ST-3248   2767  0.608963  18.311529  2063.890726  0.236718  0.038670   \n",
      "2097  ST-3249   1226  0.557912  38.988581  4327.550604  0.400489  0.047308   \n",
      "2098   ST-325    170  0.747059  33.805882  4927.292294  0.258824  0.041176   \n",
      "2099  ST-3250    810  0.698765  16.029630  1769.042716  0.285185  0.053086   \n",
      "2100  ST-3251   4383  0.651837  11.229751  1335.507495  0.022359  0.002282   \n",
      "2101  ST-3252   1552  0.664948  21.142397  2158.034259  0.208763  0.034794   \n",
      "2102  ST-3253   2229  0.650516  19.909376  2465.423306  0.302826  0.052939   \n",
      "2103  ST-3254    527  0.592030  28.091082  4111.941689  0.248577  0.161290   \n",
      "2104  ST-3255    679  0.733432  18.447717  1873.923358  0.157585  0.010309   \n",
      "2105  ST-3256   2042  0.641038  17.841822  1880.617889  0.262488  0.064643   \n",
      "2106  ST-3257     31  0.870968  27.129032  4270.973871  0.225806  0.193548   \n",
      "2107  ST-3258   2877  0.671185  22.741050  2643.913601  0.265554  0.055266   \n",
      "2108  ST-3259   1071  0.749767  13.687208  1652.242185  0.065359  0.007470   \n",
      "2109   ST-326   2121  0.610090  16.133899  1812.223206  0.253182  0.070721   \n",
      "2110  ST-3260   1512  0.794312  13.401455  1573.720456  0.068122  0.010582   \n",
      "2111  ST-3261    918  0.714597  12.462963  1286.234129  0.053377  0.015251   \n",
      "2112  ST-3262   1574  0.645489  15.524142  1776.094994  0.301779  0.024142   \n",
      "2113  ST-3263    425  0.997647  22.567059  2393.761365  0.117647  0.014118   \n",
      "2114  ST-3264   1430  0.687413  25.115385  3050.873147  0.320280  0.073427   \n",
      "2115  ST-3265   1267  0.505919  25.556433  3238.524333  0.149961  0.023678   \n",
      "2116  ST-3266    396  0.623737  19.664141  1912.094646  0.244949  0.113636   \n",
      "2117  ST-3267    830  0.604819  22.280723  2310.881807  0.244578  0.051807   \n",
      "2118  ST-3268    192  0.588542  20.151042  2398.609635  0.234375  0.020833   \n",
      "2119  ST-3269    310  0.732258  20.338710  1829.421645  0.222581  0.054839   \n",
      "2120   ST-327   1655  0.756495  19.473716  2401.043837  0.221148  0.025982   \n",
      "2121  ST-3270     95  0.578947  25.442105  3206.162737  0.168421  0.021053   \n",
      "2122  ST-3271    102  0.764706  15.490196  1771.618431  0.205882  0.078431   \n",
      "2123  ST-3272    578  0.660900  30.636678  2602.452111  0.231834  0.029412   \n",
      "2124  ST-3273    157  0.624204  14.662420  1928.733185  0.356688  0.063694   \n",
      "2125  ST-3274    191  0.659686  20.816754  2155.035236  0.256545  0.015707   \n",
      "2126  ST-3275     24  0.875000   9.833333  1455.043333  0.208333  0.000000   \n",
      "2127  ST-3276    350  0.717143  16.514286  1684.219629  0.228571  0.094286   \n",
      "2128  ST-3277     28  0.571429  11.607143  1629.912857  0.107143  0.000000   \n",
      "2129  ST-3278     40  0.750000  15.875000  1949.003500  0.125000  0.025000   \n",
      "2130  ST-3279     74  0.824324  24.270270  2283.095541  0.283784  0.108108   \n",
      "2131   ST-328   2044  0.723581  25.282779  2664.137696  0.213796  0.037182   \n",
      "2132  ST-3280     23  0.391304  13.695652  1265.184783  0.173913  0.043478   \n",
      "2133  ST-3281      4  0.500000  64.750000  3386.245000  0.250000  0.250000   \n",
      "2134   ST-329    746  0.589812  25.615282  2871.778351  0.388740  0.034853   \n",
      "2135    ST-33   3494  0.603320  27.920721  3779.729098  0.292501  0.057813   \n",
      "2136   ST-330   1301  0.614912  41.654112  5594.678663  0.249039  0.066872   \n",
      "2137   ST-331   1103  0.670898  24.184044  3220.551777  0.292838  0.087035   \n",
      "2138   ST-332    795  0.637736  16.821384  2203.143849  0.215094  0.030189   \n",
      "2139   ST-333    337  0.658754  18.629080  2158.387774  0.320475  0.091988   \n",
      "2140   ST-334   1546  0.663648  19.919793  2387.847995  0.250323  0.055627   \n",
      "2141   ST-335   2382  0.648615  25.605793  3382.870911  0.295130  0.087322   \n",
      "2142   ST-336   2834  0.645025  21.638673  2285.095113  0.189132  0.021171   \n",
      "2143   ST-338   2459  0.727125  23.311915  2402.869573  0.206181  0.040260   \n",
      "2144   ST-339   1905  0.438845  41.137533  5342.510772  0.396850  0.023622   \n",
      "2145   ST-340   1816  0.523128  37.412996  4509.266498  0.388216  0.045154   \n",
      "2146   ST-341   4094  0.463605  18.616023  2072.193930  0.250122  0.045677   \n",
      "2147   ST-342   4555  0.528869  22.959385  2398.165458  0.271131  0.062349   \n",
      "2148   ST-343   1599  0.642902  29.646654  4169.083852  0.322076  0.060663   \n",
      "2149   ST-344   3872  0.550362  47.498709  4074.827771  0.537965  0.010589   \n",
      "2150   ST-345   1353  0.587583  17.790835  2181.202683  0.243902  0.045824   \n",
      "2151   ST-346   1445  0.626298  24.353633  3634.006152  0.252595  0.058824   \n",
      "2152   ST-347   2018  0.625867  19.349851  2193.590426  0.255203  0.052032   \n",
      "2153   ST-348   1058  0.602079  17.662571  2603.914291  0.231569  0.031191   \n",
      "2154   ST-349   2463  0.515631  20.557856  2774.915644  0.276086  0.058059   \n",
      "2155    ST-35   3610  0.522992  29.254294  3648.323510  0.296953  0.053463   \n",
      "2156   ST-350   3119  0.600192  26.487015  3608.031157  0.280218  0.051619   \n",
      "2157   ST-351   1300  0.516154  20.489231  2272.094738  0.275385  0.060000   \n",
      "2158   ST-352    721  0.592233  19.320388  2089.320791  0.242718  0.054092   \n",
      "2159   ST-354   1261  0.568596  20.821570  2605.730119  0.217288  0.084853   \n",
      "2160   ST-357    161  0.596273  32.596273  4911.670248  0.397516  0.037267   \n",
      "2161   ST-358   3102  0.623469  18.094778  2047.246493  0.223082  0.055448   \n",
      "2162   ST-359   2961  0.643364  22.377237  2604.639895  0.226613  0.066532   \n",
      "2163    ST-36   1443  0.645877  26.095634  2440.560485  0.285516  0.065142   \n",
      "2164   ST-360   3903  0.662567  22.611581  2545.736395  0.275429  0.032027   \n",
      "2165   ST-361   4598  0.578947  19.769465  2102.868723  0.251196  0.045455   \n",
      "2166   ST-362   3349  0.538071  24.872201  2511.962831  0.219468  0.017020   \n",
      "2167   ST-363   2411  0.562007  18.119038  2040.421626  0.242638  0.052675   \n",
      "2168   ST-364   3073  0.630979  20.895216  2129.628467  0.125936  0.027009   \n",
      "2169   ST-365    343  0.702624  23.889213  2978.494431  0.291545  0.241983   \n",
      "2170   ST-366   6850  0.586715  44.089051  6606.470466  0.316204  0.033869   \n",
      "2171   ST-368   7250  0.598759  17.917103  1930.069859  0.179586  0.017931   \n",
      "2172   ST-369   4645  0.565554  17.969860  2301.899897  0.279440  0.046502   \n",
      "2173    ST-37   1107  0.628726  20.941283  2295.509169  0.242096  0.048780   \n",
      "2174   ST-370    495  0.755556  19.795960  2761.046889  0.307071  0.119192   \n",
      "2175   ST-371   3065  0.561175  18.549755  2287.273511  0.155954  0.034258   \n",
      "2176   ST-372   1873  0.657234  22.114255  2443.289007  0.231180  0.069941   \n",
      "2177   ST-375   3866  0.597258  27.421624  2151.116048  0.191930  0.021211   \n",
      "2178   ST-376   8830  0.579502  41.116082  6335.085955  0.340657  0.040883   \n",
      "2179   ST-377   4860  0.610288  16.672634  1897.228160  0.264815  0.056584   \n",
      "2180   ST-378   1779  0.608207  23.789207  2647.686976  0.320967  0.051152   \n",
      "2181   ST-379   1937  0.559112  27.796593  3978.680367  0.252969  0.110480   \n",
      "2182   ST-381    893  0.647256  26.562150  2269.225039  0.240761  0.050392   \n",
      "2183   ST-382   2708  0.584564  17.632570  1705.073840  0.175037  0.022526   \n",
      "2184   ST-384   3512  0.574886  14.775911  1831.171350  0.250285  0.036731   \n",
      "2185   ST-385   5207  0.602842  21.710966  2646.756069  0.275783  0.048012   \n",
      "2186   ST-386   1148  0.703833  23.905052  2322.637517  0.233449  0.040941   \n",
      "2187   ST-387   3506  0.658871  23.311466  2638.544578  0.290930  0.081004   \n",
      "2188   ST-388   3090  0.563754  26.447573  3511.572974  0.308091  0.079935   \n",
      "2189   ST-389   1048  0.735687  19.761450  2165.967672  0.279580  0.034351   \n",
      "2190    ST-39    963  0.623053  20.205607  2286.544611  0.242991  0.111111   \n",
      "2191   ST-390   2775  0.732973  22.206486  2460.978883  0.287207  0.047928   \n",
      "2192   ST-391   3520  0.718182  19.585795  1970.306861  0.253125  0.053409   \n",
      "2193   ST-392   3173  0.656792  18.601009  1941.041859  0.236369  0.042231   \n",
      "2194   ST-394   3132  0.610792  27.075990  3664.254700  0.236909  0.047573   \n",
      "2195   ST-395   2732  0.698023  22.166545  2743.405461  0.275988  0.092606   \n",
      "2196   ST-396   1713  0.737303  18.176299  2122.903030  0.223001  0.038529   \n",
      "2197   ST-397   4645  0.670398  21.639182  2114.353938  0.189236  0.032508   \n",
      "2198   ST-398   6994  0.643266  19.254647  2108.258250  0.206034  0.046325   \n",
      "2199     ST-4   5904  0.517446  26.042514  2380.577266  0.292005  0.058096   \n",
      "2200    ST-40   1127  0.700976  19.034605  2043.074082  0.254658  0.104703   \n",
      "2201   ST-400   6073  0.681871  23.520830  2659.861457  0.270377  0.058620   \n",
      "2202   ST-401   5213  0.698254  24.775945  2631.206046  0.236716  0.072703   \n",
      "2203   ST-402   3363  0.631876  20.804639  2476.744362  0.238180  0.064823   \n",
      "2204   ST-403   1041  0.640730  18.951009  2073.484121  0.179635  0.048991   \n",
      "2205   ST-404   2192  0.630931  19.772354  2485.629238  0.202555  0.060675   \n",
      "2206   ST-405   1118  0.827370  23.149374  2332.425590  0.189624  0.031306   \n",
      "2207   ST-406   1068  0.788390  15.492509  1526.348436  0.272472  0.039326   \n",
      "2208   ST-407   2131  0.710934  22.754575  2517.024355  0.245894  0.033318   \n",
      "2209   ST-408   4561  0.605350  24.086823  2855.011572  0.262004  0.030695   \n",
      "2210   ST-409   3041  0.606379  17.489642  2011.318829  0.242683  0.033870   \n",
      "2211    ST-41   1440  0.677083  19.097222  2303.613118  0.178472  0.021528   \n",
      "2212   ST-410   3660  0.602459  28.612022  3492.980484  0.251093  0.027596   \n",
      "2213   ST-413  13154  0.651665  17.996655  1527.269682  0.229360  0.040140   \n",
      "2214   ST-414   1343  0.702159  32.712584  4410.598012  0.280715  0.020849   \n",
      "2215   ST-416   8042  0.621487  17.555334  1823.236098  0.236260  0.023377   \n",
      "2216   ST-417   7054  0.682450  17.795577  1913.834874  0.201446  0.036859   \n",
      "2217   ST-418   2459  0.707605  18.480683  1752.811387  0.228142  0.056527   \n",
      "2218   ST-419   3147  0.638386  19.398157  1707.544973  0.212901  0.040356   \n",
      "2219    ST-42   1018  0.773084  19.325147  2148.880196  0.189587  0.042240   \n",
      "2220   ST-420   2807  0.636266  19.603491  1863.115383  0.244389  0.076594   \n",
      "2221   ST-421   4072  0.676817  26.172642  3075.217785  0.229617  0.060904   \n",
      "2222   ST-422   4538  0.661084  19.151829  1997.009132  0.260467  0.052446   \n",
      "2223   ST-424   2673  0.740367  27.894501  2727.897097  0.135428  0.017583   \n",
      "2224   ST-425    952  0.684874  29.853992  3388.575483  0.288866  0.025210   \n",
      "2225   ST-426   9478  0.603186  38.217029  5398.601802  0.326862  0.020574   \n",
      "2226   ST-428   2896  0.622583  16.537638  1750.637465  0.234116  0.018301   \n",
      "2227    ST-43    592  0.697635  22.699324  2425.409172  0.217905  0.099662   \n",
      "2228   ST-431   3267  0.624732  15.065810  1560.096997  0.242424  0.067952   \n",
      "2229   ST-432   1562  0.654289  18.704866  2000.309366  0.248399  0.049936   \n",
      "2230   ST-435   2940  0.619388  21.599320  2736.693058  0.245918  0.028571   \n",
      "2231   ST-436   1683  0.565657  16.810458  2229.935342  0.256090  0.042781   \n",
      "2232   ST-437   2674  0.553104  19.451758  2181.725108  0.237098  0.065071   \n",
      "2233   ST-438   3155  0.639620  17.831696  2050.384935  0.250079  0.030428   \n",
      "2234   ST-439   1574  0.713469  21.428208  2303.975216  0.227446  0.076239   \n",
      "2235   ST-440    793  0.678436  18.527112  2084.840769  0.262295  0.032787   \n",
      "2236   ST-441    522  0.699234  22.848659  2426.133314  0.252874  0.024904   \n",
      "2237   ST-442   4155  0.587244  41.873887  6014.923483  0.404813  0.029844   \n",
      "2238   ST-443   1991  0.553993  27.014566  2708.933677  0.306881  0.029633   \n",
      "2239   ST-444    937  0.606190  15.922092  1912.937951  0.274280  0.091782   \n",
      "2240   ST-445   6355  0.577183  16.829111  1677.811149  0.221873  0.056176   \n",
      "2241   ST-446   8504  0.590663  24.729539  2889.856482  0.244473  0.049036   \n",
      "2242   ST-447   1499  0.672448  19.159440  2300.048492  0.260841  0.052702   \n",
      "2243   ST-448   1472  0.641984  21.887908  2019.469171  0.194973  0.016304   \n",
      "2244    ST-45    368  0.880435  19.684783  2061.901250  0.048913  0.008152   \n",
      "2245   ST-450    985  0.669036  12.231472  1306.398234  0.250761  0.059898   \n",
      "2246   ST-451   1465  0.679181  15.525597  1658.844758  0.306485  0.038225   \n",
      "2247   ST-452   1464  0.629781  17.315574  2098.910908  0.327869  0.069672   \n",
      "2248   ST-453   4529  0.715611  19.527710  2075.438152  0.280857  0.037757   \n",
      "2249   ST-454   5179  0.596254  21.369376  2587.765547  0.279011  0.087855   \n",
      "2250   ST-455   6676  0.541342  26.584931  3395.852382  0.296585  0.042840   \n",
      "2251   ST-456   2597  0.645745  20.648441  2317.996873  0.284174  0.081633   \n",
      "2252   ST-457   1063  0.707432  18.611477  2521.558993  0.222013  0.048918   \n",
      "2253   ST-459   3717  0.608555  20.063223  2203.401679  0.267689  0.056497   \n",
      "2254    ST-46   2732  0.625183  31.620791  3221.978902  0.218155  0.019766   \n",
      "2255   ST-460   4018  0.656546  21.703833  2654.264550  0.266551  0.081135   \n",
      "2256   ST-461   4282  0.510509  18.130079  1984.592123  0.269967  0.009108   \n",
      "2257   ST-462   4538  0.592772  28.295505  3874.119625  0.291538  0.052226   \n",
      "2258   ST-463   2770  0.607220  27.644765  3345.005671  0.253069  0.045487   \n",
      "2259   ST-464   2513  0.615599  18.319538  1974.255714  0.262236  0.098687   \n",
      "2260   ST-465   2485  0.650704  16.624950  1904.866736  0.207243  0.036620   \n",
      "2261   ST-467   1419  0.598309  22.128964  2264.904397  0.241720  0.076110   \n",
      "2262   ST-469    316  0.626582  16.889241  1856.391361  0.180380  0.025316   \n",
      "2263    ST-47   6653  0.684203  29.609349  3259.155346  0.204419  0.010371   \n",
      "2264   ST-470   1152  0.683160  23.428819  2133.638628  0.242188  0.078125   \n",
      "2265   ST-471   1212  0.672442  18.748350  2114.231081  0.281353  0.075083   \n",
      "2266   ST-472    256  0.636719  18.871094  2362.797969  0.265625  0.023438   \n",
      "2267   ST-473   1334  0.613193  22.847826  2150.253051  0.230135  0.082459   \n",
      "2268   ST-475   1070  0.638318  21.808411  2159.799458  0.262617  0.076636   \n",
      "2269   ST-476    509  0.542240  27.555992  2895.115815  0.392927  0.009823   \n",
      "2270   ST-478   1589  0.617999  19.586532  2334.569924  0.239773  0.057898   \n",
      "2271   ST-479   5670  0.576720  19.890829  2370.861219  0.264374  0.052734   \n",
      "2272   ST-480   2141  0.552546  22.557683  2650.374475  0.269500  0.043438   \n",
      "2273   ST-481   3703  0.559006  23.094788  2579.794456  0.269781  0.055901   \n",
      "2274   ST-482   3251  0.601046  25.028299  2434.345198  0.210704  0.028607   \n",
      "2275   ST-483   3938  0.552311  28.386998  3121.995653  0.291265  0.050279   \n",
      "2276   ST-485   2716  0.557806  20.339838  2392.774297  0.276141  0.073270   \n",
      "2277   ST-486   3690  0.623848  21.502981  2506.648504  0.310569  0.075881   \n",
      "2278   ST-487   1879  0.588079  21.100585  1994.927036  0.291112  0.052155   \n",
      "2279   ST-488   2697  0.588802  25.542084  2895.688528  0.285873  0.054876   \n",
      "2280   ST-490    258  0.627907  19.631783  2189.763876  0.224806  0.034884   \n",
      "2281   ST-491    303  0.801980  34.854785  2647.463102  0.409241  0.006601   \n",
      "2282   ST-492   6381  0.632659  24.269080  2745.799618  0.271117  0.061903   \n",
      "2283   ST-493   8740  0.545538  22.386499  2106.039049  0.280778  0.033524   \n",
      "2284   ST-494   5223  0.605591  17.782500  1911.701388  0.233582  0.109133   \n",
      "2285   ST-495   5644  0.595854  19.533664  2035.246417  0.250000  0.068923   \n",
      "2286   ST-496   2603  0.512486  20.281598  1958.885682  0.255474  0.059931   \n",
      "2287   ST-497   4446  0.598740  17.406208  1435.296565  0.205803  0.027890   \n",
      "2288   ST-499   1429  0.735479  21.334500  2314.701372  0.279916  0.074178   \n",
      "2289     ST-5   4851  0.555349  27.725624  2770.878883  0.310864  0.062461   \n",
      "2290    ST-50   2076  0.692197  22.615125  2225.882018  0.151734  0.017823   \n",
      "2291   ST-500   1236  0.601942  19.991909  2073.572273  0.256472  0.100324   \n",
      "2292   ST-501   3054  0.623772  20.511788  2180.981274  0.284217  0.054355   \n",
      "2293   ST-502   7367  0.606896  16.784037  1692.813786  0.247862  0.051853   \n",
      "2294   ST-503   6451  0.570764  17.849326  1748.437300  0.198264  0.017982   \n",
      "2295   ST-504   2533  0.536518  17.348598  1948.709660  0.226609  0.058429   \n",
      "2296   ST-505   2623  0.599695  17.371712  1744.822703  0.252002  0.079299   \n",
      "2297   ST-506   8918  0.579839  24.838080  2107.308590  0.227181  0.014353   \n",
      "2298   ST-507    396  0.734848  21.234848  2746.265934  0.239899  0.055556   \n",
      "2299   ST-508   5096  0.670918  15.866366  1709.742192  0.225667  0.071625   \n",
      "2300   ST-509    949  0.633298  27.008430  2443.498124  0.310854  0.004215   \n",
      "2301    ST-51   3384  0.719267  21.830378  2078.402157  0.117612  0.012707   \n",
      "2302   ST-510   3230  0.697214  17.113313  1773.089294  0.245201  0.103096   \n",
      "2303   ST-511   1631  0.674433  18.649908  1942.052299  0.259963  0.072961   \n",
      "2304   ST-512   4791  0.550198  15.409518  1477.488641  0.268420  0.037153   \n",
      "2305   ST-513   7612  0.588807  13.619023  1464.940786  0.238045  0.050184   \n",
      "2306   ST-514   3944  0.698022  15.875000  1889.647343  0.264959  0.069726   \n",
      "2307   ST-516   5587  0.642384  20.504922  2339.657875  0.219259  0.031502   \n",
      "2308   ST-517   2789  0.730011  17.299390  2050.294783  0.277877  0.081391   \n",
      "2309   ST-518   3068  0.465776  20.222295  2003.914837  0.285854  0.042699   \n",
      "2310   ST-519   2337  0.607189  24.165597  3173.238036  0.299101  0.026102   \n",
      "2311    ST-52   3278  0.679683  31.918548  3334.395406  0.225137  0.007627   \n",
      "2312   ST-520   4004  0.600899  38.125375  5506.501319  0.329171  0.027972   \n",
      "2313   ST-522   8876  0.550924  15.089455  1528.783199  0.278053  0.022871   \n",
      "2314   ST-523   3654  0.594143  19.521073  1759.141352  0.267652  0.042419   \n",
      "2315   ST-524   3658  0.661290  17.776107  1818.857419  0.264079  0.081465   \n",
      "2316   ST-525   3972  0.614552  17.998238  1925.329328  0.238671  0.053877   \n",
      "2317   ST-526    950  0.704211  16.267368  1902.613379  0.270526  0.087368   \n",
      "2318   ST-528   3885  0.615444  17.463835  2224.389483  0.202831  0.060746   \n",
      "2319    ST-53   4644  0.709948  29.102498  3080.288770  0.223084  0.026916   \n",
      "2320   ST-530   3860  0.638860  16.227461  1965.370927  0.222798  0.039896   \n",
      "2321   ST-531   1431  0.714186  18.292103  2118.080538  0.255066  0.062194   \n",
      "2322   ST-532    896  0.731027  22.016741  2321.808036  0.203125  0.030134   \n",
      "2323   ST-533   1448  0.707873  18.102210  2193.586657  0.191298  0.064917   \n",
      "2324   ST-534   3937  0.608077  24.163068  2104.151689  0.244856  0.064008   \n",
      "2325   ST-535   3222  0.656425  22.833333  2877.883634  0.276536  0.074178   \n",
      "2326   ST-536   1293  0.643465  20.793503  2287.539095  0.283063  0.184841   \n",
      "2327   ST-538   2163  0.592233  19.591308  2249.971063  0.215442  0.058252   \n",
      "2328   ST-539   2401  0.556435  28.002915  3329.088817  0.274885  0.033736   \n",
      "2329   ST-540   1943  0.589810  26.920741  2389.121801  0.248585  0.039115   \n",
      "2330   ST-541   4347  0.588452  19.728318  1904.885671  0.239936  0.044398   \n",
      "2331   ST-542   4686  0.626761  19.459667  1845.289733  0.208920  0.011310   \n",
      "2332   ST-543    463  0.552916  17.058315  2201.044471  0.269978  0.023758   \n",
      "2333   ST-544   3046  0.603086  19.520026  2157.778257  0.263624  0.032830   \n",
      "2334   ST-545   1484  0.662399  17.810647  1891.446611  0.260782  0.031671   \n",
      "2335   ST-546   3824  0.588651  23.038180  2268.443415  0.269090  0.067207   \n",
      "2336   ST-547   7228  0.557692  28.217349  2791.398557  0.293304  0.042612   \n",
      "2337   ST-548   2302  0.581234  27.661164  2927.711347  0.276281  0.059079   \n",
      "2338   ST-549   1849  0.463494  17.167117  2091.646382  0.159005  0.017307   \n",
      "2339    ST-55   4003  0.687734  29.569323  3303.061002  0.247065  0.008993   \n",
      "2340   ST-550   4541  0.527637  19.649637  1902.311782  0.308743  0.008588   \n",
      "2341   ST-551   2080  0.592308  19.630288  1892.847784  0.259615  0.059615   \n",
      "2342   ST-553   4215  0.586477  22.830605  2244.808871  0.288968  0.071886   \n",
      "2343   ST-555   3838  0.638874  25.064878  3238.542897  0.241793  0.050287   \n",
      "2344   ST-558   2837  0.638350  23.679944  3112.692630  0.291505  0.082129   \n",
      "2345   ST-559    543  0.740331  19.279926  2573.205727  0.235727  0.104972   \n",
      "2346   ST-560    606  0.805281  26.508251  2599.964571  0.235974  0.112211   \n",
      "2347   ST-561   1826  0.635816  20.084885  2033.003461  0.261774  0.072289   \n",
      "2348   ST-562    579  0.773748  21.678756  2422.035820  0.257340  0.112263   \n",
      "2349   ST-563   2471  0.766896  20.766087  2124.346572  0.266694  0.090652   \n",
      "2350   ST-564   2393  0.603427  23.662766  2596.277158  0.224822  0.067697   \n",
      "2351   ST-565   2417  0.696731  19.400910  2226.579139  0.228382  0.044270   \n",
      "2352   ST-566   1862  0.672395  19.605800  2239.409463  0.288937  0.078947   \n",
      "2353   ST-567    782  0.710997  21.381074  2323.320141  0.274936  0.026854   \n",
      "2354   ST-568   1378  0.682148  15.050798  1580.138708  0.224964  0.021045   \n",
      "2355   ST-570   1925  0.617143  21.142857  2302.857242  0.227532  0.048831   \n",
      "2356   ST-571    893  0.643897  23.972004  2618.196529  0.235162  0.044793   \n",
      "2357   ST-572   1791  0.569514  19.534338  2362.897677  0.237856  0.109436   \n",
      "2358   ST-573    575  0.613913  20.925217  2556.537270  0.325217  0.067826   \n",
      "2359   ST-574   2388  0.648241  20.623534  2496.598677  0.262144  0.042714   \n",
      "2360   ST-578   3528  0.633220  23.549320  2869.692951  0.261621  0.063776   \n",
      "2361   ST-579   2876  0.594228  22.488873  2228.905640  0.246175  0.057371   \n",
      "2362   ST-580   2263  0.642510  21.891295  1940.543142  0.224481  0.079982   \n",
      "2363   ST-583    506  0.598814  16.996047  2534.149012  0.284585  0.033597   \n",
      "2364   ST-584    910  0.717582  19.734066  2709.218714  0.267033  0.098901   \n",
      "2365   ST-585   1611  0.589696  18.794538  2507.757784  0.272502  0.031657   \n",
      "2366   ST-586    712  0.747191  15.634831  2093.099199  0.227528  0.023876   \n",
      "2367   ST-587    331  0.688822  22.151057  3299.499366  0.265861  0.163142   \n",
      "2368   ST-588    437  0.615561  17.812357  2050.129199  0.228833  0.009153   \n",
      "2369   ST-589   1323  0.756614  18.195767  2189.447332  0.211640  0.056689   \n",
      "2370    ST-59   4904  0.714519  20.136215  2011.128777  0.150082  0.013458   \n",
      "2371   ST-590    881  0.590238  20.170261  2624.330136  0.290579  0.043133   \n",
      "2372   ST-593    776  0.621134  16.091495  2289.809214  0.274485  0.054124   \n",
      "2373   ST-594    838  0.693317  16.321002  2182.732315  0.252983  0.029833   \n",
      "2374   ST-595   1473  0.639511  22.798371  2986.464372  0.237610  0.120842   \n",
      "2375   ST-596   4336  0.647140  17.057426  2352.860390  0.251153  0.033902   \n",
      "2376   ST-599   2876  0.530946  16.264604  1604.688414  0.195758  0.036509   \n",
      "2377     ST-6   3031  0.616298  30.800066  2873.024494  0.280435  0.054108   \n",
      "2378    ST-60   3142  0.750796  28.235201  2302.659554  0.106302  0.007002   \n",
      "2379   ST-600   8311  0.726868  15.129347  1932.363995  0.257851  0.052461   \n",
      "2380   ST-602   2404  0.598170  19.740849  2237.445653  0.244176  0.082363   \n",
      "2381   ST-603   5566  0.566655  21.869386  2776.375792  0.250988  0.035932   \n",
      "2382   ST-604   5140  0.706420  16.215564  1675.191506  0.230934  0.043580   \n",
      "2383   ST-605   2671  0.621864  18.166604  2114.646417  0.254961  0.043804   \n",
      "2384   ST-608    771  0.552529  23.067445  2783.851064  0.317769  0.024643   \n",
      "2385   ST-609    542  0.529520  24.566421  3106.120590  0.202952  0.075646   \n",
      "2386   ST-610   3828  0.541536  18.234848  1856.181565  0.231191  0.029258   \n",
      "2387   ST-611   6919  0.569446  20.463795  1964.411437  0.281399  0.055933   \n",
      "2388   ST-612   1800  0.645000  20.748889  2447.729833  0.302778  0.091111   \n",
      "2389   ST-613   1198  0.671119  18.201169  2001.607204  0.286311  0.029215   \n",
      "2390   ST-614   2626  0.613861  23.406321  2429.935720  0.210586  0.027037   \n",
      "2391   ST-615   2316  0.653713  17.327288  1888.711813  0.235320  0.085492   \n",
      "2392   ST-616   1887  0.640700  17.852146  2115.895718  0.225755  0.081611   \n",
      "2393   ST-619   2795  0.709123  17.620394  2498.242880  0.163506  0.025403   \n",
      "2394    ST-62   4410  0.742177  23.031293  2430.443467  0.171202  0.015646   \n",
      "2395   ST-620   2194  0.754330  17.395169  2282.225314  0.152689  0.015953   \n",
      "2396   ST-621   1491  0.739101  22.790074  3480.366030  0.132126  0.022803   \n",
      "2397   ST-622   2267  0.790472  12.973974  1794.980049  0.045876  0.004411   \n",
      "2398   ST-623   1777  0.832864  18.211030  2201.070687  0.078222  0.008441   \n",
      "2399   ST-624   1404  0.748575  18.529202  1747.446011  0.170228  0.030627   \n",
      "2400   ST-625   2196  0.653461  14.490437  1678.476849  0.213570  0.019126   \n",
      "2401   ST-626    318  0.704403  25.078616  2440.706635  0.261006  0.050314   \n",
      "2402   ST-628    449  0.663697  27.222717  4165.545122  0.265033  0.106904   \n",
      "2403   ST-629   1291  0.710302  23.753679  2306.693703  0.276530  0.064291   \n",
      "2404    ST-63   2453  0.668569  21.838565  2400.730766  0.214839  0.026906   \n",
      "2405   ST-630   1208  0.694536  20.687914  2385.894288  0.218543  0.045530   \n",
      "2406   ST-631    551  0.700544  15.724138  1603.991615  0.201452  0.041742   \n",
      "2407   ST-632   3120  0.611218  33.467949  4918.322183  0.251923  0.071795   \n",
      "2408   ST-633   1102  0.581670  29.923775  4018.651198  0.232305  0.031760   \n",
      "2409   ST-634    759  0.660079  24.387352  2854.572358  0.241107  0.051383   \n",
      "2410   ST-635   1768  0.701923  16.102941  1986.848846  0.247738  0.120475   \n",
      "2411   ST-636   1705  0.653959  17.274487  1726.100346  0.225806  0.033431   \n",
      "2412   ST-637   3302  0.689279  15.570866  1887.447756  0.214113  0.021199   \n",
      "2413   ST-638   1230  0.704878  19.352033  2037.781992  0.270732  0.063415   \n",
      "2414   ST-639   1664  0.670072  14.605168  1632.501701  0.188101  0.043870   \n",
      "2415    ST-64   2882  0.656142  33.196738  4153.031069  0.268910  0.025677   \n",
      "2416   ST-640   2388  0.649079  32.095896  4905.543107  0.123953  0.010469   \n",
      "2417   ST-641   1090  0.749541  20.620183  2889.349376  0.114679  0.009174   \n",
      "2418   ST-642    587  0.684838  25.197615  2265.098126  0.190801  0.030664   \n",
      "2419   ST-643   4227  0.660989  19.694109  2169.157674  0.255974  0.097469   \n",
      "2420   ST-644    710  0.764789  20.802817  2205.708408  0.284507  0.114085   \n",
      "2421   ST-645   2136  0.582397  21.078184  1937.650983  0.224251  0.024345   \n",
      "2422   ST-646   1782  0.686869  21.295735  2328.105196  0.266554  0.081369   \n",
      "2423   ST-647    849  0.736160  23.428740  2351.520212  0.221437  0.011779   \n",
      "2424   ST-648    801  0.767790  23.051186  2398.622609  0.264669  0.133583   \n",
      "2425   ST-650   2281  0.618588  20.878562  2526.852337  0.300745  0.118808   \n",
      "2426   ST-651   1500  0.658000  22.872667  2272.419673  0.273333  0.083333   \n",
      "2427   ST-652   1181  0.623201  20.574090  2285.566842  0.237087  0.088061   \n",
      "2428   ST-654   1206  0.536484  22.540630  2267.245929  0.271144  0.099502   \n",
      "2429   ST-655   4645  0.693434  20.072766  2294.450248  0.232939  0.059203   \n",
      "2430   ST-657    600  0.643333  28.275000  3481.428067  0.266667  0.070000   \n",
      "2431   ST-658   2812  0.612376  15.308321  1889.534804  0.259602  0.082504   \n",
      "2432    ST-66   5529  0.752939  22.251040  2678.366495  0.124073  0.015916   \n",
      "2433   ST-660   3093  0.525057  42.685095  6650.066059  0.297446  0.011962   \n",
      "2434   ST-661    349  0.624642  21.143266  2232.125501  0.269341  0.005731   \n",
      "2435   ST-662   3313  0.654090  18.594325  2264.152388  0.217929  0.040447   \n",
      "2436   ST-663   3850  0.631169  19.840260  2573.901210  0.213247  0.024416   \n",
      "2437   ST-664   9574  0.629204  20.506163  2618.618445  0.247545  0.011489   \n",
      "2438   ST-665   2736  0.694079  15.657895  2033.472259  0.220029  0.052632   \n",
      "2439   ST-666   4800  0.701667  12.722083  1612.609463  0.242083  0.035000   \n",
      "2440   ST-667    648  0.643519  18.287037  1939.704614  0.262346  0.100309   \n",
      "2441   ST-668  13459  0.665800  22.803626  3022.573263  0.218961  0.048964   \n",
      "2442   ST-669   3594  0.684752  21.394268  2284.253703  0.260434  0.072621   \n",
      "2443    ST-67   2797  0.670719  31.640329  3683.689053  0.286021  0.055059   \n",
      "2444   ST-670   2412  0.718491  20.323798  2114.462720  0.235904  0.041459   \n",
      "2445   ST-671    709  0.686883  20.913963  2335.970000  0.263752  0.036671   \n",
      "2446   ST-673   2249  0.555803  20.381503  2133.992583  0.248555  0.048911   \n",
      "2447   ST-674   2134  0.696813  14.105904  1660.729620  0.212746  0.073102   \n",
      "2448   ST-675   2061  0.591946  20.495391  2750.793658  0.247938  0.028627   \n",
      "2449   ST-676   2139  0.731183  21.230949  2513.643768  0.279570  0.033193   \n",
      "2450   ST-677   1457  0.648593  15.291695  1878.523617  0.253260  0.060398   \n",
      "2451   ST-678   3174  0.764020  16.206679  2179.964972  0.246062  0.080025   \n",
      "2452   ST-679   1880  0.631383  27.508511  3689.928830  0.264362  0.097872   \n",
      "2453    ST-68   3827  0.702378  16.749412  1906.418009  0.171675  0.023517   \n",
      "2454   ST-683   5580  0.627061  37.079032  5033.486269  0.355376  0.052509   \n",
      "2455   ST-685   2570  0.678599  17.605837  2264.504813  0.209728  0.039300   \n",
      "2456   ST-686   1240  0.790323  16.858065  2168.555339  0.251613  0.094355   \n",
      "2457   ST-687   3278  0.660464  19.608908  2124.953935  0.277913  0.089689   \n",
      "2458   ST-688    352  0.681818  18.332386  2096.080256  0.275568  0.065341   \n",
      "2459    ST-69   2050  0.704390  20.548293  1903.043361  0.251220  0.025854   \n",
      "2460   ST-690   1392  0.617816  23.813937  2485.482687  0.235632  0.081178   \n",
      "2461   ST-691    919  0.682263  25.832427  3118.350773  0.264418  0.119695   \n",
      "2462   ST-692   3747  0.618094  45.590873  6708.738887  0.295970  0.033093   \n",
      "2463   ST-693   1098  0.755920  28.111111  3873.642750  0.265027  0.037341   \n",
      "2464   ST-694   1014  0.678501  20.833333  2284.562179  0.268245  0.030572   \n",
      "2465   ST-695   1144  0.668706  52.090909  6379.435927  0.409965  0.076049   \n",
      "2466   ST-696    577  0.729636  26.811092  2787.490381  0.259965  0.076256   \n",
      "2467   ST-697    380  0.689474  30.986842  3846.814947  0.265789  0.039474   \n",
      "2468   ST-699   5481  0.705528  22.285532  2524.586094  0.254333  0.072067   \n",
      "2469     ST-7   1574  0.648030  29.077510  2950.471067  0.296061  0.099746   \n",
      "2470    ST-70   3909  0.679458  22.256587  2345.284106  0.224354  0.023024   \n",
      "2471   ST-700   2470  0.770445  22.138462  2771.521190  0.295547  0.062348   \n",
      "2472   ST-701    554  0.758123  21.864621  2565.978881  0.241877  0.083032   \n",
      "2473   ST-702  13831  0.653821  24.262743  3282.510040  0.311836  0.087846   \n",
      "2474   ST-703   2890  0.702768  18.071972  1852.983246  0.274394  0.056401   \n",
      "2475   ST-704   2707  0.685630  19.516808  2174.347414  0.233099  0.055781   \n",
      "2476   ST-705   2925  0.724786  24.225299  2847.145439  0.278632  0.076923   \n",
      "2477   ST-707    717  0.824268  18.192469  2940.519693  0.295676  0.186890   \n",
      "2478   ST-709   1279  0.605160  24.095387  2427.475176  0.249414  0.083659   \n",
      "2479    ST-71   3290  0.696960  21.238906  2477.759717  0.237994  0.021277   \n",
      "2480   ST-712   2603  0.677295  22.541299  2558.779551  0.229351  0.091817   \n",
      "2481   ST-713   1649  0.620982  31.887204  5283.713948  0.343238  0.074591   \n",
      "2482   ST-714   2257  0.605671  19.385911  2189.360474  0.276473  0.050510   \n",
      "2483   ST-715   1638  0.656288  19.203907  2013.609908  0.310745  0.077534   \n",
      "2484   ST-717   1317  0.634776  19.520881  2182.862407  0.290812  0.057707   \n",
      "2485   ST-719   1109  0.559964  19.535618  2056.508945  0.297565  0.088368   \n",
      "2486    ST-72   4006  0.746380  23.525961  2899.958405  0.185971  0.035447   \n",
      "2487   ST-720   1023  0.670577  19.176931  1897.165367  0.259042  0.076246   \n",
      "2488   ST-721    686  0.619534  18.367347  1904.244927  0.266764  0.032070   \n",
      "2489   ST-722    281  0.519573  22.153025  1956.739786  0.295374  0.042705   \n",
      "2490   ST-723   1078  0.572356  17.166976  1623.405473  0.277365  0.079777   \n",
      "2491   ST-724   3892  0.751799  27.990493  3866.556842  0.287513  0.106372   \n",
      "2492   ST-725   1206  0.671642  20.800166  2982.184602  0.262852  0.043947   \n",
      "2493   ST-726   1875  0.664000  20.712533  2199.224603  0.242667  0.049067   \n",
      "2494   ST-727   2186  0.655993  17.109790  1923.282443  0.236048  0.118481   \n",
      "2495   ST-728   4777  0.671133  22.933222  2633.253284  0.266904  0.080804   \n",
      "2496   ST-729   1911  0.661957  19.789639  1838.423391  0.266876  0.052852   \n",
      "2497    ST-73  12670  0.594396  42.359669  5150.235206  0.344041  0.038753   \n",
      "2498   ST-731    333  0.570571  14.222222  1818.955495  0.231231  0.096096   \n",
      "2499   ST-732    728  0.759615  11.133242  1465.956332  0.186813  0.140110   \n",
      "2500   ST-733   1779  0.600899  16.653738  2055.136144  0.187746  0.020236   \n",
      "2501   ST-735   6833  0.646129  14.927704  1594.055750  0.223767  0.037904   \n",
      "2502   ST-736   3718  0.646046  19.002690  2152.872324  0.309306  0.025820   \n",
      "2503   ST-737   2312  0.576990  19.233131  2029.582621  0.211938  0.069637   \n",
      "2504   ST-738   1130  0.639823  31.445133  3775.445257  0.315044  0.038938   \n",
      "2505   ST-740   2196  0.581512  17.576503  2027.739977  0.196266  0.032332   \n",
      "2506   ST-741    142  0.542254  31.140845  2880.673451  0.394366  0.042254   \n",
      "2507   ST-742   2119  0.635677  14.433223  2157.772227  0.223218  0.008495   \n",
      "2508   ST-743   1088  0.597426  19.206801  2319.216719  0.281250  0.073529   \n",
      "2509   ST-744   1607  0.662726  18.256378  2233.198332  0.227131  0.069073   \n",
      "2510   ST-745    525  0.624762  21.329524  2329.351600  0.234286  0.060952   \n",
      "2511   ST-746   1152  0.679688  18.223958  2298.036536  0.282118  0.048611   \n",
      "2512   ST-747   1517  0.647989  24.876071  2976.830613  0.230059  0.019117   \n",
      "2513   ST-748   1429  0.648006  42.351994  4518.525395  0.369489  0.046886   \n",
      "2514   ST-749   2642  0.582135  35.834595  4473.374792  0.345572  0.036715   \n",
      "2515   ST-750   6095  0.604922  39.589500  4626.088824  0.328630  0.029368   \n",
      "2516   ST-752   1703  0.543159  27.452143  3155.498943  0.253670  0.039930   \n",
      "2517   ST-753   3013  0.658480  22.930634  2551.372463  0.246598  0.049784   \n",
      "2518   ST-754    624  0.786859  17.980769  2139.281506  0.227564  0.038462   \n",
      "2519   ST-755    277  0.750903  19.090253  2220.647509  0.263538  0.043321   \n",
      "2520   ST-756    368  0.714674  13.336957  1923.014185  0.211957  0.024457   \n",
      "2521   ST-757   1163  0.562339  22.960447  2305.741720  0.185727  0.037833   \n",
      "2522   ST-758   2101  0.632080  20.183722  1989.128420  0.243693  0.043789   \n",
      "2523   ST-759    981  0.744139  24.314985  2515.210591  0.237513  0.018349   \n",
      "2524    ST-76   2393  0.597994  17.023402  1963.569010  0.264522  0.014208   \n",
      "2525   ST-760   2653  0.689408  20.497550  2254.922363  0.250660  0.054278   \n",
      "2526   ST-761   2944  0.718410  24.971128  2587.637792  0.176970  0.027174   \n",
      "2527   ST-762   1038  0.767823  19.220617  1812.148112  0.210019  0.052023   \n",
      "2528   ST-763    611  0.844517  23.114566  2669.598085  0.186579  0.037643   \n",
      "2529   ST-764   1369  0.707816  23.807159  2634.372316  0.188459  0.025566   \n",
      "2530   ST-765   1390  0.653957  22.029496  2304.230712  0.180576  0.032374   \n",
      "2531   ST-766    721  0.574202  20.472954  2289.239085  0.220527  0.047157   \n",
      "2532   ST-767   1491  0.707579  18.741784  2283.395211  0.177733  0.011402   \n",
      "2533   ST-768   1373  0.684632  17.737072  2301.516635  0.172615  0.005098   \n",
      "2534   ST-769   2546  0.610369  23.109976  2709.115958  0.219953  0.047918   \n",
      "2535    ST-77   1221  0.553645  16.910729  1910.873292  0.267813  0.023751   \n",
      "2536   ST-770   1359  0.612215  26.601913  3023.169036  0.245769  0.041943   \n",
      "2537   ST-771   2008  0.617032  29.395418  4311.929313  0.243028  0.031375   \n",
      "2538   ST-772   3706  0.695899  22.636805  2683.848791  0.202644  0.010254   \n",
      "2539   ST-773    522  0.641762  27.946360  3086.346494  0.201149  0.007663   \n",
      "2540   ST-774    204  0.627451  27.642157  4078.622451  0.151961  0.019608   \n",
      "2541   ST-775    678  0.648968  19.942478  2936.761239  0.224189  0.045723   \n",
      "2542   ST-776   5421  0.541413  45.778270  6198.911398  0.386645  0.029699   \n",
      "2543   ST-777   2689  0.534771  48.862030  6149.028434  0.359241  0.056155   \n",
      "2544   ST-778    154  0.649351  25.350649  2682.225065  0.292208  0.097403   \n",
      "2545   ST-779    764  0.609948  25.498691  2919.392356  0.277487  0.075916   \n",
      "2546    ST-78   1462  0.625855  17.770862  2297.217715  0.223666  0.070451   \n",
      "2547   ST-780   2079  0.636364  23.613276  2226.993098  0.281866  0.019721   \n",
      "2548   ST-781   1754  0.762258  19.863740  2430.879019  0.215507  0.037058   \n",
      "2549   ST-782    910  0.534066  26.129670  3495.518330  0.327473  0.047253   \n",
      "2550   ST-783    639  0.615023  24.208138  3195.600720  0.197183  0.040689   \n",
      "2551   ST-784    193  0.704663  43.937824  6617.792383  0.279793  0.103627   \n",
      "2552   ST-786    484  0.677686  27.485537  3389.725248  0.326446  0.051653   \n",
      "2553   ST-787   1685  0.716320  30.069436  3198.201501  0.268843  0.116320   \n",
      "2554   ST-788   2389  0.616576  22.062369  2655.620205  0.234408  0.061951   \n",
      "2555   ST-789    678  0.644543  21.935103  3152.503732  0.233038  0.041298   \n",
      "2556   ST-790    543  0.690608  27.832413  4143.130147  0.099448  0.016575   \n",
      "2557   ST-791   3199  0.638012  31.814317  3688.740228  0.264770  0.043451   \n",
      "2558   ST-792    812  0.592365  34.975369  4273.903571  0.321429  0.087438   \n",
      "2559   ST-793   1885  0.603183  37.454111  3773.871358  0.264191  0.103979   \n",
      "2560   ST-794    784  0.778061  37.202806  5124.841773  0.256378  0.109694   \n",
      "2561   ST-795    836  0.716507  24.789474  3065.619916  0.215311  0.074163   \n",
      "2562   ST-796    886  0.602709  29.086907  4054.176659  0.209932  0.094808   \n",
      "2563   ST-797   2500  0.740400  27.301200  3324.643608  0.102400  0.031200   \n",
      "2564   ST-798    755  0.645033  41.658278  6314.146715  0.312583  0.029139   \n",
      "2565   ST-799   1447  0.700069  33.655840  4759.787035  0.266759  0.029717   \n",
      "2566     ST-8   4362  0.586657  34.797111  3946.588831  0.372077  0.060981   \n",
      "2567    ST-80   1427  0.633497  22.117029  2381.156342  0.107218  0.008409   \n",
      "2568   ST-801    307  0.687296  27.498371  3641.897003  0.315961  0.032573   \n",
      "2569   ST-802   1049  0.738799  27.484271  3093.662231  0.135367  0.046711   \n",
      "2570   ST-803   1015  0.548768  28.102463  3172.798187  0.262069  0.057143   \n",
      "2571   ST-804    782  0.524297  29.060102  2737.600639  0.329923  0.012788   \n",
      "2572   ST-806    779  0.684211  25.527599  2723.831913  0.098845  0.006418   \n",
      "2573   ST-807   1548  0.583333  28.098837  3292.785659  0.271964  0.036822   \n",
      "2574   ST-808   1706  0.616647  25.956038  2501.991325  0.259672  0.031653   \n",
      "2575   ST-809   1194  0.693467  23.650754  2213.333987  0.252931  0.058626   \n",
      "2576    ST-81   1450  0.617241  23.055172  2478.231303  0.246897  0.112414   \n",
      "2577   ST-810   2230  0.737220  24.758744  2618.865404  0.163677  0.056054   \n",
      "2578   ST-811   1277  0.709475  23.717306  2818.927525  0.188724  0.081441   \n",
      "2579   ST-812    853  0.664713  20.437280  2266.179285  0.139508  0.072685   \n",
      "2580   ST-813   1034  0.636364  22.186654  2380.988733  0.218569  0.067698   \n",
      "2581   ST-814   1029  0.752187  21.389699  1981.832575  0.186589  0.068999   \n",
      "2582   ST-815   2767  0.732924  25.160463  2832.772118  0.178894  0.056017   \n",
      "2583   ST-816   2274  0.678540  20.042216  2021.508087  0.206245  0.027265   \n",
      "2584   ST-817    501  0.680639  17.315369  2086.132695  0.185629  0.031936   \n",
      "2585   ST-818   2909  0.648333  17.930217  2016.570058  0.203850  0.015813   \n",
      "2586   ST-819    736  0.667120  16.934783  2071.876793  0.233696  0.025815   \n",
      "2587    ST-82   3633  0.470410  24.911919  2718.853705  0.203138  0.022846   \n",
      "2588   ST-820   1008  0.641865  25.897817  2928.256468  0.293651  0.033730   \n",
      "2589   ST-821   3983  0.653779  24.727843  2968.556939  0.221441  0.042681   \n",
      "2590   ST-822   1183  0.648352  22.058326  2865.926069  0.266272  0.037194   \n",
      "2591   ST-823   2597  0.705044  23.060454  2726.633296  0.232576  0.029650   \n",
      "2592   ST-824   5869  0.633328  13.886522  1608.000745  0.240586  0.055376   \n",
      "2593   ST-825   1491  0.657948  17.401744  2149.893474  0.265594  0.074447   \n",
      "2594   ST-826    456  0.763158  16.879386  2526.799649  0.225877  0.043860   \n",
      "2595   ST-827   9101  0.719042  17.073618  1983.666912  0.232502  0.067355   \n",
      "2596   ST-828   2861  0.630199  12.916463  1476.385327  0.196435  0.025865   \n",
      "2597   ST-829   3505  0.678459  16.732382  1785.647541  0.239943  0.037375   \n",
      "2598    ST-83   1515  0.546535  19.279868  1998.451729  0.210561  0.023102   \n",
      "2599   ST-830   1478  0.659675  17.621786  1858.134276  0.172530  0.031123   \n",
      "2600   ST-831   5322  0.649756  18.915257  2149.892026  0.251973  0.059752   \n",
      "2601   ST-834   6625  0.617962  15.573132  1573.830500  0.226415  0.036377   \n",
      "2602   ST-835   8248  0.609239  15.777764  1765.089530  0.256183  0.054680   \n",
      "2603   ST-838   3433  0.637343  18.841247  2046.859779  0.211768  0.096708   \n",
      "2604   ST-839   2743  0.593146  17.999271  1870.264677  0.202333  0.028071   \n",
      "2605    ST-84   1770  0.676836  17.663277  2022.625938  0.152542  0.033898   \n",
      "2606   ST-840   3475  0.570072  22.799137  2392.765401  0.303022  0.024748   \n",
      "2607   ST-842   3037  0.629569  19.621666  2390.043609  0.284821  0.063879   \n",
      "2608   ST-847   2852  0.700912  16.995792  1955.128562  0.259116  0.059257   \n",
      "2609   ST-849   5487  0.693640  20.572991  2475.858172  0.259523  0.070530   \n",
      "2610    ST-85   2237  0.600358  39.249888  3777.294251  0.461779  0.021457   \n",
      "2611   ST-850   3059  0.627983  14.858124  1603.948294  0.243871  0.060804   \n",
      "2612   ST-852    362  0.685083  17.546961  2296.931823  0.325967  0.027624   \n",
      "2613   ST-853   2199  0.711687  19.106867  1917.585921  0.253752  0.022283   \n",
      "2614   ST-854   1718  0.637369  19.561700  2282.306449  0.286380  0.054715   \n",
      "2615   ST-855   2265  0.698896  19.208830  2270.460208  0.235320  0.046358   \n",
      "2616   ST-856   2511  0.698526  17.992433  2107.702445  0.281561  0.056949   \n",
      "2617   ST-857   2979  0.621014  18.161128  1992.756170  0.260490  0.056730   \n",
      "2618   ST-859   1007  0.817279  20.308838  2258.457071  0.181728  0.053625   \n",
      "2619    ST-86   3950  0.646582  20.509114  2306.459714  0.150886  0.010127   \n",
      "2620   ST-860    561  0.787879  24.982175  2036.059911  0.254902  0.037433   \n",
      "2621   ST-861    707  0.543140  18.958982  1835.352928  0.207921  0.024045   \n",
      "2622   ST-862   3225  0.631318  27.266357  3689.529085  0.302016  0.066047   \n",
      "2623   ST-863    636  0.661950  25.984277  2821.819654  0.232704  0.130503   \n",
      "2624   ST-866   2280  0.623684  21.760088  2910.904390  0.267105  0.042544   \n",
      "2625   ST-867   1592  0.601759  18.319724  2133.831545  0.253769  0.053392   \n",
      "2626   ST-868   1795  0.564345  23.572145  3000.424072  0.262396  0.077437   \n",
      "2627   ST-869   1866  0.645230  20.630761  2227.578457  0.290461  0.056806   \n",
      "2628    ST-87   4849  0.524438  25.153846  2852.210076  0.317385  0.008043   \n",
      "2629   ST-870   1391  0.740474  22.263120  2851.753940  0.237239  0.021567   \n",
      "2630   ST-871   1773  0.689791  17.417936  2009.415296  0.236323  0.039481   \n",
      "2631   ST-872    620  0.724194  24.450000  2673.585484  0.224194  0.182258   \n",
      "2632   ST-873   4638  0.736093  16.709789  1833.281108  0.184347  0.016171   \n",
      "2633   ST-874    492  0.729675  14.475610  1720.059675  0.237805  0.016260   \n",
      "2634   ST-875   2630  0.677186  26.855513  3855.511624  0.266160  0.032319   \n",
      "2635   ST-876   1844  0.601952  13.824837  1662.496838  0.200651  0.039046   \n",
      "2636   ST-877   2216  0.671480  30.828069  4298.238809  0.295126  0.053700   \n",
      "2637   ST-879   1176  0.750000  24.616497  2525.048810  0.165816  0.056973   \n",
      "2638    ST-88    542  0.632841  20.204797  2683.820111  0.293358  0.033210   \n",
      "2639   ST-880    495  0.600000  27.355556  4396.469879  0.248485  0.020202   \n",
      "2640   ST-881   1115  0.596413  31.403587  4859.316422  0.270852  0.043049   \n",
      "2641   ST-882   5019  0.641961  21.313608  2436.334868  0.275752  0.066149   \n",
      "2642   ST-883   2667  0.641920  21.058493  2075.233318  0.262092  0.059993   \n",
      "2643   ST-884   1568  0.654337  20.713648  2513.640931  0.278699  0.197066   \n",
      "2644   ST-885    617  0.701783  30.701783  4190.244716  0.286872  0.064830   \n",
      "2645   ST-886    551  0.805808  21.214156  2705.729074  0.288566  0.063521   \n",
      "2646   ST-887   1511  0.616810  19.025149  2146.071555  0.232958  0.059563   \n",
      "2647   ST-889   1065  0.803756  24.098592  3017.896207  0.163380  0.025352   \n",
      "2648    ST-89   4013  0.538998  31.002990  3533.874139  0.401944  0.020184   \n",
      "2649   ST-890   2555  0.755382  22.637965  2540.078489  0.190998  0.016047   \n",
      "2650   ST-891  14104  0.552255  21.235323  2214.419950  0.283253  0.008012   \n",
      "2651   ST-892   4887  0.579701  22.233067  2421.072382  0.279926  0.033354   \n",
      "2652   ST-894   3067  0.522008  18.940985  1947.712742  0.230192  0.029671   \n",
      "2653   ST-895   2807  0.657998  18.642679  2444.754660  0.200214  0.043463   \n",
      "2654   ST-896   1677  0.621348  24.868813  3598.029666  0.249255  0.081097   \n",
      "2655   ST-897    928  0.662716  20.575431  2267.129763  0.312500  0.077586   \n",
      "2656   ST-899    878  0.725513  19.571754  2567.945854  0.194761  0.007973   \n",
      "2657     ST-9   3378  0.582297  22.505921  2075.252256  0.240675  0.069568   \n",
      "2658    ST-90   2559  0.563892  20.953497  2435.414330  0.152403  0.042595   \n",
      "2659   ST-900   1171  0.556789  20.874466  2561.164705  0.246798  0.059778   \n",
      "2660   ST-901    787  0.613723  23.944091  2871.884625  0.237611  0.022872   \n",
      "2661   ST-902    239  0.468619  31.079498  3309.954142  0.271967  0.012552   \n",
      "2662   ST-903   4111  0.596935  21.346631  2286.789968  0.168086  0.034298   \n",
      "2663   ST-904   4653  0.553406  21.521814  2156.532794  0.283258  0.044702   \n",
      "2664   ST-905   2510  0.532271  20.648207  2043.805765  0.292430  0.032669   \n",
      "2665   ST-906   2878  0.645240  20.414177  2444.673972  0.228978  0.009382   \n",
      "2666   ST-907   1606  0.519303  21.785803  2354.484869  0.275841  0.019925   \n",
      "2667   ST-908   4186  0.492355  21.555901  2195.216063  0.260631  0.036312   \n",
      "2668    ST-91   2635  0.671347  21.483112  2475.417495  0.163188  0.019355   \n",
      "2669   ST-910   5300  0.581321  17.804340  2234.285374  0.216604  0.032075   \n",
      "2670   ST-912   2350  0.632340  19.240426  2148.693672  0.273191  0.116170   \n",
      "2671   ST-913   3086  0.782566  15.876539  1992.127259  0.245949  0.057680   \n",
      "2672   ST-914   7433  0.653572  19.236378  2312.363515  0.255079  0.036190   \n",
      "2673   ST-915   2083  0.591935  17.850216  2013.789337  0.257321  0.052328   \n",
      "2674   ST-916   1674  0.670848  18.812425  2023.875167  0.280167  0.083035   \n",
      "2675   ST-918   4979  0.638080  21.070496  2566.035477  0.203254  0.031733   \n",
      "2676   ST-919   7074  0.657337  24.111818  3295.041667  0.266751  0.057393   \n",
      "2677    ST-92   1207  0.557581  21.096106  2489.536288  0.257664  0.023198   \n",
      "2678   ST-920   3171  0.739199  12.787133  1576.239111  0.211290  0.043519   \n",
      "2679   ST-923   3093  0.623343  19.634659  1927.367941  0.251212  0.083737   \n",
      "2680   ST-924   1284  0.695483  24.531931  2649.348396  0.263240  0.080997   \n",
      "2681   ST-925    455  0.670330  20.661538  2763.126703  0.358242  0.019780   \n",
      "2682   ST-926    265  0.724528  19.728302  2727.818491  0.222642  0.037736   \n",
      "2683   ST-927   2807  0.620948  20.082294  2113.340403  0.232989  0.028144   \n",
      "2684   ST-928   1302  0.625960  28.062212  3033.584524  0.277266  0.029954   \n",
      "2685   ST-929    298  0.677852  21.275168  2810.165302  0.187919  0.120805   \n",
      "2686    ST-93   4061  0.698104  20.235656  2518.603044  0.174834  0.030534   \n",
      "2687   ST-930   2889  0.656282  20.278297  2417.381298  0.256490  0.067844   \n",
      "2688   ST-931   1492  0.636729  17.735925  1994.571046  0.262064  0.068365   \n",
      "2689   ST-932   1090  0.726606  24.477064  3125.509807  0.233945  0.036697   \n",
      "2690   ST-933   2690  0.598885  23.969145  2210.533056  0.259108  0.059108   \n",
      "2691   ST-935   4490  0.627394  21.595546  2462.897105  0.244766  0.034298   \n",
      "2692   ST-936   4570  0.628665  20.849672  2198.068961  0.252954  0.091466   \n",
      "2693   ST-937    828  0.676329  20.199275  2807.894251  0.234300  0.095411   \n",
      "2694   ST-938   1076  0.688662  27.909851  4221.435307  0.259294  0.078067   \n",
      "2695   ST-939    145  0.751724  23.275862  3567.874069  0.248276  0.179310   \n",
      "2696    ST-94   3870  0.714470  17.745995  2120.023765  0.229457  0.035142   \n",
      "2697   ST-941    553  0.788427  23.931284  3753.691157  0.294756  0.104882   \n",
      "2698   ST-942   2733  0.601537  17.376509  2116.125163  0.249177  0.069887   \n",
      "2699   ST-943   2358  0.732824  31.137829  2210.241234  0.181934  0.016539   \n",
      "2700   ST-944   2022  0.633531  26.156775  2460.040514  0.191395  0.041048   \n",
      "2701   ST-946   2248  0.777580  18.962189  2324.243372  0.223310  0.050712   \n",
      "2702   ST-947   1902  0.575184  22.133544  2572.800962  0.256572  0.037329   \n",
      "2703   ST-948   2362  0.639289  23.002964  2141.361101  0.245131  0.079170   \n",
      "2704   ST-949   2577  0.575863  25.874272  3005.691529  0.229336  0.038029   \n",
      "2705    ST-95   5021  0.669986  16.097391  2032.863342  0.175065  0.019518   \n",
      "2706   ST-950   2246  0.620214  23.794301  2495.534599  0.235085  0.102850   \n",
      "2707   ST-951   1048  0.802481  28.337786  3194.311565  0.302481  0.050573   \n",
      "2708   ST-952   1758  0.725256  19.296359  1992.790415  0.234926  0.093288   \n",
      "2709   ST-953    296  0.716216  25.861486  3610.956351  0.236486  0.030405   \n",
      "2710   ST-954    889  0.671541  24.691789  3063.032306  0.208099  0.037120   \n",
      "2711   ST-956   1425  0.701754  19.156491  2102.019677  0.183860  0.053333   \n",
      "2712   ST-957    916  0.674672  26.314410  2059.989814  0.180131  0.052402   \n",
      "2713   ST-958   1667  0.684463  26.885423  2621.419124  0.196761  0.029994   \n",
      "2714   ST-959   1753  0.759840  20.552767  2241.884044  0.183685  0.063890   \n",
      "2715    ST-96   1438  0.561892  18.011127  2215.359868  0.234353  0.051460   \n",
      "2716   ST-960    368  0.616848  21.222826  2194.509918  0.236413  0.035326   \n",
      "2717   ST-961    471  0.779193  28.055202  2846.344692  0.180467  0.033970   \n",
      "2718   ST-962    431  0.786543  24.979118  3410.658190  0.148492  0.018561   \n",
      "2719   ST-963   1198  0.655259  22.437396  2479.388623  0.224541  0.034224   \n",
      "2720   ST-964   1799  0.450250  17.464703  2365.369161  0.250139  0.027237   \n",
      "2721   ST-965   2154  0.664345  20.266017  1923.714485  0.266017  0.074745   \n",
      "2722   ST-966    868  0.693548  20.770737  2281.317005  0.185484  0.065668   \n",
      "2723   ST-967   1378  0.750363  14.837446  1623.356030  0.163280  0.005806   \n",
      "2724   ST-968    769  0.574772  32.661899  2824.234967  0.443433  0.019506   \n",
      "2725    ST-97   3706  0.581220  14.827307  1672.436185  0.247437  0.065839   \n",
      "2726   ST-970   1437  0.578984  25.180237  3210.604690  0.257481  0.044537   \n",
      "2727   ST-971   2117  0.660368  27.898914  3938.390628  0.308928  0.043930   \n",
      "2728   ST-972   3702  0.636683  17.902215  1441.431442  0.141005  0.029173   \n",
      "2729   ST-973   1368  0.640351  17.495614  1385.188012  0.122076  0.010234   \n",
      "2730   ST-974   6314  0.662654  16.024865  1469.108492  0.143807  0.025182   \n",
      "2731   ST-975   7631  0.540689  13.582230  1313.931023  0.231162  0.030664   \n",
      "2732   ST-977   1984  0.590222  22.282258  2153.614093  0.199597  0.007056   \n",
      "2733   ST-978   1718  0.596624  23.728172  2238.835000  0.291618  0.019208   \n",
      "2734   ST-979    403  0.650124  18.620347  1987.446675  0.387097  0.027295   \n",
      "2735    ST-98   3697  0.600757  22.756018  2043.934839  0.238301  0.041385   \n",
      "2736   ST-980   2863  0.538247  21.390150  2765.628117  0.314006  0.028292   \n",
      "2737   ST-981    301  0.734219  20.481728  2557.534817  0.149502  0.046512   \n",
      "2738   ST-983   3698  0.603569  20.840725  2410.983464  0.218767  0.035425   \n",
      "2739   ST-984   3645  0.622222  16.716872  1843.668395  0.249657  0.062826   \n",
      "2740   ST-985   2342  0.634927  26.506405  3070.997583  0.233988  0.036721   \n",
      "2741   ST-986    341  0.739003  21.885630  3043.293607  0.334311  0.175953   \n",
      "2742   ST-987   4761  0.590002  17.435623  1613.908918  0.278933  0.082546   \n",
      "2743   ST-988   1879  0.587014  26.898350  2673.448606  0.266099  0.100585   \n",
      "2744    ST-99  16358  0.510392  35.128133  4144.810214  0.355300  0.032094   \n",
      "2745   ST-990    967  0.569804  24.097208  2884.898283  0.255429  0.054809   \n",
      "2746   ST-991    838  0.675418  21.360382  2161.684045  0.114558  0.025060   \n",
      "2747   ST-992   2310  0.644156  23.584848  2891.585359  0.224242  0.035498   \n",
      "2748   ST-993   2288  0.677885  18.303759  1884.028086  0.255682  0.042832   \n",
      "2749   ST-994   4450  0.640225  20.783820  2037.581463  0.224045  0.014607   \n",
      "2750   ST-995    467  0.698073  18.715203  2259.101649  0.241970  0.008565   \n",
      "2751   ST-996   1075  0.709767  20.463256  1966.129544  0.279070  0.097674   \n",
      "2752   ST-997   6979  0.640923  18.015618  1877.363578  0.252472  0.028084   \n",
      "\n",
      "      출근시간대여비율    오전대여비율    점심대여비율    오후대여비율  퇴근시간대여비율    야간대여비율  주중청소년고객비율  \\\n",
      "0     0.045224  0.061867  0.099855  0.183792  0.184877  0.295224   0.020397   \n",
      "1     0.307417  0.080677  0.093689  0.143136  0.155172  0.145413   0.266726   \n",
      "2     0.079389  0.058015  0.087532  0.188126  0.233927  0.318405   0.178105   \n",
      "3     0.142111  0.063218  0.096134  0.153083  0.166667  0.286311   0.129471   \n",
      "4     0.263772  0.059624  0.088788  0.154893  0.149060  0.207388   0.495446   \n",
      "5     0.230641  0.066481  0.076137  0.162674  0.157103  0.220056   0.221771   \n",
      "6     0.233964  0.081692  0.084617  0.189901  0.132190  0.195945   0.207527   \n",
      "7     0.224396  0.066743  0.063867  0.128884  0.127733  0.234753   0.165528   \n",
      "8     0.203585  0.062740  0.068502  0.135083  0.167734  0.236236   0.231298   \n",
      "9     0.174981  0.078183  0.093075  0.177215  0.115041  0.238645   0.262079   \n",
      "10    0.218730  0.071025  0.049026  0.145192  0.121307  0.218102   0.081260   \n",
      "11    0.130602  0.080666  0.044814  0.236876  0.157490  0.220230   0.313600   \n",
      "12    0.177814  0.053290  0.079391  0.109842  0.145188  0.295269   0.031947   \n",
      "13    0.136493  0.058294  0.047393  0.368246  0.109005  0.161611   0.438576   \n",
      "14    0.224078  0.065150  0.075060  0.162599  0.209580  0.194531   0.085151   \n",
      "15    0.157254  0.078627  0.088594  0.145072  0.140642  0.223699   0.163265   \n",
      "16    0.048219  0.047062  0.101582  0.194034  0.181947  0.384724   0.395128   \n",
      "17    0.114147  0.066074  0.094452  0.168149  0.159678  0.329945   0.176166   \n",
      "18    0.111111  0.032774  0.079137  0.234213  0.322142  0.203837   0.160367   \n",
      "19    0.121973  0.081462  0.081682  0.151915  0.170630  0.284456   0.051352   \n",
      "20    0.215686  0.100218  0.098039  0.132898  0.104575  0.237473   0.117117   \n",
      "21    0.037209  0.083721  0.134884  0.158140  0.158140  0.297674   0.067227   \n",
      "22    0.060811  0.081081  0.111486  0.179054  0.125000  0.256757   0.144385   \n",
      "23    0.095376  0.065751  0.089595  0.152457  0.213150  0.278902   0.025763   \n",
      "24    0.166985  0.147901  0.127863  0.228053  0.105916  0.137405   0.067751   \n",
      "25    0.306916  0.100865  0.089337  0.168588  0.135447  0.129683   0.035363   \n",
      "26    0.212053  0.094699  0.099230  0.167648  0.197100  0.191210   0.020697   \n",
      "27    0.091568  0.071146  0.079051  0.129776  0.326746  0.200922   0.018563   \n",
      "28    0.129310  0.077586  0.068966  0.129310  0.081897  0.344828   0.072626   \n",
      "29    0.200637  0.058121  0.066083  0.156847  0.113854  0.223726   0.112190   \n",
      "30    0.197787  0.055325  0.065007  0.138313  0.116183  0.297372   0.099083   \n",
      "31    0.177419  0.062317  0.083578  0.130499  0.208944  0.280059   0.015138   \n",
      "32    0.100968  0.069617  0.096819  0.147994  0.157215  0.327340   0.043478   \n",
      "33    0.144098  0.076194  0.127517  0.161469  0.146861  0.280695   0.101975   \n",
      "34    0.347664  0.078505  0.067290  0.100935  0.110280  0.192523   0.038567   \n",
      "35    0.114958  0.063712  0.094183  0.160665  0.149584  0.257618   0.079922   \n",
      "36    0.078416  0.084710  0.082874  0.180960  0.355625  0.186205   0.077547   \n",
      "37    0.145665  0.074125  0.102224  0.161696  0.190484  0.265471   0.080153   \n",
      "38    0.118644  0.055791  0.071328  0.175141  0.201271  0.313559   0.098723   \n",
      "39    0.239321  0.081334  0.097718  0.167349  0.121709  0.193095   0.058914   \n",
      "40    0.161808  0.059941  0.073698  0.132001  0.150999  0.289224   0.065265   \n",
      "41    0.078901  0.052016  0.070134  0.158192  0.158192  0.383596   0.047593   \n",
      "42    0.175576  0.078227  0.096045  0.130813  0.172968  0.238157   0.054688   \n",
      "43    0.213305  0.079197  0.085533  0.157339  0.131996  0.227033   0.088698   \n",
      "44    0.379971  0.101620  0.051546  0.147275  0.100147  0.145803   0.089354   \n",
      "45    0.233603  0.072844  0.083171  0.174714  0.181133  0.223556   0.009487   \n",
      "46    0.214212  0.070539  0.086100  0.133299  0.109440  0.242739   0.135678   \n",
      "47    0.232432  0.066216  0.081081  0.202703  0.120270  0.193243   0.113636   \n",
      "48    0.079775  0.041295  0.096199  0.193336  0.187705  0.330831   0.324531   \n",
      "49    0.265594  0.092555  0.090543  0.142857  0.124748  0.179074   0.024931   \n",
      "50    0.227437  0.090253  0.104693  0.196751  0.124549  0.166065   0.039702   \n",
      "51    0.245161  0.116129  0.083871  0.158065  0.161290  0.145161   0.133333   \n",
      "52    0.198646  0.064334  0.079007  0.156885  0.141084  0.209932   0.165138   \n",
      "53    0.241039  0.041219  0.111111  0.169355  0.177419  0.195341   0.115294   \n",
      "54    0.185629  0.095808  0.056886  0.179641  0.185629  0.212575   0.032727   \n",
      "55    0.137628  0.071226  0.075199  0.158768  0.137911  0.304058   0.068029   \n",
      "56    0.191382  0.062675  0.070509  0.128334  0.127588  0.300690   0.070695   \n",
      "57    0.228173  0.051931  0.062804  0.191172  0.214054  0.219085   0.065352   \n",
      "58    0.126640  0.067467  0.093464  0.156970  0.220352  0.298713   0.070651   \n",
      "59    0.094691  0.048840  0.079540  0.132700  0.180078  0.370789   0.062752   \n",
      "60    0.213811  0.074329  0.084423  0.173205  0.131911  0.249369   0.214244   \n",
      "61    0.311540  0.069314  0.086362  0.124391  0.128700  0.199326   0.056177   \n",
      "62    0.044367  0.048453  0.090485  0.178050  0.204904  0.363106   0.048756   \n",
      "63    0.099265  0.065960  0.098616  0.159602  0.175173  0.339317   0.025455   \n",
      "64    0.215311  0.055821  0.082935  0.157895  0.161882  0.245614   0.055843   \n",
      "65    0.157937  0.060317  0.087302  0.146032  0.143651  0.288889   0.021253   \n",
      "66    0.171776  0.059725  0.065539  0.140592  0.258985  0.271142   0.005758   \n",
      "67    0.115672  0.079602  0.082090  0.121891  0.155473  0.296020   0.087657   \n",
      "68    0.126305  0.065005  0.091950  0.167733  0.168070  0.294038   0.071749   \n",
      "69    0.168916  0.067076  0.073211  0.156237  0.152147  0.261759   0.091392   \n",
      "70    0.125180  0.058273  0.102518  0.216906  0.238489  0.235971   0.017157   \n",
      "71    0.146526  0.067515  0.067759  0.136252  0.152886  0.329012   0.022468   \n",
      "72    0.217676  0.073650  0.057283  0.198036  0.109656  0.188216   0.054622   \n",
      "73    0.149725  0.064101  0.084053  0.174234  0.219324  0.254203   0.048115   \n",
      "74    0.145981  0.088026  0.073264  0.129579  0.170585  0.274467   0.025992   \n",
      "75    0.190476  0.084249  0.099634  0.140659  0.178755  0.230037   0.009653   \n",
      "76    0.143976  0.119617  0.095694  0.214006  0.177468  0.215746   0.060377   \n",
      "77    0.086957  0.055129  0.080705  0.250639  0.197499  0.295254   0.049849   \n",
      "78    0.133905  0.088061  0.090699  0.166557  0.142150  0.270119   0.035531   \n",
      "79    0.139360  0.119900  0.134965  0.274953  0.139360  0.180163   0.030603   \n",
      "80    0.112227  0.061357  0.090361  0.180500  0.243195  0.268630   0.032347   \n",
      "81    0.137500  0.085484  0.107258  0.229839  0.135081  0.231452   0.240789   \n",
      "82    0.124049  0.072298  0.071791  0.114155  0.138001  0.313293   0.184035   \n",
      "83    0.234934  0.059793  0.074388  0.140301  0.124294  0.218927   0.065615   \n",
      "84    0.165333  0.109333  0.085333  0.192000  0.101333  0.178667   0.028571   \n",
      "85    0.179962  0.077537  0.066050  0.146139  0.144544  0.233248   0.056131   \n",
      "86    0.113231  0.062906  0.089537  0.131474  0.168589  0.307612   0.065455   \n",
      "87    0.049080  0.054569  0.091702  0.177268  0.158541  0.342267   0.041961   \n",
      "88    0.084296  0.058622  0.067180  0.155755  0.154899  0.311938   0.017305   \n",
      "89    0.324548  0.095256  0.084714  0.134789  0.114458  0.176958   0.054611   \n",
      "90    0.148415  0.046110  0.068444  0.146254  0.148415  0.274496   0.026777   \n",
      "91    0.101266  0.079114  0.081487  0.200158  0.183544  0.246835   0.084324   \n",
      "92    0.160321  0.127255  0.086172  0.214429  0.091182  0.167335   0.268015   \n",
      "93    0.084873  0.073580  0.087953  0.198836  0.159480  0.268309   0.080808   \n",
      "94    0.122050  0.074484  0.084808  0.173304  0.130531  0.264749   0.042857   \n",
      "95    0.069740  0.044662  0.071889  0.163602  0.163602  0.331741   0.094370   \n",
      "96    0.197708  0.068768  0.069484  0.137536  0.160458  0.201289   0.042033   \n",
      "97    0.111048  0.063698  0.075536  0.169109  0.188275  0.294250   0.079606   \n",
      "98    0.106649  0.084574  0.092553  0.144415  0.148670  0.284574   0.014354   \n",
      "99    0.135014  0.067914  0.115494  0.216348  0.219601  0.194388   0.022863   \n",
      "100   0.146086  0.071832  0.071832  0.134786  0.186441  0.265537   0.037594   \n",
      "101   0.105687  0.047780  0.078941  0.151909  0.170345  0.330044   0.018538   \n",
      "102   0.106870  0.080153  0.105598  0.226463  0.129771  0.232824   0.084006   \n",
      "103   0.127332  0.079564  0.102403  0.156441  0.148977  0.279445   0.149134   \n",
      "104   0.173575  0.065803  0.109326  0.165285  0.136788  0.249741   0.078545   \n",
      "105   0.204299  0.103989  0.087529  0.144462  0.214756  0.172347   0.010691   \n",
      "106   0.084892  0.107914  0.077698  0.188489  0.162590  0.284892   0.092402   \n",
      "107   0.092190  0.052293  0.097487  0.189564  0.207596  0.279274   0.063887   \n",
      "108   0.177665  0.062364  0.071791  0.137781  0.113851  0.297317   0.114257   \n",
      "109   0.243879  0.083671  0.100829  0.155581  0.113360  0.204743   0.090477   \n",
      "110   0.077816  0.070175  0.090266  0.148274  0.129598  0.379457   0.097522   \n",
      "111   0.094943  0.088737  0.117282  0.200434  0.291654  0.174061   0.072741   \n",
      "112   0.183589  0.074970  0.108619  0.168241  0.148760  0.246163   0.247525   \n",
      "113   0.171011  0.110532  0.120959  0.252346  0.111575  0.190824   0.297372   \n",
      "114   0.101250  0.080000  0.081250  0.191250  0.168750  0.250000   0.176471   \n",
      "115   0.165031  0.087422  0.092774  0.199822  0.166815  0.213202   0.087117   \n",
      "116   0.118534  0.077586  0.133621  0.241379  0.209052  0.185345   0.057971   \n",
      "117   0.154660  0.091870  0.102445  0.191011  0.162591  0.236616   0.041667   \n",
      "118   0.066427  0.076601  0.110114  0.231598  0.213645  0.253142   0.059022   \n",
      "119   0.102703  0.068468  0.082883  0.181982  0.133333  0.315315   0.108491   \n",
      "120   0.181699  0.094771  0.097386  0.149673  0.128105  0.229412   0.054577   \n",
      "121   0.163636  0.067483  0.088462  0.175175  0.203497  0.241958   0.061607   \n",
      "122   0.093784  0.063729  0.100236  0.188513  0.194650  0.279780   0.085052   \n",
      "123   0.189936  0.088944  0.082211  0.152729  0.151665  0.243090   0.026654   \n",
      "124   0.043709  0.027152  0.037748  0.128477  0.327815  0.372185   0.001543   \n",
      "125   0.309378  0.091148  0.049080  0.142857  0.255039  0.128834   0.003012   \n",
      "126   0.408879  0.056504  0.058057  0.085688  0.114561  0.171686   0.008426   \n",
      "127   0.276347  0.074941  0.063232  0.058548  0.107728  0.131148   0.028213   \n",
      "128   0.365410  0.044213  0.053316  0.161248  0.107932  0.172952   0.100503   \n",
      "129   0.367365  0.080279  0.039267  0.110820  0.137871  0.172775   0.059203   \n",
      "130   0.378963  0.056916  0.067003  0.112392  0.100865  0.201009   0.006341   \n",
      "131   0.157895  0.048055  0.084668  0.173913  0.155606  0.276888   0.027273   \n",
      "132   0.053409  0.028904  0.044298  0.092994  0.484134  0.263902   0.004121   \n",
      "133   0.085799  0.055137  0.103012  0.149543  0.131522  0.344271   0.034605   \n",
      "134   0.116027  0.071369  0.083472  0.162354  0.186561  0.301753   0.079714   \n",
      "135   0.276074  0.061350  0.077228  0.132804  0.125226  0.206424   0.068851   \n",
      "136   0.125000  0.071429  0.178571  0.098214  0.116071  0.267857   0.012658   \n",
      "137   0.217391  0.067633  0.085346  0.115942  0.154589  0.173913   0.008602   \n",
      "138   0.190153  0.067912  0.081494  0.125637  0.105263  0.331070   0.002469   \n",
      "139   0.124341  0.086662  0.110776  0.186888  0.219292  0.221552   0.024728   \n",
      "140   0.204545  0.120868  0.154442  0.182851  0.171488  0.134814   0.015763   \n",
      "141   0.156217  0.056854  0.068013  0.137620  0.172689  0.282678   0.022822   \n",
      "142   0.242475  0.080268  0.073579  0.076923  0.225753  0.215719   0.037113   \n",
      "143   0.248322  0.098993  0.078859  0.164430  0.149329  0.192953   0.009390   \n",
      "144   0.183078  0.099198  0.052516  0.133479  0.207877  0.251641   0.012963   \n",
      "145   0.142690  0.076023  0.108772  0.138012  0.271345  0.192982   0.020173   \n",
      "146   0.102780  0.084246  0.133109  0.178602  0.208930  0.229992   0.031488   \n",
      "147   0.201411  0.061520  0.089734  0.120298  0.189263  0.280172   0.030541   \n",
      "148   0.069930  0.209790  0.111888  0.335664  0.202797  0.041958   0.008547   \n",
      "149   0.116117  0.056472  0.085025  0.168782  0.210025  0.304569   0.024476   \n",
      "150   0.128779  0.072228  0.086226  0.152296  0.154535  0.314670   0.028592   \n",
      "151   0.204104  0.053799  0.080422  0.150305  0.171936  0.264559   0.019146   \n",
      "152   0.076125  0.036678  0.067128  0.183391  0.193080  0.311419   0.014299   \n",
      "153   0.091354  0.065253  0.075041  0.133768  0.192496  0.287113   0.004237   \n",
      "154   0.158134  0.056883  0.063709  0.102389  0.248009  0.246871   0.017760   \n",
      "155   0.043720  0.041335  0.069157  0.163752  0.220191  0.295707   0.016931   \n",
      "156   0.167416  0.070787  0.083146  0.144944  0.207865  0.234831   0.014749   \n",
      "157   0.139565  0.106522  0.093043  0.145217  0.207391  0.235217   0.006397   \n",
      "158   0.115804  0.073569  0.110354  0.170300  0.167575  0.311989   0.141509   \n",
      "159   0.170938  0.076652  0.104162  0.174230  0.199859  0.217964   0.017312   \n",
      "160   0.119645  0.112260  0.097489  0.163959  0.248154  0.162482   0.001869   \n",
      "161   0.142692  0.064702  0.116696  0.153668  0.213172  0.256499   0.120289   \n",
      "162   0.130609  0.102564  0.095353  0.193109  0.157051  0.230769   0.044593   \n",
      "163   0.187471  0.064947  0.095808  0.163980  0.197605  0.238139   0.047841   \n",
      "164   0.097074  0.047872  0.049202  0.192819  0.272606  0.297872   0.032028   \n",
      "165   0.179952  0.067045  0.089321  0.175584  0.226687  0.200480   0.019039   \n",
      "166   0.111421  0.052925  0.077994  0.147632  0.167131  0.298050   0.086957   \n",
      "167   0.183835  0.144216  0.104596  0.228209  0.156894  0.153724   0.016129   \n",
      "168   0.182882  0.117200  0.113916  0.169745  0.192939  0.181856   0.006010   \n",
      "169   0.208827  0.115716  0.081808  0.159849  0.116254  0.199677   0.036792   \n",
      "170   0.140761  0.067120  0.067935  0.151630  0.174185  0.267391   0.052689   \n",
      "171   0.202783  0.095427  0.090457  0.161034  0.148608  0.221670   0.039769   \n",
      "172   0.193999  0.072575  0.087927  0.125611  0.180042  0.234473   0.020446   \n",
      "173   0.229571  0.076356  0.078533  0.164936  0.130610  0.212827   0.020317   \n",
      "174   0.168280  0.059858  0.061633  0.151500  0.149080  0.330268   0.073907   \n",
      "175   0.130116  0.089425  0.099834  0.193045  0.202508  0.232079   0.030370   \n",
      "176   0.149116  0.075327  0.076480  0.135665  0.137394  0.306111   0.053801   \n",
      "177   0.030422  0.077711  0.096386  0.349398  0.215361  0.203916   0.090700   \n",
      "178   0.118906  0.067776  0.087990  0.140904  0.123662  0.328181   0.012403   \n",
      "179   0.166105  0.069140  0.085160  0.133642  0.121417  0.313659   0.069026   \n",
      "180   0.070861  0.056200  0.091631  0.144777  0.143250  0.364692   0.059792   \n",
      "181   0.198737  0.082838  0.083210  0.180906  0.120357  0.250371   0.023256   \n",
      "182   0.182005  0.050386  0.061183  0.162468  0.111054  0.272494   0.108801   \n",
      "183   0.257040  0.076534  0.079422  0.154513  0.128520  0.214440   0.056497   \n",
      "184   0.281843  0.081301  0.130081  0.195122  0.081301  0.143631   0.014493   \n",
      "185   0.124348  0.087863  0.065525  0.186895  0.153388  0.265823   0.067568   \n",
      "186   0.146465  0.097222  0.103535  0.135101  0.157828  0.241162   0.039724   \n",
      "187   0.167892  0.117423  0.100431  0.172711  0.267816  0.144053   0.011786   \n",
      "188   0.242779  0.049961  0.069477  0.106167  0.088993  0.212334   0.100223   \n",
      "189   0.269113  0.068807  0.076453  0.111621  0.102446  0.240061   0.050000   \n",
      "190   0.195900  0.060364  0.076310  0.134396  0.117312  0.306378   0.069277   \n",
      "191   0.123134  0.083582  0.075373  0.155224  0.138060  0.229104   0.060254   \n",
      "192   0.160113  0.063932  0.080339  0.137765  0.151909  0.261952   0.044355   \n",
      "193   0.321311  0.131148  0.075410  0.137705  0.160656  0.124590   0.055319   \n",
      "194   0.188630  0.049096  0.033592  0.087855  0.142119  0.227390   0.072202   \n",
      "195   0.234167  0.084583  0.083333  0.129583  0.212917  0.171250   0.139069   \n",
      "196   0.279200  0.084731  0.091497  0.216534  0.117387  0.130038   0.255121   \n",
      "197   0.214171  0.063446  0.096296  0.101449  0.162963  0.272142   0.037415   \n",
      "198   0.215693  0.068978  0.102190  0.202190  0.160584  0.214599   0.130435   \n",
      "199   0.197553  0.065247  0.068419  0.096058  0.130494  0.302673   0.031727   \n",
      "200   0.131114  0.045565  0.076314  0.175259  0.279480  0.270043   0.025528   \n",
      "201   0.181954  0.079791  0.093587  0.132364  0.330350  0.135347   0.028607   \n",
      "202   0.138369  0.054849  0.055597  0.239092  0.157317  0.293194   0.426632   \n",
      "203   0.149390  0.055894  0.073171  0.164634  0.160569  0.318089   0.194767   \n",
      "204   0.245107  0.060267  0.059646  0.222429  0.109661  0.220876   0.321857   \n",
      "205   0.218004  0.086768  0.111714  0.245119  0.169197  0.106291   0.195804   \n",
      "206   0.149894  0.087394  0.140890  0.191208  0.220869  0.157309   0.020699   \n",
      "207   0.232404  0.047809  0.086321  0.159363  0.110226  0.197875   0.121547   \n",
      "208   0.113095  0.104167  0.116071  0.312500  0.104167  0.187500   0.479245   \n",
      "209   0.063291  0.091139  0.065823  0.172152  0.118987  0.273418   0.076190   \n",
      "210   0.249724  0.061878  0.059669  0.135912  0.129282  0.256354   0.055882   \n",
      "211   0.119187  0.057444  0.083236  0.123095  0.168034  0.309105   0.156925   \n",
      "212   0.216370  0.056584  0.063701  0.160854  0.169395  0.269395   0.032075   \n",
      "213   0.254633  0.062853  0.066882  0.107977  0.162772  0.208703   0.059296   \n",
      "214   0.232207  0.040121  0.050838  0.179170  0.208299  0.229459   0.091778   \n",
      "215   0.115924  0.114437  0.110616  0.173885  0.346921  0.117834   0.003545   \n",
      "216   0.218147  0.106178  0.142857  0.208494  0.063707  0.137066   0.050119   \n",
      "217   0.291476  0.110350  0.064688  0.118721  0.146119  0.187215   0.094488   \n",
      "218   0.158879  0.065421  0.076324  0.135514  0.165109  0.204050   0.012000   \n",
      "219   0.124274  0.053426  0.092915  0.164925  0.195122  0.232288   0.009160   \n",
      "220   0.105072  0.049517  0.118357  0.140097  0.194444  0.291063   0.062696   \n",
      "221   0.250000  0.094298  0.125000  0.076754  0.111842  0.171053   0.024390   \n",
      "222   0.160000  0.045636  0.075189  0.145567  0.173196  0.323162   0.043122   \n",
      "223   0.105872  0.134342  0.096975  0.162811  0.255338  0.217972   0.007143   \n",
      "224   0.069401  0.070978  0.131703  0.182177  0.312303  0.199527   0.011364   \n",
      "225   0.160364  0.068382  0.089757  0.130960  0.185898  0.290357   0.027041   \n",
      "226   0.096774  0.115207  0.102535  0.237327  0.173963  0.184332   0.117566   \n",
      "227   0.275604  0.063846  0.079573  0.163640  0.164576  0.157836   0.185891   \n",
      "228   0.195748  0.081311  0.071568  0.182285  0.158547  0.222321   0.283800   \n",
      "229   0.099716  0.060795  0.097727  0.150000  0.134659  0.291477   0.012528   \n",
      "230   0.125525  0.090424  0.124762  0.152232  0.284243  0.192675   0.013116   \n",
      "231   0.084189  0.049281  0.078029  0.158111  0.131417  0.320329   0.048295   \n",
      "232   0.105967  0.057613  0.078189  0.119342  0.113169  0.349794   0.051502   \n",
      "233   0.194172  0.050372  0.069010  0.144037  0.184499  0.285124   0.017375   \n",
      "234   0.119189  0.071006  0.088757  0.136517  0.124260  0.314032   0.022834   \n",
      "235   0.260951  0.066886  0.066415  0.114461  0.100801  0.234574   0.007161   \n",
      "236   0.230511  0.083155  0.069398  0.111281  0.126567  0.237236   0.044776   \n",
      "237   0.083840  0.105711  0.160389  0.253949  0.155529  0.200486   0.021779   \n",
      "238   0.101232  0.076232  0.077113  0.130106  0.164613  0.326056   0.030193   \n",
      "239   0.180835  0.055641  0.078053  0.149150  0.102782  0.268934   0.032874   \n",
      "240   0.088612  0.044840  0.064413  0.123843  0.123488  0.315302   0.013462   \n",
      "241   0.195494  0.070245  0.065606  0.140490  0.135852  0.311465   0.268577   \n",
      "242   0.103929  0.034221  0.062104  0.112801  0.141318  0.325095   0.088210   \n",
      "243   0.175540  0.054012  0.085648  0.163194  0.226466  0.224151   0.054854   \n",
      "244   0.217076  0.096341  0.088312  0.160877  0.136946  0.218002   0.058023   \n",
      "245   0.215325  0.049467  0.045587  0.090204  0.258972  0.239573   0.041433   \n",
      "246   0.044702  0.041391  0.052980  0.107616  0.322848  0.319536   0.000000   \n",
      "247   0.165782  0.078581  0.086207  0.162135  0.135942  0.290119   0.061317   \n",
      "248   0.072264  0.063074  0.097536  0.246658  0.225773  0.223058   0.063817   \n",
      "249   0.089940  0.084884  0.092288  0.274156  0.145205  0.224129   0.037341   \n",
      "250   0.201342  0.038031  0.051454  0.123043  0.080537  0.382550   0.190000   \n",
      "251   0.124955  0.064620  0.081042  0.192074  0.151732  0.327026   0.369307   \n",
      "252   0.142760  0.092454  0.100612  0.144799  0.146839  0.227736   0.094851   \n",
      "253   0.203585  0.078458  0.076767  0.136625  0.151167  0.216097   0.179362   \n",
      "254   0.131955  0.066574  0.109499  0.189984  0.168521  0.279213   0.097374   \n",
      "255   0.136398  0.058277  0.081387  0.170811  0.149962  0.290379   0.171607   \n",
      "256   0.185387  0.085787  0.097056  0.205016  0.113413  0.220647   0.186448   \n",
      "257   0.166080  0.104152  0.146376  0.237861  0.126671  0.168191   0.063683   \n",
      "258   0.252140  0.076265  0.090272  0.144747  0.096498  0.167315   0.077007   \n",
      "259   0.091276  0.099154  0.100692  0.238470  0.164489  0.255188   0.133769   \n",
      "260   0.175202  0.111186  0.088949  0.205526  0.094340  0.281671   0.132479   \n",
      "261   0.176250  0.105000  0.092500  0.161250  0.122500  0.215000   0.038869   \n",
      "262   0.195142  0.075377  0.087102  0.211893  0.096315  0.182580   0.134328   \n",
      "263   0.104891  0.065217  0.073370  0.159783  0.167935  0.304348   0.180045   \n",
      "264   0.177950  0.122824  0.109284  0.211799  0.158607  0.126692   0.029024   \n",
      "265   0.212537  0.059745  0.061704  0.108717  0.178257  0.274731   0.018253   \n",
      "266   0.201830  0.054398  0.079309  0.180986  0.163701  0.216573   0.029221   \n",
      "267   0.094641  0.095781  0.148233  0.287913  0.225200  0.135690   0.013344   \n",
      "268   0.239264  0.073094  0.083961  0.133041  0.140228  0.243120   0.072437   \n",
      "269   0.093658  0.065519  0.063419  0.154977  0.156237  0.322974   0.082036   \n",
      "270   0.126831  0.078242  0.108253  0.147553  0.170061  0.291175   0.024878   \n",
      "271   0.137773  0.118255  0.096441  0.204363  0.214696  0.188289   0.037846   \n",
      "272   0.166667  0.078171  0.061947  0.185841  0.150442  0.213864   0.075614   \n",
      "273   0.179825  0.052632  0.063596  0.140351  0.201754  0.203947   0.008357   \n",
      "274   0.112179  0.108974  0.115385  0.102564  0.285256  0.214744   0.016129   \n",
      "275   0.347619  0.074603  0.065079  0.141270  0.130159  0.192063   0.055066   \n",
      "276   0.052632  0.105263  0.105263  0.052632  0.078947  0.184211   0.037037   \n",
      "277   0.074627  0.119403  0.149254  0.253731  0.149254  0.194030   0.038462   \n",
      "278   0.402778  0.083333  0.097222  0.152778  0.041667  0.166667   0.000000   \n",
      "279   0.165644  0.085890  0.073620  0.110429  0.110429  0.288344   0.038462   \n",
      "280   0.105135  0.080555  0.090290  0.177415  0.191044  0.285471   0.018390   \n",
      "281   0.176906  0.091607  0.121503  0.162644  0.222161  0.187329   0.009875   \n",
      "282   0.183308  0.084413  0.085366  0.165587  0.144817  0.241616   0.142715   \n",
      "283   0.207924  0.052828  0.064003  0.102608  0.198442  0.247545   0.014279   \n",
      "284   0.134345  0.051788  0.080173  0.129361  0.141278  0.343012   0.051821   \n",
      "285   0.090211  0.155470  0.099808  0.362764  0.218810  0.069098   0.015251   \n",
      "286   0.072585  0.083752  0.078727  0.174204  0.165271  0.310999   0.036576   \n",
      "287   0.119565  0.047591  0.063749  0.164806  0.192421  0.318155   0.029851   \n",
      "288   0.313697  0.094256  0.072165  0.148748  0.138439  0.179676   0.063158   \n",
      "289   0.018657  0.044776  0.093284  0.186567  0.220149  0.335821   0.005882   \n",
      "290   0.108271  0.069925  0.115789  0.214286  0.115789  0.251880   0.250538   \n",
      "291   0.218182  0.084091  0.080303  0.126010  0.134343  0.231566   0.044607   \n",
      "292   0.130800  0.055600  0.094400  0.150400  0.194400  0.301600   0.057797   \n",
      "293   0.092578  0.058839  0.067476  0.364912  0.134413  0.228880   0.507478   \n",
      "294   0.113203  0.058459  0.087193  0.151845  0.163488  0.329205   0.034387   \n",
      "295   0.182667  0.086000  0.074222  0.146444  0.145778  0.287111   0.132348   \n",
      "296   0.101060  0.069965  0.094346  0.138516  0.158304  0.323322   0.022146   \n",
      "297   0.278928  0.071025  0.086548  0.188147  0.118532  0.170743   0.188943   \n",
      "298   0.205670  0.075773  0.079897  0.141237  0.137113  0.258763   0.045897   \n",
      "299   0.165684  0.156250  0.122642  0.181604  0.172759  0.173939   0.005548   \n",
      "300   0.267610  0.088874  0.065504  0.124753  0.147795  0.221856   0.040931   \n",
      "301   0.134703  0.065068  0.079528  0.149543  0.183029  0.317732   0.028204   \n",
      "302   0.110280  0.086604  0.061682  0.159502  0.206231  0.305296   0.031746   \n",
      "303   0.121313  0.055671  0.066473  0.176984  0.221437  0.274200   0.033796   \n",
      "304   0.125000  0.041667  0.145833  0.319444  0.159722  0.149306   0.303318   \n",
      "305   0.219385  0.078932  0.079512  0.141613  0.116657  0.181080   0.169622   \n",
      "306   0.130309  0.068454  0.097732  0.143711  0.132577  0.311134   0.034206   \n",
      "307   0.064655  0.170259  0.163793  0.176724  0.163793  0.245690   0.015038   \n",
      "308   0.124825  0.100699  0.110839  0.204895  0.197902  0.213636   0.033218   \n",
      "309   0.108603  0.054496  0.067341  0.291553  0.216037  0.218373   0.161025   \n",
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      "814   0.169713  0.129896  0.110313  0.132507  0.161227  0.248695   0.002383   \n",
      "815   0.178010  0.060583  0.079656  0.148467  0.182872  0.284218   0.098715   \n",
      "816   0.148270  0.064250  0.065898  0.152389  0.185338  0.261944   0.028377   \n",
      "817   0.137901  0.054640  0.070252  0.170859  0.173461  0.313964   0.031653   \n",
      "818   0.074658  0.053628  0.132492  0.154574  0.200841  0.307571   0.022869   \n",
      "819   0.223594  0.102881  0.089163  0.212620  0.159122  0.172840   0.017921   \n",
      "820   0.239018  0.076227  0.102067  0.162791  0.142119  0.204134   0.042623   \n",
      "821   0.226555  0.076137  0.106778  0.137419  0.153203  0.225627   0.037253   \n",
      "822   0.173410  0.083815  0.078035  0.147399  0.138728  0.323699   0.018797   \n",
      "823   0.105402  0.077734  0.069829  0.129117  0.172596  0.271410   0.047700   \n",
      "824   0.156731  0.082692  0.074038  0.157692  0.137500  0.262500   0.014688   \n",
      "825   0.147074  0.078198  0.101502  0.207147  0.149146  0.264630   0.045031   \n",
      "826   0.062286  0.059548  0.091034  0.186858  0.164271  0.336756   0.097816   \n",
      "827   0.035863  0.036812  0.054269  0.179507  0.214801  0.391082   0.126819   \n",
      "828   0.014577  0.107872  0.037901  0.172012  0.204082  0.384840   0.067961   \n",
      "829   0.080858  0.073432  0.089109  0.143564  0.201320  0.351485   0.025290   \n",
      "830   0.082422  0.097009  0.084610  0.152443  0.242888  0.242888   0.024201   \n",
      "831   0.102733  0.078228  0.084826  0.155042  0.194156  0.311970   0.035783   \n",
      "832   0.153028  0.081368  0.098012  0.163662  0.171059  0.244105   0.021518   \n",
      "833   0.073864  0.056818  0.073864  0.210227  0.363636  0.166667   0.014815   \n",
      "834   0.062176  0.072539  0.080311  0.196891  0.292746  0.256477   0.044280   \n",
      "835   0.132877  0.065753  0.071233  0.172603  0.180822  0.284932   0.083164   \n",
      "836   0.224913  0.055363  0.083045  0.204152  0.138408  0.276817   0.004292   \n",
      "837   0.127767  0.069576  0.082859  0.141050  0.251739  0.259962   0.013072   \n",
      "838   0.132161  0.077387  0.096482  0.174874  0.149246  0.293970   0.060811   \n",
      "839   0.142005  0.073713  0.084011  0.163686  0.172900  0.234688   0.028530   \n",
      "840   0.180791  0.090395  0.129944  0.220339  0.129944  0.175141   0.000000   \n",
      "841   0.129052  0.047419  0.094838  0.125450  0.179472  0.285114   0.012579   \n",
      "842   0.083214  0.110473  0.169297  0.252511  0.255380  0.106169   0.013333   \n",
      "843   0.095406  0.067138  0.060071  0.180212  0.141343  0.194346   0.035503   \n",
      "844   0.393404  0.044170  0.075972  0.128386  0.104240  0.181390   0.008746   \n",
      "845   0.392713  0.048583  0.068826  0.134953  0.110661  0.107962   0.010435   \n",
      "846   0.139683  0.053968  0.074603  0.133333  0.117460  0.376190   0.075975   \n",
      "847   0.103618  0.067434  0.074013  0.180921  0.162829  0.379934   0.008584   \n",
      "848   0.254753  0.087452  0.106464  0.178707  0.140684  0.171103   0.040816   \n",
      "849   0.180402  0.032800  0.043631  0.091903  0.304899  0.294275   0.009295   \n",
      "850   0.367534  0.035222  0.045942  0.125574  0.163859  0.182236   0.063063   \n",
      "851   0.138956  0.097694  0.085558  0.140777  0.229976  0.216626   0.003897   \n",
      "852   0.170854  0.060302  0.062186  0.114322  0.116834  0.408920   0.021978   \n",
      "853   0.270864  0.081991  0.087848  0.121523  0.132504  0.185212   0.088487   \n",
      "854   0.167355  0.084711  0.097107  0.200413  0.173554  0.198347   0.066007   \n",
      "855   0.123967  0.066116  0.086777  0.239669  0.185950  0.247934   0.057143   \n",
      "856   0.492537  0.037313  0.063433  0.130597  0.104478  0.089552   0.048780   \n",
      "857   0.103723  0.074468  0.103723  0.170213  0.122340  0.343085   0.022989   \n",
      "858   0.167116  0.075472  0.118598  0.210243  0.099730  0.242588   0.068000   \n",
      "859   0.196429  0.089286  0.107143  0.169643  0.142857  0.250000   0.040000   \n",
      "860   0.183917  0.118232  0.123010  0.166003  0.173169  0.180334   0.003333   \n",
      "861   0.206349  0.068783  0.089947  0.248677  0.169312  0.164021   0.036232   \n",
      "862   0.183552  0.089392  0.076281  0.135876  0.134684  0.270560   0.094059   \n",
      "863   0.307317  0.043902  0.078049  0.224390  0.097561  0.200000   0.057325   \n",
      "864   0.350282  0.047081  0.056497  0.124294  0.099812  0.212806   0.007732   \n",
      "865   0.175810  0.063591  0.088529  0.130923  0.265586  0.192020   0.010239   \n",
      "866   0.101695  0.152542  0.107345  0.175141  0.271186  0.135593   0.008000   \n",
      "867   0.084488  0.051247  0.066482  0.163435  0.127424  0.373961   0.343750   \n",
      "868   0.171965  0.115607  0.085260  0.143064  0.154624  0.245665   0.148148   \n",
      "869   0.350547  0.067436  0.054678  0.101458  0.140948  0.146416   0.315234   \n",
      "870   0.039801  0.042289  0.054726  0.146766  0.261194  0.350746   0.006734   \n",
      "871   0.383643  0.061710  0.055762  0.118959  0.099628  0.125651   0.128638   \n",
      "872   0.278960  0.057920  0.062254  0.113081  0.140268  0.242711   0.148731   \n",
      "873   0.283146  0.067416  0.068539  0.139326  0.160674  0.205618   0.105263   \n",
      "874   0.067687  0.053561  0.070630  0.277222  0.323131  0.163626   0.173213   \n",
      "875   0.125151  0.049507  0.083261  0.158041  0.220703  0.315562   0.050288   \n",
      "876   0.341748  0.075728  0.075728  0.097087  0.114563  0.155340   0.082262   \n",
      "877   0.371009  0.050043  0.037101  0.108714  0.125971  0.208801   0.225877   \n",
      "878   0.340034  0.033501  0.045226  0.145729  0.120603  0.227806   0.045767   \n",
      "879   0.199866  0.077302  0.095451  0.132646  0.169169  0.251176   0.020299   \n",
      "880   0.275362  0.052174  0.060870  0.127536  0.220290  0.223188   0.007491   \n",
      "881   0.185890  0.050392  0.080627  0.111982  0.152296  0.210526   0.008902   \n",
      "882   0.198743  0.040848  0.055774  0.129615  0.304792  0.235664   0.002915   \n",
      "883   0.020871  0.043557  0.071688  0.151543  0.213249  0.428312   0.069421   \n",
      "884   0.129875  0.082648  0.093023  0.168873  0.260465  0.207513   0.093328   \n",
      "885   0.178862  0.076461  0.091754  0.152342  0.152149  0.268873   0.072229   \n",
      "886   0.291313  0.074599  0.059962  0.135033  0.115675  0.245515   0.046512   \n",
      "887   0.136544  0.087819  0.083853  0.124646  0.171105  0.209632   0.024682   \n",
      "888   0.254816  0.091635  0.087507  0.166758  0.124106  0.197578   0.094985   \n",
      "889   0.164596  0.071429  0.085016  0.134317  0.221273  0.237189   0.079980   \n",
      "890   0.220339  0.066667  0.066667  0.133898  0.218644  0.219209   0.119917   \n",
      "891   0.104758  0.069788  0.097704  0.144379  0.140928  0.307669   0.031015   \n",
      "892   0.281773  0.077759  0.071906  0.149666  0.107023  0.125418   0.129464   \n",
      "893   0.184481  0.064330  0.080100  0.132165  0.183980  0.253066   0.101511   \n",
      "894   0.219628  0.080880  0.066328  0.126227  0.115398  0.218274   0.031615   \n",
      "895   0.297166  0.074089  0.085020  0.134008  0.129555  0.173684   0.089696   \n",
      "896   0.296161  0.082267  0.054845  0.082267  0.179159  0.221207   0.002232   \n",
      "897   0.240577  0.053500  0.063401  0.161369  0.192809  0.235366   0.040541   \n",
      "898   0.207653  0.082975  0.088994  0.153482  0.123818  0.217111   0.083956   \n",
      "899   0.106589  0.060724  0.093669  0.144057  0.211240  0.335271   0.105307   \n",
      "900   0.415139  0.075697  0.069323  0.160159  0.109163  0.120319   0.302251   \n",
      "901   0.077808  0.041949  0.102616  0.180875  0.179296  0.325214   0.268948   \n",
      "902   0.049502  0.049082  0.090194  0.223073  0.232722  0.321552   0.108625   \n",
      "903   0.191159  0.062452  0.091344  0.172260  0.172803  0.247312   0.148280   \n",
      "904   0.108773  0.074599  0.096062  0.142321  0.210877  0.302355   0.171812   \n",
      "905   0.108929  0.058482  0.076786  0.118750  0.179018  0.339732   0.032297   \n",
      "906   0.033002  0.041907  0.087742  0.160031  0.177842  0.393662   0.032923   \n",
      "907   0.124224  0.061335  0.078416  0.131988  0.162267  0.339286   0.028896   \n",
      "908   0.139219  0.047538  0.080645  0.149406  0.168930  0.298812   0.080447   \n",
      "909   0.176111  0.073889  0.077778  0.258333  0.126667  0.177778   0.287661   \n",
      "910   0.132270  0.058161  0.057223  0.157598  0.245779  0.253283   0.120253   \n",
      "911   0.244624  0.066052  0.066820  0.119048  0.144393  0.210061   0.166920   \n",
      "912   0.200622  0.081285  0.079953  0.165235  0.152946  0.234380   0.179383   \n",
      "913   0.188955  0.077179  0.098248  0.191617  0.171878  0.220226   0.118924   \n",
      "914   0.282877  0.060252  0.084944  0.133655  0.157407  0.170827   0.195912   \n",
      "915   0.333333  0.065664  0.056140  0.107769  0.123810  0.215038   0.415265   \n",
      "916   0.159144  0.063751  0.082364  0.142392  0.183341  0.250349   0.024818   \n",
      "917   0.098575  0.073789  0.107123  0.160304  0.254796  0.278443   0.180022   \n",
      "918   0.141093  0.062886  0.096730  0.153442  0.155500  0.316945   0.281467   \n",
      "919   0.290965  0.078158  0.074627  0.171562  0.141229  0.138822   0.249734   \n",
      "920   0.190616  0.065103  0.088563  0.165396  0.233627  0.214858   0.118669   \n",
      "921   0.121228  0.050231  0.093007  0.188853  0.158857  0.343450   0.235250   \n",
      "922   0.063890  0.063472  0.109302  0.193757  0.213697  0.318092   0.133323   \n",
      "923   0.122499  0.068326  0.092728  0.129331  0.189361  0.311371   0.065232   \n",
      "924   0.115727  0.050445  0.097923  0.195846  0.163205  0.181009   0.141762   \n",
      "925   0.120342  0.058644  0.086133  0.138465  0.194869  0.306659   0.032778   \n",
      "926   0.145112  0.060807  0.087892  0.190314  0.169686  0.311749   0.107434   \n",
      "927   0.267442  0.072558  0.099070  0.157209  0.167442  0.153488   0.344148   \n",
      "928   0.271132  0.070193  0.088730  0.157192  0.139644  0.195255   0.097204   \n",
      "929   0.102644  0.072162  0.090980  0.196112  0.210731  0.286003   0.073092   \n",
      "930   0.166741  0.075751  0.078440  0.155087  0.144330  0.297176   0.042310   \n",
      "931   0.202532  0.076854  0.084087  0.169078  0.168174  0.213382   0.111500   \n",
      "932   0.295611  0.057309  0.060573  0.132028  0.092492  0.189336   0.202370   \n",
      "933   0.130689  0.074122  0.098830  0.156047  0.124837  0.265280   0.110694   \n",
      "934   0.340621  0.045963  0.047205  0.136149  0.119255  0.212174   0.112840   \n",
      "935   0.163256  0.055349  0.066047  0.135349  0.182791  0.284186   0.008782   \n",
      "936   0.194290  0.047099  0.078736  0.122790  0.219559  0.275240   0.031303   \n",
      "937   0.041537  0.067497  0.065421  0.131880  0.521288  0.130841   0.006757   \n",
      "938   0.040598  0.066383  0.059114  0.153614  0.448224  0.206830   0.005270   \n",
      "939   0.301259  0.071888  0.072727  0.154685  0.114685  0.191329   0.228082   \n",
      "940   0.065616  0.047301  0.076445  0.163561  0.373308  0.248447   0.026472   \n",
      "941   0.174443  0.056027  0.107989  0.132202  0.183457  0.277660   0.016901   \n",
      "942   0.248715  0.061249  0.075905  0.109155  0.169419  0.219950   0.023816   \n",
      "943   0.124054  0.067238  0.089427  0.168432  0.160027  0.316860   0.178699   \n",
      "944   0.119884  0.056514  0.084147  0.136505  0.204654  0.306669   0.016157   \n",
      "945   0.182457  0.074881  0.077870  0.106697  0.204254  0.257515   0.007415   \n",
      "946   0.292690  0.078931  0.065111  0.097666  0.248771  0.168305   0.002530   \n",
      "947   0.087152  0.107817  0.099730  0.247978  0.238095  0.199012   0.042751   \n",
      "948   0.144609  0.087123  0.068217  0.139244  0.408533  0.140521   0.006132   \n",
      "949   0.192194  0.040360  0.034862  0.076128  0.181620  0.405837   0.021404   \n",
      "950   0.104125  0.063455  0.071820  0.102971  0.248918  0.331410   0.012829   \n",
      "951   0.076373  0.037240  0.078687  0.130234  0.178203  0.395540   0.055003   \n",
      "952   0.263135  0.065357  0.076890  0.225545  0.098676  0.222127   0.444002   \n",
      "953   0.329343  0.076427  0.082259  0.145488  0.109883  0.120012   0.171280   \n",
      "954   0.129637  0.051162  0.064003  0.147574  0.232980  0.290664   0.052092   \n",
      "955   0.294144  0.078773  0.093082  0.143236  0.116831  0.143531   0.120747   \n",
      "956   0.147152  0.104970  0.110545  0.258182  0.219152  0.150545   0.040648   \n",
      "957   0.124396  0.066727  0.072162  0.118961  0.126510  0.314614   0.078724   \n",
      "958   0.250726  0.059624  0.071243  0.154105  0.124446  0.217245   0.189754   \n",
      "959   0.151154  0.127820  0.073632  0.100596  0.113819  0.413793   0.018562   \n",
      "960   0.311948  0.079164  0.083873  0.159800  0.117422  0.130959   0.139245   \n",
      "961   0.231114  0.117427  0.098978  0.114685  0.082772  0.318624   0.031045   \n",
      "962   0.199838  0.071342  0.083908  0.149574  0.168221  0.222537   0.025070   \n",
      "963   0.204242  0.067557  0.093480  0.151610  0.111548  0.234878   0.151270   \n",
      "964   0.206132  0.060105  0.075837  0.119403  0.114562  0.283582   0.145135   \n",
      "965   0.317225  0.091582  0.105222  0.125487  0.118472  0.141076   0.171414   \n",
      "966   0.313964  0.085754  0.085286  0.135426  0.115745  0.142455   0.192403   \n",
      "967   0.177485  0.143002  0.101420  0.130832  0.150101  0.242394   0.032624   \n",
      "968   0.166400  0.050400  0.067200  0.118800  0.140800  0.334000   0.014123   \n",
      "969   0.102238  0.045634  0.078982  0.169811  0.125055  0.386134   0.277027   \n",
      "970   0.151163  0.074128  0.056686  0.414244  0.101744  0.106105   0.345361   \n",
      "971   0.075749  0.069922  0.073252  0.228357  0.194506  0.252497   0.026744   \n",
      "972   0.129225  0.091197  0.077465  0.142606  0.153169  0.284859   0.053237   \n",
      "973   0.105657  0.063808  0.088091  0.164557  0.167140  0.278998   0.036998   \n",
      "974   0.077508  0.061816  0.092725  0.168331  0.141227  0.369472   0.105718   \n",
      "975   0.138521  0.074319  0.097665  0.217121  0.134241  0.270428   0.302449   \n",
      "976   0.250074  0.074874  0.106540  0.142350  0.128144  0.217816   0.053944   \n",
      "977   0.055495  0.106094  0.110990  0.295974  0.238847  0.151251   0.000605   \n",
      "978   0.102093  0.108374  0.179388  0.242512  0.135266  0.171498   0.014916   \n",
      "979   0.163442  0.094196  0.074338  0.219450  0.133401  0.201120   0.208741   \n",
      "980   0.050474  0.072157  0.118622  0.236334  0.189869  0.278061   0.098334   \n",
      "981   0.110656  0.070843  0.072600  0.156323  0.145199  0.333138   0.132721   \n",
      "982   0.146433  0.080754  0.109825  0.198654  0.134859  0.254105   0.183622   \n",
      "983   0.178660  0.078908  0.075931  0.177667  0.135484  0.209429   0.059406   \n",
      "984   0.074407  0.068956  0.097029  0.193241  0.164350  0.356773   0.061017   \n",
      "985   0.115426  0.093851  0.081985  0.154261  0.155340  0.240561   0.039660   \n",
      "986   0.103645  0.073342  0.066755  0.168204  0.146245  0.309618   0.124405   \n",
      "987   0.121060  0.055874  0.096705  0.248567  0.202722  0.214900   0.044809   \n",
      "988   0.147059  0.062325  0.079832  0.132353  0.123249  0.301821   0.099617   \n",
      "989   0.190231  0.118895  0.100257  0.109897  0.125964  0.222365   0.078111   \n",
      "990   0.083897  0.052774  0.075101  0.160352  0.148850  0.336265   0.028837   \n",
      "991   0.175613  0.071809  0.081052  0.134732  0.157483  0.307856   0.028861   \n",
      "992   0.169318  0.093750  0.081818  0.151705  0.161364  0.254545   0.012953   \n",
      "993   0.088632  0.057803  0.075145  0.263969  0.121387  0.238921   0.104061   \n",
      "994   0.114471  0.077754  0.095032  0.179266  0.198704  0.245140   0.029985   \n",
      "995   0.160142  0.056940  0.104093  0.186833  0.145907  0.235765   0.026250   \n",
      "996   0.168449  0.087344  0.093583  0.116756  0.210339  0.200535   0.068182   \n",
      "997   0.147573  0.077670  0.081553  0.209709  0.087379  0.166990   0.059432   \n",
      "998   0.152448  0.070104  0.072329  0.131677  0.117953  0.308976   0.074781   \n",
      "999   0.121689  0.078828  0.103381  0.162180  0.164118  0.264915   0.016008   \n",
      "1000  0.079817  0.076767  0.111337  0.164209  0.204372  0.252669   0.061123   \n",
      "1001  0.205820  0.072121  0.095318  0.140447  0.132434  0.240405   0.140321   \n",
      "1002  0.120192  0.087740  0.069712  0.155048  0.175481  0.221154   0.074913   \n",
      "1003  0.133005  0.079521  0.104152  0.213934  0.149894  0.237861   0.242181   \n",
      "1004  0.132701  0.042654  0.065403  0.141232  0.141232  0.291943   0.198693   \n",
      "1005  0.103417  0.076439  0.071942  0.143885  0.145683  0.287770   0.156410   \n",
      "1006  0.210654  0.055690  0.076271  0.135593  0.119855  0.251816   0.158784   \n",
      "1007  0.233203  0.071521  0.084525  0.127438  0.187690  0.248808   0.005482   \n",
      "1008  0.060117  0.049853  0.083578  0.172287  0.192082  0.344575   0.140082   \n",
      "1009  0.244000  0.048000  0.032000  0.152000  0.152000  0.148000   0.216080   \n",
      "1010  0.175781  0.067383  0.095703  0.172852  0.119141  0.254883   0.022989   \n",
      "1011  0.076175  0.059968  0.095219  0.188412  0.207050  0.300243   0.032609   \n",
      "1012  0.088810  0.086146  0.081705  0.139432  0.144760  0.309059   0.032995   \n",
      "1013  0.118293  0.054878  0.068293  0.163415  0.181707  0.275610   0.026578   \n",
      "1014  0.155543  0.107005  0.128516  0.170436  0.163817  0.207943   0.039318   \n",
      "1015  0.132333  0.102319  0.092087  0.145975  0.208049  0.261255   0.026094   \n",
      "1016  0.155822  0.087329  0.075342  0.214041  0.198630  0.171233   0.035545   \n",
      "1017  0.088083  0.081606  0.090026  0.121762  0.136010  0.303756   0.037931   \n",
      "1018  0.088260  0.095861  0.091639  0.180743  0.154561  0.293074   0.042301   \n",
      "1019  0.113896  0.078276  0.077397  0.131047  0.138083  0.309147   0.012419   \n",
      "1020  0.106856  0.055343  0.092110  0.185370  0.200306  0.259288   0.034070   \n",
      "1021  0.220636  0.072680  0.075600  0.132706  0.140169  0.256003   0.026626   \n",
      "1022  0.217663  0.074728  0.079620  0.148641  0.182880  0.210870   0.028010   \n",
      "1023  0.180541  0.085766  0.103423  0.148829  0.185225  0.244685   0.129380   \n",
      "1024  0.220089  0.093058  0.098966  0.127031  0.181684  0.206795   0.119374   \n",
      "1025  0.087866  0.080544  0.082985  0.187936  0.354603  0.177476   0.032915   \n",
      "1026  0.046610  0.084746  0.087571  0.214689  0.264124  0.235876   0.030075   \n",
      "1027  0.095606  0.084359  0.086819  0.161687  0.171178  0.323023   0.043705   \n",
      "1028  0.290370  0.096296  0.088889  0.177778  0.096296  0.205926   0.066288   \n",
      "1029  0.102227  0.072874  0.097166  0.151316  0.239372  0.264676   0.029703   \n",
      "1030  0.063858  0.070288  0.099335  0.189357  0.199557  0.305987   0.014873   \n",
      "1031  0.143241  0.088406  0.093554  0.166070  0.154208  0.280886   0.009975   \n",
      "1032  0.060498  0.069395  0.101423  0.225979  0.220641  0.263345   0.037915   \n",
      "1033  0.194626  0.086347  0.077060  0.137325  0.142660  0.285912   0.010210   \n",
      "1034  0.330709  0.039370  0.102362  0.149606  0.110236  0.165354   0.020202   \n",
      "1035  0.150358  0.126492  0.171838  0.212411  0.212411  0.114558   0.019178   \n",
      "1036  0.075044  0.058464  0.077661  0.292321  0.218150  0.222513   0.197030   \n",
      "1037  0.094444  0.055556  0.065079  0.167460  0.317460  0.242063   0.014231   \n",
      "1038  0.295033  0.064492  0.062268  0.084507  0.176427  0.257969   0.018088   \n",
      "1039  0.042681  0.053114  0.096111  0.177363  0.227000  0.308884   0.011399   \n",
      "1040  0.115315  0.062104  0.082303  0.169129  0.185409  0.326349   0.015378   \n",
      "1041  0.187692  0.044103  0.071795  0.154872  0.204103  0.251282   0.021935   \n",
      "1042  0.115160  0.065598  0.100583  0.173469  0.186589  0.241983   0.021154   \n",
      "1043  0.147072  0.061647  0.070013  0.147952  0.157640  0.297666   0.011965   \n",
      "1044  0.211329  0.081699  0.111111  0.153595  0.114379  0.213508   0.016105   \n",
      "1045  0.133540  0.088509  0.062112  0.169255  0.172360  0.288820   0.088983   \n",
      "1046  0.227795  0.064653  0.091239  0.114199  0.178852  0.247734   0.092186   \n",
      "1047  0.094477  0.055975  0.077595  0.189545  0.205686  0.316156   0.037922   \n",
      "1048  0.106195  0.101770  0.088496  0.203540  0.190265  0.243363   0.055556   \n",
      "1049  0.218462  0.061538  0.113846  0.196923  0.141538  0.215385   0.056338   \n",
      "1050  0.241715  0.040936  0.056530  0.101365  0.152047  0.304094   0.066496   \n",
      "1051  0.039506  0.054321  0.135802  0.207407  0.256790  0.187654   0.018315   \n",
      "1052  0.082759  0.043678  0.059770  0.206897  0.213793  0.259770   0.021277   \n",
      "1053  0.128440  0.087156  0.073394  0.243119  0.137615  0.275229   0.070312   \n",
      "1054  0.085856  0.076732  0.110328  0.170469  0.180838  0.270012   0.092432   \n",
      "1055  0.111888  0.095105  0.107692  0.313287  0.240559  0.113287   0.032328   \n",
      "1056  0.085885  0.042569  0.077670  0.131441  0.241225  0.298730   0.012464   \n",
      "1057  0.134615  0.067308  0.067308  0.250000  0.201923  0.221154   0.102941   \n",
      "1058  0.145544  0.083401  0.076043  0.269828  0.115290  0.215863   0.146341   \n",
      "1059  0.169643  0.082589  0.082589  0.132812  0.143973  0.213170   0.031646   \n",
      "1060  0.192171  0.060498  0.058719  0.172598  0.218861  0.227758   0.033981   \n",
      "1061  0.187817  0.047377  0.059222  0.142132  0.155668  0.267343   0.099307   \n",
      "1062  0.229104  0.076119  0.070896  0.158209  0.126866  0.195522   0.051387   \n",
      "1063  0.244742  0.049713  0.070746  0.124283  0.120459  0.246654   0.060870   \n",
      "1064  0.204453  0.082996  0.056680  0.137652  0.210526  0.228745   0.010444   \n",
      "1065  0.242029  0.057971  0.074638  0.142029  0.137681  0.200725   0.043344   \n",
      "1066  0.203647  0.104863  0.074468  0.214286  0.109422  0.211246   0.079229   \n",
      "1067  0.263816  0.083420  0.088634  0.189781  0.102190  0.178311   0.103811   \n",
      "1068  0.240372  0.058433  0.053785  0.146082  0.092297  0.198539   0.058401   \n",
      "1069  0.127572  0.068313  0.084774  0.143210  0.149794  0.311934   0.020948   \n",
      "1070  0.100457  0.100457  0.189498  0.246575  0.178082  0.136986   0.068768   \n",
      "1071  0.193208  0.075628  0.076199  0.147546  0.146689  0.266553   0.019878   \n",
      "1072  0.139854  0.057587  0.083638  0.156307  0.146709  0.323583   0.044852   \n",
      "1073  0.087679  0.075219  0.116290  0.194278  0.155515  0.293493   0.030807   \n",
      "1074  0.189757  0.066331  0.077246  0.127624  0.173804  0.225021   0.034483   \n",
      "1075  0.238983  0.104520  0.088701  0.154802  0.119209  0.227684   0.044926   \n",
      "1076  0.221113  0.055635  0.069900  0.132668  0.138374  0.292439   0.032567   \n",
      "1077  0.275377  0.078894  0.093970  0.144724  0.139196  0.207538   0.020365   \n",
      "1078  0.428571  0.023377  0.077922  0.127273  0.129870  0.122078   0.071685   \n",
      "1079  0.181651  0.082569  0.094495  0.172477  0.194495  0.216514   0.034869   \n",
      "1080  0.207556  0.074092  0.091757  0.195289  0.151619  0.198234   0.031790   \n",
      "1081  0.327602  0.088688  0.078733  0.122172  0.101357  0.170136   0.033800   \n",
      "1082  0.224412  0.100834  0.087945  0.174375  0.117513  0.189538   0.032563   \n",
      "1083  0.317010  0.062500  0.070876  0.123067  0.142397  0.195232   0.021739   \n",
      "1084  0.142857  0.071058  0.062916  0.155440  0.136936  0.316062   0.039960   \n",
      "1085  0.315789  0.075391  0.079659  0.112376  0.128023  0.209104   0.005964   \n",
      "1086  0.316369  0.095369  0.092160  0.155433  0.102247  0.148097   0.035782   \n",
      "1087  0.394322  0.041009  0.078864  0.123028  0.085174  0.135647   0.025316   \n",
      "1088  0.205502  0.049055  0.068943  0.118992  0.148160  0.299304   0.037195   \n",
      "1089  0.136258  0.056072  0.067693  0.130157  0.131319  0.334108   0.021626   \n",
      "1090  0.163649  0.062478  0.088747  0.126731  0.132765  0.284700   0.066826   \n",
      "1091  0.153519  0.057618  0.099768  0.139598  0.139985  0.305491   0.042857   \n",
      "1092  0.129730  0.054054  0.086486  0.144865  0.110270  0.295135   0.021638   \n",
      "1093  0.130364  0.070445  0.094737  0.145749  0.165992  0.272874   0.036209   \n",
      "1094  0.302196  0.059918  0.080015  0.149981  0.131001  0.159658   0.029798   \n",
      "1095  0.158800  0.083951  0.087660  0.173297  0.151045  0.222859   0.061717   \n",
      "1096  0.138860  0.067358  0.073575  0.205181  0.132642  0.269430   0.020915   \n",
      "1097  0.194260  0.086093  0.108168  0.152318  0.097130  0.260486   0.084034   \n",
      "1098  0.194831  0.059642  0.081511  0.101392  0.113320  0.274354   0.032609   \n",
      "1099  0.206790  0.043210  0.086420  0.137346  0.126543  0.211420   0.066667   \n",
      "1100  0.164604  0.096535  0.106436  0.165223  0.142946  0.237624   0.021331   \n",
      "1101  0.250671  0.079678  0.078335  0.166070  0.136079  0.203223   0.024938   \n",
      "1102  0.053712  0.031596  0.042654  0.134281  0.214850  0.454976   0.025510   \n",
      "1103  0.320646  0.072664  0.080738  0.175317  0.122261  0.154556   0.071778   \n",
      "1104  0.028862  0.031098  0.052439  0.201016  0.265650  0.376829   0.041111   \n",
      "1105  0.126521  0.124088  0.119221  0.201946  0.126521  0.172749   0.052288   \n",
      "1106  0.125000  0.141667  0.070833  0.212500  0.220833  0.170833   0.038889   \n",
      "1107  0.239244  0.065058  0.066107  0.162644  0.162644  0.152151   0.080688   \n",
      "1108  0.126724  0.117241  0.109483  0.259483  0.107759  0.193103   0.392157   \n",
      "1109  0.108411  0.128972  0.112150  0.310280  0.175701  0.110280   0.089286   \n",
      "1110  0.068884  0.045131  0.114014  0.116390  0.261283  0.306413   0.022581   \n",
      "1111  0.233280  0.097134  0.088376  0.170382  0.104299  0.187898   0.172343   \n",
      "1112  0.115714  0.070714  0.090714  0.156429  0.172143  0.282857   0.041041   \n",
      "1113  0.223596  0.095827  0.076249  0.121072  0.131376  0.217929   0.071631   \n",
      "1114  0.123789  0.087225  0.101322  0.168722  0.162555  0.262115   0.043326   \n",
      "1115  0.159065  0.069375  0.075508  0.129168  0.157915  0.311997   0.051872   \n",
      "1116  0.117438  0.074733  0.099644  0.291815  0.153025  0.220641   0.018072   \n",
      "1117  0.233113  0.091391  0.103311  0.154967  0.182781  0.160265   0.071074   \n",
      "1118  0.032338  0.084577  0.243781  0.407960  0.149254  0.067164   0.040404   \n",
      "1119  0.181486  0.131547  0.131547  0.224117  0.140073  0.137637   0.102439   \n",
      "1120  0.220513  0.064957  0.109402  0.150427  0.147009  0.172650   0.000000   \n",
      "1121  0.139535  0.082687  0.105943  0.160207  0.188630  0.263566   0.105785   \n",
      "1122  0.101351  0.055105  0.077177  0.154505  0.163964  0.358258   0.066667   \n",
      "1123  0.226185  0.106009  0.071812  0.113825  0.120664  0.208109   0.102647   \n",
      "1124  0.150436  0.090116  0.066134  0.143169  0.164244  0.312500   0.094280   \n",
      "1125  0.240185  0.096998  0.056197  0.140878  0.127021  0.246343   0.126008   \n",
      "1126  0.301608  0.073250  0.080396  0.118239  0.116615  0.197012   0.052827   \n",
      "1127  0.277236  0.058499  0.097499  0.140314  0.114455  0.222976   0.050000   \n",
      "1128  0.261089  0.078046  0.055587  0.137563  0.145424  0.217294   0.016216   \n",
      "1129  0.100647  0.074047  0.079224  0.143063  0.171675  0.298203   0.029913   \n",
      "1130  0.073034  0.081862  0.105939  0.196629  0.177368  0.219904   0.132017   \n",
      "1131  0.140632  0.113605  0.096198  0.300046  0.114979  0.175905   0.358319   \n",
      "1132  0.112698  0.069352  0.076492  0.118307  0.130546  0.303417   0.043776   \n",
      "1133  0.086692  0.073004  0.082890  0.183270  0.174905  0.276806   0.027900   \n",
      "1134  0.213247  0.063813  0.095315  0.147011  0.181745  0.178514   0.027689   \n",
      "1135  0.184204  0.087389  0.072866  0.223694  0.121019  0.211975   0.262880   \n",
      "1136  0.186597  0.067017  0.081472  0.099869  0.132720  0.304862   0.247331   \n",
      "1137  0.302059  0.062929  0.075515  0.102975  0.254005  0.145309   0.011673   \n",
      "1138  0.125672  0.090292  0.069912  0.161053  0.133314  0.300311   0.071678   \n",
      "1139  0.188506  0.075862  0.096552  0.181609  0.158621  0.216092   0.084034   \n",
      "1140  0.093340  0.057692  0.084428  0.158537  0.146341  0.347561   0.063316   \n",
      "1141  0.115355  0.058824  0.088872  0.157117  0.157117  0.319073   0.089204   \n",
      "1142  0.259740  0.040816  0.061224  0.148423  0.100186  0.270872   0.060976   \n",
      "1143  0.097289  0.078682  0.076555  0.170122  0.147794  0.326954   0.143161   \n",
      "1144  0.337775  0.066622  0.066622  0.108594  0.182545  0.140573   0.227160   \n",
      "1145  0.150485  0.059223  0.079612  0.205825  0.137864  0.258252   0.193916   \n",
      "1146  0.107500  0.047500  0.075000  0.145000  0.157500  0.275000   0.089965   \n",
      "1147  0.154375  0.062500  0.076250  0.133750  0.108750  0.300625   0.124245   \n",
      "1148  0.137791  0.069767  0.113372  0.170349  0.169767  0.263372   0.166284   \n",
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      "1159  0.090987  0.068670  0.083262  0.177682  0.169957  0.300429   0.048349   \n",
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      "1161  0.137555  0.111354  0.096070  0.198690  0.159389  0.251092   0.048232   \n",
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      "1165  0.182026  0.062965  0.081855  0.171151  0.180882  0.250716   0.049373   \n",
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      "1167  0.187123  0.052711  0.080949  0.173946  0.149849  0.245482   0.021148   \n",
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      "1170  0.237634  0.087901  0.088904  0.159759  0.186497  0.198864   0.011311   \n",
      "1171  0.167479  0.048730  0.075917  0.161067  0.190305  0.297256   0.024777   \n",
      "1172  0.214867  0.085114  0.081521  0.133346  0.145451  0.238699   0.016583   \n",
      "1173  0.163741  0.061437  0.072682  0.112452  0.156061  0.326385   0.011244   \n",
      "1174  0.101858  0.082559  0.107577  0.233738  0.246605  0.190136   0.008482   \n",
      "1175  0.077183  0.074475  0.117806  0.241706  0.194990  0.238998   0.013912   \n",
      "1176  0.070978  0.064669  0.076498  0.148265  0.193218  0.345426   0.029189   \n",
      "1177  0.142461  0.048104  0.050879  0.175763  0.223867  0.226642   0.015258   \n",
      "1178  0.127047  0.077655  0.098257  0.190703  0.255415  0.206022   0.014027   \n",
      "1179  0.279801  0.063742  0.063190  0.152318  0.139625  0.180740   0.041545   \n",
      "1180  0.203187  0.060646  0.053121  0.144754  0.142098  0.283754   0.070348   \n",
      "1181  0.088636  0.080682  0.089773  0.196591  0.435227  0.093182   0.016993   \n",
      "1182  0.032730  0.059889  0.110724  0.322423  0.199861  0.243036   0.054886   \n",
      "1183  0.138962  0.065084  0.089710  0.145119  0.166227  0.275286   0.044118   \n",
      "1184  0.182635  0.097305  0.073353  0.233533  0.091317  0.185629   0.217228   \n",
      "1185  0.108456  0.062500  0.060662  0.091912  0.143382  0.284926   0.073864   \n",
      "1186  0.161595  0.054565  0.054565  0.123820  0.108080  0.334732   0.098431   \n",
      "1187  0.093939  0.098485  0.109091  0.153788  0.300000  0.162121   0.015810   \n",
      "1188  0.122264  0.067925  0.092075  0.132075  0.166038  0.284528   0.055894   \n",
      "1189  0.097442  0.075571  0.113454  0.231010  0.198399  0.246632   0.028634   \n",
      "1190  0.157706  0.066722  0.074442  0.131789  0.190791  0.260822   0.035817   \n",
      "1191  0.048093  0.039801  0.041459  0.131012  0.192371  0.424544   0.068182   \n",
      "1192  0.146072  0.069639  0.059873  0.156263  0.150743  0.293418   0.042601   \n",
      "1193  0.231074  0.054923  0.054429  0.126670  0.146957  0.287481   0.040668   \n",
      "1194  0.128405  0.085603  0.058366  0.151751  0.151751  0.330739   0.021858   \n",
      "1195  0.129380  0.137466  0.064690  0.140162  0.180593  0.258760   0.007463   \n",
      "1196  0.131118  0.063185  0.062820  0.169467  0.154127  0.317020   0.058621   \n",
      "1197  0.149033  0.062571  0.079636  0.146189  0.168942  0.309443   0.012528   \n",
      "1198  0.250314  0.041509  0.074214  0.093082  0.115723  0.237736   0.017301   \n",
      "1199  0.067239  0.086552  0.086552  0.164521  0.155937  0.306867   0.014300   \n",
      "1200  0.215490  0.063804  0.082263  0.143258  0.116372  0.281701   0.167967   \n",
      "1201  0.248144  0.063738  0.068688  0.146040  0.112005  0.189975   0.036334   \n",
      "1202  0.172199  0.074689  0.100968  0.147303  0.139696  0.265560   0.020091   \n",
      "1203  0.099693  0.058282  0.050613  0.121166  0.124233  0.342025   0.008639   \n",
      "1204  0.115847  0.073770  0.095628  0.125137  0.144809  0.338798   0.023256   \n",
      "1205  0.251852  0.056019  0.077778  0.105093  0.142593  0.246759   0.031915   \n",
      "1206  0.136062  0.075774  0.097898  0.153208  0.151549  0.299226   0.018045   \n",
      "1207  0.297578  0.093426  0.072664  0.145329  0.134948  0.114187   0.013889   \n",
      "1208  0.144781  0.080808  0.074074  0.188552  0.185185  0.259259   0.004739   \n",
      "1209  0.048387  0.080645  0.094086  0.293011  0.190860  0.201613   0.021818   \n",
      "1210  0.195402  0.076403  0.055443  0.164300  0.113590  0.253550   0.175258   \n",
      "1211  0.244726  0.080169  0.143460  0.147679  0.151899  0.147679   0.025773   \n",
      "1212  0.084160  0.071844  0.073212  0.130003  0.157715  0.348614   0.035112   \n",
      "1213  0.110586  0.049149  0.073724  0.181474  0.118147  0.296786   0.033967   \n",
      "1214  0.130116  0.090047  0.078414  0.124946  0.154675  0.248600   0.096042   \n",
      "1215  0.096498  0.072374  0.093774  0.159144  0.175486  0.322179   0.025974   \n",
      "1216  0.064414  0.100317  0.077086  0.133052  0.173178  0.321014   0.010116   \n",
      "1217  0.141169  0.057124  0.087328  0.142482  0.116218  0.292186   0.010999   \n",
      "1218  0.152160  0.050094  0.082029  0.149656  0.143394  0.234189   0.009700   \n",
      "1219  0.140962  0.053068  0.081260  0.127695  0.139303  0.313433   0.073171   \n",
      "1220  0.062751  0.111022  0.086082  0.156879  0.154465  0.318584   0.010169   \n",
      "1221  0.112543  0.059278  0.053265  0.146048  0.136598  0.307560   0.079327   \n",
      "1222  0.071730  0.059072  0.113924  0.126582  0.126582  0.362869   0.017143   \n",
      "1223  0.075410  0.045902  0.085246  0.163934  0.259016  0.144262   0.019324   \n",
      "1224  0.117647  0.000000  0.058824  0.000000  0.529412  0.176471   0.000000   \n",
      "1225  0.212500  0.075000  0.112500  0.087500  0.125000  0.287500   0.132075   \n",
      "1226  0.176080  0.073090  0.106312  0.229236  0.142857  0.176080   0.213333   \n",
      "1227  0.115165  0.066135  0.084949  0.166477  0.191562  0.297035   0.020202   \n",
      "1228  0.146504  0.060367  0.077547  0.144118  0.160821  0.326891   0.250808   \n",
      "1229  0.134014  0.079973  0.099046  0.156098  0.171993  0.299314   0.197639   \n",
      "1230  0.236923  0.088205  0.082051  0.208718  0.122564  0.182821   0.266145   \n",
      "1231  0.225534  0.074223  0.092134  0.187849  0.144290  0.177533   0.215502   \n",
      "1232  0.185491  0.093982  0.117065  0.155812  0.134378  0.220940   0.047138   \n",
      "1233  0.182482  0.051095  0.051095  0.087591  0.106569  0.216058   0.061024   \n",
      "1234  0.296433  0.071341  0.056581  0.164822  0.121771  0.167282   0.020000   \n",
      "1235  0.077844  0.092814  0.107784  0.305389  0.254491  0.134731   0.009901   \n",
      "1236  0.167883  0.053528  0.068127  0.145985  0.092457  0.272506   0.114187   \n",
      "1237  0.090584  0.073302  0.095948  0.240167  0.413588  0.069726   0.005158   \n",
      "1238  0.101879  0.059347  0.100890  0.149357  0.145401  0.315529   0.049738   \n",
      "1239  0.293630  0.079843  0.060209  0.098604  0.126963  0.203752   0.173511   \n",
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      "1241  0.064175  0.102257  0.155853  0.257405  0.206629  0.177010   0.003195   \n",
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      "1243  0.047539  0.068105  0.092380  0.149022  0.167229  0.353338   0.062224   \n",
      "1244  0.313208  0.045283  0.049057  0.181132  0.090566  0.215094   0.000000   \n",
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      "1255  0.105166  0.136531  0.108856  0.271218  0.151292  0.177122   0.319809   \n",
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      "1257  0.300637  0.099045  0.079299  0.116242  0.090446  0.219108   0.022294   \n",
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      "1264  0.135135  0.121622  0.108108  0.121622  0.277027  0.182432   0.000000   \n",
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      "1269  0.059581  0.098229  0.117552  0.331723  0.223833  0.143317   0.062678   \n",
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      "1273  0.040956  0.047782  0.054608  0.180887  0.273038  0.312287   0.018605   \n",
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      "1276  0.020243  0.068826  0.117409  0.242915  0.174089  0.291498   0.034722   \n",
      "1277  0.046512  0.072674  0.089147  0.217054  0.187984  0.259690   0.030471   \n",
      "1278  0.219087  0.029046  0.077178  0.109544  0.224896  0.247303   0.008667   \n",
      "1279  0.177419  0.109677  0.096774  0.193548  0.170968  0.183871   0.030973   \n",
      "1280  0.159841  0.078498  0.079636  0.184869  0.267349  0.156428   0.036222   \n",
      "1281  0.348655  0.034753  0.062780  0.102018  0.123318  0.179372   0.028571   \n",
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      "1283  0.102576  0.054677  0.084049  0.148667  0.167646  0.316765   0.008125   \n",
      "1284  0.084314  0.045098  0.086275  0.280392  0.194118  0.172549   0.031169   \n",
      "1285  0.036437  0.024291  0.105263  0.202429  0.170040  0.295547   0.045977   \n",
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      "1287  0.049972  0.050533  0.084784  0.193150  0.204380  0.311623   0.085761   \n",
      "1288  0.173285  0.092058  0.076414  0.177497  0.126354  0.196751   0.140084   \n",
      "1289  0.099010  0.041018  0.107496  0.176803  0.115983  0.356436   0.051510   \n",
      "1290  0.192588  0.076923  0.076923  0.213925  0.129141  0.193711   0.041229   \n",
      "1291  0.198098  0.071315  0.072900  0.136292  0.141046  0.217116   0.086168   \n",
      "1292  0.205021  0.073222  0.094142  0.115063  0.115063  0.246862   0.054054   \n",
      "1293  0.217300  0.065401  0.063291  0.126582  0.084388  0.276371   0.050746   \n",
      "1294  0.171498  0.072464  0.082126  0.210145  0.161836  0.166667   0.017857   \n",
      "1295  0.290925  0.039016  0.043257  0.099237  0.100085  0.273113   0.340206   \n",
      "1296  0.093654  0.069803  0.097374  0.158643  0.185120  0.344201   0.034764   \n",
      "1297  0.212734  0.078455  0.073627  0.150272  0.144538  0.192517   0.052695   \n",
      "1298  0.101675  0.086394  0.100793  0.202468  0.225096  0.224214   0.038838   \n",
      "1299  0.152996  0.062245  0.070971  0.127400  0.356021  0.177429   0.005453   \n",
      "1300  0.072351  0.048234  0.062877  0.152455  0.166236  0.401378   0.030380   \n",
      "1301  0.070640  0.050773  0.105960  0.194260  0.284768  0.205298   0.025496   \n",
      "1302  0.138026  0.060329  0.073126  0.128885  0.148080  0.303473   0.091245   \n",
      "1303  0.113861  0.062235  0.070014  0.130127  0.171146  0.345827   0.028169   \n",
      "1304  0.144408  0.105682  0.127760  0.179877  0.237061  0.174086   0.005504   \n",
      "1305  0.236760  0.082777  0.102359  0.182911  0.172230  0.173565   0.038209   \n",
      "1306  0.224605  0.108352  0.081264  0.161400  0.297968  0.079007   0.002577   \n",
      "1307  0.250000  0.120968  0.102151  0.203405  0.162186  0.114695   0.076004   \n",
      "1308  0.275968  0.098046  0.082962  0.145698  0.135756  0.154611   0.123508   \n",
      "1309  0.199566  0.078091  0.086768  0.131598  0.152567  0.256688   0.077621   \n",
      "1310  0.221899  0.060562  0.092539  0.136628  0.227713  0.209302   0.111663   \n",
      "1311  0.228464  0.058989  0.071161  0.106742  0.102996  0.287453   0.128554   \n",
      "1312  0.275062  0.055510  0.073737  0.119304  0.117647  0.188898   0.064410   \n",
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      "1314  0.206529  0.066323  0.076289  0.148282  0.142612  0.218557   0.170999   \n",
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      "1316  0.117517  0.049889  0.094235  0.175166  0.144124  0.334812   0.116949   \n",
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      "1319  0.112069  0.081897  0.047414  0.215517  0.241379  0.271552   0.121795   \n",
      "1320  0.288308  0.079158  0.071169  0.115468  0.175381  0.211692   0.029131   \n",
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      "1327  0.155056  0.061798  0.077528  0.158427  0.149438  0.305618   0.059105   \n",
      "1328  0.115445  0.054374  0.078802  0.130418  0.157210  0.358550   0.028013   \n",
      "1329  0.182713  0.053063  0.073851  0.123085  0.246171  0.244530   0.036280   \n",
      "1330  0.193667  0.067937  0.088534  0.152475  0.137104  0.247464   0.073834   \n",
      "1331  0.143069  0.054114  0.068199  0.138621  0.185322  0.286879   0.027077   \n",
      "1332  0.106173  0.046914  0.071605  0.165432  0.167901  0.353086   0.150877   \n",
      "1333  0.213858  0.075879  0.082867  0.121406  0.128994  0.230431   0.097732   \n",
      "1334  0.184099  0.072279  0.056122  0.122024  0.122024  0.252551   0.054199   \n",
      "1335  0.097931  0.087356  0.089655  0.165517  0.228506  0.263908   0.039403   \n",
      "1336  0.213500  0.085840  0.085106  0.151871  0.136464  0.205429   0.052104   \n",
      "1337  0.137449  0.071054  0.073966  0.134537  0.161910  0.336634   0.043110   \n",
      "1338  0.229594  0.089614  0.076763  0.164641  0.170893  0.201111   0.028986   \n",
      "1339  0.270228  0.079743  0.093585  0.116982  0.153441  0.204718   0.029389   \n",
      "1340  0.169149  0.050000  0.100532  0.154255  0.166489  0.276064   0.234745   \n",
      "1341  0.124954  0.078606  0.085651  0.181313  0.314423  0.149796   0.005734   \n",
      "1342  0.147860  0.103113  0.110895  0.229572  0.215953  0.138132   0.024324   \n",
      "1343  0.151877  0.070392  0.104522  0.156143  0.157850  0.263652   0.009132   \n",
      "1344  0.166102  0.106215  0.132203  0.218079  0.171751  0.178531   0.002721   \n",
      "1345  0.163237  0.048011  0.076818  0.124829  0.204390  0.268861   0.003401   \n",
      "1346  0.142207  0.053470  0.120592  0.180887  0.219568  0.228669   0.008186   \n",
      "1347  0.177576  0.070411  0.078670  0.135247  0.266777  0.246128   0.007651   \n",
      "1348  0.121673  0.136882  0.102662  0.193916  0.269962  0.144487   0.000000   \n",
      "1349  0.165187  0.045826  0.059325  0.126110  0.152043  0.318650   0.028851   \n",
      "1350  0.082397  0.092697  0.114232  0.230337  0.239700  0.216292   0.007075   \n",
      "1351  0.074747  0.083838  0.084848  0.186869  0.245455  0.249495   0.002594   \n",
      "1352  0.053272  0.088280  0.143075  0.197869  0.263318  0.223744   0.002004   \n",
      "1353  0.170829  0.114885  0.120879  0.144855  0.223776  0.184815   0.005679   \n",
      "1354  0.131108  0.073897  0.101311  0.171633  0.245530  0.215733   0.010145   \n",
      "1355  0.084995  0.083945  0.098636  0.202518  0.342078  0.163694   0.004802   \n",
      "1356  0.109709  0.054854  0.110194  0.197087  0.200971  0.275728   0.013004   \n",
      "1357  0.129541  0.089788  0.098012  0.122687  0.244003  0.267306   0.023057   \n",
      "1358  0.108549  0.057157  0.065179  0.120832  0.139133  0.345199   0.034191   \n",
      "1359  0.138310  0.070252  0.111965  0.141603  0.136114  0.315038   0.052050   \n",
      "1360  0.081395  0.073643  0.107558  0.152132  0.225775  0.273256   0.006112   \n",
      "1361  0.070648  0.044428  0.120903  0.206846  0.200291  0.289876   0.003766   \n",
      "1362  0.255655  0.074698  0.101526  0.124145  0.118359  0.225145   0.037350   \n",
      "1363  0.045079  0.057851  0.099174  0.175808  0.190083  0.294515   0.015301   \n",
      "1364  0.235632  0.056897  0.074138  0.097701  0.136782  0.259770   0.042650   \n",
      "1365  0.077476  0.101847  0.150847  0.237814  0.197281  0.217547   0.022262   \n",
      "1366  0.094444  0.087222  0.101111  0.173889  0.333333  0.153333   0.019437   \n",
      "1367  0.204106  0.051564  0.077107  0.145858  0.202912  0.246121   0.045289   \n",
      "1368  0.268559  0.065502  0.052402  0.131004  0.139738  0.224891   0.087613   \n",
      "1369  0.065972  0.056597  0.090278  0.168750  0.210417  0.355903   0.060914   \n",
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      "1371  0.116620  0.083300  0.105514  0.146767  0.134470  0.318921   0.011329   \n",
      "1372  0.268065  0.069930  0.075369  0.124320  0.163947  0.188811   0.007239   \n",
      "1373  0.249054  0.070780  0.085541  0.113929  0.134746  0.251325   0.024237   \n",
      "1374  0.128159  0.065343  0.091336  0.145126  0.124910  0.307581   0.074964   \n",
      "1375  0.225499  0.069705  0.079535  0.174859  0.165326  0.159666   0.031533   \n",
      "1376  0.161176  0.106437  0.122656  0.161683  0.145971  0.250380   0.058640   \n",
      "1377  0.062176  0.108808  0.119171  0.269430  0.284974  0.139896   0.000000   \n",
      "1378  0.083963  0.066051  0.066611  0.234817  0.128743  0.343689   0.159054   \n",
      "1379  0.102647  0.059157  0.099136  0.173960  0.226904  0.298757   0.066368   \n",
      "1380  0.136569  0.061230  0.084932  0.175226  0.274549  0.218679   0.060670   \n",
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      "1383  0.155647  0.041545  0.041545  0.102399  0.145114  0.409011   0.119888   \n",
      "1384  0.178978  0.064758  0.059551  0.122356  0.142857  0.260657   0.043670   \n",
      "1385  0.158845  0.134477  0.094765  0.178700  0.155235  0.161552   0.149880   \n",
      "1386  0.260664  0.064876  0.074987  0.121432  0.141232  0.216535   0.038215   \n",
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      "1388  0.212404  0.065421  0.076466  0.116822  0.141461  0.248513   0.135026   \n",
      "1389  0.214163  0.099372  0.104512  0.190177  0.113649  0.220445   0.145985   \n",
      "1390  0.158648  0.062419  0.056784  0.141309  0.158214  0.258344   0.198020   \n",
      "1391  0.263211  0.060976  0.069106  0.114837  0.133130  0.178862   0.031474   \n",
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      "1394  0.163910  0.065417  0.070195  0.129732  0.168688  0.294377   0.076728   \n",
      "1395  0.228429  0.114631  0.090871  0.238016  0.158816  0.119216   0.024896   \n",
      "1396  0.391304  0.082459  0.073463  0.116942  0.103448  0.136432   0.005976   \n",
      "1397  0.158095  0.062857  0.163810  0.198095  0.120000  0.150476   0.080940   \n",
      "1398  0.065839  0.057474  0.090124  0.193470  0.269023  0.246897   0.045305   \n",
      "1399  0.176791  0.075805  0.075026  0.145379  0.149533  0.259346   0.105009   \n",
      "1400  0.159091  0.080492  0.116477  0.125947  0.214015  0.231061   0.000000   \n",
      "1401  0.089363  0.074289  0.104005  0.208010  0.289190  0.203058   0.031998   \n",
      "1402  0.077744  0.067073  0.107851  0.180640  0.170351  0.310976   0.067156   \n",
      "1403  0.107034  0.065910  0.074633  0.325395  0.215453  0.192329   0.028394   \n",
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      "1405  0.157837  0.088852  0.088852  0.145143  0.247792  0.206954   0.025384   \n",
      "1406  0.215496  0.145278  0.062954  0.181598  0.116223  0.184019   0.066007   \n",
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      "1408  0.163126  0.061457  0.094841  0.129742  0.160850  0.295903   0.100099   \n",
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      "1412  0.260791  0.072240  0.059973  0.147660  0.147206  0.193094   0.088705   \n",
      "1413  0.178069  0.027179  0.059044  0.142455  0.253983  0.268041   0.041469   \n",
      "1414  0.168639  0.054734  0.050296  0.096154  0.094675  0.186391   0.012500   \n",
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      "1419  0.143274  0.055016  0.076011  0.136081  0.145412  0.305210   0.070668   \n",
      "1420  0.316364  0.047273  0.076364  0.101818  0.083636  0.229091   0.038095   \n",
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      "1423  0.090939  0.049218  0.071382  0.183833  0.171773  0.380052   0.065253   \n",
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      "1425  0.104366  0.060703  0.082002  0.194888  0.192758  0.277955   0.019006   \n",
      "1426  0.062704  0.081516  0.115049  0.193839  0.205834  0.315703   0.022320   \n",
      "1427  0.131285  0.067039  0.072626  0.145251  0.173184  0.343575   0.137546   \n",
      "1428  0.228916  0.135972  0.098107  0.177281  0.129088  0.142857   0.020455   \n",
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      "1432  0.239281  0.055325  0.084371  0.154910  0.123098  0.215768   0.066798   \n",
      "1433  0.194837  0.077440  0.074611  0.137553  0.146040  0.255304   0.028069   \n",
      "1434  0.186202  0.077522  0.079377  0.163947  0.156899  0.252596   0.025896   \n",
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      "1436  0.247824  0.079155  0.025694  0.082884  0.161210  0.148777   0.002572   \n",
      "1437  0.163229  0.057848  0.080717  0.131390  0.177130  0.288789   0.008289   \n",
      "1438  0.241379  0.040044  0.057842  0.142380  0.107898  0.221357   0.084227   \n",
      "1439  0.117558  0.093444  0.099472  0.193670  0.185381  0.262246   0.054237   \n",
      "1440  0.158541  0.058866  0.064283  0.162875  0.165764  0.316360   0.024932   \n",
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      "1443  0.129794  0.065036  0.066148  0.120345  0.148694  0.299889   0.127013   \n",
      "1444  0.167832  0.052632  0.083180  0.111888  0.150534  0.286713   0.078103   \n",
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      "1446  0.066975  0.062356  0.062356  0.187067  0.224018  0.337182   0.034221   \n",
      "1447  0.118388  0.062972  0.088161  0.246851  0.176322  0.241814   0.003448   \n",
      "1448  0.138889  0.068841  0.065217  0.120773  0.134058  0.311594   0.008278   \n",
      "1449  0.097859  0.061162  0.088685  0.113150  0.146789  0.370031   0.014218   \n",
      "1450  0.198830  0.077973  0.066277  0.161793  0.120858  0.206628   0.036212   \n",
      "1451  0.133668  0.074642  0.083954  0.141261  0.144842  0.311748   0.152595   \n",
      "1452  0.098826  0.094912  0.107632  0.248532  0.165362  0.240705   0.103139   \n",
      "1453  0.131148  0.076503  0.092896  0.136612  0.114754  0.218579   0.136000   \n",
      "1454  0.108534  0.095547  0.084416  0.213358  0.207792  0.214750   0.016451   \n",
      "1455  0.105603  0.066810  0.086207  0.090517  0.239224  0.265086   0.014749   \n",
      "1456  0.121017  0.078149  0.103187  0.184370  0.187405  0.214719   0.005658   \n",
      "1457  0.142605  0.094284  0.094873  0.176783  0.206246  0.183265   0.010453   \n",
      "1458  0.127640  0.067952  0.051423  0.126722  0.342516  0.255280   0.005794   \n",
      "1459  0.262735  0.077748  0.115282  0.144772  0.058981  0.187668   0.032491   \n",
      "1460  0.236015  0.058071  0.072456  0.167288  0.159297  0.192328   0.060714   \n",
      "1461  0.104059  0.056149  0.079341  0.129997  0.154104  0.388465   0.059438   \n",
      "1462  0.180180  0.064189  0.073198  0.127252  0.125000  0.281532   0.032000   \n",
      "1463  0.077604  0.064670  0.083730  0.175630  0.222600  0.288632   0.194394   \n",
      "1464  0.150820  0.062705  0.069672  0.149590  0.147131  0.245492   0.191789   \n",
      "1465  0.215438  0.140553  0.093318  0.201613  0.120968  0.175115   0.137763   \n",
      "1466  0.107459  0.066100  0.092319  0.138848  0.173929  0.314993   0.131552   \n",
      "1467  0.100746  0.074966  0.093962  0.150950  0.162483  0.294776   0.082314   \n",
      "1468  0.132140  0.060564  0.086029  0.175499  0.271851  0.241569   0.009926   \n",
      "1469  0.223499  0.048531  0.060026  0.149425  0.181354  0.268199   0.012251   \n",
      "1470  0.262172  0.051186  0.068664  0.157928  0.149813  0.226592   0.039669   \n",
      "1471  0.287758  0.040276  0.048755  0.116587  0.094330  0.259671   0.035076   \n",
      "1472  0.271676  0.046012  0.055491  0.104971  0.266358  0.214798   0.006104   \n",
      "1473  0.172727  0.095455  0.082955  0.160227  0.345455  0.127273   0.006711   \n",
      "1474  0.123206  0.069378  0.068182  0.155502  0.461722  0.112440   0.002469   \n",
      "1475  0.150968  0.190968  0.166452  0.246452  0.161290  0.067097   0.000000   \n",
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      "1477  0.052743  0.130802  0.122363  0.137131  0.417722  0.128692   0.002278   \n",
      "1478  0.081794  0.113456  0.097625  0.182058  0.290237  0.208443   0.000000   \n",
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      "1480  0.110012  0.092996  0.106846  0.166601  0.222002  0.218441   0.032626   \n",
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      "1483  0.141401  0.089172  0.101911  0.174522  0.159236  0.230573   0.024390   \n",
      "1484  0.057648  0.045734  0.072636  0.139508  0.188317  0.365872   0.019108   \n",
      "1485  0.148148  0.059568  0.068210  0.109259  0.135802  0.283025   0.045551   \n",
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      "1491  0.144135  0.133201  0.115308  0.260437  0.129225  0.130219   0.203922   \n",
      "1492  0.200000  0.000000  0.072727  0.236364  0.145455  0.127273   0.022727   \n",
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      "1494  0.168011  0.064516  0.087366  0.202957  0.192204  0.235215   0.027322   \n",
      "1495  0.115302  0.062500  0.068966  0.184267  0.195043  0.304957   0.037915   \n",
      "1496  0.050000  0.075000  0.025000  0.125000  0.275000  0.125000   0.000000   \n",
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      "1498  0.137405  0.059542  0.121374  0.194656  0.209160  0.251145   0.034415   \n",
      "1499  0.215531  0.069731  0.095880  0.120444  0.154120  0.243661   0.025994   \n",
      "1500  0.142762  0.058039  0.090727  0.157438  0.169446  0.250167   0.045658   \n",
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      "1502  0.273163  0.085463  0.064696  0.124601  0.202875  0.174121   0.028249   \n",
      "1503  0.071174  0.059075  0.088968  0.193594  0.224911  0.287544   0.069098   \n",
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      "1505  0.215094  0.083019  0.105660  0.203774  0.098113  0.218868   0.134146   \n",
      "1506  0.180328  0.098361  0.100000  0.142623  0.167213  0.196721   0.057203   \n",
      "1507  0.109649  0.070175  0.093202  0.185307  0.165570  0.294956   0.027419   \n",
      "1508  0.095528  0.071646  0.104646  0.148936  0.189318  0.321320   0.126752   \n",
      "1509  0.139474  0.057895  0.107895  0.150000  0.235526  0.214474   0.010017   \n",
      "1510  0.192950  0.055659  0.064935  0.126160  0.150278  0.261596   0.089655   \n",
      "1511  0.144958  0.063025  0.111345  0.189076  0.155462  0.271008   0.052356   \n",
      "1512  0.212841  0.065963  0.091469  0.133685  0.128408  0.249780   0.036861   \n",
      "1513  0.208092  0.069364  0.054913  0.153179  0.170520  0.254335   0.003717   \n",
      "1514  0.038540  0.066937  0.089249  0.202840  0.290061  0.261663   0.073171   \n",
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      "1516  0.189274  0.059937  0.082019  0.167192  0.222397  0.239748   0.017391   \n",
      "1517  0.206107  0.081425  0.089059  0.198473  0.170483  0.178117   0.042105   \n",
      "1518  0.064649  0.043722  0.069133  0.204783  0.177877  0.364350   0.031866   \n",
      "1519  0.142154  0.069437  0.091307  0.145981  0.194642  0.266266   0.006173   \n",
      "1520  0.188637  0.090329  0.077242  0.155123  0.134376  0.266199   0.051184   \n",
      "1521  0.076503  0.057377  0.139344  0.139344  0.204918  0.270492   0.011070   \n",
      "1522  0.369289  0.069797  0.062183  0.078680  0.163706  0.152284   0.025773   \n",
      "1523  0.209871  0.057082  0.086695  0.145064  0.200858  0.260086   0.096826   \n",
      "1524  0.160731  0.122233  0.129933  0.212063  0.198268  0.151107   0.004274   \n",
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      "1527  0.315296  0.068543  0.049784  0.069264  0.231602  0.185426   0.039894   \n",
      "1528  0.240460  0.091460  0.082374  0.151423  0.105996  0.219867   0.048133   \n",
      "1529  0.090473  0.058259  0.119602  0.178547  0.174435  0.286498   0.053889   \n",
      "1530  0.066667  0.096154  0.117949  0.187179  0.201282  0.253846   0.066667   \n",
      "1531  0.290616  0.070690  0.078958  0.133113  0.138074  0.191815   0.075978   \n",
      "1532  0.149299  0.064799  0.080998  0.161559  0.146235  0.278897   0.098848   \n",
      "1533  0.098901  0.069780  0.102198  0.184066  0.135714  0.309890   0.182487   \n",
      "1534  0.136121  0.086574  0.089238  0.209643  0.165157  0.225626   0.084870   \n",
      "1535  0.195835  0.080497  0.110533  0.158991  0.132159  0.221866   0.077297   \n",
      "1536  0.149676  0.069579  0.066343  0.300162  0.163430  0.163430   0.265514   \n",
      "1537  0.089260  0.075418  0.090215  0.206683  0.168019  0.266826   0.099451   \n",
      "1538  0.083107  0.063836  0.109606  0.207769  0.158988  0.292683   0.180522   \n",
      "1539  0.182206  0.056228  0.086121  0.153025  0.110320  0.261922   0.068160   \n",
      "1540  0.182045  0.104738  0.107232  0.271820  0.115960  0.153367   0.032986   \n",
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      "1542  0.170898  0.074675  0.088543  0.132494  0.196714  0.233838   0.117965   \n",
      "1543  0.119482  0.059981  0.086852  0.157390  0.138676  0.299424   0.061170   \n",
      "1544  0.081050  0.064609  0.102682  0.215172  0.185751  0.291607   0.329104   \n",
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      "1546  0.126027  0.079452  0.059178  0.188493  0.159452  0.293151   0.044261   \n",
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      "1557  0.148543  0.068386  0.104821  0.156951  0.185538  0.235987   0.079259   \n",
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      "1559  0.140906  0.060166  0.109613  0.169260  0.174965  0.267116   0.072689   \n",
      "1560  0.113333  0.090000  0.116667  0.190000  0.176667  0.250000   0.077720   \n",
      "1561  0.117386  0.078627  0.087486  0.160576  0.189369  0.293466   0.049342   \n",
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      "1599  0.190229  0.073065  0.060527  0.130134  0.147428  0.272806   0.169389   \n",
      "1600  0.120592  0.067691  0.097270  0.135381  0.132537  0.277019   0.154887   \n",
      "1601  0.109748  0.091672  0.082634  0.608780  0.045190  0.043899   0.716955   \n",
      "1602  0.172388  0.057630  0.078426  0.150088  0.144575  0.313205   0.038131   \n",
      "1603  0.249347  0.074752  0.072661  0.142185  0.151594  0.206482   0.218881   \n",
      "1604  0.096122  0.053696  0.079881  0.123964  0.156447  0.329466   0.213291   \n",
      "1605  0.114130  0.097826  0.059783  0.255435  0.228261  0.217391   0.049587   \n",
      "1606  0.290470  0.071591  0.083903  0.141815  0.156407  0.176015   0.095764   \n",
      "1607  0.124970  0.096205  0.099347  0.319555  0.129079  0.195794   0.398082   \n",
      "1608  0.155634  0.065845  0.093310  0.133451  0.143662  0.318662   0.034263   \n",
      "1609  0.087409  0.098855  0.093652  0.159209  0.148803  0.276795   0.019915   \n",
      "1610  0.253738  0.101869  0.078505  0.131308  0.120093  0.232243   0.097875   \n",
      "1611  0.159412  0.069097  0.103373  0.158868  0.145267  0.262242   0.039688   \n",
      "1612  0.144790  0.087957  0.116373  0.178620  0.182679  0.239513   0.017308   \n",
      "1613  0.113157  0.063641  0.086812  0.166323  0.189811  0.308840   0.072704   \n",
      "1614  0.162349  0.096718  0.112263  0.164076  0.179620  0.208981   0.064677   \n",
      "1615  0.093863  0.108303  0.129964  0.252708  0.137184  0.184116   0.106481   \n",
      "1616  0.126560  0.051693  0.099822  0.187166  0.177362  0.263815   0.057243   \n",
      "1617  0.174312  0.075229  0.084404  0.148624  0.113761  0.266055   0.040094   \n",
      "1618  0.161666  0.080220  0.090631  0.137171  0.138396  0.259645   0.087404   \n",
      "1619  0.280432  0.040299  0.054425  0.104695  0.167013  0.273785   0.001058   \n",
      "1620  0.132816  0.072710  0.091129  0.161415  0.149782  0.281629   0.115163   \n",
      "1621  0.228404  0.122987  0.083455  0.152269  0.134700  0.204978   0.013540   \n",
      "1622  0.269375  0.076818  0.072721  0.146466  0.131103  0.179925   0.108341   \n",
      "1623  0.092510  0.064389  0.082260  0.143758  0.364258  0.189488   0.045221   \n",
      "1624  0.088825  0.091691  0.048711  0.229226  0.209169  0.283668   0.007782   \n",
      "1625  0.039716  0.064843  0.105572  0.228977  0.180952  0.364336   0.050316   \n",
      "1626  0.157243  0.098475  0.105464  0.181067  0.157560  0.228081   0.106067   \n",
      "1627  0.101579  0.069211  0.094474  0.136842  0.191316  0.308421   0.013378   \n",
      "1628  0.144558  0.056973  0.078231  0.238095  0.113095  0.250850   0.295583   \n",
      "1629  0.176845  0.104326  0.069975  0.170483  0.243003  0.156489   0.121951   \n",
      "1630  0.115852  0.067967  0.097509  0.145974  0.178220  0.305657   0.068876   \n",
      "1631  0.181906  0.082702  0.088721  0.123277  0.155116  0.257232   0.011713   \n",
      "1632  0.218985  0.064289  0.084380  0.133099  0.171773  0.232546   0.051701   \n",
      "1633  0.114802  0.053854  0.070622  0.184134  0.142857  0.369558   0.044949   \n",
      "1634  0.101729  0.113937  0.127162  0.203459  0.143947  0.202950   0.038114   \n",
      "1635  0.172743  0.102636  0.104319  0.142737  0.190690  0.219293   0.020301   \n",
      "1636  0.253786  0.049667  0.071472  0.149001  0.121744  0.233798   0.072800   \n",
      "1637  0.178616  0.059119  0.085535  0.129560  0.122013  0.276730   0.090301   \n",
      "1638  0.119048  0.057143  0.061905  0.242857  0.190476  0.233333   0.193548   \n",
      "1639  0.122522  0.077783  0.119471  0.139807  0.176919  0.274021   0.017520   \n",
      "1640  0.215708  0.079646  0.090708  0.128319  0.127212  0.233407   0.004644   \n",
      "1641  0.071875  0.109375  0.071875  0.100000  0.103125  0.265625   0.008000   \n",
      "1642  0.242359  0.117520  0.099440  0.119242  0.238485  0.159707   0.100244   \n",
      "1643  0.170452  0.062001  0.069777  0.118887  0.166360  0.297524   0.111383   \n",
      "1644  0.181125  0.083889  0.100095  0.095329  0.152526  0.220210   0.076531   \n",
      "1645  0.207610  0.097188  0.097188  0.175765  0.134822  0.189826   0.126214   \n",
      "1646  0.203565  0.090229  0.083407  0.119278  0.212588  0.226452   0.074236   \n",
      "1647  0.147137  0.070155  0.087979  0.127038  0.177474  0.298824   0.040773   \n",
      "1648  0.153199  0.081369  0.092873  0.280022  0.160213  0.170314   0.320495   \n",
      "1649  0.264613  0.062359  0.067318  0.106687  0.169497  0.232156   0.059269   \n",
      "1650  0.177778  0.088000  0.078222  0.169778  0.197333  0.239111   0.058893   \n",
      "1651  0.106761  0.135700  0.095817  0.174125  0.283560  0.168288   0.028746   \n",
      "1652  0.058369  0.047726  0.105198  0.224961  0.244678  0.291844   0.044135   \n",
      "1653  0.262694  0.082771  0.092163  0.140886  0.147931  0.201644   0.075581   \n",
      "1654  0.169411  0.063300  0.089279  0.198683  0.172704  0.222466   0.061314   \n",
      "1655  0.286546  0.061736  0.073384  0.130460  0.142108  0.203844   0.003165   \n",
      "1656  0.272469  0.086093  0.089404  0.124409  0.109272  0.185904   0.095745   \n",
      "1657  0.111981  0.068912  0.068128  0.191073  0.303837  0.177760   0.022827   \n",
      "1658  0.290001  0.073572  0.073157  0.129719  0.157655  0.156825   0.087299   \n",
      "1659  0.209552  0.045809  0.073099  0.162768  0.096491  0.240741   0.079681   \n",
      "1660  0.188009  0.070452  0.085371  0.129714  0.155684  0.278768   0.026159   \n",
      "1661  0.200523  0.075552  0.097173  0.150154  0.153718  0.229508   0.058243   \n",
      "1662  0.195572  0.041820  0.067651  0.115621  0.134071  0.261993   0.098333   \n",
      "1663  0.321882  0.067653  0.091966  0.107294  0.111522  0.209831   0.041176   \n",
      "1664  0.173913  0.082720  0.124192  0.163434  0.121739  0.280268   0.031398   \n",
      "1665  0.081474  0.058196  0.075655  0.146460  0.142580  0.317168   0.018893   \n",
      "1666  0.152542  0.069680  0.107345  0.171375  0.126177  0.259887   0.072727   \n",
      "1667  0.128617  0.083601  0.106109  0.163987  0.099678  0.228296   0.137339   \n",
      "1668  0.196209  0.079406  0.076332  0.121414  0.136270  0.339139   0.029243   \n",
      "1669  0.222119  0.071561  0.059480  0.134758  0.153346  0.237918   0.091270   \n",
      "1670  0.278925  0.072458  0.079470  0.121932  0.137125  0.174133   0.074899   \n",
      "1671  0.312845  0.074421  0.062293  0.152977  0.129824  0.178335   0.371898   \n",
      "1672  0.166318  0.066984  0.084491  0.136061  0.145576  0.290771   0.012471   \n",
      "1673  0.065800  0.086109  0.101543  0.182778  0.370431  0.145410   0.005561   \n",
      "1674  0.184366  0.071534  0.069813  0.115290  0.130039  0.270895   0.130508   \n",
      "1675  0.168591  0.073903  0.102771  0.144342  0.157044  0.241339   0.020000   \n",
      "1676  0.207983  0.102941  0.063025  0.170168  0.163866  0.184874   0.101877   \n",
      "1677  0.096467  0.065217  0.063859  0.177989  0.163043  0.330163   0.028517   \n",
      "1678  0.096417  0.097068  0.100326  0.202606  0.157655  0.270358   0.074366   \n",
      "1679  0.269151  0.124224  0.091097  0.175983  0.118012  0.138716   0.036620   \n",
      "1680  0.117886  0.051684  0.067944  0.122532  0.112079  0.358885   0.020129   \n",
      "1681  0.195822  0.089295  0.072585  0.142037  0.131593  0.260052   0.018881   \n",
      "1682  0.246252  0.081353  0.091408  0.168007  0.142779  0.179890   0.104642   \n",
      "1683  0.123209  0.098567  0.109456  0.158166  0.303152  0.181662   0.013981   \n",
      "1684  0.254944  0.068788  0.079966  0.123818  0.125107  0.224420   0.056452   \n",
      "1685  0.178776  0.071702  0.105163  0.219885  0.211281  0.170172   0.006993   \n",
      "1686  0.193086  0.059753  0.054815  0.145679  0.134321  0.225185   0.181333   \n",
      "1687  0.140281  0.045910  0.074877  0.131354  0.187101  0.340499   0.065991   \n",
      "1688  0.089506  0.064815  0.086420  0.169753  0.176698  0.348765   0.067949   \n",
      "1689  0.231232  0.075425  0.084986  0.130312  0.121813  0.237960   0.007496   \n",
      "1690  0.086157  0.078690  0.095348  0.146468  0.292361  0.244113   0.085999   \n",
      "1691  0.021277  0.021277  0.255319  0.414894  0.117021  0.031915   0.000000   \n",
      "1692  0.140164  0.088449  0.069116  0.159497  0.158531  0.256646   0.145946   \n",
      "1693  0.179159  0.048446  0.050274  0.138026  0.105119  0.246801   0.160830   \n",
      "1694  0.032000  0.056000  0.008000  0.232000  0.160000  0.312000   0.153846   \n",
      "1695  0.134795  0.072562  0.100529  0.161502  0.187453  0.313177   0.290721   \n",
      "1696  0.257229  0.124659  0.081288  0.142117  0.147572  0.187125   0.109293   \n",
      "1697  0.200121  0.081374  0.107896  0.176612  0.113321  0.235081   0.159938   \n",
      "1698  0.226921  0.080708  0.082642  0.150912  0.140962  0.209784   0.132883   \n",
      "1699  0.192043  0.060444  0.054705  0.126243  0.154552  0.303749   0.108662   \n",
      "1700  0.110559  0.089441  0.110559  0.186957  0.137888  0.262112   0.053321   \n",
      "1701  0.136364  0.071591  0.086364  0.172727  0.139773  0.259091   0.176962   \n",
      "1702  0.231075  0.072996  0.080948  0.132634  0.135019  0.228531   0.071102   \n",
      "1703  0.130627  0.087085  0.074539  0.149077  0.230996  0.233948   0.038610   \n",
      "1704  0.198058  0.074434  0.075081  0.174757  0.182524  0.242071   0.078727   \n",
      "1705  0.179415  0.051936  0.076487  0.176582  0.158640  0.203022   0.085749   \n",
      "1706  0.137405  0.098282  0.089695  0.167939  0.136450  0.242366   0.106439   \n",
      "1707  0.282618  0.097632  0.081546  0.088695  0.143878  0.251117   0.023871   \n",
      "1708  0.158854  0.080729  0.083333  0.148438  0.197266  0.248047   0.004769   \n",
      "1709  0.162010  0.070966  0.080527  0.143419  0.212047  0.293530   0.100671   \n",
      "1710  0.134715  0.089378  0.088083  0.137306  0.113990  0.304404   0.027372   \n",
      "1711  0.089244  0.065861  0.074825  0.146142  0.134451  0.314108   0.025890   \n",
      "1712  0.185913  0.108927  0.114660  0.162981  0.144963  0.231777   0.006826   \n",
      "1713  0.054726  0.092040  0.114428  0.236318  0.248756  0.228856   0.060071   \n",
      "1714  0.122801  0.065919  0.085081  0.144252  0.175343  0.311882   0.012928   \n",
      "1715  0.098492  0.081407  0.131658  0.169849  0.155779  0.285427   0.108333   \n",
      "1716  0.119479  0.085504  0.080408  0.158550  0.138732  0.306342   0.103448   \n",
      "1717  0.156262  0.056754  0.083239  0.132425  0.129020  0.276958   0.141151   \n",
      "1718  0.216329  0.062456  0.079204  0.120377  0.181438  0.242847   0.052200   \n",
      "1719  0.163366  0.066832  0.091584  0.207921  0.148515  0.165842   0.107807   \n",
      "1720  0.146145  0.060990  0.089758  0.151899  0.218642  0.232451   0.010703   \n",
      "1721  0.201238  0.068799  0.090471  0.148607  0.151015  0.245958   0.257466   \n",
      "1722  0.080724  0.049061  0.094294  0.189631  0.264788  0.283229   0.080223   \n",
      "1723  0.045936  0.063604  0.127208  0.195524  0.209658  0.300353   0.049927   \n",
      "1724  0.054495  0.061884  0.131158  0.193658  0.259852  0.260776   0.054647   \n",
      "1725  0.288094  0.075453  0.072513  0.156786  0.103381  0.202352   0.054377   \n",
      "1726  0.109157  0.057542  0.075511  0.144141  0.162875  0.359396   0.283701   \n",
      "1727  0.240094  0.071698  0.056604  0.185377  0.164387  0.237028   0.095130   \n",
      "1728  0.162109  0.061358  0.084739  0.168910  0.207879  0.284540   0.046765   \n",
      "1729  0.227579  0.122862  0.091239  0.167444  0.145153  0.174184   0.066025   \n",
      "1730  0.343493  0.075233  0.074959  0.134816  0.130972  0.158704   0.116460   \n",
      "1731  0.284919  0.081478  0.080972  0.106275  0.128036  0.162449   0.022059   \n",
      "1732  0.214516  0.088710  0.138710  0.159677  0.090323  0.156452   0.034632   \n",
      "1733  0.305857  0.091106  0.072668  0.146421  0.129067  0.143167   0.004144   \n",
      "1734  0.257697  0.079818  0.082098  0.149373  0.144812  0.185861   0.017991   \n",
      "1735  0.104383  0.079554  0.093235  0.137573  0.161895  0.316950   0.049505   \n",
      "1736  0.187868  0.092349  0.084201  0.137619  0.129018  0.229063   0.031579   \n",
      "1737  0.257086  0.092989  0.095972  0.133267  0.133267  0.207857   0.146801   \n",
      "1738  0.156945  0.099218  0.097414  0.180397  0.274805  0.149729   0.010355   \n",
      "1739  0.118908  0.058480  0.083821  0.146199  0.161793  0.276803   0.016438   \n",
      "1740  0.228469  0.066388  0.062799  0.104067  0.108852  0.172847   0.026751   \n",
      "1741  0.205479  0.095205  0.098630  0.141781  0.152740  0.187671   0.111836   \n",
      "1742  0.231172  0.063110  0.080893  0.163877  0.128312  0.244421   0.088668   \n",
      "1743  0.136352  0.075724  0.075229  0.191042  0.159119  0.295966   0.020657   \n",
      "1744  0.200678  0.071864  0.068475  0.110508  0.118644  0.301017   0.120504   \n",
      "1745  0.057605  0.050511  0.060216  0.162997  0.170431  0.422474   0.058613   \n",
      "1746  0.264407  0.095593  0.073898  0.120000  0.108475  0.210169   0.153340   \n",
      "1747  0.245614  0.087719  0.064593  0.161085  0.096491  0.157895   0.072893   \n",
      "1748  0.285917  0.065434  0.051920  0.138691  0.219772  0.212660   0.037567   \n",
      "1749  0.100000  0.017742  0.041935  0.174194  0.293548  0.300000   0.067485   \n",
      "1750  0.231278  0.043502  0.072687  0.135463  0.144824  0.234581   0.080064   \n",
      "1751  0.501305  0.065274  0.028721  0.154047  0.031332  0.101828   0.003257   \n",
      "1752  0.356725  0.076023  0.070175  0.087719  0.052632  0.140351   0.007692   \n",
      "1753  0.219409  0.042194  0.063291  0.101266  0.101266  0.219409   0.005525   \n",
      "1754  0.241187  0.064935  0.103896  0.096475  0.098330  0.267161   0.027638   \n",
      "1755  0.100074  0.092715  0.106696  0.172185  0.178808  0.260486   0.087277   \n",
      "1756  0.228448  0.059806  0.064655  0.142241  0.134159  0.278556   0.089573   \n",
      "1757  0.318059  0.079066  0.071878  0.118598  0.139263  0.144654   0.007177   \n",
      "1758  0.258904  0.047945  0.061644  0.115068  0.136986  0.247945   0.145390   \n",
      "1759  0.167953  0.085338  0.076260  0.135270  0.148434  0.277349   0.023342   \n",
      "1760  0.092966  0.070503  0.093786  0.166257  0.255288  0.287096   0.055007   \n",
      "1761  0.197967  0.072861  0.078791  0.156453  0.183282  0.243716   0.106628   \n",
      "1762  0.126761  0.085787  0.074904  0.140845  0.163892  0.326504   0.098261   \n",
      "1763  0.218333  0.055274  0.069093  0.137725  0.115154  0.233533   0.048108   \n",
      "1764  0.276958  0.078320  0.093076  0.161180  0.194098  0.141884   0.019499   \n",
      "1765  0.049169  0.079070  0.087375  0.159468  0.254485  0.283721   0.050554   \n",
      "1766  0.337955  0.067591  0.053726  0.107452  0.199307  0.180243   0.037344   \n",
      "1767  0.184783  0.079710  0.076087  0.170290  0.112319  0.289855   0.090047   \n",
      "1768  0.282710  0.044393  0.072430  0.142523  0.189252  0.205607   0.046196   \n",
      "1769  0.193370  0.077348  0.086030  0.149961  0.167324  0.247830   0.077856   \n",
      "1770  0.251167  0.090570  0.130719  0.331466  0.063492  0.070028   0.640509   \n",
      "1771  0.184242  0.076667  0.081212  0.134848  0.148485  0.281212   0.033764   \n",
      "1772  0.330724  0.064579  0.052838  0.162427  0.150685  0.185910   0.036364   \n",
      "1773  0.139378  0.071042  0.094723  0.148850  0.255751  0.244926   0.014834   \n",
      "1774  0.194872  0.087179  0.051282  0.087179  0.128205  0.328205   0.025806   \n",
      "1775  0.042035  0.099558  0.112832  0.232301  0.179204  0.276549   0.306991   \n",
      "1776  0.107826  0.063768  0.113043  0.200000  0.155942  0.245797   0.018913   \n",
      "1777  0.169713  0.070496  0.054830  0.195822  0.122715  0.237598   0.041353   \n",
      "1778  0.154286  0.065714  0.080000  0.148571  0.108571  0.314286   0.054545   \n",
      "1779  0.138728  0.046243  0.084778  0.117534  0.134875  0.238921   0.076294   \n",
      "1780  0.181818  0.040404  0.090909  0.262626  0.121212  0.156566   0.100775   \n",
      "1781  0.204289  0.069500  0.099177  0.137660  0.168868  0.261536   0.062455   \n",
      "1782  0.128093  0.074236  0.058224  0.320233  0.122271  0.227074   0.341053   \n",
      "1783  0.107107  0.052052  0.078078  0.136136  0.156156  0.284284   0.118594   \n",
      "1784  0.195965  0.054755  0.057637  0.208934  0.370317  0.100865   0.134426   \n",
      "1785  0.178588  0.062709  0.090129  0.132570  0.191702  0.280877   0.015129   \n",
      "1786  0.212470  0.079825  0.091739  0.196585  0.125099  0.223590   0.179704   \n",
      "1787  0.040855  0.066983  0.063183  0.119952  0.259620  0.214727   0.042064   \n",
      "1788  0.238653  0.061493  0.073939  0.111274  0.133968  0.235725   0.068762   \n",
      "1789  0.208378  0.037594  0.105263  0.137487  0.163265  0.290011   0.083095   \n",
      "1790  0.212854  0.057193  0.080778  0.112618  0.104953  0.206958   0.025869   \n",
      "1791  0.069136  0.081481  0.069136  0.135802  0.162963  0.219753   0.136519   \n",
      "1792  0.142104  0.060813  0.081394  0.141069  0.213776  0.300755   0.039351   \n",
      "1793  0.150350  0.061772  0.076923  0.122960  0.155012  0.314103   0.212097   \n",
      "1794  0.218206  0.057564  0.072289  0.101740  0.148594  0.278447   0.199637   \n",
      "1795  0.199531  0.086854  0.070423  0.161972  0.107981  0.211268   0.104918   \n",
      "1796  0.122324  0.198777  0.094801  0.159021  0.076453  0.223242   0.155556   \n",
      "1797  0.319355  0.055914  0.065591  0.102151  0.101075  0.205376   0.102190   \n",
      "1798  0.162825  0.072119  0.074349  0.139777  0.130112  0.251301   0.005780   \n",
      "1799  0.198413  0.070476  0.069841  0.132698  0.148254  0.270794   0.083516   \n",
      "1800  0.121012  0.068207  0.089109  0.167217  0.149615  0.279428   0.028744   \n",
      "1801  0.069027  0.064993  0.089198  0.216047  0.279695  0.246974   0.034698   \n",
      "1802  0.272528  0.077647  0.083990  0.157699  0.139764  0.187883   0.225361   \n",
      "1803  0.109396  0.096686  0.074898  0.497503  0.141171  0.065819   0.721429   \n",
      "1804  0.182226  0.085278  0.081688  0.171454  0.179533  0.236086   0.024705   \n",
      "1805  0.063466  0.038242  0.074044  0.148902  0.475183  0.152970   0.006470   \n",
      "1806  0.346621  0.083661  0.085091  0.117447  0.111012  0.112978   0.080704   \n",
      "1807  0.226985  0.076599  0.087843  0.122980  0.199578  0.196767   0.011797   \n",
      "1808  0.131603  0.066697  0.091316  0.174127  0.169203  0.259624   0.081243   \n",
      "1809  0.103406  0.081509  0.105839  0.282238  0.099757  0.211679   0.183144   \n",
      "1810  0.043447  0.039826  0.071325  0.231716  0.192252  0.354091   0.100719   \n",
      "1811  0.052632  0.046053  0.092105  0.144737  0.151316  0.263158   0.069565   \n",
      "1812  0.262826  0.101710  0.091809  0.119712  0.091809  0.197120   0.075243   \n",
      "1813  0.150763  0.078097  0.082751  0.141712  0.365658  0.144298   0.004910   \n",
      "1814  0.092403  0.071659  0.112069  0.173491  0.293103  0.188039   0.024481   \n",
      "1815  0.176434  0.071451  0.086493  0.131934  0.138828  0.277656   0.008330   \n",
      "1816  0.326829  0.108130  0.072358  0.153659  0.154472  0.119512   0.093679   \n",
      "1817  0.191549  0.092394  0.097465  0.181408  0.163944  0.193239   0.151786   \n",
      "1818  0.174394  0.052595  0.057439  0.104498  0.150173  0.314879   0.029602   \n",
      "1819  0.174304  0.081820  0.088652  0.143976  0.152308  0.262456   0.019355   \n",
      "1820  0.204839  0.071774  0.060484  0.118548  0.125000  0.259677   0.067520   \n",
      "1821  0.141291  0.087698  0.071864  0.133983  0.147381  0.236297   0.049751   \n",
      "1822  0.313814  0.070515  0.091546  0.133196  0.180619  0.167423   0.005868   \n",
      "1823  0.190164  0.085246  0.124590  0.236066  0.127869  0.200000   0.120000   \n",
      "1824  0.116828  0.099536  0.091523  0.172923  0.370730  0.136229   0.008718   \n",
      "1825  0.053131  0.104364  0.085389  0.176471  0.330171  0.197343   0.007371   \n",
      "1826  0.282759  0.099310  0.069655  0.164138  0.127586  0.181379   0.078996   \n",
      "1827  0.192043  0.070390  0.112471  0.130069  0.185922  0.222647   0.003128   \n",
      "1828  0.214323  0.068984  0.067404  0.132175  0.130068  0.237493   0.052031   \n",
      "1829  0.251012  0.141700  0.121457  0.141700  0.109312  0.186235   0.063492   \n",
      "1830  0.133744  0.067152  0.076105  0.153889  0.137101  0.321209   0.123007   \n",
      "1831  0.114341  0.083333  0.069767  0.174419  0.178295  0.248062   0.034392   \n",
      "1832  0.281548  0.098356  0.083775  0.158802  0.121951  0.173383   0.044889   \n",
      "1833  0.110837  0.058595  0.088952  0.169079  0.128486  0.309213   0.127451   \n",
      "1834  0.129313  0.066346  0.117218  0.147279  0.184632  0.308609   0.146679   \n",
      "1835  0.164119  0.057132  0.074236  0.126274  0.156841  0.325328   0.034532   \n",
      "1836  0.122909  0.071273  0.096727  0.146909  0.129455  0.304727   0.033493   \n",
      "1837  0.300752  0.104010  0.081036  0.108605  0.135756  0.178780   0.003962   \n",
      "1838  0.219072  0.067010  0.100515  0.117698  0.121993  0.227663   0.113716   \n",
      "1839  0.140206  0.046907  0.049485  0.140722  0.456186  0.130928   0.005747   \n",
      "1840  0.093696  0.064199  0.084442  0.140544  0.183921  0.334297   0.024623   \n",
      "1841  0.113716  0.064618  0.097244  0.146975  0.149192  0.309788   0.050191   \n",
      "1842  0.130690  0.105972  0.099364  0.156877  0.224914  0.228096   0.017463   \n",
      "1843  0.036627  0.075241  0.110449  0.243612  0.352924  0.154458   0.027037   \n",
      "1844  0.225938  0.070147  0.077488  0.168842  0.120718  0.186786   0.052095   \n",
      "1845  0.128093  0.091703  0.113537  0.209607  0.234352  0.181951   0.044807   \n",
      "1846  0.190158  0.085662  0.074727  0.165857  0.151276  0.202916   0.108454   \n",
      "1847  0.171631  0.069620  0.083395  0.174237  0.157483  0.282949   0.124874   \n",
      "1848  0.257206  0.070953  0.104213  0.159645  0.212860  0.130820   0.053968   \n",
      "1849  0.200898  0.074448  0.085672  0.168724  0.145155  0.219978   0.109756   \n",
      "1850  0.202315  0.063889  0.068056  0.139352  0.135185  0.238426   0.082009   \n",
      "1851  0.092391  0.045396  0.078645  0.174552  0.187660  0.332481   0.081851   \n",
      "1852  0.123209  0.074499  0.112703  0.179561  0.148042  0.287011   0.088859   \n",
      "1853  0.112715  0.077783  0.076386  0.188635  0.171868  0.264555   0.015818   \n",
      "1854  0.081633  0.078717  0.085520  0.130224  0.154519  0.321672   0.007895   \n",
      "1855  0.257219  0.069366  0.070030  0.165616  0.107534  0.207434   0.079462   \n",
      "1856  0.212733  0.096273  0.074534  0.156832  0.114907  0.243789   0.014286   \n",
      "1857  0.117347  0.091837  0.088010  0.151786  0.136480  0.321429   0.034247   \n",
      "1858  0.220000  0.020000  0.060000  0.060000  0.080000  0.340000   0.029412   \n",
      "1859  0.151729  0.093470  0.088348  0.184379  0.131242  0.285531   0.245928   \n",
      "1860  0.167826  0.094783  0.078261  0.163478  0.155652  0.247826   0.246769   \n",
      "1861  0.175652  0.058261  0.070435  0.173913  0.126957  0.254783   0.066746   \n",
      "1862  0.173870  0.075012  0.063587  0.199205  0.121212  0.242424   0.260813   \n",
      "1863  0.138528  0.086580  0.060606  0.121212  0.212121  0.281385   0.002747   \n",
      "1864  0.198777  0.067278  0.091743  0.140673  0.152905  0.250765   0.059072   \n",
      "1865  0.252621  0.070580  0.082110  0.123340  0.171209  0.219776   0.010934   \n",
      "1866  0.160040  0.065606  0.072233  0.139828  0.133201  0.264745   0.167842   \n",
      "1867  0.246951  0.072561  0.099390  0.143293  0.169512  0.199390   0.021061   \n",
      "1868  0.049396  0.038419  0.048299  0.121844  0.611416  0.108123   0.001821   \n",
      "1869  0.265385  0.054615  0.036154  0.121538  0.105385  0.139231   0.009662   \n",
      "1870  0.304107  0.076619  0.079779  0.152449  0.115324  0.203002   0.015135   \n",
      "1871  0.290155  0.025907  0.082902  0.134715  0.119171  0.155440   0.075342   \n",
      "1872  0.110110  0.101101  0.142142  0.303303  0.139139  0.153153   0.514839   \n",
      "1873  0.341067  0.062645  0.074246  0.109049  0.120650  0.174014   0.353741   \n",
      "1874  0.086191  0.075070  0.101946  0.184430  0.163114  0.278962   0.054971   \n",
      "1875  0.138696  0.133148  0.170596  0.200416  0.158807  0.151872   0.002415   \n",
      "1876  0.065511  0.053308  0.151574  0.233783  0.204881  0.225434   0.000000   \n",
      "1877  0.198562  0.060647  0.072776  0.142408  0.111411  0.256963   0.112720   \n",
      "1878  0.210480  0.077729  0.055022  0.131441  0.127948  0.204367   0.024149   \n",
      "1879  0.147505  0.117137  0.075922  0.143167  0.119306  0.140998   0.028736   \n",
      "1880  0.122625  0.061831  0.075993  0.140242  0.272884  0.249050   0.024891   \n",
      "1881  0.322634  0.116872  0.109259  0.154115  0.166667  0.095885   0.013754   \n",
      "1882  0.166155  0.093980  0.088759  0.159705  0.346437  0.106880   0.008886   \n",
      "1883  0.106796  0.038835  0.116505  0.165049  0.135922  0.223301   0.064516   \n",
      "1884  0.148918  0.079236  0.090194  0.134588  0.143299  0.288002   0.137032   \n",
      "1885  0.186270  0.072147  0.077831  0.184521  0.153476  0.238741   0.132970   \n",
      "1886  0.113586  0.042316  0.075724  0.093541  0.260579  0.256125   0.106742   \n",
      "1887  0.146290  0.069488  0.099269  0.169801  0.182341  0.257053   0.042379   \n",
      "1888  0.199829  0.102477  0.088813  0.148591  0.116140  0.292058   0.093716   \n",
      "1889  0.171336  0.056841  0.082014  0.130735  0.190418  0.245635   0.024615   \n",
      "1890  0.136268  0.077568  0.102725  0.226415  0.180294  0.185185   0.006639   \n",
      "1891  0.369676  0.066440  0.069847  0.103918  0.165247  0.126065   0.014463   \n",
      "1892  0.145119  0.132586  0.167546  0.209103  0.147098  0.167546   0.020183   \n",
      "1893  0.275726  0.042216  0.085752  0.083113  0.125330  0.259894   0.302632   \n",
      "1894  0.064925  0.077612  0.101493  0.218657  0.163433  0.247761   0.012168   \n",
      "1895  0.172464  0.128986  0.094203  0.184058  0.186957  0.194203   0.010638   \n",
      "1896  0.143923  0.073561  0.083156  0.153518  0.180171  0.273987   0.045780   \n",
      "1897  0.082602  0.062865  0.089181  0.170322  0.158626  0.331140   0.147929   \n",
      "1898  0.303083  0.064572  0.074462  0.104130  0.153578  0.262944   0.017953   \n",
      "1899  0.080903  0.064005  0.092717  0.152236  0.140422  0.327800   0.059622   \n",
      "1900  0.208551  0.090261  0.077910  0.147268  0.270784  0.154869   0.007386   \n",
      "1901  0.152449  0.089708  0.077600  0.149697  0.145294  0.250963   0.008258   \n",
      "1902  0.197254  0.116329  0.108382  0.204480  0.148121  0.156069   0.128713   \n",
      "1903  0.228029  0.040380  0.080760  0.144893  0.121140  0.254157   0.051724   \n",
      "1904  0.212766  0.063830  0.102128  0.123404  0.187234  0.234043   0.025641   \n",
      "1905  0.027066  0.042735  0.089744  0.189459  0.259259  0.286325   0.007380   \n",
      "1906  0.155483  0.047463  0.049100  0.206219  0.487725  0.050736   0.001919   \n",
      "1907  0.203636  0.056198  0.080661  0.107107  0.227107  0.234380   0.062551   \n",
      "1908  0.135338  0.100752  0.105263  0.224060  0.168421  0.225564   0.057214   \n",
      "1909  0.372574  0.065780  0.069914  0.104960  0.129224  0.179008   0.013303   \n",
      "1910  0.248144  0.068081  0.075928  0.139555  0.135525  0.213150   0.088337   \n",
      "1911  0.188513  0.073638  0.087629  0.116348  0.136966  0.240795   0.089021   \n",
      "1912  0.085766  0.089797  0.098832  0.206283  0.345010  0.150542   0.011022   \n",
      "1913  0.096718  0.077375  0.083592  0.164421  0.388946  0.166149   0.008309   \n",
      "1914  0.137911  0.077900  0.097519  0.147721  0.250433  0.226774   0.010431   \n",
      "1915  0.181965  0.090177  0.132045  0.130435  0.106280  0.267311   0.126338   \n",
      "1916  0.066540  0.087833  0.098479  0.245627  0.248669  0.200000   0.013170   \n",
      "1917  0.100840  0.082833  0.093637  0.201681  0.169268  0.262905   0.047078   \n",
      "1918  0.081761  0.092404  0.112724  0.242864  0.265602  0.166909   0.011862   \n",
      "1919  0.186838  0.054463  0.069213  0.125567  0.142587  0.273449   0.022901   \n",
      "1920  0.184918  0.072787  0.066885  0.148197  0.207213  0.225574   0.043890   \n",
      "1921  0.121076  0.088565  0.100897  0.213004  0.127803  0.245516   0.179811   \n",
      "1922  0.292298  0.099408  0.067149  0.129032  0.117841  0.219882   0.012739   \n",
      "1923  0.134569  0.074940  0.080580  0.214343  0.157131  0.273167   0.064698   \n",
      "1924  0.186712  0.066064  0.074158  0.137587  0.163561  0.292114   0.020606   \n",
      "1925  0.130565  0.060606  0.076693  0.157501  0.147400  0.337449   0.117527   \n",
      "1926  0.087539  0.047374  0.065225  0.144181  0.188122  0.393066   0.036450   \n",
      "1927  0.140392  0.048507  0.071362  0.142257  0.173041  0.343750   0.090854   \n",
      "1928  0.135198  0.067599  0.072261  0.160839  0.235431  0.223776   0.060606   \n",
      "1929  0.249085  0.083804  0.076821  0.130362  0.142667  0.230462   0.232350   \n",
      "1930  0.266000  0.073500  0.078750  0.146750  0.128250  0.204750   0.104394   \n",
      "1931  0.089921  0.134881  0.126976  0.246047  0.264328  0.124012   0.009390   \n",
      "1932  0.144674  0.081081  0.081081  0.189189  0.149444  0.251192   0.120902   \n",
      "1933  0.083215  0.043741  0.057255  0.136202  0.127667  0.399004   0.039098   \n",
      "1934  0.110280  0.085981  0.207477  0.242991  0.104673  0.190654   0.032070   \n",
      "1935  0.132858  0.052917  0.091135  0.160448  0.203189  0.317616   0.052835   \n",
      "1936  0.112144  0.091293  0.068752  0.143984  0.156100  0.308256   0.037891   \n",
      "1937  0.034247  0.053082  0.071918  0.145548  0.246575  0.308219   0.002237   \n",
      "1938  0.274406  0.094987  0.068602  0.124011  0.118734  0.224274   0.035714   \n",
      "1939  0.186772  0.077039  0.094325  0.167982  0.135663  0.266441   0.045646   \n",
      "1940  0.148997  0.087034  0.108883  0.110673  0.181590  0.248926   0.008582   \n",
      "1941  0.136145  0.084337  0.089759  0.156024  0.150602  0.274096   0.010526   \n",
      "1942  0.281219  0.091390  0.092397  0.144260  0.125126  0.153827   0.150578   \n",
      "1943  0.172224  0.067424  0.081715  0.114328  0.213631  0.253573   0.048980   \n",
      "1944  0.213793  0.088123  0.085824  0.154789  0.138697  0.243678   0.077813   \n",
      "1945  0.316072  0.070835  0.067904  0.111383  0.101124  0.199805   0.014667   \n",
      "1946  0.167059  0.134118  0.101176  0.200000  0.134118  0.155294   0.026706   \n",
      "1947  0.112096  0.059260  0.076872  0.164377  0.178223  0.314355   0.131780   \n",
      "1948  0.101480  0.070762  0.072752  0.175600  0.192265  0.311777   0.050086   \n",
      "1949  0.117117  0.058559  0.087838  0.184685  0.186937  0.126126   0.018809   \n",
      "1950  0.166341  0.048924  0.091977  0.154599  0.215264  0.215264   0.031915   \n",
      "1951  0.158019  0.073113  0.068396  0.195755  0.226415  0.155660   0.003067   \n",
      "1952  0.162127  0.079118  0.124514  0.107652  0.267185  0.190661   0.019355   \n",
      "1953  0.118798  0.050329  0.088921  0.168593  0.250934  0.281522   0.103819   \n",
      "1954  0.199407  0.081542  0.083766  0.194959  0.127502  0.213491   0.277164   \n",
      "1955  0.079208  0.054455  0.096535  0.153465  0.214109  0.295792   0.017488   \n",
      "1956  0.058656  0.070615  0.109339  0.200456  0.327449  0.195330   0.025660   \n",
      "1957  0.242268  0.086770  0.071306  0.136168  0.157646  0.206186   0.014226   \n",
      "1958  0.269486  0.097015  0.069652  0.157546  0.122720  0.223881   0.028953   \n",
      "1959  0.083969  0.106870  0.125954  0.175573  0.200382  0.221374   0.006652   \n",
      "1960  0.099975  0.077174  0.125282  0.191681  0.182661  0.246555   0.067420   \n",
      "1961  0.205573  0.070452  0.066246  0.147213  0.149317  0.324395   0.059550   \n",
      "1962  0.095767  0.052741  0.098543  0.210271  0.360167  0.160305   0.138449   \n",
      "1963  0.223739  0.083954  0.105045  0.148883  0.140612  0.184864   0.126380   \n",
      "1964  0.119547  0.062512  0.102172  0.181114  0.178848  0.288574   0.131232   \n",
      "1965  0.208902  0.065756  0.082448  0.113809  0.213961  0.238746   0.009674   \n",
      "1966  0.056825  0.067943  0.064237  0.152563  0.230389  0.347746   0.031811   \n",
      "1967  0.168639  0.106509  0.081657  0.166864  0.101183  0.204734   0.044882   \n",
      "1968  0.141637  0.055516  0.088968  0.180071  0.150178  0.286121   0.279644   \n",
      "1969  0.026490  0.079470  0.072848  0.238411  0.434030  0.127356   0.262929   \n",
      "1970  0.146530  0.053985  0.079692  0.147815  0.161097  0.316624   0.035880   \n",
      "1971  0.201528  0.074499  0.059217  0.185291  0.142311  0.206304   0.161074   \n",
      "1972  0.255043  0.080692  0.102305  0.187320  0.132565  0.152738   0.104762   \n",
      "1973  0.047649  0.105396  0.057116  0.226885  0.471127  0.086147   0.003670   \n",
      "1974  0.317452  0.076336  0.077126  0.141879  0.141879  0.173730   0.188025   \n",
      "1975  0.155031  0.070329  0.085216  0.140657  0.196099  0.262834   0.143426   \n",
      "1976  0.215945  0.085649  0.080638  0.141686  0.141686  0.235080   0.071967   \n",
      "1977  0.199319  0.082907  0.088018  0.170358  0.172061  0.189097   0.048909   \n",
      "1978  0.121298  0.087447  0.090268  0.172073  0.121298  0.249647   0.088933   \n",
      "1979  0.283186  0.072566  0.092035  0.169912  0.120354  0.155752   0.164649   \n",
      "1980  0.131777  0.078313  0.129518  0.146084  0.185994  0.246235   0.039542   \n",
      "1981  0.074344  0.064626  0.075316  0.152575  0.391156  0.187075   0.034584   \n",
      "1982  0.088515  0.045355  0.038771  0.100219  0.441112  0.229700   0.006617   \n",
      "1983  0.071429  0.091518  0.089286  0.162946  0.268973  0.239955   0.005908   \n",
      "1984  0.170543  0.130415  0.130415  0.194254  0.204742  0.142271   0.012274   \n",
      "1985  0.063690  0.057124  0.112278  0.182534  0.202889  0.291530   0.042152   \n",
      "1986  0.119034  0.052218  0.078608  0.121842  0.210556  0.350926   0.064024   \n",
      "1987  0.166058  0.038865  0.072665  0.122836  0.169591  0.321399   0.019249   \n",
      "1988  0.204360  0.083560  0.086285  0.168937  0.119891  0.237965   0.021818   \n",
      "1989  0.145749  0.087045  0.085020  0.165992  0.186235  0.234818   0.135417   \n",
      "1990  0.029175  0.056430  0.087524  0.144338  0.335125  0.297505   0.019806   \n",
      "1991  0.226247  0.067669  0.061517  0.113465  0.107997  0.205742   0.141959   \n",
      "1992  0.203540  0.047408  0.067004  0.106195  0.138432  0.292035   0.056109   \n",
      "1993  0.108207  0.068085  0.105775  0.175076  0.180547  0.270517   0.046229   \n",
      "1994  0.291190  0.088097  0.084062  0.167451  0.110962  0.180901   0.281604   \n",
      "1995  0.147796  0.072579  0.085379  0.195302  0.208894  0.242148   0.229725   \n",
      "1996  0.107232  0.059850  0.114713  0.279302  0.147132  0.244389   0.094463   \n",
      "1997  0.096375  0.074271  0.110522  0.176835  0.180371  0.332449   0.036946   \n",
      "1998  0.208866  0.085251  0.103154  0.123615  0.160273  0.212276   0.037628   \n",
      "1999  0.126219  0.069339  0.072048  0.145179  0.163597  0.278982   0.042491   \n",
      "2000  0.086806  0.031250  0.152778  0.243056  0.131944  0.190972   0.005435   \n",
      "2001  0.143969  0.088197  0.076524  0.137484  0.128405  0.312581   0.104673   \n",
      "2002  0.022346  0.100559  0.072626  0.374302  0.307263  0.100559   0.000000   \n",
      "2003  0.142857  0.023810  0.119048  0.404762  0.285714  0.023810   0.000000   \n",
      "2004  0.271812  0.063758  0.073826  0.137584  0.127517  0.211409   0.093458   \n",
      "2005  0.186483  0.080100  0.082603  0.147685  0.178974  0.254068   0.054487   \n",
      "2006  0.087436  0.058046  0.068332  0.219691  0.151359  0.313005   0.390268   \n",
      "2007  0.116606  0.063538  0.106137  0.198556  0.227798  0.222383   0.037096   \n",
      "2008  0.110609  0.092551  0.110609  0.167043  0.209932  0.261851   0.002857   \n",
      "2009  0.222563  0.088310  0.076059  0.111792  0.138846  0.235324   0.039163   \n",
      "2010  0.119823  0.040493  0.067366  0.147248  0.209277  0.355973   0.131398   \n",
      "2011  0.113475  0.066194  0.061466  0.189125  0.234043  0.257683   0.021084   \n",
      "2012  0.229614  0.097282  0.077969  0.138054  0.128755  0.246781   0.041121   \n",
      "2013  0.094629  0.033248  0.047315  0.171355  0.140665  0.326087   0.098390   \n",
      "2014  0.172545  0.092946  0.119161  0.137750  0.137274  0.222116   0.166667   \n",
      "2015  0.153323  0.068731  0.074396  0.146903  0.109894  0.319486   0.166278   \n",
      "2016  0.273425  0.066052  0.071429  0.132873  0.122888  0.162826   0.065748   \n",
      "2017  0.221387  0.083542  0.058480  0.322473  0.091896  0.144528   0.522983   \n",
      "2018  0.171674  0.074678  0.084979  0.150215  0.171674  0.267811   0.032370   \n",
      "2019  0.217761  0.064242  0.084081  0.130846  0.123288  0.218706   0.044631   \n",
      "2020  0.129544  0.051203  0.081413  0.145929  0.165899  0.324629   0.091151   \n",
      "2021  0.144128  0.124555  0.099644  0.126335  0.106762  0.314947   0.080488   \n",
      "2022  0.190344  0.105385  0.097493  0.213556  0.105385  0.236305   0.247405   \n",
      "2023  0.163525  0.074885  0.075395  0.156903  0.131941  0.311258   0.094048   \n",
      "2024  0.194645  0.095263  0.081359  0.232235  0.147271  0.191555   0.179962   \n",
      "2025  0.209412  0.089412  0.108235  0.178824  0.143529  0.218824   0.079038   \n",
      "2026  0.252302  0.065378  0.082873  0.113260  0.183241  0.162983   0.003593   \n",
      "2027  0.295902  0.086885  0.088115  0.146311  0.121721  0.156148   0.180435   \n",
      "2028  0.214912  0.057018  0.035088  0.250000  0.250000  0.144737   0.032258   \n",
      "2029  0.117117  0.054054  0.036036  0.162162  0.315315  0.216216   0.012195   \n",
      "2030  0.168802  0.060539  0.090588  0.191781  0.257623  0.182059   0.120598   \n",
      "2031  0.215190  0.029536  0.046414  0.067511  0.122363  0.286920   0.096386   \n",
      "2032  0.120385  0.083467  0.105939  0.133226  0.154093  0.293740   0.051282   \n",
      "2033  0.182022  0.069663  0.089888  0.132584  0.202996  0.259176   0.058095   \n",
      "2034  0.158382  0.052408  0.063584  0.106744  0.133719  0.333333   0.036059   \n",
      "2035  0.169463  0.059793  0.079469  0.143838  0.193106  0.296675   0.044055   \n",
      "2036  0.150394  0.087372  0.112915  0.166627  0.147291  0.253282   0.059950   \n",
      "2037  0.126087  0.046087  0.063478  0.154783  0.233913  0.291304   0.144086   \n",
      "2038  0.280488  0.079675  0.054472  0.104065  0.133333  0.253659   0.186693   \n",
      "2039  0.047619  0.089636  0.170868  0.294118  0.193277  0.156863   0.109929   \n",
      "2040  0.142420  0.088821  0.105666  0.223583  0.127106  0.215926   0.062771   \n",
      "2041  0.339953  0.062411  0.068558  0.119149  0.130496  0.157447   0.296319   \n",
      "2042  0.171627  0.060020  0.089782  0.180556  0.165675  0.274306   0.095745   \n",
      "2043  0.291160  0.091646  0.067315  0.107867  0.104623  0.236821   0.004269   \n",
      "2044  0.259962  0.096774  0.072106  0.203036  0.100569  0.189753   0.145455   \n",
      "2045  0.196109  0.090272  0.106615  0.178988  0.151751  0.217121   0.101402   \n",
      "2046  0.088331  0.080227  0.068071  0.174230  0.111021  0.276337   0.008102   \n",
      "2047  0.097006  0.065918  0.097582  0.183362  0.177029  0.298215   0.017357   \n",
      "2048  0.248955  0.066269  0.081791  0.171940  0.119403  0.156418   0.234633   \n",
      "2049  0.359352  0.062592  0.075110  0.166421  0.079529  0.187040   0.082534   \n",
      "2050  0.226950  0.078014  0.085106  0.138298  0.085106  0.198582   0.097436   \n",
      "2051  0.199461  0.099730  0.088949  0.176101  0.249775  0.143756   0.006237   \n",
      "2052  0.163829  0.057546  0.096301  0.169701  0.176160  0.253670   0.081967   \n",
      "2053  0.319012  0.068475  0.069012  0.108217  0.125940  0.209184   0.008153   \n",
      "2054  0.054482  0.079086  0.080844  0.246046  0.240773  0.279438   0.043732   \n",
      "2055  0.124470  0.145686  0.067893  0.149929  0.171146  0.207921   0.075229   \n",
      "2056  0.112817  0.072141  0.112817  0.156562  0.184190  0.297007   0.127613   \n",
      "2057  0.146739  0.125000  0.108696  0.190217  0.150362  0.188406   0.002398   \n",
      "2058  0.181416  0.079646  0.077434  0.179204  0.143805  0.230088   0.043121   \n",
      "2059  0.296532  0.075232  0.076698  0.135809  0.123107  0.192965   0.248756   \n",
      "2060  0.232496  0.098743  0.075404  0.102783  0.115799  0.274237   0.058824   \n",
      "2061  0.221790  0.052918  0.069261  0.120623  0.116732  0.249805   0.153611   \n",
      "2062  0.080292  0.071275  0.096179  0.169386  0.186775  0.319665   0.030222   \n",
      "2063  0.092715  0.077263  0.066225  0.205298  0.207506  0.284768   0.061162   \n",
      "2064  0.113821  0.054823  0.072621  0.132718  0.162931  0.352230   0.019108   \n",
      "2065  0.233073  0.051432  0.067708  0.132812  0.147786  0.224609   0.314407   \n",
      "2066  0.162500  0.112500  0.062500  0.225000  0.100000  0.200000   0.062500   \n",
      "2067  0.269231  0.072398  0.093891  0.117647  0.142534  0.183258   0.097484   \n",
      "2068  0.374733  0.051957  0.054448  0.088968  0.154448  0.193950   0.020739   \n",
      "2069  0.236618  0.088544  0.085043  0.128064  0.164082  0.170585   0.120908   \n",
      "2070  0.113475  0.060284  0.063830  0.209220  0.244681  0.209220   0.009302   \n",
      "2071  0.120352  0.080235  0.115460  0.138943  0.225049  0.285714   0.029639   \n",
      "2072  0.272727  0.055718  0.058651  0.219941  0.129032  0.187683   0.163347   \n",
      "2073  0.184935  0.052987  0.052987  0.119481  0.202078  0.317922   0.086575   \n",
      "2074  0.116197  0.082394  0.085211  0.367606  0.097183  0.164789   0.526561   \n",
      "2075  0.391241  0.075426  0.039173  0.056691  0.400000  0.031387   0.000314   \n",
      "2076  0.114405  0.059081  0.096242  0.175365  0.186639  0.310438   0.054827   \n",
      "2077  0.132653  0.069971  0.086006  0.100583  0.243440  0.246356   0.111111   \n",
      "2078  0.181818  0.059011  0.070175  0.178628  0.236045  0.228070   0.022000   \n",
      "2079  0.238525  0.094939  0.086701  0.138093  0.150647  0.208317   0.009916   \n",
      "2080  0.255875  0.075718  0.067885  0.156658  0.120104  0.201044   0.167247   \n",
      "2081  0.239726  0.122432  0.073630  0.149829  0.101884  0.219178   0.081776   \n",
      "2082  0.078307  0.074074  0.065608  0.155556  0.105820  0.293122   0.142020   \n",
      "2083  0.362237  0.062775  0.070835  0.103566  0.166830  0.164143   0.003884   \n",
      "2084  0.300518  0.056995  0.069085  0.122625  0.228843  0.168394   0.014846   \n",
      "2085  0.191388  0.108453  0.090909  0.170654  0.074960  0.141946   0.048626   \n",
      "2086  0.198638  0.053066  0.076371  0.100753  0.134457  0.280029   0.006003   \n",
      "2087  0.106615  0.115037  0.064092  0.205629  0.252465  0.230279   0.034913   \n",
      "2088  0.156168  0.072178  0.069554  0.204724  0.223097  0.186352   0.012478   \n",
      "2089  0.134461  0.115137  0.099034  0.136876  0.239936  0.231079   0.029316   \n",
      "2090  0.208738  0.070735  0.093620  0.129681  0.199029  0.204577   0.037866   \n",
      "2091  0.168959  0.055010  0.076621  0.132613  0.211198  0.250491   0.018634   \n",
      "2092  0.076446  0.049587  0.117769  0.148760  0.256198  0.266529   0.008130   \n",
      "2093  0.315603  0.072695  0.111702  0.140957  0.153369  0.149823   0.039474   \n",
      "2094  0.103030  0.062626  0.072727  0.139394  0.266667  0.288889   0.008427   \n",
      "2095  0.225840  0.067227  0.059874  0.112395  0.129202  0.207983   0.071023   \n",
      "2096  0.226599  0.081316  0.098663  0.159740  0.142392  0.208168   0.098485   \n",
      "2097  0.075041  0.061990  0.084829  0.192496  0.194127  0.299347   0.088435   \n",
      "2098  0.129412  0.076471  0.094118  0.200000  0.194118  0.241176   0.007937   \n",
      "2099  0.222222  0.095062  0.082716  0.177778  0.155556  0.180247   0.126079   \n",
      "2100  0.053844  0.091262  0.057951  0.118640  0.561259  0.110655   0.001634   \n",
      "2101  0.149485  0.096649  0.081830  0.177191  0.233892  0.188144   0.064332   \n",
      "2102  0.104531  0.074024  0.101391  0.173620  0.150740  0.294751   0.202703   \n",
      "2103  0.037951  0.030361  0.045541  0.142315  0.314991  0.242884   0.025253   \n",
      "2104  0.195876  0.076583  0.110457  0.220913  0.198822  0.169367   0.000000   \n",
      "2105  0.181195  0.081783  0.107248  0.147894  0.117042  0.260529   0.118194   \n",
      "2106  0.129032  0.000000  0.032258  0.387097  0.096774  0.129032   0.125000   \n",
      "2107  0.128259  0.083420  0.103580  0.170316  0.190824  0.237400   0.019404   \n",
      "2108  0.046685  0.045752  0.050420  0.135387  0.492997  0.212885   0.001998   \n",
      "2109  0.237152  0.071664  0.081565  0.135785  0.162188  0.193305   0.023990   \n",
      "2110  0.032407  0.048942  0.059524  0.122354  0.464947  0.245370   0.001419   \n",
      "2111  0.318083  0.074074  0.058824  0.094771  0.309368  0.112200   0.003452   \n",
      "2112  0.096569  0.106734  0.104193  0.210928  0.129606  0.273189   0.273885   \n",
      "2113  0.065882  0.157647  0.072941  0.148235  0.374118  0.155294   0.000000   \n",
      "2114  0.113986  0.074825  0.071329  0.200000  0.162937  0.265734   0.081276   \n",
      "2115  0.076559  0.060773  0.074980  0.187056  0.339384  0.217048   0.026927   \n",
      "2116  0.050505  0.053030  0.085859  0.227273  0.146465  0.262626   0.060201   \n",
      "2117  0.166265  0.071084  0.085542  0.149398  0.155422  0.271084   0.047847   \n",
      "2118  0.182292  0.098958  0.166667  0.223958  0.156250  0.135417   0.020408   \n",
      "2119  0.190323  0.067742  0.112903  0.196774  0.135484  0.209677   0.128631   \n",
      "2120  0.154079  0.076737  0.083384  0.174018  0.251964  0.206042   0.010861   \n",
      "2121  0.021053  0.147368  0.126316  0.389474  0.200000  0.094737   0.202532   \n",
      "2122  0.431373  0.117647  0.058824  0.127451  0.078431  0.058824   0.000000   \n",
      "2123  0.143599  0.131488  0.124567  0.219723  0.147059  0.134948   0.036036   \n",
      "2124  0.203822  0.101911  0.076433  0.146497  0.063694  0.254777   0.089109   \n",
      "2125  0.198953  0.099476  0.130890  0.188482  0.172775  0.167539   0.098592   \n",
      "2126  0.125000  0.166667  0.083333  0.333333  0.125000  0.125000   0.526316   \n",
      "2127  0.074286  0.077143  0.065714  0.157143  0.142857  0.285714   0.174074   \n",
      "2128  0.035714  0.071429  0.107143  0.250000  0.357143  0.178571   0.000000   \n",
      "2129  0.325000  0.150000  0.050000  0.075000  0.050000  0.250000   0.028571   \n",
      "2130  0.148649  0.175676  0.094595  0.175676  0.135135  0.148649   0.113208   \n",
      "2131  0.138454  0.080235  0.116438  0.147260  0.215264  0.215264   0.008712   \n",
      "2132  0.217391  0.086957  0.086957  0.043478  0.217391  0.217391   0.000000   \n",
      "2133  0.250000  0.000000  0.250000  0.000000  0.000000  0.250000   0.333333   \n",
      "2134  0.116622  0.052279  0.135389  0.335121  0.176944  0.123324   0.024123   \n",
      "2135  0.182599  0.070693  0.092158  0.139382  0.138809  0.268460   0.059061   \n",
      "2136  0.121445  0.049193  0.068409  0.127594  0.219062  0.279016   0.037871   \n",
      "2137  0.095195  0.043518  0.064370  0.179510  0.177697  0.293744   0.034615   \n",
      "2138  0.132075  0.072956  0.098113  0.227673  0.223899  0.182390   0.030449   \n",
      "2139  0.059347  0.038576  0.089021  0.240356  0.201780  0.222552   0.034934   \n",
      "2140  0.107374  0.087969  0.055627  0.186934  0.211514  0.256145   0.007765   \n",
      "2141  0.136860  0.084803  0.072628  0.162049  0.152813  0.238455   0.081596   \n",
      "2142  0.106916  0.098447  0.108680  0.180663  0.262174  0.208186   0.010444   \n",
      "2143  0.100447  0.085807  0.093127  0.193575  0.186255  0.276129   0.011783   \n",
      "2144  0.103412  0.057218  0.073491  0.183727  0.174278  0.362205   0.023499   \n",
      "2145  0.136564  0.058370  0.080947  0.174009  0.155837  0.316079   0.026103   \n",
      "2146  0.246702  0.086224  0.087445  0.146312  0.150708  0.197606   0.021498   \n",
      "2147  0.128869  0.066520  0.108013  0.157849  0.158727  0.286718   0.021687   \n",
      "2148  0.254534  0.071920  0.058161  0.116323  0.125704  0.264540   0.026753   \n",
      "2149  0.064824  0.082903  0.132231  0.327738  0.200671  0.170971   0.045277   \n",
      "2150  0.252772  0.057650  0.070953  0.135255  0.157428  0.198817   0.029326   \n",
      "2151  0.249135  0.066436  0.069204  0.123875  0.137716  0.220761   0.048148   \n",
      "2152  0.286422  0.093657  0.065411  0.128345  0.126858  0.177899   0.067199   \n",
      "2153  0.388469  0.089792  0.076560  0.123819  0.090737  0.172023   0.004920   \n",
      "2154  0.222493  0.056029  0.081202  0.132765  0.137231  0.273650   0.027482   \n",
      "2155  0.185873  0.072022  0.083657  0.151801  0.136011  0.277008   0.042553   \n",
      "2156  0.146842  0.057711  0.063482  0.136582  0.164155  0.329593   0.034298   \n",
      "2157  0.175385  0.066154  0.100769  0.126154  0.145385  0.246154   0.025478   \n",
      "2158  0.198336  0.049931  0.072122  0.144244  0.151179  0.291262   0.005495   \n",
      "2159  0.172879  0.084060  0.061856  0.163362  0.168914  0.195083   0.013171   \n",
      "2160  0.118012  0.031056  0.018634  0.180124  0.186335  0.391304   0.020619   \n",
      "2161  0.186654  0.074790  0.080271  0.139587  0.148291  0.242747   0.061411   \n",
      "2162  0.096589  0.069571  0.103006  0.170213  0.178318  0.274232   0.023144   \n",
      "2163  0.061677  0.065142  0.085932  0.186417  0.188496  0.324324   0.035887   \n",
      "2164  0.101460  0.065847  0.075839  0.178837  0.213169  0.296951   0.044908   \n",
      "2165  0.292084  0.072423  0.072640  0.113528  0.162897  0.204872   0.063026   \n",
      "2166  0.187817  0.071663  0.080024  0.178859  0.241266  0.209913   0.022953   \n",
      "2167  0.253422  0.037744  0.060556  0.133140  0.129407  0.226462   0.025192   \n",
      "2168  0.122031  0.082330  0.110316  0.132118  0.400911  0.104133   0.006701   \n",
      "2169  0.099125  0.081633  0.052478  0.116618  0.116618  0.227405   0.008230   \n",
      "2170  0.116204  0.067737  0.064234  0.174453  0.176058  0.333723   0.033732   \n",
      "2171  0.263310  0.054897  0.072138  0.134897  0.234069  0.194483   0.018494   \n",
      "2172  0.155436  0.073412  0.088482  0.139720  0.156728  0.296448   0.028682   \n",
      "2173  0.100271  0.072267  0.089431  0.146341  0.198735  0.319783   0.016687   \n",
      "2174  0.185859  0.064646  0.044444  0.115152  0.086869  0.313131   0.131195   \n",
      "2175  0.234584  0.109299  0.085155  0.128874  0.236868  0.144209   0.005025   \n",
      "2176  0.125467  0.071009  0.084891  0.132942  0.153230  0.297384   0.077083   \n",
      "2177  0.125970  0.083549  0.107087  0.234609  0.201242  0.205898   0.085147   \n",
      "2178  0.096263  0.070895  0.079502  0.177916  0.177690  0.326161   0.029543   \n",
      "2179  0.172428  0.066667  0.084568  0.127572  0.143621  0.301029   0.123706   \n",
      "2180  0.101743  0.089376  0.089376  0.130410  0.133221  0.341765   0.029801   \n",
      "2181  0.181724  0.059370  0.062984  0.139391  0.123903  0.254001   0.042847   \n",
      "2182  0.104143  0.144457  0.087346  0.151176  0.145577  0.272116   0.017699   \n",
      "2183  0.145126  0.115583  0.132201  0.228951  0.165805  0.169867   0.008505   \n",
      "2184  0.209282  0.066059  0.071754  0.156891  0.138098  0.290433   0.080517   \n",
      "2185  0.179566  0.086230  0.090647  0.173228  0.149030  0.232187   0.079024   \n",
      "2186  0.152439  0.091463  0.085366  0.182927  0.123693  0.272648   0.197727   \n",
      "2187  0.161152  0.074729  0.083571  0.153451  0.139760  0.254706   0.067981   \n",
      "2188  0.141748  0.075081  0.086731  0.157605  0.134304  0.282848   0.028064   \n",
      "2189  0.243321  0.076336  0.068702  0.164122  0.122137  0.203244   0.156291   \n",
      "2190  0.072690  0.076843  0.092420  0.136033  0.194185  0.269990   0.021948   \n",
      "2191  0.140901  0.064505  0.090090  0.158559  0.154595  0.275315   0.140040   \n",
      "2192  0.125000  0.097159  0.097159  0.176420  0.137500  0.270170   0.116394   \n",
      "2193  0.306965  0.086669  0.104318  0.118500  0.103687  0.161361   0.062319   \n",
      "2194  0.246807  0.080140  0.075032  0.130268  0.162835  0.218391   0.022594   \n",
      "2195  0.148975  0.061493  0.068814  0.143851  0.134700  0.308565   0.151163   \n",
      "2196  0.152364  0.072388  0.091068  0.251605  0.151781  0.212493   0.283997   \n",
      "2197  0.231001  0.090635  0.088267  0.173305  0.144887  0.205167   0.057886   \n",
      "2198  0.202602  0.070775  0.078496  0.121676  0.172719  0.273234   0.018909   \n",
      "2199  0.113482  0.084519  0.082486  0.166836  0.177507  0.277778   0.016029   \n",
      "2200  0.152618  0.060337  0.081633  0.156167  0.117125  0.271517   0.005952   \n",
      "2201  0.133542  0.053680  0.088753  0.161699  0.174872  0.286349   0.025051   \n",
      "2202  0.078074  0.067332  0.083637  0.199501  0.138884  0.319394   0.103795   \n",
      "2203  0.168599  0.074338  0.072257  0.175439  0.121320  0.266131   0.169009   \n",
      "2204  0.116234  0.126801  0.094140  0.169068  0.242075  0.166186   0.021077   \n",
      "2205  0.123631  0.071624  0.088047  0.197993  0.170164  0.255474   0.026888   \n",
      "2206  0.041145  0.056351  0.101073  0.288014  0.246869  0.212880   0.005519   \n",
      "2207  0.082397  0.104869  0.101124  0.226592  0.161049  0.249064   0.000000   \n",
      "2208  0.268888  0.076490  0.102769  0.139371  0.124355  0.222900   0.009956   \n",
      "2209  0.113133  0.054813  0.084631  0.171673  0.192063  0.319886   0.031491   \n",
      "2210  0.218020  0.070700  0.079579  0.114107  0.137126  0.279184   0.016066   \n",
      "2211  0.134028  0.079167  0.107639  0.258333  0.205556  0.170139   0.021978   \n",
      "2212  0.289344  0.086066  0.081421  0.121311  0.103552  0.255738   0.069683   \n",
      "2213  0.203132  0.059298  0.086286  0.136764  0.183138  0.252927   0.031173   \n",
      "2214  0.088608  0.081162  0.063291  0.132539  0.294118  0.304542   0.033126   \n",
      "2215  0.138647  0.069510  0.092639  0.160781  0.191370  0.283263   0.113969   \n",
      "2216  0.135384  0.070173  0.080380  0.139354  0.267224  0.239013   0.088053   \n",
      "2217  0.142741  0.061407  0.094754  0.128101  0.175275  0.301342   0.064278   \n",
      "2218  0.143629  0.109946  0.104862  0.175723  0.189069  0.207499   0.067420   \n",
      "2219  0.095285  0.074656  0.100196  0.174853  0.156189  0.321218   0.004848   \n",
      "2220  0.165657  0.068400  0.086213  0.148201  0.158888  0.252583   0.074022   \n",
      "2221  0.142927  0.090619  0.078831  0.137525  0.189096  0.261297   0.045904   \n",
      "2222  0.083958  0.066108  0.094094  0.143676  0.183561  0.340018   0.046484   \n",
      "2223  0.108866  0.123457  0.102132  0.162738  0.330715  0.138421   0.003894   \n",
      "2224  0.099790  0.088235  0.095588  0.185924  0.260504  0.223739   0.044313   \n",
      "2225  0.109095  0.044524  0.066153  0.148555  0.187698  0.387424   0.036364   \n",
      "2226  0.130180  0.069406  0.097721  0.135704  0.159530  0.357390   0.235798   \n",
      "2227  0.189189  0.054054  0.086149  0.172297  0.150338  0.189189   0.019438   \n",
      "2228  0.180288  0.073156  0.089379  0.138353  0.129783  0.262626   0.132525   \n",
      "2229  0.238796  0.065941  0.060819  0.154289  0.118438  0.265685   0.236797   \n",
      "2230  0.130612  0.078912  0.078571  0.148639  0.194898  0.296259   0.009021   \n",
      "2231  0.199049  0.065954  0.094474  0.118241  0.127154  0.290553   0.007188   \n",
      "2232  0.196335  0.068063  0.090875  0.142483  0.140239  0.218773   0.041176   \n",
      "2233  0.238986  0.089065  0.078922  0.180032  0.144849  0.193027   0.112426   \n",
      "2234  0.209657  0.057179  0.074968  0.145489  0.171537  0.214740   0.021382   \n",
      "2235  0.195460  0.099622  0.089533  0.121059  0.157629  0.200504   0.044444   \n",
      "2236  0.214559  0.091954  0.109195  0.176245  0.122605  0.222222   0.046154   \n",
      "2237  0.096510  0.067629  0.082070  0.168231  0.182912  0.348977   0.044885   \n",
      "2238  0.118031  0.053240  0.090909  0.193370  0.175791  0.313913   0.055072   \n",
      "2239  0.166489  0.060832  0.067236  0.116329  0.128068  0.306297   0.057353   \n",
      "2240  0.200157  0.071912  0.094414  0.158458  0.124784  0.248466   0.016785   \n",
      "2241  0.193438  0.065028  0.085489  0.152164  0.168627  0.232949   0.028482   \n",
      "2242  0.277518  0.078719  0.092728  0.130087  0.095397  0.191461   0.076715   \n",
      "2243  0.224185  0.089674  0.145380  0.150815  0.183424  0.175272   0.018565   \n",
      "2244  0.054348  0.089674  0.078804  0.176630  0.440217  0.146739   0.000000   \n",
      "2245  0.310660  0.073096  0.116751  0.164467  0.115736  0.142132   0.418699   \n",
      "2246  0.221160  0.096246  0.119454  0.182935  0.140614  0.163140   0.115157   \n",
      "2247  0.293033  0.095628  0.097678  0.137295  0.131831  0.144126   0.056911   \n",
      "2248  0.081033  0.064253  0.071539  0.150585  0.192758  0.367410   0.163955   \n",
      "2249  0.104074  0.051941  0.073953  0.164704  0.142499  0.320332   0.074183   \n",
      "2250  0.133613  0.061414  0.071899  0.133313  0.180198  0.342870   0.045997   \n",
      "2251  0.125144  0.053138  0.082788  0.172507  0.151328  0.287640   0.147929   \n",
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      "2253  0.136669  0.065644  0.072908  0.138553  0.163573  0.324186   0.018736   \n",
      "2254  0.087482  0.072108  0.103221  0.182284  0.294290  0.208638   0.014513   \n",
      "2255  0.151568  0.070433  0.079393  0.140866  0.180936  0.243156   0.066848   \n",
      "2256  0.049743  0.078702  0.121439  0.191966  0.184493  0.347735   0.014715   \n",
      "2257  0.128691  0.070736  0.084178  0.196342  0.148083  0.272587   0.093313   \n",
      "2258  0.188809  0.072563  0.081949  0.160650  0.116606  0.267870   0.073949   \n",
      "2259  0.148826  0.085157  0.089534  0.132113  0.134501  0.261838   0.099245   \n",
      "2260  0.230181  0.069215  0.072435  0.163783  0.189537  0.195976   0.019797   \n",
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      "2262  0.246835  0.104430  0.075949  0.199367  0.126582  0.189873   0.146718   \n",
      "2263  0.095295  0.094093  0.077258  0.186683  0.355028  0.164587   0.009635   \n",
      "2264  0.135417  0.059896  0.080729  0.173611  0.166667  0.261285   0.038946   \n",
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      "2267  0.141679  0.075712  0.068216  0.125937  0.128936  0.315592   0.009737   \n",
      "2268  0.109346  0.061682  0.096262  0.198131  0.113084  0.321495   0.043093   \n",
      "2269  0.119843  0.084479  0.161100  0.308448  0.184676  0.115914   0.045307   \n",
      "2270  0.183134  0.061674  0.057898  0.156073  0.127753  0.301447   0.048841   \n",
      "2271  0.238272  0.095062  0.091711  0.139859  0.122575  0.216226   0.035243   \n",
      "2272  0.118636  0.063989  0.094348  0.203643  0.157403  0.292387   0.150256   \n",
      "2273  0.142047  0.064812  0.083986  0.168782  0.136646  0.281934   0.084320   \n",
      "2274  0.100892  0.070132  0.098124  0.181483  0.262381  0.237158   0.017147   \n",
      "2275  0.070086  0.058913  0.085069  0.147537  0.166328  0.378873   0.044070   \n",
      "2276  0.124448  0.065169  0.077688  0.145434  0.159426  0.322165   0.025432   \n",
      "2277  0.200271  0.059892  0.081843  0.135501  0.141463  0.255556   0.058962   \n",
      "2278  0.128792  0.084087  0.095796  0.166578  0.130921  0.314529   0.031532   \n",
      "2279  0.129032  0.080460  0.100853  0.146459  0.143493  0.303300   0.057113   \n",
      "2280  0.193798  0.046512  0.120155  0.170543  0.124031  0.263566   0.080000   \n",
      "2281  0.231023  0.132013  0.059406  0.326733  0.155116  0.062706   0.050279   \n",
      "2282  0.130387  0.074753  0.082746  0.146215  0.153894  0.285849   0.029241   \n",
      "2283  0.102174  0.059039  0.102174  0.181808  0.209039  0.286842   0.035317   \n",
      "2284  0.186100  0.073521  0.074287  0.124832  0.146659  0.246793   0.014489   \n",
      "2285  0.178420  0.071935  0.077427  0.129164  0.142452  0.278172   0.036145   \n",
      "2286  0.116788  0.077987  0.084518  0.142144  0.149443  0.313484   0.023220   \n",
      "2287  0.174314  0.079172  0.096491  0.176113  0.199505  0.226046   0.077315   \n",
      "2288  0.127362  0.054584  0.081176  0.156753  0.132260  0.313506   0.152575   \n",
      "2289  0.090291  0.070089  0.077098  0.172336  0.169656  0.315811   0.012863   \n",
      "2290  0.182563  0.114162  0.109827  0.180636  0.222543  0.151252   0.007382   \n",
      "2291  0.112460  0.064725  0.070388  0.163430  0.144822  0.309871   0.087051   \n",
      "2292  0.172561  0.077931  0.078585  0.171251  0.140799  0.229862   0.086917   \n",
      "2293  0.206597  0.076829  0.081851  0.124338  0.153930  0.255192   0.071828   \n",
      "2294  0.244613  0.113936  0.090684  0.133623  0.160130  0.197799   0.075986   \n",
      "2295  0.224240  0.075799  0.078958  0.142124  0.161863  0.204895   0.053088   \n",
      "2296  0.180328  0.068242  0.073199  0.137247  0.131910  0.279451   0.046891   \n",
      "2297  0.169545  0.089033  0.102377  0.192868  0.214959  0.198475   0.009576   \n",
      "2298  0.196970  0.053030  0.068182  0.186869  0.136364  0.250000   0.009967   \n",
      "2299  0.137166  0.066327  0.079474  0.195055  0.157771  0.231162   0.345413   \n",
      "2300  0.150685  0.125395  0.087460  0.267650  0.160169  0.189673   0.339450   \n",
      "2301  0.250000  0.097813  0.104019  0.141253  0.246749  0.130024   0.003349   \n",
      "2302  0.202167  0.060062  0.065325  0.109907  0.116718  0.191641   0.075882   \n",
      "2303  0.189454  0.077866  0.067443  0.114654  0.134273  0.263029   0.043911   \n",
      "2304  0.178877  0.075350  0.082655  0.162179  0.175955  0.243582   0.215407   \n",
      "2305  0.142669  0.055176  0.081319  0.127562  0.155938  0.341697   0.080690   \n",
      "2306  0.209432  0.073022  0.071755  0.125254  0.137424  0.227688   0.097620   \n",
      "2307  0.155182  0.084124  0.095937  0.122248  0.231609  0.240379   0.030949   \n",
      "2308  0.191108  0.065973  0.065256  0.110434  0.130154  0.266404   0.117180   \n",
      "2309  0.229140  0.083768  0.088331  0.148631  0.137549  0.208279   0.033318   \n",
      "2310  0.116389  0.076166  0.092426  0.218228  0.202824  0.243047   0.090965   \n",
      "2311  0.065284  0.087858  0.093655  0.198902  0.369433  0.164430   0.024803   \n",
      "2312  0.110390  0.043207  0.057692  0.143357  0.166583  0.420829   0.046538   \n",
      "2313  0.099256  0.062416  0.110523  0.179247  0.201329  0.301149   0.109238   \n",
      "2314  0.102080  0.094691  0.098248  0.189655  0.188287  0.258621   0.202915   \n",
      "2315  0.091580  0.054401  0.071897  0.127392  0.156096  0.375615   0.114785   \n",
      "2316  0.130665  0.048590  0.076536  0.142497  0.164653  0.332326   0.110780   \n",
      "2317  0.156842  0.054737  0.055789  0.140000  0.156842  0.310526   0.044733   \n",
      "2318  0.253797  0.044015  0.075933  0.111969  0.154440  0.251223   0.045205   \n",
      "2319  0.122739  0.082687  0.085917  0.188630  0.289190  0.175280   0.011918   \n",
      "2320  0.257772  0.068653  0.081088  0.204922  0.108290  0.184456   0.158667   \n",
      "2321  0.139064  0.052411  0.085954  0.247379  0.147449  0.220126   0.238274   \n",
      "2322  0.255580  0.079241  0.083705  0.311384  0.104911  0.110491   0.350140   \n",
      "2323  0.208564  0.078039  0.060773  0.223066  0.131906  0.191298   0.328779   \n",
      "2324  0.207264  0.046228  0.068834  0.144780  0.151384  0.266701   0.080727   \n",
      "2325  0.236189  0.065798  0.071695  0.131906  0.137182  0.235878   0.077220   \n",
      "2326  0.122970  0.043310  0.047951  0.112916  0.112142  0.300851   0.043150   \n",
      "2327  0.398983  0.054092  0.067499  0.131761  0.103560  0.131299   0.304655   \n",
      "2328  0.092045  0.056227  0.069554  0.206164  0.270304  0.252395   0.073521   \n",
      "2329  0.164179  0.053011  0.089552  0.177046  0.190427  0.257334   0.027397   \n",
      "2330  0.173453  0.068783  0.085806  0.166552  0.152979  0.267081   0.050242   \n",
      "2331  0.197397  0.066368  0.094750  0.152796  0.201451  0.240504   0.021311   \n",
      "2332  0.179266  0.069114  0.079914  0.133909  0.133909  0.293737   0.038462   \n",
      "2333  0.166776  0.084701  0.081747  0.152659  0.173014  0.258700   0.074008   \n",
      "2334  0.144879  0.083558  0.080863  0.154313  0.140836  0.295148   0.017320   \n",
      "2335  0.213651  0.062762  0.061192  0.127354  0.150105  0.250523   0.016816   \n",
      "2336  0.107360  0.057416  0.094909  0.152048  0.179579  0.328445   0.044049   \n",
      "2337  0.121199  0.041703  0.074283  0.135534  0.203736  0.323632   0.032413   \n",
      "2338  0.194159  0.094105  0.047593  0.101677  0.129800  0.376420   0.032797   \n",
      "2339  0.046465  0.094429  0.123657  0.232576  0.315513  0.167125   0.024552   \n",
      "2340  0.087646  0.074213  0.135433  0.247743  0.202158  0.226382   0.022619   \n",
      "2341  0.116827  0.070192  0.088942  0.137981  0.149519  0.336538   0.051299   \n",
      "2342  0.120047  0.087070  0.079241  0.151839  0.138316  0.309371   0.024691   \n",
      "2343  0.219906  0.073476  0.073476  0.167535  0.119072  0.234758   0.070790   \n",
      "2344  0.074727  0.053578  0.083186  0.138527  0.136764  0.387734   0.138308   \n",
      "2345  0.285451  0.055249  0.075506  0.121547  0.095764  0.206262   0.106024   \n",
      "2346  0.127063  0.072607  0.061056  0.245875  0.123762  0.211221   0.215983   \n",
      "2347  0.145126  0.069003  0.098576  0.175246  0.160460  0.225082   0.113501   \n",
      "2348  0.105354  0.072539  0.065630  0.193437  0.145078  0.250432   0.174419   \n",
      "2349  0.103197  0.049777  0.074868  0.140834  0.187778  0.317280   0.124724   \n",
      "2350  0.201421  0.083995  0.081070  0.146678  0.134141  0.247388   0.088949   \n",
      "2351  0.275134  0.114605  0.086885  0.162598  0.132809  0.154737   0.107239   \n",
      "2352  0.103652  0.059613  0.088614  0.136950  0.132116  0.354995   0.083082   \n",
      "2353  0.143223  0.086957  0.106138  0.245524  0.153453  0.221228   0.058201   \n",
      "2354  0.187954  0.075472  0.071843  0.147315  0.195210  0.243832   0.107678   \n",
      "2355  0.228052  0.069610  0.075325  0.137143  0.145974  0.261818   0.141224   \n",
      "2356  0.118701  0.114222  0.085106  0.178052  0.225084  0.193729   0.011713   \n",
      "2357  0.120603  0.075935  0.082077  0.145729  0.166946  0.238414   0.043223   \n",
      "2358  0.201739  0.099130  0.071304  0.116522  0.132174  0.255652   0.149485   \n",
      "2359  0.193049  0.087521  0.092127  0.141122  0.152848  0.250000   0.006810   \n",
      "2360  0.121315  0.077381  0.093821  0.149093  0.132086  0.289116   0.044914   \n",
      "2361  0.157510  0.086926  0.100487  0.164117  0.154729  0.247914   0.054889   \n",
      "2362  0.190455  0.092797  0.102077  0.129032  0.121962  0.251436   0.019943   \n",
      "2363  0.308300  0.102767  0.130435  0.158103  0.116601  0.126482   0.218232   \n",
      "2364  0.253846  0.065934  0.068132  0.141758  0.140659  0.168132   0.277361   \n",
      "2365  0.163873  0.063935  0.090627  0.200497  0.157045  0.259466   0.171502   \n",
      "2366  0.219101  0.064607  0.071629  0.139045  0.171348  0.269663   0.112727   \n",
      "2367  0.129909  0.036254  0.024169  0.111782  0.214502  0.277946   0.032922   \n",
      "2368  0.167048  0.086957  0.091533  0.240275  0.116705  0.270023   0.154303   \n",
      "2369  0.186697  0.068783  0.092215  0.243386  0.103553  0.208617   0.103547   \n",
      "2370  0.267741  0.108075  0.096248  0.149674  0.164763  0.183320   0.006238   \n",
      "2371  0.195233  0.133939  0.103292  0.132804  0.133939  0.232690   0.067200   \n",
      "2372  0.139175  0.069588  0.085052  0.114691  0.115979  0.382732   0.236234   \n",
      "2373  0.252983  0.068019  0.064439  0.127685  0.112172  0.299523   0.097444   \n",
      "2374  0.241005  0.064494  0.069925  0.117447  0.120163  0.207060   0.046305   \n",
      "2375  0.150830  0.055351  0.075415  0.145526  0.178736  0.307887   0.105020   \n",
      "2376  0.209318  0.062239  0.081711  0.115786  0.091794  0.357441   0.046260   \n",
      "2377  0.090399  0.082811  0.104916  0.168261  0.192016  0.276476   0.011921   \n",
      "2378  0.067791  0.207193  0.087524  0.184278  0.327180  0.111076   0.003205   \n",
      "2379  0.115510  0.078210  0.080375  0.147876  0.151606  0.319937   0.036803   \n",
      "2380  0.090682  0.087770  0.089018  0.138519  0.188852  0.260399   0.022014   \n",
      "2381  0.143191  0.074560  0.090729  0.171757  0.174991  0.275422   0.063325   \n",
      "2382  0.093969  0.099805  0.132490  0.208171  0.143580  0.250195   0.077663   \n",
      "2383  0.144141  0.064770  0.102958  0.154249  0.140022  0.305504   0.084422   \n",
      "2384  0.186770  0.077821  0.105058  0.211414  0.103761  0.251621   0.064639   \n",
      "2385  0.138376  0.083026  0.095941  0.210332  0.162362  0.197417   0.027778   \n",
      "2386  0.132706  0.085684  0.115726  0.195664  0.176594  0.228840   0.081889   \n",
      "2387  0.080792  0.060991  0.103194  0.195404  0.180806  0.290071   0.074618   \n",
      "2388  0.106667  0.072222  0.092222  0.148333  0.141667  0.292778   0.104382   \n",
      "2389  0.176127  0.104341  0.131052  0.184474  0.139399  0.194491   0.063158   \n",
      "2390  0.108149  0.083397  0.122239  0.192688  0.183930  0.258949   0.080560   \n",
      "2391  0.084197  0.066926  0.107081  0.167530  0.148100  0.294473   0.129870   \n",
      "2392  0.152623  0.055114  0.093800  0.170111  0.195019  0.211977   0.030116   \n",
      "2393  0.313059  0.019320  0.055814  0.092665  0.218962  0.220036   0.004705   \n",
      "2394  0.171882  0.103628  0.105669  0.165079  0.244898  0.163719   0.009576   \n",
      "2395  0.269371  0.087967  0.062443  0.122607  0.211942  0.192799   0.002690   \n",
      "2396  0.093897  0.039571  0.057009  0.107981  0.450704  0.186452   0.004637   \n",
      "2397  0.035730  0.057345  0.076312  0.150860  0.583591  0.089546   0.000462   \n",
      "2398  0.075971  0.087226  0.057400  0.185144  0.440630  0.115926   0.004884   \n",
      "2399  0.095442  0.050570  0.073362  0.125356  0.333333  0.262108   0.009442   \n",
      "2400  0.352459  0.039617  0.065118  0.107923  0.111111  0.243169   0.038796   \n",
      "2401  0.235849  0.110063  0.066038  0.166667  0.119497  0.213836   0.102128   \n",
      "2402  0.182628  0.073497  0.060134  0.171492  0.180401  0.113586   0.015152   \n",
      "2403  0.187452  0.079783  0.092177  0.147947  0.118513  0.250968   0.135974   \n",
      "2404  0.118223  0.112923  0.075826  0.182634  0.238483  0.224215   0.056075   \n",
      "2405  0.200331  0.079470  0.073675  0.139901  0.161424  0.271523   0.099576   \n",
      "2406  0.150635  0.088929  0.112523  0.168784  0.136116  0.270417   0.061364   \n",
      "2407  0.237500  0.048077  0.065385  0.120833  0.144551  0.250321   0.024850   \n",
      "2408  0.389292  0.049909  0.053539  0.160617  0.117060  0.176044   0.037825   \n",
      "2409  0.313570  0.086957  0.084321  0.138340  0.061924  0.185771   0.036458   \n",
      "2410  0.230204  0.055430  0.061652  0.118213  0.145362  0.201923   0.022556   \n",
      "2411  0.180645  0.048094  0.073314  0.163050  0.161877  0.317889   0.033333   \n",
      "2412  0.313144  0.075106  0.060872  0.113568  0.162629  0.231072   0.010405   \n",
      "2413  0.184553  0.050407  0.073171  0.123577  0.200813  0.217886   0.011148   \n",
      "2414  0.224760  0.055889  0.066707  0.128005  0.198918  0.230769   0.011843   \n",
      "2415  0.199861  0.055170  0.063498  0.199514  0.160999  0.263706   0.156146   \n",
      "2416  0.119765  0.033501  0.065327  0.156198  0.454774  0.146566   0.009082   \n",
      "2417  0.351376  0.058716  0.044954  0.082569  0.244037  0.199083   0.004145   \n",
      "2418  0.107325  0.052811  0.119250  0.204429  0.201022  0.264055   0.021053   \n",
      "2419  0.077833  0.045186  0.077596  0.151408  0.178850  0.325290   0.025755   \n",
      "2420  0.156338  0.094366  0.081690  0.116901  0.091549  0.267606   0.098425   \n",
      "2421  0.268258  0.120318  0.064607  0.125468  0.147004  0.197097   0.041642   \n",
      "2422  0.080808  0.052750  0.101010  0.179012  0.143659  0.317059   0.027544   \n",
      "2423  0.146054  0.124853  0.077739  0.189635  0.195524  0.224971   0.077156   \n",
      "2424  0.187266  0.086142  0.111111  0.137328  0.099875  0.164794   0.049236   \n",
      "2425  0.098203  0.079790  0.060500  0.126260  0.124507  0.304253   0.021317   \n",
      "2426  0.120000  0.086000  0.068000  0.124000  0.115333  0.300667   0.066055   \n",
      "2427  0.223539  0.080440  0.089754  0.132091  0.103302  0.197290   0.068812   \n",
      "2428  0.096186  0.070481  0.098673  0.173300  0.154229  0.227197   0.043231   \n",
      "2429  0.198924  0.063940  0.089559  0.154575  0.128525  0.267600   0.115072   \n",
      "2430  0.060000  0.055000  0.075000  0.203333  0.223333  0.263333   0.027273   \n",
      "2431  0.152916  0.067568  0.086415  0.157895  0.126245  0.290541   0.109990   \n",
      "2432  0.121179  0.084283  0.108700  0.162235  0.353228  0.125701   0.021681   \n",
      "2433  0.195603  0.058196  0.072098  0.170061  0.183640  0.281604   0.034975   \n",
      "2434  0.209169  0.080229  0.085960  0.123209  0.126074  0.300860   0.101961   \n",
      "2435  0.248415  0.074555  0.078479  0.164503  0.153939  0.183218   0.140100   \n",
      "2436  0.230390  0.076883  0.071688  0.184156  0.115325  0.254545   0.168042   \n",
      "2437  0.219657  0.044078  0.071339  0.160852  0.223209  0.249634   0.026652   \n",
      "2438  0.333699  0.052266  0.066520  0.098684  0.144006  0.185673   0.147610   \n",
      "2439  0.285208  0.047500  0.063333  0.116042  0.234167  0.181250   0.106927   \n",
      "2440  0.250000  0.047840  0.074074  0.097222  0.097222  0.273148   0.056485   \n",
      "2441  0.156698  0.048146  0.069693  0.130396  0.222825  0.289397   0.010559   \n",
      "2442  0.188648  0.076516  0.072621  0.128269  0.147190  0.255704   0.121144   \n",
      "2443  0.154094  0.058992  0.051484  0.145871  0.208795  0.268859   0.047571   \n",
      "2444  0.236318  0.075456  0.093284  0.141376  0.160862  0.204395   0.249593   \n",
      "2445  0.215797  0.074753  0.107193  0.163611  0.170663  0.203103   0.111111   \n",
      "2446  0.146732  0.079146  0.069809  0.126278  0.156069  0.320142   0.057988   \n",
      "2447  0.319588  0.072634  0.052015  0.108716  0.151828  0.181350   0.008333   \n",
      "2448  0.137797  0.049491  0.073751  0.186803  0.161087  0.339156   0.112258   \n",
      "2449  0.173913  0.058439  0.091632  0.173446  0.158018  0.283777   0.136924   \n",
      "2450  0.161290  0.070693  0.090597  0.157172  0.170899  0.251201   0.117647   \n",
      "2451  0.279458  0.068368  0.070258  0.138311  0.136736  0.175488   0.200585   \n",
      "2452  0.220213  0.060638  0.068085  0.115957  0.138298  0.237234   0.104845   \n",
      "2453  0.179775  0.110530  0.090410  0.160178  0.220016  0.187092   0.041009   \n",
      "2454  0.151971  0.068459  0.073477  0.160036  0.133513  0.318638   0.025299   \n",
      "2455  0.145914  0.098054  0.083268  0.130739  0.187938  0.264981   0.010340   \n",
      "2456  0.232258  0.083871  0.094355  0.161290  0.116935  0.179839   0.005388   \n",
      "2457  0.147041  0.063758  0.086028  0.130567  0.150702  0.274558   0.009717   \n",
      "2458  0.170455  0.039773  0.105114  0.150568  0.127841  0.281250   0.113725   \n",
      "2459  0.143902  0.115610  0.126829  0.149268  0.175122  0.234634   0.050814   \n",
      "2460  0.130029  0.052443  0.105603  0.160920  0.145833  0.255747   0.015977   \n",
      "2461  0.117519  0.055495  0.056583  0.139282  0.134929  0.286181   0.022189   \n",
      "2462  0.110755  0.056045  0.078196  0.181212  0.203096  0.303977   0.017058   \n",
      "2463  0.096539  0.047359  0.054645  0.211293  0.222222  0.295082   0.012392   \n",
      "2464  0.163708  0.101578  0.106509  0.186391  0.145957  0.182446   0.052561   \n",
      "2465  0.054196  0.050699  0.083042  0.251748  0.201923  0.246503   0.023704   \n",
      "2466  0.126516  0.055459  0.051993  0.149047  0.201040  0.285962   0.032787   \n",
      "2467  0.278947  0.081579  0.128947  0.142105  0.131579  0.171053   0.014337   \n",
      "2468  0.114943  0.049261  0.085568  0.137749  0.142310  0.338259   0.011989   \n",
      "2469  0.067980  0.057179  0.102922  0.162008  0.168361  0.296061   0.016245   \n",
      "2470  0.119468  0.083141  0.140445  0.147096  0.217703  0.247122   0.078826   \n",
      "2471  0.202024  0.042510  0.058300  0.112955  0.126721  0.279757   0.012069   \n",
      "2472  0.198556  0.075812  0.075812  0.178700  0.072202  0.207581   0.042857   \n",
      "2473  0.077435  0.051262  0.070060  0.143880  0.153496  0.365845   0.032885   \n",
      "2474  0.244983  0.083737  0.073702  0.129758  0.133910  0.226990   0.058655   \n",
      "2475  0.223864  0.089398  0.064647  0.108607  0.100111  0.308460   0.106455   \n",
      "2476  0.246496  0.101197  0.076581  0.126154  0.124103  0.215726   0.069668   \n",
      "2477  0.167364  0.118550  0.075314  0.104603  0.093445  0.160391   0.055446   \n",
      "2478  0.218921  0.107115  0.095387  0.127443  0.116497  0.212666   0.110417   \n",
      "2479  0.181459  0.063222  0.065653  0.134650  0.203343  0.286930   0.041883   \n",
      "2480  0.138302  0.080292  0.066846  0.137149  0.155974  0.264310   0.005484   \n",
      "2481  0.188599  0.070346  0.060036  0.132201  0.120679  0.313523   0.018467   \n",
      "2482  0.138237  0.081081  0.083739  0.151972  0.142667  0.293753   0.006124   \n",
      "2483  0.065934  0.062271  0.078144  0.136142  0.155678  0.367521   0.021258   \n",
      "2484  0.041002  0.044039  0.062263  0.147304  0.162491  0.425209   0.027837   \n",
      "2485  0.084761  0.058611  0.087466  0.166817  0.143372  0.325518   0.034660   \n",
      "2486  0.195956  0.073889  0.067399  0.124314  0.245382  0.215427   0.032812   \n",
      "2487  0.093842  0.104594  0.110459  0.164223  0.134897  0.276637   0.034301   \n",
      "2488  0.180758  0.129738  0.113703  0.169096  0.135569  0.190962   0.009940   \n",
      "2489  0.046263  0.042705  0.145907  0.185053  0.192171  0.313167   0.025253   \n",
      "2490  0.116883  0.126160  0.080705  0.137291  0.149351  0.277365   0.006418   \n",
      "2491  0.181398  0.073484  0.085046  0.138232  0.115622  0.234841   0.015867   \n",
      "2492  0.223051  0.082090  0.065506  0.125207  0.092040  0.237148   0.091114   \n",
      "2493  0.132267  0.060800  0.093867  0.182933  0.153067  0.288533   0.138732   \n",
      "2494  0.145471  0.081885  0.080970  0.126258  0.180695  0.207228   0.056287   \n",
      "2495  0.186100  0.058614  0.068662  0.133975  0.130207  0.266485   0.056539   \n",
      "2496  0.137101  0.070120  0.108320  0.147043  0.120356  0.291470   0.018558   \n",
      "2497  0.083268  0.036622  0.050118  0.163378  0.220442  0.370008   0.086512   \n",
      "2498  0.186186  0.042042  0.099099  0.141141  0.129129  0.237237   0.015625   \n",
      "2499  0.138736  0.059066  0.059066  0.130495  0.129121  0.195055   0.074324   \n",
      "2500  0.280495  0.061270  0.062957  0.125913  0.098932  0.318718   0.104498   \n",
      "2501  0.153812  0.083711  0.098054  0.139617  0.150446  0.307186   0.033371   \n",
      "2502  0.082302  0.068854  0.102743  0.190963  0.172942  0.334588   0.352414   \n",
      "2503  0.149654  0.114619  0.104671  0.151817  0.158737  0.219723   0.029089   \n",
      "2504  0.242478  0.076991  0.102655  0.122124  0.119469  0.230088   0.080103   \n",
      "2505  0.210838  0.098361  0.123406  0.156193  0.122951  0.220401   0.054958   \n",
      "2506  0.098592  0.070423  0.042254  0.316901  0.211268  0.197183   0.023256   \n",
      "2507  0.269939  0.057102  0.064181  0.153374  0.226522  0.198679   0.013973   \n",
      "2508  0.209559  0.094669  0.077206  0.180147  0.176471  0.141544   0.017903   \n",
      "2509  0.276914  0.078407  0.074051  0.148724  0.145613  0.121344   0.013688   \n",
      "2510  0.131429  0.112381  0.066667  0.226667  0.131429  0.240000   0.017413   \n",
      "2511  0.240451  0.100694  0.084201  0.139757  0.144097  0.196181   0.076179   \n",
      "2512  0.199077  0.056691  0.081081  0.143705  0.271589  0.189848   0.014555   \n",
      "2513  0.092372  0.059482  0.082575  0.240728  0.162351  0.282715   0.087680   \n",
      "2514  0.125284  0.082135  0.084784  0.172975  0.170326  0.304315   0.063042   \n",
      "2515  0.059065  0.044463  0.079409  0.192617  0.218868  0.344709   0.054741   \n",
      "2516  0.158544  0.076923  0.099824  0.146800  0.179683  0.260716   0.047207   \n",
      "2517  0.132094  0.071689  0.071357  0.129107  0.147693  0.341188   0.014537   \n",
      "2518  0.084936  0.097756  0.092949  0.190705  0.158654  0.285256   0.062241   \n",
      "2519  0.151625  0.064982  0.097473  0.166065  0.335740  0.119134   0.044118   \n",
      "2520  0.152174  0.054348  0.078804  0.111413  0.336957  0.214674   0.017241   \n",
      "2521  0.202923  0.088564  0.078246  0.139295  0.140155  0.281169   0.011616   \n",
      "2522  0.130890  0.089005  0.069015  0.137554  0.187530  0.230366   0.046570   \n",
      "2523  0.183486  0.062181  0.077472  0.143731  0.197757  0.292559   0.021390   \n",
      "2524  0.293774  0.078980  0.100293  0.187213  0.122858  0.142081   0.157955   \n",
      "2525  0.134188  0.068225  0.083302  0.148134  0.166981  0.310969   0.054829   \n",
      "2526  0.084918  0.086277  0.087296  0.147079  0.296875  0.241848   0.008667   \n",
      "2527  0.180154  0.076108  0.063584  0.114644  0.132948  0.333333   0.018293   \n",
      "2528  0.191489  0.054010  0.058920  0.111293  0.260229  0.237316   0.064386   \n",
      "2529  0.189189  0.066472  0.086925  0.162162  0.235208  0.200877   0.025203   \n",
      "2530  0.145324  0.069784  0.077698  0.141727  0.181295  0.281295   0.010536   \n",
      "2531  0.217753  0.074896  0.081831  0.171983  0.165049  0.202497   0.012456   \n",
      "2532  0.238095  0.063716  0.072435  0.135480  0.228035  0.175050   0.031811   \n",
      "2533  0.287691  0.058267  0.065550  0.139840  0.209031  0.193008   0.018486   \n",
      "2534  0.099372  0.084053  0.102514  0.132364  0.191673  0.316182   0.025176   \n",
      "2535  0.298116  0.075348  0.108927  0.159705  0.126945  0.181818   0.134228   \n",
      "2536  0.175129  0.077999  0.111847  0.182487  0.186166  0.209713   0.024390   \n",
      "2537  0.305279  0.070219  0.086155  0.168327  0.141932  0.159363   0.046711   \n",
      "2538  0.256071  0.063950  0.076902  0.139773  0.230977  0.196168   0.014552   \n",
      "2539  0.090038  0.084291  0.252874  0.183908  0.260536  0.103448   0.009592   \n",
      "2540  0.039216  0.112745  0.107843  0.151961  0.460784  0.107843   0.005780   \n",
      "2541  0.253687  0.104720  0.070796  0.125369  0.162242  0.174041   0.000000   \n",
      "2542  0.087253  0.050360  0.069175  0.192769  0.184468  0.348829   0.037895   \n",
      "2543  0.056527  0.037560  0.056155  0.183711  0.199331  0.386017   0.061521   \n",
      "2544  0.175325  0.116883  0.045455  0.136364  0.168831  0.233766   0.009174   \n",
      "2545  0.140052  0.061518  0.075916  0.149215  0.138743  0.324607   0.155797   \n",
      "2546  0.166895  0.079343  0.101915  0.154583  0.213406  0.171683   0.037885   \n",
      "2547  0.166426  0.102453  0.091871  0.145262  0.200577  0.223665   0.024113   \n",
      "2548  0.139111  0.085519  0.094641  0.144242  0.216648  0.220068   0.036337   \n",
      "2549  0.128571  0.081319  0.091209  0.197802  0.130769  0.258242   0.065359   \n",
      "2550  0.259781  0.071987  0.089202  0.125196  0.161189  0.228482   0.017544   \n",
      "2551  0.108808  0.031088  0.072539  0.082902  0.165803  0.393782   0.014388   \n",
      "2552  0.163223  0.090909  0.082645  0.210744  0.183884  0.194215   0.012270   \n",
      "2553  0.098516  0.064688  0.078338  0.127596  0.165579  0.291395   0.014610   \n",
      "2554  0.154458  0.085810  0.082461  0.135203  0.205107  0.243198   0.005467   \n",
      "2555  0.150442  0.107670  0.094395  0.132743  0.289086  0.156342   0.036538   \n",
      "2556  0.062615  0.073665  0.042357  0.103131  0.429098  0.257827   0.004090   \n",
      "2557  0.140669  0.074398  0.072523  0.169428  0.192248  0.278837   0.033588   \n",
      "2558  0.082512  0.057882  0.097291  0.176108  0.211823  0.262315   0.023593   \n",
      "2559  0.108223  0.078515  0.078515  0.182493  0.165517  0.233422   0.024513   \n",
      "2560  0.033163  0.036990  0.088010  0.144133  0.246173  0.297194   0.017153   \n",
      "2561  0.229665  0.035885  0.063397  0.159091  0.178230  0.181818   0.009146   \n",
      "2562  0.102709  0.050790  0.074492  0.182844  0.276524  0.198646   0.025714   \n",
      "2563  0.077600  0.074800  0.096800  0.168400  0.360400  0.169600   0.002674   \n",
      "2564  0.051656  0.049007  0.075497  0.203974  0.201325  0.347020   0.028902   \n",
      "2565  0.197650  0.067035  0.093988  0.153421  0.212163  0.210090   0.017908   \n",
      "2566  0.049748  0.039661  0.078175  0.166667  0.216873  0.351903   0.023366   \n",
      "2567  0.140855  0.121934  0.081990  0.156973  0.339173  0.140855   0.036107   \n",
      "2568  0.120521  0.068404  0.068404  0.175896  0.182410  0.241042   0.019048   \n",
      "2569  0.047664  0.069590  0.134414  0.166826  0.317445  0.190658   0.005513   \n",
      "2570  0.119212  0.068966  0.092611  0.151724  0.181281  0.279803   0.061415   \n",
      "2571  0.140665  0.097187  0.125320  0.210997  0.156010  0.239130   0.122137   \n",
      "2572  0.042362  0.121951  0.127086  0.127086  0.439024  0.129653   0.015670   \n",
      "2573  0.096253  0.083979  0.076873  0.155685  0.200904  0.315891   0.102928   \n",
      "2574  0.094959  0.048652  0.120164  0.163540  0.159437  0.339977   0.087094   \n",
      "2575  0.112228  0.077052  0.122278  0.159966  0.195980  0.229481   0.053812   \n",
      "2576  0.166897  0.080000  0.105517  0.142759  0.131034  0.185517   0.082418   \n",
      "2577  0.130045  0.071749  0.079372  0.134529  0.295516  0.212108   0.006971   \n",
      "2578  0.137823  0.111198  0.086922  0.160532  0.220047  0.169930   0.004826   \n",
      "2579  0.130129  0.094959  0.116061  0.185229  0.198124  0.178195   0.006812   \n",
      "2580  0.144101  0.080271  0.088975  0.138298  0.244681  0.217602   0.023515   \n",
      "2581  0.171040  0.110787  0.107872  0.117590  0.214772  0.180758   0.005974   \n",
      "2582  0.132635  0.090712  0.093242  0.174196  0.193350  0.219733   0.016285   \n",
      "2583  0.178540  0.086192  0.090589  0.164908  0.198329  0.241865   0.014404   \n",
      "2584  0.177645  0.077844  0.143713  0.205589  0.205589  0.121756   0.024510   \n",
      "2585  0.223444  0.066346  0.066346  0.146786  0.205913  0.257133   0.020725   \n",
      "2586  0.206522  0.092391  0.122283  0.180707  0.131793  0.202446   0.030142   \n",
      "2587  0.173410  0.086430  0.107349  0.140930  0.169006  0.278282   0.021071   \n",
      "2588  0.217262  0.074405  0.091270  0.147817  0.177579  0.225198   0.046348   \n",
      "2589  0.176249  0.077078  0.088125  0.158674  0.201858  0.222948   0.015479   \n",
      "2590  0.145393  0.100592  0.096365  0.180051  0.217244  0.196112   0.064516   \n",
      "2591  0.145168  0.072391  0.072391  0.165191  0.192530  0.281864   0.041646   \n",
      "2592  0.171579  0.076504  0.089283  0.168172  0.146192  0.235815   0.183980   \n",
      "2593  0.179745  0.066398  0.077800  0.167002  0.155600  0.219316   0.083105   \n",
      "2594  0.241228  0.061404  0.089912  0.247807  0.098684  0.192982   0.031161   \n",
      "2595  0.065158  0.059005  0.082189  0.179321  0.180420  0.328096   0.035791   \n",
      "2596  0.220902  0.080391  0.077945  0.232786  0.119888  0.178609   0.294041   \n",
      "2597  0.154636  0.058773  0.089016  0.159201  0.203709  0.256776   0.115616   \n",
      "2598  0.139274  0.095050  0.105611  0.198680  0.196040  0.200660   0.117057   \n",
      "2599  0.121786  0.088633  0.094046  0.257781  0.161705  0.223275   0.178250   \n",
      "2600  0.150695  0.065201  0.082864  0.166291  0.164600  0.269072   0.192665   \n",
      "2601  0.120302  0.063547  0.113057  0.167245  0.183396  0.285887   0.117073   \n",
      "2602  0.149248  0.053831  0.071411  0.161979  0.150097  0.320563   0.310676   \n",
      "2603  0.154967  0.070492  0.096126  0.123507  0.153510  0.253131   0.015521   \n",
      "2604  0.263215  0.069267  0.090777  0.130149  0.133795  0.244623   0.060786   \n",
      "2605  0.065537  0.110169  0.103390  0.191525  0.309040  0.174011   0.057333   \n",
      "2606  0.101007  0.069640  0.083165  0.178129  0.208921  0.306763   0.027663   \n",
      "2607  0.106684  0.053671  0.080013  0.161673  0.137965  0.340797   0.060773   \n",
      "2608  0.113955  0.057504  0.071879  0.148668  0.154979  0.340112   0.243256   \n",
      "2609  0.124112  0.050483  0.057773  0.141061  0.185529  0.320211   0.090081   \n",
      "2610  0.062137  0.084041  0.106840  0.280733  0.199821  0.219937   0.057309   \n",
      "2611  0.145799  0.046747  0.069304  0.129781  0.147107  0.361556   0.050584   \n",
      "2612  0.099448  0.060773  0.104972  0.187845  0.168508  0.314917   0.127049   \n",
      "2613  0.170077  0.098226  0.089131  0.204184  0.136880  0.244657   0.222425   \n",
      "2614  0.124563  0.069267  0.098370  0.155413  0.168219  0.295111   0.228385   \n",
      "2615  0.146137  0.086534  0.089625  0.181015  0.189404  0.234437   0.148961   \n",
      "2616  0.071286  0.052967  0.080446  0.153724  0.211071  0.339705   0.260532   \n",
      "2617  0.094663  0.056730  0.086606  0.168849  0.163813  0.329641   0.199728   \n",
      "2618  0.142999  0.105263  0.085402  0.150943  0.222443  0.188679   0.038835   \n",
      "2619  0.062278  0.085570  0.120506  0.169620  0.396709  0.145063   0.031306   \n",
      "2620  0.156863  0.140820  0.137255  0.181818  0.162210  0.133690   0.038278   \n",
      "2621  0.326733  0.100424  0.050919  0.147100  0.099010  0.226308   0.003571   \n",
      "2622  0.139535  0.065426  0.087442  0.178605  0.150388  0.269147   0.051977   \n",
      "2623  0.124214  0.081761  0.091195  0.103774  0.168239  0.261006   0.020492   \n",
      "2624  0.091228  0.080702  0.101754  0.201316  0.170175  0.263596   0.112507   \n",
      "2625  0.107412  0.074121  0.072236  0.156407  0.150126  0.342337   0.178451   \n",
      "2626  0.194429  0.071309  0.110864  0.150975  0.120891  0.213370   0.048338   \n",
      "2627  0.117363  0.071275  0.095927  0.152733  0.164523  0.309218   0.043051   \n",
      "2628  0.056919  0.059806  0.094452  0.220664  0.188699  0.361518   0.021148   \n",
      "2629  0.240115  0.058231  0.064702  0.113587  0.159597  0.315600   0.146089   \n",
      "2630  0.170333  0.055838  0.054146  0.164693  0.178229  0.314157   0.085672   \n",
      "2631  0.067742  0.053226  0.077419  0.167742  0.185484  0.216129   0.189189   \n",
      "2632  0.216257  0.055196  0.071583  0.134756  0.256792  0.217335   0.031457   \n",
      "2633  0.243902  0.069106  0.089431  0.207317  0.146341  0.180894   0.248000   \n",
      "2634  0.212928  0.074144  0.084791  0.142586  0.151711  0.252471   0.158549   \n",
      "2635  0.151844  0.040130  0.052603  0.114967  0.148048  0.376356   0.094301   \n",
      "2636  0.148917  0.054603  0.068141  0.163809  0.132220  0.346119   0.012164   \n",
      "2637  0.255102  0.068878  0.121599  0.154762  0.164966  0.155612   0.003058   \n",
      "2638  0.108856  0.071956  0.101476  0.193727  0.215867  0.232472   0.138381   \n",
      "2639  0.406061  0.048485  0.052525  0.137374  0.125253  0.163636   0.139785   \n",
      "2640  0.207175  0.094170  0.093274  0.104933  0.230493  0.155157   0.018450   \n",
      "2641  0.219765  0.082885  0.087667  0.121737  0.119546  0.244869   0.027785   \n",
      "2642  0.246719  0.078365  0.072366  0.116235  0.154481  0.217473   0.006606   \n",
      "2643  0.133929  0.049745  0.063776  0.098214  0.134566  0.254464   0.039788   \n",
      "2644  0.147488  0.087520  0.113452  0.249595  0.131280  0.189627   0.031818   \n",
      "2645  0.156080  0.092559  0.070780  0.132486  0.163339  0.268603   0.005102   \n",
      "2646  0.174057  0.075447  0.094639  0.125083  0.152879  0.260093   0.043141   \n",
      "2647  0.228169  0.092958  0.092019  0.137089  0.238498  0.168075   0.019080   \n",
      "2648  0.070521  0.054323  0.083728  0.196113  0.180912  0.362322   0.074167   \n",
      "2649  0.090411  0.108415  0.117417  0.217613  0.263405  0.166732   0.005322   \n",
      "2650  0.131027  0.052113  0.085437  0.208735  0.273327  0.227950   0.023741   \n",
      "2651  0.102312  0.067321  0.105586  0.154287  0.179660  0.326990   0.165104   \n",
      "2652  0.191718  0.096511  0.110205  0.147049  0.153570  0.230844   0.033037   \n",
      "2653  0.258639  0.051657  0.062700  0.109369  0.204489  0.230851   0.033853   \n",
      "2654  0.215862  0.071556  0.075730  0.149076  0.136553  0.227788   0.048451   \n",
      "2655  0.082974  0.081897  0.081897  0.171336  0.156250  0.290948   0.126959   \n",
      "2656  0.290433  0.104784  0.120729  0.119590  0.211845  0.126424   0.001414   \n",
      "2657  0.114861  0.072232  0.094731  0.164890  0.167555  0.278271   0.010526   \n",
      "2658  0.093396  0.069949  0.095350  0.149277  0.323955  0.209457   0.024435   \n",
      "2659  0.157985  0.067464  0.095645  0.119556  0.192997  0.271563   0.007937   \n",
      "2660  0.138501  0.068615  0.054638  0.176620  0.177891  0.331639   0.015000   \n",
      "2661  0.179916  0.041841  0.066946  0.146444  0.313808  0.225941   0.011494   \n",
      "2662  0.107516  0.064704  0.113841  0.152031  0.292143  0.209681   0.004678   \n",
      "2663  0.106383  0.057597  0.094778  0.139050  0.176660  0.342360   0.014693   \n",
      "2664  0.152988  0.064542  0.082869  0.168127  0.191633  0.263347   0.028716   \n",
      "2665  0.171300  0.070535  0.096247  0.193885  0.245657  0.190757   0.012168   \n",
      "2666  0.114570  0.080324  0.119552  0.176214  0.223537  0.252179   0.019776   \n",
      "2667  0.156713  0.078118  0.102007  0.159818  0.176780  0.250358   0.071729   \n",
      "2668  0.094118  0.090323  0.091082  0.147249  0.340038  0.185958   0.047619   \n",
      "2669  0.153585  0.067547  0.086604  0.136792  0.175472  0.302830   0.048892   \n",
      "2670  0.087660  0.070638  0.070213  0.133617  0.136596  0.319149   0.025761   \n",
      "2671  0.089436  0.076150  0.076474  0.156837  0.141283  0.295528   0.066180   \n",
      "2672  0.168169  0.077358  0.096865  0.155926  0.173012  0.262747   0.087231   \n",
      "2673  0.126260  0.071051  0.083533  0.145463  0.199232  0.269323   0.041370   \n",
      "2674  0.136798  0.068100  0.085424  0.147551  0.185783  0.243728   0.073859   \n",
      "2675  0.209681  0.057642  0.070094  0.136172  0.195220  0.253665   0.028737   \n",
      "2676  0.123834  0.060503  0.074357  0.150975  0.154934  0.342805   0.138423   \n",
      "2677  0.180613  0.073737  0.103563  0.176471  0.206297  0.205468   0.041295   \n",
      "2678  0.265531  0.033743  0.057080  0.110375  0.165563  0.284137   0.321871   \n",
      "2679  0.097317  0.043324  0.083414  0.145167  0.177174  0.302296   0.034542   \n",
      "2680  0.129283  0.080997  0.068536  0.132399  0.130062  0.306075   0.008457   \n",
      "2681  0.131868  0.072527  0.070330  0.204396  0.171429  0.296703   0.020548   \n",
      "2682  0.396226  0.147170  0.105660  0.128302  0.094340  0.079245   0.014563   \n",
      "2683  0.103313  0.061988  0.081226  0.171714  0.236551  0.281796   0.063168   \n",
      "2684  0.143625  0.074501  0.069892  0.182028  0.139017  0.334869   0.126461   \n",
      "2685  0.412752  0.040268  0.057047  0.114094  0.097315  0.124161   0.028926   \n",
      "2686  0.258803  0.053435  0.051711  0.107363  0.213987  0.248215   0.014921   \n",
      "2687  0.124611  0.049844  0.067497  0.135341  0.178262  0.340948   0.122905   \n",
      "2688  0.232574  0.069705  0.079759  0.136729  0.097185  0.280161   0.062670   \n",
      "2689  0.167890  0.082569  0.082569  0.155046  0.176147  0.243119   0.020359   \n",
      "2690  0.175836  0.071747  0.079182  0.138662  0.152788  0.272119   0.021576   \n",
      "2691  0.175056  0.049220  0.068820  0.139198  0.173274  0.303118   0.030964   \n",
      "2692  0.102626  0.062582  0.075711  0.134792  0.166521  0.324726   0.014938   \n",
      "2693  0.135266  0.060386  0.067633  0.137681  0.173913  0.264493   0.044164   \n",
      "2694  0.138476  0.066914  0.068773  0.184015  0.141264  0.246283   0.069009   \n",
      "2695  0.172414  0.055172  0.048276  0.158621  0.137931  0.165517   0.100917   \n",
      "2696  0.111628  0.052972  0.097674  0.156331  0.193798  0.334109   0.046948   \n",
      "2697  0.206148  0.133816  0.068716  0.137432  0.101266  0.182640   0.023077   \n",
      "2698  0.179656  0.077570  0.095865  0.131723  0.139407  0.251006   0.065789   \n",
      "2699  0.206107  0.129771  0.108991  0.163274  0.189143  0.153944   0.002592   \n",
      "2700  0.116222  0.080613  0.103858  0.167656  0.221563  0.224530   0.009786   \n",
      "2701  0.286032  0.055160  0.074288  0.113434  0.117883  0.189947   0.021191   \n",
      "2702  0.156677  0.088328  0.135647  0.180336  0.154048  0.197687   0.079208   \n",
      "2703  0.093565  0.086367  0.084674  0.168925  0.142252  0.292972   0.049355   \n",
      "2704  0.188203  0.097012  0.084206  0.131548  0.176562  0.247187   0.043303   \n",
      "2705  0.204740  0.049990  0.063931  0.115714  0.216092  0.291974   0.011106   \n",
      "2706  0.122885  0.052093  0.068121  0.119768  0.158949  0.324577   0.016880   \n",
      "2707  0.213740  0.081107  0.071565  0.141221  0.116412  0.281489   0.005472   \n",
      "2708  0.224687  0.047782  0.060296  0.110922  0.138225  0.259954   0.055762   \n",
      "2709  0.168919  0.043919  0.077703  0.199324  0.195946  0.243243   0.013274   \n",
      "2710  0.192351  0.061867  0.111361  0.176603  0.165354  0.226097   0.021307   \n",
      "2711  0.152281  0.111579  0.094737  0.120000  0.206316  0.230175   0.009458   \n",
      "2712  0.192140  0.061135  0.082969  0.140830  0.172489  0.201965   0.038615   \n",
      "2713  0.277145  0.084583  0.077984  0.140372  0.149370  0.215357   0.047050   \n",
      "2714  0.214489  0.090131  0.097547  0.144324  0.120936  0.247005   0.002096   \n",
      "2715  0.091099  0.068846  0.077191  0.139082  0.247566  0.293463   0.044505   \n",
      "2716  0.116848  0.078804  0.108696  0.173913  0.176630  0.255435   0.049822   \n",
      "2717  0.099788  0.076433  0.057325  0.157113  0.333333  0.205945   0.002591   \n",
      "2718  0.134571  0.097448  0.099768  0.143852  0.359629  0.139211   0.024523   \n",
      "2719  0.192821  0.105175  0.085142  0.207012  0.186144  0.158598   0.012917   \n",
      "2720  0.160089  0.096720  0.106726  0.173986  0.156198  0.237910   0.033358   \n",
      "2721  0.059424  0.057567  0.086815  0.146240  0.153203  0.366295   0.020873   \n",
      "2722  0.164747  0.082949  0.105991  0.145161  0.186636  0.207373   0.005658   \n",
      "2723  0.088534  0.079100  0.137881  0.187954  0.373730  0.108128   0.004337   \n",
      "2724  0.039012  0.101430  0.089727  0.312094  0.263979  0.158648   0.030374   \n",
      "2725  0.110901  0.060982  0.081489  0.167836  0.162979  0.305720   0.018645   \n",
      "2726  0.228253  0.067502  0.096033  0.167015  0.173278  0.189979   0.097470   \n",
      "2727  0.143599  0.094946  0.083609  0.161077  0.136986  0.291450   0.034860   \n",
      "2728  0.147488  0.172609  0.144787  0.219881  0.117234  0.148838   0.007862   \n",
      "2729  0.046784  0.116959  0.201754  0.274854  0.178363  0.158626   0.003331   \n",
      "2730  0.053057  0.102312  0.128761  0.281121  0.220304  0.173741   0.008324   \n",
      "2731  0.112043  0.057397  0.084393  0.167344  0.174944  0.335212   0.283620   \n",
      "2732  0.148185  0.082157  0.112399  0.212198  0.254536  0.169355   0.029597   \n",
      "2733  0.209546  0.077416  0.108847  0.218859  0.190338  0.147264   0.033689   \n",
      "2734  0.143921  0.119107  0.111663  0.263027  0.213400  0.101737   0.008097   \n",
      "2735  0.176900  0.082229  0.081958  0.136327  0.122802  0.314309   0.077415   \n",
      "2736  0.289906  0.056235  0.074397  0.156479  0.110024  0.227733   0.059572   \n",
      "2737  0.202658  0.119601  0.126246  0.146179  0.142857  0.205980   0.000000   \n",
      "2738  0.211736  0.072742  0.063548  0.131422  0.176312  0.276636   0.015576   \n",
      "2739  0.155830  0.071879  0.086694  0.147051  0.156379  0.261180   0.082267   \n",
      "2740  0.127669  0.082835  0.081127  0.165243  0.176772  0.278395   0.057971   \n",
      "2741  0.099707  0.067449  0.064516  0.202346  0.175953  0.161290   0.061674   \n",
      "2742  0.113422  0.068263  0.093258  0.145558  0.133375  0.310019   0.020099   \n",
      "2743  0.107504  0.053752  0.088877  0.132517  0.121341  0.324109   0.053662   \n",
      "2744  0.088581  0.046094  0.062844  0.158821  0.184864  0.387150   0.057652   \n",
      "2745  0.145812  0.064116  0.064116  0.143744  0.180972  0.287487   0.019444   \n",
      "2746  0.120525  0.140811  0.130072  0.169451  0.208831  0.189737   0.010782   \n",
      "2747  0.158009  0.080952  0.081818  0.144156  0.222944  0.221212   0.028460   \n",
      "2748  0.194493  0.077797  0.092220  0.165210  0.152535  0.208479   0.134469   \n",
      "2749  0.076854  0.061124  0.087865  0.161348  0.276854  0.293708   0.063713   \n",
      "2750  0.233405  0.085653  0.100642  0.171306  0.175589  0.211991   0.093220   \n",
      "2751  0.042791  0.049302  0.083721  0.191628  0.236279  0.247442   0.117419   \n",
      "2752  0.260496  0.077948  0.082533  0.186130  0.156183  0.178106   0.278896   \n",
      "\n",
      "      주말청소년고객비율  주중청년1고객비율  주말청년1고객비율  주중청년2고객비율  주말청년2고객비율  주중장년고객비율  \\\n",
      "0      0.042254   0.397490   0.470657   0.372908   0.333333  0.191423   \n",
      "1      0.226438   0.215330   0.276622   0.115640   0.155447  0.364643   \n",
      "2      0.269209   0.220396   0.246443   0.211455   0.155948  0.346786   \n",
      "3      0.129845   0.265379   0.191860   0.267525   0.284884  0.304006   \n",
      "4      0.400000   0.188525   0.224719   0.073770   0.078652  0.218579   \n",
      "5      0.238227   0.250698   0.286704   0.200457   0.157895  0.295864   \n",
      "6      0.230238   0.215107   0.263239   0.152117   0.118189  0.368008   \n",
      "7      0.173397   0.236902   0.225653   0.223994   0.304038  0.328778   \n",
      "8      0.215539   0.237317   0.295739   0.232158   0.238095  0.225279   \n",
      "9      0.180534   0.243533   0.288854   0.160566   0.167975  0.268424   \n",
      "10     0.106494   0.274461   0.262338   0.201493   0.187013  0.310945   \n",
      "11     0.198718   0.302400   0.256410   0.140800   0.173077  0.185600   \n",
      "12     0.050710   0.332095   0.286004   0.364042   0.342799  0.202823   \n",
      "13     0.184783   0.187715   0.361413   0.082664   0.119565  0.244546   \n",
      "14     0.116769   0.250116   0.254609   0.230858   0.198420  0.378422   \n",
      "15     0.165414   0.229199   0.233083   0.211931   0.274436  0.320251   \n",
      "16     0.469779   0.185013   0.192580   0.119561   0.076282  0.258274   \n",
      "17     0.227620   0.221274   0.213740   0.143554   0.114504  0.410546   \n",
      "18     0.177249   0.329897   0.272487   0.309278   0.248677  0.191294   \n",
      "19     0.051159   0.410210   0.409273   0.288666   0.310951  0.194774   \n",
      "20     0.087302   0.273273   0.309524   0.321321   0.365079  0.249249   \n",
      "21     0.072917   0.252101   0.166667   0.226891   0.218750  0.294118   \n",
      "22     0.192661   0.219251   0.100917   0.128342   0.165138  0.443850   \n",
      "23     0.032738   0.267176   0.273810   0.332061   0.386905  0.320611   \n",
      "24     0.090323   0.253388   0.229032   0.268293   0.325806  0.355014   \n",
      "25     0.102703   0.330059   0.389189   0.190570   0.167568  0.361493   \n",
      "26     0.013477   0.375272   0.477089   0.217320   0.245283  0.340959   \n",
      "27     0.014337   0.284907   0.397849   0.342211   0.344086  0.321227   \n",
      "28     0.150943   0.206704   0.188679   0.217877   0.113208  0.446927   \n",
      "29     0.112462   0.268608   0.346505   0.171521   0.158055  0.271845   \n",
      "30     0.078652   0.308257   0.342697   0.302752   0.292135  0.190826   \n",
      "31     0.041494   0.284951   0.381743   0.296527   0.319502  0.389136   \n",
      "32     0.037801   0.335854   0.374570   0.301197   0.293814  0.251418   \n",
      "33     0.115152   0.281367   0.275758   0.221570   0.295455  0.327816   \n",
      "34     0.029070   0.336088   0.308140   0.349862   0.418605  0.190083   \n",
      "35     0.043062   0.321637   0.291866   0.333333   0.296651  0.159844   \n",
      "36     0.129630   0.146679   0.267490   0.359182   0.226337  0.385032   \n",
      "37     0.061618   0.253929   0.273942   0.311855   0.330364  0.330265   \n",
      "38     0.120332   0.160851   0.165975   0.312340   0.253112  0.349787   \n",
      "39     0.027363   0.297628   0.373134   0.270849   0.303483  0.312930   \n",
      "40     0.105195   0.291283   0.331169   0.275077   0.279221  0.341656   \n",
      "41     0.057549   0.353118   0.380501   0.330416   0.343263  0.224836   \n",
      "42     0.037677   0.248197   0.274725   0.335337   0.378336  0.299279   \n",
      "43     0.120968   0.163090   0.221774   0.301860   0.245968  0.343348   \n",
      "44     0.084967   0.192015   0.189542   0.161597   0.215686  0.368821   \n",
      "45     0.020353   0.263879   0.362280   0.396346   0.389417  0.308855   \n",
      "46     0.196262   0.195980   0.228037   0.185930   0.173832  0.361091   \n",
      "47     0.155660   0.229167   0.339623   0.327652   0.146226  0.297348   \n",
      "48     0.423410   0.277276   0.273121   0.121612   0.093931  0.250174   \n",
      "49     0.095588   0.171745   0.139706   0.116343   0.169118  0.448753   \n",
      "50     0.099338   0.084367   0.165563   0.163772   0.185430  0.578164   \n",
      "51     0.223529   0.235556   0.188235   0.240000   0.258824  0.351111   \n",
      "52     0.206897   0.237003   0.224138   0.226300   0.206897  0.327217   \n",
      "53     0.116541   0.201176   0.266917   0.184706   0.195489  0.437647   \n",
      "54     0.084746   0.309091   0.271186   0.410909   0.440678  0.218182   \n",
      "55     0.101695   0.292146   0.296112   0.317731   0.309571  0.233637   \n",
      "56     0.086410   0.301614   0.366064   0.342710   0.285153  0.245597   \n",
      "57     0.127273   0.189869   0.255556   0.238786   0.194949  0.463650   \n",
      "58     0.089504   0.263908   0.343207   0.283065   0.242756  0.354176   \n",
      "59     0.102775   0.326293   0.372080   0.324102   0.282770  0.250131   \n",
      "60     0.127072   0.193399   0.276243   0.299363   0.331492  0.259988   \n",
      "61     0.071565   0.296970   0.349237   0.345688   0.355916  0.265268   \n",
      "62     0.055085   0.391045   0.399718   0.306468   0.300847  0.206965   \n",
      "63     0.037009   0.326061   0.341390   0.388485   0.424471  0.223030   \n",
      "64     0.062718   0.271975   0.334495   0.304033   0.320557  0.319545   \n",
      "65     0.030055   0.417226   0.336066   0.326622   0.445355  0.192394   \n",
      "66     0.009119   0.169546   0.212766   0.372361   0.340426  0.400512   \n",
      "67     0.085714   0.205725   0.163265   0.307692   0.314286  0.336315   \n",
      "68     0.144790   0.314350   0.346414   0.230493   0.231394  0.318386   \n",
      "69     0.078153   0.250266   0.374778   0.291711   0.230906  0.306057   \n",
      "70     0.033784   0.361275   0.456757   0.387745   0.325676  0.208333   \n",
      "71     0.036166   0.345741   0.378843   0.366868   0.381555  0.226023   \n",
      "72     0.111111   0.178571   0.244444   0.231092   0.207407  0.455882   \n",
      "73     0.061381   0.317017   0.320972   0.314518   0.350384  0.247032   \n",
      "74     0.021798   0.259234   0.237057   0.358413   0.356948  0.286594   \n",
      "75     0.009119   0.216216   0.246201   0.485521   0.471125  0.196911   \n",
      "76     0.087447   0.261006   0.246827   0.316352   0.282087  0.280503   \n",
      "77     0.045010   0.298590   0.284410   0.340886   0.307893  0.268379   \n",
      "78     0.026876   0.281440   0.266517   0.281440   0.318029  0.348761   \n",
      "79     0.037344   0.233123   0.263485   0.232223   0.259336  0.419442   \n",
      "80     0.029876   0.383277   0.486307   0.357644   0.309544  0.210558   \n",
      "81     0.130199   0.266736   0.325497   0.225221   0.292948  0.226258   \n",
      "82     0.254219   0.225451   0.217300   0.257181   0.227848  0.281563   \n",
      "83     0.120594   0.251735   0.304267   0.261830   0.235622  0.293375   \n",
      "84     0.052632   0.100000   0.157895   0.375000   0.431579  0.410714   \n",
      "85     0.101467   0.316494   0.327628   0.291451   0.297066  0.280656   \n",
      "86     0.084590   0.296783   0.359296   0.318881   0.277219  0.269371   \n",
      "87     0.039959   0.302687   0.342213   0.262612   0.268443  0.301273   \n",
      "88     0.036161   0.394932   0.389430   0.391224   0.378303  0.182324   \n",
      "89     0.057343   0.347759   0.372028   0.339001   0.304895  0.216383   \n",
      "90     0.021583   0.383110   0.282974   0.213182   0.306954  0.317199   \n",
      "91     0.082596   0.308108   0.356932   0.190270   0.188791  0.307027   \n",
      "92     0.164251   0.155499   0.260870   0.155499   0.144928  0.285714   \n",
      "93     0.067204   0.366391   0.325269   0.179063   0.212366  0.266758   \n",
      "94     0.046543   0.328061   0.356383   0.232143   0.238032  0.317857   \n",
      "95     0.109515   0.335177   0.369838   0.212821   0.236086  0.312398   \n",
      "96     0.096515   0.255132   0.206434   0.200391   0.219839  0.365591   \n",
      "97     0.092308   0.329795   0.349451   0.203184   0.197802  0.313116   \n",
      "98     0.028763   0.426941   0.410355   0.270151   0.254075  0.245859   \n",
      "99     0.038031   0.352386   0.398210   0.335984   0.250559  0.270875   \n",
      "100    0.051948   0.329753   0.334416   0.218045   0.224026  0.311493   \n",
      "101    0.034274   0.347674   0.427419   0.265827   0.228831  0.329136   \n",
      "102    0.071856   0.529887   0.293413   0.109855   0.167665  0.231018   \n",
      "103    0.153690   0.299535   0.283969   0.144909   0.174555  0.305661   \n",
      "104    0.129730   0.324364   0.261261   0.234182   0.210811  0.298182   \n",
      "105    0.028272   0.375386   0.440838   0.372060   0.328796  0.215253   \n",
      "106    0.100962   0.283368   0.365385   0.182752   0.187500  0.386037   \n",
      "107    0.089754   0.394020   0.410643   0.215893   0.215647  0.259009   \n",
      "108    0.151282   0.279070   0.330769   0.235592   0.210256  0.304348   \n",
      "109    0.072513   0.242939   0.278246   0.235941   0.230185  0.360660   \n",
      "110    0.109496   0.358913   0.350775   0.234213   0.227713  0.257794   \n",
      "111    0.043912   0.226672   0.255489   0.277002   0.271457  0.359662   \n",
      "112    0.219917   0.241749   0.265560   0.124587   0.093361  0.353960   \n",
      "113    0.182203   0.295989   0.402542   0.114799   0.139831  0.275242   \n",
      "114    0.144144   0.294118   0.310811   0.294118   0.288288  0.195502   \n",
      "115    0.081699   0.381595   0.316993   0.296933   0.290850  0.187730   \n",
      "116    0.142857   0.234783   0.201681   0.275362   0.310924  0.362319   \n",
      "117    0.089716   0.289773   0.223195   0.178030   0.199125  0.297348   \n",
      "118    0.088660   0.163575   0.191753   0.227656   0.228866  0.395447   \n",
      "119    0.061069   0.216981   0.160305   0.292453   0.229008  0.271226   \n",
      "120    0.055838   0.256162   0.286802   0.231514   0.213198  0.440141   \n",
      "121    0.114320   0.149828   0.203369   0.320848   0.208183  0.389354   \n",
      "122    0.110169   0.241973   0.286925   0.254093   0.246368  0.351265   \n",
      "123    0.026352   0.482627   0.495146   0.286054   0.291262  0.160876   \n",
      "124    0.028037   0.370370   0.439252   0.399691   0.406542  0.213735   \n",
      "125    0.013793   0.216867   0.289655   0.600402   0.489655  0.171687   \n",
      "126    0.009836   0.410571   0.465574   0.390655   0.344262  0.171582   \n",
      "127    0.037037   0.291536   0.398148   0.235110   0.388889  0.407524   \n",
      "128    0.029070   0.221106   0.360465   0.420436   0.308140  0.242881   \n",
      "129    0.059908   0.200215   0.271889   0.400431   0.410138  0.315393   \n",
      "130    0.003521   0.246377   0.320423   0.434783   0.397887  0.296196   \n",
      "131    0.056075   0.215152   0.205607   0.290909   0.205607  0.424242   \n",
      "132    0.000000   0.268887   0.365314   0.448146   0.413284  0.256868   \n",
      "133    0.058723   0.413291   0.453617   0.349980   0.328511  0.173810   \n",
      "134    0.114385   0.257834   0.327556   0.259483   0.266898  0.352941   \n",
      "135    0.042105   0.334758   0.371429   0.326686   0.323308  0.215100   \n",
      "136    0.090909   0.253165   0.333333   0.177215   0.030303  0.417722   \n",
      "137    0.032051   0.264516   0.333333   0.313978   0.282051  0.223656   \n",
      "138    0.010870   0.377778   0.429348   0.387654   0.288043  0.202469   \n",
      "139    0.022152   0.257171   0.386076   0.354105   0.278481  0.287834   \n",
      "140    0.031429   0.121690   0.148571   0.346154   0.328571  0.462799   \n",
      "141    0.045872   0.209544   0.275229   0.360996   0.392202  0.396957   \n",
      "142    0.008850   0.226804   0.389381   0.348454   0.371681  0.377320   \n",
      "143    0.000000   0.215962   0.170588   0.382629   0.282353  0.293427   \n",
      "144    0.030928   0.233333   0.254296   0.312963   0.336770  0.350000   \n",
      "145    0.024845   0.197406   0.254658   0.321326   0.304348  0.348703   \n",
      "146    0.105263   0.210641   0.244361   0.337676   0.327068  0.370250   \n",
      "147    0.056266   0.231837   0.289003   0.357242   0.337596  0.315132   \n",
      "148    0.000000   0.025641   0.076923   0.205128   0.153846  0.623932   \n",
      "149    0.020833   0.220280   0.259259   0.375874   0.333333  0.328671   \n",
      "150    0.030806   0.241935   0.260664   0.270528   0.289100  0.414223   \n",
      "151    0.022472   0.203976   0.296629   0.312224   0.420225  0.409426   \n",
      "152    0.030303   0.295520   0.358586   0.364156   0.376263  0.294566   \n",
      "153    0.028369   0.230932   0.248227   0.381356   0.354610  0.332627   \n",
      "154    0.034014   0.284153   0.367347   0.299180   0.306122  0.337432   \n",
      "155    0.054313   0.300529   0.376997   0.293122   0.287540  0.339683   \n",
      "156    0.033019   0.190265   0.183962   0.268437   0.235849  0.417404   \n",
      "157    0.023585   0.192964   0.330189   0.337953   0.254717  0.400320   \n",
      "158    0.142157   0.320755   0.348039   0.218868   0.205882  0.300000   \n",
      "159    0.023234   0.241108   0.343866   0.323261   0.344796  0.359459   \n",
      "160    0.000000   0.211215   0.176056   0.390654   0.295775  0.325234   \n",
      "161    0.136364   0.237370   0.233471   0.153168   0.136364  0.402566   \n",
      "162    0.022792   0.438127   0.444444   0.169454   0.168091  0.284281   \n",
      "163    0.056893   0.229872   0.242888   0.291132   0.304158  0.351225   \n",
      "164    0.021053   0.222420   0.205263   0.240214   0.268421  0.414591   \n",
      "165    0.025472   0.179312   0.254717   0.331344   0.303774  0.372549   \n",
      "166    0.047170   0.268775   0.283019   0.347826   0.377358  0.264822   \n",
      "167    0.037037   0.254032   0.251852   0.274194   0.237037  0.405242   \n",
      "168    0.021067   0.175481   0.242978   0.347596   0.348315  0.405288   \n",
      "169    0.050100   0.391464   0.458918   0.311258   0.298597  0.227373   \n",
      "170    0.045105   0.320101   0.360836   0.340310   0.319032  0.224468   \n",
      "171    0.028698   0.489416   0.439294   0.248877   0.302428  0.178961   \n",
      "172    0.030812   0.468401   0.504202   0.298327   0.299720  0.196097   \n",
      "173    0.023443   0.637866   0.679839   0.192454   0.162760  0.137531   \n",
      "174    0.059296   0.240257   0.251759   0.217918   0.231156  0.383793   \n",
      "175    0.053471   0.294843   0.352720   0.359696   0.332083  0.266055   \n",
      "176    0.048996   0.302349   0.379920   0.364486   0.331727  0.240717   \n",
      "177    0.055767   0.395522   0.369455   0.233065   0.217997  0.252009   \n",
      "178    0.015306   0.562016   0.530612   0.292248   0.306122  0.108527   \n",
      "179    0.091049   0.316705   0.317901   0.245940   0.195988  0.311485   \n",
      "180    0.073499   0.449740   0.436853   0.248700   0.213251  0.211005   \n",
      "181    0.031297   0.425037   0.436662   0.306779   0.299553  0.170213   \n",
      "182    0.105578   0.308385   0.400398   0.230076   0.181275  0.309078   \n",
      "183    0.040248   0.307910   0.263158   0.255179   0.368421  0.362524   \n",
      "184    0.064516   0.130435   0.161290   0.344203   0.344086  0.452899   \n",
      "185    0.049869   0.383576   0.430446   0.209979   0.183727  0.311850   \n",
      "186    0.070423   0.226252   0.258216   0.286701   0.230047  0.371330   \n",
      "187    0.016393   0.157042   0.318761   0.318503   0.316940  0.442251   \n",
      "188    0.151436   0.173719   0.154047   0.145880   0.117493  0.496659   \n",
      "189    0.064935   0.196000   0.253247   0.222000   0.110390  0.428000   \n",
      "190    0.079439   0.292169   0.345794   0.150602   0.172897  0.433735   \n",
      "191    0.060914   0.359408   0.380711   0.187104   0.192893  0.327696   \n",
      "192    0.048327   0.373167   0.411400   0.271994   0.247831  0.272361   \n",
      "193    0.042857   0.161702   0.242857   0.306383   0.228571  0.387234   \n",
      "194    0.072727   0.353791   0.390909   0.223827   0.218182  0.296029   \n",
      "195    0.204710   0.173160   0.201087   0.261905   0.250000  0.351190   \n",
      "196    0.161064   0.243203   0.348739   0.151583   0.175070  0.284544   \n",
      "197    0.047809   0.326105   0.357238   0.353741   0.383798  0.267857   \n",
      "198    0.088186   0.313230   0.349418   0.294530   0.334443  0.233287   \n",
      "199    0.031690   0.326419   0.378521   0.364246   0.353873  0.233679   \n",
      "200    0.037099   0.277199   0.326307   0.327319   0.342327  0.307805   \n",
      "201    0.003279   0.253681   0.396721   0.433319   0.318033  0.247371   \n",
      "202    0.425300   0.160633   0.206107   0.166774   0.160305  0.227214   \n",
      "203    0.163851   0.192587   0.219595   0.271802   0.277027  0.302326   \n",
      "204    0.234397   0.209367   0.259362   0.145316   0.178918  0.286629   \n",
      "205    0.207729   0.302098   0.231884   0.155245   0.251208  0.285315   \n",
      "206    0.020468   0.170763   0.251462   0.371928   0.333333  0.393920   \n",
      "207    0.133333   0.226519   0.238095   0.294659   0.342857  0.208103   \n",
      "208    0.253521   0.158491   0.169014   0.098113   0.154930  0.245283   \n",
      "209    0.062500   0.304762   0.475000   0.260317   0.225000  0.339683   \n",
      "210    0.097778   0.222059   0.248889   0.288235   0.235556  0.386765   \n",
      "211    0.159091   0.220116   0.286364   0.262243   0.237879  0.325434   \n",
      "212    0.027536   0.236321   0.339130   0.334906   0.321739  0.353302   \n",
      "213    0.056911   0.225126   0.268293   0.398995   0.378049  0.289447   \n",
      "214    0.077684   0.213238   0.221751   0.276015   0.309322  0.390993   \n",
      "215    0.027140   0.161428   0.233820   0.371307   0.308977  0.422595   \n",
      "216    0.060606   0.243437   0.222222   0.341289   0.373737  0.312649   \n",
      "217    0.077181   0.273622   0.305369   0.152559   0.281879  0.372047   \n",
      "218    0.021127   0.168000   0.190141   0.374000   0.295775  0.406000   \n",
      "219    0.038835   0.276336   0.213592   0.364885   0.364078  0.302290   \n",
      "220    0.063158   0.274295   0.357895   0.282132   0.289474  0.333856   \n",
      "221    0.015625   0.112805   0.109375   0.100610   0.062500  0.542683   \n",
      "222    0.041034   0.253093   0.324340   0.367358   0.339517  0.282569   \n",
      "223    0.013889   0.186735   0.201389   0.309184   0.451389  0.439796   \n",
      "224    0.061321   0.250947   0.188679   0.246212   0.254717  0.417614   \n",
      "225    0.031901   0.290561   0.301574   0.411617   0.443216  0.234602   \n",
      "226    0.062069   0.271093   0.282759   0.244813   0.206897  0.275242   \n",
      "227    0.188317   0.169554   0.202921   0.174257   0.172175  0.424505   \n",
      "228    0.226293   0.165295   0.244253   0.226193   0.239943  0.300024   \n",
      "229    0.015801   0.390661   0.399549   0.353455   0.370203  0.208049   \n",
      "230    0.009756   0.180914   0.285366   0.353234   0.314634  0.400271   \n",
      "231    0.029630   0.343750   0.400000   0.377841   0.370370  0.215909   \n",
      "232    0.010989   0.369099   0.432234   0.321888   0.347985  0.221745   \n",
      "233    0.027573   0.406454   0.455441   0.322681   0.321024  0.236581   \n",
      "234    0.037994   0.400468   0.424012   0.300937   0.282675  0.221311   \n",
      "235    0.018739   0.358073   0.333901   0.367188   0.369676  0.195312   \n",
      "236    0.059371   0.290216   0.356228   0.370647   0.311991  0.246269   \n",
      "237    0.033088   0.372051   0.235294   0.303085   0.319853  0.237750   \n",
      "238    0.040260   0.356763   0.377273   0.372464   0.335065  0.179469   \n",
      "239    0.028490   0.361612   0.316239   0.316013   0.398860  0.234358   \n",
      "240    0.015068   0.412500   0.432877   0.330769   0.332877  0.207212   \n",
      "241    0.250000   0.271262   0.244898   0.153089   0.168367  0.281110   \n",
      "242    0.101617   0.274236   0.281755   0.294323   0.293303  0.319651   \n",
      "243    0.114662   0.258252   0.321429   0.369417   0.308271  0.296602   \n",
      "244    0.053435   0.341433   0.362302   0.314202   0.327657  0.264349   \n",
      "245    0.014493   0.300112   0.282609   0.408735   0.420290  0.228443   \n",
      "246    0.039474   0.314394   0.381579   0.344697   0.407895  0.314394   \n",
      "247    0.082707   0.284040   0.310777   0.228133   0.210526  0.325969   \n",
      "248    0.083902   0.353402   0.363574   0.255268   0.257844  0.276942   \n",
      "249    0.064629   0.734290   0.688210   0.104053   0.118777  0.106557   \n",
      "250    0.238095   0.300000   0.312925   0.100000   0.061224  0.350000   \n",
      "251    0.400768   0.244059   0.235595   0.100495   0.092190  0.245050   \n",
      "252    0.107143   0.315266   0.379121   0.231256   0.225275  0.307136   \n",
      "253    0.157368   0.224092   0.287554   0.200620   0.185980  0.344553   \n",
      "254    0.096657   0.332604   0.348110   0.212254   0.247093  0.314278   \n",
      "255    0.130159   0.246706   0.295238   0.206192   0.233862  0.323123   \n",
      "256    0.146739   0.244657   0.304348   0.174625   0.168478  0.344247   \n",
      "257    0.061776   0.407917   0.243243   0.188468   0.250965  0.240964   \n",
      "258    0.118457   0.328633   0.371901   0.062907   0.096419  0.382863   \n",
      "259    0.073350   0.307518   0.343928   0.226050   0.240424  0.263515   \n",
      "260    0.108280   0.229060   0.270701   0.195726   0.207006  0.329060   \n",
      "261    0.055556   0.222615   0.188034   0.231449   0.230769  0.321555   \n",
      "262    0.203125   0.174840   0.218750   0.197228   0.207031  0.446695   \n",
      "263    0.175542   0.351838   0.329389   0.201800   0.236686  0.240810   \n",
      "264    0.047101   0.188654   0.202899   0.249340   0.202899  0.468338   \n",
      "265    0.025591   0.247066   0.289370   0.321382   0.354331  0.327901   \n",
      "266    0.051522   0.474026   0.482436   0.140260   0.175644  0.262338   \n",
      "267    0.025225   0.291076   0.340541   0.311093   0.304505  0.355296   \n",
      "268    0.069364   0.283268   0.285405   0.240222   0.256503  0.340199   \n",
      "269    0.094233   0.354491   0.407876   0.219760   0.247539  0.256287   \n",
      "270    0.031022   0.275433   0.370438   0.286095   0.299270  0.319858   \n",
      "271    0.054348   0.292576   0.396739   0.248908   0.184783  0.321689   \n",
      "272    0.026846   0.190926   0.281879   0.344045   0.295302  0.323251   \n",
      "273    0.010309   0.211699   0.257732   0.342618   0.360825  0.359331   \n",
      "274    0.046875   0.161290   0.343750   0.544355   0.421875  0.262097   \n",
      "275    0.056818   0.143172   0.085227   0.154185   0.244318  0.522026   \n",
      "276    0.090909   0.111111   0.090909   0.370370   0.181818  0.370370   \n",
      "277    0.066667   0.250000   0.133333   0.384615   0.266667  0.326923   \n",
      "278    0.000000   0.016949   0.076923   0.406780   0.076923  0.542373   \n",
      "279    0.060606   0.276923   0.454545   0.253846   0.151515  0.369231   \n",
      "280    0.018939   0.690986   0.655303   0.156768   0.166667  0.118782   \n",
      "281    0.029605   0.218236   0.361842   0.320606   0.299342  0.383805   \n",
      "282    0.093519   0.234053   0.262510   0.323654   0.340443  0.260362   \n",
      "283    0.016854   0.367247   0.436798   0.380187   0.400281  0.206158   \n",
      "284    0.057351   0.264732   0.289984   0.378739   0.376414  0.271543   \n",
      "285    0.032258   0.237473   0.435484   0.305011   0.161290  0.407407   \n",
      "286    0.053360   0.294163   0.343874   0.315175   0.353755  0.275486   \n",
      "287    0.041741   0.315628   0.337478   0.318701   0.341030  0.244074   \n",
      "288    0.107843   0.117895   0.220588   0.410526   0.289216  0.343158   \n",
      "289    0.040816   0.270588   0.387755   0.400000   0.377551  0.300000   \n",
      "290    0.237500   0.262366   0.275000   0.112903   0.122500  0.315054   \n",
      "291    0.058577   0.183422   0.243724   0.254993   0.229079  0.441744   \n",
      "292    0.091592   0.351690   0.379880   0.317339   0.271772  0.221374   \n",
      "293    0.339450   0.188647   0.302752   0.088035   0.161206  0.166213   \n",
      "294    0.058722   0.423411   0.421416   0.273359   0.285838  0.235846   \n",
      "295    0.151406   0.232573   0.256669   0.234822   0.276857  0.345647   \n",
      "296    0.026316   0.387795   0.432331   0.338583   0.348371  0.198327   \n",
      "297    0.245833   0.175577   0.197917   0.296476   0.241667  0.295261   \n",
      "298    0.067729   0.159249   0.247012   0.296940   0.229084  0.455494   \n",
      "299    0.019685   0.156727   0.299213   0.382802   0.381890  0.405687   \n",
      "300    0.089261   0.205084   0.306834   0.311935   0.352859  0.394227   \n",
      "301    0.031301   0.288471   0.337727   0.369619   0.405272  0.224146   \n",
      "302    0.067416   0.203548   0.262172   0.251167   0.277154  0.446312   \n",
      "303    0.053333   0.244418   0.276000   0.309596   0.349333  0.341581   \n",
      "304    0.194805   0.218009   0.259740   0.161137   0.155844  0.236967   \n",
      "305    0.190141   0.222051   0.326291   0.279877   0.220657  0.270625   \n",
      "306    0.059812   0.387269   0.334677   0.212374   0.243952  0.289114   \n",
      "307    0.076923   0.333333   0.323077   0.328321   0.261538  0.300752   \n",
      "308    0.029656   0.475459   0.480427   0.149232   0.136418  0.243431   \n",
      "309    0.113772   0.293037   0.273453   0.241296   0.249501  0.260638   \n",
      "310    0.061028   0.237050   0.301927   0.338422   0.328694  0.306861   \n",
      "311    0.246921   0.289913   0.337243   0.177474   0.137243  0.280812   \n",
      "312    0.082079   0.350098   0.324213   0.256348   0.229822  0.287109   \n",
      "313    0.000000   0.297297   0.153846   0.297297   0.230769  0.351351   \n",
      "314    0.026316   0.211688   0.289474   0.376623   0.388158  0.362338   \n",
      "315    0.017787   0.433586   0.399209   0.325888   0.367589  0.191065   \n",
      "316    0.014085   0.143519   0.316901   0.336934   0.387324  0.424383   \n",
      "317    0.061372   0.235099   0.220217   0.293046   0.335740  0.383278   \n",
      "318    0.031034   0.336894   0.325862   0.306631   0.339655  0.277259   \n",
      "319    0.017931   0.214957   0.233103   0.390598   0.406897  0.302991   \n",
      "320    0.004545   0.244152   0.295455   0.378655   0.327273  0.323099   \n",
      "321    0.007407   0.245455   0.325926   0.434091   0.362963  0.243182   \n",
      "322    0.140893   0.191981   0.288660   0.442284   0.340206  0.303767   \n",
      "323    0.019830   0.208945   0.291785   0.344514   0.325779  0.371768   \n",
      "324    0.074074   0.233010   0.370370   0.242718   0.037037  0.184466   \n",
      "325    0.133803   0.242197   0.204225   0.205993   0.292254  0.387016   \n",
      "326    0.032061   0.271626   0.438168   0.325444   0.235115  0.334742   \n",
      "327    0.006803   0.157579   0.238095   0.315159   0.285714  0.458358   \n",
      "328    0.018382   0.225806   0.367647   0.226439   0.147059  0.428210   \n",
      "329    0.075856   0.390302   0.433858   0.326434   0.275671  0.205204   \n",
      "330    0.046742   0.227076   0.284703   0.298010   0.347025  0.358131   \n",
      "331    0.059247   0.356753   0.429944   0.304296   0.339472  0.235936   \n",
      "332    0.116959   0.226328   0.210526   0.147806   0.187135  0.355658   \n",
      "333    0.015000   0.222798   0.335000   0.260794   0.255000  0.416235   \n",
      "334    0.224012   0.314997   0.278184   0.186450   0.177160  0.264621   \n",
      "335    0.090164   0.302920   0.262295   0.296837   0.331967  0.251825   \n",
      "336    0.089286   0.303725   0.315476   0.177650   0.160714  0.318052   \n",
      "337    0.120944   0.336207   0.315634   0.181034   0.144543  0.311576   \n",
      "338    0.089147   0.292419   0.290698   0.246691   0.209302  0.297232   \n",
      "339    0.008310   0.396947   0.324100   0.181679   0.177285  0.271756   \n",
      "340    0.113821   0.306397   0.219512   0.259259   0.308943  0.292929   \n",
      "341    0.103261   0.403564   0.282609   0.167715   0.184783  0.298742   \n",
      "342    0.074803   0.315867   0.342520   0.287823   0.218504  0.274539   \n",
      "343    0.046296   0.271739   0.231481   0.170290   0.166667  0.409420   \n",
      "344    0.120000   0.270925   0.280000   0.266520   0.160000  0.233480   \n",
      "345    0.025862   0.674024   0.517241   0.088285   0.112069  0.185059   \n",
      "346    0.043796   0.847095   0.613139   0.076453   0.094891  0.058104   \n",
      "347    0.166667   0.809859   0.458333   0.063380   0.125000  0.070423   \n",
      "348    0.095462   0.230610   0.258216   0.310238   0.264476  0.336608   \n",
      "349    0.325726   0.192243   0.221992   0.205734   0.163900  0.258010   \n",
      "350    0.047337   0.148490   0.245562   0.317114   0.292899  0.479027   \n",
      "351    0.208835   0.168714   0.196787   0.187460   0.180723  0.366516   \n",
      "352    0.065574   0.204866   0.249180   0.256934   0.193443  0.392701   \n",
      "353    0.011016   0.206635   0.299878   0.356967   0.342717  0.381611   \n",
      "354    0.061224   0.293305   0.310204   0.303932   0.281633  0.336876   \n",
      "355    0.027668   0.198473   0.229249   0.392176   0.292490  0.339695   \n",
      "356    0.092838   0.281120   0.360743   0.198133   0.209549  0.327801   \n",
      "357    0.059701   0.228070   0.247761   0.285862   0.295522  0.389061   \n",
      "358    0.036205   0.254579   0.363296   0.380952   0.322097  0.297070   \n",
      "359    0.088496   0.183288   0.327434   0.148248   0.168142  0.560647   \n",
      "360    0.044776   0.360544   0.422886   0.188776   0.233831  0.277211   \n",
      "361    0.105337   0.200869   0.242978   0.333655   0.297753  0.338967   \n",
      "362    0.000000   0.181818   0.264706   0.309091   0.279412  0.368182   \n",
      "363    0.020513   0.215719   0.276923   0.160535   0.210256  0.530100   \n",
      "364    0.089147   0.228835   0.234496   0.284996   0.228682  0.349539   \n",
      "365    0.145078   0.184358   0.181347   0.178771   0.202073  0.512104   \n",
      "366    0.084536   0.239344   0.216495   0.295082   0.280412  0.352459   \n",
      "367    0.048832   0.197520   0.326964   0.312356   0.305732  0.397795   \n",
      "368    0.117462   0.374231   0.356581   0.244507   0.218668  0.253823   \n",
      "369    0.176568   0.280308   0.260726   0.246600   0.247525  0.229450   \n",
      "370    0.027451   0.470994   0.435294   0.241713   0.235294  0.237569   \n",
      "371    0.050725   0.249106   0.275362   0.174017   0.206522  0.407628   \n",
      "372    0.078680   0.214339   0.312183   0.310680   0.294416  0.309186   \n",
      "373    0.196078   0.292262   0.331933   0.095121   0.092437  0.344505   \n",
      "374    0.155477   0.254768   0.272085   0.153951   0.155477  0.347411   \n",
      "375    0.047297   0.204108   0.260135   0.260591   0.317568  0.382542   \n",
      "376    0.022222   0.846154   0.688889   0.110577   0.266667  0.043269   \n",
      "377    0.015707   0.786329   0.853403   0.066835   0.089005  0.063291   \n",
      "378    0.024518   0.235535   0.323993   0.265233   0.304729  0.421915   \n",
      "379    0.016736   0.249221   0.359833   0.261682   0.263598  0.420561   \n",
      "380    0.022026   0.275103   0.189427   0.305365   0.215859  0.350757   \n",
      "381    0.032609   0.211082   0.152174   0.176781   0.239130  0.538259   \n",
      "382    0.013294   0.247511   0.420975   0.319583   0.324963  0.356567   \n",
      "383    0.045593   0.168299   0.191489   0.319679   0.410334  0.458593   \n",
      "384    0.026596   0.156021   0.382979   0.294241   0.382979  0.482723   \n",
      "385    0.057971   0.142857   0.231884   0.306878   0.304348  0.338624   \n",
      "386    0.002915   0.440529   0.463557   0.207930   0.268222  0.323348   \n",
      "387    0.015544   0.311828   0.383420   0.301971   0.318653  0.294803   \n",
      "388    0.041612   0.209815   0.225618   0.320174   0.287386  0.363141   \n",
      "389    0.076744   0.240656   0.367442   0.265269   0.267442  0.247037   \n",
      "390    0.019608   0.253676   0.303922   0.319853   0.318627  0.305147   \n",
      "391    0.035545   0.271824   0.376777   0.371540   0.355450  0.275373   \n",
      "392    0.052632   0.308046   0.354067   0.381609   0.387560  0.268966   \n",
      "393    0.053860   0.182945   0.228007   0.258746   0.258528  0.359329   \n",
      "394    0.081081   0.206649   0.207207   0.167116   0.165165  0.426774   \n",
      "395    0.096692   0.325153   0.356234   0.253579   0.277354  0.315951   \n",
      "396    0.015280   0.273157   0.349745   0.339319   0.368421  0.346881   \n",
      "397    0.085714   0.384110   0.402597   0.308273   0.284848  0.197965   \n",
      "398    0.204082   0.257053   0.278912   0.282132   0.129252  0.278997   \n",
      "399    0.048458   0.434237   0.475771   0.203313   0.227606  0.296687   \n",
      "400    0.039095   0.475453   0.460905   0.218656   0.227366  0.238671   \n",
      "401    0.030023   0.243164   0.309469   0.305664   0.284065  0.291992   \n",
      "402    0.022388   0.162983   0.179104   0.428177   0.358209  0.356354   \n",
      "403    0.040323   0.309392   0.338710   0.129834   0.129032  0.472376   \n",
      "404    0.114583   0.277870   0.317708   0.239601   0.135417  0.410982   \n",
      "405    0.032338   0.529561   0.425373   0.206081   0.186567  0.223818   \n",
      "406    0.060034   0.291946   0.349914   0.275168   0.259005  0.256711   \n",
      "407    0.066116   0.335548   0.305785   0.295681   0.223140  0.275748   \n",
      "408    0.036232   0.316327   0.260870   0.098639   0.137681  0.472789   \n",
      "409    0.091803   0.283964   0.337705   0.246102   0.242623  0.253898   \n",
      "410    0.083815   0.252654   0.289017   0.227176   0.242775  0.319533   \n",
      "411    0.093023   0.313725   0.351744   0.227669   0.250000  0.266885   \n",
      "412    0.085837   0.342387   0.291845   0.245267   0.281116  0.262551   \n",
      "413    0.097826   0.296765   0.318841   0.308017   0.329710  0.223629   \n",
      "414    0.069191   0.281235   0.328982   0.212915   0.225849  0.380440   \n",
      "415    0.000000   0.135821   0.407895   0.394030   0.342105  0.445522   \n",
      "416    0.063652   0.286640   0.318258   0.238285   0.239531  0.329511   \n",
      "417    0.186650   0.299145   0.374536   0.104701   0.111248  0.327991   \n",
      "418    0.037411   0.465815   0.498219   0.240939   0.229216  0.215610   \n",
      "419    0.243750   0.304258   0.359375   0.089823   0.085938  0.322949   \n",
      "420    0.060168   0.316721   0.318893   0.237075   0.253911  0.325105   \n",
      "421    0.073379   0.297248   0.293515   0.288685   0.249147  0.292355   \n",
      "422    0.000000   0.240000   0.320225   0.327273   0.404494  0.380000   \n",
      "423    0.090909   0.190311   0.181818   0.349481   0.218182  0.290657   \n",
      "424    0.078125   0.221000   0.218750   0.237000   0.277344  0.333000   \n",
      "425    0.025140   0.298925   0.319832   0.269355   0.303073  0.310753   \n",
      "426    0.213689   0.319903   0.330551   0.171636   0.158598  0.272361   \n",
      "427    0.058824   0.312318   0.248366   0.195926   0.196078  0.324927   \n",
      "428    0.096591   0.416342   0.357955   0.245136   0.255682  0.180934   \n",
      "429    0.150235   0.248731   0.267606   0.235195   0.225352  0.346870   \n",
      "430    0.044444   0.058201   0.066667   0.296296   0.244444  0.534392   \n",
      "431    0.051429   0.248804   0.257143   0.251196   0.308571  0.404306   \n",
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      "440    0.124847   0.287671   0.334149   0.290959   0.283966  0.299178   \n",
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      "445    0.114833   0.247152   0.322967   0.228747   0.165072  0.366345   \n",
      "446    0.112500   0.202806   0.237500   0.158163   0.216667  0.346939   \n",
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      "448    0.231214   0.326750   0.316474   0.065829   0.089595  0.363854   \n",
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      "450    0.076923   0.279450   0.328205   0.244196   0.312821  0.349097   \n",
      "451    0.201161   0.232626   0.303675   0.203365   0.176015  0.349671   \n",
      "452    0.072046   0.225458   0.191643   0.349834   0.355908  0.274542   \n",
      "453    0.017857   0.258565   0.267857   0.341306   0.377976  0.319328   \n",
      "454    0.042222   0.365465   0.397037   0.360314   0.382963  0.189110   \n",
      "455    0.042969   0.253717   0.380859   0.386026   0.337891  0.277502   \n",
      "456    0.058939   0.238023   0.263261   0.392839   0.422397  0.288452   \n",
      "457    0.197548   0.245614   0.320163   0.154521   0.110354  0.287112   \n",
      "458    0.137387   0.196311   0.247748   0.318841   0.344595  0.326746   \n",
      "459    0.153846   0.268540   0.320850   0.240177   0.226721  0.363778   \n",
      "460    0.022727   0.046125   0.113636   0.332103   0.250000  0.579336   \n",
      "461    0.071217   0.271007   0.328388   0.328002   0.337290  0.286551   \n",
      "462    0.010256   0.264463   0.335897   0.300826   0.297436  0.348209   \n",
      "463    0.053140   0.377129   0.265700   0.278589   0.381643  0.299270   \n",
      "464    0.026055   0.264314   0.347395   0.408485   0.330025  0.291158   \n",
      "465    0.116379   0.166667   0.221983   0.159125   0.215517  0.419306   \n",
      "466    0.202781   0.238987   0.286211   0.195301   0.193511  0.323789   \n",
      "467    0.115226   0.282873   0.326475   0.305525   0.311385  0.237569   \n",
      "468    0.144444   0.135526   0.288889   0.272368   0.311111  0.230263   \n",
      "469    0.100000   0.276796   0.337037   0.270907   0.240741  0.329800   \n",
      "470    0.076531   0.219839   0.278061   0.360143   0.334184  0.326184   \n",
      "471    0.028986   0.343750   0.443478   0.232537   0.226087  0.361213   \n",
      "472    0.093882   0.184791   0.210970   0.325475   0.325949  0.388213   \n",
      "473    0.044444   0.405899   0.433333   0.400281   0.350000  0.185393   \n",
      "474    0.007968   0.332168   0.346614   0.494755   0.498008  0.150350   \n",
      "475    0.000000   0.087087   0.075269   0.066066   0.118280  0.387387   \n",
      "476    0.032178   0.487361   0.448020   0.243680   0.306931  0.148635   \n",
      "477    0.021505   0.091445   0.236559   0.448378   0.387097  0.418879   \n",
      "478    0.106787   0.229925   0.305882   0.302137   0.266968  0.322646   \n",
      "479    0.014085   0.179377   0.328638   0.314715   0.314554  0.432868   \n",
      "480    0.109375   0.267222   0.310547   0.323240   0.333984  0.314156   \n",
      "481    0.041872   0.393939   0.381773   0.292929   0.307882  0.211344   \n",
      "482    0.052174   0.383488   0.452174   0.306327   0.300000  0.229938   \n",
      "483    0.067929   0.257307   0.267261   0.267050   0.324053  0.364039   \n",
      "484    0.027027   0.536424   0.405405   0.059603   0.162162  0.278146   \n",
      "485    0.034314   0.382385   0.417892   0.363239   0.362745  0.208425   \n",
      "486    0.038241   0.358719   0.429389   0.315232   0.303222  0.223448   \n",
      "487    0.037209   0.615789   0.539535   0.221053   0.223256  0.149123   \n",
      "488    0.036741   0.381514   0.418530   0.398263   0.396166  0.145782   \n",
      "489    0.037915   0.178552   0.360190   0.299196   0.308057  0.441287   \n",
      "490    0.063158   0.145221   0.168421   0.261029   0.284211  0.487132   \n",
      "491    0.013453   0.221583   0.381166   0.401439   0.246637  0.306475   \n",
      "492    0.053073   0.221739   0.262570   0.405072   0.385475  0.311594   \n",
      "493    0.036511   0.265070   0.346856   0.336086   0.342799  0.324525   \n",
      "494    0.032668   0.239284   0.303085   0.339992   0.337568  0.354141   \n",
      "495    0.000000   0.252336   0.245902   0.373832   0.327869  0.308411   \n",
      "496    0.058166   0.244323   0.288591   0.199818   0.208054  0.369664   \n",
      "497    0.030702   0.411647   0.432749   0.240964   0.241228  0.262550   \n",
      "498    0.087248   0.202934   0.161074   0.178484   0.214765  0.430318   \n",
      "499    0.000000   0.230769   0.200000   0.384615   0.400000  0.307692   \n",
      "500    0.016129   0.227273   0.258065   0.424242   0.258065  0.227273   \n",
      "501    0.000000   0.187500   0.363636   0.359375   0.212121  0.429688   \n",
      "502    0.047337   0.243493   0.298817   0.287154   0.254438  0.329135   \n",
      "503    0.000000   0.288136   0.240000   0.338983   0.440000  0.237288   \n",
      "504    0.044000   0.270386   0.208000   0.248927   0.280000  0.347639   \n",
      "505    0.010417   0.212719   0.312500   0.445175   0.354167  0.256579   \n",
      "506    0.013746   0.394291   0.512027   0.274311   0.259450  0.249153   \n",
      "507    0.080537   0.320276   0.268456   0.235023   0.241611  0.350230   \n",
      "508    0.043919   0.161905   0.173986   0.273993   0.324324  0.435165   \n",
      "509    0.072376   0.233222   0.252111   0.245121   0.258142  0.411709   \n",
      "510    0.019868   0.273042   0.294702   0.325710   0.261589  0.320166   \n",
      "511    0.054054   0.324766   0.189189   0.301402   0.396396  0.315421   \n",
      "512    0.039474   0.221649   0.313910   0.345876   0.396617  0.353608   \n",
      "513    0.046263   0.239258   0.295374   0.331055   0.217082  0.317383   \n",
      "514    0.041791   0.228604   0.241791   0.199324   0.271642  0.463964   \n",
      "515    0.032802   0.395246   0.449859   0.249413   0.241799  0.272594   \n",
      "516    0.135542   0.646261   0.530120   0.072147   0.180723  0.086576   \n",
      "517    0.041420   0.317730   0.326923   0.391773   0.383136  0.241135   \n",
      "518    0.066842   0.289247   0.362105   0.368115   0.337368  0.282877   \n",
      "519    0.032710   0.329268   0.352804   0.384146   0.387850  0.240854   \n",
      "520    0.033314   0.343969   0.371128   0.405262   0.424313  0.202351   \n",
      "521    0.084821   0.177465   0.370536   0.191549   0.183036  0.314085   \n",
      "522    0.048232   0.248904   0.308682   0.259868   0.209003  0.350877   \n",
      "523    0.042289   0.318291   0.353234   0.257521   0.298507  0.296631   \n",
      "524    0.015536   0.305294   0.362224   0.441262   0.406378  0.203408   \n",
      "525    0.046272   0.238302   0.316195   0.247834   0.195373  0.369151   \n",
      "526    0.000000   0.241379   1.000000   0.206897   0.000000  0.103448   \n",
      "527    0.015748   0.332645   0.267717   0.196281   0.220472  0.367769   \n",
      "528    0.090909   0.090278   0.115152   0.273148   0.242424  0.488426   \n",
      "529    0.095238   0.197822   0.196429   0.451906   0.386905  0.274047   \n",
      "530    0.157205   0.297679   0.266376   0.202825   0.179039  0.351160   \n",
      "531    0.077181   0.245823   0.244966   0.304296   0.204698  0.346062   \n",
      "532    0.024427   0.556505   0.552672   0.287779   0.299237  0.130092   \n",
      "533    0.030303   0.699358   0.712919   0.102355   0.089314  0.139615   \n",
      "534    0.000000   0.473684   0.200000   0.157895   0.400000  0.210526   \n",
      "535    0.062500   0.273754   0.237772   0.158804   0.150815  0.456478   \n",
      "536    0.018141   0.454175   0.394558   0.232179   0.299320  0.241344   \n",
      "537    0.014085   0.191339   0.369718   0.285827   0.232394  0.442520   \n",
      "538    0.014981   0.255639   0.301498   0.290548   0.342697  0.357680   \n",
      "539    0.013216   0.281046   0.425110   0.315508   0.299559  0.335710   \n",
      "540    0.003571   0.098737   0.185714   0.281286   0.267857  0.491389   \n",
      "541    0.027578   0.246220   0.237410   0.361987   0.310552  0.289417   \n",
      "542    0.023166   0.229852   0.297297   0.212208   0.389961  0.479733   \n",
      "543    0.027692   0.193961   0.273846   0.242160   0.218462  0.400697   \n",
      "544    0.032926   0.230173   0.321731   0.340505   0.394167  0.371779   \n",
      "545    0.028571   0.201964   0.314286   0.290323   0.297143  0.441795   \n",
      "546    0.025641   0.211082   0.282051   0.435356   0.333333  0.232190   \n",
      "547    0.107438   0.229773   0.214876   0.262136   0.330579  0.339806   \n",
      "548    0.047619   0.094891   0.142857   0.594891   0.571429  0.182482   \n",
      "549    0.007273   0.157738   0.200000   0.319196   0.425455  0.483631   \n",
      "550    0.053731   0.295610   0.358209   0.244170   0.259701  0.399177   \n",
      "551    0.058962   0.332212   0.358491   0.317073   0.290094  0.227923   \n",
      "552    0.077079   0.316948   0.320487   0.347029   0.338742  0.220836   \n",
      "553    0.168675   0.117470   0.156627   0.192771   0.192771  0.337349   \n",
      "554    0.156522   0.171745   0.182609   0.252078   0.173913  0.409972   \n",
      "555    0.052506   0.561786   0.577566   0.157866   0.198091  0.206859   \n",
      "556    0.049645   0.336150   0.313830   0.427882   0.448582  0.159324   \n",
      "557    0.025295   0.370394   0.384486   0.292249   0.281619  0.225540   \n",
      "558    0.099783   0.255086   0.249458   0.269171   0.279826  0.282473   \n",
      "559    0.092308   0.286759   0.333728   0.231113   0.254438  0.380179   \n",
      "560    0.040984   0.390311   0.471311   0.274223   0.266393  0.270567   \n",
      "561    0.043127   0.471303   0.469003   0.234662   0.230907  0.224767   \n",
      "562    0.023580   0.323938   0.314041   0.267193   0.263666  0.307027   \n",
      "563    0.032895   0.186207   0.230263   0.335632   0.243421  0.427586   \n",
      "564    0.038055   0.767256   0.731501   0.142613   0.145877  0.066172   \n",
      "565    0.046693   0.309859   0.338521   0.193933   0.167315  0.375948   \n",
      "566    0.047273   0.376062   0.390909   0.285411   0.278182  0.268414   \n",
      "567    0.101124   0.228620   0.248596   0.298899   0.266854  0.349704   \n",
      "568    0.106529   0.238540   0.294387   0.280730   0.258877  0.286004   \n",
      "569    0.081772   0.349644   0.308348   0.209026   0.287905  0.280760   \n",
      "570    0.072238   0.351397   0.354108   0.189944   0.181303  0.288268   \n",
      "571    0.082935   0.316263   0.353270   0.277739   0.257576  0.286736   \n",
      "572    0.035120   0.299065   0.308688   0.369897   0.380776  0.251353   \n",
      "573    0.192460   0.344652   0.307540   0.269949   0.210317  0.226938   \n",
      "574    0.082707   0.192308   0.278195   0.215976   0.293233  0.470414   \n",
      "575    0.015968   0.256506   0.326680   0.466078   0.483699  0.204693   \n",
      "576    0.008547   0.203409   0.270655   0.248864   0.262108  0.448864   \n",
      "577    0.034512   0.279011   0.333333   0.406693   0.401515  0.269189   \n",
      "578    0.028662   0.328848   0.331210   0.383516   0.385350  0.221194   \n",
      "579    0.041667   0.282810   0.308712   0.308688   0.238636  0.330253   \n",
      "580    0.048518   0.324080   0.337826   0.386957   0.458221  0.216388   \n",
      "581    0.032064   0.225061   0.184369   0.357056   0.348697  0.270073   \n",
      "582    0.019417   0.263116   0.305825   0.324324   0.199029  0.360890   \n",
      "583    0.025943   0.216327   0.304245   0.286880   0.356132  0.441399   \n",
      "584    0.085389   0.238563   0.238140   0.198488   0.235294  0.390170   \n",
      "585    0.000000   0.230769   0.000000   0.076923   0.000000  0.692308   \n",
      "586    0.037569   0.402220   0.438913   0.279122   0.318265  0.241332   \n",
      "587    0.048016   0.480573   0.542460   0.296054   0.265873  0.177358   \n",
      "588    0.053571   0.416891   0.467857   0.290040   0.283036  0.211642   \n",
      "589    0.101227   0.230079   0.276074   0.237935   0.248466  0.343434   \n",
      "590    0.066667   0.295455   0.300000   0.218531   0.277778  0.363636   \n",
      "591    0.039216   0.605053   0.513725   0.142287   0.235294  0.178191   \n",
      "592    0.015474   0.203405   0.282398   0.336098   0.371373  0.419467   \n",
      "593    0.065637   0.290780   0.305019   0.228369   0.231660  0.344681   \n",
      "594    0.042105   0.222423   0.287719   0.213382   0.203509  0.372514   \n",
      "595    0.017391   0.168798   0.156522   0.388747   0.417391  0.355499   \n",
      "596    0.037356   0.543383   0.564655   0.192438   0.183908  0.193892   \n",
      "597    0.103604   0.360420   0.351351   0.198289   0.250000  0.260886   \n",
      "598    0.043956   0.276204   0.324176   0.253541   0.263736  0.382436   \n",
      "599    0.026239   0.441731   0.419825   0.274140   0.282799  0.188679   \n",
      "600    0.040767   0.183916   0.225420   0.253790   0.235012  0.456163   \n",
      "601    0.069767   0.165368   0.265116   0.339724   0.358140  0.412822   \n",
      "602    0.029553   0.327300   0.318213   0.342383   0.362199  0.250377   \n",
      "603    0.046997   0.230008   0.248042   0.346535   0.383812  0.368621   \n",
      "604    0.065693   0.145729   0.189781   0.326633   0.394161  0.374372   \n",
      "605    0.013575   0.246479   0.230769   0.388330   0.407240  0.330986   \n",
      "606    0.029197   0.303778   0.338686   0.317419   0.362044  0.320147   \n",
      "607    0.080000   0.152941   0.120000   0.120588   0.240000  0.308824   \n",
      "608    0.111111   0.228733   0.277778   0.333648   0.297893  0.276938   \n",
      "609    0.034483   0.173077   0.103448   0.461538   0.517241  0.326923   \n",
      "610    0.023622   0.083333   0.110236   0.185185   0.181102  0.662037   \n",
      "611    0.067159   0.338626   0.373432   0.310048   0.297417  0.268542   \n",
      "612    0.063457   0.316508   0.394967   0.322065   0.301969  0.305163   \n",
      "613    0.060503   0.323471   0.363018   0.363796   0.379334  0.250274   \n",
      "614    0.022371   0.295474   0.322148   0.326217   0.337808  0.291204   \n",
      "615    0.024460   0.477639   0.548201   0.314848   0.284892  0.157424   \n",
      "616    0.162011   0.450902   0.400372   0.253173   0.212291  0.177021   \n",
      "617    0.016105   0.286693   0.329429   0.372359   0.361640  0.299258   \n",
      "618    0.217712   0.254476   0.340713   0.192668   0.189422  0.277067   \n",
      "619    0.043210   0.273622   0.234568   0.269685   0.314815  0.375984   \n",
      "620    0.073980   0.239752   0.229592   0.303106   0.306122  0.325466   \n",
      "621    0.117100   0.321724   0.355019   0.285714   0.226766  0.219008   \n",
      "622    0.098398   0.276873   0.252860   0.321291   0.342105  0.265324   \n",
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      "642    0.080460   0.268376   0.367816   0.280342   0.206897  0.295726   \n",
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      "649    0.100160   0.352298   0.425481   0.218049   0.195513  0.289238   \n",
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      "652    0.153348   0.266541   0.233261   0.155009   0.125270  0.412098   \n",
      "653    0.053493   0.510233   0.491266   0.157728   0.171397  0.249118   \n",
      "654    0.297340   0.140331   0.215962   0.128913   0.134585  0.340700   \n",
      "655    0.024548   0.293710   0.326873   0.421000   0.412145  0.226845   \n",
      "656    0.037844   0.329325   0.371560   0.375097   0.365826  0.223817   \n",
      "657    0.034423   0.600000   0.621343   0.174344   0.177281  0.165598   \n",
      "658    0.032339   0.331398   0.354053   0.361393   0.380512  0.244960   \n",
      "659    0.249505   0.321731   0.336304   0.198585   0.166997  0.289280   \n",
      "660    0.269373   0.161972   0.254613   0.153756   0.140221  0.253521   \n",
      "661    0.099237   0.299140   0.269720   0.236676   0.237913  0.312321   \n",
      "662    0.032258   0.288973   0.241935   0.330798   0.306452  0.365019   \n",
      "663    0.051282   0.161458   0.217949   0.309896   0.294872  0.510417   \n",
      "664    0.054159   0.188636   0.226306   0.194697   0.210832  0.434848   \n",
      "665    0.037221   0.297148   0.317618   0.361546   0.339950  0.303588   \n",
      "666    0.005367   0.502262   0.586762   0.257014   0.295170  0.195475   \n",
      "667    0.070755   0.429017   0.382075   0.240250   0.202830  0.165367   \n",
      "668    0.106122   0.241470   0.224490   0.322835   0.302041  0.316273   \n",
      "669    0.000000   0.540948   0.575758   0.398707   0.393939  0.060345   \n",
      "670    0.000000   0.528777   0.425532   0.312950   0.446809  0.143885   \n",
      "671    0.043453   0.341970   0.356775   0.268051   0.259005  0.316060   \n",
      "672    0.097561   0.208333   0.195122   0.116667   0.243902  0.516667   \n",
      "673    0.018605   0.298963   0.372093   0.428167   0.374419  0.248664   \n",
      "674    0.040428   0.278100   0.304400   0.329085   0.332937  0.282735   \n",
      "675    0.010390   0.195378   0.272727   0.300420   0.257143  0.390756   \n",
      "676    0.011080   0.504961   0.473684   0.264609   0.249307  0.181918   \n",
      "677    0.000000   0.723810   0.668605   0.129762   0.133721  0.132143   \n",
      "678    0.000000   0.223529   0.071429   0.235294   0.357143  0.482353   \n",
      "679    0.009314   0.351118   0.297206   0.311182   0.300593  0.223642   \n",
      "680    0.010204   0.841549   0.887755   0.095070   0.051020  0.047535   \n",
      "681    0.022901   0.131951   0.213740   0.375118   0.343511  0.470311   \n",
      "682    0.159601   0.202614   0.264339   0.118736   0.097257  0.265795   \n",
      "683    0.062500   0.276596   0.306818   0.345154   0.323864  0.290780   \n",
      "684    0.071038   0.253638   0.251366   0.270270   0.327869  0.234927   \n",
      "685    0.025641   0.182648   0.294872   0.232877   0.320513  0.369863   \n",
      "686    0.194313   0.213855   0.189573   0.251506   0.274882  0.176205   \n",
      "687    0.376045   0.219931   0.164345   0.235968   0.194986  0.245132   \n",
      "688    0.013605   0.180266   0.292517   0.332068   0.374150  0.430740   \n",
      "689    0.000000   0.148855   0.219512   0.351145   0.365854  0.488550   \n",
      "690    0.050633   0.379326   0.413924   0.261191   0.284810  0.262114   \n",
      "691    0.010724   0.128215   0.249330   0.365173   0.268097  0.434974   \n",
      "692    0.000000   0.183432   0.341667   0.346746   0.325000  0.403550   \n",
      "693    0.018692   0.151335   0.271028   0.378338   0.392523  0.449555   \n",
      "694    0.030303   0.164138   0.339394   0.318621   0.315152  0.489655   \n",
      "695    0.042553   0.205970   0.234043   0.382090   0.340426  0.316418   \n",
      "696    0.010417   0.182670   0.156250   0.311475   0.302083  0.461358   \n",
      "697    0.005917   0.222099   0.372781   0.341436   0.278107  0.388950   \n",
      "698    0.018634   0.137280   0.372671   0.412469   0.316770  0.421914   \n",
      "699    0.014845   0.237843   0.356275   0.388092   0.437247  0.312656   \n",
      "700    0.011952   0.243458   0.250996   0.311718   0.310757  0.356086   \n",
      "701    0.069347   0.336452   0.406030   0.317742   0.282412  0.272581   \n",
      "702    0.039474   0.217559   0.243421   0.301927   0.246711  0.411563   \n",
      "703    0.015625   0.395698   0.466518   0.237288   0.301339  0.290091   \n",
      "704    0.003448   0.484262   0.486207   0.214286   0.186207  0.217918   \n",
      "705    0.015686   0.380062   0.478431   0.250779   0.247059  0.333333   \n",
      "706    0.072165   0.273717   0.360825   0.315708   0.329897  0.289269   \n",
      "707    0.027881   0.295409   0.310409   0.273120   0.265799  0.367265   \n",
      "708    0.022388   0.228311   0.164179   0.285388   0.305970  0.344749   \n",
      "709    0.103448   0.163793   0.241379   0.267241   0.206897  0.525862   \n",
      "710    0.046875   0.154689   0.259375   0.388551   0.390625  0.390378   \n",
      "711    0.034586   0.245161   0.309774   0.367742   0.369173  0.300836   \n",
      "712    0.076000   0.195804   0.166000   0.214161   0.218000  0.492133   \n",
      "713    0.031746   0.335556   0.436508   0.293333   0.246032  0.233333   \n",
      "714    0.043046   0.238326   0.269868   0.268648   0.291391  0.391146   \n",
      "715    0.080760   0.260965   0.268409   0.239035   0.247031  0.418860   \n",
      "716    0.082192   0.169935   0.246575   0.316993   0.315068  0.261438   \n",
      "717    0.005208   0.298044   0.375000   0.300345   0.291667  0.390104   \n",
      "718    0.036513   0.326065   0.410315   0.342895   0.330443  0.280697   \n",
      "719    0.048000   0.133739   0.188000   0.245694   0.244000  0.526849   \n",
      "720    0.062500   0.225681   0.250000   0.369650   0.375000  0.342412   \n",
      "721    0.030380   0.160900   0.129114   0.301903   0.400000  0.422145   \n",
      "722    0.020513   0.266243   0.335897   0.291158   0.325641  0.352711   \n",
      "723    0.008427   0.208745   0.339888   0.351669   0.370787  0.367184   \n",
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      "725    0.011799   0.218497   0.330383   0.290173   0.292035  0.401734   \n",
      "726    0.011673   0.181504   0.291829   0.358686   0.326848  0.350908   \n",
      "727    0.015464   0.222661   0.314433   0.314399   0.310997  0.421324   \n",
      "728    0.008803   0.231898   0.438380   0.292519   0.343310  0.422901   \n",
      "729    0.023438   0.258345   0.323437   0.269956   0.303125  0.378326   \n",
      "730    0.012500   0.439200   0.472917   0.212389   0.167708  0.255326   \n",
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      "732    0.070450   0.254557   0.236791   0.280599   0.303327  0.395833   \n",
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      "735    0.016644   0.598121   0.572816   0.179019   0.188627  0.179541   \n",
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      "737    0.022676   0.644015   0.595238   0.131425   0.141723  0.185236   \n",
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      "744    0.011905   0.100000   0.142857   0.354167   0.190476  0.341667   \n",
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      "762    0.030769   0.203883   0.184615   0.258900   0.169231  0.187702   \n",
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      "765    0.216301   0.315985   0.347962   0.235440   0.231975  0.260223   \n",
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      "768    0.008850   0.154829   0.237168   0.370361   0.364602  0.428115   \n",
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      "771    0.052045   0.155556   0.167286   0.322222   0.368030  0.412500   \n",
      "772    0.030075   0.257782   0.259398   0.355058   0.357143  0.277237   \n",
      "773    0.025701   0.254626   0.252336   0.485463   0.457944  0.209692   \n",
      "774    0.029380   0.278988   0.376496   0.352704   0.340588  0.289481   \n",
      "775    0.063001   0.334006   0.361970   0.328756   0.305842  0.242730   \n",
      "776    0.026316   0.278297   0.308271   0.314642   0.421053  0.197300   \n",
      "777    0.029553   0.298105   0.337859   0.427472   0.409744  0.217880   \n",
      "778    0.041667   0.433079   0.295139   0.239391   0.270833  0.253536   \n",
      "779    0.040000   0.314214   0.307273   0.326683   0.281818  0.272652   \n",
      "780    0.090164   0.220767   0.243169   0.090739   0.114754  0.497661   \n",
      "781    0.055512   0.321641   0.374511   0.312559   0.304144  0.273411   \n",
      "782    0.036795   0.299637   0.346688   0.310533   0.315617  0.312954   \n",
      "783    0.027100   0.327575   0.387534   0.393355   0.382114  0.213068   \n",
      "784    0.092961   0.329942   0.275564   0.278585   0.292165  0.264777   \n",
      "785    0.043445   0.334999   0.409299   0.367605   0.333841  0.255851   \n",
      "786    0.023339   0.188852   0.251346   0.273443   0.310592  0.353443   \n",
      "787    0.070381   0.311864   0.293255   0.239548   0.302053  0.254237   \n",
      "788    0.007463   0.255814   0.253731   0.334884   0.335821  0.251163   \n",
      "789    0.125000   0.164404   0.175000   0.245852   0.210000  0.497738   \n",
      "790    0.074349   0.252376   0.315985   0.371700   0.321561  0.220169   \n",
      "791    0.064286   0.200333   0.285714   0.319202   0.283333  0.375727   \n",
      "792    0.112518   0.276081   0.298172   0.231552   0.215190  0.328880   \n",
      "793    0.050336   0.242759   0.305369   0.257931   0.181208  0.402759   \n",
      "794    0.092166   0.257384   0.308756   0.234880   0.248848  0.406470   \n",
      "795    0.097421   0.245655   0.209169   0.221321   0.220630  0.324450   \n",
      "796    0.051491   0.224339   0.303523   0.328211   0.363144  0.318992   \n",
      "797    0.055556   0.268127   0.295019   0.181269   0.183908  0.434290   \n",
      "798    0.055010   0.267436   0.353635   0.300231   0.214145  0.302079   \n",
      "799    0.100386   0.351605   0.343629   0.235709   0.249035  0.288175   \n",
      "800    0.097087   0.298982   0.262136   0.241730   0.213592  0.329517   \n",
      "801    0.000000   0.236915   0.257143   0.380165   0.304762  0.336088   \n",
      "802    0.064516   0.212744   0.272401   0.346351   0.333333  0.361768   \n",
      "803    0.044164   0.233853   0.277603   0.289532   0.299685  0.400891   \n",
      "804    0.076056   0.203279   0.287324   0.250273   0.208451  0.432787   \n",
      "805    0.054348   0.246817   0.385870   0.441724   0.372283  0.277179   \n",
      "806    0.048110   0.200240   0.237113   0.196643   0.185567  0.474820   \n",
      "807    0.077039   0.351530   0.330816   0.181764   0.205438  0.352130   \n",
      "808    0.042386   0.304617   0.259027   0.328524   0.350078  0.263397   \n",
      "809    0.213483   0.290323   0.191011   0.133641   0.134831  0.373272   \n",
      "810    0.167630   0.279584   0.317919   0.191157   0.184971  0.299090   \n",
      "811    0.051643   0.346354   0.262911   0.220052   0.276995  0.291667   \n",
      "812    0.049774   0.372917   0.330317   0.222917   0.239819  0.291667   \n",
      "813    0.034247   0.282810   0.337900   0.349353   0.308219  0.269871   \n",
      "814    0.014652   0.258936   0.355311   0.367752   0.391941  0.308181   \n",
      "815    0.142661   0.330591   0.331962   0.129049   0.130316  0.350643   \n",
      "816    0.069069   0.179342   0.273273   0.311010   0.246246  0.460840   \n",
      "817    0.040000   0.336460   0.393333   0.309496   0.296667  0.277843   \n",
      "818    0.032680   0.343728   0.444444   0.319473   0.259259  0.298683   \n",
      "819    0.058480   0.143369   0.187135   0.120072   0.187135  0.473118   \n",
      "820    0.079268   0.278689   0.317073   0.291803   0.219512  0.352459   \n",
      "821    0.055046   0.284051   0.422018   0.245634   0.197248  0.391153   \n",
      "822    0.062500   0.236842   0.287500   0.255639   0.262500  0.454887   \n",
      "823    0.058140   0.298126   0.418605   0.236797   0.250000  0.357751   \n",
      "824    0.040359   0.231334   0.358744   0.263158   0.237668  0.421053   \n",
      "825    0.073095   0.270963   0.236392   0.196429   0.183515  0.428571   \n",
      "826    0.193627   0.250712   0.286765   0.235518   0.215686  0.377018   \n",
      "827    0.131372   0.324027   0.395691   0.211464   0.234367  0.285120   \n",
      "828    0.058394   0.456311   0.518248   0.155340   0.197080  0.310680   \n",
      "829    0.049430   0.244468   0.235741   0.331928   0.269962  0.347734   \n",
      "830    0.053254   0.292352   0.396450   0.291384   0.254438  0.355276   \n",
      "831    0.037702   0.214696   0.262118   0.293291   0.256732  0.373802   \n",
      "832    0.053061   0.201435   0.236735   0.237298   0.263265  0.485356   \n",
      "833    0.032520   0.209877   0.195122   0.276543   0.325203  0.437037   \n",
      "834    0.060870   0.243542   0.260870   0.232472   0.260870  0.457565   \n",
      "835    0.101266   0.241379   0.278481   0.190669   0.210970  0.452333   \n",
      "836    0.035714   0.214592   0.214286   0.450644   0.196429  0.317597   \n",
      "837    0.022409   0.241013   0.271709   0.360294   0.313725  0.330882   \n",
      "838    0.031915   0.355856   0.443769   0.141141   0.194529  0.319820   \n",
      "839    0.073222   0.210680   0.320084   0.310168   0.251046  0.369422   \n",
      "840    0.014286   0.084112   0.128571   0.140187   0.271429  0.682243   \n",
      "841    0.053299   0.261006   0.380711   0.375000   0.342640  0.312893   \n",
      "842    0.011628   0.173333   0.203488   0.287619   0.226744  0.447619   \n",
      "843    0.026316   0.218935   0.219298   0.159763   0.175439  0.514793   \n",
      "844    0.036810   0.262391   0.306748   0.515306   0.420245  0.196064   \n",
      "845    0.036145   0.391304   0.283133   0.337391   0.295181  0.215652   \n",
      "846    0.041958   0.273101   0.384615   0.441478   0.398601  0.180698   \n",
      "847    0.028169   0.263948   0.288732   0.369099   0.260563  0.332618   \n",
      "848    0.059701   0.346939   0.328358   0.224490   0.164179  0.367347   \n",
      "849    0.014174   0.380010   0.462084   0.384838   0.338058  0.210164   \n",
      "850    0.122449   0.250450   0.357143   0.234234   0.204082  0.403604   \n",
      "851    0.010959   0.187062   0.282192   0.380359   0.400000  0.381917   \n",
      "852    0.053459   0.239403   0.298742   0.363422   0.349057  0.343799   \n",
      "853    0.050794   0.333016   0.380952   0.300666   0.292063  0.235966   \n",
      "854    0.077348   0.207921   0.220994   0.171617   0.209945  0.415842   \n",
      "855    0.044776   0.222857   0.149254   0.280000   0.179104  0.371429   \n",
      "856    0.126984   0.126829   0.126984   0.321951   0.301587  0.478049   \n",
      "857    0.008696   0.191571   0.156522   0.325670   0.269565  0.360153   \n",
      "858    0.049587   0.304000   0.239669   0.180000   0.181818  0.292000   \n",
      "859    0.067568   0.120000   0.162162   0.500000   0.540541  0.340000   \n",
      "860    0.012136   0.269048   0.330097   0.428571   0.461165  0.257619   \n",
      "861    0.058824   0.166667   0.176471   0.311594   0.313725  0.398551   \n",
      "862    0.111588   0.273927   0.291845   0.255776   0.227468  0.334983   \n",
      "863    0.041667   0.101911   0.187500   0.522293   0.333333  0.312102   \n",
      "864    0.027972   0.247423   0.202797   0.461340   0.468531  0.255155   \n",
      "865    0.027778   0.206485   0.333333   0.283276   0.314815  0.452218   \n",
      "866    0.038462   0.288000   0.250000   0.144000   0.057692  0.520000   \n",
      "867    0.423810   0.273438   0.271429   0.205078   0.176190  0.173828   \n",
      "868    0.223684   0.420370   0.322368   0.212963   0.309211  0.168519   \n",
      "869    0.303125   0.226244   0.268750   0.204374   0.159375  0.228507   \n",
      "870    0.038095   0.407407   0.295238   0.373737   0.438095  0.178451   \n",
      "871    0.075000   0.167136   0.257143   0.342723   0.375000  0.352113   \n",
      "872    0.160211   0.278173   0.279930   0.173604   0.158451  0.371066   \n",
      "873    0.091255   0.255183   0.224335   0.100478   0.209125  0.440191   \n",
      "874    0.184932   0.202189   0.267123   0.265293   0.226027  0.300708   \n",
      "875    0.076283   0.270358   0.326630   0.306574   0.316227  0.315802   \n",
      "876    0.119048   0.282776   0.190476   0.190231   0.269841  0.421594   \n",
      "877    0.137652   0.283991   0.307692   0.242325   0.238866  0.242325   \n",
      "878    0.087500   0.343249   0.350000   0.251716   0.237500  0.338673   \n",
      "879    0.024259   0.330448   0.305481   0.399701   0.431267  0.233433   \n",
      "880    0.076923   0.202247   0.307692   0.243446   0.346154  0.513109   \n",
      "881    0.022831   0.261128   0.433790   0.385757   0.305936  0.284866   \n",
      "882    0.036885   0.270165   0.266393   0.419825   0.397541  0.293489   \n",
      "883    0.084507   0.360331   0.346076   0.302479   0.344064  0.254545   \n",
      "884    0.114754   0.272382   0.302108   0.328547   0.377049  0.277449   \n",
      "885    0.104433   0.231551   0.244929   0.343937   0.305034  0.317601   \n",
      "886    0.101240   0.285802   0.266529   0.449816   0.394628  0.167687   \n",
      "887    0.032710   0.193717   0.242991   0.326103   0.292056  0.413613   \n",
      "888    0.067864   0.198328   0.210579   0.303191   0.338323  0.381459   \n",
      "889    0.097691   0.216095   0.268206   0.312469   0.248668  0.343766   \n",
      "890    0.119122   0.263267   0.376176   0.221227   0.231975  0.325293   \n",
      "891    0.032480   0.312920   0.377889   0.365073   0.306683  0.238246   \n",
      "892    0.110000   0.132812   0.146667   0.170759   0.206667  0.534598   \n",
      "893    0.106204   0.283837   0.309148   0.257556   0.238696  0.285808   \n",
      "894    0.022247   0.226654   0.291435   0.334630   0.322581  0.374514   \n",
      "895    0.067002   0.218366   0.328308   0.308596   0.335008  0.345435   \n",
      "896    0.010101   0.279018   0.565657   0.301339   0.252525  0.377232   \n",
      "897    0.051195   0.276328   0.391126   0.311510   0.252560  0.328518   \n",
      "898    0.153322   0.262795   0.269165   0.248994   0.228279  0.377228   \n",
      "899    0.108033   0.217355   0.349030   0.342881   0.296399  0.304971   \n",
      "900    0.319876   0.160772   0.254658   0.131833   0.127329  0.310825   \n",
      "901    0.375669   0.210106   0.210406   0.154461   0.109411  0.323633   \n",
      "902    0.146693   0.303811   0.334971   0.222188   0.167976  0.333128   \n",
      "903    0.103665   0.297657   0.412565   0.208031   0.183770  0.315335   \n",
      "904    0.284397   0.279874   0.266718   0.205260   0.127594  0.321326   \n",
      "905    0.061770   0.270567   0.248748   0.309567   0.353923  0.322364   \n",
      "906    0.067362   0.407019   0.426945   0.328509   0.324478  0.203329   \n",
      "907    0.047022   0.243550   0.275862   0.390093   0.347962  0.292054   \n",
      "908    0.084806   0.315084   0.236749   0.309497   0.349823  0.269274   \n",
      "909    0.125261   0.226344   0.258873   0.197578   0.235908  0.265708   \n",
      "910    0.137681   0.208861   0.289855   0.268354   0.275362  0.350633   \n",
      "911    0.121212   0.299444   0.338118   0.245321   0.248804  0.249874   \n",
      "912    0.250274   0.268872   0.344469   0.176542   0.130887  0.317573   \n",
      "913    0.122980   0.160726   0.154603   0.146792   0.148981  0.434219   \n",
      "914    0.253835   0.257227   0.286492   0.154299   0.126175  0.314123   \n",
      "915    0.338530   0.183700   0.258352   0.102199   0.066815  0.219276   \n",
      "916    0.054326   0.242131   0.309859   0.312954   0.340040  0.367433   \n",
      "917    0.376233   0.230150   0.184041   0.189291   0.123552  0.358092   \n",
      "918    0.296449   0.192916   0.184145   0.124605   0.096614  0.352625   \n",
      "919    0.222947   0.197147   0.260756   0.182883   0.166232  0.303598   \n",
      "920    0.129715   0.270109   0.317387   0.194389   0.206992  0.346822   \n",
      "921    0.278750   0.284085   0.313750   0.128904   0.110000  0.326475   \n",
      "922    0.211627   0.240012   0.257356   0.186742   0.145339  0.394791   \n",
      "923    0.089147   0.268754   0.389535   0.278539   0.251938  0.353555   \n",
      "924    0.184211   0.168582   0.223684   0.206897   0.144737  0.375479   \n",
      "925    0.046257   0.232402   0.308663   0.343632   0.355761  0.350081   \n",
      "926    0.058411   0.255418   0.309969   0.329760   0.359813  0.289210   \n",
      "927    0.333910   0.162850   0.235294   0.204198   0.159170  0.243003   \n",
      "928    0.086372   0.216045   0.281190   0.270639   0.252399  0.344874   \n",
      "929    0.064138   0.264458   0.280690   0.311044   0.281379  0.266064   \n",
      "930    0.037736   0.140363   0.152291   0.377435   0.373315  0.305574   \n",
      "931    0.108216   0.324577   0.286573   0.311734   0.332665  0.193812   \n",
      "932    0.108192   0.231754   0.282844   0.224645   0.293663  0.256398   \n",
      "933    0.110169   0.340525   0.300847   0.260788   0.222458  0.222326   \n",
      "934    0.078640   0.306744   0.303932   0.343061   0.385760  0.188392   \n",
      "935    0.018100   0.211358   0.312217   0.298595   0.303167  0.416276   \n",
      "936    0.078667   0.272732   0.336950   0.391235   0.350126  0.279141   \n",
      "937    0.000000   0.186937   0.226667   0.399775   0.333333  0.350225   \n",
      "938    0.022646   0.232331   0.325387   0.458617   0.432658  0.287353   \n",
      "939    0.117978   0.240307   0.363764   0.158226   0.167135  0.347538   \n",
      "940    0.074116   0.242133   0.266819   0.406701   0.367161  0.298408   \n",
      "941    0.028131   0.317164   0.351180   0.435470   0.441016  0.206980   \n",
      "942    0.030641   0.380920   0.425627   0.396162   0.357660  0.180593   \n",
      "943    0.236301   0.218728   0.204338   0.143912   0.103881  0.422683   \n",
      "944    0.037862   0.215522   0.282851   0.358050   0.332591  0.364108   \n",
      "945    0.023551   0.314504   0.336051   0.444275   0.460145  0.215703   \n",
      "946    0.002045   0.309722   0.327198   0.532346   0.443763  0.120708   \n",
      "947    0.040850   0.224907   0.338235   0.280669   0.339869  0.245973   \n",
      "948    0.064417   0.195373   0.239264   0.450669   0.361963  0.336120   \n",
      "949    0.053132   0.255296   0.327976   0.388313   0.338144  0.299733   \n",
      "950    0.033663   0.312627   0.394059   0.381837   0.368317  0.259959   \n",
      "951    0.085463   0.317579   0.389427   0.351023   0.289868  0.247374   \n",
      "952    0.361446   0.215032   0.213855   0.126929   0.126506  0.198606   \n",
      "953    0.192157   0.180104   0.205229   0.136382   0.138562  0.403129   \n",
      "954    0.094063   0.193128   0.281419   0.323081   0.306862  0.382377   \n",
      "955    0.131641   0.170501   0.224321   0.272566   0.228453  0.391544   \n",
      "956    0.069863   0.199705   0.193151   0.222680   0.228767  0.465390   \n",
      "957    0.087425   0.303593   0.355689   0.276948   0.295808  0.271700   \n",
      "958    0.216917   0.179310   0.218281   0.239015   0.190314  0.347980   \n",
      "959    0.045356   0.204184   0.252700   0.330878   0.341253  0.389806   \n",
      "960    0.098930   0.172830   0.245989   0.221887   0.252674  0.387547   \n",
      "961    0.034000   0.214184   0.252000   0.395899   0.332000  0.311307   \n",
      "962    0.023810   0.181058   0.203869   0.279109   0.250000  0.472981   \n",
      "963    0.206388   0.251732   0.267813   0.099307   0.093366  0.413395   \n",
      "964    0.150000   0.249588   0.280303   0.255635   0.186364  0.251237   \n",
      "965    0.167164   0.211498   0.294030   0.161392   0.149254  0.415612   \n",
      "966    0.174242   0.265255   0.242424   0.110212   0.092803  0.409714   \n",
      "967    0.071174   0.269504   0.274021   0.208511   0.281139  0.458156   \n",
      "968    0.024279   0.407387   0.452200   0.332971   0.330804  0.204780   \n",
      "969    0.296467   0.278256   0.251920   0.049140   0.046083  0.342752   \n",
      "970    0.141509   0.190722   0.254717   0.230241   0.226415  0.170103   \n",
      "971    0.065711   0.729671   0.677419   0.094687   0.086022  0.138778   \n",
      "972    0.076821   0.372662   0.380132   0.219664   0.251656  0.294005   \n",
      "973    0.038722   0.417195   0.460794   0.219521   0.219748  0.261099   \n",
      "974    0.118531   0.350399   0.340568   0.182181   0.196995  0.292553   \n",
      "975    0.200867   0.296592   0.343931   0.126198   0.163295  0.255591   \n",
      "976    0.079399   0.194933   0.206009   0.236616   0.263948  0.405394   \n",
      "977    0.000000   0.766949   0.704301   0.148910   0.177419  0.073850   \n",
      "978    0.008006   0.877242   0.869496   0.068736   0.078463  0.034469   \n",
      "979    0.120650   0.225701   0.273782   0.176778   0.169374  0.257665   \n",
      "980    0.091733   0.293122   0.312571   0.202311   0.185730  0.346051   \n",
      "981    0.121569   0.320534   0.364706   0.160267   0.152941  0.353088   \n",
      "982    0.178155   0.249639   0.306469   0.168831   0.171792  0.365440   \n",
      "983    0.076000   0.289769   0.332000   0.186799   0.220000  0.340594   \n",
      "984    0.055227   0.251977   0.280079   0.311488   0.287968  0.337476   \n",
      "985    0.022624   0.277620   0.298643   0.273371   0.244344  0.361190   \n",
      "986    0.122278   0.242262   0.278057   0.226190   0.221106  0.350595   \n",
      "987    0.037422   0.160656   0.185031   0.244809   0.201663  0.426230   \n",
      "988    0.093750   0.250958   0.229167   0.208812   0.208333  0.342912   \n",
      "989    0.052747   0.221617   0.261538   0.353315   0.329670  0.303361   \n",
      "990    0.047146   0.418605   0.414392   0.236279   0.210918  0.253953   \n",
      "991    0.065632   0.254177   0.303103   0.311899   0.315036  0.297722   \n",
      "992    0.029340   0.318283   0.334963   0.390081   0.383863  0.247964   \n",
      "993    0.088000   0.269036   0.288000   0.243655   0.216000  0.296954   \n",
      "994    0.019305   0.383808   0.332046   0.184408   0.262548  0.323838   \n",
      "995    0.040123   0.307500   0.305556   0.350000   0.225309  0.251250   \n",
      "996    0.066116   0.226136   0.210744   0.240909   0.272727  0.438636   \n",
      "997    0.062500   0.136951   0.132812   0.343669   0.328125  0.379845   \n",
      "998    0.120211   0.269211   0.299868   0.304796   0.301189  0.290872   \n",
      "999    0.039121   0.259259   0.297186   0.411802   0.373370  0.258318   \n",
      "1000   0.112500   0.334755   0.378571   0.214641   0.241071  0.338308   \n",
      "1001   0.104000   0.214204   0.264000   0.224513   0.254400  0.341352   \n",
      "1002   0.073643   0.277003   0.275194   0.167247   0.240310  0.318815   \n",
      "1003   0.195364   0.228776   0.268212   0.174263   0.185430  0.302949   \n",
      "1004   0.137931   0.305882   0.365517   0.155556   0.158621  0.189542   \n",
      "1005   0.189759   0.291026   0.280120   0.226923   0.274096  0.297436   \n",
      "1006   0.089744   0.241554   0.350427   0.293919   0.273504  0.271959   \n",
      "1007   0.014493   0.300439   0.316770   0.320724   0.356108  0.348136   \n",
      "1008   0.168394   0.201431   0.303109   0.267894   0.256477  0.340491   \n",
      "1009   0.098039   0.065327   0.156863   0.120603   0.078431  0.502513   \n",
      "1010   0.048780   0.265805   0.253049   0.211207   0.207317  0.442529   \n",
      "1011   0.029167   0.388444   0.405556   0.247140   0.211111  0.278032   \n",
      "1012   0.076923   0.319797   0.343195   0.251269   0.207101  0.331218   \n",
      "1013   0.036697   0.315615   0.339450   0.227575   0.197248  0.320598   \n",
      "1014   0.088172   0.270030   0.219355   0.222552   0.262366  0.394659   \n",
      "1015   0.039568   0.288721   0.276978   0.319024   0.366906  0.334175   \n",
      "1016   0.061728   0.322275   0.296296   0.203791   0.203704  0.267773   \n",
      "1017   0.036458   0.268966   0.307292   0.232759   0.210938  0.378448   \n",
      "1018   0.072269   0.469261   0.349580   0.201354   0.226891  0.219966   \n",
      "1019   0.022298   0.439385   0.478559   0.247191   0.221269  0.261384   \n",
      "1020   0.058097   0.365410   0.408134   0.225748   0.265795  0.289207   \n",
      "1021   0.036662   0.197730   0.219975   0.371454   0.380531  0.347883   \n",
      "1022   0.039742   0.281557   0.274973   0.293925   0.293233  0.325209   \n",
      "1023   0.147541   0.283917   0.358834   0.249775   0.214936  0.308625   \n",
      "1024   0.102410   0.281800   0.210843   0.248532   0.240964  0.315068   \n",
      "1025   0.094812   0.226938   0.398927   0.308792   0.225403  0.407103   \n",
      "1026   0.056818   0.212406   0.221591   0.289474   0.187500  0.424812   \n",
      "1027   0.027027   0.356295   0.394595   0.318290   0.345946  0.259857   \n",
      "1028   0.054422   0.174242   0.306122   0.308712   0.278912  0.375000   \n",
      "1029   0.041215   0.166337   0.195228   0.353135   0.312364  0.415842   \n",
      "1030   0.019259   0.325949   0.380741   0.338924   0.358519  0.292089   \n",
      "1031   0.008730   0.354738   0.419841   0.430798   0.375397  0.184227   \n",
      "1032   0.014286   0.462085   0.385714   0.312796   0.364286  0.156398   \n",
      "1033   0.013222   0.389901   0.395268   0.361203   0.386221  0.214128   \n",
      "1034   0.142857   0.242424   0.250000   0.181818   0.285714  0.414141   \n",
      "1035   0.018519   0.194521   0.166667   0.345205   0.370370  0.391781   \n",
      "1036   0.139706   0.159406   0.316176   0.207921   0.176471  0.397030   \n",
      "1037   0.033981   0.321632   0.344660   0.331120   0.349515  0.301708   \n",
      "1038   0.053191   0.262705   0.281915   0.289406   0.281915  0.406546   \n",
      "1039   0.039683   0.476107   0.464853   0.323542   0.332200  0.175800   \n",
      "1040   0.027442   0.377182   0.457739   0.390898   0.348518  0.197423   \n",
      "1041   0.020000   0.212903   0.215000   0.246452   0.320000  0.438710   \n",
      "1042   0.030120   0.250000   0.319277   0.394231   0.373494  0.290385   \n",
      "1043   0.019034   0.255038   0.327965   0.374055   0.363104  0.323678   \n",
      "1044   0.046809   0.272328   0.217021   0.346999   0.387234  0.336750   \n",
      "1045   0.069767   0.235169   0.145349   0.256356   0.267442  0.290254   \n",
      "1046   0.094961   0.175593   0.257752   0.302019   0.302326  0.381036   \n",
      "1047   0.062529   0.336475   0.397992   0.291977   0.318576  0.268523   \n",
      "1048   0.048780   0.312500   0.390244   0.298611   0.317073  0.256944   \n",
      "1049   0.035714   0.178404   0.366071   0.276995   0.348214  0.446009   \n",
      "1050   0.049180   0.158568   0.221311   0.253197   0.204918  0.401535   \n",
      "1051   0.007576   0.311355   0.386364   0.329670   0.348485  0.285714   \n",
      "1052   0.032680   0.297872   0.392157   0.365248   0.379085  0.290780   \n",
      "1053   0.022222   0.343750   0.266667   0.226562   0.233333  0.281250   \n",
      "1054   0.115144   0.204715   0.275344   0.172457   0.222778  0.447891   \n",
      "1055   0.023904   0.211207   0.330677   0.340517   0.346614  0.323276   \n",
      "1056   0.030405   0.211889   0.378378   0.354746   0.344595  0.399808   \n",
      "1057   0.000000   0.279412   0.305556   0.279412   0.444444  0.220588   \n",
      "1058   0.012552   0.525407   0.686192   0.150407   0.142259  0.164634   \n",
      "1059   0.030303   0.246835   0.272727   0.294304   0.261364  0.405063   \n",
      "1060   0.053333   0.259709   0.446667   0.378641   0.220000  0.286408   \n",
      "1061   0.044304   0.267898   0.297468   0.221709   0.208861  0.265589   \n",
      "1062   0.054496   0.257965   0.294278   0.262076   0.242507  0.320658   \n",
      "1063   0.101124   0.147826   0.168539   0.327536   0.252809  0.379710   \n",
      "1064   0.000000   0.151436   0.162162   0.467363   0.531532  0.334204   \n",
      "1065   0.046229   0.179567   0.231144   0.227038   0.274939  0.437564   \n",
      "1066   0.094241   0.265525   0.225131   0.291221   0.418848  0.299786   \n",
      "1067   0.126263   0.403417   0.429293   0.172142   0.166667  0.303548   \n",
      "1068   0.035623   0.289308   0.323155   0.266846   0.312977  0.316262   \n",
      "1069   0.029221   0.482911   0.512987   0.287762   0.227273  0.184123   \n",
      "1070   0.011236   0.696275   0.674157   0.131805   0.134831  0.088825   \n",
      "1071   0.025901   0.504587   0.511261   0.276758   0.305180  0.169725   \n",
      "1072   0.054545   0.278585   0.342149   0.349968   0.304132  0.293746   \n",
      "1073   0.071691   0.327788   0.356618   0.240912   0.242647  0.357363   \n",
      "1074   0.023973   0.263626   0.253425   0.230256   0.215753  0.368187   \n",
      "1075   0.041754   0.209915   0.260960   0.168087   0.212944  0.459334   \n",
      "1076   0.055866   0.229885   0.284916   0.237548   0.184358  0.454023   \n",
      "1077   0.026502   0.230337   0.252650   0.268258   0.259717  0.383427   \n",
      "1078   0.018868   0.526882   0.547170   0.172043   0.207547  0.161290   \n",
      "1079   0.034843   0.268991   0.254355   0.249066   0.163763  0.366127   \n",
      "1080   0.038917   0.190739   0.241963   0.304768   0.250423  0.364893   \n",
      "1081   0.052632   0.222611   0.263158   0.203963   0.198381  0.510490   \n",
      "1082   0.057221   0.226891   0.267030   0.241597   0.228883  0.439076   \n",
      "1083   0.055804   0.180254   0.189732   0.307971   0.223214  0.450181   \n",
      "1084   0.017143   0.257742   0.300000   0.216783   0.208571  0.387612   \n",
      "1085   0.025000   0.107356   0.130000   0.435388   0.435000  0.389662   \n",
      "1086   0.042517   0.219083   0.173469   0.188952   0.159864  0.495920   \n",
      "1087   0.187500   0.037975   0.137500   0.227848   0.137500  0.687764   \n",
      "1088   0.050147   0.359128   0.371681   0.215904   0.216814  0.344164   \n",
      "1089   0.037037   0.329596   0.343915   0.218262   0.233862  0.326392   \n",
      "1090   0.110803   0.371838   0.390582   0.223389   0.204986  0.296897   \n",
      "1091   0.047923   0.389796   0.394569   0.222959   0.230032  0.262755   \n",
      "1092   0.032374   0.324575   0.316547   0.173107   0.230216  0.431221   \n",
      "1093   0.087838   0.397231   0.341216   0.203408   0.199324  0.336528   \n",
      "1094   0.036775   0.224747   0.224894   0.320707   0.297030  0.377273   \n",
      "1095   0.061644   0.320215   0.373973   0.222272   0.209589  0.328712   \n",
      "1096   0.045000   0.462745   0.455000   0.192157   0.215000  0.275817   \n",
      "1097   0.031250   0.182073   0.229167   0.168067   0.187500  0.512605   \n",
      "1098   0.022222   0.353261   0.303704   0.206522   0.185185  0.380435   \n",
      "1099   0.062842   0.337634   0.352459   0.230108   0.191257  0.298925   \n",
      "1100   0.051802   0.337031   0.380631   0.233788   0.279279  0.388225   \n",
      "1101   0.055556   0.284289   0.238095   0.208229   0.212698  0.382793   \n",
      "1102   0.107884   0.505102   0.452282   0.265306   0.278008  0.186224   \n",
      "1103   0.110236   0.238173   0.334646   0.313214   0.263780  0.298532   \n",
      "1104   0.051700   0.456545   0.486726   0.279120   0.286446  0.188244   \n",
      "1105   0.038095   0.235294   0.200000   0.323529   0.295238  0.254902   \n",
      "1106   0.033333   0.277778   0.200000   0.305556   0.283333  0.250000   \n",
      "1107   0.086294   0.183862   0.243655   0.206349   0.279188  0.496032   \n",
      "1108   0.293515   0.167243   0.225256   0.131488   0.126280  0.250288   \n",
      "1109   0.090909   0.288265   0.391608   0.198980   0.125874  0.341837   \n",
      "1110   0.027027   0.264516   0.189189   0.232258   0.333333  0.367742   \n",
      "1111   0.062718   0.256966   0.303136   0.218782   0.289199  0.299278   \n",
      "1112   0.042394   0.288288   0.334165   0.214214   0.274314  0.374374   \n",
      "1113   0.067797   0.220567   0.250471   0.285106   0.291902  0.323404   \n",
      "1114   0.069395   0.286300   0.345196   0.285129   0.279359  0.320258   \n",
      "1115   0.059540   0.297861   0.263870   0.241176   0.251691  0.341176   \n",
      "1116   0.043478   0.222892   0.130435   0.156627   0.260870  0.289157   \n",
      "1117   0.046667   0.171901   0.246667   0.262810   0.253333  0.421488   \n",
      "1118   0.029412   0.141414   0.151961   0.267677   0.308824  0.373737   \n",
      "1119   0.067961   0.261789   0.233010   0.373984   0.441748  0.211382   \n",
      "1120   0.011429   0.229268   0.217143   0.253659   0.211429  0.363415   \n",
      "1121   0.183432   0.403306   0.242604   0.196694   0.242604  0.233058   \n",
      "1122   0.063978   0.295208   0.305914   0.308125   0.317742  0.277083   \n",
      "1123   0.120482   0.255649   0.277108   0.202711   0.226908  0.349258   \n",
      "1124   0.115741   0.301907   0.312500   0.286017   0.247685  0.272246   \n",
      "1125   0.114007   0.275202   0.312704   0.205645   0.159609  0.360887   \n",
      "1126   0.069162   0.246234   0.267766   0.338791   0.317259  0.301681   \n",
      "1127   0.082902   0.209551   0.269430   0.275281   0.259067  0.379775   \n",
      "1128   0.030864   0.285714   0.314815   0.333591   0.240741  0.324324   \n",
      "1129   0.032512   0.526743   0.544310   0.223653   0.255375  0.185618   \n",
      "1130   0.119718   0.417879   0.426056   0.176715   0.225352  0.220374   \n",
      "1131   0.163507   0.207836   0.345972   0.182851   0.218009  0.200454   \n",
      "1132   0.044088   0.630643   0.629259   0.199042   0.154309  0.112859   \n",
      "1133   0.063032   0.726872   0.696763   0.125795   0.102215  0.104258   \n",
      "1134   0.050167   0.313099   0.277592   0.291800   0.321070  0.298190   \n",
      "1135   0.156076   0.151585   0.204013   0.151915   0.139353  0.348085   \n",
      "1136   0.271357   0.197509   0.180905   0.179715   0.170854  0.302491   \n",
      "1137   0.009709   0.125811   0.291262   0.370947   0.330097  0.461738   \n",
      "1138   0.063025   0.594343   0.579832   0.207284   0.173319  0.114297   \n",
      "1139   0.115385   0.434174   0.333333   0.198880   0.282051  0.235294   \n",
      "1140   0.073333   0.399478   0.393333   0.206266   0.268333  0.268930   \n",
      "1141   0.101633   0.384071   0.392922   0.252035   0.239564  0.237168   \n",
      "1142   0.108527   0.358537   0.387597   0.178049   0.108527  0.304878   \n",
      "1143   0.138298   0.281361   0.340426   0.260099   0.223404  0.265769   \n",
      "1144   0.265734   0.184362   0.160839   0.175309   0.136364  0.372016   \n",
      "1145   0.199170   0.200253   0.298755   0.225602   0.178423  0.361217   \n",
      "1146   0.108108   0.290657   0.342342   0.183391   0.189189  0.328720   \n",
      "1147   0.113379   0.282140   0.292517   0.281277   0.265306  0.271786   \n",
      "1148   0.183133   0.329502   0.330120   0.204598   0.255422  0.263602   \n",
      "1149   0.183794   0.224749   0.268775   0.231438   0.213439  0.319064   \n",
      "1150   0.158163   0.282555   0.306122   0.185504   0.230867  0.253481   \n",
      "1151   0.424837   0.118655   0.196078   0.174687   0.135076  0.199077   \n",
      "1152   0.072727   0.398352   0.375758   0.267857   0.294949  0.239011   \n",
      "1153   0.117450   0.321117   0.308725   0.302792   0.322148  0.280105   \n",
      "1154   0.070707   0.162080   0.232323   0.250765   0.222222  0.483180   \n",
      "1155   0.143043   0.349799   0.342003   0.259621   0.271782  0.233774   \n",
      "1156   0.021605   0.367238   0.382716   0.213062   0.191358  0.302998   \n",
      "1157   0.024194   0.153704   0.193548   0.350000   0.298387  0.387037   \n",
      "1158   0.066667   0.266892   0.333333   0.258446   0.216667  0.375000   \n",
      "1159   0.044164   0.214623   0.261830   0.273585   0.283912  0.366745   \n",
      "1160   0.277778   0.269006   0.190476   0.169591   0.246032  0.307018   \n",
      "1161   0.088435   0.279743   0.224490   0.109325   0.231293  0.504823   \n",
      "1162   0.058228   0.404784   0.403797   0.292683   0.298734  0.219043   \n",
      "1163   0.042553   0.623945   0.597820   0.189234   0.232486  0.145808   \n",
      "1164   0.081395   0.396923   0.412449   0.265275   0.326265  0.234286   \n",
      "1165   0.065817   0.233542   0.254777   0.293887   0.256900  0.369122   \n",
      "1166   0.034868   0.450665   0.492105   0.330837   0.306579  0.160831   \n",
      "1167   0.035821   0.495468   0.440299   0.257301   0.307463  0.206445   \n",
      "1168   0.063316   0.454625   0.455614   0.276414   0.290470  0.170978   \n",
      "1169   0.018164   0.528462   0.543977   0.275235   0.276291  0.166373   \n",
      "1170   0.016529   0.287809   0.338843   0.277336   0.262810  0.342271   \n",
      "1171   0.025229   0.527255   0.548165   0.269243   0.286697  0.163198   \n",
      "1172   0.026014   0.591206   0.616679   0.247990   0.239480  0.125879   \n",
      "1173   0.013498   0.409140   0.444319   0.347479   0.367829  0.207472   \n",
      "1174   0.021505   0.607589   0.623656   0.246875   0.234767  0.129018   \n",
      "1175   0.031373   0.630115   0.533333   0.203764   0.258824  0.133388   \n",
      "1176   0.046647   0.403243   0.443149   0.324324   0.291545  0.208649   \n",
      "1177   0.013100   0.266432   0.344978   0.302817   0.375546  0.293427   \n",
      "1178   0.037080   0.346220   0.391657   0.396853   0.347625  0.214506   \n",
      "1179   0.046591   0.352041   0.444318   0.270773   0.236364  0.267493   \n",
      "1180   0.065041   0.244576   0.279133   0.248521   0.257453  0.395792   \n",
      "1181   0.069565   0.053595   0.000000   0.205229   0.269565  0.687582   \n",
      "1182   0.062409   0.390897   0.364296   0.258367   0.271408  0.246319   \n",
      "1183   0.067194   0.351810   0.355731   0.308824   0.300395  0.235294   \n",
      "1184   0.164179   0.234082   0.313433   0.249064   0.253731  0.258427   \n",
      "1185   0.088542   0.198864   0.213542   0.099432   0.135417  0.477273   \n",
      "1186   0.138889   0.313837   0.214286   0.184023   0.186508  0.316690   \n",
      "1187   0.032468   0.146245   0.227273   0.334980   0.201299  0.399209   \n",
      "1188   0.052786   0.524390   0.548387   0.219512   0.246334  0.176829   \n",
      "1189   0.022008   0.351786   0.436039   0.351786   0.334938  0.231252   \n",
      "1190   0.056287   0.305158   0.362874   0.254298   0.267066  0.363539   \n",
      "1191   0.067485   0.352273   0.300613   0.250000   0.355828  0.313636   \n",
      "1192   0.054291   0.325112   0.327496   0.290919   0.309982  0.293722   \n",
      "1193   0.040373   0.343500   0.388199   0.323893   0.315217  0.236020   \n",
      "1194   0.013514   0.344262   0.256757   0.202186   0.364865  0.393443   \n",
      "1195   0.009709   0.742537   0.650485   0.145522   0.194175  0.097015   \n",
      "1196   0.077684   0.288670   0.360169   0.310345   0.254237  0.316256   \n",
      "1197   0.014963   0.343405   0.321696   0.416360   0.483791  0.208548   \n",
      "1198   0.018433   0.083045   0.156682   0.207612   0.248848  0.602076   \n",
      "1199   0.033413   0.493361   0.436754   0.242084   0.250597  0.215526   \n",
      "1200   0.110721   0.256890   0.307557   0.284971   0.261863  0.249610   \n",
      "1201   0.059259   0.215524   0.249383   0.337737   0.296296  0.354253   \n",
      "1202   0.054131   0.326027   0.279202   0.382648   0.387464  0.225571   \n",
      "1203   0.026455   0.496760   0.417989   0.228942   0.222222  0.211663   \n",
      "1204   0.011013   0.336483   0.374449   0.355378   0.337004  0.257994   \n",
      "1205   0.021352   0.352315   0.338078   0.294118   0.325623  0.285982   \n",
      "1206   0.020921   0.326316   0.376569   0.392481   0.351464  0.217293   \n",
      "1207   0.013699   0.226852   0.150685   0.268519   0.369863  0.449074   \n",
      "1208   0.000000   0.469194   0.337209   0.118483   0.139535  0.388626   \n",
      "1209   0.051546   0.661818   0.484536   0.141818   0.237113  0.163636   \n",
      "1210   0.070388   0.329897   0.254854   0.189316   0.279126  0.271790   \n",
      "1211   0.116279   0.453608   0.534884   0.170103   0.232558  0.335052   \n",
      "1212   0.028767   0.416325   0.486301   0.292750   0.293151  0.220246   \n",
      "1213   0.040373   0.406250   0.465839   0.379076   0.316770  0.148098   \n",
      "1214   0.121061   0.346333   0.338308   0.220605   0.199005  0.277066   \n",
      "1215   0.017054   0.417662   0.443411   0.341299   0.361240  0.178182   \n",
      "1216   0.011765   0.424855   0.513725   0.361272   0.333333  0.193642   \n",
      "1217   0.013889   0.345555   0.321759   0.296975   0.331019  0.283226   \n",
      "1218   0.019438   0.352734   0.427646   0.368607   0.330454  0.260141   \n",
      "1219   0.072368   0.197339   0.269737   0.268293   0.276316  0.379157   \n",
      "1220   0.027933   0.467797   0.396648   0.334463   0.391061  0.172881   \n",
      "1221   0.042169   0.377404   0.442771   0.382212   0.373494  0.139423   \n",
      "1222   0.032258   0.440000   0.516129   0.360000   0.354839  0.171429   \n",
      "1223   0.051020   0.077295   0.163265   0.357488   0.306122  0.449275   \n",
      "1224   0.250000   0.230769   0.250000   0.461538   0.000000  0.307692   \n",
      "1225   0.111111   0.150943   0.259259   0.320755   0.296296  0.301887   \n",
      "1226   0.098684   0.266667   0.269737   0.277778   0.401316  0.222222   \n",
      "1227   0.024457   0.406205   0.429348   0.380952   0.339674  0.132035   \n",
      "1228   0.322698   0.266968   0.254330   0.133484   0.105743  0.309955   \n",
      "1229   0.245902   0.258199   0.292231   0.164626   0.131148  0.339309   \n",
      "1230   0.202505   0.196805   0.226514   0.102311   0.133612  0.373895   \n",
      "1231   0.198396   0.259151   0.308556   0.132316   0.105348  0.333725   \n",
      "1232   0.040373   0.404040   0.437888   0.204265   0.279503  0.218855   \n",
      "1233   0.073446   0.183071   0.259887   0.185039   0.180791  0.496063   \n",
      "1234   0.051643   0.281667   0.253521   0.216667   0.215962  0.331667   \n",
      "1235   0.045455   0.247525   0.295455   0.316832   0.204545  0.287129   \n",
      "1236   0.098361   0.377163   0.360656   0.134948   0.196721  0.245675   \n",
      "1237   0.031496   0.229529   0.173228   0.320438   0.244094  0.395874   \n",
      "1238   0.056680   0.277487   0.291498   0.218586   0.251012  0.397906   \n",
      "1239   0.230906   0.295547   0.271758   0.194332   0.133215  0.301330   \n",
      "1240   0.251557   0.293071   0.333748   0.197566   0.166874  0.247191   \n",
      "1241   0.000000   0.765176   0.765060   0.105431   0.132530  0.112620   \n",
      "1242   0.010309   0.146820   0.173196   0.379244   0.400000  0.411765   \n",
      "1243   0.082162   0.629593   0.587027   0.202352   0.194595  0.094561   \n",
      "1244   0.034483   0.236715   0.293103   0.241546   0.224138  0.342995   \n",
      "1245   0.179348   0.212056   0.237319   0.223330   0.163949  0.410234   \n",
      "1246   0.088586   0.128479   0.182283   0.291651   0.250426  0.503622   \n",
      "1247   0.038741   0.175064   0.234867   0.250213   0.191283  0.518360   \n",
      "1248   0.018182   0.253333   0.313636   0.440000   0.418182  0.283333   \n",
      "1249   0.011494   0.119593   0.130268   0.426209   0.390805  0.321883   \n",
      "1250   0.004310   0.161644   0.237069   0.326027   0.314655  0.408219   \n",
      "1251   0.189607   0.178126   0.276685   0.177322   0.148876  0.433052   \n",
      "1252   0.021898   0.181818   0.270073   0.311295   0.350365  0.473829   \n",
      "1253   0.046851   0.582244   0.579109   0.168028   0.204301  0.171296   \n",
      "1254   0.009494   0.167923   0.338608   0.381910   0.297468  0.402010   \n",
      "1255   0.097561   0.205251   0.317073   0.214797   0.382114  0.245823   \n",
      "1256   0.080586   0.207697   0.256410   0.319841   0.285714  0.331121   \n",
      "1257   0.020802   0.233077   0.313522   0.358330   0.271917  0.347791   \n",
      "1258   0.018634   0.451303   0.459627   0.316872   0.378882  0.190672   \n",
      "1259   0.024221   0.272300   0.350865   0.289863   0.309343  0.357765   \n",
      "1260   0.025000   0.216590   0.350000   0.271889   0.175000  0.470046   \n",
      "1261   0.054865   0.312908   0.343685   0.268673   0.273292  0.353517   \n",
      "1262   0.000000   0.153226   0.255319   0.276882   0.265957  0.534946   \n",
      "1263   0.000000   0.156522   0.180000   0.345652   0.360000  0.467391   \n",
      "1264   0.035714   0.158333   0.178571   0.375000   0.392857  0.416667   \n",
      "1265   0.074866   0.143536   0.157754   0.142586   0.128342  0.575095   \n",
      "1266   0.061404   0.507375   0.350877   0.233038   0.298246  0.206490   \n",
      "1267   0.011905   0.177045   0.386905   0.462759   0.392857  0.307692   \n",
      "1268   0.061697   0.519713   0.501285   0.249104   0.269923  0.175627   \n",
      "1269   0.014815   0.236467   0.370370   0.310541   0.333333  0.336182   \n",
      "1270   0.075444   0.234293   0.248521   0.304538   0.247041  0.337696   \n",
      "1271   0.048544   0.233480   0.368932   0.246696   0.310680  0.378855   \n",
      "1272   0.168539   0.269953   0.247191   0.258216   0.269663  0.342723   \n",
      "1273   0.025641   0.286047   0.403846   0.311628   0.282051  0.360465   \n",
      "1274   0.089888   0.202970   0.247191   0.301980   0.292135  0.440594   \n",
      "1275   0.044444   0.425287   0.422222   0.390805   0.377778  0.149425   \n",
      "1276   0.048544   0.298611   0.349515   0.430556   0.466019  0.215278   \n",
      "1277   0.041935   0.304709   0.374194   0.275623   0.270968  0.306094   \n",
      "1278   0.028369   0.227519   0.273050   0.340195   0.365248  0.393283   \n",
      "1279   0.059524   0.159292   0.297619   0.283186   0.321429  0.398230   \n",
      "1280   0.071429   0.159801   0.268571   0.287642   0.268571  0.454545   \n",
      "1281   0.066079   0.180451   0.317181   0.225564   0.193833  0.386466   \n",
      "1282   0.099693   0.216057   0.340491   0.345953   0.297546  0.351828   \n",
      "1283   0.024470   0.283750   0.336052   0.347500   0.391517  0.283750   \n",
      "1284   0.056000   0.171429   0.336000   0.306494   0.264000  0.436364   \n",
      "1285   0.013699   0.333333   0.383562   0.436782   0.452055  0.143678   \n",
      "1286   0.075000   0.284685   0.355000   0.329730   0.270000  0.351351   \n",
      "1287   0.069725   0.250809   0.355963   0.291262   0.306422  0.316343   \n",
      "1288   0.129979   0.274262   0.348008   0.272574   0.238994  0.249789   \n",
      "1289   0.041667   0.394316   0.326389   0.214920   0.222222  0.316163   \n",
      "1290   0.042506   0.392804   0.418345   0.267616   0.230425  0.260120   \n",
      "1291   0.078947   0.206349   0.273684   0.269841   0.268421  0.319728   \n",
      "1292   0.062069   0.273273   0.200000   0.201201   0.213793  0.357357   \n",
      "1293   0.050360   0.298507   0.223022   0.194030   0.273381  0.361194   \n",
      "1294   0.014925   0.085714   0.097015   0.246429   0.268657  0.632143   \n",
      "1295   0.333333   0.175258   0.209150   0.174112   0.199346  0.276060   \n",
      "1296   0.045166   0.306832   0.303487   0.312273   0.382726  0.313785   \n",
      "1297   0.051916   0.275449   0.316440   0.361677   0.341162  0.267465   \n",
      "1298   0.033951   0.309256   0.396605   0.339020   0.331790  0.286025   \n",
      "1299   0.015873   0.278119   0.388889   0.372188   0.329365  0.331970   \n",
      "1300   0.029650   0.501266   0.474394   0.275949   0.296496  0.139241   \n",
      "1301   0.040000   0.277620   0.250000   0.305949   0.390000  0.320113   \n",
      "1302   0.067138   0.260173   0.261484   0.240444   0.265018  0.367448   \n",
      "1303   0.045845   0.284507   0.343840   0.299531   0.255014  0.306103   \n",
      "1304   0.009975   0.164691   0.311721   0.353091   0.291771  0.408975   \n",
      "1305   0.033217   0.223284   0.311189   0.322388   0.333916  0.344478   \n",
      "1306   0.000000   0.210052   0.154545   0.365979   0.209091  0.320876   \n",
      "1307   0.051282   0.198697   0.307692   0.297503   0.328205  0.404995   \n",
      "1308   0.144790   0.241047   0.288227   0.114784   0.138024  0.506428   \n",
      "1309   0.086957   0.234879   0.299233   0.309476   0.314578  0.330645   \n",
      "1310   0.077434   0.195409   0.243363   0.404467   0.413717  0.260546   \n",
      "1311   0.104247   0.239802   0.301158   0.280593   0.247104  0.275649   \n",
      "1312   0.075601   0.304585   0.374570   0.311135   0.305842  0.253275   \n",
      "1313   0.068035   0.323813   0.387689   0.286350   0.288337  0.272255   \n",
      "1314   0.199442   0.216826   0.270572   0.273370   0.238494  0.293662   \n",
      "1315   0.010870   0.216941   0.245652   0.351005   0.471739  0.360146   \n",
      "1316   0.125000   0.255932   0.317308   0.238983   0.221154  0.372881   \n",
      "1317   0.096658   0.333204   0.343270   0.303620   0.311653  0.264694   \n",
      "1318   0.047362   0.284863   0.314748   0.423719   0.413070  0.207390   \n",
      "1319   0.157895   0.282051   0.197368   0.160256   0.276316  0.416667   \n",
      "1320   0.027273   0.229704   0.225758   0.494747   0.477273  0.213467   \n",
      "1321   0.085667   0.598361   0.535420   0.227166   0.253707  0.100703   \n",
      "1322   0.066282   0.148260   0.230548   0.299546   0.327089  0.373172   \n",
      "1323   0.047513   0.169496   0.215293   0.335252   0.317001  0.366619   \n",
      "1324   0.053571   0.202581   0.209821   0.278710   0.312500  0.343226   \n",
      "1325   0.071901   0.137287   0.181818   0.263376   0.304959  0.434260   \n",
      "1326   0.110664   0.250856   0.313883   0.227740   0.221328  0.382705   \n",
      "1327   0.151515   0.466454   0.439394   0.162939   0.162879  0.292332   \n",
      "1328   0.044892   0.503171   0.444272   0.197146   0.224458  0.212474   \n",
      "1329   0.051282   0.288259   0.304487   0.282322   0.355769  0.329815   \n",
      "1330   0.090715   0.231865   0.219851   0.177461   0.183565  0.417098   \n",
      "1331   0.046763   0.228758   0.226619   0.328665   0.356115  0.341737   \n",
      "1332   0.175000   0.354386   0.375000   0.214035   0.175000  0.214035   \n",
      "1333   0.120399   0.269978   0.293712   0.326674   0.317485  0.271058   \n",
      "1334   0.089153   0.427040   0.383358   0.268017   0.222883  0.176295   \n",
      "1335   0.044000   0.374328   0.414000   0.269254   0.204000  0.281194   \n",
      "1336   0.087671   0.321643   0.326027   0.262525   0.282192  0.238477   \n",
      "1337   0.069378   0.428791   0.466507   0.232487   0.227273  0.270978   \n",
      "1338   0.046512   0.357927   0.397010   0.303030   0.315615  0.238472   \n",
      "1339   0.023689   0.268812   0.291878   0.340512   0.350254  0.316696   \n",
      "1340   0.252567   0.241206   0.277207   0.189519   0.193018  0.248385   \n",
      "1341   0.020930   0.154389   0.227907   0.368769   0.265116  0.380238   \n",
      "1342   0.118056   0.551351   0.430556   0.240541   0.256944  0.167568   \n",
      "1343   0.010135   0.231735   0.317568   0.335046   0.417230  0.260845   \n",
      "1344   0.006667   0.152381   0.246667   0.401361   0.420000  0.401361   \n",
      "1345   0.014184   0.333333   0.510638   0.333333   0.255319  0.261905   \n",
      "1346   0.034247   0.169168   0.356164   0.323329   0.301370  0.469304   \n",
      "1347   0.013906   0.182379   0.269279   0.357848   0.361568  0.410168   \n",
      "1348   0.000000   0.161157   0.238095   0.404959   0.380952  0.421488   \n",
      "1349   0.046753   0.328606   0.335065   0.330073   0.333766  0.283619   \n",
      "1350   0.036364   0.219340   0.322727   0.366745   0.300000  0.325472   \n",
      "1351   0.018265   0.250324   0.369863   0.330739   0.351598  0.376135   \n",
      "1352   0.012658   0.146293   0.240506   0.330661   0.379747  0.472946   \n",
      "1353   0.020747   0.156729   0.352697   0.308348   0.340249  0.503123   \n",
      "1354   0.013423   0.249275   0.409396   0.318841   0.335570  0.344928   \n",
      "1355   0.008333   0.154862   0.308333   0.318127   0.391667  0.435774   \n",
      "1356   0.030651   0.306892   0.342912   0.318596   0.365900  0.337451   \n",
      "1357   0.013889   0.229718   0.277778   0.356106   0.322917  0.343296   \n",
      "1358   0.034783   0.507786   0.496618   0.267773   0.273430  0.173663   \n",
      "1359   0.046931   0.375394   0.440433   0.225552   0.263538  0.302839   \n",
      "1360   0.023364   0.405868   0.457944   0.336186   0.299065  0.213936   \n",
      "1361   0.016077   0.391714   0.459807   0.290019   0.276527  0.297552   \n",
      "1362   0.029046   0.343904   0.342324   0.259338   0.288382  0.314306   \n",
      "1363   0.019231   0.396721   0.444712   0.360656   0.382212  0.215301   \n",
      "1364   0.063232   0.348058   0.339578   0.384615   0.330211  0.200305   \n",
      "1365   0.030548   0.280072   0.256065   0.324596   0.336029  0.335368   \n",
      "1366   0.042208   0.211126   0.250000   0.368633   0.285714  0.382708   \n",
      "1367   0.125695   0.315198   0.319244   0.316717   0.228031  0.270517   \n",
      "1368   0.125984   0.371601   0.330709   0.359517   0.299213  0.154079   \n",
      "1369   0.052747   0.384772   0.404396   0.222843   0.293407  0.287310   \n",
      "1370   0.024291   0.499154   0.500000   0.275804   0.281377  0.166385   \n",
      "1371   0.017271   0.662719   0.673575   0.200309   0.196891  0.121524   \n",
      "1372   0.012500   0.295760   0.415625   0.458118   0.362500  0.222337   \n",
      "1373   0.029361   0.433834   0.388601   0.272904   0.314335  0.251091   \n",
      "1374   0.098694   0.399327   0.358491   0.274387   0.261248  0.227295   \n",
      "1375   0.065854   0.230981   0.301220   0.377217   0.345122  0.276705   \n",
      "1376   0.083784   0.296943   0.348649   0.318777   0.340541  0.299439   \n",
      "1377   0.000000   0.588608   0.342857   0.303797   0.200000  0.107595   \n",
      "1378   0.084494   0.170272   0.212628   0.179487   0.192201  0.333333   \n",
      "1379   0.095098   0.268456   0.287255   0.268084   0.292157  0.351976   \n",
      "1380   0.064880   0.222575   0.277856   0.357319   0.373766  0.325220   \n",
      "1381   0.046205   0.347701   0.376238   0.264368   0.240924  0.277778   \n",
      "1382   0.057034   0.270115   0.239544   0.302956   0.342205  0.293924   \n",
      "1383   0.118483   0.207249   0.257504   0.330855   0.325434  0.299257   \n",
      "1384   0.037221   0.358624   0.385856   0.261579   0.217122  0.309660   \n",
      "1385   0.120438   0.276978   0.262774   0.227818   0.215328  0.280576   \n",
      "1386   0.044280   0.347345   0.343635   0.352532   0.369465  0.231336   \n",
      "1387   0.224756   0.264913   0.267101   0.207826   0.234528  0.291854   \n",
      "1388   0.083736   0.260819   0.288245   0.251587   0.286634  0.335257   \n",
      "1389   0.140927   0.201135   0.235521   0.184915   0.187259  0.405515   \n",
      "1390   0.161017   0.282469   0.303390   0.237624   0.225424  0.238789   \n",
      "1391   0.084211   0.324750   0.315789   0.213162   0.171930  0.317597   \n",
      "1392   0.000000   0.301887   0.125000   0.323899   0.517857  0.238994   \n",
      "1393   0.142857   0.288114   0.299107   0.241075   0.232143  0.339353   \n",
      "1394   0.086321   0.264228   0.353254   0.316565   0.294821  0.324187   \n",
      "1395   0.010616   0.175311   0.284501   0.347510   0.322718  0.405083   \n",
      "1396   0.006061   0.145418   0.224242   0.211155   0.169697  0.541833   \n",
      "1397   0.063380   0.054830   0.091549   0.185379   0.197183  0.592689   \n",
      "1398   0.050000   0.279054   0.348485   0.327315   0.266667  0.308601   \n",
      "1399   0.083595   0.342314   0.380355   0.306736   0.335423  0.213817   \n",
      "1400   0.004545   0.104067   0.222727   0.433014   0.395455  0.397129   \n",
      "1401   0.071250   0.199792   0.332500   0.266389   0.270000  0.470343   \n",
      "1402   0.122066   0.238713   0.247653   0.244921   0.226526  0.384876   \n",
      "1403   0.008505   0.393392   0.523742   0.288935   0.291283  0.270521   \n",
      "1404   0.061303   0.247924   0.291188   0.443654   0.348659  0.246738   \n",
      "1405   0.047619   0.267201   0.228571   0.327989   0.285714  0.357381   \n",
      "1406   0.054545   0.198020   0.418182   0.343234   0.218182  0.366337   \n",
      "1407   0.071197   0.250554   0.317152   0.304878   0.271845  0.325942   \n",
      "1408   0.113269   0.289395   0.372168   0.243806   0.236246  0.313181   \n",
      "1409   0.061453   0.356972   0.396648   0.353222   0.281724  0.222639   \n",
      "1410   0.041397   0.297973   0.327296   0.309760   0.357050  0.336634   \n",
      "1411   0.045455   0.311453   0.329154   0.354749   0.352665  0.254190   \n",
      "1412   0.035294   0.172088   0.168627   0.254287   0.266667  0.431697   \n",
      "1413   0.089686   0.213270   0.282511   0.285545   0.282511  0.405213   \n",
      "1414   0.035714   0.195833   0.280612   0.247917   0.219388  0.458333   \n",
      "1415   0.084906   0.169935   0.179245   0.349673   0.349057  0.369281   \n",
      "1416   0.127072   0.368327   0.309392   0.279359   0.287293  0.233096   \n",
      "1417   0.032967   0.348915   0.401099   0.208681   0.131868  0.292154   \n",
      "1418   0.046569   0.245588   0.291667   0.361765   0.333333  0.276471   \n",
      "1419   0.069642   0.279400   0.327248   0.282947   0.299527  0.327694   \n",
      "1420   0.030769   0.342857   0.323077   0.233333   0.261538  0.300000   \n",
      "1421   0.029316   0.177800   0.198697   0.315324   0.335505  0.447937   \n",
      "1422   0.039133   0.242766   0.240391   0.301864   0.337526  0.370034   \n",
      "1423   0.070789   0.295813   0.284784   0.234910   0.274207  0.365960   \n",
      "1424   0.064782   0.237563   0.318021   0.327420   0.292108  0.333205   \n",
      "1425   0.058824   0.293860   0.364706   0.365497   0.270588  0.308480   \n",
      "1426   0.036364   0.237468   0.256684   0.356751   0.360428  0.346506   \n",
      "1427   0.146067   0.200743   0.370787   0.230483   0.179775  0.390335   \n",
      "1428   0.042553   0.209091   0.120567   0.150000   0.191489  0.570455   \n",
      "1429   0.045627   0.261516   0.249049   0.255572   0.262357  0.366518   \n",
      "1430   0.055794   0.480643   0.433476   0.254200   0.274678  0.170928   \n",
      "1431   0.087912   0.290000   0.241758   0.204000   0.181319  0.322000   \n",
      "1432   0.140187   0.243615   0.285047   0.306483   0.303738  0.328094   \n",
      "1433   0.024793   0.271646   0.276860   0.243578   0.214876  0.399144   \n",
      "1434   0.039244   0.271912   0.296512   0.294323   0.328488  0.354582   \n",
      "1435   0.051471   0.238168   0.308824   0.448855   0.404412  0.227481   \n",
      "1436   0.004264   0.161523   0.211087   0.314300   0.285714  0.475309   \n",
      "1437   0.014787   0.182948   0.203327   0.327413   0.349353  0.378922   \n",
      "1438   0.052846   0.252680   0.260163   0.358346   0.272358  0.294028   \n",
      "1439   0.033937   0.311864   0.316742   0.301695   0.319005  0.272316   \n",
      "1440   0.050866   0.285637   0.266234   0.270461   0.264069  0.352846   \n",
      "1441   0.050459   0.242909   0.240826   0.288000   0.279817  0.326545   \n",
      "1442   0.067391   0.416941   0.445652   0.175987   0.154348  0.241776   \n",
      "1443   0.139723   0.252562   0.272517   0.283309   0.274827  0.299048   \n",
      "1444   0.069841   0.291327   0.290476   0.284619   0.314286  0.296119   \n",
      "1445   0.068592   0.351404   0.362816   0.267146   0.341155  0.160026   \n",
      "1446   0.035294   0.365019   0.311765   0.273764   0.282353  0.292776   \n",
      "1447   0.018692   0.400000   0.551402   0.320690   0.261682  0.179310   \n",
      "1448   0.017857   0.403974   0.433036   0.349338   0.357143  0.226821   \n",
      "1449   0.034483   0.507109   0.422414   0.369668   0.396552  0.104265   \n",
      "1450   0.103896   0.206128   0.272727   0.111421   0.071429  0.515320   \n",
      "1451   0.206498   0.234895   0.263216   0.254260   0.235132  0.305577   \n",
      "1452   0.067989   0.269058   0.320113   0.275037   0.320113  0.282511   \n",
      "1453   0.241379   0.168000   0.137931   0.136000   0.206897  0.440000   \n",
      "1454   0.035242   0.249706   0.229075   0.321974   0.464758  0.360165   \n",
      "1455   0.032000   0.194690   0.288000   0.410029   0.344000  0.330383   \n",
      "1456   0.013592   0.430457   0.464078   0.280528   0.287379  0.225837   \n",
      "1457   0.007634   0.402787   0.480916   0.282927   0.297710  0.212544   \n",
      "1458   0.013274   0.254925   0.292035   0.345307   0.243363  0.358053   \n",
      "1459   0.031250   0.429603   0.375000   0.234657   0.270833  0.194946   \n",
      "1460   0.062893   0.362857   0.404612   0.288571   0.306080  0.242857   \n",
      "1461   0.073698   0.433333   0.410419   0.291165   0.346887  0.189558   \n",
      "1462   0.038023   0.361600   0.403042   0.401600   0.384030  0.179200   \n",
      "1463   0.330579   0.254973   0.245179   0.217902   0.134986  0.218807   \n",
      "1464   0.222054   0.266592   0.216012   0.233408   0.243202  0.219348   \n",
      "1465   0.067729   0.179903   0.179283   0.367909   0.350598  0.235008   \n",
      "1466   0.109116   0.319556   0.350829   0.244456   0.241713  0.238911   \n",
      "1467   0.121655   0.256350   0.285888   0.295861   0.267640  0.288335   \n",
      "1468   0.053279   0.182796   0.323770   0.363937   0.327869  0.407775   \n",
      "1469   0.061538   0.281776   0.284615   0.381317   0.300000  0.294028   \n",
      "1470   0.063776   0.255372   0.260204   0.318182   0.341837  0.301653   \n",
      "1471   0.066975   0.330812   0.281755   0.288171   0.297921  0.298487   \n",
      "1472   0.023339   0.276274   0.389587   0.466561   0.364452  0.234607   \n",
      "1473   0.022222   0.151678   0.118519   0.326174   0.407407  0.464430   \n",
      "1474   0.000000   0.177778   0.269231   0.333333   0.307692  0.422222   \n",
      "1475   0.000000   0.291785   0.275362   0.317280   0.434783  0.310198   \n",
      "1476   0.012048   0.126866   0.150602   0.332623   0.355422  0.432836   \n",
      "1477   0.057143   0.207289   0.142857   0.232346   0.257143  0.523918   \n",
      "1478   0.011494   0.181507   0.241379   0.342466   0.310345  0.407534   \n",
      "1479   0.062500   0.262958   0.225694   0.284450   0.256944  0.364096   \n",
      "1480   0.025168   0.270844   0.276846   0.345417   0.323826  0.253237   \n",
      "1481   0.028369   0.361022   0.333333   0.175719   0.326241  0.434505   \n",
      "1482   0.026667   0.115869   0.140000   0.282116   0.306667  0.375315   \n",
      "1483   0.014218   0.346690   0.255924   0.311847   0.350711  0.233449   \n",
      "1484   0.025070   0.357749   0.378830   0.310510   0.314763  0.257431   \n",
      "1485   0.057239   0.335036   0.370370   0.323116   0.315376  0.254151   \n",
      "1486   0.021875   0.227503   0.268750   0.306717   0.328125  0.404943   \n",
      "1487   0.057471   0.165746   0.367816   0.408840   0.195402  0.273481   \n",
      "1488   0.063492   0.177419   0.253968   0.474194   0.253968  0.261290   \n",
      "1489   0.036496   0.271765   0.332117   0.337647   0.321168  0.330588   \n",
      "1490   0.096618   0.280067   0.314010   0.265770   0.246377  0.370059   \n",
      "1491   0.095436   0.341176   0.398340   0.210458   0.290456  0.198693   \n",
      "1492   0.000000   0.227273   0.454545   0.318182   0.000000  0.386364   \n",
      "1493   0.074074   0.042373   0.148148   0.144068   0.259259  0.644068   \n",
      "1494   0.066667   0.324226   0.384615   0.247723   0.210256  0.378871   \n",
      "1495   0.057627   0.224329   0.261017   0.263823   0.223729  0.387046   \n",
      "1496   0.000000   0.290323   0.555556   0.129032   0.000000  0.548387   \n",
      "1497   0.000000   0.147059   0.290598   0.380392   0.376068  0.429412   \n",
      "1498   0.064846   0.333333   0.382253   0.238938   0.259386  0.355949   \n",
      "1499   0.033808   0.285423   0.250890   0.325688   0.368327  0.288991   \n",
      "1500   0.041885   0.283796   0.356021   0.322292   0.287958  0.296329   \n",
      "1501   0.067901   0.342770   0.416667   0.198180   0.216049  0.342770   \n",
      "1502   0.015789   0.265537   0.268421   0.343691   0.352632  0.321092   \n",
      "1503   0.041322   0.316699   0.371901   0.311900   0.297521  0.273512   \n",
      "1504   0.044776   0.198276   0.288557   0.295567   0.298507  0.374384   \n",
      "1505   0.049505   0.195122   0.148515   0.158537   0.277228  0.280488   \n",
      "1506   0.094203   0.262712   0.311594   0.216102   0.246377  0.364407   \n",
      "1507   0.054795   0.279032   0.356164   0.266129   0.184932  0.400000   \n",
      "1508   0.202417   0.315052   0.318731   0.144424   0.108761  0.364412   \n",
      "1509   0.031056   0.248748   0.285714   0.377295   0.366460  0.343907   \n",
      "1510   0.173077   0.418391   0.278846   0.149425   0.201923  0.268966   \n",
      "1511   0.106383   0.188482   0.212766   0.175393   0.191489  0.541885   \n",
      "1512   0.070946   0.274673   0.307432   0.246136   0.250000  0.324614   \n",
      "1513   0.025974   0.178439   0.298701   0.390335   0.337662  0.390335   \n",
      "1514   0.048387   0.243902   0.322581   0.346883   0.266129  0.308943   \n",
      "1515   0.170732   0.361022   0.382114   0.182109   0.065041  0.367412   \n",
      "1516   0.022989   0.221739   0.258621   0.284783   0.235632  0.393478   \n",
      "1517   0.018519   0.228070   0.259259   0.200000   0.185185  0.473684   \n",
      "1518   0.050526   0.280417   0.317895   0.303013   0.307368  0.308806   \n",
      "1519   0.021563   0.209191   0.231806   0.393690   0.382749  0.340192   \n",
      "1520   0.106632   0.414129   0.401821   0.194162   0.191157  0.303723   \n",
      "1521   0.073684   0.265683   0.284211   0.405904   0.389474  0.280443   \n",
      "1522   0.019417   0.226804   0.237864   0.288660   0.281553  0.365979   \n",
      "1523   0.129512   0.263045   0.326964   0.218397   0.225053  0.367402   \n",
      "1524   0.025783   0.148019   0.237569   0.338384   0.303867  0.435509   \n",
      "1525   0.090909   0.209581   0.265734   0.347305   0.328671  0.317365   \n",
      "1526   0.136364   0.167105   0.171717   0.267105   0.287879  0.390789   \n",
      "1527   0.089147   0.088652   0.085271   0.313830   0.302326  0.455674   \n",
      "1528   0.058296   0.341909   0.309417   0.224066   0.237668  0.313693   \n",
      "1529   0.054847   0.417994   0.436224   0.214620   0.248724  0.259606   \n",
      "1530   0.107692   0.652991   0.574359   0.164103   0.138462  0.105983   \n",
      "1531   0.085851   0.275419   0.249603   0.256425   0.290938  0.318436   \n",
      "1532   0.113386   0.271680   0.285039   0.192238   0.179528  0.382050   \n",
      "1533   0.199566   0.342163   0.316703   0.122884   0.140998  0.280353   \n",
      "1534   0.060296   0.384696   0.439135   0.190261   0.216155  0.286957   \n",
      "1535   0.088099   0.240000   0.261206   0.276216   0.247295  0.335676   \n",
      "1536   0.150198   0.143438   0.221344   0.180061   0.185771  0.308240   \n",
      "1537   0.103070   0.450275   0.361842   0.175107   0.236842  0.224527   \n",
      "1538   0.174164   0.300733   0.331027   0.167482   0.156863  0.277099   \n",
      "1539   0.060847   0.276534   0.312169   0.226874   0.216931  0.344693   \n",
      "1540   0.048673   0.269097   0.207965   0.135417   0.128319  0.390625   \n",
      "1541   0.069018   0.124800   0.148773   0.416000   0.466258  0.362667   \n",
      "1542   0.122099   0.323864   0.297679   0.235119   0.286579  0.264610   \n",
      "1543   0.056897   0.304521   0.334483   0.244016   0.256897  0.294548   \n",
      "1544   0.400000   0.256542   0.262434   0.131642   0.079365  0.256542   \n",
      "1545   0.193103   0.189831   0.268966   0.132203   0.165517  0.413559   \n",
      "1546   0.097561   0.402101   0.306911   0.198800   0.156504  0.289572   \n",
      "1547   0.087603   0.508603   0.400000   0.161437   0.228099  0.213057   \n",
      "1548   0.104762   0.357367   0.358095   0.181818   0.175238  0.353448   \n",
      "1549   0.132219   0.266738   0.281155   0.201913   0.145897  0.342189   \n",
      "1550   0.130952   0.410701   0.408730   0.146782   0.154762  0.252350   \n",
      "1551   0.142987   0.217961   0.237705   0.166505   0.165301  0.391748   \n",
      "1552   0.434726   0.266368   0.240209   0.089536   0.080940  0.254617   \n",
      "1553   0.030103   0.371374   0.342427   0.268199   0.259643  0.294472   \n",
      "1554   0.080321   0.329235   0.317269   0.258197   0.273092  0.273224   \n",
      "1555   0.098413   0.425732   0.400000   0.277197   0.200000  0.213389   \n",
      "1556   0.081081   0.268041   0.221622   0.212371   0.240541  0.346392   \n",
      "1557   0.069124   0.227407   0.276498   0.263704   0.311060  0.377037   \n",
      "1558   0.100962   0.218115   0.317308   0.160813   0.129808  0.445471   \n",
      "1559   0.081539   0.263703   0.273973   0.215949   0.242009  0.350271   \n",
      "1560   0.074766   0.238342   0.289720   0.274611   0.271028  0.393782   \n",
      "1561   0.057627   0.250000   0.379661   0.248355   0.223729  0.407895   \n",
      "1562   0.279221   0.254181   0.267532   0.132346   0.106494  0.297181   \n",
      "1563   0.066437   0.419173   0.432269   0.290413   0.285591  0.182176   \n",
      "1564   0.054054   0.381454   0.370270   0.239199   0.297297  0.206533   \n",
      "1565   0.060329   0.284810   0.294333   0.241913   0.217550  0.367792   \n",
      "1566   0.070796   0.313094   0.304204   0.378356   0.362832  0.230483   \n",
      "1567   0.153631   0.192731   0.162011   0.151982   0.178771  0.401982   \n",
      "1568   0.238095   0.286501   0.269841   0.151515   0.206349  0.294766   \n",
      "1569   0.357576   0.162500   0.169697   0.150000   0.193939  0.283929   \n",
      "1570   0.107527   0.173448   0.198925   0.214133   0.209677  0.364026   \n",
      "1571   0.125405   0.311086   0.341424   0.292421   0.279126  0.245475   \n",
      "1572   0.176678   0.184049   0.169611   0.314110   0.229682  0.328834   \n",
      "1573   0.106352   0.341274   0.363368   0.199446   0.221566  0.296953   \n",
      "1574   0.077649   0.285842   0.317852   0.323523   0.342525  0.251951   \n",
      "1575   0.105202   0.432742   0.405780   0.230375   0.238150  0.204734   \n",
      "1576   0.045267   0.099849   0.119342   0.211800   0.218107  0.390318   \n",
      "1577   0.063291   0.135258   0.145570   0.191489   0.208861  0.420973   \n",
      "1578   0.057592   0.116751   0.130890   0.345178   0.293194  0.423858   \n",
      "1579   0.000000   0.500000   0.363636   0.400000   0.181818  0.100000   \n",
      "1580   0.151734   0.244229   0.278902   0.323176   0.385838  0.194829   \n",
      "1581   0.040212   0.341641   0.390744   0.332295   0.324734  0.232191   \n",
      "1582   0.059843   0.389480   0.362730   0.317607   0.352231  0.204778   \n",
      "1583   0.162602   0.487047   0.455285   0.170984   0.154472  0.233161   \n",
      "1584   0.013274   0.306011   0.296460   0.291439   0.358407  0.318761   \n",
      "1585   0.073718   0.377626   0.360577   0.281658   0.277244  0.227712   \n",
      "1586   0.108225   0.316327   0.311688   0.194805   0.177489  0.294063   \n",
      "1587   0.177370   0.266298   0.269113   0.218785   0.262997  0.303867   \n",
      "1588   0.109626   0.192180   0.259358   0.263727   0.203209  0.372712   \n",
      "1589   0.034483   0.246753   0.271552   0.298701   0.306034  0.346939   \n",
      "1590   0.054974   0.275258   0.280105   0.303093   0.337696  0.332990   \n",
      "1591   0.198842   0.282178   0.303089   0.163366   0.194981  0.303395   \n",
      "1592   0.155527   0.341052   0.343188   0.193439   0.197943  0.294260   \n",
      "1593   0.363305   0.193285   0.226610   0.130771   0.119077  0.308151   \n",
      "1594   0.194511   0.317237   0.362172   0.204768   0.187947  0.251426   \n",
      "1595   0.180328   0.296811   0.305514   0.215535   0.166915  0.298354   \n",
      "1596   0.182213   0.173370   0.203905   0.196255   0.151844  0.399445   \n",
      "1597   0.200495   0.266612   0.241955   0.171492   0.191832  0.315688   \n",
      "1598   0.380673   0.252740   0.256273   0.125923   0.089696  0.247372   \n",
      "1599   0.157576   0.237750   0.278788   0.340593   0.306061  0.237145   \n",
      "1600   0.170561   0.206767   0.287383   0.231579   0.226636  0.326316   \n",
      "1601   0.173077   0.085813   0.201923   0.061592   0.076923  0.107958   \n",
      "1602   0.058511   0.265794   0.294833   0.341308   0.330547  0.291963   \n",
      "1603   0.204969   0.180420   0.240166   0.199301   0.182195  0.281119   \n",
      "1604   0.230380   0.301751   0.303797   0.133363   0.149367  0.292771   \n",
      "1605   0.079365   0.181818   0.238095   0.231405   0.158730  0.363636   \n",
      "1606   0.102837   0.178637   0.202128   0.141191   0.193262  0.531001   \n",
      "1607   0.327091   0.146583   0.167291   0.116906   0.106117  0.309952   \n",
      "1608   0.051443   0.302007   0.297365   0.312775   0.317440  0.303475   \n",
      "1609   0.027132   0.301565   0.236434   0.263158   0.399225  0.275960   \n",
      "1610   0.098807   0.147457   0.211244   0.344495   0.320273  0.353509   \n",
      "1611   0.042155   0.369950   0.295082   0.340184   0.370023  0.206237   \n",
      "1612   0.022831   0.221154   0.223744   0.355769   0.347032  0.323077   \n",
      "1613   0.073245   0.284792   0.345036   0.378576   0.351090  0.240052   \n",
      "1614   0.090395   0.373134   0.265537   0.151741   0.180791  0.278607   \n",
      "1615   0.049180   0.305556   0.327869   0.152778   0.163934  0.375000   \n",
      "1616   0.037594   0.311916   0.402256   0.348131   0.327068  0.250000   \n",
      "1617   0.041322   0.304245   0.264463   0.349057   0.380165  0.240566   \n",
      "1618   0.087983   0.179949   0.223176   0.297344   0.266094  0.407883   \n",
      "1619   0.005814   0.167107   0.236434   0.365944   0.379845  0.441036   \n",
      "1620   0.204000   0.291107   0.284000   0.243762   0.214000  0.248880   \n",
      "1621   0.042169   0.311412   0.271084   0.249516   0.289157  0.323017   \n",
      "1622   0.107884   0.139619   0.200553   0.307344   0.283541  0.418404   \n",
      "1623   0.110626   0.223220   0.264920   0.331944   0.321689  0.341244   \n",
      "1624   0.010870   0.143969   0.217391   0.365759   0.347826  0.307393   \n",
      "1625   0.042079   0.291353   0.316832   0.257306   0.248144  0.329617   \n",
      "1626   0.099874   0.305049   0.359039   0.152312   0.194690  0.368689   \n",
      "1627   0.022222   0.436455   0.448148   0.283278   0.260494  0.238127   \n",
      "1628   0.143345   0.229898   0.303754   0.206116   0.259386  0.244621   \n",
      "1629   0.130769   0.231707   0.346154   0.312500   0.269231  0.312500   \n",
      "1630   0.053151   0.313568   0.326500   0.377784   0.398633  0.199379   \n",
      "1631   0.021390   0.302707   0.349121   0.418792   0.407945  0.230088   \n",
      "1632   0.072937   0.244218   0.318618   0.338776   0.332054  0.335374   \n",
      "1633   0.065891   0.143548   0.180233   0.184630   0.163760  0.481392   \n",
      "1634   0.031100   0.582687   0.574163   0.147287   0.184211  0.177649   \n",
      "1635   0.031030   0.292265   0.396333   0.347217   0.339915  0.278614   \n",
      "1636   0.124688   0.215200   0.274314   0.246400   0.214464  0.452000   \n",
      "1637   0.116751   0.287625   0.233503   0.214047   0.157360  0.387960   \n",
      "1638   0.109091   0.400000   0.309091   0.116129   0.272727  0.277419   \n",
      "1639   0.014493   0.295148   0.354037   0.341644   0.310559  0.279650   \n",
      "1640   0.011628   0.328173   0.302326   0.204334   0.189922  0.371517   \n",
      "1641   0.028571   0.240000   0.314286   0.204000   0.342857  0.480000   \n",
      "1642   0.122302   0.195110   0.366906   0.382396   0.273381  0.306112   \n",
      "1643   0.093827   0.279412   0.326749   0.334423   0.333333  0.244009   \n",
      "1644   0.109434   0.338010   0.332075   0.295918   0.211321  0.270408   \n",
      "1645   0.138298   0.322546   0.329787   0.183387   0.180851  0.312837   \n",
      "1646   0.102273   0.231168   0.276136   0.354803   0.314773  0.307587   \n",
      "1647   0.036223   0.305258   0.341527   0.344421   0.376455  0.280043   \n",
      "1648   0.149390   0.158872   0.298780   0.193260   0.256098  0.262724   \n",
      "1649   0.068413   0.274190   0.357351   0.361106   0.339884  0.261125   \n",
      "1650   0.083333   0.254417   0.307971   0.270907   0.163043  0.380448   \n",
      "1651   0.046318   0.159633   0.294537   0.341590   0.280285  0.425382   \n",
      "1652   0.050219   0.297030   0.294911   0.385132   0.403101  0.257258   \n",
      "1653   0.085852   0.306977   0.347037   0.293023   0.269649  0.281395   \n",
      "1654   0.054572   0.334307   0.382006   0.310462   0.327434  0.258394   \n",
      "1655   0.030905   0.404272   0.362031   0.379747   0.434879  0.203323   \n",
      "1656   0.081395   0.244055   0.298450   0.202128   0.203488  0.444305   \n",
      "1657   0.115942   0.156277   0.188406   0.373134   0.260870  0.373134   \n",
      "1658   0.102377   0.213417   0.243754   0.316816   0.297380  0.328444   \n",
      "1659   0.106227   0.257636   0.351648   0.213811   0.142857  0.409031   \n",
      "1660   0.043042   0.331950   0.372052   0.391485   0.387972  0.205845   \n",
      "1661   0.078725   0.274029   0.316776   0.274666   0.224930  0.299491   \n",
      "1662   0.075117   0.186667   0.276995   0.373333   0.333333  0.265000   \n",
      "1663   0.052632   0.145588   0.156015   0.336029   0.323308  0.425735   \n",
      "1664   0.035167   0.454088   0.496844   0.294431   0.274121  0.165877   \n",
      "1665   0.020690   0.628880   0.513793   0.171390   0.289655  0.160594   \n",
      "1666   0.082192   0.363636   0.294521   0.153247   0.171233  0.355844   \n",
      "1667   0.205128   0.231760   0.243590   0.244635   0.166667  0.369099   \n",
      "1668   0.087071   0.239669   0.292876   0.331850   0.282322  0.355372   \n",
      "1669   0.171875   0.243386   0.243750   0.279101   0.231250  0.347884   \n",
      "1670   0.094755   0.164474   0.194585   0.295040   0.282572  0.449393   \n",
      "1671   0.319426   0.195386   0.276402   0.088081   0.083442  0.305488   \n",
      "1672   0.014936   0.289686   0.351351   0.429982   0.413940  0.239023   \n",
      "1673   0.032895   0.341057   0.407895   0.288230   0.289474  0.319741   \n",
      "1674   0.121646   0.290508   0.326476   0.169153   0.171735  0.336271   \n",
      "1675   0.037037   0.209231   0.226852   0.330769   0.208333  0.358462   \n",
      "1676   0.106796   0.300268   0.398058   0.061662   0.067961  0.412869   \n",
      "1677   0.019048   0.235741   0.285714   0.264259   0.280952  0.385932   \n",
      "1678   0.114796   0.329834   0.323980   0.266842   0.252551  0.269466   \n",
      "1679   0.070312   0.202817   0.234375   0.281690   0.281250  0.388732   \n",
      "1680   0.014583   0.488728   0.472917   0.366345   0.389583  0.102254   \n",
      "1681   0.024742   0.255944   0.257732   0.297203   0.307216  0.349650   \n",
      "1682   0.138721   0.158093   0.183165   0.146048   0.125253  0.551066   \n",
      "1683   0.008230   0.192410   0.222222   0.380826   0.349794  0.390146   \n",
      "1684   0.054237   0.252304   0.316949   0.262097   0.244068  0.360599   \n",
      "1685   0.015957   0.395105   0.351064   0.193473   0.239362  0.358974   \n",
      "1686   0.165714   0.213333   0.297143   0.166000   0.127619  0.277333   \n",
      "1687   0.083160   0.235788   0.315315   0.309936   0.356202  0.346515   \n",
      "1688   0.085271   0.279487   0.298450   0.225641   0.269380  0.393590   \n",
      "1689   0.017011   0.510245   0.520049   0.316342   0.335358  0.141429   \n",
      "1690   0.134731   0.318408   0.311377   0.265814   0.332335  0.302061   \n",
      "1691   0.000000   0.058824   0.076923   0.220588   0.307692  0.367647   \n",
      "1692   0.137521   0.157432   0.156197   0.250000   0.252971  0.372973   \n",
      "1693   0.145511   0.138781   0.226006   0.238651   0.191950  0.416342   \n",
      "1694   0.148936   0.230769   0.255319   0.141026   0.255319  0.358974   \n",
      "1695   0.388489   0.221963   0.227133   0.213952   0.125385  0.246662   \n",
      "1696   0.209836   0.232330   0.254098   0.223168   0.168852  0.411649   \n",
      "1697   0.118598   0.246894   0.320755   0.191770   0.183288  0.390528   \n",
      "1698   0.128931   0.298048   0.299790   0.197072   0.225367  0.349474   \n",
      "1699   0.125189   0.261404   0.273002   0.241927   0.315234  0.348027   \n",
      "1700   0.059150   0.501403   0.478743   0.170253   0.199630  0.239476   \n",
      "1701   0.291815   0.238731   0.217082   0.156928   0.096085  0.358932   \n",
      "1702   0.076377   0.377908   0.350503   0.288324   0.310243  0.236356   \n",
      "1703   0.059561   0.251931   0.263323   0.327220   0.382445  0.302124   \n",
      "1704   0.051282   0.235343   0.373219   0.271357   0.168091  0.292295   \n",
      "1705   0.086580   0.223430   0.216450   0.236715   0.268398  0.336957   \n",
      "1706   0.080139   0.258870   0.282230   0.111695   0.128920  0.411301   \n",
      "1707   0.029310   0.247177   0.246552   0.346766   0.401724  0.344456   \n",
      "1708   0.028777   0.274245   0.330935   0.357711   0.370504  0.316375   \n",
      "1709   0.137817   0.236742   0.271775   0.282669   0.239250  0.349914   \n",
      "1710   0.022321   0.412409   0.433036   0.344891   0.397321  0.189781   \n",
      "1711   0.028090   0.442826   0.425562   0.269148   0.306180  0.211974   \n",
      "1712   0.008772   0.408419   0.456140   0.318544   0.307018  0.246871   \n",
      "1713   0.025210   0.113074   0.067227   0.137809   0.126050  0.526502   \n",
      "1714   0.020495   0.361988   0.400512   0.348724   0.366354  0.247146   \n",
      "1715   0.123636   0.316667   0.287273   0.262500   0.247273  0.229167   \n",
      "1716   0.114967   0.250575   0.312364   0.245211   0.273319  0.335632   \n",
      "1717   0.182272   0.351249   0.399501   0.162866   0.161049  0.298046   \n",
      "1718   0.069343   0.243745   0.310219   0.374892   0.324818  0.294219   \n",
      "1719   0.148148   0.141264   0.140741   0.323420   0.200000  0.327138   \n",
      "1720   0.037209   0.255352   0.265116   0.373089   0.381395  0.273700   \n",
      "1721   0.216643   0.235294   0.241033   0.276471   0.288379  0.206335   \n",
      "1722   0.127072   0.330759   0.386740   0.253968   0.213628  0.306735   \n",
      "1723   0.095238   0.343612   0.422619   0.296623   0.261905  0.274596   \n",
      "1724   0.069892   0.274349   0.336918   0.340520   0.317204  0.308550   \n",
      "1725   0.099437   0.301724   0.388368   0.250663   0.181989  0.372679   \n",
      "1726   0.332581   0.271656   0.241535   0.196310   0.166290  0.202460   \n",
      "1727   0.146893   0.194790   0.231638   0.199604   0.175141  0.466591   \n",
      "1728   0.059502   0.259889   0.284153   0.314787   0.332119  0.339002   \n",
      "1729   0.052632   0.311554   0.284211   0.297799   0.280000  0.299175   \n",
      "1730   0.116279   0.272212   0.313341   0.271150   0.298654  0.282478   \n",
      "1731   0.051042   0.348930   0.361458   0.321858   0.296875  0.235963   \n",
      "1732   0.056962   0.188312   0.297468   0.259740   0.227848  0.402597   \n",
      "1733   0.045455   0.165746   0.176768   0.390884   0.429293  0.334254   \n",
      "1734   0.047619   0.293853   0.285714   0.397301   0.400000  0.242879   \n",
      "1735   0.052345   0.452475   0.459106   0.213201   0.251908  0.247195   \n",
      "1736   0.055556   0.240248   0.262626   0.252012   0.207071  0.426625   \n",
      "1737   0.153477   0.241531   0.249400   0.232120   0.211031  0.337516   \n",
      "1738   0.067524   0.230769   0.372990   0.335059   0.302251  0.362426   \n",
      "1739   0.020270   0.479452   0.506757   0.279452   0.236486  0.183562   \n",
      "1740   0.034913   0.222659   0.291771   0.438238   0.403990  0.269079   \n",
      "1741   0.116279   0.266542   0.273902   0.213420   0.237726  0.388630   \n",
      "1742   0.100132   0.262210   0.299078   0.359412   0.341238  0.258416   \n",
      "1743   0.022978   0.234677   0.280331   0.311548   0.314338  0.355232   \n",
      "1744   0.228650   0.230216   0.214876   0.203237   0.217631  0.344424   \n",
      "1745   0.072655   0.365703   0.377146   0.268401   0.273314  0.263275   \n",
      "1746   0.114078   0.248354   0.315534   0.248354   0.366505  0.310442   \n",
      "1747   0.127660   0.140091   0.143617   0.088838   0.114362  0.544419   \n",
      "1748   0.072917   0.194991   0.284722   0.328265   0.295139  0.366726   \n",
      "1749   0.045802   0.173824   0.335878   0.335378   0.221374  0.337423   \n",
      "1750   0.082892   0.277822   0.303351   0.317854   0.352734  0.304243   \n",
      "1751   0.065789   0.410423   0.526316   0.231270   0.184211  0.299674   \n",
      "1752   0.024390   0.261538   0.292683   0.207692   0.048780  0.484615   \n",
      "1753   0.107143   0.320442   0.303571   0.292818   0.250000  0.287293   \n",
      "1754   0.056738   0.238693   0.241135   0.437186   0.482270  0.155779   \n",
      "1755   0.073529   0.203996   0.242647   0.321767   0.311275  0.349106   \n",
      "1756   0.086651   0.214836   0.281030   0.275017   0.241218  0.337999   \n",
      "1757   0.000000   0.174641   0.245487   0.368421   0.361011  0.375598   \n",
      "1758   0.150602   0.205674   0.234940   0.157801   0.222892  0.338652   \n",
      "1759   0.017391   0.302211   0.358261   0.367322   0.393043  0.255528   \n",
      "1760   0.065120   0.236616   0.251497   0.322276   0.310629  0.352299   \n",
      "1761   0.092810   0.224784   0.329412   0.337536   0.359477  0.307997   \n",
      "1762   0.160194   0.303478   0.269417   0.313913   0.330097  0.263478   \n",
      "1763   0.040850   0.302758   0.325163   0.425273   0.405229  0.205901   \n",
      "1764   0.018405   0.119777   0.153374   0.353760   0.276074  0.455432   \n",
      "1765   0.058278   0.297561   0.364238   0.325942   0.376159  0.255876   \n",
      "1766   0.031579   0.215768   0.315789   0.392116   0.336842  0.296680   \n",
      "1767   0.046154   0.383886   0.553846   0.289100   0.246154  0.199052   \n",
      "1768   0.000000   0.184783   0.333333   0.421196   0.300000  0.307065   \n",
      "1769   0.097122   0.248736   0.323741   0.314459   0.255396  0.276036   \n",
      "1770   0.203125   0.106045   0.234375   0.054083   0.218750  0.185578   \n",
      "1771   0.047725   0.293872   0.320755   0.365569   0.338513  0.286369   \n",
      "1772   0.055556   0.181818   0.166667   0.368831   0.238095  0.405195   \n",
      "1773   0.045181   0.246946   0.237952   0.431937   0.400602  0.268761   \n",
      "1774   0.050000   0.470968   0.425000   0.316129   0.400000  0.161290   \n",
      "1775   0.138211   0.191489   0.300813   0.191489   0.227642  0.288754   \n",
      "1776   0.041667   0.689519   0.679825   0.200946   0.188596  0.071710   \n",
      "1777   0.025641   0.281955   0.299145   0.191729   0.247863  0.390977   \n",
      "1778   0.106667   0.207273   0.240000   0.389091   0.333333  0.312727   \n",
      "1779   0.052632   0.226158   0.263158   0.204360   0.177632  0.425068   \n",
      "1780   0.115942   0.294574   0.144928   0.155039   0.173913  0.333333   \n",
      "1781   0.073420   0.296841   0.355948   0.347721   0.359665  0.252231   \n",
      "1782   0.099057   0.193684   0.311321   0.208421   0.264151  0.206316   \n",
      "1783   0.136076   0.231332   0.218354   0.288433   0.291139  0.262079   \n",
      "1784   0.214286   0.183607   0.202381   0.316393   0.321429  0.347541   \n",
      "1785   0.033746   0.258094   0.323960   0.437216   0.420697  0.261120   \n",
      "1786   0.135783   0.226744   0.260383   0.250000   0.244409  0.275899   \n",
      "1787   0.076087   0.269209   0.285714   0.282950   0.262422  0.338755   \n",
      "1788   0.129310   0.179764   0.206897   0.228880   0.238506  0.466601   \n",
      "1789   0.171674   0.196275   0.244635   0.369628   0.218884  0.309456   \n",
      "1790   0.006536   0.320129   0.315904   0.311237   0.372549  0.269200   \n",
      "1791   0.223214   0.208191   0.187500   0.221843   0.267857  0.324232   \n",
      "1792   0.043315   0.273941   0.317368   0.352504   0.376926  0.286874   \n",
      "1793   0.233193   0.333065   0.329832   0.234677   0.195378  0.150806   \n",
      "1794   0.224490   0.295826   0.311224   0.223230   0.173469  0.208711   \n",
      "1795   0.066116   0.268852   0.231405   0.334426   0.355372  0.262295   \n",
      "1796   0.049020   0.235556   0.235294   0.191111   0.333333  0.311111   \n",
      "1797   0.110204   0.210219   0.310204   0.316788   0.228571  0.270073   \n",
      "1798   0.026059   0.203276   0.260586   0.184971   0.195440  0.455684   \n",
      "1799   0.098494   0.247923   0.280417   0.341058   0.338355  0.273721   \n",
      "1800   0.072581   0.288956   0.262097   0.366112   0.407258  0.285930   \n",
      "1801   0.073418   0.209577   0.330380   0.335184   0.279747  0.380291   \n",
      "1802   0.228897   0.227510   0.225856   0.169788   0.141445  0.347866   \n",
      "1803   0.197531   0.060714   0.329218   0.045408   0.222222  0.155102   \n",
      "1804   0.010929   0.194415   0.196721   0.396348   0.486339  0.360902   \n",
      "1805   0.074830   0.283734   0.333333   0.303142   0.319728  0.346580   \n",
      "1806   0.077049   0.165295   0.227869   0.299497   0.280328  0.425240   \n",
      "1807   0.021807   0.195100   0.283489   0.362069   0.299065  0.414701   \n",
      "1808   0.067857   0.261649   0.282143   0.219235   0.228571  0.366189   \n",
      "1809   0.092683   0.439222   0.336585   0.181524   0.292683  0.175041   \n",
      "1810   0.095064   0.325540   0.396709   0.229017   0.236746  0.317746   \n",
      "1811   0.108108   0.217391   0.405405   0.086957   0.081081  0.391304   \n",
      "1812   0.142857   0.379854   0.344948   0.137136   0.101045  0.371359   \n",
      "1813   0.027160   0.274408   0.330864   0.388793   0.301235  0.248122   \n",
      "1814   0.053178   0.308739   0.356680   0.305338   0.300908  0.334920   \n",
      "1815   0.019780   0.492328   0.483516   0.274003   0.284615  0.205173   \n",
      "1816   0.081395   0.306998   0.345930   0.367946   0.348837  0.181716   \n",
      "1817   0.176334   0.243304   0.269142   0.188988   0.141531  0.335565   \n",
      "1818   0.065934   0.240518   0.217033   0.349676   0.337912  0.283996   \n",
      "1819   0.028552   0.433148   0.432935   0.310345   0.312749  0.204672   \n",
      "1820   0.073491   0.350407   0.412073   0.266589   0.249344  0.295693   \n",
      "1821   0.036697   0.364842   0.399083   0.291874   0.284404  0.225539   \n",
      "1822   0.018421   0.212714   0.389474   0.383863   0.307895  0.372127   \n",
      "1823   0.000000   0.084444   0.187500   0.328889   0.287500  0.386667   \n",
      "1824   0.009501   0.184103   0.180523   0.365641   0.294537  0.398462   \n",
      "1825   0.016667   0.154791   0.225000   0.292383   0.200000  0.491400   \n",
      "1826   0.029412   0.257435   0.291444   0.326208   0.368984  0.270446   \n",
      "1827   0.014368   0.280501   0.321839   0.223149   0.152299  0.319082   \n",
      "1828   0.064516   0.230221   0.205645   0.376336   0.403226  0.313614   \n",
      "1829   0.051724   0.206349   0.310345   0.439153   0.293103  0.264550   \n",
      "1830   0.102128   0.253607   0.287234   0.244495   0.214894  0.347001   \n",
      "1831   0.028986   0.343915   0.355072   0.248677   0.239130  0.312169   \n",
      "1832   0.061552   0.202188   0.242640   0.265937   0.306869  0.428895   \n",
      "1833   0.095839   0.321569   0.384615   0.259314   0.261034  0.254902   \n",
      "1834   0.225352   0.253232   0.282570   0.248105   0.202465  0.338609   \n",
      "1835   0.036199   0.323741   0.333333   0.417746   0.432881  0.203357   \n",
      "1836   0.018182   0.379904   0.463636   0.359809   0.339394  0.210526   \n",
      "1837   0.014354   0.398981   0.531100   0.404075   0.293461  0.187889   \n",
      "1838   0.106109   0.365768   0.395498   0.261430   0.250804  0.188746   \n",
      "1839   0.035000   0.278736   0.315000   0.386207   0.290000  0.312644   \n",
      "1840   0.034043   0.514694   0.529787   0.266878   0.278723  0.158856   \n",
      "1841   0.066998   0.313058   0.354839   0.285410   0.286600  0.318162   \n",
      "1842   0.020681   0.348039   0.377129   0.383578   0.356448  0.235600   \n",
      "1843   0.018284   0.332266   0.492264   0.352544   0.347398  0.219495   \n",
      "1844   0.046647   0.201586   0.247813   0.210646   0.209913  0.421291   \n",
      "1845   0.071429   0.321792   0.295918   0.336049   0.352041  0.264766   \n",
      "1846   0.174737   0.316823   0.269474   0.163962   0.221053  0.357814   \n",
      "1847   0.114407   0.291709   0.312147   0.283114   0.299435  0.274520   \n",
      "1848   0.000000   0.365079   0.382353   0.238095   0.227941  0.279365   \n",
      "1849   0.203327   0.249531   0.323475   0.333490   0.247689  0.292214   \n",
      "1850   0.151618   0.272727   0.255537   0.164654   0.214651  0.430388   \n",
      "1851   0.103409   0.318505   0.344318   0.290036   0.286364  0.272242   \n",
      "1852   0.092851   0.332885   0.323747   0.270953   0.311422  0.272972   \n",
      "1853   0.024531   0.292297   0.366522   0.409904   0.406926  0.270977   \n",
      "1854   0.029740   0.410526   0.472119   0.357895   0.323420  0.205263   \n",
      "1855   0.088732   0.172818   0.205634   0.301780   0.300000  0.408163   \n",
      "1856   0.045455   0.153061   0.266234   0.432653   0.350649  0.322449   \n",
      "1857   0.040000   0.445205   0.400000   0.256849   0.280000  0.248288   \n",
      "1858   0.000000   0.205882   0.125000   0.529412   0.750000  0.235294   \n",
      "1859   0.137725   0.185668   0.260479   0.273616   0.308383  0.227199   \n",
      "1860   0.200669   0.249119   0.307692   0.305523   0.301003  0.184489   \n",
      "1861   0.077170   0.343266   0.379421   0.274136   0.254019  0.241955   \n",
      "1862   0.125257   0.178244   0.223819   0.189384   0.186858  0.311927   \n",
      "1863   0.020408   0.370879   0.520408   0.368132   0.255102  0.197802   \n",
      "1864   0.100000   0.265823   0.255556   0.367089   0.355556  0.240506   \n",
      "1865   0.031484   0.438269   0.460270   0.403189   0.310345  0.134396   \n",
      "1866   0.178451   0.296662   0.342312   0.243065   0.200898  0.261871   \n",
      "1867   0.030726   0.298752   0.363128   0.340874   0.337989  0.295632   \n",
      "1868   0.017143   0.395871   0.285714   0.309047   0.302857  0.274438   \n",
      "1869   0.030189   0.185507   0.162264   0.384541   0.396226  0.376812   \n",
      "1870   0.026393   0.304865   0.284457   0.341622   0.343109  0.299459   \n",
      "1871   0.212766   0.047945   0.085106   0.239726   0.255319  0.520548   \n",
      "1872   0.294643   0.181935   0.178571   0.112258   0.321429  0.179355   \n",
      "1873   0.299270   0.146259   0.160584   0.176871   0.145985  0.241497   \n",
      "1874   0.040179   0.635088   0.580357   0.118129   0.178571  0.171930   \n",
      "1875   0.015000   0.752013   0.785000   0.169887   0.105000  0.067633   \n",
      "1876   0.000000   0.701368   0.618257   0.172492   0.170124  0.111702   \n",
      "1877   0.101881   0.258186   0.294671   0.160579   0.184953  0.365239   \n",
      "1878   0.042963   0.253870   0.271111   0.380186   0.312593  0.288545   \n",
      "1879   0.088496   0.247126   0.318584   0.316092   0.300885  0.272989   \n",
      "1880   0.066116   0.300437   0.363636   0.441485   0.348760  0.222707   \n",
      "1881   0.010886   0.442495   0.527216   0.334835   0.275272  0.194451   \n",
      "1882   0.018182   0.304853   0.409091   0.401914   0.324242  0.264525   \n",
      "1883   0.024390   0.225806   0.073171   0.096774   0.170732  0.500000   \n",
      "1884   0.174432   0.393828   0.359618   0.210507   0.222222  0.230345   \n",
      "1885   0.183628   0.327520   0.329646   0.222343   0.150442  0.291553   \n",
      "1886   0.225806   0.188202   0.204301   0.123596   0.150538  0.471910   \n",
      "1887   0.059754   0.315242   0.318102   0.222305   0.231986  0.359851   \n",
      "1888   0.125000   0.210584   0.212121   0.265711   0.250000  0.390298   \n",
      "1889   0.037037   0.233333   0.245614   0.281538   0.327485  0.372308   \n",
      "1890   0.013274   0.445643   0.579646   0.224066   0.238938  0.303734   \n",
      "1891   0.024272   0.279959   0.305825   0.331612   0.266990  0.305785   \n",
      "1892   0.025822   0.141284   0.138498   0.183486   0.204225  0.470642   \n",
      "1893   0.373333   0.108553   0.206667   0.264803   0.186667  0.268092   \n",
      "1894   0.032110   0.369469   0.433486   0.377212   0.357798  0.215708   \n",
      "1895   0.007937   0.175532   0.277778   0.386525   0.301587  0.349291   \n",
      "1896   0.062762   0.344778   0.309623   0.316166   0.313808  0.257511   \n",
      "1897   0.237288   0.272189   0.251412   0.150888   0.110169  0.408284   \n",
      "1898   0.026829   0.367074   0.413415   0.454927   0.446341  0.147441   \n",
      "1899   0.080636   0.607525   0.580362   0.136719   0.146462  0.172492   \n",
      "1900   0.028986   0.207955   0.286957   0.364205   0.333333  0.373295   \n",
      "1901   0.008247   0.478228   0.435052   0.321321   0.350515  0.147147   \n",
      "1902   0.186813   0.215122   0.271062   0.181818   0.208791  0.399640   \n",
      "1903   0.160305   0.244828   0.236641   0.286207   0.259542  0.386207   \n",
      "1904   0.050633   0.211538   0.265823   0.256410   0.303797  0.365385   \n",
      "1905   0.043750   0.326568   0.375000   0.431734   0.393750  0.217712   \n",
      "1906   0.011111   0.072937   0.222222   0.145873   0.166667  0.758157   \n",
      "1907   0.111901   0.181966   0.298401   0.314785   0.250444  0.393176   \n",
      "1908   0.034221   0.350746   0.387833   0.273632   0.273764  0.278607   \n",
      "1909   0.029900   0.216972   0.312292   0.312156   0.273256  0.404358   \n",
      "1910   0.068745   0.273383   0.278977   0.268764   0.278977  0.251443   \n",
      "1911   0.100865   0.155292   0.158501   0.217606   0.299712  0.490603   \n",
      "1912   0.041949   0.208712   0.309878   0.410952   0.416103  0.349545   \n",
      "1913   0.053279   0.182800   0.356557   0.429165   0.362705  0.356460   \n",
      "1914   0.013559   0.201669   0.240678   0.327538   0.413559  0.426287   \n",
      "1915   0.077922   0.197002   0.240260   0.286938   0.311688  0.349036   \n",
      "1916   0.067460   0.216839   0.293651   0.288805   0.291667  0.461900   \n",
      "1917   0.032258   0.253247   0.285714   0.311688   0.271889  0.334416   \n",
      "1918   0.023622   0.225979   0.259843   0.376038   0.370079  0.340451   \n",
      "1919   0.044183   0.241730   0.248895   0.385242   0.421208  0.291094   \n",
      "1920   0.060606   0.320998   0.319559   0.371773   0.341598  0.224613   \n",
      "1921   0.089147   0.205047   0.244186   0.255521   0.302326  0.244479   \n",
      "1922   0.019048   0.263876   0.223810   0.389445   0.345238  0.255687   \n",
      "1923   0.054717   0.144866   0.228302   0.234880   0.266038  0.492264   \n",
      "1924   0.020202   0.275394   0.341751   0.405576   0.406566  0.246788   \n",
      "1925   0.167598   0.278998   0.304469   0.246295   0.202514  0.290240   \n",
      "1926   0.044118   0.339672   0.321569   0.307448   0.297059  0.257264   \n",
      "1927   0.165975   0.196751   0.226141   0.248496   0.232365  0.396510   \n",
      "1928   0.060606   0.209366   0.166667   0.358127   0.242424  0.297521   \n",
      "1929   0.215865   0.237712   0.266580   0.157730   0.149545  0.321269   \n",
      "1930   0.110997   0.325405   0.318602   0.235216   0.250771  0.281797   \n",
      "1931   0.018750   0.198357   0.287500   0.315728   0.450000  0.428991   \n",
      "1932   0.092199   0.194672   0.241135   0.284836   0.248227  0.311475   \n",
      "1933   0.075887   0.407018   0.370869   0.267168   0.305998  0.252130   \n",
      "1934   0.005208   0.218659   0.177083   0.195335   0.192708  0.387755   \n",
      "1935   0.036087   0.311962   0.345679   0.349955   0.372745  0.253785   \n",
      "1936   0.031345   0.330469   0.304348   0.232031   0.228514  0.326562   \n",
      "1937   0.014599   0.199105   0.270073   0.275168   0.291971  0.483221   \n",
      "1938   0.040404   0.260714   0.404040   0.214286   0.272727  0.453571   \n",
      "1939   0.071285   0.290691   0.233936   0.234234   0.259036  0.333333   \n",
      "1940   0.038062   0.357724   0.410035   0.322042   0.320069  0.270551   \n",
      "1941   0.028235   0.466397   0.515294   0.289069   0.258824  0.211336   \n",
      "1942   0.145631   0.270904   0.401942   0.142080   0.131068  0.401428   \n",
      "1943   0.049618   0.328345   0.374046   0.309297   0.381679  0.289342   \n",
      "1944   0.090395   0.231335   0.177966   0.125131   0.169492  0.362776   \n",
      "1945   0.018282   0.356000   0.383912   0.384667   0.398537  0.228000   \n",
      "1946   0.045455   0.540059   0.431818   0.219585   0.431818  0.195846   \n",
      "1947   0.117407   0.356933   0.452856   0.208883   0.196283  0.258135   \n",
      "1948   0.070191   0.298273   0.318969   0.335060   0.309196  0.284111   \n",
      "1949   0.072000   0.184953   0.152000   0.216301   0.280000  0.438871   \n",
      "1950   0.007407   0.271277   0.296296   0.308511   0.333333  0.311170   \n",
      "1951   0.061224   0.285276   0.387755   0.352761   0.295918  0.276074   \n",
      "1952   0.079470   0.229032   0.298013   0.304839   0.317881  0.372581   \n",
      "1953   0.203070   0.266826   0.328681   0.212411   0.179344  0.358234   \n",
      "1954   0.190114   0.174033   0.292776   0.113260   0.121673  0.385820   \n",
      "1955   0.027933   0.333863   0.329609   0.243243   0.335196  0.303657   \n",
      "1956   0.033163   0.225073   0.285714   0.323314   0.339286  0.373900   \n",
      "1957   0.037441   0.363960   0.385335   0.287493   0.262090  0.303497   \n",
      "1958   0.029221   0.297327   0.344156   0.336303   0.275974  0.283964   \n",
      "1959   0.013699   0.246120   0.328767   0.458980   0.479452  0.252772   \n",
      "1960   0.101029   0.309035   0.332086   0.239904   0.220767  0.318617   \n",
      "1961   0.064762   0.230937   0.274286   0.318083   0.283810  0.350036   \n",
      "1962   0.096045   0.207278   0.192090   0.295886   0.350282  0.321203   \n",
      "1963   0.092409   0.230684   0.272277   0.243377   0.267327  0.278146   \n",
      "1964   0.161264   0.297898   0.374896   0.221896   0.173732  0.296921   \n",
      "1965   0.030960   0.315599   0.414861   0.409915   0.383901  0.241233   \n",
      "1966   0.068702   0.389886   0.480916   0.377651   0.310433  0.172104   \n",
      "1967   0.078571   0.360630   0.350000   0.229134   0.202381  0.317323   \n",
      "1968   0.206107   0.207510   0.211196   0.178854   0.185751  0.260870   \n",
      "1969   0.222222   0.174741   0.277778   0.214480   0.357143  0.289058   \n",
      "1970   0.036304   0.326968   0.402640   0.351273   0.334983  0.245949   \n",
      "1971   0.178808   0.288591   0.314570   0.151678   0.155629  0.332886   \n",
      "1972   0.100592   0.247619   0.319527   0.348571   0.319527  0.249524   \n",
      "1973   0.017442   0.180848   0.203488   0.513514   0.505814  0.285953   \n",
      "1974   0.187699   0.210084   0.249205   0.320028   0.303287  0.252451   \n",
      "1975   0.214932   0.274236   0.282805   0.204515   0.194570  0.286853   \n",
      "1976   0.046610   0.253627   0.277542   0.294835   0.309322  0.351712   \n",
      "1977   0.016204   0.295711   0.317130   0.284424   0.425926  0.338600   \n",
      "1978   0.083744   0.276680   0.285714   0.229249   0.197044  0.328063   \n",
      "1979   0.125000   0.266344   0.335526   0.179177   0.243421  0.266344   \n",
      "1980   0.046322   0.286160   0.250681   0.352758   0.389646  0.277836   \n",
      "1981   0.073864   0.349355   0.414773   0.381594   0.309659  0.206917   \n",
      "1982   0.000000   0.345740   0.202532   0.364764   0.348101  0.258892   \n",
      "1983   0.009132   0.317578   0.401826   0.271787   0.347032  0.378139   \n",
      "1984   0.031120   0.226768   0.259336   0.254237   0.275934  0.446523   \n",
      "1985   0.049020   0.551570   0.536765   0.293274   0.299020  0.103139   \n",
      "1986   0.053305   0.333841   0.368870   0.263720   0.313433  0.269817   \n",
      "1987   0.025552   0.334358   0.385881   0.366710   0.386748  0.252669   \n",
      "1988   0.036232   0.307879   0.333333   0.326061   0.326087  0.258182   \n",
      "1989   0.072727   0.140625   0.272727   0.294271   0.345455  0.377604   \n",
      "1990   0.051051   0.264525   0.288288   0.349912   0.351351  0.325264   \n",
      "1991   0.102857   0.247978   0.351429   0.221923   0.202857  0.318059   \n",
      "1992   0.100629   0.284163   0.310273   0.339367   0.312369  0.263348   \n",
      "1993   0.050971   0.373074   0.376214   0.313869   0.349515  0.231144   \n",
      "1994   0.173529   0.150828   0.138235   0.185702   0.202941  0.324324   \n",
      "1995   0.249716   0.213574   0.259386   0.220447   0.170648  0.307216   \n",
      "1996   0.063830   0.459283   0.372340   0.214984   0.255319  0.201954   \n",
      "1997   0.040752   0.476601   0.463950   0.206897   0.257053  0.233990   \n",
      "1998   0.067568   0.369441   0.361486   0.258837   0.283784  0.265678   \n",
      "1999   0.054054   0.279853   0.272349   0.350916   0.370062  0.288645   \n",
      "2000   0.028846   0.097826   0.057692   0.391304   0.519231  0.451087   \n",
      "2001   0.093220   0.555140   0.444915   0.119626   0.190678  0.186916   \n",
      "2002   0.000000   0.273810   0.090909   0.083333   0.363636  0.607143   \n",
      "2003   0.000000   0.250000   0.166667   0.166667   0.500000  0.583333   \n",
      "2004   0.166667   0.341121   0.250000   0.172897   0.214286  0.383178   \n",
      "2005   0.022857   0.149038   0.228571   0.302885   0.445714  0.458333   \n",
      "2006   0.353107   0.239325   0.336158   0.098312   0.079096  0.238332   \n",
      "2007   0.052095   0.227875   0.378256   0.282989   0.271801  0.409115   \n",
      "2008   0.000000   0.282857   0.333333   0.282857   0.322581  0.368571   \n",
      "2009   0.012552   0.257259   0.357741   0.399730   0.366109  0.268737   \n",
      "2010   0.208912   0.271161   0.309715   0.223671   0.171658  0.323081   \n",
      "2011   0.054945   0.192771   0.219780   0.240964   0.252747  0.484940   \n",
      "2012   0.030488   0.542991   0.527439   0.234579   0.259146  0.156075   \n",
      "2013   0.125561   0.227191   0.206278   0.359571   0.313901  0.275492   \n",
      "2014   0.156475   0.303502   0.330935   0.261997   0.237410  0.241245   \n",
      "2015   0.277302   0.208285   0.255889   0.237456   0.168094  0.284131   \n",
      "2016   0.061281   0.255567   0.314763   0.327678   0.306407  0.271474   \n",
      "2017   0.399083   0.116445   0.165138   0.128703   0.155963  0.204290   \n",
      "2018   0.040000   0.319075   0.330000   0.346821   0.396667  0.275145   \n",
      "2019   0.026270   0.353169   0.385289   0.279431   0.345009  0.273609   \n",
      "2020   0.088889   0.312043   0.351111   0.244844   0.206667  0.289421   \n",
      "2021   0.065789   0.307317   0.315789   0.273171   0.230263  0.307317   \n",
      "2022   0.128571   0.352941   0.528571   0.159746   0.128571  0.227797   \n",
      "2023   0.063123   0.224835   0.242525   0.276267   0.299003  0.348273   \n",
      "2024   0.064000   0.241863   0.277333   0.214422   0.237333  0.298022   \n",
      "2025   0.126866   0.144330   0.208955   0.171821   0.216418  0.477663   \n",
      "2026   0.003984   0.295808   0.398406   0.279042   0.215139  0.322156   \n",
      "2027   0.220000   0.272283   0.330000   0.171196   0.203333  0.319022   \n",
      "2028   0.166667   0.080645   0.166667   0.204301   0.166667  0.650538   \n",
      "2029   0.103448   0.170732   0.137931   0.317073   0.275862  0.475610   \n",
      "2030   0.128535   0.249733   0.233933   0.318036   0.367609  0.268943   \n",
      "2031   0.084507   0.222892   0.211268   0.463855   0.323944  0.180723   \n",
      "2032   0.103226   0.232906   0.270968   0.170940   0.225806  0.461538   \n",
      "2033   0.080702   0.200952   0.238596   0.330476   0.305263  0.376190   \n",
      "2034   0.051118   0.315389   0.345048   0.373794   0.354633  0.236668   \n",
      "2035   0.062916   0.320008   0.369631   0.329798   0.389595  0.282072   \n",
      "2036   0.067797   0.424357   0.458624   0.302260   0.333001  0.187382   \n",
      "2037   0.081818   0.327957   0.450000   0.280645   0.281818  0.184946   \n",
      "2038   0.201794   0.223436   0.286996   0.213505   0.206278  0.347567   \n",
      "2039   0.133333   0.460993   0.333333   0.184397   0.146667  0.138298   \n",
      "2040   0.047120   0.205628   0.204188   0.196970   0.267016  0.303030   \n",
      "2041   0.203057   0.133374   0.176856   0.284249   0.318777  0.247435   \n",
      "2042   0.094059   0.144681   0.178218   0.423404   0.404290  0.283688   \n",
      "2043   0.000000   0.512273   0.462838   0.389541   0.432432  0.062967   \n",
      "2044   0.126761   0.249351   0.239437   0.192208   0.246479  0.397403   \n",
      "2045   0.092179   0.338727   0.293296   0.277238   0.173184  0.189860   \n",
      "2046   0.016216   0.472222   0.470270   0.333333   0.329730  0.152778   \n",
      "2047   0.021299   0.418935   0.425985   0.310848   0.335463  0.220513   \n",
      "2048   0.175953   0.179160   0.325513   0.208396   0.152493  0.355322   \n",
      "2049   0.066456   0.374280   0.351266   0.205374   0.291139  0.285988   \n",
      "2050   0.034483   0.492308   0.459770   0.133333   0.091954  0.133333   \n",
      "2051   0.033113   0.178794   0.245033   0.320166   0.364238  0.472973   \n",
      "2052   0.088235   0.274374   0.318015   0.216566   0.242647  0.392580   \n",
      "2053   0.017719   0.391705   0.429679   0.438143   0.404208  0.155619   \n",
      "2054   0.048673   0.411079   0.438053   0.291545   0.314159  0.209913   \n",
      "2055   0.074074   0.194495   0.191358   0.288073   0.290123  0.377982   \n",
      "2056   0.152284   0.210121   0.177665   0.194719   0.177665  0.352035   \n",
      "2057   0.000000   0.290168   0.325926   0.424460   0.392593  0.237410   \n",
      "2058   0.091623   0.344969   0.337696   0.240246   0.290576  0.313142   \n",
      "2059   0.189066   0.228234   0.232346   0.235075   0.273349  0.228856   \n",
      "2060   0.098446   0.209824   0.202073   0.307459   0.376511  0.335961   \n",
      "2061   0.135762   0.284842   0.350993   0.248220   0.271523  0.287894   \n",
      "2062   0.050663   0.302222   0.299299   0.387259   0.431800  0.236741   \n",
      "2063   0.079365   0.290520   0.238095   0.324159   0.420635  0.272171   \n",
      "2064   0.027113   0.334850   0.375997   0.377009   0.366029  0.241280   \n",
      "2065   0.334270   0.301695   0.272472   0.112712   0.151685  0.227119   \n",
      "2066   0.031250   0.041667   0.093750   0.458333   0.437500  0.354167   \n",
      "2067   0.145161   0.202830   0.221774   0.254717   0.209677  0.397799   \n",
      "2068   0.020270   0.323264   0.430743   0.534716   0.488176  0.096934   \n",
      "2069   0.083665   0.300601   0.292829   0.334001   0.384462  0.181029   \n",
      "2070   0.044776   0.172093   0.238806   0.409302   0.253731  0.362791   \n",
      "2071   0.024390   0.215206   0.247967   0.332474   0.329268  0.372423   \n",
      "2072   0.122222   0.290837   0.233333   0.151394   0.288889  0.338645   \n",
      "2073   0.105740   0.284191   0.302115   0.232748   0.244713  0.368883   \n",
      "2074   0.296830   0.154706   0.224784   0.095993   0.198847  0.175210   \n",
      "2075   0.000000   0.116797   0.122162   0.251491   0.227027  0.605651   \n",
      "2076   0.064854   0.296782   0.338912   0.345948   0.320781  0.273242   \n",
      "2077   0.188482   0.230303   0.157068   0.444444   0.329843  0.133333   \n",
      "2078   0.031496   0.250000   0.401575   0.306000   0.267717  0.326000   \n",
      "2079   0.020677   0.300446   0.327068   0.380764   0.390977  0.249380   \n",
      "2080   0.114583   0.205575   0.229167   0.236934   0.281250  0.358885   \n",
      "2081   0.092949   0.239486   0.163462   0.276869   0.304487  0.297897   \n",
      "2082   0.129771   0.317716   0.320611   0.130307   0.190840  0.314788   \n",
      "2083   0.017403   0.328951   0.385542   0.485509   0.479250  0.175680   \n",
      "2084   0.023256   0.297985   0.395349   0.499470   0.404651  0.183457   \n",
      "2085   0.071429   0.251586   0.318182   0.300211   0.207792  0.186047   \n",
      "2086   0.020253   0.341171   0.382278   0.482241   0.462025  0.141571   \n",
      "2087   0.101115   0.200965   0.415613   0.341186   0.273606  0.392563   \n",
      "2088   0.029851   0.286988   0.378109   0.399287   0.343284  0.274510   \n",
      "2089   0.077882   0.205212   0.327103   0.355049   0.149533  0.344191   \n",
      "2090   0.082143   0.279690   0.275000   0.374355   0.428571  0.228055   \n",
      "2091   0.042254   0.296894   0.319249   0.315528   0.338028  0.326708   \n",
      "2092   0.034783   0.233062   0.286957   0.466125   0.382609  0.214092   \n",
      "2093   0.075342   0.265550   0.284247   0.113636   0.140411  0.478469   \n",
      "2094   0.014388   0.179775   0.244604   0.292135   0.223022  0.412921   \n",
      "2095   0.084677   0.193182   0.205645   0.211648   0.290323  0.485795   \n",
      "2096   0.076336   0.330492   0.439695   0.327652   0.279389  0.205492   \n",
      "2097   0.095723   0.261224   0.336049   0.206803   0.287169  0.361905   \n",
      "2098   0.022727   0.349206   0.522727   0.222222   0.227273  0.373016   \n",
      "2099   0.168831   0.288428   0.324675   0.271157   0.225108  0.269430   \n",
      "2100   0.010204   0.217036   0.295918   0.470945   0.408163  0.288681   \n",
      "2101   0.070988   0.286645   0.348765   0.234528   0.222222  0.380293   \n",
      "2102   0.207407   0.280566   0.303704   0.184685   0.162963  0.274775   \n",
      "2103   0.030534   0.325758   0.404580   0.265152   0.206107  0.308081   \n",
      "2104   0.009346   0.307692   0.261682   0.281469   0.392523  0.381119   \n",
      "2105   0.136194   0.298141   0.328358   0.221780   0.212687  0.322709   \n",
      "2106   0.000000   0.250000   0.000000   0.166667   0.285714  0.458333   \n",
      "2107   0.041885   0.265973   0.246073   0.251301   0.238220  0.378609   \n",
      "2108   0.042857   0.232767   0.171429   0.534466   0.442857  0.214785   \n",
      "2109   0.037244   0.255682   0.275605   0.290404   0.355680  0.395833   \n",
      "2110   0.000000   0.161107   0.242718   0.522356   0.378641  0.290987   \n",
      "2111   0.020408   0.211738   0.346939   0.367089   0.326531  0.400460   \n",
      "2112   0.189474   0.350318   0.467368   0.106460   0.128421  0.223840   \n",
      "2113   0.000000   0.160000   0.280000   0.213333   0.320000  0.600000   \n",
      "2114   0.124454   0.356996   0.344978   0.172840   0.185590  0.332305   \n",
      "2115   0.063158   0.322191   0.284211   0.351903   0.389474  0.264624   \n",
      "2116   0.041237   0.301003   0.360825   0.214047   0.185567  0.381271   \n",
      "2117   0.014778   0.267943   0.334975   0.296651   0.295567  0.311005   \n",
      "2118   0.022222   0.095238   0.133333   0.435374   0.333333  0.401361   \n",
      "2119   0.101449   0.174274   0.217391   0.224066   0.260870  0.402490   \n",
      "2120   0.051913   0.272304   0.248634   0.334368   0.344262  0.312645   \n",
      "2121   0.000000   0.544304   0.250000   0.075949   0.375000  0.139241   \n",
      "2122   0.000000   0.209877   0.476190   0.395062   0.285714  0.308642   \n",
      "2123   0.059701   0.193694   0.171642   0.204955   0.216418  0.515766   \n",
      "2124   0.053571   0.237624   0.339286   0.257426   0.178571  0.306931   \n",
      "2125   0.061224   0.352113   0.265306   0.126761   0.244898  0.295775   \n",
      "2126   0.200000   0.157895   0.000000   0.105263   0.400000  0.210526   \n",
      "2127   0.087500   0.255556   0.275000   0.211111   0.162500  0.281481   \n",
      "2128   0.000000   0.000000   0.000000   0.160000   0.000000  0.360000   \n",
      "2129   0.200000   0.142857   0.000000   0.371429   0.400000  0.400000   \n",
      "2130   0.095238   0.358491   0.285714   0.226415   0.095238  0.226415   \n",
      "2131   0.027460   0.172993   0.302059   0.421904   0.331808  0.342875   \n",
      "2132   0.000000   0.210526   0.250000   0.263158   0.250000  0.526316   \n",
      "2133   0.000000   0.333333   0.000000   0.000000   0.000000  0.333333   \n",
      "2134   0.041379   0.282895   0.424138   0.232456   0.300000  0.429825   \n",
      "2135   0.074364   0.286003   0.302348   0.295712   0.283757  0.305421   \n",
      "2136   0.021605   0.280450   0.330247   0.272262   0.311728  0.334698   \n",
      "2137   0.046440   0.346154   0.408669   0.373077   0.349845  0.194872   \n",
      "2138   0.017544   0.304487   0.385965   0.366987   0.374269  0.246795   \n",
      "2139   0.037037   0.314410   0.425926   0.318777   0.305556  0.301310   \n",
      "2140   0.025840   0.308887   0.405685   0.377912   0.441860  0.262295   \n",
      "2141   0.137980   0.241215   0.204836   0.186420   0.240398  0.381775   \n",
      "2142   0.031716   0.236728   0.406716   0.315057   0.313433  0.333768   \n",
      "2143   0.021696   0.200307   0.258383   0.279201   0.362919  0.381660   \n",
      "2144   0.039683   0.402959   0.505291   0.323760   0.289683  0.217581   \n",
      "2145   0.022695   0.378938   0.458156   0.279928   0.292199  0.277228   \n",
      "2146   0.046875   0.369381   0.369141   0.369707   0.372070  0.211075   \n",
      "2147   0.036437   0.298795   0.337652   0.366867   0.339271  0.286145   \n",
      "2148   0.029126   0.258303   0.318447   0.259225   0.248544  0.344096   \n",
      "2149   0.042247   0.155394   0.111378   0.195081   0.215074  0.476803   \n",
      "2150   0.081818   0.217986   0.269697   0.335288   0.312121  0.404692   \n",
      "2151   0.038356   0.362963   0.361644   0.193519   0.169863  0.296296   \n",
      "2152   0.108738   0.232868   0.287379   0.307385   0.225243  0.363939   \n",
      "2153   0.008163   0.333333   0.391837   0.300123   0.289796  0.325953   \n",
      "2154   0.073529   0.275939   0.266176   0.384184   0.357353  0.265283   \n",
      "2155   0.061567   0.217494   0.234142   0.330969   0.281716  0.371946   \n",
      "2156   0.037757   0.272606   0.305492   0.279287   0.247140  0.361693   \n",
      "2157   0.016760   0.328025   0.365922   0.311040   0.324022  0.263270   \n",
      "2158   0.040000   0.276557   0.291429   0.428571   0.405714  0.271062   \n",
      "2159   0.043796   0.263425   0.332117   0.365755   0.295620  0.273556   \n",
      "2160   0.093750   0.360825   0.453125   0.298969   0.296875  0.319588   \n",
      "2161   0.070809   0.194191   0.251445   0.258921   0.218208  0.403320   \n",
      "2162   0.014903   0.328821   0.414307   0.280349   0.292101  0.310044   \n",
      "2163   0.026699   0.462658   0.497573   0.360815   0.276699  0.123181   \n",
      "2164   0.081860   0.321075   0.363721   0.314356   0.309767  0.285714   \n",
      "2165   0.077922   0.392100   0.396537   0.270404   0.274459  0.250073   \n",
      "2166   0.043537   0.300306   0.383673   0.418898   0.385034  0.234889   \n",
      "2167   0.041026   0.296276   0.370940   0.383352   0.340171  0.269441   \n",
      "2168   0.007752   0.251675   0.390181   0.361504   0.325581  0.328369   \n",
      "2169   0.030000   0.127572   0.190000   0.242798   0.220000  0.555556   \n",
      "2170   0.040628   0.231426   0.262696   0.234202   0.253463  0.396883   \n",
      "2171   0.028418   0.306321   0.401690   0.401311   0.367896  0.250168   \n",
      "2172   0.041602   0.304153   0.334361   0.322079   0.348228  0.294891   \n",
      "2173   0.018657   0.464839   0.470149   0.404052   0.361940  0.104887   \n",
      "2174   0.131579   0.195335   0.217105   0.276968   0.256579  0.300292   \n",
      "2175   0.012552   0.253576   0.309623   0.383456   0.433054  0.328952   \n",
      "2176   0.069284   0.375694   0.399538   0.254167   0.307159  0.229861   \n",
      "2177   0.041779   0.249040   0.315364   0.410051   0.388140  0.227913   \n",
      "2178   0.055186   0.256956   0.261636   0.214875   0.220745  0.391790   \n",
      "2179   0.119658   0.375315   0.365967   0.218024   0.228438  0.227540   \n",
      "2180   0.047285   0.449503   0.399299   0.221026   0.273205  0.278974   \n",
      "2181   0.028571   0.230131   0.271429   0.252246   0.338776  0.405667   \n",
      "2182   0.065116   0.300885   0.274419   0.362832   0.381395  0.284661   \n",
      "2183   0.014768   0.688004   0.578059   0.199642   0.265823  0.096240   \n",
      "2184   0.062571   0.350171   0.369738   0.284846   0.326507  0.244208   \n",
      "2185   0.077994   0.300186   0.317549   0.272342   0.325905  0.308937   \n",
      "2186   0.108209   0.289773   0.414179   0.181818   0.223881  0.240909   \n",
      "2187   0.086275   0.282784   0.271569   0.242156   0.234314  0.337892   \n",
      "2188   0.029412   0.313845   0.332983   0.306361   0.261555  0.297942   \n",
      "2189   0.249147   0.200000   0.225256   0.215894   0.191126  0.356291   \n",
      "2190   0.021368   0.500686   0.542735   0.297668   0.264957  0.159122   \n",
      "2191   0.217064   0.323559   0.331242   0.148129   0.153074  0.301820   \n",
      "2192   0.108866   0.572841   0.567901   0.152910   0.168350  0.148345   \n",
      "2193   0.100000   0.298390   0.301333   0.275279   0.242667  0.328106   \n",
      "2194   0.039084   0.279079   0.323450   0.362762   0.355795  0.276987   \n",
      "2195   0.177719   0.261881   0.270557   0.226997   0.216180  0.276542   \n",
      "2196   0.081152   0.386927   0.562827   0.140496   0.149215  0.150263   \n",
      "2197   0.083049   0.311471   0.346985   0.293149   0.336746  0.281200   \n",
      "2198   0.030534   0.289033   0.359473   0.324149   0.292158  0.291374   \n",
      "2199   0.029582   0.380861   0.409513   0.346651   0.351508  0.219378   \n",
      "2200   0.000000   0.565476   0.578397   0.244048   0.247387  0.176190   \n",
      "2201   0.040195   0.334462   0.338611   0.262695   0.280146  0.315956   \n",
      "2202   0.080227   0.576527   0.585900   0.169641   0.186386  0.117366   \n",
      "2203   0.104869   0.450429   0.503121   0.222092   0.242197  0.122560   \n",
      "2204   0.026738   0.367681   0.401070   0.288056   0.251337  0.298595   \n",
      "2205   0.015766   0.442792   0.490991   0.241991   0.186937  0.263730   \n",
      "2206   0.004717   0.783664   0.561321   0.088300   0.155660  0.110375   \n",
      "2207   0.006873   0.840412   0.831615   0.061776   0.075601  0.084942   \n",
      "2208   0.020992   0.270691   0.324427   0.360299   0.354962  0.303671   \n",
      "2209   0.049372   0.311943   0.341423   0.282531   0.274477  0.306298   \n",
      "2210   0.032520   0.330439   0.387534   0.359531   0.318428  0.259227   \n",
      "2211   0.011673   0.369400   0.377432   0.331361   0.315175  0.262046   \n",
      "2212   0.107726   0.188982   0.236126   0.237505   0.219804  0.433418   \n",
      "2213   0.048061   0.266154   0.355651   0.354839   0.357640  0.302851   \n",
      "2214   0.061008   0.237060   0.278515   0.328157   0.270557  0.359213   \n",
      "2215   0.149474   0.247151   0.301053   0.294692   0.292105  0.295344   \n",
      "2216   0.109078   0.274809   0.298381   0.311024   0.289233  0.286703   \n",
      "2217   0.040998   0.240253   0.294118   0.316122   0.367201  0.252371   \n",
      "2218   0.117910   0.228906   0.298507   0.334679   0.273134  0.262010   \n",
      "2219   0.046632   0.669091   0.595855   0.241212   0.274611  0.078788   \n",
      "2220   0.059767   0.253654   0.319242   0.338520   0.367347  0.264969   \n",
      "2221   0.067380   0.242907   0.380749   0.354160   0.373262  0.331208   \n",
      "2222   0.053299   0.275328   0.356176   0.322408   0.345178  0.321216   \n",
      "2223   0.035912   0.196019   0.339779   0.398096   0.353591  0.375595   \n",
      "2224   0.069091   0.245199   0.261818   0.257016   0.272727  0.404727   \n",
      "2225   0.039057   0.283229   0.354099   0.344984   0.355713  0.292476   \n",
      "2226   0.390855   0.254734   0.191740   0.184400   0.117994  0.307484   \n",
      "2227   0.062016   0.544276   0.534884   0.282937   0.240310  0.125270   \n",
      "2228   0.089646   0.346263   0.396465   0.230303   0.220960  0.265455   \n",
      "2229   0.291237   0.143952   0.224227   0.209540   0.115979  0.342419   \n",
      "2230   0.022130   0.298602   0.337483   0.354533   0.395574  0.282364   \n",
      "2231   0.025522   0.305112   0.341067   0.511182   0.464037  0.166134   \n",
      "2232   0.058360   0.389706   0.369085   0.338235   0.369085  0.211275   \n",
      "2233   0.025349   0.282333   0.348542   0.365596   0.428390  0.228233   \n",
      "2234   0.041899   0.171875   0.237430   0.358553   0.416201  0.352796   \n",
      "2235   0.100962   0.251282   0.317308   0.273504   0.278846  0.273504   \n",
      "2236   0.143939   0.182051   0.166667   0.341026   0.431818  0.297436   \n",
      "2237   0.042806   0.283866   0.329370   0.308937   0.290725  0.309341   \n",
      "2238   0.081833   0.219565   0.265139   0.234058   0.333879  0.452174   \n",
      "2239   0.054475   0.358824   0.377432   0.263235   0.284047  0.257353   \n",
      "2240   0.028369   0.561375   0.627660   0.241052   0.217730  0.164408   \n",
      "2241   0.033670   0.308171   0.332371   0.339455   0.332371  0.275798   \n",
      "2242   0.051151   0.257220   0.263427   0.270758   0.237852  0.357401   \n",
      "2243   0.034843   0.199156   0.310105   0.217722   0.285714  0.494515   \n",
      "2244   0.000000   0.191429   0.111111   0.428571   0.555556  0.351429   \n",
      "2245   0.404858   0.294038   0.287449   0.039295   0.028340  0.178862   \n",
      "2246   0.211581   0.250984   0.273942   0.198819   0.149220  0.366142   \n",
      "2247   0.060417   0.371951   0.325000   0.086382   0.160417  0.342480   \n",
      "2248   0.159591   0.305496   0.315252   0.160884   0.187107  0.278477   \n",
      "2249   0.074048   0.345474   0.380623   0.272362   0.316955  0.271291   \n",
      "2250   0.054040   0.279387   0.310101   0.290247   0.263636  0.324957   \n",
      "2251   0.219512   0.285637   0.288618   0.284562   0.211382  0.262507   \n",
      "2252   0.161017   0.241838   0.224576   0.125756   0.177966  0.396614   \n",
      "2253   0.028141   0.304923   0.323618   0.282880   0.313568  0.350110   \n",
      "2254   0.060403   0.188202   0.256711   0.314139   0.328859  0.403090   \n",
      "2255   0.061625   0.287072   0.326797   0.214455   0.240896  0.375297   \n",
      "2256   0.017301   0.210813   0.204152   0.303583   0.326990  0.400832   \n",
      "2257   0.052910   0.214308   0.291761   0.252877   0.288738  0.375739   \n",
      "2258   0.091298   0.258096   0.316690   0.208313   0.228245  0.420493   \n",
      "2259   0.062215   0.346278   0.365706   0.276160   0.314112  0.260518   \n",
      "2260   0.038835   0.248731   0.262136   0.297970   0.335922  0.356853   \n",
      "2261   0.029155   0.263941   0.239067   0.233271   0.329446  0.422862   \n",
      "2262   0.070175   0.316602   0.298246   0.274131   0.315789  0.231660   \n",
      "2263   0.065441   0.190440   0.218382   0.373512   0.336029  0.396750   \n",
      "2264   0.039427   0.420389   0.483871   0.226804   0.250896  0.241695   \n",
      "2265   0.058651   0.239954   0.190616   0.292767   0.319648  0.340987   \n",
      "2266   0.073529   0.313830   0.264706   0.186170   0.220588  0.297872   \n",
      "2267   0.026059   0.299903   0.302932   0.211295   0.283388  0.404090   \n",
      "2268   0.032028   0.353612   0.409253   0.195184   0.245552  0.338403   \n",
      "2269   0.020000   0.152104   0.145000   0.310680   0.325000  0.411003   \n",
      "2270   0.044619   0.254967   0.299213   0.287252   0.307087  0.375000   \n",
      "2271   0.058706   0.298969   0.314209   0.279310   0.300867  0.328938   \n",
      "2272   0.147314   0.285166   0.292894   0.230818   0.258232  0.281969   \n",
      "2273   0.072072   0.217086   0.301301   0.244822   0.276276  0.383876   \n",
      "2274   0.040876   0.401013   0.477372   0.332814   0.278832  0.181216   \n",
      "2275   0.073235   0.420279   0.446382   0.276245   0.278989  0.242207   \n",
      "2276   0.049333   0.300610   0.314667   0.380468   0.342667  0.253306   \n",
      "2277   0.068935   0.320362   0.320244   0.295204   0.348168  0.269261   \n",
      "2278   0.063985   0.305556   0.307130   0.337838   0.327239  0.284535   \n",
      "2279   0.097276   0.314642   0.316472   0.271028   0.272374  0.308411   \n",
      "2280   0.137931   0.275000   0.241379   0.170000   0.362069  0.420000   \n",
      "2281   0.040323   0.139665   0.088710   0.122905   0.193548  0.474860   \n",
      "2282   0.061272   0.296710   0.271098   0.345732   0.337572  0.275210   \n",
      "2283   0.058680   0.316577   0.335371   0.339007   0.346781  0.257875   \n",
      "2284   0.019672   0.317762   0.316393   0.339995   0.331967  0.267799   \n",
      "2285   0.041106   0.408930   0.380581   0.296244   0.328845  0.230806   \n",
      "2286   0.034586   0.418473   0.401504   0.332817   0.375940  0.183695   \n",
      "2287   0.061202   0.301048   0.358470   0.306146   0.320219  0.264798   \n",
      "2288   0.170000   0.273081   0.245000   0.194363   0.230000  0.352770   \n",
      "2289   0.023873   0.373317   0.387931   0.340114   0.342838  0.248579   \n",
      "2290   0.025397   0.237933   0.228571   0.354912   0.377778  0.370244   \n",
      "2291   0.091483   0.253536   0.246057   0.206746   0.261830  0.399347   \n",
      "2292   0.058756   0.303294   0.350230   0.334401   0.353687  0.251144   \n",
      "2293   0.071742   0.387656   0.422234   0.273958   0.254107  0.253203   \n",
      "2294   0.089132   0.294664   0.327600   0.336040   0.337764  0.259667   \n",
      "2295   0.064460   0.282797   0.299652   0.287392   0.306620  0.283308   \n",
      "2296   0.052950   0.353721   0.372163   0.299185   0.273828  0.244648   \n",
      "2297   0.027641   0.384649   0.452122   0.360708   0.335143  0.204150   \n",
      "2298   0.042105   0.192691   0.221053   0.475083   0.400000  0.289037   \n",
      "2299   0.261739   0.218196   0.287826   0.146984   0.144348  0.240243   \n",
      "2300   0.206780   0.081040   0.145763   0.165138   0.291525  0.235474   \n",
      "2301   0.025126   0.163429   0.193467   0.381782   0.417085  0.400536   \n",
      "2302   0.157828   0.277687   0.266414   0.240771   0.231061  0.327728   \n",
      "2303   0.143868   0.320630   0.299528   0.304888   0.268868  0.272577   \n",
      "2304   0.269051   0.187732   0.186625   0.143795   0.127527  0.432525   \n",
      "2305   0.120861   0.311379   0.331126   0.325862   0.313466  0.262069   \n",
      "2306   0.157895   0.217661   0.213397   0.375302   0.311005  0.234564   \n",
      "2307   0.043265   0.314305   0.349388   0.346171   0.371429  0.282898   \n",
      "2308   0.118710   0.230884   0.305806   0.305859   0.265806  0.294439   \n",
      "2309   0.035348   0.167047   0.180160   0.358740   0.361460  0.348699   \n",
      "2310   0.037196   0.217338   0.253219   0.321734   0.340486  0.320513   \n",
      "2311   0.035230   0.224803   0.230352   0.358661   0.311653  0.348819   \n",
      "2312   0.051593   0.247580   0.270865   0.286672   0.377086  0.338049   \n",
      "2313   0.173420   0.327403   0.330632   0.274032   0.243517  0.259207   \n",
      "2314   0.219836   0.176383   0.203476   0.178251   0.161554  0.396487   \n",
      "2315   0.139752   0.339153   0.317805   0.259287   0.270186  0.242571   \n",
      "2316   0.127637   0.340939   0.386076   0.288690   0.275316  0.204365   \n",
      "2317   0.046693   0.288600   0.381323   0.362193   0.268482  0.271284   \n",
      "2318   0.015228   0.302551   0.346447   0.369067   0.399746  0.226994   \n",
      "2319   0.029923   0.187361   0.182432   0.265521   0.263514  0.493071   \n",
      "2320   0.069767   0.220333   0.258140   0.290667   0.316279  0.250667   \n",
      "2321   0.197260   0.217636   0.232877   0.167917   0.221918  0.343340   \n",
      "2322   0.148352   0.133053   0.236264   0.226891   0.164835  0.275910   \n",
      "2323   0.129964   0.204099   0.314079   0.208369   0.216606  0.232280   \n",
      "2324   0.084025   0.285906   0.304979   0.208544   0.218880  0.375042   \n",
      "2325   0.113356   0.207636   0.234568   0.272415   0.271605  0.387816   \n",
      "2326   0.062842   0.261057   0.333333   0.330097   0.245902  0.288026   \n",
      "2327   0.210300   0.196229   0.278970   0.148497   0.208155  0.337065   \n",
      "2328   0.053030   0.208501   0.292424   0.319357   0.334848  0.327972   \n",
      "2329   0.057971   0.218493   0.287785   0.304110   0.347826  0.360274   \n",
      "2330   0.027804   0.294492   0.294343   0.304479   0.332694  0.276634   \n",
      "2331   0.029622   0.280011   0.323800   0.323712   0.297242  0.331535   \n",
      "2332   0.064000   0.218935   0.248000   0.289941   0.184000  0.390533   \n",
      "2333   0.070984   0.297815   0.333748   0.283995   0.270237  0.293357   \n",
      "2334   0.028424   0.250684   0.284238   0.275296   0.214470  0.403829   \n",
      "2335   0.023324   0.265832   0.335277   0.392844   0.382896  0.278712   \n",
      "2336   0.051415   0.294049   0.324057   0.263508   0.257547  0.354933   \n",
      "2337   0.034591   0.231693   0.281447   0.232293   0.254717  0.477191   \n",
      "2338   0.068027   0.175563   0.183673   0.351125   0.367347  0.394212   \n",
      "2339   0.057634   0.224618   0.398382   0.316191   0.353893  0.401128   \n",
      "2340   0.027817   0.262185   0.267475   0.345333   0.368046  0.323989   \n",
      "2341   0.094444   0.268182   0.331481   0.293506   0.187037  0.321429   \n",
      "2342   0.028736   0.277611   0.309524   0.318318   0.309524  0.306306   \n",
      "2343   0.051724   0.538488   0.561422   0.193127   0.184267  0.179038   \n",
      "2344   0.125756   0.321891   0.332527   0.261194   0.250302  0.206468   \n",
      "2345   0.156250   0.310843   0.289062   0.202410   0.218750  0.306024   \n",
      "2346   0.062937   0.479482   0.573427   0.125270   0.174825  0.174946   \n",
      "2347   0.154812   0.325668   0.286611   0.227003   0.246862  0.271513   \n",
      "2348   0.046980   0.481395   0.543624   0.148837   0.234899  0.190698   \n",
      "2349   0.232170   0.324503   0.311077   0.150662   0.212443  0.338852   \n",
      "2350   0.089219   0.373585   0.321561   0.206469   0.197026  0.295957   \n",
      "2351   0.143116   0.355496   0.288043   0.171046   0.135870  0.314209   \n",
      "2352   0.091078   0.366314   0.429368   0.238671   0.250929  0.265106   \n",
      "2353   0.060465   0.250441   0.255814   0.195767   0.195349  0.391534   \n",
      "2354   0.141935   0.333333   0.341935   0.228464   0.280645  0.294007   \n",
      "2355   0.184932   0.260928   0.242009   0.234701   0.237443  0.256221   \n",
      "2356   0.023810   0.306003   0.319048   0.306003   0.314286  0.301611   \n",
      "2357   0.037559   0.393407   0.467136   0.235165   0.166667  0.284982   \n",
      "2358   0.144385   0.283505   0.374332   0.175258   0.213904  0.358247   \n",
      "2359   0.025559   0.338820   0.408946   0.329171   0.321086  0.285471   \n",
      "2360   0.059588   0.368906   0.400867   0.203071   0.191766  0.320537   \n",
      "2361   0.057910   0.364391   0.411017   0.213561   0.182203  0.310424   \n",
      "2362   0.017717   0.528775   0.505906   0.223362   0.253937  0.141311   \n",
      "2363   0.256944   0.149171   0.222222   0.256906   0.229167  0.309392   \n",
      "2364   0.329218   0.127436   0.152263   0.215892   0.238683  0.295352   \n",
      "2365   0.271071   0.313140   0.330296   0.228669   0.125285  0.230375   \n",
      "2366   0.117284   0.227273   0.234568   0.263636   0.271605  0.320000   \n",
      "2367   0.079545   0.255144   0.204545   0.218107   0.227273  0.423868   \n",
      "2368   0.210000   0.382789   0.240000   0.127596   0.320000  0.308605   \n",
      "2369   0.082143   0.450623   0.400000   0.190796   0.267857  0.240652   \n",
      "2370   0.017663   0.215691   0.302989   0.395873   0.369565  0.354846   \n",
      "2371   0.050781   0.348800   0.351562   0.268800   0.265625  0.249600   \n",
      "2372   0.262911   0.394316   0.460094   0.119005   0.117371  0.218472   \n",
      "2373   0.108491   0.332268   0.400943   0.293930   0.259434  0.210863   \n",
      "2374   0.074286   0.215494   0.254286   0.309884   0.217143  0.393589   \n",
      "2375   0.173554   0.299045   0.292011   0.224207   0.237833  0.316600   \n",
      "2376   0.078153   0.300043   0.303730   0.305664   0.277087  0.290532   \n",
      "2377   0.030588   0.332416   0.407059   0.325539   0.350588  0.303989   \n",
      "2378   0.035928   0.155983   0.308383   0.428063   0.368263  0.384972   \n",
      "2379   0.054130   0.509403   0.479701   0.184663   0.196920  0.222763   \n",
      "2380   0.040886   0.425427   0.454855   0.268575   0.240204  0.250413   \n",
      "2381   0.099499   0.409691   0.435934   0.163109   0.169649  0.317102   \n",
      "2382   0.090143   0.715153   0.609099   0.087781   0.128054  0.097394   \n",
      "2383   0.069016   0.289950   0.303965   0.225628   0.221733  0.336683   \n",
      "2384   0.122449   0.247148   0.285714   0.152091   0.208163  0.486692   \n",
      "2385   0.018182   0.405093   0.281818   0.152778   0.254545  0.300926   \n",
      "2386   0.075706   0.325178   0.316384   0.235134   0.271186  0.303092   \n",
      "2387   0.106831   0.379726   0.418079   0.210981   0.213148  0.270113   \n",
      "2388   0.124771   0.240637   0.266055   0.166534   0.165138  0.396016   \n",
      "2389   0.081633   0.403509   0.396501   0.222222   0.180758  0.259649   \n",
      "2390   0.151899   0.252291   0.245931   0.268693   0.235081  0.325133   \n",
      "2391   0.124771   0.270469   0.258716   0.231508   0.308257  0.293055   \n",
      "2392   0.049296   0.309377   0.352113   0.242300   0.237089  0.318960   \n",
      "2393   0.008753   0.224123   0.256018   0.361848   0.437637  0.350299   \n",
      "2394   0.037086   0.221067   0.328477   0.302599   0.340397  0.381669   \n",
      "2395   0.005970   0.312534   0.420896   0.383540   0.334328  0.264658   \n",
      "2396   0.030457   0.261978   0.258883   0.353941   0.314721  0.342349   \n",
      "2397   0.009615   0.234859   0.221154   0.378178   0.432692  0.361997   \n",
      "2398   0.035971   0.149573   0.100719   0.352869   0.438849  0.485958   \n",
      "2399   0.020921   0.335622   0.368201   0.344206   0.380753  0.301288   \n",
      "2400   0.074627   0.359583   0.377399   0.349160   0.251599  0.231616   \n",
      "2401   0.024096   0.140426   0.144578   0.276596   0.445783  0.408511   \n",
      "2402   0.016807   0.269697   0.210084   0.190909   0.361345  0.496970   \n",
      "2403   0.120448   0.342612   0.347339   0.230193   0.252101  0.258030   \n",
      "2404   0.049336   0.217549   0.333966   0.292316   0.277040  0.334891   \n",
      "2405   0.079545   0.270127   0.261364   0.235169   0.314394  0.359110   \n",
      "2406   0.099099   0.329545   0.405405   0.359091   0.288288  0.227273   \n",
      "2407   0.044529   0.251071   0.278626   0.290917   0.319338  0.387746   \n",
      "2408   0.039062   0.256501   0.277344   0.300236   0.250000  0.358156   \n",
      "2409   0.032787   0.244792   0.245902   0.305556   0.256831  0.338542   \n",
      "2410   0.038813   0.275940   0.331050   0.366917   0.390411  0.284962   \n",
      "2411   0.018182   0.331061   0.335065   0.365909   0.387013  0.225000   \n",
      "2412   0.036775   0.336031   0.398868   0.418112   0.349364  0.200771   \n",
      "2413   0.036036   0.336678   0.396396   0.403567   0.363363  0.232999   \n",
      "2414   0.038339   0.314582   0.293930   0.399704   0.431310  0.247224   \n",
      "2415   0.098065   0.195064   0.357419   0.224490   0.242581  0.356431   \n",
      "2416   0.037162   0.214149   0.304054   0.314054   0.361486  0.407266   \n",
      "2417   0.032000   0.235233   0.240000   0.376166   0.512000  0.370984   \n",
      "2418   0.008929   0.218947   0.232143   0.317895   0.250000  0.381053   \n",
      "2419   0.040665   0.394595   0.426063   0.222258   0.229205  0.292210   \n",
      "2420   0.108911   0.208661   0.188119   0.265748   0.262376  0.291339   \n",
      "2421   0.058455   0.350634   0.346555   0.219674   0.210856  0.287870   \n",
      "2422   0.012632   0.352716   0.362105   0.266259   0.282105  0.302219   \n",
      "2423   0.085106   0.252648   0.271277   0.169440   0.223404  0.490166   \n",
      "2424   0.061321   0.202037   0.226415   0.151104   0.183962  0.482173   \n",
      "2425   0.020408   0.423197   0.443149   0.252038   0.265306  0.272727   \n",
      "2426   0.082927   0.302752   0.319512   0.227523   0.219512  0.277064   \n",
      "2427   0.085714   0.334073   0.303571   0.205327   0.225000  0.288568   \n",
      "2428   0.061162   0.293515   0.281346   0.213879   0.238532  0.391354   \n",
      "2429   0.060074   0.469829   0.543438   0.185798   0.160813  0.179063   \n",
      "2430   0.068750   0.345455   0.193750   0.131818   0.168750  0.468182   \n",
      "2431   0.120548   0.319885   0.320548   0.259846   0.261644  0.260807   \n",
      "2432   0.055394   0.156102   0.311953   0.301260   0.307580  0.481107   \n",
      "2433   0.072826   0.232398   0.207609   0.235159   0.229348  0.398067   \n",
      "2434   0.042553   0.313725   0.308511   0.360784   0.308511  0.168627   \n",
      "2435   0.175900   0.182169   0.217452   0.257044   0.207756  0.328445   \n",
      "2436   0.119367   0.233741   0.309379   0.236052   0.295981  0.327171   \n",
      "2437   0.052743   0.277624   0.318143   0.333565   0.333755  0.325930   \n",
      "2438   0.220930   0.210872   0.194352   0.235239   0.207641  0.383786   \n",
      "2439   0.104991   0.193788   0.212565   0.272402   0.245267  0.387301   \n",
      "2440   0.100000   0.255230   0.294118   0.407950   0.305882  0.269874   \n",
      "2441   0.020360   0.325342   0.354598   0.357021   0.365796  0.249905   \n",
      "2442   0.142094   0.250941   0.267094   0.283296   0.280983  0.316780   \n",
      "2443   0.078750   0.262394   0.313750   0.228843   0.240000  0.394592   \n",
      "2444   0.246046   0.229517   0.191564   0.204015   0.216169  0.254476   \n",
      "2445   0.187166   0.214559   0.192513   0.310345   0.256684  0.306513   \n",
      "2446   0.073345   0.279882   0.350626   0.295266   0.300537  0.334911   \n",
      "2447   0.011013   0.387500   0.420705   0.383929   0.389868  0.208929   \n",
      "2448   0.117417   0.280000   0.295499   0.259355   0.285714  0.319355   \n",
      "2449   0.175585   0.248540   0.290970   0.192083   0.133779  0.368592   \n",
      "2450   0.102981   0.375919   0.352304   0.255515   0.246612  0.217831   \n",
      "2451   0.184379   0.259925   0.311140   0.154200   0.185659  0.306310   \n",
      "2452   0.118712   0.326103   0.245473   0.195951   0.221328  0.311641   \n",
      "2453   0.070015   0.183912   0.312024   0.342902   0.220700  0.362461   \n",
      "2454   0.039334   0.320545   0.358548   0.350292   0.330812  0.256047   \n",
      "2455   0.009276   0.259478   0.337662   0.427376   0.356215  0.257509   \n",
      "2456   0.022436   0.590517   0.612179   0.150862   0.131410  0.210129   \n",
      "2457   0.024149   0.268272   0.317234   0.298268   0.316136  0.346008   \n",
      "2458   0.113402   0.282353   0.360825   0.274510   0.257732  0.301961   \n",
      "2459   0.133981   0.193485   0.277670   0.306189   0.283495  0.351140   \n",
      "2460   0.033537   0.317669   0.335366   0.319549   0.286585  0.307331   \n",
      "2461   0.065844   0.461538   0.460905   0.178994   0.176955  0.281065   \n",
      "2462   0.045086   0.423048   0.403066   0.203184   0.213706  0.311600   \n",
      "2463   0.017182   0.583643   0.477663   0.174721   0.268041  0.216853   \n",
      "2464   0.088235   0.269542   0.286765   0.194070   0.227941  0.380054   \n",
      "2465   0.040512   0.282963   0.379531   0.242963   0.319829  0.367407   \n",
      "2466   0.053333   0.196721   0.386667   0.426230   0.306667  0.292740   \n",
      "2467   0.029703   0.283154   0.247525   0.132616   0.158416  0.480287   \n",
      "2468   0.020803   0.373868   0.398852   0.318326   0.375179  0.253976   \n",
      "2469   0.017167   0.407942   0.433476   0.356498   0.369099  0.183213   \n",
      "2470   0.151653   0.187005   0.272520   0.281332   0.263398  0.407322   \n",
      "2471   0.017808   0.285057   0.278082   0.434483   0.446575  0.202874   \n",
      "2472   0.052239   0.228571   0.261194   0.257143   0.216418  0.421429   \n",
      "2473   0.036402   0.407649   0.437051   0.335995   0.332483  0.192793   \n",
      "2474   0.055485   0.371483   0.432535   0.318073   0.305170  0.215069   \n",
      "2475   0.093502   0.253854   0.369255   0.348266   0.272583  0.229287   \n",
      "2476   0.109202   0.225118   0.258896   0.272512   0.198773  0.324645   \n",
      "2477   0.042453   0.188119   0.221698   0.178218   0.174528  0.445545   \n",
      "2478   0.134796   0.178125   0.266458   0.286458   0.288401  0.401042   \n",
      "2479   0.053640   0.185880   0.309068   0.352214   0.268199  0.334264   \n",
      "2480   0.011725   0.379860   0.371859   0.340479   0.318258  0.239781   \n",
      "2481   0.028269   0.313019   0.296820   0.314866   0.337456  0.273315   \n",
      "2482   0.019231   0.357012   0.365385   0.310472   0.312500  0.267606   \n",
      "2483   0.025540   0.449956   0.473477   0.371125   0.373281  0.131089   \n",
      "2484   0.054830   0.443255   0.469974   0.331906   0.305483  0.145610   \n",
      "2485   0.036364   0.428755   0.436364   0.331194   0.333333  0.173299   \n",
      "2486   0.063087   0.204232   0.297987   0.367372   0.347651  0.356639   \n",
      "2487   0.018868   0.500000   0.490566   0.279683   0.347170  0.135884   \n",
      "2488   0.021858   0.401590   0.393443   0.284294   0.322404  0.250497   \n",
      "2489   0.036145   0.404040   0.277108   0.308081   0.277108  0.222222   \n",
      "2490   0.016722   0.512195   0.571906   0.318357   0.264214  0.129653   \n",
      "2491   0.026810   0.306167   0.339589   0.280923   0.301162  0.331771   \n",
      "2492   0.129338   0.345332   0.435331   0.231721   0.205047  0.277840   \n",
      "2493   0.103297   0.294366   0.336264   0.283803   0.281319  0.269014   \n",
      "2494   0.032946   0.266467   0.333333   0.265269   0.296512  0.313174   \n",
      "2495   0.086275   0.309537   0.375686   0.308110   0.279216  0.284123   \n",
      "2496   0.033333   0.335475   0.321569   0.361171   0.378431  0.244825   \n",
      "2497   0.143840   0.372518   0.492315   0.248947   0.215187  0.252918   \n",
      "2498   0.000000   0.375000   0.285714   0.308594   0.259740  0.226562   \n",
      "2499   0.088235   0.182432   0.205882   0.280405   0.375000  0.407095   \n",
      "2500   0.068862   0.204844   0.302395   0.245675   0.227545  0.421453   \n",
      "2501   0.042511   0.499811   0.444081   0.179864   0.242642  0.237557   \n",
      "2502   0.393913   0.225857   0.217391   0.089564   0.067826  0.297118   \n",
      "2503   0.024490   0.243688   0.259184   0.362239   0.348980  0.319429   \n",
      "2504   0.061798   0.215762   0.286517   0.251938   0.252809  0.374677   \n",
      "2505   0.069606   0.260057   0.336427   0.323513   0.343387  0.312181   \n",
      "2506   0.035714   0.162791   0.178571   0.267442   0.267857  0.395349   \n",
      "2507   0.044397   0.170717   0.224101   0.331106   0.325581  0.385176   \n",
      "2508   0.019608   0.203325   0.215686   0.260870   0.254902  0.390026   \n",
      "2509   0.019178   0.174718   0.156164   0.254428   0.317808  0.373591   \n",
      "2510   0.024390   0.263682   0.325203   0.278607   0.268293  0.417910   \n",
      "2511   0.101538   0.266022   0.292308   0.151149   0.163077  0.464329   \n",
      "2512   0.022923   0.154110   0.289398   0.302226   0.283668  0.404110   \n",
      "2513   0.113636   0.316315   0.371212   0.230855   0.208333  0.324084   \n",
      "2514   0.085433   0.296125   0.349398   0.172932   0.220153  0.436090   \n",
      "2515   0.070894   0.319404   0.404893   0.237292   0.262107  0.332600   \n",
      "2516   0.055556   0.263572   0.293981   0.248623   0.252315  0.354052   \n",
      "2517   0.020188   0.285903   0.374159   0.323348   0.351279  0.322907   \n",
      "2518   0.014085   0.342324   0.274648   0.286307   0.288732  0.226141   \n",
      "2519   0.054795   0.151961   0.232877   0.210784   0.178082  0.436275   \n",
      "2520   0.038462   0.206897   0.230769   0.255172   0.333333  0.441379   \n",
      "2521   0.027778   0.201690   0.314815   0.311510   0.282407  0.418163   \n",
      "2522   0.046875   0.302706   0.306641   0.292637   0.312500  0.329138   \n",
      "2523   0.060086   0.205882   0.218884   0.399733   0.364807  0.308824   \n",
      "2524   0.124803   0.222727   0.282780   0.184659   0.164297  0.361932   \n",
      "2525   0.052632   0.255030   0.308271   0.294769   0.318797  0.300805   \n",
      "2526   0.015355   0.223690   0.339731   0.371028   0.333973  0.373091   \n",
      "2527   0.050459   0.178049   0.211009   0.346341   0.302752  0.423171   \n",
      "2528   0.078947   0.142857   0.254386   0.245473   0.219298  0.430584   \n",
      "2529   0.050388   0.265527   0.329457   0.278128   0.290698  0.343834   \n",
      "2530   0.039841   0.230904   0.366534   0.444249   0.306773  0.233538   \n",
      "2531   0.000000   0.302491   0.289308   0.259786   0.314465  0.357651   \n",
      "2532   0.022642   0.176998   0.249057   0.347471   0.415094  0.371126   \n",
      "2533   0.012658   0.204225   0.198312   0.304577   0.451477  0.426937   \n",
      "2534   0.017857   0.240181   0.278571   0.380161   0.337500  0.280967   \n",
      "2535   0.146789   0.222595   0.302752   0.319911   0.226300  0.281879   \n",
      "2536   0.038922   0.166829   0.128743   0.267317   0.254491  0.449756   \n",
      "2537   0.051230   0.219737   0.170082   0.163158   0.159836  0.434211   \n",
      "2538   0.021305   0.158037   0.195739   0.354653   0.358189  0.382403   \n",
      "2539   0.028571   0.127098   0.209524   0.407674   0.304762  0.374101   \n",
      "2540   0.000000   0.092486   0.193548   0.231214   0.193548  0.531792   \n",
      "2541   0.019737   0.262357   0.309211   0.325095   0.296053  0.399240   \n",
      "2542   0.052958   0.298647   0.313931   0.277293   0.277195  0.339850   \n",
      "2543   0.060041   0.338944   0.417184   0.297737   0.296066  0.255949   \n",
      "2544   0.044444   0.201835   0.133333   0.330275   0.288889  0.376147   \n",
      "2545   0.165094   0.192029   0.297170   0.168478   0.174528  0.349638   \n",
      "2546   0.048930   0.289868   0.342508   0.349780   0.253823  0.262555   \n",
      "2547   0.032423   0.266577   0.266212   0.278634   0.226962  0.334896   \n",
      "2548   0.042328   0.234012   0.195767   0.346657   0.375661  0.339390   \n",
      "2549   0.050336   0.212418   0.218121   0.214052   0.255034  0.423203   \n",
      "2550   0.047619   0.282651   0.246032   0.401559   0.333333  0.267057   \n",
      "2551   0.018519   0.223022   0.407407   0.388489   0.166667  0.280576   \n",
      "2552   0.069620   0.233129   0.259494   0.300613   0.303797  0.417178   \n",
      "2553   0.030905   0.286526   0.364238   0.376623   0.304636  0.293019   \n",
      "2554   0.010714   0.258065   0.407143   0.420995   0.371429  0.287042   \n",
      "2555   0.050633   0.178846   0.208861   0.373077   0.310127  0.363462   \n",
      "2556   0.074074   0.245399   0.203704   0.335378   0.222222  0.398773   \n",
      "2557   0.056671   0.230867   0.312869   0.357143   0.306966  0.298895   \n",
      "2558   0.019157   0.335753   0.398467   0.299456   0.360153  0.283122   \n",
      "2559   0.028112   0.267484   0.345382   0.263879   0.230924  0.402307   \n",
      "2560   0.044776   0.277873   0.447761   0.332762   0.208955  0.320755   \n",
      "2561   0.072222   0.253049   0.288889   0.295732   0.266667  0.376524   \n",
      "2562   0.026882   0.232857   0.274194   0.272857   0.295699  0.385714   \n",
      "2563   0.031250   0.188948   0.253906   0.353387   0.355469  0.418895   \n",
      "2564   0.029661   0.208092   0.305085   0.310212   0.258475  0.431599   \n",
      "2565   0.028497   0.187559   0.287565   0.335533   0.326425  0.391140   \n",
      "2566   0.036352   0.361811   0.434997   0.342096   0.385705  0.228551   \n",
      "2567   0.065359   0.168760   0.215686   0.296703   0.261438  0.490581   \n",
      "2568   0.041237   0.276190   0.195876   0.290476   0.257732  0.285714   \n",
      "2569   0.021127   0.229327   0.253521   0.340684   0.387324  0.382580   \n",
      "2570   0.109023   0.192256   0.180451   0.184246   0.154135  0.472630   \n",
      "2571   0.062016   0.173664   0.162791   0.293893   0.306202  0.349237   \n",
      "2572   0.077922   0.138177   0.259740   0.388889   0.311688  0.336182   \n",
      "2573   0.109264   0.266193   0.342043   0.256433   0.161520  0.341615   \n",
      "2574   0.155756   0.364212   0.349887   0.209818   0.119639  0.324624   \n",
      "2575   0.115894   0.273543   0.400662   0.275785   0.175497  0.320628   \n",
      "2576   0.128492   0.119048   0.139665   0.216117   0.131285  0.454212   \n",
      "2577   0.027397   0.194638   0.243836   0.366756   0.443836  0.389276   \n",
      "2578   0.058091   0.213320   0.269710   0.394788   0.336100  0.344595   \n",
      "2579   0.016807   0.317439   0.294118   0.348774   0.327731  0.258856   \n",
      "2580   0.026549   0.269802   0.225664   0.344059   0.371681  0.279703   \n",
      "2581   0.036458   0.169654   0.223958   0.292712   0.302083  0.451613   \n",
      "2582   0.038384   0.207306   0.294949   0.349472   0.305051  0.341989   \n",
      "2583   0.019190   0.230471   0.266525   0.407756   0.409382  0.319668   \n",
      "2584   0.021505   0.330882   0.333333   0.247549   0.279570  0.323529   \n",
      "2585   0.020236   0.246114   0.273187   0.318653   0.254637  0.335924   \n",
      "2586   0.069767   0.234043   0.267442   0.221631   0.308140  0.471631   \n",
      "2587   0.039295   0.216235   0.313008   0.313990   0.280488  0.412781   \n",
      "2588   0.054054   0.221910   0.236486   0.160112   0.195946  0.464888   \n",
      "2589   0.043084   0.277975   0.281179   0.327636   0.333333  0.304418   \n",
      "2590   0.085714   0.201613   0.180952   0.185484   0.215873  0.468894   \n",
      "2591   0.044702   0.207727   0.246689   0.268941   0.273179  0.377321   \n",
      "2592   0.189802   0.191609   0.220255   0.243213   0.291785  0.299978   \n",
      "2593   0.053030   0.330594   0.323232   0.272146   0.280303  0.287671   \n",
      "2594   0.019417   0.152975   0.233010   0.334278   0.281553  0.453258   \n",
      "2595   0.064745   0.687187   0.611531   0.174374   0.190454  0.085898   \n",
      "2596   0.233096   0.206177   0.282918   0.170074   0.224199  0.290126   \n",
      "2597   0.142687   0.308559   0.373365   0.252252   0.253270  0.221847   \n",
      "2598   0.219436   0.218227   0.272727   0.183110   0.100313  0.419732   \n",
      "2599   0.200000   0.247751   0.301961   0.292723   0.231373  0.224857   \n",
      "2600   0.238628   0.224064   0.260254   0.253454   0.215511  0.291384   \n",
      "2601   0.158000   0.286244   0.324000   0.296976   0.267333  0.259902   \n",
      "2602   0.351159   0.213529   0.254614   0.152078   0.141505  0.303015   \n",
      "2603   0.031637   0.209165   0.220083   0.346268   0.381018  0.349593   \n",
      "2604   0.059459   0.218007   0.336937   0.320841   0.295495  0.320841   \n",
      "2605   0.200000   0.194667   0.311111   0.332000   0.177778  0.375333   \n",
      "2606   0.063628   0.321222   0.355176   0.303881   0.308642  0.309249   \n",
      "2607   0.032370   0.404696   0.423121   0.255525   0.261272  0.233886   \n",
      "2608   0.285521   0.340274   0.351827   0.246569   0.204330  0.155230   \n",
      "2609   0.092697   0.293872   0.330758   0.298056   0.269663  0.259168   \n",
      "2610   0.055179   0.156146   0.218780   0.308140   0.262343  0.363787   \n",
      "2611   0.069705   0.287938   0.323056   0.397752   0.371314  0.236489   \n",
      "2612   0.118644   0.327869   0.330508   0.340164   0.254237  0.172131   \n",
      "2613   0.306452   0.224254   0.220430   0.230957   0.184588  0.269348   \n",
      "2614   0.272358   0.230832   0.258130   0.184339   0.217480  0.278140   \n",
      "2615   0.215760   0.195727   0.240150   0.236721   0.219512  0.342956   \n",
      "2616   0.329562   0.295455   0.275813   0.185144   0.148515  0.176275   \n",
      "2617   0.211340   0.301861   0.338918   0.239673   0.224227  0.216977   \n",
      "2618   0.032787   0.169903   0.229508   0.250000   0.311475  0.453883   \n",
      "2619   0.085570   0.301133   0.296980   0.318426   0.239933  0.325581   \n",
      "2620   0.097902   0.325359   0.307692   0.145933   0.048951  0.375598   \n",
      "2621   0.006803   0.257143   0.224490   0.157143   0.244898  0.426786   \n",
      "2622   0.087269   0.354953   0.313142   0.272323   0.247433  0.260329   \n",
      "2623   0.020270   0.430328   0.418919   0.194672   0.175676  0.305328   \n",
      "2624   0.110016   0.274087   0.295567   0.165769   0.157635  0.396768   \n",
      "2625   0.183168   0.258418   0.316832   0.134680   0.111386  0.330808   \n",
      "2626   0.059448   0.250755   0.233546   0.185045   0.218684  0.456193   \n",
      "2627   0.049815   0.269637   0.252768   0.223565   0.271218  0.363293   \n",
      "2628   0.044185   0.193958   0.223522   0.281571   0.311241  0.427492   \n",
      "2629   0.157576   0.197926   0.257576   0.286522   0.248485  0.328935   \n",
      "2630   0.085919   0.278434   0.310263   0.295421   0.284010  0.302806   \n",
      "2631   0.107914   0.278586   0.316547   0.214137   0.215827  0.261954   \n",
      "2632   0.053801   0.241872   0.305263   0.367962   0.319298  0.316151   \n",
      "2633   0.230769   0.194667   0.196581   0.301333   0.393162  0.216000   \n",
      "2634   0.122857   0.288601   0.304286   0.118653   0.165714  0.362694   \n",
      "2635   0.178378   0.267978   0.302703   0.222524   0.235135  0.394166   \n",
      "2636   0.018349   0.421255   0.422018   0.323944   0.310398  0.190781   \n",
      "2637   0.015385   0.175331   0.128205   0.254842   0.358974  0.355759   \n",
      "2638   0.220126   0.169713   0.163522   0.287206   0.207547  0.378590   \n",
      "2639   0.138211   0.206989   0.146341   0.182796   0.227642  0.422043   \n",
      "2640   0.023179   0.151292   0.145695   0.234932   0.377483  0.396064   \n",
      "2641   0.045520   0.390922   0.401012   0.295736   0.322254  0.231362   \n",
      "2642   0.001431   0.313008   0.311874   0.349593   0.339056  0.289126   \n",
      "2643   0.043478   0.318302   0.315789   0.371353   0.391304  0.248453   \n",
      "2644   0.033898   0.234091   0.310734   0.290909   0.220339  0.315909   \n",
      "2645   0.018868   0.522959   0.427673   0.321429   0.402516  0.127551   \n",
      "2646   0.039773   0.398619   0.440341   0.373598   0.360795  0.150992   \n",
      "2647   0.028736   0.185185   0.120690   0.374860   0.339080  0.373737   \n",
      "2648   0.080595   0.225833   0.255425   0.274167   0.267824  0.326250   \n",
      "2649   0.018443   0.161103   0.182377   0.331398   0.346311  0.452346   \n",
      "2650   0.044055   0.328321   0.383479   0.363933   0.373467  0.250569   \n",
      "2651   0.215643   0.257175   0.280702   0.223927   0.198099  0.306621   \n",
      "2652   0.073654   0.248623   0.276204   0.268530   0.211048  0.389242   \n",
      "2653   0.076512   0.232962   0.284698   0.242762   0.213523  0.424944   \n",
      "2654   0.050239   0.223193   0.236842   0.294678   0.258373  0.341541   \n",
      "2655   0.134483   0.289969   0.258621   0.257053   0.251724  0.285266   \n",
      "2656   0.035088   0.190948   0.204678   0.468175   0.368421  0.315417   \n",
      "2657   0.011070   0.334893   0.448954   0.342690   0.295203  0.273294   \n",
      "2658   0.056410   0.243891   0.338462   0.328262   0.287179  0.385431   \n",
      "2659   0.010381   0.301587   0.245675   0.392290   0.484429  0.264172   \n",
      "2660   0.005348   0.301667   0.294118   0.358333   0.385027  0.161667   \n",
      "2661   0.030769   0.143678   0.153846   0.482759   0.338462  0.298851   \n",
      "2662   0.010130   0.245906   0.296671   0.395322   0.392185  0.310234   \n",
      "2663   0.027314   0.296252   0.317906   0.411694   0.376328  0.229985   \n",
      "2664   0.039510   0.255631   0.294278   0.313063   0.333787  0.367117   \n",
      "2665   0.037936   0.174854   0.236722   0.318612   0.297420  0.408292   \n",
      "2666   0.033860   0.213242   0.225734   0.347377   0.297968  0.368014   \n",
      "2667   0.091659   0.223910   0.269478   0.301777   0.263978  0.328918   \n",
      "2668   0.074419   0.198639   0.220930   0.329705   0.309302  0.410431   \n",
      "2669   0.056620   0.435212   0.460801   0.211705   0.227352  0.267341   \n",
      "2670   0.035826   0.294496   0.378505   0.371780   0.359813  0.256440   \n",
      "2671   0.109354   0.526429   0.509881   0.152987   0.148880  0.167168   \n",
      "2672   0.106540   0.262778   0.343354   0.196858   0.210970  0.365180   \n",
      "2673   0.070896   0.333549   0.302239   0.209438   0.218284  0.342599   \n",
      "2674   0.061834   0.273859   0.277186   0.229046   0.257996  0.331120   \n",
      "2675   0.037549   0.289387   0.343874   0.313335   0.317194  0.323418   \n",
      "2676   0.196608   0.383844   0.341282   0.212647   0.221516  0.236746   \n",
      "2677   0.073955   0.243304   0.299035   0.197545   0.196141  0.430804   \n",
      "2678   0.349254   0.211116   0.247761   0.159136   0.176119  0.267893   \n",
      "2679   0.029601   0.244387   0.365508   0.313903   0.314028  0.354491   \n",
      "2680   0.050296   0.362579   0.360947   0.316068   0.357988  0.233615   \n",
      "2681   0.024540   0.215753   0.202454   0.273973   0.331288  0.407534   \n",
      "2682   0.000000   0.213592   0.305085   0.393204   0.237288  0.281553   \n",
      "2683   0.071865   0.277752   0.310398   0.232234   0.189602  0.407339   \n",
      "2684   0.091413   0.200850   0.246537   0.218916   0.174515  0.407014   \n",
      "2685   0.035714   0.148760   0.178571   0.351240   0.357143  0.392562   \n",
      "2686   0.039437   0.212474   0.307042   0.313936   0.264789  0.424351   \n",
      "2687   0.209177   0.270950   0.248313   0.232309   0.233468  0.304935   \n",
      "2688   0.040921   0.345141   0.457801   0.185286   0.145780  0.379655   \n",
      "2689   0.039216   0.373653   0.349020   0.216766   0.274510  0.330539   \n",
      "2690   0.024390   0.272454   0.311334   0.422980   0.439024  0.227797   \n",
      "2691   0.043676   0.303745   0.363057   0.261575   0.234759  0.350929   \n",
      "2692   0.015571   0.364382   0.386678   0.339192   0.358131  0.231400   \n",
      "2693   0.041237   0.157729   0.144330   0.257098   0.252577  0.460568   \n",
      "2694   0.121864   0.323714   0.222222   0.207026   0.236559  0.314931   \n",
      "2695   0.138889   0.192661   0.222222   0.201835   0.138889  0.330275   \n",
      "2696   0.059685   0.298457   0.341216   0.302817   0.307432  0.320926   \n",
      "2697   0.036810   0.353846   0.282209   0.146154   0.147239  0.438462   \n",
      "2698   0.064611   0.304581   0.346549   0.281189   0.246696  0.274854   \n",
      "2699   0.002331   0.174702   0.261072   0.350441   0.377622  0.388284   \n",
      "2700   0.012920   0.353517   0.467700   0.283792   0.279070  0.279511   \n",
      "2701   0.021912   0.141466   0.249004   0.458190   0.426295  0.337915   \n",
      "2702   0.073770   0.338755   0.280738   0.198727   0.237705  0.333805   \n",
      "2703   0.079447   0.401010   0.379965   0.215367   0.243523  0.270331   \n",
      "2704   0.062606   0.283484   0.302876   0.280463   0.274112  0.350957   \n",
      "2705   0.021615   0.243361   0.349261   0.328827   0.346985  0.377837   \n",
      "2706   0.028409   0.364377   0.410985   0.349825   0.357955  0.250873   \n",
      "2707   0.015773   0.343365   0.353312   0.285910   0.277603  0.299590   \n",
      "2708   0.048426   0.250558   0.300242   0.335316   0.295400  0.258736   \n",
      "2709   0.057143   0.261062   0.271429   0.225664   0.257143  0.446903   \n",
      "2710   0.054054   0.205966   0.243243   0.281250   0.194595  0.369318   \n",
      "2711   0.022901   0.239897   0.282443   0.337919   0.374046  0.283749   \n",
      "2712   0.018182   0.339547   0.393939   0.205060   0.187879  0.332889   \n",
      "2713   0.067073   0.274085   0.207317   0.261389   0.265244  0.273338   \n",
      "2714   0.003106   0.175402   0.273292   0.380154   0.369565  0.387142   \n",
      "2715   0.065282   0.278837   0.284866   0.237965   0.284866  0.387829   \n",
      "2716   0.068966   0.241993   0.321839   0.234875   0.172414  0.434164   \n",
      "2717   0.011765   0.142487   0.352941   0.313472   0.211765  0.531088   \n",
      "2718   0.046875   0.100817   0.250000   0.275204   0.250000  0.550409   \n",
      "2719   0.040892   0.237890   0.241636   0.434876   0.379182  0.291712   \n",
      "2720   0.088889   0.607858   0.448889   0.127502   0.171111  0.180875   \n",
      "2721   0.043630   0.508539   0.452007   0.303605   0.349040  0.117647   \n",
      "2722   0.006211   0.301273   0.298137   0.325318   0.322981  0.343706   \n",
      "2723   0.013333   0.317433   0.391111   0.111015   0.226667  0.460538   \n",
      "2724   0.043988   0.245327   0.322581   0.280374   0.334311  0.245327   \n",
      "2725   0.021810   0.615633   0.603053   0.226963   0.259542  0.125134   \n",
      "2726   0.062162   0.243674   0.191892   0.201500   0.213514  0.300843   \n",
      "2727   0.050459   0.274094   0.302752   0.265892   0.305810  0.350649   \n",
      "2728   0.007663   0.798113   0.714559   0.125472   0.191571  0.060692   \n",
      "2729   0.000000   0.793505   0.568862   0.137386   0.305389  0.061615   \n",
      "2730   0.017621   0.819275   0.765419   0.096929   0.127753  0.067333   \n",
      "2731   0.293084   0.199080   0.244898   0.245952   0.212585  0.254986   \n",
      "2732   0.040404   0.122166   0.335859   0.318640   0.267677  0.477330   \n",
      "2733   0.031936   0.203780   0.299401   0.311422   0.257485  0.364010   \n",
      "2734   0.025641   0.246964   0.250000   0.384615   0.250000  0.242915   \n",
      "2735   0.096481   0.316406   0.347333   0.246449   0.241771  0.300071   \n",
      "2736   0.063404   0.306517   0.373749   0.336049   0.303671  0.259674   \n",
      "2737   0.000000   0.242188   0.266667   0.378906   0.466667  0.320312   \n",
      "2738   0.021014   0.317757   0.325093   0.368640   0.388133  0.273451   \n",
      "2739   0.054945   0.429616   0.447253   0.271298   0.340659  0.193419   \n",
      "2740   0.089416   0.284281   0.281022   0.305463   0.286496  0.289855   \n",
      "2741   0.105263   0.308370   0.333333   0.334802   0.280702  0.233480   \n",
      "2742   0.034639   0.472764   0.492470   0.286047   0.286145  0.195456   \n",
      "2743   0.078000   0.454677   0.448000   0.253082   0.244000  0.211022   \n",
      "2744   0.091879   0.436374   0.466621   0.253461   0.241053  0.225394   \n",
      "2745   0.080972   0.261111   0.307692   0.286111   0.307692  0.375000   \n",
      "2746   0.020833   0.204852   0.166667   0.308625   0.312500  0.443396   \n",
      "2747   0.028958   0.179688   0.189189   0.353795   0.359073  0.369978   \n",
      "2748   0.174359   0.298884   0.314530   0.195537   0.206838  0.328244   \n",
      "2749   0.149448   0.264697   0.334002   0.254851   0.201605  0.387200   \n",
      "2750   0.132743   0.231638   0.203540   0.206215   0.283186  0.392655   \n",
      "2751   0.126667   0.305806   0.270000   0.234839   0.300000  0.269677   \n",
      "2752   0.267310   0.227525   0.265607   0.111175   0.095346  0.345793   \n",
      "\n",
      "      주말장년고객비율  주중노인고객비율  주말노인고객비율  \n",
      "0     0.142019  0.017782  0.011737  \n",
      "1     0.291310  0.037661  0.048960  \n",
      "2     0.308480  0.040841  0.018782  \n",
      "3     0.331395  0.032904  0.062016  \n",
      "4     0.265169  0.023679  0.031461  \n",
      "5     0.281163  0.031210  0.036011  \n",
      "6     0.339985  0.052797  0.048350  \n",
      "7     0.232779  0.043280  0.064133  \n",
      "8     0.172932  0.073947  0.077694  \n",
      "9     0.304553  0.063934  0.056515  \n",
      "10    0.376623  0.128524  0.067532  \n",
      "11    0.314103  0.057600  0.051282  \n",
      "12    0.227181  0.065379  0.093306  \n",
      "13    0.282609  0.045350  0.051630  \n",
      "14    0.346795  0.052204  0.077261  \n",
      "15    0.259398  0.075353  0.067669  \n",
      "16    0.233847  0.042023  0.027511  \n",
      "17    0.412908  0.047242  0.031228  \n",
      "18    0.283069  0.006873  0.018519  \n",
      "19    0.190248  0.054998  0.038369  \n",
      "20    0.174603  0.039039  0.063492  \n",
      "21    0.437500  0.159664  0.104167  \n",
      "22    0.431193  0.064171  0.110092  \n",
      "23    0.235119  0.044847  0.068452  \n",
      "24    0.322581  0.055556  0.032258  \n",
      "25    0.254054  0.082515  0.081081  \n",
      "26    0.242588  0.045752  0.021563  \n",
      "27    0.207885  0.033091  0.035842  \n",
      "28    0.490566  0.055866  0.056604  \n",
      "29    0.221884  0.171521  0.151976  \n",
      "30    0.202247  0.099083  0.084270  \n",
      "31    0.224066  0.013357  0.033195  \n",
      "32    0.225086  0.068053  0.068729  \n",
      "33    0.272727  0.067272  0.040909  \n",
      "34    0.186047  0.085399  0.058140  \n",
      "35    0.287081  0.105263  0.081340  \n",
      "36    0.292181  0.031560  0.084362  \n",
      "37    0.314031  0.023574  0.020045  \n",
      "38    0.344398  0.078298  0.116183  \n",
      "39    0.243781  0.059679  0.052239  \n",
      "40    0.270130  0.026719  0.014286  \n",
      "41    0.188896  0.043764  0.028436  \n",
      "42    0.284144  0.061899  0.023548  \n",
      "43    0.326613  0.103004  0.084677  \n",
      "44    0.326797  0.188213  0.183007  \n",
      "45    0.207598  0.021082  0.020353  \n",
      "46    0.327103  0.121321  0.074766  \n",
      "47    0.292453  0.032197  0.066038  \n",
      "48    0.195087  0.025712  0.014451  \n",
      "49    0.360294  0.238227  0.235294  \n",
      "50    0.443709  0.133995  0.105960  \n",
      "51    0.188235  0.040000  0.141176  \n",
      "52    0.310345  0.044343  0.051724  \n",
      "53    0.357143  0.061176  0.063910  \n",
      "54    0.186441  0.029091  0.016949  \n",
      "55    0.229811  0.088457  0.062313  \n",
      "56    0.217596  0.039384  0.044776  \n",
      "57    0.378788  0.041377  0.043434  \n",
      "58    0.282679  0.028199  0.039279  \n",
      "59    0.209673  0.036372  0.031877  \n",
      "60    0.218785  0.033005  0.046409  \n",
      "61    0.205153  0.035897  0.018130  \n",
      "62    0.197740  0.046766  0.046610  \n",
      "63    0.165408  0.036970  0.031722  \n",
      "64    0.250871  0.048604  0.031359  \n",
      "65    0.139344  0.042506  0.049180  \n",
      "66    0.361702  0.051823  0.075988  \n",
      "67    0.355102  0.062612  0.081633  \n",
      "68    0.234100  0.062332  0.041949  \n",
      "69    0.275311  0.060043  0.039076  \n",
      "70    0.164865  0.025000  0.018919  \n",
      "71    0.180832  0.038900  0.022604  \n",
      "72    0.385185  0.079832  0.051852  \n",
      "73    0.218031  0.073110  0.049233  \n",
      "74    0.348774  0.069767  0.035422  \n",
      "75    0.231003  0.091699  0.042553  \n",
      "76    0.322990  0.080503  0.057828  \n",
      "77    0.319635  0.035247  0.038487  \n",
      "78    0.341545  0.052361  0.047032  \n",
      "79    0.363071  0.084608  0.076763  \n",
      "80    0.150207  0.016173  0.024066  \n",
      "81    0.202532  0.040477  0.048825  \n",
      "82    0.241561  0.051770  0.059072  \n",
      "83    0.233766  0.127445  0.105751  \n",
      "84    0.347368  0.085714  0.010526  \n",
      "85    0.217604  0.055268  0.053790  \n",
      "86    0.238693  0.046993  0.038526  \n",
      "87    0.281762  0.090995  0.067623  \n",
      "88    0.178025  0.014215  0.018081  \n",
      "89    0.209790  0.041216  0.054545  \n",
      "90    0.335731  0.059732  0.050360  \n",
      "91    0.312684  0.110270  0.058997  \n",
      "92    0.309179  0.127686  0.106280  \n",
      "93    0.280914  0.106979  0.114247  \n",
      "94    0.276596  0.075510  0.078457  \n",
      "95    0.246858  0.044256  0.035907  \n",
      "96    0.353887  0.135875  0.123324  \n",
      "97    0.276923  0.074299  0.083516  \n",
      "98    0.258869  0.042326  0.047939  \n",
      "99    0.290828  0.017396  0.022371  \n",
      "100   0.253247  0.103115  0.136364  \n",
      "101   0.262097  0.038825  0.047379  \n",
      "102   0.377246  0.045234  0.089820  \n",
      "103   0.302290  0.100760  0.085496  \n",
      "104   0.358559  0.064000  0.039640  \n",
      "105   0.176963  0.026610  0.024084  \n",
      "106   0.312500  0.055441  0.033654  \n",
      "107   0.217633  0.064044  0.061160  \n",
      "108   0.243590  0.061678  0.053846  \n",
      "109   0.339798  0.069733  0.079258  \n",
      "110   0.275194  0.051559  0.036822  \n",
      "111   0.387226  0.063924  0.041916  \n",
      "112   0.396266  0.032178  0.024896  \n",
      "113   0.245763  0.016598  0.029661  \n",
      "114   0.234234  0.039792  0.022523  \n",
      "115   0.238562  0.046626  0.071895  \n",
      "116   0.319328  0.069565  0.025210  \n",
      "117   0.321663  0.192235  0.166302  \n",
      "118   0.323711  0.154300  0.167010  \n",
      "119   0.374046  0.110849  0.175573  \n",
      "120   0.395939  0.017606  0.048223  \n",
      "121   0.410349  0.077871  0.063779  \n",
      "122   0.268765  0.058261  0.086562  \n",
      "123   0.140083  0.043789  0.047157  \n",
      "124   0.126168  0.014660  0.000000  \n",
      "125   0.200000  0.008032  0.006897  \n",
      "126   0.160656  0.018767  0.019672  \n",
      "127   0.157407  0.037618  0.018519  \n",
      "128   0.284884  0.015075  0.017442  \n",
      "129   0.225806  0.024758  0.032258  \n",
      "130   0.271127  0.016304  0.007042  \n",
      "131   0.457944  0.042424  0.074766  \n",
      "132   0.217712  0.021635  0.003690  \n",
      "133   0.148085  0.028313  0.011064  \n",
      "134   0.270364  0.050027  0.020797  \n",
      "135   0.221053  0.054606  0.042105  \n",
      "136   0.333333  0.126582  0.212121  \n",
      "137   0.224359  0.189247  0.128205  \n",
      "138   0.211957  0.029630  0.059783  \n",
      "139   0.291139  0.076162  0.022152  \n",
      "140   0.431429  0.053594  0.060000  \n",
      "141   0.277523  0.009682  0.009174  \n",
      "142   0.212389  0.010309  0.017699  \n",
      "143   0.411765  0.098592  0.135294  \n",
      "144   0.309278  0.089815  0.068729  \n",
      "145   0.385093  0.112392  0.031056  \n",
      "146   0.293233  0.048860  0.030075  \n",
      "147   0.253197  0.065248  0.063939  \n",
      "148   0.692308  0.136752  0.076923  \n",
      "149   0.347222  0.050699  0.039352  \n",
      "150   0.379147  0.044721  0.040284  \n",
      "151   0.233708  0.055228  0.026966  \n",
      "152   0.212121  0.031459  0.022727  \n",
      "153   0.297872  0.050847  0.070922  \n",
      "154   0.238095  0.060109  0.054422  \n",
      "155   0.220447  0.049735  0.060703  \n",
      "156   0.433962  0.109145  0.113208  \n",
      "157   0.344340  0.061301  0.047170  \n",
      "158   0.294118  0.018868  0.009804  \n",
      "159   0.244424  0.058546  0.043680  \n",
      "160   0.436620  0.071028  0.091549  \n",
      "161   0.454545  0.082598  0.039256  \n",
      "162   0.304843  0.063545  0.059829  \n",
      "163   0.332604  0.079930  0.063457  \n",
      "164   0.442105  0.085409  0.047368  \n",
      "165   0.328302  0.097755  0.087736  \n",
      "166   0.283019  0.031621  0.009434  \n",
      "167   0.370370  0.050403  0.103704  \n",
      "168   0.332865  0.065144  0.053371  \n",
      "169   0.182365  0.033113  0.010020  \n",
      "170   0.214521  0.062432  0.059406  \n",
      "171   0.189845  0.042976  0.039735  \n",
      "172   0.137255  0.015799  0.028011  \n",
      "173   0.121902  0.011833  0.012056  \n",
      "174   0.386432  0.076521  0.061809  \n",
      "175   0.219512  0.048086  0.038462  \n",
      "176   0.200000  0.037888  0.037751  \n",
      "177   0.331432  0.028129  0.025349  \n",
      "178   0.119898  0.024806  0.028061  \n",
      "179   0.327160  0.056845  0.067901  \n",
      "180   0.245342  0.030763  0.031056  \n",
      "181   0.181818  0.074715  0.050671  \n",
      "182   0.268924  0.043659  0.043825  \n",
      "183   0.294118  0.017891  0.034056  \n",
      "184   0.419355  0.057971  0.010753  \n",
      "185   0.288714  0.025988  0.047244  \n",
      "186   0.370892  0.075993  0.070423  \n",
      "187   0.285974  0.069829  0.060109  \n",
      "188   0.477807  0.083519  0.099217  \n",
      "189   0.480519  0.104000  0.090909  \n",
      "190   0.350467  0.054217  0.051402  \n",
      "191   0.286802  0.065539  0.078680  \n",
      "192   0.258984  0.038123  0.033457  \n",
      "193   0.328571  0.085106  0.157143  \n",
      "194   0.272727  0.054152  0.045455  \n",
      "195   0.284420  0.074675  0.059783  \n",
      "196   0.240896  0.064432  0.074230  \n",
      "197   0.205843  0.014881  0.005312  \n",
      "198   0.209651  0.028518  0.018303  \n",
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      "1757  0.317690  0.071770  0.072202  \n",
      "1758  0.259036  0.152482  0.120482  \n",
      "1759  0.177391  0.051597  0.053913  \n",
      "1760  0.329341  0.033802  0.043413  \n",
      "1761  0.214379  0.023055  0.003922  \n",
      "1762  0.220874  0.020870  0.019417  \n",
      "1763  0.210784  0.012187  0.014706  \n",
      "1764  0.503067  0.051532  0.049080  \n",
      "1765  0.168212  0.070067  0.033113  \n",
      "1766  0.200000  0.058091  0.115789  \n",
      "1767  0.153846  0.037915  0.000000  \n",
      "1768  0.283333  0.040761  0.083333  \n",
      "1769  0.298561  0.082912  0.021583  \n",
      "1770  0.320312  0.013786  0.023438  \n",
      "1771  0.271920  0.019591  0.021088  \n",
      "1772  0.523810  0.007792  0.015873  \n",
      "1773  0.298193  0.036649  0.018072  \n",
      "1774  0.125000  0.025806  0.000000  \n",
      "1775  0.292683  0.021277  0.040650  \n",
      "1776  0.072368  0.018125  0.017544  \n",
      "1777  0.341880  0.093985  0.068376  \n",
      "1778  0.280000  0.036364  0.040000  \n",
      "1779  0.486842  0.068120  0.019737  \n",
      "1780  0.420290  0.116279  0.130435  \n",
      "1781  0.165428  0.040270  0.045539  \n",
      "1782  0.207547  0.050526  0.117925  \n",
      "1783  0.281646  0.099561  0.072785  \n",
      "1784  0.250000  0.018033  0.011905  \n",
      "1785  0.195726  0.028442  0.025872  \n",
      "1786  0.295527  0.067653  0.063898  \n",
      "1787  0.329193  0.066461  0.046584  \n",
      "1788  0.385057  0.055992  0.040230  \n",
      "1789  0.330472  0.041547  0.034335  \n",
      "1790  0.228758  0.073565  0.076253  \n",
      "1791  0.303571  0.109215  0.017857  \n",
      "1792  0.227405  0.045955  0.034569  \n",
      "1793  0.182773  0.069355  0.058824  \n",
      "1794  0.214286  0.072595  0.076531  \n",
      "1795  0.322314  0.029508  0.016529  \n",
      "1796  0.294118  0.102222  0.088235  \n",
      "1797  0.224490  0.100730  0.122449  \n",
      "1798  0.397394  0.150289  0.120521  \n",
      "1799  0.253766  0.053782  0.028969  \n",
      "1800  0.221774  0.030257  0.036290  \n",
      "1801  0.278481  0.040250  0.037975  \n",
      "1802  0.393156  0.029475  0.010646  \n",
      "1803  0.234568  0.017347  0.016461  \n",
      "1804  0.295082  0.023631  0.010929  \n",
      "1805  0.163265  0.059150  0.108844  \n",
      "1806  0.385246  0.026749  0.028689  \n",
      "1807  0.355140  0.016334  0.040498  \n",
      "1808  0.337500  0.071685  0.083929  \n",
      "1809  0.263415  0.021070  0.014634  \n",
      "1810  0.251371  0.026978  0.020110  \n",
      "1811  0.297297  0.234783  0.108108  \n",
      "1812  0.379791  0.036408  0.031359  \n",
      "1813  0.232099  0.083767  0.108642  \n",
      "1814  0.245136  0.025842  0.044099  \n",
      "1815  0.197802  0.020167  0.014286  \n",
      "1816  0.206395  0.049661  0.017442  \n",
      "1817  0.292343  0.080357  0.120650  \n",
      "1818  0.318681  0.096207  0.060440  \n",
      "1819  0.194555  0.032481  0.031208  \n",
      "1820  0.244094  0.019790  0.020997  \n",
      "1821  0.238532  0.067993  0.041284  \n",
      "1822  0.250000  0.024939  0.034211  \n",
      "1823  0.475000  0.080000  0.050000  \n",
      "1824  0.434679  0.043077  0.080760  \n",
      "1825  0.533333  0.054054  0.025000  \n",
      "1826  0.259358  0.066914  0.050802  \n",
      "1827  0.321839  0.174140  0.189655  \n",
      "1828  0.298387  0.027798  0.028226  \n",
      "1829  0.275862  0.026455  0.068966  \n",
      "1830  0.351064  0.031891  0.044681  \n",
      "1831  0.326087  0.060847  0.050725  \n",
      "1832  0.326494  0.058091  0.062444  \n",
      "1833  0.216898  0.036275  0.041614  \n",
      "1834  0.273768  0.013375  0.015845  \n",
      "1835  0.179487  0.020144  0.018100  \n",
      "1836  0.157576  0.016268  0.021212  \n",
      "1837  0.153110  0.005093  0.007974  \n",
      "1838  0.212219  0.070340  0.035370  \n",
      "1839  0.330000  0.016092  0.030000  \n",
      "1840  0.131915  0.034154  0.025532  \n",
      "1841  0.271712  0.033177  0.019851  \n",
      "1842  0.217762  0.015319  0.027981  \n",
      "1843  0.129395  0.068659  0.012658  \n",
      "1844  0.413994  0.114383  0.081633  \n",
      "1845  0.239796  0.032587  0.040816  \n",
      "1846  0.294737  0.052092  0.033684  \n",
      "1847  0.242938  0.025784  0.031073  \n",
      "1848  0.294118  0.060317  0.095588  \n",
      "1849  0.207024  0.015009  0.018484  \n",
      "1850  0.349233  0.050223  0.028961  \n",
      "1851  0.231818  0.036922  0.034091  \n",
      "1852  0.239934  0.034332  0.032046  \n",
      "1853  0.181818  0.011004  0.018759  \n",
      "1854  0.148699  0.017105  0.026022  \n",
      "1855  0.371831  0.037343  0.033803  \n",
      "1856  0.246753  0.077551  0.090909  \n",
      "1857  0.255000  0.015411  0.025000  \n",
      "1858  0.125000  0.000000  0.000000  \n",
      "1859  0.236527  0.067590  0.056886  \n",
      "1860  0.183946  0.014101  0.006689  \n",
      "1861  0.244373  0.073897  0.045016  \n",
      "1862  0.416838  0.059633  0.047228  \n",
      "1863  0.142857  0.060440  0.061224  \n",
      "1864  0.200000  0.067511  0.088889  \n",
      "1865  0.179910  0.013212  0.017991  \n",
      "1866  0.242424  0.030559  0.035915  \n",
      "1867  0.226257  0.043682  0.041899  \n",
      "1868  0.308571  0.018822  0.085714  \n",
      "1869  0.358491  0.043478  0.052830  \n",
      "1870  0.299120  0.037838  0.046921  \n",
      "1871  0.361702  0.116438  0.085106  \n",
      "1872  0.178571  0.011613  0.026786  \n",
      "1873  0.328467  0.081633  0.065693  \n",
      "1874  0.174107  0.019883  0.026786  \n",
      "1875  0.090000  0.008052  0.005000  \n",
      "1876  0.195021  0.013678  0.016598  \n",
      "1877  0.313480  0.103275  0.105016  \n",
      "1878  0.297778  0.053251  0.075556  \n",
      "1879  0.265487  0.135057  0.026549  \n",
      "1880  0.193388  0.010480  0.028099  \n",
      "1881  0.161742  0.014465  0.024883  \n",
      "1882  0.218182  0.019822  0.030303  \n",
      "1883  0.585366  0.112903  0.146341  \n",
      "1884  0.203106  0.028288  0.038232  \n",
      "1885  0.307522  0.025613  0.028761  \n",
      "1886  0.354839  0.109551  0.064516  \n",
      "1887  0.321617  0.059480  0.068541  \n",
      "1888  0.359848  0.039691  0.053030  \n",
      "1889  0.282651  0.088205  0.107212  \n",
      "1890  0.154867  0.019917  0.013274  \n",
      "1891  0.310680  0.068182  0.087379  \n",
      "1892  0.483568  0.170642  0.143192  \n",
      "1893  0.180000  0.029605  0.013333  \n",
      "1894  0.167431  0.024336  0.009174  \n",
      "1895  0.380952  0.078014  0.031746  \n",
      "1896  0.255230  0.034335  0.058577  \n",
      "1897  0.370056  0.020710  0.031073  \n",
      "1898  0.110976  0.011841  0.002439  \n",
      "1899  0.181020  0.023643  0.011519  \n",
      "1900  0.275362  0.046591  0.075362  \n",
      "1901  0.160825  0.045045  0.045361  \n",
      "1902  0.296703  0.074707  0.036630  \n",
      "1903  0.320611  0.031034  0.022901  \n",
      "1904  0.354430  0.141026  0.025316  \n",
      "1905  0.131250  0.016605  0.056250  \n",
      "1906  0.600000  0.021113  0.000000  \n",
      "1907  0.289520  0.047522  0.049734  \n",
      "1908  0.266160  0.039801  0.038023  \n",
      "1909  0.341362  0.048624  0.043189  \n",
      "1910  0.281375  0.115185  0.087130  \n",
      "1911  0.394813  0.047478  0.046110  \n",
      "1912  0.218539  0.018369  0.013532  \n",
      "1913  0.217213  0.022850  0.010246  \n",
      "1914  0.264407  0.032684  0.067797  \n",
      "1915  0.350649  0.036403  0.019481  \n",
      "1916  0.325397  0.018815  0.021825  \n",
      "1917  0.345622  0.051948  0.064516  \n",
      "1918  0.309711  0.043891  0.034121  \n",
      "1919  0.240059  0.056489  0.042710  \n",
      "1920  0.253444  0.038726  0.024793  \n",
      "1921  0.236434  0.115142  0.127907  \n",
      "1922  0.300000  0.078253  0.111905  \n",
      "1923  0.396226  0.061885  0.054717  \n",
      "1924  0.192761  0.051636  0.038721  \n",
      "1925  0.263966  0.066939  0.061453  \n",
      "1926  0.294118  0.059165  0.043137  \n",
      "1927  0.329876  0.067389  0.045643  \n",
      "1928  0.454545  0.074380  0.075758  \n",
      "1929  0.302991  0.050938  0.065020  \n",
      "1930  0.271326  0.051867  0.048304  \n",
      "1931  0.228125  0.047535  0.015625  \n",
      "1932  0.319149  0.088115  0.099291  \n",
      "1933  0.223990  0.034085  0.023256  \n",
      "1934  0.489583  0.166181  0.135417  \n",
      "1935  0.205603  0.031315  0.039411  \n",
      "1936  0.362993  0.073047  0.072801  \n",
      "1937  0.372263  0.040268  0.051095  \n",
      "1938  0.262626  0.035714  0.020202  \n",
      "1939  0.345382  0.096096  0.090361  \n",
      "1940  0.193772  0.041102  0.038062  \n",
      "1941  0.183529  0.022672  0.014118  \n",
      "1942  0.282524  0.035010  0.038835  \n",
      "1943  0.171756  0.024036  0.022901  \n",
      "1944  0.338983  0.202944  0.223164  \n",
      "1945  0.175503  0.016667  0.023766  \n",
      "1946  0.090909  0.017804  0.000000  \n",
      "1947  0.201269  0.043536  0.031732  \n",
      "1948  0.270102  0.031952  0.031097  \n",
      "1949  0.336000  0.137931  0.160000  \n",
      "1950  0.229630  0.077128  0.133333  \n",
      "1951  0.234694  0.082822  0.020408  \n",
      "1952  0.264901  0.074194  0.039735  \n",
      "1953  0.252617  0.057757  0.036288  \n",
      "1954  0.326996  0.049724  0.068441  \n",
      "1955  0.273743  0.101749  0.033520  \n",
      "1956  0.306122  0.052053  0.035714  \n",
      "1957  0.294852  0.030824  0.018721  \n",
      "1958  0.272727  0.053452  0.077922  \n",
      "1959  0.164384  0.035477  0.013699  \n",
      "1960  0.307764  0.064682  0.038354  \n",
      "1961  0.344762  0.041394  0.032381  \n",
      "1962  0.282486  0.037184  0.079096  \n",
      "1963  0.257426  0.121413  0.110561  \n",
      "1964  0.243558  0.051564  0.045719  \n",
      "1965  0.145511  0.023579  0.024768  \n",
      "1966  0.119593  0.028548  0.020356  \n",
      "1967  0.302381  0.048031  0.066667  \n",
      "1968  0.330789  0.073123  0.066158  \n",
      "1969  0.111111  0.057158  0.031746  \n",
      "1970  0.204620  0.039931  0.021452  \n",
      "1971  0.268212  0.065772  0.079470  \n",
      "1972  0.230769  0.049524  0.029586  \n",
      "1973  0.261628  0.016016  0.011628  \n",
      "1974  0.230117  0.029062  0.029692  \n",
      "1975  0.210407  0.090969  0.097285  \n",
      "1976  0.343220  0.027858  0.023305  \n",
      "1977  0.215278  0.027088  0.025463  \n",
      "1978  0.344828  0.077075  0.088670  \n",
      "1979  0.151316  0.121065  0.144737  \n",
      "1980  0.275204  0.043704  0.038147  \n",
      "1981  0.184659  0.027550  0.017045  \n",
      "1982  0.405063  0.023987  0.044304  \n",
      "1983  0.214612  0.026588  0.027397  \n",
      "1984  0.371369  0.060199  0.060166  \n",
      "1985  0.102941  0.009865  0.012255  \n",
      "1986  0.238806  0.067835  0.023454  \n",
      "1987  0.176700  0.026852  0.024686  \n",
      "1988  0.250000  0.083636  0.054348  \n",
      "1989  0.290909  0.052083  0.018182  \n",
      "1990  0.243243  0.040493  0.066066  \n",
      "1991  0.291429  0.070081  0.051429  \n",
      "1992  0.236897  0.057014  0.039832  \n",
      "1993  0.203883  0.032441  0.016990  \n",
      "1994  0.408824  0.057541  0.076471  \n",
      "1995  0.302048  0.029038  0.018203  \n",
      "1996  0.255319  0.029316  0.053191  \n",
      "1997  0.184953  0.045567  0.053292  \n",
      "1998  0.226351  0.068415  0.060811  \n",
      "1999  0.270270  0.038095  0.031185  \n",
      "2000  0.365385  0.054348  0.028846  \n",
      "2001  0.194915  0.033645  0.076271  \n",
      "2002  0.545455  0.035714  0.000000  \n",
      "2003  0.333333  0.000000  0.000000  \n",
      "2004  0.321429  0.009346  0.047619  \n",
      "2005  0.274286  0.035256  0.028571  \n",
      "2006  0.223164  0.019861  0.008475  \n",
      "2007  0.263873  0.042925  0.033975  \n",
      "2008  0.311828  0.062857  0.032258  \n",
      "2009  0.230126  0.034436  0.033473  \n",
      "2010  0.271001  0.048720  0.038714  \n",
      "2011  0.406593  0.060241  0.065934  \n",
      "2012  0.155488  0.025234  0.027439  \n",
      "2013  0.300448  0.039356  0.053812  \n",
      "2014  0.248201  0.026589  0.026978  \n",
      "2015  0.237687  0.103851  0.061028  \n",
      "2016  0.233983  0.079533  0.083565  \n",
      "2017  0.243119  0.027579  0.036697  \n",
      "2018  0.203333  0.026590  0.030000  \n",
      "2019  0.218914  0.049159  0.024518  \n",
      "2020  0.300000  0.062542  0.053333  \n",
      "2021  0.355263  0.031707  0.032895  \n",
      "2022  0.204762  0.012111  0.009524  \n",
      "2023  0.358804  0.056576  0.036545  \n",
      "2024  0.360000  0.065731  0.061333  \n",
      "2025  0.365672  0.127148  0.082090  \n",
      "2026  0.262948  0.099401  0.119522  \n",
      "2027  0.218333  0.056522  0.028333  \n",
      "2028  0.500000  0.032258  0.000000  \n",
      "2029  0.413793  0.024390  0.068966  \n",
      "2030  0.231362  0.042689  0.038560  \n",
      "2031  0.366197  0.036145  0.014085  \n",
      "2032  0.329032  0.083333  0.070968  \n",
      "2033  0.336842  0.034286  0.038596  \n",
      "2034  0.209265  0.037583  0.039936  \n",
      "2035  0.165759  0.023455  0.012099  \n",
      "2036  0.125623  0.026051  0.014955  \n",
      "2037  0.150000  0.062366  0.036364  \n",
      "2038  0.255605  0.028798  0.049327  \n",
      "2039  0.320000  0.106383  0.066667  \n",
      "2040  0.251309  0.231602  0.230366  \n",
      "2041  0.272926  0.038624  0.028384  \n",
      "2042  0.288779  0.052482  0.034653  \n",
      "2043  0.087838  0.030950  0.016892  \n",
      "2044  0.345070  0.015584  0.042254  \n",
      "2045  0.307263  0.092772  0.134078  \n",
      "2046  0.175676  0.033565  0.008108  \n",
      "2047  0.184239  0.032347  0.033014  \n",
      "2048  0.313783  0.022489  0.029326  \n",
      "2049  0.231013  0.051823  0.060127  \n",
      "2050  0.229885  0.143590  0.172414  \n",
      "2051  0.304636  0.021830  0.052980  \n",
      "2052  0.294118  0.034513  0.056985  \n",
      "2053  0.131783  0.006381  0.016611  \n",
      "2054  0.190265  0.043732  0.008850  \n",
      "2055  0.401235  0.058716  0.037037  \n",
      "2056  0.393401  0.115512  0.098985  \n",
      "2057  0.251852  0.045564  0.029630  \n",
      "2058  0.246073  0.058522  0.034031  \n",
      "2059  0.243736  0.058458  0.059226  \n",
      "2060  0.274611  0.087932  0.048359  \n",
      "2061  0.228477  0.025432  0.013245  \n",
      "2062  0.193297  0.043556  0.024942  \n",
      "2063  0.238095  0.051988  0.023810  \n",
      "2064  0.196970  0.027753  0.033892  \n",
      "2065  0.196629  0.044068  0.042135  \n",
      "2066  0.312500  0.083333  0.125000  \n",
      "2067  0.383065  0.047170  0.040323  \n",
      "2068  0.057432  0.024346  0.003378  \n",
      "2069  0.203187  0.063460  0.035857  \n",
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      "2680  0.180473  0.079281  0.050296  \n",
      "2681  0.349693  0.082192  0.092025  \n",
      "2682  0.220339  0.097087  0.237288  \n",
      "2683  0.400612  0.019508  0.027523  \n",
      "2684  0.440443  0.045696  0.044321  \n",
      "2685  0.392857  0.078512  0.035714  \n",
      "2686  0.345070  0.031931  0.042254  \n",
      "2687  0.260459  0.068901  0.048583  \n",
      "2688  0.345269  0.027248  0.010230  \n",
      "2689  0.282353  0.049102  0.047059  \n",
      "2690  0.192253  0.054691  0.032999  \n",
      "2691  0.289354  0.051312  0.069154  \n",
      "2692  0.196367  0.048916  0.043253  \n",
      "2693  0.474227  0.080442  0.087629  \n",
      "2694  0.326165  0.085320  0.093190  \n",
      "2695  0.361111  0.174312  0.138889  \n",
      "2696  0.269144  0.030516  0.022523  \n",
      "2697  0.472393  0.038462  0.061350  \n",
      "2698  0.281938  0.073099  0.060206  \n",
      "2699  0.310023  0.074650  0.048951  \n",
      "2700  0.209302  0.067278  0.031008  \n",
      "2701  0.276892  0.041237  0.025896  \n",
      "2702  0.360656  0.049505  0.047131  \n",
      "2703  0.243523  0.063376  0.053541  \n",
      "2704  0.328257  0.041289  0.028765  \n",
      "2705  0.230944  0.038146  0.051195  \n",
      "2706  0.178030  0.018044  0.022727  \n",
      "2707  0.287066  0.065663  0.063091  \n",
      "2708  0.297821  0.099628  0.058111  \n",
      "2709  0.371429  0.053097  0.042857  \n",
      "2710  0.437838  0.122159  0.070270  \n",
      "2711  0.255725  0.128977  0.064885  \n",
      "2712  0.333333  0.083888  0.066667  \n",
      "2713  0.341463  0.144137  0.118902  \n",
      "2714  0.298137  0.053110  0.052795  \n",
      "2715  0.344214  0.050863  0.020772  \n",
      "2716  0.402299  0.039146  0.034483  \n",
      "2717  0.388235  0.010363  0.035294  \n",
      "2718  0.328125  0.049046  0.125000  \n",
      "2719  0.286245  0.021529  0.052045  \n",
      "2720  0.242222  0.050408  0.048889  \n",
      "2721  0.109948  0.049336  0.045375  \n",
      "2722  0.329193  0.024045  0.043478  \n",
      "2723  0.231111  0.106678  0.137778  \n",
      "2724  0.260997  0.196262  0.038123  \n",
      "2725  0.107961  0.013625  0.007634  \n",
      "2726  0.383784  0.156514  0.145946  \n",
      "2727  0.287462  0.074504  0.053517  \n",
      "2728  0.080460  0.007862  0.005747  \n",
      "2729  0.125749  0.004163  0.000000  \n",
      "2730  0.080396  0.008139  0.008811  \n",
      "2731  0.234127  0.016192  0.014172  \n",
      "2732  0.325758  0.051008  0.030303  \n",
      "2733  0.345309  0.087099  0.065868  \n",
      "2734  0.358974  0.113360  0.115385  \n",
      "2735  0.263337  0.059659  0.051078  \n",
      "2736  0.233593  0.038187  0.025584  \n",
      "2737  0.266667  0.058594  0.000000  \n",
      "2738  0.248455  0.024230  0.017305  \n",
      "2739  0.132967  0.023400  0.024176  \n",
      "2740  0.242701  0.062430  0.098540  \n",
      "2741  0.236842  0.061674  0.043860  \n",
      "2742  0.161145  0.025634  0.025602  \n",
      "2743  0.174000  0.026831  0.056000  \n",
      "2744  0.175671  0.027024  0.024604  \n",
      "2745  0.246964  0.055556  0.056680  \n",
      "2746  0.447917  0.030997  0.041667  \n",
      "2747  0.339768  0.068080  0.083012  \n",
      "2748  0.251282  0.042866  0.052991  \n",
      "2749  0.292879  0.029540  0.022066  \n",
      "2750  0.300885  0.076271  0.079646  \n",
      "2751  0.256667  0.072258  0.046667  \n",
      "2752  0.319523  0.033736  0.048241  \n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "df1_ins['대여일자'] = pd.to_datetime(df1_ins['대여일자'])\n",
    "\n",
    "# 주중/주말 구분\n",
    "df1_ins['주말여부'] = df1_ins['대여요일'].isin(['Saturday', 'Sunday'])\n",
    "\n",
    "# 시간대 구분\n",
    "df1_ins['새벽시간'] = (df1_ins['대여시간'] >= 0) & (df1_ins['대여시간'] < 6)\n",
    "df1_ins['출근시간'] = (df1_ins['대여시간'] >= 7) & (df1_ins['대여시간'] < 10)\n",
    "df1_ins['오전시간'] = (df1_ins['대여시간'] >= 10) & (df1_ins['대여시간'] < 12)\n",
    "df1_ins['점심시간'] = (df1_ins['대여시간'] >= 12) & (df1_ins['대여시간'] < 14)\n",
    "df1_ins['오후시간'] = (df1_ins['대여시간'] >= 14) & (df1_ins['대여시간'] < 17)\n",
    "df1_ins['퇴근시간'] = (df1_ins['대여시간'] >= 17) & (df1_ins['대여시간'] < 19)\n",
    "df1_ins['야간시간'] = (df1_ins['대여시간'] >= 19) & (df1_ins['대여시간'] < 24)\n",
    "\n",
    "# 대여대여소ID 기준 그룹화하여 통계 피처 생성\n",
    "total_counts = df1_ins.groupby('대여대여소ID')['대여일자'].count()\n",
    "\n",
    "grouped = df1_ins.groupby('대여대여소ID').agg({\n",
    "    '대여일자': 'count',  # 총 대여 횟수\n",
    "    '성별_M': 'mean',  # 남성 방문고객 비율\n",
    "    '이용시간(분)': 'mean',  # 평균 이용시간\n",
    "    '이용거리(M)': 'mean',  # 평균 이용거리\n",
    "    '주말여부': lambda x: x.sum() / x.count(),  # 주말 대여 비율\n",
    "    '새벽시간': lambda x: x.sum() / x.count(),  # 새벽 대여 비율\n",
    "    '출근시간': lambda x: x.sum() / x.count(),  # 출근 시간대 대여 비율\n",
    "    '오전시간': lambda x: x.sum() / x.count(),  # 오전 대여 비율\n",
    "    '점심시간': lambda x: x.sum() / x.count(),  # 점심시간 대여 비율\n",
    "    '오후시간': lambda x: x.sum() / x.count(),  # 오후시간 대여 비율\n",
    "    '퇴근시간': lambda x: x.sum() / x.count(),  # 퇴근 시간대 대여 비율\n",
    "    '야간시간': lambda x: x.sum() / x.count()   # 야간 대여 비율\n",
    "}).reset_index()\n",
    "\n",
    "# 컬럼 이름 변경\n",
    "grouped.columns = [\n",
    "    '대여대여소ID', '총대여횟수', '남성고객비율', '평균이용시간', '평균이용거리',\n",
    "    '주말대여비율', '새벽대여비율', '출근시간대여비율', '오전대여비율', '점심대여비율', '오후대여비율',\n",
    "    '퇴근시간대여비율', '야간대여비율'\n",
    "]\n",
    "\n",
    "# 주중/주말 연령대별 고객 비율 계산 함수\n",
    "def calculate_ratios(df):\n",
    "    weekday_data = df[~df['주말여부']]\n",
    "    weekend_data = df[df['주말여부']]\n",
    "    total_weekday = len(weekday_data)\n",
    "    total_weekend = len(weekend_data)\n",
    "    \n",
    "    ratios = {\n",
    "        '주중청소년고객비율': len(weekday_data[weekday_data['연령대'] == 10]) / total_weekday if total_weekday > 0 else 0,\n",
    "        '주말청소년고객비율': len(weekend_data[weekend_data['연령대'] == 10]) / total_weekend if total_weekend > 0 else 0,\n",
    "        '주중청년1고객비율': len(weekday_data[weekday_data['연령대'] == 20]) / total_weekday if total_weekday > 0 else 0,\n",
    "        '주말청년1고객비율': len(weekend_data[weekend_data['연령대'] == 20]) / total_weekend if total_weekend > 0 else 0,\n",
    "        '주중청년2고객비율': len(weekday_data[weekday_data['연령대'] == 30]) / total_weekday if total_weekday > 0 else 0,\n",
    "        '주말청년2고객비율': len(weekend_data[weekend_data['연령대'] == 30]) / total_weekend if total_weekend > 0 else 0,\n",
    "        '주중장년고객비율': len(weekday_data[(weekday_data['연령대'] == 40) | (weekday_data['연령대'] == 50)]) / total_weekday if total_weekday > 0 else 0,\n",
    "        '주말장년고객비율': len(weekend_data[(weekend_data['연령대'] == 40) | (weekend_data['연령대'] == 50)]) / total_weekend if total_weekend > 0 else 0,\n",
    "        '주중노인고객비율': len(weekday_data[(weekday_data['연령대'] == 60) | (weekday_data['연령대'] == 70)]) / total_weekday if total_weekday > 0 else 0,\n",
    "        '주말노인고객비율': len(weekend_data[(weekend_data['연령대'] == 60) | (weekend_data['연령대'] == 70)]) / total_weekend if total_weekend > 0 else 0\n",
    "    }\n",
    "    return pd.Series(ratios)\n",
    "\n",
    "# 그룹화하여 추가 피처 계산\n",
    "additional_features = df1_ins.groupby('대여대여소ID').apply(calculate_ratios).reset_index()\n",
    "grouped = pd.merge(grouped, additional_features, on='대여대여소ID')\n",
    "\n",
    "print(grouped)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [],
   "source": [
    "grouped = grouped.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "\n",
    "# # 군집분석에 사용할 피처 선택\n",
    "# features = grouped.drop(columns=['대여대여소ID'])\n",
    "\n",
    "sum_of_squared_distances = []\n",
    "K = range(1, 15)\n",
    "for k in K:\n",
    "    km = KMeans(n_clusters = k)\n",
    "    km = km.fit(features)\n",
    "    sum_of_squared_distances.append(km.inertia_)\n",
    "    \n",
    "# 시각화\n",
    "\n",
    "plt.plot(K, sum_of_squared_distances, 'bx-')\n",
    "plt.xlabel('k')\n",
    "plt.ylabel('Sum_of_squared_distances')\n",
    "plt.title('Elbow Method For Optimal k')\n",
    "plt.axvline(2,c= 'r',alpha =0.4)\n",
    "plt.axvline(3,c= 'r',alpha =0.4)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "k : 2 score : 0.5859813557595944\n",
      "k : 3 score : 0.46252569834593826\n",
      "k : 4 score : 0.42627474767742846\n",
      "k : 5 score : 0.4396390887003232\n",
      "k : 6 score : 0.42642627689897433\n",
      "k : 7 score : 0.3886246695201724\n",
      "k : 8 score : 0.3786767354457498\n",
      "k : 9 score : 0.36149019937405097\n",
      "k : 10 score : 0.3625252089320405\n",
      "k : 11 score : 0.37362008549473263\n",
      "k : 12 score : 0.3613642276562695\n",
      "k : 13 score : 0.3617205187544004\n",
      "best n : 2 best score : 0.5859813557595944\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import silhouette_score\n",
    "k_range = range(2,14)\n",
    "\n",
    "best_n = -1\n",
    "best_silhouette_score = -1\n",
    "\n",
    "for k in k_range:\n",
    "\n",
    "  kmeans = KMeans(n_clusters=k, random_state=200)\n",
    "  kmeans.fit(features)\n",
    "  clusters = kmeans.predict(features)\n",
    "\n",
    "  score = silhouette_score(features, clusters)\n",
    "  print('k :',  k, 'score :', score)\n",
    "\n",
    "  if score > best_silhouette_score:\n",
    "    best_n = k\n",
    "    best_silhouette_score = score\n",
    "\n",
    "print('best n :', best_n, 'best score :', best_silhouette_score )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      대여대여소ID  총대여횟수    남성고객비율     평균이용시간       평균이용거리    주말대여비율    새벽대여비율  \\\n",
      "0       ST-10   2764  0.641823  30.027135  2896.118784  0.308249  0.099493   \n",
      "1     ST-1000   3074  0.625895  19.268705  2427.495573  0.265777  0.036760   \n",
      "2     ST-1002   5895  0.658863  20.319932  2289.621218  0.298049  0.013740   \n",
      "3     ST-1003   1914  0.641066  17.774817  2121.170564  0.269592  0.060084   \n",
      "4     ST-1004   1543  0.736876  15.806870  1868.960045  0.288399  0.038885   \n",
      "5     ST-1005   5385  0.666295  16.411513  2028.707627  0.268152  0.043825   \n",
      "6     ST-1006   5129  0.584909  17.895301  2063.188239  0.254046  0.037044   \n",
      "7     ST-1007   1738  0.702532  19.873418  2323.346559  0.242232  0.107020   \n",
      "8     ST-1008   1562  0.620999  17.128681  2057.830787  0.255442  0.090909   \n",
      "9     ST-1010   2686  0.615041  17.107967  2060.121754  0.237156  0.084885   \n",
      "10    ST-1011   1591  0.698931  17.680075  2151.094519  0.241986  0.108737   \n",
      "11    ST-1012    781  0.580026  20.120359  2546.327324  0.199744  0.079385   \n",
      "12    ST-1013   1839  0.652529  17.926047  2100.868532  0.268080  0.079391   \n",
      "13    ST-1014   2110  0.757346  16.622749  1976.020043  0.174408  0.092891   \n",
      "14    ST-1015   5449  0.664342  15.335474  2033.100934  0.209029  0.027528   \n",
      "15    ST-1016    903  0.700997  17.579181  1963.192946  0.294574  0.058693   \n",
      "16    ST-1017   7777  0.607818  18.608332  1880.443046  0.308474  0.023531   \n",
      "17    ST-1018   4722  0.603558  20.476493  1754.971576  0.305167  0.027319   \n",
      "18    ST-1019   1251  0.494804  20.408473  2096.043909  0.302158  0.011191   \n",
      "19     ST-102   4542  0.589828  17.608983  1861.184447  0.275429  0.064069   \n",
      "20    ST-1020    459  0.612200  22.507625  2352.459869  0.274510  0.069717   \n",
      "21    ST-1023    215  0.623256  33.083721  4119.819721  0.446512  0.083721   \n",
      "22    ST-1024    296  0.652027  32.084459  3604.316115  0.368243  0.084459   \n",
      "23    ST-1025   1384  0.627168  17.930636  1936.868772  0.242775  0.055636   \n",
      "24    ST-1027   1048  0.743321  23.715649  1857.247023  0.295802  0.030534   \n",
      "25    ST-1028    694  0.550432  15.579251  1840.226585  0.266571  0.017291   \n",
      "26    ST-1029   2207  0.687812  18.700498  1917.995179  0.168101  0.023561   \n",
      "27     ST-103   1518  0.517128  19.182477  2629.554190  0.183794  0.050066   \n",
      "28    ST-1031    232  0.801724  11.461207  1623.920603  0.228448  0.116379   \n",
      "29    ST-1032   1256  0.703025  18.134554  2114.573957  0.261943  0.058121   \n",
      "30    ST-1033    723  0.623790  20.230982  2706.198396  0.246196  0.059474   \n",
      "31    ST-1034   1364  0.689150  16.321848  1968.103387  0.176686  0.016129   \n",
      "32    ST-1035   2169  0.626095  20.044260  2067.914786  0.268326  0.067312   \n",
      "33    ST-1036   2533  0.527438  22.032373  2410.296368  0.260561  0.037505   \n",
      "34    ST-1038    535  0.485981  12.620561  1467.208785  0.321495  0.057944   \n",
      "35    ST-1039    722  0.595568  15.493075  1939.576205  0.289474  0.055402   \n",
      "36    ST-1040   3813  0.683714  19.521637  2057.314377  0.127459  0.012064   \n",
      "37    ST-1041   5801  0.552491  22.614722  2040.038411  0.232201  0.036545   \n",
      "38    ST-1042   1416  0.715395  21.580508  2413.034562  0.170198  0.033898   \n",
      "39    ST-1044   1709  0.760094  18.361615  1864.995810  0.235225  0.037449   \n",
      "40    ST-1045   3053  0.633803  19.516869  1738.346931  0.252211  0.081559   \n",
      "41    ST-1046   5133  0.624196  19.441457  1859.437278  0.287746  0.055913   \n",
      "42    ST-1047   2301  0.520643  19.689266  2051.637631  0.276836  0.057366   \n",
      "43    ST-1048    947  0.658923  26.570222  3142.622027  0.261880  0.025343   \n",
      "44    ST-1049    679  0.678940  24.058910  3097.871149  0.225331  0.013255   \n",
      "45     ST-105   3583  0.583031  19.155735  1876.295093  0.205694  0.010047   \n",
      "46    ST-1050   1928  0.688797  17.575726  1997.172951  0.277490  0.066390   \n",
      "47    ST-1051    740  0.651351  23.005405  2353.244797  0.286486  0.040541   \n",
      "48    ST-1053   2131  0.696856  17.221492  1859.324298  0.324730  0.040357   \n",
      "49    ST-1054    497  0.501006  21.289738  2526.898672  0.273642  0.042254   \n",
      "50    ST-1055    554  0.575812  31.705776  2636.074639  0.272563  0.043321   \n",
      "51    ST-1056    310  0.606452  13.954839  1644.136226  0.274194  0.009677   \n",
      "52    ST-1058    886  0.628668  19.101580  1991.193352  0.261851  0.059819   \n",
      "53    ST-1059   1116  0.499104  19.947133  2235.886711  0.238351  0.034946   \n",
      "54     ST-106    334  0.631737  28.317365  2695.232695  0.176647  0.053892   \n",
      "55    ST-1061   7048  0.624858  21.274262  2094.012518  0.284620  0.064983   \n",
      "56    ST-1062   5361  0.653236  14.421004  1713.027691  0.237456  0.059690   \n",
      "57    ST-1063   6162  0.623337   8.630477   932.610446  0.160662  0.004869   \n",
      "58    ST-1064   8078  0.515227  10.692622  1166.555553  0.192251  0.012998   \n",
      "59    ST-1065  15049  0.626620  14.625689  1632.228739  0.241810  0.051764   \n",
      "60    ST-1067   4359  0.664373  17.231705  2208.648892  0.207616  0.021794   \n",
      "61    ST-1069   5338  0.617647  16.973586  2134.785384  0.196328  0.048707   \n",
      "62     ST-107   1713  0.521308  42.304729  4551.956287  0.413310  0.042615   \n",
      "63    ST-1070   4624  0.544983  21.247837  1899.899862  0.286332  0.033521   \n",
      "64    ST-1072   1254  0.578947  18.772727  2016.758676  0.228868  0.034290   \n",
      "65    ST-1075   1260  0.655556  16.850794  1861.088111  0.290476  0.053968   \n",
      "66    ST-1076   1892  0.618922  15.489429  1704.607077  0.173890  0.011628   \n",
      "67    ST-1077    804  0.717662  18.808458  2206.681381  0.304726  0.087065   \n",
      "68    ST-1078   2969  0.574267  20.889862  2307.792179  0.248905  0.049848   \n",
      "69    ST-1079   2445  0.567280  19.366871  2276.790524  0.230266  0.053988   \n",
      "70     ST-108   2780  0.572302  31.375540  2990.469169  0.266187  0.010791   \n",
      "71    ST-1081   4088  0.568982  19.916585  1978.505729  0.270548  0.048679   \n",
      "72    ST-1082    611  0.680851  15.851064  2406.016628  0.220949  0.067103   \n",
      "73    ST-1083   6365  0.527730  18.722074  1953.921962  0.245719  0.025609   \n",
      "74    ST-1084   1829  0.607983  18.451066  1992.090252  0.200656  0.049754   \n",
      "75    ST-1085   1365  0.561905  22.117949  2462.271436  0.241026  0.046154   \n",
      "76    ST-1086   2299  0.512832  26.902131  2449.067843  0.308395  0.006960   \n",
      "77    ST-1087   3519  0.509236  32.593635  2951.444899  0.435635  0.017903   \n",
      "78    ST-1088   3032  0.604222  21.590369  2052.265792  0.294525  0.043536   \n",
      "79    ST-1089   1593  0.662272  25.385436  2514.144903  0.302574  0.006277   \n",
      "80     ST-109   4482  0.525212  27.005355  3074.579643  0.268853  0.021419   \n",
      "81    ST-1092   2480  0.468548  18.181452  1698.632286  0.222984  0.040323   \n",
      "82    ST-1093   3942  0.628615  16.402588  1795.793983  0.240487  0.104515   \n",
      "83    ST-1095   2124  0.581450  25.928908  3289.557392  0.253766  0.055556   \n",
      "84    ST-1096    375  0.680000  24.805333  3089.876640  0.253333  0.125333   \n",
      "85    ST-1097   3134  0.621889  16.756860  1914.754968  0.261008  0.099553   \n",
      "86    ST-1098   4769  0.664290  19.116377  2158.201958  0.250367  0.070455   \n",
      "87    ST-1099   3097  0.570552  19.387149  2055.147514  0.315144  0.091702   \n",
      "88      ST-11   2337  0.621309  32.154044  3731.511819  0.307659  0.109970   \n",
      "89     ST-110   2656  0.627259  19.899849  2112.669326  0.269202  0.031250   \n",
      "90    ST-1100   1388  0.596542  22.574207  2244.815202  0.300432  0.120317   \n",
      "91    ST-1101   1264  0.673259  22.055380  2254.576661  0.268196  0.060918   \n",
      "92    ST-1102    998  0.791583  18.692385  2056.407926  0.207415  0.077154   \n",
      "93    ST-1103   2922  0.592745  25.811431  2519.954418  0.254620  0.079055   \n",
      "94    ST-1104   2712  0.610988  20.172198  2169.339889  0.277286  0.077434   \n",
      "95    ST-1105   4187  0.647003  19.841414  2160.874275  0.266062  0.101027   \n",
      "96    ST-1106   1396  0.722063  26.028653  3239.239900  0.267192  0.098138   \n",
      "97    ST-1107   1774  0.607103  22.138670  2681.525846  0.256483  0.062007   \n",
      "98    ST-1109   3760  0.682447  21.211170  2271.967191  0.277394  0.094415   \n",
      "99     ST-111   2459  0.581537  23.303782  2087.445868  0.181781  0.026434   \n",
      "100   ST-1110   1239  0.598063  20.874092  2134.039266  0.248588  0.071025   \n",
      "101   ST-1111   3851  0.622695  22.389509  3008.212885  0.257595  0.064139   \n",
      "102   ST-1114    786  0.678117  29.972010  4532.624148  0.212468  0.076336   \n",
      "103   ST-1118   6699  0.577400  20.352590  2371.064750  0.293327  0.056874   \n",
      "104   ST-1119   1930  0.606218  17.773057  1920.393715  0.287565  0.058549   \n",
      "105    ST-112   5164  0.600310  18.300542  1795.162949  0.184934  0.047637   \n",
      "106   ST-1120    695  0.558273  19.420144  2243.307482  0.299281  0.057554   \n",
      "107   ST-1121   8873  0.662910  19.400654  1944.299549  0.283782  0.055336   \n",
      "108   ST-1122   1379  0.604061  18.316171  2346.212088  0.282814  0.070341   \n",
      "109   ST-1123   5187  0.581646  19.331791  2287.494157  0.228649  0.040679   \n",
      "110   ST-1124   3534  0.597906  17.070741  1789.777295  0.292020  0.062535   \n",
      "111   ST-1125   3223  0.610922  23.040335  2499.410323  0.155445  0.020168   \n",
      "112   ST-1127   1694  0.533058  15.701299  1846.908601  0.284534  0.030697   \n",
      "113   ST-1128    959  0.637122  14.968717  1698.702669  0.246090  0.023983   \n",
      "114   ST-1129    800  0.666250  19.033750  2646.654437  0.277500  0.101250   \n",
      "115    ST-113   1121  0.536128  25.518287  3074.595558  0.272971  0.033898   \n",
      "116   ST-1130    464  0.566810  16.474138  1861.273556  0.256466  0.019397   \n",
      "117   ST-1131   1513  0.608063  28.517515  2966.239861  0.302049  0.028420   \n",
      "118   ST-1132   1671  0.508079  22.239378  2535.781149  0.290245  0.027528   \n",
      "119   ST-1133    555  0.542342  21.657658  2220.882541  0.236036  0.054054   \n",
      "120   ST-1135   1530  0.607190  20.215686  2232.636170  0.257516  0.081046   \n",
      "121   ST-1136   2860  0.555594  28.894406  4115.404559  0.290559  0.027273   \n",
      "122   ST-1137   6355  0.669394  17.154524  1561.205791  0.259953  0.053186   \n",
      "123    ST-114   2822  0.619064  20.434444  2025.994784  0.255493  0.047838   \n",
      "124   ST-1140   1510  0.675497  16.352318  1770.802742  0.141722  0.039735   \n",
      "125   ST-1141   1141  0.663453  11.937774  1447.839833  0.127082  0.005259   \n",
      "126   ST-1142   3221  0.737349  12.432474  1415.808476  0.189382  0.062093   \n",
      "127   ST-1143    427  0.796253  14.297424  1875.409906  0.252927  0.199063   \n",
      "128   ST-1144    769  0.669701  16.396619  1761.320494  0.223667  0.057217   \n",
      "129   ST-1146   1146  0.586387  14.601222  2028.565314  0.189354  0.032286   \n",
      "130   ST-1147   1388  0.540346  14.694524  1852.000829  0.204611  0.011527   \n",
      "131   ST-1148    437  0.601831  29.151030  3356.255675  0.244851  0.034325   \n",
      "132   ST-1149   3183  0.632108  13.736726  1720.410474  0.085140  0.017279   \n",
      "133   ST-1150   3718  0.710059  26.958042  3292.252367  0.316030  0.077999   \n",
      "134   ST-1151   2396  0.596828  22.177379  2515.873222  0.240818  0.030467   \n",
      "135   ST-1152   2771  0.704439  21.083003  2430.353685  0.239986  0.052328   \n",
      "136   ST-1153    112  0.571429  24.401786  2890.046429  0.294643  0.089286   \n",
      "137   ST-1154    621  0.602254  16.380032  1964.016023  0.251208  0.127214   \n",
      "138   ST-1156    589  0.516129  19.921902  2053.219525  0.312394  0.057725   \n",
      "139   ST-1158   1327  0.675207  28.834213  2710.231010  0.238131  0.027129   \n",
      "140    ST-116   1936  0.676653  17.768079  1779.244540  0.180785  0.011364   \n",
      "141   ST-1160   1882  0.665250  22.785866  2588.801913  0.231668  0.081296   \n",
      "142   ST-1161    598  0.561873  26.498328  2801.054465  0.188963  0.070234   \n",
      "143   ST-1162    596  0.498322  25.879195  3209.117819  0.285235  0.016779   \n",
      "144   ST-1163   1371  0.641867  26.277899  2767.285988  0.212254  0.037199   \n",
      "145   ST-1164    855  0.683041  28.208187  3441.749427  0.188304  0.036257   \n",
      "146   ST-1165   1187  0.605729  22.728728  2622.783454  0.224094  0.021061   \n",
      "147   ST-1166   2552  0.661050  17.622649  2016.343523  0.153213  0.016066   \n",
      "148   ST-1167    143  0.587413  24.790210  3067.858531  0.181818  0.006993   \n",
      "149   ST-1168   1576  0.592005  28.174492  3581.595057  0.274112  0.030457   \n",
      "150   ST-1169   1786  0.643337  29.842105  3990.740817  0.236282  0.049272   \n",
      "151    ST-117   1803  0.680532  20.404881  2068.360238  0.246811  0.031059   \n",
      "152   ST-1171   1445  0.632526  33.070588  3513.469488  0.274048  0.089273   \n",
      "153   ST-1172    613  0.727569  26.061990  2989.834095  0.230016  0.117455   \n",
      "154   ST-1173    879  0.642776  23.769056  3101.743003  0.167235  0.084187   \n",
      "155   ST-1174   1258  0.674086  36.511924  4270.344086  0.248808  0.124006   \n",
      "156   ST-1177    890  0.621348  18.125843  2066.816798  0.238202  0.056180   \n",
      "157   ST-1178   2300  0.721739  27.421304  2813.762561  0.184348  0.051304   \n",
      "158   ST-1179    734  0.675749  24.465940  2395.337357  0.277929  0.039510   \n",
      "159    ST-118   4253  0.613684  20.500353  2071.649979  0.252998  0.023748   \n",
      "160   ST-1180    677  0.608567  22.849335  2786.622762  0.209749  0.048744   \n",
      "161   ST-1181   1731  0.616407  29.139804  3354.262282  0.279607  0.030040   \n",
      "162   ST-1182   1248  0.706731  25.733173  3325.230986  0.281250  0.041667   \n",
      "163   ST-1184   2171  0.654998  21.248733  2658.103620  0.210502  0.021649   \n",
      "164   ST-1185    752  0.679521  17.087766  2583.411396  0.252660  0.018617   \n",
      "165   ST-1186   4579  0.716095  23.215768  3107.442804  0.231492  0.032103   \n",
      "166   ST-1188    359  0.635097  19.835655  2459.245125  0.295265  0.083565   \n",
      "167   ST-1189    631  0.477021  25.177496  3158.183170  0.213946  0.020602   \n",
      "168    ST-119   4872  0.668309  19.033662  1773.091121  0.146141  0.015599   \n",
      "169   ST-1190   1858  0.514532  20.266416  2292.608326  0.268568  0.052207   \n",
      "170   ST-1191   3680  0.567120  22.569565  2370.896601  0.247011  0.076902   \n",
      "171   ST-1192   2012  0.546720  13.868290  1704.157043  0.225149  0.046720   \n",
      "172   ST-1193   1433  0.576413  17.553385  1860.902742  0.249128  0.060014   \n",
      "173   ST-1194   5972  0.589920  16.874749  1708.040198  0.250000  0.058272   \n",
      "174   ST-1195   6198  0.630042  37.381736  5622.197331  0.321071  0.030494   \n",
      "175   ST-1197   4227  0.606104  15.951975  1711.975117  0.252188  0.028152   \n",
      "176   ST-1198   5204  0.586472  17.559185  2031.106412  0.239239  0.076480   \n",
      "177   ST-1199   3320  0.475000  44.250602  3691.817789  0.475301  0.010542   \n",
      "178     ST-12   1682  0.530321  21.862069  2252.724174  0.233056  0.076694   \n",
      "179   ST-1200   2372  0.600337  21.911889  2964.714427  0.273187  0.064503   \n",
      "180   ST-1201   3274  0.604459  23.789554  2955.940031  0.295052  0.078497   \n",
      "181   ST-1202   2692  0.578380  18.307207  2189.489060  0.249257  0.033804   \n",
      "182   ST-1203   1945  0.624679  20.215938  2335.302329  0.258098  0.103342   \n",
      "183   ST-1204   1385  0.691697  19.203610  2466.583365  0.233213  0.037545   \n",
      "184   ST-1206    369  0.772358  17.653117  2051.293198  0.252033  0.043360   \n",
      "185   ST-1207   1343  0.690990  15.015637  1698.292144  0.283693  0.050633   \n",
      "186   ST-1208    792  0.734848  20.229798  2402.817917  0.268939  0.068182   \n",
      "187    ST-121   3943  0.700228  22.020289  2238.113759  0.139234  0.014202   \n",
      "188   ST-1210   1281  0.721311  17.760343  2066.324660  0.298985  0.093677   \n",
      "189   ST-1211    654  0.706422  21.755352  2087.114343  0.235474  0.076453   \n",
      "190   ST-1212    878  0.691344  17.717540  1863.238235  0.243736  0.058087   \n",
      "191   ST-1213   1340  0.614925  22.971642  3251.619866  0.294030  0.068657   \n",
      "192   ST-1215   3535  0.679208  18.200566  2125.594690  0.228289  0.077511   \n",
      "193   ST-1216    305  0.511475  18.832787  2347.881738  0.229508  0.019672   \n",
      "194   ST-1217    387  0.764858  19.488372  3050.785168  0.284238  0.227390   \n",
      "195   ST-1218   2400  0.750000  18.035833  2108.616071  0.230000  0.037917   \n",
      "196   ST-1219   3399  0.745513  16.415711  2216.939503  0.210062  0.025596   \n",
      "197   ST-1220   3105  0.653462  20.847343  2488.483961  0.242512  0.047665   \n",
      "198   ST-1221   2740  0.632482  21.060584  2270.747602  0.219343  0.017153   \n",
      "199   ST-1222   2207  0.645220  17.060716  2090.559470  0.257363  0.070684   \n",
      "200   ST-1223   9854  0.660645  17.839761  2218.154577  0.240714  0.006393   \n",
      "201   ST-1224   2682  0.721849  17.469053  1789.674579  0.113721  0.022744   \n",
      "202   ST-1226   4011  0.674894  17.730491  2153.198018  0.228621  0.032660   \n",
      "203   ST-1227   1968  0.671748  19.765244  2358.961214  0.300813  0.033028   \n",
      "204   ST-1228   3219  0.684685  19.341410  2672.177335  0.223983  0.036968   \n",
      "205   ST-1229    922  0.584599  18.155098  2138.218297  0.224512  0.023861   \n",
      "206    ST-123   1888  0.704979  20.916314  2120.844815  0.181144  0.033898   \n",
      "207   ST-1230    753  0.772908  14.455511  1863.088486  0.278884  0.126162   \n",
      "208   ST-1231    336  0.755952  24.416667  3187.396071  0.211310  0.032738   \n",
      "209   ST-1233    395  0.741772  17.584810  2418.080101  0.202532  0.144304   \n",
      "210   ST-1235    905  0.648619  14.138122  1688.768287  0.248619  0.056354   \n",
      "211   ST-1236   2559  0.691286  19.160610  2268.380145  0.257913  0.062134   \n",
      "212   ST-1237   2810  0.692527  20.400000  2320.948915  0.245552  0.028470   \n",
      "213   ST-1238   1241  0.780822  21.576954  2057.391958  0.198227  0.089444   \n",
      "214   ST-1239   3639  0.744985  10.508656  1412.256980  0.194559  0.023083   \n",
      "215    ST-124   4710  0.754565  17.878344  1825.415115  0.101699  0.014013   \n",
      "216   ST-1241    518  0.669884  17.835907  2107.448861  0.191120  0.077220   \n",
      "217   ST-1243   1314  0.700152  18.422374  2737.817884  0.226788  0.037291   \n",
      "218   ST-1245    642  0.730530  24.130841  2678.868551  0.221184  0.077882   \n",
      "219   ST-1246    861  0.695703  24.782811  3193.397085  0.239257  0.078978   \n",
      "220   ST-1247    828  0.731884  26.368357  2320.820942  0.229469  0.055556   \n",
      "221   ST-1248    456  0.758772  34.570175  3331.034978  0.280702  0.140351   \n",
      "222   ST-1249   7275  0.614983  16.725361  1723.481446  0.244536  0.035739   \n",
      "223    ST-125   1124  0.702847  20.552491  2095.903665  0.128114  0.016904   \n",
      "224   ST-1250   1268  0.692429  17.152208  1908.498265  0.167192  0.016562   \n",
      "225   ST-1251  10339  0.600445  15.080472  1708.168325  0.227391  0.031531   \n",
      "226   ST-1252    868  0.697005  14.366359  1630.874735  0.167051  0.014977   \n",
      "227   ST-1253   5341  0.587530  10.330462  1153.954020  0.243587  0.018536   \n",
      "228   ST-1254   5645  0.663419  13.166342  1360.599708  0.246590  0.038441   \n",
      "229   ST-1259   3520  0.595739  19.021591  2167.140506  0.251705  0.116477   \n",
      "230    ST-126   2621  0.682564  22.457459  2686.550149  0.156429  0.008775   \n",
      "231   ST-1260    487  0.591376  22.607803  2691.566756  0.277207  0.092402   \n",
      "232   ST-1262    972  0.580247  22.306584  2550.786739  0.280864  0.104938   \n",
      "233   ST-1263   8477  0.608116  17.234281  1957.062178  0.239589  0.036923   \n",
      "234   ST-1264   2366  0.618343  18.035926  1931.783178  0.278107  0.095097   \n",
      "235   ST-1265   2123  0.658031  17.389543  1897.454249  0.276496  0.081959   \n",
      "236   ST-1266   3271  0.613574  26.042189  3045.158423  0.262611  0.075206   \n",
      "237   ST-1267    823  0.732685  25.334143  3291.074070  0.330498  0.021871   \n",
      "238   ST-1268   5680  0.648944  22.920775  2586.963039  0.271127  0.061444   \n",
      "239   ST-1269   1294  0.680835  21.035549  2409.153532  0.271252  0.097372   \n",
      "240   ST-1270   2810  0.674377  23.136299  2382.512527  0.259786  0.165480   \n",
      "241   ST-1271   1509  0.611001  16.195494  1812.585898  0.259775  0.046388   \n",
      "242   ST-1273   1578  0.700887  20.761090  2383.951248  0.274398  0.130545   \n",
      "243   ST-1274   2592  0.693673  19.795910  2167.221848  0.205247  0.042824   \n",
      "244   ST-1275   6477  0.659565  17.482631  2028.586647  0.262930  0.036128   \n",
      "245   ST-1276   1031  0.699321  17.540252  2021.299767  0.133851  0.059166   \n",
      "246   ST-1277    604  0.791391  17.706954  2013.560679  0.125828  0.051325   \n",
      "247   ST-1278   3016  0.598143  21.468170  2484.282321  0.264589  0.042772   \n",
      "248   ST-1279   4788  0.586884  22.746867  2429.207957  0.306182  0.047410   \n",
      "249   ST-1280   5537  0.704714  18.108904  2364.417347  0.206791  0.047499   \n",
      "250   ST-1281    447  0.619687  21.192394  2309.931320  0.328859  0.078300   \n",
      "251   ST-1282   2801  0.704034  16.544805  1987.019704  0.278829  0.034273   \n",
      "252   ST-1283   1471  0.683889  17.583277  2394.721224  0.247451  0.062542   \n",
      "253   ST-1284   2957  0.609063  16.998647  1973.534954  0.236388  0.041934   \n",
      "254   ST-1285   5032  0.633545  17.540143  1942.812077  0.273450  0.026033   \n",
      "255   ST-1286   3981  0.604873  17.695303  1831.609256  0.237378  0.065059   \n",
      "256   ST-1287   2751  0.589967  18.338059  2054.048437  0.200654  0.062886   \n",
      "257   ST-1288   1421  0.660099  21.714989  2657.699254  0.182266  0.026742   \n",
      "258   ST-1289   1285  0.559533  20.403891  2959.139650  0.282490  0.075486   \n",
      "259   ST-1291   5204  0.590892  22.616641  2435.647936  0.235780  0.030553   \n",
      "260   ST-1292   1484  0.508760  20.487197  2343.366301  0.211590  0.012129   \n",
      "261   ST-1293    800  0.671250  22.402500  2740.620388  0.292500  0.030000   \n",
      "262   ST-1295   1194  0.757956  17.494975  2109.565251  0.214405  0.091290   \n",
      "263   ST-1296   1840  0.647283  18.636957  2146.651793  0.275543  0.067391   \n",
      "264   ST-1297   1034  0.470986  23.968085  2967.246025  0.266925  0.037718   \n",
      "265   ST-1298   2042  0.663075  17.331048  1911.393624  0.248776  0.049951   \n",
      "266   ST-1299   1967  0.679207  22.095577  2002.349654  0.217082  0.048805   \n",
      "267    ST-130   1754  0.596351  24.425314  1994.376591  0.316420  0.006271   \n",
      "268   ST-1300   5705  0.622086  20.882033  2101.468924  0.242594  0.045223   \n",
      "269   ST-1302   2381  0.591348  24.032759  3176.374481  0.298614  0.097438   \n",
      "270   ST-1305   2799  0.732404  25.994284  2432.848146  0.195784  0.041086   \n",
      "271   ST-1306    871  0.644087  21.861079  2295.644179  0.211251  0.017222   \n",
      "272   ST-1307    678  0.626844  21.749263  2124.992389  0.219764  0.081121   \n",
      "273   ST-1309    456  0.631579  14.092105  1586.872763  0.212719  0.105263   \n",
      "274   ST-1310    312  0.727564  15.548077  2193.217212  0.205128  0.041667   \n",
      "275   ST-1311    630  0.593651  31.476190  4191.489159  0.279365  0.025397   \n",
      "276   ST-1312     38  0.631579  23.157895  2874.690789  0.289474  0.368421   \n",
      "277   ST-1313     67  0.716418  19.910448  2530.448358  0.223881  0.044776   \n",
      "278   ST-1314     72  0.583333  20.208333  2892.218750  0.180556  0.055556   \n",
      "279   ST-1315    163  0.840491  20.588957  2854.023681  0.202454  0.079755   \n",
      "280   ST-1317   4109  0.676077  19.337065  1955.076554  0.192748  0.039912   \n",
      "281    ST-132   3646  0.675535  19.889468  2008.315277  0.166758  0.023039   \n",
      "282   ST-1320   5248  0.657774  17.972942  1895.629057  0.232279  0.049543   \n",
      "283   ST-1321   2953  0.650525  20.554690  2451.277199  0.241111  0.053166   \n",
      "284   ST-1323   4615  0.669122  21.230553  2780.322141  0.268256  0.058722   \n",
      "285   ST-1324    521  0.856046  19.107486  1966.127678  0.119002  0.001919   \n",
      "286   ST-1325   1791  0.667783  20.907314  2292.379162  0.282524  0.065885   \n",
      "287   ST-1326   3404  0.600470  29.553760  3910.293364  0.330787  0.052585   \n",
      "288   ST-1327    679  0.686303  16.888071  2512.480619  0.300442  0.011782   \n",
      "289   ST-1328    268  0.649254  27.884328  2511.765112  0.365672  0.067164   \n",
      "290   ST-1329   1330  0.689474  15.939098  1678.546639  0.300752  0.075940   \n",
      "291   ST-1331   3960  0.534091  20.636111  2422.702646  0.241414  0.059091   \n",
      "292   ST-1332   2500  0.601200  15.194000  1751.533792  0.266400  0.035600   \n",
      "293   ST-1333   3705  0.663428  20.746559  2711.901120  0.205938  0.024291   \n",
      "294   ST-1334   4037  0.609116  24.087689  3349.411573  0.286847  0.054991   \n",
      "295   ST-1335   4500  0.602889  30.842667  3932.837776  0.308222  0.035333   \n",
      "296   ST-1337   2830  0.616608  20.629682  2305.669438  0.281979  0.068198   \n",
      "297   ST-1338   2126  0.706021  12.733772  1309.973579  0.225776  0.025870   \n",
      "298   ST-1339   1940  0.622680  28.392784  3183.315773  0.258763  0.028866   \n",
      "299    ST-134   1696  0.714033  22.360849  2240.543101  0.149764  0.014151   \n",
      "300   ST-1341   3038  0.656682  20.232719  1973.239477  0.236011  0.048387   \n",
      "301   ST-1342   2628  0.671994  16.487062  1734.887272  0.230974  0.037671   \n",
      "302   ST-1343   1605  0.572586  37.996262  5459.141813  0.332710  0.024299   \n",
      "303   ST-1344   2407  0.517657  43.778563  6369.290320  0.311591  0.053594   \n",
      "304   ST-1345    288  0.704861  21.208333  2396.757187  0.267361  0.027778   \n",
      "305   ST-1346   1723  0.668021  16.041788  1794.380424  0.247243  0.121300   \n",
      "306   ST-1347   4850  0.587835  24.850309  3504.064728  0.306804  0.064330   \n",
      "307   ST-1348    464  0.691810  15.903017  1581.889741  0.140086  0.008621   \n",
      "308   ST-1349   2860  0.529720  23.475874  3100.380535  0.294755  0.021329   \n",
      "309   ST-1350   2569  0.572207  22.599455  2965.164173  0.195018  0.016738   \n",
      "310   ST-1351   7698  0.598467  16.427903  1637.772616  0.242660  0.034295   \n",
      "311   ST-1352   6979  0.538616  11.373406  1278.228647  0.244304  0.023212   \n",
      "312   ST-1353   2779  0.620727  16.497661  1924.495707  0.263044  0.066931   \n",
      "313   ST-1355     63  0.777778  18.444444  2183.338095  0.412698  0.079365   \n",
      "314   ST-1356    922  0.599783  17.595445  1919.295586  0.164859  0.016269   \n",
      "315   ST-1357   3519  0.577721  23.651890  3128.517096  0.287582  0.042626   \n",
      "316    ST-136   2228  0.738330  26.028725  2517.103658  0.127469  0.010323   \n",
      "317   ST-1360   1485  0.690909  19.783165  2239.239044  0.186532  0.030303   \n",
      "318   ST-1361   2827  0.711709  22.063672  2360.300141  0.205164  0.042448   \n",
      "319   ST-1364   3065  0.578140  18.622186  2491.834225  0.236542  0.063622   \n",
      "320   ST-1365    904  0.675885  24.949115  2822.665022  0.243363  0.087389   \n",
      "321   ST-1366    575  0.624348  26.446957  2885.239357  0.234783  0.043478   \n",
      "322   ST-1367   1114  0.642729  23.125673  2655.024336  0.261221  0.011670   \n",
      "323    ST-137   1784  0.693946  28.883408  2565.823027  0.197870  0.029709   \n",
      "324   ST-1370    130  0.761538  19.415385  1784.324538  0.207692  0.069231   \n",
      "325   ST-1371   1085  0.546544  19.903226  1975.707097  0.261751  0.047005   \n",
      "326   ST-1372   4204  0.529020  25.097764  2334.431665  0.155804  0.021646   \n",
      "327   ST-1373   1963  0.724911  17.431482  1952.360092  0.149771  0.013245   \n",
      "328   ST-1374   2125  0.693176  16.478588  1968.286800  0.256000  0.051294   \n",
      "329   ST-1375   4463  0.613713  15.644858  1780.828949  0.242214  0.040332   \n",
      "330   ST-1376   3018  0.730948  20.933400  2271.121471  0.233930  0.062624   \n",
      "331   ST-1378   5462  0.598316  16.400220  1764.259226  0.228671  0.056573   \n",
      "332   ST-1379    604  0.658940  20.221854  2128.184189  0.283113  0.100993   \n",
      "333    ST-138    779  0.722721  23.955071  2276.525366  0.256739  0.005135   \n",
      "334   ST-1380   2410  0.719917  18.849378  2027.571905  0.283402  0.097925   \n",
      "335   ST-1381   1066  0.647280  17.814259  1959.002129  0.228893  0.074109   \n",
      "336   ST-1383    517  0.787234  23.667311  2924.624178  0.324952  0.147002   \n",
      "337   ST-1384   1151  0.735013  21.944396  2732.575352  0.294526  0.129453   \n",
      "338   ST-1386   1089  0.748393  20.852158  2583.808613  0.236915  0.132231   \n",
      "339   ST-1387   1016  0.635827  26.195866  3782.419400  0.355315  0.039370   \n",
      "340   ST-1388    420  0.490476  24.428571  2774.399286  0.292857  0.085714   \n",
      "341   ST-1389   1322  0.528744  24.670953  2591.711641  0.278366  0.048411   \n",
      "342   ST-1390   1863  0.645196  19.319914  1859.588164  0.272678  0.069780   \n",
      "343   ST-1391    384  0.750000  20.739583  1875.521979  0.281250  0.062500   \n",
      "344   ST-1392    629  0.775835  22.745628  2508.010731  0.278219  0.087440   \n",
      "345   ST-1394    705  0.529078  22.774468  1974.998071  0.164539  0.024113   \n",
      "346   ST-1395    791  0.725664  24.958281  3562.536296  0.173198  0.069532   \n",
      "347   ST-1396    166  0.680723  26.000000  4033.812892  0.144578  0.030120   \n",
      "348   ST-1397   2573  0.643995  19.718228  2266.619254  0.248348  0.035756   \n",
      "349   ST-1398   1668  0.686451  17.715228  2081.343016  0.288969  0.067746   \n",
      "350    ST-140   1530  0.694771  26.747059  2799.329039  0.220915  0.023529   \n",
      "351   ST-1400   2045  0.668949  20.725672  2522.151267  0.243521  0.037164   \n",
      "352   ST-1402   2665  0.560225  13.079925  1451.030589  0.228893  0.045403   \n",
      "353   ST-1403   6092  0.759849  17.309258  2298.317896  0.134110  0.013296   \n",
      "354   ST-1404   1186  0.684654  21.913153  2509.551492  0.206577  0.035413   \n",
      "355   ST-1406   1301  0.622598  21.936972  2135.224504  0.194466  0.025365   \n",
      "356   ST-1407   1341  0.673378  20.136465  2514.481186  0.281133  0.126025   \n",
      "357   ST-1408   1304  0.619632  24.750767  2839.603811  0.256902  0.053681   \n",
      "358   ST-1409   3531  0.631266  23.237893  2376.456389  0.226848  0.043047   \n",
      "359   ST-1410    484  0.652893  17.514463  2362.497087  0.233471  0.035124   \n",
      "360   ST-1411    789  0.628644  24.456274  2730.265944  0.254753  0.051965   \n",
      "361   ST-1413   2783  0.608696  24.053899  3064.106213  0.255839  0.061085   \n",
      "362   ST-1414    288  0.565972  19.899306  1998.548056  0.236111  0.065972   \n",
      "363   ST-1416    793  0.727617  20.071879  2321.972963  0.245902  0.056747   \n",
      "364   ST-1417   1709  0.609128  20.459333  2602.000690  0.301931  0.067876   \n",
      "365   ST-1418    730  0.682192  21.272603  2260.299849  0.264384  0.057534   \n",
      "366   ST-1419   1705  0.608798  17.935484  1995.773977  0.284457  0.076246   \n",
      "367    ST-142   2648  0.694864  19.780211  2082.671507  0.177870  0.014728   \n",
      "368   ST-1420   7596  0.611901  16.560953  1704.521496  0.251053  0.057662   \n",
      "369   ST-1421   2297  0.688724  22.854593  2792.127423  0.263822  0.041794   \n",
      "370   ST-1422    979  0.595506  23.249234  2491.592594  0.260470  0.013279   \n",
      "371   ST-1423   1115  0.707623  21.213453  2436.637166  0.247534  0.097758   \n",
      "372   ST-1424   1733  0.620889  16.112522  2108.564686  0.227351  0.065782   \n",
      "373   ST-1425   2743  0.607364  16.605177  2080.454287  0.260299  0.045935   \n",
      "374   ST-1426   1017  0.652901  22.127827  2076.725644  0.278269  0.036382   \n",
      "375   ST-1427   1075  0.571163  19.080930  2290.061172  0.275349  0.120000   \n",
      "376   ST-1428    253  0.671937  16.158103  1503.812016  0.177866  0.031621   \n",
      "377   ST-1429   2166  0.706371  14.831025  1353.293717  0.088181  0.006002   \n",
      "378    ST-143   2524  0.702060  19.233756  1863.164699  0.226228  0.041997   \n",
      "379   ST-1432    881  0.643587  21.414302  2330.577639  0.271283  0.040863   \n",
      "380   ST-1433    954  0.697065  23.349057  2759.556268  0.237945  0.035639   \n",
      "381   ST-1434    471  0.675159  18.594480  2335.212548  0.195329  0.040340   \n",
      "382   ST-1435   2786  0.689519  22.298995  2387.098945  0.243001  0.028356   \n",
      "383   ST-1436   1452  0.729339  16.384298  2132.200888  0.226584  0.049587   \n",
      "384   ST-1437   1143  0.687664  33.789151  2103.086789  0.164479  0.021872   \n",
      "385   ST-1438    258  0.790698  17.724806  1974.424341  0.267442  0.077519   \n",
      "386   ST-1439   1478  0.627199  21.067659  2067.325318  0.232070  0.046008   \n",
      "387    ST-144   1502  0.685752  21.533955  2298.822144  0.256991  0.059920   \n",
      "388   ST-1440   6123  0.599869  20.466765  2479.503092  0.251184  0.125102   \n",
      "389   ST-1441   1527  0.602489  34.693517  5136.122207  0.281598  0.056974   \n",
      "390   ST-1442    748  0.624332  23.627005  2255.384933  0.272727  0.048128   \n",
      "391   ST-1443   3662  0.661114  25.641453  3359.152414  0.230475  0.029219   \n",
      "392   ST-1445    644  0.658385  25.319876  3284.745543  0.324534  0.059006   \n",
      "393   ST-1446   1929  0.641783  26.455677  3190.137963  0.288751  0.062208   \n",
      "394   ST-1447   1446  0.719225  25.515906  3527.408492  0.230290  0.024205   \n",
      "395   ST-1449   1371  0.725018  18.940190  1972.387987  0.286652  0.084610   \n",
      "396    ST-145   2705  0.618484  23.089464  2453.782717  0.217745  0.029205   \n",
      "397   ST-1451   4201  0.632468  15.884551  1876.712461  0.274935  0.064032   \n",
      "398   ST-1452    466  0.759657  24.223176  3104.603498  0.315451  0.128755   \n",
      "399   ST-1454   2673  0.653947  18.964834  2165.549031  0.254770  0.069211   \n",
      "400   ST-1455   3620  0.634254  17.063536  2127.608633  0.268508  0.051657   \n",
      "401   ST-1456   1457  0.610158  16.322581  2136.428332  0.297186  0.083734   \n",
      "402   ST-1457    496  0.659274  16.495968  2063.609577  0.270161  0.026210   \n",
      "403   ST-1458    486  0.508230  22.269547  2714.107593  0.255144  0.043210   \n",
      "404   ST-1459    793  0.558638  15.279950  1582.625687  0.242119  0.045397   \n",
      "405   ST-1460   1586  0.505044  23.930643  2572.765530  0.253468  0.031526   \n",
      "406   ST-1461   1775  0.680563  19.233239  2291.835758  0.328451  0.079437   \n",
      "407   ST-1462    422  0.703791  22.824645  3045.942275  0.286730  0.059242   \n",
      "408   ST-1463    432  0.712963  26.391204  3101.123264  0.319444  0.034722   \n",
      "409   ST-1464   1203  0.698254  20.424771  2084.982984  0.253533  0.087282   \n",
      "410   ST-1465   1288  0.670807  19.329969  2189.206421  0.268634  0.104814   \n",
      "411   ST-1466   1262  0.636292  19.492868  2267.597750  0.272583  0.061807   \n",
      "412   ST-1467   1681  0.619274  22.016062  2259.358084  0.277216  0.080309   \n",
      "413   ST-1468    987  0.643364  18.950355  2025.831692  0.279635  0.030395   \n",
      "414   ST-1469   2903  0.661385  23.137788  2993.475529  0.263865  0.092663   \n",
      "415    ST-147   1492  0.745308  21.769437  2254.640402  0.101877  0.012064   \n",
      "416   ST-1470   2603  0.586631  19.141375  2304.255367  0.229351  0.044948   \n",
      "417   ST-1473   3617  0.647774  18.060547  2095.902275  0.223666  0.067736   \n",
      "418   ST-1474   6540  0.608869  19.198624  2219.610318  0.257492  0.080734   \n",
      "419   ST-1475   2566  0.723694  16.909587  2107.142966  0.249415  0.043648   \n",
      "420   ST-1476   2978  0.607790  20.703828  2355.010850  0.279046  0.084956   \n",
      "421   ST-1479   2221  0.665916  16.016659  1789.040941  0.263845  0.058532   \n",
      "422    ST-148   1278  0.691706  21.061033  2090.425430  0.139280  0.015649   \n",
      "423   ST-1480    454  0.640969  33.605727  3917.254251  0.363436  0.158590   \n",
      "424   ST-1481   1256  0.717357  13.144904  1586.657707  0.203822  0.050159   \n",
      "425   ST-1482   2576  0.668090  20.633540  2174.235524  0.277950  0.075311   \n",
      "426   ST-1483   1840  0.640761  17.257065  1838.703701  0.325543  0.059783   \n",
      "427   ST-1484   1490  0.647651  19.052349  1865.010188  0.308054  0.052349   \n",
      "428   ST-1485    690  0.672464  16.456522  1809.317406  0.255072  0.127536   \n",
      "429   ST-1486    804  0.741294  16.324627  2002.640386  0.264925  0.048507   \n",
      "430   ST-1487    324  0.592593  28.320988  1917.918951  0.416667  0.012346   \n",
      "431   ST-1488    593  0.590219  24.229342  2478.521197  0.295110  0.065767   \n",
      "432   ST-1489    184  0.771739  10.510870  1547.943424  0.309783  0.021739   \n",
      "433   ST-1490    250  0.864000  19.116000  1894.943640  0.216000  0.016000   \n",
      "434   ST-1491   1889  0.686077  28.459502  3366.321662  0.257808  0.093700   \n",
      "435   ST-1492   1354  0.618907  17.111521  2009.865251  0.256278  0.077548   \n",
      "436   ST-1493    646  0.551084  18.291022  2224.518483  0.258514  0.043344   \n",
      "437   ST-1494    613  0.574225  22.481240  2033.812953  0.243067  0.029364   \n",
      "438   ST-1495   3649  0.640723  16.308304  1664.609830  0.325295  0.031790   \n",
      "439   ST-1496   5700  0.624737  19.376140  1858.026212  0.270175  0.034561   \n",
      "440   ST-1497   2642  0.627555  20.580999  2328.944557  0.309235  0.035958   \n",
      "441   ST-1498   1296  0.747685  18.910494  2179.929182  0.243827  0.035494   \n",
      "442   ST-1499   2240  0.669643  15.928571  1822.587960  0.307143  0.038393   \n",
      "443     ST-15   1310  0.607634  32.538931  3909.020870  0.356489  0.083206   \n",
      "444    ST-150   2643  0.692773  21.087779  1979.798131  0.204313  0.050322   \n",
      "445   ST-1500   1559  0.684413  18.201411  2388.473085  0.268121  0.035920   \n",
      "446   ST-1501   1024  0.710938  20.549805  2456.970361  0.234375  0.058594   \n",
      "447   ST-1503    941  0.646121  28.676939  3351.104176  0.293305  0.049947   \n",
      "448   ST-1504   2363  0.632670  15.487093  1584.178963  0.292848  0.033009   \n",
      "449   ST-1506   4664  0.746355  15.362350  1851.739981  0.207333  0.026587   \n",
      "450   ST-1507   1553  0.637476  20.657437  2338.256291  0.251127  0.043786   \n",
      "451   ST-1508   1884  0.613057  18.980361  2157.403546  0.274416  0.054140   \n",
      "452   ST-1509   3098  0.602324  19.522918  2299.129383  0.224015  0.039380   \n",
      "453    ST-151   1883  0.711099  22.121083  2116.130765  0.178439  0.044610   \n",
      "454   ST-1510   5427  0.573429  14.674774  1670.178006  0.248756  0.077575   \n",
      "455   ST-1511   2530  0.526877  14.052964  1689.767941  0.202372  0.019368   \n",
      "456   ST-1512   2492  0.640449  15.240770  1788.166481  0.204254  0.035714   \n",
      "457   ST-1514   3698  0.558951  13.453759  1586.976677  0.198486  0.029475   \n",
      "458   ST-1515   1962  0.765545  17.408767  1881.692176  0.226300  0.069827   \n",
      "459   ST-1517   4831  0.566342  12.499897  1336.801898  0.204513  0.034775   \n",
      "460   ST-1518    586  0.747440  16.428328  2091.578038  0.075085  0.129693   \n",
      "461   ST-1519   5450  0.521651  15.226789  1687.829602  0.185505  0.027890   \n",
      "462    ST-152   2205  0.700680  22.883900  2208.688830  0.176871  0.039456   \n",
      "463   ST-1520   1029  0.844509  17.190476  2125.123936  0.201166  0.011662   \n",
      "464   ST-1521   6133  0.618621  24.026904  2835.957062  0.131420  0.019892   \n",
      "465   ST-1522   1790  0.702793  30.896089  4744.812374  0.259218  0.061453   \n",
      "466   ST-1523   3587  0.630332  19.454419  2509.098893  0.240591  0.039866   \n",
      "467   ST-1526   2539  0.671524  19.967704  2419.519527  0.287121  0.108704   \n",
      "468   ST-1527   1030  0.737864  13.007767  1699.012427  0.262136  0.061165   \n",
      "469   ST-1528   1119  0.594281  12.932082  1457.884799  0.241287  0.029491   \n",
      "470   ST-1529   3022  0.632694  15.536400  1841.047310  0.259431  0.041363   \n",
      "471    ST-153   1433  0.590370  15.294487  1704.947202  0.240754  0.030007   \n",
      "472   ST-1531   3578  0.628843  30.631079  4641.282714  0.264952  0.014254   \n",
      "473   ST-1534    892  0.617713  15.687220  1726.617096  0.201794  0.033632   \n",
      "474   ST-1535   1395  0.718996  14.281720  1760.615297  0.179928  0.030108   \n",
      "475   ST-1536    426  0.875587  27.903756  3268.893685  0.218310  0.140845   \n",
      "476   ST-1537   1393  0.712132  21.316583  2222.789462  0.290022  0.027997   \n",
      "477   ST-1538    432  0.650463  18.546296  2248.209954  0.215278  0.023148   \n",
      "478   ST-1539   4567  0.683819  16.469017  1673.869170  0.241953  0.051675   \n",
      "479    ST-154   1144  0.647727  21.826923  1817.262107  0.186189  0.040210   \n",
      "480   ST-1540   1833  0.708129  24.107474  3027.695565  0.279324  0.043099   \n",
      "481   ST-1541   1693  0.593030  22.531010  2122.913503  0.239811  0.089191   \n",
      "482   ST-1542   1756  0.625285  17.463554  2065.794072  0.261959  0.044419   \n",
      "483   ST-1543   3156  0.629278  23.288023  2638.843565  0.284537  0.046895   \n",
      "484   ST-1544    188  0.734043  15.909574  1662.686649  0.196809  0.058511   \n",
      "485   ST-1545   2644  0.704614  27.965204  3693.916161  0.308623  0.048033   \n",
      "486   ST-1546  12473  0.650766  20.811272  2362.459600  0.266255  0.031187   \n",
      "487   ST-1547    785  0.751592  19.871338  2834.606115  0.273885  0.026752   \n",
      "488   ST-1548   2238  0.577748  18.104111  2005.052927  0.279714  0.075961   \n",
      "489    ST-155   2287  0.682991  25.048972  1699.258312  0.184521  0.027984   \n",
      "490   ST-1552    734  0.574932  21.408719  3091.584959  0.258856  0.046322   \n",
      "491   ST-1553    918  0.659041  22.610022  2468.615991  0.242919  0.035948   \n",
      "492   ST-1554   1738  0.653049  21.569620  2727.064350  0.205984  0.060990   \n",
      "493   ST-1555   1704  0.666667  27.110915  3203.208844  0.289319  0.091549   \n",
      "494   ST-1556   2954  0.728165  29.866283  2501.315105  0.186527  0.037576   \n",
      "495   ST-1557    168  0.750000  20.440476  2079.906607  0.363095  0.053571   \n",
      "496   ST-1559   1548  0.678941  23.485788  2682.896977  0.288760  0.096899   \n",
      "497    ST-156   2676  0.618087  15.628550  1786.628479  0.255605  0.106502   \n",
      "498   ST-1560    558  0.693548  21.322581  2633.222061  0.267025  0.145161   \n",
      "499   ST-1561     18  0.611111  16.055556  2419.310000  0.277778  0.055556   \n",
      "500   ST-1562    194  0.577320  13.118557  2031.338351  0.319588  0.067010   \n",
      "501   ST-1563    161  0.633540  18.639752  2243.300745  0.204969  0.062112   \n",
      "502   ST-1564   1529  0.738391  17.488555  2191.978855  0.221060  0.047744   \n",
      "503   ST-1565     84  0.809524  18.702381  1640.210595  0.297619  0.035714   \n",
      "504   ST-1566    716  0.548883  32.877095  4407.557346  0.349162  0.048883   \n",
      "505   ST-1568    552  0.606884  20.117754  2321.453080  0.173913  0.061594   \n",
      "506    ST-157   2649  0.658362  17.579464  1625.972118  0.219706  0.035485   \n",
      "507   ST-1571    583  0.668954  22.600343  2765.943345  0.255575  0.073756   \n",
      "508   ST-1573   1957  0.599898  23.968830  2844.648406  0.302504  0.055697   \n",
      "509   ST-1574   2930  0.644027  25.418089  3326.482495  0.282935  0.049147   \n",
      "510   ST-1575   1745  0.677937  21.413754  2769.878229  0.173066  0.021203   \n",
      "511   ST-1576    539  0.643785  29.912801  3540.165269  0.205937  0.070501   \n",
      "512   ST-1577   2472  0.745550  26.324838  2737.286076  0.215210  0.082120   \n",
      "513   ST-1578   1305  0.523372  17.876628  1994.663732  0.215326  0.032184   \n",
      "514   ST-1579   1223  0.556827  24.107931  2922.702600  0.273917  0.080948   \n",
      "515    ST-158   4475  0.584358  17.521341  1886.590561  0.238436  0.046927   \n",
      "516   ST-1580   2619  0.630011  18.561665  1957.901260  0.126766  0.010691   \n",
      "517   ST-1582   4877  0.517736  18.645274  1804.747564  0.277220  0.048595   \n",
      "518   ST-1584   7238  0.559409  24.509533  2567.870771  0.262503  0.017823   \n",
      "519   ST-1585   1412  0.521246  18.480878  1883.675581  0.303116  0.027620   \n",
      "520   ST-1586   5284  0.517033  21.183952  2080.342916  0.323808  0.027631   \n",
      "521   ST-1588    934  0.664882  19.458244  2157.557966  0.239829  0.036403   \n",
      "522   ST-1589   1223  0.689289  23.053148  2773.370760  0.254293  0.088307   \n",
      "523    ST-159   2064  0.722384  17.139050  1629.944767  0.194767  0.053779   \n",
      "524   ST-1590   3981  0.548857  18.360211  1890.275931  0.307209  0.047224   \n",
      "525   ST-1592   1543  0.544394  17.619572  1797.499119  0.252106  0.029812   \n",
      "526   ST-1593     32  0.687500  15.781250  1759.193438  0.093750  0.000000   \n",
      "527   ST-1594    611  0.649755  24.386252  2407.164632  0.207856  0.022913   \n",
      "528   ST-1595    597  0.730318  22.189280  2060.479129  0.276382  0.020101   \n",
      "529   ST-1597    719  0.520167  25.235049  2604.455577  0.233658  0.027816   \n",
      "530   ST-1598   1220  0.476230  25.353279  2087.593377  0.187705  0.013115   \n",
      "531   ST-1599   1136  0.588028  34.081866  4353.406664  0.262324  0.062500   \n",
      "532     ST-16   2177  0.654111  29.108865  3211.692393  0.300873  0.106109   \n",
      "533    ST-160   2962  0.773464  13.380824  1561.779483  0.211681  0.055706   \n",
      "534   ST-1601     29  0.793103  19.827586  2113.989310  0.344828  0.034483   \n",
      "535   ST-1602   2241  0.573405  32.231593  4282.160986  0.328425  0.012941   \n",
      "536   ST-1603   1423  0.567112  21.819396  2190.852741  0.309909  0.028812   \n",
      "537   ST-1605   1554  0.694981  26.828185  1955.664028  0.182754  0.055985   \n",
      "538   ST-1606   2396  0.689900  21.233723  1960.016461  0.222871  0.043406   \n",
      "539   ST-1607   2137  0.722040  21.653720  2168.513800  0.212447  0.066448   \n",
      "540   ST-1608   2022  0.795747  26.306627  2317.727186  0.138477  0.030168   \n",
      "541   ST-1609   3149  0.610035  17.224198  1749.736729  0.264846  0.115275   \n",
      "542    ST-161   2356  0.685908  19.126061  1655.901689  0.109932  0.009762   \n",
      "543   ST-1610   2047  0.691744  22.141182  1715.526009  0.158769  0.029800   \n",
      "544   ST-1611   5060  0.645455  22.530040  2595.783818  0.210079  0.015415   \n",
      "545   ST-1615    888  0.759009  21.171171  2315.466351  0.197072  0.021396   \n",
      "546   ST-1616    496  0.820565  12.116935  1523.419819  0.235887  0.151210   \n",
      "547   ST-1617    430  0.732558  24.253488  3014.471442  0.281395  0.113953   \n",
      "548   ST-1618    337  0.786350  15.139466  1717.745846  0.186944  0.020772   \n",
      "549   ST-1619   1619  0.661519  19.032736  2005.069981  0.169858  0.016059   \n",
      "550    ST-162   1793  0.546570  23.446737  2740.357373  0.186838  0.153374   \n",
      "551   ST-1620   1613  0.685679  17.970862  1884.998624  0.262864  0.073156   \n",
      "552   ST-1621   1856  0.719289  17.592134  1831.468761  0.265625  0.055496   \n",
      "553   ST-1622    415  0.650602  14.932530  1730.639518  0.200000  0.055422   \n",
      "554   ST-1623    476  0.670168  19.716387  2370.267164  0.241597  0.039916   \n",
      "555   ST-1625   2256  0.650709  23.867465  3272.387057  0.185727  0.037677   \n",
      "556   ST-1626   2221  0.579018  19.915353  2147.835083  0.253940  0.095002   \n",
      "557   ST-1627   2167  0.674665  22.097831  2425.090891  0.273650  0.030457   \n",
      "558   ST-1628   1739  0.718804  21.728005  2061.639500  0.265095  0.024152   \n",
      "559   ST-1629   3307  0.631993  20.985183  2296.233632  0.255519  0.055942   \n",
      "560    ST-163   1338  0.573244  21.266816  2272.825800  0.182362  0.136024   \n",
      "561   ST-1631   4650  0.676344  17.712258  1789.562563  0.239355  0.044516   \n",
      "562   ST-1632   3594  0.635225  20.978019  2153.887835  0.259599  0.047579   \n",
      "563   ST-1634    587  0.717206  18.574106  2371.547070  0.258944  0.027257   \n",
      "564   ST-1636   2226  0.718329  18.991914  2021.937260  0.212489  0.048967   \n",
      "565   ST-1637   1180  0.615254  24.194068  2628.422746  0.217797  0.035593   \n",
      "566   ST-1638   1962  0.605505  21.477574  2678.069144  0.280326  0.086646   \n",
      "567   ST-1639   3074  0.596291  18.030904  1796.300966  0.231620  0.022446   \n",
      "568   ST-1640   3338  0.645596  18.789694  1895.636660  0.261534  0.051228   \n",
      "569   ST-1641   2692  0.554978  19.563522  2288.620297  0.218053  0.055349   \n",
      "570   ST-1642   2496  0.625000  19.624599  2130.037640  0.282853  0.048478   \n",
      "571   ST-1645   5589  0.673287  12.750760  1583.841059  0.224369  0.048667   \n",
      "572   ST-1646   2574  0.546620  18.627428  1908.016554  0.210179  0.038462   \n",
      "573   ST-1647   2271  0.730956  14.448701  1621.221907  0.221929  0.051959   \n",
      "574   ST-1648    471  0.721868  51.276008  8261.555180  0.282378  0.114650   \n",
      "575   ST-1649   5807  0.663682  22.500258  2271.300580  0.258826  0.043396   \n",
      "576    ST-165   1231  0.667750  22.480097  2256.988424  0.285134  0.071487   \n",
      "577   ST-1650   3937  0.590551  17.878334  1902.934681  0.301753  0.028194   \n",
      "578   ST-1651   1503  0.675981  19.433799  1966.043859  0.208916  0.015968   \n",
      "579   ST-1652   2151  0.598791  22.474663  2147.385281  0.245467  0.093445   \n",
      "580   ST-1653   4103  0.584938  20.371436  1989.668428  0.271265  0.045820   \n",
      "581   ST-1654   2143  0.650023  25.215586  3268.018493  0.232851  0.053196   \n",
      "582   ST-1655   1464  0.600410  18.898224  2046.986291  0.140710  0.015027   \n",
      "583   ST-1656   2139  0.723703  25.622253  3452.769612  0.198223  0.048621   \n",
      "584   ST-1657   3699  0.539335  22.866450  2269.685566  0.284942  0.020276   \n",
      "585   ST-1659     13  0.769231  14.692308  2360.027692  0.000000  0.000000   \n",
      "586   ST-1660  11292  0.544545  20.938452  2119.424064  0.289940  0.030730   \n",
      "587   ST-1661   9083  0.557635  23.085324  2223.572327  0.277441  0.073214   \n",
      "588   ST-1663   4092  0.578690  16.445748  1837.112454  0.273705  0.064272   \n",
      "589   ST-1664   1217  0.608874  18.202958  2397.931142  0.267872  0.045193   \n",
      "590   ST-1665    752  0.652926  20.902926  2151.207606  0.239362  0.061170   \n",
      "591   ST-1667   1007  0.713009  25.812314  3369.454330  0.253227  0.117180   \n",
      "592   ST-1668   2808  0.660256  20.125712  2056.276595  0.184117  0.021011   \n",
      "593   ST-1669    964  0.784232  17.475104  2104.868869  0.268672  0.041494   \n",
      "594    ST-167   1391  0.655643  22.926671  2196.220036  0.204889  0.079080   \n",
      "595   ST-1670    506  0.701581  22.308300  2596.475791  0.227273  0.043478   \n",
      "596   ST-1671   2759  0.644799  20.355201  2624.158728  0.252265  0.032621   \n",
      "597   ST-1672   3460  0.634393  15.373699  1819.982668  0.256647  0.055202   \n",
      "598   ST-1674    888  0.748874  14.097973  1881.291802  0.204955  0.018018   \n",
      "599   ST-1675   1244  0.622186  19.569132  2008.396889  0.275723  0.031350   \n",
      "600   ST-1676   1934  0.695450  13.103930  1671.157332  0.215615  0.059979   \n",
      "601   ST-1677   2099  0.660791  19.974750  1850.030186  0.204859  0.060981   \n",
      "602   ST-1678   4770  0.697694  32.426415  5389.662260  0.305031  0.073585   \n",
      "603   ST-1679   1696  0.698113  24.468160  2293.606963  0.225825  0.063679   \n",
      "604    ST-168    535  0.781308  17.614953  2097.427850  0.256075  0.028037   \n",
      "605   ST-1680   1215  0.725103  24.670782  2473.126831  0.181893  0.057613   \n",
      "606   ST-1681  10071  0.557740  22.998511  2178.818385  0.272068  0.014696   \n",
      "607   ST-1682    365  0.753425  15.024658  1823.345096  0.068493  0.008219   \n",
      "608   ST-1684   4218  0.589616  16.711475  1618.327812  0.247511  0.038644   \n",
      "609   ST-1685     81  0.654321  29.259259  4336.256543  0.358025  0.049383   \n",
      "610   ST-1686    343  0.795918  42.758017  7217.325977  0.370262  0.113703   \n",
      "611   ST-1687   5764  0.517523  18.125434  2003.268878  0.235080  0.015788   \n",
      "612   ST-1688   5233  0.572521  13.284540  1488.493675  0.174661  0.033633   \n",
      "613   ST-1689   6034  0.598111  11.846205  1363.082116  0.243785  0.028339   \n",
      "614    ST-169   1618  0.624845  26.070457  2293.469567  0.276267  0.016069   \n",
      "615   ST-1690   2372  0.542159  21.483137  2281.221602  0.293002  0.094013   \n",
      "616   ST-1691   2034  0.702065  19.236971  1997.127984  0.264012  0.033923   \n",
      "617   ST-1692   2434  0.515201  24.509449  3154.399864  0.280608  0.022186   \n",
      "618   ST-1694   3159  0.616967  17.898386  1829.373916  0.257360  0.042418   \n",
      "619   ST-1695    670  0.870149  29.159701  3487.242672  0.241791  0.053731   \n",
      "620   ST-1696   1197  0.621554  27.482038  3535.977059  0.327485  0.043442   \n",
      "621   ST-1697   2232  0.675627  18.584229  1875.364987  0.241039  0.061828   \n",
      "622   ST-1698   4251  0.590685  16.868031  1626.795032  0.205599  0.043049   \n",
      "623   ST-1699   4907  0.665376  20.192582  2440.955490  0.154066  0.022621   \n",
      "624     ST-17   5356  0.587752  30.809933  4670.904268  0.270538  0.046677   \n",
      "625    ST-170   2000  0.640000  17.920000  1958.021840  0.247000  0.052500   \n",
      "626   ST-1700   2087  0.748443  15.275994  1744.320968  0.284140  0.112602   \n",
      "627   ST-1701   6482  0.601820  20.977168  2279.223537  0.266584  0.024684   \n",
      "628   ST-1702    425  0.788235  20.192941  2641.382894  0.249412  0.103529   \n",
      "629   ST-1703   1071  0.618114  22.428571  2261.249879  0.290383  0.020542   \n",
      "630   ST-1704   1676  0.650955  20.504177  2461.501265  0.199881  0.036396   \n",
      "631   ST-1705   3487  0.564095  36.377115  4370.783900  0.396616  0.026097   \n",
      "632   ST-1706    852  0.519953  18.293427  1924.203603  0.199531  0.093897   \n",
      "633   ST-1707   4343  0.614322  16.772277  1845.956424  0.145752  0.034999   \n",
      "634   ST-1708    793  0.738966  15.040353  1738.665195  0.153846  0.020177   \n",
      "635   ST-1709   4786  0.720852   8.542624  1028.617413  0.139574  0.016715   \n",
      "636    ST-171   3128  0.599425  15.211957  1561.483654  0.195332  0.040601   \n",
      "637   ST-1710   4308  0.516017  11.089833  1164.342326  0.235144  0.022284   \n",
      "638   ST-1712   3597  0.631081  13.097859  1433.983272  0.059772  0.003336   \n",
      "639   ST-1713   1066  0.770169  12.103189  1385.531379  0.184803  0.002814   \n",
      "640   ST-1714   4381  0.637069  15.241726  1783.109123  0.255878  0.110934   \n",
      "641   ST-1715   2751  0.778626  10.420211  1297.102690  0.122864  0.009088   \n",
      "642   ST-1716    759  0.517787  19.952569  2400.307747  0.229249  0.076416   \n",
      "643   ST-1717    678  0.594395  19.452802  2040.906490  0.274336  0.070796   \n",
      "644   ST-1718  16166  0.641532   9.105159  1109.351895  0.139614  0.003278   \n",
      "645   ST-1719   4587  0.498147  29.816874  2676.125284  0.366470  0.032483   \n",
      "646    ST-172   2318  0.623382  18.088438  1772.578292  0.219586  0.036238   \n",
      "647   ST-1720   9916  0.540440  27.827350  2360.822824  0.317769  0.007463   \n",
      "648   ST-1721   1786  0.694289  16.158455  2149.573964  0.273236  0.111422   \n",
      "649   ST-1722   4816  0.621055  14.739826  1798.485384  0.259136  0.057309   \n",
      "650   ST-1723   2316  0.634283  21.588946  2691.882219  0.222366  0.047496   \n",
      "651   ST-1724    689  0.799710  17.116110  2115.689492  0.280116  0.085631   \n",
      "652   ST-1725    992  0.574597  33.180444  2410.136351  0.466734  0.049395   \n",
      "653   ST-1726   3750  0.528533  19.964000  2472.676325  0.244267  0.067467   \n",
      "654   ST-1727   3354  0.573643  15.717949  1464.714517  0.190519  0.033989   \n",
      "655   ST-1728   2793  0.530254  21.279628  2065.952359  0.277121  0.041532   \n",
      "656   ST-1729   3450  0.586377  19.857391  1969.630038  0.252754  0.062899   \n",
      "657    ST-173   2296  0.652439  15.859321  1835.568362  0.253049  0.076220   \n",
      "658   ST-1730   8582  0.550454  21.548823  2192.495311  0.277441  0.058378   \n",
      "659   ST-1731  10241  0.643101  19.705693  2120.509662  0.295870  0.029685   \n",
      "660   ST-1732   1123  0.809439  20.652716  2687.114853  0.241318  0.054319   \n",
      "661   ST-1733   2531  0.682339  24.925326  3335.742940  0.310549  0.041486   \n",
      "662   ST-1734   1114  0.683124  22.552065  3251.728941  0.055655  0.015260   \n",
      "663   ST-1735    462  0.729437  19.997835  2521.165563  0.168831  0.025974   \n",
      "664   ST-1736   1837  0.630920  30.802395  4459.551889  0.281437  0.026674   \n",
      "665   ST-1739   1490  0.642282  24.095973  2497.648597  0.270470  0.056376   \n",
      "666    ST-174   2769  0.554352  16.014807  1554.225641  0.201878  0.042615   \n",
      "667   ST-1740    853  0.631887  19.119578  2050.252931  0.248535  0.041032   \n",
      "668   ST-1742   1007  0.722939  11.515392  1569.647805  0.243297  0.067527   \n",
      "669   ST-1745    497  0.756539  17.004024  1874.259698  0.066398  0.016097   \n",
      "670   ST-1746    325  0.676923  27.415385  2470.350554  0.144615  0.033846   \n",
      "671    ST-175   6998  0.634610  19.439697  1999.793427  0.249929  0.085739   \n",
      "672   ST-1752    161  0.732919  25.608696  3959.068199  0.254658  0.062112   \n",
      "673   ST-1753   3611  0.661313  21.806702  2812.012251  0.119081  0.016616   \n",
      "674   ST-1754   1704  0.605634  38.442488  4686.271138  0.493545  0.012324   \n",
      "675   ST-1756   1813  0.643133  24.715389  2307.820745  0.212355  0.052951   \n",
      "676   ST-1757   1268  0.783123  26.511830  3382.813667  0.284700  0.073344   \n",
      "677   ST-1758   1012  0.740119  22.595850  1720.262045  0.169960  0.020751   \n",
      "678   ST-1759    226  0.725664  23.411504  2937.185752  0.247788  0.000000   \n",
      "679    ST-176   4311  0.563210  24.700997  2415.736736  0.273950  0.046625   \n",
      "680   ST-1760    666  0.713213  20.067568  1655.334820  0.147147  0.043544   \n",
      "681   ST-1761   1192  0.666107  17.332215  1697.273901  0.109899  0.015101   \n",
      "682   ST-1762   1319  0.763457  35.981046  2383.665686  0.304018  0.119788   \n",
      "683   ST-1763    599  0.604341  19.447412  2061.077245  0.293823  0.016694   \n",
      "684   ST-1764    664  0.655120  17.602410  1925.341852  0.275602  0.003012   \n",
      "685   ST-1765    297  0.683502  23.010101  2344.631717  0.262626  0.057239   \n",
      "686   ST-1766    875  0.544000  19.939429  2103.495817  0.241143  0.032000   \n",
      "687   ST-1767   1232  0.613636  19.343344  2018.344935  0.291396  0.017045   \n",
      "688   ST-1768    674  0.716617  13.954006  1666.815134  0.218101  0.017804   \n",
      "689   ST-1769    303  0.722772  15.429043  1659.810561  0.135314  0.059406   \n",
      "690    ST-177   2957  0.677038  16.171796  1841.001245  0.267163  0.095367   \n",
      "691   ST-1771   3095  0.712116  24.294023  2301.850126  0.120517  0.009370   \n",
      "692   ST-1772    965  0.751295  24.070466  2461.849389  0.124352  0.036269   \n",
      "693   ST-1773    781  0.723431  22.428937  2636.628668  0.137004  0.010243   \n",
      "694   ST-1774    890  0.760674  24.649438  2792.408393  0.185393  0.039326   \n",
      "695   ST-1775    476  0.670168  25.792017  2517.339916  0.296218  0.073529   \n",
      "696   ST-1776    523  0.661568  28.072658  2595.778929  0.183556  0.043977   \n",
      "697   ST-1777   1074  0.671322  26.025140  2273.035400  0.157356  0.038175   \n",
      "698   ST-1778   1749  0.672956  28.576901  2709.825923  0.092053  0.012007   \n",
      "699   ST-1779   3949  0.696632  20.932135  2122.351464  0.187642  0.027349   \n",
      "700    ST-178   1130  0.600000  15.808850  2256.193239  0.222124  0.114159   \n",
      "701   ST-1780   4095  0.644933  23.576557  2376.664752  0.242979  0.083272   \n",
      "702   ST-1781   2639  0.681319  23.093975  2333.197363  0.115195  0.255400   \n",
      "703   ST-1782   1982  0.616044  23.858224  1913.620131  0.226034  0.113522   \n",
      "704   ST-1783   1116  0.582437  17.559140  1967.401703  0.259857  0.030466   \n",
      "705   ST-1785    897  0.647715  21.268673  2450.892664  0.284281  0.033445   \n",
      "706   ST-1786    837  0.755078  21.738351  2635.010311  0.231780  0.145759   \n",
      "707   ST-1787   3544  0.589729  20.717269  2068.770302  0.151806  0.151806   \n",
      "708   ST-1789    572  0.746503  23.277972  2410.395752  0.234266  0.062937   \n",
      "709   ST-1790    174  0.706897  26.212644  2741.949080  0.333333  0.017241   \n",
      "710   ST-1791   1962  0.763507  26.352192  3026.327712  0.163099  0.024465   \n",
      "711   ST-1793   5515  0.586401  20.914959  2104.415113  0.241160  0.047507   \n",
      "712   ST-1794   1644  0.621655  27.482968  3892.706283  0.304136  0.131995   \n",
      "713   ST-1795    576  0.491319  20.043403  2548.919444  0.218750  0.052083   \n",
      "714   ST-1796   2253  0.623613  23.577896  2752.941709  0.268087  0.035064   \n",
      "715   ST-1797   1333  0.591898  31.423106  3531.981118  0.315829  0.024006   \n",
      "716   ST-1798    379  0.717678  22.738786  2419.042639  0.192612  0.068602   \n",
      "717   ST-1799   1061  0.737041  13.758718  1481.332639  0.180961  0.057493   \n",
      "718     ST-18   9024  0.613697  20.625997  2036.678551  0.242797  0.031472   \n",
      "719    ST-180   2474  0.772433  17.205740  2240.497344  0.202102  0.045675   \n",
      "720   ST-1801    289  0.692042  16.968858  1596.481315  0.110727  0.038062   \n",
      "721   ST-1802   1551  0.692456  18.714378  1887.234333  0.254674  0.043843   \n",
      "722   ST-1804   2827  0.599929  22.304209  2029.233113  0.275911  0.015210   \n",
      "723   ST-1805   2483  0.708820  22.540475  2197.345473  0.143375  0.021345   \n",
      "724   ST-1807   4602  0.641243  20.839635  1842.266777  0.187744  0.029987   \n",
      "725   ST-1808   2069  0.679555  23.653939  1762.626974  0.163847  0.054132   \n",
      "726   ST-1809   1414  0.737624  20.959689  2067.924682  0.181754  0.045262   \n",
      "727    ST-181   3874  0.672173  27.621838  2862.061902  0.150232  0.006970   \n",
      "728   ST-1810   4725  0.647831  23.228571  1570.059010  0.120212  0.024127   \n",
      "729   ST-1811   2707  0.688216  21.273735  1953.884584  0.236424  0.037680   \n",
      "730   ST-1812   4011  0.713787  21.442284  2081.674717  0.239342  0.110945   \n",
      "731   ST-1813   4228  0.618732  20.627010  2227.579948  0.195601  0.181646   \n",
      "732   ST-1814   2047  0.622374  15.324866  1725.718661  0.249634  0.087934   \n",
      "733   ST-1815    354  0.559322  13.166667  1657.042175  0.276836  0.064972   \n",
      "734   ST-1816    976  0.598361  16.760246  1906.950123  0.262295  0.031762   \n",
      "735   ST-1817   2637  0.599545  16.459992  1915.549609  0.273417  0.083807   \n",
      "736   ST-1818   4735  0.648574  16.013939  1708.652729  0.239704  0.059345   \n",
      "737   ST-1819   3781  0.687913  16.819889  1861.882568  0.233272  0.078286   \n",
      "738    ST-182    318  0.672956  16.292453  1948.654088  0.075472  0.003145   \n",
      "739   ST-1820   1935  0.649096  14.032558  1465.969597  0.188630  0.025840   \n",
      "740   ST-1822   1477  0.691943  19.464455  1955.923866  0.258632  0.060934   \n",
      "741   ST-1823    559  0.747764  17.937388  2353.372558  0.241503  0.067979   \n",
      "742   ST-1824    434  0.778802  19.758065  2720.934516  0.202765  0.057604   \n",
      "743   ST-1825    381  0.551181  26.461942  3626.932966  0.317585  0.125984   \n",
      "744   ST-1826    324  0.626543  28.925926  4444.267747  0.259259  0.101852   \n",
      "745   ST-1827    270  0.807407  20.800000  3301.224296  0.262963  0.059259   \n",
      "746   ST-1828    468  0.801282  25.215812  3483.992585  0.226496  0.083333   \n",
      "747   ST-1829   2550  0.656078  23.681176  2125.039541  0.226275  0.056471   \n",
      "748    ST-183   2001  0.642679  16.897551  2173.969875  0.216892  0.066467   \n",
      "749   ST-1830    909  0.570957  17.848185  2095.694136  0.251925  0.011001   \n",
      "750   ST-1831   1217  0.619556  24.914544  2161.786393  0.251438  0.014790   \n",
      "751   ST-1832    355  0.642254  21.261972  2273.672592  0.326761  0.042254   \n",
      "752   ST-1833   3965  0.626986  19.307945  1779.291037  0.307188  0.013115   \n",
      "753   ST-1834   1485  0.668013  17.797980  1895.345118  0.277441  0.050505   \n",
      "754   ST-1835   2299  0.650283  18.468465  2086.500583  0.270117  0.097869   \n",
      "755   ST-1836   3039  0.642646  16.855874  1718.679480  0.268838  0.055281   \n",
      "756   ST-1837   3108  0.641570  19.254183  1825.520042  0.283784  0.063707   \n",
      "757   ST-1838   3527  0.596824  19.626878  1965.783538  0.257443  0.050468   \n",
      "758   ST-1839   5533  0.611965  18.037412  1908.695684  0.296584  0.029098   \n",
      "759   ST-1840    638  0.653605  22.816614  2532.493856  0.231975  0.020376   \n",
      "760   ST-1841   2138  0.611787  18.593545  1911.447035  0.252105  0.081384   \n",
      "761   ST-1842   2436  0.554187  21.809113  1978.243842  0.320197  0.064860   \n",
      "762   ST-1843    374  0.729947  28.122995  2253.038342  0.173797  0.002674   \n",
      "763   ST-1844   1272  0.724057  17.286950  1869.353160  0.204403  0.029874   \n",
      "764   ST-1845   1843  0.621270  17.308736  1936.823673  0.274552  0.024959   \n",
      "765   ST-1846   1126  0.641208  18.436057  1934.827229  0.283304  0.053286   \n",
      "766   ST-1848   2753  0.494007  19.378496  1956.504442  0.255358  0.046131   \n",
      "767   ST-1849    265  0.811321  19.750943  2709.136491  0.362264  0.116981   \n",
      "768    ST-185   4634  0.746871  23.887786  2365.051821  0.121925  0.010142   \n",
      "769   ST-1850   3660  0.622678  20.154372  1996.490096  0.223770  0.026776   \n",
      "770   ST-1851   4679  0.589015  20.670015  1950.314016  0.265869  0.041034   \n",
      "771   ST-1852    989  0.568251  22.243680  3087.207998  0.271992  0.019211   \n",
      "772   ST-1853   1294  0.570325  21.314529  2242.497125  0.205564  0.038640   \n",
      "773   ST-1854   1563  0.638516  16.886756  2071.269923  0.273832  0.075496   \n",
      "774   ST-1855   4636  0.611950  18.523512  2020.688156  0.198231  0.067515   \n",
      "775   ST-1857   3349  0.618991  19.668558  2174.830690  0.260675  0.048373   \n",
      "776   ST-1858   1229  0.567941  20.738812  2535.019292  0.216436  0.028478   \n",
      "777   ST-1859   4630  0.561987  19.511879  1918.524592  0.270410  0.051188   \n",
      "778    ST-186   1207  0.603977  24.584921  2431.686744  0.238608  0.033140   \n",
      "779   ST-1860   1753  0.556189  20.934398  2412.973360  0.313748  0.062750   \n",
      "780   ST-1861   1435  0.579094  22.131010  2397.143345  0.255052  0.041115   \n",
      "781   ST-1862   4472  0.537567  20.655859  2103.543055  0.286002  0.025492   \n",
      "782   ST-1864   4527  0.595538  25.865474  2470.937055  0.270157  0.047935   \n",
      "783   ST-1866   5991  0.551828  18.086129  1708.628793  0.246370  0.034552   \n",
      "784   ST-1867   5634  0.495918  20.021654  1923.224226  0.267306  0.044018   \n",
      "785   ST-1868   5115  0.539198  17.219746  1841.283425  0.256500  0.013490   \n",
      "786   ST-1869   2082  0.688280  21.564361  2897.026278  0.267531  0.031700   \n",
      "787    ST-187   1226  0.687602  24.253670  2894.554307  0.278140  0.165579   \n",
      "788   ST-1870    564  0.535461  19.613475  1943.539911  0.237589  0.072695   \n",
      "789   ST-1871    863  0.589803  19.137891  2372.205527  0.231750  0.038239   \n",
      "790   ST-1872   2432  0.611020  20.638158  2364.989359  0.221217  0.041530   \n",
      "791   ST-1873   1623  0.589649  20.364140  2609.527646  0.258780  0.047443   \n",
      "792   ST-1874   2283  0.611038  19.515550  2218.534196  0.311432  0.043802   \n",
      "793   ST-1875   1023  0.581623  19.146628  2401.326706  0.291300  0.056696   \n",
      "794   ST-1876    928  0.613147  19.459052  2222.940366  0.233836  0.068966   \n",
      "795   ST-1877   1212  0.400165  16.344884  1732.043853  0.287954  0.058581   \n",
      "796   ST-1878   1996  0.558116  17.774549  2199.888918  0.184870  0.027054   \n",
      "797   ST-1879   1846  0.601842  29.236728  3420.972259  0.282774  0.028711   \n",
      "798   ST-1880   2674  0.596485  21.231114  2538.847191  0.190352  0.028796   \n",
      "799   ST-1881   1795  0.604457  23.910306  2412.432763  0.288579  0.038997   \n",
      "800   ST-1882    992  0.684476  22.787298  2407.596250  0.207661  0.029234   \n",
      "801   ST-1883    468  0.771368  21.467949  2242.314380  0.224359  0.061966   \n",
      "802   ST-1884   1252  0.719649  33.571885  4590.354944  0.222843  0.014377   \n",
      "803   ST-1885   1215  0.688066  30.871605  4130.246272  0.260905  0.032099   \n",
      "804   ST-1886   1270  0.584252  25.374016  2897.046669  0.279528  0.018898   \n",
      "805   ST-1887   1389  0.716343  31.657307  3206.975018  0.264939  0.059755   \n",
      "806   ST-1888   1125  0.598222  19.904889  2376.606418  0.258667  0.042667   \n",
      "807   ST-1889   2329  0.692572  24.136110  2608.871370  0.284242  0.050666   \n",
      "808    ST-189   3063  0.643160  21.620307  2225.643950  0.207966  0.083905   \n",
      "809   ST-1891    306  0.627451  24.137255  3081.332157  0.290850  0.091503   \n",
      "810   ST-1892    942  0.632696  14.358811  1798.524257  0.183652  0.057325   \n",
      "811   ST-1893    981  0.725790  22.308869  2356.499001  0.217125  0.042813   \n",
      "812   ST-1894    701  0.690442  24.844508  2875.661469  0.315264  0.057061   \n",
      "813   ST-1895   1520  0.636842  32.076316  3960.471816  0.288158  0.086184   \n",
      "814   ST-1896   1532  0.755222  20.081593  2163.850796  0.178198  0.031332   \n",
      "815   ST-1897   2674  0.599850  23.910247  2770.847266  0.272625  0.040763   \n",
      "816   ST-1899   1214  0.627677  18.393740  1732.289152  0.274300  0.066722   \n",
      "817     ST-19   1153  0.683435  22.013010  2289.105794  0.260191  0.054640   \n",
      "818   ST-1900   1902  0.655626  26.894848  2925.427639  0.241325  0.046267   \n",
      "819   ST-1901    729  0.633745  23.921811  3492.660329  0.234568  0.013717   \n",
      "820   ST-1902    774  0.630491  22.852713  2430.150969  0.211886  0.036176   \n",
      "821   ST-1903   1077  0.695450  23.349118  2324.453110  0.202414  0.025998   \n",
      "822   ST-1904    346  0.624277  23.205202  2379.722168  0.231214  0.034682   \n",
      "823   ST-1905    759  0.718050  21.387352  2101.725652  0.226614  0.096179   \n",
      "824   ST-1906   1040  0.700000  19.604808  2058.992644  0.214423  0.071154   \n",
      "825   ST-1908   1931  0.633351  23.206629  2952.844055  0.332988  0.019679   \n",
      "826   ST-1909   1461  0.663244  23.224504  2856.361410  0.279261  0.045175   \n",
      "827   ST-1910   5270  0.610436  43.303416  5086.964459  0.361101  0.053131   \n",
      "828   ST-1912    343  0.583090  48.728863  5337.886822  0.399417  0.052478   \n",
      "829   ST-1913   1212  0.660066  24.425743  2794.949521  0.216997  0.022277   \n",
      "830   ST-1914   1371  0.574763  24.107221  2505.618009  0.246535  0.037929   \n",
      "831   ST-1915   2122  0.622526  27.409048  3076.426541  0.262488  0.042413   \n",
      "832   ST-1916   2163  0.562644  21.424873  2341.331711  0.226537  0.062876   \n",
      "833   ST-1917    528  0.573864  19.996212  3138.064867  0.232955  0.011364   \n",
      "834   ST-1918    386  0.585492  26.220207  3501.617332  0.297927  0.012953   \n",
      "835   ST-1920    730  0.584932  28.413699  2814.526548  0.324658  0.060274   \n",
      "836   ST-1921    289  0.633218  26.044983  2092.750796  0.193772  0.010381   \n",
      "837   ST-1922   1581  0.650854  18.523087  2081.709500  0.225806  0.036053   \n",
      "838   ST-1923   1990  0.656784  32.147739  3863.561724  0.330653  0.035176   \n",
      "839   ST-1924   1845  0.664499  20.508401  2309.312770  0.259079  0.067209   \n",
      "840   ST-1925    177  0.672316  28.694915  6313.712712  0.395480  0.033898   \n",
      "841   ST-1926   1666  0.701681  30.877551  3429.466801  0.236495  0.097239   \n",
      "842   ST-1929    697  0.658537  24.253945  3356.538364  0.246772  0.004304   \n",
      "843   ST-1932    283  0.752650  37.568905  5480.984876  0.402827  0.183746   \n",
      "844   ST-1933   1698  0.598351  15.154299  1895.483757  0.191991  0.027680   \n",
      "845   ST-1934    741  0.584345  18.089069  2273.881768  0.224022  0.056680   \n",
      "846   ST-1935    630  0.663492  17.896825  1895.165111  0.226984  0.066667   \n",
      "847   ST-1936    608  0.601974  20.129934  1995.216316  0.233553  0.008224   \n",
      "848   ST-1937    263  0.695817  31.403042  4090.851901  0.254753  0.030418   \n",
      "849   ST-1938   9695  0.682414  13.419288  1654.419759  0.145539  0.019701   \n",
      "850   ST-1939    653  0.581930  17.702910  2340.693890  0.150077  0.038285   \n",
      "851    ST-194   1648  0.749393  23.668689  2763.950364  0.221481  0.037015   \n",
      "852   ST-1940   1592  0.555905  15.250000  1757.726193  0.199749  0.013819   \n",
      "853   ST-1941   1366  0.703514  17.407760  2001.402840  0.230600  0.053441   \n",
      "854   ST-1944    484  0.469008  33.985537  4226.357128  0.373967  0.045455   \n",
      "855   ST-1945    242  0.475207  21.921488  2579.710826  0.276860  0.024793   \n",
      "856   ST-1946    268  0.753731  16.891791  2375.353955  0.235075  0.033582   \n",
      "857   ST-1947    376  0.670213  30.231383  3083.885399  0.305851  0.045213   \n",
      "858   ST-1948    371  0.547170  23.272237  2313.573854  0.326146  0.048518   \n",
      "859   ST-1949    224  0.531250  33.339286  3756.484643  0.330357  0.031250   \n",
      "860    ST-195   2512  0.630573  20.974124  2259.965199  0.164013  0.028662   \n",
      "861   ST-1950    189  0.455026  34.566138  3232.768836  0.269841  0.026455   \n",
      "862   ST-1952    839  0.610250  20.545888  2365.124720  0.277712  0.053635   \n",
      "863   ST-1953    205  0.556098  22.692683  2022.618244  0.234146  0.034146   \n",
      "864   ST-1954    531  0.572505  20.212806  2489.600471  0.269303  0.050847   \n",
      "865   ST-1955    802  0.705736  25.648379  3728.153155  0.269327  0.053616   \n",
      "866   ST-1956    177  0.559322  20.497175  2310.235593  0.293785  0.045198   \n",
      "867   ST-1957    722  0.666205  13.883657  1884.164349  0.290859  0.052632   \n",
      "868   ST-1958    692  0.539017  11.942197  1418.657962  0.219653  0.030347   \n",
      "869   ST-1959   1646  0.730863  14.243013  1934.542600  0.194411  0.074727   \n",
      "870    ST-196    402  0.689055  21.798507  2322.119005  0.261194  0.062189   \n",
      "871   ST-1960   1345  0.532342  21.214126  2501.738171  0.208178  0.087732   \n",
      "872   ST-1961   2538  0.561466  20.324271  2522.204007  0.223798  0.044917   \n",
      "873   ST-1962    890  0.550562  18.933708  2012.662427  0.295506  0.040449   \n",
      "874   ST-1963   1699  0.714538  14.738081  1917.344008  0.085933  0.023543   \n",
      "875   ST-1964   5777  0.638567  20.943569  2513.869060  0.249611  0.023195   \n",
      "876   ST-1965    515  0.675728  18.889320  2179.231223  0.244660  0.091262   \n",
      "877   ST-1966   1159  0.767903  15.244176  1923.154107  0.213115  0.051769   \n",
      "878   ST-1967    597  0.780570  18.973199  2051.164188  0.268007  0.041876   \n",
      "879   ST-1968   4463  0.601837  18.257226  1674.590509  0.249384  0.028232   \n",
      "880   ST-1969    345  0.727536  21.852174  2903.955855  0.226087  0.023188   \n",
      "881    ST-197    893  0.696529  21.595745  2629.767828  0.245241  0.122060   \n",
      "882   ST-1970   1273  0.695994  23.794973  2901.196457  0.191673  0.008641   \n",
      "883   ST-1971   1102  0.570780  42.229583  5063.853131  0.450998  0.030853   \n",
      "884   ST-1972   2795  0.610733  17.246154  1815.588004  0.152773  0.023971   \n",
      "885   ST-1973   5166  0.626984  18.347464  1751.118024  0.257646  0.033101   \n",
      "886   ST-1974   2118  0.643532  16.024551  1890.623810  0.228517  0.016525   \n",
      "887   ST-1975   1765  0.692918  15.843059  1931.450935  0.242493  0.111615   \n",
      "888   ST-1976   3634  0.572097  25.069070  3456.730281  0.275729  0.015960   \n",
      "889   ST-1977   2576  0.581134  18.458463  1868.100004  0.218556  0.036491   \n",
      "890   ST-1978   1770  0.598305  14.767797  1648.456119  0.180226  0.031638   \n",
      "891    ST-198   6663  0.610686  21.328981  2231.283549  0.240282  0.092751   \n",
      "892   ST-1982   1196  0.736622  22.983278  2346.888085  0.250836  0.077759   \n",
      "893   ST-1983   3995  0.709136  18.493867  1664.504618  0.238048  0.050313   \n",
      "894   ST-1985   2955  0.578003  15.424365  1970.135127  0.304230  0.077496   \n",
      "895   ST-1986   2470  0.651822  21.799595  2379.614785  0.241700  0.025911   \n",
      "896    ST-199    547  0.698355  16.791590  1812.702322  0.180987  0.034735   \n",
      "897   ST-1990   5757  0.691506  14.520757  1713.893550  0.254473  0.033003   \n",
      "898   ST-1991   2326  0.703783  18.588564  2025.904991  0.252365  0.067498   \n",
      "899   ST-1992   1548  0.594315  18.885659  1843.294722  0.233204  0.023256   \n",
      "900   ST-1993   1255  0.644622  13.113147  1713.909203  0.256574  0.026295   \n",
      "901   ST-1994   4434  0.649075  19.504511  2087.644215  0.294768  0.058412   \n",
      "902   ST-1995   9535  0.585107  19.358364  2009.728489  0.320294  0.013844   \n",
      "903   ST-1996   9207  0.576518  15.980558  1702.772546  0.207451  0.034973   \n",
      "904   ST-1997   4799  0.568869  17.484268  1792.044357  0.271098  0.032924   \n",
      "905   ST-1999   2240  0.674107  22.410268  2837.554464  0.267411  0.061607   \n",
      "906     ST-20   3818  0.619958  28.036145  2733.848816  0.276061  0.065217   \n",
      "907    ST-200   1288  0.665373  16.082298  1981.914907  0.247671  0.062112   \n",
      "908   ST-2000   1178  0.651104  19.848896  2208.951486  0.240238  0.057725   \n",
      "909   ST-2001   1800  0.663333  17.758889  2127.049017  0.266111  0.072778   \n",
      "910   ST-2002   1066  0.680113  18.405253  2359.538058  0.258912  0.045966   \n",
      "911   ST-2003   2604  0.698541  21.271505  2347.393038  0.240783  0.084869   \n",
      "912   ST-2005   6754  0.705804  17.607048  1967.746768  0.270358  0.044862   \n",
      "913   ST-2006   4509  0.660457  36.330894  4916.656999  0.315591  0.016855   \n",
      "914   ST-2007   7452  0.713500  16.554214  1906.931373  0.271202  0.047772   \n",
      "915   ST-2008   1995  0.675188  15.300752  1788.115885  0.225063  0.052632   \n",
      "916    ST-201   2149  0.705444  23.653327  2637.541661  0.231270  0.048395   \n",
      "917   ST-2011  10530  0.581576  18.868091  1763.802706  0.221368  0.010731   \n",
      "918   ST-2012   4373  0.632518  15.559113  1603.798573  0.276927  0.018980   \n",
      "919   ST-2013   6231  0.563312  16.023913  2023.082022  0.246188  0.047344   \n",
      "920   ST-2014   5115  0.692864  13.209775  1470.497939  0.212512  0.011339   \n",
      "921   ST-2016   5634  0.545438  17.760383  1801.457614  0.283990  0.020057   \n",
      "922   ST-2017   9579  0.592859  18.903330  1892.248693  0.294498  0.019835   \n",
      "923   ST-2018   2049  0.644217  21.414348  2381.985129  0.251830  0.041484   \n",
      "924   ST-2019    337  0.637982  24.572700  3363.987003  0.225519  0.133531   \n",
      "925    ST-202   4911  0.656893  28.279984  3287.618131  0.242110  0.056404   \n",
      "926   ST-2020   5575  0.559283  15.836054  1689.926002  0.230314  0.019013   \n",
      "927   ST-2022   2150  0.687442  17.090233  1910.028795  0.268837  0.048837   \n",
      "928   ST-2023   4046  0.615670  16.933515  2141.911537  0.257538  0.034602   \n",
      "929   ST-2024   6430  0.600311  18.974650  2152.827193  0.225505  0.023017   \n",
      "930   ST-2025   2231  0.690273  33.865531  4172.992394  0.332586  0.039444   \n",
      "931   ST-2026   2212  0.603978  17.022152  2327.327970  0.225588  0.057866   \n",
      "932   ST-2027   2757  0.627494  19.099383  2044.999692  0.234675  0.079797   \n",
      "933   ST-2028   1538  0.549415  18.956437  1853.666151  0.306892  0.088427   \n",
      "934   ST-2029   4025  0.663106  18.534907  2191.725516  0.233789  0.057391   \n",
      "935    ST-203   2150  0.634884  20.960465  2521.151619  0.205581  0.051163   \n",
      "936   ST-2031  25287  0.606557  12.126785  1454.068516  0.204097  0.017044   \n",
      "937   ST-2032    963  0.602285  13.563863  1851.617767  0.077882  0.015576   \n",
      "938   ST-2033   7291  0.682622  14.264847  1677.565533  0.115073  0.013716   \n",
      "939   ST-2034   3575  0.560559  12.180699  1295.507751  0.199161  0.025734   \n",
      "940   ST-2035   6279  0.623985  13.093805  1510.327960  0.139672  0.010033   \n",
      "941   ST-2036   5658  0.575999  11.479321  1333.394919  0.194768  0.031813   \n",
      "942   ST-2037   9143  0.598053  12.301323  1428.890733  0.196325  0.053155   \n",
      "943   ST-2039   5949  0.595394  19.146411  1834.825204  0.294503  0.022189   \n",
      "944    ST-204   4813  0.627675  32.285685  4448.960810  0.279867  0.052150   \n",
      "945   ST-2040   5689  0.563016  13.881174  1528.576302  0.194059  0.055897   \n",
      "946   ST-2041   3256  0.629607  12.604423  1608.363342  0.150184  0.018120   \n",
      "947   ST-2042   2226  0.582210  19.252022  2188.989699  0.274933  0.007637   \n",
      "948   ST-2044   3914  0.725345  14.291518  1760.544990  0.083291  0.003066   \n",
      "949   ST-2045  16551  0.645701  11.774273  1482.050099  0.184218  0.008096   \n",
      "950   ST-2046   3467  0.546870  16.844246  2173.991731  0.145659  0.035189   \n",
      "951   ST-2047   4753  0.584473  14.774669  1698.869971  0.238797  0.060383   \n",
      "952   ST-2048   2341  0.630073  13.062367  1468.742268  0.141820  0.016232   \n",
      "953   ST-2049   3258  0.561387  10.891344  1212.778186  0.234807  0.059239   \n",
      "954    ST-205   4906  0.629433  31.063596  4210.711724  0.264370  0.043416   \n",
      "955   ST-2050   6779  0.604661  10.465260  1219.470230  0.249889  0.032306   \n",
      "956   ST-2052   4125  0.674424  11.996848  1216.325234  0.176970  0.002909   \n",
      "957   ST-2054   3312  0.700785  24.079106  2465.378385  0.252114  0.114734   \n",
      "958   ST-2056   6541  0.577740  14.274882  1458.540501  0.224125  0.042043   \n",
      "959   ST-2057   3857  0.555095  14.880736  1885.245891  0.120041  0.005445   \n",
      "960   ST-2058   3398  0.587404  14.596822  1675.033420  0.220129  0.040024   \n",
      "961   ST-2059   4011  0.514086  18.180504  1526.470633  0.124657  0.011967   \n",
      "962    ST-206   2467  0.674503  30.789218  4101.896534  0.272396  0.039724   \n",
      "963   ST-2062   1273  0.606441  17.452474  2276.252569  0.319717  0.080911   \n",
      "964   ST-2063   2479  0.692618  17.959258  2078.240694  0.266236  0.058895   \n",
      "965   ST-2067   2566  0.687062  15.356976  1865.871617  0.261107  0.030787   \n",
      "966   ST-2068   2134  0.709934  15.212277  1795.496256  0.247423  0.038425   \n",
      "967   ST-2069    986  0.741379  25.693712  2758.414929  0.284990  0.029412   \n",
      "968    ST-207   2500  0.676400  24.778000  3139.237472  0.263600  0.069600   \n",
      "969   ST-2070   2279  0.691970  17.826240  2095.491444  0.285652  0.042124   \n",
      "970   ST-2073    688  0.697674  12.497093  1723.464230  0.154070  0.021802   \n",
      "971   ST-2074   3604  0.708935  18.604606  2335.837112  0.232242  0.065483   \n",
      "972   ST-2075   2840  0.645070  22.114437  2544.336623  0.265845  0.070775   \n",
      "973   ST-2076   3871  0.649186  19.588220  2193.463043  0.266856  0.075174   \n",
      "974   ST-2077   2103  0.685212  23.712316  2845.098317  0.284831  0.038516   \n",
      "975   ST-2078   2570  0.687938  17.857198  1968.982961  0.269261  0.031907   \n",
      "976   ST-2079   3379  0.593963  25.547203  3417.656961  0.275821  0.047647   \n",
      "977   ST-2080   1838  0.789989  18.559304  1730.001578  0.101197  0.022307   \n",
      "978   ST-2081   6210  0.610467  15.128986  1457.336026  0.201127  0.031401   \n",
      "979   ST-2083   1964  0.698574  24.744399  3520.842770  0.219450  0.041242   \n",
      "980   ST-2085   5488  0.569242  22.785714  2273.143639  0.321793  0.030430   \n",
      "981   ST-2086   1708  0.566745  17.322014  2162.590498  0.298595  0.071429   \n",
      "982   ST-2087   3715  0.610767  15.288022  1773.520272  0.253836  0.023957   \n",
      "983   ST-2088   2015  0.593548  19.700248  2264.818591  0.248139  0.075931   \n",
      "984   ST-2089   3669  0.553829  18.535841  1915.768607  0.276370  0.017171   \n",
      "985   ST-2093    927  0.633225  17.720604  1854.979159  0.238403  0.108954   \n",
      "986   ST-2094   2277  0.662714  20.902942  2315.469868  0.262187  0.088274   \n",
      "987   ST-2095   1396  0.538682  31.261461  5175.177500  0.344556  0.026504   \n",
      "988   ST-2096   1428  0.693277  21.476190  2001.335399  0.268908  0.082633   \n",
      "989   ST-2097   1556  0.694730  14.933162  1520.174049  0.292416  0.056555   \n",
      "990   ST-2099   1478  0.608254  20.698241  2528.969885  0.272666  0.093369   \n",
      "991     ST-21   2813  0.625311  33.667970  4578.947256  0.297903  0.037327   \n",
      "992    ST-210   3520  0.496307  21.672159  2469.152148  0.232386  0.041193   \n",
      "993   ST-2101    519  0.687861  20.339114  2160.317091  0.240848  0.080925   \n",
      "994   ST-2102    926  0.622030  25.568035  3444.639719  0.279698  0.055076   \n",
      "995   ST-2103   1124  0.577402  23.670819  3153.171059  0.288256  0.053381   \n",
      "996   ST-2104   1122  0.603387  19.565954  2536.130954  0.215686  0.059715   \n",
      "997   ST-2106    515  0.617476  24.893204  2887.677223  0.248544  0.128155   \n",
      "998   ST-2107   2696  0.657270  15.149110  1721.722804  0.280786  0.075668   \n",
      "999    ST-211   4643  0.554168  24.890373  2582.805585  0.313806  0.061813   \n",
      "1000  ST-2110   1967  0.619217  17.690391  2031.987712  0.284698  0.070666   \n",
      "1001  ST-2112   2371  0.600590  19.749473  2371.544863  0.263602  0.069591   \n",
      "1002  ST-2113    832  0.722356  22.358173  2808.410276  0.310096  0.106971   \n",
      "1003  ST-2115   1421  0.600281  23.482759  3092.337002  0.212526  0.017593   \n",
      "1004  ST-2116   1055  0.721327  18.292891  2107.260502  0.274882  0.131754   \n",
      "1005  ST-2117   1112  0.541367  16.102518  1813.930441  0.298561  0.095324   \n",
      "1006  ST-2119    826  0.682809  17.462470  2091.817651  0.283293  0.094431   \n",
      "1007   ST-212   2307  0.562635  18.137408  2296.654395  0.209363  0.015171   \n",
      "1008  ST-2120   1364  0.651026  18.085777  1903.138541  0.282991  0.064516   \n",
      "1009  ST-2123    250  0.928000  17.756000  2417.816320  0.204000  0.156000   \n",
      "1010  ST-2124   1024  0.631836  22.218750  2438.803623  0.320312  0.047852   \n",
      "1011  ST-2125   2468  0.639384  20.320502  2154.857378  0.291734  0.047002   \n",
      "1012  ST-2126   1126  0.681172  21.631439  2534.514893  0.300178  0.095915   \n",
      "1013  ST-2127    820  0.671951  18.563415  2346.099024  0.265854  0.073171   \n",
      "1014  ST-2129   1813  0.597904  25.027027  3340.101291  0.256481  0.037507   \n",
      "1015   ST-213   1466  0.663029  22.633697  2376.557619  0.189632  0.033424   \n",
      "1016  ST-2130    584  0.592466  25.647260  3078.640771  0.277397  0.065068   \n",
      "1017  ST-2132   1544  0.652202  22.189119  2114.754935  0.248705  0.108808   \n",
      "1018  ST-2133   2368  0.531672  22.788429  2581.905916  0.251267  0.049409   \n",
      "1019  ST-2134   2274  0.587951  24.111258  2442.706429  0.256376  0.094987   \n",
      "1020  ST-2137   5222  0.625048  19.696859  2110.787080  0.263692  0.059364   \n",
      "1021   ST-214   3082  0.705386  19.549319  2307.256330  0.256652  0.042180   \n",
      "1022  ST-2146   3680  0.629076  26.503261  3283.935283  0.252989  0.053261   \n",
      "1023  ST-2147   2775  0.546306  14.475676  1641.981186  0.197838  0.026306   \n",
      "1024  ST-2148    677  0.519941  15.319055  1695.329099  0.245199  0.044313   \n",
      "1025  ST-2149   2868  0.713040  17.404812  1862.806151  0.194909  0.013250   \n",
      "1026  ST-2150    708  0.594633  27.242938  3425.970890  0.248588  0.048023   \n",
      "1027  ST-2152   2845  0.626362  24.589104  2338.622506  0.260105  0.043234   \n",
      "1028  ST-2153    675  0.598519  24.480000  2379.984830  0.217778  0.011852   \n",
      "1029  ST-2154   1976  0.663968  28.977733  3494.581857  0.233300  0.031377   \n",
      "1030  ST-2156   4510  0.561197  27.121729  2712.114450  0.299335  0.050998   \n",
      "1031  ST-2157   4468  0.510743  20.228290  2129.523648  0.282005  0.038272   \n",
      "1032   ST-216    562  0.501779  19.117438  1986.215552  0.249110  0.039146   \n",
      "1033  ST-2160   5061  0.475203  23.165580  2548.429591  0.283936  0.030429   \n",
      "1034  ST-2161    127  0.874016  17.740157  2122.412677  0.220472  0.086614   \n",
      "1035  ST-2163    419  0.513126  22.319809  2126.433652  0.128878  0.000000   \n",
      "1036  ST-2164   1146  0.510471  17.898778  2249.902801  0.118674  0.032286   \n",
      "1037  ST-2165   1260  0.653175  19.609524  2373.596484  0.163492  0.034921   \n",
      "1038  ST-2166   1349  0.616012  14.088955  1853.532958  0.139362  0.022239   \n",
      "1039  ST-2167   3163  0.560228  22.968701  2309.257822  0.278849  0.061018   \n",
      "1040  ST-2168   6634  0.574917  22.130389  2265.089563  0.274646  0.035574   \n",
      "1041   ST-217    975  0.668718  21.607179  3286.746759  0.205128  0.060513   \n",
      "1042  ST-2172    686  0.728863  22.097668  2478.399125  0.241983  0.078717   \n",
      "1043  ST-2173   2271  0.603258  20.774108  2298.860255  0.300749  0.062087   \n",
      "1044  ST-2174    918  0.623094  21.199346  2004.224357  0.255991  0.032680   \n",
      "1045  ST-2175    644  0.590062  18.990683  2180.350311  0.267081  0.038820   \n",
      "1046  ST-2176   1655  0.668278  30.551662  4197.993106  0.311782  0.034441   \n",
      "1047  ST-2177   6753  0.632460  25.365023  3101.599542  0.324448  0.026803   \n",
      "1048  ST-2178    226  0.615044  28.495575  2942.149071  0.362832  0.035398   \n",
      "1049  ST-2179    325  0.566154  23.704615  2604.112277  0.344615  0.021538   \n",
      "1050   ST-218    513  0.656920  23.389864  2954.132982  0.237817  0.058480   \n",
      "1051  ST-2181    405  0.627160  23.780247  2949.299704  0.325926  0.101235   \n",
      "1052  ST-2182    435  0.625287  20.754023  2823.031103  0.351724  0.091954   \n",
      "1053  ST-2183    218  0.697248  26.701835  3117.142569  0.412844  0.036697   \n",
      "1054  ST-2184   2411  0.598092  33.449606  4003.722207  0.331398  0.040647   \n",
      "1055  ST-2187    715  0.502098  24.186014  2519.023748  0.351049  0.009790   \n",
      "1056  ST-2188   1339  0.645258  34.416729  5119.742532  0.221060  0.091860   \n",
      "1057  ST-2189    104  0.769231  19.807692  2903.680192  0.346154  0.038462   \n",
      "1058   ST-219   1223  0.461161  15.459526  2077.285863  0.195421  0.045789   \n",
      "1059  ST-2190    896  0.664062  18.828125  2336.337333  0.294643  0.078125   \n",
      "1060  ST-2191    562  0.681495  24.943060  2979.929270  0.266904  0.042705   \n",
      "1061  ST-2194    591  0.659898  24.177665  2796.346007  0.267343  0.081218   \n",
      "1062  ST-2195   1340  0.619403  29.764925  4064.380209  0.273881  0.093284   \n",
      "1063  ST-2196    523  0.720841  24.931166  3211.027266  0.340344  0.068834   \n",
      "1064  ST-2198    494  0.795547  16.356275  1958.302085  0.224696  0.018219   \n",
      "1065  ST-2199   1380  0.657971  23.835507  2730.408449  0.297826  0.073188   \n",
      "1066    ST-22    658  0.544073  22.231003  2743.668511  0.290274  0.054711   \n",
      "1067   ST-220    959  0.711157  22.032325  2930.345172  0.206465  0.065693   \n",
      "1068  ST-2200   1506  0.593625  17.671979  1884.179754  0.260956  0.090969   \n",
      "1069  ST-2201   1215  0.657613  23.575309  2306.903292  0.253498  0.059259   \n",
      "1070  ST-2202    438  0.356164  15.497717  1811.235046  0.203196  0.022831   \n",
      "1071  ST-2204   3504  0.583904  22.500000  2583.255197  0.253425  0.051084   \n",
      "1072  ST-2205   2188  0.595978  20.436015  2383.086490  0.276508  0.035192   \n",
      "1073  ST-2206   2167  0.646516  18.476234  2071.227300  0.251038  0.045224   \n",
      "1074  ST-2207   1191  0.637280  17.953820  2439.756725  0.245172  0.079765   \n",
      "1075  ST-2208   1770  0.694350  25.862712  2653.456418  0.270621  0.034463   \n",
      "1076   ST-221    701  0.611983  17.609130  2122.581056  0.255350  0.031384   \n",
      "1077  ST-2210   1990  0.502010  29.490452  3489.078337  0.284422  0.024623   \n",
      "1078  ST-2211    385  0.651948  21.449351  2846.234286  0.275325  0.041558   \n",
      "1079  ST-2212   1090  0.628440  23.755963  3265.876596  0.263303  0.033945   \n",
      "1080  ST-2213   2038  0.575074  29.739941  3635.382522  0.289990  0.042689   \n",
      "1081  ST-2214   1105  0.780995  19.080543  2442.374950  0.223529  0.052489   \n",
      "1082  ST-2215   1319  0.585292  23.868840  2600.760576  0.278241  0.041698   \n",
      "1083  ST-2216   1552  0.564433  24.293170  3000.615702  0.288660  0.036082   \n",
      "1084  ST-2217   1351  0.540340  31.843819  4470.352798  0.259067  0.045152   \n",
      "1085  ST-2219    703  0.741110  20.405405  2480.288706  0.284495  0.025605   \n",
      "1086   ST-222   2181  0.665291  21.289317  2366.908647  0.269601  0.023384   \n",
      "1087  ST-2221    317  0.810726  13.126183  1811.716530  0.252366  0.041009   \n",
      "1088  ST-2222   3017  0.556845  24.618827  3459.005111  0.224727  0.067285   \n",
      "1089  ST-2223   3442  0.640616  29.009006  3971.692644  0.274550  0.081639   \n",
      "1090  ST-2225   2817  0.601349  21.318779  2550.141899  0.256301  0.081292   \n",
      "1091  ST-2226   2586  0.664346  21.197989  2284.853855  0.242073  0.061098   \n",
      "1092  ST-2227    925  0.695135  26.280000  2943.539286  0.300541  0.121081   \n",
      "1093  ST-2229   1235  0.614575  17.590283  2102.311360  0.239676  0.055061   \n",
      "1094   ST-223   2687  0.643096  21.963900  2672.047722  0.263119  0.043543   \n",
      "1095  ST-2231   2966  0.610249  23.129130  2438.933001  0.246123  0.066757   \n",
      "1096  ST-2232    965  0.694301  15.711917  2052.679016  0.207254  0.074611   \n",
      "1097  ST-2233    453  0.600442  19.203091  2187.849934  0.211921  0.041943   \n",
      "1098  ST-2234    503  0.687873  16.153082  2109.486382  0.268390  0.091451   \n",
      "1099  ST-2235   1296  0.617284  19.057099  2124.023418  0.282407  0.091049   \n",
      "1100  ST-2236   1616  0.659653  22.197401  3098.911293  0.274752  0.043936   \n",
      "1101  ST-2237   2234  0.743062  22.376007  2918.388201  0.282005  0.047449   \n",
      "1102  ST-2239    633  0.538705  32.890995  4379.556651  0.380727  0.033175   \n",
      "1103   ST-224    867  0.716263  19.463668  2487.230588  0.292964  0.032295   \n",
      "1104  ST-2240   4920  0.521545  34.229065  4059.991724  0.436382  0.020528   \n",
      "1105  ST-2241    411  0.625304  17.119221  2432.028248  0.255474  0.072993   \n",
      "1106  ST-2242    240  0.595833  15.754167  1804.030750  0.250000  0.025000   \n",
      "1107  ST-2243    953  0.674711  19.198321  2228.203221  0.206716  0.096537   \n",
      "1108  ST-2244   1160  0.652586  15.167241  1440.667759  0.252586  0.037931   \n",
      "1109  ST-2245    535  0.779439  14.330841  1833.235421  0.267290  0.028037   \n",
      "1110  ST-2246    421  0.681710  21.337292  2467.199810  0.263658  0.061758   \n",
      "1111  ST-2247   1256  0.654459  20.141720  2480.292118  0.228503  0.066083   \n",
      "1112  ST-2250   1400  0.659286  20.533571  1927.205350  0.286429  0.057143   \n",
      "1113  ST-2252   1941  0.608449  22.683153  3102.878418  0.273570  0.066976   \n",
      "1114  ST-2253   2270  0.639648  18.921145  1964.164040  0.247577  0.050220   \n",
      "1115  ST-2257   2609  0.612495  23.501342  2996.191993  0.283250  0.061709   \n",
      "1116  ST-2259    281  0.715302  28.213523  3151.388932  0.409253  0.024911   \n",
      "1117   ST-226    755  0.582781  18.173510  2473.999404  0.198675  0.039735   \n",
      "1118  ST-2260    402  0.569652  31.024876  3719.015299  0.507463  0.009950   \n",
      "1119  ST-2261    821  0.649208  18.029233  1977.779890  0.250914  0.036541   \n",
      "1120  ST-2262    585  0.611966  15.343590  1904.332769  0.299145  0.037607   \n",
      "1121  ST-2263    774  0.686047  19.196382  2054.710814  0.218346  0.034884   \n",
      "1122  ST-2264   6660  0.600751  21.809459  2425.254797  0.279279  0.040691   \n",
      "1123  ST-2265   2047  0.714704  26.056668  2688.374284  0.243283  0.062531   \n",
      "1124  ST-2266   1376  0.702035  36.739826  4110.151170  0.313953  0.036337   \n",
      "1125  ST-2267   1299  0.719784  17.532717  1920.752179  0.236336  0.041570   \n",
      "1126  ST-2268   6157  0.629852  21.574468  2286.478509  0.255969  0.062855   \n",
      "1127  ST-2269   2359  0.638406  19.851208  2413.208843  0.245443  0.045358   \n",
      "1128   ST-227   1781  0.602471  24.942729  3072.557518  0.272880  0.056148   \n",
      "1129  ST-2270   6955  0.630050  23.409346  2851.432932  0.274191  0.080086   \n",
      "1130  ST-2271   1246  0.707865  15.110754  1668.557456  0.227929  0.070626   \n",
      "1131  ST-2272   2183  0.654146  19.267980  2280.922739  0.193312  0.028859   \n",
      "1132  ST-2273   1961  0.739929  19.190209  2345.154141  0.254462  0.108108   \n",
      "1133  ST-2274   2630  0.634601  21.418251  2351.117795  0.223194  0.075285   \n",
      "1134  ST-2276   1238  0.739095  20.496769  2621.624693  0.241519  0.073506   \n",
      "1135  ST-2278   3925  0.741401  23.731465  2860.771373  0.228535  0.061656   \n",
      "1136  ST-2279    761  0.842313  16.483574  1889.721787  0.261498  0.044678   \n",
      "1137   ST-228    874  0.718535  14.633867  1636.161751  0.117849  0.025172   \n",
      "1138  ST-2280   3533  0.634305  23.075573  2591.204478  0.269459  0.071894   \n",
      "1139  ST-2281    435  0.666667  15.712644  1725.459954  0.179310  0.052874   \n",
      "1140  ST-2282   2132  0.565666  19.010788  2140.173082  0.281426  0.077861   \n",
      "1141  ST-2283   3927  0.559206  17.605042  1981.369778  0.280621  0.059078   \n",
      "1142  ST-2284    539  0.658627  30.243043  3971.471484  0.239332  0.055659   \n",
      "1143  ST-2285   1881  0.640617  18.371079  1961.754981  0.249867  0.055290   \n",
      "1144  ST-2286   1501  0.612258  17.431712  2548.345989  0.190540  0.057295   \n",
      "1145  ST-2287   1030  0.643689  19.914563  2901.193563  0.233981  0.053398   \n",
      "1146  ST-2288    400  0.722500  19.807500  3001.759750  0.277500  0.122500   \n",
      "1147  ST-2289   1600  0.700000  21.614375  2613.091031  0.275625  0.118125   \n",
      "1148  ST-2290   1720  0.642442  21.207558  2360.032105  0.241279  0.033721   \n",
      "1149  ST-2291   2001  0.586207  19.407296  2105.602529  0.252874  0.090955   \n",
      "1150  ST-2292   3226  0.636702  20.534408  2266.514141  0.243025  0.080285   \n",
      "1151  ST-2293   1976  0.692814  16.168016  1693.077318  0.232287  0.030870   \n",
      "1152  ST-2294   1951  0.697591  19.652998  2176.899103  0.253716  0.027166   \n",
      "1153  ST-2295   1444  0.565097  15.820637  1683.999301  0.206371  0.070637   \n",
      "1154  ST-2298    426  0.553991  33.152582  4077.028052  0.232394  0.035211   \n",
      "1155  ST-2299   2510  0.578486  18.224701  2039.254203  0.306375  0.041036   \n",
      "1156    ST-23   1258  0.674881  24.156598  2751.040056  0.257552  0.059618   \n",
      "1157   ST-230    664  0.715361  17.739458  2035.109669  0.186747  0.024096   \n",
      "1158  ST-2300    832  0.641827  27.305288  3386.583714  0.288462  0.070913   \n",
      "1159  ST-2301   1165  0.557940  28.858369  3725.599245  0.272103  0.051502   \n",
      "1160  ST-2302    468  0.715812  16.145299  1792.197607  0.269231  0.023504   \n",
      "1161  ST-2303    458  0.665939  27.358079  2380.193297  0.320961  0.015284   \n",
      "1162  ST-2305   2922  0.599932  16.840520  1648.014346  0.270363  0.029774   \n",
      "1163  ST-2308   8559  0.606029  16.940063  1717.364291  0.225143  0.054913   \n",
      "1164  ST-2309   6012  0.596640  20.806221  2031.610805  0.243180  0.054391   \n",
      "1165   ST-231   1747  0.527762  26.652547  3604.912433  0.269605  0.025186   \n",
      "1166  ST-2310   6861  0.567118  18.148812  1978.991073  0.221542  0.061361   \n",
      "1167  ST-2312   2656  0.580949  17.372364  1822.653980  0.252259  0.073042   \n",
      "1168  ST-2314   6094  0.603216  16.833115  1614.466426  0.251395  0.039547   \n",
      "1169  ST-2318   4454  0.607768  17.856758  2016.759874  0.234845  0.073417   \n",
      "1170   ST-232   2992  0.630348  17.032086  2046.500618  0.202206  0.023730   \n",
      "1171  ST-2320   3899  0.603745  14.199025  1541.109700  0.223647  0.028982   \n",
      "1172  ST-2321   5287  0.554190  18.354454  1859.781122  0.247210  0.058256   \n",
      "1173  ST-2325   3646  0.559792  20.464070  2612.148511  0.243829  0.062260   \n",
      "1174  ST-2326   2798  0.677984  22.496426  2982.661112  0.199428  0.017870   \n",
      "1175  ST-2327   1477  0.679756  23.142857  2828.894861  0.172647  0.030467   \n",
      "1176  ST-2329   1268  0.576498  18.394322  2039.006648  0.270505  0.059937   \n",
      "1177   ST-233   1081  0.685476  21.410731  2695.000934  0.211841  0.094357   \n",
      "1178  ST-2330   3786  0.576862  22.278922  2350.031482  0.227945  0.023772   \n",
      "1179  ST-2331   3624  0.556015  17.516556  1977.126410  0.242826  0.065397   \n",
      "1180  ST-2332   2259  0.622399  36.953962  5402.188424  0.326693  0.058876   \n",
      "1181  ST-2333    880  0.914773  18.429545  2198.458682  0.130682  0.007955   \n",
      "1182  ST-2334   1436  0.531337  48.439415  4414.882709  0.479805  0.012535   \n",
      "1183  ST-2335   1137  0.686895  20.953386  2222.685048  0.222515  0.064204   \n",
      "1184  ST-2337    668  0.687126  18.209581  2194.400943  0.200599  0.053892   \n",
      "1185  ST-2338    544  0.731618  27.194853  2661.661195  0.352941  0.141544   \n",
      "1186  ST-2339    953  0.730325  26.318993  3331.169286  0.264428  0.091291   \n",
      "1187   ST-234   1320  0.623485  30.312121  3675.914773  0.233333  0.050000   \n",
      "1188  ST-2340   1325  0.655094  16.714717  2062.863600  0.257358  0.070943   \n",
      "1189  ST-2341   5121  0.515134  31.121851  2990.719590  0.283929  0.014060   \n",
      "1190  ST-2342   3627  0.642956  22.150813  2527.791050  0.230218  0.059553   \n",
      "1191  ST-2343    603  0.568823  26.384743  3180.666517  0.270315  0.064677   \n",
      "1192   ST-235   2355  0.569851  19.266667  2349.893006  0.242463  0.067941   \n",
      "1193  ST-2350   2021  0.682335  33.248887  4778.592751  0.318654  0.046017   \n",
      "1194  ST-2351    257  0.688716  25.918288  3430.894163  0.287938  0.038911   \n",
      "1195  ST-2352    371  0.719677  24.482480  3812.960081  0.277628  0.035040   \n",
      "1196  ST-2353   2738  0.710007  19.999635  2336.162469  0.258583  0.056611   \n",
      "1197  ST-2355   1758  0.672355  16.352105  1690.865933  0.228100  0.042662   \n",
      "1198  ST-2356    795  0.805031  26.280503  3409.829585  0.272956  0.085535   \n",
      "1199  ST-2357   1398  0.665236  20.530758  2350.054034  0.299714  0.079399   \n",
      "1200  ST-2358   2492  0.705457  17.758828  1993.694350  0.228331  0.057785   \n",
      "1201  ST-2359   1616  0.732673  15.084777  1771.622228  0.250619  0.035272   \n",
      "1202   ST-236   1446  0.562241  17.329184  1987.141632  0.242739  0.040111   \n",
      "1203  ST-2361    652  0.733129  23.601227  3182.289264  0.289877  0.111963   \n",
      "1204  ST-2362   1830  0.678689  20.551913  2164.738825  0.248087  0.050273   \n",
      "1205  ST-2363   2160  0.672685  23.376389  2108.790167  0.260185  0.057407   \n",
      "1206  ST-2364   1808  0.631084  19.450774  1905.958291  0.264381  0.048673   \n",
      "1207  ST-2365    289  0.626298  19.145329  2935.358443  0.252595  0.044983   \n",
      "1208  ST-2366    297  0.636364  17.848485  2567.620269  0.289562  0.037037   \n",
      "1209  ST-2367    372  0.771505  23.134409  2817.294543  0.260753  0.045699   \n",
      "1210  ST-2368   1479  0.657201  24.062880  2734.225301  0.278567  0.094659   \n",
      "1211  ST-2369    237  0.856540  20.991561  2478.022321  0.181435  0.059072   \n",
      "1212   ST-237   2923  0.630517  22.460828  2537.345884  0.249743  0.076634   \n",
      "1213  ST-2370   1058  0.647448  19.156900  2269.243686  0.304348  0.084121   \n",
      "1214  ST-2371   2321  0.692805  17.797932  2109.156898  0.259802  0.093063   \n",
      "1215  ST-2373   2570  0.588716  17.077432  1820.598148  0.250973  0.053307   \n",
      "1216  ST-2374    947  0.661035  14.913411  1610.692978  0.269271  0.087645   \n",
      "1217  ST-2375   1523  0.799081  29.267236  3307.460657  0.283651  0.084701   \n",
      "1218  ST-2379   1597  0.617408  20.919224  2237.275861  0.289919  0.130244   \n",
      "1219   ST-238    603  0.721393  22.729685  2557.419900  0.252073  0.097844   \n",
      "1220  ST-2380   1243  0.641995  18.674980  1854.488319  0.288013  0.079646   \n",
      "1221  ST-2382   1164  0.628007  17.430412  1934.593900  0.285223  0.103952   \n",
      "1222  ST-2383    237  0.603376  19.029536  2059.049072  0.261603  0.071730   \n",
      "1223   ST-239    305  0.816393  27.150820  3493.787049  0.321311  0.163934   \n",
      "1224  ST-2390     17  0.764706  12.705882  2035.398824  0.235294  0.117647   \n",
      "1225  ST-2391     80  0.800000  23.412500  2806.458875  0.337500  0.075000   \n",
      "1226  ST-2393    602  0.794020  15.378738  2007.110365  0.252492  0.043189   \n",
      "1227  ST-2394   1754  0.597491  19.098632  1940.249036  0.209806  0.046180   \n",
      "1228  ST-2395   4191  0.593653  16.702696  1765.130188  0.261751  0.038893   \n",
      "1229  ST-2396   5977  0.593107  14.926552  1536.226441  0.234733  0.031454   \n",
      "1230  ST-2397   3900  0.649487  17.174103  1978.982541  0.245641  0.025897   \n",
      "1231  ST-2398   6979  0.625161  16.258633  1783.609039  0.267947  0.039404   \n",
      "1232    ST-24   1213  0.751855  25.986810  2193.278730  0.265458  0.043693   \n",
      "1233   ST-240    685  0.738686  26.105109  3539.098321  0.258394  0.150365   \n",
      "1234  ST-2401    813  0.709717  22.932349  3350.214453  0.261993  0.035670   \n",
      "1235  ST-2402    334  0.658683  29.772455  3811.424042  0.395210  0.014970   \n",
      "1236  ST-2403    411  0.739659  21.815085  2738.229440  0.296837  0.072993   \n",
      "1237  ST-2404   1678  0.723480  21.918355  2959.098057  0.075685  0.008939   \n",
      "1238  ST-2405   1011  0.751731  25.419387  2438.543660  0.244313  0.074184   \n",
      "1239  ST-2406   2292  0.733857  16.160122  2116.759490  0.245637  0.068063   \n",
      "1240  ST-2407   2939  0.600885  18.532154  2003.589146  0.273222  0.027220   \n",
      "1241  ST-2408   1418  0.720733  18.763752  1727.188004  0.117066  0.020451   \n",
      "1242  ST-2409   2576  0.651009  16.767857  2014.443203  0.188276  0.154115   \n",
      "1243   ST-241   2966  0.690492  24.955158  3176.864666  0.311868  0.072488   \n",
      "1244  ST-2410    265  0.709434  18.381132  2648.592604  0.218868  0.033962   \n",
      "1245  ST-2411   5716  0.526767   9.993177  1075.409888  0.193142  0.034115   \n",
      "1246  ST-2412   3210  0.636760  11.760125  1478.490779  0.182866  0.038006   \n",
      "1247  ST-2414   1584  0.688763  25.087753  3212.107563  0.260732  0.022096   \n",
      "1248  ST-2415    820  0.543902  24.262195  3287.088037  0.268293  0.024390   \n",
      "1249  ST-2416   1047  0.649475  27.265521  3941.680420  0.249284  0.051576   \n",
      "1250  ST-2417    962  0.742204  23.043659  2866.941455  0.241164  0.123701   \n",
      "1251  ST-2419   3199  0.684589  12.276649  1376.460991  0.222570  0.022194   \n",
      "1252   ST-242   1226  0.713703  18.406199  2448.230400  0.111746  0.018760   \n",
      "1253  ST-2420   4974  0.591275  30.397266  4373.513727  0.261761  0.055489   \n",
      "1254  ST-2422   2704  0.718565  25.665680  2554.970692  0.116864  0.017751   \n",
      "1255  ST-2424    542  0.623616  16.750923  1843.917362  0.226937  0.031365   \n",
      "1256  ST-2425   2053  0.665855  16.712616  2001.160146  0.265952  0.050658   \n",
      "1257  ST-2427   3140  0.693631  15.995860  1682.295994  0.214331  0.015605   \n",
      "1258  ST-2428    890  0.468539  18.069663  1612.388865  0.180899  0.004494   \n",
      "1259   ST-243   8676  0.700323  17.214269  1961.147811  0.166551  0.029161   \n",
      "1260  ST-2430    257  0.696498  28.420233  3346.990467  0.155642  0.035019   \n",
      "1261  ST-2431   3724  0.603652  22.695489  2356.483625  0.259398  0.067669   \n",
      "1262  ST-2432    466  0.753219  16.942060  1993.244936  0.201717  0.019313   \n",
      "1263  ST-2433    560  0.703571  16.666071  1880.905714  0.178571  0.025000   \n",
      "1264  ST-2434    148  0.682432  18.750000  2036.610743  0.189189  0.013514   \n",
      "1265  ST-2435   1426  0.791024  28.206171  3625.253198  0.262272  0.053296   \n",
      "1266  ST-2436    453  0.465784  17.529801  1965.878675  0.251656  0.028698   \n",
      "1267  ST-2437    987  0.728470  25.433637  3711.314559  0.170213  0.030395   \n",
      "1268  ST-2438    947  0.488912  35.294615  4246.835618  0.410771  0.025343   \n",
      "1269  ST-2439    621  0.560386  26.824477  2789.541304  0.434783  0.009662   \n",
      "1270   ST-244   2968  0.650606  21.568396  2719.113181  0.227763  0.074461   \n",
      "1271  ST-2440    330  0.512121  25.390909  2624.372364  0.312121  0.003030   \n",
      "1272  ST-2441    604  0.617550  19.584437  2278.570728  0.294702  0.039735   \n",
      "1273  ST-2442    586  0.604096  38.684300  5165.032457  0.266212  0.066553   \n",
      "1274  ST-2443    291  0.711340  32.463918  3980.226838  0.305842  0.092784   \n",
      "1275  ST-2444    132  0.606061  31.787879  4186.557803  0.340909  0.083333   \n",
      "1276  ST-2445    247  0.607287  27.558704  3362.307328  0.417004  0.064777   \n",
      "1277  ST-2446   1032  0.642442  32.384690  4407.020010  0.300388  0.077519   \n",
      "1278  ST-2447   1205  0.784232  18.784232  2357.325469  0.234025  0.037344   \n",
      "1279  ST-2448    310  0.609677  24.861290  2818.282742  0.270968  0.041935   \n",
      "1280  ST-2449   1758  0.708191  23.715586  3430.307673  0.199090  0.032992   \n",
      "1281   ST-245    892  0.582960  31.633408  4211.059854  0.254484  0.079596   \n",
      "1282  ST-2450   2184  0.616758  28.493590  3712.686314  0.298535  0.030678   \n",
      "1283  ST-2451   2213  0.740624  22.023046  2369.831333  0.277000  0.067329   \n",
      "1284  ST-2452    510  0.566667  27.001961  3482.268961  0.245098  0.070588   \n",
      "1285  ST-2453    247  0.716599  24.105263  2999.924494  0.295547  0.129555   \n",
      "1286  ST-2455    755  0.676821  17.872848  1859.252477  0.264901  0.034437   \n",
      "1287  ST-2456   1781  0.647389  29.857945  3817.759994  0.306008  0.066816   \n",
      "1288  ST-2457   1662  0.577617  19.238267  2061.811913  0.287004  0.069795   \n",
      "1289  ST-2458    707  0.570014  23.405941  2075.087115  0.203678  0.056577   \n",
      "1290  ST-2459   1781  0.642897  17.741157  2147.595081  0.250983  0.067378   \n",
      "1291   ST-246    631  0.613312  27.293185  3780.820206  0.301109  0.101426   \n",
      "1292  ST-2460    478  0.648536  27.259414  3942.718138  0.303347  0.087866   \n",
      "1293  ST-2461    474  0.727848  22.588608  2444.425211  0.293249  0.101266   \n",
      "1294  ST-2462    414  0.434783  28.630435  2583.676957  0.323671  0.028986   \n",
      "1295  ST-2463   1179  0.658185  24.458015  3505.367447  0.259542  0.061069   \n",
      "1296  ST-2464   4570  0.621225  18.061269  2088.369033  0.276149  0.030416   \n",
      "1297  ST-2465   3314  0.643331  15.818648  1708.090009  0.244116  0.089922   \n",
      "1298  ST-2466   3403  0.573905  23.677050  2486.830044  0.190420  0.029386   \n",
      "1299  ST-2467   1719  0.623618  16.308901  2037.008232  0.146597  0.030250   \n",
      "1300  ST-2468   1161  0.608958  38.943152  5383.625047  0.319552  0.043928   \n",
      "1301  ST-2469    453  0.699779  19.019868  2197.940419  0.220751  0.044150   \n",
      "1302   ST-247   1094  0.702925  19.855576  2469.837770  0.258684  0.078611   \n",
      "1303  ST-2470   1414  0.618105  20.041018  2251.559222  0.246818  0.068600   \n",
      "1304  ST-2472   2763  0.695983  21.508505  1796.489059  0.145132  0.020630   \n",
      "1305  ST-2473   2247  0.585225  22.980863  2205.610129  0.254562  0.022252   \n",
      "1306  ST-2474    886  0.718962  13.077878  1733.715485  0.124153  0.011287   \n",
      "1307  ST-2476   1116  0.600358  12.924731  1498.052715  0.174731  0.019713   \n",
      "1308  ST-2477   2917  0.553994  12.420980  1297.168639  0.253342  0.021598   \n",
      "1309  ST-2478   1383  0.654375  27.068691  3750.351171  0.282719  0.049168   \n",
      "1310  ST-2479   2064  0.609496  19.695252  2185.185528  0.218992  0.016473   \n",
      "1311   ST-248   1068  0.725655  23.556180  2834.532612  0.242509  0.096442   \n",
      "1312  ST-2480   1207  0.724109  18.072908  2210.834416  0.241094  0.093621   \n",
      "1313  ST-2481   3622  0.674213  17.953893  2133.675947  0.255660  0.059083   \n",
      "1314  ST-2482   5820  0.629725  14.154467  1356.351553  0.246392  0.051203   \n",
      "1315  ST-2483   2101  0.638267  17.190386  1732.518229  0.218943  0.032366   \n",
      "1316  ST-2484    902  0.758315  18.154102  2019.273880  0.345898  0.062084   \n",
      "1317  ST-2486   3676  0.655604  19.769859  2207.506336  0.301143  0.052503   \n",
      "1318  ST-2487   6702  0.576097  17.628469  2108.410209  0.248881  0.055804   \n",
      "1319  ST-2488    232  0.836207  27.297414  3479.536853  0.327586  0.004310   \n",
      "1320  ST-2489   2754  0.595861  16.916485  2341.536866  0.239651  0.020334   \n",
      "1321   ST-249   2315  0.698488  21.937365  2690.617654  0.262203  0.062203   \n",
      "1322  ST-2490   2677  0.703399  17.902129  2512.169395  0.259245  0.035487   \n",
      "1323  ST-2491   4822  0.579428  24.759436  3740.073801  0.279345  0.037744   \n",
      "1324  ST-2492   1223  0.586263  40.639411  6054.558144  0.366312  0.032706   \n",
      "1325  ST-2494   3621  0.625518  35.757526  5289.410851  0.334162  0.024579   \n",
      "1326  ST-2496   1665  0.637838  27.824024  3527.944078  0.298498  0.050450   \n",
      "1327  ST-2497    890  0.640449  21.883146  2827.098258  0.296629  0.024719   \n",
      "1328  ST-2498   2538  0.670213  25.959811  3561.587325  0.254531  0.052403   \n",
      "1329  ST-2499   1828  0.630744  19.987965  2319.249043  0.170678  0.028993   \n",
      "1330    ST-25   3253  0.558254  33.896711  5035.760618  0.288042  0.060252   \n",
      "1331   ST-250   1349  0.646405  22.450704  2685.646449  0.206079  0.053373   \n",
      "1332  ST-2500    405  0.708642  20.311111  2452.753407  0.296296  0.049383   \n",
      "1333  ST-2501   5008  0.650160  20.855032  2304.555865  0.260383  0.057708   \n",
      "1334  ST-2502   2352  0.687925  16.937500  1877.704345  0.286139  0.117772   \n",
      "1335  ST-2504   2175  0.671724  21.424368  2747.711508  0.229885  0.041379   \n",
      "1336  ST-2505   1363  0.660308  25.110051  2910.376456  0.267792  0.068966   \n",
      "1337  ST-2506   1717  0.577752  22.654048  2983.468957  0.243448  0.046010   \n",
      "1338  ST-2507   2879  0.547760  19.531435  2361.217385  0.209100  0.031261   \n",
      "1339  ST-2508   5129  0.597192  20.799766  2639.462921  0.230454  0.040749   \n",
      "1340  ST-2509   1880  0.673936  20.760638  2449.006362  0.259043  0.034574   \n",
      "1341   ST-251   2697  0.740452  23.214312  3080.302696  0.159436  0.024842   \n",
      "1342  ST-2511    514  0.745136  16.196498  2256.642471  0.280156  0.031128   \n",
      "1343  ST-2513   2344  0.686007  30.619881  2177.520734  0.252560  0.054181   \n",
      "1344  ST-2514    885  0.661017  22.750282  1957.144780  0.169492  0.009040   \n",
      "1345  ST-2516    729  0.624143  21.362140  2135.941139  0.193416  0.054870   \n",
      "1346  ST-2517    879  0.712173  22.037543  2447.157907  0.166098  0.030717   \n",
      "1347  ST-2518   4843  0.671485  21.135040  2247.812443  0.163329  0.010737   \n",
      "1348  ST-2519    263  0.764259  19.574144  2070.020913  0.079848  0.011407   \n",
      "1349   ST-252   2815  0.551687  28.815631  3971.528124  0.273535  0.094494   \n",
      "1350  ST-2520   1068  0.584270  24.981273  1997.477669  0.205993  0.013109   \n",
      "1351  ST-2521    990  0.695960  24.739394  2423.503929  0.221212  0.038384   \n",
      "1352  ST-2522    657  0.669711  26.171994  2626.883927  0.240487  0.021309   \n",
      "1353  ST-2523   2002  0.772727  22.429570  2217.349665  0.120380  0.018981   \n",
      "1354  ST-2525    839  0.638856  23.277712  2220.366079  0.177592  0.023838   \n",
      "1355  ST-2526    953  0.724029  23.882476  2407.505593  0.125918  0.015740   \n",
      "1356  ST-2527   2060  0.689806  24.251456  2386.037485  0.253398  0.025728   \n",
      "1357  ST-2528   1459  0.723783  23.106923  2463.715147  0.197395  0.030843   \n",
      "1358   ST-253   3989  0.583104  18.063174  2076.853928  0.259464  0.109802   \n",
      "1359  ST-2530    911  0.671789  25.601537  2973.234610  0.304061  0.058178   \n",
      "1360  ST-2531   1032  0.573643  24.921512  2226.441822  0.207364  0.053295   \n",
      "1361  ST-2532   1373  0.563001  23.148580  2190.539432  0.226511  0.036417   \n",
      "1362  ST-2533   1901  0.564966  19.730142  2500.617585  0.253551  0.053656   \n",
      "1363  ST-2534   1331  0.547708  29.096920  2973.738655  0.312547  0.080391   \n",
      "1364  ST-2535   1740  0.553448  15.424713  1836.508891  0.245402  0.098851   \n",
      "1365  ST-2536   3898  0.515393  22.961262  2408.421734  0.285531  0.007696   \n",
      "1366  ST-2537   1800  0.622222  17.425556  2109.308328  0.171111  0.037778   \n",
      "1367  ST-2538   4189  0.526617  15.208164  1510.900298  0.214610  0.035808   \n",
      "1368  ST-2539    458  0.805677  18.137555  1468.872140  0.277293  0.065502   \n",
      "1369   ST-254   2880  0.632639  26.714931  3706.021059  0.315972  0.021875   \n",
      "1370  ST-2541   2267  0.613586  13.824879  1691.921760  0.217909  0.028231   \n",
      "1371  ST-2542   2521  0.609679  15.646172  1606.575173  0.229671  0.063467   \n",
      "1372  ST-2543   1287  0.709402  16.307692  2067.492836  0.248640  0.040404   \n",
      "1373  ST-2544   2642  0.583270  13.132097  1539.349633  0.219152  0.035958   \n",
      "1374  ST-2545   2770  0.536462  21.033213  1888.185617  0.248736  0.076895   \n",
      "1375  ST-2546   3357  0.538576  19.468871  1856.582270  0.244266  0.074471   \n",
      "1376  ST-2547   1973  0.640142  18.933604  1859.694328  0.187532  0.018246   \n",
      "1377  ST-2548    193  0.772021  24.891192  2878.238187  0.181347  0.005181   \n",
      "1378  ST-2549   3573  0.586622  34.131542  5465.897084  0.301427  0.040022   \n",
      "1379   ST-255   3702  0.642896  19.913560  2314.824943  0.275527  0.015397   \n",
      "1380  ST-2550   3544  0.586061  21.083239  2603.339571  0.200056  0.025959   \n",
      "1381  ST-2551   1347  0.676318  17.858203  2030.539933  0.224944  0.060134   \n",
      "1382  ST-2552   1481  0.584065  18.789332  1740.908602  0.177583  0.012829   \n",
      "1383  ST-2553   1709  0.613224  39.889994  5961.160316  0.370392  0.033353   \n",
      "1384  ST-2555   3073  0.673609  13.352424  1752.927637  0.262284  0.091767   \n",
      "1385  ST-2556   1108  0.595668  18.081227  2142.901679  0.247292  0.071300   \n",
      "1386  ST-2557   9495  0.588310  14.751659  1786.060563  0.228331  0.072038   \n",
      "1387  ST-2558   2173  0.624482  17.244363  1840.357133  0.282559  0.046940   \n",
      "1388  ST-2559   2354  0.663976  18.975361  2215.624172  0.263806  0.065845   \n",
      "1389   ST-256   1751  0.609937  31.930326  4375.697493  0.295831  0.017704   \n",
      "1390  ST-2560   2307  0.595145  22.065020  2907.964361  0.255743  0.091894   \n",
      "1391  ST-2561    984  0.623984  24.272358  3264.739715  0.289634  0.093496   \n",
      "1392  ST-2562    374  0.780749  27.173797  3639.246524  0.149733  0.026738   \n",
      "1393  ST-2563   2829  0.590315  15.796394  1486.149268  0.158360  0.018381   \n",
      "1394  ST-2564   2721  0.716648  19.442484  2213.793444  0.276736  0.058067   \n",
      "1395  ST-2565   2399  0.675698  20.293456  1857.404060  0.196332  0.021676   \n",
      "1396  ST-2567    667  0.595202  27.547226  3305.892474  0.247376  0.044978   \n",
      "1397  ST-2568    525  0.601905  31.860952  2466.681238  0.270476  0.026667   \n",
      "1398  ST-2569   3706  0.499191  15.536967  1661.750888  0.178090  0.034808   \n",
      "1399   ST-257   3852  0.595275  18.143821  1812.164813  0.248442  0.069055   \n",
      "1400  ST-2570   1056  0.648674  26.930871  2908.955199  0.208333  0.033144   \n",
      "1401  ST-2571   4644  0.581180  24.431525  2769.003351  0.172265  0.016150   \n",
      "1402  ST-2572   2624  0.577363  23.971799  2431.974432  0.324695  0.044588   \n",
      "1403  ST-2574   7222  0.427444  20.470368  2488.133398  0.195375  0.006508   \n",
      "1404  ST-2575   1104  0.634964  19.061594  2277.894538  0.236413  0.075181   \n",
      "1405  ST-2576   1812  0.591060  20.177704  2021.867047  0.173841  0.030905   \n",
      "1406  ST-2577    413  0.581114  20.125908  2264.163923  0.266344  0.043584   \n",
      "1407  ST-2578   1211  0.596201  17.678778  1911.208860  0.255161  0.136251   \n",
      "1408  ST-2579   1318  0.512898  20.179818  2267.750303  0.234446  0.046282   \n",
      "1409   ST-258   4186  0.563306  20.604873  2419.190131  0.299331  0.031534   \n",
      "1410  ST-2580   2894  0.466137  27.050104  2510.554323  0.267104  0.024188   \n",
      "1411  ST-2581   2786  0.572146  19.236899  2141.617243  0.229002  0.071788   \n",
      "1412  ST-2583   2201  0.617901  20.054066  2516.861999  0.231713  0.065425   \n",
      "1413  ST-2584   1067  0.621368  14.308341  1872.935473  0.208997  0.044986   \n",
      "1414  ST-2585    676  0.715976  18.411243  2625.461686  0.289941  0.149408   \n",
      "1415  ST-2586    412  0.582524  18.759709  2721.978786  0.257282  0.094660   \n",
      "1416  ST-2587    743  0.654105  16.767160  1869.825949  0.243607  0.078062   \n",
      "1417  ST-2588    781  0.615877  20.098592  1905.593982  0.233035  0.038412   \n",
      "1418  ST-2589   1768  0.568439  17.910068  1956.241052  0.230769  0.049774   \n",
      "1419   ST-259   5144  0.631804  18.634526  2332.703698  0.287519  0.079899   \n",
      "1420  ST-2590    275  0.640000  16.480000  1975.326873  0.236364  0.054545   \n",
      "1421  ST-2591   1325  0.636981  27.740377  1986.492694  0.231698  0.030189   \n",
      "1422  ST-2592   5509  0.459793  27.386459  2897.938684  0.259757  0.012888   \n",
      "1423  ST-2593   3068  0.540417  37.476858  4701.100740  0.400587  0.024120   \n",
      "1424  ST-2594   3442  0.629285  25.036316  2775.664605  0.246659  0.021790   \n",
      "1425  ST-2595    939  0.658147  22.040469  1963.893525  0.271565  0.035144   \n",
      "1426  ST-2596   3668  0.586968  23.955834  2320.921150  0.254907  0.015540   \n",
      "1427  ST-2597    358  0.569832  17.067039  1727.686788  0.248603  0.030726   \n",
      "1428  ST-2598    581  0.588640  24.292599  2623.268726  0.242685  0.034423   \n",
      "1429  ST-2599   2545  0.614931  16.812967  1919.044743  0.206680  0.051473   \n",
      "1430    ST-26   1835  0.675749  20.293188  1959.740719  0.253951  0.049591   \n",
      "1431   ST-260    682  0.601173  23.482405  2730.417053  0.266862  0.029326   \n",
      "1432  ST-2600    723  0.601660  21.391425  2621.556404  0.295989  0.055325   \n",
      "1433  ST-2601   2828  0.615983  19.902051  1941.471008  0.256719  0.051980   \n",
      "1434  ST-2602   2696  0.576780  23.201780  2608.896907  0.255193  0.036350   \n",
      "1435  ST-2603    927  0.668824  16.991370  2022.999374  0.293420  0.064725   \n",
      "1436  ST-2605   2413  0.745131  20.109407  2699.596022  0.194364  0.228761   \n",
      "1437  ST-2606   2230  0.637668  18.571300  1902.804426  0.242601  0.050224   \n",
      "1438  ST-2607    899  0.684093  20.116796  2507.672992  0.273637  0.116796   \n",
      "1439  ST-2608   1327  0.488320  24.473248  2520.121025  0.333082  0.024115   \n",
      "1440  ST-2609   2769  0.555435  33.446732  4204.385367  0.333694  0.032503   \n",
      "1441   ST-261   1811  0.667587  20.410823  1911.932772  0.240751  0.041966   \n",
      "1442  ST-2610   1676  0.605012  25.026850  3317.182041  0.274463  0.074582   \n",
      "1443  ST-2611   3598  0.601167  15.171762  1595.751754  0.240689  0.072262   \n",
      "1444  ST-2613   2717  0.549135  14.727273  1566.488325  0.231873  0.094222   \n",
      "1445  ST-2614   2085  0.673861  17.762110  1951.992998  0.265707  0.102638   \n",
      "1446  ST-2615    433  0.454965  26.364896  1997.798083  0.392610  0.020785   \n",
      "1447  ST-2616    397  0.574307  17.221662  1935.179824  0.269521  0.032746   \n",
      "1448  ST-2617    828  0.611111  19.021739  1999.281389  0.270531  0.107488   \n",
      "1449  ST-2618    327  0.614679  17.623853  1821.227982  0.354740  0.051988   \n",
      "1450  ST-2619    513  0.627680  18.953216  2539.642943  0.300195  0.089669   \n",
      "1451   ST-262   6980  0.709456  22.763467  2448.189049  0.260172  0.069484   \n",
      "1452  ST-2621   1022  0.519569  25.057730  2439.972994  0.345401  0.020548   \n",
      "1453  ST-2622    183  0.672131  20.273224  3038.414645  0.316940  0.180328   \n",
      "1454  ST-2623   2156  0.656772  19.312152  1899.487727  0.210575  0.049165   \n",
      "1455  ST-2624    464  0.745690  14.172414  1716.279418  0.269397  0.077586   \n",
      "1456  ST-2625   2636  0.658953  19.040592  1915.737219  0.195372  0.069044   \n",
      "1457  ST-2626   1697  0.648203  21.289334  1925.363394  0.154390  0.059517   \n",
      "1458  ST-2627   1089  0.792470  20.723600  2420.464206  0.207530  0.021120   \n",
      "1459  ST-2628    373  0.710456  11.016086  1652.673056  0.257373  0.107239   \n",
      "1460  ST-2629   1877  0.573788  15.408631  1680.559707  0.254129  0.083644   \n",
      "1461  ST-2630   3277  0.637778  15.969179  1751.265743  0.240159  0.043332   \n",
      "1462  ST-2631    888  0.673423  17.771396  2001.859685  0.296171  0.072072   \n",
      "1463  ST-2632   1469  0.674609  17.660313  1998.624799  0.247107  0.031314   \n",
      "1464  ST-2633   2440  0.698770  18.475000  2432.857586  0.271311  0.090984   \n",
      "1465  ST-2634    868  0.707373  18.888249  2242.356509  0.289171  0.024194   \n",
      "1466  ST-2635   2708  0.546160  20.333087  2152.659790  0.267356  0.068316   \n",
      "1467  ST-2636   2948  0.564111  17.360583  1790.792534  0.278833  0.065807   \n",
      "1468  ST-2637   1453  0.622161  28.700619  3963.343765  0.167928  0.015141   \n",
      "1469  ST-2638    783  0.647510  16.151980  2160.876284  0.166028  0.021711   \n",
      "1470  ST-2639   1602  0.607990  25.393258  3241.726398  0.244694  0.053683   \n",
      "1471  ST-2641   1887  0.715951  18.926338  2387.498686  0.229465  0.101219   \n",
      "1472  ST-2642   4325  0.623121  12.482312  1545.326652  0.128786  0.022428   \n",
      "1473  ST-2643    880  0.767045  21.636364  2476.223000  0.153409  0.010227   \n",
      "1474  ST-2644    836  0.801435  22.935407  2700.677380  0.031100  0.004785   \n",
      "1475  ST-2645    775  0.827097  18.553548  1607.016581  0.089032  0.010323   \n",
      "1476  ST-2646   1104  0.746377  28.040761  2632.053451  0.150362  0.000000   \n",
      "1477  ST-2647    474  0.770042  27.755274  3275.837511  0.073840  0.000000   \n",
      "1478  ST-2648    379  0.786280  21.387863  2441.793113  0.229551  0.010554   \n",
      "1479  ST-2649   1079  0.699722  20.569972  2236.634634  0.266914  0.130677   \n",
      "1480   ST-265   2527  0.628809  24.165018  2128.824998  0.235853  0.048674   \n",
      "1481  ST-2650    454  0.764317  21.614537  3238.508392  0.310573  0.044053   \n",
      "1482  ST-2651    547  0.709324  22.363803  1852.618080  0.274223  0.073126   \n",
      "1483  ST-2652    785  0.756688  17.717197  2164.480866  0.268790  0.070064   \n",
      "1484  ST-2653   2602  0.647194  23.369331  3068.099377  0.275942  0.082629   \n",
      "1485  ST-2654   3240  0.664506  22.955247  2754.572040  0.275000  0.124074   \n",
      "1486  ST-2655   1898  0.674394  20.791359  2055.779299  0.168599  0.015806   \n",
      "1487  ST-2656    449  0.714922  27.806236  2684.847728  0.193764  0.033408   \n",
      "1488  ST-2657    373  0.817694  26.327078  2061.495845  0.168901  0.058981   \n",
      "1489  ST-2658   1124  0.597865  26.395018  3238.842082  0.243772  0.044484   \n",
      "1490  ST-2659   1603  0.628821  22.406737  2584.835608  0.258266  0.031815   \n",
      "1491   ST-266   1006  0.638171  32.691849  4260.155030  0.239563  0.021869   \n",
      "1492  ST-2661     55  0.654545  15.672727  1811.490545  0.200000  0.218182   \n",
      "1493  ST-2662    263  0.730038  15.893536  2206.533802  0.102662  0.045627   \n",
      "1494  ST-2663    744  0.516129  19.696237  1886.889059  0.262097  0.029570   \n",
      "1495  ST-2664    928  0.631466  33.688578  4602.285905  0.317888  0.037716   \n",
      "1496  ST-2665     40  0.600000  21.025000  3502.040500  0.225000  0.250000   \n",
      "1497  ST-2666    627  0.719298  25.258373  2755.779011  0.186603  0.035088   \n",
      "1498  ST-2667   1310  0.683206  24.660305  2609.810298  0.223664  0.011450   \n",
      "1499  ST-2668   2524  0.612520  21.990491  2497.849849  0.222662  0.037639   \n",
      "1500  ST-2669   1499  0.733155  23.523682  2713.062789  0.254837  0.074049   \n",
      "1501   ST-267   1313  0.694593  27.402133  2896.729223  0.246763  0.023610   \n",
      "1502  ST-2671   1252  0.725240  21.491214  2561.841166  0.151757  0.030351   \n",
      "1503  ST-2673   1405  0.503203  44.481851  5317.113680  0.258363  0.054093   \n",
      "1504  ST-2674   1013  0.628825  23.218164  2817.376071  0.198421  0.047384   \n",
      "1505  ST-2675    265  0.509434  26.320755  2711.595849  0.381132  0.033962   \n",
      "1506  ST-2676    610  0.698361  17.075410  2262.729082  0.226230  0.059016   \n",
      "1507  ST-2677    912  0.623904  21.883772  2689.591469  0.320175  0.049342   \n",
      "1508  ST-2678   2303  0.653930  21.737733  2468.958133  0.287451  0.048198   \n",
      "1509  ST-2679    760  0.598684  23.855263  2858.099566  0.211842  0.055263   \n",
      "1510   ST-268    539  0.749536  18.538033  2217.008312  0.192950  0.077922   \n",
      "1511  ST-2680    476  0.699580  31.817227  2609.949475  0.197479  0.039916   \n",
      "1512  ST-2681   1137  0.586631  20.096746  2485.116447  0.260334  0.075638   \n",
      "1513  ST-2682    346  0.693642  24.312139  3164.445318  0.222543  0.026012   \n",
      "1514  ST-2683    493  0.640974  24.833671  3088.067890  0.251521  0.030426   \n",
      "1515  ST-2684    436  0.711009  22.706422  2529.419197  0.282110  0.055046   \n",
      "1516  ST-2685    634  0.586751  27.580442  3837.063912  0.274448  0.020505   \n",
      "1517  ST-2686    393  0.562341  28.147583  3556.930458  0.274809  0.045802   \n",
      "1518  ST-2688   2676  0.527280  48.255605  7386.736839  0.355007  0.044469   \n",
      "1519  ST-2689   1829  0.749043  26.066703  2376.791110  0.202843  0.061782   \n",
      "1520   ST-269   3133  0.696776  22.628471  2664.605618  0.245452  0.038940   \n",
      "1521  ST-2690    366  0.617486  29.008197  3787.310219  0.259563  0.084699   \n",
      "1522  ST-2691    788  0.704315  21.467005  2294.747538  0.261421  0.036802   \n",
      "1523  ST-2692   2330  0.685408  13.075966  1566.157755  0.202146  0.011588   \n",
      "1524  ST-2693   3117  0.706128  22.803337  2187.447639  0.174206  0.006737   \n",
      "1525  ST-2694    477  0.635220  34.276730  4068.424088  0.299790  0.020964   \n",
      "1526  ST-2696    958  0.605428  16.938413  2027.927234  0.206681  0.058455   \n",
      "1527  ST-2697   1386  0.595960  19.011544  2372.868492  0.186147  0.039683   \n",
      "1528  ST-2698   1651  0.644458  16.387644  1644.653798  0.270139  0.030285   \n",
      "1529  ST-2699   2918  0.595956  20.030500  1808.800679  0.268677  0.062714   \n",
      "1530    ST-27    780  0.728205  17.708974  1899.399756  0.250000  0.044872   \n",
      "1531   ST-270   2419  0.693262  17.702356  1997.827313  0.260025  0.031005   \n",
      "1532  ST-2700   2284  0.563485  20.663748  2875.968778  0.278021  0.071366   \n",
      "1533  ST-2701   1820  0.654945  18.900000  2027.929610  0.253297  0.054396   \n",
      "1534  ST-2702   3754  0.666489  18.955781  2031.061185  0.234150  0.051145   \n",
      "1535  ST-2703   2497  0.599519  21.379255  2454.738638  0.259111  0.027633   \n",
      "1536  ST-2704   1236  0.627023  16.915858  2387.522654  0.204693  0.033981   \n",
      "1537  ST-2705   2095  0.726014  22.296420  2814.112382  0.217661  0.050597   \n",
      "1538  ST-2706   3321  0.587775  18.130684  1872.555185  0.261066  0.041253   \n",
      "1539  ST-2707   1405  0.617794  19.652669  2790.128014  0.269039  0.062633   \n",
      "1540  ST-2708    802  0.753117  19.345387  2415.429638  0.281796  0.036160   \n",
      "1541  ST-2709   2527  0.615354  18.856351  2171.806003  0.258013  0.049861   \n",
      "1542   ST-271   4687  0.639001  16.152123  1753.859296  0.211436  0.049712   \n",
      "1543  ST-2710   2084  0.579175  20.226967  2381.840043  0.278311  0.088292   \n",
      "1544  ST-2711   3467  0.646380  15.885203  1847.415472  0.272570  0.034900   \n",
      "1545  ST-2712    440  0.663636  18.450000  2353.583068  0.329545  0.011364   \n",
      "1546  ST-2713   1825  0.664658  21.146301  2648.600345  0.269589  0.052055   \n",
      "1547  ST-2714   2581  0.669120  19.433553  2570.508501  0.234405  0.058892   \n",
      "1548  ST-2715   1801  0.624098  30.028318  4386.218884  0.291505  0.043309   \n",
      "1549  ST-2716   2540  0.628740  15.931890  1671.645512  0.259055  0.061811   \n",
      "1550  ST-2717   1887  0.645999  17.196608  2101.963863  0.267091  0.076312   \n",
      "1551  ST-2718   8376  0.558142  21.766237  2973.559256  0.262178  0.028653   \n",
      "1552  ST-2719   2553  0.653349  15.996866  1796.957658  0.300039  0.029377   \n",
      "1553   ST-272   4717  0.659953  18.026288  1945.480278  0.225355  0.050880   \n",
      "1554  ST-2720    981  0.637105  22.602446  2480.399154  0.253823  0.014271   \n",
      "1555  ST-2722   1271  0.673485  20.576711  2740.125869  0.247836  0.112510   \n",
      "1556  ST-2723    855  0.699415  36.582456  5520.350035  0.432749  0.037427   \n",
      "1557  ST-2724   1784  0.584641  21.840247  2590.652377  0.243274  0.056614   \n",
      "1558  ST-2725    749  0.694259  18.738318  2395.470601  0.277704  0.056075   \n",
      "1559  ST-2726   5784  0.614799  19.944848  2327.084723  0.265041  0.040456   \n",
      "1560  ST-2727    300  0.623333  23.333333  2470.924833  0.356667  0.046667   \n",
      "1561  ST-2728    903  0.589147  34.349945  4150.598250  0.326689  0.028793   \n",
      "1562  ST-2729   2863  0.560950  17.641285  2128.450929  0.268949  0.039469   \n",
      "1563   ST-273   4716  0.635708  19.007846  2022.662326  0.245759  0.064673   \n",
      "1564  ST-2730   1319  0.606520  17.742987  2075.575823  0.280516  0.084913   \n",
      "1565  ST-2731   1969  0.609954  24.120874  3095.161828  0.277806  0.063992   \n",
      "1566  ST-2732   3325  0.594286  19.616842  2356.232508  0.271880  0.059850   \n",
      "1567  ST-2733   1266  0.657188  19.515798  2430.738807  0.282780  0.043444   \n",
      "1568  ST-2734    489  0.713701  18.754601  2056.986708  0.257669  0.055215   \n",
      "1569  ST-2736    725  0.693793  18.760000  1890.859945  0.227586  0.034483   \n",
      "1570  ST-2737    653  0.644717  23.886677  2773.053660  0.284839  0.052067   \n",
      "1571  ST-2738   4772  0.638516  20.510687  1885.338034  0.259011  0.050712   \n",
      "1572  ST-2739   1098  0.630237  19.305100  2059.257086  0.257741  0.054645   \n",
      "1573   ST-274   2482  0.599919  19.968171  2262.135359  0.272764  0.043916   \n",
      "1574  ST-2740   5863  0.579908  17.096708  1670.818958  0.235033  0.031895   \n",
      "1575  ST-2742   3400  0.607353  18.616176  1789.918185  0.254412  0.078235   \n",
      "1576  ST-2743    904  0.529867  32.360619  3327.443761  0.268805  0.054204   \n",
      "1577  ST-2744    816  0.674020  24.615196  3296.714375  0.193627  0.077206   \n",
      "1578  ST-2745    979  0.629213  22.309499  2628.989796  0.195097  0.043922   \n",
      "1579  ST-2746     52  0.673077  35.288462  5562.285192  0.423077  0.000000   \n",
      "1580  ST-2747   2858  0.723583  18.361791  2004.520175  0.242127  0.041638   \n",
      "1581  ST-2748   6133  0.631665  17.820153  1746.277743  0.214903  0.042231   \n",
      "1582  ST-2749   6886  0.670346  18.819344  1882.053124  0.276648  0.078856   \n",
      "1583   ST-275    509  0.726916  16.862475  2080.277132  0.241650  0.029470   \n",
      "1584  ST-2750    775  0.645161  18.087742  1946.548658  0.291613  0.037419   \n",
      "1585  ST-2751   2385  0.637317  20.050734  1890.910939  0.261635  0.106499   \n",
      "1586  ST-2752   1309  0.647823  15.284186  1895.518839  0.176471  0.026738   \n",
      "1587  ST-2753   1232  0.692370  23.688312  2578.339903  0.265422  0.085227   \n",
      "1588  ST-2754   1576  0.601523  23.381345  2838.324619  0.237310  0.019036   \n",
      "1589  ST-2756    771  0.527886  21.592737  2877.414241  0.300908  0.071336   \n",
      "1590  ST-2757   1352  0.576183  18.280325  2216.326361  0.282544  0.036982   \n",
      "1591  ST-2759   1932  0.666667  18.208592  2123.724472  0.268116  0.040890   \n",
      "1592   ST-276   2851  0.707120  22.634865  2637.401459  0.272887  0.072957   \n",
      "1593  ST-2760   6173  0.688158  16.202819  1665.448072  0.266645  0.038069   \n",
      "1594  ST-2761   6584  0.637151  19.584143  1919.330143  0.254557  0.049210   \n",
      "1595  ST-2762   2615  0.659656  20.078394  2125.092612  0.256597  0.096367   \n",
      "1596  ST-2763   1903  0.626905  16.985812  2073.841661  0.242249  0.018392   \n",
      "1597  ST-2764   5243  0.603471  16.164028  1635.121184  0.308220  0.024604   \n",
      "1598  ST-2765   6344  0.639975  15.736917  1638.878053  0.295240  0.022541   \n",
      "1599  ST-2767   2313  0.706874  18.960657  2277.883796  0.285344  0.063554   \n",
      "1600  ST-2768   1758  0.754835  19.831627  2342.307008  0.243458  0.067122   \n",
      "1601  ST-2769   1549  0.723047  14.909619  2071.410755  0.067140  0.010329   \n",
      "1602   ST-277   3991  0.628414  35.376597  4718.079386  0.329742  0.038086   \n",
      "1603  ST-2770   1913  0.742290  19.266597  2141.660387  0.252483  0.059592   \n",
      "1604  ST-2771   3017  0.737156  17.313225  2000.190792  0.261850  0.087173   \n",
      "1605  ST-2772    184  0.690217  26.695652  3163.096304  0.342391  0.027174   \n",
      "1606  ST-2773   2193  0.618331  16.305518  1828.091154  0.257182  0.031920   \n",
      "1607  ST-2774   4137  0.655789  20.585690  2200.903553  0.193619  0.013053   \n",
      "1608  ST-2775   2840  0.596831  17.459507  1872.487370  0.280634  0.038380   \n",
      "1609  ST-2776    961  0.663892  18.998959  2164.705442  0.268470  0.085328   \n",
      "1610  ST-2777   2140  0.634579  20.551402  2311.213570  0.274299  0.045794   \n",
      "1611  ST-2778   1838  0.663221  20.573449  2252.667214  0.232318  0.053863   \n",
      "1612  ST-2779    739  0.562923  33.144790  3751.736509  0.296346  0.040595   \n",
      "1613   ST-278   6301  0.589748  26.513093  2817.035182  0.262181  0.039041   \n",
      "1614  ST-2780    579  0.694301  18.091537  1951.850138  0.305699  0.031088   \n",
      "1615  ST-2781    277  0.754513  12.891697  1825.873105  0.220217  0.032491   \n",
      "1616  ST-2782   1122  0.598039  23.028520  2298.565009  0.237077  0.043672   \n",
      "1617  ST-2783    545  0.543119  20.607339  2541.043835  0.222018  0.053211   \n",
      "1618  ST-2785   1633  0.676669  20.155542  2397.718034  0.285364  0.073484   \n",
      "1619  ST-2786   2407  0.788533  15.087661  1839.033133  0.214375  0.013710   \n",
      "1620  ST-2787   2063  0.663597  23.264178  2678.568182  0.242365  0.070771   \n",
      "1621  ST-2788    683  0.715959  21.521230  2974.531772  0.243045  0.046852   \n",
      "1622  ST-2789   2929  0.616934  12.016388  1341.110959  0.246842  0.045749   \n",
      "1623   ST-279   3805  0.612089  30.445466  4002.790378  0.180552  0.032326   \n",
      "1624  ST-2790    349  0.747851  20.498567  2060.664269  0.263610  0.011461   \n",
      "1625  ST-2791   4935  0.594124  23.678825  2765.960946  0.327457  0.005066   \n",
      "1626  ST-2792   3148  0.632465  20.223952  1901.214686  0.251271  0.031766   \n",
      "1627  ST-2793   3800  0.635000  16.617632  1861.193145  0.213158  0.057368   \n",
      "1628  ST-2794   1176  0.698980  15.441327  1796.917619  0.249150  0.083333   \n",
      "1629  ST-2795    786  0.548346  17.162850  2519.944860  0.165394  0.053435   \n",
      "1630  ST-2796   5179  0.574049  19.817919  2208.383543  0.254296  0.053871   \n",
      "1631  ST-2797   5151  0.497185  22.706853  2242.166366  0.254125  0.073772   \n",
      "1632  ST-2798   1991  0.569563  16.632848  1981.505329  0.261678  0.033149   \n",
      "1633  ST-2799   3101  0.585295  36.642696  6441.358288  0.332796  0.031925   \n",
      "1634    ST-28   1966  0.730926  20.506104  2061.171623  0.212614  0.061038   \n",
      "1635   ST-280   3566  0.637970  18.654795  1648.747793  0.198822  0.031688   \n",
      "1636  ST-2800   1651  0.678982  19.932162  2110.854337  0.242883  0.058752   \n",
      "1637  ST-2801    795  0.693082  16.494340  1990.492252  0.247799  0.104403   \n",
      "1638  ST-2802    210  0.695238  18.190476  2043.491476  0.261905  0.042857   \n",
      "1639  ST-2803   1967  0.680224  17.965938  1994.120402  0.245552  0.043721   \n",
      "1640  ST-2804    904  0.595133  18.596239  2047.837865  0.285398  0.045354   \n",
      "1641  ST-2805    320  0.706250  23.175000  2174.809938  0.218750  0.212500   \n",
      "1642  ST-2806   2323  0.597934  15.994834  1558.950263  0.119673  0.012053   \n",
      "1643  ST-2807   4887  0.596685  17.583998  1738.243260  0.248619  0.072232   \n",
      "1644  ST-2808   1049  0.632031  17.938036  1857.495052  0.252622  0.120114   \n",
      "1645  ST-2809   2418  0.666667  18.992969  2116.444773  0.233251  0.064103   \n",
      "1646   ST-281   4544  0.624340  21.224912  2150.253242  0.193662  0.018486   \n",
      "1647  ST-2810   2637  0.708760  22.874099  2615.127899  0.293136  0.040576   \n",
      "1648  ST-2811   3564  0.746352  19.018238  2280.008639  0.184063  0.012626   \n",
      "1649  ST-2812   6655  0.674230  17.687904  1944.472696  0.206461  0.043276   \n",
      "1650  ST-2813   1125  0.657778  21.300444  2092.923191  0.245333  0.025778   \n",
      "1651  ST-2814   4112  0.705739  28.291586  3245.030581  0.204767  0.015321   \n",
      "1652  ST-2815   8926  0.583912  19.470087  2021.368304  0.332400  0.014004   \n",
      "1653  ST-2816   3407  0.678896  18.358673  2089.070883  0.242736  0.027884   \n",
      "1654  ST-2817   2733  0.555068  17.673985  1955.153249  0.248079  0.038419   \n",
      "1655  ST-2818   1717  0.625510  20.790332  2146.735824  0.263832  0.055911   \n",
      "1656  ST-2819   2114  0.701987  18.761116  2069.482417  0.244087  0.069063   \n",
      "1657   ST-282   1277  0.632733  18.018011  2114.973171  0.108066  0.023493   \n",
      "1658  ST-2820   7231  0.666574  17.053381  2056.945255  0.226940  0.046605   \n",
      "1659  ST-2821   1026  0.608187  16.565302  1757.458908  0.266082  0.109162   \n",
      "1660  ST-2822   7239  0.627435  17.150021  1557.012336  0.234287  0.041304   \n",
      "1661  ST-2823   4209  0.650036  20.794726  1849.843179  0.253504  0.056545   \n",
      "1662  ST-2824    813  0.639606  16.020910  1964.917626  0.261993  0.066421   \n",
      "1663  ST-2825   1892  0.716702  20.214588  2667.718832  0.281184  0.037526   \n",
      "1664  ST-2826   4485  0.593534  16.188183  1665.222381  0.247269  0.020290   \n",
      "1665  ST-2827   1031  0.677983  24.294859  3513.959593  0.281280  0.111542   \n",
      "1666  ST-2828    531  0.604520  24.621469  2691.394030  0.274953  0.065913   \n",
      "1667  ST-2829    311  0.742765  25.890675  3104.998682  0.250804  0.106109   \n",
      "1668   ST-283   1952  0.560451  16.898053  1676.858817  0.194160  0.027152   \n",
      "1669  ST-2830   1076  0.635688  20.749071  2720.197230  0.297398  0.051115   \n",
      "1670  ST-2831   2567  0.550058  12.967667  1245.229092  0.230230  0.033892   \n",
      "1671  ST-2832   3628  0.620728  11.613837  1372.992770  0.211411  0.034179   \n",
      "1672  ST-2833   5255  0.540628  18.392769  1611.828729  0.267555  0.055947   \n",
      "1673  ST-2834   1231  0.639318  28.720552  3319.962721  0.123477  0.020309   \n",
      "1674  ST-2835   4068  0.630039  18.632006  2369.563122  0.274828  0.081613   \n",
      "1675  ST-2837    866  0.703233  23.267898  2468.027021  0.249423  0.063510   \n",
      "1676  ST-2838    476  0.571429  22.310924  2504.958382  0.216387  0.048319   \n",
      "1677  ST-2839    736  0.557065  42.592391  6403.853342  0.285326  0.048913   \n",
      "1678   ST-284   1535  0.641694  18.091857  1844.791114  0.255375  0.041694   \n",
      "1679  ST-2841    483  0.631470  21.134576  2533.242650  0.265010  0.051760   \n",
      "1680  ST-2842   1722  0.646922  17.297329  1896.398891  0.278746  0.085366   \n",
      "1681  ST-2843   1915  0.615144  32.743081  5073.650016  0.253264  0.045431   \n",
      "1682  ST-2844   5470  0.618830  20.466362  2015.172547  0.271481  0.027239   \n",
      "1683  ST-2845   1745  0.731232  18.745559  2034.535054  0.139255  0.014900   \n",
      "1684  ST-2846   2326  0.600602  20.608340  2485.923633  0.253654  0.061049   \n",
      "1685  ST-2847   1046  0.589866  21.503824  2632.106759  0.179732  0.026769   \n",
      "1686  ST-2849   2025  0.739753  22.875556  2852.933817  0.259259  0.098272   \n",
      "1687   ST-285   5489  0.648023  19.166697  1995.490261  0.262889  0.038076   \n",
      "1688  ST-2850   1296  0.526235  37.451389  4821.255193  0.398148  0.028549   \n",
      "1689  ST-2851   2824  0.676346  16.710340  1796.556916  0.291431  0.067280   \n",
      "1690  ST-2852   1741  0.599081  16.035612  1631.738811  0.191844  0.034463   \n",
      "1691  ST-2853     94  0.936170  23.361702  4112.706383  0.276596  0.138298   \n",
      "1692  ST-2854   2069  0.641856  24.973900  2434.663842  0.284679  0.056066   \n",
      "1693  ST-2855   1094  0.701097  22.199269  2806.564808  0.295247  0.152651   \n",
      "1694  ST-2856    125  0.712000  18.960000  2266.800960  0.376000  0.136000   \n",
      "1695  ST-2857   3969  0.560091  13.891156  1303.764142  0.245150  0.009070   \n",
      "1696  ST-2858   3666  0.593562  10.450355  1140.285000  0.166394  0.030551   \n",
      "1697  ST-2859   1659  0.541290  19.981314  2200.134165  0.223629  0.051838   \n",
      "1698   ST-286   3618  0.692371  19.601437  2339.517778  0.263682  0.058872   \n",
      "1699  ST-2860   2614  0.662586  14.449503  1629.759881  0.253634  0.039021   \n",
      "1700  ST-2861   1610  0.564596  21.217391  2637.296453  0.336025  0.046584   \n",
      "1701  ST-2862    880  0.682955  20.363636  2201.761386  0.319318  0.069318   \n",
      "1702  ST-2865   6288  0.552004  17.431934  1743.000530  0.268607  0.068225   \n",
      "1703  ST-2866   1355  0.755720  20.415498  2581.135513  0.235424  0.071587   \n",
      "1704  ST-2867   1545  0.653074  18.938511  2049.521340  0.227184  0.014887   \n",
      "1705  ST-2868   1059  0.709160  19.293673  2406.296053  0.218130  0.089707   \n",
      "1706  ST-2869   1048  0.655534  21.560115  2507.642271  0.273855  0.060115   \n",
      "1707   ST-287   4476  0.545353  15.094951  1477.039294  0.129580  0.018097   \n",
      "1708  ST-2870   1536  0.705729  23.158854  2354.260768  0.180990  0.052083   \n",
      "1709  ST-2871   9413  0.576968  10.216615  1128.552704  0.192712  0.014448   \n",
      "1710  ST-2872    772  0.678756  20.279793  2301.078057  0.290155  0.075130   \n",
      "1711  ST-2873   2566  0.702650  22.509743  1880.915090  0.277475  0.118083   \n",
      "1712  ST-2874   1221  0.606880  23.979525  2886.062154  0.280098  0.026208   \n",
      "1713  ST-2875    402  0.646766  22.529851  2582.519478  0.296020  0.014925   \n",
      "1714  ST-2876   8298  0.512774  22.119306  2240.029638  0.282237  0.056640   \n",
      "1715  ST-2877    995  0.566834  20.927638  2102.790643  0.276382  0.040201   \n",
      "1716  ST-2878   1766  0.615515  22.273499  2339.783222  0.261042  0.066251   \n",
      "1717  ST-2879   2643  0.720772  19.764661  2402.907832  0.303065  0.094589   \n",
      "1718   ST-288   2866  0.589323  19.171319  1932.888664  0.191207  0.051989   \n",
      "1719  ST-2880    404  0.720297  27.792079  3780.901832  0.334158  0.108911   \n",
      "1720  ST-2882    869  0.714614  22.112773  2321.395374  0.247411  0.049482   \n",
      "1721  ST-2883   2907  0.664259  20.239766  2072.836106  0.239766  0.040592   \n",
      "1722  ST-2884   2874  0.605776  11.132220  1247.137032  0.188935  0.019137   \n",
      "1723  ST-2885    849  0.514723  13.930506  1508.620035  0.197880  0.027091   \n",
      "1724  ST-2886   3248  0.545874  12.847906  1432.806693  0.171798  0.018165   \n",
      "1725  ST-2887   2041  0.675159  24.803038  2759.254787  0.261146  0.048506   \n",
      "1726  ST-2888   5231  0.662015  15.651692  1631.247943  0.254062  0.051424   \n",
      "1727  ST-2889   4240  0.608019  10.663915  1216.959884  0.166981  0.010377   \n",
      "1728   ST-289   7057  0.638232  15.514241  1368.953903  0.233385  0.007085   \n",
      "1729  ST-2890   1929  0.618974  15.593572  1745.452649  0.246242  0.023328   \n",
      "1730  ST-2891   3642  0.605986  15.298462  1796.967861  0.224327  0.017298   \n",
      "1731  ST-2892   3952  0.603998  15.794787  1856.003811  0.242915  0.048836   \n",
      "1732  ST-2893    620  0.808065  19.445161  2436.167742  0.254839  0.083871   \n",
      "1733  ST-2894    922  0.552061  15.479393  2185.667267  0.214751  0.079176   \n",
      "1734  ST-2895    877  0.576967  17.192702  2405.163592  0.239453  0.044470   \n",
      "1735  ST-2896   3947  0.626298  18.188751  2095.405044  0.232328  0.055232   \n",
      "1736  ST-2897   2209  0.645541  21.383884  2627.043843  0.268900  0.046627   \n",
      "1737  ST-2898   2011  0.686226  17.208851  1794.337146  0.207360  0.031825   \n",
      "1738  ST-2899   1663  0.682502  28.754660  2664.766091  0.187011  0.016236   \n",
      "1739    ST-29    513  0.752437  19.181287  2142.428226  0.288499  0.099415   \n",
      "1740   ST-290   1672  0.714713  14.216507  1801.084629  0.239833  0.134569   \n",
      "1741  ST-2901   1460  0.579452  13.176027  1738.534562  0.265068  0.055479   \n",
      "1742  ST-2902   2868  0.653068  22.691771  2535.994836  0.264644  0.033473   \n",
      "1743  ST-2903   4041  0.566444  19.111854  2205.265006  0.269240  0.035635   \n",
      "1744  ST-2904   1475  0.543729  25.736271  3469.988041  0.246102  0.072542   \n",
      "1745  ST-2905  17620  0.493019  42.800000  5455.544369  0.413224  0.036720   \n",
      "1746  ST-2906   1475  0.591186  15.322034  1921.181593  0.279322  0.067119   \n",
      "1747  ST-2907   1254  0.624402  21.065391  2842.635845  0.299841  0.098884   \n",
      "1748  ST-2908   1406  0.660740  13.472262  1358.601679  0.204836  0.007112   \n",
      "1749  ST-2909    620  0.598387  19.058065  1848.939565  0.211290  0.014516   \n",
      "1750   ST-291   1816  0.701542  17.083150  2032.995402  0.312225  0.085352   \n",
      "1751  ST-2910    383  0.723238  19.665796  2849.391723  0.198433  0.041775   \n",
      "1752  ST-2911    171  0.543860  27.497076  3447.818246  0.239766  0.087719   \n",
      "1753  ST-2912    237  0.814346  14.713080  2085.117679  0.236287  0.177215   \n",
      "1754  ST-2913    539  0.751391  16.923933  2017.161540  0.261596  0.074212   \n",
      "1755  ST-2914   1359  0.565121  22.396615  2958.692038  0.300221  0.044150   \n",
      "1756  ST-2915   1856  0.587284  21.126616  2593.086988  0.230065  0.058190   \n",
      "1757  ST-2916   1113  0.642408  26.613657  3341.688203  0.248877  0.059299   \n",
      "1758  ST-2917    730  0.600000  18.995890  2226.916288  0.227397  0.045205   \n",
      "1759  ST-2918   2203  0.579210  20.905129  2059.733246  0.261008  0.057195   \n",
      "1760   ST-292   6099  0.608952  18.788490  1936.612625  0.219052  0.009510   \n",
      "1761  ST-2920   3541  0.639932  23.211240  2780.073318  0.216041  0.029935   \n",
      "1762  ST-2921   1562  0.585787  16.850192  1916.413355  0.263764  0.037772   \n",
      "1763  ST-2922   2171  0.569784  16.603409  1883.748881  0.281898  0.087057   \n",
      "1764  ST-2923    881  0.742338  17.195233  1958.189818  0.185017  0.037457   \n",
      "1765  ST-2924   3010  0.624585  27.426910  3593.277718  0.250831  0.051827   \n",
      "1766  ST-2925    577  0.745234  15.206239  1671.576378  0.164645  0.005199   \n",
      "1767  ST-2926    276  0.818841  20.489130  2030.990471  0.235507  0.028986   \n",
      "1768  ST-2927    428  0.785047  18.250000  2033.979042  0.140187  0.007009   \n",
      "1769  ST-2928   1267  0.595107  18.922652  1946.652084  0.219416  0.032360   \n",
      "1770  ST-2929   1071  0.850607  15.263305  1855.504818  0.119514  0.040149   \n",
      "1771   ST-293   3300  0.679394  19.615455  1857.786397  0.273030  0.043939   \n",
      "1772  ST-2931    511  0.747554  26.968689  2881.445695  0.246575  0.023483   \n",
      "1773  ST-2932   1478  0.590663  15.652233  1785.927348  0.224628  0.020974   \n",
      "1774  ST-2933    195  0.671795  20.076923  2876.921077  0.205128  0.076923   \n",
      "1775  ST-2934    452  0.674779  31.148230  2979.666150  0.272124  0.022124   \n",
      "1776  ST-2935   1725  0.698551  19.762899  2131.208609  0.264348  0.068986   \n",
      "1777  ST-2936    383  0.530026  25.255875  2384.319399  0.305483  0.083551   \n",
      "1778  ST-2937    350  0.660000  18.411429  2337.243543  0.214286  0.074286   \n",
      "1779  ST-2938    519  0.736031  21.574181  2225.026474  0.292871  0.102119   \n",
      "1780  ST-2939    198  0.681818  18.757576  2292.564141  0.348485  0.080808   \n",
      "1781   ST-294   5223  0.628757  15.123492  1481.588455  0.206012  0.028528   \n",
      "1782  ST-2940    687  0.700146  19.919942  2285.120393  0.308588  0.048035   \n",
      "1783  ST-2941    999  0.680681  18.788789  2511.330951  0.316316  0.132132   \n",
      "1784  ST-2942    694  0.693084  21.923631  2619.095115  0.121037  0.005764   \n",
      "1785  ST-2943   4194  0.593467  12.758226  1573.852442  0.211969  0.022890   \n",
      "1786  ST-2944   2518  0.655679  20.770056  2321.368666  0.248610  0.021843   \n",
      "1787  ST-2945   4210  0.661995  13.735392  1546.495135  0.152969  0.107126   \n",
      "1788  ST-2946   1366  0.669107  18.733529  2070.852921  0.254758  0.074671   \n",
      "1789  ST-2947    931  0.696026  19.717508  2616.799280  0.250269  0.021482   \n",
      "1790  ST-2948   1696  0.612618  19.038915  2297.858225  0.270637  0.160967   \n",
      "1791  ST-2949    405  0.730864  14.506173  1645.727728  0.276543  0.138272   \n",
      "1792   ST-295   9669  0.638225  18.629331  2100.989318  0.248319  0.024822   \n",
      "1793  ST-2952   1716  0.683566  15.385198  1839.448362  0.277389  0.057110   \n",
      "1794  ST-2953    747  0.689424  15.270415  1880.237122  0.262383  0.060241   \n",
      "1795  ST-2954    426  0.739437  14.687793  1549.650000  0.284038  0.070423   \n",
      "1796  ST-2955    327  0.724771  17.403670  2280.110948  0.311927  0.076453   \n",
      "1797  ST-2956    930  0.645161  15.076344  1783.130376  0.263441  0.079570   \n",
      "1798  ST-2957   1345  0.590335  20.220074  2357.732885  0.228253  0.127138   \n",
      "1799  ST-2958   3150  0.627302  23.455238  2630.773225  0.273968  0.068571   \n",
      "1800  ST-2959    909  0.690869  20.746975  2103.950121  0.272827  0.074807   \n",
      "1801   ST-296   2231  0.616316  41.630659  4706.285742  0.354101  0.013447   \n",
      "1802  ST-2960   4572  0.647638  17.332458  1806.705420  0.287620  0.023403   \n",
      "1803  ST-2961   2203  0.644122  18.072174  1890.392819  0.110304  0.002724   \n",
      "1804  ST-2962   1114  0.675045  22.464991  2105.106643  0.164273  0.024237   \n",
      "1805  ST-2964   1229  0.715216  30.931652  4489.884272  0.119609  0.025224   \n",
      "1806  ST-2965   5594  0.591705  11.943868  1336.089322  0.218091  0.046657   \n",
      "1807  ST-2966   1423  0.529164  18.966268  1817.556831  0.225580  0.056219   \n",
      "1808  ST-2967   2234  0.595792  21.888541  2682.827963  0.250671  0.060877   \n",
      "1809  ST-2969    822  0.727494  17.069343  1974.689453  0.249392  0.059611   \n",
      "1810   ST-297   2762  0.574222  48.965605  5795.921043  0.396090  0.026430   \n",
      "1811  ST-2970    152  0.789474  21.684211  1618.500461  0.243421  0.157895   \n",
      "1812  ST-2971   1111  0.594059  18.944194  2635.187102  0.258326  0.051305   \n",
      "1813  ST-2972   3867  0.615723  16.460305  2060.506002  0.104732  0.008017   \n",
      "1814  ST-2974   3712  0.639009  18.215517  1996.544704  0.207705  0.037446   \n",
      "1815  ST-2975   3191  0.612974  23.983391  2932.222883  0.285177  0.054842   \n",
      "1816  ST-2976   1230  0.586992  15.543902  1818.494163  0.279675  0.037398   \n",
      "1817  ST-2977   1775  0.579155  19.708169  2287.789854  0.242817  0.051831   \n",
      "1818  ST-2978   1445  0.686505  17.923183  2179.337543  0.251903  0.036678   \n",
      "1819  ST-2979   6001  0.512248  20.012665  2018.145131  0.250958  0.060823   \n",
      "1820   ST-298   1240  0.683871  17.554839  2095.549387  0.307258  0.080645   \n",
      "1821  ST-2980    821  0.646772  15.377588  1812.093496  0.265530  0.113276   \n",
      "1822  ST-2981   2425  0.648247  18.515464  2458.146445  0.156701  0.016082   \n",
      "1823  ST-2983    305  0.763934  15.659016  1793.634656  0.262295  0.009836   \n",
      "1824  ST-2984   2371  0.613665  23.313370  2639.982813  0.177562  0.006748   \n",
      "1825  ST-2985    527  0.702087  24.743833  3096.676926  0.227704  0.041746   \n",
      "1826  ST-2986   1450  0.604828  21.240690  2545.658531  0.257931  0.040000   \n",
      "1827  ST-2987   1307  0.637337  22.718439  2702.053573  0.266259  0.030604   \n",
      "1828  ST-2988   1899  0.584518  18.932596  1821.775255  0.261190  0.066351   \n",
      "1829  ST-2989    247  0.578947  25.773279  2019.161498  0.234818  0.020243   \n",
      "1830   ST-299   1787  0.663682  18.902630  2072.369351  0.263011  0.068830   \n",
      "1831  ST-2990    516  0.558140  22.265504  2716.523566  0.267442  0.073643   \n",
      "1832  ST-2991   3772  0.629639  19.241251  2127.034976  0.297190  0.022800   \n",
      "1833  ST-2992   2833  0.659019  17.877162  1978.886004  0.279915  0.077303   \n",
      "1834  ST-2993   5622  0.549093  12.882604  1336.636697  0.202063  0.015297   \n",
      "1835  ST-2994   2748  0.589520  16.758006  2118.854582  0.241266  0.047307   \n",
      "1836  ST-2995   1375  0.723636  20.640727  1809.214793  0.240000  0.084364   \n",
      "1837  ST-2996   2394  0.558062  14.919799  1918.611896  0.261905  0.047619   \n",
      "1838  ST-2997   1164  0.674399  20.496564  2283.308617  0.267182  0.096220   \n",
      "1839  ST-2999   1940  0.663918  24.980412  3889.767840  0.103093  0.021134   \n",
      "1840    ST-30   1729  0.659341  26.317525  2749.802140  0.271833  0.056102   \n",
      "1841   ST-300   3157  0.590751  21.692113  2044.045274  0.255306  0.060184   \n",
      "1842  ST-3002   4086  0.580029  22.410181  2257.433904  0.201175  0.029613   \n",
      "1843  ST-3003   3522  0.546281  27.543441  2413.959032  0.201874  0.014196   \n",
      "1844  ST-3004   1226  0.614192  19.460848  2367.776387  0.279772  0.047308   \n",
      "1845  ST-3005    687  0.506550  19.049491  2177.004876  0.285298  0.026201   \n",
      "1846  ST-3006   1646  0.638518  20.064399  2297.391555  0.288578  0.080194   \n",
      "1847  ST-3008   2686  0.633284  20.871929  2144.648649  0.263589  0.027923   \n",
      "1848  ST-3009    451  0.598670  15.006652  1785.797871  0.301552  0.026608   \n",
      "1849  ST-3011   2673  0.664422  17.153386  1587.470774  0.202394  0.044893   \n",
      "1850  ST-3012   2160  0.672685  15.155093  1899.406037  0.271759  0.049537   \n",
      "1851  ST-3013   3128  0.602302  19.010230  2237.828283  0.281330  0.043478   \n",
      "1852  ST-3015   4188  0.590974  19.214900  1927.149269  0.290592  0.048233   \n",
      "1853  ST-3017   2147  0.587797  36.671169  4728.489832  0.322776  0.065673   \n",
      "1854  ST-3019   1029  0.639456  28.103984  3412.491759  0.261419  0.098154   \n",
      "1855   ST-302   3013  0.732493  17.557584  1887.572808  0.235646  0.084965   \n",
      "1856  ST-3020    644  0.692547  22.608696  2999.058494  0.239130  0.035714   \n",
      "1857  ST-3021    784  0.693878  21.382653  2286.839732  0.255102  0.049745   \n",
      "1858  ST-3022     50  0.780000  21.600000  2876.861000  0.320000  0.140000   \n",
      "1859  ST-3023   1562  0.675416  16.820102  2194.233630  0.213828  0.023688   \n",
      "1860  ST-3024   1150  0.575652  16.559130  2193.040070  0.260000  0.026087   \n",
      "1861  ST-3025   1150  0.673043  20.896522  1925.642217  0.270435  0.064348   \n",
      "1862  ST-3026   2013  0.712866  15.947839  1956.232300  0.241927  0.063090   \n",
      "1863  ST-3027    462  0.800866  18.781385  1930.302208  0.212121  0.056277   \n",
      "1864  ST-3028    327  0.675841  16.620795  2001.750612  0.275229  0.051988   \n",
      "1865  ST-3029   2862  0.577918  11.923829  1388.331709  0.233054  0.034591   \n",
      "1866   ST-303   3018  0.699801  16.202121  1851.649394  0.295229  0.104374   \n",
      "1867  ST-3030   1640  0.648171  21.498780  2053.959061  0.218293  0.029878   \n",
      "1868  ST-3031   1822  0.821076  15.943469  2016.512887  0.096048  0.008782   \n",
      "1869  ST-3032   1300  0.700000  17.580769  2698.676738  0.203846  0.101538   \n",
      "1870  ST-3033   1266  0.574250  26.661137  3903.788081  0.269352  0.028436   \n",
      "1871  ST-3034    193  0.746114  21.461140  3316.145699  0.243523  0.134715   \n",
      "1872  ST-3035    999  0.795796  18.932933  2272.394885  0.224224  0.028028   \n",
      "1873  ST-3036    431  0.649652  18.013921  2723.926543  0.317865  0.051044   \n",
      "1874  ST-3037   1079  0.645042  14.943466  2037.714217  0.207600  0.065802   \n",
      "1875  ST-3038   1442  0.481276  16.498613  1394.137053  0.138696  0.027046   \n",
      "1876  ST-3039   1557  0.448940  15.991651  1310.885890  0.154785  0.041105   \n",
      "1877   ST-304   2226  0.723720  15.933064  1764.129034  0.286613  0.101527   \n",
      "1878  ST-3040   2290  0.641048  23.275546  3183.300672  0.294760  0.124891   \n",
      "1879  ST-3041    461  0.707158  13.780911  1727.218416  0.245119  0.101952   \n",
      "1880  ST-3042   2895  0.555095  27.721244  3438.870249  0.208981  0.042832   \n",
      "1881  ST-3043   4860  0.554527  16.752058  1889.194885  0.132305  0.019136   \n",
      "1882  ST-3044   3256  0.645270  16.851044  1794.350541  0.101351  0.025799   \n",
      "1883  ST-3045    103  0.825243  26.077670  2954.726602  0.398058  0.135922   \n",
      "1884  ST-3046   3559  0.626019  19.781961  2444.875780  0.235178  0.073616   \n",
      "1885  ST-3047   2287  0.608220  15.937473  1455.833533  0.197639  0.034543   \n",
      "1886  ST-3048    449  0.830735  15.579065  1901.088864  0.207127  0.086860   \n",
      "1887  ST-3049   1914  0.567398  25.563741  3334.131505  0.297283  0.026123   \n",
      "1888  ST-3050   1171  0.574722  17.560205  2303.432878  0.225448  0.023057   \n",
      "1889  ST-3051   2463  0.705644  20.121803  2403.395510  0.208283  0.059683   \n",
      "1890  ST-3052   1431  0.738644  25.338225  2284.547358  0.157932  0.060098   \n",
      "1891  ST-3053   1174  0.694208  15.028961  1833.329693  0.175468  0.051959   \n",
      "1892  ST-3054   1516  0.751319  34.164248  2659.978885  0.281003  0.015172   \n",
      "1893  ST-3055    758  0.733509  16.638522  2082.517164  0.197889  0.067282   \n",
      "1894  ST-3056   1340  0.682836  24.385075  2898.420015  0.325373  0.092537   \n",
      "1895  ST-3057    690  0.728986  24.966667  2948.899899  0.182609  0.028986   \n",
      "1896  ST-3058    938  0.609808  21.662047  2787.800640  0.254797  0.051173   \n",
      "1897  ST-3059   1368  0.547515  19.499269  2045.991703  0.258772  0.059211   \n",
      "1898   ST-306   3438  0.674229  16.177720  1690.959186  0.238511  0.009308   \n",
      "1899  ST-3060   6687  0.630627  17.428742  2015.582641  0.272619  0.085390   \n",
      "1900  ST-3061   2105  0.784798  21.586698  2222.799150  0.163895  0.014252   \n",
      "1901  ST-3062   1817  0.637865  23.062190  2222.644816  0.266924  0.075399   \n",
      "1902  ST-3063   1384  0.667630  22.343931  2785.776575  0.197254  0.018064   \n",
      "1903  ST-3064    421  0.743468  22.760095  2674.082162  0.311164  0.078385   \n",
      "1904  ST-3065    235  0.685106  25.902128  3461.003404  0.336170  0.046809   \n",
      "1905  ST-3066    702  0.631054  39.091168  4785.064117  0.227920  0.081197   \n",
      "1906  ST-3067    611  0.888707  15.252046  2296.272455  0.147300  0.000000   \n",
      "1907  ST-3068   3025  0.696529  15.563636  1944.939964  0.186116  0.030413   \n",
      "1908  ST-3069    665  0.521805  23.212030  2672.577158  0.395489  0.024060   \n",
      "1909   ST-307   5564  0.731668  21.204170  2548.480602  0.216391  0.037383   \n",
      "1910  ST-3070   4715  0.625663  19.815695  2163.766210  0.265323  0.040085   \n",
      "1911  ST-3071   1358  0.590574  20.094993  2179.232901  0.255523  0.043446   \n",
      "1912  ST-3072   7194  0.672505  27.360161  3244.522848  0.205449  0.008757   \n",
      "1913  ST-3073   2895  0.703972  27.334715  3274.869979  0.168566  0.013817   \n",
      "1914  ST-3075   1733  0.687825  21.908252  2245.351506  0.170225  0.036930   \n",
      "1915  ST-3076    621  0.706924  14.299517  1593.512061  0.247987  0.033816   \n",
      "1916  ST-3077   2630  0.673004  29.680228  3468.374692  0.191635  0.033840   \n",
      "1917  ST-3078    833  0.591837  34.420168  4251.421248  0.260504  0.057623   \n",
      "1918  ST-3079   2067  0.670537  31.834543  4165.047775  0.184325  0.022738   \n",
      "1919   ST-308   2644  0.637670  23.056354  3004.063313  0.256808  0.086611   \n",
      "1920  ST-3080   1525  0.695082  19.981639  1972.917954  0.238033  0.042623   \n",
      "1921  ST-3081    892  0.656951  26.894619  2917.552881  0.289238  0.070628   \n",
      "1922  ST-3082   1519  0.624753  17.958525  2070.433219  0.276498  0.033575   \n",
      "1923  ST-3083   1241  0.642224  36.364222  4540.252006  0.427075  0.041096   \n",
      "1924  ST-3084   5313  0.648033  15.103708  1537.413934  0.223602  0.046490   \n",
      "1925  ST-3085   2673  0.641227  17.363262  1877.376180  0.267864  0.043023   \n",
      "1926  ST-3086   2913  0.596292  34.209406  4385.633292  0.350154  0.041538   \n",
      "1927  ST-3087   2144  0.625000  20.039179  2231.319585  0.224813  0.037313   \n",
      "1928  ST-3088    429  0.671329  17.048951  1969.088368  0.153846  0.053613   \n",
      "1929  ST-3089   3007  0.632192  19.152644  2404.723469  0.255737  0.038577   \n",
      "1930   ST-309   4000  0.642250  20.062000  1991.606027  0.243250  0.055000   \n",
      "1931  ST-3090   2024  0.719368  19.767292  1866.682258  0.158103  0.008893   \n",
      "1932  ST-3091    629  0.643879  18.852146  2047.649682  0.224165  0.063593   \n",
      "1933  ST-3092   2812  0.596728  29.428876  3652.562735  0.290541  0.097084   \n",
      "1934  ST-3093    535  0.762617  27.783178  3841.510991  0.358879  0.024299   \n",
      "1935  ST-3094   8844  0.586047  15.802578  1637.426364  0.238128  0.016621   \n",
      "1936  ST-3095   3549  0.649760  25.848972  3274.229794  0.278670  0.071006   \n",
      "1937  ST-3096    584  0.613014  31.484589  3887.827295  0.234589  0.113014   \n",
      "1938  ST-3097    379  0.686016  19.881266  2446.772612  0.261214  0.073879   \n",
      "1939  ST-3098   2661  0.602405  36.738068  4611.645971  0.374295  0.030440   \n",
      "1940  ST-3099   2792  0.564828  19.458095  2170.043023  0.207020  0.066977   \n",
      "1941    ST-31   1660  0.698193  23.263855  2479.865880  0.256024  0.049398   \n",
      "1942   ST-310   3972  0.565458  15.145519  1705.963847  0.259315  0.030211   \n",
      "1943  ST-3100   2729  0.604984  17.556614  1805.942833  0.192012  0.042873   \n",
      "1944  ST-3101   1305  0.652107  21.514176  3081.650797  0.271264  0.038314   \n",
      "1945  ST-3102   2047  0.708354  17.885686  2237.093351  0.267220  0.081094   \n",
      "1946  ST-3103    425  0.625882  20.070588  2383.237624  0.207059  0.091765   \n",
      "1947  ST-3104   9028  0.623505  16.039211  1666.702926  0.244351  0.052171   \n",
      "1948  ST-3105   8041  0.589976  27.184554  3139.213789  0.279940  0.042035   \n",
      "1949  ST-3106    444  0.704955  28.939189  3679.187432  0.281532  0.159910   \n",
      "1950  ST-3107    511  0.729941  19.000000  2290.304149  0.264188  0.050881   \n",
      "1951  ST-3108    424  0.688679  26.254717  2683.176108  0.231132  0.082547   \n",
      "1952  ST-3109    771  0.701686  17.813230  2024.687938  0.195850  0.041505   \n",
      "1953   ST-311   5623  0.666192  16.178730  1637.670802  0.254846  0.021519   \n",
      "1954  ST-3110   1349  0.662713  16.991846  1736.984077  0.194959  0.046701   \n",
      "1955  ST-3111    808  0.693069  29.248762  3153.001757  0.221535  0.080446   \n",
      "1956  ST-3112   1756  0.705581  30.208428  3431.165569  0.223235  0.027335   \n",
      "1957  ST-3113   2328  0.503866  26.082045  3336.415378  0.275344  0.051546   \n",
      "1958  ST-3114   1206  0.502488  24.244610  3615.549569  0.255390  0.016584   \n",
      "1959  ST-3115    524  0.774809  23.328244  2732.603588  0.139313  0.041985   \n",
      "1960  ST-3116   3991  0.518166  22.068905  1986.874375  0.267853  0.052618   \n",
      "1961  ST-3117   1902  0.592534  22.770242  2231.810605  0.276025  0.011041   \n",
      "1962  ST-3118   1441  0.689105  23.749480  3196.247745  0.122831  0.013185   \n",
      "1963  ST-3119   2418  0.613730  20.915219  2242.936844  0.250620  0.049628   \n",
      "1964   ST-312   5295  0.546742  17.664400  1608.725890  0.227195  0.033428   \n",
      "1965  ST-3120   1977  0.561963  17.745068  2176.001912  0.163379  0.038442   \n",
      "1966  ST-3121   1619  0.592959  21.618283  2302.856597  0.242742  0.043854   \n",
      "1967  ST-3122   1690  0.737870  19.402959  2175.260953  0.248521  0.092308   \n",
      "1968  ST-3123   1405  0.756584  18.933096  1781.174093  0.279715  0.030605   \n",
      "1969  ST-3124   1963  0.671931  18.372389  2121.854249  0.064187  0.010188   \n",
      "1970  ST-3125   2334  0.614396  20.827335  2288.611632  0.259640  0.056984   \n",
      "1971  ST-3126   1047  0.756447  14.170965  1606.024365  0.288443  0.064947   \n",
      "1972  ST-3127    694  0.729107  18.416427  2596.584568  0.243516  0.020173   \n",
      "1973  ST-3128   3169  0.615021  11.622909  1332.437050  0.054276  0.002524   \n",
      "1974  ST-3129   3799  0.692287  18.395630  2385.033804  0.248223  0.028165   \n",
      "1975   ST-313   1948  0.727413  15.355236  1815.806355  0.226899  0.050308   \n",
      "1976  ST-3130   2195  0.649658  16.135763  1881.974241  0.215034  0.032346   \n",
      "1977  ST-3131   1761  0.579784  19.223169  2278.641925  0.245315  0.023850   \n",
      "1978  ST-3133    709  0.648801  19.255289  2222.352779  0.286319  0.086037   \n",
      "1979  ST-3134    565  0.688496  16.819469  2497.833027  0.269027  0.037168   \n",
      "1980  ST-3135   1328  0.658133  21.670934  2209.428652  0.276355  0.044428   \n",
      "1981  ST-3136   2058  0.656948  22.863460  2686.279140  0.171040  0.029155   \n",
      "1982  ST-3137   1367  0.622531  15.092173  2039.206598  0.115582  0.024872   \n",
      "1983  ST-3138    896  0.695312  19.822545  2294.375335  0.244420  0.040179   \n",
      "1984  ST-3139   2193  0.442772  22.493844  3021.594181  0.219790  0.013224   \n",
      "1985  ST-3140   1523  0.592252  25.806960  2634.018155  0.267892  0.058437   \n",
      "1986  ST-3141   1781  0.559798  19.684447  1876.424413  0.263335  0.039304   \n",
      "1987  ST-3142   8491  0.674243  20.457661  2478.843202  0.271935  0.056766   \n",
      "1988  ST-3143   1101  0.722071  25.585831  3167.469537  0.250681  0.057221   \n",
      "1989  ST-3144    494  0.763158  22.340081  2366.412692  0.222672  0.036437   \n",
      "1990  ST-3145   2605  0.625720  12.479846  1464.254119  0.127831  0.018810   \n",
      "1991  ST-3146   1463  0.628845  20.516063  2696.735537  0.239234  0.151059   \n",
      "1992  ST-3147   1582  0.733881  18.140329  2113.596593  0.301517  0.069532   \n",
      "1993  ST-3148   1645  0.590274  21.141033  2169.320316  0.250456  0.040729   \n",
      "1994  ST-3149   1487  0.724950  18.600538  1982.004311  0.228648  0.028245   \n",
      "1995   ST-315   7578  0.614806  16.318158  1548.708775  0.231987  0.015835   \n",
      "1996  ST-3150    401  0.593516  18.645885  2100.092918  0.234414  0.024938   \n",
      "1997  ST-3151   1131  0.549072  19.883289  2262.211733  0.282051  0.007958   \n",
      "1998  ST-3152   1173  0.590793  22.949702  2703.848338  0.252344  0.052003   \n",
      "1999  ST-3153   1846  0.567714  19.968039  2466.702324  0.260563  0.099675   \n",
      "2000  ST-3154    288  0.736111  21.187500  2313.641562  0.361111  0.072917   \n",
      "2001  ST-3155    771  0.805447  21.826200  2653.195746  0.306096  0.077821   \n",
      "2002  ST-3156    179  0.748603  16.882682  1902.766034  0.061453  0.000000   \n",
      "2003  ST-3157     42  0.642857  15.619048  2550.333810  0.142857  0.000000   \n",
      "2004  ST-3158    298  0.614094  18.530201  2600.417987  0.281879  0.033557   \n",
      "2005  ST-3159    799  0.733417  23.254068  2394.514280  0.219024  0.045056   \n",
      "2006   ST-316   1361  0.751653  13.535636  1641.712506  0.260103  0.059515   \n",
      "2007  ST-3160   2770  0.645848  30.689892  3705.476700  0.318773  0.024549   \n",
      "2008  ST-3161    443  0.735892  24.934537  2177.976998  0.209932  0.024831   \n",
      "2009  ST-3162   1959  0.541603  19.598775  2005.861685  0.244002  0.063298   \n",
      "2010  ST-3163   5433  0.676606  18.183508  2023.774152  0.251979  0.029450   \n",
      "2011  ST-3164    423  0.647754  29.846336  4214.900284  0.215130  0.044917   \n",
      "2012  ST-3165   1398  0.670959  17.708870  1916.775644  0.234621  0.047210   \n",
      "2013  ST-3166    782  0.700767  20.787724  2275.930128  0.285166  0.106138   \n",
      "2014  ST-3167   2098  0.636320  18.338894  1818.549185  0.265014  0.058627   \n",
      "2015  ST-3168   2648  0.698263  27.758686  3601.588191  0.352719  0.071752   \n",
      "2016  ST-3169   1302  0.665899  16.609063  2285.369363  0.275730  0.073733   \n",
      "2017   ST-317   1197  0.710109  17.290727  2216.047602  0.182122  0.043442   \n",
      "2018  ST-3170   1165  0.714163  20.638627  2253.507863  0.257511  0.038627   \n",
      "2019  ST-3171   2117  0.737837  20.283420  2057.309556  0.269721  0.078885   \n",
      "2020  ST-3172   1953  0.651306  17.461342  2112.706446  0.230415  0.067076   \n",
      "2021  ST-3173    562  0.692171  24.711744  2473.558559  0.270463  0.065836   \n",
      "2022  ST-3174   2154  0.606314  15.572888  1703.043055  0.194986  0.023677   \n",
      "2023  ST-3175   1963  0.539480  23.263882  3005.224824  0.306673  0.045848   \n",
      "2024  ST-3177   1942  0.660659  22.129248  2961.569238  0.193100  0.031411   \n",
      "2025  ST-3178    425  0.651765  26.484706  3116.251882  0.315294  0.025882   \n",
      "2026  ST-3179   1086  0.649171  19.481584  2440.955138  0.231123  0.063536   \n",
      "2027   ST-318   2440  0.659836  13.765984  1785.969922  0.245902  0.024180   \n",
      "2028  ST-3180    228  0.824561  17.828947  2302.454211  0.184211  0.026316   \n",
      "2029  ST-3181    111  0.594595  16.198198  2415.843694  0.261261  0.072072   \n",
      "2030  ST-3182   2263  0.683164  21.931065  2648.050486  0.171896  0.023420   \n",
      "2031  ST-3183    237  0.586498  19.008439  2167.327975  0.299578  0.156118   \n",
      "2032  ST-3184    623  0.712681  23.492777  2468.138604  0.248796  0.077047   \n",
      "2033  ST-3185   1335  0.653933  18.955805  2071.614801  0.213483  0.032959   \n",
      "2034  ST-3186   2595  0.618882  24.571484  2806.230686  0.241233  0.099037   \n",
      "2035  ST-3187   6556  0.642007  16.324893  1738.662323  0.252135  0.030049   \n",
      "2036  ST-3188   4189  0.598950  17.293626  1714.046262  0.239437  0.036286   \n",
      "2037  ST-3189   1150  0.735652  13.424348  1513.323626  0.191304  0.026087   \n",
      "2038   ST-319   1230  0.675610  17.607317  2219.532545  0.181301  0.071545   \n",
      "2039  ST-3192    357  0.641457  26.042017  3936.089384  0.210084  0.042017   \n",
      "2040  ST-3193    653  0.626340  30.381317  2421.235804  0.292496  0.041348   \n",
      "2041  ST-3194   2115  0.666667  17.167376  2102.039381  0.216548  0.062411   \n",
      "2042  ST-3195   2016  0.639385  22.791171  2793.198204  0.300595  0.017361   \n",
      "2043  ST-3196   1233  0.662612  14.595296  1599.991111  0.240065  0.047040   \n",
      "2044  ST-3197    527  0.502846  15.827324  2065.324820  0.269450  0.039848   \n",
      "2045  ST-3198   1285  0.645136  23.306615  2322.768825  0.278599  0.019455   \n",
      "2046  ST-3199   1234  0.710697  24.534846  2885.842002  0.299838  0.129660   \n",
      "2047    ST-32   3474  0.632700  21.649971  2442.094963  0.270294  0.045481   \n",
      "2048   ST-320   1675  0.576716  21.472239  2272.027994  0.203582  0.059104   \n",
      "2049  ST-3200   1358  0.735641  22.798969  2347.333306  0.232695  0.033137   \n",
      "2050  ST-3201    282  0.723404  10.627660  1745.910922  0.308511  0.124113   \n",
      "2051  ST-3202   1113  0.714286  16.357592  1784.676640  0.135669  0.023360   \n",
      "2052  ST-3203   1703  0.628303  22.688197  2540.969178  0.319436  0.026424   \n",
      "2053  ST-3204   3724  0.634801  17.891515  2120.487401  0.242481  0.044039   \n",
      "2054  ST-3205    569  0.534271  36.500879  3481.462812  0.397188  0.008787   \n",
      "2055  ST-3206    707  0.690240  22.899576  2318.269958  0.229137  0.110325   \n",
      "2056  ST-3207   1303  0.634689  23.133538  2363.040806  0.302379  0.026861   \n",
      "2057  ST-3208    552  0.623188  24.007246  2491.618152  0.244565  0.052536   \n",
      "2058  ST-3209   1356  0.679204  16.286873  1604.113695  0.281711  0.058260   \n",
      "2059   ST-321   2047  0.631656  15.842697  1962.682447  0.214460  0.036639   \n",
      "2060  ST-3210   2228  0.674596  21.806104  1879.980426  0.259874  0.046230   \n",
      "2061  ST-3211   1285  0.602335  18.639689  2744.566506  0.235019  0.075486   \n",
      "2062  ST-3212   4658  0.590382  17.962430  1650.501949  0.275440  0.043796   \n",
      "2063  ST-3213    453  0.637969  18.940397  2435.888102  0.278146  0.048565   \n",
      "2064  ST-3214   9102  0.600088  20.874094  2167.002390  0.275544  0.068996   \n",
      "2065  ST-3215   1536  0.705729  20.446615  2230.330671  0.231771  0.048828   \n",
      "2066  ST-3216     80  0.625000  30.337500  4085.455375  0.400000  0.012500   \n",
      "2067  ST-3218    884  0.645928  20.684389  2431.359152  0.280543  0.030543   \n",
      "2068  ST-3219   2810  0.694306  11.440925  1436.625470  0.210676  0.052669   \n",
      "2069   ST-322   1999  0.626313  22.514257  2707.119220  0.251126  0.072536   \n",
      "2070  ST-3220    282  0.528369  13.411348  2036.358191  0.237589  0.049645   \n",
      "2071  ST-3221   1022  0.536204  24.564579  2856.199335  0.240705  0.018591   \n",
      "2072  ST-3222    341  0.782991  19.354839  2490.006628  0.263930  0.052786   \n",
      "2073  ST-3223   1925  0.667532  13.600000  1483.723922  0.171948  0.019740   \n",
      "2074  ST-3224   1420  0.725352  15.723944  1911.433585  0.244366  0.054930   \n",
      "2075  ST-3225   4110  0.881752  10.154745  1367.625363  0.225061  0.002433   \n",
      "2076  ST-3226   4790  0.510021  16.731733  1701.199889  0.299374  0.035073   \n",
      "2077  ST-3227    686  0.816327  18.523324  2156.638032  0.278426  0.016035   \n",
      "2078  ST-3228    627  0.614035  17.208931  1863.009410  0.202552  0.014354   \n",
      "2079  ST-3230   2549  0.590035  19.790114  2244.370302  0.208709  0.051000   \n",
      "2080  ST-3232    383  0.639687  24.232376  3132.290757  0.250653  0.049608   \n",
      "2081  ST-3233   1168  0.678938  23.767123  3250.890180  0.267123  0.035103   \n",
      "2082  ST-3234    945  0.813757  24.583069  2834.934952  0.277249  0.120635   \n",
      "2083  ST-3235   4094  0.601124  16.380801  1781.202667  0.182462  0.020762   \n",
      "2084  ST-3236   1158  0.833333  13.870466  1550.786822  0.185665  0.025907   \n",
      "2085  ST-3237    627  0.663477  13.456140  1618.460877  0.245614  0.148325   \n",
      "2086  ST-3238   2789  0.745428  24.067766  2289.139387  0.283256  0.101829   \n",
      "2087  ST-3239   4868  0.687962  37.858463  4580.763164  0.276294  0.015407   \n",
      "2088   ST-324    762  0.635171  21.011811  2423.675446  0.263780  0.038058   \n",
      "2089  ST-3240   1242  0.536232  28.657810  3255.757464  0.258454  0.015298   \n",
      "2090  ST-3241   1442  0.675451  18.099168  1721.208218  0.194175  0.065881   \n",
      "2091  ST-3242   1018  0.564833  18.581532  1987.718153  0.209234  0.052063   \n",
      "2092  ST-3243    484  0.609504  26.216942  3548.227665  0.237603  0.064050   \n",
      "2093  ST-3244   1128  0.654255  19.451241  2501.656215  0.258865  0.022163   \n",
      "2094  ST-3245    495  0.632323  15.107071  1813.111232  0.280808  0.046465   \n",
      "2095  ST-3247    952  0.735294  19.456933  2144.399496  0.260504  0.107143   \n",
      "2096  ST-3248   2767  0.608963  18.311529  2063.890726  0.236718  0.038670   \n",
      "2097  ST-3249   1226  0.557912  38.988581  4327.550604  0.400489  0.047308   \n",
      "2098   ST-325    170  0.747059  33.805882  4927.292294  0.258824  0.041176   \n",
      "2099  ST-3250    810  0.698765  16.029630  1769.042716  0.285185  0.053086   \n",
      "2100  ST-3251   4383  0.651837  11.229751  1335.507495  0.022359  0.002282   \n",
      "2101  ST-3252   1552  0.664948  21.142397  2158.034259  0.208763  0.034794   \n",
      "2102  ST-3253   2229  0.650516  19.909376  2465.423306  0.302826  0.052939   \n",
      "2103  ST-3254    527  0.592030  28.091082  4111.941689  0.248577  0.161290   \n",
      "2104  ST-3255    679  0.733432  18.447717  1873.923358  0.157585  0.010309   \n",
      "2105  ST-3256   2042  0.641038  17.841822  1880.617889  0.262488  0.064643   \n",
      "2106  ST-3257     31  0.870968  27.129032  4270.973871  0.225806  0.193548   \n",
      "2107  ST-3258   2877  0.671185  22.741050  2643.913601  0.265554  0.055266   \n",
      "2108  ST-3259   1071  0.749767  13.687208  1652.242185  0.065359  0.007470   \n",
      "2109   ST-326   2121  0.610090  16.133899  1812.223206  0.253182  0.070721   \n",
      "2110  ST-3260   1512  0.794312  13.401455  1573.720456  0.068122  0.010582   \n",
      "2111  ST-3261    918  0.714597  12.462963  1286.234129  0.053377  0.015251   \n",
      "2112  ST-3262   1574  0.645489  15.524142  1776.094994  0.301779  0.024142   \n",
      "2113  ST-3263    425  0.997647  22.567059  2393.761365  0.117647  0.014118   \n",
      "2114  ST-3264   1430  0.687413  25.115385  3050.873147  0.320280  0.073427   \n",
      "2115  ST-3265   1267  0.505919  25.556433  3238.524333  0.149961  0.023678   \n",
      "2116  ST-3266    396  0.623737  19.664141  1912.094646  0.244949  0.113636   \n",
      "2117  ST-3267    830  0.604819  22.280723  2310.881807  0.244578  0.051807   \n",
      "2118  ST-3268    192  0.588542  20.151042  2398.609635  0.234375  0.020833   \n",
      "2119  ST-3269    310  0.732258  20.338710  1829.421645  0.222581  0.054839   \n",
      "2120   ST-327   1655  0.756495  19.473716  2401.043837  0.221148  0.025982   \n",
      "2121  ST-3270     95  0.578947  25.442105  3206.162737  0.168421  0.021053   \n",
      "2122  ST-3271    102  0.764706  15.490196  1771.618431  0.205882  0.078431   \n",
      "2123  ST-3272    578  0.660900  30.636678  2602.452111  0.231834  0.029412   \n",
      "2124  ST-3273    157  0.624204  14.662420  1928.733185  0.356688  0.063694   \n",
      "2125  ST-3274    191  0.659686  20.816754  2155.035236  0.256545  0.015707   \n",
      "2126  ST-3275     24  0.875000   9.833333  1455.043333  0.208333  0.000000   \n",
      "2127  ST-3276    350  0.717143  16.514286  1684.219629  0.228571  0.094286   \n",
      "2128  ST-3277     28  0.571429  11.607143  1629.912857  0.107143  0.000000   \n",
      "2129  ST-3278     40  0.750000  15.875000  1949.003500  0.125000  0.025000   \n",
      "2130  ST-3279     74  0.824324  24.270270  2283.095541  0.283784  0.108108   \n",
      "2131   ST-328   2044  0.723581  25.282779  2664.137696  0.213796  0.037182   \n",
      "2132  ST-3280     23  0.391304  13.695652  1265.184783  0.173913  0.043478   \n",
      "2133  ST-3281      4  0.500000  64.750000  3386.245000  0.250000  0.250000   \n",
      "2134   ST-329    746  0.589812  25.615282  2871.778351  0.388740  0.034853   \n",
      "2135    ST-33   3494  0.603320  27.920721  3779.729098  0.292501  0.057813   \n",
      "2136   ST-330   1301  0.614912  41.654112  5594.678663  0.249039  0.066872   \n",
      "2137   ST-331   1103  0.670898  24.184044  3220.551777  0.292838  0.087035   \n",
      "2138   ST-332    795  0.637736  16.821384  2203.143849  0.215094  0.030189   \n",
      "2139   ST-333    337  0.658754  18.629080  2158.387774  0.320475  0.091988   \n",
      "2140   ST-334   1546  0.663648  19.919793  2387.847995  0.250323  0.055627   \n",
      "2141   ST-335   2382  0.648615  25.605793  3382.870911  0.295130  0.087322   \n",
      "2142   ST-336   2834  0.645025  21.638673  2285.095113  0.189132  0.021171   \n",
      "2143   ST-338   2459  0.727125  23.311915  2402.869573  0.206181  0.040260   \n",
      "2144   ST-339   1905  0.438845  41.137533  5342.510772  0.396850  0.023622   \n",
      "2145   ST-340   1816  0.523128  37.412996  4509.266498  0.388216  0.045154   \n",
      "2146   ST-341   4094  0.463605  18.616023  2072.193930  0.250122  0.045677   \n",
      "2147   ST-342   4555  0.528869  22.959385  2398.165458  0.271131  0.062349   \n",
      "2148   ST-343   1599  0.642902  29.646654  4169.083852  0.322076  0.060663   \n",
      "2149   ST-344   3872  0.550362  47.498709  4074.827771  0.537965  0.010589   \n",
      "2150   ST-345   1353  0.587583  17.790835  2181.202683  0.243902  0.045824   \n",
      "2151   ST-346   1445  0.626298  24.353633  3634.006152  0.252595  0.058824   \n",
      "2152   ST-347   2018  0.625867  19.349851  2193.590426  0.255203  0.052032   \n",
      "2153   ST-348   1058  0.602079  17.662571  2603.914291  0.231569  0.031191   \n",
      "2154   ST-349   2463  0.515631  20.557856  2774.915644  0.276086  0.058059   \n",
      "2155    ST-35   3610  0.522992  29.254294  3648.323510  0.296953  0.053463   \n",
      "2156   ST-350   3119  0.600192  26.487015  3608.031157  0.280218  0.051619   \n",
      "2157   ST-351   1300  0.516154  20.489231  2272.094738  0.275385  0.060000   \n",
      "2158   ST-352    721  0.592233  19.320388  2089.320791  0.242718  0.054092   \n",
      "2159   ST-354   1261  0.568596  20.821570  2605.730119  0.217288  0.084853   \n",
      "2160   ST-357    161  0.596273  32.596273  4911.670248  0.397516  0.037267   \n",
      "2161   ST-358   3102  0.623469  18.094778  2047.246493  0.223082  0.055448   \n",
      "2162   ST-359   2961  0.643364  22.377237  2604.639895  0.226613  0.066532   \n",
      "2163    ST-36   1443  0.645877  26.095634  2440.560485  0.285516  0.065142   \n",
      "2164   ST-360   3903  0.662567  22.611581  2545.736395  0.275429  0.032027   \n",
      "2165   ST-361   4598  0.578947  19.769465  2102.868723  0.251196  0.045455   \n",
      "2166   ST-362   3349  0.538071  24.872201  2511.962831  0.219468  0.017020   \n",
      "2167   ST-363   2411  0.562007  18.119038  2040.421626  0.242638  0.052675   \n",
      "2168   ST-364   3073  0.630979  20.895216  2129.628467  0.125936  0.027009   \n",
      "2169   ST-365    343  0.702624  23.889213  2978.494431  0.291545  0.241983   \n",
      "2170   ST-366   6850  0.586715  44.089051  6606.470466  0.316204  0.033869   \n",
      "2171   ST-368   7250  0.598759  17.917103  1930.069859  0.179586  0.017931   \n",
      "2172   ST-369   4645  0.565554  17.969860  2301.899897  0.279440  0.046502   \n",
      "2173    ST-37   1107  0.628726  20.941283  2295.509169  0.242096  0.048780   \n",
      "2174   ST-370    495  0.755556  19.795960  2761.046889  0.307071  0.119192   \n",
      "2175   ST-371   3065  0.561175  18.549755  2287.273511  0.155954  0.034258   \n",
      "2176   ST-372   1873  0.657234  22.114255  2443.289007  0.231180  0.069941   \n",
      "2177   ST-375   3866  0.597258  27.421624  2151.116048  0.191930  0.021211   \n",
      "2178   ST-376   8830  0.579502  41.116082  6335.085955  0.340657  0.040883   \n",
      "2179   ST-377   4860  0.610288  16.672634  1897.228160  0.264815  0.056584   \n",
      "2180   ST-378   1779  0.608207  23.789207  2647.686976  0.320967  0.051152   \n",
      "2181   ST-379   1937  0.559112  27.796593  3978.680367  0.252969  0.110480   \n",
      "2182   ST-381    893  0.647256  26.562150  2269.225039  0.240761  0.050392   \n",
      "2183   ST-382   2708  0.584564  17.632570  1705.073840  0.175037  0.022526   \n",
      "2184   ST-384   3512  0.574886  14.775911  1831.171350  0.250285  0.036731   \n",
      "2185   ST-385   5207  0.602842  21.710966  2646.756069  0.275783  0.048012   \n",
      "2186   ST-386   1148  0.703833  23.905052  2322.637517  0.233449  0.040941   \n",
      "2187   ST-387   3506  0.658871  23.311466  2638.544578  0.290930  0.081004   \n",
      "2188   ST-388   3090  0.563754  26.447573  3511.572974  0.308091  0.079935   \n",
      "2189   ST-389   1048  0.735687  19.761450  2165.967672  0.279580  0.034351   \n",
      "2190    ST-39    963  0.623053  20.205607  2286.544611  0.242991  0.111111   \n",
      "2191   ST-390   2775  0.732973  22.206486  2460.978883  0.287207  0.047928   \n",
      "2192   ST-391   3520  0.718182  19.585795  1970.306861  0.253125  0.053409   \n",
      "2193   ST-392   3173  0.656792  18.601009  1941.041859  0.236369  0.042231   \n",
      "2194   ST-394   3132  0.610792  27.075990  3664.254700  0.236909  0.047573   \n",
      "2195   ST-395   2732  0.698023  22.166545  2743.405461  0.275988  0.092606   \n",
      "2196   ST-396   1713  0.737303  18.176299  2122.903030  0.223001  0.038529   \n",
      "2197   ST-397   4645  0.670398  21.639182  2114.353938  0.189236  0.032508   \n",
      "2198   ST-398   6994  0.643266  19.254647  2108.258250  0.206034  0.046325   \n",
      "2199     ST-4   5904  0.517446  26.042514  2380.577266  0.292005  0.058096   \n",
      "2200    ST-40   1127  0.700976  19.034605  2043.074082  0.254658  0.104703   \n",
      "2201   ST-400   6073  0.681871  23.520830  2659.861457  0.270377  0.058620   \n",
      "2202   ST-401   5213  0.698254  24.775945  2631.206046  0.236716  0.072703   \n",
      "2203   ST-402   3363  0.631876  20.804639  2476.744362  0.238180  0.064823   \n",
      "2204   ST-403   1041  0.640730  18.951009  2073.484121  0.179635  0.048991   \n",
      "2205   ST-404   2192  0.630931  19.772354  2485.629238  0.202555  0.060675   \n",
      "2206   ST-405   1118  0.827370  23.149374  2332.425590  0.189624  0.031306   \n",
      "2207   ST-406   1068  0.788390  15.492509  1526.348436  0.272472  0.039326   \n",
      "2208   ST-407   2131  0.710934  22.754575  2517.024355  0.245894  0.033318   \n",
      "2209   ST-408   4561  0.605350  24.086823  2855.011572  0.262004  0.030695   \n",
      "2210   ST-409   3041  0.606379  17.489642  2011.318829  0.242683  0.033870   \n",
      "2211    ST-41   1440  0.677083  19.097222  2303.613118  0.178472  0.021528   \n",
      "2212   ST-410   3660  0.602459  28.612022  3492.980484  0.251093  0.027596   \n",
      "2213   ST-413  13154  0.651665  17.996655  1527.269682  0.229360  0.040140   \n",
      "2214   ST-414   1343  0.702159  32.712584  4410.598012  0.280715  0.020849   \n",
      "2215   ST-416   8042  0.621487  17.555334  1823.236098  0.236260  0.023377   \n",
      "2216   ST-417   7054  0.682450  17.795577  1913.834874  0.201446  0.036859   \n",
      "2217   ST-418   2459  0.707605  18.480683  1752.811387  0.228142  0.056527   \n",
      "2218   ST-419   3147  0.638386  19.398157  1707.544973  0.212901  0.040356   \n",
      "2219    ST-42   1018  0.773084  19.325147  2148.880196  0.189587  0.042240   \n",
      "2220   ST-420   2807  0.636266  19.603491  1863.115383  0.244389  0.076594   \n",
      "2221   ST-421   4072  0.676817  26.172642  3075.217785  0.229617  0.060904   \n",
      "2222   ST-422   4538  0.661084  19.151829  1997.009132  0.260467  0.052446   \n",
      "2223   ST-424   2673  0.740367  27.894501  2727.897097  0.135428  0.017583   \n",
      "2224   ST-425    952  0.684874  29.853992  3388.575483  0.288866  0.025210   \n",
      "2225   ST-426   9478  0.603186  38.217029  5398.601802  0.326862  0.020574   \n",
      "2226   ST-428   2896  0.622583  16.537638  1750.637465  0.234116  0.018301   \n",
      "2227    ST-43    592  0.697635  22.699324  2425.409172  0.217905  0.099662   \n",
      "2228   ST-431   3267  0.624732  15.065810  1560.096997  0.242424  0.067952   \n",
      "2229   ST-432   1562  0.654289  18.704866  2000.309366  0.248399  0.049936   \n",
      "2230   ST-435   2940  0.619388  21.599320  2736.693058  0.245918  0.028571   \n",
      "2231   ST-436   1683  0.565657  16.810458  2229.935342  0.256090  0.042781   \n",
      "2232   ST-437   2674  0.553104  19.451758  2181.725108  0.237098  0.065071   \n",
      "2233   ST-438   3155  0.639620  17.831696  2050.384935  0.250079  0.030428   \n",
      "2234   ST-439   1574  0.713469  21.428208  2303.975216  0.227446  0.076239   \n",
      "2235   ST-440    793  0.678436  18.527112  2084.840769  0.262295  0.032787   \n",
      "2236   ST-441    522  0.699234  22.848659  2426.133314  0.252874  0.024904   \n",
      "2237   ST-442   4155  0.587244  41.873887  6014.923483  0.404813  0.029844   \n",
      "2238   ST-443   1991  0.553993  27.014566  2708.933677  0.306881  0.029633   \n",
      "2239   ST-444    937  0.606190  15.922092  1912.937951  0.274280  0.091782   \n",
      "2240   ST-445   6355  0.577183  16.829111  1677.811149  0.221873  0.056176   \n",
      "2241   ST-446   8504  0.590663  24.729539  2889.856482  0.244473  0.049036   \n",
      "2242   ST-447   1499  0.672448  19.159440  2300.048492  0.260841  0.052702   \n",
      "2243   ST-448   1472  0.641984  21.887908  2019.469171  0.194973  0.016304   \n",
      "2244    ST-45    368  0.880435  19.684783  2061.901250  0.048913  0.008152   \n",
      "2245   ST-450    985  0.669036  12.231472  1306.398234  0.250761  0.059898   \n",
      "2246   ST-451   1465  0.679181  15.525597  1658.844758  0.306485  0.038225   \n",
      "2247   ST-452   1464  0.629781  17.315574  2098.910908  0.327869  0.069672   \n",
      "2248   ST-453   4529  0.715611  19.527710  2075.438152  0.280857  0.037757   \n",
      "2249   ST-454   5179  0.596254  21.369376  2587.765547  0.279011  0.087855   \n",
      "2250   ST-455   6676  0.541342  26.584931  3395.852382  0.296585  0.042840   \n",
      "2251   ST-456   2597  0.645745  20.648441  2317.996873  0.284174  0.081633   \n",
      "2252   ST-457   1063  0.707432  18.611477  2521.558993  0.222013  0.048918   \n",
      "2253   ST-459   3717  0.608555  20.063223  2203.401679  0.267689  0.056497   \n",
      "2254    ST-46   2732  0.625183  31.620791  3221.978902  0.218155  0.019766   \n",
      "2255   ST-460   4018  0.656546  21.703833  2654.264550  0.266551  0.081135   \n",
      "2256   ST-461   4282  0.510509  18.130079  1984.592123  0.269967  0.009108   \n",
      "2257   ST-462   4538  0.592772  28.295505  3874.119625  0.291538  0.052226   \n",
      "2258   ST-463   2770  0.607220  27.644765  3345.005671  0.253069  0.045487   \n",
      "2259   ST-464   2513  0.615599  18.319538  1974.255714  0.262236  0.098687   \n",
      "2260   ST-465   2485  0.650704  16.624950  1904.866736  0.207243  0.036620   \n",
      "2261   ST-467   1419  0.598309  22.128964  2264.904397  0.241720  0.076110   \n",
      "2262   ST-469    316  0.626582  16.889241  1856.391361  0.180380  0.025316   \n",
      "2263    ST-47   6653  0.684203  29.609349  3259.155346  0.204419  0.010371   \n",
      "2264   ST-470   1152  0.683160  23.428819  2133.638628  0.242188  0.078125   \n",
      "2265   ST-471   1212  0.672442  18.748350  2114.231081  0.281353  0.075083   \n",
      "2266   ST-472    256  0.636719  18.871094  2362.797969  0.265625  0.023438   \n",
      "2267   ST-473   1334  0.613193  22.847826  2150.253051  0.230135  0.082459   \n",
      "2268   ST-475   1070  0.638318  21.808411  2159.799458  0.262617  0.076636   \n",
      "2269   ST-476    509  0.542240  27.555992  2895.115815  0.392927  0.009823   \n",
      "2270   ST-478   1589  0.617999  19.586532  2334.569924  0.239773  0.057898   \n",
      "2271   ST-479   5670  0.576720  19.890829  2370.861219  0.264374  0.052734   \n",
      "2272   ST-480   2141  0.552546  22.557683  2650.374475  0.269500  0.043438   \n",
      "2273   ST-481   3703  0.559006  23.094788  2579.794456  0.269781  0.055901   \n",
      "2274   ST-482   3251  0.601046  25.028299  2434.345198  0.210704  0.028607   \n",
      "2275   ST-483   3938  0.552311  28.386998  3121.995653  0.291265  0.050279   \n",
      "2276   ST-485   2716  0.557806  20.339838  2392.774297  0.276141  0.073270   \n",
      "2277   ST-486   3690  0.623848  21.502981  2506.648504  0.310569  0.075881   \n",
      "2278   ST-487   1879  0.588079  21.100585  1994.927036  0.291112  0.052155   \n",
      "2279   ST-488   2697  0.588802  25.542084  2895.688528  0.285873  0.054876   \n",
      "2280   ST-490    258  0.627907  19.631783  2189.763876  0.224806  0.034884   \n",
      "2281   ST-491    303  0.801980  34.854785  2647.463102  0.409241  0.006601   \n",
      "2282   ST-492   6381  0.632659  24.269080  2745.799618  0.271117  0.061903   \n",
      "2283   ST-493   8740  0.545538  22.386499  2106.039049  0.280778  0.033524   \n",
      "2284   ST-494   5223  0.605591  17.782500  1911.701388  0.233582  0.109133   \n",
      "2285   ST-495   5644  0.595854  19.533664  2035.246417  0.250000  0.068923   \n",
      "2286   ST-496   2603  0.512486  20.281598  1958.885682  0.255474  0.059931   \n",
      "2287   ST-497   4446  0.598740  17.406208  1435.296565  0.205803  0.027890   \n",
      "2288   ST-499   1429  0.735479  21.334500  2314.701372  0.279916  0.074178   \n",
      "2289     ST-5   4851  0.555349  27.725624  2770.878883  0.310864  0.062461   \n",
      "2290    ST-50   2076  0.692197  22.615125  2225.882018  0.151734  0.017823   \n",
      "2291   ST-500   1236  0.601942  19.991909  2073.572273  0.256472  0.100324   \n",
      "2292   ST-501   3054  0.623772  20.511788  2180.981274  0.284217  0.054355   \n",
      "2293   ST-502   7367  0.606896  16.784037  1692.813786  0.247862  0.051853   \n",
      "2294   ST-503   6451  0.570764  17.849326  1748.437300  0.198264  0.017982   \n",
      "2295   ST-504   2533  0.536518  17.348598  1948.709660  0.226609  0.058429   \n",
      "2296   ST-505   2623  0.599695  17.371712  1744.822703  0.252002  0.079299   \n",
      "2297   ST-506   8918  0.579839  24.838080  2107.308590  0.227181  0.014353   \n",
      "2298   ST-507    396  0.734848  21.234848  2746.265934  0.239899  0.055556   \n",
      "2299   ST-508   5096  0.670918  15.866366  1709.742192  0.225667  0.071625   \n",
      "2300   ST-509    949  0.633298  27.008430  2443.498124  0.310854  0.004215   \n",
      "2301    ST-51   3384  0.719267  21.830378  2078.402157  0.117612  0.012707   \n",
      "2302   ST-510   3230  0.697214  17.113313  1773.089294  0.245201  0.103096   \n",
      "2303   ST-511   1631  0.674433  18.649908  1942.052299  0.259963  0.072961   \n",
      "2304   ST-512   4791  0.550198  15.409518  1477.488641  0.268420  0.037153   \n",
      "2305   ST-513   7612  0.588807  13.619023  1464.940786  0.238045  0.050184   \n",
      "2306   ST-514   3944  0.698022  15.875000  1889.647343  0.264959  0.069726   \n",
      "2307   ST-516   5587  0.642384  20.504922  2339.657875  0.219259  0.031502   \n",
      "2308   ST-517   2789  0.730011  17.299390  2050.294783  0.277877  0.081391   \n",
      "2309   ST-518   3068  0.465776  20.222295  2003.914837  0.285854  0.042699   \n",
      "2310   ST-519   2337  0.607189  24.165597  3173.238036  0.299101  0.026102   \n",
      "2311    ST-52   3278  0.679683  31.918548  3334.395406  0.225137  0.007627   \n",
      "2312   ST-520   4004  0.600899  38.125375  5506.501319  0.329171  0.027972   \n",
      "2313   ST-522   8876  0.550924  15.089455  1528.783199  0.278053  0.022871   \n",
      "2314   ST-523   3654  0.594143  19.521073  1759.141352  0.267652  0.042419   \n",
      "2315   ST-524   3658  0.661290  17.776107  1818.857419  0.264079  0.081465   \n",
      "2316   ST-525   3972  0.614552  17.998238  1925.329328  0.238671  0.053877   \n",
      "2317   ST-526    950  0.704211  16.267368  1902.613379  0.270526  0.087368   \n",
      "2318   ST-528   3885  0.615444  17.463835  2224.389483  0.202831  0.060746   \n",
      "2319    ST-53   4644  0.709948  29.102498  3080.288770  0.223084  0.026916   \n",
      "2320   ST-530   3860  0.638860  16.227461  1965.370927  0.222798  0.039896   \n",
      "2321   ST-531   1431  0.714186  18.292103  2118.080538  0.255066  0.062194   \n",
      "2322   ST-532    896  0.731027  22.016741  2321.808036  0.203125  0.030134   \n",
      "2323   ST-533   1448  0.707873  18.102210  2193.586657  0.191298  0.064917   \n",
      "2324   ST-534   3937  0.608077  24.163068  2104.151689  0.244856  0.064008   \n",
      "2325   ST-535   3222  0.656425  22.833333  2877.883634  0.276536  0.074178   \n",
      "2326   ST-536   1293  0.643465  20.793503  2287.539095  0.283063  0.184841   \n",
      "2327   ST-538   2163  0.592233  19.591308  2249.971063  0.215442  0.058252   \n",
      "2328   ST-539   2401  0.556435  28.002915  3329.088817  0.274885  0.033736   \n",
      "2329   ST-540   1943  0.589810  26.920741  2389.121801  0.248585  0.039115   \n",
      "2330   ST-541   4347  0.588452  19.728318  1904.885671  0.239936  0.044398   \n",
      "2331   ST-542   4686  0.626761  19.459667  1845.289733  0.208920  0.011310   \n",
      "2332   ST-543    463  0.552916  17.058315  2201.044471  0.269978  0.023758   \n",
      "2333   ST-544   3046  0.603086  19.520026  2157.778257  0.263624  0.032830   \n",
      "2334   ST-545   1484  0.662399  17.810647  1891.446611  0.260782  0.031671   \n",
      "2335   ST-546   3824  0.588651  23.038180  2268.443415  0.269090  0.067207   \n",
      "2336   ST-547   7228  0.557692  28.217349  2791.398557  0.293304  0.042612   \n",
      "2337   ST-548   2302  0.581234  27.661164  2927.711347  0.276281  0.059079   \n",
      "2338   ST-549   1849  0.463494  17.167117  2091.646382  0.159005  0.017307   \n",
      "2339    ST-55   4003  0.687734  29.569323  3303.061002  0.247065  0.008993   \n",
      "2340   ST-550   4541  0.527637  19.649637  1902.311782  0.308743  0.008588   \n",
      "2341   ST-551   2080  0.592308  19.630288  1892.847784  0.259615  0.059615   \n",
      "2342   ST-553   4215  0.586477  22.830605  2244.808871  0.288968  0.071886   \n",
      "2343   ST-555   3838  0.638874  25.064878  3238.542897  0.241793  0.050287   \n",
      "2344   ST-558   2837  0.638350  23.679944  3112.692630  0.291505  0.082129   \n",
      "2345   ST-559    543  0.740331  19.279926  2573.205727  0.235727  0.104972   \n",
      "2346   ST-560    606  0.805281  26.508251  2599.964571  0.235974  0.112211   \n",
      "2347   ST-561   1826  0.635816  20.084885  2033.003461  0.261774  0.072289   \n",
      "2348   ST-562    579  0.773748  21.678756  2422.035820  0.257340  0.112263   \n",
      "2349   ST-563   2471  0.766896  20.766087  2124.346572  0.266694  0.090652   \n",
      "2350   ST-564   2393  0.603427  23.662766  2596.277158  0.224822  0.067697   \n",
      "2351   ST-565   2417  0.696731  19.400910  2226.579139  0.228382  0.044270   \n",
      "2352   ST-566   1862  0.672395  19.605800  2239.409463  0.288937  0.078947   \n",
      "2353   ST-567    782  0.710997  21.381074  2323.320141  0.274936  0.026854   \n",
      "2354   ST-568   1378  0.682148  15.050798  1580.138708  0.224964  0.021045   \n",
      "2355   ST-570   1925  0.617143  21.142857  2302.857242  0.227532  0.048831   \n",
      "2356   ST-571    893  0.643897  23.972004  2618.196529  0.235162  0.044793   \n",
      "2357   ST-572   1791  0.569514  19.534338  2362.897677  0.237856  0.109436   \n",
      "2358   ST-573    575  0.613913  20.925217  2556.537270  0.325217  0.067826   \n",
      "2359   ST-574   2388  0.648241  20.623534  2496.598677  0.262144  0.042714   \n",
      "2360   ST-578   3528  0.633220  23.549320  2869.692951  0.261621  0.063776   \n",
      "2361   ST-579   2876  0.594228  22.488873  2228.905640  0.246175  0.057371   \n",
      "2362   ST-580   2263  0.642510  21.891295  1940.543142  0.224481  0.079982   \n",
      "2363   ST-583    506  0.598814  16.996047  2534.149012  0.284585  0.033597   \n",
      "2364   ST-584    910  0.717582  19.734066  2709.218714  0.267033  0.098901   \n",
      "2365   ST-585   1611  0.589696  18.794538  2507.757784  0.272502  0.031657   \n",
      "2366   ST-586    712  0.747191  15.634831  2093.099199  0.227528  0.023876   \n",
      "2367   ST-587    331  0.688822  22.151057  3299.499366  0.265861  0.163142   \n",
      "2368   ST-588    437  0.615561  17.812357  2050.129199  0.228833  0.009153   \n",
      "2369   ST-589   1323  0.756614  18.195767  2189.447332  0.211640  0.056689   \n",
      "2370    ST-59   4904  0.714519  20.136215  2011.128777  0.150082  0.013458   \n",
      "2371   ST-590    881  0.590238  20.170261  2624.330136  0.290579  0.043133   \n",
      "2372   ST-593    776  0.621134  16.091495  2289.809214  0.274485  0.054124   \n",
      "2373   ST-594    838  0.693317  16.321002  2182.732315  0.252983  0.029833   \n",
      "2374   ST-595   1473  0.639511  22.798371  2986.464372  0.237610  0.120842   \n",
      "2375   ST-596   4336  0.647140  17.057426  2352.860390  0.251153  0.033902   \n",
      "2376   ST-599   2876  0.530946  16.264604  1604.688414  0.195758  0.036509   \n",
      "2377     ST-6   3031  0.616298  30.800066  2873.024494  0.280435  0.054108   \n",
      "2378    ST-60   3142  0.750796  28.235201  2302.659554  0.106302  0.007002   \n",
      "2379   ST-600   8311  0.726868  15.129347  1932.363995  0.257851  0.052461   \n",
      "2380   ST-602   2404  0.598170  19.740849  2237.445653  0.244176  0.082363   \n",
      "2381   ST-603   5566  0.566655  21.869386  2776.375792  0.250988  0.035932   \n",
      "2382   ST-604   5140  0.706420  16.215564  1675.191506  0.230934  0.043580   \n",
      "2383   ST-605   2671  0.621864  18.166604  2114.646417  0.254961  0.043804   \n",
      "2384   ST-608    771  0.552529  23.067445  2783.851064  0.317769  0.024643   \n",
      "2385   ST-609    542  0.529520  24.566421  3106.120590  0.202952  0.075646   \n",
      "2386   ST-610   3828  0.541536  18.234848  1856.181565  0.231191  0.029258   \n",
      "2387   ST-611   6919  0.569446  20.463795  1964.411437  0.281399  0.055933   \n",
      "2388   ST-612   1800  0.645000  20.748889  2447.729833  0.302778  0.091111   \n",
      "2389   ST-613   1198  0.671119  18.201169  2001.607204  0.286311  0.029215   \n",
      "2390   ST-614   2626  0.613861  23.406321  2429.935720  0.210586  0.027037   \n",
      "2391   ST-615   2316  0.653713  17.327288  1888.711813  0.235320  0.085492   \n",
      "2392   ST-616   1887  0.640700  17.852146  2115.895718  0.225755  0.081611   \n",
      "2393   ST-619   2795  0.709123  17.620394  2498.242880  0.163506  0.025403   \n",
      "2394    ST-62   4410  0.742177  23.031293  2430.443467  0.171202  0.015646   \n",
      "2395   ST-620   2194  0.754330  17.395169  2282.225314  0.152689  0.015953   \n",
      "2396   ST-621   1491  0.739101  22.790074  3480.366030  0.132126  0.022803   \n",
      "2397   ST-622   2267  0.790472  12.973974  1794.980049  0.045876  0.004411   \n",
      "2398   ST-623   1777  0.832864  18.211030  2201.070687  0.078222  0.008441   \n",
      "2399   ST-624   1404  0.748575  18.529202  1747.446011  0.170228  0.030627   \n",
      "2400   ST-625   2196  0.653461  14.490437  1678.476849  0.213570  0.019126   \n",
      "2401   ST-626    318  0.704403  25.078616  2440.706635  0.261006  0.050314   \n",
      "2402   ST-628    449  0.663697  27.222717  4165.545122  0.265033  0.106904   \n",
      "2403   ST-629   1291  0.710302  23.753679  2306.693703  0.276530  0.064291   \n",
      "2404    ST-63   2453  0.668569  21.838565  2400.730766  0.214839  0.026906   \n",
      "2405   ST-630   1208  0.694536  20.687914  2385.894288  0.218543  0.045530   \n",
      "2406   ST-631    551  0.700544  15.724138  1603.991615  0.201452  0.041742   \n",
      "2407   ST-632   3120  0.611218  33.467949  4918.322183  0.251923  0.071795   \n",
      "2408   ST-633   1102  0.581670  29.923775  4018.651198  0.232305  0.031760   \n",
      "2409   ST-634    759  0.660079  24.387352  2854.572358  0.241107  0.051383   \n",
      "2410   ST-635   1768  0.701923  16.102941  1986.848846  0.247738  0.120475   \n",
      "2411   ST-636   1705  0.653959  17.274487  1726.100346  0.225806  0.033431   \n",
      "2412   ST-637   3302  0.689279  15.570866  1887.447756  0.214113  0.021199   \n",
      "2413   ST-638   1230  0.704878  19.352033  2037.781992  0.270732  0.063415   \n",
      "2414   ST-639   1664  0.670072  14.605168  1632.501701  0.188101  0.043870   \n",
      "2415    ST-64   2882  0.656142  33.196738  4153.031069  0.268910  0.025677   \n",
      "2416   ST-640   2388  0.649079  32.095896  4905.543107  0.123953  0.010469   \n",
      "2417   ST-641   1090  0.749541  20.620183  2889.349376  0.114679  0.009174   \n",
      "2418   ST-642    587  0.684838  25.197615  2265.098126  0.190801  0.030664   \n",
      "2419   ST-643   4227  0.660989  19.694109  2169.157674  0.255974  0.097469   \n",
      "2420   ST-644    710  0.764789  20.802817  2205.708408  0.284507  0.114085   \n",
      "2421   ST-645   2136  0.582397  21.078184  1937.650983  0.224251  0.024345   \n",
      "2422   ST-646   1782  0.686869  21.295735  2328.105196  0.266554  0.081369   \n",
      "2423   ST-647    849  0.736160  23.428740  2351.520212  0.221437  0.011779   \n",
      "2424   ST-648    801  0.767790  23.051186  2398.622609  0.264669  0.133583   \n",
      "2425   ST-650   2281  0.618588  20.878562  2526.852337  0.300745  0.118808   \n",
      "2426   ST-651   1500  0.658000  22.872667  2272.419673  0.273333  0.083333   \n",
      "2427   ST-652   1181  0.623201  20.574090  2285.566842  0.237087  0.088061   \n",
      "2428   ST-654   1206  0.536484  22.540630  2267.245929  0.271144  0.099502   \n",
      "2429   ST-655   4645  0.693434  20.072766  2294.450248  0.232939  0.059203   \n",
      "2430   ST-657    600  0.643333  28.275000  3481.428067  0.266667  0.070000   \n",
      "2431   ST-658   2812  0.612376  15.308321  1889.534804  0.259602  0.082504   \n",
      "2432    ST-66   5529  0.752939  22.251040  2678.366495  0.124073  0.015916   \n",
      "2433   ST-660   3093  0.525057  42.685095  6650.066059  0.297446  0.011962   \n",
      "2434   ST-661    349  0.624642  21.143266  2232.125501  0.269341  0.005731   \n",
      "2435   ST-662   3313  0.654090  18.594325  2264.152388  0.217929  0.040447   \n",
      "2436   ST-663   3850  0.631169  19.840260  2573.901210  0.213247  0.024416   \n",
      "2437   ST-664   9574  0.629204  20.506163  2618.618445  0.247545  0.011489   \n",
      "2438   ST-665   2736  0.694079  15.657895  2033.472259  0.220029  0.052632   \n",
      "2439   ST-666   4800  0.701667  12.722083  1612.609463  0.242083  0.035000   \n",
      "2440   ST-667    648  0.643519  18.287037  1939.704614  0.262346  0.100309   \n",
      "2441   ST-668  13459  0.665800  22.803626  3022.573263  0.218961  0.048964   \n",
      "2442   ST-669   3594  0.684752  21.394268  2284.253703  0.260434  0.072621   \n",
      "2443    ST-67   2797  0.670719  31.640329  3683.689053  0.286021  0.055059   \n",
      "2444   ST-670   2412  0.718491  20.323798  2114.462720  0.235904  0.041459   \n",
      "2445   ST-671    709  0.686883  20.913963  2335.970000  0.263752  0.036671   \n",
      "2446   ST-673   2249  0.555803  20.381503  2133.992583  0.248555  0.048911   \n",
      "2447   ST-674   2134  0.696813  14.105904  1660.729620  0.212746  0.073102   \n",
      "2448   ST-675   2061  0.591946  20.495391  2750.793658  0.247938  0.028627   \n",
      "2449   ST-676   2139  0.731183  21.230949  2513.643768  0.279570  0.033193   \n",
      "2450   ST-677   1457  0.648593  15.291695  1878.523617  0.253260  0.060398   \n",
      "2451   ST-678   3174  0.764020  16.206679  2179.964972  0.246062  0.080025   \n",
      "2452   ST-679   1880  0.631383  27.508511  3689.928830  0.264362  0.097872   \n",
      "2453    ST-68   3827  0.702378  16.749412  1906.418009  0.171675  0.023517   \n",
      "2454   ST-683   5580  0.627061  37.079032  5033.486269  0.355376  0.052509   \n",
      "2455   ST-685   2570  0.678599  17.605837  2264.504813  0.209728  0.039300   \n",
      "2456   ST-686   1240  0.790323  16.858065  2168.555339  0.251613  0.094355   \n",
      "2457   ST-687   3278  0.660464  19.608908  2124.953935  0.277913  0.089689   \n",
      "2458   ST-688    352  0.681818  18.332386  2096.080256  0.275568  0.065341   \n",
      "2459    ST-69   2050  0.704390  20.548293  1903.043361  0.251220  0.025854   \n",
      "2460   ST-690   1392  0.617816  23.813937  2485.482687  0.235632  0.081178   \n",
      "2461   ST-691    919  0.682263  25.832427  3118.350773  0.264418  0.119695   \n",
      "2462   ST-692   3747  0.618094  45.590873  6708.738887  0.295970  0.033093   \n",
      "2463   ST-693   1098  0.755920  28.111111  3873.642750  0.265027  0.037341   \n",
      "2464   ST-694   1014  0.678501  20.833333  2284.562179  0.268245  0.030572   \n",
      "2465   ST-695   1144  0.668706  52.090909  6379.435927  0.409965  0.076049   \n",
      "2466   ST-696    577  0.729636  26.811092  2787.490381  0.259965  0.076256   \n",
      "2467   ST-697    380  0.689474  30.986842  3846.814947  0.265789  0.039474   \n",
      "2468   ST-699   5481  0.705528  22.285532  2524.586094  0.254333  0.072067   \n",
      "2469     ST-7   1574  0.648030  29.077510  2950.471067  0.296061  0.099746   \n",
      "2470    ST-70   3909  0.679458  22.256587  2345.284106  0.224354  0.023024   \n",
      "2471   ST-700   2470  0.770445  22.138462  2771.521190  0.295547  0.062348   \n",
      "2472   ST-701    554  0.758123  21.864621  2565.978881  0.241877  0.083032   \n",
      "2473   ST-702  13831  0.653821  24.262743  3282.510040  0.311836  0.087846   \n",
      "2474   ST-703   2890  0.702768  18.071972  1852.983246  0.274394  0.056401   \n",
      "2475   ST-704   2707  0.685630  19.516808  2174.347414  0.233099  0.055781   \n",
      "2476   ST-705   2925  0.724786  24.225299  2847.145439  0.278632  0.076923   \n",
      "2477   ST-707    717  0.824268  18.192469  2940.519693  0.295676  0.186890   \n",
      "2478   ST-709   1279  0.605160  24.095387  2427.475176  0.249414  0.083659   \n",
      "2479    ST-71   3290  0.696960  21.238906  2477.759717  0.237994  0.021277   \n",
      "2480   ST-712   2603  0.677295  22.541299  2558.779551  0.229351  0.091817   \n",
      "2481   ST-713   1649  0.620982  31.887204  5283.713948  0.343238  0.074591   \n",
      "2482   ST-714   2257  0.605671  19.385911  2189.360474  0.276473  0.050510   \n",
      "2483   ST-715   1638  0.656288  19.203907  2013.609908  0.310745  0.077534   \n",
      "2484   ST-717   1317  0.634776  19.520881  2182.862407  0.290812  0.057707   \n",
      "2485   ST-719   1109  0.559964  19.535618  2056.508945  0.297565  0.088368   \n",
      "2486    ST-72   4006  0.746380  23.525961  2899.958405  0.185971  0.035447   \n",
      "2487   ST-720   1023  0.670577  19.176931  1897.165367  0.259042  0.076246   \n",
      "2488   ST-721    686  0.619534  18.367347  1904.244927  0.266764  0.032070   \n",
      "2489   ST-722    281  0.519573  22.153025  1956.739786  0.295374  0.042705   \n",
      "2490   ST-723   1078  0.572356  17.166976  1623.405473  0.277365  0.079777   \n",
      "2491   ST-724   3892  0.751799  27.990493  3866.556842  0.287513  0.106372   \n",
      "2492   ST-725   1206  0.671642  20.800166  2982.184602  0.262852  0.043947   \n",
      "2493   ST-726   1875  0.664000  20.712533  2199.224603  0.242667  0.049067   \n",
      "2494   ST-727   2186  0.655993  17.109790  1923.282443  0.236048  0.118481   \n",
      "2495   ST-728   4777  0.671133  22.933222  2633.253284  0.266904  0.080804   \n",
      "2496   ST-729   1911  0.661957  19.789639  1838.423391  0.266876  0.052852   \n",
      "2497    ST-73  12670  0.594396  42.359669  5150.235206  0.344041  0.038753   \n",
      "2498   ST-731    333  0.570571  14.222222  1818.955495  0.231231  0.096096   \n",
      "2499   ST-732    728  0.759615  11.133242  1465.956332  0.186813  0.140110   \n",
      "2500   ST-733   1779  0.600899  16.653738  2055.136144  0.187746  0.020236   \n",
      "2501   ST-735   6833  0.646129  14.927704  1594.055750  0.223767  0.037904   \n",
      "2502   ST-736   3718  0.646046  19.002690  2152.872324  0.309306  0.025820   \n",
      "2503   ST-737   2312  0.576990  19.233131  2029.582621  0.211938  0.069637   \n",
      "2504   ST-738   1130  0.639823  31.445133  3775.445257  0.315044  0.038938   \n",
      "2505   ST-740   2196  0.581512  17.576503  2027.739977  0.196266  0.032332   \n",
      "2506   ST-741    142  0.542254  31.140845  2880.673451  0.394366  0.042254   \n",
      "2507   ST-742   2119  0.635677  14.433223  2157.772227  0.223218  0.008495   \n",
      "2508   ST-743   1088  0.597426  19.206801  2319.216719  0.281250  0.073529   \n",
      "2509   ST-744   1607  0.662726  18.256378  2233.198332  0.227131  0.069073   \n",
      "2510   ST-745    525  0.624762  21.329524  2329.351600  0.234286  0.060952   \n",
      "2511   ST-746   1152  0.679688  18.223958  2298.036536  0.282118  0.048611   \n",
      "2512   ST-747   1517  0.647989  24.876071  2976.830613  0.230059  0.019117   \n",
      "2513   ST-748   1429  0.648006  42.351994  4518.525395  0.369489  0.046886   \n",
      "2514   ST-749   2642  0.582135  35.834595  4473.374792  0.345572  0.036715   \n",
      "2515   ST-750   6095  0.604922  39.589500  4626.088824  0.328630  0.029368   \n",
      "2516   ST-752   1703  0.543159  27.452143  3155.498943  0.253670  0.039930   \n",
      "2517   ST-753   3013  0.658480  22.930634  2551.372463  0.246598  0.049784   \n",
      "2518   ST-754    624  0.786859  17.980769  2139.281506  0.227564  0.038462   \n",
      "2519   ST-755    277  0.750903  19.090253  2220.647509  0.263538  0.043321   \n",
      "2520   ST-756    368  0.714674  13.336957  1923.014185  0.211957  0.024457   \n",
      "2521   ST-757   1163  0.562339  22.960447  2305.741720  0.185727  0.037833   \n",
      "2522   ST-758   2101  0.632080  20.183722  1989.128420  0.243693  0.043789   \n",
      "2523   ST-759    981  0.744139  24.314985  2515.210591  0.237513  0.018349   \n",
      "2524    ST-76   2393  0.597994  17.023402  1963.569010  0.264522  0.014208   \n",
      "2525   ST-760   2653  0.689408  20.497550  2254.922363  0.250660  0.054278   \n",
      "2526   ST-761   2944  0.718410  24.971128  2587.637792  0.176970  0.027174   \n",
      "2527   ST-762   1038  0.767823  19.220617  1812.148112  0.210019  0.052023   \n",
      "2528   ST-763    611  0.844517  23.114566  2669.598085  0.186579  0.037643   \n",
      "2529   ST-764   1369  0.707816  23.807159  2634.372316  0.188459  0.025566   \n",
      "2530   ST-765   1390  0.653957  22.029496  2304.230712  0.180576  0.032374   \n",
      "2531   ST-766    721  0.574202  20.472954  2289.239085  0.220527  0.047157   \n",
      "2532   ST-767   1491  0.707579  18.741784  2283.395211  0.177733  0.011402   \n",
      "2533   ST-768   1373  0.684632  17.737072  2301.516635  0.172615  0.005098   \n",
      "2534   ST-769   2546  0.610369  23.109976  2709.115958  0.219953  0.047918   \n",
      "2535    ST-77   1221  0.553645  16.910729  1910.873292  0.267813  0.023751   \n",
      "2536   ST-770   1359  0.612215  26.601913  3023.169036  0.245769  0.041943   \n",
      "2537   ST-771   2008  0.617032  29.395418  4311.929313  0.243028  0.031375   \n",
      "2538   ST-772   3706  0.695899  22.636805  2683.848791  0.202644  0.010254   \n",
      "2539   ST-773    522  0.641762  27.946360  3086.346494  0.201149  0.007663   \n",
      "2540   ST-774    204  0.627451  27.642157  4078.622451  0.151961  0.019608   \n",
      "2541   ST-775    678  0.648968  19.942478  2936.761239  0.224189  0.045723   \n",
      "2542   ST-776   5421  0.541413  45.778270  6198.911398  0.386645  0.029699   \n",
      "2543   ST-777   2689  0.534771  48.862030  6149.028434  0.359241  0.056155   \n",
      "2544   ST-778    154  0.649351  25.350649  2682.225065  0.292208  0.097403   \n",
      "2545   ST-779    764  0.609948  25.498691  2919.392356  0.277487  0.075916   \n",
      "2546    ST-78   1462  0.625855  17.770862  2297.217715  0.223666  0.070451   \n",
      "2547   ST-780   2079  0.636364  23.613276  2226.993098  0.281866  0.019721   \n",
      "2548   ST-781   1754  0.762258  19.863740  2430.879019  0.215507  0.037058   \n",
      "2549   ST-782    910  0.534066  26.129670  3495.518330  0.327473  0.047253   \n",
      "2550   ST-783    639  0.615023  24.208138  3195.600720  0.197183  0.040689   \n",
      "2551   ST-784    193  0.704663  43.937824  6617.792383  0.279793  0.103627   \n",
      "2552   ST-786    484  0.677686  27.485537  3389.725248  0.326446  0.051653   \n",
      "2553   ST-787   1685  0.716320  30.069436  3198.201501  0.268843  0.116320   \n",
      "2554   ST-788   2389  0.616576  22.062369  2655.620205  0.234408  0.061951   \n",
      "2555   ST-789    678  0.644543  21.935103  3152.503732  0.233038  0.041298   \n",
      "2556   ST-790    543  0.690608  27.832413  4143.130147  0.099448  0.016575   \n",
      "2557   ST-791   3199  0.638012  31.814317  3688.740228  0.264770  0.043451   \n",
      "2558   ST-792    812  0.592365  34.975369  4273.903571  0.321429  0.087438   \n",
      "2559   ST-793   1885  0.603183  37.454111  3773.871358  0.264191  0.103979   \n",
      "2560   ST-794    784  0.778061  37.202806  5124.841773  0.256378  0.109694   \n",
      "2561   ST-795    836  0.716507  24.789474  3065.619916  0.215311  0.074163   \n",
      "2562   ST-796    886  0.602709  29.086907  4054.176659  0.209932  0.094808   \n",
      "2563   ST-797   2500  0.740400  27.301200  3324.643608  0.102400  0.031200   \n",
      "2564   ST-798    755  0.645033  41.658278  6314.146715  0.312583  0.029139   \n",
      "2565   ST-799   1447  0.700069  33.655840  4759.787035  0.266759  0.029717   \n",
      "2566     ST-8   4362  0.586657  34.797111  3946.588831  0.372077  0.060981   \n",
      "2567    ST-80   1427  0.633497  22.117029  2381.156342  0.107218  0.008409   \n",
      "2568   ST-801    307  0.687296  27.498371  3641.897003  0.315961  0.032573   \n",
      "2569   ST-802   1049  0.738799  27.484271  3093.662231  0.135367  0.046711   \n",
      "2570   ST-803   1015  0.548768  28.102463  3172.798187  0.262069  0.057143   \n",
      "2571   ST-804    782  0.524297  29.060102  2737.600639  0.329923  0.012788   \n",
      "2572   ST-806    779  0.684211  25.527599  2723.831913  0.098845  0.006418   \n",
      "2573   ST-807   1548  0.583333  28.098837  3292.785659  0.271964  0.036822   \n",
      "2574   ST-808   1706  0.616647  25.956038  2501.991325  0.259672  0.031653   \n",
      "2575   ST-809   1194  0.693467  23.650754  2213.333987  0.252931  0.058626   \n",
      "2576    ST-81   1450  0.617241  23.055172  2478.231303  0.246897  0.112414   \n",
      "2577   ST-810   2230  0.737220  24.758744  2618.865404  0.163677  0.056054   \n",
      "2578   ST-811   1277  0.709475  23.717306  2818.927525  0.188724  0.081441   \n",
      "2579   ST-812    853  0.664713  20.437280  2266.179285  0.139508  0.072685   \n",
      "2580   ST-813   1034  0.636364  22.186654  2380.988733  0.218569  0.067698   \n",
      "2581   ST-814   1029  0.752187  21.389699  1981.832575  0.186589  0.068999   \n",
      "2582   ST-815   2767  0.732924  25.160463  2832.772118  0.178894  0.056017   \n",
      "2583   ST-816   2274  0.678540  20.042216  2021.508087  0.206245  0.027265   \n",
      "2584   ST-817    501  0.680639  17.315369  2086.132695  0.185629  0.031936   \n",
      "2585   ST-818   2909  0.648333  17.930217  2016.570058  0.203850  0.015813   \n",
      "2586   ST-819    736  0.667120  16.934783  2071.876793  0.233696  0.025815   \n",
      "2587    ST-82   3633  0.470410  24.911919  2718.853705  0.203138  0.022846   \n",
      "2588   ST-820   1008  0.641865  25.897817  2928.256468  0.293651  0.033730   \n",
      "2589   ST-821   3983  0.653779  24.727843  2968.556939  0.221441  0.042681   \n",
      "2590   ST-822   1183  0.648352  22.058326  2865.926069  0.266272  0.037194   \n",
      "2591   ST-823   2597  0.705044  23.060454  2726.633296  0.232576  0.029650   \n",
      "2592   ST-824   5869  0.633328  13.886522  1608.000745  0.240586  0.055376   \n",
      "2593   ST-825   1491  0.657948  17.401744  2149.893474  0.265594  0.074447   \n",
      "2594   ST-826    456  0.763158  16.879386  2526.799649  0.225877  0.043860   \n",
      "2595   ST-827   9101  0.719042  17.073618  1983.666912  0.232502  0.067355   \n",
      "2596   ST-828   2861  0.630199  12.916463  1476.385327  0.196435  0.025865   \n",
      "2597   ST-829   3505  0.678459  16.732382  1785.647541  0.239943  0.037375   \n",
      "2598    ST-83   1515  0.546535  19.279868  1998.451729  0.210561  0.023102   \n",
      "2599   ST-830   1478  0.659675  17.621786  1858.134276  0.172530  0.031123   \n",
      "2600   ST-831   5322  0.649756  18.915257  2149.892026  0.251973  0.059752   \n",
      "2601   ST-834   6625  0.617962  15.573132  1573.830500  0.226415  0.036377   \n",
      "2602   ST-835   8248  0.609239  15.777764  1765.089530  0.256183  0.054680   \n",
      "2603   ST-838   3433  0.637343  18.841247  2046.859779  0.211768  0.096708   \n",
      "2604   ST-839   2743  0.593146  17.999271  1870.264677  0.202333  0.028071   \n",
      "2605    ST-84   1770  0.676836  17.663277  2022.625938  0.152542  0.033898   \n",
      "2606   ST-840   3475  0.570072  22.799137  2392.765401  0.303022  0.024748   \n",
      "2607   ST-842   3037  0.629569  19.621666  2390.043609  0.284821  0.063879   \n",
      "2608   ST-847   2852  0.700912  16.995792  1955.128562  0.259116  0.059257   \n",
      "2609   ST-849   5487  0.693640  20.572991  2475.858172  0.259523  0.070530   \n",
      "2610    ST-85   2237  0.600358  39.249888  3777.294251  0.461779  0.021457   \n",
      "2611   ST-850   3059  0.627983  14.858124  1603.948294  0.243871  0.060804   \n",
      "2612   ST-852    362  0.685083  17.546961  2296.931823  0.325967  0.027624   \n",
      "2613   ST-853   2199  0.711687  19.106867  1917.585921  0.253752  0.022283   \n",
      "2614   ST-854   1718  0.637369  19.561700  2282.306449  0.286380  0.054715   \n",
      "2615   ST-855   2265  0.698896  19.208830  2270.460208  0.235320  0.046358   \n",
      "2616   ST-856   2511  0.698526  17.992433  2107.702445  0.281561  0.056949   \n",
      "2617   ST-857   2979  0.621014  18.161128  1992.756170  0.260490  0.056730   \n",
      "2618   ST-859   1007  0.817279  20.308838  2258.457071  0.181728  0.053625   \n",
      "2619    ST-86   3950  0.646582  20.509114  2306.459714  0.150886  0.010127   \n",
      "2620   ST-860    561  0.787879  24.982175  2036.059911  0.254902  0.037433   \n",
      "2621   ST-861    707  0.543140  18.958982  1835.352928  0.207921  0.024045   \n",
      "2622   ST-862   3225  0.631318  27.266357  3689.529085  0.302016  0.066047   \n",
      "2623   ST-863    636  0.661950  25.984277  2821.819654  0.232704  0.130503   \n",
      "2624   ST-866   2280  0.623684  21.760088  2910.904390  0.267105  0.042544   \n",
      "2625   ST-867   1592  0.601759  18.319724  2133.831545  0.253769  0.053392   \n",
      "2626   ST-868   1795  0.564345  23.572145  3000.424072  0.262396  0.077437   \n",
      "2627   ST-869   1866  0.645230  20.630761  2227.578457  0.290461  0.056806   \n",
      "2628    ST-87   4849  0.524438  25.153846  2852.210076  0.317385  0.008043   \n",
      "2629   ST-870   1391  0.740474  22.263120  2851.753940  0.237239  0.021567   \n",
      "2630   ST-871   1773  0.689791  17.417936  2009.415296  0.236323  0.039481   \n",
      "2631   ST-872    620  0.724194  24.450000  2673.585484  0.224194  0.182258   \n",
      "2632   ST-873   4638  0.736093  16.709789  1833.281108  0.184347  0.016171   \n",
      "2633   ST-874    492  0.729675  14.475610  1720.059675  0.237805  0.016260   \n",
      "2634   ST-875   2630  0.677186  26.855513  3855.511624  0.266160  0.032319   \n",
      "2635   ST-876   1844  0.601952  13.824837  1662.496838  0.200651  0.039046   \n",
      "2636   ST-877   2216  0.671480  30.828069  4298.238809  0.295126  0.053700   \n",
      "2637   ST-879   1176  0.750000  24.616497  2525.048810  0.165816  0.056973   \n",
      "2638    ST-88    542  0.632841  20.204797  2683.820111  0.293358  0.033210   \n",
      "2639   ST-880    495  0.600000  27.355556  4396.469879  0.248485  0.020202   \n",
      "2640   ST-881   1115  0.596413  31.403587  4859.316422  0.270852  0.043049   \n",
      "2641   ST-882   5019  0.641961  21.313608  2436.334868  0.275752  0.066149   \n",
      "2642   ST-883   2667  0.641920  21.058493  2075.233318  0.262092  0.059993   \n",
      "2643   ST-884   1568  0.654337  20.713648  2513.640931  0.278699  0.197066   \n",
      "2644   ST-885    617  0.701783  30.701783  4190.244716  0.286872  0.064830   \n",
      "2645   ST-886    551  0.805808  21.214156  2705.729074  0.288566  0.063521   \n",
      "2646   ST-887   1511  0.616810  19.025149  2146.071555  0.232958  0.059563   \n",
      "2647   ST-889   1065  0.803756  24.098592  3017.896207  0.163380  0.025352   \n",
      "2648    ST-89   4013  0.538998  31.002990  3533.874139  0.401944  0.020184   \n",
      "2649   ST-890   2555  0.755382  22.637965  2540.078489  0.190998  0.016047   \n",
      "2650   ST-891  14104  0.552255  21.235323  2214.419950  0.283253  0.008012   \n",
      "2651   ST-892   4887  0.579701  22.233067  2421.072382  0.279926  0.033354   \n",
      "2652   ST-894   3067  0.522008  18.940985  1947.712742  0.230192  0.029671   \n",
      "2653   ST-895   2807  0.657998  18.642679  2444.754660  0.200214  0.043463   \n",
      "2654   ST-896   1677  0.621348  24.868813  3598.029666  0.249255  0.081097   \n",
      "2655   ST-897    928  0.662716  20.575431  2267.129763  0.312500  0.077586   \n",
      "2656   ST-899    878  0.725513  19.571754  2567.945854  0.194761  0.007973   \n",
      "2657     ST-9   3378  0.582297  22.505921  2075.252256  0.240675  0.069568   \n",
      "2658    ST-90   2559  0.563892  20.953497  2435.414330  0.152403  0.042595   \n",
      "2659   ST-900   1171  0.556789  20.874466  2561.164705  0.246798  0.059778   \n",
      "2660   ST-901    787  0.613723  23.944091  2871.884625  0.237611  0.022872   \n",
      "2661   ST-902    239  0.468619  31.079498  3309.954142  0.271967  0.012552   \n",
      "2662   ST-903   4111  0.596935  21.346631  2286.789968  0.168086  0.034298   \n",
      "2663   ST-904   4653  0.553406  21.521814  2156.532794  0.283258  0.044702   \n",
      "2664   ST-905   2510  0.532271  20.648207  2043.805765  0.292430  0.032669   \n",
      "2665   ST-906   2878  0.645240  20.414177  2444.673972  0.228978  0.009382   \n",
      "2666   ST-907   1606  0.519303  21.785803  2354.484869  0.275841  0.019925   \n",
      "2667   ST-908   4186  0.492355  21.555901  2195.216063  0.260631  0.036312   \n",
      "2668    ST-91   2635  0.671347  21.483112  2475.417495  0.163188  0.019355   \n",
      "2669   ST-910   5300  0.581321  17.804340  2234.285374  0.216604  0.032075   \n",
      "2670   ST-912   2350  0.632340  19.240426  2148.693672  0.273191  0.116170   \n",
      "2671   ST-913   3086  0.782566  15.876539  1992.127259  0.245949  0.057680   \n",
      "2672   ST-914   7433  0.653572  19.236378  2312.363515  0.255079  0.036190   \n",
      "2673   ST-915   2083  0.591935  17.850216  2013.789337  0.257321  0.052328   \n",
      "2674   ST-916   1674  0.670848  18.812425  2023.875167  0.280167  0.083035   \n",
      "2675   ST-918   4979  0.638080  21.070496  2566.035477  0.203254  0.031733   \n",
      "2676   ST-919   7074  0.657337  24.111818  3295.041667  0.266751  0.057393   \n",
      "2677    ST-92   1207  0.557581  21.096106  2489.536288  0.257664  0.023198   \n",
      "2678   ST-920   3171  0.739199  12.787133  1576.239111  0.211290  0.043519   \n",
      "2679   ST-923   3093  0.623343  19.634659  1927.367941  0.251212  0.083737   \n",
      "2680   ST-924   1284  0.695483  24.531931  2649.348396  0.263240  0.080997   \n",
      "2681   ST-925    455  0.670330  20.661538  2763.126703  0.358242  0.019780   \n",
      "2682   ST-926    265  0.724528  19.728302  2727.818491  0.222642  0.037736   \n",
      "2683   ST-927   2807  0.620948  20.082294  2113.340403  0.232989  0.028144   \n",
      "2684   ST-928   1302  0.625960  28.062212  3033.584524  0.277266  0.029954   \n",
      "2685   ST-929    298  0.677852  21.275168  2810.165302  0.187919  0.120805   \n",
      "2686    ST-93   4061  0.698104  20.235656  2518.603044  0.174834  0.030534   \n",
      "2687   ST-930   2889  0.656282  20.278297  2417.381298  0.256490  0.067844   \n",
      "2688   ST-931   1492  0.636729  17.735925  1994.571046  0.262064  0.068365   \n",
      "2689   ST-932   1090  0.726606  24.477064  3125.509807  0.233945  0.036697   \n",
      "2690   ST-933   2690  0.598885  23.969145  2210.533056  0.259108  0.059108   \n",
      "2691   ST-935   4490  0.627394  21.595546  2462.897105  0.244766  0.034298   \n",
      "2692   ST-936   4570  0.628665  20.849672  2198.068961  0.252954  0.091466   \n",
      "2693   ST-937    828  0.676329  20.199275  2807.894251  0.234300  0.095411   \n",
      "2694   ST-938   1076  0.688662  27.909851  4221.435307  0.259294  0.078067   \n",
      "2695   ST-939    145  0.751724  23.275862  3567.874069  0.248276  0.179310   \n",
      "2696    ST-94   3870  0.714470  17.745995  2120.023765  0.229457  0.035142   \n",
      "2697   ST-941    553  0.788427  23.931284  3753.691157  0.294756  0.104882   \n",
      "2698   ST-942   2733  0.601537  17.376509  2116.125163  0.249177  0.069887   \n",
      "2699   ST-943   2358  0.732824  31.137829  2210.241234  0.181934  0.016539   \n",
      "2700   ST-944   2022  0.633531  26.156775  2460.040514  0.191395  0.041048   \n",
      "2701   ST-946   2248  0.777580  18.962189  2324.243372  0.223310  0.050712   \n",
      "2702   ST-947   1902  0.575184  22.133544  2572.800962  0.256572  0.037329   \n",
      "2703   ST-948   2362  0.639289  23.002964  2141.361101  0.245131  0.079170   \n",
      "2704   ST-949   2577  0.575863  25.874272  3005.691529  0.229336  0.038029   \n",
      "2705    ST-95   5021  0.669986  16.097391  2032.863342  0.175065  0.019518   \n",
      "2706   ST-950   2246  0.620214  23.794301  2495.534599  0.235085  0.102850   \n",
      "2707   ST-951   1048  0.802481  28.337786  3194.311565  0.302481  0.050573   \n",
      "2708   ST-952   1758  0.725256  19.296359  1992.790415  0.234926  0.093288   \n",
      "2709   ST-953    296  0.716216  25.861486  3610.956351  0.236486  0.030405   \n",
      "2710   ST-954    889  0.671541  24.691789  3063.032306  0.208099  0.037120   \n",
      "2711   ST-956   1425  0.701754  19.156491  2102.019677  0.183860  0.053333   \n",
      "2712   ST-957    916  0.674672  26.314410  2059.989814  0.180131  0.052402   \n",
      "2713   ST-958   1667  0.684463  26.885423  2621.419124  0.196761  0.029994   \n",
      "2714   ST-959   1753  0.759840  20.552767  2241.884044  0.183685  0.063890   \n",
      "2715    ST-96   1438  0.561892  18.011127  2215.359868  0.234353  0.051460   \n",
      "2716   ST-960    368  0.616848  21.222826  2194.509918  0.236413  0.035326   \n",
      "2717   ST-961    471  0.779193  28.055202  2846.344692  0.180467  0.033970   \n",
      "2718   ST-962    431  0.786543  24.979118  3410.658190  0.148492  0.018561   \n",
      "2719   ST-963   1198  0.655259  22.437396  2479.388623  0.224541  0.034224   \n",
      "2720   ST-964   1799  0.450250  17.464703  2365.369161  0.250139  0.027237   \n",
      "2721   ST-965   2154  0.664345  20.266017  1923.714485  0.266017  0.074745   \n",
      "2722   ST-966    868  0.693548  20.770737  2281.317005  0.185484  0.065668   \n",
      "2723   ST-967   1378  0.750363  14.837446  1623.356030  0.163280  0.005806   \n",
      "2724   ST-968    769  0.574772  32.661899  2824.234967  0.443433  0.019506   \n",
      "2725    ST-97   3706  0.581220  14.827307  1672.436185  0.247437  0.065839   \n",
      "2726   ST-970   1437  0.578984  25.180237  3210.604690  0.257481  0.044537   \n",
      "2727   ST-971   2117  0.660368  27.898914  3938.390628  0.308928  0.043930   \n",
      "2728   ST-972   3702  0.636683  17.902215  1441.431442  0.141005  0.029173   \n",
      "2729   ST-973   1368  0.640351  17.495614  1385.188012  0.122076  0.010234   \n",
      "2730   ST-974   6314  0.662654  16.024865  1469.108492  0.143807  0.025182   \n",
      "2731   ST-975   7631  0.540689  13.582230  1313.931023  0.231162  0.030664   \n",
      "2732   ST-977   1984  0.590222  22.282258  2153.614093  0.199597  0.007056   \n",
      "2733   ST-978   1718  0.596624  23.728172  2238.835000  0.291618  0.019208   \n",
      "2734   ST-979    403  0.650124  18.620347  1987.446675  0.387097  0.027295   \n",
      "2735    ST-98   3697  0.600757  22.756018  2043.934839  0.238301  0.041385   \n",
      "2736   ST-980   2863  0.538247  21.390150  2765.628117  0.314006  0.028292   \n",
      "2737   ST-981    301  0.734219  20.481728  2557.534817  0.149502  0.046512   \n",
      "2738   ST-983   3698  0.603569  20.840725  2410.983464  0.218767  0.035425   \n",
      "2739   ST-984   3645  0.622222  16.716872  1843.668395  0.249657  0.062826   \n",
      "2740   ST-985   2342  0.634927  26.506405  3070.997583  0.233988  0.036721   \n",
      "2741   ST-986    341  0.739003  21.885630  3043.293607  0.334311  0.175953   \n",
      "2742   ST-987   4761  0.590002  17.435623  1613.908918  0.278933  0.082546   \n",
      "2743   ST-988   1879  0.587014  26.898350  2673.448606  0.266099  0.100585   \n",
      "2744    ST-99  16358  0.510392  35.128133  4144.810214  0.355300  0.032094   \n",
      "2745   ST-990    967  0.569804  24.097208  2884.898283  0.255429  0.054809   \n",
      "2746   ST-991    838  0.675418  21.360382  2161.684045  0.114558  0.025060   \n",
      "2747   ST-992   2310  0.644156  23.584848  2891.585359  0.224242  0.035498   \n",
      "2748   ST-993   2288  0.677885  18.303759  1884.028086  0.255682  0.042832   \n",
      "2749   ST-994   4450  0.640225  20.783820  2037.581463  0.224045  0.014607   \n",
      "2750   ST-995    467  0.698073  18.715203  2259.101649  0.241970  0.008565   \n",
      "2751   ST-996   1075  0.709767  20.463256  1966.129544  0.279070  0.097674   \n",
      "2752   ST-997   6979  0.640923  18.015618  1877.363578  0.252472  0.028084   \n",
      "\n",
      "      출근시간대여비율    오전대여비율    점심대여비율    오후대여비율  퇴근시간대여비율    야간대여비율  주중청소년고객비율  \\\n",
      "0     0.045224  0.061867  0.099855  0.183792  0.184877  0.295224   0.020397   \n",
      "1     0.307417  0.080677  0.093689  0.143136  0.155172  0.145413   0.266726   \n",
      "2     0.079389  0.058015  0.087532  0.188126  0.233927  0.318405   0.178105   \n",
      "3     0.142111  0.063218  0.096134  0.153083  0.166667  0.286311   0.129471   \n",
      "4     0.263772  0.059624  0.088788  0.154893  0.149060  0.207388   0.495446   \n",
      "5     0.230641  0.066481  0.076137  0.162674  0.157103  0.220056   0.221771   \n",
      "6     0.233964  0.081692  0.084617  0.189901  0.132190  0.195945   0.207527   \n",
      "7     0.224396  0.066743  0.063867  0.128884  0.127733  0.234753   0.165528   \n",
      "8     0.203585  0.062740  0.068502  0.135083  0.167734  0.236236   0.231298   \n",
      "9     0.174981  0.078183  0.093075  0.177215  0.115041  0.238645   0.262079   \n",
      "10    0.218730  0.071025  0.049026  0.145192  0.121307  0.218102   0.081260   \n",
      "11    0.130602  0.080666  0.044814  0.236876  0.157490  0.220230   0.313600   \n",
      "12    0.177814  0.053290  0.079391  0.109842  0.145188  0.295269   0.031947   \n",
      "13    0.136493  0.058294  0.047393  0.368246  0.109005  0.161611   0.438576   \n",
      "14    0.224078  0.065150  0.075060  0.162599  0.209580  0.194531   0.085151   \n",
      "15    0.157254  0.078627  0.088594  0.145072  0.140642  0.223699   0.163265   \n",
      "16    0.048219  0.047062  0.101582  0.194034  0.181947  0.384724   0.395128   \n",
      "17    0.114147  0.066074  0.094452  0.168149  0.159678  0.329945   0.176166   \n",
      "18    0.111111  0.032774  0.079137  0.234213  0.322142  0.203837   0.160367   \n",
      "19    0.121973  0.081462  0.081682  0.151915  0.170630  0.284456   0.051352   \n",
      "20    0.215686  0.100218  0.098039  0.132898  0.104575  0.237473   0.117117   \n",
      "21    0.037209  0.083721  0.134884  0.158140  0.158140  0.297674   0.067227   \n",
      "22    0.060811  0.081081  0.111486  0.179054  0.125000  0.256757   0.144385   \n",
      "23    0.095376  0.065751  0.089595  0.152457  0.213150  0.278902   0.025763   \n",
      "24    0.166985  0.147901  0.127863  0.228053  0.105916  0.137405   0.067751   \n",
      "25    0.306916  0.100865  0.089337  0.168588  0.135447  0.129683   0.035363   \n",
      "26    0.212053  0.094699  0.099230  0.167648  0.197100  0.191210   0.020697   \n",
      "27    0.091568  0.071146  0.079051  0.129776  0.326746  0.200922   0.018563   \n",
      "28    0.129310  0.077586  0.068966  0.129310  0.081897  0.344828   0.072626   \n",
      "29    0.200637  0.058121  0.066083  0.156847  0.113854  0.223726   0.112190   \n",
      "30    0.197787  0.055325  0.065007  0.138313  0.116183  0.297372   0.099083   \n",
      "31    0.177419  0.062317  0.083578  0.130499  0.208944  0.280059   0.015138   \n",
      "32    0.100968  0.069617  0.096819  0.147994  0.157215  0.327340   0.043478   \n",
      "33    0.144098  0.076194  0.127517  0.161469  0.146861  0.280695   0.101975   \n",
      "34    0.347664  0.078505  0.067290  0.100935  0.110280  0.192523   0.038567   \n",
      "35    0.114958  0.063712  0.094183  0.160665  0.149584  0.257618   0.079922   \n",
      "36    0.078416  0.084710  0.082874  0.180960  0.355625  0.186205   0.077547   \n",
      "37    0.145665  0.074125  0.102224  0.161696  0.190484  0.265471   0.080153   \n",
      "38    0.118644  0.055791  0.071328  0.175141  0.201271  0.313559   0.098723   \n",
      "39    0.239321  0.081334  0.097718  0.167349  0.121709  0.193095   0.058914   \n",
      "40    0.161808  0.059941  0.073698  0.132001  0.150999  0.289224   0.065265   \n",
      "41    0.078901  0.052016  0.070134  0.158192  0.158192  0.383596   0.047593   \n",
      "42    0.175576  0.078227  0.096045  0.130813  0.172968  0.238157   0.054688   \n",
      "43    0.213305  0.079197  0.085533  0.157339  0.131996  0.227033   0.088698   \n",
      "44    0.379971  0.101620  0.051546  0.147275  0.100147  0.145803   0.089354   \n",
      "45    0.233603  0.072844  0.083171  0.174714  0.181133  0.223556   0.009487   \n",
      "46    0.214212  0.070539  0.086100  0.133299  0.109440  0.242739   0.135678   \n",
      "47    0.232432  0.066216  0.081081  0.202703  0.120270  0.193243   0.113636   \n",
      "48    0.079775  0.041295  0.096199  0.193336  0.187705  0.330831   0.324531   \n",
      "49    0.265594  0.092555  0.090543  0.142857  0.124748  0.179074   0.024931   \n",
      "50    0.227437  0.090253  0.104693  0.196751  0.124549  0.166065   0.039702   \n",
      "51    0.245161  0.116129  0.083871  0.158065  0.161290  0.145161   0.133333   \n",
      "52    0.198646  0.064334  0.079007  0.156885  0.141084  0.209932   0.165138   \n",
      "53    0.241039  0.041219  0.111111  0.169355  0.177419  0.195341   0.115294   \n",
      "54    0.185629  0.095808  0.056886  0.179641  0.185629  0.212575   0.032727   \n",
      "55    0.137628  0.071226  0.075199  0.158768  0.137911  0.304058   0.068029   \n",
      "56    0.191382  0.062675  0.070509  0.128334  0.127588  0.300690   0.070695   \n",
      "57    0.228173  0.051931  0.062804  0.191172  0.214054  0.219085   0.065352   \n",
      "58    0.126640  0.067467  0.093464  0.156970  0.220352  0.298713   0.070651   \n",
      "59    0.094691  0.048840  0.079540  0.132700  0.180078  0.370789   0.062752   \n",
      "60    0.213811  0.074329  0.084423  0.173205  0.131911  0.249369   0.214244   \n",
      "61    0.311540  0.069314  0.086362  0.124391  0.128700  0.199326   0.056177   \n",
      "62    0.044367  0.048453  0.090485  0.178050  0.204904  0.363106   0.048756   \n",
      "63    0.099265  0.065960  0.098616  0.159602  0.175173  0.339317   0.025455   \n",
      "64    0.215311  0.055821  0.082935  0.157895  0.161882  0.245614   0.055843   \n",
      "65    0.157937  0.060317  0.087302  0.146032  0.143651  0.288889   0.021253   \n",
      "66    0.171776  0.059725  0.065539  0.140592  0.258985  0.271142   0.005758   \n",
      "67    0.115672  0.079602  0.082090  0.121891  0.155473  0.296020   0.087657   \n",
      "68    0.126305  0.065005  0.091950  0.167733  0.168070  0.294038   0.071749   \n",
      "69    0.168916  0.067076  0.073211  0.156237  0.152147  0.261759   0.091392   \n",
      "70    0.125180  0.058273  0.102518  0.216906  0.238489  0.235971   0.017157   \n",
      "71    0.146526  0.067515  0.067759  0.136252  0.152886  0.329012   0.022468   \n",
      "72    0.217676  0.073650  0.057283  0.198036  0.109656  0.188216   0.054622   \n",
      "73    0.149725  0.064101  0.084053  0.174234  0.219324  0.254203   0.048115   \n",
      "74    0.145981  0.088026  0.073264  0.129579  0.170585  0.274467   0.025992   \n",
      "75    0.190476  0.084249  0.099634  0.140659  0.178755  0.230037   0.009653   \n",
      "76    0.143976  0.119617  0.095694  0.214006  0.177468  0.215746   0.060377   \n",
      "77    0.086957  0.055129  0.080705  0.250639  0.197499  0.295254   0.049849   \n",
      "78    0.133905  0.088061  0.090699  0.166557  0.142150  0.270119   0.035531   \n",
      "79    0.139360  0.119900  0.134965  0.274953  0.139360  0.180163   0.030603   \n",
      "80    0.112227  0.061357  0.090361  0.180500  0.243195  0.268630   0.032347   \n",
      "81    0.137500  0.085484  0.107258  0.229839  0.135081  0.231452   0.240789   \n",
      "82    0.124049  0.072298  0.071791  0.114155  0.138001  0.313293   0.184035   \n",
      "83    0.234934  0.059793  0.074388  0.140301  0.124294  0.218927   0.065615   \n",
      "84    0.165333  0.109333  0.085333  0.192000  0.101333  0.178667   0.028571   \n",
      "85    0.179962  0.077537  0.066050  0.146139  0.144544  0.233248   0.056131   \n",
      "86    0.113231  0.062906  0.089537  0.131474  0.168589  0.307612   0.065455   \n",
      "87    0.049080  0.054569  0.091702  0.177268  0.158541  0.342267   0.041961   \n",
      "88    0.084296  0.058622  0.067180  0.155755  0.154899  0.311938   0.017305   \n",
      "89    0.324548  0.095256  0.084714  0.134789  0.114458  0.176958   0.054611   \n",
      "90    0.148415  0.046110  0.068444  0.146254  0.148415  0.274496   0.026777   \n",
      "91    0.101266  0.079114  0.081487  0.200158  0.183544  0.246835   0.084324   \n",
      "92    0.160321  0.127255  0.086172  0.214429  0.091182  0.167335   0.268015   \n",
      "93    0.084873  0.073580  0.087953  0.198836  0.159480  0.268309   0.080808   \n",
      "94    0.122050  0.074484  0.084808  0.173304  0.130531  0.264749   0.042857   \n",
      "95    0.069740  0.044662  0.071889  0.163602  0.163602  0.331741   0.094370   \n",
      "96    0.197708  0.068768  0.069484  0.137536  0.160458  0.201289   0.042033   \n",
      "97    0.111048  0.063698  0.075536  0.169109  0.188275  0.294250   0.079606   \n",
      "98    0.106649  0.084574  0.092553  0.144415  0.148670  0.284574   0.014354   \n",
      "99    0.135014  0.067914  0.115494  0.216348  0.219601  0.194388   0.022863   \n",
      "100   0.146086  0.071832  0.071832  0.134786  0.186441  0.265537   0.037594   \n",
      "101   0.105687  0.047780  0.078941  0.151909  0.170345  0.330044   0.018538   \n",
      "102   0.106870  0.080153  0.105598  0.226463  0.129771  0.232824   0.084006   \n",
      "103   0.127332  0.079564  0.102403  0.156441  0.148977  0.279445   0.149134   \n",
      "104   0.173575  0.065803  0.109326  0.165285  0.136788  0.249741   0.078545   \n",
      "105   0.204299  0.103989  0.087529  0.144462  0.214756  0.172347   0.010691   \n",
      "106   0.084892  0.107914  0.077698  0.188489  0.162590  0.284892   0.092402   \n",
      "107   0.092190  0.052293  0.097487  0.189564  0.207596  0.279274   0.063887   \n",
      "108   0.177665  0.062364  0.071791  0.137781  0.113851  0.297317   0.114257   \n",
      "109   0.243879  0.083671  0.100829  0.155581  0.113360  0.204743   0.090477   \n",
      "110   0.077816  0.070175  0.090266  0.148274  0.129598  0.379457   0.097522   \n",
      "111   0.094943  0.088737  0.117282  0.200434  0.291654  0.174061   0.072741   \n",
      "112   0.183589  0.074970  0.108619  0.168241  0.148760  0.246163   0.247525   \n",
      "113   0.171011  0.110532  0.120959  0.252346  0.111575  0.190824   0.297372   \n",
      "114   0.101250  0.080000  0.081250  0.191250  0.168750  0.250000   0.176471   \n",
      "115   0.165031  0.087422  0.092774  0.199822  0.166815  0.213202   0.087117   \n",
      "116   0.118534  0.077586  0.133621  0.241379  0.209052  0.185345   0.057971   \n",
      "117   0.154660  0.091870  0.102445  0.191011  0.162591  0.236616   0.041667   \n",
      "118   0.066427  0.076601  0.110114  0.231598  0.213645  0.253142   0.059022   \n",
      "119   0.102703  0.068468  0.082883  0.181982  0.133333  0.315315   0.108491   \n",
      "120   0.181699  0.094771  0.097386  0.149673  0.128105  0.229412   0.054577   \n",
      "121   0.163636  0.067483  0.088462  0.175175  0.203497  0.241958   0.061607   \n",
      "122   0.093784  0.063729  0.100236  0.188513  0.194650  0.279780   0.085052   \n",
      "123   0.189936  0.088944  0.082211  0.152729  0.151665  0.243090   0.026654   \n",
      "124   0.043709  0.027152  0.037748  0.128477  0.327815  0.372185   0.001543   \n",
      "125   0.309378  0.091148  0.049080  0.142857  0.255039  0.128834   0.003012   \n",
      "126   0.408879  0.056504  0.058057  0.085688  0.114561  0.171686   0.008426   \n",
      "127   0.276347  0.074941  0.063232  0.058548  0.107728  0.131148   0.028213   \n",
      "128   0.365410  0.044213  0.053316  0.161248  0.107932  0.172952   0.100503   \n",
      "129   0.367365  0.080279  0.039267  0.110820  0.137871  0.172775   0.059203   \n",
      "130   0.378963  0.056916  0.067003  0.112392  0.100865  0.201009   0.006341   \n",
      "131   0.157895  0.048055  0.084668  0.173913  0.155606  0.276888   0.027273   \n",
      "132   0.053409  0.028904  0.044298  0.092994  0.484134  0.263902   0.004121   \n",
      "133   0.085799  0.055137  0.103012  0.149543  0.131522  0.344271   0.034605   \n",
      "134   0.116027  0.071369  0.083472  0.162354  0.186561  0.301753   0.079714   \n",
      "135   0.276074  0.061350  0.077228  0.132804  0.125226  0.206424   0.068851   \n",
      "136   0.125000  0.071429  0.178571  0.098214  0.116071  0.267857   0.012658   \n",
      "137   0.217391  0.067633  0.085346  0.115942  0.154589  0.173913   0.008602   \n",
      "138   0.190153  0.067912  0.081494  0.125637  0.105263  0.331070   0.002469   \n",
      "139   0.124341  0.086662  0.110776  0.186888  0.219292  0.221552   0.024728   \n",
      "140   0.204545  0.120868  0.154442  0.182851  0.171488  0.134814   0.015763   \n",
      "141   0.156217  0.056854  0.068013  0.137620  0.172689  0.282678   0.022822   \n",
      "142   0.242475  0.080268  0.073579  0.076923  0.225753  0.215719   0.037113   \n",
      "143   0.248322  0.098993  0.078859  0.164430  0.149329  0.192953   0.009390   \n",
      "144   0.183078  0.099198  0.052516  0.133479  0.207877  0.251641   0.012963   \n",
      "145   0.142690  0.076023  0.108772  0.138012  0.271345  0.192982   0.020173   \n",
      "146   0.102780  0.084246  0.133109  0.178602  0.208930  0.229992   0.031488   \n",
      "147   0.201411  0.061520  0.089734  0.120298  0.189263  0.280172   0.030541   \n",
      "148   0.069930  0.209790  0.111888  0.335664  0.202797  0.041958   0.008547   \n",
      "149   0.116117  0.056472  0.085025  0.168782  0.210025  0.304569   0.024476   \n",
      "150   0.128779  0.072228  0.086226  0.152296  0.154535  0.314670   0.028592   \n",
      "151   0.204104  0.053799  0.080422  0.150305  0.171936  0.264559   0.019146   \n",
      "152   0.076125  0.036678  0.067128  0.183391  0.193080  0.311419   0.014299   \n",
      "153   0.091354  0.065253  0.075041  0.133768  0.192496  0.287113   0.004237   \n",
      "154   0.158134  0.056883  0.063709  0.102389  0.248009  0.246871   0.017760   \n",
      "155   0.043720  0.041335  0.069157  0.163752  0.220191  0.295707   0.016931   \n",
      "156   0.167416  0.070787  0.083146  0.144944  0.207865  0.234831   0.014749   \n",
      "157   0.139565  0.106522  0.093043  0.145217  0.207391  0.235217   0.006397   \n",
      "158   0.115804  0.073569  0.110354  0.170300  0.167575  0.311989   0.141509   \n",
      "159   0.170938  0.076652  0.104162  0.174230  0.199859  0.217964   0.017312   \n",
      "160   0.119645  0.112260  0.097489  0.163959  0.248154  0.162482   0.001869   \n",
      "161   0.142692  0.064702  0.116696  0.153668  0.213172  0.256499   0.120289   \n",
      "162   0.130609  0.102564  0.095353  0.193109  0.157051  0.230769   0.044593   \n",
      "163   0.187471  0.064947  0.095808  0.163980  0.197605  0.238139   0.047841   \n",
      "164   0.097074  0.047872  0.049202  0.192819  0.272606  0.297872   0.032028   \n",
      "165   0.179952  0.067045  0.089321  0.175584  0.226687  0.200480   0.019039   \n",
      "166   0.111421  0.052925  0.077994  0.147632  0.167131  0.298050   0.086957   \n",
      "167   0.183835  0.144216  0.104596  0.228209  0.156894  0.153724   0.016129   \n",
      "168   0.182882  0.117200  0.113916  0.169745  0.192939  0.181856   0.006010   \n",
      "169   0.208827  0.115716  0.081808  0.159849  0.116254  0.199677   0.036792   \n",
      "170   0.140761  0.067120  0.067935  0.151630  0.174185  0.267391   0.052689   \n",
      "171   0.202783  0.095427  0.090457  0.161034  0.148608  0.221670   0.039769   \n",
      "172   0.193999  0.072575  0.087927  0.125611  0.180042  0.234473   0.020446   \n",
      "173   0.229571  0.076356  0.078533  0.164936  0.130610  0.212827   0.020317   \n",
      "174   0.168280  0.059858  0.061633  0.151500  0.149080  0.330268   0.073907   \n",
      "175   0.130116  0.089425  0.099834  0.193045  0.202508  0.232079   0.030370   \n",
      "176   0.149116  0.075327  0.076480  0.135665  0.137394  0.306111   0.053801   \n",
      "177   0.030422  0.077711  0.096386  0.349398  0.215361  0.203916   0.090700   \n",
      "178   0.118906  0.067776  0.087990  0.140904  0.123662  0.328181   0.012403   \n",
      "179   0.166105  0.069140  0.085160  0.133642  0.121417  0.313659   0.069026   \n",
      "180   0.070861  0.056200  0.091631  0.144777  0.143250  0.364692   0.059792   \n",
      "181   0.198737  0.082838  0.083210  0.180906  0.120357  0.250371   0.023256   \n",
      "182   0.182005  0.050386  0.061183  0.162468  0.111054  0.272494   0.108801   \n",
      "183   0.257040  0.076534  0.079422  0.154513  0.128520  0.214440   0.056497   \n",
      "184   0.281843  0.081301  0.130081  0.195122  0.081301  0.143631   0.014493   \n",
      "185   0.124348  0.087863  0.065525  0.186895  0.153388  0.265823   0.067568   \n",
      "186   0.146465  0.097222  0.103535  0.135101  0.157828  0.241162   0.039724   \n",
      "187   0.167892  0.117423  0.100431  0.172711  0.267816  0.144053   0.011786   \n",
      "188   0.242779  0.049961  0.069477  0.106167  0.088993  0.212334   0.100223   \n",
      "189   0.269113  0.068807  0.076453  0.111621  0.102446  0.240061   0.050000   \n",
      "190   0.195900  0.060364  0.076310  0.134396  0.117312  0.306378   0.069277   \n",
      "191   0.123134  0.083582  0.075373  0.155224  0.138060  0.229104   0.060254   \n",
      "192   0.160113  0.063932  0.080339  0.137765  0.151909  0.261952   0.044355   \n",
      "193   0.321311  0.131148  0.075410  0.137705  0.160656  0.124590   0.055319   \n",
      "194   0.188630  0.049096  0.033592  0.087855  0.142119  0.227390   0.072202   \n",
      "195   0.234167  0.084583  0.083333  0.129583  0.212917  0.171250   0.139069   \n",
      "196   0.279200  0.084731  0.091497  0.216534  0.117387  0.130038   0.255121   \n",
      "197   0.214171  0.063446  0.096296  0.101449  0.162963  0.272142   0.037415   \n",
      "198   0.215693  0.068978  0.102190  0.202190  0.160584  0.214599   0.130435   \n",
      "199   0.197553  0.065247  0.068419  0.096058  0.130494  0.302673   0.031727   \n",
      "200   0.131114  0.045565  0.076314  0.175259  0.279480  0.270043   0.025528   \n",
      "201   0.181954  0.079791  0.093587  0.132364  0.330350  0.135347   0.028607   \n",
      "202   0.138369  0.054849  0.055597  0.239092  0.157317  0.293194   0.426632   \n",
      "203   0.149390  0.055894  0.073171  0.164634  0.160569  0.318089   0.194767   \n",
      "204   0.245107  0.060267  0.059646  0.222429  0.109661  0.220876   0.321857   \n",
      "205   0.218004  0.086768  0.111714  0.245119  0.169197  0.106291   0.195804   \n",
      "206   0.149894  0.087394  0.140890  0.191208  0.220869  0.157309   0.020699   \n",
      "207   0.232404  0.047809  0.086321  0.159363  0.110226  0.197875   0.121547   \n",
      "208   0.113095  0.104167  0.116071  0.312500  0.104167  0.187500   0.479245   \n",
      "209   0.063291  0.091139  0.065823  0.172152  0.118987  0.273418   0.076190   \n",
      "210   0.249724  0.061878  0.059669  0.135912  0.129282  0.256354   0.055882   \n",
      "211   0.119187  0.057444  0.083236  0.123095  0.168034  0.309105   0.156925   \n",
      "212   0.216370  0.056584  0.063701  0.160854  0.169395  0.269395   0.032075   \n",
      "213   0.254633  0.062853  0.066882  0.107977  0.162772  0.208703   0.059296   \n",
      "214   0.232207  0.040121  0.050838  0.179170  0.208299  0.229459   0.091778   \n",
      "215   0.115924  0.114437  0.110616  0.173885  0.346921  0.117834   0.003545   \n",
      "216   0.218147  0.106178  0.142857  0.208494  0.063707  0.137066   0.050119   \n",
      "217   0.291476  0.110350  0.064688  0.118721  0.146119  0.187215   0.094488   \n",
      "218   0.158879  0.065421  0.076324  0.135514  0.165109  0.204050   0.012000   \n",
      "219   0.124274  0.053426  0.092915  0.164925  0.195122  0.232288   0.009160   \n",
      "220   0.105072  0.049517  0.118357  0.140097  0.194444  0.291063   0.062696   \n",
      "221   0.250000  0.094298  0.125000  0.076754  0.111842  0.171053   0.024390   \n",
      "222   0.160000  0.045636  0.075189  0.145567  0.173196  0.323162   0.043122   \n",
      "223   0.105872  0.134342  0.096975  0.162811  0.255338  0.217972   0.007143   \n",
      "224   0.069401  0.070978  0.131703  0.182177  0.312303  0.199527   0.011364   \n",
      "225   0.160364  0.068382  0.089757  0.130960  0.185898  0.290357   0.027041   \n",
      "226   0.096774  0.115207  0.102535  0.237327  0.173963  0.184332   0.117566   \n",
      "227   0.275604  0.063846  0.079573  0.163640  0.164576  0.157836   0.185891   \n",
      "228   0.195748  0.081311  0.071568  0.182285  0.158547  0.222321   0.283800   \n",
      "229   0.099716  0.060795  0.097727  0.150000  0.134659  0.291477   0.012528   \n",
      "230   0.125525  0.090424  0.124762  0.152232  0.284243  0.192675   0.013116   \n",
      "231   0.084189  0.049281  0.078029  0.158111  0.131417  0.320329   0.048295   \n",
      "232   0.105967  0.057613  0.078189  0.119342  0.113169  0.349794   0.051502   \n",
      "233   0.194172  0.050372  0.069010  0.144037  0.184499  0.285124   0.017375   \n",
      "234   0.119189  0.071006  0.088757  0.136517  0.124260  0.314032   0.022834   \n",
      "235   0.260951  0.066886  0.066415  0.114461  0.100801  0.234574   0.007161   \n",
      "236   0.230511  0.083155  0.069398  0.111281  0.126567  0.237236   0.044776   \n",
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      "567   0.142160  0.068640  0.077749  0.151919  0.168835  0.324984   0.069009   \n",
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      "569   0.135215  0.084324  0.101783  0.224740  0.148217  0.221397   0.126366   \n",
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      "734   0.156762  0.087090  0.096311  0.168033  0.149590  0.251025   0.012500   \n",
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      "736   0.095459  0.070750  0.095037  0.155649  0.157973  0.315945   0.038889   \n",
      "737   0.154985  0.087543  0.091775  0.151018  0.114255  0.244115   0.020007   \n",
      "738   0.194969  0.113208  0.078616  0.116352  0.235849  0.235849   0.000000   \n",
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      "742   0.354839  0.036866  0.050691  0.078341  0.101382  0.110599   0.023121   \n",
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      "776   0.301871  0.092758  0.081367  0.200163  0.146461  0.124491   0.143302   \n",
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      "778   0.099420  0.103563  0.147473  0.222038  0.147473  0.211268   0.007617   \n",
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      "780   0.331707  0.094077  0.091986  0.140767  0.119164  0.121951   0.057998   \n",
      "781   0.114267  0.085644  0.112701  0.185152  0.172406  0.277281   0.034764   \n",
      "782   0.080406  0.059421  0.113541  0.170311  0.206539  0.296002   0.030569   \n",
      "783   0.166249  0.086964  0.087798  0.145051  0.152061  0.288933   0.028350   \n",
      "784   0.100639  0.091409  0.097089  0.149450  0.167199  0.291445   0.068072   \n",
      "785   0.179081  0.050831  0.094233  0.151906  0.226002  0.265885   0.022614   \n",
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      "787   0.097064  0.046493  0.053834  0.153344  0.141109  0.265905   0.064407   \n",
      "788   0.125887  0.039007  0.074468  0.127660  0.179078  0.301418   0.048837   \n",
      "789   0.302433  0.090382  0.100811  0.120510  0.104287  0.190035   0.039216   \n",
      "790   0.194490  0.072368  0.081003  0.113487  0.157895  0.267681   0.100845   \n",
      "791   0.185459  0.075786  0.076402  0.142329  0.181762  0.202095   0.041563   \n",
      "792   0.113009  0.064389  0.085852  0.130092  0.172142  0.318003   0.113232   \n",
      "793   0.173998  0.098729  0.084066  0.180841  0.132942  0.221896   0.030345   \n",
      "794   0.197198  0.077586  0.071121  0.148707  0.129310  0.216595   0.046414   \n",
      "795   0.250000  0.094884  0.079208  0.149340  0.142739  0.169967   0.106605   \n",
      "796   0.186874  0.083667  0.085671  0.167836  0.175351  0.222445   0.046097   \n",
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      "798   0.146597  0.087509  0.110322  0.168287  0.190352  0.253179   0.050808   \n",
      "799   0.083008  0.071866  0.102507  0.178830  0.181616  0.315320   0.082224   \n",
      "800   0.137097  0.055444  0.088710  0.156250  0.165323  0.295363   0.050891   \n",
      "801   0.224359  0.087607  0.108974  0.130342  0.134615  0.217949   0.005510   \n",
      "802   0.130192  0.047923  0.084665  0.186901  0.255591  0.257188   0.043165   \n",
      "803   0.120165  0.062551  0.086420  0.161317  0.240329  0.253498   0.016704   \n",
      "804   0.239370  0.066929  0.081890  0.176378  0.192126  0.182677   0.075410   \n",
      "805   0.156228  0.061195  0.092153  0.161267  0.190065  0.248380   0.018609   \n",
      "806   0.207111  0.092444  0.096000  0.131556  0.139556  0.243556   0.031175   \n",
      "807   0.176900  0.064835  0.095320  0.166166  0.171318  0.231859   0.059988   \n",
      "808   0.168462  0.080966  0.080640  0.127326  0.151159  0.258244   0.019373   \n",
      "809   0.094771  0.107843  0.068627  0.156863  0.228758  0.209150   0.069124   \n",
      "810   0.406582  0.064756  0.066879  0.151805  0.072187  0.119958   0.144343   \n",
      "811   0.221203  0.093782  0.078491  0.266055  0.109072  0.140673   0.053385   \n",
      "812   0.108417  0.084165  0.114123  0.203994  0.124108  0.286733   0.045833   \n",
      "813   0.092105  0.069737  0.092763  0.188816  0.194079  0.246711   0.018484   \n",
      "814   0.169713  0.129896  0.110313  0.132507  0.161227  0.248695   0.002383   \n",
      "815   0.178010  0.060583  0.079656  0.148467  0.182872  0.284218   0.098715   \n",
      "816   0.148270  0.064250  0.065898  0.152389  0.185338  0.261944   0.028377   \n",
      "817   0.137901  0.054640  0.070252  0.170859  0.173461  0.313964   0.031653   \n",
      "818   0.074658  0.053628  0.132492  0.154574  0.200841  0.307571   0.022869   \n",
      "819   0.223594  0.102881  0.089163  0.212620  0.159122  0.172840   0.017921   \n",
      "820   0.239018  0.076227  0.102067  0.162791  0.142119  0.204134   0.042623   \n",
      "821   0.226555  0.076137  0.106778  0.137419  0.153203  0.225627   0.037253   \n",
      "822   0.173410  0.083815  0.078035  0.147399  0.138728  0.323699   0.018797   \n",
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      "824   0.156731  0.082692  0.074038  0.157692  0.137500  0.262500   0.014688   \n",
      "825   0.147074  0.078198  0.101502  0.207147  0.149146  0.264630   0.045031   \n",
      "826   0.062286  0.059548  0.091034  0.186858  0.164271  0.336756   0.097816   \n",
      "827   0.035863  0.036812  0.054269  0.179507  0.214801  0.391082   0.126819   \n",
      "828   0.014577  0.107872  0.037901  0.172012  0.204082  0.384840   0.067961   \n",
      "829   0.080858  0.073432  0.089109  0.143564  0.201320  0.351485   0.025290   \n",
      "830   0.082422  0.097009  0.084610  0.152443  0.242888  0.242888   0.024201   \n",
      "831   0.102733  0.078228  0.084826  0.155042  0.194156  0.311970   0.035783   \n",
      "832   0.153028  0.081368  0.098012  0.163662  0.171059  0.244105   0.021518   \n",
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      "835   0.132877  0.065753  0.071233  0.172603  0.180822  0.284932   0.083164   \n",
      "836   0.224913  0.055363  0.083045  0.204152  0.138408  0.276817   0.004292   \n",
      "837   0.127767  0.069576  0.082859  0.141050  0.251739  0.259962   0.013072   \n",
      "838   0.132161  0.077387  0.096482  0.174874  0.149246  0.293970   0.060811   \n",
      "839   0.142005  0.073713  0.084011  0.163686  0.172900  0.234688   0.028530   \n",
      "840   0.180791  0.090395  0.129944  0.220339  0.129944  0.175141   0.000000   \n",
      "841   0.129052  0.047419  0.094838  0.125450  0.179472  0.285114   0.012579   \n",
      "842   0.083214  0.110473  0.169297  0.252511  0.255380  0.106169   0.013333   \n",
      "843   0.095406  0.067138  0.060071  0.180212  0.141343  0.194346   0.035503   \n",
      "844   0.393404  0.044170  0.075972  0.128386  0.104240  0.181390   0.008746   \n",
      "845   0.392713  0.048583  0.068826  0.134953  0.110661  0.107962   0.010435   \n",
      "846   0.139683  0.053968  0.074603  0.133333  0.117460  0.376190   0.075975   \n",
      "847   0.103618  0.067434  0.074013  0.180921  0.162829  0.379934   0.008584   \n",
      "848   0.254753  0.087452  0.106464  0.178707  0.140684  0.171103   0.040816   \n",
      "849   0.180402  0.032800  0.043631  0.091903  0.304899  0.294275   0.009295   \n",
      "850   0.367534  0.035222  0.045942  0.125574  0.163859  0.182236   0.063063   \n",
      "851   0.138956  0.097694  0.085558  0.140777  0.229976  0.216626   0.003897   \n",
      "852   0.170854  0.060302  0.062186  0.114322  0.116834  0.408920   0.021978   \n",
      "853   0.270864  0.081991  0.087848  0.121523  0.132504  0.185212   0.088487   \n",
      "854   0.167355  0.084711  0.097107  0.200413  0.173554  0.198347   0.066007   \n",
      "855   0.123967  0.066116  0.086777  0.239669  0.185950  0.247934   0.057143   \n",
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      "857   0.103723  0.074468  0.103723  0.170213  0.122340  0.343085   0.022989   \n",
      "858   0.167116  0.075472  0.118598  0.210243  0.099730  0.242588   0.068000   \n",
      "859   0.196429  0.089286  0.107143  0.169643  0.142857  0.250000   0.040000   \n",
      "860   0.183917  0.118232  0.123010  0.166003  0.173169  0.180334   0.003333   \n",
      "861   0.206349  0.068783  0.089947  0.248677  0.169312  0.164021   0.036232   \n",
      "862   0.183552  0.089392  0.076281  0.135876  0.134684  0.270560   0.094059   \n",
      "863   0.307317  0.043902  0.078049  0.224390  0.097561  0.200000   0.057325   \n",
      "864   0.350282  0.047081  0.056497  0.124294  0.099812  0.212806   0.007732   \n",
      "865   0.175810  0.063591  0.088529  0.130923  0.265586  0.192020   0.010239   \n",
      "866   0.101695  0.152542  0.107345  0.175141  0.271186  0.135593   0.008000   \n",
      "867   0.084488  0.051247  0.066482  0.163435  0.127424  0.373961   0.343750   \n",
      "868   0.171965  0.115607  0.085260  0.143064  0.154624  0.245665   0.148148   \n",
      "869   0.350547  0.067436  0.054678  0.101458  0.140948  0.146416   0.315234   \n",
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      "873   0.283146  0.067416  0.068539  0.139326  0.160674  0.205618   0.105263   \n",
      "874   0.067687  0.053561  0.070630  0.277222  0.323131  0.163626   0.173213   \n",
      "875   0.125151  0.049507  0.083261  0.158041  0.220703  0.315562   0.050288   \n",
      "876   0.341748  0.075728  0.075728  0.097087  0.114563  0.155340   0.082262   \n",
      "877   0.371009  0.050043  0.037101  0.108714  0.125971  0.208801   0.225877   \n",
      "878   0.340034  0.033501  0.045226  0.145729  0.120603  0.227806   0.045767   \n",
      "879   0.199866  0.077302  0.095451  0.132646  0.169169  0.251176   0.020299   \n",
      "880   0.275362  0.052174  0.060870  0.127536  0.220290  0.223188   0.007491   \n",
      "881   0.185890  0.050392  0.080627  0.111982  0.152296  0.210526   0.008902   \n",
      "882   0.198743  0.040848  0.055774  0.129615  0.304792  0.235664   0.002915   \n",
      "883   0.020871  0.043557  0.071688  0.151543  0.213249  0.428312   0.069421   \n",
      "884   0.129875  0.082648  0.093023  0.168873  0.260465  0.207513   0.093328   \n",
      "885   0.178862  0.076461  0.091754  0.152342  0.152149  0.268873   0.072229   \n",
      "886   0.291313  0.074599  0.059962  0.135033  0.115675  0.245515   0.046512   \n",
      "887   0.136544  0.087819  0.083853  0.124646  0.171105  0.209632   0.024682   \n",
      "888   0.254816  0.091635  0.087507  0.166758  0.124106  0.197578   0.094985   \n",
      "889   0.164596  0.071429  0.085016  0.134317  0.221273  0.237189   0.079980   \n",
      "890   0.220339  0.066667  0.066667  0.133898  0.218644  0.219209   0.119917   \n",
      "891   0.104758  0.069788  0.097704  0.144379  0.140928  0.307669   0.031015   \n",
      "892   0.281773  0.077759  0.071906  0.149666  0.107023  0.125418   0.129464   \n",
      "893   0.184481  0.064330  0.080100  0.132165  0.183980  0.253066   0.101511   \n",
      "894   0.219628  0.080880  0.066328  0.126227  0.115398  0.218274   0.031615   \n",
      "895   0.297166  0.074089  0.085020  0.134008  0.129555  0.173684   0.089696   \n",
      "896   0.296161  0.082267  0.054845  0.082267  0.179159  0.221207   0.002232   \n",
      "897   0.240577  0.053500  0.063401  0.161369  0.192809  0.235366   0.040541   \n",
      "898   0.207653  0.082975  0.088994  0.153482  0.123818  0.217111   0.083956   \n",
      "899   0.106589  0.060724  0.093669  0.144057  0.211240  0.335271   0.105307   \n",
      "900   0.415139  0.075697  0.069323  0.160159  0.109163  0.120319   0.302251   \n",
      "901   0.077808  0.041949  0.102616  0.180875  0.179296  0.325214   0.268948   \n",
      "902   0.049502  0.049082  0.090194  0.223073  0.232722  0.321552   0.108625   \n",
      "903   0.191159  0.062452  0.091344  0.172260  0.172803  0.247312   0.148280   \n",
      "904   0.108773  0.074599  0.096062  0.142321  0.210877  0.302355   0.171812   \n",
      "905   0.108929  0.058482  0.076786  0.118750  0.179018  0.339732   0.032297   \n",
      "906   0.033002  0.041907  0.087742  0.160031  0.177842  0.393662   0.032923   \n",
      "907   0.124224  0.061335  0.078416  0.131988  0.162267  0.339286   0.028896   \n",
      "908   0.139219  0.047538  0.080645  0.149406  0.168930  0.298812   0.080447   \n",
      "909   0.176111  0.073889  0.077778  0.258333  0.126667  0.177778   0.287661   \n",
      "910   0.132270  0.058161  0.057223  0.157598  0.245779  0.253283   0.120253   \n",
      "911   0.244624  0.066052  0.066820  0.119048  0.144393  0.210061   0.166920   \n",
      "912   0.200622  0.081285  0.079953  0.165235  0.152946  0.234380   0.179383   \n",
      "913   0.188955  0.077179  0.098248  0.191617  0.171878  0.220226   0.118924   \n",
      "914   0.282877  0.060252  0.084944  0.133655  0.157407  0.170827   0.195912   \n",
      "915   0.333333  0.065664  0.056140  0.107769  0.123810  0.215038   0.415265   \n",
      "916   0.159144  0.063751  0.082364  0.142392  0.183341  0.250349   0.024818   \n",
      "917   0.098575  0.073789  0.107123  0.160304  0.254796  0.278443   0.180022   \n",
      "918   0.141093  0.062886  0.096730  0.153442  0.155500  0.316945   0.281467   \n",
      "919   0.290965  0.078158  0.074627  0.171562  0.141229  0.138822   0.249734   \n",
      "920   0.190616  0.065103  0.088563  0.165396  0.233627  0.214858   0.118669   \n",
      "921   0.121228  0.050231  0.093007  0.188853  0.158857  0.343450   0.235250   \n",
      "922   0.063890  0.063472  0.109302  0.193757  0.213697  0.318092   0.133323   \n",
      "923   0.122499  0.068326  0.092728  0.129331  0.189361  0.311371   0.065232   \n",
      "924   0.115727  0.050445  0.097923  0.195846  0.163205  0.181009   0.141762   \n",
      "925   0.120342  0.058644  0.086133  0.138465  0.194869  0.306659   0.032778   \n",
      "926   0.145112  0.060807  0.087892  0.190314  0.169686  0.311749   0.107434   \n",
      "927   0.267442  0.072558  0.099070  0.157209  0.167442  0.153488   0.344148   \n",
      "928   0.271132  0.070193  0.088730  0.157192  0.139644  0.195255   0.097204   \n",
      "929   0.102644  0.072162  0.090980  0.196112  0.210731  0.286003   0.073092   \n",
      "930   0.166741  0.075751  0.078440  0.155087  0.144330  0.297176   0.042310   \n",
      "931   0.202532  0.076854  0.084087  0.169078  0.168174  0.213382   0.111500   \n",
      "932   0.295611  0.057309  0.060573  0.132028  0.092492  0.189336   0.202370   \n",
      "933   0.130689  0.074122  0.098830  0.156047  0.124837  0.265280   0.110694   \n",
      "934   0.340621  0.045963  0.047205  0.136149  0.119255  0.212174   0.112840   \n",
      "935   0.163256  0.055349  0.066047  0.135349  0.182791  0.284186   0.008782   \n",
      "936   0.194290  0.047099  0.078736  0.122790  0.219559  0.275240   0.031303   \n",
      "937   0.041537  0.067497  0.065421  0.131880  0.521288  0.130841   0.006757   \n",
      "938   0.040598  0.066383  0.059114  0.153614  0.448224  0.206830   0.005270   \n",
      "939   0.301259  0.071888  0.072727  0.154685  0.114685  0.191329   0.228082   \n",
      "940   0.065616  0.047301  0.076445  0.163561  0.373308  0.248447   0.026472   \n",
      "941   0.174443  0.056027  0.107989  0.132202  0.183457  0.277660   0.016901   \n",
      "942   0.248715  0.061249  0.075905  0.109155  0.169419  0.219950   0.023816   \n",
      "943   0.124054  0.067238  0.089427  0.168432  0.160027  0.316860   0.178699   \n",
      "944   0.119884  0.056514  0.084147  0.136505  0.204654  0.306669   0.016157   \n",
      "945   0.182457  0.074881  0.077870  0.106697  0.204254  0.257515   0.007415   \n",
      "946   0.292690  0.078931  0.065111  0.097666  0.248771  0.168305   0.002530   \n",
      "947   0.087152  0.107817  0.099730  0.247978  0.238095  0.199012   0.042751   \n",
      "948   0.144609  0.087123  0.068217  0.139244  0.408533  0.140521   0.006132   \n",
      "949   0.192194  0.040360  0.034862  0.076128  0.181620  0.405837   0.021404   \n",
      "950   0.104125  0.063455  0.071820  0.102971  0.248918  0.331410   0.012829   \n",
      "951   0.076373  0.037240  0.078687  0.130234  0.178203  0.395540   0.055003   \n",
      "952   0.263135  0.065357  0.076890  0.225545  0.098676  0.222127   0.444002   \n",
      "953   0.329343  0.076427  0.082259  0.145488  0.109883  0.120012   0.171280   \n",
      "954   0.129637  0.051162  0.064003  0.147574  0.232980  0.290664   0.052092   \n",
      "955   0.294144  0.078773  0.093082  0.143236  0.116831  0.143531   0.120747   \n",
      "956   0.147152  0.104970  0.110545  0.258182  0.219152  0.150545   0.040648   \n",
      "957   0.124396  0.066727  0.072162  0.118961  0.126510  0.314614   0.078724   \n",
      "958   0.250726  0.059624  0.071243  0.154105  0.124446  0.217245   0.189754   \n",
      "959   0.151154  0.127820  0.073632  0.100596  0.113819  0.413793   0.018562   \n",
      "960   0.311948  0.079164  0.083873  0.159800  0.117422  0.130959   0.139245   \n",
      "961   0.231114  0.117427  0.098978  0.114685  0.082772  0.318624   0.031045   \n",
      "962   0.199838  0.071342  0.083908  0.149574  0.168221  0.222537   0.025070   \n",
      "963   0.204242  0.067557  0.093480  0.151610  0.111548  0.234878   0.151270   \n",
      "964   0.206132  0.060105  0.075837  0.119403  0.114562  0.283582   0.145135   \n",
      "965   0.317225  0.091582  0.105222  0.125487  0.118472  0.141076   0.171414   \n",
      "966   0.313964  0.085754  0.085286  0.135426  0.115745  0.142455   0.192403   \n",
      "967   0.177485  0.143002  0.101420  0.130832  0.150101  0.242394   0.032624   \n",
      "968   0.166400  0.050400  0.067200  0.118800  0.140800  0.334000   0.014123   \n",
      "969   0.102238  0.045634  0.078982  0.169811  0.125055  0.386134   0.277027   \n",
      "970   0.151163  0.074128  0.056686  0.414244  0.101744  0.106105   0.345361   \n",
      "971   0.075749  0.069922  0.073252  0.228357  0.194506  0.252497   0.026744   \n",
      "972   0.129225  0.091197  0.077465  0.142606  0.153169  0.284859   0.053237   \n",
      "973   0.105657  0.063808  0.088091  0.164557  0.167140  0.278998   0.036998   \n",
      "974   0.077508  0.061816  0.092725  0.168331  0.141227  0.369472   0.105718   \n",
      "975   0.138521  0.074319  0.097665  0.217121  0.134241  0.270428   0.302449   \n",
      "976   0.250074  0.074874  0.106540  0.142350  0.128144  0.217816   0.053944   \n",
      "977   0.055495  0.106094  0.110990  0.295974  0.238847  0.151251   0.000605   \n",
      "978   0.102093  0.108374  0.179388  0.242512  0.135266  0.171498   0.014916   \n",
      "979   0.163442  0.094196  0.074338  0.219450  0.133401  0.201120   0.208741   \n",
      "980   0.050474  0.072157  0.118622  0.236334  0.189869  0.278061   0.098334   \n",
      "981   0.110656  0.070843  0.072600  0.156323  0.145199  0.333138   0.132721   \n",
      "982   0.146433  0.080754  0.109825  0.198654  0.134859  0.254105   0.183622   \n",
      "983   0.178660  0.078908  0.075931  0.177667  0.135484  0.209429   0.059406   \n",
      "984   0.074407  0.068956  0.097029  0.193241  0.164350  0.356773   0.061017   \n",
      "985   0.115426  0.093851  0.081985  0.154261  0.155340  0.240561   0.039660   \n",
      "986   0.103645  0.073342  0.066755  0.168204  0.146245  0.309618   0.124405   \n",
      "987   0.121060  0.055874  0.096705  0.248567  0.202722  0.214900   0.044809   \n",
      "988   0.147059  0.062325  0.079832  0.132353  0.123249  0.301821   0.099617   \n",
      "989   0.190231  0.118895  0.100257  0.109897  0.125964  0.222365   0.078111   \n",
      "990   0.083897  0.052774  0.075101  0.160352  0.148850  0.336265   0.028837   \n",
      "991   0.175613  0.071809  0.081052  0.134732  0.157483  0.307856   0.028861   \n",
      "992   0.169318  0.093750  0.081818  0.151705  0.161364  0.254545   0.012953   \n",
      "993   0.088632  0.057803  0.075145  0.263969  0.121387  0.238921   0.104061   \n",
      "994   0.114471  0.077754  0.095032  0.179266  0.198704  0.245140   0.029985   \n",
      "995   0.160142  0.056940  0.104093  0.186833  0.145907  0.235765   0.026250   \n",
      "996   0.168449  0.087344  0.093583  0.116756  0.210339  0.200535   0.068182   \n",
      "997   0.147573  0.077670  0.081553  0.209709  0.087379  0.166990   0.059432   \n",
      "998   0.152448  0.070104  0.072329  0.131677  0.117953  0.308976   0.074781   \n",
      "999   0.121689  0.078828  0.103381  0.162180  0.164118  0.264915   0.016008   \n",
      "1000  0.079817  0.076767  0.111337  0.164209  0.204372  0.252669   0.061123   \n",
      "1001  0.205820  0.072121  0.095318  0.140447  0.132434  0.240405   0.140321   \n",
      "1002  0.120192  0.087740  0.069712  0.155048  0.175481  0.221154   0.074913   \n",
      "1003  0.133005  0.079521  0.104152  0.213934  0.149894  0.237861   0.242181   \n",
      "1004  0.132701  0.042654  0.065403  0.141232  0.141232  0.291943   0.198693   \n",
      "1005  0.103417  0.076439  0.071942  0.143885  0.145683  0.287770   0.156410   \n",
      "1006  0.210654  0.055690  0.076271  0.135593  0.119855  0.251816   0.158784   \n",
      "1007  0.233203  0.071521  0.084525  0.127438  0.187690  0.248808   0.005482   \n",
      "1008  0.060117  0.049853  0.083578  0.172287  0.192082  0.344575   0.140082   \n",
      "1009  0.244000  0.048000  0.032000  0.152000  0.152000  0.148000   0.216080   \n",
      "1010  0.175781  0.067383  0.095703  0.172852  0.119141  0.254883   0.022989   \n",
      "1011  0.076175  0.059968  0.095219  0.188412  0.207050  0.300243   0.032609   \n",
      "1012  0.088810  0.086146  0.081705  0.139432  0.144760  0.309059   0.032995   \n",
      "1013  0.118293  0.054878  0.068293  0.163415  0.181707  0.275610   0.026578   \n",
      "1014  0.155543  0.107005  0.128516  0.170436  0.163817  0.207943   0.039318   \n",
      "1015  0.132333  0.102319  0.092087  0.145975  0.208049  0.261255   0.026094   \n",
      "1016  0.155822  0.087329  0.075342  0.214041  0.198630  0.171233   0.035545   \n",
      "1017  0.088083  0.081606  0.090026  0.121762  0.136010  0.303756   0.037931   \n",
      "1018  0.088260  0.095861  0.091639  0.180743  0.154561  0.293074   0.042301   \n",
      "1019  0.113896  0.078276  0.077397  0.131047  0.138083  0.309147   0.012419   \n",
      "1020  0.106856  0.055343  0.092110  0.185370  0.200306  0.259288   0.034070   \n",
      "1021  0.220636  0.072680  0.075600  0.132706  0.140169  0.256003   0.026626   \n",
      "1022  0.217663  0.074728  0.079620  0.148641  0.182880  0.210870   0.028010   \n",
      "1023  0.180541  0.085766  0.103423  0.148829  0.185225  0.244685   0.129380   \n",
      "1024  0.220089  0.093058  0.098966  0.127031  0.181684  0.206795   0.119374   \n",
      "1025  0.087866  0.080544  0.082985  0.187936  0.354603  0.177476   0.032915   \n",
      "1026  0.046610  0.084746  0.087571  0.214689  0.264124  0.235876   0.030075   \n",
      "1027  0.095606  0.084359  0.086819  0.161687  0.171178  0.323023   0.043705   \n",
      "1028  0.290370  0.096296  0.088889  0.177778  0.096296  0.205926   0.066288   \n",
      "1029  0.102227  0.072874  0.097166  0.151316  0.239372  0.264676   0.029703   \n",
      "1030  0.063858  0.070288  0.099335  0.189357  0.199557  0.305987   0.014873   \n",
      "1031  0.143241  0.088406  0.093554  0.166070  0.154208  0.280886   0.009975   \n",
      "1032  0.060498  0.069395  0.101423  0.225979  0.220641  0.263345   0.037915   \n",
      "1033  0.194626  0.086347  0.077060  0.137325  0.142660  0.285912   0.010210   \n",
      "1034  0.330709  0.039370  0.102362  0.149606  0.110236  0.165354   0.020202   \n",
      "1035  0.150358  0.126492  0.171838  0.212411  0.212411  0.114558   0.019178   \n",
      "1036  0.075044  0.058464  0.077661  0.292321  0.218150  0.222513   0.197030   \n",
      "1037  0.094444  0.055556  0.065079  0.167460  0.317460  0.242063   0.014231   \n",
      "1038  0.295033  0.064492  0.062268  0.084507  0.176427  0.257969   0.018088   \n",
      "1039  0.042681  0.053114  0.096111  0.177363  0.227000  0.308884   0.011399   \n",
      "1040  0.115315  0.062104  0.082303  0.169129  0.185409  0.326349   0.015378   \n",
      "1041  0.187692  0.044103  0.071795  0.154872  0.204103  0.251282   0.021935   \n",
      "1042  0.115160  0.065598  0.100583  0.173469  0.186589  0.241983   0.021154   \n",
      "1043  0.147072  0.061647  0.070013  0.147952  0.157640  0.297666   0.011965   \n",
      "1044  0.211329  0.081699  0.111111  0.153595  0.114379  0.213508   0.016105   \n",
      "1045  0.133540  0.088509  0.062112  0.169255  0.172360  0.288820   0.088983   \n",
      "1046  0.227795  0.064653  0.091239  0.114199  0.178852  0.247734   0.092186   \n",
      "1047  0.094477  0.055975  0.077595  0.189545  0.205686  0.316156   0.037922   \n",
      "1048  0.106195  0.101770  0.088496  0.203540  0.190265  0.243363   0.055556   \n",
      "1049  0.218462  0.061538  0.113846  0.196923  0.141538  0.215385   0.056338   \n",
      "1050  0.241715  0.040936  0.056530  0.101365  0.152047  0.304094   0.066496   \n",
      "1051  0.039506  0.054321  0.135802  0.207407  0.256790  0.187654   0.018315   \n",
      "1052  0.082759  0.043678  0.059770  0.206897  0.213793  0.259770   0.021277   \n",
      "1053  0.128440  0.087156  0.073394  0.243119  0.137615  0.275229   0.070312   \n",
      "1054  0.085856  0.076732  0.110328  0.170469  0.180838  0.270012   0.092432   \n",
      "1055  0.111888  0.095105  0.107692  0.313287  0.240559  0.113287   0.032328   \n",
      "1056  0.085885  0.042569  0.077670  0.131441  0.241225  0.298730   0.012464   \n",
      "1057  0.134615  0.067308  0.067308  0.250000  0.201923  0.221154   0.102941   \n",
      "1058  0.145544  0.083401  0.076043  0.269828  0.115290  0.215863   0.146341   \n",
      "1059  0.169643  0.082589  0.082589  0.132812  0.143973  0.213170   0.031646   \n",
      "1060  0.192171  0.060498  0.058719  0.172598  0.218861  0.227758   0.033981   \n",
      "1061  0.187817  0.047377  0.059222  0.142132  0.155668  0.267343   0.099307   \n",
      "1062  0.229104  0.076119  0.070896  0.158209  0.126866  0.195522   0.051387   \n",
      "1063  0.244742  0.049713  0.070746  0.124283  0.120459  0.246654   0.060870   \n",
      "1064  0.204453  0.082996  0.056680  0.137652  0.210526  0.228745   0.010444   \n",
      "1065  0.242029  0.057971  0.074638  0.142029  0.137681  0.200725   0.043344   \n",
      "1066  0.203647  0.104863  0.074468  0.214286  0.109422  0.211246   0.079229   \n",
      "1067  0.263816  0.083420  0.088634  0.189781  0.102190  0.178311   0.103811   \n",
      "1068  0.240372  0.058433  0.053785  0.146082  0.092297  0.198539   0.058401   \n",
      "1069  0.127572  0.068313  0.084774  0.143210  0.149794  0.311934   0.020948   \n",
      "1070  0.100457  0.100457  0.189498  0.246575  0.178082  0.136986   0.068768   \n",
      "1071  0.193208  0.075628  0.076199  0.147546  0.146689  0.266553   0.019878   \n",
      "1072  0.139854  0.057587  0.083638  0.156307  0.146709  0.323583   0.044852   \n",
      "1073  0.087679  0.075219  0.116290  0.194278  0.155515  0.293493   0.030807   \n",
      "1074  0.189757  0.066331  0.077246  0.127624  0.173804  0.225021   0.034483   \n",
      "1075  0.238983  0.104520  0.088701  0.154802  0.119209  0.227684   0.044926   \n",
      "1076  0.221113  0.055635  0.069900  0.132668  0.138374  0.292439   0.032567   \n",
      "1077  0.275377  0.078894  0.093970  0.144724  0.139196  0.207538   0.020365   \n",
      "1078  0.428571  0.023377  0.077922  0.127273  0.129870  0.122078   0.071685   \n",
      "1079  0.181651  0.082569  0.094495  0.172477  0.194495  0.216514   0.034869   \n",
      "1080  0.207556  0.074092  0.091757  0.195289  0.151619  0.198234   0.031790   \n",
      "1081  0.327602  0.088688  0.078733  0.122172  0.101357  0.170136   0.033800   \n",
      "1082  0.224412  0.100834  0.087945  0.174375  0.117513  0.189538   0.032563   \n",
      "1083  0.317010  0.062500  0.070876  0.123067  0.142397  0.195232   0.021739   \n",
      "1084  0.142857  0.071058  0.062916  0.155440  0.136936  0.316062   0.039960   \n",
      "1085  0.315789  0.075391  0.079659  0.112376  0.128023  0.209104   0.005964   \n",
      "1086  0.316369  0.095369  0.092160  0.155433  0.102247  0.148097   0.035782   \n",
      "1087  0.394322  0.041009  0.078864  0.123028  0.085174  0.135647   0.025316   \n",
      "1088  0.205502  0.049055  0.068943  0.118992  0.148160  0.299304   0.037195   \n",
      "1089  0.136258  0.056072  0.067693  0.130157  0.131319  0.334108   0.021626   \n",
      "1090  0.163649  0.062478  0.088747  0.126731  0.132765  0.284700   0.066826   \n",
      "1091  0.153519  0.057618  0.099768  0.139598  0.139985  0.305491   0.042857   \n",
      "1092  0.129730  0.054054  0.086486  0.144865  0.110270  0.295135   0.021638   \n",
      "1093  0.130364  0.070445  0.094737  0.145749  0.165992  0.272874   0.036209   \n",
      "1094  0.302196  0.059918  0.080015  0.149981  0.131001  0.159658   0.029798   \n",
      "1095  0.158800  0.083951  0.087660  0.173297  0.151045  0.222859   0.061717   \n",
      "1096  0.138860  0.067358  0.073575  0.205181  0.132642  0.269430   0.020915   \n",
      "1097  0.194260  0.086093  0.108168  0.152318  0.097130  0.260486   0.084034   \n",
      "1098  0.194831  0.059642  0.081511  0.101392  0.113320  0.274354   0.032609   \n",
      "1099  0.206790  0.043210  0.086420  0.137346  0.126543  0.211420   0.066667   \n",
      "1100  0.164604  0.096535  0.106436  0.165223  0.142946  0.237624   0.021331   \n",
      "1101  0.250671  0.079678  0.078335  0.166070  0.136079  0.203223   0.024938   \n",
      "1102  0.053712  0.031596  0.042654  0.134281  0.214850  0.454976   0.025510   \n",
      "1103  0.320646  0.072664  0.080738  0.175317  0.122261  0.154556   0.071778   \n",
      "1104  0.028862  0.031098  0.052439  0.201016  0.265650  0.376829   0.041111   \n",
      "1105  0.126521  0.124088  0.119221  0.201946  0.126521  0.172749   0.052288   \n",
      "1106  0.125000  0.141667  0.070833  0.212500  0.220833  0.170833   0.038889   \n",
      "1107  0.239244  0.065058  0.066107  0.162644  0.162644  0.152151   0.080688   \n",
      "1108  0.126724  0.117241  0.109483  0.259483  0.107759  0.193103   0.392157   \n",
      "1109  0.108411  0.128972  0.112150  0.310280  0.175701  0.110280   0.089286   \n",
      "1110  0.068884  0.045131  0.114014  0.116390  0.261283  0.306413   0.022581   \n",
      "1111  0.233280  0.097134  0.088376  0.170382  0.104299  0.187898   0.172343   \n",
      "1112  0.115714  0.070714  0.090714  0.156429  0.172143  0.282857   0.041041   \n",
      "1113  0.223596  0.095827  0.076249  0.121072  0.131376  0.217929   0.071631   \n",
      "1114  0.123789  0.087225  0.101322  0.168722  0.162555  0.262115   0.043326   \n",
      "1115  0.159065  0.069375  0.075508  0.129168  0.157915  0.311997   0.051872   \n",
      "1116  0.117438  0.074733  0.099644  0.291815  0.153025  0.220641   0.018072   \n",
      "1117  0.233113  0.091391  0.103311  0.154967  0.182781  0.160265   0.071074   \n",
      "1118  0.032338  0.084577  0.243781  0.407960  0.149254  0.067164   0.040404   \n",
      "1119  0.181486  0.131547  0.131547  0.224117  0.140073  0.137637   0.102439   \n",
      "1120  0.220513  0.064957  0.109402  0.150427  0.147009  0.172650   0.000000   \n",
      "1121  0.139535  0.082687  0.105943  0.160207  0.188630  0.263566   0.105785   \n",
      "1122  0.101351  0.055105  0.077177  0.154505  0.163964  0.358258   0.066667   \n",
      "1123  0.226185  0.106009  0.071812  0.113825  0.120664  0.208109   0.102647   \n",
      "1124  0.150436  0.090116  0.066134  0.143169  0.164244  0.312500   0.094280   \n",
      "1125  0.240185  0.096998  0.056197  0.140878  0.127021  0.246343   0.126008   \n",
      "1126  0.301608  0.073250  0.080396  0.118239  0.116615  0.197012   0.052827   \n",
      "1127  0.277236  0.058499  0.097499  0.140314  0.114455  0.222976   0.050000   \n",
      "1128  0.261089  0.078046  0.055587  0.137563  0.145424  0.217294   0.016216   \n",
      "1129  0.100647  0.074047  0.079224  0.143063  0.171675  0.298203   0.029913   \n",
      "1130  0.073034  0.081862  0.105939  0.196629  0.177368  0.219904   0.132017   \n",
      "1131  0.140632  0.113605  0.096198  0.300046  0.114979  0.175905   0.358319   \n",
      "1132  0.112698  0.069352  0.076492  0.118307  0.130546  0.303417   0.043776   \n",
      "1133  0.086692  0.073004  0.082890  0.183270  0.174905  0.276806   0.027900   \n",
      "1134  0.213247  0.063813  0.095315  0.147011  0.181745  0.178514   0.027689   \n",
      "1135  0.184204  0.087389  0.072866  0.223694  0.121019  0.211975   0.262880   \n",
      "1136  0.186597  0.067017  0.081472  0.099869  0.132720  0.304862   0.247331   \n",
      "1137  0.302059  0.062929  0.075515  0.102975  0.254005  0.145309   0.011673   \n",
      "1138  0.125672  0.090292  0.069912  0.161053  0.133314  0.300311   0.071678   \n",
      "1139  0.188506  0.075862  0.096552  0.181609  0.158621  0.216092   0.084034   \n",
      "1140  0.093340  0.057692  0.084428  0.158537  0.146341  0.347561   0.063316   \n",
      "1141  0.115355  0.058824  0.088872  0.157117  0.157117  0.319073   0.089204   \n",
      "1142  0.259740  0.040816  0.061224  0.148423  0.100186  0.270872   0.060976   \n",
      "1143  0.097289  0.078682  0.076555  0.170122  0.147794  0.326954   0.143161   \n",
      "1144  0.337775  0.066622  0.066622  0.108594  0.182545  0.140573   0.227160   \n",
      "1145  0.150485  0.059223  0.079612  0.205825  0.137864  0.258252   0.193916   \n",
      "1146  0.107500  0.047500  0.075000  0.145000  0.157500  0.275000   0.089965   \n",
      "1147  0.154375  0.062500  0.076250  0.133750  0.108750  0.300625   0.124245   \n",
      "1148  0.137791  0.069767  0.113372  0.170349  0.169767  0.263372   0.166284   \n",
      "1149  0.137431  0.091954  0.085457  0.148426  0.132434  0.284858   0.155853   \n",
      "1150  0.174830  0.057037  0.065096  0.127712  0.116863  0.277743   0.217854   \n",
      "1151  0.109312  0.073887  0.084514  0.205972  0.150304  0.313765   0.449572   \n",
      "1152  0.260892  0.070220  0.083547  0.100974  0.150692  0.263455   0.064560   \n",
      "1153  0.107341  0.076870  0.090028  0.160665  0.158587  0.296399   0.057592   \n",
      "1154  0.274648  0.056338  0.070423  0.225352  0.103286  0.194836   0.033639   \n",
      "1155  0.094821  0.082072  0.084064  0.188048  0.167729  0.309163   0.101091   \n",
      "1156  0.197138  0.072337  0.076312  0.115262  0.125596  0.287758   0.019272   \n",
      "1157  0.213855  0.129518  0.120482  0.141566  0.197289  0.155120   0.024074   \n",
      "1158  0.060096  0.096154  0.115385  0.150240  0.169471  0.318510   0.027027   \n",
      "1159  0.090987  0.068670  0.083262  0.177682  0.169957  0.300429   0.048349   \n",
      "1160  0.324786  0.096154  0.072650  0.106838  0.183761  0.168803   0.236842   \n",
      "1161  0.137555  0.111354  0.096070  0.198690  0.159389  0.251092   0.048232   \n",
      "1162  0.239562  0.062286  0.089322  0.139973  0.126968  0.239904   0.062383   \n",
      "1163  0.130272  0.065779  0.082954  0.165440  0.170347  0.284262   0.028498   \n",
      "1164  0.173819  0.075682  0.077512  0.151364  0.152029  0.272788   0.070549   \n",
      "1165  0.182026  0.062965  0.081855  0.171151  0.180882  0.250716   0.049373   \n",
      "1166  0.205655  0.066025  0.072876  0.116310  0.172424  0.238012   0.029957   \n",
      "1167  0.187123  0.052711  0.080949  0.173946  0.149849  0.245482   0.021148   \n",
      "1168  0.127995  0.099114  0.087299  0.162619  0.159173  0.272727   0.056116   \n",
      "1169  0.240233  0.063763  0.072744  0.108666  0.178716  0.220251   0.017019   \n",
      "1170  0.237634  0.087901  0.088904  0.159759  0.186497  0.198864   0.011311   \n",
      "1171  0.167479  0.048730  0.075917  0.161067  0.190305  0.297256   0.024777   \n",
      "1172  0.214867  0.085114  0.081521  0.133346  0.145451  0.238699   0.016583   \n",
      "1173  0.163741  0.061437  0.072682  0.112452  0.156061  0.326385   0.011244   \n",
      "1174  0.101858  0.082559  0.107577  0.233738  0.246605  0.190136   0.008482   \n",
      "1175  0.077183  0.074475  0.117806  0.241706  0.194990  0.238998   0.013912   \n",
      "1176  0.070978  0.064669  0.076498  0.148265  0.193218  0.345426   0.029189   \n",
      "1177  0.142461  0.048104  0.050879  0.175763  0.223867  0.226642   0.015258   \n",
      "1178  0.127047  0.077655  0.098257  0.190703  0.255415  0.206022   0.014027   \n",
      "1179  0.279801  0.063742  0.063190  0.152318  0.139625  0.180740   0.041545   \n",
      "1180  0.203187  0.060646  0.053121  0.144754  0.142098  0.283754   0.070348   \n",
      "1181  0.088636  0.080682  0.089773  0.196591  0.435227  0.093182   0.016993   \n",
      "1182  0.032730  0.059889  0.110724  0.322423  0.199861  0.243036   0.054886   \n",
      "1183  0.138962  0.065084  0.089710  0.145119  0.166227  0.275286   0.044118   \n",
      "1184  0.182635  0.097305  0.073353  0.233533  0.091317  0.185629   0.217228   \n",
      "1185  0.108456  0.062500  0.060662  0.091912  0.143382  0.284926   0.073864   \n",
      "1186  0.161595  0.054565  0.054565  0.123820  0.108080  0.334732   0.098431   \n",
      "1187  0.093939  0.098485  0.109091  0.153788  0.300000  0.162121   0.015810   \n",
      "1188  0.122264  0.067925  0.092075  0.132075  0.166038  0.284528   0.055894   \n",
      "1189  0.097442  0.075571  0.113454  0.231010  0.198399  0.246632   0.028634   \n",
      "1190  0.157706  0.066722  0.074442  0.131789  0.190791  0.260822   0.035817   \n",
      "1191  0.048093  0.039801  0.041459  0.131012  0.192371  0.424544   0.068182   \n",
      "1192  0.146072  0.069639  0.059873  0.156263  0.150743  0.293418   0.042601   \n",
      "1193  0.231074  0.054923  0.054429  0.126670  0.146957  0.287481   0.040668   \n",
      "1194  0.128405  0.085603  0.058366  0.151751  0.151751  0.330739   0.021858   \n",
      "1195  0.129380  0.137466  0.064690  0.140162  0.180593  0.258760   0.007463   \n",
      "1196  0.131118  0.063185  0.062820  0.169467  0.154127  0.317020   0.058621   \n",
      "1197  0.149033  0.062571  0.079636  0.146189  0.168942  0.309443   0.012528   \n",
      "1198  0.250314  0.041509  0.074214  0.093082  0.115723  0.237736   0.017301   \n",
      "1199  0.067239  0.086552  0.086552  0.164521  0.155937  0.306867   0.014300   \n",
      "1200  0.215490  0.063804  0.082263  0.143258  0.116372  0.281701   0.167967   \n",
      "1201  0.248144  0.063738  0.068688  0.146040  0.112005  0.189975   0.036334   \n",
      "1202  0.172199  0.074689  0.100968  0.147303  0.139696  0.265560   0.020091   \n",
      "1203  0.099693  0.058282  0.050613  0.121166  0.124233  0.342025   0.008639   \n",
      "1204  0.115847  0.073770  0.095628  0.125137  0.144809  0.338798   0.023256   \n",
      "1205  0.251852  0.056019  0.077778  0.105093  0.142593  0.246759   0.031915   \n",
      "1206  0.136062  0.075774  0.097898  0.153208  0.151549  0.299226   0.018045   \n",
      "1207  0.297578  0.093426  0.072664  0.145329  0.134948  0.114187   0.013889   \n",
      "1208  0.144781  0.080808  0.074074  0.188552  0.185185  0.259259   0.004739   \n",
      "1209  0.048387  0.080645  0.094086  0.293011  0.190860  0.201613   0.021818   \n",
      "1210  0.195402  0.076403  0.055443  0.164300  0.113590  0.253550   0.175258   \n",
      "1211  0.244726  0.080169  0.143460  0.147679  0.151899  0.147679   0.025773   \n",
      "1212  0.084160  0.071844  0.073212  0.130003  0.157715  0.348614   0.035112   \n",
      "1213  0.110586  0.049149  0.073724  0.181474  0.118147  0.296786   0.033967   \n",
      "1214  0.130116  0.090047  0.078414  0.124946  0.154675  0.248600   0.096042   \n",
      "1215  0.096498  0.072374  0.093774  0.159144  0.175486  0.322179   0.025974   \n",
      "1216  0.064414  0.100317  0.077086  0.133052  0.173178  0.321014   0.010116   \n",
      "1217  0.141169  0.057124  0.087328  0.142482  0.116218  0.292186   0.010999   \n",
      "1218  0.152160  0.050094  0.082029  0.149656  0.143394  0.234189   0.009700   \n",
      "1219  0.140962  0.053068  0.081260  0.127695  0.139303  0.313433   0.073171   \n",
      "1220  0.062751  0.111022  0.086082  0.156879  0.154465  0.318584   0.010169   \n",
      "1221  0.112543  0.059278  0.053265  0.146048  0.136598  0.307560   0.079327   \n",
      "1222  0.071730  0.059072  0.113924  0.126582  0.126582  0.362869   0.017143   \n",
      "1223  0.075410  0.045902  0.085246  0.163934  0.259016  0.144262   0.019324   \n",
      "1224  0.117647  0.000000  0.058824  0.000000  0.529412  0.176471   0.000000   \n",
      "1225  0.212500  0.075000  0.112500  0.087500  0.125000  0.287500   0.132075   \n",
      "1226  0.176080  0.073090  0.106312  0.229236  0.142857  0.176080   0.213333   \n",
      "1227  0.115165  0.066135  0.084949  0.166477  0.191562  0.297035   0.020202   \n",
      "1228  0.146504  0.060367  0.077547  0.144118  0.160821  0.326891   0.250808   \n",
      "1229  0.134014  0.079973  0.099046  0.156098  0.171993  0.299314   0.197639   \n",
      "1230  0.236923  0.088205  0.082051  0.208718  0.122564  0.182821   0.266145   \n",
      "1231  0.225534  0.074223  0.092134  0.187849  0.144290  0.177533   0.215502   \n",
      "1232  0.185491  0.093982  0.117065  0.155812  0.134378  0.220940   0.047138   \n",
      "1233  0.182482  0.051095  0.051095  0.087591  0.106569  0.216058   0.061024   \n",
      "1234  0.296433  0.071341  0.056581  0.164822  0.121771  0.167282   0.020000   \n",
      "1235  0.077844  0.092814  0.107784  0.305389  0.254491  0.134731   0.009901   \n",
      "1236  0.167883  0.053528  0.068127  0.145985  0.092457  0.272506   0.114187   \n",
      "1237  0.090584  0.073302  0.095948  0.240167  0.413588  0.069726   0.005158   \n",
      "1238  0.101879  0.059347  0.100890  0.149357  0.145401  0.315529   0.049738   \n",
      "1239  0.293630  0.079843  0.060209  0.098604  0.126963  0.203752   0.173511   \n",
      "1240  0.158557  0.057162  0.093909  0.140524  0.127254  0.343995   0.251404   \n",
      "1241  0.064175  0.102257  0.155853  0.257405  0.206629  0.177010   0.003195   \n",
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      "1244  0.313208  0.045283  0.049057  0.181132  0.090566  0.215094   0.000000   \n",
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      "1290  0.192588  0.076923  0.076923  0.213925  0.129141  0.193711   0.041229   \n",
      "1291  0.198098  0.071315  0.072900  0.136292  0.141046  0.217116   0.086168   \n",
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      "1294  0.171498  0.072464  0.082126  0.210145  0.161836  0.166667   0.017857   \n",
      "1295  0.290925  0.039016  0.043257  0.099237  0.100085  0.273113   0.340206   \n",
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      "1298  0.101675  0.086394  0.100793  0.202468  0.225096  0.224214   0.038838   \n",
      "1299  0.152996  0.062245  0.070971  0.127400  0.356021  0.177429   0.005453   \n",
      "1300  0.072351  0.048234  0.062877  0.152455  0.166236  0.401378   0.030380   \n",
      "1301  0.070640  0.050773  0.105960  0.194260  0.284768  0.205298   0.025496   \n",
      "1302  0.138026  0.060329  0.073126  0.128885  0.148080  0.303473   0.091245   \n",
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      "1305  0.236760  0.082777  0.102359  0.182911  0.172230  0.173565   0.038209   \n",
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      "1307  0.250000  0.120968  0.102151  0.203405  0.162186  0.114695   0.076004   \n",
      "1308  0.275968  0.098046  0.082962  0.145698  0.135756  0.154611   0.123508   \n",
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      "1377  0.062176  0.108808  0.119171  0.269430  0.284974  0.139896   0.000000   \n",
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      "1387  0.117349  0.088817  0.099402  0.176254  0.171192  0.262310   0.200128   \n",
      "1388  0.212404  0.065421  0.076466  0.116822  0.141461  0.248513   0.135026   \n",
      "1389  0.214163  0.099372  0.104512  0.190177  0.113649  0.220445   0.145985   \n",
      "1390  0.158648  0.062419  0.056784  0.141309  0.158214  0.258344   0.198020   \n",
      "1391  0.263211  0.060976  0.069106  0.114837  0.133130  0.178862   0.031474   \n",
      "1392  0.168449  0.066845  0.088235  0.157754  0.189840  0.205882   0.006289   \n",
      "1393  0.277483  0.082361  0.066808  0.112407  0.221987  0.175680   0.091978   \n",
      "1394  0.163910  0.065417  0.070195  0.129732  0.168688  0.294377   0.076728   \n",
      "1395  0.228429  0.114631  0.090871  0.238016  0.158816  0.119216   0.024896   \n",
      "1396  0.391304  0.082459  0.073463  0.116942  0.103448  0.136432   0.005976   \n",
      "1397  0.158095  0.062857  0.163810  0.198095  0.120000  0.150476   0.080940   \n",
      "1398  0.065839  0.057474  0.090124  0.193470  0.269023  0.246897   0.045305   \n",
      "1399  0.176791  0.075805  0.075026  0.145379  0.149533  0.259346   0.105009   \n",
      "1400  0.159091  0.080492  0.116477  0.125947  0.214015  0.231061   0.000000   \n",
      "1401  0.089363  0.074289  0.104005  0.208010  0.289190  0.203058   0.031998   \n",
      "1402  0.077744  0.067073  0.107851  0.180640  0.170351  0.310976   0.067156   \n",
      "1403  0.107034  0.065910  0.074633  0.325395  0.215453  0.192329   0.028394   \n",
      "1404  0.178442  0.051630  0.087862  0.172101  0.146739  0.207428   0.034401   \n",
      "1405  0.157837  0.088852  0.088852  0.145143  0.247792  0.206954   0.025384   \n",
      "1406  0.215496  0.145278  0.062954  0.181598  0.116223  0.184019   0.066007   \n",
      "1407  0.115607  0.055326  0.075145  0.135425  0.132122  0.298927   0.064302   \n",
      "1408  0.163126  0.061457  0.094841  0.129742  0.160850  0.295903   0.100099   \n",
      "1409  0.242475  0.067845  0.078118  0.115624  0.127329  0.274486   0.037845   \n",
      "1410  0.096406  0.094333  0.115757  0.167243  0.163442  0.303386   0.028289   \n",
      "1411  0.146805  0.065686  0.061737  0.120962  0.181622  0.300790   0.037709   \n",
      "1412  0.260791  0.072240  0.059973  0.147660  0.147206  0.193094   0.088705   \n",
      "1413  0.178069  0.027179  0.059044  0.142455  0.253983  0.268041   0.041469   \n",
      "1414  0.168639  0.054734  0.050296  0.096154  0.094675  0.186391   0.012500   \n",
      "1415  0.225728  0.060680  0.070388  0.131068  0.114078  0.186893   0.075163   \n",
      "1416  0.091521  0.065949  0.080754  0.125168  0.135935  0.329744   0.078292   \n",
      "1417  0.241997  0.058899  0.080666  0.148528  0.111396  0.233035   0.033389   \n",
      "1418  0.206448  0.072964  0.071267  0.135181  0.141403  0.257919   0.080147   \n",
      "1419  0.143274  0.055016  0.076011  0.136081  0.145412  0.305210   0.070668   \n",
      "1420  0.316364  0.047273  0.076364  0.101818  0.083636  0.229091   0.038095   \n",
      "1421  0.120000  0.088302  0.086792  0.174340  0.186415  0.292075   0.007859   \n",
      "1422  0.159376  0.089127  0.113451  0.131240  0.157016  0.317299   0.022315   \n",
      "1423  0.090939  0.049218  0.071382  0.183833  0.171773  0.380052   0.065253   \n",
      "1424  0.190877  0.063335  0.068855  0.176641  0.196107  0.245206   0.019668   \n",
      "1425  0.104366  0.060703  0.082002  0.194888  0.192758  0.277955   0.019006   \n",
      "1426  0.062704  0.081516  0.115049  0.193839  0.205834  0.315703   0.022320   \n",
      "1427  0.131285  0.067039  0.072626  0.145251  0.173184  0.343575   0.137546   \n",
      "1428  0.228916  0.135972  0.098107  0.177281  0.129088  0.142857   0.020455   \n",
      "1429  0.181139  0.080943  0.086444  0.168566  0.188605  0.203536   0.040119   \n",
      "1430  0.106267  0.073025  0.108447  0.183651  0.156948  0.291008   0.042367   \n",
      "1431  0.099707  0.131965  0.118768  0.252199  0.127566  0.212610   0.082000   \n",
      "1432  0.239281  0.055325  0.084371  0.154910  0.123098  0.215768   0.066798   \n",
      "1433  0.194837  0.077440  0.074611  0.137553  0.146040  0.255304   0.028069   \n",
      "1434  0.186202  0.077522  0.079377  0.163947  0.156899  0.252596   0.025896   \n",
      "1435  0.138080  0.085221  0.074434  0.138080  0.144552  0.251348   0.071756   \n",
      "1436  0.247824  0.079155  0.025694  0.082884  0.161210  0.148777   0.002572   \n",
      "1437  0.163229  0.057848  0.080717  0.131390  0.177130  0.288789   0.008289   \n",
      "1438  0.241379  0.040044  0.057842  0.142380  0.107898  0.221357   0.084227   \n",
      "1439  0.117558  0.093444  0.099472  0.193670  0.185381  0.262246   0.054237   \n",
      "1440  0.158541  0.058866  0.064283  0.162875  0.165764  0.316360   0.024932   \n",
      "1441  0.120928  0.080066  0.099945  0.177802  0.130867  0.294313   0.048000   \n",
      "1442  0.156921  0.090095  0.087709  0.145585  0.153341  0.245823   0.045230   \n",
      "1443  0.129794  0.065036  0.066148  0.120345  0.148694  0.299889   0.127013   \n",
      "1444  0.167832  0.052632  0.083180  0.111888  0.150534  0.286713   0.078103   \n",
      "1445  0.128058  0.074820  0.083933  0.169305  0.141966  0.252278   0.151535   \n",
      "1446  0.066975  0.062356  0.062356  0.187067  0.224018  0.337182   0.034221   \n",
      "1447  0.118388  0.062972  0.088161  0.246851  0.176322  0.241814   0.003448   \n",
      "1448  0.138889  0.068841  0.065217  0.120773  0.134058  0.311594   0.008278   \n",
      "1449  0.097859  0.061162  0.088685  0.113150  0.146789  0.370031   0.014218   \n",
      "1450  0.198830  0.077973  0.066277  0.161793  0.120858  0.206628   0.036212   \n",
      "1451  0.133668  0.074642  0.083954  0.141261  0.144842  0.311748   0.152595   \n",
      "1452  0.098826  0.094912  0.107632  0.248532  0.165362  0.240705   0.103139   \n",
      "1453  0.131148  0.076503  0.092896  0.136612  0.114754  0.218579   0.136000   \n",
      "1454  0.108534  0.095547  0.084416  0.213358  0.207792  0.214750   0.016451   \n",
      "1455  0.105603  0.066810  0.086207  0.090517  0.239224  0.265086   0.014749   \n",
      "1456  0.121017  0.078149  0.103187  0.184370  0.187405  0.214719   0.005658   \n",
      "1457  0.142605  0.094284  0.094873  0.176783  0.206246  0.183265   0.010453   \n",
      "1458  0.127640  0.067952  0.051423  0.126722  0.342516  0.255280   0.005794   \n",
      "1459  0.262735  0.077748  0.115282  0.144772  0.058981  0.187668   0.032491   \n",
      "1460  0.236015  0.058071  0.072456  0.167288  0.159297  0.192328   0.060714   \n",
      "1461  0.104059  0.056149  0.079341  0.129997  0.154104  0.388465   0.059438   \n",
      "1462  0.180180  0.064189  0.073198  0.127252  0.125000  0.281532   0.032000   \n",
      "1463  0.077604  0.064670  0.083730  0.175630  0.222600  0.288632   0.194394   \n",
      "1464  0.150820  0.062705  0.069672  0.149590  0.147131  0.245492   0.191789   \n",
      "1465  0.215438  0.140553  0.093318  0.201613  0.120968  0.175115   0.137763   \n",
      "1466  0.107459  0.066100  0.092319  0.138848  0.173929  0.314993   0.131552   \n",
      "1467  0.100746  0.074966  0.093962  0.150950  0.162483  0.294776   0.082314   \n",
      "1468  0.132140  0.060564  0.086029  0.175499  0.271851  0.241569   0.009926   \n",
      "1469  0.223499  0.048531  0.060026  0.149425  0.181354  0.268199   0.012251   \n",
      "1470  0.262172  0.051186  0.068664  0.157928  0.149813  0.226592   0.039669   \n",
      "1471  0.287758  0.040276  0.048755  0.116587  0.094330  0.259671   0.035076   \n",
      "1472  0.271676  0.046012  0.055491  0.104971  0.266358  0.214798   0.006104   \n",
      "1473  0.172727  0.095455  0.082955  0.160227  0.345455  0.127273   0.006711   \n",
      "1474  0.123206  0.069378  0.068182  0.155502  0.461722  0.112440   0.002469   \n",
      "1475  0.150968  0.190968  0.166452  0.246452  0.161290  0.067097   0.000000   \n",
      "1476  0.021739  0.102355  0.240942  0.240036  0.308877  0.086051   0.002132   \n",
      "1477  0.052743  0.130802  0.122363  0.137131  0.417722  0.128692   0.002278   \n",
      "1478  0.081794  0.113456  0.097625  0.182058  0.290237  0.208443   0.000000   \n",
      "1479  0.120482  0.083411  0.084337  0.133457  0.151993  0.251158   0.016435   \n",
      "1480  0.110012  0.092996  0.106846  0.166601  0.222002  0.218441   0.032626   \n",
      "1481  0.158590  0.033040  0.079295  0.149780  0.187225  0.273128   0.003195   \n",
      "1482  0.219378  0.058501  0.062157  0.217550  0.107861  0.206581   0.120907   \n",
      "1483  0.141401  0.089172  0.101911  0.174522  0.159236  0.230573   0.024390   \n",
      "1484  0.057648  0.045734  0.072636  0.139508  0.188317  0.365872   0.019108   \n",
      "1485  0.148148  0.059568  0.068210  0.109259  0.135802  0.283025   0.045551   \n",
      "1486  0.185985  0.067966  0.106428  0.139094  0.182297  0.272919   0.013942   \n",
      "1487  0.142539  0.142539  0.086860  0.151448  0.227171  0.191537   0.096685   \n",
      "1488  0.243968  0.050938  0.091153  0.123324  0.104558  0.313673   0.051613   \n",
      "1489  0.153025  0.093416  0.104093  0.201068  0.182384  0.180605   0.012941   \n",
      "1490  0.181535  0.056769  0.087960  0.169682  0.160948  0.274485   0.056350   \n",
      "1491  0.144135  0.133201  0.115308  0.260437  0.129225  0.130219   0.203922   \n",
      "1492  0.200000  0.000000  0.072727  0.236364  0.145455  0.127273   0.022727   \n",
      "1493  0.209125  0.060837  0.098859  0.250951  0.117871  0.087452   0.105932   \n",
      "1494  0.168011  0.064516  0.087366  0.202957  0.192204  0.235215   0.027322   \n",
      "1495  0.115302  0.062500  0.068966  0.184267  0.195043  0.304957   0.037915   \n",
      "1496  0.050000  0.075000  0.025000  0.125000  0.275000  0.125000   0.000000   \n",
      "1497  0.141946  0.095694  0.092504  0.156300  0.231260  0.223285   0.011765   \n",
      "1498  0.137405  0.059542  0.121374  0.194656  0.209160  0.251145   0.034415   \n",
      "1499  0.215531  0.069731  0.095880  0.120444  0.154120  0.243661   0.025994   \n",
      "1500  0.142762  0.058039  0.090727  0.157438  0.169446  0.250167   0.045658   \n",
      "1501  0.155369  0.063214  0.055598  0.153846  0.156893  0.349581   0.054601   \n",
      "1502  0.273163  0.085463  0.064696  0.124601  0.202875  0.174121   0.028249   \n",
      "1503  0.071174  0.059075  0.088968  0.193594  0.224911  0.287544   0.069098   \n",
      "1504  0.104640  0.064166  0.066140  0.171767  0.202369  0.299112   0.030788   \n",
      "1505  0.215094  0.083019  0.105660  0.203774  0.098113  0.218868   0.134146   \n",
      "1506  0.180328  0.098361  0.100000  0.142623  0.167213  0.196721   0.057203   \n",
      "1507  0.109649  0.070175  0.093202  0.185307  0.165570  0.294956   0.027419   \n",
      "1508  0.095528  0.071646  0.104646  0.148936  0.189318  0.321320   0.126752   \n",
      "1509  0.139474  0.057895  0.107895  0.150000  0.235526  0.214474   0.010017   \n",
      "1510  0.192950  0.055659  0.064935  0.126160  0.150278  0.261596   0.089655   \n",
      "1511  0.144958  0.063025  0.111345  0.189076  0.155462  0.271008   0.052356   \n",
      "1512  0.212841  0.065963  0.091469  0.133685  0.128408  0.249780   0.036861   \n",
      "1513  0.208092  0.069364  0.054913  0.153179  0.170520  0.254335   0.003717   \n",
      "1514  0.038540  0.066937  0.089249  0.202840  0.290061  0.261663   0.073171   \n",
      "1515  0.151376  0.057339  0.077982  0.158257  0.144495  0.330275   0.054313   \n",
      "1516  0.189274  0.059937  0.082019  0.167192  0.222397  0.239748   0.017391   \n",
      "1517  0.206107  0.081425  0.089059  0.198473  0.170483  0.178117   0.042105   \n",
      "1518  0.064649  0.043722  0.069133  0.204783  0.177877  0.364350   0.031866   \n",
      "1519  0.142154  0.069437  0.091307  0.145981  0.194642  0.266266   0.006173   \n",
      "1520  0.188637  0.090329  0.077242  0.155123  0.134376  0.266199   0.051184   \n",
      "1521  0.076503  0.057377  0.139344  0.139344  0.204918  0.270492   0.011070   \n",
      "1522  0.369289  0.069797  0.062183  0.078680  0.163706  0.152284   0.025773   \n",
      "1523  0.209871  0.057082  0.086695  0.145064  0.200858  0.260086   0.096826   \n",
      "1524  0.160731  0.122233  0.129933  0.212063  0.198268  0.151107   0.004274   \n",
      "1525  0.067086  0.067086  0.102725  0.249476  0.257862  0.220126   0.014970   \n",
      "1526  0.208768  0.040710  0.070981  0.115866  0.146138  0.311065   0.146053   \n",
      "1527  0.315296  0.068543  0.049784  0.069264  0.231602  0.185426   0.039894   \n",
      "1528  0.240460  0.091460  0.082374  0.151423  0.105996  0.219867   0.048133   \n",
      "1529  0.090473  0.058259  0.119602  0.178547  0.174435  0.286498   0.053889   \n",
      "1530  0.066667  0.096154  0.117949  0.187179  0.201282  0.253846   0.066667   \n",
      "1531  0.290616  0.070690  0.078958  0.133113  0.138074  0.191815   0.075978   \n",
      "1532  0.149299  0.064799  0.080998  0.161559  0.146235  0.278897   0.098848   \n",
      "1533  0.098901  0.069780  0.102198  0.184066  0.135714  0.309890   0.182487   \n",
      "1534  0.136121  0.086574  0.089238  0.209643  0.165157  0.225626   0.084870   \n",
      "1535  0.195835  0.080497  0.110533  0.158991  0.132159  0.221866   0.077297   \n",
      "1536  0.149676  0.069579  0.066343  0.300162  0.163430  0.163430   0.265514   \n",
      "1537  0.089260  0.075418  0.090215  0.206683  0.168019  0.266826   0.099451   \n",
      "1538  0.083107  0.063836  0.109606  0.207769  0.158988  0.292683   0.180522   \n",
      "1539  0.182206  0.056228  0.086121  0.153025  0.110320  0.261922   0.068160   \n",
      "1540  0.182045  0.104738  0.107232  0.271820  0.115960  0.153367   0.032986   \n",
      "1541  0.173328  0.071231  0.083894  0.146419  0.129007  0.270281   0.059200   \n",
      "1542  0.170898  0.074675  0.088543  0.132494  0.196714  0.233838   0.117965   \n",
      "1543  0.119482  0.059981  0.086852  0.157390  0.138676  0.299424   0.061170   \n",
      "1544  0.081050  0.064609  0.102682  0.215172  0.185751  0.291607   0.329104   \n",
      "1545  0.193182  0.104545  0.084091  0.240909  0.181818  0.163636   0.138983   \n",
      "1546  0.126027  0.079452  0.059178  0.188493  0.159452  0.293151   0.044261   \n",
      "1547  0.148392  0.085626  0.103061  0.168927  0.145680  0.240992   0.076417   \n",
      "1548  0.128262  0.064964  0.081066  0.153248  0.130483  0.334259   0.064263   \n",
      "1549  0.231890  0.071260  0.081890  0.156693  0.131890  0.190551   0.154091   \n",
      "1550  0.152093  0.075782  0.080551  0.163222  0.127186  0.240594   0.140275   \n",
      "1551  0.259670  0.067813  0.069962  0.141117  0.138252  0.244031   0.162783   \n",
      "1552  0.068547  0.073247  0.104583  0.204465  0.168821  0.327458   0.361500   \n",
      "1553  0.156243  0.066356  0.095824  0.144371  0.180199  0.276023   0.022715   \n",
      "1554  0.181448  0.100917  0.095821  0.203874  0.189602  0.186544   0.081967   \n",
      "1555  0.098348  0.071597  0.084186  0.148702  0.111723  0.330448   0.032427   \n",
      "1556  0.061988  0.066667  0.086550  0.195322  0.157895  0.354386   0.090722   \n",
      "1557  0.148543  0.068386  0.104821  0.156951  0.185538  0.235987   0.079259   \n",
      "1558  0.335113  0.046729  0.089453  0.120160  0.101469  0.154873   0.125693   \n",
      "1559  0.140906  0.060166  0.109613  0.169260  0.174965  0.267116   0.072689   \n",
      "1560  0.113333  0.090000  0.116667  0.190000  0.176667  0.250000   0.077720   \n",
      "1561  0.117386  0.078627  0.087486  0.160576  0.189369  0.293466   0.049342   \n",
      "1562  0.115962  0.075096  0.088020  0.162417  0.136221  0.345093   0.256092   \n",
      "1563  0.143554  0.087150  0.091391  0.138465  0.144614  0.278202   0.071971   \n",
      "1564  0.273692  0.094769  0.075057  0.127369  0.106141  0.214556   0.109589   \n",
      "1565  0.181818  0.060945  0.054342  0.143220  0.142712  0.301168   0.052743   \n",
      "1566  0.133835  0.055038  0.074887  0.121504  0.169323  0.347068   0.038414   \n",
      "1567  0.246445  0.068720  0.096367  0.152449  0.118483  0.223539   0.176211   \n",
      "1568  0.081800  0.047035  0.073620  0.194274  0.128834  0.370143   0.223140   \n",
      "1569  0.173793  0.088276  0.077241  0.195862  0.150345  0.249655   0.353571   \n",
      "1570  0.208270  0.070444  0.076570  0.199081  0.117917  0.197550   0.130621   \n",
      "1571  0.133906  0.084451  0.105197  0.156748  0.138935  0.286044   0.138009   \n",
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      "1573  0.238920  0.070508  0.070911  0.154311  0.112812  0.245770   0.119114   \n",
      "1574  0.276821  0.072659  0.071806  0.133038  0.145659  0.208255   0.098328   \n",
      "1575  0.110588  0.085588  0.084118  0.141765  0.137059  0.310882   0.096252   \n",
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      "1577  0.344363  0.077206  0.061275  0.134804  0.094363  0.125000   0.066869   \n",
      "1578  0.382022  0.048008  0.077630  0.123596  0.077630  0.138917   0.032995   \n",
      "1579  0.019231  0.096154  0.038462  0.288462  0.346154  0.192308   0.000000   \n",
      "1580  0.208188  0.069979  0.068579  0.168999  0.144857  0.229531   0.193906   \n",
      "1581  0.204794  0.063917  0.075167  0.136638  0.167129  0.248166   0.050883   \n",
      "1582  0.116613  0.071014  0.079291  0.146094  0.146820  0.299739   0.038948   \n",
      "1583  0.090373  0.064833  0.080550  0.200393  0.198428  0.277014   0.088083   \n",
      "1584  0.223226  0.077419  0.103226  0.134194  0.122581  0.225806   0.018215   \n",
      "1585  0.168973  0.067925  0.072956  0.141300  0.128302  0.233124   0.059625   \n",
      "1586  0.203972  0.087089  0.084034  0.180290  0.196333  0.173415   0.102968   \n",
      "1587  0.176136  0.091721  0.073052  0.121753  0.134740  0.252435   0.167956   \n",
      "1588  0.169416  0.070431  0.085660  0.173223  0.168147  0.287437   0.101498   \n",
      "1589  0.107652  0.063554  0.063554  0.163424  0.168612  0.272374   0.029685   \n",
      "1590  0.231509  0.070266  0.068047  0.114645  0.149408  0.257396   0.035052   \n",
      "1591  0.161491  0.091097  0.106108  0.171843  0.155797  0.240683   0.163366   \n",
      "1592  0.199930  0.071554  0.082076  0.136093  0.127324  0.258857   0.129764   \n",
      "1593  0.115503  0.052487  0.086020  0.175279  0.156164  0.350397   0.337309   \n",
      "1594  0.156288  0.069866  0.082928  0.154465  0.138821  0.302704   0.197433   \n",
      "1595  0.144933  0.075335  0.069216  0.126195  0.158317  0.278776   0.138889   \n",
      "1596  0.156595  0.063584  0.078297  0.214398  0.160799  0.267472   0.186546   \n",
      "1597  0.131604  0.078772  0.084875  0.171467  0.150868  0.321572   0.208712   \n",
      "1598  0.094578  0.057219  0.083701  0.157314  0.155107  0.389660   0.346902   \n",
      "1599  0.190229  0.073065  0.060527  0.130134  0.147428  0.272806   0.169389   \n",
      "1600  0.120592  0.067691  0.097270  0.135381  0.132537  0.277019   0.154887   \n",
      "1601  0.109748  0.091672  0.082634  0.608780  0.045190  0.043899   0.716955   \n",
      "1602  0.172388  0.057630  0.078426  0.150088  0.144575  0.313205   0.038131   \n",
      "1603  0.249347  0.074752  0.072661  0.142185  0.151594  0.206482   0.218881   \n",
      "1604  0.096122  0.053696  0.079881  0.123964  0.156447  0.329466   0.213291   \n",
      "1605  0.114130  0.097826  0.059783  0.255435  0.228261  0.217391   0.049587   \n",
      "1606  0.290470  0.071591  0.083903  0.141815  0.156407  0.176015   0.095764   \n",
      "1607  0.124970  0.096205  0.099347  0.319555  0.129079  0.195794   0.398082   \n",
      "1608  0.155634  0.065845  0.093310  0.133451  0.143662  0.318662   0.034263   \n",
      "1609  0.087409  0.098855  0.093652  0.159209  0.148803  0.276795   0.019915   \n",
      "1610  0.253738  0.101869  0.078505  0.131308  0.120093  0.232243   0.097875   \n",
      "1611  0.159412  0.069097  0.103373  0.158868  0.145267  0.262242   0.039688   \n",
      "1612  0.144790  0.087957  0.116373  0.178620  0.182679  0.239513   0.017308   \n",
      "1613  0.113157  0.063641  0.086812  0.166323  0.189811  0.308840   0.072704   \n",
      "1614  0.162349  0.096718  0.112263  0.164076  0.179620  0.208981   0.064677   \n",
      "1615  0.093863  0.108303  0.129964  0.252708  0.137184  0.184116   0.106481   \n",
      "1616  0.126560  0.051693  0.099822  0.187166  0.177362  0.263815   0.057243   \n",
      "1617  0.174312  0.075229  0.084404  0.148624  0.113761  0.266055   0.040094   \n",
      "1618  0.161666  0.080220  0.090631  0.137171  0.138396  0.259645   0.087404   \n",
      "1619  0.280432  0.040299  0.054425  0.104695  0.167013  0.273785   0.001058   \n",
      "1620  0.132816  0.072710  0.091129  0.161415  0.149782  0.281629   0.115163   \n",
      "1621  0.228404  0.122987  0.083455  0.152269  0.134700  0.204978   0.013540   \n",
      "1622  0.269375  0.076818  0.072721  0.146466  0.131103  0.179925   0.108341   \n",
      "1623  0.092510  0.064389  0.082260  0.143758  0.364258  0.189488   0.045221   \n",
      "1624  0.088825  0.091691  0.048711  0.229226  0.209169  0.283668   0.007782   \n",
      "1625  0.039716  0.064843  0.105572  0.228977  0.180952  0.364336   0.050316   \n",
      "1626  0.157243  0.098475  0.105464  0.181067  0.157560  0.228081   0.106067   \n",
      "1627  0.101579  0.069211  0.094474  0.136842  0.191316  0.308421   0.013378   \n",
      "1628  0.144558  0.056973  0.078231  0.238095  0.113095  0.250850   0.295583   \n",
      "1629  0.176845  0.104326  0.069975  0.170483  0.243003  0.156489   0.121951   \n",
      "1630  0.115852  0.067967  0.097509  0.145974  0.178220  0.305657   0.068876   \n",
      "1631  0.181906  0.082702  0.088721  0.123277  0.155116  0.257232   0.011713   \n",
      "1632  0.218985  0.064289  0.084380  0.133099  0.171773  0.232546   0.051701   \n",
      "1633  0.114802  0.053854  0.070622  0.184134  0.142857  0.369558   0.044949   \n",
      "1634  0.101729  0.113937  0.127162  0.203459  0.143947  0.202950   0.038114   \n",
      "1635  0.172743  0.102636  0.104319  0.142737  0.190690  0.219293   0.020301   \n",
      "1636  0.253786  0.049667  0.071472  0.149001  0.121744  0.233798   0.072800   \n",
      "1637  0.178616  0.059119  0.085535  0.129560  0.122013  0.276730   0.090301   \n",
      "1638  0.119048  0.057143  0.061905  0.242857  0.190476  0.233333   0.193548   \n",
      "1639  0.122522  0.077783  0.119471  0.139807  0.176919  0.274021   0.017520   \n",
      "1640  0.215708  0.079646  0.090708  0.128319  0.127212  0.233407   0.004644   \n",
      "1641  0.071875  0.109375  0.071875  0.100000  0.103125  0.265625   0.008000   \n",
      "1642  0.242359  0.117520  0.099440  0.119242  0.238485  0.159707   0.100244   \n",
      "1643  0.170452  0.062001  0.069777  0.118887  0.166360  0.297524   0.111383   \n",
      "1644  0.181125  0.083889  0.100095  0.095329  0.152526  0.220210   0.076531   \n",
      "1645  0.207610  0.097188  0.097188  0.175765  0.134822  0.189826   0.126214   \n",
      "1646  0.203565  0.090229  0.083407  0.119278  0.212588  0.226452   0.074236   \n",
      "1647  0.147137  0.070155  0.087979  0.127038  0.177474  0.298824   0.040773   \n",
      "1648  0.153199  0.081369  0.092873  0.280022  0.160213  0.170314   0.320495   \n",
      "1649  0.264613  0.062359  0.067318  0.106687  0.169497  0.232156   0.059269   \n",
      "1650  0.177778  0.088000  0.078222  0.169778  0.197333  0.239111   0.058893   \n",
      "1651  0.106761  0.135700  0.095817  0.174125  0.283560  0.168288   0.028746   \n",
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      "1654  0.169411  0.063300  0.089279  0.198683  0.172704  0.222466   0.061314   \n",
      "1655  0.286546  0.061736  0.073384  0.130460  0.142108  0.203844   0.003165   \n",
      "1656  0.272469  0.086093  0.089404  0.124409  0.109272  0.185904   0.095745   \n",
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      "1659  0.209552  0.045809  0.073099  0.162768  0.096491  0.240741   0.079681   \n",
      "1660  0.188009  0.070452  0.085371  0.129714  0.155684  0.278768   0.026159   \n",
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      "1667  0.128617  0.083601  0.106109  0.163987  0.099678  0.228296   0.137339   \n",
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      "1670  0.278925  0.072458  0.079470  0.121932  0.137125  0.174133   0.074899   \n",
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      "1672  0.166318  0.066984  0.084491  0.136061  0.145576  0.290771   0.012471   \n",
      "1673  0.065800  0.086109  0.101543  0.182778  0.370431  0.145410   0.005561   \n",
      "1674  0.184366  0.071534  0.069813  0.115290  0.130039  0.270895   0.130508   \n",
      "1675  0.168591  0.073903  0.102771  0.144342  0.157044  0.241339   0.020000   \n",
      "1676  0.207983  0.102941  0.063025  0.170168  0.163866  0.184874   0.101877   \n",
      "1677  0.096467  0.065217  0.063859  0.177989  0.163043  0.330163   0.028517   \n",
      "1678  0.096417  0.097068  0.100326  0.202606  0.157655  0.270358   0.074366   \n",
      "1679  0.269151  0.124224  0.091097  0.175983  0.118012  0.138716   0.036620   \n",
      "1680  0.117886  0.051684  0.067944  0.122532  0.112079  0.358885   0.020129   \n",
      "1681  0.195822  0.089295  0.072585  0.142037  0.131593  0.260052   0.018881   \n",
      "1682  0.246252  0.081353  0.091408  0.168007  0.142779  0.179890   0.104642   \n",
      "1683  0.123209  0.098567  0.109456  0.158166  0.303152  0.181662   0.013981   \n",
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      "1685  0.178776  0.071702  0.105163  0.219885  0.211281  0.170172   0.006993   \n",
      "1686  0.193086  0.059753  0.054815  0.145679  0.134321  0.225185   0.181333   \n",
      "1687  0.140281  0.045910  0.074877  0.131354  0.187101  0.340499   0.065991   \n",
      "1688  0.089506  0.064815  0.086420  0.169753  0.176698  0.348765   0.067949   \n",
      "1689  0.231232  0.075425  0.084986  0.130312  0.121813  0.237960   0.007496   \n",
      "1690  0.086157  0.078690  0.095348  0.146468  0.292361  0.244113   0.085999   \n",
      "1691  0.021277  0.021277  0.255319  0.414894  0.117021  0.031915   0.000000   \n",
      "1692  0.140164  0.088449  0.069116  0.159497  0.158531  0.256646   0.145946   \n",
      "1693  0.179159  0.048446  0.050274  0.138026  0.105119  0.246801   0.160830   \n",
      "1694  0.032000  0.056000  0.008000  0.232000  0.160000  0.312000   0.153846   \n",
      "1695  0.134795  0.072562  0.100529  0.161502  0.187453  0.313177   0.290721   \n",
      "1696  0.257229  0.124659  0.081288  0.142117  0.147572  0.187125   0.109293   \n",
      "1697  0.200121  0.081374  0.107896  0.176612  0.113321  0.235081   0.159938   \n",
      "1698  0.226921  0.080708  0.082642  0.150912  0.140962  0.209784   0.132883   \n",
      "1699  0.192043  0.060444  0.054705  0.126243  0.154552  0.303749   0.108662   \n",
      "1700  0.110559  0.089441  0.110559  0.186957  0.137888  0.262112   0.053321   \n",
      "1701  0.136364  0.071591  0.086364  0.172727  0.139773  0.259091   0.176962   \n",
      "1702  0.231075  0.072996  0.080948  0.132634  0.135019  0.228531   0.071102   \n",
      "1703  0.130627  0.087085  0.074539  0.149077  0.230996  0.233948   0.038610   \n",
      "1704  0.198058  0.074434  0.075081  0.174757  0.182524  0.242071   0.078727   \n",
      "1705  0.179415  0.051936  0.076487  0.176582  0.158640  0.203022   0.085749   \n",
      "1706  0.137405  0.098282  0.089695  0.167939  0.136450  0.242366   0.106439   \n",
      "1707  0.282618  0.097632  0.081546  0.088695  0.143878  0.251117   0.023871   \n",
      "1708  0.158854  0.080729  0.083333  0.148438  0.197266  0.248047   0.004769   \n",
      "1709  0.162010  0.070966  0.080527  0.143419  0.212047  0.293530   0.100671   \n",
      "1710  0.134715  0.089378  0.088083  0.137306  0.113990  0.304404   0.027372   \n",
      "1711  0.089244  0.065861  0.074825  0.146142  0.134451  0.314108   0.025890   \n",
      "1712  0.185913  0.108927  0.114660  0.162981  0.144963  0.231777   0.006826   \n",
      "1713  0.054726  0.092040  0.114428  0.236318  0.248756  0.228856   0.060071   \n",
      "1714  0.122801  0.065919  0.085081  0.144252  0.175343  0.311882   0.012928   \n",
      "1715  0.098492  0.081407  0.131658  0.169849  0.155779  0.285427   0.108333   \n",
      "1716  0.119479  0.085504  0.080408  0.158550  0.138732  0.306342   0.103448   \n",
      "1717  0.156262  0.056754  0.083239  0.132425  0.129020  0.276958   0.141151   \n",
      "1718  0.216329  0.062456  0.079204  0.120377  0.181438  0.242847   0.052200   \n",
      "1719  0.163366  0.066832  0.091584  0.207921  0.148515  0.165842   0.107807   \n",
      "1720  0.146145  0.060990  0.089758  0.151899  0.218642  0.232451   0.010703   \n",
      "1721  0.201238  0.068799  0.090471  0.148607  0.151015  0.245958   0.257466   \n",
      "1722  0.080724  0.049061  0.094294  0.189631  0.264788  0.283229   0.080223   \n",
      "1723  0.045936  0.063604  0.127208  0.195524  0.209658  0.300353   0.049927   \n",
      "1724  0.054495  0.061884  0.131158  0.193658  0.259852  0.260776   0.054647   \n",
      "1725  0.288094  0.075453  0.072513  0.156786  0.103381  0.202352   0.054377   \n",
      "1726  0.109157  0.057542  0.075511  0.144141  0.162875  0.359396   0.283701   \n",
      "1727  0.240094  0.071698  0.056604  0.185377  0.164387  0.237028   0.095130   \n",
      "1728  0.162109  0.061358  0.084739  0.168910  0.207879  0.284540   0.046765   \n",
      "1729  0.227579  0.122862  0.091239  0.167444  0.145153  0.174184   0.066025   \n",
      "1730  0.343493  0.075233  0.074959  0.134816  0.130972  0.158704   0.116460   \n",
      "1731  0.284919  0.081478  0.080972  0.106275  0.128036  0.162449   0.022059   \n",
      "1732  0.214516  0.088710  0.138710  0.159677  0.090323  0.156452   0.034632   \n",
      "1733  0.305857  0.091106  0.072668  0.146421  0.129067  0.143167   0.004144   \n",
      "1734  0.257697  0.079818  0.082098  0.149373  0.144812  0.185861   0.017991   \n",
      "1735  0.104383  0.079554  0.093235  0.137573  0.161895  0.316950   0.049505   \n",
      "1736  0.187868  0.092349  0.084201  0.137619  0.129018  0.229063   0.031579   \n",
      "1737  0.257086  0.092989  0.095972  0.133267  0.133267  0.207857   0.146801   \n",
      "1738  0.156945  0.099218  0.097414  0.180397  0.274805  0.149729   0.010355   \n",
      "1739  0.118908  0.058480  0.083821  0.146199  0.161793  0.276803   0.016438   \n",
      "1740  0.228469  0.066388  0.062799  0.104067  0.108852  0.172847   0.026751   \n",
      "1741  0.205479  0.095205  0.098630  0.141781  0.152740  0.187671   0.111836   \n",
      "1742  0.231172  0.063110  0.080893  0.163877  0.128312  0.244421   0.088668   \n",
      "1743  0.136352  0.075724  0.075229  0.191042  0.159119  0.295966   0.020657   \n",
      "1744  0.200678  0.071864  0.068475  0.110508  0.118644  0.301017   0.120504   \n",
      "1745  0.057605  0.050511  0.060216  0.162997  0.170431  0.422474   0.058613   \n",
      "1746  0.264407  0.095593  0.073898  0.120000  0.108475  0.210169   0.153340   \n",
      "1747  0.245614  0.087719  0.064593  0.161085  0.096491  0.157895   0.072893   \n",
      "1748  0.285917  0.065434  0.051920  0.138691  0.219772  0.212660   0.037567   \n",
      "1749  0.100000  0.017742  0.041935  0.174194  0.293548  0.300000   0.067485   \n",
      "1750  0.231278  0.043502  0.072687  0.135463  0.144824  0.234581   0.080064   \n",
      "1751  0.501305  0.065274  0.028721  0.154047  0.031332  0.101828   0.003257   \n",
      "1752  0.356725  0.076023  0.070175  0.087719  0.052632  0.140351   0.007692   \n",
      "1753  0.219409  0.042194  0.063291  0.101266  0.101266  0.219409   0.005525   \n",
      "1754  0.241187  0.064935  0.103896  0.096475  0.098330  0.267161   0.027638   \n",
      "1755  0.100074  0.092715  0.106696  0.172185  0.178808  0.260486   0.087277   \n",
      "1756  0.228448  0.059806  0.064655  0.142241  0.134159  0.278556   0.089573   \n",
      "1757  0.318059  0.079066  0.071878  0.118598  0.139263  0.144654   0.007177   \n",
      "1758  0.258904  0.047945  0.061644  0.115068  0.136986  0.247945   0.145390   \n",
      "1759  0.167953  0.085338  0.076260  0.135270  0.148434  0.277349   0.023342   \n",
      "1760  0.092966  0.070503  0.093786  0.166257  0.255288  0.287096   0.055007   \n",
      "1761  0.197967  0.072861  0.078791  0.156453  0.183282  0.243716   0.106628   \n",
      "1762  0.126761  0.085787  0.074904  0.140845  0.163892  0.326504   0.098261   \n",
      "1763  0.218333  0.055274  0.069093  0.137725  0.115154  0.233533   0.048108   \n",
      "1764  0.276958  0.078320  0.093076  0.161180  0.194098  0.141884   0.019499   \n",
      "1765  0.049169  0.079070  0.087375  0.159468  0.254485  0.283721   0.050554   \n",
      "1766  0.337955  0.067591  0.053726  0.107452  0.199307  0.180243   0.037344   \n",
      "1767  0.184783  0.079710  0.076087  0.170290  0.112319  0.289855   0.090047   \n",
      "1768  0.282710  0.044393  0.072430  0.142523  0.189252  0.205607   0.046196   \n",
      "1769  0.193370  0.077348  0.086030  0.149961  0.167324  0.247830   0.077856   \n",
      "1770  0.251167  0.090570  0.130719  0.331466  0.063492  0.070028   0.640509   \n",
      "1771  0.184242  0.076667  0.081212  0.134848  0.148485  0.281212   0.033764   \n",
      "1772  0.330724  0.064579  0.052838  0.162427  0.150685  0.185910   0.036364   \n",
      "1773  0.139378  0.071042  0.094723  0.148850  0.255751  0.244926   0.014834   \n",
      "1774  0.194872  0.087179  0.051282  0.087179  0.128205  0.328205   0.025806   \n",
      "1775  0.042035  0.099558  0.112832  0.232301  0.179204  0.276549   0.306991   \n",
      "1776  0.107826  0.063768  0.113043  0.200000  0.155942  0.245797   0.018913   \n",
      "1777  0.169713  0.070496  0.054830  0.195822  0.122715  0.237598   0.041353   \n",
      "1778  0.154286  0.065714  0.080000  0.148571  0.108571  0.314286   0.054545   \n",
      "1779  0.138728  0.046243  0.084778  0.117534  0.134875  0.238921   0.076294   \n",
      "1780  0.181818  0.040404  0.090909  0.262626  0.121212  0.156566   0.100775   \n",
      "1781  0.204289  0.069500  0.099177  0.137660  0.168868  0.261536   0.062455   \n",
      "1782  0.128093  0.074236  0.058224  0.320233  0.122271  0.227074   0.341053   \n",
      "1783  0.107107  0.052052  0.078078  0.136136  0.156156  0.284284   0.118594   \n",
      "1784  0.195965  0.054755  0.057637  0.208934  0.370317  0.100865   0.134426   \n",
      "1785  0.178588  0.062709  0.090129  0.132570  0.191702  0.280877   0.015129   \n",
      "1786  0.212470  0.079825  0.091739  0.196585  0.125099  0.223590   0.179704   \n",
      "1787  0.040855  0.066983  0.063183  0.119952  0.259620  0.214727   0.042064   \n",
      "1788  0.238653  0.061493  0.073939  0.111274  0.133968  0.235725   0.068762   \n",
      "1789  0.208378  0.037594  0.105263  0.137487  0.163265  0.290011   0.083095   \n",
      "1790  0.212854  0.057193  0.080778  0.112618  0.104953  0.206958   0.025869   \n",
      "1791  0.069136  0.081481  0.069136  0.135802  0.162963  0.219753   0.136519   \n",
      "1792  0.142104  0.060813  0.081394  0.141069  0.213776  0.300755   0.039351   \n",
      "1793  0.150350  0.061772  0.076923  0.122960  0.155012  0.314103   0.212097   \n",
      "1794  0.218206  0.057564  0.072289  0.101740  0.148594  0.278447   0.199637   \n",
      "1795  0.199531  0.086854  0.070423  0.161972  0.107981  0.211268   0.104918   \n",
      "1796  0.122324  0.198777  0.094801  0.159021  0.076453  0.223242   0.155556   \n",
      "1797  0.319355  0.055914  0.065591  0.102151  0.101075  0.205376   0.102190   \n",
      "1798  0.162825  0.072119  0.074349  0.139777  0.130112  0.251301   0.005780   \n",
      "1799  0.198413  0.070476  0.069841  0.132698  0.148254  0.270794   0.083516   \n",
      "1800  0.121012  0.068207  0.089109  0.167217  0.149615  0.279428   0.028744   \n",
      "1801  0.069027  0.064993  0.089198  0.216047  0.279695  0.246974   0.034698   \n",
      "1802  0.272528  0.077647  0.083990  0.157699  0.139764  0.187883   0.225361   \n",
      "1803  0.109396  0.096686  0.074898  0.497503  0.141171  0.065819   0.721429   \n",
      "1804  0.182226  0.085278  0.081688  0.171454  0.179533  0.236086   0.024705   \n",
      "1805  0.063466  0.038242  0.074044  0.148902  0.475183  0.152970   0.006470   \n",
      "1806  0.346621  0.083661  0.085091  0.117447  0.111012  0.112978   0.080704   \n",
      "1807  0.226985  0.076599  0.087843  0.122980  0.199578  0.196767   0.011797   \n",
      "1808  0.131603  0.066697  0.091316  0.174127  0.169203  0.259624   0.081243   \n",
      "1809  0.103406  0.081509  0.105839  0.282238  0.099757  0.211679   0.183144   \n",
      "1810  0.043447  0.039826  0.071325  0.231716  0.192252  0.354091   0.100719   \n",
      "1811  0.052632  0.046053  0.092105  0.144737  0.151316  0.263158   0.069565   \n",
      "1812  0.262826  0.101710  0.091809  0.119712  0.091809  0.197120   0.075243   \n",
      "1813  0.150763  0.078097  0.082751  0.141712  0.365658  0.144298   0.004910   \n",
      "1814  0.092403  0.071659  0.112069  0.173491  0.293103  0.188039   0.024481   \n",
      "1815  0.176434  0.071451  0.086493  0.131934  0.138828  0.277656   0.008330   \n",
      "1816  0.326829  0.108130  0.072358  0.153659  0.154472  0.119512   0.093679   \n",
      "1817  0.191549  0.092394  0.097465  0.181408  0.163944  0.193239   0.151786   \n",
      "1818  0.174394  0.052595  0.057439  0.104498  0.150173  0.314879   0.029602   \n",
      "1819  0.174304  0.081820  0.088652  0.143976  0.152308  0.262456   0.019355   \n",
      "1820  0.204839  0.071774  0.060484  0.118548  0.125000  0.259677   0.067520   \n",
      "1821  0.141291  0.087698  0.071864  0.133983  0.147381  0.236297   0.049751   \n",
      "1822  0.313814  0.070515  0.091546  0.133196  0.180619  0.167423   0.005868   \n",
      "1823  0.190164  0.085246  0.124590  0.236066  0.127869  0.200000   0.120000   \n",
      "1824  0.116828  0.099536  0.091523  0.172923  0.370730  0.136229   0.008718   \n",
      "1825  0.053131  0.104364  0.085389  0.176471  0.330171  0.197343   0.007371   \n",
      "1826  0.282759  0.099310  0.069655  0.164138  0.127586  0.181379   0.078996   \n",
      "1827  0.192043  0.070390  0.112471  0.130069  0.185922  0.222647   0.003128   \n",
      "1828  0.214323  0.068984  0.067404  0.132175  0.130068  0.237493   0.052031   \n",
      "1829  0.251012  0.141700  0.121457  0.141700  0.109312  0.186235   0.063492   \n",
      "1830  0.133744  0.067152  0.076105  0.153889  0.137101  0.321209   0.123007   \n",
      "1831  0.114341  0.083333  0.069767  0.174419  0.178295  0.248062   0.034392   \n",
      "1832  0.281548  0.098356  0.083775  0.158802  0.121951  0.173383   0.044889   \n",
      "1833  0.110837  0.058595  0.088952  0.169079  0.128486  0.309213   0.127451   \n",
      "1834  0.129313  0.066346  0.117218  0.147279  0.184632  0.308609   0.146679   \n",
      "1835  0.164119  0.057132  0.074236  0.126274  0.156841  0.325328   0.034532   \n",
      "1836  0.122909  0.071273  0.096727  0.146909  0.129455  0.304727   0.033493   \n",
      "1837  0.300752  0.104010  0.081036  0.108605  0.135756  0.178780   0.003962   \n",
      "1838  0.219072  0.067010  0.100515  0.117698  0.121993  0.227663   0.113716   \n",
      "1839  0.140206  0.046907  0.049485  0.140722  0.456186  0.130928   0.005747   \n",
      "1840  0.093696  0.064199  0.084442  0.140544  0.183921  0.334297   0.024623   \n",
      "1841  0.113716  0.064618  0.097244  0.146975  0.149192  0.309788   0.050191   \n",
      "1842  0.130690  0.105972  0.099364  0.156877  0.224914  0.228096   0.017463   \n",
      "1843  0.036627  0.075241  0.110449  0.243612  0.352924  0.154458   0.027037   \n",
      "1844  0.225938  0.070147  0.077488  0.168842  0.120718  0.186786   0.052095   \n",
      "1845  0.128093  0.091703  0.113537  0.209607  0.234352  0.181951   0.044807   \n",
      "1846  0.190158  0.085662  0.074727  0.165857  0.151276  0.202916   0.108454   \n",
      "1847  0.171631  0.069620  0.083395  0.174237  0.157483  0.282949   0.124874   \n",
      "1848  0.257206  0.070953  0.104213  0.159645  0.212860  0.130820   0.053968   \n",
      "1849  0.200898  0.074448  0.085672  0.168724  0.145155  0.219978   0.109756   \n",
      "1850  0.202315  0.063889  0.068056  0.139352  0.135185  0.238426   0.082009   \n",
      "1851  0.092391  0.045396  0.078645  0.174552  0.187660  0.332481   0.081851   \n",
      "1852  0.123209  0.074499  0.112703  0.179561  0.148042  0.287011   0.088859   \n",
      "1853  0.112715  0.077783  0.076386  0.188635  0.171868  0.264555   0.015818   \n",
      "1854  0.081633  0.078717  0.085520  0.130224  0.154519  0.321672   0.007895   \n",
      "1855  0.257219  0.069366  0.070030  0.165616  0.107534  0.207434   0.079462   \n",
      "1856  0.212733  0.096273  0.074534  0.156832  0.114907  0.243789   0.014286   \n",
      "1857  0.117347  0.091837  0.088010  0.151786  0.136480  0.321429   0.034247   \n",
      "1858  0.220000  0.020000  0.060000  0.060000  0.080000  0.340000   0.029412   \n",
      "1859  0.151729  0.093470  0.088348  0.184379  0.131242  0.285531   0.245928   \n",
      "1860  0.167826  0.094783  0.078261  0.163478  0.155652  0.247826   0.246769   \n",
      "1861  0.175652  0.058261  0.070435  0.173913  0.126957  0.254783   0.066746   \n",
      "1862  0.173870  0.075012  0.063587  0.199205  0.121212  0.242424   0.260813   \n",
      "1863  0.138528  0.086580  0.060606  0.121212  0.212121  0.281385   0.002747   \n",
      "1864  0.198777  0.067278  0.091743  0.140673  0.152905  0.250765   0.059072   \n",
      "1865  0.252621  0.070580  0.082110  0.123340  0.171209  0.219776   0.010934   \n",
      "1866  0.160040  0.065606  0.072233  0.139828  0.133201  0.264745   0.167842   \n",
      "1867  0.246951  0.072561  0.099390  0.143293  0.169512  0.199390   0.021061   \n",
      "1868  0.049396  0.038419  0.048299  0.121844  0.611416  0.108123   0.001821   \n",
      "1869  0.265385  0.054615  0.036154  0.121538  0.105385  0.139231   0.009662   \n",
      "1870  0.304107  0.076619  0.079779  0.152449  0.115324  0.203002   0.015135   \n",
      "1871  0.290155  0.025907  0.082902  0.134715  0.119171  0.155440   0.075342   \n",
      "1872  0.110110  0.101101  0.142142  0.303303  0.139139  0.153153   0.514839   \n",
      "1873  0.341067  0.062645  0.074246  0.109049  0.120650  0.174014   0.353741   \n",
      "1874  0.086191  0.075070  0.101946  0.184430  0.163114  0.278962   0.054971   \n",
      "1875  0.138696  0.133148  0.170596  0.200416  0.158807  0.151872   0.002415   \n",
      "1876  0.065511  0.053308  0.151574  0.233783  0.204881  0.225434   0.000000   \n",
      "1877  0.198562  0.060647  0.072776  0.142408  0.111411  0.256963   0.112720   \n",
      "1878  0.210480  0.077729  0.055022  0.131441  0.127948  0.204367   0.024149   \n",
      "1879  0.147505  0.117137  0.075922  0.143167  0.119306  0.140998   0.028736   \n",
      "1880  0.122625  0.061831  0.075993  0.140242  0.272884  0.249050   0.024891   \n",
      "1881  0.322634  0.116872  0.109259  0.154115  0.166667  0.095885   0.013754   \n",
      "1882  0.166155  0.093980  0.088759  0.159705  0.346437  0.106880   0.008886   \n",
      "1883  0.106796  0.038835  0.116505  0.165049  0.135922  0.223301   0.064516   \n",
      "1884  0.148918  0.079236  0.090194  0.134588  0.143299  0.288002   0.137032   \n",
      "1885  0.186270  0.072147  0.077831  0.184521  0.153476  0.238741   0.132970   \n",
      "1886  0.113586  0.042316  0.075724  0.093541  0.260579  0.256125   0.106742   \n",
      "1887  0.146290  0.069488  0.099269  0.169801  0.182341  0.257053   0.042379   \n",
      "1888  0.199829  0.102477  0.088813  0.148591  0.116140  0.292058   0.093716   \n",
      "1889  0.171336  0.056841  0.082014  0.130735  0.190418  0.245635   0.024615   \n",
      "1890  0.136268  0.077568  0.102725  0.226415  0.180294  0.185185   0.006639   \n",
      "1891  0.369676  0.066440  0.069847  0.103918  0.165247  0.126065   0.014463   \n",
      "1892  0.145119  0.132586  0.167546  0.209103  0.147098  0.167546   0.020183   \n",
      "1893  0.275726  0.042216  0.085752  0.083113  0.125330  0.259894   0.302632   \n",
      "1894  0.064925  0.077612  0.101493  0.218657  0.163433  0.247761   0.012168   \n",
      "1895  0.172464  0.128986  0.094203  0.184058  0.186957  0.194203   0.010638   \n",
      "1896  0.143923  0.073561  0.083156  0.153518  0.180171  0.273987   0.045780   \n",
      "1897  0.082602  0.062865  0.089181  0.170322  0.158626  0.331140   0.147929   \n",
      "1898  0.303083  0.064572  0.074462  0.104130  0.153578  0.262944   0.017953   \n",
      "1899  0.080903  0.064005  0.092717  0.152236  0.140422  0.327800   0.059622   \n",
      "1900  0.208551  0.090261  0.077910  0.147268  0.270784  0.154869   0.007386   \n",
      "1901  0.152449  0.089708  0.077600  0.149697  0.145294  0.250963   0.008258   \n",
      "1902  0.197254  0.116329  0.108382  0.204480  0.148121  0.156069   0.128713   \n",
      "1903  0.228029  0.040380  0.080760  0.144893  0.121140  0.254157   0.051724   \n",
      "1904  0.212766  0.063830  0.102128  0.123404  0.187234  0.234043   0.025641   \n",
      "1905  0.027066  0.042735  0.089744  0.189459  0.259259  0.286325   0.007380   \n",
      "1906  0.155483  0.047463  0.049100  0.206219  0.487725  0.050736   0.001919   \n",
      "1907  0.203636  0.056198  0.080661  0.107107  0.227107  0.234380   0.062551   \n",
      "1908  0.135338  0.100752  0.105263  0.224060  0.168421  0.225564   0.057214   \n",
      "1909  0.372574  0.065780  0.069914  0.104960  0.129224  0.179008   0.013303   \n",
      "1910  0.248144  0.068081  0.075928  0.139555  0.135525  0.213150   0.088337   \n",
      "1911  0.188513  0.073638  0.087629  0.116348  0.136966  0.240795   0.089021   \n",
      "1912  0.085766  0.089797  0.098832  0.206283  0.345010  0.150542   0.011022   \n",
      "1913  0.096718  0.077375  0.083592  0.164421  0.388946  0.166149   0.008309   \n",
      "1914  0.137911  0.077900  0.097519  0.147721  0.250433  0.226774   0.010431   \n",
      "1915  0.181965  0.090177  0.132045  0.130435  0.106280  0.267311   0.126338   \n",
      "1916  0.066540  0.087833  0.098479  0.245627  0.248669  0.200000   0.013170   \n",
      "1917  0.100840  0.082833  0.093637  0.201681  0.169268  0.262905   0.047078   \n",
      "1918  0.081761  0.092404  0.112724  0.242864  0.265602  0.166909   0.011862   \n",
      "1919  0.186838  0.054463  0.069213  0.125567  0.142587  0.273449   0.022901   \n",
      "1920  0.184918  0.072787  0.066885  0.148197  0.207213  0.225574   0.043890   \n",
      "1921  0.121076  0.088565  0.100897  0.213004  0.127803  0.245516   0.179811   \n",
      "1922  0.292298  0.099408  0.067149  0.129032  0.117841  0.219882   0.012739   \n",
      "1923  0.134569  0.074940  0.080580  0.214343  0.157131  0.273167   0.064698   \n",
      "1924  0.186712  0.066064  0.074158  0.137587  0.163561  0.292114   0.020606   \n",
      "1925  0.130565  0.060606  0.076693  0.157501  0.147400  0.337449   0.117527   \n",
      "1926  0.087539  0.047374  0.065225  0.144181  0.188122  0.393066   0.036450   \n",
      "1927  0.140392  0.048507  0.071362  0.142257  0.173041  0.343750   0.090854   \n",
      "1928  0.135198  0.067599  0.072261  0.160839  0.235431  0.223776   0.060606   \n",
      "1929  0.249085  0.083804  0.076821  0.130362  0.142667  0.230462   0.232350   \n",
      "1930  0.266000  0.073500  0.078750  0.146750  0.128250  0.204750   0.104394   \n",
      "1931  0.089921  0.134881  0.126976  0.246047  0.264328  0.124012   0.009390   \n",
      "1932  0.144674  0.081081  0.081081  0.189189  0.149444  0.251192   0.120902   \n",
      "1933  0.083215  0.043741  0.057255  0.136202  0.127667  0.399004   0.039098   \n",
      "1934  0.110280  0.085981  0.207477  0.242991  0.104673  0.190654   0.032070   \n",
      "1935  0.132858  0.052917  0.091135  0.160448  0.203189  0.317616   0.052835   \n",
      "1936  0.112144  0.091293  0.068752  0.143984  0.156100  0.308256   0.037891   \n",
      "1937  0.034247  0.053082  0.071918  0.145548  0.246575  0.308219   0.002237   \n",
      "1938  0.274406  0.094987  0.068602  0.124011  0.118734  0.224274   0.035714   \n",
      "1939  0.186772  0.077039  0.094325  0.167982  0.135663  0.266441   0.045646   \n",
      "1940  0.148997  0.087034  0.108883  0.110673  0.181590  0.248926   0.008582   \n",
      "1941  0.136145  0.084337  0.089759  0.156024  0.150602  0.274096   0.010526   \n",
      "1942  0.281219  0.091390  0.092397  0.144260  0.125126  0.153827   0.150578   \n",
      "1943  0.172224  0.067424  0.081715  0.114328  0.213631  0.253573   0.048980   \n",
      "1944  0.213793  0.088123  0.085824  0.154789  0.138697  0.243678   0.077813   \n",
      "1945  0.316072  0.070835  0.067904  0.111383  0.101124  0.199805   0.014667   \n",
      "1946  0.167059  0.134118  0.101176  0.200000  0.134118  0.155294   0.026706   \n",
      "1947  0.112096  0.059260  0.076872  0.164377  0.178223  0.314355   0.131780   \n",
      "1948  0.101480  0.070762  0.072752  0.175600  0.192265  0.311777   0.050086   \n",
      "1949  0.117117  0.058559  0.087838  0.184685  0.186937  0.126126   0.018809   \n",
      "1950  0.166341  0.048924  0.091977  0.154599  0.215264  0.215264   0.031915   \n",
      "1951  0.158019  0.073113  0.068396  0.195755  0.226415  0.155660   0.003067   \n",
      "1952  0.162127  0.079118  0.124514  0.107652  0.267185  0.190661   0.019355   \n",
      "1953  0.118798  0.050329  0.088921  0.168593  0.250934  0.281522   0.103819   \n",
      "1954  0.199407  0.081542  0.083766  0.194959  0.127502  0.213491   0.277164   \n",
      "1955  0.079208  0.054455  0.096535  0.153465  0.214109  0.295792   0.017488   \n",
      "1956  0.058656  0.070615  0.109339  0.200456  0.327449  0.195330   0.025660   \n",
      "1957  0.242268  0.086770  0.071306  0.136168  0.157646  0.206186   0.014226   \n",
      "1958  0.269486  0.097015  0.069652  0.157546  0.122720  0.223881   0.028953   \n",
      "1959  0.083969  0.106870  0.125954  0.175573  0.200382  0.221374   0.006652   \n",
      "1960  0.099975  0.077174  0.125282  0.191681  0.182661  0.246555   0.067420   \n",
      "1961  0.205573  0.070452  0.066246  0.147213  0.149317  0.324395   0.059550   \n",
      "1962  0.095767  0.052741  0.098543  0.210271  0.360167  0.160305   0.138449   \n",
      "1963  0.223739  0.083954  0.105045  0.148883  0.140612  0.184864   0.126380   \n",
      "1964  0.119547  0.062512  0.102172  0.181114  0.178848  0.288574   0.131232   \n",
      "1965  0.208902  0.065756  0.082448  0.113809  0.213961  0.238746   0.009674   \n",
      "1966  0.056825  0.067943  0.064237  0.152563  0.230389  0.347746   0.031811   \n",
      "1967  0.168639  0.106509  0.081657  0.166864  0.101183  0.204734   0.044882   \n",
      "1968  0.141637  0.055516  0.088968  0.180071  0.150178  0.286121   0.279644   \n",
      "1969  0.026490  0.079470  0.072848  0.238411  0.434030  0.127356   0.262929   \n",
      "1970  0.146530  0.053985  0.079692  0.147815  0.161097  0.316624   0.035880   \n",
      "1971  0.201528  0.074499  0.059217  0.185291  0.142311  0.206304   0.161074   \n",
      "1972  0.255043  0.080692  0.102305  0.187320  0.132565  0.152738   0.104762   \n",
      "1973  0.047649  0.105396  0.057116  0.226885  0.471127  0.086147   0.003670   \n",
      "1974  0.317452  0.076336  0.077126  0.141879  0.141879  0.173730   0.188025   \n",
      "1975  0.155031  0.070329  0.085216  0.140657  0.196099  0.262834   0.143426   \n",
      "1976  0.215945  0.085649  0.080638  0.141686  0.141686  0.235080   0.071967   \n",
      "1977  0.199319  0.082907  0.088018  0.170358  0.172061  0.189097   0.048909   \n",
      "1978  0.121298  0.087447  0.090268  0.172073  0.121298  0.249647   0.088933   \n",
      "1979  0.283186  0.072566  0.092035  0.169912  0.120354  0.155752   0.164649   \n",
      "1980  0.131777  0.078313  0.129518  0.146084  0.185994  0.246235   0.039542   \n",
      "1981  0.074344  0.064626  0.075316  0.152575  0.391156  0.187075   0.034584   \n",
      "1982  0.088515  0.045355  0.038771  0.100219  0.441112  0.229700   0.006617   \n",
      "1983  0.071429  0.091518  0.089286  0.162946  0.268973  0.239955   0.005908   \n",
      "1984  0.170543  0.130415  0.130415  0.194254  0.204742  0.142271   0.012274   \n",
      "1985  0.063690  0.057124  0.112278  0.182534  0.202889  0.291530   0.042152   \n",
      "1986  0.119034  0.052218  0.078608  0.121842  0.210556  0.350926   0.064024   \n",
      "1987  0.166058  0.038865  0.072665  0.122836  0.169591  0.321399   0.019249   \n",
      "1988  0.204360  0.083560  0.086285  0.168937  0.119891  0.237965   0.021818   \n",
      "1989  0.145749  0.087045  0.085020  0.165992  0.186235  0.234818   0.135417   \n",
      "1990  0.029175  0.056430  0.087524  0.144338  0.335125  0.297505   0.019806   \n",
      "1991  0.226247  0.067669  0.061517  0.113465  0.107997  0.205742   0.141959   \n",
      "1992  0.203540  0.047408  0.067004  0.106195  0.138432  0.292035   0.056109   \n",
      "1993  0.108207  0.068085  0.105775  0.175076  0.180547  0.270517   0.046229   \n",
      "1994  0.291190  0.088097  0.084062  0.167451  0.110962  0.180901   0.281604   \n",
      "1995  0.147796  0.072579  0.085379  0.195302  0.208894  0.242148   0.229725   \n",
      "1996  0.107232  0.059850  0.114713  0.279302  0.147132  0.244389   0.094463   \n",
      "1997  0.096375  0.074271  0.110522  0.176835  0.180371  0.332449   0.036946   \n",
      "1998  0.208866  0.085251  0.103154  0.123615  0.160273  0.212276   0.037628   \n",
      "1999  0.126219  0.069339  0.072048  0.145179  0.163597  0.278982   0.042491   \n",
      "2000  0.086806  0.031250  0.152778  0.243056  0.131944  0.190972   0.005435   \n",
      "2001  0.143969  0.088197  0.076524  0.137484  0.128405  0.312581   0.104673   \n",
      "2002  0.022346  0.100559  0.072626  0.374302  0.307263  0.100559   0.000000   \n",
      "2003  0.142857  0.023810  0.119048  0.404762  0.285714  0.023810   0.000000   \n",
      "2004  0.271812  0.063758  0.073826  0.137584  0.127517  0.211409   0.093458   \n",
      "2005  0.186483  0.080100  0.082603  0.147685  0.178974  0.254068   0.054487   \n",
      "2006  0.087436  0.058046  0.068332  0.219691  0.151359  0.313005   0.390268   \n",
      "2007  0.116606  0.063538  0.106137  0.198556  0.227798  0.222383   0.037096   \n",
      "2008  0.110609  0.092551  0.110609  0.167043  0.209932  0.261851   0.002857   \n",
      "2009  0.222563  0.088310  0.076059  0.111792  0.138846  0.235324   0.039163   \n",
      "2010  0.119823  0.040493  0.067366  0.147248  0.209277  0.355973   0.131398   \n",
      "2011  0.113475  0.066194  0.061466  0.189125  0.234043  0.257683   0.021084   \n",
      "2012  0.229614  0.097282  0.077969  0.138054  0.128755  0.246781   0.041121   \n",
      "2013  0.094629  0.033248  0.047315  0.171355  0.140665  0.326087   0.098390   \n",
      "2014  0.172545  0.092946  0.119161  0.137750  0.137274  0.222116   0.166667   \n",
      "2015  0.153323  0.068731  0.074396  0.146903  0.109894  0.319486   0.166278   \n",
      "2016  0.273425  0.066052  0.071429  0.132873  0.122888  0.162826   0.065748   \n",
      "2017  0.221387  0.083542  0.058480  0.322473  0.091896  0.144528   0.522983   \n",
      "2018  0.171674  0.074678  0.084979  0.150215  0.171674  0.267811   0.032370   \n",
      "2019  0.217761  0.064242  0.084081  0.130846  0.123288  0.218706   0.044631   \n",
      "2020  0.129544  0.051203  0.081413  0.145929  0.165899  0.324629   0.091151   \n",
      "2021  0.144128  0.124555  0.099644  0.126335  0.106762  0.314947   0.080488   \n",
      "2022  0.190344  0.105385  0.097493  0.213556  0.105385  0.236305   0.247405   \n",
      "2023  0.163525  0.074885  0.075395  0.156903  0.131941  0.311258   0.094048   \n",
      "2024  0.194645  0.095263  0.081359  0.232235  0.147271  0.191555   0.179962   \n",
      "2025  0.209412  0.089412  0.108235  0.178824  0.143529  0.218824   0.079038   \n",
      "2026  0.252302  0.065378  0.082873  0.113260  0.183241  0.162983   0.003593   \n",
      "2027  0.295902  0.086885  0.088115  0.146311  0.121721  0.156148   0.180435   \n",
      "2028  0.214912  0.057018  0.035088  0.250000  0.250000  0.144737   0.032258   \n",
      "2029  0.117117  0.054054  0.036036  0.162162  0.315315  0.216216   0.012195   \n",
      "2030  0.168802  0.060539  0.090588  0.191781  0.257623  0.182059   0.120598   \n",
      "2031  0.215190  0.029536  0.046414  0.067511  0.122363  0.286920   0.096386   \n",
      "2032  0.120385  0.083467  0.105939  0.133226  0.154093  0.293740   0.051282   \n",
      "2033  0.182022  0.069663  0.089888  0.132584  0.202996  0.259176   0.058095   \n",
      "2034  0.158382  0.052408  0.063584  0.106744  0.133719  0.333333   0.036059   \n",
      "2035  0.169463  0.059793  0.079469  0.143838  0.193106  0.296675   0.044055   \n",
      "2036  0.150394  0.087372  0.112915  0.166627  0.147291  0.253282   0.059950   \n",
      "2037  0.126087  0.046087  0.063478  0.154783  0.233913  0.291304   0.144086   \n",
      "2038  0.280488  0.079675  0.054472  0.104065  0.133333  0.253659   0.186693   \n",
      "2039  0.047619  0.089636  0.170868  0.294118  0.193277  0.156863   0.109929   \n",
      "2040  0.142420  0.088821  0.105666  0.223583  0.127106  0.215926   0.062771   \n",
      "2041  0.339953  0.062411  0.068558  0.119149  0.130496  0.157447   0.296319   \n",
      "2042  0.171627  0.060020  0.089782  0.180556  0.165675  0.274306   0.095745   \n",
      "2043  0.291160  0.091646  0.067315  0.107867  0.104623  0.236821   0.004269   \n",
      "2044  0.259962  0.096774  0.072106  0.203036  0.100569  0.189753   0.145455   \n",
      "2045  0.196109  0.090272  0.106615  0.178988  0.151751  0.217121   0.101402   \n",
      "2046  0.088331  0.080227  0.068071  0.174230  0.111021  0.276337   0.008102   \n",
      "2047  0.097006  0.065918  0.097582  0.183362  0.177029  0.298215   0.017357   \n",
      "2048  0.248955  0.066269  0.081791  0.171940  0.119403  0.156418   0.234633   \n",
      "2049  0.359352  0.062592  0.075110  0.166421  0.079529  0.187040   0.082534   \n",
      "2050  0.226950  0.078014  0.085106  0.138298  0.085106  0.198582   0.097436   \n",
      "2051  0.199461  0.099730  0.088949  0.176101  0.249775  0.143756   0.006237   \n",
      "2052  0.163829  0.057546  0.096301  0.169701  0.176160  0.253670   0.081967   \n",
      "2053  0.319012  0.068475  0.069012  0.108217  0.125940  0.209184   0.008153   \n",
      "2054  0.054482  0.079086  0.080844  0.246046  0.240773  0.279438   0.043732   \n",
      "2055  0.124470  0.145686  0.067893  0.149929  0.171146  0.207921   0.075229   \n",
      "2056  0.112817  0.072141  0.112817  0.156562  0.184190  0.297007   0.127613   \n",
      "2057  0.146739  0.125000  0.108696  0.190217  0.150362  0.188406   0.002398   \n",
      "2058  0.181416  0.079646  0.077434  0.179204  0.143805  0.230088   0.043121   \n",
      "2059  0.296532  0.075232  0.076698  0.135809  0.123107  0.192965   0.248756   \n",
      "2060  0.232496  0.098743  0.075404  0.102783  0.115799  0.274237   0.058824   \n",
      "2061  0.221790  0.052918  0.069261  0.120623  0.116732  0.249805   0.153611   \n",
      "2062  0.080292  0.071275  0.096179  0.169386  0.186775  0.319665   0.030222   \n",
      "2063  0.092715  0.077263  0.066225  0.205298  0.207506  0.284768   0.061162   \n",
      "2064  0.113821  0.054823  0.072621  0.132718  0.162931  0.352230   0.019108   \n",
      "2065  0.233073  0.051432  0.067708  0.132812  0.147786  0.224609   0.314407   \n",
      "2066  0.162500  0.112500  0.062500  0.225000  0.100000  0.200000   0.062500   \n",
      "2067  0.269231  0.072398  0.093891  0.117647  0.142534  0.183258   0.097484   \n",
      "2068  0.374733  0.051957  0.054448  0.088968  0.154448  0.193950   0.020739   \n",
      "2069  0.236618  0.088544  0.085043  0.128064  0.164082  0.170585   0.120908   \n",
      "2070  0.113475  0.060284  0.063830  0.209220  0.244681  0.209220   0.009302   \n",
      "2071  0.120352  0.080235  0.115460  0.138943  0.225049  0.285714   0.029639   \n",
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      "2074  0.116197  0.082394  0.085211  0.367606  0.097183  0.164789   0.526561   \n",
      "2075  0.391241  0.075426  0.039173  0.056691  0.400000  0.031387   0.000314   \n",
      "2076  0.114405  0.059081  0.096242  0.175365  0.186639  0.310438   0.054827   \n",
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      "2078  0.181818  0.059011  0.070175  0.178628  0.236045  0.228070   0.022000   \n",
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      "2080  0.255875  0.075718  0.067885  0.156658  0.120104  0.201044   0.167247   \n",
      "2081  0.239726  0.122432  0.073630  0.149829  0.101884  0.219178   0.081776   \n",
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      "2083  0.362237  0.062775  0.070835  0.103566  0.166830  0.164143   0.003884   \n",
      "2084  0.300518  0.056995  0.069085  0.122625  0.228843  0.168394   0.014846   \n",
      "2085  0.191388  0.108453  0.090909  0.170654  0.074960  0.141946   0.048626   \n",
      "2086  0.198638  0.053066  0.076371  0.100753  0.134457  0.280029   0.006003   \n",
      "2087  0.106615  0.115037  0.064092  0.205629  0.252465  0.230279   0.034913   \n",
      "2088  0.156168  0.072178  0.069554  0.204724  0.223097  0.186352   0.012478   \n",
      "2089  0.134461  0.115137  0.099034  0.136876  0.239936  0.231079   0.029316   \n",
      "2090  0.208738  0.070735  0.093620  0.129681  0.199029  0.204577   0.037866   \n",
      "2091  0.168959  0.055010  0.076621  0.132613  0.211198  0.250491   0.018634   \n",
      "2092  0.076446  0.049587  0.117769  0.148760  0.256198  0.266529   0.008130   \n",
      "2093  0.315603  0.072695  0.111702  0.140957  0.153369  0.149823   0.039474   \n",
      "2094  0.103030  0.062626  0.072727  0.139394  0.266667  0.288889   0.008427   \n",
      "2095  0.225840  0.067227  0.059874  0.112395  0.129202  0.207983   0.071023   \n",
      "2096  0.226599  0.081316  0.098663  0.159740  0.142392  0.208168   0.098485   \n",
      "2097  0.075041  0.061990  0.084829  0.192496  0.194127  0.299347   0.088435   \n",
      "2098  0.129412  0.076471  0.094118  0.200000  0.194118  0.241176   0.007937   \n",
      "2099  0.222222  0.095062  0.082716  0.177778  0.155556  0.180247   0.126079   \n",
      "2100  0.053844  0.091262  0.057951  0.118640  0.561259  0.110655   0.001634   \n",
      "2101  0.149485  0.096649  0.081830  0.177191  0.233892  0.188144   0.064332   \n",
      "2102  0.104531  0.074024  0.101391  0.173620  0.150740  0.294751   0.202703   \n",
      "2103  0.037951  0.030361  0.045541  0.142315  0.314991  0.242884   0.025253   \n",
      "2104  0.195876  0.076583  0.110457  0.220913  0.198822  0.169367   0.000000   \n",
      "2105  0.181195  0.081783  0.107248  0.147894  0.117042  0.260529   0.118194   \n",
      "2106  0.129032  0.000000  0.032258  0.387097  0.096774  0.129032   0.125000   \n",
      "2107  0.128259  0.083420  0.103580  0.170316  0.190824  0.237400   0.019404   \n",
      "2108  0.046685  0.045752  0.050420  0.135387  0.492997  0.212885   0.001998   \n",
      "2109  0.237152  0.071664  0.081565  0.135785  0.162188  0.193305   0.023990   \n",
      "2110  0.032407  0.048942  0.059524  0.122354  0.464947  0.245370   0.001419   \n",
      "2111  0.318083  0.074074  0.058824  0.094771  0.309368  0.112200   0.003452   \n",
      "2112  0.096569  0.106734  0.104193  0.210928  0.129606  0.273189   0.273885   \n",
      "2113  0.065882  0.157647  0.072941  0.148235  0.374118  0.155294   0.000000   \n",
      "2114  0.113986  0.074825  0.071329  0.200000  0.162937  0.265734   0.081276   \n",
      "2115  0.076559  0.060773  0.074980  0.187056  0.339384  0.217048   0.026927   \n",
      "2116  0.050505  0.053030  0.085859  0.227273  0.146465  0.262626   0.060201   \n",
      "2117  0.166265  0.071084  0.085542  0.149398  0.155422  0.271084   0.047847   \n",
      "2118  0.182292  0.098958  0.166667  0.223958  0.156250  0.135417   0.020408   \n",
      "2119  0.190323  0.067742  0.112903  0.196774  0.135484  0.209677   0.128631   \n",
      "2120  0.154079  0.076737  0.083384  0.174018  0.251964  0.206042   0.010861   \n",
      "2121  0.021053  0.147368  0.126316  0.389474  0.200000  0.094737   0.202532   \n",
      "2122  0.431373  0.117647  0.058824  0.127451  0.078431  0.058824   0.000000   \n",
      "2123  0.143599  0.131488  0.124567  0.219723  0.147059  0.134948   0.036036   \n",
      "2124  0.203822  0.101911  0.076433  0.146497  0.063694  0.254777   0.089109   \n",
      "2125  0.198953  0.099476  0.130890  0.188482  0.172775  0.167539   0.098592   \n",
      "2126  0.125000  0.166667  0.083333  0.333333  0.125000  0.125000   0.526316   \n",
      "2127  0.074286  0.077143  0.065714  0.157143  0.142857  0.285714   0.174074   \n",
      "2128  0.035714  0.071429  0.107143  0.250000  0.357143  0.178571   0.000000   \n",
      "2129  0.325000  0.150000  0.050000  0.075000  0.050000  0.250000   0.028571   \n",
      "2130  0.148649  0.175676  0.094595  0.175676  0.135135  0.148649   0.113208   \n",
      "2131  0.138454  0.080235  0.116438  0.147260  0.215264  0.215264   0.008712   \n",
      "2132  0.217391  0.086957  0.086957  0.043478  0.217391  0.217391   0.000000   \n",
      "2133  0.250000  0.000000  0.250000  0.000000  0.000000  0.250000   0.333333   \n",
      "2134  0.116622  0.052279  0.135389  0.335121  0.176944  0.123324   0.024123   \n",
      "2135  0.182599  0.070693  0.092158  0.139382  0.138809  0.268460   0.059061   \n",
      "2136  0.121445  0.049193  0.068409  0.127594  0.219062  0.279016   0.037871   \n",
      "2137  0.095195  0.043518  0.064370  0.179510  0.177697  0.293744   0.034615   \n",
      "2138  0.132075  0.072956  0.098113  0.227673  0.223899  0.182390   0.030449   \n",
      "2139  0.059347  0.038576  0.089021  0.240356  0.201780  0.222552   0.034934   \n",
      "2140  0.107374  0.087969  0.055627  0.186934  0.211514  0.256145   0.007765   \n",
      "2141  0.136860  0.084803  0.072628  0.162049  0.152813  0.238455   0.081596   \n",
      "2142  0.106916  0.098447  0.108680  0.180663  0.262174  0.208186   0.010444   \n",
      "2143  0.100447  0.085807  0.093127  0.193575  0.186255  0.276129   0.011783   \n",
      "2144  0.103412  0.057218  0.073491  0.183727  0.174278  0.362205   0.023499   \n",
      "2145  0.136564  0.058370  0.080947  0.174009  0.155837  0.316079   0.026103   \n",
      "2146  0.246702  0.086224  0.087445  0.146312  0.150708  0.197606   0.021498   \n",
      "2147  0.128869  0.066520  0.108013  0.157849  0.158727  0.286718   0.021687   \n",
      "2148  0.254534  0.071920  0.058161  0.116323  0.125704  0.264540   0.026753   \n",
      "2149  0.064824  0.082903  0.132231  0.327738  0.200671  0.170971   0.045277   \n",
      "2150  0.252772  0.057650  0.070953  0.135255  0.157428  0.198817   0.029326   \n",
      "2151  0.249135  0.066436  0.069204  0.123875  0.137716  0.220761   0.048148   \n",
      "2152  0.286422  0.093657  0.065411  0.128345  0.126858  0.177899   0.067199   \n",
      "2153  0.388469  0.089792  0.076560  0.123819  0.090737  0.172023   0.004920   \n",
      "2154  0.222493  0.056029  0.081202  0.132765  0.137231  0.273650   0.027482   \n",
      "2155  0.185873  0.072022  0.083657  0.151801  0.136011  0.277008   0.042553   \n",
      "2156  0.146842  0.057711  0.063482  0.136582  0.164155  0.329593   0.034298   \n",
      "2157  0.175385  0.066154  0.100769  0.126154  0.145385  0.246154   0.025478   \n",
      "2158  0.198336  0.049931  0.072122  0.144244  0.151179  0.291262   0.005495   \n",
      "2159  0.172879  0.084060  0.061856  0.163362  0.168914  0.195083   0.013171   \n",
      "2160  0.118012  0.031056  0.018634  0.180124  0.186335  0.391304   0.020619   \n",
      "2161  0.186654  0.074790  0.080271  0.139587  0.148291  0.242747   0.061411   \n",
      "2162  0.096589  0.069571  0.103006  0.170213  0.178318  0.274232   0.023144   \n",
      "2163  0.061677  0.065142  0.085932  0.186417  0.188496  0.324324   0.035887   \n",
      "2164  0.101460  0.065847  0.075839  0.178837  0.213169  0.296951   0.044908   \n",
      "2165  0.292084  0.072423  0.072640  0.113528  0.162897  0.204872   0.063026   \n",
      "2166  0.187817  0.071663  0.080024  0.178859  0.241266  0.209913   0.022953   \n",
      "2167  0.253422  0.037744  0.060556  0.133140  0.129407  0.226462   0.025192   \n",
      "2168  0.122031  0.082330  0.110316  0.132118  0.400911  0.104133   0.006701   \n",
      "2169  0.099125  0.081633  0.052478  0.116618  0.116618  0.227405   0.008230   \n",
      "2170  0.116204  0.067737  0.064234  0.174453  0.176058  0.333723   0.033732   \n",
      "2171  0.263310  0.054897  0.072138  0.134897  0.234069  0.194483   0.018494   \n",
      "2172  0.155436  0.073412  0.088482  0.139720  0.156728  0.296448   0.028682   \n",
      "2173  0.100271  0.072267  0.089431  0.146341  0.198735  0.319783   0.016687   \n",
      "2174  0.185859  0.064646  0.044444  0.115152  0.086869  0.313131   0.131195   \n",
      "2175  0.234584  0.109299  0.085155  0.128874  0.236868  0.144209   0.005025   \n",
      "2176  0.125467  0.071009  0.084891  0.132942  0.153230  0.297384   0.077083   \n",
      "2177  0.125970  0.083549  0.107087  0.234609  0.201242  0.205898   0.085147   \n",
      "2178  0.096263  0.070895  0.079502  0.177916  0.177690  0.326161   0.029543   \n",
      "2179  0.172428  0.066667  0.084568  0.127572  0.143621  0.301029   0.123706   \n",
      "2180  0.101743  0.089376  0.089376  0.130410  0.133221  0.341765   0.029801   \n",
      "2181  0.181724  0.059370  0.062984  0.139391  0.123903  0.254001   0.042847   \n",
      "2182  0.104143  0.144457  0.087346  0.151176  0.145577  0.272116   0.017699   \n",
      "2183  0.145126  0.115583  0.132201  0.228951  0.165805  0.169867   0.008505   \n",
      "2184  0.209282  0.066059  0.071754  0.156891  0.138098  0.290433   0.080517   \n",
      "2185  0.179566  0.086230  0.090647  0.173228  0.149030  0.232187   0.079024   \n",
      "2186  0.152439  0.091463  0.085366  0.182927  0.123693  0.272648   0.197727   \n",
      "2187  0.161152  0.074729  0.083571  0.153451  0.139760  0.254706   0.067981   \n",
      "2188  0.141748  0.075081  0.086731  0.157605  0.134304  0.282848   0.028064   \n",
      "2189  0.243321  0.076336  0.068702  0.164122  0.122137  0.203244   0.156291   \n",
      "2190  0.072690  0.076843  0.092420  0.136033  0.194185  0.269990   0.021948   \n",
      "2191  0.140901  0.064505  0.090090  0.158559  0.154595  0.275315   0.140040   \n",
      "2192  0.125000  0.097159  0.097159  0.176420  0.137500  0.270170   0.116394   \n",
      "2193  0.306965  0.086669  0.104318  0.118500  0.103687  0.161361   0.062319   \n",
      "2194  0.246807  0.080140  0.075032  0.130268  0.162835  0.218391   0.022594   \n",
      "2195  0.148975  0.061493  0.068814  0.143851  0.134700  0.308565   0.151163   \n",
      "2196  0.152364  0.072388  0.091068  0.251605  0.151781  0.212493   0.283997   \n",
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      "2198  0.202602  0.070775  0.078496  0.121676  0.172719  0.273234   0.018909   \n",
      "2199  0.113482  0.084519  0.082486  0.166836  0.177507  0.277778   0.016029   \n",
      "2200  0.152618  0.060337  0.081633  0.156167  0.117125  0.271517   0.005952   \n",
      "2201  0.133542  0.053680  0.088753  0.161699  0.174872  0.286349   0.025051   \n",
      "2202  0.078074  0.067332  0.083637  0.199501  0.138884  0.319394   0.103795   \n",
      "2203  0.168599  0.074338  0.072257  0.175439  0.121320  0.266131   0.169009   \n",
      "2204  0.116234  0.126801  0.094140  0.169068  0.242075  0.166186   0.021077   \n",
      "2205  0.123631  0.071624  0.088047  0.197993  0.170164  0.255474   0.026888   \n",
      "2206  0.041145  0.056351  0.101073  0.288014  0.246869  0.212880   0.005519   \n",
      "2207  0.082397  0.104869  0.101124  0.226592  0.161049  0.249064   0.000000   \n",
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      "2209  0.113133  0.054813  0.084631  0.171673  0.192063  0.319886   0.031491   \n",
      "2210  0.218020  0.070700  0.079579  0.114107  0.137126  0.279184   0.016066   \n",
      "2211  0.134028  0.079167  0.107639  0.258333  0.205556  0.170139   0.021978   \n",
      "2212  0.289344  0.086066  0.081421  0.121311  0.103552  0.255738   0.069683   \n",
      "2213  0.203132  0.059298  0.086286  0.136764  0.183138  0.252927   0.031173   \n",
      "2214  0.088608  0.081162  0.063291  0.132539  0.294118  0.304542   0.033126   \n",
      "2215  0.138647  0.069510  0.092639  0.160781  0.191370  0.283263   0.113969   \n",
      "2216  0.135384  0.070173  0.080380  0.139354  0.267224  0.239013   0.088053   \n",
      "2217  0.142741  0.061407  0.094754  0.128101  0.175275  0.301342   0.064278   \n",
      "2218  0.143629  0.109946  0.104862  0.175723  0.189069  0.207499   0.067420   \n",
      "2219  0.095285  0.074656  0.100196  0.174853  0.156189  0.321218   0.004848   \n",
      "2220  0.165657  0.068400  0.086213  0.148201  0.158888  0.252583   0.074022   \n",
      "2221  0.142927  0.090619  0.078831  0.137525  0.189096  0.261297   0.045904   \n",
      "2222  0.083958  0.066108  0.094094  0.143676  0.183561  0.340018   0.046484   \n",
      "2223  0.108866  0.123457  0.102132  0.162738  0.330715  0.138421   0.003894   \n",
      "2224  0.099790  0.088235  0.095588  0.185924  0.260504  0.223739   0.044313   \n",
      "2225  0.109095  0.044524  0.066153  0.148555  0.187698  0.387424   0.036364   \n",
      "2226  0.130180  0.069406  0.097721  0.135704  0.159530  0.357390   0.235798   \n",
      "2227  0.189189  0.054054  0.086149  0.172297  0.150338  0.189189   0.019438   \n",
      "2228  0.180288  0.073156  0.089379  0.138353  0.129783  0.262626   0.132525   \n",
      "2229  0.238796  0.065941  0.060819  0.154289  0.118438  0.265685   0.236797   \n",
      "2230  0.130612  0.078912  0.078571  0.148639  0.194898  0.296259   0.009021   \n",
      "2231  0.199049  0.065954  0.094474  0.118241  0.127154  0.290553   0.007188   \n",
      "2232  0.196335  0.068063  0.090875  0.142483  0.140239  0.218773   0.041176   \n",
      "2233  0.238986  0.089065  0.078922  0.180032  0.144849  0.193027   0.112426   \n",
      "2234  0.209657  0.057179  0.074968  0.145489  0.171537  0.214740   0.021382   \n",
      "2235  0.195460  0.099622  0.089533  0.121059  0.157629  0.200504   0.044444   \n",
      "2236  0.214559  0.091954  0.109195  0.176245  0.122605  0.222222   0.046154   \n",
      "2237  0.096510  0.067629  0.082070  0.168231  0.182912  0.348977   0.044885   \n",
      "2238  0.118031  0.053240  0.090909  0.193370  0.175791  0.313913   0.055072   \n",
      "2239  0.166489  0.060832  0.067236  0.116329  0.128068  0.306297   0.057353   \n",
      "2240  0.200157  0.071912  0.094414  0.158458  0.124784  0.248466   0.016785   \n",
      "2241  0.193438  0.065028  0.085489  0.152164  0.168627  0.232949   0.028482   \n",
      "2242  0.277518  0.078719  0.092728  0.130087  0.095397  0.191461   0.076715   \n",
      "2243  0.224185  0.089674  0.145380  0.150815  0.183424  0.175272   0.018565   \n",
      "2244  0.054348  0.089674  0.078804  0.176630  0.440217  0.146739   0.000000   \n",
      "2245  0.310660  0.073096  0.116751  0.164467  0.115736  0.142132   0.418699   \n",
      "2246  0.221160  0.096246  0.119454  0.182935  0.140614  0.163140   0.115157   \n",
      "2247  0.293033  0.095628  0.097678  0.137295  0.131831  0.144126   0.056911   \n",
      "2248  0.081033  0.064253  0.071539  0.150585  0.192758  0.367410   0.163955   \n",
      "2249  0.104074  0.051941  0.073953  0.164704  0.142499  0.320332   0.074183   \n",
      "2250  0.133613  0.061414  0.071899  0.133313  0.180198  0.342870   0.045997   \n",
      "2251  0.125144  0.053138  0.082788  0.172507  0.151328  0.287640   0.147929   \n",
      "2252  0.230480  0.082785  0.103481  0.214487  0.084666  0.184384   0.223700   \n",
      "2253  0.136669  0.065644  0.072908  0.138553  0.163573  0.324186   0.018736   \n",
      "2254  0.087482  0.072108  0.103221  0.182284  0.294290  0.208638   0.014513   \n",
      "2255  0.151568  0.070433  0.079393  0.140866  0.180936  0.243156   0.066848   \n",
      "2256  0.049743  0.078702  0.121439  0.191966  0.184493  0.347735   0.014715   \n",
      "2257  0.128691  0.070736  0.084178  0.196342  0.148083  0.272587   0.093313   \n",
      "2258  0.188809  0.072563  0.081949  0.160650  0.116606  0.267870   0.073949   \n",
      "2259  0.148826  0.085157  0.089534  0.132113  0.134501  0.261838   0.099245   \n",
      "2260  0.230181  0.069215  0.072435  0.163783  0.189537  0.195976   0.019797   \n",
      "2261  0.124031  0.093728  0.092319  0.187456  0.162086  0.210007   0.007435   \n",
      "2262  0.246835  0.104430  0.075949  0.199367  0.126582  0.189873   0.146718   \n",
      "2263  0.095295  0.094093  0.077258  0.186683  0.355028  0.164587   0.009635   \n",
      "2264  0.135417  0.059896  0.080729  0.173611  0.166667  0.261285   0.038946   \n",
      "2265  0.152640  0.050330  0.086634  0.169142  0.143564  0.234323   0.053961   \n",
      "2266  0.121094  0.109375  0.125000  0.203125  0.191406  0.199219   0.042553   \n",
      "2267  0.141679  0.075712  0.068216  0.125937  0.128936  0.315592   0.009737   \n",
      "2268  0.109346  0.061682  0.096262  0.198131  0.113084  0.321495   0.043093   \n",
      "2269  0.119843  0.084479  0.161100  0.308448  0.184676  0.115914   0.045307   \n",
      "2270  0.183134  0.061674  0.057898  0.156073  0.127753  0.301447   0.048841   \n",
      "2271  0.238272  0.095062  0.091711  0.139859  0.122575  0.216226   0.035243   \n",
      "2272  0.118636  0.063989  0.094348  0.203643  0.157403  0.292387   0.150256   \n",
      "2273  0.142047  0.064812  0.083986  0.168782  0.136646  0.281934   0.084320   \n",
      "2274  0.100892  0.070132  0.098124  0.181483  0.262381  0.237158   0.017147   \n",
      "2275  0.070086  0.058913  0.085069  0.147537  0.166328  0.378873   0.044070   \n",
      "2276  0.124448  0.065169  0.077688  0.145434  0.159426  0.322165   0.025432   \n",
      "2277  0.200271  0.059892  0.081843  0.135501  0.141463  0.255556   0.058962   \n",
      "2278  0.128792  0.084087  0.095796  0.166578  0.130921  0.314529   0.031532   \n",
      "2279  0.129032  0.080460  0.100853  0.146459  0.143493  0.303300   0.057113   \n",
      "2280  0.193798  0.046512  0.120155  0.170543  0.124031  0.263566   0.080000   \n",
      "2281  0.231023  0.132013  0.059406  0.326733  0.155116  0.062706   0.050279   \n",
      "2282  0.130387  0.074753  0.082746  0.146215  0.153894  0.285849   0.029241   \n",
      "2283  0.102174  0.059039  0.102174  0.181808  0.209039  0.286842   0.035317   \n",
      "2284  0.186100  0.073521  0.074287  0.124832  0.146659  0.246793   0.014489   \n",
      "2285  0.178420  0.071935  0.077427  0.129164  0.142452  0.278172   0.036145   \n",
      "2286  0.116788  0.077987  0.084518  0.142144  0.149443  0.313484   0.023220   \n",
      "2287  0.174314  0.079172  0.096491  0.176113  0.199505  0.226046   0.077315   \n",
      "2288  0.127362  0.054584  0.081176  0.156753  0.132260  0.313506   0.152575   \n",
      "2289  0.090291  0.070089  0.077098  0.172336  0.169656  0.315811   0.012863   \n",
      "2290  0.182563  0.114162  0.109827  0.180636  0.222543  0.151252   0.007382   \n",
      "2291  0.112460  0.064725  0.070388  0.163430  0.144822  0.309871   0.087051   \n",
      "2292  0.172561  0.077931  0.078585  0.171251  0.140799  0.229862   0.086917   \n",
      "2293  0.206597  0.076829  0.081851  0.124338  0.153930  0.255192   0.071828   \n",
      "2294  0.244613  0.113936  0.090684  0.133623  0.160130  0.197799   0.075986   \n",
      "2295  0.224240  0.075799  0.078958  0.142124  0.161863  0.204895   0.053088   \n",
      "2296  0.180328  0.068242  0.073199  0.137247  0.131910  0.279451   0.046891   \n",
      "2297  0.169545  0.089033  0.102377  0.192868  0.214959  0.198475   0.009576   \n",
      "2298  0.196970  0.053030  0.068182  0.186869  0.136364  0.250000   0.009967   \n",
      "2299  0.137166  0.066327  0.079474  0.195055  0.157771  0.231162   0.345413   \n",
      "2300  0.150685  0.125395  0.087460  0.267650  0.160169  0.189673   0.339450   \n",
      "2301  0.250000  0.097813  0.104019  0.141253  0.246749  0.130024   0.003349   \n",
      "2302  0.202167  0.060062  0.065325  0.109907  0.116718  0.191641   0.075882   \n",
      "2303  0.189454  0.077866  0.067443  0.114654  0.134273  0.263029   0.043911   \n",
      "2304  0.178877  0.075350  0.082655  0.162179  0.175955  0.243582   0.215407   \n",
      "2305  0.142669  0.055176  0.081319  0.127562  0.155938  0.341697   0.080690   \n",
      "2306  0.209432  0.073022  0.071755  0.125254  0.137424  0.227688   0.097620   \n",
      "2307  0.155182  0.084124  0.095937  0.122248  0.231609  0.240379   0.030949   \n",
      "2308  0.191108  0.065973  0.065256  0.110434  0.130154  0.266404   0.117180   \n",
      "2309  0.229140  0.083768  0.088331  0.148631  0.137549  0.208279   0.033318   \n",
      "2310  0.116389  0.076166  0.092426  0.218228  0.202824  0.243047   0.090965   \n",
      "2311  0.065284  0.087858  0.093655  0.198902  0.369433  0.164430   0.024803   \n",
      "2312  0.110390  0.043207  0.057692  0.143357  0.166583  0.420829   0.046538   \n",
      "2313  0.099256  0.062416  0.110523  0.179247  0.201329  0.301149   0.109238   \n",
      "2314  0.102080  0.094691  0.098248  0.189655  0.188287  0.258621   0.202915   \n",
      "2315  0.091580  0.054401  0.071897  0.127392  0.156096  0.375615   0.114785   \n",
      "2316  0.130665  0.048590  0.076536  0.142497  0.164653  0.332326   0.110780   \n",
      "2317  0.156842  0.054737  0.055789  0.140000  0.156842  0.310526   0.044733   \n",
      "2318  0.253797  0.044015  0.075933  0.111969  0.154440  0.251223   0.045205   \n",
      "2319  0.122739  0.082687  0.085917  0.188630  0.289190  0.175280   0.011918   \n",
      "2320  0.257772  0.068653  0.081088  0.204922  0.108290  0.184456   0.158667   \n",
      "2321  0.139064  0.052411  0.085954  0.247379  0.147449  0.220126   0.238274   \n",
      "2322  0.255580  0.079241  0.083705  0.311384  0.104911  0.110491   0.350140   \n",
      "2323  0.208564  0.078039  0.060773  0.223066  0.131906  0.191298   0.328779   \n",
      "2324  0.207264  0.046228  0.068834  0.144780  0.151384  0.266701   0.080727   \n",
      "2325  0.236189  0.065798  0.071695  0.131906  0.137182  0.235878   0.077220   \n",
      "2326  0.122970  0.043310  0.047951  0.112916  0.112142  0.300851   0.043150   \n",
      "2327  0.398983  0.054092  0.067499  0.131761  0.103560  0.131299   0.304655   \n",
      "2328  0.092045  0.056227  0.069554  0.206164  0.270304  0.252395   0.073521   \n",
      "2329  0.164179  0.053011  0.089552  0.177046  0.190427  0.257334   0.027397   \n",
      "2330  0.173453  0.068783  0.085806  0.166552  0.152979  0.267081   0.050242   \n",
      "2331  0.197397  0.066368  0.094750  0.152796  0.201451  0.240504   0.021311   \n",
      "2332  0.179266  0.069114  0.079914  0.133909  0.133909  0.293737   0.038462   \n",
      "2333  0.166776  0.084701  0.081747  0.152659  0.173014  0.258700   0.074008   \n",
      "2334  0.144879  0.083558  0.080863  0.154313  0.140836  0.295148   0.017320   \n",
      "2335  0.213651  0.062762  0.061192  0.127354  0.150105  0.250523   0.016816   \n",
      "2336  0.107360  0.057416  0.094909  0.152048  0.179579  0.328445   0.044049   \n",
      "2337  0.121199  0.041703  0.074283  0.135534  0.203736  0.323632   0.032413   \n",
      "2338  0.194159  0.094105  0.047593  0.101677  0.129800  0.376420   0.032797   \n",
      "2339  0.046465  0.094429  0.123657  0.232576  0.315513  0.167125   0.024552   \n",
      "2340  0.087646  0.074213  0.135433  0.247743  0.202158  0.226382   0.022619   \n",
      "2341  0.116827  0.070192  0.088942  0.137981  0.149519  0.336538   0.051299   \n",
      "2342  0.120047  0.087070  0.079241  0.151839  0.138316  0.309371   0.024691   \n",
      "2343  0.219906  0.073476  0.073476  0.167535  0.119072  0.234758   0.070790   \n",
      "2344  0.074727  0.053578  0.083186  0.138527  0.136764  0.387734   0.138308   \n",
      "2345  0.285451  0.055249  0.075506  0.121547  0.095764  0.206262   0.106024   \n",
      "2346  0.127063  0.072607  0.061056  0.245875  0.123762  0.211221   0.215983   \n",
      "2347  0.145126  0.069003  0.098576  0.175246  0.160460  0.225082   0.113501   \n",
      "2348  0.105354  0.072539  0.065630  0.193437  0.145078  0.250432   0.174419   \n",
      "2349  0.103197  0.049777  0.074868  0.140834  0.187778  0.317280   0.124724   \n",
      "2350  0.201421  0.083995  0.081070  0.146678  0.134141  0.247388   0.088949   \n",
      "2351  0.275134  0.114605  0.086885  0.162598  0.132809  0.154737   0.107239   \n",
      "2352  0.103652  0.059613  0.088614  0.136950  0.132116  0.354995   0.083082   \n",
      "2353  0.143223  0.086957  0.106138  0.245524  0.153453  0.221228   0.058201   \n",
      "2354  0.187954  0.075472  0.071843  0.147315  0.195210  0.243832   0.107678   \n",
      "2355  0.228052  0.069610  0.075325  0.137143  0.145974  0.261818   0.141224   \n",
      "2356  0.118701  0.114222  0.085106  0.178052  0.225084  0.193729   0.011713   \n",
      "2357  0.120603  0.075935  0.082077  0.145729  0.166946  0.238414   0.043223   \n",
      "2358  0.201739  0.099130  0.071304  0.116522  0.132174  0.255652   0.149485   \n",
      "2359  0.193049  0.087521  0.092127  0.141122  0.152848  0.250000   0.006810   \n",
      "2360  0.121315  0.077381  0.093821  0.149093  0.132086  0.289116   0.044914   \n",
      "2361  0.157510  0.086926  0.100487  0.164117  0.154729  0.247914   0.054889   \n",
      "2362  0.190455  0.092797  0.102077  0.129032  0.121962  0.251436   0.019943   \n",
      "2363  0.308300  0.102767  0.130435  0.158103  0.116601  0.126482   0.218232   \n",
      "2364  0.253846  0.065934  0.068132  0.141758  0.140659  0.168132   0.277361   \n",
      "2365  0.163873  0.063935  0.090627  0.200497  0.157045  0.259466   0.171502   \n",
      "2366  0.219101  0.064607  0.071629  0.139045  0.171348  0.269663   0.112727   \n",
      "2367  0.129909  0.036254  0.024169  0.111782  0.214502  0.277946   0.032922   \n",
      "2368  0.167048  0.086957  0.091533  0.240275  0.116705  0.270023   0.154303   \n",
      "2369  0.186697  0.068783  0.092215  0.243386  0.103553  0.208617   0.103547   \n",
      "2370  0.267741  0.108075  0.096248  0.149674  0.164763  0.183320   0.006238   \n",
      "2371  0.195233  0.133939  0.103292  0.132804  0.133939  0.232690   0.067200   \n",
      "2372  0.139175  0.069588  0.085052  0.114691  0.115979  0.382732   0.236234   \n",
      "2373  0.252983  0.068019  0.064439  0.127685  0.112172  0.299523   0.097444   \n",
      "2374  0.241005  0.064494  0.069925  0.117447  0.120163  0.207060   0.046305   \n",
      "2375  0.150830  0.055351  0.075415  0.145526  0.178736  0.307887   0.105020   \n",
      "2376  0.209318  0.062239  0.081711  0.115786  0.091794  0.357441   0.046260   \n",
      "2377  0.090399  0.082811  0.104916  0.168261  0.192016  0.276476   0.011921   \n",
      "2378  0.067791  0.207193  0.087524  0.184278  0.327180  0.111076   0.003205   \n",
      "2379  0.115510  0.078210  0.080375  0.147876  0.151606  0.319937   0.036803   \n",
      "2380  0.090682  0.087770  0.089018  0.138519  0.188852  0.260399   0.022014   \n",
      "2381  0.143191  0.074560  0.090729  0.171757  0.174991  0.275422   0.063325   \n",
      "2382  0.093969  0.099805  0.132490  0.208171  0.143580  0.250195   0.077663   \n",
      "2383  0.144141  0.064770  0.102958  0.154249  0.140022  0.305504   0.084422   \n",
      "2384  0.186770  0.077821  0.105058  0.211414  0.103761  0.251621   0.064639   \n",
      "2385  0.138376  0.083026  0.095941  0.210332  0.162362  0.197417   0.027778   \n",
      "2386  0.132706  0.085684  0.115726  0.195664  0.176594  0.228840   0.081889   \n",
      "2387  0.080792  0.060991  0.103194  0.195404  0.180806  0.290071   0.074618   \n",
      "2388  0.106667  0.072222  0.092222  0.148333  0.141667  0.292778   0.104382   \n",
      "2389  0.176127  0.104341  0.131052  0.184474  0.139399  0.194491   0.063158   \n",
      "2390  0.108149  0.083397  0.122239  0.192688  0.183930  0.258949   0.080560   \n",
      "2391  0.084197  0.066926  0.107081  0.167530  0.148100  0.294473   0.129870   \n",
      "2392  0.152623  0.055114  0.093800  0.170111  0.195019  0.211977   0.030116   \n",
      "2393  0.313059  0.019320  0.055814  0.092665  0.218962  0.220036   0.004705   \n",
      "2394  0.171882  0.103628  0.105669  0.165079  0.244898  0.163719   0.009576   \n",
      "2395  0.269371  0.087967  0.062443  0.122607  0.211942  0.192799   0.002690   \n",
      "2396  0.093897  0.039571  0.057009  0.107981  0.450704  0.186452   0.004637   \n",
      "2397  0.035730  0.057345  0.076312  0.150860  0.583591  0.089546   0.000462   \n",
      "2398  0.075971  0.087226  0.057400  0.185144  0.440630  0.115926   0.004884   \n",
      "2399  0.095442  0.050570  0.073362  0.125356  0.333333  0.262108   0.009442   \n",
      "2400  0.352459  0.039617  0.065118  0.107923  0.111111  0.243169   0.038796   \n",
      "2401  0.235849  0.110063  0.066038  0.166667  0.119497  0.213836   0.102128   \n",
      "2402  0.182628  0.073497  0.060134  0.171492  0.180401  0.113586   0.015152   \n",
      "2403  0.187452  0.079783  0.092177  0.147947  0.118513  0.250968   0.135974   \n",
      "2404  0.118223  0.112923  0.075826  0.182634  0.238483  0.224215   0.056075   \n",
      "2405  0.200331  0.079470  0.073675  0.139901  0.161424  0.271523   0.099576   \n",
      "2406  0.150635  0.088929  0.112523  0.168784  0.136116  0.270417   0.061364   \n",
      "2407  0.237500  0.048077  0.065385  0.120833  0.144551  0.250321   0.024850   \n",
      "2408  0.389292  0.049909  0.053539  0.160617  0.117060  0.176044   0.037825   \n",
      "2409  0.313570  0.086957  0.084321  0.138340  0.061924  0.185771   0.036458   \n",
      "2410  0.230204  0.055430  0.061652  0.118213  0.145362  0.201923   0.022556   \n",
      "2411  0.180645  0.048094  0.073314  0.163050  0.161877  0.317889   0.033333   \n",
      "2412  0.313144  0.075106  0.060872  0.113568  0.162629  0.231072   0.010405   \n",
      "2413  0.184553  0.050407  0.073171  0.123577  0.200813  0.217886   0.011148   \n",
      "2414  0.224760  0.055889  0.066707  0.128005  0.198918  0.230769   0.011843   \n",
      "2415  0.199861  0.055170  0.063498  0.199514  0.160999  0.263706   0.156146   \n",
      "2416  0.119765  0.033501  0.065327  0.156198  0.454774  0.146566   0.009082   \n",
      "2417  0.351376  0.058716  0.044954  0.082569  0.244037  0.199083   0.004145   \n",
      "2418  0.107325  0.052811  0.119250  0.204429  0.201022  0.264055   0.021053   \n",
      "2419  0.077833  0.045186  0.077596  0.151408  0.178850  0.325290   0.025755   \n",
      "2420  0.156338  0.094366  0.081690  0.116901  0.091549  0.267606   0.098425   \n",
      "2421  0.268258  0.120318  0.064607  0.125468  0.147004  0.197097   0.041642   \n",
      "2422  0.080808  0.052750  0.101010  0.179012  0.143659  0.317059   0.027544   \n",
      "2423  0.146054  0.124853  0.077739  0.189635  0.195524  0.224971   0.077156   \n",
      "2424  0.187266  0.086142  0.111111  0.137328  0.099875  0.164794   0.049236   \n",
      "2425  0.098203  0.079790  0.060500  0.126260  0.124507  0.304253   0.021317   \n",
      "2426  0.120000  0.086000  0.068000  0.124000  0.115333  0.300667   0.066055   \n",
      "2427  0.223539  0.080440  0.089754  0.132091  0.103302  0.197290   0.068812   \n",
      "2428  0.096186  0.070481  0.098673  0.173300  0.154229  0.227197   0.043231   \n",
      "2429  0.198924  0.063940  0.089559  0.154575  0.128525  0.267600   0.115072   \n",
      "2430  0.060000  0.055000  0.075000  0.203333  0.223333  0.263333   0.027273   \n",
      "2431  0.152916  0.067568  0.086415  0.157895  0.126245  0.290541   0.109990   \n",
      "2432  0.121179  0.084283  0.108700  0.162235  0.353228  0.125701   0.021681   \n",
      "2433  0.195603  0.058196  0.072098  0.170061  0.183640  0.281604   0.034975   \n",
      "2434  0.209169  0.080229  0.085960  0.123209  0.126074  0.300860   0.101961   \n",
      "2435  0.248415  0.074555  0.078479  0.164503  0.153939  0.183218   0.140100   \n",
      "2436  0.230390  0.076883  0.071688  0.184156  0.115325  0.254545   0.168042   \n",
      "2437  0.219657  0.044078  0.071339  0.160852  0.223209  0.249634   0.026652   \n",
      "2438  0.333699  0.052266  0.066520  0.098684  0.144006  0.185673   0.147610   \n",
      "2439  0.285208  0.047500  0.063333  0.116042  0.234167  0.181250   0.106927   \n",
      "2440  0.250000  0.047840  0.074074  0.097222  0.097222  0.273148   0.056485   \n",
      "2441  0.156698  0.048146  0.069693  0.130396  0.222825  0.289397   0.010559   \n",
      "2442  0.188648  0.076516  0.072621  0.128269  0.147190  0.255704   0.121144   \n",
      "2443  0.154094  0.058992  0.051484  0.145871  0.208795  0.268859   0.047571   \n",
      "2444  0.236318  0.075456  0.093284  0.141376  0.160862  0.204395   0.249593   \n",
      "2445  0.215797  0.074753  0.107193  0.163611  0.170663  0.203103   0.111111   \n",
      "2446  0.146732  0.079146  0.069809  0.126278  0.156069  0.320142   0.057988   \n",
      "2447  0.319588  0.072634  0.052015  0.108716  0.151828  0.181350   0.008333   \n",
      "2448  0.137797  0.049491  0.073751  0.186803  0.161087  0.339156   0.112258   \n",
      "2449  0.173913  0.058439  0.091632  0.173446  0.158018  0.283777   0.136924   \n",
      "2450  0.161290  0.070693  0.090597  0.157172  0.170899  0.251201   0.117647   \n",
      "2451  0.279458  0.068368  0.070258  0.138311  0.136736  0.175488   0.200585   \n",
      "2452  0.220213  0.060638  0.068085  0.115957  0.138298  0.237234   0.104845   \n",
      "2453  0.179775  0.110530  0.090410  0.160178  0.220016  0.187092   0.041009   \n",
      "2454  0.151971  0.068459  0.073477  0.160036  0.133513  0.318638   0.025299   \n",
      "2455  0.145914  0.098054  0.083268  0.130739  0.187938  0.264981   0.010340   \n",
      "2456  0.232258  0.083871  0.094355  0.161290  0.116935  0.179839   0.005388   \n",
      "2457  0.147041  0.063758  0.086028  0.130567  0.150702  0.274558   0.009717   \n",
      "2458  0.170455  0.039773  0.105114  0.150568  0.127841  0.281250   0.113725   \n",
      "2459  0.143902  0.115610  0.126829  0.149268  0.175122  0.234634   0.050814   \n",
      "2460  0.130029  0.052443  0.105603  0.160920  0.145833  0.255747   0.015977   \n",
      "2461  0.117519  0.055495  0.056583  0.139282  0.134929  0.286181   0.022189   \n",
      "2462  0.110755  0.056045  0.078196  0.181212  0.203096  0.303977   0.017058   \n",
      "2463  0.096539  0.047359  0.054645  0.211293  0.222222  0.295082   0.012392   \n",
      "2464  0.163708  0.101578  0.106509  0.186391  0.145957  0.182446   0.052561   \n",
      "2465  0.054196  0.050699  0.083042  0.251748  0.201923  0.246503   0.023704   \n",
      "2466  0.126516  0.055459  0.051993  0.149047  0.201040  0.285962   0.032787   \n",
      "2467  0.278947  0.081579  0.128947  0.142105  0.131579  0.171053   0.014337   \n",
      "2468  0.114943  0.049261  0.085568  0.137749  0.142310  0.338259   0.011989   \n",
      "2469  0.067980  0.057179  0.102922  0.162008  0.168361  0.296061   0.016245   \n",
      "2470  0.119468  0.083141  0.140445  0.147096  0.217703  0.247122   0.078826   \n",
      "2471  0.202024  0.042510  0.058300  0.112955  0.126721  0.279757   0.012069   \n",
      "2472  0.198556  0.075812  0.075812  0.178700  0.072202  0.207581   0.042857   \n",
      "2473  0.077435  0.051262  0.070060  0.143880  0.153496  0.365845   0.032885   \n",
      "2474  0.244983  0.083737  0.073702  0.129758  0.133910  0.226990   0.058655   \n",
      "2475  0.223864  0.089398  0.064647  0.108607  0.100111  0.308460   0.106455   \n",
      "2476  0.246496  0.101197  0.076581  0.126154  0.124103  0.215726   0.069668   \n",
      "2477  0.167364  0.118550  0.075314  0.104603  0.093445  0.160391   0.055446   \n",
      "2478  0.218921  0.107115  0.095387  0.127443  0.116497  0.212666   0.110417   \n",
      "2479  0.181459  0.063222  0.065653  0.134650  0.203343  0.286930   0.041883   \n",
      "2480  0.138302  0.080292  0.066846  0.137149  0.155974  0.264310   0.005484   \n",
      "2481  0.188599  0.070346  0.060036  0.132201  0.120679  0.313523   0.018467   \n",
      "2482  0.138237  0.081081  0.083739  0.151972  0.142667  0.293753   0.006124   \n",
      "2483  0.065934  0.062271  0.078144  0.136142  0.155678  0.367521   0.021258   \n",
      "2484  0.041002  0.044039  0.062263  0.147304  0.162491  0.425209   0.027837   \n",
      "2485  0.084761  0.058611  0.087466  0.166817  0.143372  0.325518   0.034660   \n",
      "2486  0.195956  0.073889  0.067399  0.124314  0.245382  0.215427   0.032812   \n",
      "2487  0.093842  0.104594  0.110459  0.164223  0.134897  0.276637   0.034301   \n",
      "2488  0.180758  0.129738  0.113703  0.169096  0.135569  0.190962   0.009940   \n",
      "2489  0.046263  0.042705  0.145907  0.185053  0.192171  0.313167   0.025253   \n",
      "2490  0.116883  0.126160  0.080705  0.137291  0.149351  0.277365   0.006418   \n",
      "2491  0.181398  0.073484  0.085046  0.138232  0.115622  0.234841   0.015867   \n",
      "2492  0.223051  0.082090  0.065506  0.125207  0.092040  0.237148   0.091114   \n",
      "2493  0.132267  0.060800  0.093867  0.182933  0.153067  0.288533   0.138732   \n",
      "2494  0.145471  0.081885  0.080970  0.126258  0.180695  0.207228   0.056287   \n",
      "2495  0.186100  0.058614  0.068662  0.133975  0.130207  0.266485   0.056539   \n",
      "2496  0.137101  0.070120  0.108320  0.147043  0.120356  0.291470   0.018558   \n",
      "2497  0.083268  0.036622  0.050118  0.163378  0.220442  0.370008   0.086512   \n",
      "2498  0.186186  0.042042  0.099099  0.141141  0.129129  0.237237   0.015625   \n",
      "2499  0.138736  0.059066  0.059066  0.130495  0.129121  0.195055   0.074324   \n",
      "2500  0.280495  0.061270  0.062957  0.125913  0.098932  0.318718   0.104498   \n",
      "2501  0.153812  0.083711  0.098054  0.139617  0.150446  0.307186   0.033371   \n",
      "2502  0.082302  0.068854  0.102743  0.190963  0.172942  0.334588   0.352414   \n",
      "2503  0.149654  0.114619  0.104671  0.151817  0.158737  0.219723   0.029089   \n",
      "2504  0.242478  0.076991  0.102655  0.122124  0.119469  0.230088   0.080103   \n",
      "2505  0.210838  0.098361  0.123406  0.156193  0.122951  0.220401   0.054958   \n",
      "2506  0.098592  0.070423  0.042254  0.316901  0.211268  0.197183   0.023256   \n",
      "2507  0.269939  0.057102  0.064181  0.153374  0.226522  0.198679   0.013973   \n",
      "2508  0.209559  0.094669  0.077206  0.180147  0.176471  0.141544   0.017903   \n",
      "2509  0.276914  0.078407  0.074051  0.148724  0.145613  0.121344   0.013688   \n",
      "2510  0.131429  0.112381  0.066667  0.226667  0.131429  0.240000   0.017413   \n",
      "2511  0.240451  0.100694  0.084201  0.139757  0.144097  0.196181   0.076179   \n",
      "2512  0.199077  0.056691  0.081081  0.143705  0.271589  0.189848   0.014555   \n",
      "2513  0.092372  0.059482  0.082575  0.240728  0.162351  0.282715   0.087680   \n",
      "2514  0.125284  0.082135  0.084784  0.172975  0.170326  0.304315   0.063042   \n",
      "2515  0.059065  0.044463  0.079409  0.192617  0.218868  0.344709   0.054741   \n",
      "2516  0.158544  0.076923  0.099824  0.146800  0.179683  0.260716   0.047207   \n",
      "2517  0.132094  0.071689  0.071357  0.129107  0.147693  0.341188   0.014537   \n",
      "2518  0.084936  0.097756  0.092949  0.190705  0.158654  0.285256   0.062241   \n",
      "2519  0.151625  0.064982  0.097473  0.166065  0.335740  0.119134   0.044118   \n",
      "2520  0.152174  0.054348  0.078804  0.111413  0.336957  0.214674   0.017241   \n",
      "2521  0.202923  0.088564  0.078246  0.139295  0.140155  0.281169   0.011616   \n",
      "2522  0.130890  0.089005  0.069015  0.137554  0.187530  0.230366   0.046570   \n",
      "2523  0.183486  0.062181  0.077472  0.143731  0.197757  0.292559   0.021390   \n",
      "2524  0.293774  0.078980  0.100293  0.187213  0.122858  0.142081   0.157955   \n",
      "2525  0.134188  0.068225  0.083302  0.148134  0.166981  0.310969   0.054829   \n",
      "2526  0.084918  0.086277  0.087296  0.147079  0.296875  0.241848   0.008667   \n",
      "2527  0.180154  0.076108  0.063584  0.114644  0.132948  0.333333   0.018293   \n",
      "2528  0.191489  0.054010  0.058920  0.111293  0.260229  0.237316   0.064386   \n",
      "2529  0.189189  0.066472  0.086925  0.162162  0.235208  0.200877   0.025203   \n",
      "2530  0.145324  0.069784  0.077698  0.141727  0.181295  0.281295   0.010536   \n",
      "2531  0.217753  0.074896  0.081831  0.171983  0.165049  0.202497   0.012456   \n",
      "2532  0.238095  0.063716  0.072435  0.135480  0.228035  0.175050   0.031811   \n",
      "2533  0.287691  0.058267  0.065550  0.139840  0.209031  0.193008   0.018486   \n",
      "2534  0.099372  0.084053  0.102514  0.132364  0.191673  0.316182   0.025176   \n",
      "2535  0.298116  0.075348  0.108927  0.159705  0.126945  0.181818   0.134228   \n",
      "2536  0.175129  0.077999  0.111847  0.182487  0.186166  0.209713   0.024390   \n",
      "2537  0.305279  0.070219  0.086155  0.168327  0.141932  0.159363   0.046711   \n",
      "2538  0.256071  0.063950  0.076902  0.139773  0.230977  0.196168   0.014552   \n",
      "2539  0.090038  0.084291  0.252874  0.183908  0.260536  0.103448   0.009592   \n",
      "2540  0.039216  0.112745  0.107843  0.151961  0.460784  0.107843   0.005780   \n",
      "2541  0.253687  0.104720  0.070796  0.125369  0.162242  0.174041   0.000000   \n",
      "2542  0.087253  0.050360  0.069175  0.192769  0.184468  0.348829   0.037895   \n",
      "2543  0.056527  0.037560  0.056155  0.183711  0.199331  0.386017   0.061521   \n",
      "2544  0.175325  0.116883  0.045455  0.136364  0.168831  0.233766   0.009174   \n",
      "2545  0.140052  0.061518  0.075916  0.149215  0.138743  0.324607   0.155797   \n",
      "2546  0.166895  0.079343  0.101915  0.154583  0.213406  0.171683   0.037885   \n",
      "2547  0.166426  0.102453  0.091871  0.145262  0.200577  0.223665   0.024113   \n",
      "2548  0.139111  0.085519  0.094641  0.144242  0.216648  0.220068   0.036337   \n",
      "2549  0.128571  0.081319  0.091209  0.197802  0.130769  0.258242   0.065359   \n",
      "2550  0.259781  0.071987  0.089202  0.125196  0.161189  0.228482   0.017544   \n",
      "2551  0.108808  0.031088  0.072539  0.082902  0.165803  0.393782   0.014388   \n",
      "2552  0.163223  0.090909  0.082645  0.210744  0.183884  0.194215   0.012270   \n",
      "2553  0.098516  0.064688  0.078338  0.127596  0.165579  0.291395   0.014610   \n",
      "2554  0.154458  0.085810  0.082461  0.135203  0.205107  0.243198   0.005467   \n",
      "2555  0.150442  0.107670  0.094395  0.132743  0.289086  0.156342   0.036538   \n",
      "2556  0.062615  0.073665  0.042357  0.103131  0.429098  0.257827   0.004090   \n",
      "2557  0.140669  0.074398  0.072523  0.169428  0.192248  0.278837   0.033588   \n",
      "2558  0.082512  0.057882  0.097291  0.176108  0.211823  0.262315   0.023593   \n",
      "2559  0.108223  0.078515  0.078515  0.182493  0.165517  0.233422   0.024513   \n",
      "2560  0.033163  0.036990  0.088010  0.144133  0.246173  0.297194   0.017153   \n",
      "2561  0.229665  0.035885  0.063397  0.159091  0.178230  0.181818   0.009146   \n",
      "2562  0.102709  0.050790  0.074492  0.182844  0.276524  0.198646   0.025714   \n",
      "2563  0.077600  0.074800  0.096800  0.168400  0.360400  0.169600   0.002674   \n",
      "2564  0.051656  0.049007  0.075497  0.203974  0.201325  0.347020   0.028902   \n",
      "2565  0.197650  0.067035  0.093988  0.153421  0.212163  0.210090   0.017908   \n",
      "2566  0.049748  0.039661  0.078175  0.166667  0.216873  0.351903   0.023366   \n",
      "2567  0.140855  0.121934  0.081990  0.156973  0.339173  0.140855   0.036107   \n",
      "2568  0.120521  0.068404  0.068404  0.175896  0.182410  0.241042   0.019048   \n",
      "2569  0.047664  0.069590  0.134414  0.166826  0.317445  0.190658   0.005513   \n",
      "2570  0.119212  0.068966  0.092611  0.151724  0.181281  0.279803   0.061415   \n",
      "2571  0.140665  0.097187  0.125320  0.210997  0.156010  0.239130   0.122137   \n",
      "2572  0.042362  0.121951  0.127086  0.127086  0.439024  0.129653   0.015670   \n",
      "2573  0.096253  0.083979  0.076873  0.155685  0.200904  0.315891   0.102928   \n",
      "2574  0.094959  0.048652  0.120164  0.163540  0.159437  0.339977   0.087094   \n",
      "2575  0.112228  0.077052  0.122278  0.159966  0.195980  0.229481   0.053812   \n",
      "2576  0.166897  0.080000  0.105517  0.142759  0.131034  0.185517   0.082418   \n",
      "2577  0.130045  0.071749  0.079372  0.134529  0.295516  0.212108   0.006971   \n",
      "2578  0.137823  0.111198  0.086922  0.160532  0.220047  0.169930   0.004826   \n",
      "2579  0.130129  0.094959  0.116061  0.185229  0.198124  0.178195   0.006812   \n",
      "2580  0.144101  0.080271  0.088975  0.138298  0.244681  0.217602   0.023515   \n",
      "2581  0.171040  0.110787  0.107872  0.117590  0.214772  0.180758   0.005974   \n",
      "2582  0.132635  0.090712  0.093242  0.174196  0.193350  0.219733   0.016285   \n",
      "2583  0.178540  0.086192  0.090589  0.164908  0.198329  0.241865   0.014404   \n",
      "2584  0.177645  0.077844  0.143713  0.205589  0.205589  0.121756   0.024510   \n",
      "2585  0.223444  0.066346  0.066346  0.146786  0.205913  0.257133   0.020725   \n",
      "2586  0.206522  0.092391  0.122283  0.180707  0.131793  0.202446   0.030142   \n",
      "2587  0.173410  0.086430  0.107349  0.140930  0.169006  0.278282   0.021071   \n",
      "2588  0.217262  0.074405  0.091270  0.147817  0.177579  0.225198   0.046348   \n",
      "2589  0.176249  0.077078  0.088125  0.158674  0.201858  0.222948   0.015479   \n",
      "2590  0.145393  0.100592  0.096365  0.180051  0.217244  0.196112   0.064516   \n",
      "2591  0.145168  0.072391  0.072391  0.165191  0.192530  0.281864   0.041646   \n",
      "2592  0.171579  0.076504  0.089283  0.168172  0.146192  0.235815   0.183980   \n",
      "2593  0.179745  0.066398  0.077800  0.167002  0.155600  0.219316   0.083105   \n",
      "2594  0.241228  0.061404  0.089912  0.247807  0.098684  0.192982   0.031161   \n",
      "2595  0.065158  0.059005  0.082189  0.179321  0.180420  0.328096   0.035791   \n",
      "2596  0.220902  0.080391  0.077945  0.232786  0.119888  0.178609   0.294041   \n",
      "2597  0.154636  0.058773  0.089016  0.159201  0.203709  0.256776   0.115616   \n",
      "2598  0.139274  0.095050  0.105611  0.198680  0.196040  0.200660   0.117057   \n",
      "2599  0.121786  0.088633  0.094046  0.257781  0.161705  0.223275   0.178250   \n",
      "2600  0.150695  0.065201  0.082864  0.166291  0.164600  0.269072   0.192665   \n",
      "2601  0.120302  0.063547  0.113057  0.167245  0.183396  0.285887   0.117073   \n",
      "2602  0.149248  0.053831  0.071411  0.161979  0.150097  0.320563   0.310676   \n",
      "2603  0.154967  0.070492  0.096126  0.123507  0.153510  0.253131   0.015521   \n",
      "2604  0.263215  0.069267  0.090777  0.130149  0.133795  0.244623   0.060786   \n",
      "2605  0.065537  0.110169  0.103390  0.191525  0.309040  0.174011   0.057333   \n",
      "2606  0.101007  0.069640  0.083165  0.178129  0.208921  0.306763   0.027663   \n",
      "2607  0.106684  0.053671  0.080013  0.161673  0.137965  0.340797   0.060773   \n",
      "2608  0.113955  0.057504  0.071879  0.148668  0.154979  0.340112   0.243256   \n",
      "2609  0.124112  0.050483  0.057773  0.141061  0.185529  0.320211   0.090081   \n",
      "2610  0.062137  0.084041  0.106840  0.280733  0.199821  0.219937   0.057309   \n",
      "2611  0.145799  0.046747  0.069304  0.129781  0.147107  0.361556   0.050584   \n",
      "2612  0.099448  0.060773  0.104972  0.187845  0.168508  0.314917   0.127049   \n",
      "2613  0.170077  0.098226  0.089131  0.204184  0.136880  0.244657   0.222425   \n",
      "2614  0.124563  0.069267  0.098370  0.155413  0.168219  0.295111   0.228385   \n",
      "2615  0.146137  0.086534  0.089625  0.181015  0.189404  0.234437   0.148961   \n",
      "2616  0.071286  0.052967  0.080446  0.153724  0.211071  0.339705   0.260532   \n",
      "2617  0.094663  0.056730  0.086606  0.168849  0.163813  0.329641   0.199728   \n",
      "2618  0.142999  0.105263  0.085402  0.150943  0.222443  0.188679   0.038835   \n",
      "2619  0.062278  0.085570  0.120506  0.169620  0.396709  0.145063   0.031306   \n",
      "2620  0.156863  0.140820  0.137255  0.181818  0.162210  0.133690   0.038278   \n",
      "2621  0.326733  0.100424  0.050919  0.147100  0.099010  0.226308   0.003571   \n",
      "2622  0.139535  0.065426  0.087442  0.178605  0.150388  0.269147   0.051977   \n",
      "2623  0.124214  0.081761  0.091195  0.103774  0.168239  0.261006   0.020492   \n",
      "2624  0.091228  0.080702  0.101754  0.201316  0.170175  0.263596   0.112507   \n",
      "2625  0.107412  0.074121  0.072236  0.156407  0.150126  0.342337   0.178451   \n",
      "2626  0.194429  0.071309  0.110864  0.150975  0.120891  0.213370   0.048338   \n",
      "2627  0.117363  0.071275  0.095927  0.152733  0.164523  0.309218   0.043051   \n",
      "2628  0.056919  0.059806  0.094452  0.220664  0.188699  0.361518   0.021148   \n",
      "2629  0.240115  0.058231  0.064702  0.113587  0.159597  0.315600   0.146089   \n",
      "2630  0.170333  0.055838  0.054146  0.164693  0.178229  0.314157   0.085672   \n",
      "2631  0.067742  0.053226  0.077419  0.167742  0.185484  0.216129   0.189189   \n",
      "2632  0.216257  0.055196  0.071583  0.134756  0.256792  0.217335   0.031457   \n",
      "2633  0.243902  0.069106  0.089431  0.207317  0.146341  0.180894   0.248000   \n",
      "2634  0.212928  0.074144  0.084791  0.142586  0.151711  0.252471   0.158549   \n",
      "2635  0.151844  0.040130  0.052603  0.114967  0.148048  0.376356   0.094301   \n",
      "2636  0.148917  0.054603  0.068141  0.163809  0.132220  0.346119   0.012164   \n",
      "2637  0.255102  0.068878  0.121599  0.154762  0.164966  0.155612   0.003058   \n",
      "2638  0.108856  0.071956  0.101476  0.193727  0.215867  0.232472   0.138381   \n",
      "2639  0.406061  0.048485  0.052525  0.137374  0.125253  0.163636   0.139785   \n",
      "2640  0.207175  0.094170  0.093274  0.104933  0.230493  0.155157   0.018450   \n",
      "2641  0.219765  0.082885  0.087667  0.121737  0.119546  0.244869   0.027785   \n",
      "2642  0.246719  0.078365  0.072366  0.116235  0.154481  0.217473   0.006606   \n",
      "2643  0.133929  0.049745  0.063776  0.098214  0.134566  0.254464   0.039788   \n",
      "2644  0.147488  0.087520  0.113452  0.249595  0.131280  0.189627   0.031818   \n",
      "2645  0.156080  0.092559  0.070780  0.132486  0.163339  0.268603   0.005102   \n",
      "2646  0.174057  0.075447  0.094639  0.125083  0.152879  0.260093   0.043141   \n",
      "2647  0.228169  0.092958  0.092019  0.137089  0.238498  0.168075   0.019080   \n",
      "2648  0.070521  0.054323  0.083728  0.196113  0.180912  0.362322   0.074167   \n",
      "2649  0.090411  0.108415  0.117417  0.217613  0.263405  0.166732   0.005322   \n",
      "2650  0.131027  0.052113  0.085437  0.208735  0.273327  0.227950   0.023741   \n",
      "2651  0.102312  0.067321  0.105586  0.154287  0.179660  0.326990   0.165104   \n",
      "2652  0.191718  0.096511  0.110205  0.147049  0.153570  0.230844   0.033037   \n",
      "2653  0.258639  0.051657  0.062700  0.109369  0.204489  0.230851   0.033853   \n",
      "2654  0.215862  0.071556  0.075730  0.149076  0.136553  0.227788   0.048451   \n",
      "2655  0.082974  0.081897  0.081897  0.171336  0.156250  0.290948   0.126959   \n",
      "2656  0.290433  0.104784  0.120729  0.119590  0.211845  0.126424   0.001414   \n",
      "2657  0.114861  0.072232  0.094731  0.164890  0.167555  0.278271   0.010526   \n",
      "2658  0.093396  0.069949  0.095350  0.149277  0.323955  0.209457   0.024435   \n",
      "2659  0.157985  0.067464  0.095645  0.119556  0.192997  0.271563   0.007937   \n",
      "2660  0.138501  0.068615  0.054638  0.176620  0.177891  0.331639   0.015000   \n",
      "2661  0.179916  0.041841  0.066946  0.146444  0.313808  0.225941   0.011494   \n",
      "2662  0.107516  0.064704  0.113841  0.152031  0.292143  0.209681   0.004678   \n",
      "2663  0.106383  0.057597  0.094778  0.139050  0.176660  0.342360   0.014693   \n",
      "2664  0.152988  0.064542  0.082869  0.168127  0.191633  0.263347   0.028716   \n",
      "2665  0.171300  0.070535  0.096247  0.193885  0.245657  0.190757   0.012168   \n",
      "2666  0.114570  0.080324  0.119552  0.176214  0.223537  0.252179   0.019776   \n",
      "2667  0.156713  0.078118  0.102007  0.159818  0.176780  0.250358   0.071729   \n",
      "2668  0.094118  0.090323  0.091082  0.147249  0.340038  0.185958   0.047619   \n",
      "2669  0.153585  0.067547  0.086604  0.136792  0.175472  0.302830   0.048892   \n",
      "2670  0.087660  0.070638  0.070213  0.133617  0.136596  0.319149   0.025761   \n",
      "2671  0.089436  0.076150  0.076474  0.156837  0.141283  0.295528   0.066180   \n",
      "2672  0.168169  0.077358  0.096865  0.155926  0.173012  0.262747   0.087231   \n",
      "2673  0.126260  0.071051  0.083533  0.145463  0.199232  0.269323   0.041370   \n",
      "2674  0.136798  0.068100  0.085424  0.147551  0.185783  0.243728   0.073859   \n",
      "2675  0.209681  0.057642  0.070094  0.136172  0.195220  0.253665   0.028737   \n",
      "2676  0.123834  0.060503  0.074357  0.150975  0.154934  0.342805   0.138423   \n",
      "2677  0.180613  0.073737  0.103563  0.176471  0.206297  0.205468   0.041295   \n",
      "2678  0.265531  0.033743  0.057080  0.110375  0.165563  0.284137   0.321871   \n",
      "2679  0.097317  0.043324  0.083414  0.145167  0.177174  0.302296   0.034542   \n",
      "2680  0.129283  0.080997  0.068536  0.132399  0.130062  0.306075   0.008457   \n",
      "2681  0.131868  0.072527  0.070330  0.204396  0.171429  0.296703   0.020548   \n",
      "2682  0.396226  0.147170  0.105660  0.128302  0.094340  0.079245   0.014563   \n",
      "2683  0.103313  0.061988  0.081226  0.171714  0.236551  0.281796   0.063168   \n",
      "2684  0.143625  0.074501  0.069892  0.182028  0.139017  0.334869   0.126461   \n",
      "2685  0.412752  0.040268  0.057047  0.114094  0.097315  0.124161   0.028926   \n",
      "2686  0.258803  0.053435  0.051711  0.107363  0.213987  0.248215   0.014921   \n",
      "2687  0.124611  0.049844  0.067497  0.135341  0.178262  0.340948   0.122905   \n",
      "2688  0.232574  0.069705  0.079759  0.136729  0.097185  0.280161   0.062670   \n",
      "2689  0.167890  0.082569  0.082569  0.155046  0.176147  0.243119   0.020359   \n",
      "2690  0.175836  0.071747  0.079182  0.138662  0.152788  0.272119   0.021576   \n",
      "2691  0.175056  0.049220  0.068820  0.139198  0.173274  0.303118   0.030964   \n",
      "2692  0.102626  0.062582  0.075711  0.134792  0.166521  0.324726   0.014938   \n",
      "2693  0.135266  0.060386  0.067633  0.137681  0.173913  0.264493   0.044164   \n",
      "2694  0.138476  0.066914  0.068773  0.184015  0.141264  0.246283   0.069009   \n",
      "2695  0.172414  0.055172  0.048276  0.158621  0.137931  0.165517   0.100917   \n",
      "2696  0.111628  0.052972  0.097674  0.156331  0.193798  0.334109   0.046948   \n",
      "2697  0.206148  0.133816  0.068716  0.137432  0.101266  0.182640   0.023077   \n",
      "2698  0.179656  0.077570  0.095865  0.131723  0.139407  0.251006   0.065789   \n",
      "2699  0.206107  0.129771  0.108991  0.163274  0.189143  0.153944   0.002592   \n",
      "2700  0.116222  0.080613  0.103858  0.167656  0.221563  0.224530   0.009786   \n",
      "2701  0.286032  0.055160  0.074288  0.113434  0.117883  0.189947   0.021191   \n",
      "2702  0.156677  0.088328  0.135647  0.180336  0.154048  0.197687   0.079208   \n",
      "2703  0.093565  0.086367  0.084674  0.168925  0.142252  0.292972   0.049355   \n",
      "2704  0.188203  0.097012  0.084206  0.131548  0.176562  0.247187   0.043303   \n",
      "2705  0.204740  0.049990  0.063931  0.115714  0.216092  0.291974   0.011106   \n",
      "2706  0.122885  0.052093  0.068121  0.119768  0.158949  0.324577   0.016880   \n",
      "2707  0.213740  0.081107  0.071565  0.141221  0.116412  0.281489   0.005472   \n",
      "2708  0.224687  0.047782  0.060296  0.110922  0.138225  0.259954   0.055762   \n",
      "2709  0.168919  0.043919  0.077703  0.199324  0.195946  0.243243   0.013274   \n",
      "2710  0.192351  0.061867  0.111361  0.176603  0.165354  0.226097   0.021307   \n",
      "2711  0.152281  0.111579  0.094737  0.120000  0.206316  0.230175   0.009458   \n",
      "2712  0.192140  0.061135  0.082969  0.140830  0.172489  0.201965   0.038615   \n",
      "2713  0.277145  0.084583  0.077984  0.140372  0.149370  0.215357   0.047050   \n",
      "2714  0.214489  0.090131  0.097547  0.144324  0.120936  0.247005   0.002096   \n",
      "2715  0.091099  0.068846  0.077191  0.139082  0.247566  0.293463   0.044505   \n",
      "2716  0.116848  0.078804  0.108696  0.173913  0.176630  0.255435   0.049822   \n",
      "2717  0.099788  0.076433  0.057325  0.157113  0.333333  0.205945   0.002591   \n",
      "2718  0.134571  0.097448  0.099768  0.143852  0.359629  0.139211   0.024523   \n",
      "2719  0.192821  0.105175  0.085142  0.207012  0.186144  0.158598   0.012917   \n",
      "2720  0.160089  0.096720  0.106726  0.173986  0.156198  0.237910   0.033358   \n",
      "2721  0.059424  0.057567  0.086815  0.146240  0.153203  0.366295   0.020873   \n",
      "2722  0.164747  0.082949  0.105991  0.145161  0.186636  0.207373   0.005658   \n",
      "2723  0.088534  0.079100  0.137881  0.187954  0.373730  0.108128   0.004337   \n",
      "2724  0.039012  0.101430  0.089727  0.312094  0.263979  0.158648   0.030374   \n",
      "2725  0.110901  0.060982  0.081489  0.167836  0.162979  0.305720   0.018645   \n",
      "2726  0.228253  0.067502  0.096033  0.167015  0.173278  0.189979   0.097470   \n",
      "2727  0.143599  0.094946  0.083609  0.161077  0.136986  0.291450   0.034860   \n",
      "2728  0.147488  0.172609  0.144787  0.219881  0.117234  0.148838   0.007862   \n",
      "2729  0.046784  0.116959  0.201754  0.274854  0.178363  0.158626   0.003331   \n",
      "2730  0.053057  0.102312  0.128761  0.281121  0.220304  0.173741   0.008324   \n",
      "2731  0.112043  0.057397  0.084393  0.167344  0.174944  0.335212   0.283620   \n",
      "2732  0.148185  0.082157  0.112399  0.212198  0.254536  0.169355   0.029597   \n",
      "2733  0.209546  0.077416  0.108847  0.218859  0.190338  0.147264   0.033689   \n",
      "2734  0.143921  0.119107  0.111663  0.263027  0.213400  0.101737   0.008097   \n",
      "2735  0.176900  0.082229  0.081958  0.136327  0.122802  0.314309   0.077415   \n",
      "2736  0.289906  0.056235  0.074397  0.156479  0.110024  0.227733   0.059572   \n",
      "2737  0.202658  0.119601  0.126246  0.146179  0.142857  0.205980   0.000000   \n",
      "2738  0.211736  0.072742  0.063548  0.131422  0.176312  0.276636   0.015576   \n",
      "2739  0.155830  0.071879  0.086694  0.147051  0.156379  0.261180   0.082267   \n",
      "2740  0.127669  0.082835  0.081127  0.165243  0.176772  0.278395   0.057971   \n",
      "2741  0.099707  0.067449  0.064516  0.202346  0.175953  0.161290   0.061674   \n",
      "2742  0.113422  0.068263  0.093258  0.145558  0.133375  0.310019   0.020099   \n",
      "2743  0.107504  0.053752  0.088877  0.132517  0.121341  0.324109   0.053662   \n",
      "2744  0.088581  0.046094  0.062844  0.158821  0.184864  0.387150   0.057652   \n",
      "2745  0.145812  0.064116  0.064116  0.143744  0.180972  0.287487   0.019444   \n",
      "2746  0.120525  0.140811  0.130072  0.169451  0.208831  0.189737   0.010782   \n",
      "2747  0.158009  0.080952  0.081818  0.144156  0.222944  0.221212   0.028460   \n",
      "2748  0.194493  0.077797  0.092220  0.165210  0.152535  0.208479   0.134469   \n",
      "2749  0.076854  0.061124  0.087865  0.161348  0.276854  0.293708   0.063713   \n",
      "2750  0.233405  0.085653  0.100642  0.171306  0.175589  0.211991   0.093220   \n",
      "2751  0.042791  0.049302  0.083721  0.191628  0.236279  0.247442   0.117419   \n",
      "2752  0.260496  0.077948  0.082533  0.186130  0.156183  0.178106   0.278896   \n",
      "\n",
      "      주말청소년고객비율  주중청년1고객비율  주말청년1고객비율  주중청년2고객비율  주말청년2고객비율  주중장년고객비율  \\\n",
      "0      0.042254   0.397490   0.470657   0.372908   0.333333  0.191423   \n",
      "1      0.226438   0.215330   0.276622   0.115640   0.155447  0.364643   \n",
      "2      0.269209   0.220396   0.246443   0.211455   0.155948  0.346786   \n",
      "3      0.129845   0.265379   0.191860   0.267525   0.284884  0.304006   \n",
      "4      0.400000   0.188525   0.224719   0.073770   0.078652  0.218579   \n",
      "5      0.238227   0.250698   0.286704   0.200457   0.157895  0.295864   \n",
      "6      0.230238   0.215107   0.263239   0.152117   0.118189  0.368008   \n",
      "7      0.173397   0.236902   0.225653   0.223994   0.304038  0.328778   \n",
      "8      0.215539   0.237317   0.295739   0.232158   0.238095  0.225279   \n",
      "9      0.180534   0.243533   0.288854   0.160566   0.167975  0.268424   \n",
      "10     0.106494   0.274461   0.262338   0.201493   0.187013  0.310945   \n",
      "11     0.198718   0.302400   0.256410   0.140800   0.173077  0.185600   \n",
      "12     0.050710   0.332095   0.286004   0.364042   0.342799  0.202823   \n",
      "13     0.184783   0.187715   0.361413   0.082664   0.119565  0.244546   \n",
      "14     0.116769   0.250116   0.254609   0.230858   0.198420  0.378422   \n",
      "15     0.165414   0.229199   0.233083   0.211931   0.274436  0.320251   \n",
      "16     0.469779   0.185013   0.192580   0.119561   0.076282  0.258274   \n",
      "17     0.227620   0.221274   0.213740   0.143554   0.114504  0.410546   \n",
      "18     0.177249   0.329897   0.272487   0.309278   0.248677  0.191294   \n",
      "19     0.051159   0.410210   0.409273   0.288666   0.310951  0.194774   \n",
      "20     0.087302   0.273273   0.309524   0.321321   0.365079  0.249249   \n",
      "21     0.072917   0.252101   0.166667   0.226891   0.218750  0.294118   \n",
      "22     0.192661   0.219251   0.100917   0.128342   0.165138  0.443850   \n",
      "23     0.032738   0.267176   0.273810   0.332061   0.386905  0.320611   \n",
      "24     0.090323   0.253388   0.229032   0.268293   0.325806  0.355014   \n",
      "25     0.102703   0.330059   0.389189   0.190570   0.167568  0.361493   \n",
      "26     0.013477   0.375272   0.477089   0.217320   0.245283  0.340959   \n",
      "27     0.014337   0.284907   0.397849   0.342211   0.344086  0.321227   \n",
      "28     0.150943   0.206704   0.188679   0.217877   0.113208  0.446927   \n",
      "29     0.112462   0.268608   0.346505   0.171521   0.158055  0.271845   \n",
      "30     0.078652   0.308257   0.342697   0.302752   0.292135  0.190826   \n",
      "31     0.041494   0.284951   0.381743   0.296527   0.319502  0.389136   \n",
      "32     0.037801   0.335854   0.374570   0.301197   0.293814  0.251418   \n",
      "33     0.115152   0.281367   0.275758   0.221570   0.295455  0.327816   \n",
      "34     0.029070   0.336088   0.308140   0.349862   0.418605  0.190083   \n",
      "35     0.043062   0.321637   0.291866   0.333333   0.296651  0.159844   \n",
      "36     0.129630   0.146679   0.267490   0.359182   0.226337  0.385032   \n",
      "37     0.061618   0.253929   0.273942   0.311855   0.330364  0.330265   \n",
      "38     0.120332   0.160851   0.165975   0.312340   0.253112  0.349787   \n",
      "39     0.027363   0.297628   0.373134   0.270849   0.303483  0.312930   \n",
      "40     0.105195   0.291283   0.331169   0.275077   0.279221  0.341656   \n",
      "41     0.057549   0.353118   0.380501   0.330416   0.343263  0.224836   \n",
      "42     0.037677   0.248197   0.274725   0.335337   0.378336  0.299279   \n",
      "43     0.120968   0.163090   0.221774   0.301860   0.245968  0.343348   \n",
      "44     0.084967   0.192015   0.189542   0.161597   0.215686  0.368821   \n",
      "45     0.020353   0.263879   0.362280   0.396346   0.389417  0.308855   \n",
      "46     0.196262   0.195980   0.228037   0.185930   0.173832  0.361091   \n",
      "47     0.155660   0.229167   0.339623   0.327652   0.146226  0.297348   \n",
      "48     0.423410   0.277276   0.273121   0.121612   0.093931  0.250174   \n",
      "49     0.095588   0.171745   0.139706   0.116343   0.169118  0.448753   \n",
      "50     0.099338   0.084367   0.165563   0.163772   0.185430  0.578164   \n",
      "51     0.223529   0.235556   0.188235   0.240000   0.258824  0.351111   \n",
      "52     0.206897   0.237003   0.224138   0.226300   0.206897  0.327217   \n",
      "53     0.116541   0.201176   0.266917   0.184706   0.195489  0.437647   \n",
      "54     0.084746   0.309091   0.271186   0.410909   0.440678  0.218182   \n",
      "55     0.101695   0.292146   0.296112   0.317731   0.309571  0.233637   \n",
      "56     0.086410   0.301614   0.366064   0.342710   0.285153  0.245597   \n",
      "57     0.127273   0.189869   0.255556   0.238786   0.194949  0.463650   \n",
      "58     0.089504   0.263908   0.343207   0.283065   0.242756  0.354176   \n",
      "59     0.102775   0.326293   0.372080   0.324102   0.282770  0.250131   \n",
      "60     0.127072   0.193399   0.276243   0.299363   0.331492  0.259988   \n",
      "61     0.071565   0.296970   0.349237   0.345688   0.355916  0.265268   \n",
      "62     0.055085   0.391045   0.399718   0.306468   0.300847  0.206965   \n",
      "63     0.037009   0.326061   0.341390   0.388485   0.424471  0.223030   \n",
      "64     0.062718   0.271975   0.334495   0.304033   0.320557  0.319545   \n",
      "65     0.030055   0.417226   0.336066   0.326622   0.445355  0.192394   \n",
      "66     0.009119   0.169546   0.212766   0.372361   0.340426  0.400512   \n",
      "67     0.085714   0.205725   0.163265   0.307692   0.314286  0.336315   \n",
      "68     0.144790   0.314350   0.346414   0.230493   0.231394  0.318386   \n",
      "69     0.078153   0.250266   0.374778   0.291711   0.230906  0.306057   \n",
      "70     0.033784   0.361275   0.456757   0.387745   0.325676  0.208333   \n",
      "71     0.036166   0.345741   0.378843   0.366868   0.381555  0.226023   \n",
      "72     0.111111   0.178571   0.244444   0.231092   0.207407  0.455882   \n",
      "73     0.061381   0.317017   0.320972   0.314518   0.350384  0.247032   \n",
      "74     0.021798   0.259234   0.237057   0.358413   0.356948  0.286594   \n",
      "75     0.009119   0.216216   0.246201   0.485521   0.471125  0.196911   \n",
      "76     0.087447   0.261006   0.246827   0.316352   0.282087  0.280503   \n",
      "77     0.045010   0.298590   0.284410   0.340886   0.307893  0.268379   \n",
      "78     0.026876   0.281440   0.266517   0.281440   0.318029  0.348761   \n",
      "79     0.037344   0.233123   0.263485   0.232223   0.259336  0.419442   \n",
      "80     0.029876   0.383277   0.486307   0.357644   0.309544  0.210558   \n",
      "81     0.130199   0.266736   0.325497   0.225221   0.292948  0.226258   \n",
      "82     0.254219   0.225451   0.217300   0.257181   0.227848  0.281563   \n",
      "83     0.120594   0.251735   0.304267   0.261830   0.235622  0.293375   \n",
      "84     0.052632   0.100000   0.157895   0.375000   0.431579  0.410714   \n",
      "85     0.101467   0.316494   0.327628   0.291451   0.297066  0.280656   \n",
      "86     0.084590   0.296783   0.359296   0.318881   0.277219  0.269371   \n",
      "87     0.039959   0.302687   0.342213   0.262612   0.268443  0.301273   \n",
      "88     0.036161   0.394932   0.389430   0.391224   0.378303  0.182324   \n",
      "89     0.057343   0.347759   0.372028   0.339001   0.304895  0.216383   \n",
      "90     0.021583   0.383110   0.282974   0.213182   0.306954  0.317199   \n",
      "91     0.082596   0.308108   0.356932   0.190270   0.188791  0.307027   \n",
      "92     0.164251   0.155499   0.260870   0.155499   0.144928  0.285714   \n",
      "93     0.067204   0.366391   0.325269   0.179063   0.212366  0.266758   \n",
      "94     0.046543   0.328061   0.356383   0.232143   0.238032  0.317857   \n",
      "95     0.109515   0.335177   0.369838   0.212821   0.236086  0.312398   \n",
      "96     0.096515   0.255132   0.206434   0.200391   0.219839  0.365591   \n",
      "97     0.092308   0.329795   0.349451   0.203184   0.197802  0.313116   \n",
      "98     0.028763   0.426941   0.410355   0.270151   0.254075  0.245859   \n",
      "99     0.038031   0.352386   0.398210   0.335984   0.250559  0.270875   \n",
      "100    0.051948   0.329753   0.334416   0.218045   0.224026  0.311493   \n",
      "101    0.034274   0.347674   0.427419   0.265827   0.228831  0.329136   \n",
      "102    0.071856   0.529887   0.293413   0.109855   0.167665  0.231018   \n",
      "103    0.153690   0.299535   0.283969   0.144909   0.174555  0.305661   \n",
      "104    0.129730   0.324364   0.261261   0.234182   0.210811  0.298182   \n",
      "105    0.028272   0.375386   0.440838   0.372060   0.328796  0.215253   \n",
      "106    0.100962   0.283368   0.365385   0.182752   0.187500  0.386037   \n",
      "107    0.089754   0.394020   0.410643   0.215893   0.215647  0.259009   \n",
      "108    0.151282   0.279070   0.330769   0.235592   0.210256  0.304348   \n",
      "109    0.072513   0.242939   0.278246   0.235941   0.230185  0.360660   \n",
      "110    0.109496   0.358913   0.350775   0.234213   0.227713  0.257794   \n",
      "111    0.043912   0.226672   0.255489   0.277002   0.271457  0.359662   \n",
      "112    0.219917   0.241749   0.265560   0.124587   0.093361  0.353960   \n",
      "113    0.182203   0.295989   0.402542   0.114799   0.139831  0.275242   \n",
      "114    0.144144   0.294118   0.310811   0.294118   0.288288  0.195502   \n",
      "115    0.081699   0.381595   0.316993   0.296933   0.290850  0.187730   \n",
      "116    0.142857   0.234783   0.201681   0.275362   0.310924  0.362319   \n",
      "117    0.089716   0.289773   0.223195   0.178030   0.199125  0.297348   \n",
      "118    0.088660   0.163575   0.191753   0.227656   0.228866  0.395447   \n",
      "119    0.061069   0.216981   0.160305   0.292453   0.229008  0.271226   \n",
      "120    0.055838   0.256162   0.286802   0.231514   0.213198  0.440141   \n",
      "121    0.114320   0.149828   0.203369   0.320848   0.208183  0.389354   \n",
      "122    0.110169   0.241973   0.286925   0.254093   0.246368  0.351265   \n",
      "123    0.026352   0.482627   0.495146   0.286054   0.291262  0.160876   \n",
      "124    0.028037   0.370370   0.439252   0.399691   0.406542  0.213735   \n",
      "125    0.013793   0.216867   0.289655   0.600402   0.489655  0.171687   \n",
      "126    0.009836   0.410571   0.465574   0.390655   0.344262  0.171582   \n",
      "127    0.037037   0.291536   0.398148   0.235110   0.388889  0.407524   \n",
      "128    0.029070   0.221106   0.360465   0.420436   0.308140  0.242881   \n",
      "129    0.059908   0.200215   0.271889   0.400431   0.410138  0.315393   \n",
      "130    0.003521   0.246377   0.320423   0.434783   0.397887  0.296196   \n",
      "131    0.056075   0.215152   0.205607   0.290909   0.205607  0.424242   \n",
      "132    0.000000   0.268887   0.365314   0.448146   0.413284  0.256868   \n",
      "133    0.058723   0.413291   0.453617   0.349980   0.328511  0.173810   \n",
      "134    0.114385   0.257834   0.327556   0.259483   0.266898  0.352941   \n",
      "135    0.042105   0.334758   0.371429   0.326686   0.323308  0.215100   \n",
      "136    0.090909   0.253165   0.333333   0.177215   0.030303  0.417722   \n",
      "137    0.032051   0.264516   0.333333   0.313978   0.282051  0.223656   \n",
      "138    0.010870   0.377778   0.429348   0.387654   0.288043  0.202469   \n",
      "139    0.022152   0.257171   0.386076   0.354105   0.278481  0.287834   \n",
      "140    0.031429   0.121690   0.148571   0.346154   0.328571  0.462799   \n",
      "141    0.045872   0.209544   0.275229   0.360996   0.392202  0.396957   \n",
      "142    0.008850   0.226804   0.389381   0.348454   0.371681  0.377320   \n",
      "143    0.000000   0.215962   0.170588   0.382629   0.282353  0.293427   \n",
      "144    0.030928   0.233333   0.254296   0.312963   0.336770  0.350000   \n",
      "145    0.024845   0.197406   0.254658   0.321326   0.304348  0.348703   \n",
      "146    0.105263   0.210641   0.244361   0.337676   0.327068  0.370250   \n",
      "147    0.056266   0.231837   0.289003   0.357242   0.337596  0.315132   \n",
      "148    0.000000   0.025641   0.076923   0.205128   0.153846  0.623932   \n",
      "149    0.020833   0.220280   0.259259   0.375874   0.333333  0.328671   \n",
      "150    0.030806   0.241935   0.260664   0.270528   0.289100  0.414223   \n",
      "151    0.022472   0.203976   0.296629   0.312224   0.420225  0.409426   \n",
      "152    0.030303   0.295520   0.358586   0.364156   0.376263  0.294566   \n",
      "153    0.028369   0.230932   0.248227   0.381356   0.354610  0.332627   \n",
      "154    0.034014   0.284153   0.367347   0.299180   0.306122  0.337432   \n",
      "155    0.054313   0.300529   0.376997   0.293122   0.287540  0.339683   \n",
      "156    0.033019   0.190265   0.183962   0.268437   0.235849  0.417404   \n",
      "157    0.023585   0.192964   0.330189   0.337953   0.254717  0.400320   \n",
      "158    0.142157   0.320755   0.348039   0.218868   0.205882  0.300000   \n",
      "159    0.023234   0.241108   0.343866   0.323261   0.344796  0.359459   \n",
      "160    0.000000   0.211215   0.176056   0.390654   0.295775  0.325234   \n",
      "161    0.136364   0.237370   0.233471   0.153168   0.136364  0.402566   \n",
      "162    0.022792   0.438127   0.444444   0.169454   0.168091  0.284281   \n",
      "163    0.056893   0.229872   0.242888   0.291132   0.304158  0.351225   \n",
      "164    0.021053   0.222420   0.205263   0.240214   0.268421  0.414591   \n",
      "165    0.025472   0.179312   0.254717   0.331344   0.303774  0.372549   \n",
      "166    0.047170   0.268775   0.283019   0.347826   0.377358  0.264822   \n",
      "167    0.037037   0.254032   0.251852   0.274194   0.237037  0.405242   \n",
      "168    0.021067   0.175481   0.242978   0.347596   0.348315  0.405288   \n",
      "169    0.050100   0.391464   0.458918   0.311258   0.298597  0.227373   \n",
      "170    0.045105   0.320101   0.360836   0.340310   0.319032  0.224468   \n",
      "171    0.028698   0.489416   0.439294   0.248877   0.302428  0.178961   \n",
      "172    0.030812   0.468401   0.504202   0.298327   0.299720  0.196097   \n",
      "173    0.023443   0.637866   0.679839   0.192454   0.162760  0.137531   \n",
      "174    0.059296   0.240257   0.251759   0.217918   0.231156  0.383793   \n",
      "175    0.053471   0.294843   0.352720   0.359696   0.332083  0.266055   \n",
      "176    0.048996   0.302349   0.379920   0.364486   0.331727  0.240717   \n",
      "177    0.055767   0.395522   0.369455   0.233065   0.217997  0.252009   \n",
      "178    0.015306   0.562016   0.530612   0.292248   0.306122  0.108527   \n",
      "179    0.091049   0.316705   0.317901   0.245940   0.195988  0.311485   \n",
      "180    0.073499   0.449740   0.436853   0.248700   0.213251  0.211005   \n",
      "181    0.031297   0.425037   0.436662   0.306779   0.299553  0.170213   \n",
      "182    0.105578   0.308385   0.400398   0.230076   0.181275  0.309078   \n",
      "183    0.040248   0.307910   0.263158   0.255179   0.368421  0.362524   \n",
      "184    0.064516   0.130435   0.161290   0.344203   0.344086  0.452899   \n",
      "185    0.049869   0.383576   0.430446   0.209979   0.183727  0.311850   \n",
      "186    0.070423   0.226252   0.258216   0.286701   0.230047  0.371330   \n",
      "187    0.016393   0.157042   0.318761   0.318503   0.316940  0.442251   \n",
      "188    0.151436   0.173719   0.154047   0.145880   0.117493  0.496659   \n",
      "189    0.064935   0.196000   0.253247   0.222000   0.110390  0.428000   \n",
      "190    0.079439   0.292169   0.345794   0.150602   0.172897  0.433735   \n",
      "191    0.060914   0.359408   0.380711   0.187104   0.192893  0.327696   \n",
      "192    0.048327   0.373167   0.411400   0.271994   0.247831  0.272361   \n",
      "193    0.042857   0.161702   0.242857   0.306383   0.228571  0.387234   \n",
      "194    0.072727   0.353791   0.390909   0.223827   0.218182  0.296029   \n",
      "195    0.204710   0.173160   0.201087   0.261905   0.250000  0.351190   \n",
      "196    0.161064   0.243203   0.348739   0.151583   0.175070  0.284544   \n",
      "197    0.047809   0.326105   0.357238   0.353741   0.383798  0.267857   \n",
      "198    0.088186   0.313230   0.349418   0.294530   0.334443  0.233287   \n",
      "199    0.031690   0.326419   0.378521   0.364246   0.353873  0.233679   \n",
      "200    0.037099   0.277199   0.326307   0.327319   0.342327  0.307805   \n",
      "201    0.003279   0.253681   0.396721   0.433319   0.318033  0.247371   \n",
      "202    0.425300   0.160633   0.206107   0.166774   0.160305  0.227214   \n",
      "203    0.163851   0.192587   0.219595   0.271802   0.277027  0.302326   \n",
      "204    0.234397   0.209367   0.259362   0.145316   0.178918  0.286629   \n",
      "205    0.207729   0.302098   0.231884   0.155245   0.251208  0.285315   \n",
      "206    0.020468   0.170763   0.251462   0.371928   0.333333  0.393920   \n",
      "207    0.133333   0.226519   0.238095   0.294659   0.342857  0.208103   \n",
      "208    0.253521   0.158491   0.169014   0.098113   0.154930  0.245283   \n",
      "209    0.062500   0.304762   0.475000   0.260317   0.225000  0.339683   \n",
      "210    0.097778   0.222059   0.248889   0.288235   0.235556  0.386765   \n",
      "211    0.159091   0.220116   0.286364   0.262243   0.237879  0.325434   \n",
      "212    0.027536   0.236321   0.339130   0.334906   0.321739  0.353302   \n",
      "213    0.056911   0.225126   0.268293   0.398995   0.378049  0.289447   \n",
      "214    0.077684   0.213238   0.221751   0.276015   0.309322  0.390993   \n",
      "215    0.027140   0.161428   0.233820   0.371307   0.308977  0.422595   \n",
      "216    0.060606   0.243437   0.222222   0.341289   0.373737  0.312649   \n",
      "217    0.077181   0.273622   0.305369   0.152559   0.281879  0.372047   \n",
      "218    0.021127   0.168000   0.190141   0.374000   0.295775  0.406000   \n",
      "219    0.038835   0.276336   0.213592   0.364885   0.364078  0.302290   \n",
      "220    0.063158   0.274295   0.357895   0.282132   0.289474  0.333856   \n",
      "221    0.015625   0.112805   0.109375   0.100610   0.062500  0.542683   \n",
      "222    0.041034   0.253093   0.324340   0.367358   0.339517  0.282569   \n",
      "223    0.013889   0.186735   0.201389   0.309184   0.451389  0.439796   \n",
      "224    0.061321   0.250947   0.188679   0.246212   0.254717  0.417614   \n",
      "225    0.031901   0.290561   0.301574   0.411617   0.443216  0.234602   \n",
      "226    0.062069   0.271093   0.282759   0.244813   0.206897  0.275242   \n",
      "227    0.188317   0.169554   0.202921   0.174257   0.172175  0.424505   \n",
      "228    0.226293   0.165295   0.244253   0.226193   0.239943  0.300024   \n",
      "229    0.015801   0.390661   0.399549   0.353455   0.370203  0.208049   \n",
      "230    0.009756   0.180914   0.285366   0.353234   0.314634  0.400271   \n",
      "231    0.029630   0.343750   0.400000   0.377841   0.370370  0.215909   \n",
      "232    0.010989   0.369099   0.432234   0.321888   0.347985  0.221745   \n",
      "233    0.027573   0.406454   0.455441   0.322681   0.321024  0.236581   \n",
      "234    0.037994   0.400468   0.424012   0.300937   0.282675  0.221311   \n",
      "235    0.018739   0.358073   0.333901   0.367188   0.369676  0.195312   \n",
      "236    0.059371   0.290216   0.356228   0.370647   0.311991  0.246269   \n",
      "237    0.033088   0.372051   0.235294   0.303085   0.319853  0.237750   \n",
      "238    0.040260   0.356763   0.377273   0.372464   0.335065  0.179469   \n",
      "239    0.028490   0.361612   0.316239   0.316013   0.398860  0.234358   \n",
      "240    0.015068   0.412500   0.432877   0.330769   0.332877  0.207212   \n",
      "241    0.250000   0.271262   0.244898   0.153089   0.168367  0.281110   \n",
      "242    0.101617   0.274236   0.281755   0.294323   0.293303  0.319651   \n",
      "243    0.114662   0.258252   0.321429   0.369417   0.308271  0.296602   \n",
      "244    0.053435   0.341433   0.362302   0.314202   0.327657  0.264349   \n",
      "245    0.014493   0.300112   0.282609   0.408735   0.420290  0.228443   \n",
      "246    0.039474   0.314394   0.381579   0.344697   0.407895  0.314394   \n",
      "247    0.082707   0.284040   0.310777   0.228133   0.210526  0.325969   \n",
      "248    0.083902   0.353402   0.363574   0.255268   0.257844  0.276942   \n",
      "249    0.064629   0.734290   0.688210   0.104053   0.118777  0.106557   \n",
      "250    0.238095   0.300000   0.312925   0.100000   0.061224  0.350000   \n",
      "251    0.400768   0.244059   0.235595   0.100495   0.092190  0.245050   \n",
      "252    0.107143   0.315266   0.379121   0.231256   0.225275  0.307136   \n",
      "253    0.157368   0.224092   0.287554   0.200620   0.185980  0.344553   \n",
      "254    0.096657   0.332604   0.348110   0.212254   0.247093  0.314278   \n",
      "255    0.130159   0.246706   0.295238   0.206192   0.233862  0.323123   \n",
      "256    0.146739   0.244657   0.304348   0.174625   0.168478  0.344247   \n",
      "257    0.061776   0.407917   0.243243   0.188468   0.250965  0.240964   \n",
      "258    0.118457   0.328633   0.371901   0.062907   0.096419  0.382863   \n",
      "259    0.073350   0.307518   0.343928   0.226050   0.240424  0.263515   \n",
      "260    0.108280   0.229060   0.270701   0.195726   0.207006  0.329060   \n",
      "261    0.055556   0.222615   0.188034   0.231449   0.230769  0.321555   \n",
      "262    0.203125   0.174840   0.218750   0.197228   0.207031  0.446695   \n",
      "263    0.175542   0.351838   0.329389   0.201800   0.236686  0.240810   \n",
      "264    0.047101   0.188654   0.202899   0.249340   0.202899  0.468338   \n",
      "265    0.025591   0.247066   0.289370   0.321382   0.354331  0.327901   \n",
      "266    0.051522   0.474026   0.482436   0.140260   0.175644  0.262338   \n",
      "267    0.025225   0.291076   0.340541   0.311093   0.304505  0.355296   \n",
      "268    0.069364   0.283268   0.285405   0.240222   0.256503  0.340199   \n",
      "269    0.094233   0.354491   0.407876   0.219760   0.247539  0.256287   \n",
      "270    0.031022   0.275433   0.370438   0.286095   0.299270  0.319858   \n",
      "271    0.054348   0.292576   0.396739   0.248908   0.184783  0.321689   \n",
      "272    0.026846   0.190926   0.281879   0.344045   0.295302  0.323251   \n",
      "273    0.010309   0.211699   0.257732   0.342618   0.360825  0.359331   \n",
      "274    0.046875   0.161290   0.343750   0.544355   0.421875  0.262097   \n",
      "275    0.056818   0.143172   0.085227   0.154185   0.244318  0.522026   \n",
      "276    0.090909   0.111111   0.090909   0.370370   0.181818  0.370370   \n",
      "277    0.066667   0.250000   0.133333   0.384615   0.266667  0.326923   \n",
      "278    0.000000   0.016949   0.076923   0.406780   0.076923  0.542373   \n",
      "279    0.060606   0.276923   0.454545   0.253846   0.151515  0.369231   \n",
      "280    0.018939   0.690986   0.655303   0.156768   0.166667  0.118782   \n",
      "281    0.029605   0.218236   0.361842   0.320606   0.299342  0.383805   \n",
      "282    0.093519   0.234053   0.262510   0.323654   0.340443  0.260362   \n",
      "283    0.016854   0.367247   0.436798   0.380187   0.400281  0.206158   \n",
      "284    0.057351   0.264732   0.289984   0.378739   0.376414  0.271543   \n",
      "285    0.032258   0.237473   0.435484   0.305011   0.161290  0.407407   \n",
      "286    0.053360   0.294163   0.343874   0.315175   0.353755  0.275486   \n",
      "287    0.041741   0.315628   0.337478   0.318701   0.341030  0.244074   \n",
      "288    0.107843   0.117895   0.220588   0.410526   0.289216  0.343158   \n",
      "289    0.040816   0.270588   0.387755   0.400000   0.377551  0.300000   \n",
      "290    0.237500   0.262366   0.275000   0.112903   0.122500  0.315054   \n",
      "291    0.058577   0.183422   0.243724   0.254993   0.229079  0.441744   \n",
      "292    0.091592   0.351690   0.379880   0.317339   0.271772  0.221374   \n",
      "293    0.339450   0.188647   0.302752   0.088035   0.161206  0.166213   \n",
      "294    0.058722   0.423411   0.421416   0.273359   0.285838  0.235846   \n",
      "295    0.151406   0.232573   0.256669   0.234822   0.276857  0.345647   \n",
      "296    0.026316   0.387795   0.432331   0.338583   0.348371  0.198327   \n",
      "297    0.245833   0.175577   0.197917   0.296476   0.241667  0.295261   \n",
      "298    0.067729   0.159249   0.247012   0.296940   0.229084  0.455494   \n",
      "299    0.019685   0.156727   0.299213   0.382802   0.381890  0.405687   \n",
      "300    0.089261   0.205084   0.306834   0.311935   0.352859  0.394227   \n",
      "301    0.031301   0.288471   0.337727   0.369619   0.405272  0.224146   \n",
      "302    0.067416   0.203548   0.262172   0.251167   0.277154  0.446312   \n",
      "303    0.053333   0.244418   0.276000   0.309596   0.349333  0.341581   \n",
      "304    0.194805   0.218009   0.259740   0.161137   0.155844  0.236967   \n",
      "305    0.190141   0.222051   0.326291   0.279877   0.220657  0.270625   \n",
      "306    0.059812   0.387269   0.334677   0.212374   0.243952  0.289114   \n",
      "307    0.076923   0.333333   0.323077   0.328321   0.261538  0.300752   \n",
      "308    0.029656   0.475459   0.480427   0.149232   0.136418  0.243431   \n",
      "309    0.113772   0.293037   0.273453   0.241296   0.249501  0.260638   \n",
      "310    0.061028   0.237050   0.301927   0.338422   0.328694  0.306861   \n",
      "311    0.246921   0.289913   0.337243   0.177474   0.137243  0.280812   \n",
      "312    0.082079   0.350098   0.324213   0.256348   0.229822  0.287109   \n",
      "313    0.000000   0.297297   0.153846   0.297297   0.230769  0.351351   \n",
      "314    0.026316   0.211688   0.289474   0.376623   0.388158  0.362338   \n",
      "315    0.017787   0.433586   0.399209   0.325888   0.367589  0.191065   \n",
      "316    0.014085   0.143519   0.316901   0.336934   0.387324  0.424383   \n",
      "317    0.061372   0.235099   0.220217   0.293046   0.335740  0.383278   \n",
      "318    0.031034   0.336894   0.325862   0.306631   0.339655  0.277259   \n",
      "319    0.017931   0.214957   0.233103   0.390598   0.406897  0.302991   \n",
      "320    0.004545   0.244152   0.295455   0.378655   0.327273  0.323099   \n",
      "321    0.007407   0.245455   0.325926   0.434091   0.362963  0.243182   \n",
      "322    0.140893   0.191981   0.288660   0.442284   0.340206  0.303767   \n",
      "323    0.019830   0.208945   0.291785   0.344514   0.325779  0.371768   \n",
      "324    0.074074   0.233010   0.370370   0.242718   0.037037  0.184466   \n",
      "325    0.133803   0.242197   0.204225   0.205993   0.292254  0.387016   \n",
      "326    0.032061   0.271626   0.438168   0.325444   0.235115  0.334742   \n",
      "327    0.006803   0.157579   0.238095   0.315159   0.285714  0.458358   \n",
      "328    0.018382   0.225806   0.367647   0.226439   0.147059  0.428210   \n",
      "329    0.075856   0.390302   0.433858   0.326434   0.275671  0.205204   \n",
      "330    0.046742   0.227076   0.284703   0.298010   0.347025  0.358131   \n",
      "331    0.059247   0.356753   0.429944   0.304296   0.339472  0.235936   \n",
      "332    0.116959   0.226328   0.210526   0.147806   0.187135  0.355658   \n",
      "333    0.015000   0.222798   0.335000   0.260794   0.255000  0.416235   \n",
      "334    0.224012   0.314997   0.278184   0.186450   0.177160  0.264621   \n",
      "335    0.090164   0.302920   0.262295   0.296837   0.331967  0.251825   \n",
      "336    0.089286   0.303725   0.315476   0.177650   0.160714  0.318052   \n",
      "337    0.120944   0.336207   0.315634   0.181034   0.144543  0.311576   \n",
      "338    0.089147   0.292419   0.290698   0.246691   0.209302  0.297232   \n",
      "339    0.008310   0.396947   0.324100   0.181679   0.177285  0.271756   \n",
      "340    0.113821   0.306397   0.219512   0.259259   0.308943  0.292929   \n",
      "341    0.103261   0.403564   0.282609   0.167715   0.184783  0.298742   \n",
      "342    0.074803   0.315867   0.342520   0.287823   0.218504  0.274539   \n",
      "343    0.046296   0.271739   0.231481   0.170290   0.166667  0.409420   \n",
      "344    0.120000   0.270925   0.280000   0.266520   0.160000  0.233480   \n",
      "345    0.025862   0.674024   0.517241   0.088285   0.112069  0.185059   \n",
      "346    0.043796   0.847095   0.613139   0.076453   0.094891  0.058104   \n",
      "347    0.166667   0.809859   0.458333   0.063380   0.125000  0.070423   \n",
      "348    0.095462   0.230610   0.258216   0.310238   0.264476  0.336608   \n",
      "349    0.325726   0.192243   0.221992   0.205734   0.163900  0.258010   \n",
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      "351    0.208835   0.168714   0.196787   0.187460   0.180723  0.366516   \n",
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      "353    0.011016   0.206635   0.299878   0.356967   0.342717  0.381611   \n",
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      "355    0.027668   0.198473   0.229249   0.392176   0.292490  0.339695   \n",
      "356    0.092838   0.281120   0.360743   0.198133   0.209549  0.327801   \n",
      "357    0.059701   0.228070   0.247761   0.285862   0.295522  0.389061   \n",
      "358    0.036205   0.254579   0.363296   0.380952   0.322097  0.297070   \n",
      "359    0.088496   0.183288   0.327434   0.148248   0.168142  0.560647   \n",
      "360    0.044776   0.360544   0.422886   0.188776   0.233831  0.277211   \n",
      "361    0.105337   0.200869   0.242978   0.333655   0.297753  0.338967   \n",
      "362    0.000000   0.181818   0.264706   0.309091   0.279412  0.368182   \n",
      "363    0.020513   0.215719   0.276923   0.160535   0.210256  0.530100   \n",
      "364    0.089147   0.228835   0.234496   0.284996   0.228682  0.349539   \n",
      "365    0.145078   0.184358   0.181347   0.178771   0.202073  0.512104   \n",
      "366    0.084536   0.239344   0.216495   0.295082   0.280412  0.352459   \n",
      "367    0.048832   0.197520   0.326964   0.312356   0.305732  0.397795   \n",
      "368    0.117462   0.374231   0.356581   0.244507   0.218668  0.253823   \n",
      "369    0.176568   0.280308   0.260726   0.246600   0.247525  0.229450   \n",
      "370    0.027451   0.470994   0.435294   0.241713   0.235294  0.237569   \n",
      "371    0.050725   0.249106   0.275362   0.174017   0.206522  0.407628   \n",
      "372    0.078680   0.214339   0.312183   0.310680   0.294416  0.309186   \n",
      "373    0.196078   0.292262   0.331933   0.095121   0.092437  0.344505   \n",
      "374    0.155477   0.254768   0.272085   0.153951   0.155477  0.347411   \n",
      "375    0.047297   0.204108   0.260135   0.260591   0.317568  0.382542   \n",
      "376    0.022222   0.846154   0.688889   0.110577   0.266667  0.043269   \n",
      "377    0.015707   0.786329   0.853403   0.066835   0.089005  0.063291   \n",
      "378    0.024518   0.235535   0.323993   0.265233   0.304729  0.421915   \n",
      "379    0.016736   0.249221   0.359833   0.261682   0.263598  0.420561   \n",
      "380    0.022026   0.275103   0.189427   0.305365   0.215859  0.350757   \n",
      "381    0.032609   0.211082   0.152174   0.176781   0.239130  0.538259   \n",
      "382    0.013294   0.247511   0.420975   0.319583   0.324963  0.356567   \n",
      "383    0.045593   0.168299   0.191489   0.319679   0.410334  0.458593   \n",
      "384    0.026596   0.156021   0.382979   0.294241   0.382979  0.482723   \n",
      "385    0.057971   0.142857   0.231884   0.306878   0.304348  0.338624   \n",
      "386    0.002915   0.440529   0.463557   0.207930   0.268222  0.323348   \n",
      "387    0.015544   0.311828   0.383420   0.301971   0.318653  0.294803   \n",
      "388    0.041612   0.209815   0.225618   0.320174   0.287386  0.363141   \n",
      "389    0.076744   0.240656   0.367442   0.265269   0.267442  0.247037   \n",
      "390    0.019608   0.253676   0.303922   0.319853   0.318627  0.305147   \n",
      "391    0.035545   0.271824   0.376777   0.371540   0.355450  0.275373   \n",
      "392    0.052632   0.308046   0.354067   0.381609   0.387560  0.268966   \n",
      "393    0.053860   0.182945   0.228007   0.258746   0.258528  0.359329   \n",
      "394    0.081081   0.206649   0.207207   0.167116   0.165165  0.426774   \n",
      "395    0.096692   0.325153   0.356234   0.253579   0.277354  0.315951   \n",
      "396    0.015280   0.273157   0.349745   0.339319   0.368421  0.346881   \n",
      "397    0.085714   0.384110   0.402597   0.308273   0.284848  0.197965   \n",
      "398    0.204082   0.257053   0.278912   0.282132   0.129252  0.278997   \n",
      "399    0.048458   0.434237   0.475771   0.203313   0.227606  0.296687   \n",
      "400    0.039095   0.475453   0.460905   0.218656   0.227366  0.238671   \n",
      "401    0.030023   0.243164   0.309469   0.305664   0.284065  0.291992   \n",
      "402    0.022388   0.162983   0.179104   0.428177   0.358209  0.356354   \n",
      "403    0.040323   0.309392   0.338710   0.129834   0.129032  0.472376   \n",
      "404    0.114583   0.277870   0.317708   0.239601   0.135417  0.410982   \n",
      "405    0.032338   0.529561   0.425373   0.206081   0.186567  0.223818   \n",
      "406    0.060034   0.291946   0.349914   0.275168   0.259005  0.256711   \n",
      "407    0.066116   0.335548   0.305785   0.295681   0.223140  0.275748   \n",
      "408    0.036232   0.316327   0.260870   0.098639   0.137681  0.472789   \n",
      "409    0.091803   0.283964   0.337705   0.246102   0.242623  0.253898   \n",
      "410    0.083815   0.252654   0.289017   0.227176   0.242775  0.319533   \n",
      "411    0.093023   0.313725   0.351744   0.227669   0.250000  0.266885   \n",
      "412    0.085837   0.342387   0.291845   0.245267   0.281116  0.262551   \n",
      "413    0.097826   0.296765   0.318841   0.308017   0.329710  0.223629   \n",
      "414    0.069191   0.281235   0.328982   0.212915   0.225849  0.380440   \n",
      "415    0.000000   0.135821   0.407895   0.394030   0.342105  0.445522   \n",
      "416    0.063652   0.286640   0.318258   0.238285   0.239531  0.329511   \n",
      "417    0.186650   0.299145   0.374536   0.104701   0.111248  0.327991   \n",
      "418    0.037411   0.465815   0.498219   0.240939   0.229216  0.215610   \n",
      "419    0.243750   0.304258   0.359375   0.089823   0.085938  0.322949   \n",
      "420    0.060168   0.316721   0.318893   0.237075   0.253911  0.325105   \n",
      "421    0.073379   0.297248   0.293515   0.288685   0.249147  0.292355   \n",
      "422    0.000000   0.240000   0.320225   0.327273   0.404494  0.380000   \n",
      "423    0.090909   0.190311   0.181818   0.349481   0.218182  0.290657   \n",
      "424    0.078125   0.221000   0.218750   0.237000   0.277344  0.333000   \n",
      "425    0.025140   0.298925   0.319832   0.269355   0.303073  0.310753   \n",
      "426    0.213689   0.319903   0.330551   0.171636   0.158598  0.272361   \n",
      "427    0.058824   0.312318   0.248366   0.195926   0.196078  0.324927   \n",
      "428    0.096591   0.416342   0.357955   0.245136   0.255682  0.180934   \n",
      "429    0.150235   0.248731   0.267606   0.235195   0.225352  0.346870   \n",
      "430    0.044444   0.058201   0.066667   0.296296   0.244444  0.534392   \n",
      "431    0.051429   0.248804   0.257143   0.251196   0.308571  0.404306   \n",
      "432    0.035088   0.330709   0.298246   0.322835   0.280702  0.212598   \n",
      "433    0.092593   0.132653   0.240741   0.178571   0.185185  0.397959   \n",
      "434    0.086242   0.224679   0.219713   0.241084   0.250513  0.388730   \n",
      "435    0.057637   0.239325   0.308357   0.284012   0.302594  0.334657   \n",
      "436    0.041916   0.231733   0.179641   0.265136   0.269461  0.344468   \n",
      "437    0.026846   0.370690   0.476510   0.299569   0.275168  0.290948   \n",
      "438    0.151643   0.182372   0.215670   0.125508   0.080034  0.500000   \n",
      "439    0.292208   0.221635   0.251299   0.169471   0.127922  0.337019   \n",
      "440    0.124847   0.287671   0.334149   0.290959   0.283966  0.299178   \n",
      "441    0.224684   0.140816   0.237342   0.051020   0.066456  0.432653   \n",
      "442    0.252907   0.281572   0.312500   0.158505   0.162791  0.297036   \n",
      "443    0.053533   0.467378   0.507495   0.349941   0.327623  0.128114   \n",
      "444    0.018519   0.253923   0.379630   0.294341   0.338889  0.368521   \n",
      "445    0.114833   0.247152   0.322967   0.228747   0.165072  0.366345   \n",
      "446    0.112500   0.202806   0.237500   0.158163   0.216667  0.346939   \n",
      "447    0.094203   0.321805   0.384058   0.306767   0.235507  0.242105   \n",
      "448    0.231214   0.326750   0.316474   0.065829   0.089595  0.363854   \n",
      "449    0.091003   0.242359   0.323681   0.333514   0.326784  0.346768   \n",
      "450    0.076923   0.279450   0.328205   0.244196   0.312821  0.349097   \n",
      "451    0.201161   0.232626   0.303675   0.203365   0.176015  0.349671   \n",
      "452    0.072046   0.225458   0.191643   0.349834   0.355908  0.274542   \n",
      "453    0.017857   0.258565   0.267857   0.341306   0.377976  0.319328   \n",
      "454    0.042222   0.365465   0.397037   0.360314   0.382963  0.189110   \n",
      "455    0.042969   0.253717   0.380859   0.386026   0.337891  0.277502   \n",
      "456    0.058939   0.238023   0.263261   0.392839   0.422397  0.288452   \n",
      "457    0.197548   0.245614   0.320163   0.154521   0.110354  0.287112   \n",
      "458    0.137387   0.196311   0.247748   0.318841   0.344595  0.326746   \n",
      "459    0.153846   0.268540   0.320850   0.240177   0.226721  0.363778   \n",
      "460    0.022727   0.046125   0.113636   0.332103   0.250000  0.579336   \n",
      "461    0.071217   0.271007   0.328388   0.328002   0.337290  0.286551   \n",
      "462    0.010256   0.264463   0.335897   0.300826   0.297436  0.348209   \n",
      "463    0.053140   0.377129   0.265700   0.278589   0.381643  0.299270   \n",
      "464    0.026055   0.264314   0.347395   0.408485   0.330025  0.291158   \n",
      "465    0.116379   0.166667   0.221983   0.159125   0.215517  0.419306   \n",
      "466    0.202781   0.238987   0.286211   0.195301   0.193511  0.323789   \n",
      "467    0.115226   0.282873   0.326475   0.305525   0.311385  0.237569   \n",
      "468    0.144444   0.135526   0.288889   0.272368   0.311111  0.230263   \n",
      "469    0.100000   0.276796   0.337037   0.270907   0.240741  0.329800   \n",
      "470    0.076531   0.219839   0.278061   0.360143   0.334184  0.326184   \n",
      "471    0.028986   0.343750   0.443478   0.232537   0.226087  0.361213   \n",
      "472    0.093882   0.184791   0.210970   0.325475   0.325949  0.388213   \n",
      "473    0.044444   0.405899   0.433333   0.400281   0.350000  0.185393   \n",
      "474    0.007968   0.332168   0.346614   0.494755   0.498008  0.150350   \n",
      "475    0.000000   0.087087   0.075269   0.066066   0.118280  0.387387   \n",
      "476    0.032178   0.487361   0.448020   0.243680   0.306931  0.148635   \n",
      "477    0.021505   0.091445   0.236559   0.448378   0.387097  0.418879   \n",
      "478    0.106787   0.229925   0.305882   0.302137   0.266968  0.322646   \n",
      "479    0.014085   0.179377   0.328638   0.314715   0.314554  0.432868   \n",
      "480    0.109375   0.267222   0.310547   0.323240   0.333984  0.314156   \n",
      "481    0.041872   0.393939   0.381773   0.292929   0.307882  0.211344   \n",
      "482    0.052174   0.383488   0.452174   0.306327   0.300000  0.229938   \n",
      "483    0.067929   0.257307   0.267261   0.267050   0.324053  0.364039   \n",
      "484    0.027027   0.536424   0.405405   0.059603   0.162162  0.278146   \n",
      "485    0.034314   0.382385   0.417892   0.363239   0.362745  0.208425   \n",
      "486    0.038241   0.358719   0.429389   0.315232   0.303222  0.223448   \n",
      "487    0.037209   0.615789   0.539535   0.221053   0.223256  0.149123   \n",
      "488    0.036741   0.381514   0.418530   0.398263   0.396166  0.145782   \n",
      "489    0.037915   0.178552   0.360190   0.299196   0.308057  0.441287   \n",
      "490    0.063158   0.145221   0.168421   0.261029   0.284211  0.487132   \n",
      "491    0.013453   0.221583   0.381166   0.401439   0.246637  0.306475   \n",
      "492    0.053073   0.221739   0.262570   0.405072   0.385475  0.311594   \n",
      "493    0.036511   0.265070   0.346856   0.336086   0.342799  0.324525   \n",
      "494    0.032668   0.239284   0.303085   0.339992   0.337568  0.354141   \n",
      "495    0.000000   0.252336   0.245902   0.373832   0.327869  0.308411   \n",
      "496    0.058166   0.244323   0.288591   0.199818   0.208054  0.369664   \n",
      "497    0.030702   0.411647   0.432749   0.240964   0.241228  0.262550   \n",
      "498    0.087248   0.202934   0.161074   0.178484   0.214765  0.430318   \n",
      "499    0.000000   0.230769   0.200000   0.384615   0.400000  0.307692   \n",
      "500    0.016129   0.227273   0.258065   0.424242   0.258065  0.227273   \n",
      "501    0.000000   0.187500   0.363636   0.359375   0.212121  0.429688   \n",
      "502    0.047337   0.243493   0.298817   0.287154   0.254438  0.329135   \n",
      "503    0.000000   0.288136   0.240000   0.338983   0.440000  0.237288   \n",
      "504    0.044000   0.270386   0.208000   0.248927   0.280000  0.347639   \n",
      "505    0.010417   0.212719   0.312500   0.445175   0.354167  0.256579   \n",
      "506    0.013746   0.394291   0.512027   0.274311   0.259450  0.249153   \n",
      "507    0.080537   0.320276   0.268456   0.235023   0.241611  0.350230   \n",
      "508    0.043919   0.161905   0.173986   0.273993   0.324324  0.435165   \n",
      "509    0.072376   0.233222   0.252111   0.245121   0.258142  0.411709   \n",
      "510    0.019868   0.273042   0.294702   0.325710   0.261589  0.320166   \n",
      "511    0.054054   0.324766   0.189189   0.301402   0.396396  0.315421   \n",
      "512    0.039474   0.221649   0.313910   0.345876   0.396617  0.353608   \n",
      "513    0.046263   0.239258   0.295374   0.331055   0.217082  0.317383   \n",
      "514    0.041791   0.228604   0.241791   0.199324   0.271642  0.463964   \n",
      "515    0.032802   0.395246   0.449859   0.249413   0.241799  0.272594   \n",
      "516    0.135542   0.646261   0.530120   0.072147   0.180723  0.086576   \n",
      "517    0.041420   0.317730   0.326923   0.391773   0.383136  0.241135   \n",
      "518    0.066842   0.289247   0.362105   0.368115   0.337368  0.282877   \n",
      "519    0.032710   0.329268   0.352804   0.384146   0.387850  0.240854   \n",
      "520    0.033314   0.343969   0.371128   0.405262   0.424313  0.202351   \n",
      "521    0.084821   0.177465   0.370536   0.191549   0.183036  0.314085   \n",
      "522    0.048232   0.248904   0.308682   0.259868   0.209003  0.350877   \n",
      "523    0.042289   0.318291   0.353234   0.257521   0.298507  0.296631   \n",
      "524    0.015536   0.305294   0.362224   0.441262   0.406378  0.203408   \n",
      "525    0.046272   0.238302   0.316195   0.247834   0.195373  0.369151   \n",
      "526    0.000000   0.241379   1.000000   0.206897   0.000000  0.103448   \n",
      "527    0.015748   0.332645   0.267717   0.196281   0.220472  0.367769   \n",
      "528    0.090909   0.090278   0.115152   0.273148   0.242424  0.488426   \n",
      "529    0.095238   0.197822   0.196429   0.451906   0.386905  0.274047   \n",
      "530    0.157205   0.297679   0.266376   0.202825   0.179039  0.351160   \n",
      "531    0.077181   0.245823   0.244966   0.304296   0.204698  0.346062   \n",
      "532    0.024427   0.556505   0.552672   0.287779   0.299237  0.130092   \n",
      "533    0.030303   0.699358   0.712919   0.102355   0.089314  0.139615   \n",
      "534    0.000000   0.473684   0.200000   0.157895   0.400000  0.210526   \n",
      "535    0.062500   0.273754   0.237772   0.158804   0.150815  0.456478   \n",
      "536    0.018141   0.454175   0.394558   0.232179   0.299320  0.241344   \n",
      "537    0.014085   0.191339   0.369718   0.285827   0.232394  0.442520   \n",
      "538    0.014981   0.255639   0.301498   0.290548   0.342697  0.357680   \n",
      "539    0.013216   0.281046   0.425110   0.315508   0.299559  0.335710   \n",
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      "561    0.043127   0.471303   0.469003   0.234662   0.230907  0.224767   \n",
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      "567    0.101124   0.228620   0.248596   0.298899   0.266854  0.349704   \n",
      "568    0.106529   0.238540   0.294387   0.280730   0.258877  0.286004   \n",
      "569    0.081772   0.349644   0.308348   0.209026   0.287905  0.280760   \n",
      "570    0.072238   0.351397   0.354108   0.189944   0.181303  0.288268   \n",
      "571    0.082935   0.316263   0.353270   0.277739   0.257576  0.286736   \n",
      "572    0.035120   0.299065   0.308688   0.369897   0.380776  0.251353   \n",
      "573    0.192460   0.344652   0.307540   0.269949   0.210317  0.226938   \n",
      "574    0.082707   0.192308   0.278195   0.215976   0.293233  0.470414   \n",
      "575    0.015968   0.256506   0.326680   0.466078   0.483699  0.204693   \n",
      "576    0.008547   0.203409   0.270655   0.248864   0.262108  0.448864   \n",
      "577    0.034512   0.279011   0.333333   0.406693   0.401515  0.269189   \n",
      "578    0.028662   0.328848   0.331210   0.383516   0.385350  0.221194   \n",
      "579    0.041667   0.282810   0.308712   0.308688   0.238636  0.330253   \n",
      "580    0.048518   0.324080   0.337826   0.386957   0.458221  0.216388   \n",
      "581    0.032064   0.225061   0.184369   0.357056   0.348697  0.270073   \n",
      "582    0.019417   0.263116   0.305825   0.324324   0.199029  0.360890   \n",
      "583    0.025943   0.216327   0.304245   0.286880   0.356132  0.441399   \n",
      "584    0.085389   0.238563   0.238140   0.198488   0.235294  0.390170   \n",
      "585    0.000000   0.230769   0.000000   0.076923   0.000000  0.692308   \n",
      "586    0.037569   0.402220   0.438913   0.279122   0.318265  0.241332   \n",
      "587    0.048016   0.480573   0.542460   0.296054   0.265873  0.177358   \n",
      "588    0.053571   0.416891   0.467857   0.290040   0.283036  0.211642   \n",
      "589    0.101227   0.230079   0.276074   0.237935   0.248466  0.343434   \n",
      "590    0.066667   0.295455   0.300000   0.218531   0.277778  0.363636   \n",
      "591    0.039216   0.605053   0.513725   0.142287   0.235294  0.178191   \n",
      "592    0.015474   0.203405   0.282398   0.336098   0.371373  0.419467   \n",
      "593    0.065637   0.290780   0.305019   0.228369   0.231660  0.344681   \n",
      "594    0.042105   0.222423   0.287719   0.213382   0.203509  0.372514   \n",
      "595    0.017391   0.168798   0.156522   0.388747   0.417391  0.355499   \n",
      "596    0.037356   0.543383   0.564655   0.192438   0.183908  0.193892   \n",
      "597    0.103604   0.360420   0.351351   0.198289   0.250000  0.260886   \n",
      "598    0.043956   0.276204   0.324176   0.253541   0.263736  0.382436   \n",
      "599    0.026239   0.441731   0.419825   0.274140   0.282799  0.188679   \n",
      "600    0.040767   0.183916   0.225420   0.253790   0.235012  0.456163   \n",
      "601    0.069767   0.165368   0.265116   0.339724   0.358140  0.412822   \n",
      "602    0.029553   0.327300   0.318213   0.342383   0.362199  0.250377   \n",
      "603    0.046997   0.230008   0.248042   0.346535   0.383812  0.368621   \n",
      "604    0.065693   0.145729   0.189781   0.326633   0.394161  0.374372   \n",
      "605    0.013575   0.246479   0.230769   0.388330   0.407240  0.330986   \n",
      "606    0.029197   0.303778   0.338686   0.317419   0.362044  0.320147   \n",
      "607    0.080000   0.152941   0.120000   0.120588   0.240000  0.308824   \n",
      "608    0.111111   0.228733   0.277778   0.333648   0.297893  0.276938   \n",
      "609    0.034483   0.173077   0.103448   0.461538   0.517241  0.326923   \n",
      "610    0.023622   0.083333   0.110236   0.185185   0.181102  0.662037   \n",
      "611    0.067159   0.338626   0.373432   0.310048   0.297417  0.268542   \n",
      "612    0.063457   0.316508   0.394967   0.322065   0.301969  0.305163   \n",
      "613    0.060503   0.323471   0.363018   0.363796   0.379334  0.250274   \n",
      "614    0.022371   0.295474   0.322148   0.326217   0.337808  0.291204   \n",
      "615    0.024460   0.477639   0.548201   0.314848   0.284892  0.157424   \n",
      "616    0.162011   0.450902   0.400372   0.253173   0.212291  0.177021   \n",
      "617    0.016105   0.286693   0.329429   0.372359   0.361640  0.299258   \n",
      "618    0.217712   0.254476   0.340713   0.192668   0.189422  0.277067   \n",
      "619    0.043210   0.273622   0.234568   0.269685   0.314815  0.375984   \n",
      "620    0.073980   0.239752   0.229592   0.303106   0.306122  0.325466   \n",
      "621    0.117100   0.321724   0.355019   0.285714   0.226766  0.219008   \n",
      "622    0.098398   0.276873   0.252860   0.321291   0.342105  0.265324   \n",
      "623    0.037037   0.262346   0.310847   0.324741   0.338624  0.342568   \n",
      "624    0.068323   0.241874   0.298137   0.239826   0.237405  0.377783   \n",
      "625    0.026316   0.167995   0.186235   0.345286   0.313765  0.397078   \n",
      "626    0.106239   0.218876   0.256324   0.279786   0.310287  0.344043   \n",
      "627    0.014468   0.403450   0.435764   0.426798   0.440394  0.136096   \n",
      "628    0.103774   0.219436   0.207547   0.260188   0.245283  0.426332   \n",
      "629    0.080386   0.217105   0.147910   0.265789   0.250804  0.419737   \n",
      "630    0.008955   0.227442   0.250746   0.306488   0.295522  0.315436   \n",
      "631    0.087491   0.313213   0.345625   0.240970   0.270427  0.264734   \n",
      "632    0.082353   0.252199   0.247059   0.288856   0.282353  0.340176   \n",
      "633    0.030016   0.285175   0.290679   0.432345   0.388626  0.247170   \n",
      "634    0.024590   0.166915   0.204918   0.286140   0.286885  0.429210   \n",
      "635    0.041916   0.259592   0.281437   0.324186   0.275449  0.349927   \n",
      "636    0.039280   0.400874   0.482815   0.282479   0.242226  0.230830   \n",
      "637    0.180652   0.267071   0.340573   0.151442   0.149062  0.337785   \n",
      "638    0.051163   0.175931   0.344186   0.444412   0.325581  0.351271   \n",
      "639    0.015228   0.118527   0.228426   0.340621   0.279188  0.369390   \n",
      "640    0.046387   0.349080   0.429973   0.356442   0.348796  0.258896   \n",
      "641    0.056213   0.167841   0.207101   0.302942   0.301775  0.459594   \n",
      "642    0.080460   0.268376   0.367816   0.280342   0.206897  0.295726   \n",
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      "646    0.003929   0.363184   0.500982   0.296296   0.318271  0.276396   \n",
      "647    0.054586   0.336142   0.347191   0.304656   0.305617  0.264006   \n",
      "648    0.020492   0.229584   0.325820   0.393683   0.360656  0.259630   \n",
      "649    0.100160   0.352298   0.425481   0.218049   0.195513  0.289238   \n",
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      "651    0.093264   0.276210   0.259067   0.310484   0.259067  0.268145   \n",
      "652    0.153348   0.266541   0.233261   0.155009   0.125270  0.412098   \n",
      "653    0.053493   0.510233   0.491266   0.157728   0.171397  0.249118   \n",
      "654    0.297340   0.140331   0.215962   0.128913   0.134585  0.340700   \n",
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      "657    0.034423   0.600000   0.621343   0.174344   0.177281  0.165598   \n",
      "658    0.032339   0.331398   0.354053   0.361393   0.380512  0.244960   \n",
      "659    0.249505   0.321731   0.336304   0.198585   0.166997  0.289280   \n",
      "660    0.269373   0.161972   0.254613   0.153756   0.140221  0.253521   \n",
      "661    0.099237   0.299140   0.269720   0.236676   0.237913  0.312321   \n",
      "662    0.032258   0.288973   0.241935   0.330798   0.306452  0.365019   \n",
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      "664    0.054159   0.188636   0.226306   0.194697   0.210832  0.434848   \n",
      "665    0.037221   0.297148   0.317618   0.361546   0.339950  0.303588   \n",
      "666    0.005367   0.502262   0.586762   0.257014   0.295170  0.195475   \n",
      "667    0.070755   0.429017   0.382075   0.240250   0.202830  0.165367   \n",
      "668    0.106122   0.241470   0.224490   0.322835   0.302041  0.316273   \n",
      "669    0.000000   0.540948   0.575758   0.398707   0.393939  0.060345   \n",
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      "671    0.043453   0.341970   0.356775   0.268051   0.259005  0.316060   \n",
      "672    0.097561   0.208333   0.195122   0.116667   0.243902  0.516667   \n",
      "673    0.018605   0.298963   0.372093   0.428167   0.374419  0.248664   \n",
      "674    0.040428   0.278100   0.304400   0.329085   0.332937  0.282735   \n",
      "675    0.010390   0.195378   0.272727   0.300420   0.257143  0.390756   \n",
      "676    0.011080   0.504961   0.473684   0.264609   0.249307  0.181918   \n",
      "677    0.000000   0.723810   0.668605   0.129762   0.133721  0.132143   \n",
      "678    0.000000   0.223529   0.071429   0.235294   0.357143  0.482353   \n",
      "679    0.009314   0.351118   0.297206   0.311182   0.300593  0.223642   \n",
      "680    0.010204   0.841549   0.887755   0.095070   0.051020  0.047535   \n",
      "681    0.022901   0.131951   0.213740   0.375118   0.343511  0.470311   \n",
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      "683    0.062500   0.276596   0.306818   0.345154   0.323864  0.290780   \n",
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      "685    0.025641   0.182648   0.294872   0.232877   0.320513  0.369863   \n",
      "686    0.194313   0.213855   0.189573   0.251506   0.274882  0.176205   \n",
      "687    0.376045   0.219931   0.164345   0.235968   0.194986  0.245132   \n",
      "688    0.013605   0.180266   0.292517   0.332068   0.374150  0.430740   \n",
      "689    0.000000   0.148855   0.219512   0.351145   0.365854  0.488550   \n",
      "690    0.050633   0.379326   0.413924   0.261191   0.284810  0.262114   \n",
      "691    0.010724   0.128215   0.249330   0.365173   0.268097  0.434974   \n",
      "692    0.000000   0.183432   0.341667   0.346746   0.325000  0.403550   \n",
      "693    0.018692   0.151335   0.271028   0.378338   0.392523  0.449555   \n",
      "694    0.030303   0.164138   0.339394   0.318621   0.315152  0.489655   \n",
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      "696    0.010417   0.182670   0.156250   0.311475   0.302083  0.461358   \n",
      "697    0.005917   0.222099   0.372781   0.341436   0.278107  0.388950   \n",
      "698    0.018634   0.137280   0.372671   0.412469   0.316770  0.421914   \n",
      "699    0.014845   0.237843   0.356275   0.388092   0.437247  0.312656   \n",
      "700    0.011952   0.243458   0.250996   0.311718   0.310757  0.356086   \n",
      "701    0.069347   0.336452   0.406030   0.317742   0.282412  0.272581   \n",
      "702    0.039474   0.217559   0.243421   0.301927   0.246711  0.411563   \n",
      "703    0.015625   0.395698   0.466518   0.237288   0.301339  0.290091   \n",
      "704    0.003448   0.484262   0.486207   0.214286   0.186207  0.217918   \n",
      "705    0.015686   0.380062   0.478431   0.250779   0.247059  0.333333   \n",
      "706    0.072165   0.273717   0.360825   0.315708   0.329897  0.289269   \n",
      "707    0.027881   0.295409   0.310409   0.273120   0.265799  0.367265   \n",
      "708    0.022388   0.228311   0.164179   0.285388   0.305970  0.344749   \n",
      "709    0.103448   0.163793   0.241379   0.267241   0.206897  0.525862   \n",
      "710    0.046875   0.154689   0.259375   0.388551   0.390625  0.390378   \n",
      "711    0.034586   0.245161   0.309774   0.367742   0.369173  0.300836   \n",
      "712    0.076000   0.195804   0.166000   0.214161   0.218000  0.492133   \n",
      "713    0.031746   0.335556   0.436508   0.293333   0.246032  0.233333   \n",
      "714    0.043046   0.238326   0.269868   0.268648   0.291391  0.391146   \n",
      "715    0.080760   0.260965   0.268409   0.239035   0.247031  0.418860   \n",
      "716    0.082192   0.169935   0.246575   0.316993   0.315068  0.261438   \n",
      "717    0.005208   0.298044   0.375000   0.300345   0.291667  0.390104   \n",
      "718    0.036513   0.326065   0.410315   0.342895   0.330443  0.280697   \n",
      "719    0.048000   0.133739   0.188000   0.245694   0.244000  0.526849   \n",
      "720    0.062500   0.225681   0.250000   0.369650   0.375000  0.342412   \n",
      "721    0.030380   0.160900   0.129114   0.301903   0.400000  0.422145   \n",
      "722    0.020513   0.266243   0.335897   0.291158   0.325641  0.352711   \n",
      "723    0.008427   0.208745   0.339888   0.351669   0.370787  0.367184   \n",
      "724    0.005787   0.196897   0.350694   0.341894   0.353009  0.402354   \n",
      "725    0.011799   0.218497   0.330383   0.290173   0.292035  0.401734   \n",
      "726    0.011673   0.181504   0.291829   0.358686   0.326848  0.350908   \n",
      "727    0.015464   0.222661   0.314433   0.314399   0.310997  0.421324   \n",
      "728    0.008803   0.231898   0.438380   0.292519   0.343310  0.422901   \n",
      "729    0.023438   0.258345   0.323437   0.269956   0.303125  0.378326   \n",
      "730    0.012500   0.439200   0.472917   0.212389   0.167708  0.255326   \n",
      "731    0.031439   0.262276   0.292624   0.346957   0.295042  0.344605   \n",
      "732    0.070450   0.254557   0.236791   0.280599   0.303327  0.395833   \n",
      "733    0.020408   0.109375   0.204082   0.378906   0.316327  0.417969   \n",
      "734    0.015625   0.377778   0.421875   0.298611   0.308594  0.250000   \n",
      "735    0.016644   0.598121   0.572816   0.179019   0.188627  0.179541   \n",
      "736    0.022026   0.476111   0.497797   0.222222   0.222026  0.223889   \n",
      "737    0.022676   0.644015   0.595238   0.131425   0.141723  0.185236   \n",
      "738    0.083333   0.146259   0.291667   0.316327   0.416667  0.479592   \n",
      "739    0.010959   0.393631   0.561644   0.301911   0.208219  0.280255   \n",
      "740    0.034031   0.186301   0.232984   0.228311   0.348168  0.463927   \n",
      "741    0.096296   0.125000   0.207407   0.214623   0.192593  0.533019   \n",
      "742    0.011364   0.089595   0.204545   0.323699   0.227273  0.421965   \n",
      "743    0.016529   0.192308   0.297521   0.353846   0.280992  0.215385   \n",
      "744    0.011905   0.100000   0.142857   0.354167   0.190476  0.341667   \n",
      "745    0.140845   0.175879   0.154930   0.110553   0.112676  0.316583   \n",
      "746    0.084906   0.215470   0.207547   0.096685   0.169811  0.342541   \n",
      "747    0.017331   0.307653   0.407279   0.266092   0.289428  0.287886   \n",
      "748    0.073733   0.252712   0.301843   0.257817   0.271889  0.408424   \n",
      "749    0.183406   0.283824   0.288210   0.213235   0.253275  0.295588   \n",
      "750    0.156863   0.228321   0.189542   0.161361   0.156863  0.398463   \n",
      "751    0.198276   0.184100   0.163793   0.163180   0.215517  0.376569   \n",
      "752    0.344828   0.211139   0.217570   0.184929   0.176519  0.259920   \n",
      "753    0.082524   0.315005   0.315534   0.387698   0.378641  0.213420   \n",
      "754    0.122383   0.243743   0.260870   0.248510   0.222222  0.339094   \n",
      "755    0.063647   0.284878   0.325581   0.428443   0.392901  0.169217   \n",
      "756    0.040816   0.327942   0.348073   0.326146   0.325397  0.226864   \n",
      "757    0.044053   0.340206   0.344714   0.348606   0.339207  0.245514   \n",
      "758    0.095673   0.363052   0.351005   0.216598   0.249238  0.237153   \n",
      "759    0.054054   0.179592   0.236486   0.353061   0.290541  0.322449   \n",
      "760    0.083488   0.404628   0.463822   0.296435   0.267161  0.175735   \n",
      "761    0.055128   0.336353   0.339744   0.395531   0.382051  0.192029   \n",
      "762    0.030769   0.203883   0.184615   0.258900   0.169231  0.187702   \n",
      "763    0.288462   0.212451   0.196154   0.160079   0.184615  0.181818   \n",
      "764    0.254941   0.218399   0.243083   0.211668   0.199605  0.369484   \n",
      "765    0.216301   0.315985   0.347962   0.235440   0.231975  0.260223   \n",
      "766    0.039829   0.308293   0.379801   0.294634   0.277383  0.279512   \n",
      "767    0.218750   0.159763   0.229167   0.130178   0.145833  0.378698   \n",
      "768    0.008850   0.154829   0.237168   0.370361   0.364602  0.428115   \n",
      "769    0.123321   0.223161   0.178266   0.261176   0.269841  0.376276   \n",
      "770    0.034566   0.276856   0.270900   0.398836   0.430868  0.256477   \n",
      "771    0.052045   0.155556   0.167286   0.322222   0.368030  0.412500   \n",
      "772    0.030075   0.257782   0.259398   0.355058   0.357143  0.277237   \n",
      "773    0.025701   0.254626   0.252336   0.485463   0.457944  0.209692   \n",
      "774    0.029380   0.278988   0.376496   0.352704   0.340588  0.289481   \n",
      "775    0.063001   0.334006   0.361970   0.328756   0.305842  0.242730   \n",
      "776    0.026316   0.278297   0.308271   0.314642   0.421053  0.197300   \n",
      "777    0.029553   0.298105   0.337859   0.427472   0.409744  0.217880   \n",
      "778    0.041667   0.433079   0.295139   0.239391   0.270833  0.253536   \n",
      "779    0.040000   0.314214   0.307273   0.326683   0.281818  0.272652   \n",
      "780    0.090164   0.220767   0.243169   0.090739   0.114754  0.497661   \n",
      "781    0.055512   0.321641   0.374511   0.312559   0.304144  0.273411   \n",
      "782    0.036795   0.299637   0.346688   0.310533   0.315617  0.312954   \n",
      "783    0.027100   0.327575   0.387534   0.393355   0.382114  0.213068   \n",
      "784    0.092961   0.329942   0.275564   0.278585   0.292165  0.264777   \n",
      "785    0.043445   0.334999   0.409299   0.367605   0.333841  0.255851   \n",
      "786    0.023339   0.188852   0.251346   0.273443   0.310592  0.353443   \n",
      "787    0.070381   0.311864   0.293255   0.239548   0.302053  0.254237   \n",
      "788    0.007463   0.255814   0.253731   0.334884   0.335821  0.251163   \n",
      "789    0.125000   0.164404   0.175000   0.245852   0.210000  0.497738   \n",
      "790    0.074349   0.252376   0.315985   0.371700   0.321561  0.220169   \n",
      "791    0.064286   0.200333   0.285714   0.319202   0.283333  0.375727   \n",
      "792    0.112518   0.276081   0.298172   0.231552   0.215190  0.328880   \n",
      "793    0.050336   0.242759   0.305369   0.257931   0.181208  0.402759   \n",
      "794    0.092166   0.257384   0.308756   0.234880   0.248848  0.406470   \n",
      "795    0.097421   0.245655   0.209169   0.221321   0.220630  0.324450   \n",
      "796    0.051491   0.224339   0.303523   0.328211   0.363144  0.318992   \n",
      "797    0.055556   0.268127   0.295019   0.181269   0.183908  0.434290   \n",
      "798    0.055010   0.267436   0.353635   0.300231   0.214145  0.302079   \n",
      "799    0.100386   0.351605   0.343629   0.235709   0.249035  0.288175   \n",
      "800    0.097087   0.298982   0.262136   0.241730   0.213592  0.329517   \n",
      "801    0.000000   0.236915   0.257143   0.380165   0.304762  0.336088   \n",
      "802    0.064516   0.212744   0.272401   0.346351   0.333333  0.361768   \n",
      "803    0.044164   0.233853   0.277603   0.289532   0.299685  0.400891   \n",
      "804    0.076056   0.203279   0.287324   0.250273   0.208451  0.432787   \n",
      "805    0.054348   0.246817   0.385870   0.441724   0.372283  0.277179   \n",
      "806    0.048110   0.200240   0.237113   0.196643   0.185567  0.474820   \n",
      "807    0.077039   0.351530   0.330816   0.181764   0.205438  0.352130   \n",
      "808    0.042386   0.304617   0.259027   0.328524   0.350078  0.263397   \n",
      "809    0.213483   0.290323   0.191011   0.133641   0.134831  0.373272   \n",
      "810    0.167630   0.279584   0.317919   0.191157   0.184971  0.299090   \n",
      "811    0.051643   0.346354   0.262911   0.220052   0.276995  0.291667   \n",
      "812    0.049774   0.372917   0.330317   0.222917   0.239819  0.291667   \n",
      "813    0.034247   0.282810   0.337900   0.349353   0.308219  0.269871   \n",
      "814    0.014652   0.258936   0.355311   0.367752   0.391941  0.308181   \n",
      "815    0.142661   0.330591   0.331962   0.129049   0.130316  0.350643   \n",
      "816    0.069069   0.179342   0.273273   0.311010   0.246246  0.460840   \n",
      "817    0.040000   0.336460   0.393333   0.309496   0.296667  0.277843   \n",
      "818    0.032680   0.343728   0.444444   0.319473   0.259259  0.298683   \n",
      "819    0.058480   0.143369   0.187135   0.120072   0.187135  0.473118   \n",
      "820    0.079268   0.278689   0.317073   0.291803   0.219512  0.352459   \n",
      "821    0.055046   0.284051   0.422018   0.245634   0.197248  0.391153   \n",
      "822    0.062500   0.236842   0.287500   0.255639   0.262500  0.454887   \n",
      "823    0.058140   0.298126   0.418605   0.236797   0.250000  0.357751   \n",
      "824    0.040359   0.231334   0.358744   0.263158   0.237668  0.421053   \n",
      "825    0.073095   0.270963   0.236392   0.196429   0.183515  0.428571   \n",
      "826    0.193627   0.250712   0.286765   0.235518   0.215686  0.377018   \n",
      "827    0.131372   0.324027   0.395691   0.211464   0.234367  0.285120   \n",
      "828    0.058394   0.456311   0.518248   0.155340   0.197080  0.310680   \n",
      "829    0.049430   0.244468   0.235741   0.331928   0.269962  0.347734   \n",
      "830    0.053254   0.292352   0.396450   0.291384   0.254438  0.355276   \n",
      "831    0.037702   0.214696   0.262118   0.293291   0.256732  0.373802   \n",
      "832    0.053061   0.201435   0.236735   0.237298   0.263265  0.485356   \n",
      "833    0.032520   0.209877   0.195122   0.276543   0.325203  0.437037   \n",
      "834    0.060870   0.243542   0.260870   0.232472   0.260870  0.457565   \n",
      "835    0.101266   0.241379   0.278481   0.190669   0.210970  0.452333   \n",
      "836    0.035714   0.214592   0.214286   0.450644   0.196429  0.317597   \n",
      "837    0.022409   0.241013   0.271709   0.360294   0.313725  0.330882   \n",
      "838    0.031915   0.355856   0.443769   0.141141   0.194529  0.319820   \n",
      "839    0.073222   0.210680   0.320084   0.310168   0.251046  0.369422   \n",
      "840    0.014286   0.084112   0.128571   0.140187   0.271429  0.682243   \n",
      "841    0.053299   0.261006   0.380711   0.375000   0.342640  0.312893   \n",
      "842    0.011628   0.173333   0.203488   0.287619   0.226744  0.447619   \n",
      "843    0.026316   0.218935   0.219298   0.159763   0.175439  0.514793   \n",
      "844    0.036810   0.262391   0.306748   0.515306   0.420245  0.196064   \n",
      "845    0.036145   0.391304   0.283133   0.337391   0.295181  0.215652   \n",
      "846    0.041958   0.273101   0.384615   0.441478   0.398601  0.180698   \n",
      "847    0.028169   0.263948   0.288732   0.369099   0.260563  0.332618   \n",
      "848    0.059701   0.346939   0.328358   0.224490   0.164179  0.367347   \n",
      "849    0.014174   0.380010   0.462084   0.384838   0.338058  0.210164   \n",
      "850    0.122449   0.250450   0.357143   0.234234   0.204082  0.403604   \n",
      "851    0.010959   0.187062   0.282192   0.380359   0.400000  0.381917   \n",
      "852    0.053459   0.239403   0.298742   0.363422   0.349057  0.343799   \n",
      "853    0.050794   0.333016   0.380952   0.300666   0.292063  0.235966   \n",
      "854    0.077348   0.207921   0.220994   0.171617   0.209945  0.415842   \n",
      "855    0.044776   0.222857   0.149254   0.280000   0.179104  0.371429   \n",
      "856    0.126984   0.126829   0.126984   0.321951   0.301587  0.478049   \n",
      "857    0.008696   0.191571   0.156522   0.325670   0.269565  0.360153   \n",
      "858    0.049587   0.304000   0.239669   0.180000   0.181818  0.292000   \n",
      "859    0.067568   0.120000   0.162162   0.500000   0.540541  0.340000   \n",
      "860    0.012136   0.269048   0.330097   0.428571   0.461165  0.257619   \n",
      "861    0.058824   0.166667   0.176471   0.311594   0.313725  0.398551   \n",
      "862    0.111588   0.273927   0.291845   0.255776   0.227468  0.334983   \n",
      "863    0.041667   0.101911   0.187500   0.522293   0.333333  0.312102   \n",
      "864    0.027972   0.247423   0.202797   0.461340   0.468531  0.255155   \n",
      "865    0.027778   0.206485   0.333333   0.283276   0.314815  0.452218   \n",
      "866    0.038462   0.288000   0.250000   0.144000   0.057692  0.520000   \n",
      "867    0.423810   0.273438   0.271429   0.205078   0.176190  0.173828   \n",
      "868    0.223684   0.420370   0.322368   0.212963   0.309211  0.168519   \n",
      "869    0.303125   0.226244   0.268750   0.204374   0.159375  0.228507   \n",
      "870    0.038095   0.407407   0.295238   0.373737   0.438095  0.178451   \n",
      "871    0.075000   0.167136   0.257143   0.342723   0.375000  0.352113   \n",
      "872    0.160211   0.278173   0.279930   0.173604   0.158451  0.371066   \n",
      "873    0.091255   0.255183   0.224335   0.100478   0.209125  0.440191   \n",
      "874    0.184932   0.202189   0.267123   0.265293   0.226027  0.300708   \n",
      "875    0.076283   0.270358   0.326630   0.306574   0.316227  0.315802   \n",
      "876    0.119048   0.282776   0.190476   0.190231   0.269841  0.421594   \n",
      "877    0.137652   0.283991   0.307692   0.242325   0.238866  0.242325   \n",
      "878    0.087500   0.343249   0.350000   0.251716   0.237500  0.338673   \n",
      "879    0.024259   0.330448   0.305481   0.399701   0.431267  0.233433   \n",
      "880    0.076923   0.202247   0.307692   0.243446   0.346154  0.513109   \n",
      "881    0.022831   0.261128   0.433790   0.385757   0.305936  0.284866   \n",
      "882    0.036885   0.270165   0.266393   0.419825   0.397541  0.293489   \n",
      "883    0.084507   0.360331   0.346076   0.302479   0.344064  0.254545   \n",
      "884    0.114754   0.272382   0.302108   0.328547   0.377049  0.277449   \n",
      "885    0.104433   0.231551   0.244929   0.343937   0.305034  0.317601   \n",
      "886    0.101240   0.285802   0.266529   0.449816   0.394628  0.167687   \n",
      "887    0.032710   0.193717   0.242991   0.326103   0.292056  0.413613   \n",
      "888    0.067864   0.198328   0.210579   0.303191   0.338323  0.381459   \n",
      "889    0.097691   0.216095   0.268206   0.312469   0.248668  0.343766   \n",
      "890    0.119122   0.263267   0.376176   0.221227   0.231975  0.325293   \n",
      "891    0.032480   0.312920   0.377889   0.365073   0.306683  0.238246   \n",
      "892    0.110000   0.132812   0.146667   0.170759   0.206667  0.534598   \n",
      "893    0.106204   0.283837   0.309148   0.257556   0.238696  0.285808   \n",
      "894    0.022247   0.226654   0.291435   0.334630   0.322581  0.374514   \n",
      "895    0.067002   0.218366   0.328308   0.308596   0.335008  0.345435   \n",
      "896    0.010101   0.279018   0.565657   0.301339   0.252525  0.377232   \n",
      "897    0.051195   0.276328   0.391126   0.311510   0.252560  0.328518   \n",
      "898    0.153322   0.262795   0.269165   0.248994   0.228279  0.377228   \n",
      "899    0.108033   0.217355   0.349030   0.342881   0.296399  0.304971   \n",
      "900    0.319876   0.160772   0.254658   0.131833   0.127329  0.310825   \n",
      "901    0.375669   0.210106   0.210406   0.154461   0.109411  0.323633   \n",
      "902    0.146693   0.303811   0.334971   0.222188   0.167976  0.333128   \n",
      "903    0.103665   0.297657   0.412565   0.208031   0.183770  0.315335   \n",
      "904    0.284397   0.279874   0.266718   0.205260   0.127594  0.321326   \n",
      "905    0.061770   0.270567   0.248748   0.309567   0.353923  0.322364   \n",
      "906    0.067362   0.407019   0.426945   0.328509   0.324478  0.203329   \n",
      "907    0.047022   0.243550   0.275862   0.390093   0.347962  0.292054   \n",
      "908    0.084806   0.315084   0.236749   0.309497   0.349823  0.269274   \n",
      "909    0.125261   0.226344   0.258873   0.197578   0.235908  0.265708   \n",
      "910    0.137681   0.208861   0.289855   0.268354   0.275362  0.350633   \n",
      "911    0.121212   0.299444   0.338118   0.245321   0.248804  0.249874   \n",
      "912    0.250274   0.268872   0.344469   0.176542   0.130887  0.317573   \n",
      "913    0.122980   0.160726   0.154603   0.146792   0.148981  0.434219   \n",
      "914    0.253835   0.257227   0.286492   0.154299   0.126175  0.314123   \n",
      "915    0.338530   0.183700   0.258352   0.102199   0.066815  0.219276   \n",
      "916    0.054326   0.242131   0.309859   0.312954   0.340040  0.367433   \n",
      "917    0.376233   0.230150   0.184041   0.189291   0.123552  0.358092   \n",
      "918    0.296449   0.192916   0.184145   0.124605   0.096614  0.352625   \n",
      "919    0.222947   0.197147   0.260756   0.182883   0.166232  0.303598   \n",
      "920    0.129715   0.270109   0.317387   0.194389   0.206992  0.346822   \n",
      "921    0.278750   0.284085   0.313750   0.128904   0.110000  0.326475   \n",
      "922    0.211627   0.240012   0.257356   0.186742   0.145339  0.394791   \n",
      "923    0.089147   0.268754   0.389535   0.278539   0.251938  0.353555   \n",
      "924    0.184211   0.168582   0.223684   0.206897   0.144737  0.375479   \n",
      "925    0.046257   0.232402   0.308663   0.343632   0.355761  0.350081   \n",
      "926    0.058411   0.255418   0.309969   0.329760   0.359813  0.289210   \n",
      "927    0.333910   0.162850   0.235294   0.204198   0.159170  0.243003   \n",
      "928    0.086372   0.216045   0.281190   0.270639   0.252399  0.344874   \n",
      "929    0.064138   0.264458   0.280690   0.311044   0.281379  0.266064   \n",
      "930    0.037736   0.140363   0.152291   0.377435   0.373315  0.305574   \n",
      "931    0.108216   0.324577   0.286573   0.311734   0.332665  0.193812   \n",
      "932    0.108192   0.231754   0.282844   0.224645   0.293663  0.256398   \n",
      "933    0.110169   0.340525   0.300847   0.260788   0.222458  0.222326   \n",
      "934    0.078640   0.306744   0.303932   0.343061   0.385760  0.188392   \n",
      "935    0.018100   0.211358   0.312217   0.298595   0.303167  0.416276   \n",
      "936    0.078667   0.272732   0.336950   0.391235   0.350126  0.279141   \n",
      "937    0.000000   0.186937   0.226667   0.399775   0.333333  0.350225   \n",
      "938    0.022646   0.232331   0.325387   0.458617   0.432658  0.287353   \n",
      "939    0.117978   0.240307   0.363764   0.158226   0.167135  0.347538   \n",
      "940    0.074116   0.242133   0.266819   0.406701   0.367161  0.298408   \n",
      "941    0.028131   0.317164   0.351180   0.435470   0.441016  0.206980   \n",
      "942    0.030641   0.380920   0.425627   0.396162   0.357660  0.180593   \n",
      "943    0.236301   0.218728   0.204338   0.143912   0.103881  0.422683   \n",
      "944    0.037862   0.215522   0.282851   0.358050   0.332591  0.364108   \n",
      "945    0.023551   0.314504   0.336051   0.444275   0.460145  0.215703   \n",
      "946    0.002045   0.309722   0.327198   0.532346   0.443763  0.120708   \n",
      "947    0.040850   0.224907   0.338235   0.280669   0.339869  0.245973   \n",
      "948    0.064417   0.195373   0.239264   0.450669   0.361963  0.336120   \n",
      "949    0.053132   0.255296   0.327976   0.388313   0.338144  0.299733   \n",
      "950    0.033663   0.312627   0.394059   0.381837   0.368317  0.259959   \n",
      "951    0.085463   0.317579   0.389427   0.351023   0.289868  0.247374   \n",
      "952    0.361446   0.215032   0.213855   0.126929   0.126506  0.198606   \n",
      "953    0.192157   0.180104   0.205229   0.136382   0.138562  0.403129   \n",
      "954    0.094063   0.193128   0.281419   0.323081   0.306862  0.382377   \n",
      "955    0.131641   0.170501   0.224321   0.272566   0.228453  0.391544   \n",
      "956    0.069863   0.199705   0.193151   0.222680   0.228767  0.465390   \n",
      "957    0.087425   0.303593   0.355689   0.276948   0.295808  0.271700   \n",
      "958    0.216917   0.179310   0.218281   0.239015   0.190314  0.347980   \n",
      "959    0.045356   0.204184   0.252700   0.330878   0.341253  0.389806   \n",
      "960    0.098930   0.172830   0.245989   0.221887   0.252674  0.387547   \n",
      "961    0.034000   0.214184   0.252000   0.395899   0.332000  0.311307   \n",
      "962    0.023810   0.181058   0.203869   0.279109   0.250000  0.472981   \n",
      "963    0.206388   0.251732   0.267813   0.099307   0.093366  0.413395   \n",
      "964    0.150000   0.249588   0.280303   0.255635   0.186364  0.251237   \n",
      "965    0.167164   0.211498   0.294030   0.161392   0.149254  0.415612   \n",
      "966    0.174242   0.265255   0.242424   0.110212   0.092803  0.409714   \n",
      "967    0.071174   0.269504   0.274021   0.208511   0.281139  0.458156   \n",
      "968    0.024279   0.407387   0.452200   0.332971   0.330804  0.204780   \n",
      "969    0.296467   0.278256   0.251920   0.049140   0.046083  0.342752   \n",
      "970    0.141509   0.190722   0.254717   0.230241   0.226415  0.170103   \n",
      "971    0.065711   0.729671   0.677419   0.094687   0.086022  0.138778   \n",
      "972    0.076821   0.372662   0.380132   0.219664   0.251656  0.294005   \n",
      "973    0.038722   0.417195   0.460794   0.219521   0.219748  0.261099   \n",
      "974    0.118531   0.350399   0.340568   0.182181   0.196995  0.292553   \n",
      "975    0.200867   0.296592   0.343931   0.126198   0.163295  0.255591   \n",
      "976    0.079399   0.194933   0.206009   0.236616   0.263948  0.405394   \n",
      "977    0.000000   0.766949   0.704301   0.148910   0.177419  0.073850   \n",
      "978    0.008006   0.877242   0.869496   0.068736   0.078463  0.034469   \n",
      "979    0.120650   0.225701   0.273782   0.176778   0.169374  0.257665   \n",
      "980    0.091733   0.293122   0.312571   0.202311   0.185730  0.346051   \n",
      "981    0.121569   0.320534   0.364706   0.160267   0.152941  0.353088   \n",
      "982    0.178155   0.249639   0.306469   0.168831   0.171792  0.365440   \n",
      "983    0.076000   0.289769   0.332000   0.186799   0.220000  0.340594   \n",
      "984    0.055227   0.251977   0.280079   0.311488   0.287968  0.337476   \n",
      "985    0.022624   0.277620   0.298643   0.273371   0.244344  0.361190   \n",
      "986    0.122278   0.242262   0.278057   0.226190   0.221106  0.350595   \n",
      "987    0.037422   0.160656   0.185031   0.244809   0.201663  0.426230   \n",
      "988    0.093750   0.250958   0.229167   0.208812   0.208333  0.342912   \n",
      "989    0.052747   0.221617   0.261538   0.353315   0.329670  0.303361   \n",
      "990    0.047146   0.418605   0.414392   0.236279   0.210918  0.253953   \n",
      "991    0.065632   0.254177   0.303103   0.311899   0.315036  0.297722   \n",
      "992    0.029340   0.318283   0.334963   0.390081   0.383863  0.247964   \n",
      "993    0.088000   0.269036   0.288000   0.243655   0.216000  0.296954   \n",
      "994    0.019305   0.383808   0.332046   0.184408   0.262548  0.323838   \n",
      "995    0.040123   0.307500   0.305556   0.350000   0.225309  0.251250   \n",
      "996    0.066116   0.226136   0.210744   0.240909   0.272727  0.438636   \n",
      "997    0.062500   0.136951   0.132812   0.343669   0.328125  0.379845   \n",
      "998    0.120211   0.269211   0.299868   0.304796   0.301189  0.290872   \n",
      "999    0.039121   0.259259   0.297186   0.411802   0.373370  0.258318   \n",
      "1000   0.112500   0.334755   0.378571   0.214641   0.241071  0.338308   \n",
      "1001   0.104000   0.214204   0.264000   0.224513   0.254400  0.341352   \n",
      "1002   0.073643   0.277003   0.275194   0.167247   0.240310  0.318815   \n",
      "1003   0.195364   0.228776   0.268212   0.174263   0.185430  0.302949   \n",
      "1004   0.137931   0.305882   0.365517   0.155556   0.158621  0.189542   \n",
      "1005   0.189759   0.291026   0.280120   0.226923   0.274096  0.297436   \n",
      "1006   0.089744   0.241554   0.350427   0.293919   0.273504  0.271959   \n",
      "1007   0.014493   0.300439   0.316770   0.320724   0.356108  0.348136   \n",
      "1008   0.168394   0.201431   0.303109   0.267894   0.256477  0.340491   \n",
      "1009   0.098039   0.065327   0.156863   0.120603   0.078431  0.502513   \n",
      "1010   0.048780   0.265805   0.253049   0.211207   0.207317  0.442529   \n",
      "1011   0.029167   0.388444   0.405556   0.247140   0.211111  0.278032   \n",
      "1012   0.076923   0.319797   0.343195   0.251269   0.207101  0.331218   \n",
      "1013   0.036697   0.315615   0.339450   0.227575   0.197248  0.320598   \n",
      "1014   0.088172   0.270030   0.219355   0.222552   0.262366  0.394659   \n",
      "1015   0.039568   0.288721   0.276978   0.319024   0.366906  0.334175   \n",
      "1016   0.061728   0.322275   0.296296   0.203791   0.203704  0.267773   \n",
      "1017   0.036458   0.268966   0.307292   0.232759   0.210938  0.378448   \n",
      "1018   0.072269   0.469261   0.349580   0.201354   0.226891  0.219966   \n",
      "1019   0.022298   0.439385   0.478559   0.247191   0.221269  0.261384   \n",
      "1020   0.058097   0.365410   0.408134   0.225748   0.265795  0.289207   \n",
      "1021   0.036662   0.197730   0.219975   0.371454   0.380531  0.347883   \n",
      "1022   0.039742   0.281557   0.274973   0.293925   0.293233  0.325209   \n",
      "1023   0.147541   0.283917   0.358834   0.249775   0.214936  0.308625   \n",
      "1024   0.102410   0.281800   0.210843   0.248532   0.240964  0.315068   \n",
      "1025   0.094812   0.226938   0.398927   0.308792   0.225403  0.407103   \n",
      "1026   0.056818   0.212406   0.221591   0.289474   0.187500  0.424812   \n",
      "1027   0.027027   0.356295   0.394595   0.318290   0.345946  0.259857   \n",
      "1028   0.054422   0.174242   0.306122   0.308712   0.278912  0.375000   \n",
      "1029   0.041215   0.166337   0.195228   0.353135   0.312364  0.415842   \n",
      "1030   0.019259   0.325949   0.380741   0.338924   0.358519  0.292089   \n",
      "1031   0.008730   0.354738   0.419841   0.430798   0.375397  0.184227   \n",
      "1032   0.014286   0.462085   0.385714   0.312796   0.364286  0.156398   \n",
      "1033   0.013222   0.389901   0.395268   0.361203   0.386221  0.214128   \n",
      "1034   0.142857   0.242424   0.250000   0.181818   0.285714  0.414141   \n",
      "1035   0.018519   0.194521   0.166667   0.345205   0.370370  0.391781   \n",
      "1036   0.139706   0.159406   0.316176   0.207921   0.176471  0.397030   \n",
      "1037   0.033981   0.321632   0.344660   0.331120   0.349515  0.301708   \n",
      "1038   0.053191   0.262705   0.281915   0.289406   0.281915  0.406546   \n",
      "1039   0.039683   0.476107   0.464853   0.323542   0.332200  0.175800   \n",
      "1040   0.027442   0.377182   0.457739   0.390898   0.348518  0.197423   \n",
      "1041   0.020000   0.212903   0.215000   0.246452   0.320000  0.438710   \n",
      "1042   0.030120   0.250000   0.319277   0.394231   0.373494  0.290385   \n",
      "1043   0.019034   0.255038   0.327965   0.374055   0.363104  0.323678   \n",
      "1044   0.046809   0.272328   0.217021   0.346999   0.387234  0.336750   \n",
      "1045   0.069767   0.235169   0.145349   0.256356   0.267442  0.290254   \n",
      "1046   0.094961   0.175593   0.257752   0.302019   0.302326  0.381036   \n",
      "1047   0.062529   0.336475   0.397992   0.291977   0.318576  0.268523   \n",
      "1048   0.048780   0.312500   0.390244   0.298611   0.317073  0.256944   \n",
      "1049   0.035714   0.178404   0.366071   0.276995   0.348214  0.446009   \n",
      "1050   0.049180   0.158568   0.221311   0.253197   0.204918  0.401535   \n",
      "1051   0.007576   0.311355   0.386364   0.329670   0.348485  0.285714   \n",
      "1052   0.032680   0.297872   0.392157   0.365248   0.379085  0.290780   \n",
      "1053   0.022222   0.343750   0.266667   0.226562   0.233333  0.281250   \n",
      "1054   0.115144   0.204715   0.275344   0.172457   0.222778  0.447891   \n",
      "1055   0.023904   0.211207   0.330677   0.340517   0.346614  0.323276   \n",
      "1056   0.030405   0.211889   0.378378   0.354746   0.344595  0.399808   \n",
      "1057   0.000000   0.279412   0.305556   0.279412   0.444444  0.220588   \n",
      "1058   0.012552   0.525407   0.686192   0.150407   0.142259  0.164634   \n",
      "1059   0.030303   0.246835   0.272727   0.294304   0.261364  0.405063   \n",
      "1060   0.053333   0.259709   0.446667   0.378641   0.220000  0.286408   \n",
      "1061   0.044304   0.267898   0.297468   0.221709   0.208861  0.265589   \n",
      "1062   0.054496   0.257965   0.294278   0.262076   0.242507  0.320658   \n",
      "1063   0.101124   0.147826   0.168539   0.327536   0.252809  0.379710   \n",
      "1064   0.000000   0.151436   0.162162   0.467363   0.531532  0.334204   \n",
      "1065   0.046229   0.179567   0.231144   0.227038   0.274939  0.437564   \n",
      "1066   0.094241   0.265525   0.225131   0.291221   0.418848  0.299786   \n",
      "1067   0.126263   0.403417   0.429293   0.172142   0.166667  0.303548   \n",
      "1068   0.035623   0.289308   0.323155   0.266846   0.312977  0.316262   \n",
      "1069   0.029221   0.482911   0.512987   0.287762   0.227273  0.184123   \n",
      "1070   0.011236   0.696275   0.674157   0.131805   0.134831  0.088825   \n",
      "1071   0.025901   0.504587   0.511261   0.276758   0.305180  0.169725   \n",
      "1072   0.054545   0.278585   0.342149   0.349968   0.304132  0.293746   \n",
      "1073   0.071691   0.327788   0.356618   0.240912   0.242647  0.357363   \n",
      "1074   0.023973   0.263626   0.253425   0.230256   0.215753  0.368187   \n",
      "1075   0.041754   0.209915   0.260960   0.168087   0.212944  0.459334   \n",
      "1076   0.055866   0.229885   0.284916   0.237548   0.184358  0.454023   \n",
      "1077   0.026502   0.230337   0.252650   0.268258   0.259717  0.383427   \n",
      "1078   0.018868   0.526882   0.547170   0.172043   0.207547  0.161290   \n",
      "1079   0.034843   0.268991   0.254355   0.249066   0.163763  0.366127   \n",
      "1080   0.038917   0.190739   0.241963   0.304768   0.250423  0.364893   \n",
      "1081   0.052632   0.222611   0.263158   0.203963   0.198381  0.510490   \n",
      "1082   0.057221   0.226891   0.267030   0.241597   0.228883  0.439076   \n",
      "1083   0.055804   0.180254   0.189732   0.307971   0.223214  0.450181   \n",
      "1084   0.017143   0.257742   0.300000   0.216783   0.208571  0.387612   \n",
      "1085   0.025000   0.107356   0.130000   0.435388   0.435000  0.389662   \n",
      "1086   0.042517   0.219083   0.173469   0.188952   0.159864  0.495920   \n",
      "1087   0.187500   0.037975   0.137500   0.227848   0.137500  0.687764   \n",
      "1088   0.050147   0.359128   0.371681   0.215904   0.216814  0.344164   \n",
      "1089   0.037037   0.329596   0.343915   0.218262   0.233862  0.326392   \n",
      "1090   0.110803   0.371838   0.390582   0.223389   0.204986  0.296897   \n",
      "1091   0.047923   0.389796   0.394569   0.222959   0.230032  0.262755   \n",
      "1092   0.032374   0.324575   0.316547   0.173107   0.230216  0.431221   \n",
      "1093   0.087838   0.397231   0.341216   0.203408   0.199324  0.336528   \n",
      "1094   0.036775   0.224747   0.224894   0.320707   0.297030  0.377273   \n",
      "1095   0.061644   0.320215   0.373973   0.222272   0.209589  0.328712   \n",
      "1096   0.045000   0.462745   0.455000   0.192157   0.215000  0.275817   \n",
      "1097   0.031250   0.182073   0.229167   0.168067   0.187500  0.512605   \n",
      "1098   0.022222   0.353261   0.303704   0.206522   0.185185  0.380435   \n",
      "1099   0.062842   0.337634   0.352459   0.230108   0.191257  0.298925   \n",
      "1100   0.051802   0.337031   0.380631   0.233788   0.279279  0.388225   \n",
      "1101   0.055556   0.284289   0.238095   0.208229   0.212698  0.382793   \n",
      "1102   0.107884   0.505102   0.452282   0.265306   0.278008  0.186224   \n",
      "1103   0.110236   0.238173   0.334646   0.313214   0.263780  0.298532   \n",
      "1104   0.051700   0.456545   0.486726   0.279120   0.286446  0.188244   \n",
      "1105   0.038095   0.235294   0.200000   0.323529   0.295238  0.254902   \n",
      "1106   0.033333   0.277778   0.200000   0.305556   0.283333  0.250000   \n",
      "1107   0.086294   0.183862   0.243655   0.206349   0.279188  0.496032   \n",
      "1108   0.293515   0.167243   0.225256   0.131488   0.126280  0.250288   \n",
      "1109   0.090909   0.288265   0.391608   0.198980   0.125874  0.341837   \n",
      "1110   0.027027   0.264516   0.189189   0.232258   0.333333  0.367742   \n",
      "1111   0.062718   0.256966   0.303136   0.218782   0.289199  0.299278   \n",
      "1112   0.042394   0.288288   0.334165   0.214214   0.274314  0.374374   \n",
      "1113   0.067797   0.220567   0.250471   0.285106   0.291902  0.323404   \n",
      "1114   0.069395   0.286300   0.345196   0.285129   0.279359  0.320258   \n",
      "1115   0.059540   0.297861   0.263870   0.241176   0.251691  0.341176   \n",
      "1116   0.043478   0.222892   0.130435   0.156627   0.260870  0.289157   \n",
      "1117   0.046667   0.171901   0.246667   0.262810   0.253333  0.421488   \n",
      "1118   0.029412   0.141414   0.151961   0.267677   0.308824  0.373737   \n",
      "1119   0.067961   0.261789   0.233010   0.373984   0.441748  0.211382   \n",
      "1120   0.011429   0.229268   0.217143   0.253659   0.211429  0.363415   \n",
      "1121   0.183432   0.403306   0.242604   0.196694   0.242604  0.233058   \n",
      "1122   0.063978   0.295208   0.305914   0.308125   0.317742  0.277083   \n",
      "1123   0.120482   0.255649   0.277108   0.202711   0.226908  0.349258   \n",
      "1124   0.115741   0.301907   0.312500   0.286017   0.247685  0.272246   \n",
      "1125   0.114007   0.275202   0.312704   0.205645   0.159609  0.360887   \n",
      "1126   0.069162   0.246234   0.267766   0.338791   0.317259  0.301681   \n",
      "1127   0.082902   0.209551   0.269430   0.275281   0.259067  0.379775   \n",
      "1128   0.030864   0.285714   0.314815   0.333591   0.240741  0.324324   \n",
      "1129   0.032512   0.526743   0.544310   0.223653   0.255375  0.185618   \n",
      "1130   0.119718   0.417879   0.426056   0.176715   0.225352  0.220374   \n",
      "1131   0.163507   0.207836   0.345972   0.182851   0.218009  0.200454   \n",
      "1132   0.044088   0.630643   0.629259   0.199042   0.154309  0.112859   \n",
      "1133   0.063032   0.726872   0.696763   0.125795   0.102215  0.104258   \n",
      "1134   0.050167   0.313099   0.277592   0.291800   0.321070  0.298190   \n",
      "1135   0.156076   0.151585   0.204013   0.151915   0.139353  0.348085   \n",
      "1136   0.271357   0.197509   0.180905   0.179715   0.170854  0.302491   \n",
      "1137   0.009709   0.125811   0.291262   0.370947   0.330097  0.461738   \n",
      "1138   0.063025   0.594343   0.579832   0.207284   0.173319  0.114297   \n",
      "1139   0.115385   0.434174   0.333333   0.198880   0.282051  0.235294   \n",
      "1140   0.073333   0.399478   0.393333   0.206266   0.268333  0.268930   \n",
      "1141   0.101633   0.384071   0.392922   0.252035   0.239564  0.237168   \n",
      "1142   0.108527   0.358537   0.387597   0.178049   0.108527  0.304878   \n",
      "1143   0.138298   0.281361   0.340426   0.260099   0.223404  0.265769   \n",
      "1144   0.265734   0.184362   0.160839   0.175309   0.136364  0.372016   \n",
      "1145   0.199170   0.200253   0.298755   0.225602   0.178423  0.361217   \n",
      "1146   0.108108   0.290657   0.342342   0.183391   0.189189  0.328720   \n",
      "1147   0.113379   0.282140   0.292517   0.281277   0.265306  0.271786   \n",
      "1148   0.183133   0.329502   0.330120   0.204598   0.255422  0.263602   \n",
      "1149   0.183794   0.224749   0.268775   0.231438   0.213439  0.319064   \n",
      "1150   0.158163   0.282555   0.306122   0.185504   0.230867  0.253481   \n",
      "1151   0.424837   0.118655   0.196078   0.174687   0.135076  0.199077   \n",
      "1152   0.072727   0.398352   0.375758   0.267857   0.294949  0.239011   \n",
      "1153   0.117450   0.321117   0.308725   0.302792   0.322148  0.280105   \n",
      "1154   0.070707   0.162080   0.232323   0.250765   0.222222  0.483180   \n",
      "1155   0.143043   0.349799   0.342003   0.259621   0.271782  0.233774   \n",
      "1156   0.021605   0.367238   0.382716   0.213062   0.191358  0.302998   \n",
      "1157   0.024194   0.153704   0.193548   0.350000   0.298387  0.387037   \n",
      "1158   0.066667   0.266892   0.333333   0.258446   0.216667  0.375000   \n",
      "1159   0.044164   0.214623   0.261830   0.273585   0.283912  0.366745   \n",
      "1160   0.277778   0.269006   0.190476   0.169591   0.246032  0.307018   \n",
      "1161   0.088435   0.279743   0.224490   0.109325   0.231293  0.504823   \n",
      "1162   0.058228   0.404784   0.403797   0.292683   0.298734  0.219043   \n",
      "1163   0.042553   0.623945   0.597820   0.189234   0.232486  0.145808   \n",
      "1164   0.081395   0.396923   0.412449   0.265275   0.326265  0.234286   \n",
      "1165   0.065817   0.233542   0.254777   0.293887   0.256900  0.369122   \n",
      "1166   0.034868   0.450665   0.492105   0.330837   0.306579  0.160831   \n",
      "1167   0.035821   0.495468   0.440299   0.257301   0.307463  0.206445   \n",
      "1168   0.063316   0.454625   0.455614   0.276414   0.290470  0.170978   \n",
      "1169   0.018164   0.528462   0.543977   0.275235   0.276291  0.166373   \n",
      "1170   0.016529   0.287809   0.338843   0.277336   0.262810  0.342271   \n",
      "1171   0.025229   0.527255   0.548165   0.269243   0.286697  0.163198   \n",
      "1172   0.026014   0.591206   0.616679   0.247990   0.239480  0.125879   \n",
      "1173   0.013498   0.409140   0.444319   0.347479   0.367829  0.207472   \n",
      "1174   0.021505   0.607589   0.623656   0.246875   0.234767  0.129018   \n",
      "1175   0.031373   0.630115   0.533333   0.203764   0.258824  0.133388   \n",
      "1176   0.046647   0.403243   0.443149   0.324324   0.291545  0.208649   \n",
      "1177   0.013100   0.266432   0.344978   0.302817   0.375546  0.293427   \n",
      "1178   0.037080   0.346220   0.391657   0.396853   0.347625  0.214506   \n",
      "1179   0.046591   0.352041   0.444318   0.270773   0.236364  0.267493   \n",
      "1180   0.065041   0.244576   0.279133   0.248521   0.257453  0.395792   \n",
      "1181   0.069565   0.053595   0.000000   0.205229   0.269565  0.687582   \n",
      "1182   0.062409   0.390897   0.364296   0.258367   0.271408  0.246319   \n",
      "1183   0.067194   0.351810   0.355731   0.308824   0.300395  0.235294   \n",
      "1184   0.164179   0.234082   0.313433   0.249064   0.253731  0.258427   \n",
      "1185   0.088542   0.198864   0.213542   0.099432   0.135417  0.477273   \n",
      "1186   0.138889   0.313837   0.214286   0.184023   0.186508  0.316690   \n",
      "1187   0.032468   0.146245   0.227273   0.334980   0.201299  0.399209   \n",
      "1188   0.052786   0.524390   0.548387   0.219512   0.246334  0.176829   \n",
      "1189   0.022008   0.351786   0.436039   0.351786   0.334938  0.231252   \n",
      "1190   0.056287   0.305158   0.362874   0.254298   0.267066  0.363539   \n",
      "1191   0.067485   0.352273   0.300613   0.250000   0.355828  0.313636   \n",
      "1192   0.054291   0.325112   0.327496   0.290919   0.309982  0.293722   \n",
      "1193   0.040373   0.343500   0.388199   0.323893   0.315217  0.236020   \n",
      "1194   0.013514   0.344262   0.256757   0.202186   0.364865  0.393443   \n",
      "1195   0.009709   0.742537   0.650485   0.145522   0.194175  0.097015   \n",
      "1196   0.077684   0.288670   0.360169   0.310345   0.254237  0.316256   \n",
      "1197   0.014963   0.343405   0.321696   0.416360   0.483791  0.208548   \n",
      "1198   0.018433   0.083045   0.156682   0.207612   0.248848  0.602076   \n",
      "1199   0.033413   0.493361   0.436754   0.242084   0.250597  0.215526   \n",
      "1200   0.110721   0.256890   0.307557   0.284971   0.261863  0.249610   \n",
      "1201   0.059259   0.215524   0.249383   0.337737   0.296296  0.354253   \n",
      "1202   0.054131   0.326027   0.279202   0.382648   0.387464  0.225571   \n",
      "1203   0.026455   0.496760   0.417989   0.228942   0.222222  0.211663   \n",
      "1204   0.011013   0.336483   0.374449   0.355378   0.337004  0.257994   \n",
      "1205   0.021352   0.352315   0.338078   0.294118   0.325623  0.285982   \n",
      "1206   0.020921   0.326316   0.376569   0.392481   0.351464  0.217293   \n",
      "1207   0.013699   0.226852   0.150685   0.268519   0.369863  0.449074   \n",
      "1208   0.000000   0.469194   0.337209   0.118483   0.139535  0.388626   \n",
      "1209   0.051546   0.661818   0.484536   0.141818   0.237113  0.163636   \n",
      "1210   0.070388   0.329897   0.254854   0.189316   0.279126  0.271790   \n",
      "1211   0.116279   0.453608   0.534884   0.170103   0.232558  0.335052   \n",
      "1212   0.028767   0.416325   0.486301   0.292750   0.293151  0.220246   \n",
      "1213   0.040373   0.406250   0.465839   0.379076   0.316770  0.148098   \n",
      "1214   0.121061   0.346333   0.338308   0.220605   0.199005  0.277066   \n",
      "1215   0.017054   0.417662   0.443411   0.341299   0.361240  0.178182   \n",
      "1216   0.011765   0.424855   0.513725   0.361272   0.333333  0.193642   \n",
      "1217   0.013889   0.345555   0.321759   0.296975   0.331019  0.283226   \n",
      "1218   0.019438   0.352734   0.427646   0.368607   0.330454  0.260141   \n",
      "1219   0.072368   0.197339   0.269737   0.268293   0.276316  0.379157   \n",
      "1220   0.027933   0.467797   0.396648   0.334463   0.391061  0.172881   \n",
      "1221   0.042169   0.377404   0.442771   0.382212   0.373494  0.139423   \n",
      "1222   0.032258   0.440000   0.516129   0.360000   0.354839  0.171429   \n",
      "1223   0.051020   0.077295   0.163265   0.357488   0.306122  0.449275   \n",
      "1224   0.250000   0.230769   0.250000   0.461538   0.000000  0.307692   \n",
      "1225   0.111111   0.150943   0.259259   0.320755   0.296296  0.301887   \n",
      "1226   0.098684   0.266667   0.269737   0.277778   0.401316  0.222222   \n",
      "1227   0.024457   0.406205   0.429348   0.380952   0.339674  0.132035   \n",
      "1228   0.322698   0.266968   0.254330   0.133484   0.105743  0.309955   \n",
      "1229   0.245902   0.258199   0.292231   0.164626   0.131148  0.339309   \n",
      "1230   0.202505   0.196805   0.226514   0.102311   0.133612  0.373895   \n",
      "1231   0.198396   0.259151   0.308556   0.132316   0.105348  0.333725   \n",
      "1232   0.040373   0.404040   0.437888   0.204265   0.279503  0.218855   \n",
      "1233   0.073446   0.183071   0.259887   0.185039   0.180791  0.496063   \n",
      "1234   0.051643   0.281667   0.253521   0.216667   0.215962  0.331667   \n",
      "1235   0.045455   0.247525   0.295455   0.316832   0.204545  0.287129   \n",
      "1236   0.098361   0.377163   0.360656   0.134948   0.196721  0.245675   \n",
      "1237   0.031496   0.229529   0.173228   0.320438   0.244094  0.395874   \n",
      "1238   0.056680   0.277487   0.291498   0.218586   0.251012  0.397906   \n",
      "1239   0.230906   0.295547   0.271758   0.194332   0.133215  0.301330   \n",
      "1240   0.251557   0.293071   0.333748   0.197566   0.166874  0.247191   \n",
      "1241   0.000000   0.765176   0.765060   0.105431   0.132530  0.112620   \n",
      "1242   0.010309   0.146820   0.173196   0.379244   0.400000  0.411765   \n",
      "1243   0.082162   0.629593   0.587027   0.202352   0.194595  0.094561   \n",
      "1244   0.034483   0.236715   0.293103   0.241546   0.224138  0.342995   \n",
      "1245   0.179348   0.212056   0.237319   0.223330   0.163949  0.410234   \n",
      "1246   0.088586   0.128479   0.182283   0.291651   0.250426  0.503622   \n",
      "1247   0.038741   0.175064   0.234867   0.250213   0.191283  0.518360   \n",
      "1248   0.018182   0.253333   0.313636   0.440000   0.418182  0.283333   \n",
      "1249   0.011494   0.119593   0.130268   0.426209   0.390805  0.321883   \n",
      "1250   0.004310   0.161644   0.237069   0.326027   0.314655  0.408219   \n",
      "1251   0.189607   0.178126   0.276685   0.177322   0.148876  0.433052   \n",
      "1252   0.021898   0.181818   0.270073   0.311295   0.350365  0.473829   \n",
      "1253   0.046851   0.582244   0.579109   0.168028   0.204301  0.171296   \n",
      "1254   0.009494   0.167923   0.338608   0.381910   0.297468  0.402010   \n",
      "1255   0.097561   0.205251   0.317073   0.214797   0.382114  0.245823   \n",
      "1256   0.080586   0.207697   0.256410   0.319841   0.285714  0.331121   \n",
      "1257   0.020802   0.233077   0.313522   0.358330   0.271917  0.347791   \n",
      "1258   0.018634   0.451303   0.459627   0.316872   0.378882  0.190672   \n",
      "1259   0.024221   0.272300   0.350865   0.289863   0.309343  0.357765   \n",
      "1260   0.025000   0.216590   0.350000   0.271889   0.175000  0.470046   \n",
      "1261   0.054865   0.312908   0.343685   0.268673   0.273292  0.353517   \n",
      "1262   0.000000   0.153226   0.255319   0.276882   0.265957  0.534946   \n",
      "1263   0.000000   0.156522   0.180000   0.345652   0.360000  0.467391   \n",
      "1264   0.035714   0.158333   0.178571   0.375000   0.392857  0.416667   \n",
      "1265   0.074866   0.143536   0.157754   0.142586   0.128342  0.575095   \n",
      "1266   0.061404   0.507375   0.350877   0.233038   0.298246  0.206490   \n",
      "1267   0.011905   0.177045   0.386905   0.462759   0.392857  0.307692   \n",
      "1268   0.061697   0.519713   0.501285   0.249104   0.269923  0.175627   \n",
      "1269   0.014815   0.236467   0.370370   0.310541   0.333333  0.336182   \n",
      "1270   0.075444   0.234293   0.248521   0.304538   0.247041  0.337696   \n",
      "1271   0.048544   0.233480   0.368932   0.246696   0.310680  0.378855   \n",
      "1272   0.168539   0.269953   0.247191   0.258216   0.269663  0.342723   \n",
      "1273   0.025641   0.286047   0.403846   0.311628   0.282051  0.360465   \n",
      "1274   0.089888   0.202970   0.247191   0.301980   0.292135  0.440594   \n",
      "1275   0.044444   0.425287   0.422222   0.390805   0.377778  0.149425   \n",
      "1276   0.048544   0.298611   0.349515   0.430556   0.466019  0.215278   \n",
      "1277   0.041935   0.304709   0.374194   0.275623   0.270968  0.306094   \n",
      "1278   0.028369   0.227519   0.273050   0.340195   0.365248  0.393283   \n",
      "1279   0.059524   0.159292   0.297619   0.283186   0.321429  0.398230   \n",
      "1280   0.071429   0.159801   0.268571   0.287642   0.268571  0.454545   \n",
      "1281   0.066079   0.180451   0.317181   0.225564   0.193833  0.386466   \n",
      "1282   0.099693   0.216057   0.340491   0.345953   0.297546  0.351828   \n",
      "1283   0.024470   0.283750   0.336052   0.347500   0.391517  0.283750   \n",
      "1284   0.056000   0.171429   0.336000   0.306494   0.264000  0.436364   \n",
      "1285   0.013699   0.333333   0.383562   0.436782   0.452055  0.143678   \n",
      "1286   0.075000   0.284685   0.355000   0.329730   0.270000  0.351351   \n",
      "1287   0.069725   0.250809   0.355963   0.291262   0.306422  0.316343   \n",
      "1288   0.129979   0.274262   0.348008   0.272574   0.238994  0.249789   \n",
      "1289   0.041667   0.394316   0.326389   0.214920   0.222222  0.316163   \n",
      "1290   0.042506   0.392804   0.418345   0.267616   0.230425  0.260120   \n",
      "1291   0.078947   0.206349   0.273684   0.269841   0.268421  0.319728   \n",
      "1292   0.062069   0.273273   0.200000   0.201201   0.213793  0.357357   \n",
      "1293   0.050360   0.298507   0.223022   0.194030   0.273381  0.361194   \n",
      "1294   0.014925   0.085714   0.097015   0.246429   0.268657  0.632143   \n",
      "1295   0.333333   0.175258   0.209150   0.174112   0.199346  0.276060   \n",
      "1296   0.045166   0.306832   0.303487   0.312273   0.382726  0.313785   \n",
      "1297   0.051916   0.275449   0.316440   0.361677   0.341162  0.267465   \n",
      "1298   0.033951   0.309256   0.396605   0.339020   0.331790  0.286025   \n",
      "1299   0.015873   0.278119   0.388889   0.372188   0.329365  0.331970   \n",
      "1300   0.029650   0.501266   0.474394   0.275949   0.296496  0.139241   \n",
      "1301   0.040000   0.277620   0.250000   0.305949   0.390000  0.320113   \n",
      "1302   0.067138   0.260173   0.261484   0.240444   0.265018  0.367448   \n",
      "1303   0.045845   0.284507   0.343840   0.299531   0.255014  0.306103   \n",
      "1304   0.009975   0.164691   0.311721   0.353091   0.291771  0.408975   \n",
      "1305   0.033217   0.223284   0.311189   0.322388   0.333916  0.344478   \n",
      "1306   0.000000   0.210052   0.154545   0.365979   0.209091  0.320876   \n",
      "1307   0.051282   0.198697   0.307692   0.297503   0.328205  0.404995   \n",
      "1308   0.144790   0.241047   0.288227   0.114784   0.138024  0.506428   \n",
      "1309   0.086957   0.234879   0.299233   0.309476   0.314578  0.330645   \n",
      "1310   0.077434   0.195409   0.243363   0.404467   0.413717  0.260546   \n",
      "1311   0.104247   0.239802   0.301158   0.280593   0.247104  0.275649   \n",
      "1312   0.075601   0.304585   0.374570   0.311135   0.305842  0.253275   \n",
      "1313   0.068035   0.323813   0.387689   0.286350   0.288337  0.272255   \n",
      "1314   0.199442   0.216826   0.270572   0.273370   0.238494  0.293662   \n",
      "1315   0.010870   0.216941   0.245652   0.351005   0.471739  0.360146   \n",
      "1316   0.125000   0.255932   0.317308   0.238983   0.221154  0.372881   \n",
      "1317   0.096658   0.333204   0.343270   0.303620   0.311653  0.264694   \n",
      "1318   0.047362   0.284863   0.314748   0.423719   0.413070  0.207390   \n",
      "1319   0.157895   0.282051   0.197368   0.160256   0.276316  0.416667   \n",
      "1320   0.027273   0.229704   0.225758   0.494747   0.477273  0.213467   \n",
      "1321   0.085667   0.598361   0.535420   0.227166   0.253707  0.100703   \n",
      "1322   0.066282   0.148260   0.230548   0.299546   0.327089  0.373172   \n",
      "1323   0.047513   0.169496   0.215293   0.335252   0.317001  0.366619   \n",
      "1324   0.053571   0.202581   0.209821   0.278710   0.312500  0.343226   \n",
      "1325   0.071901   0.137287   0.181818   0.263376   0.304959  0.434260   \n",
      "1326   0.110664   0.250856   0.313883   0.227740   0.221328  0.382705   \n",
      "1327   0.151515   0.466454   0.439394   0.162939   0.162879  0.292332   \n",
      "1328   0.044892   0.503171   0.444272   0.197146   0.224458  0.212474   \n",
      "1329   0.051282   0.288259   0.304487   0.282322   0.355769  0.329815   \n",
      "1330   0.090715   0.231865   0.219851   0.177461   0.183565  0.417098   \n",
      "1331   0.046763   0.228758   0.226619   0.328665   0.356115  0.341737   \n",
      "1332   0.175000   0.354386   0.375000   0.214035   0.175000  0.214035   \n",
      "1333   0.120399   0.269978   0.293712   0.326674   0.317485  0.271058   \n",
      "1334   0.089153   0.427040   0.383358   0.268017   0.222883  0.176295   \n",
      "1335   0.044000   0.374328   0.414000   0.269254   0.204000  0.281194   \n",
      "1336   0.087671   0.321643   0.326027   0.262525   0.282192  0.238477   \n",
      "1337   0.069378   0.428791   0.466507   0.232487   0.227273  0.270978   \n",
      "1338   0.046512   0.357927   0.397010   0.303030   0.315615  0.238472   \n",
      "1339   0.023689   0.268812   0.291878   0.340512   0.350254  0.316696   \n",
      "1340   0.252567   0.241206   0.277207   0.189519   0.193018  0.248385   \n",
      "1341   0.020930   0.154389   0.227907   0.368769   0.265116  0.380238   \n",
      "1342   0.118056   0.551351   0.430556   0.240541   0.256944  0.167568   \n",
      "1343   0.010135   0.231735   0.317568   0.335046   0.417230  0.260845   \n",
      "1344   0.006667   0.152381   0.246667   0.401361   0.420000  0.401361   \n",
      "1345   0.014184   0.333333   0.510638   0.333333   0.255319  0.261905   \n",
      "1346   0.034247   0.169168   0.356164   0.323329   0.301370  0.469304   \n",
      "1347   0.013906   0.182379   0.269279   0.357848   0.361568  0.410168   \n",
      "1348   0.000000   0.161157   0.238095   0.404959   0.380952  0.421488   \n",
      "1349   0.046753   0.328606   0.335065   0.330073   0.333766  0.283619   \n",
      "1350   0.036364   0.219340   0.322727   0.366745   0.300000  0.325472   \n",
      "1351   0.018265   0.250324   0.369863   0.330739   0.351598  0.376135   \n",
      "1352   0.012658   0.146293   0.240506   0.330661   0.379747  0.472946   \n",
      "1353   0.020747   0.156729   0.352697   0.308348   0.340249  0.503123   \n",
      "1354   0.013423   0.249275   0.409396   0.318841   0.335570  0.344928   \n",
      "1355   0.008333   0.154862   0.308333   0.318127   0.391667  0.435774   \n",
      "1356   0.030651   0.306892   0.342912   0.318596   0.365900  0.337451   \n",
      "1357   0.013889   0.229718   0.277778   0.356106   0.322917  0.343296   \n",
      "1358   0.034783   0.507786   0.496618   0.267773   0.273430  0.173663   \n",
      "1359   0.046931   0.375394   0.440433   0.225552   0.263538  0.302839   \n",
      "1360   0.023364   0.405868   0.457944   0.336186   0.299065  0.213936   \n",
      "1361   0.016077   0.391714   0.459807   0.290019   0.276527  0.297552   \n",
      "1362   0.029046   0.343904   0.342324   0.259338   0.288382  0.314306   \n",
      "1363   0.019231   0.396721   0.444712   0.360656   0.382212  0.215301   \n",
      "1364   0.063232   0.348058   0.339578   0.384615   0.330211  0.200305   \n",
      "1365   0.030548   0.280072   0.256065   0.324596   0.336029  0.335368   \n",
      "1366   0.042208   0.211126   0.250000   0.368633   0.285714  0.382708   \n",
      "1367   0.125695   0.315198   0.319244   0.316717   0.228031  0.270517   \n",
      "1368   0.125984   0.371601   0.330709   0.359517   0.299213  0.154079   \n",
      "1369   0.052747   0.384772   0.404396   0.222843   0.293407  0.287310   \n",
      "1370   0.024291   0.499154   0.500000   0.275804   0.281377  0.166385   \n",
      "1371   0.017271   0.662719   0.673575   0.200309   0.196891  0.121524   \n",
      "1372   0.012500   0.295760   0.415625   0.458118   0.362500  0.222337   \n",
      "1373   0.029361   0.433834   0.388601   0.272904   0.314335  0.251091   \n",
      "1374   0.098694   0.399327   0.358491   0.274387   0.261248  0.227295   \n",
      "1375   0.065854   0.230981   0.301220   0.377217   0.345122  0.276705   \n",
      "1376   0.083784   0.296943   0.348649   0.318777   0.340541  0.299439   \n",
      "1377   0.000000   0.588608   0.342857   0.303797   0.200000  0.107595   \n",
      "1378   0.084494   0.170272   0.212628   0.179487   0.192201  0.333333   \n",
      "1379   0.095098   0.268456   0.287255   0.268084   0.292157  0.351976   \n",
      "1380   0.064880   0.222575   0.277856   0.357319   0.373766  0.325220   \n",
      "1381   0.046205   0.347701   0.376238   0.264368   0.240924  0.277778   \n",
      "1382   0.057034   0.270115   0.239544   0.302956   0.342205  0.293924   \n",
      "1383   0.118483   0.207249   0.257504   0.330855   0.325434  0.299257   \n",
      "1384   0.037221   0.358624   0.385856   0.261579   0.217122  0.309660   \n",
      "1385   0.120438   0.276978   0.262774   0.227818   0.215328  0.280576   \n",
      "1386   0.044280   0.347345   0.343635   0.352532   0.369465  0.231336   \n",
      "1387   0.224756   0.264913   0.267101   0.207826   0.234528  0.291854   \n",
      "1388   0.083736   0.260819   0.288245   0.251587   0.286634  0.335257   \n",
      "1389   0.140927   0.201135   0.235521   0.184915   0.187259  0.405515   \n",
      "1390   0.161017   0.282469   0.303390   0.237624   0.225424  0.238789   \n",
      "1391   0.084211   0.324750   0.315789   0.213162   0.171930  0.317597   \n",
      "1392   0.000000   0.301887   0.125000   0.323899   0.517857  0.238994   \n",
      "1393   0.142857   0.288114   0.299107   0.241075   0.232143  0.339353   \n",
      "1394   0.086321   0.264228   0.353254   0.316565   0.294821  0.324187   \n",
      "1395   0.010616   0.175311   0.284501   0.347510   0.322718  0.405083   \n",
      "1396   0.006061   0.145418   0.224242   0.211155   0.169697  0.541833   \n",
      "1397   0.063380   0.054830   0.091549   0.185379   0.197183  0.592689   \n",
      "1398   0.050000   0.279054   0.348485   0.327315   0.266667  0.308601   \n",
      "1399   0.083595   0.342314   0.380355   0.306736   0.335423  0.213817   \n",
      "1400   0.004545   0.104067   0.222727   0.433014   0.395455  0.397129   \n",
      "1401   0.071250   0.199792   0.332500   0.266389   0.270000  0.470343   \n",
      "1402   0.122066   0.238713   0.247653   0.244921   0.226526  0.384876   \n",
      "1403   0.008505   0.393392   0.523742   0.288935   0.291283  0.270521   \n",
      "1404   0.061303   0.247924   0.291188   0.443654   0.348659  0.246738   \n",
      "1405   0.047619   0.267201   0.228571   0.327989   0.285714  0.357381   \n",
      "1406   0.054545   0.198020   0.418182   0.343234   0.218182  0.366337   \n",
      "1407   0.071197   0.250554   0.317152   0.304878   0.271845  0.325942   \n",
      "1408   0.113269   0.289395   0.372168   0.243806   0.236246  0.313181   \n",
      "1409   0.061453   0.356972   0.396648   0.353222   0.281724  0.222639   \n",
      "1410   0.041397   0.297973   0.327296   0.309760   0.357050  0.336634   \n",
      "1411   0.045455   0.311453   0.329154   0.354749   0.352665  0.254190   \n",
      "1412   0.035294   0.172088   0.168627   0.254287   0.266667  0.431697   \n",
      "1413   0.089686   0.213270   0.282511   0.285545   0.282511  0.405213   \n",
      "1414   0.035714   0.195833   0.280612   0.247917   0.219388  0.458333   \n",
      "1415   0.084906   0.169935   0.179245   0.349673   0.349057  0.369281   \n",
      "1416   0.127072   0.368327   0.309392   0.279359   0.287293  0.233096   \n",
      "1417   0.032967   0.348915   0.401099   0.208681   0.131868  0.292154   \n",
      "1418   0.046569   0.245588   0.291667   0.361765   0.333333  0.276471   \n",
      "1419   0.069642   0.279400   0.327248   0.282947   0.299527  0.327694   \n",
      "1420   0.030769   0.342857   0.323077   0.233333   0.261538  0.300000   \n",
      "1421   0.029316   0.177800   0.198697   0.315324   0.335505  0.447937   \n",
      "1422   0.039133   0.242766   0.240391   0.301864   0.337526  0.370034   \n",
      "1423   0.070789   0.295813   0.284784   0.234910   0.274207  0.365960   \n",
      "1424   0.064782   0.237563   0.318021   0.327420   0.292108  0.333205   \n",
      "1425   0.058824   0.293860   0.364706   0.365497   0.270588  0.308480   \n",
      "1426   0.036364   0.237468   0.256684   0.356751   0.360428  0.346506   \n",
      "1427   0.146067   0.200743   0.370787   0.230483   0.179775  0.390335   \n",
      "1428   0.042553   0.209091   0.120567   0.150000   0.191489  0.570455   \n",
      "1429   0.045627   0.261516   0.249049   0.255572   0.262357  0.366518   \n",
      "1430   0.055794   0.480643   0.433476   0.254200   0.274678  0.170928   \n",
      "1431   0.087912   0.290000   0.241758   0.204000   0.181319  0.322000   \n",
      "1432   0.140187   0.243615   0.285047   0.306483   0.303738  0.328094   \n",
      "1433   0.024793   0.271646   0.276860   0.243578   0.214876  0.399144   \n",
      "1434   0.039244   0.271912   0.296512   0.294323   0.328488  0.354582   \n",
      "1435   0.051471   0.238168   0.308824   0.448855   0.404412  0.227481   \n",
      "1436   0.004264   0.161523   0.211087   0.314300   0.285714  0.475309   \n",
      "1437   0.014787   0.182948   0.203327   0.327413   0.349353  0.378922   \n",
      "1438   0.052846   0.252680   0.260163   0.358346   0.272358  0.294028   \n",
      "1439   0.033937   0.311864   0.316742   0.301695   0.319005  0.272316   \n",
      "1440   0.050866   0.285637   0.266234   0.270461   0.264069  0.352846   \n",
      "1441   0.050459   0.242909   0.240826   0.288000   0.279817  0.326545   \n",
      "1442   0.067391   0.416941   0.445652   0.175987   0.154348  0.241776   \n",
      "1443   0.139723   0.252562   0.272517   0.283309   0.274827  0.299048   \n",
      "1444   0.069841   0.291327   0.290476   0.284619   0.314286  0.296119   \n",
      "1445   0.068592   0.351404   0.362816   0.267146   0.341155  0.160026   \n",
      "1446   0.035294   0.365019   0.311765   0.273764   0.282353  0.292776   \n",
      "1447   0.018692   0.400000   0.551402   0.320690   0.261682  0.179310   \n",
      "1448   0.017857   0.403974   0.433036   0.349338   0.357143  0.226821   \n",
      "1449   0.034483   0.507109   0.422414   0.369668   0.396552  0.104265   \n",
      "1450   0.103896   0.206128   0.272727   0.111421   0.071429  0.515320   \n",
      "1451   0.206498   0.234895   0.263216   0.254260   0.235132  0.305577   \n",
      "1452   0.067989   0.269058   0.320113   0.275037   0.320113  0.282511   \n",
      "1453   0.241379   0.168000   0.137931   0.136000   0.206897  0.440000   \n",
      "1454   0.035242   0.249706   0.229075   0.321974   0.464758  0.360165   \n",
      "1455   0.032000   0.194690   0.288000   0.410029   0.344000  0.330383   \n",
      "1456   0.013592   0.430457   0.464078   0.280528   0.287379  0.225837   \n",
      "1457   0.007634   0.402787   0.480916   0.282927   0.297710  0.212544   \n",
      "1458   0.013274   0.254925   0.292035   0.345307   0.243363  0.358053   \n",
      "1459   0.031250   0.429603   0.375000   0.234657   0.270833  0.194946   \n",
      "1460   0.062893   0.362857   0.404612   0.288571   0.306080  0.242857   \n",
      "1461   0.073698   0.433333   0.410419   0.291165   0.346887  0.189558   \n",
      "1462   0.038023   0.361600   0.403042   0.401600   0.384030  0.179200   \n",
      "1463   0.330579   0.254973   0.245179   0.217902   0.134986  0.218807   \n",
      "1464   0.222054   0.266592   0.216012   0.233408   0.243202  0.219348   \n",
      "1465   0.067729   0.179903   0.179283   0.367909   0.350598  0.235008   \n",
      "1466   0.109116   0.319556   0.350829   0.244456   0.241713  0.238911   \n",
      "1467   0.121655   0.256350   0.285888   0.295861   0.267640  0.288335   \n",
      "1468   0.053279   0.182796   0.323770   0.363937   0.327869  0.407775   \n",
      "1469   0.061538   0.281776   0.284615   0.381317   0.300000  0.294028   \n",
      "1470   0.063776   0.255372   0.260204   0.318182   0.341837  0.301653   \n",
      "1471   0.066975   0.330812   0.281755   0.288171   0.297921  0.298487   \n",
      "1472   0.023339   0.276274   0.389587   0.466561   0.364452  0.234607   \n",
      "1473   0.022222   0.151678   0.118519   0.326174   0.407407  0.464430   \n",
      "1474   0.000000   0.177778   0.269231   0.333333   0.307692  0.422222   \n",
      "1475   0.000000   0.291785   0.275362   0.317280   0.434783  0.310198   \n",
      "1476   0.012048   0.126866   0.150602   0.332623   0.355422  0.432836   \n",
      "1477   0.057143   0.207289   0.142857   0.232346   0.257143  0.523918   \n",
      "1478   0.011494   0.181507   0.241379   0.342466   0.310345  0.407534   \n",
      "1479   0.062500   0.262958   0.225694   0.284450   0.256944  0.364096   \n",
      "1480   0.025168   0.270844   0.276846   0.345417   0.323826  0.253237   \n",
      "1481   0.028369   0.361022   0.333333   0.175719   0.326241  0.434505   \n",
      "1482   0.026667   0.115869   0.140000   0.282116   0.306667  0.375315   \n",
      "1483   0.014218   0.346690   0.255924   0.311847   0.350711  0.233449   \n",
      "1484   0.025070   0.357749   0.378830   0.310510   0.314763  0.257431   \n",
      "1485   0.057239   0.335036   0.370370   0.323116   0.315376  0.254151   \n",
      "1486   0.021875   0.227503   0.268750   0.306717   0.328125  0.404943   \n",
      "1487   0.057471   0.165746   0.367816   0.408840   0.195402  0.273481   \n",
      "1488   0.063492   0.177419   0.253968   0.474194   0.253968  0.261290   \n",
      "1489   0.036496   0.271765   0.332117   0.337647   0.321168  0.330588   \n",
      "1490   0.096618   0.280067   0.314010   0.265770   0.246377  0.370059   \n",
      "1491   0.095436   0.341176   0.398340   0.210458   0.290456  0.198693   \n",
      "1492   0.000000   0.227273   0.454545   0.318182   0.000000  0.386364   \n",
      "1493   0.074074   0.042373   0.148148   0.144068   0.259259  0.644068   \n",
      "1494   0.066667   0.324226   0.384615   0.247723   0.210256  0.378871   \n",
      "1495   0.057627   0.224329   0.261017   0.263823   0.223729  0.387046   \n",
      "1496   0.000000   0.290323   0.555556   0.129032   0.000000  0.548387   \n",
      "1497   0.000000   0.147059   0.290598   0.380392   0.376068  0.429412   \n",
      "1498   0.064846   0.333333   0.382253   0.238938   0.259386  0.355949   \n",
      "1499   0.033808   0.285423   0.250890   0.325688   0.368327  0.288991   \n",
      "1500   0.041885   0.283796   0.356021   0.322292   0.287958  0.296329   \n",
      "1501   0.067901   0.342770   0.416667   0.198180   0.216049  0.342770   \n",
      "1502   0.015789   0.265537   0.268421   0.343691   0.352632  0.321092   \n",
      "1503   0.041322   0.316699   0.371901   0.311900   0.297521  0.273512   \n",
      "1504   0.044776   0.198276   0.288557   0.295567   0.298507  0.374384   \n",
      "1505   0.049505   0.195122   0.148515   0.158537   0.277228  0.280488   \n",
      "1506   0.094203   0.262712   0.311594   0.216102   0.246377  0.364407   \n",
      "1507   0.054795   0.279032   0.356164   0.266129   0.184932  0.400000   \n",
      "1508   0.202417   0.315052   0.318731   0.144424   0.108761  0.364412   \n",
      "1509   0.031056   0.248748   0.285714   0.377295   0.366460  0.343907   \n",
      "1510   0.173077   0.418391   0.278846   0.149425   0.201923  0.268966   \n",
      "1511   0.106383   0.188482   0.212766   0.175393   0.191489  0.541885   \n",
      "1512   0.070946   0.274673   0.307432   0.246136   0.250000  0.324614   \n",
      "1513   0.025974   0.178439   0.298701   0.390335   0.337662  0.390335   \n",
      "1514   0.048387   0.243902   0.322581   0.346883   0.266129  0.308943   \n",
      "1515   0.170732   0.361022   0.382114   0.182109   0.065041  0.367412   \n",
      "1516   0.022989   0.221739   0.258621   0.284783   0.235632  0.393478   \n",
      "1517   0.018519   0.228070   0.259259   0.200000   0.185185  0.473684   \n",
      "1518   0.050526   0.280417   0.317895   0.303013   0.307368  0.308806   \n",
      "1519   0.021563   0.209191   0.231806   0.393690   0.382749  0.340192   \n",
      "1520   0.106632   0.414129   0.401821   0.194162   0.191157  0.303723   \n",
      "1521   0.073684   0.265683   0.284211   0.405904   0.389474  0.280443   \n",
      "1522   0.019417   0.226804   0.237864   0.288660   0.281553  0.365979   \n",
      "1523   0.129512   0.263045   0.326964   0.218397   0.225053  0.367402   \n",
      "1524   0.025783   0.148019   0.237569   0.338384   0.303867  0.435509   \n",
      "1525   0.090909   0.209581   0.265734   0.347305   0.328671  0.317365   \n",
      "1526   0.136364   0.167105   0.171717   0.267105   0.287879  0.390789   \n",
      "1527   0.089147   0.088652   0.085271   0.313830   0.302326  0.455674   \n",
      "1528   0.058296   0.341909   0.309417   0.224066   0.237668  0.313693   \n",
      "1529   0.054847   0.417994   0.436224   0.214620   0.248724  0.259606   \n",
      "1530   0.107692   0.652991   0.574359   0.164103   0.138462  0.105983   \n",
      "1531   0.085851   0.275419   0.249603   0.256425   0.290938  0.318436   \n",
      "1532   0.113386   0.271680   0.285039   0.192238   0.179528  0.382050   \n",
      "1533   0.199566   0.342163   0.316703   0.122884   0.140998  0.280353   \n",
      "1534   0.060296   0.384696   0.439135   0.190261   0.216155  0.286957   \n",
      "1535   0.088099   0.240000   0.261206   0.276216   0.247295  0.335676   \n",
      "1536   0.150198   0.143438   0.221344   0.180061   0.185771  0.308240   \n",
      "1537   0.103070   0.450275   0.361842   0.175107   0.236842  0.224527   \n",
      "1538   0.174164   0.300733   0.331027   0.167482   0.156863  0.277099   \n",
      "1539   0.060847   0.276534   0.312169   0.226874   0.216931  0.344693   \n",
      "1540   0.048673   0.269097   0.207965   0.135417   0.128319  0.390625   \n",
      "1541   0.069018   0.124800   0.148773   0.416000   0.466258  0.362667   \n",
      "1542   0.122099   0.323864   0.297679   0.235119   0.286579  0.264610   \n",
      "1543   0.056897   0.304521   0.334483   0.244016   0.256897  0.294548   \n",
      "1544   0.400000   0.256542   0.262434   0.131642   0.079365  0.256542   \n",
      "1545   0.193103   0.189831   0.268966   0.132203   0.165517  0.413559   \n",
      "1546   0.097561   0.402101   0.306911   0.198800   0.156504  0.289572   \n",
      "1547   0.087603   0.508603   0.400000   0.161437   0.228099  0.213057   \n",
      "1548   0.104762   0.357367   0.358095   0.181818   0.175238  0.353448   \n",
      "1549   0.132219   0.266738   0.281155   0.201913   0.145897  0.342189   \n",
      "1550   0.130952   0.410701   0.408730   0.146782   0.154762  0.252350   \n",
      "1551   0.142987   0.217961   0.237705   0.166505   0.165301  0.391748   \n",
      "1552   0.434726   0.266368   0.240209   0.089536   0.080940  0.254617   \n",
      "1553   0.030103   0.371374   0.342427   0.268199   0.259643  0.294472   \n",
      "1554   0.080321   0.329235   0.317269   0.258197   0.273092  0.273224   \n",
      "1555   0.098413   0.425732   0.400000   0.277197   0.200000  0.213389   \n",
      "1556   0.081081   0.268041   0.221622   0.212371   0.240541  0.346392   \n",
      "1557   0.069124   0.227407   0.276498   0.263704   0.311060  0.377037   \n",
      "1558   0.100962   0.218115   0.317308   0.160813   0.129808  0.445471   \n",
      "1559   0.081539   0.263703   0.273973   0.215949   0.242009  0.350271   \n",
      "1560   0.074766   0.238342   0.289720   0.274611   0.271028  0.393782   \n",
      "1561   0.057627   0.250000   0.379661   0.248355   0.223729  0.407895   \n",
      "1562   0.279221   0.254181   0.267532   0.132346   0.106494  0.297181   \n",
      "1563   0.066437   0.419173   0.432269   0.290413   0.285591  0.182176   \n",
      "1564   0.054054   0.381454   0.370270   0.239199   0.297297  0.206533   \n",
      "1565   0.060329   0.284810   0.294333   0.241913   0.217550  0.367792   \n",
      "1566   0.070796   0.313094   0.304204   0.378356   0.362832  0.230483   \n",
      "1567   0.153631   0.192731   0.162011   0.151982   0.178771  0.401982   \n",
      "1568   0.238095   0.286501   0.269841   0.151515   0.206349  0.294766   \n",
      "1569   0.357576   0.162500   0.169697   0.150000   0.193939  0.283929   \n",
      "1570   0.107527   0.173448   0.198925   0.214133   0.209677  0.364026   \n",
      "1571   0.125405   0.311086   0.341424   0.292421   0.279126  0.245475   \n",
      "1572   0.176678   0.184049   0.169611   0.314110   0.229682  0.328834   \n",
      "1573   0.106352   0.341274   0.363368   0.199446   0.221566  0.296953   \n",
      "1574   0.077649   0.285842   0.317852   0.323523   0.342525  0.251951   \n",
      "1575   0.105202   0.432742   0.405780   0.230375   0.238150  0.204734   \n",
      "1576   0.045267   0.099849   0.119342   0.211800   0.218107  0.390318   \n",
      "1577   0.063291   0.135258   0.145570   0.191489   0.208861  0.420973   \n",
      "1578   0.057592   0.116751   0.130890   0.345178   0.293194  0.423858   \n",
      "1579   0.000000   0.500000   0.363636   0.400000   0.181818  0.100000   \n",
      "1580   0.151734   0.244229   0.278902   0.323176   0.385838  0.194829   \n",
      "1581   0.040212   0.341641   0.390744   0.332295   0.324734  0.232191   \n",
      "1582   0.059843   0.389480   0.362730   0.317607   0.352231  0.204778   \n",
      "1583   0.162602   0.487047   0.455285   0.170984   0.154472  0.233161   \n",
      "1584   0.013274   0.306011   0.296460   0.291439   0.358407  0.318761   \n",
      "1585   0.073718   0.377626   0.360577   0.281658   0.277244  0.227712   \n",
      "1586   0.108225   0.316327   0.311688   0.194805   0.177489  0.294063   \n",
      "1587   0.177370   0.266298   0.269113   0.218785   0.262997  0.303867   \n",
      "1588   0.109626   0.192180   0.259358   0.263727   0.203209  0.372712   \n",
      "1589   0.034483   0.246753   0.271552   0.298701   0.306034  0.346939   \n",
      "1590   0.054974   0.275258   0.280105   0.303093   0.337696  0.332990   \n",
      "1591   0.198842   0.282178   0.303089   0.163366   0.194981  0.303395   \n",
      "1592   0.155527   0.341052   0.343188   0.193439   0.197943  0.294260   \n",
      "1593   0.363305   0.193285   0.226610   0.130771   0.119077  0.308151   \n",
      "1594   0.194511   0.317237   0.362172   0.204768   0.187947  0.251426   \n",
      "1595   0.180328   0.296811   0.305514   0.215535   0.166915  0.298354   \n",
      "1596   0.182213   0.173370   0.203905   0.196255   0.151844  0.399445   \n",
      "1597   0.200495   0.266612   0.241955   0.171492   0.191832  0.315688   \n",
      "1598   0.380673   0.252740   0.256273   0.125923   0.089696  0.247372   \n",
      "1599   0.157576   0.237750   0.278788   0.340593   0.306061  0.237145   \n",
      "1600   0.170561   0.206767   0.287383   0.231579   0.226636  0.326316   \n",
      "1601   0.173077   0.085813   0.201923   0.061592   0.076923  0.107958   \n",
      "1602   0.058511   0.265794   0.294833   0.341308   0.330547  0.291963   \n",
      "1603   0.204969   0.180420   0.240166   0.199301   0.182195  0.281119   \n",
      "1604   0.230380   0.301751   0.303797   0.133363   0.149367  0.292771   \n",
      "1605   0.079365   0.181818   0.238095   0.231405   0.158730  0.363636   \n",
      "1606   0.102837   0.178637   0.202128   0.141191   0.193262  0.531001   \n",
      "1607   0.327091   0.146583   0.167291   0.116906   0.106117  0.309952   \n",
      "1608   0.051443   0.302007   0.297365   0.312775   0.317440  0.303475   \n",
      "1609   0.027132   0.301565   0.236434   0.263158   0.399225  0.275960   \n",
      "1610   0.098807   0.147457   0.211244   0.344495   0.320273  0.353509   \n",
      "1611   0.042155   0.369950   0.295082   0.340184   0.370023  0.206237   \n",
      "1612   0.022831   0.221154   0.223744   0.355769   0.347032  0.323077   \n",
      "1613   0.073245   0.284792   0.345036   0.378576   0.351090  0.240052   \n",
      "1614   0.090395   0.373134   0.265537   0.151741   0.180791  0.278607   \n",
      "1615   0.049180   0.305556   0.327869   0.152778   0.163934  0.375000   \n",
      "1616   0.037594   0.311916   0.402256   0.348131   0.327068  0.250000   \n",
      "1617   0.041322   0.304245   0.264463   0.349057   0.380165  0.240566   \n",
      "1618   0.087983   0.179949   0.223176   0.297344   0.266094  0.407883   \n",
      "1619   0.005814   0.167107   0.236434   0.365944   0.379845  0.441036   \n",
      "1620   0.204000   0.291107   0.284000   0.243762   0.214000  0.248880   \n",
      "1621   0.042169   0.311412   0.271084   0.249516   0.289157  0.323017   \n",
      "1622   0.107884   0.139619   0.200553   0.307344   0.283541  0.418404   \n",
      "1623   0.110626   0.223220   0.264920   0.331944   0.321689  0.341244   \n",
      "1624   0.010870   0.143969   0.217391   0.365759   0.347826  0.307393   \n",
      "1625   0.042079   0.291353   0.316832   0.257306   0.248144  0.329617   \n",
      "1626   0.099874   0.305049   0.359039   0.152312   0.194690  0.368689   \n",
      "1627   0.022222   0.436455   0.448148   0.283278   0.260494  0.238127   \n",
      "1628   0.143345   0.229898   0.303754   0.206116   0.259386  0.244621   \n",
      "1629   0.130769   0.231707   0.346154   0.312500   0.269231  0.312500   \n",
      "1630   0.053151   0.313568   0.326500   0.377784   0.398633  0.199379   \n",
      "1631   0.021390   0.302707   0.349121   0.418792   0.407945  0.230088   \n",
      "1632   0.072937   0.244218   0.318618   0.338776   0.332054  0.335374   \n",
      "1633   0.065891   0.143548   0.180233   0.184630   0.163760  0.481392   \n",
      "1634   0.031100   0.582687   0.574163   0.147287   0.184211  0.177649   \n",
      "1635   0.031030   0.292265   0.396333   0.347217   0.339915  0.278614   \n",
      "1636   0.124688   0.215200   0.274314   0.246400   0.214464  0.452000   \n",
      "1637   0.116751   0.287625   0.233503   0.214047   0.157360  0.387960   \n",
      "1638   0.109091   0.400000   0.309091   0.116129   0.272727  0.277419   \n",
      "1639   0.014493   0.295148   0.354037   0.341644   0.310559  0.279650   \n",
      "1640   0.011628   0.328173   0.302326   0.204334   0.189922  0.371517   \n",
      "1641   0.028571   0.240000   0.314286   0.204000   0.342857  0.480000   \n",
      "1642   0.122302   0.195110   0.366906   0.382396   0.273381  0.306112   \n",
      "1643   0.093827   0.279412   0.326749   0.334423   0.333333  0.244009   \n",
      "1644   0.109434   0.338010   0.332075   0.295918   0.211321  0.270408   \n",
      "1645   0.138298   0.322546   0.329787   0.183387   0.180851  0.312837   \n",
      "1646   0.102273   0.231168   0.276136   0.354803   0.314773  0.307587   \n",
      "1647   0.036223   0.305258   0.341527   0.344421   0.376455  0.280043   \n",
      "1648   0.149390   0.158872   0.298780   0.193260   0.256098  0.262724   \n",
      "1649   0.068413   0.274190   0.357351   0.361106   0.339884  0.261125   \n",
      "1650   0.083333   0.254417   0.307971   0.270907   0.163043  0.380448   \n",
      "1651   0.046318   0.159633   0.294537   0.341590   0.280285  0.425382   \n",
      "1652   0.050219   0.297030   0.294911   0.385132   0.403101  0.257258   \n",
      "1653   0.085852   0.306977   0.347037   0.293023   0.269649  0.281395   \n",
      "1654   0.054572   0.334307   0.382006   0.310462   0.327434  0.258394   \n",
      "1655   0.030905   0.404272   0.362031   0.379747   0.434879  0.203323   \n",
      "1656   0.081395   0.244055   0.298450   0.202128   0.203488  0.444305   \n",
      "1657   0.115942   0.156277   0.188406   0.373134   0.260870  0.373134   \n",
      "1658   0.102377   0.213417   0.243754   0.316816   0.297380  0.328444   \n",
      "1659   0.106227   0.257636   0.351648   0.213811   0.142857  0.409031   \n",
      "1660   0.043042   0.331950   0.372052   0.391485   0.387972  0.205845   \n",
      "1661   0.078725   0.274029   0.316776   0.274666   0.224930  0.299491   \n",
      "1662   0.075117   0.186667   0.276995   0.373333   0.333333  0.265000   \n",
      "1663   0.052632   0.145588   0.156015   0.336029   0.323308  0.425735   \n",
      "1664   0.035167   0.454088   0.496844   0.294431   0.274121  0.165877   \n",
      "1665   0.020690   0.628880   0.513793   0.171390   0.289655  0.160594   \n",
      "1666   0.082192   0.363636   0.294521   0.153247   0.171233  0.355844   \n",
      "1667   0.205128   0.231760   0.243590   0.244635   0.166667  0.369099   \n",
      "1668   0.087071   0.239669   0.292876   0.331850   0.282322  0.355372   \n",
      "1669   0.171875   0.243386   0.243750   0.279101   0.231250  0.347884   \n",
      "1670   0.094755   0.164474   0.194585   0.295040   0.282572  0.449393   \n",
      "1671   0.319426   0.195386   0.276402   0.088081   0.083442  0.305488   \n",
      "1672   0.014936   0.289686   0.351351   0.429982   0.413940  0.239023   \n",
      "1673   0.032895   0.341057   0.407895   0.288230   0.289474  0.319741   \n",
      "1674   0.121646   0.290508   0.326476   0.169153   0.171735  0.336271   \n",
      "1675   0.037037   0.209231   0.226852   0.330769   0.208333  0.358462   \n",
      "1676   0.106796   0.300268   0.398058   0.061662   0.067961  0.412869   \n",
      "1677   0.019048   0.235741   0.285714   0.264259   0.280952  0.385932   \n",
      "1678   0.114796   0.329834   0.323980   0.266842   0.252551  0.269466   \n",
      "1679   0.070312   0.202817   0.234375   0.281690   0.281250  0.388732   \n",
      "1680   0.014583   0.488728   0.472917   0.366345   0.389583  0.102254   \n",
      "1681   0.024742   0.255944   0.257732   0.297203   0.307216  0.349650   \n",
      "1682   0.138721   0.158093   0.183165   0.146048   0.125253  0.551066   \n",
      "1683   0.008230   0.192410   0.222222   0.380826   0.349794  0.390146   \n",
      "1684   0.054237   0.252304   0.316949   0.262097   0.244068  0.360599   \n",
      "1685   0.015957   0.395105   0.351064   0.193473   0.239362  0.358974   \n",
      "1686   0.165714   0.213333   0.297143   0.166000   0.127619  0.277333   \n",
      "1687   0.083160   0.235788   0.315315   0.309936   0.356202  0.346515   \n",
      "1688   0.085271   0.279487   0.298450   0.225641   0.269380  0.393590   \n",
      "1689   0.017011   0.510245   0.520049   0.316342   0.335358  0.141429   \n",
      "1690   0.134731   0.318408   0.311377   0.265814   0.332335  0.302061   \n",
      "1691   0.000000   0.058824   0.076923   0.220588   0.307692  0.367647   \n",
      "1692   0.137521   0.157432   0.156197   0.250000   0.252971  0.372973   \n",
      "1693   0.145511   0.138781   0.226006   0.238651   0.191950  0.416342   \n",
      "1694   0.148936   0.230769   0.255319   0.141026   0.255319  0.358974   \n",
      "1695   0.388489   0.221963   0.227133   0.213952   0.125385  0.246662   \n",
      "1696   0.209836   0.232330   0.254098   0.223168   0.168852  0.411649   \n",
      "1697   0.118598   0.246894   0.320755   0.191770   0.183288  0.390528   \n",
      "1698   0.128931   0.298048   0.299790   0.197072   0.225367  0.349474   \n",
      "1699   0.125189   0.261404   0.273002   0.241927   0.315234  0.348027   \n",
      "1700   0.059150   0.501403   0.478743   0.170253   0.199630  0.239476   \n",
      "1701   0.291815   0.238731   0.217082   0.156928   0.096085  0.358932   \n",
      "1702   0.076377   0.377908   0.350503   0.288324   0.310243  0.236356   \n",
      "1703   0.059561   0.251931   0.263323   0.327220   0.382445  0.302124   \n",
      "1704   0.051282   0.235343   0.373219   0.271357   0.168091  0.292295   \n",
      "1705   0.086580   0.223430   0.216450   0.236715   0.268398  0.336957   \n",
      "1706   0.080139   0.258870   0.282230   0.111695   0.128920  0.411301   \n",
      "1707   0.029310   0.247177   0.246552   0.346766   0.401724  0.344456   \n",
      "1708   0.028777   0.274245   0.330935   0.357711   0.370504  0.316375   \n",
      "1709   0.137817   0.236742   0.271775   0.282669   0.239250  0.349914   \n",
      "1710   0.022321   0.412409   0.433036   0.344891   0.397321  0.189781   \n",
      "1711   0.028090   0.442826   0.425562   0.269148   0.306180  0.211974   \n",
      "1712   0.008772   0.408419   0.456140   0.318544   0.307018  0.246871   \n",
      "1713   0.025210   0.113074   0.067227   0.137809   0.126050  0.526502   \n",
      "1714   0.020495   0.361988   0.400512   0.348724   0.366354  0.247146   \n",
      "1715   0.123636   0.316667   0.287273   0.262500   0.247273  0.229167   \n",
      "1716   0.114967   0.250575   0.312364   0.245211   0.273319  0.335632   \n",
      "1717   0.182272   0.351249   0.399501   0.162866   0.161049  0.298046   \n",
      "1718   0.069343   0.243745   0.310219   0.374892   0.324818  0.294219   \n",
      "1719   0.148148   0.141264   0.140741   0.323420   0.200000  0.327138   \n",
      "1720   0.037209   0.255352   0.265116   0.373089   0.381395  0.273700   \n",
      "1721   0.216643   0.235294   0.241033   0.276471   0.288379  0.206335   \n",
      "1722   0.127072   0.330759   0.386740   0.253968   0.213628  0.306735   \n",
      "1723   0.095238   0.343612   0.422619   0.296623   0.261905  0.274596   \n",
      "1724   0.069892   0.274349   0.336918   0.340520   0.317204  0.308550   \n",
      "1725   0.099437   0.301724   0.388368   0.250663   0.181989  0.372679   \n",
      "1726   0.332581   0.271656   0.241535   0.196310   0.166290  0.202460   \n",
      "1727   0.146893   0.194790   0.231638   0.199604   0.175141  0.466591   \n",
      "1728   0.059502   0.259889   0.284153   0.314787   0.332119  0.339002   \n",
      "1729   0.052632   0.311554   0.284211   0.297799   0.280000  0.299175   \n",
      "1730   0.116279   0.272212   0.313341   0.271150   0.298654  0.282478   \n",
      "1731   0.051042   0.348930   0.361458   0.321858   0.296875  0.235963   \n",
      "1732   0.056962   0.188312   0.297468   0.259740   0.227848  0.402597   \n",
      "1733   0.045455   0.165746   0.176768   0.390884   0.429293  0.334254   \n",
      "1734   0.047619   0.293853   0.285714   0.397301   0.400000  0.242879   \n",
      "1735   0.052345   0.452475   0.459106   0.213201   0.251908  0.247195   \n",
      "1736   0.055556   0.240248   0.262626   0.252012   0.207071  0.426625   \n",
      "1737   0.153477   0.241531   0.249400   0.232120   0.211031  0.337516   \n",
      "1738   0.067524   0.230769   0.372990   0.335059   0.302251  0.362426   \n",
      "1739   0.020270   0.479452   0.506757   0.279452   0.236486  0.183562   \n",
      "1740   0.034913   0.222659   0.291771   0.438238   0.403990  0.269079   \n",
      "1741   0.116279   0.266542   0.273902   0.213420   0.237726  0.388630   \n",
      "1742   0.100132   0.262210   0.299078   0.359412   0.341238  0.258416   \n",
      "1743   0.022978   0.234677   0.280331   0.311548   0.314338  0.355232   \n",
      "1744   0.228650   0.230216   0.214876   0.203237   0.217631  0.344424   \n",
      "1745   0.072655   0.365703   0.377146   0.268401   0.273314  0.263275   \n",
      "1746   0.114078   0.248354   0.315534   0.248354   0.366505  0.310442   \n",
      "1747   0.127660   0.140091   0.143617   0.088838   0.114362  0.544419   \n",
      "1748   0.072917   0.194991   0.284722   0.328265   0.295139  0.366726   \n",
      "1749   0.045802   0.173824   0.335878   0.335378   0.221374  0.337423   \n",
      "1750   0.082892   0.277822   0.303351   0.317854   0.352734  0.304243   \n",
      "1751   0.065789   0.410423   0.526316   0.231270   0.184211  0.299674   \n",
      "1752   0.024390   0.261538   0.292683   0.207692   0.048780  0.484615   \n",
      "1753   0.107143   0.320442   0.303571   0.292818   0.250000  0.287293   \n",
      "1754   0.056738   0.238693   0.241135   0.437186   0.482270  0.155779   \n",
      "1755   0.073529   0.203996   0.242647   0.321767   0.311275  0.349106   \n",
      "1756   0.086651   0.214836   0.281030   0.275017   0.241218  0.337999   \n",
      "1757   0.000000   0.174641   0.245487   0.368421   0.361011  0.375598   \n",
      "1758   0.150602   0.205674   0.234940   0.157801   0.222892  0.338652   \n",
      "1759   0.017391   0.302211   0.358261   0.367322   0.393043  0.255528   \n",
      "1760   0.065120   0.236616   0.251497   0.322276   0.310629  0.352299   \n",
      "1761   0.092810   0.224784   0.329412   0.337536   0.359477  0.307997   \n",
      "1762   0.160194   0.303478   0.269417   0.313913   0.330097  0.263478   \n",
      "1763   0.040850   0.302758   0.325163   0.425273   0.405229  0.205901   \n",
      "1764   0.018405   0.119777   0.153374   0.353760   0.276074  0.455432   \n",
      "1765   0.058278   0.297561   0.364238   0.325942   0.376159  0.255876   \n",
      "1766   0.031579   0.215768   0.315789   0.392116   0.336842  0.296680   \n",
      "1767   0.046154   0.383886   0.553846   0.289100   0.246154  0.199052   \n",
      "1768   0.000000   0.184783   0.333333   0.421196   0.300000  0.307065   \n",
      "1769   0.097122   0.248736   0.323741   0.314459   0.255396  0.276036   \n",
      "1770   0.203125   0.106045   0.234375   0.054083   0.218750  0.185578   \n",
      "1771   0.047725   0.293872   0.320755   0.365569   0.338513  0.286369   \n",
      "1772   0.055556   0.181818   0.166667   0.368831   0.238095  0.405195   \n",
      "1773   0.045181   0.246946   0.237952   0.431937   0.400602  0.268761   \n",
      "1774   0.050000   0.470968   0.425000   0.316129   0.400000  0.161290   \n",
      "1775   0.138211   0.191489   0.300813   0.191489   0.227642  0.288754   \n",
      "1776   0.041667   0.689519   0.679825   0.200946   0.188596  0.071710   \n",
      "1777   0.025641   0.281955   0.299145   0.191729   0.247863  0.390977   \n",
      "1778   0.106667   0.207273   0.240000   0.389091   0.333333  0.312727   \n",
      "1779   0.052632   0.226158   0.263158   0.204360   0.177632  0.425068   \n",
      "1780   0.115942   0.294574   0.144928   0.155039   0.173913  0.333333   \n",
      "1781   0.073420   0.296841   0.355948   0.347721   0.359665  0.252231   \n",
      "1782   0.099057   0.193684   0.311321   0.208421   0.264151  0.206316   \n",
      "1783   0.136076   0.231332   0.218354   0.288433   0.291139  0.262079   \n",
      "1784   0.214286   0.183607   0.202381   0.316393   0.321429  0.347541   \n",
      "1785   0.033746   0.258094   0.323960   0.437216   0.420697  0.261120   \n",
      "1786   0.135783   0.226744   0.260383   0.250000   0.244409  0.275899   \n",
      "1787   0.076087   0.269209   0.285714   0.282950   0.262422  0.338755   \n",
      "1788   0.129310   0.179764   0.206897   0.228880   0.238506  0.466601   \n",
      "1789   0.171674   0.196275   0.244635   0.369628   0.218884  0.309456   \n",
      "1790   0.006536   0.320129   0.315904   0.311237   0.372549  0.269200   \n",
      "1791   0.223214   0.208191   0.187500   0.221843   0.267857  0.324232   \n",
      "1792   0.043315   0.273941   0.317368   0.352504   0.376926  0.286874   \n",
      "1793   0.233193   0.333065   0.329832   0.234677   0.195378  0.150806   \n",
      "1794   0.224490   0.295826   0.311224   0.223230   0.173469  0.208711   \n",
      "1795   0.066116   0.268852   0.231405   0.334426   0.355372  0.262295   \n",
      "1796   0.049020   0.235556   0.235294   0.191111   0.333333  0.311111   \n",
      "1797   0.110204   0.210219   0.310204   0.316788   0.228571  0.270073   \n",
      "1798   0.026059   0.203276   0.260586   0.184971   0.195440  0.455684   \n",
      "1799   0.098494   0.247923   0.280417   0.341058   0.338355  0.273721   \n",
      "1800   0.072581   0.288956   0.262097   0.366112   0.407258  0.285930   \n",
      "1801   0.073418   0.209577   0.330380   0.335184   0.279747  0.380291   \n",
      "1802   0.228897   0.227510   0.225856   0.169788   0.141445  0.347866   \n",
      "1803   0.197531   0.060714   0.329218   0.045408   0.222222  0.155102   \n",
      "1804   0.010929   0.194415   0.196721   0.396348   0.486339  0.360902   \n",
      "1805   0.074830   0.283734   0.333333   0.303142   0.319728  0.346580   \n",
      "1806   0.077049   0.165295   0.227869   0.299497   0.280328  0.425240   \n",
      "1807   0.021807   0.195100   0.283489   0.362069   0.299065  0.414701   \n",
      "1808   0.067857   0.261649   0.282143   0.219235   0.228571  0.366189   \n",
      "1809   0.092683   0.439222   0.336585   0.181524   0.292683  0.175041   \n",
      "1810   0.095064   0.325540   0.396709   0.229017   0.236746  0.317746   \n",
      "1811   0.108108   0.217391   0.405405   0.086957   0.081081  0.391304   \n",
      "1812   0.142857   0.379854   0.344948   0.137136   0.101045  0.371359   \n",
      "1813   0.027160   0.274408   0.330864   0.388793   0.301235  0.248122   \n",
      "1814   0.053178   0.308739   0.356680   0.305338   0.300908  0.334920   \n",
      "1815   0.019780   0.492328   0.483516   0.274003   0.284615  0.205173   \n",
      "1816   0.081395   0.306998   0.345930   0.367946   0.348837  0.181716   \n",
      "1817   0.176334   0.243304   0.269142   0.188988   0.141531  0.335565   \n",
      "1818   0.065934   0.240518   0.217033   0.349676   0.337912  0.283996   \n",
      "1819   0.028552   0.433148   0.432935   0.310345   0.312749  0.204672   \n",
      "1820   0.073491   0.350407   0.412073   0.266589   0.249344  0.295693   \n",
      "1821   0.036697   0.364842   0.399083   0.291874   0.284404  0.225539   \n",
      "1822   0.018421   0.212714   0.389474   0.383863   0.307895  0.372127   \n",
      "1823   0.000000   0.084444   0.187500   0.328889   0.287500  0.386667   \n",
      "1824   0.009501   0.184103   0.180523   0.365641   0.294537  0.398462   \n",
      "1825   0.016667   0.154791   0.225000   0.292383   0.200000  0.491400   \n",
      "1826   0.029412   0.257435   0.291444   0.326208   0.368984  0.270446   \n",
      "1827   0.014368   0.280501   0.321839   0.223149   0.152299  0.319082   \n",
      "1828   0.064516   0.230221   0.205645   0.376336   0.403226  0.313614   \n",
      "1829   0.051724   0.206349   0.310345   0.439153   0.293103  0.264550   \n",
      "1830   0.102128   0.253607   0.287234   0.244495   0.214894  0.347001   \n",
      "1831   0.028986   0.343915   0.355072   0.248677   0.239130  0.312169   \n",
      "1832   0.061552   0.202188   0.242640   0.265937   0.306869  0.428895   \n",
      "1833   0.095839   0.321569   0.384615   0.259314   0.261034  0.254902   \n",
      "1834   0.225352   0.253232   0.282570   0.248105   0.202465  0.338609   \n",
      "1835   0.036199   0.323741   0.333333   0.417746   0.432881  0.203357   \n",
      "1836   0.018182   0.379904   0.463636   0.359809   0.339394  0.210526   \n",
      "1837   0.014354   0.398981   0.531100   0.404075   0.293461  0.187889   \n",
      "1838   0.106109   0.365768   0.395498   0.261430   0.250804  0.188746   \n",
      "1839   0.035000   0.278736   0.315000   0.386207   0.290000  0.312644   \n",
      "1840   0.034043   0.514694   0.529787   0.266878   0.278723  0.158856   \n",
      "1841   0.066998   0.313058   0.354839   0.285410   0.286600  0.318162   \n",
      "1842   0.020681   0.348039   0.377129   0.383578   0.356448  0.235600   \n",
      "1843   0.018284   0.332266   0.492264   0.352544   0.347398  0.219495   \n",
      "1844   0.046647   0.201586   0.247813   0.210646   0.209913  0.421291   \n",
      "1845   0.071429   0.321792   0.295918   0.336049   0.352041  0.264766   \n",
      "1846   0.174737   0.316823   0.269474   0.163962   0.221053  0.357814   \n",
      "1847   0.114407   0.291709   0.312147   0.283114   0.299435  0.274520   \n",
      "1848   0.000000   0.365079   0.382353   0.238095   0.227941  0.279365   \n",
      "1849   0.203327   0.249531   0.323475   0.333490   0.247689  0.292214   \n",
      "1850   0.151618   0.272727   0.255537   0.164654   0.214651  0.430388   \n",
      "1851   0.103409   0.318505   0.344318   0.290036   0.286364  0.272242   \n",
      "1852   0.092851   0.332885   0.323747   0.270953   0.311422  0.272972   \n",
      "1853   0.024531   0.292297   0.366522   0.409904   0.406926  0.270977   \n",
      "1854   0.029740   0.410526   0.472119   0.357895   0.323420  0.205263   \n",
      "1855   0.088732   0.172818   0.205634   0.301780   0.300000  0.408163   \n",
      "1856   0.045455   0.153061   0.266234   0.432653   0.350649  0.322449   \n",
      "1857   0.040000   0.445205   0.400000   0.256849   0.280000  0.248288   \n",
      "1858   0.000000   0.205882   0.125000   0.529412   0.750000  0.235294   \n",
      "1859   0.137725   0.185668   0.260479   0.273616   0.308383  0.227199   \n",
      "1860   0.200669   0.249119   0.307692   0.305523   0.301003  0.184489   \n",
      "1861   0.077170   0.343266   0.379421   0.274136   0.254019  0.241955   \n",
      "1862   0.125257   0.178244   0.223819   0.189384   0.186858  0.311927   \n",
      "1863   0.020408   0.370879   0.520408   0.368132   0.255102  0.197802   \n",
      "1864   0.100000   0.265823   0.255556   0.367089   0.355556  0.240506   \n",
      "1865   0.031484   0.438269   0.460270   0.403189   0.310345  0.134396   \n",
      "1866   0.178451   0.296662   0.342312   0.243065   0.200898  0.261871   \n",
      "1867   0.030726   0.298752   0.363128   0.340874   0.337989  0.295632   \n",
      "1868   0.017143   0.395871   0.285714   0.309047   0.302857  0.274438   \n",
      "1869   0.030189   0.185507   0.162264   0.384541   0.396226  0.376812   \n",
      "1870   0.026393   0.304865   0.284457   0.341622   0.343109  0.299459   \n",
      "1871   0.212766   0.047945   0.085106   0.239726   0.255319  0.520548   \n",
      "1872   0.294643   0.181935   0.178571   0.112258   0.321429  0.179355   \n",
      "1873   0.299270   0.146259   0.160584   0.176871   0.145985  0.241497   \n",
      "1874   0.040179   0.635088   0.580357   0.118129   0.178571  0.171930   \n",
      "1875   0.015000   0.752013   0.785000   0.169887   0.105000  0.067633   \n",
      "1876   0.000000   0.701368   0.618257   0.172492   0.170124  0.111702   \n",
      "1877   0.101881   0.258186   0.294671   0.160579   0.184953  0.365239   \n",
      "1878   0.042963   0.253870   0.271111   0.380186   0.312593  0.288545   \n",
      "1879   0.088496   0.247126   0.318584   0.316092   0.300885  0.272989   \n",
      "1880   0.066116   0.300437   0.363636   0.441485   0.348760  0.222707   \n",
      "1881   0.010886   0.442495   0.527216   0.334835   0.275272  0.194451   \n",
      "1882   0.018182   0.304853   0.409091   0.401914   0.324242  0.264525   \n",
      "1883   0.024390   0.225806   0.073171   0.096774   0.170732  0.500000   \n",
      "1884   0.174432   0.393828   0.359618   0.210507   0.222222  0.230345   \n",
      "1885   0.183628   0.327520   0.329646   0.222343   0.150442  0.291553   \n",
      "1886   0.225806   0.188202   0.204301   0.123596   0.150538  0.471910   \n",
      "1887   0.059754   0.315242   0.318102   0.222305   0.231986  0.359851   \n",
      "1888   0.125000   0.210584   0.212121   0.265711   0.250000  0.390298   \n",
      "1889   0.037037   0.233333   0.245614   0.281538   0.327485  0.372308   \n",
      "1890   0.013274   0.445643   0.579646   0.224066   0.238938  0.303734   \n",
      "1891   0.024272   0.279959   0.305825   0.331612   0.266990  0.305785   \n",
      "1892   0.025822   0.141284   0.138498   0.183486   0.204225  0.470642   \n",
      "1893   0.373333   0.108553   0.206667   0.264803   0.186667  0.268092   \n",
      "1894   0.032110   0.369469   0.433486   0.377212   0.357798  0.215708   \n",
      "1895   0.007937   0.175532   0.277778   0.386525   0.301587  0.349291   \n",
      "1896   0.062762   0.344778   0.309623   0.316166   0.313808  0.257511   \n",
      "1897   0.237288   0.272189   0.251412   0.150888   0.110169  0.408284   \n",
      "1898   0.026829   0.367074   0.413415   0.454927   0.446341  0.147441   \n",
      "1899   0.080636   0.607525   0.580362   0.136719   0.146462  0.172492   \n",
      "1900   0.028986   0.207955   0.286957   0.364205   0.333333  0.373295   \n",
      "1901   0.008247   0.478228   0.435052   0.321321   0.350515  0.147147   \n",
      "1902   0.186813   0.215122   0.271062   0.181818   0.208791  0.399640   \n",
      "1903   0.160305   0.244828   0.236641   0.286207   0.259542  0.386207   \n",
      "1904   0.050633   0.211538   0.265823   0.256410   0.303797  0.365385   \n",
      "1905   0.043750   0.326568   0.375000   0.431734   0.393750  0.217712   \n",
      "1906   0.011111   0.072937   0.222222   0.145873   0.166667  0.758157   \n",
      "1907   0.111901   0.181966   0.298401   0.314785   0.250444  0.393176   \n",
      "1908   0.034221   0.350746   0.387833   0.273632   0.273764  0.278607   \n",
      "1909   0.029900   0.216972   0.312292   0.312156   0.273256  0.404358   \n",
      "1910   0.068745   0.273383   0.278977   0.268764   0.278977  0.251443   \n",
      "1911   0.100865   0.155292   0.158501   0.217606   0.299712  0.490603   \n",
      "1912   0.041949   0.208712   0.309878   0.410952   0.416103  0.349545   \n",
      "1913   0.053279   0.182800   0.356557   0.429165   0.362705  0.356460   \n",
      "1914   0.013559   0.201669   0.240678   0.327538   0.413559  0.426287   \n",
      "1915   0.077922   0.197002   0.240260   0.286938   0.311688  0.349036   \n",
      "1916   0.067460   0.216839   0.293651   0.288805   0.291667  0.461900   \n",
      "1917   0.032258   0.253247   0.285714   0.311688   0.271889  0.334416   \n",
      "1918   0.023622   0.225979   0.259843   0.376038   0.370079  0.340451   \n",
      "1919   0.044183   0.241730   0.248895   0.385242   0.421208  0.291094   \n",
      "1920   0.060606   0.320998   0.319559   0.371773   0.341598  0.224613   \n",
      "1921   0.089147   0.205047   0.244186   0.255521   0.302326  0.244479   \n",
      "1922   0.019048   0.263876   0.223810   0.389445   0.345238  0.255687   \n",
      "1923   0.054717   0.144866   0.228302   0.234880   0.266038  0.492264   \n",
      "1924   0.020202   0.275394   0.341751   0.405576   0.406566  0.246788   \n",
      "1925   0.167598   0.278998   0.304469   0.246295   0.202514  0.290240   \n",
      "1926   0.044118   0.339672   0.321569   0.307448   0.297059  0.257264   \n",
      "1927   0.165975   0.196751   0.226141   0.248496   0.232365  0.396510   \n",
      "1928   0.060606   0.209366   0.166667   0.358127   0.242424  0.297521   \n",
      "1929   0.215865   0.237712   0.266580   0.157730   0.149545  0.321269   \n",
      "1930   0.110997   0.325405   0.318602   0.235216   0.250771  0.281797   \n",
      "1931   0.018750   0.198357   0.287500   0.315728   0.450000  0.428991   \n",
      "1932   0.092199   0.194672   0.241135   0.284836   0.248227  0.311475   \n",
      "1933   0.075887   0.407018   0.370869   0.267168   0.305998  0.252130   \n",
      "1934   0.005208   0.218659   0.177083   0.195335   0.192708  0.387755   \n",
      "1935   0.036087   0.311962   0.345679   0.349955   0.372745  0.253785   \n",
      "1936   0.031345   0.330469   0.304348   0.232031   0.228514  0.326562   \n",
      "1937   0.014599   0.199105   0.270073   0.275168   0.291971  0.483221   \n",
      "1938   0.040404   0.260714   0.404040   0.214286   0.272727  0.453571   \n",
      "1939   0.071285   0.290691   0.233936   0.234234   0.259036  0.333333   \n",
      "1940   0.038062   0.357724   0.410035   0.322042   0.320069  0.270551   \n",
      "1941   0.028235   0.466397   0.515294   0.289069   0.258824  0.211336   \n",
      "1942   0.145631   0.270904   0.401942   0.142080   0.131068  0.401428   \n",
      "1943   0.049618   0.328345   0.374046   0.309297   0.381679  0.289342   \n",
      "1944   0.090395   0.231335   0.177966   0.125131   0.169492  0.362776   \n",
      "1945   0.018282   0.356000   0.383912   0.384667   0.398537  0.228000   \n",
      "1946   0.045455   0.540059   0.431818   0.219585   0.431818  0.195846   \n",
      "1947   0.117407   0.356933   0.452856   0.208883   0.196283  0.258135   \n",
      "1948   0.070191   0.298273   0.318969   0.335060   0.309196  0.284111   \n",
      "1949   0.072000   0.184953   0.152000   0.216301   0.280000  0.438871   \n",
      "1950   0.007407   0.271277   0.296296   0.308511   0.333333  0.311170   \n",
      "1951   0.061224   0.285276   0.387755   0.352761   0.295918  0.276074   \n",
      "1952   0.079470   0.229032   0.298013   0.304839   0.317881  0.372581   \n",
      "1953   0.203070   0.266826   0.328681   0.212411   0.179344  0.358234   \n",
      "1954   0.190114   0.174033   0.292776   0.113260   0.121673  0.385820   \n",
      "1955   0.027933   0.333863   0.329609   0.243243   0.335196  0.303657   \n",
      "1956   0.033163   0.225073   0.285714   0.323314   0.339286  0.373900   \n",
      "1957   0.037441   0.363960   0.385335   0.287493   0.262090  0.303497   \n",
      "1958   0.029221   0.297327   0.344156   0.336303   0.275974  0.283964   \n",
      "1959   0.013699   0.246120   0.328767   0.458980   0.479452  0.252772   \n",
      "1960   0.101029   0.309035   0.332086   0.239904   0.220767  0.318617   \n",
      "1961   0.064762   0.230937   0.274286   0.318083   0.283810  0.350036   \n",
      "1962   0.096045   0.207278   0.192090   0.295886   0.350282  0.321203   \n",
      "1963   0.092409   0.230684   0.272277   0.243377   0.267327  0.278146   \n",
      "1964   0.161264   0.297898   0.374896   0.221896   0.173732  0.296921   \n",
      "1965   0.030960   0.315599   0.414861   0.409915   0.383901  0.241233   \n",
      "1966   0.068702   0.389886   0.480916   0.377651   0.310433  0.172104   \n",
      "1967   0.078571   0.360630   0.350000   0.229134   0.202381  0.317323   \n",
      "1968   0.206107   0.207510   0.211196   0.178854   0.185751  0.260870   \n",
      "1969   0.222222   0.174741   0.277778   0.214480   0.357143  0.289058   \n",
      "1970   0.036304   0.326968   0.402640   0.351273   0.334983  0.245949   \n",
      "1971   0.178808   0.288591   0.314570   0.151678   0.155629  0.332886   \n",
      "1972   0.100592   0.247619   0.319527   0.348571   0.319527  0.249524   \n",
      "1973   0.017442   0.180848   0.203488   0.513514   0.505814  0.285953   \n",
      "1974   0.187699   0.210084   0.249205   0.320028   0.303287  0.252451   \n",
      "1975   0.214932   0.274236   0.282805   0.204515   0.194570  0.286853   \n",
      "1976   0.046610   0.253627   0.277542   0.294835   0.309322  0.351712   \n",
      "1977   0.016204   0.295711   0.317130   0.284424   0.425926  0.338600   \n",
      "1978   0.083744   0.276680   0.285714   0.229249   0.197044  0.328063   \n",
      "1979   0.125000   0.266344   0.335526   0.179177   0.243421  0.266344   \n",
      "1980   0.046322   0.286160   0.250681   0.352758   0.389646  0.277836   \n",
      "1981   0.073864   0.349355   0.414773   0.381594   0.309659  0.206917   \n",
      "1982   0.000000   0.345740   0.202532   0.364764   0.348101  0.258892   \n",
      "1983   0.009132   0.317578   0.401826   0.271787   0.347032  0.378139   \n",
      "1984   0.031120   0.226768   0.259336   0.254237   0.275934  0.446523   \n",
      "1985   0.049020   0.551570   0.536765   0.293274   0.299020  0.103139   \n",
      "1986   0.053305   0.333841   0.368870   0.263720   0.313433  0.269817   \n",
      "1987   0.025552   0.334358   0.385881   0.366710   0.386748  0.252669   \n",
      "1988   0.036232   0.307879   0.333333   0.326061   0.326087  0.258182   \n",
      "1989   0.072727   0.140625   0.272727   0.294271   0.345455  0.377604   \n",
      "1990   0.051051   0.264525   0.288288   0.349912   0.351351  0.325264   \n",
      "1991   0.102857   0.247978   0.351429   0.221923   0.202857  0.318059   \n",
      "1992   0.100629   0.284163   0.310273   0.339367   0.312369  0.263348   \n",
      "1993   0.050971   0.373074   0.376214   0.313869   0.349515  0.231144   \n",
      "1994   0.173529   0.150828   0.138235   0.185702   0.202941  0.324324   \n",
      "1995   0.249716   0.213574   0.259386   0.220447   0.170648  0.307216   \n",
      "1996   0.063830   0.459283   0.372340   0.214984   0.255319  0.201954   \n",
      "1997   0.040752   0.476601   0.463950   0.206897   0.257053  0.233990   \n",
      "1998   0.067568   0.369441   0.361486   0.258837   0.283784  0.265678   \n",
      "1999   0.054054   0.279853   0.272349   0.350916   0.370062  0.288645   \n",
      "2000   0.028846   0.097826   0.057692   0.391304   0.519231  0.451087   \n",
      "2001   0.093220   0.555140   0.444915   0.119626   0.190678  0.186916   \n",
      "2002   0.000000   0.273810   0.090909   0.083333   0.363636  0.607143   \n",
      "2003   0.000000   0.250000   0.166667   0.166667   0.500000  0.583333   \n",
      "2004   0.166667   0.341121   0.250000   0.172897   0.214286  0.383178   \n",
      "2005   0.022857   0.149038   0.228571   0.302885   0.445714  0.458333   \n",
      "2006   0.353107   0.239325   0.336158   0.098312   0.079096  0.238332   \n",
      "2007   0.052095   0.227875   0.378256   0.282989   0.271801  0.409115   \n",
      "2008   0.000000   0.282857   0.333333   0.282857   0.322581  0.368571   \n",
      "2009   0.012552   0.257259   0.357741   0.399730   0.366109  0.268737   \n",
      "2010   0.208912   0.271161   0.309715   0.223671   0.171658  0.323081   \n",
      "2011   0.054945   0.192771   0.219780   0.240964   0.252747  0.484940   \n",
      "2012   0.030488   0.542991   0.527439   0.234579   0.259146  0.156075   \n",
      "2013   0.125561   0.227191   0.206278   0.359571   0.313901  0.275492   \n",
      "2014   0.156475   0.303502   0.330935   0.261997   0.237410  0.241245   \n",
      "2015   0.277302   0.208285   0.255889   0.237456   0.168094  0.284131   \n",
      "2016   0.061281   0.255567   0.314763   0.327678   0.306407  0.271474   \n",
      "2017   0.399083   0.116445   0.165138   0.128703   0.155963  0.204290   \n",
      "2018   0.040000   0.319075   0.330000   0.346821   0.396667  0.275145   \n",
      "2019   0.026270   0.353169   0.385289   0.279431   0.345009  0.273609   \n",
      "2020   0.088889   0.312043   0.351111   0.244844   0.206667  0.289421   \n",
      "2021   0.065789   0.307317   0.315789   0.273171   0.230263  0.307317   \n",
      "2022   0.128571   0.352941   0.528571   0.159746   0.128571  0.227797   \n",
      "2023   0.063123   0.224835   0.242525   0.276267   0.299003  0.348273   \n",
      "2024   0.064000   0.241863   0.277333   0.214422   0.237333  0.298022   \n",
      "2025   0.126866   0.144330   0.208955   0.171821   0.216418  0.477663   \n",
      "2026   0.003984   0.295808   0.398406   0.279042   0.215139  0.322156   \n",
      "2027   0.220000   0.272283   0.330000   0.171196   0.203333  0.319022   \n",
      "2028   0.166667   0.080645   0.166667   0.204301   0.166667  0.650538   \n",
      "2029   0.103448   0.170732   0.137931   0.317073   0.275862  0.475610   \n",
      "2030   0.128535   0.249733   0.233933   0.318036   0.367609  0.268943   \n",
      "2031   0.084507   0.222892   0.211268   0.463855   0.323944  0.180723   \n",
      "2032   0.103226   0.232906   0.270968   0.170940   0.225806  0.461538   \n",
      "2033   0.080702   0.200952   0.238596   0.330476   0.305263  0.376190   \n",
      "2034   0.051118   0.315389   0.345048   0.373794   0.354633  0.236668   \n",
      "2035   0.062916   0.320008   0.369631   0.329798   0.389595  0.282072   \n",
      "2036   0.067797   0.424357   0.458624   0.302260   0.333001  0.187382   \n",
      "2037   0.081818   0.327957   0.450000   0.280645   0.281818  0.184946   \n",
      "2038   0.201794   0.223436   0.286996   0.213505   0.206278  0.347567   \n",
      "2039   0.133333   0.460993   0.333333   0.184397   0.146667  0.138298   \n",
      "2040   0.047120   0.205628   0.204188   0.196970   0.267016  0.303030   \n",
      "2041   0.203057   0.133374   0.176856   0.284249   0.318777  0.247435   \n",
      "2042   0.094059   0.144681   0.178218   0.423404   0.404290  0.283688   \n",
      "2043   0.000000   0.512273   0.462838   0.389541   0.432432  0.062967   \n",
      "2044   0.126761   0.249351   0.239437   0.192208   0.246479  0.397403   \n",
      "2045   0.092179   0.338727   0.293296   0.277238   0.173184  0.189860   \n",
      "2046   0.016216   0.472222   0.470270   0.333333   0.329730  0.152778   \n",
      "2047   0.021299   0.418935   0.425985   0.310848   0.335463  0.220513   \n",
      "2048   0.175953   0.179160   0.325513   0.208396   0.152493  0.355322   \n",
      "2049   0.066456   0.374280   0.351266   0.205374   0.291139  0.285988   \n",
      "2050   0.034483   0.492308   0.459770   0.133333   0.091954  0.133333   \n",
      "2051   0.033113   0.178794   0.245033   0.320166   0.364238  0.472973   \n",
      "2052   0.088235   0.274374   0.318015   0.216566   0.242647  0.392580   \n",
      "2053   0.017719   0.391705   0.429679   0.438143   0.404208  0.155619   \n",
      "2054   0.048673   0.411079   0.438053   0.291545   0.314159  0.209913   \n",
      "2055   0.074074   0.194495   0.191358   0.288073   0.290123  0.377982   \n",
      "2056   0.152284   0.210121   0.177665   0.194719   0.177665  0.352035   \n",
      "2057   0.000000   0.290168   0.325926   0.424460   0.392593  0.237410   \n",
      "2058   0.091623   0.344969   0.337696   0.240246   0.290576  0.313142   \n",
      "2059   0.189066   0.228234   0.232346   0.235075   0.273349  0.228856   \n",
      "2060   0.098446   0.209824   0.202073   0.307459   0.376511  0.335961   \n",
      "2061   0.135762   0.284842   0.350993   0.248220   0.271523  0.287894   \n",
      "2062   0.050663   0.302222   0.299299   0.387259   0.431800  0.236741   \n",
      "2063   0.079365   0.290520   0.238095   0.324159   0.420635  0.272171   \n",
      "2064   0.027113   0.334850   0.375997   0.377009   0.366029  0.241280   \n",
      "2065   0.334270   0.301695   0.272472   0.112712   0.151685  0.227119   \n",
      "2066   0.031250   0.041667   0.093750   0.458333   0.437500  0.354167   \n",
      "2067   0.145161   0.202830   0.221774   0.254717   0.209677  0.397799   \n",
      "2068   0.020270   0.323264   0.430743   0.534716   0.488176  0.096934   \n",
      "2069   0.083665   0.300601   0.292829   0.334001   0.384462  0.181029   \n",
      "2070   0.044776   0.172093   0.238806   0.409302   0.253731  0.362791   \n",
      "2071   0.024390   0.215206   0.247967   0.332474   0.329268  0.372423   \n",
      "2072   0.122222   0.290837   0.233333   0.151394   0.288889  0.338645   \n",
      "2073   0.105740   0.284191   0.302115   0.232748   0.244713  0.368883   \n",
      "2074   0.296830   0.154706   0.224784   0.095993   0.198847  0.175210   \n",
      "2075   0.000000   0.116797   0.122162   0.251491   0.227027  0.605651   \n",
      "2076   0.064854   0.296782   0.338912   0.345948   0.320781  0.273242   \n",
      "2077   0.188482   0.230303   0.157068   0.444444   0.329843  0.133333   \n",
      "2078   0.031496   0.250000   0.401575   0.306000   0.267717  0.326000   \n",
      "2079   0.020677   0.300446   0.327068   0.380764   0.390977  0.249380   \n",
      "2080   0.114583   0.205575   0.229167   0.236934   0.281250  0.358885   \n",
      "2081   0.092949   0.239486   0.163462   0.276869   0.304487  0.297897   \n",
      "2082   0.129771   0.317716   0.320611   0.130307   0.190840  0.314788   \n",
      "2083   0.017403   0.328951   0.385542   0.485509   0.479250  0.175680   \n",
      "2084   0.023256   0.297985   0.395349   0.499470   0.404651  0.183457   \n",
      "2085   0.071429   0.251586   0.318182   0.300211   0.207792  0.186047   \n",
      "2086   0.020253   0.341171   0.382278   0.482241   0.462025  0.141571   \n",
      "2087   0.101115   0.200965   0.415613   0.341186   0.273606  0.392563   \n",
      "2088   0.029851   0.286988   0.378109   0.399287   0.343284  0.274510   \n",
      "2089   0.077882   0.205212   0.327103   0.355049   0.149533  0.344191   \n",
      "2090   0.082143   0.279690   0.275000   0.374355   0.428571  0.228055   \n",
      "2091   0.042254   0.296894   0.319249   0.315528   0.338028  0.326708   \n",
      "2092   0.034783   0.233062   0.286957   0.466125   0.382609  0.214092   \n",
      "2093   0.075342   0.265550   0.284247   0.113636   0.140411  0.478469   \n",
      "2094   0.014388   0.179775   0.244604   0.292135   0.223022  0.412921   \n",
      "2095   0.084677   0.193182   0.205645   0.211648   0.290323  0.485795   \n",
      "2096   0.076336   0.330492   0.439695   0.327652   0.279389  0.205492   \n",
      "2097   0.095723   0.261224   0.336049   0.206803   0.287169  0.361905   \n",
      "2098   0.022727   0.349206   0.522727   0.222222   0.227273  0.373016   \n",
      "2099   0.168831   0.288428   0.324675   0.271157   0.225108  0.269430   \n",
      "2100   0.010204   0.217036   0.295918   0.470945   0.408163  0.288681   \n",
      "2101   0.070988   0.286645   0.348765   0.234528   0.222222  0.380293   \n",
      "2102   0.207407   0.280566   0.303704   0.184685   0.162963  0.274775   \n",
      "2103   0.030534   0.325758   0.404580   0.265152   0.206107  0.308081   \n",
      "2104   0.009346   0.307692   0.261682   0.281469   0.392523  0.381119   \n",
      "2105   0.136194   0.298141   0.328358   0.221780   0.212687  0.322709   \n",
      "2106   0.000000   0.250000   0.000000   0.166667   0.285714  0.458333   \n",
      "2107   0.041885   0.265973   0.246073   0.251301   0.238220  0.378609   \n",
      "2108   0.042857   0.232767   0.171429   0.534466   0.442857  0.214785   \n",
      "2109   0.037244   0.255682   0.275605   0.290404   0.355680  0.395833   \n",
      "2110   0.000000   0.161107   0.242718   0.522356   0.378641  0.290987   \n",
      "2111   0.020408   0.211738   0.346939   0.367089   0.326531  0.400460   \n",
      "2112   0.189474   0.350318   0.467368   0.106460   0.128421  0.223840   \n",
      "2113   0.000000   0.160000   0.280000   0.213333   0.320000  0.600000   \n",
      "2114   0.124454   0.356996   0.344978   0.172840   0.185590  0.332305   \n",
      "2115   0.063158   0.322191   0.284211   0.351903   0.389474  0.264624   \n",
      "2116   0.041237   0.301003   0.360825   0.214047   0.185567  0.381271   \n",
      "2117   0.014778   0.267943   0.334975   0.296651   0.295567  0.311005   \n",
      "2118   0.022222   0.095238   0.133333   0.435374   0.333333  0.401361   \n",
      "2119   0.101449   0.174274   0.217391   0.224066   0.260870  0.402490   \n",
      "2120   0.051913   0.272304   0.248634   0.334368   0.344262  0.312645   \n",
      "2121   0.000000   0.544304   0.250000   0.075949   0.375000  0.139241   \n",
      "2122   0.000000   0.209877   0.476190   0.395062   0.285714  0.308642   \n",
      "2123   0.059701   0.193694   0.171642   0.204955   0.216418  0.515766   \n",
      "2124   0.053571   0.237624   0.339286   0.257426   0.178571  0.306931   \n",
      "2125   0.061224   0.352113   0.265306   0.126761   0.244898  0.295775   \n",
      "2126   0.200000   0.157895   0.000000   0.105263   0.400000  0.210526   \n",
      "2127   0.087500   0.255556   0.275000   0.211111   0.162500  0.281481   \n",
      "2128   0.000000   0.000000   0.000000   0.160000   0.000000  0.360000   \n",
      "2129   0.200000   0.142857   0.000000   0.371429   0.400000  0.400000   \n",
      "2130   0.095238   0.358491   0.285714   0.226415   0.095238  0.226415   \n",
      "2131   0.027460   0.172993   0.302059   0.421904   0.331808  0.342875   \n",
      "2132   0.000000   0.210526   0.250000   0.263158   0.250000  0.526316   \n",
      "2133   0.000000   0.333333   0.000000   0.000000   0.000000  0.333333   \n",
      "2134   0.041379   0.282895   0.424138   0.232456   0.300000  0.429825   \n",
      "2135   0.074364   0.286003   0.302348   0.295712   0.283757  0.305421   \n",
      "2136   0.021605   0.280450   0.330247   0.272262   0.311728  0.334698   \n",
      "2137   0.046440   0.346154   0.408669   0.373077   0.349845  0.194872   \n",
      "2138   0.017544   0.304487   0.385965   0.366987   0.374269  0.246795   \n",
      "2139   0.037037   0.314410   0.425926   0.318777   0.305556  0.301310   \n",
      "2140   0.025840   0.308887   0.405685   0.377912   0.441860  0.262295   \n",
      "2141   0.137980   0.241215   0.204836   0.186420   0.240398  0.381775   \n",
      "2142   0.031716   0.236728   0.406716   0.315057   0.313433  0.333768   \n",
      "2143   0.021696   0.200307   0.258383   0.279201   0.362919  0.381660   \n",
      "2144   0.039683   0.402959   0.505291   0.323760   0.289683  0.217581   \n",
      "2145   0.022695   0.378938   0.458156   0.279928   0.292199  0.277228   \n",
      "2146   0.046875   0.369381   0.369141   0.369707   0.372070  0.211075   \n",
      "2147   0.036437   0.298795   0.337652   0.366867   0.339271  0.286145   \n",
      "2148   0.029126   0.258303   0.318447   0.259225   0.248544  0.344096   \n",
      "2149   0.042247   0.155394   0.111378   0.195081   0.215074  0.476803   \n",
      "2150   0.081818   0.217986   0.269697   0.335288   0.312121  0.404692   \n",
      "2151   0.038356   0.362963   0.361644   0.193519   0.169863  0.296296   \n",
      "2152   0.108738   0.232868   0.287379   0.307385   0.225243  0.363939   \n",
      "2153   0.008163   0.333333   0.391837   0.300123   0.289796  0.325953   \n",
      "2154   0.073529   0.275939   0.266176   0.384184   0.357353  0.265283   \n",
      "2155   0.061567   0.217494   0.234142   0.330969   0.281716  0.371946   \n",
      "2156   0.037757   0.272606   0.305492   0.279287   0.247140  0.361693   \n",
      "2157   0.016760   0.328025   0.365922   0.311040   0.324022  0.263270   \n",
      "2158   0.040000   0.276557   0.291429   0.428571   0.405714  0.271062   \n",
      "2159   0.043796   0.263425   0.332117   0.365755   0.295620  0.273556   \n",
      "2160   0.093750   0.360825   0.453125   0.298969   0.296875  0.319588   \n",
      "2161   0.070809   0.194191   0.251445   0.258921   0.218208  0.403320   \n",
      "2162   0.014903   0.328821   0.414307   0.280349   0.292101  0.310044   \n",
      "2163   0.026699   0.462658   0.497573   0.360815   0.276699  0.123181   \n",
      "2164   0.081860   0.321075   0.363721   0.314356   0.309767  0.285714   \n",
      "2165   0.077922   0.392100   0.396537   0.270404   0.274459  0.250073   \n",
      "2166   0.043537   0.300306   0.383673   0.418898   0.385034  0.234889   \n",
      "2167   0.041026   0.296276   0.370940   0.383352   0.340171  0.269441   \n",
      "2168   0.007752   0.251675   0.390181   0.361504   0.325581  0.328369   \n",
      "2169   0.030000   0.127572   0.190000   0.242798   0.220000  0.555556   \n",
      "2170   0.040628   0.231426   0.262696   0.234202   0.253463  0.396883   \n",
      "2171   0.028418   0.306321   0.401690   0.401311   0.367896  0.250168   \n",
      "2172   0.041602   0.304153   0.334361   0.322079   0.348228  0.294891   \n",
      "2173   0.018657   0.464839   0.470149   0.404052   0.361940  0.104887   \n",
      "2174   0.131579   0.195335   0.217105   0.276968   0.256579  0.300292   \n",
      "2175   0.012552   0.253576   0.309623   0.383456   0.433054  0.328952   \n",
      "2176   0.069284   0.375694   0.399538   0.254167   0.307159  0.229861   \n",
      "2177   0.041779   0.249040   0.315364   0.410051   0.388140  0.227913   \n",
      "2178   0.055186   0.256956   0.261636   0.214875   0.220745  0.391790   \n",
      "2179   0.119658   0.375315   0.365967   0.218024   0.228438  0.227540   \n",
      "2180   0.047285   0.449503   0.399299   0.221026   0.273205  0.278974   \n",
      "2181   0.028571   0.230131   0.271429   0.252246   0.338776  0.405667   \n",
      "2182   0.065116   0.300885   0.274419   0.362832   0.381395  0.284661   \n",
      "2183   0.014768   0.688004   0.578059   0.199642   0.265823  0.096240   \n",
      "2184   0.062571   0.350171   0.369738   0.284846   0.326507  0.244208   \n",
      "2185   0.077994   0.300186   0.317549   0.272342   0.325905  0.308937   \n",
      "2186   0.108209   0.289773   0.414179   0.181818   0.223881  0.240909   \n",
      "2187   0.086275   0.282784   0.271569   0.242156   0.234314  0.337892   \n",
      "2188   0.029412   0.313845   0.332983   0.306361   0.261555  0.297942   \n",
      "2189   0.249147   0.200000   0.225256   0.215894   0.191126  0.356291   \n",
      "2190   0.021368   0.500686   0.542735   0.297668   0.264957  0.159122   \n",
      "2191   0.217064   0.323559   0.331242   0.148129   0.153074  0.301820   \n",
      "2192   0.108866   0.572841   0.567901   0.152910   0.168350  0.148345   \n",
      "2193   0.100000   0.298390   0.301333   0.275279   0.242667  0.328106   \n",
      "2194   0.039084   0.279079   0.323450   0.362762   0.355795  0.276987   \n",
      "2195   0.177719   0.261881   0.270557   0.226997   0.216180  0.276542   \n",
      "2196   0.081152   0.386927   0.562827   0.140496   0.149215  0.150263   \n",
      "2197   0.083049   0.311471   0.346985   0.293149   0.336746  0.281200   \n",
      "2198   0.030534   0.289033   0.359473   0.324149   0.292158  0.291374   \n",
      "2199   0.029582   0.380861   0.409513   0.346651   0.351508  0.219378   \n",
      "2200   0.000000   0.565476   0.578397   0.244048   0.247387  0.176190   \n",
      "2201   0.040195   0.334462   0.338611   0.262695   0.280146  0.315956   \n",
      "2202   0.080227   0.576527   0.585900   0.169641   0.186386  0.117366   \n",
      "2203   0.104869   0.450429   0.503121   0.222092   0.242197  0.122560   \n",
      "2204   0.026738   0.367681   0.401070   0.288056   0.251337  0.298595   \n",
      "2205   0.015766   0.442792   0.490991   0.241991   0.186937  0.263730   \n",
      "2206   0.004717   0.783664   0.561321   0.088300   0.155660  0.110375   \n",
      "2207   0.006873   0.840412   0.831615   0.061776   0.075601  0.084942   \n",
      "2208   0.020992   0.270691   0.324427   0.360299   0.354962  0.303671   \n",
      "2209   0.049372   0.311943   0.341423   0.282531   0.274477  0.306298   \n",
      "2210   0.032520   0.330439   0.387534   0.359531   0.318428  0.259227   \n",
      "2211   0.011673   0.369400   0.377432   0.331361   0.315175  0.262046   \n",
      "2212   0.107726   0.188982   0.236126   0.237505   0.219804  0.433418   \n",
      "2213   0.048061   0.266154   0.355651   0.354839   0.357640  0.302851   \n",
      "2214   0.061008   0.237060   0.278515   0.328157   0.270557  0.359213   \n",
      "2215   0.149474   0.247151   0.301053   0.294692   0.292105  0.295344   \n",
      "2216   0.109078   0.274809   0.298381   0.311024   0.289233  0.286703   \n",
      "2217   0.040998   0.240253   0.294118   0.316122   0.367201  0.252371   \n",
      "2218   0.117910   0.228906   0.298507   0.334679   0.273134  0.262010   \n",
      "2219   0.046632   0.669091   0.595855   0.241212   0.274611  0.078788   \n",
      "2220   0.059767   0.253654   0.319242   0.338520   0.367347  0.264969   \n",
      "2221   0.067380   0.242907   0.380749   0.354160   0.373262  0.331208   \n",
      "2222   0.053299   0.275328   0.356176   0.322408   0.345178  0.321216   \n",
      "2223   0.035912   0.196019   0.339779   0.398096   0.353591  0.375595   \n",
      "2224   0.069091   0.245199   0.261818   0.257016   0.272727  0.404727   \n",
      "2225   0.039057   0.283229   0.354099   0.344984   0.355713  0.292476   \n",
      "2226   0.390855   0.254734   0.191740   0.184400   0.117994  0.307484   \n",
      "2227   0.062016   0.544276   0.534884   0.282937   0.240310  0.125270   \n",
      "2228   0.089646   0.346263   0.396465   0.230303   0.220960  0.265455   \n",
      "2229   0.291237   0.143952   0.224227   0.209540   0.115979  0.342419   \n",
      "2230   0.022130   0.298602   0.337483   0.354533   0.395574  0.282364   \n",
      "2231   0.025522   0.305112   0.341067   0.511182   0.464037  0.166134   \n",
      "2232   0.058360   0.389706   0.369085   0.338235   0.369085  0.211275   \n",
      "2233   0.025349   0.282333   0.348542   0.365596   0.428390  0.228233   \n",
      "2234   0.041899   0.171875   0.237430   0.358553   0.416201  0.352796   \n",
      "2235   0.100962   0.251282   0.317308   0.273504   0.278846  0.273504   \n",
      "2236   0.143939   0.182051   0.166667   0.341026   0.431818  0.297436   \n",
      "2237   0.042806   0.283866   0.329370   0.308937   0.290725  0.309341   \n",
      "2238   0.081833   0.219565   0.265139   0.234058   0.333879  0.452174   \n",
      "2239   0.054475   0.358824   0.377432   0.263235   0.284047  0.257353   \n",
      "2240   0.028369   0.561375   0.627660   0.241052   0.217730  0.164408   \n",
      "2241   0.033670   0.308171   0.332371   0.339455   0.332371  0.275798   \n",
      "2242   0.051151   0.257220   0.263427   0.270758   0.237852  0.357401   \n",
      "2243   0.034843   0.199156   0.310105   0.217722   0.285714  0.494515   \n",
      "2244   0.000000   0.191429   0.111111   0.428571   0.555556  0.351429   \n",
      "2245   0.404858   0.294038   0.287449   0.039295   0.028340  0.178862   \n",
      "2246   0.211581   0.250984   0.273942   0.198819   0.149220  0.366142   \n",
      "2247   0.060417   0.371951   0.325000   0.086382   0.160417  0.342480   \n",
      "2248   0.159591   0.305496   0.315252   0.160884   0.187107  0.278477   \n",
      "2249   0.074048   0.345474   0.380623   0.272362   0.316955  0.271291   \n",
      "2250   0.054040   0.279387   0.310101   0.290247   0.263636  0.324957   \n",
      "2251   0.219512   0.285637   0.288618   0.284562   0.211382  0.262507   \n",
      "2252   0.161017   0.241838   0.224576   0.125756   0.177966  0.396614   \n",
      "2253   0.028141   0.304923   0.323618   0.282880   0.313568  0.350110   \n",
      "2254   0.060403   0.188202   0.256711   0.314139   0.328859  0.403090   \n",
      "2255   0.061625   0.287072   0.326797   0.214455   0.240896  0.375297   \n",
      "2256   0.017301   0.210813   0.204152   0.303583   0.326990  0.400832   \n",
      "2257   0.052910   0.214308   0.291761   0.252877   0.288738  0.375739   \n",
      "2258   0.091298   0.258096   0.316690   0.208313   0.228245  0.420493   \n",
      "2259   0.062215   0.346278   0.365706   0.276160   0.314112  0.260518   \n",
      "2260   0.038835   0.248731   0.262136   0.297970   0.335922  0.356853   \n",
      "2261   0.029155   0.263941   0.239067   0.233271   0.329446  0.422862   \n",
      "2262   0.070175   0.316602   0.298246   0.274131   0.315789  0.231660   \n",
      "2263   0.065441   0.190440   0.218382   0.373512   0.336029  0.396750   \n",
      "2264   0.039427   0.420389   0.483871   0.226804   0.250896  0.241695   \n",
      "2265   0.058651   0.239954   0.190616   0.292767   0.319648  0.340987   \n",
      "2266   0.073529   0.313830   0.264706   0.186170   0.220588  0.297872   \n",
      "2267   0.026059   0.299903   0.302932   0.211295   0.283388  0.404090   \n",
      "2268   0.032028   0.353612   0.409253   0.195184   0.245552  0.338403   \n",
      "2269   0.020000   0.152104   0.145000   0.310680   0.325000  0.411003   \n",
      "2270   0.044619   0.254967   0.299213   0.287252   0.307087  0.375000   \n",
      "2271   0.058706   0.298969   0.314209   0.279310   0.300867  0.328938   \n",
      "2272   0.147314   0.285166   0.292894   0.230818   0.258232  0.281969   \n",
      "2273   0.072072   0.217086   0.301301   0.244822   0.276276  0.383876   \n",
      "2274   0.040876   0.401013   0.477372   0.332814   0.278832  0.181216   \n",
      "2275   0.073235   0.420279   0.446382   0.276245   0.278989  0.242207   \n",
      "2276   0.049333   0.300610   0.314667   0.380468   0.342667  0.253306   \n",
      "2277   0.068935   0.320362   0.320244   0.295204   0.348168  0.269261   \n",
      "2278   0.063985   0.305556   0.307130   0.337838   0.327239  0.284535   \n",
      "2279   0.097276   0.314642   0.316472   0.271028   0.272374  0.308411   \n",
      "2280   0.137931   0.275000   0.241379   0.170000   0.362069  0.420000   \n",
      "2281   0.040323   0.139665   0.088710   0.122905   0.193548  0.474860   \n",
      "2282   0.061272   0.296710   0.271098   0.345732   0.337572  0.275210   \n",
      "2283   0.058680   0.316577   0.335371   0.339007   0.346781  0.257875   \n",
      "2284   0.019672   0.317762   0.316393   0.339995   0.331967  0.267799   \n",
      "2285   0.041106   0.408930   0.380581   0.296244   0.328845  0.230806   \n",
      "2286   0.034586   0.418473   0.401504   0.332817   0.375940  0.183695   \n",
      "2287   0.061202   0.301048   0.358470   0.306146   0.320219  0.264798   \n",
      "2288   0.170000   0.273081   0.245000   0.194363   0.230000  0.352770   \n",
      "2289   0.023873   0.373317   0.387931   0.340114   0.342838  0.248579   \n",
      "2290   0.025397   0.237933   0.228571   0.354912   0.377778  0.370244   \n",
      "2291   0.091483   0.253536   0.246057   0.206746   0.261830  0.399347   \n",
      "2292   0.058756   0.303294   0.350230   0.334401   0.353687  0.251144   \n",
      "2293   0.071742   0.387656   0.422234   0.273958   0.254107  0.253203   \n",
      "2294   0.089132   0.294664   0.327600   0.336040   0.337764  0.259667   \n",
      "2295   0.064460   0.282797   0.299652   0.287392   0.306620  0.283308   \n",
      "2296   0.052950   0.353721   0.372163   0.299185   0.273828  0.244648   \n",
      "2297   0.027641   0.384649   0.452122   0.360708   0.335143  0.204150   \n",
      "2298   0.042105   0.192691   0.221053   0.475083   0.400000  0.289037   \n",
      "2299   0.261739   0.218196   0.287826   0.146984   0.144348  0.240243   \n",
      "2300   0.206780   0.081040   0.145763   0.165138   0.291525  0.235474   \n",
      "2301   0.025126   0.163429   0.193467   0.381782   0.417085  0.400536   \n",
      "2302   0.157828   0.277687   0.266414   0.240771   0.231061  0.327728   \n",
      "2303   0.143868   0.320630   0.299528   0.304888   0.268868  0.272577   \n",
      "2304   0.269051   0.187732   0.186625   0.143795   0.127527  0.432525   \n",
      "2305   0.120861   0.311379   0.331126   0.325862   0.313466  0.262069   \n",
      "2306   0.157895   0.217661   0.213397   0.375302   0.311005  0.234564   \n",
      "2307   0.043265   0.314305   0.349388   0.346171   0.371429  0.282898   \n",
      "2308   0.118710   0.230884   0.305806   0.305859   0.265806  0.294439   \n",
      "2309   0.035348   0.167047   0.180160   0.358740   0.361460  0.348699   \n",
      "2310   0.037196   0.217338   0.253219   0.321734   0.340486  0.320513   \n",
      "2311   0.035230   0.224803   0.230352   0.358661   0.311653  0.348819   \n",
      "2312   0.051593   0.247580   0.270865   0.286672   0.377086  0.338049   \n",
      "2313   0.173420   0.327403   0.330632   0.274032   0.243517  0.259207   \n",
      "2314   0.219836   0.176383   0.203476   0.178251   0.161554  0.396487   \n",
      "2315   0.139752   0.339153   0.317805   0.259287   0.270186  0.242571   \n",
      "2316   0.127637   0.340939   0.386076   0.288690   0.275316  0.204365   \n",
      "2317   0.046693   0.288600   0.381323   0.362193   0.268482  0.271284   \n",
      "2318   0.015228   0.302551   0.346447   0.369067   0.399746  0.226994   \n",
      "2319   0.029923   0.187361   0.182432   0.265521   0.263514  0.493071   \n",
      "2320   0.069767   0.220333   0.258140   0.290667   0.316279  0.250667   \n",
      "2321   0.197260   0.217636   0.232877   0.167917   0.221918  0.343340   \n",
      "2322   0.148352   0.133053   0.236264   0.226891   0.164835  0.275910   \n",
      "2323   0.129964   0.204099   0.314079   0.208369   0.216606  0.232280   \n",
      "2324   0.084025   0.285906   0.304979   0.208544   0.218880  0.375042   \n",
      "2325   0.113356   0.207636   0.234568   0.272415   0.271605  0.387816   \n",
      "2326   0.062842   0.261057   0.333333   0.330097   0.245902  0.288026   \n",
      "2327   0.210300   0.196229   0.278970   0.148497   0.208155  0.337065   \n",
      "2328   0.053030   0.208501   0.292424   0.319357   0.334848  0.327972   \n",
      "2329   0.057971   0.218493   0.287785   0.304110   0.347826  0.360274   \n",
      "2330   0.027804   0.294492   0.294343   0.304479   0.332694  0.276634   \n",
      "2331   0.029622   0.280011   0.323800   0.323712   0.297242  0.331535   \n",
      "2332   0.064000   0.218935   0.248000   0.289941   0.184000  0.390533   \n",
      "2333   0.070984   0.297815   0.333748   0.283995   0.270237  0.293357   \n",
      "2334   0.028424   0.250684   0.284238   0.275296   0.214470  0.403829   \n",
      "2335   0.023324   0.265832   0.335277   0.392844   0.382896  0.278712   \n",
      "2336   0.051415   0.294049   0.324057   0.263508   0.257547  0.354933   \n",
      "2337   0.034591   0.231693   0.281447   0.232293   0.254717  0.477191   \n",
      "2338   0.068027   0.175563   0.183673   0.351125   0.367347  0.394212   \n",
      "2339   0.057634   0.224618   0.398382   0.316191   0.353893  0.401128   \n",
      "2340   0.027817   0.262185   0.267475   0.345333   0.368046  0.323989   \n",
      "2341   0.094444   0.268182   0.331481   0.293506   0.187037  0.321429   \n",
      "2342   0.028736   0.277611   0.309524   0.318318   0.309524  0.306306   \n",
      "2343   0.051724   0.538488   0.561422   0.193127   0.184267  0.179038   \n",
      "2344   0.125756   0.321891   0.332527   0.261194   0.250302  0.206468   \n",
      "2345   0.156250   0.310843   0.289062   0.202410   0.218750  0.306024   \n",
      "2346   0.062937   0.479482   0.573427   0.125270   0.174825  0.174946   \n",
      "2347   0.154812   0.325668   0.286611   0.227003   0.246862  0.271513   \n",
      "2348   0.046980   0.481395   0.543624   0.148837   0.234899  0.190698   \n",
      "2349   0.232170   0.324503   0.311077   0.150662   0.212443  0.338852   \n",
      "2350   0.089219   0.373585   0.321561   0.206469   0.197026  0.295957   \n",
      "2351   0.143116   0.355496   0.288043   0.171046   0.135870  0.314209   \n",
      "2352   0.091078   0.366314   0.429368   0.238671   0.250929  0.265106   \n",
      "2353   0.060465   0.250441   0.255814   0.195767   0.195349  0.391534   \n",
      "2354   0.141935   0.333333   0.341935   0.228464   0.280645  0.294007   \n",
      "2355   0.184932   0.260928   0.242009   0.234701   0.237443  0.256221   \n",
      "2356   0.023810   0.306003   0.319048   0.306003   0.314286  0.301611   \n",
      "2357   0.037559   0.393407   0.467136   0.235165   0.166667  0.284982   \n",
      "2358   0.144385   0.283505   0.374332   0.175258   0.213904  0.358247   \n",
      "2359   0.025559   0.338820   0.408946   0.329171   0.321086  0.285471   \n",
      "2360   0.059588   0.368906   0.400867   0.203071   0.191766  0.320537   \n",
      "2361   0.057910   0.364391   0.411017   0.213561   0.182203  0.310424   \n",
      "2362   0.017717   0.528775   0.505906   0.223362   0.253937  0.141311   \n",
      "2363   0.256944   0.149171   0.222222   0.256906   0.229167  0.309392   \n",
      "2364   0.329218   0.127436   0.152263   0.215892   0.238683  0.295352   \n",
      "2365   0.271071   0.313140   0.330296   0.228669   0.125285  0.230375   \n",
      "2366   0.117284   0.227273   0.234568   0.263636   0.271605  0.320000   \n",
      "2367   0.079545   0.255144   0.204545   0.218107   0.227273  0.423868   \n",
      "2368   0.210000   0.382789   0.240000   0.127596   0.320000  0.308605   \n",
      "2369   0.082143   0.450623   0.400000   0.190796   0.267857  0.240652   \n",
      "2370   0.017663   0.215691   0.302989   0.395873   0.369565  0.354846   \n",
      "2371   0.050781   0.348800   0.351562   0.268800   0.265625  0.249600   \n",
      "2372   0.262911   0.394316   0.460094   0.119005   0.117371  0.218472   \n",
      "2373   0.108491   0.332268   0.400943   0.293930   0.259434  0.210863   \n",
      "2374   0.074286   0.215494   0.254286   0.309884   0.217143  0.393589   \n",
      "2375   0.173554   0.299045   0.292011   0.224207   0.237833  0.316600   \n",
      "2376   0.078153   0.300043   0.303730   0.305664   0.277087  0.290532   \n",
      "2377   0.030588   0.332416   0.407059   0.325539   0.350588  0.303989   \n",
      "2378   0.035928   0.155983   0.308383   0.428063   0.368263  0.384972   \n",
      "2379   0.054130   0.509403   0.479701   0.184663   0.196920  0.222763   \n",
      "2380   0.040886   0.425427   0.454855   0.268575   0.240204  0.250413   \n",
      "2381   0.099499   0.409691   0.435934   0.163109   0.169649  0.317102   \n",
      "2382   0.090143   0.715153   0.609099   0.087781   0.128054  0.097394   \n",
      "2383   0.069016   0.289950   0.303965   0.225628   0.221733  0.336683   \n",
      "2384   0.122449   0.247148   0.285714   0.152091   0.208163  0.486692   \n",
      "2385   0.018182   0.405093   0.281818   0.152778   0.254545  0.300926   \n",
      "2386   0.075706   0.325178   0.316384   0.235134   0.271186  0.303092   \n",
      "2387   0.106831   0.379726   0.418079   0.210981   0.213148  0.270113   \n",
      "2388   0.124771   0.240637   0.266055   0.166534   0.165138  0.396016   \n",
      "2389   0.081633   0.403509   0.396501   0.222222   0.180758  0.259649   \n",
      "2390   0.151899   0.252291   0.245931   0.268693   0.235081  0.325133   \n",
      "2391   0.124771   0.270469   0.258716   0.231508   0.308257  0.293055   \n",
      "2392   0.049296   0.309377   0.352113   0.242300   0.237089  0.318960   \n",
      "2393   0.008753   0.224123   0.256018   0.361848   0.437637  0.350299   \n",
      "2394   0.037086   0.221067   0.328477   0.302599   0.340397  0.381669   \n",
      "2395   0.005970   0.312534   0.420896   0.383540   0.334328  0.264658   \n",
      "2396   0.030457   0.261978   0.258883   0.353941   0.314721  0.342349   \n",
      "2397   0.009615   0.234859   0.221154   0.378178   0.432692  0.361997   \n",
      "2398   0.035971   0.149573   0.100719   0.352869   0.438849  0.485958   \n",
      "2399   0.020921   0.335622   0.368201   0.344206   0.380753  0.301288   \n",
      "2400   0.074627   0.359583   0.377399   0.349160   0.251599  0.231616   \n",
      "2401   0.024096   0.140426   0.144578   0.276596   0.445783  0.408511   \n",
      "2402   0.016807   0.269697   0.210084   0.190909   0.361345  0.496970   \n",
      "2403   0.120448   0.342612   0.347339   0.230193   0.252101  0.258030   \n",
      "2404   0.049336   0.217549   0.333966   0.292316   0.277040  0.334891   \n",
      "2405   0.079545   0.270127   0.261364   0.235169   0.314394  0.359110   \n",
      "2406   0.099099   0.329545   0.405405   0.359091   0.288288  0.227273   \n",
      "2407   0.044529   0.251071   0.278626   0.290917   0.319338  0.387746   \n",
      "2408   0.039062   0.256501   0.277344   0.300236   0.250000  0.358156   \n",
      "2409   0.032787   0.244792   0.245902   0.305556   0.256831  0.338542   \n",
      "2410   0.038813   0.275940   0.331050   0.366917   0.390411  0.284962   \n",
      "2411   0.018182   0.331061   0.335065   0.365909   0.387013  0.225000   \n",
      "2412   0.036775   0.336031   0.398868   0.418112   0.349364  0.200771   \n",
      "2413   0.036036   0.336678   0.396396   0.403567   0.363363  0.232999   \n",
      "2414   0.038339   0.314582   0.293930   0.399704   0.431310  0.247224   \n",
      "2415   0.098065   0.195064   0.357419   0.224490   0.242581  0.356431   \n",
      "2416   0.037162   0.214149   0.304054   0.314054   0.361486  0.407266   \n",
      "2417   0.032000   0.235233   0.240000   0.376166   0.512000  0.370984   \n",
      "2418   0.008929   0.218947   0.232143   0.317895   0.250000  0.381053   \n",
      "2419   0.040665   0.394595   0.426063   0.222258   0.229205  0.292210   \n",
      "2420   0.108911   0.208661   0.188119   0.265748   0.262376  0.291339   \n",
      "2421   0.058455   0.350634   0.346555   0.219674   0.210856  0.287870   \n",
      "2422   0.012632   0.352716   0.362105   0.266259   0.282105  0.302219   \n",
      "2423   0.085106   0.252648   0.271277   0.169440   0.223404  0.490166   \n",
      "2424   0.061321   0.202037   0.226415   0.151104   0.183962  0.482173   \n",
      "2425   0.020408   0.423197   0.443149   0.252038   0.265306  0.272727   \n",
      "2426   0.082927   0.302752   0.319512   0.227523   0.219512  0.277064   \n",
      "2427   0.085714   0.334073   0.303571   0.205327   0.225000  0.288568   \n",
      "2428   0.061162   0.293515   0.281346   0.213879   0.238532  0.391354   \n",
      "2429   0.060074   0.469829   0.543438   0.185798   0.160813  0.179063   \n",
      "2430   0.068750   0.345455   0.193750   0.131818   0.168750  0.468182   \n",
      "2431   0.120548   0.319885   0.320548   0.259846   0.261644  0.260807   \n",
      "2432   0.055394   0.156102   0.311953   0.301260   0.307580  0.481107   \n",
      "2433   0.072826   0.232398   0.207609   0.235159   0.229348  0.398067   \n",
      "2434   0.042553   0.313725   0.308511   0.360784   0.308511  0.168627   \n",
      "2435   0.175900   0.182169   0.217452   0.257044   0.207756  0.328445   \n",
      "2436   0.119367   0.233741   0.309379   0.236052   0.295981  0.327171   \n",
      "2437   0.052743   0.277624   0.318143   0.333565   0.333755  0.325930   \n",
      "2438   0.220930   0.210872   0.194352   0.235239   0.207641  0.383786   \n",
      "2439   0.104991   0.193788   0.212565   0.272402   0.245267  0.387301   \n",
      "2440   0.100000   0.255230   0.294118   0.407950   0.305882  0.269874   \n",
      "2441   0.020360   0.325342   0.354598   0.357021   0.365796  0.249905   \n",
      "2442   0.142094   0.250941   0.267094   0.283296   0.280983  0.316780   \n",
      "2443   0.078750   0.262394   0.313750   0.228843   0.240000  0.394592   \n",
      "2444   0.246046   0.229517   0.191564   0.204015   0.216169  0.254476   \n",
      "2445   0.187166   0.214559   0.192513   0.310345   0.256684  0.306513   \n",
      "2446   0.073345   0.279882   0.350626   0.295266   0.300537  0.334911   \n",
      "2447   0.011013   0.387500   0.420705   0.383929   0.389868  0.208929   \n",
      "2448   0.117417   0.280000   0.295499   0.259355   0.285714  0.319355   \n",
      "2449   0.175585   0.248540   0.290970   0.192083   0.133779  0.368592   \n",
      "2450   0.102981   0.375919   0.352304   0.255515   0.246612  0.217831   \n",
      "2451   0.184379   0.259925   0.311140   0.154200   0.185659  0.306310   \n",
      "2452   0.118712   0.326103   0.245473   0.195951   0.221328  0.311641   \n",
      "2453   0.070015   0.183912   0.312024   0.342902   0.220700  0.362461   \n",
      "2454   0.039334   0.320545   0.358548   0.350292   0.330812  0.256047   \n",
      "2455   0.009276   0.259478   0.337662   0.427376   0.356215  0.257509   \n",
      "2456   0.022436   0.590517   0.612179   0.150862   0.131410  0.210129   \n",
      "2457   0.024149   0.268272   0.317234   0.298268   0.316136  0.346008   \n",
      "2458   0.113402   0.282353   0.360825   0.274510   0.257732  0.301961   \n",
      "2459   0.133981   0.193485   0.277670   0.306189   0.283495  0.351140   \n",
      "2460   0.033537   0.317669   0.335366   0.319549   0.286585  0.307331   \n",
      "2461   0.065844   0.461538   0.460905   0.178994   0.176955  0.281065   \n",
      "2462   0.045086   0.423048   0.403066   0.203184   0.213706  0.311600   \n",
      "2463   0.017182   0.583643   0.477663   0.174721   0.268041  0.216853   \n",
      "2464   0.088235   0.269542   0.286765   0.194070   0.227941  0.380054   \n",
      "2465   0.040512   0.282963   0.379531   0.242963   0.319829  0.367407   \n",
      "2466   0.053333   0.196721   0.386667   0.426230   0.306667  0.292740   \n",
      "2467   0.029703   0.283154   0.247525   0.132616   0.158416  0.480287   \n",
      "2468   0.020803   0.373868   0.398852   0.318326   0.375179  0.253976   \n",
      "2469   0.017167   0.407942   0.433476   0.356498   0.369099  0.183213   \n",
      "2470   0.151653   0.187005   0.272520   0.281332   0.263398  0.407322   \n",
      "2471   0.017808   0.285057   0.278082   0.434483   0.446575  0.202874   \n",
      "2472   0.052239   0.228571   0.261194   0.257143   0.216418  0.421429   \n",
      "2473   0.036402   0.407649   0.437051   0.335995   0.332483  0.192793   \n",
      "2474   0.055485   0.371483   0.432535   0.318073   0.305170  0.215069   \n",
      "2475   0.093502   0.253854   0.369255   0.348266   0.272583  0.229287   \n",
      "2476   0.109202   0.225118   0.258896   0.272512   0.198773  0.324645   \n",
      "2477   0.042453   0.188119   0.221698   0.178218   0.174528  0.445545   \n",
      "2478   0.134796   0.178125   0.266458   0.286458   0.288401  0.401042   \n",
      "2479   0.053640   0.185880   0.309068   0.352214   0.268199  0.334264   \n",
      "2480   0.011725   0.379860   0.371859   0.340479   0.318258  0.239781   \n",
      "2481   0.028269   0.313019   0.296820   0.314866   0.337456  0.273315   \n",
      "2482   0.019231   0.357012   0.365385   0.310472   0.312500  0.267606   \n",
      "2483   0.025540   0.449956   0.473477   0.371125   0.373281  0.131089   \n",
      "2484   0.054830   0.443255   0.469974   0.331906   0.305483  0.145610   \n",
      "2485   0.036364   0.428755   0.436364   0.331194   0.333333  0.173299   \n",
      "2486   0.063087   0.204232   0.297987   0.367372   0.347651  0.356639   \n",
      "2487   0.018868   0.500000   0.490566   0.279683   0.347170  0.135884   \n",
      "2488   0.021858   0.401590   0.393443   0.284294   0.322404  0.250497   \n",
      "2489   0.036145   0.404040   0.277108   0.308081   0.277108  0.222222   \n",
      "2490   0.016722   0.512195   0.571906   0.318357   0.264214  0.129653   \n",
      "2491   0.026810   0.306167   0.339589   0.280923   0.301162  0.331771   \n",
      "2492   0.129338   0.345332   0.435331   0.231721   0.205047  0.277840   \n",
      "2493   0.103297   0.294366   0.336264   0.283803   0.281319  0.269014   \n",
      "2494   0.032946   0.266467   0.333333   0.265269   0.296512  0.313174   \n",
      "2495   0.086275   0.309537   0.375686   0.308110   0.279216  0.284123   \n",
      "2496   0.033333   0.335475   0.321569   0.361171   0.378431  0.244825   \n",
      "2497   0.143840   0.372518   0.492315   0.248947   0.215187  0.252918   \n",
      "2498   0.000000   0.375000   0.285714   0.308594   0.259740  0.226562   \n",
      "2499   0.088235   0.182432   0.205882   0.280405   0.375000  0.407095   \n",
      "2500   0.068862   0.204844   0.302395   0.245675   0.227545  0.421453   \n",
      "2501   0.042511   0.499811   0.444081   0.179864   0.242642  0.237557   \n",
      "2502   0.393913   0.225857   0.217391   0.089564   0.067826  0.297118   \n",
      "2503   0.024490   0.243688   0.259184   0.362239   0.348980  0.319429   \n",
      "2504   0.061798   0.215762   0.286517   0.251938   0.252809  0.374677   \n",
      "2505   0.069606   0.260057   0.336427   0.323513   0.343387  0.312181   \n",
      "2506   0.035714   0.162791   0.178571   0.267442   0.267857  0.395349   \n",
      "2507   0.044397   0.170717   0.224101   0.331106   0.325581  0.385176   \n",
      "2508   0.019608   0.203325   0.215686   0.260870   0.254902  0.390026   \n",
      "2509   0.019178   0.174718   0.156164   0.254428   0.317808  0.373591   \n",
      "2510   0.024390   0.263682   0.325203   0.278607   0.268293  0.417910   \n",
      "2511   0.101538   0.266022   0.292308   0.151149   0.163077  0.464329   \n",
      "2512   0.022923   0.154110   0.289398   0.302226   0.283668  0.404110   \n",
      "2513   0.113636   0.316315   0.371212   0.230855   0.208333  0.324084   \n",
      "2514   0.085433   0.296125   0.349398   0.172932   0.220153  0.436090   \n",
      "2515   0.070894   0.319404   0.404893   0.237292   0.262107  0.332600   \n",
      "2516   0.055556   0.263572   0.293981   0.248623   0.252315  0.354052   \n",
      "2517   0.020188   0.285903   0.374159   0.323348   0.351279  0.322907   \n",
      "2518   0.014085   0.342324   0.274648   0.286307   0.288732  0.226141   \n",
      "2519   0.054795   0.151961   0.232877   0.210784   0.178082  0.436275   \n",
      "2520   0.038462   0.206897   0.230769   0.255172   0.333333  0.441379   \n",
      "2521   0.027778   0.201690   0.314815   0.311510   0.282407  0.418163   \n",
      "2522   0.046875   0.302706   0.306641   0.292637   0.312500  0.329138   \n",
      "2523   0.060086   0.205882   0.218884   0.399733   0.364807  0.308824   \n",
      "2524   0.124803   0.222727   0.282780   0.184659   0.164297  0.361932   \n",
      "2525   0.052632   0.255030   0.308271   0.294769   0.318797  0.300805   \n",
      "2526   0.015355   0.223690   0.339731   0.371028   0.333973  0.373091   \n",
      "2527   0.050459   0.178049   0.211009   0.346341   0.302752  0.423171   \n",
      "2528   0.078947   0.142857   0.254386   0.245473   0.219298  0.430584   \n",
      "2529   0.050388   0.265527   0.329457   0.278128   0.290698  0.343834   \n",
      "2530   0.039841   0.230904   0.366534   0.444249   0.306773  0.233538   \n",
      "2531   0.000000   0.302491   0.289308   0.259786   0.314465  0.357651   \n",
      "2532   0.022642   0.176998   0.249057   0.347471   0.415094  0.371126   \n",
      "2533   0.012658   0.204225   0.198312   0.304577   0.451477  0.426937   \n",
      "2534   0.017857   0.240181   0.278571   0.380161   0.337500  0.280967   \n",
      "2535   0.146789   0.222595   0.302752   0.319911   0.226300  0.281879   \n",
      "2536   0.038922   0.166829   0.128743   0.267317   0.254491  0.449756   \n",
      "2537   0.051230   0.219737   0.170082   0.163158   0.159836  0.434211   \n",
      "2538   0.021305   0.158037   0.195739   0.354653   0.358189  0.382403   \n",
      "2539   0.028571   0.127098   0.209524   0.407674   0.304762  0.374101   \n",
      "2540   0.000000   0.092486   0.193548   0.231214   0.193548  0.531792   \n",
      "2541   0.019737   0.262357   0.309211   0.325095   0.296053  0.399240   \n",
      "2542   0.052958   0.298647   0.313931   0.277293   0.277195  0.339850   \n",
      "2543   0.060041   0.338944   0.417184   0.297737   0.296066  0.255949   \n",
      "2544   0.044444   0.201835   0.133333   0.330275   0.288889  0.376147   \n",
      "2545   0.165094   0.192029   0.297170   0.168478   0.174528  0.349638   \n",
      "2546   0.048930   0.289868   0.342508   0.349780   0.253823  0.262555   \n",
      "2547   0.032423   0.266577   0.266212   0.278634   0.226962  0.334896   \n",
      "2548   0.042328   0.234012   0.195767   0.346657   0.375661  0.339390   \n",
      "2549   0.050336   0.212418   0.218121   0.214052   0.255034  0.423203   \n",
      "2550   0.047619   0.282651   0.246032   0.401559   0.333333  0.267057   \n",
      "2551   0.018519   0.223022   0.407407   0.388489   0.166667  0.280576   \n",
      "2552   0.069620   0.233129   0.259494   0.300613   0.303797  0.417178   \n",
      "2553   0.030905   0.286526   0.364238   0.376623   0.304636  0.293019   \n",
      "2554   0.010714   0.258065   0.407143   0.420995   0.371429  0.287042   \n",
      "2555   0.050633   0.178846   0.208861   0.373077   0.310127  0.363462   \n",
      "2556   0.074074   0.245399   0.203704   0.335378   0.222222  0.398773   \n",
      "2557   0.056671   0.230867   0.312869   0.357143   0.306966  0.298895   \n",
      "2558   0.019157   0.335753   0.398467   0.299456   0.360153  0.283122   \n",
      "2559   0.028112   0.267484   0.345382   0.263879   0.230924  0.402307   \n",
      "2560   0.044776   0.277873   0.447761   0.332762   0.208955  0.320755   \n",
      "2561   0.072222   0.253049   0.288889   0.295732   0.266667  0.376524   \n",
      "2562   0.026882   0.232857   0.274194   0.272857   0.295699  0.385714   \n",
      "2563   0.031250   0.188948   0.253906   0.353387   0.355469  0.418895   \n",
      "2564   0.029661   0.208092   0.305085   0.310212   0.258475  0.431599   \n",
      "2565   0.028497   0.187559   0.287565   0.335533   0.326425  0.391140   \n",
      "2566   0.036352   0.361811   0.434997   0.342096   0.385705  0.228551   \n",
      "2567   0.065359   0.168760   0.215686   0.296703   0.261438  0.490581   \n",
      "2568   0.041237   0.276190   0.195876   0.290476   0.257732  0.285714   \n",
      "2569   0.021127   0.229327   0.253521   0.340684   0.387324  0.382580   \n",
      "2570   0.109023   0.192256   0.180451   0.184246   0.154135  0.472630   \n",
      "2571   0.062016   0.173664   0.162791   0.293893   0.306202  0.349237   \n",
      "2572   0.077922   0.138177   0.259740   0.388889   0.311688  0.336182   \n",
      "2573   0.109264   0.266193   0.342043   0.256433   0.161520  0.341615   \n",
      "2574   0.155756   0.364212   0.349887   0.209818   0.119639  0.324624   \n",
      "2575   0.115894   0.273543   0.400662   0.275785   0.175497  0.320628   \n",
      "2576   0.128492   0.119048   0.139665   0.216117   0.131285  0.454212   \n",
      "2577   0.027397   0.194638   0.243836   0.366756   0.443836  0.389276   \n",
      "2578   0.058091   0.213320   0.269710   0.394788   0.336100  0.344595   \n",
      "2579   0.016807   0.317439   0.294118   0.348774   0.327731  0.258856   \n",
      "2580   0.026549   0.269802   0.225664   0.344059   0.371681  0.279703   \n",
      "2581   0.036458   0.169654   0.223958   0.292712   0.302083  0.451613   \n",
      "2582   0.038384   0.207306   0.294949   0.349472   0.305051  0.341989   \n",
      "2583   0.019190   0.230471   0.266525   0.407756   0.409382  0.319668   \n",
      "2584   0.021505   0.330882   0.333333   0.247549   0.279570  0.323529   \n",
      "2585   0.020236   0.246114   0.273187   0.318653   0.254637  0.335924   \n",
      "2586   0.069767   0.234043   0.267442   0.221631   0.308140  0.471631   \n",
      "2587   0.039295   0.216235   0.313008   0.313990   0.280488  0.412781   \n",
      "2588   0.054054   0.221910   0.236486   0.160112   0.195946  0.464888   \n",
      "2589   0.043084   0.277975   0.281179   0.327636   0.333333  0.304418   \n",
      "2590   0.085714   0.201613   0.180952   0.185484   0.215873  0.468894   \n",
      "2591   0.044702   0.207727   0.246689   0.268941   0.273179  0.377321   \n",
      "2592   0.189802   0.191609   0.220255   0.243213   0.291785  0.299978   \n",
      "2593   0.053030   0.330594   0.323232   0.272146   0.280303  0.287671   \n",
      "2594   0.019417   0.152975   0.233010   0.334278   0.281553  0.453258   \n",
      "2595   0.064745   0.687187   0.611531   0.174374   0.190454  0.085898   \n",
      "2596   0.233096   0.206177   0.282918   0.170074   0.224199  0.290126   \n",
      "2597   0.142687   0.308559   0.373365   0.252252   0.253270  0.221847   \n",
      "2598   0.219436   0.218227   0.272727   0.183110   0.100313  0.419732   \n",
      "2599   0.200000   0.247751   0.301961   0.292723   0.231373  0.224857   \n",
      "2600   0.238628   0.224064   0.260254   0.253454   0.215511  0.291384   \n",
      "2601   0.158000   0.286244   0.324000   0.296976   0.267333  0.259902   \n",
      "2602   0.351159   0.213529   0.254614   0.152078   0.141505  0.303015   \n",
      "2603   0.031637   0.209165   0.220083   0.346268   0.381018  0.349593   \n",
      "2604   0.059459   0.218007   0.336937   0.320841   0.295495  0.320841   \n",
      "2605   0.200000   0.194667   0.311111   0.332000   0.177778  0.375333   \n",
      "2606   0.063628   0.321222   0.355176   0.303881   0.308642  0.309249   \n",
      "2607   0.032370   0.404696   0.423121   0.255525   0.261272  0.233886   \n",
      "2608   0.285521   0.340274   0.351827   0.246569   0.204330  0.155230   \n",
      "2609   0.092697   0.293872   0.330758   0.298056   0.269663  0.259168   \n",
      "2610   0.055179   0.156146   0.218780   0.308140   0.262343  0.363787   \n",
      "2611   0.069705   0.287938   0.323056   0.397752   0.371314  0.236489   \n",
      "2612   0.118644   0.327869   0.330508   0.340164   0.254237  0.172131   \n",
      "2613   0.306452   0.224254   0.220430   0.230957   0.184588  0.269348   \n",
      "2614   0.272358   0.230832   0.258130   0.184339   0.217480  0.278140   \n",
      "2615   0.215760   0.195727   0.240150   0.236721   0.219512  0.342956   \n",
      "2616   0.329562   0.295455   0.275813   0.185144   0.148515  0.176275   \n",
      "2617   0.211340   0.301861   0.338918   0.239673   0.224227  0.216977   \n",
      "2618   0.032787   0.169903   0.229508   0.250000   0.311475  0.453883   \n",
      "2619   0.085570   0.301133   0.296980   0.318426   0.239933  0.325581   \n",
      "2620   0.097902   0.325359   0.307692   0.145933   0.048951  0.375598   \n",
      "2621   0.006803   0.257143   0.224490   0.157143   0.244898  0.426786   \n",
      "2622   0.087269   0.354953   0.313142   0.272323   0.247433  0.260329   \n",
      "2623   0.020270   0.430328   0.418919   0.194672   0.175676  0.305328   \n",
      "2624   0.110016   0.274087   0.295567   0.165769   0.157635  0.396768   \n",
      "2625   0.183168   0.258418   0.316832   0.134680   0.111386  0.330808   \n",
      "2626   0.059448   0.250755   0.233546   0.185045   0.218684  0.456193   \n",
      "2627   0.049815   0.269637   0.252768   0.223565   0.271218  0.363293   \n",
      "2628   0.044185   0.193958   0.223522   0.281571   0.311241  0.427492   \n",
      "2629   0.157576   0.197926   0.257576   0.286522   0.248485  0.328935   \n",
      "2630   0.085919   0.278434   0.310263   0.295421   0.284010  0.302806   \n",
      "2631   0.107914   0.278586   0.316547   0.214137   0.215827  0.261954   \n",
      "2632   0.053801   0.241872   0.305263   0.367962   0.319298  0.316151   \n",
      "2633   0.230769   0.194667   0.196581   0.301333   0.393162  0.216000   \n",
      "2634   0.122857   0.288601   0.304286   0.118653   0.165714  0.362694   \n",
      "2635   0.178378   0.267978   0.302703   0.222524   0.235135  0.394166   \n",
      "2636   0.018349   0.421255   0.422018   0.323944   0.310398  0.190781   \n",
      "2637   0.015385   0.175331   0.128205   0.254842   0.358974  0.355759   \n",
      "2638   0.220126   0.169713   0.163522   0.287206   0.207547  0.378590   \n",
      "2639   0.138211   0.206989   0.146341   0.182796   0.227642  0.422043   \n",
      "2640   0.023179   0.151292   0.145695   0.234932   0.377483  0.396064   \n",
      "2641   0.045520   0.390922   0.401012   0.295736   0.322254  0.231362   \n",
      "2642   0.001431   0.313008   0.311874   0.349593   0.339056  0.289126   \n",
      "2643   0.043478   0.318302   0.315789   0.371353   0.391304  0.248453   \n",
      "2644   0.033898   0.234091   0.310734   0.290909   0.220339  0.315909   \n",
      "2645   0.018868   0.522959   0.427673   0.321429   0.402516  0.127551   \n",
      "2646   0.039773   0.398619   0.440341   0.373598   0.360795  0.150992   \n",
      "2647   0.028736   0.185185   0.120690   0.374860   0.339080  0.373737   \n",
      "2648   0.080595   0.225833   0.255425   0.274167   0.267824  0.326250   \n",
      "2649   0.018443   0.161103   0.182377   0.331398   0.346311  0.452346   \n",
      "2650   0.044055   0.328321   0.383479   0.363933   0.373467  0.250569   \n",
      "2651   0.215643   0.257175   0.280702   0.223927   0.198099  0.306621   \n",
      "2652   0.073654   0.248623   0.276204   0.268530   0.211048  0.389242   \n",
      "2653   0.076512   0.232962   0.284698   0.242762   0.213523  0.424944   \n",
      "2654   0.050239   0.223193   0.236842   0.294678   0.258373  0.341541   \n",
      "2655   0.134483   0.289969   0.258621   0.257053   0.251724  0.285266   \n",
      "2656   0.035088   0.190948   0.204678   0.468175   0.368421  0.315417   \n",
      "2657   0.011070   0.334893   0.448954   0.342690   0.295203  0.273294   \n",
      "2658   0.056410   0.243891   0.338462   0.328262   0.287179  0.385431   \n",
      "2659   0.010381   0.301587   0.245675   0.392290   0.484429  0.264172   \n",
      "2660   0.005348   0.301667   0.294118   0.358333   0.385027  0.161667   \n",
      "2661   0.030769   0.143678   0.153846   0.482759   0.338462  0.298851   \n",
      "2662   0.010130   0.245906   0.296671   0.395322   0.392185  0.310234   \n",
      "2663   0.027314   0.296252   0.317906   0.411694   0.376328  0.229985   \n",
      "2664   0.039510   0.255631   0.294278   0.313063   0.333787  0.367117   \n",
      "2665   0.037936   0.174854   0.236722   0.318612   0.297420  0.408292   \n",
      "2666   0.033860   0.213242   0.225734   0.347377   0.297968  0.368014   \n",
      "2667   0.091659   0.223910   0.269478   0.301777   0.263978  0.328918   \n",
      "2668   0.074419   0.198639   0.220930   0.329705   0.309302  0.410431   \n",
      "2669   0.056620   0.435212   0.460801   0.211705   0.227352  0.267341   \n",
      "2670   0.035826   0.294496   0.378505   0.371780   0.359813  0.256440   \n",
      "2671   0.109354   0.526429   0.509881   0.152987   0.148880  0.167168   \n",
      "2672   0.106540   0.262778   0.343354   0.196858   0.210970  0.365180   \n",
      "2673   0.070896   0.333549   0.302239   0.209438   0.218284  0.342599   \n",
      "2674   0.061834   0.273859   0.277186   0.229046   0.257996  0.331120   \n",
      "2675   0.037549   0.289387   0.343874   0.313335   0.317194  0.323418   \n",
      "2676   0.196608   0.383844   0.341282   0.212647   0.221516  0.236746   \n",
      "2677   0.073955   0.243304   0.299035   0.197545   0.196141  0.430804   \n",
      "2678   0.349254   0.211116   0.247761   0.159136   0.176119  0.267893   \n",
      "2679   0.029601   0.244387   0.365508   0.313903   0.314028  0.354491   \n",
      "2680   0.050296   0.362579   0.360947   0.316068   0.357988  0.233615   \n",
      "2681   0.024540   0.215753   0.202454   0.273973   0.331288  0.407534   \n",
      "2682   0.000000   0.213592   0.305085   0.393204   0.237288  0.281553   \n",
      "2683   0.071865   0.277752   0.310398   0.232234   0.189602  0.407339   \n",
      "2684   0.091413   0.200850   0.246537   0.218916   0.174515  0.407014   \n",
      "2685   0.035714   0.148760   0.178571   0.351240   0.357143  0.392562   \n",
      "2686   0.039437   0.212474   0.307042   0.313936   0.264789  0.424351   \n",
      "2687   0.209177   0.270950   0.248313   0.232309   0.233468  0.304935   \n",
      "2688   0.040921   0.345141   0.457801   0.185286   0.145780  0.379655   \n",
      "2689   0.039216   0.373653   0.349020   0.216766   0.274510  0.330539   \n",
      "2690   0.024390   0.272454   0.311334   0.422980   0.439024  0.227797   \n",
      "2691   0.043676   0.303745   0.363057   0.261575   0.234759  0.350929   \n",
      "2692   0.015571   0.364382   0.386678   0.339192   0.358131  0.231400   \n",
      "2693   0.041237   0.157729   0.144330   0.257098   0.252577  0.460568   \n",
      "2694   0.121864   0.323714   0.222222   0.207026   0.236559  0.314931   \n",
      "2695   0.138889   0.192661   0.222222   0.201835   0.138889  0.330275   \n",
      "2696   0.059685   0.298457   0.341216   0.302817   0.307432  0.320926   \n",
      "2697   0.036810   0.353846   0.282209   0.146154   0.147239  0.438462   \n",
      "2698   0.064611   0.304581   0.346549   0.281189   0.246696  0.274854   \n",
      "2699   0.002331   0.174702   0.261072   0.350441   0.377622  0.388284   \n",
      "2700   0.012920   0.353517   0.467700   0.283792   0.279070  0.279511   \n",
      "2701   0.021912   0.141466   0.249004   0.458190   0.426295  0.337915   \n",
      "2702   0.073770   0.338755   0.280738   0.198727   0.237705  0.333805   \n",
      "2703   0.079447   0.401010   0.379965   0.215367   0.243523  0.270331   \n",
      "2704   0.062606   0.283484   0.302876   0.280463   0.274112  0.350957   \n",
      "2705   0.021615   0.243361   0.349261   0.328827   0.346985  0.377837   \n",
      "2706   0.028409   0.364377   0.410985   0.349825   0.357955  0.250873   \n",
      "2707   0.015773   0.343365   0.353312   0.285910   0.277603  0.299590   \n",
      "2708   0.048426   0.250558   0.300242   0.335316   0.295400  0.258736   \n",
      "2709   0.057143   0.261062   0.271429   0.225664   0.257143  0.446903   \n",
      "2710   0.054054   0.205966   0.243243   0.281250   0.194595  0.369318   \n",
      "2711   0.022901   0.239897   0.282443   0.337919   0.374046  0.283749   \n",
      "2712   0.018182   0.339547   0.393939   0.205060   0.187879  0.332889   \n",
      "2713   0.067073   0.274085   0.207317   0.261389   0.265244  0.273338   \n",
      "2714   0.003106   0.175402   0.273292   0.380154   0.369565  0.387142   \n",
      "2715   0.065282   0.278837   0.284866   0.237965   0.284866  0.387829   \n",
      "2716   0.068966   0.241993   0.321839   0.234875   0.172414  0.434164   \n",
      "2717   0.011765   0.142487   0.352941   0.313472   0.211765  0.531088   \n",
      "2718   0.046875   0.100817   0.250000   0.275204   0.250000  0.550409   \n",
      "2719   0.040892   0.237890   0.241636   0.434876   0.379182  0.291712   \n",
      "2720   0.088889   0.607858   0.448889   0.127502   0.171111  0.180875   \n",
      "2721   0.043630   0.508539   0.452007   0.303605   0.349040  0.117647   \n",
      "2722   0.006211   0.301273   0.298137   0.325318   0.322981  0.343706   \n",
      "2723   0.013333   0.317433   0.391111   0.111015   0.226667  0.460538   \n",
      "2724   0.043988   0.245327   0.322581   0.280374   0.334311  0.245327   \n",
      "2725   0.021810   0.615633   0.603053   0.226963   0.259542  0.125134   \n",
      "2726   0.062162   0.243674   0.191892   0.201500   0.213514  0.300843   \n",
      "2727   0.050459   0.274094   0.302752   0.265892   0.305810  0.350649   \n",
      "2728   0.007663   0.798113   0.714559   0.125472   0.191571  0.060692   \n",
      "2729   0.000000   0.793505   0.568862   0.137386   0.305389  0.061615   \n",
      "2730   0.017621   0.819275   0.765419   0.096929   0.127753  0.067333   \n",
      "2731   0.293084   0.199080   0.244898   0.245952   0.212585  0.254986   \n",
      "2732   0.040404   0.122166   0.335859   0.318640   0.267677  0.477330   \n",
      "2733   0.031936   0.203780   0.299401   0.311422   0.257485  0.364010   \n",
      "2734   0.025641   0.246964   0.250000   0.384615   0.250000  0.242915   \n",
      "2735   0.096481   0.316406   0.347333   0.246449   0.241771  0.300071   \n",
      "2736   0.063404   0.306517   0.373749   0.336049   0.303671  0.259674   \n",
      "2737   0.000000   0.242188   0.266667   0.378906   0.466667  0.320312   \n",
      "2738   0.021014   0.317757   0.325093   0.368640   0.388133  0.273451   \n",
      "2739   0.054945   0.429616   0.447253   0.271298   0.340659  0.193419   \n",
      "2740   0.089416   0.284281   0.281022   0.305463   0.286496  0.289855   \n",
      "2741   0.105263   0.308370   0.333333   0.334802   0.280702  0.233480   \n",
      "2742   0.034639   0.472764   0.492470   0.286047   0.286145  0.195456   \n",
      "2743   0.078000   0.454677   0.448000   0.253082   0.244000  0.211022   \n",
      "2744   0.091879   0.436374   0.466621   0.253461   0.241053  0.225394   \n",
      "2745   0.080972   0.261111   0.307692   0.286111   0.307692  0.375000   \n",
      "2746   0.020833   0.204852   0.166667   0.308625   0.312500  0.443396   \n",
      "2747   0.028958   0.179688   0.189189   0.353795   0.359073  0.369978   \n",
      "2748   0.174359   0.298884   0.314530   0.195537   0.206838  0.328244   \n",
      "2749   0.149448   0.264697   0.334002   0.254851   0.201605  0.387200   \n",
      "2750   0.132743   0.231638   0.203540   0.206215   0.283186  0.392655   \n",
      "2751   0.126667   0.305806   0.270000   0.234839   0.300000  0.269677   \n",
      "2752   0.267310   0.227525   0.265607   0.111175   0.095346  0.345793   \n",
      "\n",
      "      주말장년고객비율  주중노인고객비율  주말노인고객비율  군집      PCA1      PCA2  \n",
      "0     0.142019  0.017782  0.011737   0 -3.501513 -0.169895  \n",
      "1     0.291310  0.037661  0.048960   1  2.160521  3.021214  \n",
      "2     0.308480  0.040841  0.018782   1  0.500962  2.590659  \n",
      "3     0.331395  0.032904  0.062016   1  0.471294  0.857450  \n",
      "4     0.265169  0.023679  0.031461   1  2.328693  6.584697  \n",
      "5     0.281163  0.031210  0.036011   1  0.592878  3.079777  \n",
      "6     0.339985  0.052797  0.048350   1  1.904773  3.072337  \n",
      "7     0.232779  0.043280  0.064133   1  0.819849  1.563440  \n",
      "8     0.172932  0.073947  0.077694   1  0.216262  2.724155  \n",
      "9     0.304553  0.063934  0.056515   1  1.106534  3.343583  \n",
      "10    0.376623  0.128524  0.067532   3  1.831793  1.466709  \n",
      "11    0.314103  0.057600  0.051282   1  1.018115  3.646466  \n",
      "12    0.227181  0.065379  0.093306   0 -1.317137 -0.237138  \n",
      "13    0.282609  0.045350  0.051630   1  1.881010  5.118625  \n",
      "14    0.346795  0.052204  0.077261   1  1.163772  0.397939  \n",
      "15    0.259398  0.075353  0.067669   1  1.276418  1.588808  \n",
      "16    0.233847  0.042023  0.027511   1  0.680096  6.706218  \n",
      "17    0.412908  0.047242  0.031228   1  1.669333  3.071903  \n",
      "18    0.283069  0.006873  0.018519   1 -1.065535  0.943764  \n",
      "19    0.190248  0.054998  0.038369   0 -2.699922  0.577418  \n",
      "20    0.174603  0.039039  0.063492   0 -0.635365  0.166306  \n",
      "21    0.437500  0.159664  0.104167   3  2.787519  0.766179  \n",
      "22    0.431193  0.064171  0.110092   3  3.923736  2.203146  \n",
      "23    0.235119  0.044847  0.068452   2 -0.896831 -1.351338  \n",
      "24    0.322581  0.055556  0.032258   2  1.723175 -0.549830  \n",
      "25    0.254054  0.082515  0.081081   1  1.026961  0.935727  \n",
      "26    0.242588  0.045752  0.021563   2 -1.011847 -0.593087  \n",
      "27    0.207885  0.033091  0.035842   2 -1.754361 -2.272469  \n",
      "28    0.490566  0.055866  0.056604   1  2.610044  1.898732  \n",
      "29    0.221884  0.171521  0.151976   3  1.668092  2.253559  \n",
      "30    0.202247  0.099083  0.084270   0 -0.777069  0.867729  \n",
      "31    0.224066  0.013357  0.033195   2 -1.206868 -1.254113  \n",
      "32    0.225086  0.068053  0.068729   0 -1.538542  0.229781  \n",
      "33    0.272727  0.067272  0.040909   3  0.040103  0.730875  \n",
      "34    0.186047  0.085399  0.058140   0 -1.377042 -0.435235  \n",
      "35    0.287081  0.105263  0.081340   0 -0.617240  0.317734  \n",
      "36    0.292181  0.031560  0.084362   2  0.856717 -1.772780  \n",
      "37    0.314031  0.023574  0.020045   0 -0.833004 -0.667752  \n",
      "38    0.344398  0.078298  0.116183   2  1.797647 -0.322474  \n",
      "39    0.243781  0.059679  0.052239   2 -0.100500 -0.301903  \n",
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      "1894  0.167431  0.024336  0.009174   0 -2.613601 -0.513678  \n",
      "1895  0.380952  0.078014  0.031746   2  1.442349 -2.732997  \n",
      "1896  0.255230  0.034335  0.058577   0 -1.014839 -0.363001  \n",
      "1897  0.370056  0.020710  0.031073   1  1.061327  3.046582  \n",
      "1898  0.110976  0.011841  0.002439   0 -3.927459 -1.555039  \n",
      "1899  0.181020  0.023643  0.011519   0 -4.254117  3.331597  \n",
      "1900  0.275362  0.046591  0.075362   2  0.692394 -2.908048  \n",
      "1901  0.160825  0.045045  0.045361   0 -3.043482 -0.231071  \n",
      "1902  0.296703  0.074707  0.036630   1  2.325964  0.837040  \n",
      "1903  0.320611  0.031034  0.022901   3  0.976553  0.743045  \n",
      "1904  0.354430  0.141026  0.025316   3  1.747434 -0.850611  \n",
      "1905  0.131250  0.016605  0.056250   0 -2.444237 -2.128940  \n",
      "1906  0.600000  0.021113  0.000000   2  4.905199 -3.590527  \n",
      "1907  0.289520  0.047522  0.049734   2  0.445592 -0.687464  \n",
      "1908  0.266160  0.039801  0.038023   0 -0.780396  0.298659  \n",
      "1909  0.341362  0.048624  0.043189   2  0.802206 -1.223334  \n",
      "1910  0.281375  0.115185  0.087130   3  0.427148  0.442291  \n",
      "1911  0.394813  0.047478  0.046110   3  2.262591 -0.226419  \n",
      "1912  0.218539  0.018369  0.013532   2 -1.162904 -3.568204  \n",
      "1913  0.217213  0.022850  0.010246   2 -0.882276 -3.763686  \n",
      "1914  0.264407  0.032684  0.067797   2  0.276409 -2.897006  \n",
      "1915  0.350649  0.036403  0.019481   2  0.789029  0.006747  \n",
      "1916  0.325397  0.018815  0.021825   2  0.840433 -1.927939  \n",
      "1917  0.345622  0.051948  0.064516   3  0.773667 -0.988408  \n",
      "1918  0.309711  0.043891  0.034121   2  0.521798 -3.212639  \n",
      "1919  0.240059  0.056489  0.042710   0 -0.848081 -1.379796  \n",
      "1920  0.253444  0.038726  0.024793   0 -1.311242 -1.025930  \n",
      "1921  0.236434  0.115142  0.127907   3  1.487731  0.988549  \n",
      "1922  0.300000  0.078253  0.111905   2  0.483378 -1.370676  \n",
      "1923  0.396226  0.061885  0.054717   3  2.682874 -0.281833  \n",
      "1924  0.192761  0.051636  0.038721   0 -2.376877 -1.323465  \n",
      "1925  0.263966  0.066939  0.061453   1 -0.196545  2.019100  \n",
      "1926  0.294118  0.059165  0.043137   3 -1.299093 -0.072270  \n",
      "1927  0.329876  0.067389  0.045643   1  0.921901  0.862289  \n",
      "1928  0.454545  0.074380  0.075758   2  1.646872 -1.357604  \n",
      "1929  0.302991  0.050938  0.065020   1  1.596757  2.928632  \n",
      "1930  0.271326  0.051867  0.048304   1 -0.114651  1.118745  \n",
      "1931  0.228125  0.047535  0.015625   2  0.381938 -3.479408  \n",
      "1932  0.319149  0.088115  0.099291   3  1.468570  0.442902  \n",
      "1933  0.223990  0.034085  0.023256   0 -2.446931  1.028873  \n",
      "1934  0.489583  0.166181  0.135417   3  4.569495 -0.317643  \n",
      "1935  0.205603  0.031315  0.039411   0 -2.918596 -0.609886  \n",
      "1936  0.362993  0.073047  0.072801   3  0.286716  0.231942  \n",
      "1937  0.372263  0.040268  0.051095   3  0.891896 -1.665224  \n",
      "1938  0.262626  0.035714  0.020202   2  0.370824 -0.068848  \n",
      "1939  0.345382  0.096096  0.090361   3  1.615709  0.132380  \n",
      "1940  0.193772  0.041102  0.038062   0 -2.141621 -0.820305  \n",
      "1941  0.183529  0.022672  0.014118   0 -2.953737  0.252973  \n",
      "1942  0.282524  0.035010  0.038835   1  0.810987  2.289186  \n",
      "1943  0.171756  0.024036  0.022901   0 -2.254544 -0.985979  \n",
      "1944  0.338983  0.202944  0.223164   3  4.171674  1.196692  \n",
      "1945  0.175503  0.016667  0.023766   0 -2.165206 -0.912290  \n",
      "1946  0.090909  0.017804  0.000000   0 -2.930232 -0.207300  \n",
      "1947  0.201269  0.043536  0.031732   0 -2.450407  2.368095  \n",
      "1948  0.270102  0.031952  0.031097   0 -1.698942 -0.297887  \n",
      "1949  0.336000  0.137931  0.160000   3  3.791242 -0.575870  \n",
      "1950  0.229630  0.077128  0.133333   2  0.305578 -1.168533  \n",
      "1951  0.234694  0.082822  0.020408   2 -0.422551 -1.249966  \n",
      "1952  0.264901  0.074194  0.039735   2  0.438825 -1.776614  \n",
      "1953  0.252617  0.057757  0.036288   1 -0.240300  1.674476  \n",
      "1954  0.326996  0.049724  0.068441   1  2.461801  3.171336  \n",
      "1955  0.273743  0.101749  0.033520   3 -0.451135 -0.839143  \n",
      "1956  0.306122  0.052053  0.035714   2  0.462589 -2.655385  \n",
      "1957  0.294852  0.030824  0.018721   0 -0.926857 -0.436188  \n",
      "1958  0.272727  0.053452  0.077922   3 -0.108413 -0.813276  \n",
      "1959  0.164384  0.035477  0.013699   2 -1.647741 -3.467127  \n",
      "1960  0.307764  0.064682  0.038354   0 -0.286467  0.773871  \n",
      "1961  0.344762  0.041394  0.032381   2  0.039554 -0.341204  \n",
      "1962  0.282486  0.037184  0.079096   2  1.034848 -1.972720  \n",
      "1963  0.257426  0.121413  0.110561   3  1.377727  0.601885  \n",
      "1964  0.243558  0.051564  0.045719   1 -0.903550  2.068274  \n",
      "1965  0.145511  0.023579  0.024768   0 -2.839061 -1.905031  \n",
      "1966  0.119593  0.028548  0.020356   0 -3.894271 -0.180868  \n",
      "1967  0.302381  0.048031  0.066667   3  0.360746  0.954189  \n",
      "1968  0.330789  0.073123  0.066158   1  1.764537  3.155733  \n",
      "1969  0.111111  0.057158  0.031746   2  0.142129 -0.346629  \n",
      "1970  0.204620  0.039931  0.021452   0 -2.398697 -0.314340  \n",
      "1971  0.268212  0.065772  0.079470   1  1.386917  2.867984  \n",
      "1972  0.230769  0.049524  0.029586   2  0.123621 -0.343345  \n",
      "1973  0.261628  0.016016  0.011628   2 -1.267993 -5.724924  \n",
      "1974  0.230117  0.029062  0.029692   1  0.309370  0.896614  \n",
      "1975  0.210407  0.090969  0.097285   1  0.753834  2.101422  \n",
      "1976  0.343220  0.027858  0.023305   2  0.113813 -0.642726  \n",
      "1977  0.215278  0.027088  0.025463   2 -0.948289 -1.438813  \n",
      "1978  0.344828  0.077075  0.088670   3  1.228186  1.225075  \n",
      "1979  0.151316  0.121065  0.144737   1  1.473521  1.840039  \n",
      "1980  0.275204  0.043704  0.038147   2 -0.611633 -1.391774  \n",
      "1981  0.184659  0.027550  0.017045   2 -2.434408 -2.035488  \n",
      "1982  0.405063  0.023987  0.044304   2 -1.036426 -3.379530  \n",
      "1983  0.214612  0.026588  0.027397   2 -1.259810 -1.640868  \n",
      "1984  0.371369  0.060199  0.060166   2  1.749276 -1.889965  \n",
      "1985  0.102941  0.009865  0.012255   0 -4.634634  0.750237  \n",
      "1986  0.238806  0.067835  0.023454   0 -1.869566  0.216792  \n",
      "1987  0.176700  0.026852  0.024686   0 -3.296553 -0.634525  \n",
      "1988  0.250000  0.083636  0.054348   3 -0.185542 -0.752812  \n",
      "1989  0.290909  0.052083  0.018182   2  1.014209 -0.884777  \n",
      "1990  0.243243  0.040493  0.066066   2 -1.461899 -2.131516  \n",
      "1991  0.291429  0.070081  0.051429   1  0.720971  1.767472  \n",
      "1992  0.236897  0.057014  0.039832   0 -0.891693  0.377206  \n",
      "1993  0.203883  0.032441  0.016990   0 -2.265434 -0.351301  \n",
      "1994  0.408824  0.057541  0.076471   1  3.451667  2.062110  \n",
      "1995  0.302048  0.029038  0.018203   1  0.289002  2.582387  \n",
      "1996  0.255319  0.029316  0.053191   0 -1.374089  1.312518  \n",
      "1997  0.184953  0.045567  0.053292   0 -2.568048  0.941435  \n",
      "1998  0.226351  0.068415  0.060811   0 -0.625010 -0.031928  \n",
      "1999  0.270270  0.038095  0.031185   0 -1.109505 -0.661961  \n",
      "2000  0.365385  0.054348  0.028846   2  1.923288 -2.609075  \n",
      "2001  0.194915  0.033645  0.076271   0 -1.683040  2.937612  \n",
      "2002  0.545455  0.035714  0.000000   2  3.615745 -2.993111  \n",
      "2003  0.333333  0.000000  0.000000   2  1.857407 -3.291614  \n",
      "2004  0.321429  0.009346  0.047619   1  1.030787  1.588340  \n",
      "2005  0.274286  0.035256  0.028571   2  0.775182 -2.236154  \n",
      "2006  0.223164  0.019861  0.008475   1  0.453511  6.225917  \n",
      "2007  0.263873  0.042925  0.033975   3  0.155583 -0.915280  \n",
      "2008  0.311828  0.062857  0.032258   2  0.059575 -1.835957  \n",
      "2009  0.230126  0.034436  0.033473   0 -1.551767 -1.319903  \n",
      "2010  0.271001  0.048720  0.038714   1 -0.494305  2.257016  \n",
      "2011  0.406593  0.060241  0.065934   3  2.331339 -1.451805  \n",
      "2012  0.155488  0.025234  0.027439   0 -3.234787  1.034632  \n",
      "2013  0.300448  0.039356  0.053812   0 -0.150948  0.688834  \n",
      "2014  0.248201  0.026589  0.026978   1 -0.496745  1.671026  \n",
      "2015  0.237687  0.103851  0.061028   1  1.349131  3.194781  \n",
      "2016  0.233983  0.079533  0.083565   2  0.274081 -0.089466  \n",
      "2017  0.243119  0.027579  0.036697   1  3.042171  5.886787  \n",
      "2018  0.203333  0.026590  0.030000   0 -1.550005 -1.154219  \n",
      "2019  0.218914  0.049159  0.024518   0 -1.315837 -0.088287  \n",
      "2020  0.300000  0.062542  0.053333   0 -0.535753  1.243158  \n",
      "2021  0.355263  0.031707  0.032895   3  0.168478  0.450491  \n",
      "2022  0.204762  0.012111  0.009524   1 -1.340851  3.327742  \n",
      "2023  0.358804  0.056576  0.036545   3  0.526540  0.167078  \n",
      "2024  0.360000  0.065731  0.061333   1  1.616269  0.583770  \n",
      "2025  0.365672  0.127148  0.082090   3  3.750156  0.438106  \n",
      "2026  0.262948  0.099401  0.119522   3  0.536600 -0.674857  \n",
      "2027  0.218333  0.056522  0.028333   1  0.810494  2.468931  \n",
      "2028  0.500000  0.032258  0.000000   2  4.475975 -0.807202  \n",
      "2029  0.413793  0.024390  0.068966   2  1.875998 -1.541975  \n",
      "2030  0.231362  0.042689  0.038560   2 -0.048148 -0.977447  \n",
      "2031  0.366197  0.036145  0.014085   0 -0.835231  0.115633  \n",
      "2032  0.329032  0.083333  0.070968   3  1.841659  0.517518  \n",
      "2033  0.336842  0.034286  0.038596   2  0.531404 -1.134902  \n",
      "2034  0.209265  0.037583  0.039936   0 -2.159444 -0.354687  \n",
      "2035  0.165759  0.023455  0.012099   0 -2.821690 -0.499510  \n",
      "2036  0.125623  0.026051  0.014955   0 -3.350989  0.422161  \n",
      "2037  0.150000  0.062366  0.036364   0 -2.232125  0.813245  \n",
      "2038  0.255605  0.028798  0.049327   1  0.917784  1.973026  \n",
      "2039  0.320000  0.106383  0.066667   3  0.705956  1.540631  \n",
      "2040  0.251309  0.231602  0.230366   3  3.485096  0.260646  \n",
      "2041  0.272926  0.038624  0.028384   1  1.402584  1.572184  \n",
      "2042  0.288779  0.052482  0.034653   2  0.221575 -1.243078  \n",
      "2043  0.087838  0.030950  0.016892   0 -4.408506 -0.682047  \n",
      "2044  0.345070  0.015584  0.042254   1  1.494629  1.368039  \n",
      "2045  0.307263  0.092772  0.134078   3  0.912908  1.001862  \n",
      "2046  0.175676  0.033565  0.008108   0 -3.274102  0.392250  \n",
      "2047  0.184239  0.032347  0.033014   0 -2.916034 -0.227423  \n",
      "2048  0.313783  0.022489  0.029326   1  1.481191  2.218199  \n",
      "2049  0.231013  0.051823  0.060127   0  0.081455  0.781583  \n",
      "2050  0.229885  0.143590  0.172414   0  0.077816  3.475719  \n",
      "2051  0.304636  0.021830  0.052980   2  1.215701 -2.991053  \n",
      "2052  0.294118  0.034513  0.056985   3  0.459735  0.643746  \n",
      "2053  0.131783  0.006381  0.016611   0 -3.575659 -1.234531  \n",
      "2054  0.190265  0.043732  0.008850   0 -2.262634 -0.077042  \n",
      "2055  0.401235  0.058716  0.037037   2  1.950072 -0.872441  \n",
      "2056  0.393401  0.115512  0.098985   3  2.577942  1.378190  \n",
      "2057  0.251852  0.045564  0.029630   2 -0.963870 -2.293938  \n",
      "2058  0.246073  0.058522  0.034031   0 -0.470066  0.652380  \n",
      "2059  0.243736  0.058458  0.059226   1  0.873249  2.004148  \n",
      "2060  0.274611  0.087932  0.048359   2  0.683668 -0.597878  \n",
      "2061  0.228477  0.025432  0.013245   1 -0.738880  1.541630  \n",
      "2062  0.193297  0.043556  0.024942   0 -2.599155 -1.025919  \n",
      "2063  0.238095  0.051988  0.023810   0 -0.878409 -0.788855  \n",
      "2064  0.196970  0.027753  0.033892   0 -3.462765 -0.379188  \n",
      "2065  0.196629  0.044068  0.042135   1  0.826970  4.706929  \n",
      "2066  0.312500  0.083333  0.125000   3  2.769463 -2.442296  \n",
      "2067  0.383065  0.047170  0.040323   1  2.129816  0.458638  \n",
      "2068  0.057432  0.024346  0.003378   0 -4.200747 -2.039932  \n",
      "2069  0.203187  0.063460  0.035857   0 -0.793934 -0.354726  \n",
      "2070  0.417910  0.046512  0.044776   2  0.779134 -1.688104  \n",
      "2071  0.386179  0.050258  0.012195   2  0.282746 -2.003291  \n",
      "2072  0.322222  0.055777  0.033333   1  1.698179  1.518490  \n",
      "2073  0.320242  0.027604  0.027190   1 -0.344469  0.415993  \n",
      "2074  0.259366  0.047530  0.020173   1  2.258110  5.800583  \n",
      "2075  0.608649  0.025746  0.042162   2  4.356481 -3.635935  \n",
      "2076  0.253138  0.029201  0.022315   0 -2.126355  0.000254  \n",
      "2077  0.256545  0.080808  0.068063   2  0.111222 -0.558819  \n",
      "2078  0.157480  0.096000  0.141732   2 -0.194747 -0.907990  \n",
      "2079  0.216165  0.058999  0.045113   2 -1.267661 -1.708510  \n",
      "2080  0.302083  0.031359  0.072917   3  1.712674  0.660174  \n",
      "2081  0.358974  0.103972  0.080128   3  2.219818 -0.290362  \n",
      "2082  0.270992  0.093704  0.087786   3  1.098408  2.686309  \n",
      "2083  0.115127  0.005976  0.002677   0 -3.498525 -2.586377  \n",
      "2084  0.153488  0.004242  0.023256   2 -2.512833 -2.582192  \n",
      "2085  0.272727  0.213531  0.129870   3  1.749320  1.022925  \n",
      "2086  0.106329  0.029015  0.029114   0 -3.547392 -1.430297  \n",
      "2087  0.194796  0.030372  0.014870   3 -0.357039 -1.464660  \n",
      "2088  0.238806  0.026738  0.004975   2 -1.424622 -1.686123  \n",
      "2089  0.404984  0.066232  0.040498   3  1.125773 -1.188416  \n",
      "2090  0.142857  0.080034  0.071429   2 -1.028549 -1.432813  \n",
      "2091  0.258216  0.042236  0.042254   2 -0.998411 -1.130688  \n",
      "2092  0.226087  0.078591  0.060870   2 -1.099596 -2.472411  \n",
      "2093  0.486301  0.102871  0.006849   3  3.135207  0.439710  \n",
      "2094  0.467626  0.098315  0.043165   2  1.514482 -1.206247  \n",
      "2095  0.399194  0.038352  0.020161   3  2.061790  0.010762  \n",
      "2096  0.174046  0.036458  0.029008   0 -1.885956  0.433038  \n",
      "2097  0.244399  0.081633  0.036660   3  0.329561  0.659373  \n",
      "2098  0.227273  0.047619  0.000000   3 -0.611862 -0.555730  \n",
      "2099  0.238095  0.044905  0.043290   1  0.304850  1.435910  \n",
      "2100  0.285714  0.021704  0.000000   2 -1.835512 -5.580711  \n",
      "2101  0.330247  0.034202  0.027778   2  0.483585 -0.431725  \n",
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      "2528  0.377193  0.116700  0.070175   2  2.661048 -1.023865  \n",
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      "2711  0.255725  0.128977  0.064885   2  0.234426 -2.092336  \n",
      "2712  0.333333  0.083888  0.066667   3  0.500566 -0.050153  \n",
      "2713  0.341463  0.144137  0.118902   3  2.074162 -0.560213  \n",
      "2714  0.298137  0.053110  0.052795   2  0.527217 -2.233042  \n",
      "2715  0.344214  0.050863  0.020772   2 -0.130008 -0.489953  \n",
      "2716  0.402299  0.039146  0.034483   3  1.186443  0.018052  \n",
      "2717  0.388235  0.010363  0.035294   2  1.465556 -2.796538  \n",
      "2718  0.328125  0.049046  0.125000   2  3.209475 -3.237082  \n",
      "2719  0.286245  0.021529  0.052045   2  0.051313 -2.494035  \n",
      "2720  0.242222  0.050408  0.048889   0 -2.182833  2.122020  \n",
      "2721  0.109948  0.049336  0.045375   0 -4.200886  0.767303  \n",
      "2722  0.329193  0.024045  0.043478   2 -0.117021 -1.812570  \n",
      "2723  0.231111  0.106678  0.137778   2  1.449592 -1.485820  \n",
      "2724  0.260997  0.196262  0.038123   3  1.031623 -0.778558  \n",
      "2725  0.107961  0.013625  0.007634   0 -5.362152  1.665763  \n",
      "2726  0.383784  0.156514  0.145946   3  3.017608  0.309954  \n",
      "2727  0.287462  0.074504  0.053517   3  0.412186 -0.402006  \n",
      "2728  0.080460  0.007862  0.005747   0 -5.178428  1.649135  \n",
      "2729  0.125749  0.004163  0.000000   0 -4.833331  0.506829  \n",
      "2730  0.080396  0.008139  0.008811   0 -5.951603  2.312318  \n",
      "2731  0.234127  0.016192  0.014172   1 -0.911978  3.527846  \n",
      "2732  0.325758  0.051008  0.030303   2  1.202411 -2.128272  \n",
      "2733  0.345309  0.087099  0.065868   3  1.486338 -1.110144  \n",
      "2734  0.358974  0.113360  0.115385   3  1.808924 -1.245412  \n",
      "2735  0.263337  0.059659  0.051078   0 -0.696045  0.981688  \n",
      "2736  0.233593  0.038187  0.025584   0 -1.268938  0.205390  \n",
      "2737  0.266667  0.058594  0.000000   2 -0.188626 -3.141193  \n",
      "2738  0.248455  0.024230  0.017305   0 -1.955028 -1.541502  \n",
      "2739  0.132967  0.023400  0.024176   0 -3.234430  0.747538  \n",
      "2740  0.242701  0.062430  0.098540   3  0.002798 -0.316754  \n",
      "2741  0.236842  0.061674  0.043860   0 -0.250394  0.693256  \n",
      "2742  0.161145  0.025634  0.025602   0 -3.886257  1.039860  \n",
      "2743  0.174000  0.026831  0.056000   0 -2.663237  1.582101  \n",
      "2744  0.175671  0.027024  0.024604   0 -4.260611  1.754057  \n",
      "2745  0.246964  0.055556  0.056680   3 -0.204390 -0.497596  \n",
      "2746  0.447917  0.030997  0.041667   2  2.072858 -2.982095  \n",
      "2747  0.339768  0.068080  0.083012   2  1.183204 -2.348658  \n",
      "2748  0.251282  0.042866  0.052991   1  0.507971  1.835769  \n",
      "2749  0.292879  0.029540  0.022066   2 -0.483516  0.252676  \n",
      "2750  0.300885  0.076271  0.079646   2  2.108104  0.103359  \n",
      "2751  0.256667  0.072258  0.046667   0 -0.147548  0.964250  \n",
      "2752  0.319523  0.033736  0.048241   1  1.821527  3.942984  \n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.decomposition import PCA\n",
    "\n",
    "# 군집분석에 사용할 피처 선택\n",
    "features = grouped.drop(columns=['대여대여소ID'])\n",
    "\n",
    "# 표준화\n",
    "scaler = StandardScaler()\n",
    "scaled_features = scaler.fit_transform(features)\n",
    "\n",
    "# K-means 군집분석\n",
    "kmeans = KMeans(n_clusters=4, random_state=42)\n",
    "grouped['군집'] = kmeans.fit_predict(scaled_features)\n",
    "\n",
    "# PCA 적용\n",
    "pca = PCA(n_components=2)\n",
    "pca_features = pca.fit_transform(scaled_features)\n",
    "\n",
    "# PCA 결과를 데이터프레임에 추가\n",
    "grouped['PCA1'] = pca_features[:, 0]\n",
    "grouped['PCA2'] = pca_features[:, 1]\n",
    "\n",
    "# 결과 출력\n",
    "print(grouped)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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GiHebK3fXWb9+fcQEVZfLlfDORlvLzc2tkYeRqNWrV0dcUlRf5557btzdlrYOGk477TRWrFhBKBQiGAzi9/s588wzMQwDr9db9Rg2bFjShRPbtm1bp2Uwp512GnfddRejRo3ivffeixnovPTSS1xwwQU1lgBVOuWUUxg/fnxVknhj2WOPPWjXrh0vvfRSxLv2kXTu3Jnff/+9xnPffvttxLY2m43TTz+df//9l//9739Vzzscjlo/AwcffDDz589n1113RSmV5DuxZGdnc/PNN/PDDz8wZ86cqs8zmRyNM844g/PPP5/7778/Zrt///23zj+PQgiRShJoCNGEkknejSc3NzfihWMsp556Kl988UXU16Mlk/fr1y/qBV08V111VZ2O69KlS8xK5XvttVed+gW46KKLalx8bm3ri83bbruN8vJylFLYbDZsNhsOhwOn04nL5cLtdpORkUFGRkbCy7kq9e3bl3nz5tW4c54Ih8PBO++8w+DBg+nXrx9jxoxh3333JRAIsHz5ct544w0efvhhVq1axW+//cawYcMi9jNixAieeuopli5dym677caiRYs44IAD2LBhQ0rvmttsNh566CFGjRqFw+Fg+PDhGIbB22+/zZVXXknHjh1rHTN8+HCuuuoqzj//fA4++GDmzp3LCy+8UKPN3XffTYcOHejXrx8ej4e33367xvf1LrvswtNPP83nn39OdnY2ffr04aqrrqJXr16cccYZXHbZZeTm5rJkyRImTZrE+++/H/N9nHPOOZx00knsuuuurFy5km+//bZGnYtEczR+//13fv75Zx577LFa3/c2m63G7Ma3337Lfvvtl1C/QgjRmCTQEGI7NmfOnEY5z+bNm2MGCWAltMba3tM0zZg7N4VCoboOj1AoFDcvxmazVY2vPkFNPIMGDWLkyJGEQqGkKsSDNSuwcOFCHn74Ye6++25WrlyJy+Wic+fOHHPMMeTl5XHnnXfSq1cvunXrFrGP/v3707lzZyZMmMBDDz3EF198wZFHHtkoS3POPvtssrKyuO+++3jmmWfIyspi0KBBUc89atQo/vnnH8444wzKyso44IADeOSRRzjhhBOq2nTp0oV77rmHf/75h9atWzN06NAaMwRnnnkmM2fO5LjjjqNPnz58+eWXdOnShS+++IJrr72WI488EpfLxW677ZbQ7FR+fj6jR4+moKCArl27csMNN8RdqhVJ5azWEUccUeu1Vq1aVf0smKbJ7NmzefXVV5M+hxBCpJwWQjRLhYWFGtDLly/XWmu966676pdeeqnO/Z1zzjn6sssua5jBJWHPPffUQNzH559/HrWPd955J6E+6vL5nHPOOQn1/eyzz9bp/X/11Vc6mV+1pmnq3XffXb/55pt1Ol9DO+mkk/Srr77a1MMQUbz55pt6991316ZpNvVQhBCiFqW11o0S0Qgh6iUUCmEYRp3XjFcWDYuUwCpSKxgMYrcnPoH8xhtvcP/99zN//vykjmtoWmt23HFHfv3111p1QZL15ZdfRq0P0qVLl1q5FiK+YDDIfvvtx3XXXVermKAQQjQHEmgIIUQzdPrpp9OjRw/uvvvuph5Kg6ioqOCff/6J+JrD4WCnnXZq5BG1fHfccQdLlixpkF3dhBAiFSTQEEIIIYQQogXQWjNp0iSeffZZ5s2bF7HNTz/9xOjRo1m3bh0ZGRmMHTuWwYMHN/JILZIMLoQQQgghRDP34Ycfcu211+LxeKIuqy0tLeX444/n5ZdfrqqvdOKJJ7J06VLat2/fyCOWgn1CCCGEEEI0e+Xl5Tz44IO8+OKLUdtMnjyZ/fbbj0GDBgFw6KGHMmDAgCYpxAoyoyGEEEIIIUSzd/LJJwOxt6afN28eBx10UI3n+vXrx8KFC1M4sui2qUDDNE3Wrl1LVlZWnXfmEUIIIYQQqaO1prS0lI4dOzbLnRC9Xi9+vz/l59Fa17pedblcuFyuOve5bt06Bg4cWOO5tm3b8t1339W5z/rYpgKNtWvX1qiWKoQQQgghmqdVq1bRqVOnph5GDV6vl25dMlm/oe5FYBOVmZlJWVlZjeduv/127rjjjjr3GQwG2Xqfp1Ao1GQ34LepQKOyeuyqVavqvee7EEIIIYRoeCUlJXTu3Lnquq058fv9rN8QYuWPXcnOSt1sS0mpSZc+K2pds9ZnNgMgPz+fTZs21Xhu48aNTZIIDttYoFEZrWVnZ0ugIYQQQgjRjDXnZe6ZWYrMrNSNzyQ116x9+vThm2++4b///W/Vc9988w3Dhw9vsHMko/ktjBNCCCGEEEIkbeTIkXz22WfMnj0bgA8++IDffvuNU089tUnGs03NaAghhBBCCFFfIW0SSmFJ65A2G6yvV199lR9++IGxY8fSqVMnpkyZwqWXXkpBQQE9evTg/fffJyMjo8HOl4xtqjJ4SUkJOTk5FBcXy9IpIYQQQohmqDlfr1WObcPvXVKeo9F215XN8jNoSDKjIYQQQgghRDUmGpPU3YtPZd/NieRoCCGEEEIIIRqczGgIIYQQQghRjYlJw2VRRO5/eyAzGkIIIYQQQogGJzMaQgghhBBCVBPSmlAK90tKZd/NicxoCCGEEEIIIRqczGgIIYQQQghRjew61TBkRkMIIYQQQgjR4GRGQwghhBBCiGpMNCGZ0ag3mdEQQgghhBBCNDgJNIQQQgghhBANTpZOCSGEEEIIUY0kgzcMmdEQQgghhBBCNDiZ0RBCiGZI6wD4PkP7vgZCKMfe4D4eZWQ09dCEEGKbJwX7GoYEGkII0czo4HJ04XkQWgPYrOc8b0HpQ5D7NMp1YNMOUAghhEiALJ0SQohmRJvl6IKzILQ+/Ewo/AB0ObrwQnRweVMNTwghtgtmIzy2BxJoCCFEc+J9H8wNVAUXNWgghK6Y2MiDEkIIIZIngYYQQjQj2vsxoGK0CIFnVmMNRwghtkuhcMG+VD62BxJoCCFEc6IrIO4fIF9jjEQIIYSoF0kGF0KI5sSxOwQWEXnpFIAB9l0ac0RCCLHdCWnrkcr+twcyoyGEEM2ISjud6EEGgIlKP7OxhiOEEELUmQQaQgjRjCjHLqjMq8NfVf8VrayH+1jrIYQQImVk16mGIUunhBCiDrQ2wT8PAgsAA5z9wbEPSsVK5E6MyhwN9p3Q5S+El1EBts6ojFGQNgKl5B6REEKI5k8CDSGESJIO/okuHA2hlVQW1IOxYO8JeU+jbO3rfQ7lHoJyD0GbFUAIVGaDBDFCCCHiM1GEYu4AWP/+twdyW0wIIZKgQ5vQm0dCaHX4mWoF9YJL0AVnobWnwc6njHSUkSVBhhBCiBZHAg0hhEiCrngNdDGRE7ZD1iyHZ2ZjD0sIIUQDMnXqH9sDCTSEECIZ3veIncan0N73G2s0QgghRLMlORpCCJEMszROAw1mcaMMJdW0NsH7PrriVQj+AbjBfRQq4xyUvXtTD08IIVImlOIcjVT23ZzIjIYQQiTD3oXYvzptsA1chGsdQhddjS6+FgKLQXtAF4JnKnrTCWjfN009RCGEEM2cBBpCCJEElX4GsZdOhVBppzXWcFKn4nXwfRj+ovr7DQEBdNHlaLO8CQYmhBCipZBAQwghkuE+DpwHEfXXp/tkcPZr1CE1NK01uuKVWC1Al4HkogghtlGVS6dS+dgeSKAhhBBJUMqByhsHGReDyt7ygtEGlXU9Kufelr8VrS6D0D9ArG1RbOjAz401IiGEEC2QJIMLIUSSlHKisq5GZ14GweWgbGDrilLbyq/URO9B2eI3EUKIFsjUClOnsGBfCvtuTmRGQwgh6kgpJ8qxK8reYxsKMkAZGeDoRew/ESGU6+DGGpIQQogWSAINIYQQtaiMi4ie9G4DWydwHdGYQxJCiEYjORoNY9u5BSeEEM2EDvyM9n4K2ouy7wLuY1BGelMPKynKPRgyr0GX/Q9riVQIUIC28lHyJmxTszhCCCEanvyVEEKIBqLNYnThFRD4FuviXKEJQum9kPMIyt2yZgBU5sXgGoj2TIHAUlBpKPcQcB/X4gInIYRIRgiDUAoX/oRS1nPzIoGGEEI0AK01unA0BH4KP1Ptz4iuQBddDvlTUM5eTTK+ulKOnVGOW5t6GEIIIVogydEQQoiGEPgBAvOJfJ/K2iZWlz/bqEMSQghRNzq861SqHlp2nRJCCJEo7f2I2Nu9hsD3OVr7GmtIooXQ2o82y9A6Vt0SIYRoeWTplBBCRKC1hsDP4VkKwLk/ytEzxgHlifQK2gvK1SBjFC2b9i9Cl48D32zABKMNpI+EjFEoldbUwxNiu5bqnaFk1ykhhNhO6dBaK6k7uJgtE78m2tELlfsEytah1jHK1g0ds5I2oHJBZTX0cEULpL2fWnk7KKq2ETY3osueAO9syJ8oCfdCiBZPlk4JIUQ12ixDbx4JwSXhZ0yqLgQDv6ALRqLNstoHpp0MMe9QGeA+Cvw/oIP/NOygRYuizTJ08Ris3J2tc3pMCP5izXQIIZpMSBspf2wPto93KYQQifK8BeZaIid1hyC0BjzTa72ibK1R2beFv9r6V6sC7OCZgi48C71pEObmkejAEsR2yDsDdAVEnQEzoeJ1tA405qiEEKLBSaAhhBDVaM+7RL8ADLfxTo/4vEo/HZX7HNj3rPasO9yfv2bjwI/ozSMk2NgO6eDvxF25rIvB3Nwo4xFC1GaiMDFS+Ng+cjQk0BBCiOrMwjgNdMw2yj0Qo/XbqDbfQOuPgGiJ3ybgR5fchTYL5e71dsWdWDPZNEAI0cJJoCGEENXZdyT2r0YDbF3jdqNsrVHBZUBxjFYmBBagN/RD/7svZvHN6OCq5MYrWhyrQnwwRgsDHPugjLzGGpIQYiuVu06l8rE9kEBDCLHd0qENmKWPYm44DPPffTE3DQXbjlQlf0dkotJPS+wEobUk/mvWB55p6M3D0ME/EzxGtEiOPuDoTfS6KyYqY3RjjkgIIVJCtrcVQmyXdGAZumAk6BKqAovgb9ZuUyon/PzWuRoKXIeBa1BiJzFyiR20bC0EuhxdfCOq1ZtJHCdaEqUU5D2LLrgwvIWyHet7TQMKlX0byn140w5SiO1cqneGCm0nBTqb5YzG999/z4ABA+jSpQsdO3Zk2rRpTT0kIUQLoLVG++ZiFl6OufEYzM0j0BWv1dqOVmsTXXQZ6FJqBgLhX/y6BBx7g8rc8pLKhIyLULlPolSsCuDVuI4AnEm+ixAEFqEDvyd5nGhJlJGPavUmKu8lSDsV3MeiMq9CtfkSlX56Uw9PCCEaRLOb0Vi6dClDhw5l4sSJDBo0CL/fT1FRUVMPSwjRzGkdQhffAN53sZakhCCk0IGfoOwFyH8VZe9kNfbPg9CKWL1B8E9oMxsV/AeUAvsuKJVgEm+YMrIg8zJ02WPJv6HgMnDsmvxxosVQygDXQSjXQU09FCGESIlmF2jcfPPNXHHFFQwaZC1NcDqdtG3btolHJYRo9sonhIMM2FIDIzxDYf6LLroUWr1rLVsJLKIqGIlGl6NC61DOXvUbV8YlKECXPY21xa0i3va5ACQZ1AghhGg41va2qUvYlu1tm4DX62XGjBmMGjWqqYcihGhBtA6iK16K0SIEwaUQmB/+2iChi/0GuBejlEJljka1nYfKeRAyryb+cio3OA+o97mFEEKIptSsZjT++OMP0tLS+Pzzz7n//vspKytj8ODBPPzww2RnZ9dq7/P58Pl8VV+XlJQ05nCFEFvRoX/RFW+Afy7oEDj3s4rY2buk9sShlWBuitPIhvbNQzn3A9dBUPZo7OZGa7B3b7AhKiML0oahAFP7oPzp6I0zzkUZmdFf38bo4Arr+ya4BFQayjUQ3MehjPSmHpoQYjtlYhBK4f14M6GbXS1fs5rRKC0tJRgMMn/+fL7//nsWLVrExo0b+c9//hOx/f33309OTk7Vo3Pnzo08YiFEJe37Gr1xEJQ/A4GF1m46Fa+gNx0Zrrad0rMn1U45elpbjEbdXhRUxnkolZp7MSrzckg7I/yVrdoDSBuOyoz8O6+S1hqt/THbtBS6fCJ605FQ8bKVO+P7HF1yi/V9E/y7qYcnhBCiHpTWzWd/rd9//529996bsrIyHA4HAD///DOHH344mzdvrtU+0oxG586dKS4ujjgDIoRIDR361woy8BP5ot9AtZqGcuyRmvNrP3rDwaCLYrZTeS9VJd7q0EZ0wTkQ+hPrnotJVd5G2qmo7LutZN0U0sG/0Z7pYG4Aow0q7USUvUeM9v+gy8eDZzrgASMf0kagMs5FGbkpHWsqaN9X6MLzo7xqA6Mtqs0nKJXszl1CiOaspKSEnJycZnm9Vjm2KQv3ID0rwR0G66CiNMSIfZY0y8+gITWrpVNdunTB6XTi9XqrAg3DMHC7IydFulwuXC5XYw5RCBGBrngDCBB9ZkGhyyeich9IyfmVckLGWeiyp6KMwQa2zuA8cMsxtjbQejp4Z6E974MuBltXqxifo6+VNJ5iyt4dlfXfhNrqwBJ0wZmgPVQlsZsFUP4c2jMdnXMfyrEXymiYP1g6tAa8n4Autyqhuwc3+AW/Ln+BLUHe1kJgrgPvx5B2XIOeVwghRONoVoGG2+3m7LPP5pprruGZZ54hFApx++23c+aZZzb10IQQsfi/InZhuhD4v0ztGDIugcCv4JtNzYtXA4xcVN6ztWYolHJC2omotBNTO7Z60lqji66uGWRUMcFcC4XnorGj3ceisq5F2eq2W5/WfnTJHeB5G2uHLAMIQkkO5NyPcg+q1tYLOgAqM+nATOsA+L8j9rI3G9r3FUoCDSFEIzMxMCVHo96aVY4GwIMPPojH42GHHXZgzz33pEePHtx9991NPSwhRCw6xjaxVW2SqZCdPKUcqNynUTmPg6MvGG3A1h2V+R9U65ko+04pPX9KBeZDaDkxt+MFIAjeGejNp6FD8ZLjI9PFt4aDDI0VrAXDL5Sgiy5H+79H+77BLDgb/e/e6A190BsHoMueTzJvxCR+bo3ecn4hhBAtTrOa0QDIzMxk0qRJTT0MIUQynPtB8DeiXwjbrDYpppQN0o5BpR2T8nM1qsBvJFx/g5BVN6TsSVTOnUmdRgdXgPedaK8CygpEQivC4wkz/0WX/c/abSzvxYSWWCnlQtt2gtDfRH9f2krcF0KIRhbSipBO3RLaVPbdnDS7GQ0hRMuj0s8g9kVwCJVxdmMNZ9uTdG5ECDzvoLUvftPqvLOItRMXmOGZlcrZjuq0tRSq4tWET6cyziFWXg84IW1Ywv0JIYRoXiTQEELUm7J3QeU8gPUrpfqFqvX/KvMaq36FqBvXgDoc5AWz9m59sWizGOpVrVajyycm3jztNHAfG/6i+p8ja7tflTsWZeTUYzxCCFE3oXAdjVQ+tgfNbumUEKJlUmlDwb6LdaHp/zJcsG9/VMbZ21WQobUG/5fo8tes5WTKDe6jUOkjUbb2depT2Tqi3ceBdyaxk+63PjC5on/KviM6bh5IHOZatPahVPwdAZUyIOd/4DoMXT7Jqt6unOAaYm3Z69itfmMRQgjRpCTQEEI0GOXYI2Vb2LYEWuvwjk2TqarJAVD+ArpiEuS9hHL2rlPfKucetFkU3uGrWt8R2cB5QPJb3bqPg5L7gWhLrhLJEzFI5k+LUkaL2PlLCLF9MbWBqVO461TzKWOXUtvHvI0QQjQGz7RwkAE1AwETtBddeLG1JWwdKJWGynsRlf8apJ0KRrTZEWvpk8q8IvlzGNmo7Ftr9LOFDVS8wMUGrsOtpHwhhBDbPZnREEKIJGmtwTvTmqUI/BZe7jMI/POJftfftCqXe2ZC+sl1Oq9SCpz7oZz7obUPXXwzeN8Pn1MBIaumRc4jKOe+dTtH+mlg5KJLx0JoWfhZG7iPgsxroOhiCP5N7RkV632rjIvqdF4hhGhOUp1HEdpO6mhIoCGEEEnQ2kQX3wTeaVQVBtRe8L5L/DoXNnRgPoq6BRrVKeWCnPvQ2MD73pZz6zK09z1w9kYZuXXr2z0EXIMhtBJ0Gdh2QBl5Vvd549GFF0DwD6w/IZU7UDlRuQ/VeWmYEEKIbY8EGkIIkQzP9HCQATUTsxNJoq6ceUieDv0LnnfRobVg5IH7GCh7BHxzqDmDosH7ITr4O+S/iTIy6nQ+pRTYu9Z+3tYeWr0H/q/Q3tmAD2XfDdKG1jmwEUKI5sYktbUuUlvCtvmQQEMIIZKgK14m8eJ5WwuinP2SO5/WUP4cumxs+BnDOnf50zGOCkHwL/C8CRnn1mGcsSllgOtQlOvQBu9bCCHEtkOSwYUQIkFaB60tWOsUZNjAaAPuo5M7zPMGuuwxrPtfJhAksdkT0BVvJDnGKP2E1qN9X6B936C1p0H6FEIIse2TGQ0hhEiYQVVeRlSVsx3Vt6BVoLJQeS+gkqjyrXUIXfZkHceqwVxfx2PDPYQ2Wtv1+j6j6j2rDHT6uajMy2V3KSHENsvEwEzh/fhU9t2cSKAhhBAJUspAOw8E/7dEn1XQkDEaQqshsARUGsp9FKSfgjLykzth4BcwN9Z9wEarOh+qzSJ0wXAIraNGYKXLofwZdGjddl0zRQghRHwSaAghRBJUxgVo/9dRXrWBkY/KvDShythx6Yp6HGyg0k6p+6nLX4HQWiLP3mjwTkMHRqIcPet8DiGEaK5C2iCUwoJ9qey7Odk+3qUQQjQQ5ToIlX071hKpyqVD4Z1JjDxU3ssNE2QA2LtRt12qbFZBv/TT635uzxvEXiJmQ3vernv/QgghtnkyoyGEEElS6SPBeTC6YgoEfwHcKPdAcJ9Q5+1kI57H1h7tOgx8XxJ5qZYC3ICPGkGBoy8q92GUkVOn82qtwdwUp1UIQvXLARFCiObKRGHWcTvyRPvfHkigIYQQdaDsXVDZ19d4TpulaO9HVgE/+y4ox+71P0/WrejAqWAWUTPYsAE2VP4EsO1g5Y3oEDh7oew96ndOpdAqB3RxjFbWMjEhhBAiGgk0hBCinrQOosseh/JXsGYXws/b90blPlCvC39l7wSt3kGXPQ2edwA/YIDrCFTmZVuCmbSh9XgHEaSdBBUTiZ70HkI19DmFEKKZkByNhiGBhhBC1JMuuR08b1GrvkbwV/Tm4dDqHZR9xzr3r2ztUTl3o7NvAbPQ2iq3AZdoRTxnxii0ZzroEmoHGwY4DwbHfikdgxBCiJZt+winhBAiRXTwT6sCd8QifiHQFejycQ1yLqVcVtCR4iADwsFNqylg33r5lwHuoai8p1Bq+1hjLITY/oQwUv7YHsiMhhBC1IP2TKdmcb6thcDzLjr7DpRyNN7AGoCyd0O1noYO/AKBX0E5wXkQyta2qYcmhBCiBZBAQwgh6iOUSEE9P+gyUHkpH04qKMde4NirqYchhBCNxtQKU6dw16kU9t2cSKAhhBD1YWuXQCMXqMyUDyVRWnusWRbPWxDaALYOqLTTIO14lHI29fCEEEJsIyTQEEKIelBpQ9Hlz8VoYYO0k5ps2ZQO/okufxV8c4AQOHpBYAmYq7HqcGgw/0UHfoKK1yH/FZTRfIIiIYRoCmaK8yjM7SRHY/t4l0IIAEoLy/hn6RqKNsaqjyCSoezdIe3MKK/aQGWjMi9u1DFV0t5Z6E3HW1W+zbVg/gu+j8NBBmxJYA//N/gruuTOphiqEEKIbZDMaAixHVj9x1peumUyc9/5HjNkgoK+g3tx7j2ns2vfnZp6eC2eyr4FbHno8vGgK7a84OiNyrkPZevY6GPSoTXoomuwKoZH2hErEhO8M9Ch61G21ikcnRBCNG+mNjBTWOsilX03JxJoCLGNW7lkFf856BY8ZV4ryADQsOCzxSyc8ysPfnwrew/Yo2kHmSJa+yH0j/WFrStKpeZXnlIGZF4B6edD4IdwZfAeKHvTBXG6YgpWgJFokFEpBIFFYDsiBaMSQgixPZFAQ4ht3BOXvVgzyAgzQyZaax4e9TSvLHsSw9h27q5oHYDycejyiaCLrCeNVpB+LmRcgFK2lJxXGengOjQlfSfN/x3Rt9yNp/nvhqJDG8H/LegAOHqiHDs39ZCEENuQEIpQCn8XprLv5kQCDSG2YWv+XMfPXyyJ+ro2NeuXb+DnL5awz+HbxvalWofQRVeCbzY17uabm9Flj0JwKeQ8uh0Um6tr4GgH5z4NOZAGpbUHXXwneKdjLQsLP+/oi8p5CGXv1GRjE0IIUdO2cwtTCFHLmmXrE2q3+o91KR5JI/J9Ar7PiLxkSIN3Jvi/bOxRNT5nf5L/FW+A+0SUkZ+KEdWb1ia68NJaQQYAgZ/QBSPQoc1NMTQhxDamMkcjlY/twfbxLoXYTqVnuRNrl52W4pE0Hl0xmdi/2mzhNts2lT4ccBB7GVTla+HPy9HLSmxvrvzfgP9ragUZAITA3ISumNTYoxJCCBGFBBpCbMN2P2AX8jvkxmzjcDvod0zvxhlQYwj+TeQL0UohCC5vrNE0GWVrh8p7GivYqP6rPpyf4j4JHPuBrQs49kflPIrKfxVlZDTBaBOjPdOpGn9EJnjeaqTRCCGEiEdyNITYhtnsNs65YziPXTwuapvTrjmBjJzme3GZNCPbqhcRlbLaNCGtQ+D7Au37FLQXZd8F0k5G2do06HmUawC0+diawfF9BQTAuT8qfSTK3qNBz9UozI3ETXA3CxplKEKIbVuI1CZs13WrjpZGAg0htnHHXDiI8uIKJtz8OqGQic1mhHecgpOuOpaz7zytqYfYoJT7BCvpO8a2rsp9fOMNaCs69C+68DwILsO6O6/RfABlT0D23aj0kxv0fMrWEZV1DWRd06D9NglbB6zPLMafaKNtY41GCCFEHBJoCLEdOHXMCQw59zA+n/w1G1dtIrdtDoeNOIg2nVo19dAaXvppUDExfGd76wtSGxjtIO2kphhZOJn5/PDyLqg5PhNdchPYOqBc/ZtieM2eSjsZ7ZkWo4URzk0RQoj6kYJ9DUMCDSG2Ezmtsxl6xdFNPYyUU0Ye5L+KLhwNob/ZsqY/ZBXRy30WZWQ2zeD8X0HwjxgNDHT58xJoROPoC66jwPcRtWesbGDrBOkjm2JkQgghIpBAQwixzVH2btB6Fvjnof3zrZoZzn7g2K9J62do7+dYidnRktVD4P8Grb0oldiOYdsTpRTk/g9d1gnKXwW8la+AayAq+05UE+ffiMajzQKoeCuc6+S3dk1LPx3l2K2phya2ASFtEErhrEMq+25OJNAQQmyTlFLg6t+8ZgdC8XbECtN+aGGBhg5tgsCPgAbHPihb+5ScRykHKus6dMalEFgQrgy+Z8rOJ5on7V9k5TrpMqpmt4K/oz2TIet6VMb5TTo+IYRl+winhBCikejganTFm+iKKejAlqrsWpsQ+C1+B6otqKwUjrBhabMMs+ha9MZD0EVXoIuuRG88DLPwP2izOGXnVUYmyjUA5T5CgoztjDbL0IUXgC6n5hI6K+dJlz6I9s1tkrGJbYdGYabwoeuwo5XH4+Giiy6iS5cudOrUieuuuw6ta298Mn36dPbcc0923HFH9t9/f+bObbqfB5nREEKIBqDNMnTxjeD7mOoXP9rRC5XzqLXlrk7gwtt1aJMu70qG1n7rrnLgZ2rO1Jjg+xhdsBxaTZVlYKJhed+P87NkQ5e/iHId3GhDEqIxXHPNNZimyV9//UV5eTmDBg3iqaee4oorrqhqs3z5cs4++2xmz55N3759+eSTTzjhhBNYvnw5OTk5jT5mmdEQQoh60jpo7Sbl+4RaScqBX9AFp6MTLRLobEHFE70fQWAhUSt1B5eCZ3rjjkls87RvHrEr3ofA/13EO71CJKoyRyOVj2SUlZXxyiuv8NBDD2G328nJyeHGG29kwoQJNdotXryYXXbZhb59+wIwePBg0tPTWbZsWYN9NsmQQEMIIerL9zkEfiLqBbe5yconSICydWjQoaWS9rxF7D8jKtxGiIaUSKmzBHKhhGhBfvzxR7p160Z+fn7Vc/369eOXX34hFNryM3HIIYewYcMGPvnkEwAmT55Mfn4+e++9d6OPGWTplBBC1Jv2vEvsQnIm+OaBbQcIrSVqMUGjLTgPSM0gUyG0ntgXdBpCsaq0C5E85dzX2mkqKgMce7eYJYiieTK1wtSp+x6q7LukpKTG8y6XC5fLVav9unXraNeuXY3n2rZtSzAYpLi4uCoAycvL45FHHmHIkCFkZGTg9/v56quvcDqdKXonscmMhhCi2dLBfzBLH8YsuAiz6Cq0ZyZa+5t6WLWZm4h7l1UXorJuDn8R+Y+XyroJpWwRX2uWbO2IN6MhlbpFg0s7CXARffmUicoY1YgDEqLuOnfuTE5OTtXj/vvvj9guGAzWWg5YOZNRPaj+/vvvuemmm/jpp58oLS3lgw8+4OSTT2bFihUpew+xyIyGEKJZ0uXj0aUPYV3IhgAD7f0AyrpC/ivNa4mRrRMEFhE92FBgtEe5B0HuU+iSe8Bct+Vlo60VZKQd0xijbTAq7RS0/9sYLTQq/dSE+9M6CL4vILQcVIZVG8PWLv6BYruijDzIe8oqyonJlp+78Kxi+rlWYUch6iGEQSiF9+Mr+161ahXZ2Vvq/0SazQDIz89n06ZNNZ7buHEjbre7RpL32LFjueyyy9hnn30AGDRoEMOGDeOFF17g3nvvbeB3EZ8EGkKIZkd7P0aXPhj+qvIiIrxEJ7QKXXghtHoPpRpvUlZrDYH5aN83gIly9gbnIShlsy64ve/FPF6lj7D+6x4MriPA/wOYG8BoDc79W9ZMRiX3UVA+EYK/UHsJlQ3sO0HaiQl1pX1fo4uvDc8O2cL93YlOG47KvgWlHA07dtGiKdcAaD0DXfEqeD8JF+zrico4E5wDZNmUaDGys7NrBBrR7Lvvvvz+++8UFhaSl5cHwDfffEO/fv0wjC1/C/1+P3Z7zct7h8OB3980qwFk6ZQQotnRZc8T/ddTCIJ/gP+bxhtPaC1684nogpFQ/hyUj0MXXoT+tyfm5nPQOgDOI4m8lMMG9p0h7bSqZ5QyUK5+qLTjUa4DW2aQASjlROW/BO5jqPnvpcB1BCp/Ekqlxe3HKr52IZibw8+EsPJYTPBMQRff1vCDFy2esnfDyL4Vo+2XGO2+xch/AdWCtocWzVtljkYqH8lo3749Rx11FDfddBPBYJBNmzZx7733ctVVV9Vod+qpp/Lkk0/yzz//ALBw4UImTpzIsGHDGuqjSYrMaAghmhVtlkDw5zit7GjfnEbZJ1+bFeiCMyFUudSp+vKoIATmQdE8cJ8A6ReA5zXQFVXjxH2sdUfeyEj5WJuCMrJQuY+iQzdYlcG1BmfvpJa26bKxWDMYkZLkNXjfRgcvQdm7NNSwhRCixRk/fjznn38+HTp0ICMjgzFjxjB06FBeffVVfvjhB8aOHctpp51GSUkJRx11FOXl5eTl5fH888/Tv3//Jhmz0tvQRtMlJSXk5ORQXFyc0DSUEKL50aFN6I3xfiHaIe0UjJy7ah4bWGLlcZil1kVp2lCUkR+ljwTHU/EGuuTWhNqqrOsh7fRwAbsQOHav9/m3ddosQm/oR9SduACwoTIvR2Ve1ljDEkKkUHO+Xqsc2+Vzh+HKTN2STV9ZgKcOfqdZfgYNSWY0hBBNQgdXWvUntA8cu4PzYCvnwsi3dioyN8Q4Oohy7GXlTfi/Q3umgW8u6Mr1/QpNCEofgexbUOln1D6/9llru0OrwMgB1xCUrXXtdt6ZWEui4t+T0eUTUOnnoFwHhM/hR/u+gNBma4cm5wEtdplUypglxP9sFdosilmiTQghRPMjgYYQolFpswxdfCP4PsJa16+AEBgdIfdxlHMfSD8LXfYokS9AFagMtOsIKDwP/F9v9XrNpU265A4wWqHcR24Zg2cmuuQ20KVsSTy+G51+LiprTM1gwCyOMo4IzI3oomsh/RR0aB2UPgy6cMvrRlvIvg3lHpJYf9sDozXgAAIxGoVQts5RX9XaBP88CPwKygGuQ1H27g09UiGEEEmSQEMI0Wi01uiiy8D/XfiZajsVmevRBedA63cgYxT4v62W8F15oW8DDFTuWHTp/dbFZVwKXfakNWOhFNo3B13832qvh7b8t2I8WilU1nVbXrb3sJLPE6pGDPg+RPtmRn7N3IguugJyn7a2uhUoIx3tPh687xL9M7ZB2vERX9GBX9FFV1ozU9gADaX3o10DUTkPo4ysFI1cCLEtC2lFKIUF+1LZd3Miu04JIRpP4IdwcBCpmrQJ+NFlL1i7GeU9j8q+DWzdsWY90sB9IqrVNOvi3/t+lH62pq1AIbTaCnRKH9nyfCTlL6FDm6u+VOnDSTjIgDhtrXPq0vutu/ACAJV1FRh5WIFCpNdvsGonbEUH/wkn6q8JPxOi6nvCN8faGUw+ZyGEaDISaAghGo32zCDaxaQlBN4ZaG2ilAOVPhKjzSxUu6UY7Rdh5D6AcuwKvq9IeDlT1ckrILQiPDsR61gTfB9v+dKxX42taetPW3ffA/F21kqiR22iA4vRvm/QVRfdLYeytUe1ehNch1Pjz5KtMyrnEVTG2RGP0+UTQHuJGrgGfmzUbZCFENuO5ra9bUslS6eEEI1HJ5Lv4AP8gLvqmVr74ms/iSZoW5xg2wGCfybQ1gCzqOa5s+8C+87osnHhhPMGYG5skG60Zzq69LEalca18yBU9m0oe7cGOUdjULYdUHnPoEMbrY0CVAbKsVvsmgje94g9g2RDe95vlG2QhRBC1CaBhhCi8dg6EbmoXTVGPuCK3caxF4kHGTZIOxFlZKJtHYkfoIRgq8RjpQzIOAfSz0QHFoN3BvjmQOifBMcQaVjtkj5Eaz9UTEVXvBY+tw3w1m7o/xa9+VRo9XbU2hPaLLRqg6gslD16onVj0v4f0OUvhmesQmj7Htbn7j6xVsChtQZdFqfHUDi4FUKI5GhtYOrULfzRKey7Odk+3qUQollQaacQ+w60AWkj4lf2dfQC+y7EXoaF9bqtAyrTSv5WtrbgPDTGcQpUFrgHR35V2TCc+1jJ4hlXULd7NQpUK3RwgxU4JEhrL7pgFLr0bgj9jbVLU4QgA7AusEvQm4ehK6agdXBLP6E1mIX/QW84EL15KHrTEZibhqJ9c+rwXhqOrphq5Vv4vgSCWLk1v6GLr0MX38jWJZ+UUmC0j9OrrVbQKIQQovFIoCGEaDTK3g0yLonyqg1sO6Iyzovfj1KonMdAZRI1aFBpkD4S1eotlK3VlqezbwCVHuE4FX79LpSKPqOizSL05tOg5FqsC+JkadCbofhS9IaDw3krCRxV9oyVc4Am4dkcXYYuuQ1dOBqtA+jQGvTmk8M5KNXyGoJL0YUXYRZegrnhIMz1e2JuGIguew5txps1qD8dXGVtN4ymZiAaHqN3Gnhr7+Sl0k8n9p+xECrt1IYbqBBiuxFCpfyxPZBAQwjRqFTm1ajsO7a6G+0A91BUqzdQRmIVUpVjZ1Tr9yD9LGsWAsBoAxkXQ6uZqLY/YGTfUqsyt7J3txKPnYdQYxmXfRdU7nOotGNjnlcXXQvB3+OMzioaiKq9U9JWnaGL/4v2fhS7mfZDxesktstWBP4voeIVdMnD4bogW88qVe7UNDucOxIAczW67DH0pqFos6Bu502Q9rwRp4WBrphY++n0s6wdyKIFm+mjUI5d6js8IYQQdSQ5GkKIRqWUgvQzIG04BJdZlcHt3RIOMGr0ZeuAyr4Jsm8K71SV2L0TZe+Oyn8eHdoAobVWZXBb17hLtnRwBfi/iH8C5yGozEvBsTfa/x0UXkz0ZU4KXfoguAZHH39oLeiS+OeNSqPLXwZzE8kFKxrMf9BFV6PyX6nH+eMI/ELscZkQWFLrWWVkQv7r6NKHwfMO1iYCgNEGlXGxFYgIIUQdmJqU7gxlJrlxYkslgYYQokkoZQPHbg3YX/ITtMrWFmxtEz/AP49EdrtSmRdaFc4BdCk6apCB1VdoNQQWg7NXlA4diY8xGnND3Y/1z8MMrMBwdK3/OCJyEv9z9WOu3xscPa3tbsMFGJWRjcq5G511HQT/tj4r+y4oJX/ehBCiqcnSKSGESJROsHBf9XaJLjuK1c7oCLYdibtjVypVvJyyrpX7cBLLO/FC4Ed00RXokntqJIgrIwvl7IVy7CFBhhCi3szwrlOpfGwPto93KYQQDcHZm/gXxE5w7L7lS1uHxPqO0U4phcq4JIFzR2OEd+raizr/2o+bl1IP7hPAaEViYwsvsfJMqllYUQghRLMjgYYQQiRIOfYEx95E3x7XgLRhKCNny1POg8BoTfTZCAPsu6OiLCPTWqP9C9D+H8HYYcsx1f9rdAPVKsY5TFTGRaisq7GClTrMjFQm3KeAMjJQea+Egw1I7E+TgS6PkCAuhBANwESl/LE9kEBDCLFd0qG16MAv6FByFbpVzuPhwKH6r8/wHwz7Hqis62u2V3Zrl63q7bY+ztkP7XnHKqJXfYw6ZNWRKBgB3ulgrgmf1wSVDa6BqNyxqDYzUK3fCi+votrYrN2vVNb1KPdglOsQVM6joDKSes8AytUv6WOS6t+xC6rNp6js+8B9JKj8OEeYVl6LEEKIZksWsgohtiva/wO69H8QWBB+RqGdA1BZ1ya0Faqyd4LW70HFFLRnmpVbYeuESh9hzWYod+1j3EMg9zl06QMQWl7tFTsQsLaeRQMOdPo5qKxrUMqGLnsavO+F21bmfYSXDukyUE6U+2jra9sO0HomeD9Gez8GXQH2nVHpw1H2rlvGknYsuI9AF14G/rkkthzLDWknJdCufpRKg/RTUOmnYBZcAP6viDk+Fa9goxBC1E1IK0Ip3HUqlX03J8020Bg9ejSff/45S5cubeqhCCG2Edo3F114ITUvXjX456ILvof8Kajq+RVRKCMPMkejMkcnfG7lPhxch0FwCdo/H0ofZEvwUDmeAFS8iNY+yL42nIAd7ULbBO8sdOhalM1aUqWUE9KOQ6UdF3ssyg0ZF6H9XyUwcicq7ynrPTci5RoQZ3w26/MUQgjRbDXLpVOrVq1i4kRZeytEXVSUeij8t4hQMMEdkrYT1jKkm7BmBLau2RAC7UOX3JXSMSilrDwP35dYAUSU2hGeSWjvbGvWIiYNvq8jv2IWoMuexyy4ALPgQnT5+JpLs5z7gz1WvgngGoRqPQPlGhB7FNqH9s9H++ZFLO6ntUb7vkWXjUOXv4gO/BbnfQFpw0DlEP3PlEZljIrfjxBC1IHsOtUwmuWMxtVXX82oUaP49NNPm3ooQrQYi774ldfvfZsFn1rr1rPyMjj24iGcfuMw0rPSmnRs2iwGz3R04FdruY/LuruvGnPpi38emOtjNDCtrVODy1H2blXPWluoBqzZggagzcLElixVJFIgTwGB2ufwfWUtjcJXdR7t/wJKH0FnXmUlhisFeePQhRdA8FesPweaymRxlX0HKn147PeiQ1D+HLp8AujS8LM2tPtYVPbNKCMPHfwTXXg5hP7GCmo08BDa0Q+VN7ZW5faqd2ZkQf4EdMGoasUKNVbgoVA5D6AceyfwGQkhhGgqzS7QmDlzJps3b+byyy+PG2j4fD58Pl/V1yUl9amcK0TLNeeNr7nvjLEoY8uaz9LCcqY+/C7ff7CAR7+8i4zs9CYZm/Z+jC66Bqtqs3UHR3umgq0r5L9Utewn5UL/JNhuFdi7oQPL0OUvgPcDwI822qHSz4D0c1BGPT5Ls4iE8iICPxG/iJ0GR8+azwT/QReOxgpAtj42BGX/Qwd+h9z/oWytoNXb4P+mKq9D2XtA2skoW5u4Q9TFt4L3rdrn8M60Eu1zn4WCkdUChWqzbIH56IJzoNXbUYM45dgL2sy2glTfl9Z7cuxj5Z0kum2wEELUgYlKbWVw2XWq8W3evJkrr7ySZ599NqH2999/Pzk5OVWPzp07p3iEQjQ/5cXlPHLeM2g0ZqjmUhwzZLLi11VMvm9ak4xNBxaji65ky531EFUXm6FV6IJz0drfOINR2Qm30/7v0ZuHgfd9rAAJMP9Fl41FF5yBNuMtaYrBaEPM5Uo1GxP917QN7HvWuquvK17D+oxjBCi+GeCZClgV1ZXrYIycuzByH0FlXpJYkOFfFCHIqBSC0AoouRV0MTUCjOptgr+DN3YtDGVkoTLOwsh/ASP/ZYysqyTIEEKIFqLZBBpaa84//3yuuuoqdtst8n7yW7vxxhspLi6ueqxatSrFoxSi+fnstbn4vYGo15VmyGTm858SDAQbd2CALnsxxqshCK0EbyMtkXQdBrhitzE6oO27hoOjILUvkE0ILkWXPVHnYSgjE9xHk9iv3xCorbfSBbCBkYPKfbT2Ib7ZRL6wr0mXT6hRWTtZ2vMWsQMmEwLziZqHAoCB9r5f5zEIIYRo3prN0qkHHniAQCDA5ZdfnvAxLpcLlyvOhYMQ27gVv67CZjcIBqJfXJYVlVO0sYTWHePVJmg4Wutw5eY4F5q+z1Bpx6R8PMrIhMxL0GVjozdy7gfed6wta6MyoeINTJUF5iYw8lFpJ9TI64g7lsyrrGRvKuK0NCDjTBQGumKKlWNi5ELaSaj0s1G2trUP0bVzNiIKLQddBKqOu0mF1hA/oIn1bx9+favaIUII0RzoFBfV09vJ0qlmE2g88cQTlJeXk5dn/dELBoN4PB5yc3P54Ycf2HnnnZt4hEI0T2kZLhK5Me1Ka5hk5kRpM9qSmepM0N7GGI4l41LrQrx8HBHH5n2vWt2KWDxQ/iSVd/R1+dPotNOsBGoV/9eqsu+IznsSCs+P09JE2XZEpR2DyrwogXEBzt7gXUdi9THq8YfOyMd6/7H+jW1YwUa0sdisXB0hhBDbpGazdGrdunWUlJRQVFREUVERM2bMYOedd6aoqEiCDCFiOGjY/jG3sjVsBj0H7E5WXmYjjgqUb2ZiDW2JzwTUl1IKI+sqyLy0gXqslnPieRNd+kjCRxquQ8Lby8b4NawywT0w4kta+60tY72fo4OrtxySfiYJBRm2HuHtY+tGpZ1I3CDD2S/OWEKo9NPqPIbmSOugtdNWYFnj5R8JIRqcqVXKH9uDZhNoCCHqZvcDdqHXYXtg2CL/OJumycibT27kUYEOriShXzHuQ1M+luq0DkHFG6noGSomoc2ihI9Q2TcRK+FbZd1Yq9K41hpd9gJ6Q3904dnooovRm47ALDgfHVyNcvaBjPhLUFXG+dYWt3XlPAgc/aKM3WYl32ffDY7eUdoA7pPB0afuY2hGtA6hy55HbzwEvekY9OZj0RsOwiwdKwGHEGK71WwDjcMOO0yqgguRAKUUt799LXv23xUAm92GzWFDGQq70861Ey6jz+BejT8uI4dEluYo+06pH0x1odVgbkhR5wHwJVJt26Kc+6LyXwF7j5ovGO1QOQ+j0k+tdYwufRBd9nC1LWPBqm7+DbrgNHRoPUbWlZB1O7VXx4Z/5aedBWknJTzOiGNXBirvOXAfxZZ/5/B/7TujWr2OYe+MynsJ0s8CqtVyMfJRmWNQOffWL9hpJrTW6OIb0GWPgLm52gvFUP4MuvAyK8AVQrQYUrCvYTSbHA0hRN1l5WXyvzl3smTeH3z19rd4y7zsuEcnBp01gOz8rKYZlPtoiJV4jQJnv6gF21Kn7jstJdS7ZyrYdgTH3gldRCvnfui8yVAxDvzfAw5wDQRX7ZkeHVwJFROi9BQCsxBdPg6VfTtGxkh02tFQ8SbaOwt0Bdh3t2qBOPdP+ALfSur/EF3+CgQWAzZwHWzNiDj7oHIfRwfHWEUIdQAce9d478pIR2XfjM68GkJ/Wcfbd0YpR0LnbxH8X4P33SgvavB/Ad5ZkHZcow5LCCGamgQaQmwjlFLs2X/XqpmNpqbs3dHuE8O1KLbefUgBCpV5RVJ9aq2tKtZmARgdUI465G/ZOoHRquad54bkn48uOBVcR0Du4yhl7YynzTLwzkAHlwJulPsIcPSFwEIovAB0tdocgfnWFrp5T6NcB1c9rT3TiJ2AHYKKaeism1HKbgVxmRejMi+u01vRWqNL7gbPq1izISbWrM3naN9nkH0PKv1UlL0T2EfE7EsZ6WD0jNmmpdIVU4j972KgK15HSaAhRIuR6jyK7SVHQwINIUTKqJx70djBOw0ruDCAIKhsVM4DKOd+CfelvZ+hSx+wam9UPmffE5V9K8q5b+KDCq0m8YJ5dRG+2PR9ji6+A5V7vzX24musWYXwr11dMQHse0JwOeCh9kyLF114CbT+AGXfMdz1+gTO77GCFpVb/7fi+yQcZEDNYNF6j7rkVmtWqnJ826vQcmInxptWAUMhhNjOSKAhhEgZpZzWhXbocqsCtC63dplyD0apxLfb1d5Z6KKrar8Q/A1dcBbkT0oo2NChjeiC0xOo3aCo/xIrE7zvYHqHQNHlbLlQr1Y4MfhrjOOtSuq64tVw0jhga5XAeR2gMuo04lojKJ/ElpmMSBTa8wYq69oGOV+LpSrzkWJ8z6gmWsIohKgTM8V1NFLZd3OyfWSiCCGalLLtgMoYhcq8HJV2bHJBhg6gS+7Euojb+kLOBELoknsS66tiUjjIiFFILv0scPSiXjUmqo+v7PHKs9fh+BB4P6n6SrlPIPadcwOM9ugN+2Gu3wNz0zB0xTS0jlc4L4rgYmIX3QuBf2Hd+t6GqLTjif3va6DShjbSaIQQovmQGQ3RbK39az2zX59L8aYS2u7YhkFnHkJeu9ymHpZIgtYazH8B09pJSdVhyZLvq/iVuoO/oAPL4udseKYR+8LZBqHNGK2mWtuVbj4Fgr/FOSYWBcGl1G92ZMvWqMqxWzjv5b0IfYZnHsw1VI03+Bu65AbwfQG5j9bh84/3J0JBEkHjNst9ApS/AKF11A4EbWDkQfrwphiZEKKOJEejYUigIZqdUDDEU1eOZ8a4TzAMA8NQhEIm4298lXPvGsGIG4Y19RBFHFpr8ExDl4/bsjbdaG3NFmRckNyOQ+a6JNrFCTTi1rgIgd4U/n+jnkEG1H/5lc3axakalXMf2siBitepsQyr6lzVxxv+f9+H4DkQ0mMnbNfiOhy8M4g+i6JRrsOT63MbpIwMyH8VXTg6/D1TGdCFwLYjKu/ZJthdTQghmp4EGnXg9/r58q1v+fXrpSjDYJ/D96T/ifthdzTdx7lpzWZmPv8p332wgFAgxJ79d+X40UPo1rNLk42prl684VVmjvsENJghEzN8jRMyNeNvep2s/EyOvWhw0w5SxKTLHrHu8FZffmRuQpc9Dv6fIO8ZlErw5yXRC7Q47bT2hHebihW42MDWOdxeU7/lUzawdQGzFPTGOvYRClf63kIpByr7FnTmpeCbC9qLDv4OFZNi9qTLX0ElGWiojFFo7/sxWhhoR08rO8EsswI5IxdlNG4V+uZA2TpCq+kQ+BH83wLaKkboPHCbqBUixPZGZjQahgQaSfrtu2XcevwDFG8qwWa3gYL3n/2INp1bcd8HN9N1z86NPqafZi/m1uMfIOAPYoasO5grl6zi/XEfc/kT53PiZUc1+pjqqnhTCdOfnIWOcSN40l1vctT5A7HZUrlz0PZn3fJ/+f6Dnwj4AnTv1ZV9Dt8Tw0g+jUsHfgkHGVD7jr4G/xxr6U+iBeNch1nJzbo8SgNl1a2w7xl5PGYpumwseN4E7YlzshAq7WS0WQCFlxI7H6Ly9LmgS7dqawPlRuU+atWwKB8Xv59IMi5AuQ6KfFojH9JOAEAX/ZfYSdsaQn+hta9qu91EKMce6OwHoOS66I0KL8R07Gf9uxICDLRrCCrrStTWhQi3cUopcPa1HkIIISTQSMbG1Zu5fshd+CqsNdOh4JYLi81rCxkz8A5eWjqWrLzGu5tXtLGYW094EL8vgDa3XNSFgtYFx1NXjGenXl3Y6+DdG21M9fHdzAUEA7Ev7javLeT3H/5ijwN2aaRRbds85V4evfA55rzxNQqFUmCamo47tePmKVezS5/kKnfrijeIXVNAoctfRSUYaCiVBplXo0ujJ3yrrBsi3jXWZhm64AwILiP+EigF7uPQ9t5QcBoEl8Rpb1izKK3egopXoeKNcMDhgrQTUBkXoexd0L4v473FyGPJeRDlPjHB9g7iz74o6rKtryIUYwGYaVUo98+mxtIt3ydo/5eQ/zrKsUfS5xRCiKYmMxoNQ3adSsJ7T3+Ir8JfNWtQnRkyKdlUyscvz2nUMX04fjZ+r79GkFGdzW7w9mMzGnVM9eEp8ya0zMBTGu/OtEiE1pq7Tn6EL9+cB9r62gx/L61fsZExA+9g9bIEcyQqBZcReyZAQ+jv5PpMPwuVdUu1bVvD3yNGPir3cav4XSQVLycWZKhMyLgUlfMQKvBNeLelOLMZRj4q72UMW0eMrOtQbeej2i5EtVuEkXMvyh5ethhaSXIX+AoyLsRIG5rwkhvlOiTOeG3hJTzJ31vS3hnED2K2/v0TspZ0Fd+U9PmEEEJsOyTQSMKXb82LGGRU0lrzxVvzGnFEsOCzxVGDDLBmNhZ8urgRR1Q/nXfbIbw2PgYFnXbp2DgD2sb9Mncp8z9eFDV49nv8TH1oesOfOMk6D0opVMbZqLbfoHLHorJvQ+WOQ7X5CuU+OuIxWmt0xevEDjIMcA9Ftf0GI+s/KGVDez8ifmCgoNWHKMeWWTWlFMpIR6mtfq2qNBLL9Qif030yKvOqBNpX4x4CRkeijzuEyrgwuT4rmUXULandhOASdCBWrRAhhGieKmc0UvnYHkigkQRPuS9uG2+ZtxFGskXci/IE2zQX+xy+J+26tkEZkX8ADZtB38G9aNelTSOPrGXwlHspL6lI+N989utfYbNH/zUQCpp89vrc5L6HdPyfE5z9E++vGqXSUO6jUekjUe7D4+xe5QNzU4zXK/lRyr3lS11B/AtrjTIS2zlLuYZQc3eoCIy2kDEK1WoGRu59Sc88KOVE5b8ERuXPReXPjwEoVPYdUXM94rJ3p16V1INJzl4JIYTYZkiORhK699yRnzaWRJ3VsNkNuvdq3F2e9j5kD36eswTTjDwmw2bQc0Dzz89Y9fsaZjz3CX/8+BfZ+ZlsWr0ZrVSNz9qwG2TmZHD5U+c34Uibp7nvfMfUh97lt++WAbDDzh04+apjOfbiwRETulf/sZblv6xixa+rqpZKReP3+HnsoucwDIM9+u/KoacdiCstckKx1p4EchsAlR6/Tb05sXIXArEGYi2bqv6MvXv8+/dGW8AdrxXa9w26/MW47dA+lNEKwsnTZnA9lP0PfHNAB8DeFTIuR7mPiLqcStm7QZuP0RXvg+9T6zjnHqi04Sh73TepUOnD4+w8FbeDuh8rhBCiRZNAIwknXHoUP37yc9TXQ0GT4y85shFHBEdfeASv3z8NM2BGvAlrhkxO+s+xjTqmZL379Ic8deV4DJuBGTStm7Ea7A4b2lRorbE7bBx++sGcfcdptO/atqmH3Ky8ft80XrplMka1WaC1f67nicteZPHcpdww6YqqYGPtX+t59MLnWDQnueUsH708B6UUM1/4lHFjJnL3+zdETsY3y4g/GxArUbzhKGWg3UeH60BEWz4VQrmPqfpKm2Vo7DHaAxjWjEqc/AldPjGcwJ7AbIAuRpc+CMHlaOdAKL605hiCS6D4UrTncMh7tvbyLEAHFqPLngPfbCAERmuU2tfa0rc+HPuB+xTwvpX8sSodnAfW7/xCCNEENGDWa4vz+P1vD2TpVBIOPKEvg88+FKDGRUblMp9TrzmePfvv2qhjat0xn1umXI3NZsOotgSmcjnMuXeNoM/gXo02Hm+Fj4Wf/8IPHy2kYH1h3PY/zV7MU1eMt2pmhHfKqvzpM01NVn4mzy/+H9MKXua6ly+XIGMryxev5KVbJgPUmJmoXOr0+eS5fDHVyhvasGoTVx54E4u/+i3p85ghs2qXtbKicm448m42rIqwLMnIIf6dfo2y7ZD0GGr0oDXa+zlmwSjMf/tg/nsAZtFN6MDvNRvadyV60GCrqnMAoP0/oTcMgLJHY5zZAPtekHFu7PEFlqFL7w1/lURQ5ZlaO8iozv85uvy5mucKrcEsvhO9+VTwfbblfOYmdNlT6IKRaDPa1sARxq6D6MDv6MAStLY2Z1A596Cyrq+2NAtrJsjWLWZfKuMilCEzGkIIsb2SGY0kKKUYM+FSdu+3M28/PpM14d14uu7ZmVPHnMCgMwc0ybgOGro/z//8P959ahbfzviRUNAq2Df0imPoeUjjLJsKBUNMuvNNpj0xE0+pladi2AwOOfkALn/yPHLb5NRor7VGKcWbj7xnzWRE28lrcylLv11Gtz13bJT3sbVgIMiPHy9iw6rN5LbJZv9jekddNtQU3n/uE2x2o2o7460ZNoN3n/6Qw0ccxOT7plFaVB5zQ4NEmCETX4Wf95/5iPPvH1njNaWc6PSTrK1eY11gp9W9urvWGl16v7WjVPXZEe87aO87kPs4yn2ktWSp7GGqpsi25tgPlfcUSilMzydQfAUxZzJUFqSPRGVcYm25G2uMnslY93HqMnMT59+nfDw6YzRoD7rklvCMTYy+gr+hy59BZV0bs1utTaiYgC6fsCW3RWWg009HZV6Jyjgf0s+B0Aq0ZyaUj4fQcmp+vpU3OzSknwcZl8R/u0II0QzJ9rYNQ+mWlCkcR0lJCTk5ORQXF5OdnZ3Sc2mtKS0oQxmKzNyM7bryq9aaB856gtmT59a6njPsBh27t+Op7+4HpZj+5CxmjvuEjas3k5aVhrfMGzPRWBmKQ04+gFvf+G+K30VtX741jycvH0/RhuKq59Kz0xh1z+kMvTzyTkeN7T8H3cySeX/EbJOenca0TS9xYs7Z+Dz+xDqOcm1eXYfu7Zj451O1ntehDejNJ4G5mUgX2irzalTm6MTGEYH2foQuuiLKqwqwQ/5kKDiV6G/CQGVehsq8Au37Al14UYy2VnvSR2FkX5/QGM3Np0Ag+jLLemszD4r/C/7viF8fBFBZqLbzUMoZ8WWtNbr45ijLowxw9EXlT7ACSc8MdHGMn0fHAajcB6xK2UIIEUFjXq8lq3JsA2degj0jdTcWg+U+Zh/7XLP8DBqSzGjUkVKK7FZZTT2MZmHJvD+Y/frciK+ZQZM1f65n6sPv8fX071m1dE3VEp+EamFoXaMwYmOZ9/587h7+aK1rz4oSD09fOQGgWQQb7kw3ShGzkrrT7aSi1BM3yDAMRd+jenP6DUN57OJx/PPbmpjtvRWRd5dStrbQ6k10yb1WUnLlhbDR3rq4Tx8es18d+B1d/lL42ADY90ClnwXuo1FKoctfIXoVbA2EoPRhYs8omOiK19Hpl0DxjcRfLWuGx5NYoGEloqeQfz74k9hKW5dCaAPYO0V+PTA/Rg6GCYHvwfMuOu1kdNn/Yp8rsKBWgj2El/MF5luzIboIbJ1Qaaeg7F0Tfx9CCNFIZEajYUigIertwwmzYy7f0aZm2tiZ+L2BuDsc1aIUu/dr3ArgWmvGjZkY86b+S7dM5qjzBuJOb9plVAcP3Z8Fn0a/c27YDQaccgBpmW4cLjsBX/RtVpWh6LpnZ/Y6eHd26bsTa5ati7kkq3vP6MvZlK0DKu8pdGgjhFZYtSTsu6NU7MRo7f0UXXQlVQEDQOAndPGP4PsKcu6DwCJi38U3wwUB43yvmZvBOzPBLXCpsW2vDq5Ae96E4HJrtiDtGHAeUpWkrdxHoAM/xh9DnTjCCd9JJtWr6LkzCVVzr5iMcuwOodgBKPit8aUN3dK/WY4uuhz8X4fPo60+y59HZ4xGZV61Xc8KCyHEtkqSwUW9bfhnU9QL0krecl/yuQEKHE47R513eD1Gl7xlC/5mzbJ1MWcJKko8fP/BgsYbVBSDzhpAfvs8DFvtH2VlKGx2G8OuPAa7w84RIwfErZkx6Cwrz+j40UfG/Dc1QyYnXHpU3PEpWxuUcz+UY6/4QYZZgC66Gutit/oFb3gc3rfBO534v7YU1ra28drZoDRW4nd1Bjj2tsZZ9hR60xAon2AlX3vfQxdeiN58KtoMb4CQdpKV05GKX7H2PcJF9JIIMoz2YORHfz24PE5/GkIr0aF/EziZArPECi78C9H+Reii66rNwISw/k3D5yt/FjxTEnkXQgjRaKRgX8OQQEPEpbXm5y+X8Nq9b/P6fdNYMu/3GnkVee1yIl7oJqv6HU2b3cBms3HzlKvJad24axeLN5bEb6SgaEMC7VIsLTONhz+7ndY7WBeRNrvNCiYUpGW6uXfGjVVV1M+4+STSMtMiByUKjjrvcLrtZc1S7HHALgy/7kTrterFE8P/O+ScwzjwhL4N+2Y80wA/0WcBwsumXAcTd8tY10DiFskjDfT6BAdnotLPRHveQZc9EX4uRI2Zl+ASdOGV1kiNPKuAHinYcclcA7Z2JFVEz1yPLr4hej6UkUvcPwcqGyreTOBkGu2fh95wILrgNHTBqeD/hFizULrsWbRu/CWSQgghUkuWTqXAsgV/M/P5T1n522oystM59NQDOfS0A3G6U7xuOwXW/rWeO056mOWL/6m6QH3pFpOd+3TnjrfH0HbHNhxx5gA+e+2rqH0oQ6HjLZlS0GGndhT9W4zdaeegofsx7D/HVl34NqY2nVvHb6ShTed61idoIDvutgOvLHuSr6f/wIJPFhEKmux+wM4MPONg0jK37I7UoVs7Hvvqbh4e9TR/zP+r6nmH28GwK47hvHtPr9Hv+fePpFvPLkx9+F3+/nklADv06MDJVx/HsRcNavClLtofL3laW/Uksm4MLx2KxLDyAzKvstoGFhH9Tn1ZEqNT6OI7rNyCqEIQ+A7TvwDl6I1y9EQ7doOGXkJlbgJH7+RnAbzT0e6j0c6DUb4P0RWvQ/AvUBng2IV4tUNwHQGeVxM4kR18n8fpbyvmegj+AY7mX1xUCLF9kByNhiG7TjUgrTXjb3yNNx56typnofIiu2OP9jz82e20TeQitpkoKSjlor2voWhDca1lNDa7QZvOrRm38BHcGS6uH3w3P3+5pNbyKJvdIDMvE601JZtKY57v5T+eYIceHRr8fcTi9/op2lhCRk46Gdlb7j6P7nMdfy1aETVAymmTzZTV47A7Wmas/udPy1n+yz+40pzsO2hvMnMzYrYvLy7HNHXVDmueMg/z3ptPwfoiWnXM58AT+tY7X8Usuhq8s4hbLK/dEvBMRZfcTs2Eb6vKt8qbgHL2QpvF6KKrwnkB0ZLHU0TlgvtY8LyWmu7zJqK9M8HzRn16ofa2tFD7c7JZsxmZl0JVbZCGp/LfRDkbr+ZPQ9PaB96P0IGFgA3l7A+uAXGXDAqxPWrq67VYKsd28HuXpXzXqbknPN0sP4OG1DKvkpqpj176nDceeheg6sK88kL13xUbuPWEB3huwcMtJulx1ouzKVhfFPFiOxQ0Wb9iA59O+pITLj2Su967nrGXPM/syXNrtO/Ruzs3vnYl896bz7gxEyOex7AZHHBcn0YNMjatLeDVu97ik4lz8HsDKEPR79h9Oeu2U9mlz05c9sR5XDvwDkKYNd9/+J/u8ifOa7FBBkCP3t3o0Tt2sbXqMnK2BCLTn5zF+Jtew1vuq6qBkp6dxsUPn80xFw6q85iU8xDr4jkqGzj7WwnX6SPA2Q9dMRkCC0E5Ua7DIe1klJFr9WfkoPJfwvT/CoXngy6o89iSpovA83qKOjfA3h2VfSfaaG3lONQpiKr+c21a/WKr9v8KCIGtMyrvGfAvSHBeJoG9kWtxQAvefUr7F6ALR4MupPLPqq54BWxdIe9FlL1p6gAJIepOa4VO4axDKvtuTlrulVIzo7VmyoPTo/6NDQVN/l60kkVzfmWfw/dq7OHVyWevfhlzyZMCPnvNCjTSMtzcMOlKzr9/JD9+8jNBf5Bd99uJnfftDsDJVx/Hvys3Mv3JWVWzPZX/3bP/rlz3yuWN9K6sCtlXHHATxRuLawSE33/wE/M/XMh9s26m98CePPzZ7Tx15QT+Wrii6tiO3dtx0cNnc9DQ/RttvM3J+89+xNP/mVD1deUMVkWJh8cuHofD7WDwWYfWrfO0Y6Dsf+H6G5EunENW0bgwZe+Gyr4pgY79jRtkVEn2Yrvyl0es3Z8McA20thAGtC6s+/BqMdnyuZtgtIW0U61ifUqhdbycl0rJvm8buI9HGTnxmzZDOrgKXTiq2q5k1T6n0Cp0wVnQepZUSBdCbJck0Gggm9YUVFUKj8ZmtzH/o4UtJtAoKYy9hl1rKC2o2aZNp1YcNar2LlFKKS4bex5Hn38Es178jPUrNpDVKpOBpx/CvoN6YhiNty/Bc/99haKNxZhbLQczQyZaKx48+0leW/ksex28O88teJjli1dWVQbfpe9OLWZGqqH5fQFeumVyzDYv3vAaA884GJst+eUiSrkhbwK68FwwKwODygtvE5V9G8rVP+H+dHC5tbzK/23SY2kSRidU5mgrKbr01iiNTHAfCYA2y6DiLVK2JMzcBOVPg3JB5iUox25oR+9wIcJIgZDN2kJXlydxEsOaMUmwEGJzpCsmgfYTLTjGXAfe9yFO/RghRPNiojBJYY5GCvtuTiTQaCCJFJVTirjbwDYnnXbuQOH6oqjb0ho2g067Jlf9t/veXbjsifOSOsbvC1C0oZiM7LQaS3jqonBDMV9P/z7qe9KmZvPaQuZ/uJB+x/YBoFvPLnTr2aVe590WLPjkZ0oLY19EFqwr5Je5S+l16J5J96+1tnZTyp8Kvi/DCd8+sO+FSh+RVGE3HVyF3nwa6GQSvpuY3gRpx0LBOUTPKVFQ+gjafRw6uBxrl65UCc/2lT0K7sEo+06onEfQBSMizDoZYOsC7qPCS7lizWqEZ2xULqSPQGWc32JnMwCrFkvMrYEV2vth3EKVQgixLZJAo4G06dSKnDbZMbdGDQZC7NZv50YcVd1sWrOZ9cs3sP8xvVk059eo7cyQybH1WJMfT+GGYibd+SYfv/y5VdVaQd/BvTjr9lPZ48Bd69TnmmXr4tbzMGwGK35dXRVobEt+/nIJbz36Pj/N/gVtavY6aFdOvvo49juqd9xjSzbHTuavahcn6T8S7ZmBLn8egkutJ4yOqIxzIf2sOiXT6rKnwkFGC9oyVXvQvu+snJPojcD816pJEfi7kQZmQ1e8gcq+CWXvDK3fR5dPAs9bYBaCrR0qbQSknw4E0Z63w0UQt/7sbVbOQqu3w7OC7m1jdlB74zVoWQGvEAKQXacaigQaDcRmtzH08qOZeOfUiHkNhmGQ0yaLg4bu1wSjS8zqP9by7H9f5vtZP1XdkHRnuPBV+Gvtv68UHHLyAex3dPwL1LooWF/IlQfezMbVm7cEBhoWfLaYn2Yv5s7p19PvmH0T7q94Uwnrl29I6GJZm5r0rOhVlFuq6U/O4un/TMCwG1XLxn6a/Qs/fvIzZ99+GmfdfmrM49t1bZPQeRJtV8ksHWst0ak+jWyuRZfeD/4FkPt4VcXtRGjtsZaqtKQgo5K5OaFm2r8QyseldixVQtbWs2HKyEdl/Qey/hO5ef7r6KL/QPAXtuxmZYKjDyr38W0vV8G+U3g5WbQbGDaw79aYIxJCiGZDAo0GNPz6E/n166XM/3hRjdoRht3A5XZy5/Trm+1ORauXreOKA26iotRTY9WDt9xKcHSlO/FVWMs0sltlMezKYzj9xmEpy6148YbXagYZYWbIRCkrj2LKmudxuhwx+9nwz0bGXTuRuW9/hxn+97ASW2Ms7VA0fDG6etBa8827P/D24zP4bd4fKEOxz8CenHrN8fQe2DOhPpYvXsnTV1lJ3NVzUyo/34l3TmXvw/aIuuTp759XWpsdxKAMxY67d6raAKC68pIKPnv1K/5auByHy0G/4/rQZ/DeqNBv4SADai+30eD7ELwfQNpxCb1P600VEr9YX3OjwNYDbAnuBFbxEuCL28xapqSpXx6HYdXaSJCyd4ZWb1sX34EfreOdB6AcWy62tQ5A8E9rXPadrPycFkqlj0QXL4zRIoRKH9FYwxFCNBDZdaphNM+r3hbK4XRw9/s38OmkL3nvmQ9Z9fta3BluBp5+MEOvPJoO3do19RCjevH6V6ko9UTPXdAw9ut7cGe46bxbRxzO2Bf49VFWVM7nk+fGGIumtKCMb6Z/z2HDD4raz4ZVm7i8340UbSypMcsUK8hQhuKoUYfTeofmUYwPqKrNUrmVLMCPHy/ih1k/MfqxcznpP8fG7eO9Zz7CZjOi5gjZ7AbTn5wVMdD448e/+O+A2wj4o1+8G4bCsBn855kLay2H+ea9H7j/jLF4Pb6qJPF3n/6Q7nt34bFZBm4Ve5clXfEqKplAQ2XTcHUzFBjtQVeALm6A/qLRqMxLwdkLrbJAx5p5M+K8Xo1Ki7FsxwW2Hay+zE1Ez6swUeEE9FqjNssh8BPoADh2R9naW6dVCpy9rEf19joE5S+gy18KbwULqAx0+umozP+gVOr2rE8Z93Hg/Rh8n1LzMwzvIpZxMcqRfM6SEEJsCyTQaGB2h52jzhvIUecNbOqhJKxoYzHfvPdDzK1s/V4/q35fy5Hn1t5RqqGtX7GBYCD2shebw8Y/v62J2WbCza9TvFWQEa0vtCYUNDl8xEFc/tQFSY85VX78ZFFVbZbqgVfl/z979cv0HrhX3GT1X+f9HnMjglDQ5Ldv/4j42uMXP0/AH4yZ27Jzn+5c8ui57HVQzSUiv8//i7tOecQ6VtfcNGHlklWs/W053feI9W9tQnBZjNdrU0Ym2jUIfJ9Rv+VTBmBH5T2P3nxKgod0AnN10mdSWdej0o7FrJiaQBCRRAAVdQcoG+S/iuHshQ7+id40FAhQO9iwWcGI+6ia3eoAumwslE8CPOFnDbTrCFT2nShb7cKkWmt08fXgfa/2GMsnoAO/QN54lErdTYxUUMoGuWOh4hV0+StWlXMAew9UxoXgPrFpByiEqBPJ0WgYEmi0YH6vny/enMcvc5eiFPQZsg/9T+iLzZ5c8uym1QXxL8btNtYv31Cf4SYsLTP+MgodMmO2Ky+pYM6Ub6qWS8Wyz+F7sdv+PTh8xEF02aNzUmNNtelPzaqRU7E1m93g/Wc/5spnLozZTyJL9myO2t83f/+8kmUL4icdRwoyAKY+NB2wZsS2FgqaFG0KorVCqVhL2ZJfVqMyr0T7vsS6KE+2roMdCILRCpX7ONh3IbHdndJQrd8B7wx0yd3h53Sc8ytwD0VlnI/p+w5Kom1rW1cxzl0+AZxjUfYekPcCuujycJBT+b0SBFs3VP4LKOXc0qPW6OLrrCVtWxf9881GF/xuJXxvvZOUf17tIKP6sf5vwfM+pJ+U/NtMkDbLIPQ3VoHAnVGqYf4EKmWHjPMhfZQ1O6TsoPK2jWR3IYSoBwk0Wqgl837nxqPvpaLEU/XczOc/JSs/k//NuZNueyVeiTYrPzNuGzNkkt0qq05jTVbHndqz4+47sGrp2qjLnExTc9Cw6EXzNq0pSHjL4dYd8zn3rua5hnrpd39GDTLAulhfEmUmoroDju3DXz+twDSjbFVsNzjwuNp5KWv+XJ/QONf+ub5WoKG15ut3f4g5k/L1h3n0PiTWjjw2cMdfGlaLfWfIugFKHwYSqetggEqHtBEoIwPsu4LrsKoLUW3fOTyzEuPCPX2EdXGdPhJcR4DnLXTgV2urXoIRjlWAHZV5MTq0GQovjN1/0mJV6A6B72O09qOUE+U6ENrOBc8H6MBiUA6UawA4D6qdiB/4Kbyla5R+Q6uh4jXIvLTGK7piKvGKEWrP66gkAg1tFoBZAbY2oD1W/RWjVa0gR5tl6LL/heuOhHNbjNaQcSGkn9tgAYFSBoSLKQohhJBAo0Xa8M9Gxgy8g4Cv9pr50oIyLtv/Bt5Y8zxZefEDCIB2Xdqwe7+dWfrDn1FnNpRSHHLKAfUZdsKUUpx9x3DuGf5oxNcNQ3Ho8P503Kl91D4ycxNNXlX8uXA5t57wAIbNYN9BezPorAFkZDePnXHszvg/ovES4gGOuWgQUx95D7/XX/vfWIGhFCdeflSt4zJzE/scMnJqtzNDJqE4S+A+ezOXc64rIDvXS+0LUAU4UelnJjQGbRaAZwY6+Ad4PwO9mS27HsXhPs6qgG2PHKCr9LPQMWcbDFTG2Vva29pD5uXWpb5/EbrwgnCOR/ULWicq7ymUvTu67FkSS+5OhkHspWMhK/ckPFuhVBqkn4zi5Ji9as/bxA4YTHTFFCvnpMbplscZjwnBf2Keu2oMvm/RZU9C4IfwM9Vzcgy0ayAq82qUY2e09ljVuYO/UWPZmbnJ2tksuAqVc1tC5xVCbD8kGbxhNF45ZtFgXrt3WsQgo1LAG+DpKyck1eeoe08HrDv8tSgYesXRtO6Yn1Sf9XHoqQdyxVMXYHfYUIbC7rBhs1vfrv2H7c81L46OeXx2q0yy8uIHG1pr/lq0gm9n/Mi89+bz1JXjObPbpfz2XXJ5AaliLYWL/mOqDMUBx8ffIat1x3zunXkj7nQXytjyj2wYCofTwW1vjaHzrjvUOq7nIbuT0zr2TFZalps+Q3rVet5mt9Ghe1tiFT/1ee18PutCMDpEbpA+Emyxl7NprdFlz6A3HIwuvRc8U8NBBiSWz2AH/zx0xWR0aF3kJmkng2sQ1pup/oasfxuVfTvKVvvzA1DOXqg2n6Oy7wDXEHAdgcq6DtX2S5TrUOs9+L6iQWcz7L3j96cyQdVhljK0jri5L+bG2s8ZecT8ZgAwsuOeXntnoQvPCe9oVXXCmv/v+xxdcAo6sAQqXofgEqJ+L3hetfJDhBBCNDiZ0WiB5rzxddw2X7/7Q9w21fUe2JM73r6WRy98luJNpdYOR6aJzWbjpP8cw/kPjKzrcOvshEuP5NDTDuTTSV+y9q/1ZOZmcNjw/glV6X75limUFiWyZIaq67HKZVoVxR5uPOoeXln2JDmt41/4pNLQK47mgxc+RanaeQ6GoXBnujn6giMS6qvXoXvy6vJn+HDC7HDBPpOeh+zB0RcMJL99XsRj7A4759w1gicufSFqvyNvPgV3euTdgk687GjGjZmIjnbRqzUHn3oCGB+DGWGnqIoX0cqOyvpv9DdW8Qq67PHor8cVtC6MK15Ge6ZC/iSUY48aLZSyQ+4TUDEZXfEKhP4BlLVta8aFKFf03c/ASlAn/QxU+hlAOFfA+wFmaLW1zEd7Yh4fudO8LTs3Vec4HHJuhk1DYh0MrsOo070mozWxZzQAI7f2Gd3Ho/3fxOoYlTY05qm1WY4uvjH8VawgMgTahy6+OZx3ErtSua54E5WzV8xzCyG2LzrFyeDby4yG0jELCrQsJSUl5OTkUFxcTHZ2014gptLRrhFxd2VCwSehN5PuO+AP8O2MBawLX9j3H7ofuW1y4h639q/1fPzKHDas2kROq2yOOPMQeuyTYE2ABuYp83BahwuraoDUhTIUF9w/ktOubfodY76b+SN3nfo/Av4g2tRW0AFkZKdz3wc31blKejKmPvwuL906hVAgZCWnh0wMw2DkzSdz5m2nRF3jHvAHuOmY+1g059caS7Yqt+q98ukLOO6sleiyR4l14ahaf2AlLW9Fax96w0GgS+r9Hi02MNqh2nwWtSK51hptFoJvNng/tJZE2bqj0k8Dx75x1/vriqnoknuwlkrZsN53XbbijZKDYd8DlT8BKt608hJicR6Myn3SykuJQ2sT/N+gK6aA7+PY40o/C5V5lRVgVR3vRW86MRykRagabuSiWs1A2aJvLa0r3kKX3BR3rLX6jjcD4+yPkf9ykv0KIeqqOV+vVY5t37f+iy0jdVtuh8p9LDjl0Wb5GTQkmdFogdJz0inZFHsLzMp6BclyOB0cclK/hNtrrZlw0+tMeWi6VbxPgULx1qPvc9jw/lz78uVRcwhCwRCGzWjwnVn+mP93vYIMsKqDz3t/frMINPod24dXVzzLRxNm8+s3v6MMxb5H7M3gsweQkZN4IbX6OO3aEznq/IF8MXUem9cUkNc+l0NPOzBuEOpwOrh35k28/egMpj81i4J11h34PQ7chdNvPIn9j+6NueEwYl9oh+84Z99Y+yX/dw0YZACEwFwL/q/Cd/y30NoPFVOsGhDmVlsrB35Be9+BtOGQfWfUSubaOwtdcku1Z+pTWDDKPaLgb+jC0aj8KSijDbr0wcgzH2AFDsU3oPKejH2m0Fp04YXhhPhYv1vCP8sVE9EVE9GOvqjMS1CuAVZRvvxJ6KIrrITy6lXDbd2sfJUYQYY1jr+p2hUsYS6gIsbrRnhZlxBCbKGJvGNiQ/a/PZBAowU69NQDef/ZWHcUoc/gvRtlLNMen1lVMXrrOgtfvDmPjNwMrnr2oqrnPOVepj8xi/ee/YhNqzfjdDs4bPhBnHbdiXTZvVODjCkUo95DMgK+QIP0s7XfvlvGzHEfs+LXVWTkpHPoqf05/IyDScuIvo1rXtscRtwwLCXjSVR2fhbHXxJrOU5kTpeD028cxvDrT6S0oAyHy0F6VhoQXq5mro3TQyh8F7y2qDkV9WJH+xehqgUaWvutC23/t0T+8xC+Y+55A+zdIWNU7bFqjS59jNi7QUH9iw1q60I+8BPaNQBK7o3R1gTfR+jgCpS9a+TetB9dcI61mxQQe3Zgq/cVWGAlwmffhUofgbK1RbV6A7PiNSifCKGVWBf6WRD8A23rFvPGg1Lp0ZfhRePqD77PY4zbRLmTKAgphBAiYRJotEAXPHgmH708B78n8t7+SinOu++MlI8jGAgy+f5pUV/XpmbW+M84547TyGuXS0Wph2sOu52/Fq2oWkbj9wb47LUvmfPG1zzw0a30PGT3eo+rR++u2J12gjEqWYO1PCraLluG3WD3frvEPD4UCvHdzAUs/W4Zhs2g75Be7HnQblEvlLTWjBszkbcfm4HNblXpVkqx4NPFvHbv2zzy+R0pqx6/fsUG3n3qQ+a88TXeCh9d99qRE0ZbOTCGUf89IeZ/sogPXviUzWsLadM5nwEnH0j/E/erUb/DMIxaOS9KKbRKt3Y/ispmJS5vRXs/h5K76j322kJYxevCsxie6eiyJ8BMrI6MLn0MbbRFuQ6tsXSI4DIIrYhztAL73hBcCUSZhUiIQnumg/cjIF4BQMNaBmY/L/LL3o/CAUH0c2F0DAeMW/88WQGTLrkTXANRtrbo8olQeg9blo0BgUXooish/VzIujF6sOE6EsqeiPN+qg8tG7KuDc98VRBxyZZ9Dwgn5QshRCUThYq3gUU9+98eSKDRAqVnpvHsjw/yn4NuoaywZsKzzWHj1qn/ZadeXVM+jqXf/0lxnCVcZtDkuw9+4qhRh/PKbW/w988ra13ch4Im2tTcder/mLzquYSKy8WSnZ/FPofvyfyPFkVt06pjPpvXFkQfd8jkuEsGR339z5+Wc/uwh9jwz6aqyuKv3fM2O/fpzl3Tr6P1DrWXgMwaP5u3H5sBUFVbojJFatPaAm4+9n7Ou+8MZr/+FYXri2i7Y2uOHDWQ3gP3qtfysiXzfuf6IXfj9waqZp2WfPM7v3z1G3OnfctNk6+q81K7v39eyW1DH+TfFTV3GfrijXl03rUjD35yG206xV4Og/t48LxF9DvOIVRazVoaOvgnuugy6rf0KBoN5RMwzSLwf59AcLA1LxRfjcaJdg20LnBD/wCJVLxW4DoQo/VUzIKzwP8DdZvd0OD9OLylbgLn1NGXGmrvR8SeZdFRgoyt2njeRrsGWTuDATX/vcN9V7xszUBstWytaqSOndGuIeD7NMZ4qrXPHI2yd0Pnv2ot2Qr9gxXgaOt4Z39U7v8arHCfEEKImuS3awu1426dmLruBeZO+y5cFC3EXv13Y/A5h5Kd3ziF9XwV8fMglFL4PX58Hh8fjP+s1vKqSqapKdpQzLz35nPIyfWr16G1jltozu/1M+zKY3jniQ+qEpOBqpmGyx4/L2qV8A2rNjFm4B14yrwANWpF/L1oBdcecSfjFj6C012zmvLUh9+NumrGDJqsWrqGO096uGo8ht1g9utzOfikftw8+ao6BWB+X4DbTnwIv8dfo0p65fv96u3vmP7ELE6+OvmlIyuXrOKKA27E7428xGz1snXcdMy9jFv4SMxZE5VxPtr7Xvhid+vvDxvY9wTnITWe1eWTSG6Fa7zlSlsLWtvk1osffB9WO3ciwaIJ5c9hBldYW/v6v6/76XX0QLqmkFWgMGo/5cS/qI//2ergsvCsUKz6HjZ0+as1lq1tTeU8hC4eEw42Ykg7FdKtWRrl2B1af2xVJw8XJMQ5AOXYOe64hRDbJ6mj0TCkjkYL5nA6OHzEwdwy+Wpuf3MMJ199XKMFGQBd9ugUf4cdrem6V2fWL9+AN3xhHo3NYWPZgr9rPV+8qYQpD07nygNv4uLeY/jfBc/yx49/Re3n9x/+ZN1f/8Y8V2lBGX2G9OK2t8awx4G7YLMb2J12+gzpxcOf3c7QK46Oeuy7T87CU+aNGDSFgiar/1jHF2/Oq/H85rUFrFm2LqFr3cp+KyuCf/3O97x0y5T4B0bw1VvfUryppEaQUZ3WmmljZ0atGB7LhJsnRw0ywFo6t+KXVSz4dHHMfpS9KyrvlfC2qWDd/wjPsDj7ofJfrL0DlO9T4u4ktOUM4Ir+75l6eqv/JtDe9xGUPAZZt2F9HgbJ/bq2k1hgo8BoG3vpkH1nYieAJ0KBcoP/Z+IWEQz8HLsnIx2Vfhax75Mpa8lXtRkdpQyU6yArOT3jfAkyhBCiEciMhqiz1ju04oDj+/D9BwuqlgJVZ9gMOu7Ujp6H7M765fHXt2tT15gFAPjjx7+4fsjdlBdXVC25WvnrKj6cMJtz7xrByFtqVzEuWFeU0PgL1hVy9PlHJLXLFsBnr38VdWYGrNyPOVO+ZvBZWy7eYrWPR2vNu09/yJm3nkxaZlpSxy6Z9zs2hy1mhe4N/2yiaENx1FoakZRsLmXee/PjtlOG4rsZP9I3QkG/Gu2c+0CbOeD7Ah34BaWc4Doc5dgt8gE6yUT9rGus2g6e10lou9MmZ4K53Fq21eZTKBgVrqydKIPElpXZUbmPR93KF0ClD0dXvBynm93CO1LFWP7mHoIOJvAeVOwlZlp7rWVQMd+ftupneN6GjPPjn1MIIbZiaoVK4axDKmt0NCcyoyHq5fInzye3bQ6Grea3ks1u4HQ7uPG1/6CUon23tuywc4eYN1nNkMkBx/Wp+tpb4eOmo++josRTI6+jMqh5+bYpfPNe7cKE+R1yExp7foe6bWlZURK7uJo2NWVbFQtstUM+ee0TG1ckvgofv32bXLXyBZ8tZt7782MGGZW2/veLp2B9EYmW4El09y6l7Cj3ERhZ/7HW1kcLMgAce5PYXXYD3Mdi2Dtb1bvzxlt371V7wBn36CZXMRFK/hcnGXtrCoi8UURNdmj1BsoZu7K8su+Eyry6Wt9bnct5cHjmJdryMJu1NMt5CMo1MEqbam1d0XOjAPDOSnBLY432zk6gnRBCiFSRQEPUS9vOrXlm/oOccOmRuMOFbewOG4effjDPzH+QXfrsBFi5GmfcdFLU1SOGzWCfw/eiR+8tRf7mTPnaWvYTZTbAsBm8+ch7tZ7fdb8edOzRPuayrpzWWXXeArjTLh1QRvS+bXaDzrvtUPM5m42TrjymXkndoWDid+FnPv8J1w++i01rYq/TV0rRZc/OSVdAz2md2BI9bWp67Ns9qb4ToTLOIqFZCddhqBwr+VgphXIdgko/FyghsYvxpqbBN4PkEsITXKKVcTGGI7Fq2CpzNCrncbBX2xXOaIPKvBqV9xyGqy8qdyxWzQqFNVkenjC374rKm2DNmqSfHN5BLNKfHgUoVMaZMceiA0tIfDK+JfwbCyGaI61T/9geyNIpUW/57fO4bOx5XPK/cygvqSAt043DWXv5w5BzDuPflRuZeMdUDJuBNk0Mm5V8vUuf7tz65n9rtF/4+S81ErW3ZoZMfpm7lFAwhM2+5e62UopLHx/Frcc/YFXRjvDDfMmj59Z5d6vjRx/Joxc+F/X1UNDk2Itq35U95ZrjWTLvD+a9Px/DUFV5E7G22a2kbKpGEBbLhn828sSlLwDE7VdrzfDrTkw6AMprl8u+g3ry02e/xJzZcKe7OGLkwUn1nRDnAEgfBRUvUXNHpHDitaMfKvtalGNLMKm1Rvu/hsJLaFkXoIn8NUq0iF142ZjraFTmZUmNQqUdA64B6MCvgGFVQTeq/dy5j4S2/cH7HjrwGyi3NYPhPLDq+0sZ+ZA3waqtUWtWwonKfSJiBfiaA0lk9y4AGzhiL9kTQgiRWhJoiAZjs9viJqOfddupHH76wXw4/jPW/Lme9Ow0DjutP32G9Kq1M1GiCcqRLnT7HbMvt79tJY6XFpRVPe90OzjlmuPZtHozZ/e4nMJ/i8htm8PR5x/B8aOHkJVXu17D1gaffShz3vian2b/EvFCfugVR7N7v9qJpnaHndunjWHOlG9475kP+WfpGtIy3WhTx5156LbnjuS1y407NoAPXvwMVGK7LI24fiiDzhyQUL9bO+++kVx18C1R65UoQ3HL1P8mnVeSCKUUZN0Azn2tSt2BRYBhXdRmnI9yHVijvfZ8gC57LMklSC1JAkGGagXO/VDpp4HzoFrBpQ4uR3vesgrzqVxU2nHg6GvVOjGL0aWPgmcaEN5tztYZnTEa7ToM5f8atB8cu6PSR8ZcHKWcvaDN5+B9F+37BjBRjt6QfooViMR7G85D0eUvxn+/mKj00xNoJ4QQtcmuUw1D6UQXWrcAJSUl5OTkUFxcTHZ2cktBRPPz7tMf8tSV46NeLytD0WOfbjwz/8Far4WCIe4e/ihfv/O9daEU/javmiHZ6jpcGYp2Xdrw2Fd307pj/Isdvy/A6/e+zXtPf0hpuJZJ2y5tGH7tiRw/ekjCMwQbV2/mjB0viduuz5BePPDhLQn1eesJD/DtjB/jtnvy2/vYbX8rIFq9bB0znv2IRV8sQWtNXrtc2nVpTdsd23DoaQeyQ48OEftY/NVvPDzqadb9XXOXr+57d2HMS5eyc++GXzYVidY6eqHEiinokttIfovbbY0Tlf+adaFfjdYaXfYolI9jS40JBYTAeRDkPAgF54aT0SMtV9vqc7Xvicp9BGXfKe6ItFkG3vfRgcXW+FwDwHVozOR0rTV684kQXBqzb5V1W9xlWEKIptGcr9cqx7bHlOuwpbtSdp5QhY8lIx5qlp9BQ5IZjWZs4+rNfPPuD3hKPXTatSMHHNen3sXsYilYX8is8bNZ+t0ybA4bfQb34oiRh5Ce1fB3pBMx6KwBjL/pdbzl3ogzB9rUUes/zBj3CV9Pt2oQVI+lq5ZhbdWdNjUbV23ikfOeSeiC3ulyVO16tX75Bmx2G+27tU2qyrbfF+C6QXfGbaeUwpWWeOKyM81ZY2lWxDZuR1WQ8cmkL3jkvGeA2rtjKUPx0i2TGXLuYVz13EW1lsT1PGR3Xln2JIu/+o01y9aRluVm/6P3rfP3jA6tB+9HaLMYZd8R3EeiVPy+ogYZZim6pLJAXEsMMmxg62TNMtR7p6ygVeSwzZyaBeoqXgsHGdQ+h39eOMj4m5gF+2qcZil68+nQejrK1jHqaLTvS6sauK7ACnAU2vM62LpC3niUPXIdG3QhmGWRXwMwdkDlPIBy1dxNTusQmOutcxnt6pUvJYTY9smMRsOQQKMZCvgDPHXFBGaN/ww0GDZFKGiS0yab61+5nP2O6t3g5/zq7W+5b+RYQsEQ2rTuDn89/XtevnUK9394c1VSd2PKyE7nzneu5ZbjHiAYCFZdBFfOSpx42VEMPKP2+n+tNe88MROFQidxcRkKmvz48SLW/Lku6h38rTmcDjrvukP8hhHMfftbVv+xLm47jab3ET0T7vfA4/vy5VZ1PKqz2Q36D90PgD8XLufhUU9HzeWofP6TV77AZrfx3+drz74opdh7wB7sPWCPhMdY4xzBv9Hlr4N3JujNWHfIbWiCUHIXZN9lLeOJOL4i8ExD+760trx19kalDd9ykeqdSYPkYzgPAf/X1K1Kd7y+DwP/nAgv2MBoA3nPQuFlSW5vG4lpFczzfQ5uK4dI6xC6/NnYx4T+TPI8IdCl6PLxqOxbI7bQgT/QhZewJbCpFuCEVqELz0HnPg2eN8H3FVbezf6ojDPR5RPAjPZzY4SL8e2/5Vw6AOUvoismgbnJetLWBTIuhLRTJeAQQogUkl2nmqHHLhrHrPGfoU2N1rpqO9eSTaXcesID/PrN7w16vr8WreCeEY8RDASrLiy11qChrKicG4bcU2O71sJ/i3jzkfd4+soJTLrrTdb8Gf9iOZ6yonIm3/8OZ/e4nOMyR3JW98t47Z636dG7Gy/+8ijDrjiadl3akNcuh75H9uLemTdx2RPnRbxI8Hn8rFm2PuHtV7f2+w/RiwE2pC/f+jbm7lWVMnMzGHx2jIJqWxlwygG069IGm732j7e1jAxO+e8JAEx/chZGAmPQWvPh+NlsWLUp4XEkQldMQW86GjwTw0EGWHfIwzkHugxd/F9Mzwe1j/UvRG88Al36IPi/gcAPUD4evWkw2jPNahNaRb2LzaVfBLZupGxGxL47ZFwMqvp2ywa4BqJavYlh7xG7oF5yJ0MHFqMDv1gzCt5PwNzYQH1XFwLP21F/BnX5BKzPM9LrIWsGZ/NQqJhs5dWE/gHvO+jNw8A7g+izO6ZVeyRgbXutdRBddAW67PEtQQZA6B90yS3W944QQoiUkRmNZmb1snV8MvGLiK9prdFaMfGON3jw49sa7JzvjJ0ZNXfYDJmUFZXzycQvGHblMUx54B1evm0K2tTWzIKpmXjHVI65aBBXPnVBjd2fElX4bxFXHXIr6/7+tyrQWb9iAxPveINZEz7j8bn3cMmj53LJo+cm1J/NbtRrOX5d3kNdVJR64u4KBXDfBzeTkZ2ecL9Ot5OHPr2N64fcHV7WZVhBK1ZC+o2vXsmufa0ZqvkfL4pYbDEiZVUpH3blMQmPJRbt/yGcO5GA4qsxA4tRWdeglN1KTi48H3Q5Nf+hrQtQXXwjOvg3mKXUbxZChWdaikhZoFERnlFwDYH0M6xEavtOKFs7AEzf1xCvYF7CTKiYjC6Pvmtag9EVQICI9Up8HxF/KZjeqk2o2vOxGBD41ZrV8M4AX6RaGuE+Kiag3UfXylsRQggp2NcwJNBoZuZM+Trulq4LPl1MyeZSslslVssgnnnvz495sam15tsZ83G6HYy/6fUtYzG3XATMeuFT3OkuRscIBjas2sRHL33Omj/XkZGdzmHDD2Kvg3fjsYvGsX75hloX3aap2bh6c8J5E2Algb/92EzsDnvU3ZBisdlt7H1o3ZYAJavLHp34+YtfY372O+6+Q8QdrOLpuFN7Xlo6lq+n/8D3sxYQ8AXYed+dOPLcw2p83+gEd/YCMAwjbrFCAE+5lzlTvubPn5bjcDnod+y+7HP4XrV3OSqfQOJVujVUjEfrMlTO3dbuR7qM6Bedmv+zd97hURRtAP/N7l3u0huE3gREEQVRRMAuIIqIWFBQsCP2joIFRLHiZ8Gu2BUQUUAQEBQBQRARQYpIl97Sk7vkbne+PzaVXNlLLo3s73nugczOzry7V3beeRs575sY18S8+h4qbBUxQ94C8P6LjDgLlJXgvARhbwtZz4VxEh1kRjnOK5lC2CQiwajw7guZVw4ZzCJBGAGcMvdLAsuuInOnGFnavFtARBsZuZTg2ecsLCwsLIJjKRo1jKzUbCOQN8jaKzs9J2yKhicv+II8z5XPZ09P9XtcSpjx5lwGj7rCZ/G3qeNn8sFjXxTn0xeCmW/P48Rux7Pxt3/9jqsXxE3s3ryPpm0Dx03ous5zg19jybTl5SqEoyiCXjecS2JKfOgnl4NLbuvJ9Alz/HcQMODevuUe32a3ce7V3Tj36m5++5x8Tnt+nbbclFVD82o0PT7we7By7mqevfZVcjNdqHYVJEx7dRZtO7fime9HklyyGnver4Qc4Oyagoy+BVnot19lVDQQ2wwFbj+u/wCBzHkL6ehjLICrFUHoViEVogb6P2xrDd5/qbT3MKIgZbM3UBA7gAbuWUj3NyXanMjomxEx9yKE5V1sYVFXqeyiesdOztfAWL+iNYxGxzUIuuizO2wkNkwI25zturRBUf1/FBRVoUGL+qTuSws4jubVfKZV/XnSr7w/4nOkLtE1HV3Ti6pc/7NisykZ/10ZfLG19LvfWfxNcCUjwmnssioFMQyF197pgg7c9frNpuQJB606NOf6J68CymZNEoqg84Un0+fm8ytVhgH3XGJKyRACYpNi6Na/i98+W9fs4Kn+L+LKcgOgebSi93nb2p082vuZo6qbl8elSUW6ZlTyjnh1o1Ok2OTNo+KL8Yqa50OdXwUlBRHt/7skooaUY1wzKOC8GGFrWjiRiXPcZf/OebtEtjILCwsLi/JiKRo1jAuuO8vYCfaDalO4YNBZREY7wzbn5fdc7NdVCwzXqdN6BfdhFkLgyi790JZS8vnYqfhL7GImRgHMxU18/+6PARUmBLTr0ppphyfy3JzHOefKMzmpRzvOvrIr42aP4vm5T+CsxJzZvrjh6Wt49LN7aN6+aVFbQko8Q0cP5JnvR5ZKZ6zrOuuXbWLxN7+xftkm0wUND+46zCdPTWZEr7GM7PMs3/zvezJTswA4qXs7bh8/FDCym/lCURWEovDIx3cR4fBflfnrl2egS+kzAFjz6uxcv6u0ImrvSOg/QcJYfHv+DPG82koYFuO24yHy6oqPYwph1MFInhK4+F7kFeC4gPIpQSooxxX/vyBLGQARZyLiSigIzkspt9ub6wuk97/ynWthYVHrMSwaohJf1X2FVYPlOlXDiEuKZfgrN/DmPRPLBDSrNoW45FhuGHttWOfs3r8Ll915ETPfnlcqPkS1KWiazr1v3Uan808KGmAtpaT5CaVTve7bdoDdm/ZWSD7VpnLKeScF7fffxt0BFSYkuLLdOKOcdLmoE10u6lQhucJFz+vP4cLrzibtQDpej0Zyo8QyitVv3//B2/d/zP7tB4vaGrSsz52v3kT3AFaGX6Ys5YWhE4qsSQCr5q/li2e+4bkfRtG+WzuuerAf7bsdz3cTfmD1z+twZbnx5HmKlMCTzz6RoWMGBkxfK6VkybTl6AGsI4qq8Ot3K+hxuZF6VETfiEz/I/gNKoUXvFupnTUxqgcRfTMIJ9Ll3/UxPNig3vyC2hn5AYsoCmGDhDeRmS8YGcdCQkckjgcijBiM/FUgs0BJgYiuIF1AtDFP9BCka0pBYHqoFjQB7u8h5q4Qz7OwsLCwKMRSNGog/e/qQ1xyLJ+OnsKezUbqWEVV6HH5Gdw+fij1myYHHUNKydpFG9i4YjOqTeW0Xqdw3CktfPYVQnD3hFs45Zz2fPv6bDat3IKiKnTpcypXPnBp0QLz9N6d+HPBWp+LeaEIUprVo9MFHUq157mC1zAQigho2Tiz32mm4iai4qI4sjeAe5eA6PjooONUB0IIkhom+jy2bOZKxgx4maMX1wd2HmL0FS8xZtojRYv3kmz5azvPX/9GmfdLSokry8XIi8fx2ZY3ia8XR/tu7WjfrR37th0gdX86UXGR2CNsRMdHkdggIaj8uq4HjfXRNb20xcvRC6JugtyPMR8UDpaSEQoR4OgJwma4EclcP/0E5YvFKIH9DMh+E+meBeSBkoSMHISIvgmhlI3bEsKGDMkypQI6Iu4ZhL0DMv8PQxEozDym74PstcjstyHhDYTzfEPpSfoEmXZHQRrfwkeemUQRClI/VGHHMwsLi9qJVbAvPFiKRg3l/Gt7cN413dm5YTe5WS4aHdfAdJDyzg27ePqq8ez6Z2+RK9H7j+h0Or8DT0x5wGewthCCcwd259yB3f2Oe8+bt3DPmaPIycgp5devqAqqTeHRz+4pUxm7YasUHJERARWOYO5Tm1ZuRfNqQd2nLhh0Fp8//bXfitgCwfnX9gg4Rk1D13Xeuu9jQJY1s0pAwFv3fUS3y04vc++/e/0Hvy5rui5xZbuZ9/FCrnqoH9+9Pptv/jeLw3tSi/p0OOsEhr081JSioaoqjVo3YN+2AwH1gA3LNrFh+b+0P/N4Y7c79jFwdEPmfAaeNSAVIAdzC8FwUoF8yDUYEXMXQilIGhHzIDLrWT89pVEcUD/o53gwVMOdzeOhSGHUUyHnHaT7B0iejFBKK9JSauDdYHL4loZbVNR1CHs7pHYImXZrgfWi5PsmgTxk+p1QbzbCdhzCfgrU/wXyfkLmrzaULvtpkH4XgZVbHaE0MHn9FhYWFha+sGI0ajBCCFqe1Iz2Zx5vWsk4vDeVB88dzZ7N+wGKgq8B1i7ZwKO9xuLJ95RLnsatG/L2Hy9y4XXnYIswdFShCLr27cwby57j5LNPLHNOZLST3jee7zd2QijCb2xA0TXtPsKyGSuDytf39l7EJsX4nEu1KSQ3TqT3jecFHacmsX7pJg7uPOTfl1PCoV1H+HvxxjKHls9aFThtsS5ZPG0517W8g3cf+qyUkgGwftkmHjz3KZbNXMmaRev586e/+Xr8DO7t/jjDOj7EizdMYMNvxcUj+9/ZBxFk/zf9UCYPnz+aTQXB/UIIhOM8lKSPUBqsQqTMB6o2Tsbg2FMysJ8J0SUquUcNQcQ+AUT6OcFGuWMmRCRGUPXRC3e9oDjeS2VPk27MWlBEvbko8WMR9nZGg2uKDyWjJBoy59Pi84Ud4eyDEjcSJfYRFOcF4OxL4PgNiXT2R+b/icz9Epk7FantNyWvhYVF7UdWwasuYFk0jjFmTJhDdnqOT/cm3auzdc1Olk1fGdByEYgGLerzyMd3cfebt5BxKJPYxOig7kg3PXstaxetZ9emvaXkUlQFRRF4PYFdZlS7yppf1nP2lWcG7JeYEs/4hU/zRL/nObDjUFF6Vc2r0bhNI56Z+WhIhe+qEyklf/y4hk+enGyq/9FKAoCmBXdF2rxqm9+4FqlLvPleRl/uY5GIEROz4PPFXPvo5dz83GD63XkRy2auZO3iDX5/QaVuVLp/75HP+N8vY8t2cE0D/Ln3WISCiHu0VIyEEALp7AlZr+GztoR+oKBdlj0WEK2gpkmA4+6ZSH1kaRcqEQk4KZv16SiUZmXSzErXjwR9TLtnQ/zTfg+LmHuReQsL3Ml8fFcir4S025DaZootXgrS2R8R/zRChC8hh4WFhcWxSo2zaPz888/06NGDNm3a0Lp1ayZMmFDdItUq5n++OGBAtKIo/DzpV7weL9vW7mTLX9vJc4WeKjQy2knDlimmYh5iE2N4femzXPvo5UW1PxRV4awrzmDcD4+bms9XJiNftDypGZ9unsCz3z/GVQ9cytUP9eP5uU/w4br/0aRN4BoQNQVN03jphjcZdfE4Nv+5zdQ5SY0SyrSd2PX4gFm4hBCBg+eDUGgtmfzidBZO+pUIh53n5zzOWQO6BjxP13T+XryR/TsOsm3tTibc/SGP9HyaMVe8TNqu75A1eZ8nclB1S2ACFSK6IexlEygYu/wufCsSmvESvmOFKoYHvNtLtQihQJSJxBax95Ztk4eCnxdQ+QFha45InlKQ/azkgTiIHgbuuaBtLRys4F8d3DOQ6feZ/k2ysLConVRuxqnKjf+oSdQ4i8aMGTP46KOPaNeuHdu2beOcc86hbdu29OnTp7pFqxXkZOQEPK7rOltWb+faJsPIOGykOI2Ki+KyO3ozZMzAgOlLK0J0fDQ3PTuIG8ZegyvbjSMyApvdhpQyqG+/5tECZjw6GlVV6dr3NLr2PS1M0lct3772Awu+XAyYS/+b3DjRZzXzAfdewh/z/vJ7XrgWSkIRTH5xOq1Obk5sUgwnnNGW32auDFqf49OnJrPgiyVGdjOvjlAEA2/dRULnsIgVfkQCIm4MMm8p6BVIeypagq0ZeJaETbSjJoBoH4tzAPdMggbdyyNhlwgoqtZdqilmONI9p8Ca4oOIs1Ei+/s44M/9qyQ6UnqNDFf+RLK1QSRPRnq3FlQGj4GI05GZzxW4Zvn6DOuQtxA8qyGipn5YLSwsLGoGNc6i8frrr9OuneGHe9xxxzFw4EB+/vnnapaq9tCwVYrfAGAABBz873CRkgGQm5nLlJdn8GS/5/F6/AfhSinZsno7y2auZMNv5us4lERRFKLjoorqQwghuOqBfn6VDEVVSGqUSI8BZbMqHYtomsa0V78PyXlz+Cs3oKplfc3PuPhUBj5iLNJKWjZUmwICouLMLNaCI3XJ9r//Y1jHhxnUbDhzJi4wVQRwwRfGQruwr9Ql/66JwlvVceBmiRps7JLHDA/eNxByRyUqGQAaZNyLlD5ckvTAu/yVhtIQbG3LNAslCZE8zchAVjI+RERC9N2IxA99j+djrLKomK2hIWytEc6LEI4eQAS4phNYIVORrpmmxrawsKilWEEaYaHGWTSO5tChQ5xwwgk+j+Xl5ZGXV+z2k5mZWVVi1Vguvb03b9070X+HAL7zfy74m4WTl9JryLlljq9dvIEJd3/IjnW7itpSWtTn9peHcM5V3Som8/Be/LtqK/M+XliqjoeiCKLiIhk3q3ThuppC2sEMZr49jwWfLyLtQAZCGIregHsu4cLrz8YRGXpQ875tBwOn6C1BYsME7vjfjXTt25npb85h3icLSdufQUrzelxy64VccN3Z3Pbi9Zx89ol8+/psNvz2L6qqcHqfjlz5QD8mjvySv5dsNF000Sx7twQOmBWKwGa34c33lAlyn/lxPfrdWEk76hUiAvRU5MHuQE2vSi5BP4TMfAup2AEbOHshbG1AbVbgDlTFT7joGxHC96JfqCmIxLeQ2iGjRopwgL0DQhjWVantB+9moxaI0gSRtwBERJAJBTh6+a3jERgPhntZIHQjq5aFhYWFRUCErMGOpr///jsXXXQRf/75J61atSpzfMyYMTz9dNlgv4yMDOLiyqZwrQvku/N5+IIxbFq51bf/fYAsnooiOPHM43nt19IpMNcu3sCInmPRdd3nonTkF/dyweCzKyS3lJLf56xm5jvz2L72P6JinZw7sDt9h/X0W1+iOln360ZGXjwOd47vRWebU1vx8k+jiUkIrW7H7n/3ctMJ9wXtd+qFJzPgvr7EJccw/qa32F1QbwVZXJfkhK5tePHHp4iKjWTXpj38MW8N3nwvx3dpzSnntOeXKct4bvBrIclXUYQQRmxIAGtYZLTGoPsOcPWdh1CqxOYqADs4LzLqMpT5kkSA/RTwrKLObEGFFQH2Toikr/wqG76Q2n5k5ljI+4nS911gGOMDWxxE8hQjtW2ISCmRB7uCTA84PlFDUeJGhjy+hYWFsTEcHx9fI9drhbId98njKFGVl/RBz3Wz7cZxNfIehJMaq2hMnjyZ+++/n/fff5/LLrvMZx9fFo1mzZod829aMFzZLj56fBJzJv5MXq5xfxJS4hGKIG1/esBzE1LimLq/tEVkeOdH2LZ2p9+d77jkWCbveQ97ROXEd9Q0MlOzuL7VXbiy/O96CkVw3jU9GPVlcKWhJJpXo1/sEDx55UtBXBJFVTj/2u7kZLhYPmsVQhFFAeDNTmjC45Pu5+MnJ7Ni1qoKz+WPo2uopDSvx9CnBzL+preDnCl5b+G/tDjeHdgVMCzYIOlbhL4TmT6CsrvZDmq+FaPmIxLeQTgvNNVXakeQR64oqOthppCjQnHBQQci4RWEs1e5ZdWzxkPOxIBzi+TZCLsZFy4LC4ujsRSN8ikaLpeL++67j3nz5qFpGoMHD+bFF18sY72VUvLqq6/y3nvv4XK5iIiIYOPGjdjtVb9Oq3H+KJqmcc8997Bw4ULmzZtHx44d/fZ1OBw4HNWRc79mExkTyV2v38zN4wbx38Y9qDaVlh2a8dhFz5J+ICNgEHBMQkypv7ev+4+tf+0IOF/mkSxWzv2L7pd1CYf4NZ55H/+COztwSk6pSxZ9vYzhrwwNySKj2tQKZYIqia7p/PTlrwhFFMlUmNFpz+Z9PHLBGN7640Xandaa6W/OIfNIVoDRQkcIweAnrqTFiU3JPJJFw1YpdDzvJJZ//4eZs/lxShK3PbmPyrciaJDzLjJvjp+5LCWj4ihI13TzikbOByEoGQAR4LwEYe8Akf2LixSWExF9C9I9G7T9vmWIHGIpGRYWxzhS4r+GVZjGD5WHHnoIXdfZunUrOTk59OzZkzfffJN77rmnVL9x48axYMEClixZQkpKCnv37vUZy1kV1DhF4/7772fbtm388ccfREeH5nZiUZrImEjadWlT9PcFg89mzS/r/fYXiqDn9eeUaju8O7i/vBBwePex46+ck5HDrk17sUXYaNWheZmK5PM/+8VUxiZd09m4fDM9LjcfyC6lRPOaXVyZHNOHJUrXdHIyXXz/9jyGvTyUa0dezt4t+8nNcnNvt1HhmVdKNv2+hcEjryhqc+W4eWHom6bOnzcpkYF3HiK+no4wveAsDxLyFlTi+BZGTMNhUz2llOD6GvNKBoAbEXUlIiLwZoeUbiPeA8DW1m8tDKEkQtLXBa5b8ynKPiXiEdG3QfStIchmYWFhUXGys7P59NNP2bVrFzabjfj4eEaOHMkzzzxTStE4dOgQL7zwAhs3biQlJQWAxo0bV5fYNUvRcLvdvPPOO+zatctSMsKMlJKGrVJIaBBP5qFM9KMWn4qqEF8vlr639yzVntggwcTYhstVRXBlu1j8zXL2bz9IbFIM51zdjXqNkyo0Zqhkp+fwwaNfMP+zRUWuS4kNE7j20csZcO8lCCGY8dZctv9tPrVpqMGoQgiaHN+IPf/uC+m88qBrOj9+tohhLw/FHmGnRftmePI9Relmw8Fv3//Bod1HqN80GYBFU5YFdDkrSXaGjYevOI73FmeiUtn3Iz94Fwsf+Cj85xNhBKIHQUoPMuu1oDUwfKL7TwYiZT4y+w3I+YLigpBRyOghiJh7ED6Cy4VaH5E4AakdLAhGd4D9FJ99y84nyxmIXr1Iz3rIXw5Sh4hTwX5arbwOC4twUNm1LgrHPjqRkT9vnVWrVtGqVSuSkorXRl27dmXdunVomlZksZg1axZnnXUWzZoF/82tCmqUorFt2zZ0Xadbt9JZjNq1a8e8efOqSaqai+bV2PDbv+RmuWh6fCO/BenW/LKeV29/jz2bSy/WhBAIBXRN0qxdY8Z8+wgJ9eNL9WndqSVN2zVmz7/7/O7iR8VF0rVv+fPJz/14IW/dOxF3bl6R69C7D33KgHsvYdjLQ6rE3OfKdvHguU+xc8PuUq5LafvTeeeBTziw4xBDRl/New9/anpM1abSvvvxRX97PV6WTl/JoqnLyE7LofkJTbjktp4cd0qLUuf1v7MP7zzwSZUUBMtON+quaJrGH/PWsHT678QmxZB+MDwZ3IQQ/PjpL1z3+JUAbP1rBza7GrQafCG7tjjJkwOJEs+ERR4LfxQEwItkkKmYd1fTjQJ3MtjnRSKirg7cQ+rI9PsLLAjlwNbCZ7OUGjJ1OHh+PepILuS8h8z/G5ImBsyKhZoSdHopJbi/R+Z8Bt71SFRwnIOIvgURUbNr+kjtIDL9XvD8SXHWex1sx0PCWwg/99bCwqLiHK0QjB49mjFjxpTpt2/fPho0aFCqLSUlBa/XS0ZGRpEC8vfff9OiRQtuv/12fvzxR+Lj43nwwQcZOnRopV1DIGqUotG+ffty1Waoa0gpmfXefD5/+mvSDmQUtZ9ybnvuffs2WpzYtKht3dJ/eLT3Mz7vq5SSLr1PZeCI/pxyTnufO1dCCIa/cgNP9nvBb8aqW567rlypXAGWTFvOK7cUBwZrJRag374+G0VVuP3lyv9yTJ8wlx3rd/kNeP/29dk4Y5x4880tkIUi6DX0nCLFLXV/Go/2eoYd63ehqAJdk6xdtJ4Zb83lmhH9ueX564ru/6XDe7Fs5krW/LI+7Klnj6ZekyRev/MDfnh/fhkrVzgQQrB/+8GivyMiI0LyS23UugFRkavAHSBdWhEqKPGgp5noezQR1D2rhgqRAxERp4OeDmpTpHc3ZIeg1DmvAFsbyH4pyFRtwH564D55i8qpZCiGpcHWxudR6Z7rQ8kogWcZ0j0L4bMwoDmklMiMx8H9DcVWHg3yFiLzfoK45xBRV5Z7/MpESjcydQhohZbaEs8K71Zk6mCo9z1CqVoLs4VFXWHXrl2lgsH9xR57vd4yG5CaZqxJSq7fsrKymD17Np999hnvvvsua9asoXfv3rRo0YJzzy1bvqCyqXEF+yyCM+XF6bxx5wellAyAdb/+w309Hi9OdQq8P+JzpJ+0tGBYO9qc2iqgebzrJZ0ZPe1hkhuVDmqOSYjm3rdv47I7LyrXdUgp+eiJSf6zCkn47vUfSDuY4aeDuTlcOe6iL6M/Zr33Y8BFvWpT+GPuaqPYnQlO6t6OO1+7qUiGMVeM579NewDDggTFheqmvDSDuR8VF6W0R9gZN3sUNzx9DYkNE0zNVx6EEGQeyWbWuz9WipJhIIlLLg7M7d6/i6kYFCEkJ5+ZzdmX7AbvXkwrDo4LEXGjwdYOcGLuJ06A81JKFYyrEahgPxPUpsG7howwxo8aBPpBZO4nyPQ7zCsZSgoibjQi/jlE9M3g9J0ZsAhtC+QvDthFuqZgtsBeMSoIByJujP8u2e8EHybzRfTUoeiHL0VPuxuZtzg0i6J7doGSAaVdyTRAIjMfR2p7zI9XlbhmgbYd3zExGuhHIHdKVUtlYVH9SFH5LyAuLq7Uy5+ikZSUxOHDpWPdDh06hNPpJD6+2BulXr169OnTh549eyKEoFOnTlx//fXMnFk9RUZrlEXDIjhpBzP45CnfP/q6puPOdvPp6Mk8/tUD7Nt2gI2//RtwvDxXPkumLeeUc9qzcNJS0g9l0KBFfS68/hwSU4o/uD0uP4Mz+53G6p/WcfC/wyTUj+P0izoS4Qzur+yPHet3sXvT3oB9NE3jtxkrueS2ngH7HY0r28U3/5vF9+/MI+1ABqpd5ewru3LtowNo3bFlqb5SSg7tChyoqnl13Ll5pjJC3fv2bVx8ywVFRQY3Lv+XjcsDvA8CJr/wHX1uvqBI4Ytw2Lnu8SsZNHIAGYcysTvsfPnsNL753/dB5zeDUATOaAeuHHPxEuVF8+pcMPisor/bdzue9t2OZ+OKzX4Vu1O6ZfPAK7to3LLAwmC6UrgG3l0QNwYlajAA+pEh4FkR5DwJ9pMg/zfQKz82xhwC1EaIhJfA/SMy69ngpwCIRIgaAjkf4L/onAAcED8eMkYivRsIzQKUjKi/pNTmhFRbEDheQ0XmfIJw+N5NkzIfPJsILQBcGK5JMQ8h7Mf776btDD6UPAz5RwBp7OLn/QiOPpDwP4QI/piUuZ8RLF5F5k5BxD4YXJYqRrpnErDAErqRMSzmjiqUysLC4mg6d+7Mpk2bSEtLIzHR2PhdtmwZXbt2RSlRdKp9+/Zs2bKl1LmKolRbllZL0ahl/PzlkoDuZZpXZ8k3y8l5J4fUIDUzCnn/kc/JSs1GURUURaBpOh8+9gU3PTuYa0YUuxOoqsrpvf2nGw6VnIL4gEAoilIUR2B63MxcHjr3Kbb//V/RTr3m0VjyzXJ+/fZ3xs0aSeeep5Cf5+HXacv5c8HfqLbAcQOKqtCifVN2BVCMFEVw8jnt6Te8d6n2lXP/ChxgLWHv1gPs33GQRq1K+18qilIUkG/WmmIGKSWurMApeiuKUARnX3kmiQ3imfrK9xzZcwRHtJHlx5+S0erEXJ6btA1VLaeFxbMcmf4wIvF1dM9mE0pGgazCDvW+Q6Y/AfnVnIFKbYmIusZwa1JikVGDIWscppSBmAcgbw6ox4FwgrCDEmfEUegZIEBEdIbIK5DZE8D7j7lxS6IoZS2gnlUEDgrXCvz/SyOlhNyPkNnvg0wLPrfaCpH0uVGVW00JsztP4X0o+B3Imwc570DMPX7PKMKzgcDXr4Pn7wrKV0mYcTXU06tCEguLGkVNS2/bsGFD+vTpw6hRo5gwYQLp6emMGzeOsWPHlup31VVX8eijj7JgwQJ69uzJxo0b+eqrr5g7d24YpTePpWjUMg7tPoKqKnh1/4tizauTdjCTpEYJpsbMSjUyvOiaTuGwmi758LEviEuO4eJbzOW+98XerfvZ/e8+omKdnHjm8aVSxTZslRJ4I61ApkatG/o9npmaRb4rn8QGCUVjfzb6a7av21XGHUjz6ghF8uy1r/LCj0/y1GUvcGRvmqEEBLFU6JpOn5svpEGL+nzz6qwyMgtFIBTBjc9cW+Zcb74XM1XnvPn+t+5dOW5mvh2+hAhCiEoJNldUxVAiBPS+4TzqNU1mULPhICVCEUGzWe3b6eDAf3aatqlAvETeHPT0RPD6T+VcBnsHhJKESHobXUs10qt6/wVph7zvyi9LSKjgvBQR+5ChAHjWIu2nIpQoJDGAiTonWU9R/KVSAQ2ihiJiHy9tgdBzIPcbQrMgFKD7kEPPLdtWBgWpZxuphPXDoKQg8/8E11cmJxaIqKtNB2cXoTYFbav5/kVII7A7+vbgmaaEDWSgz6zAiAOqgagtwbsF/58FBWzNq1AgCwsLf0ycOJFbbrmFRo0aER0dzcMPP8zll1/OF198wcqVK3n99deJjIxk2rRp3HnnnRw6dIj69eszceJETjnllGqR2VI0ahkJ9eOC+9MLiEuOIS4plg5nncC6X/8p93yfPT2V3jeeh6qqSCn5a+E6fpv5B/mufI7r2JILrzuL6PiyqYj/+2cPb9z5Qam6HYkN4hny1NVcOrw3QgjqNUnmjItP5Y95a3y6JAkBsUmxnHlp2YxWv89ZzZfjprFh2SYAYhOj6Xt7b658oC9zJv7k18VJ6pKs1GweuWAM7hyjEFuwxa+iKpzQtS2nX9SR0y/qiN1hZ+or3+PN9xYt2JMbJfLwR3fSoccJZc5v3r5ZqSB3XzgiI3BE+Tdr/vvHVlxBigSGQmUEmdsdxs9JdFwUfW65kKhYJx89Pqm4g4k589wKU95qwEOv7gLAlSPITLMRl+jFGSXNVwl3m128Ampro9BbAYqaBDHDjQDf7NeqqF6fAkoj0NORh86jeHc8Euko+bcZjtqZz/0MbG0h6priLtp2oLyfp9JV66V3iwmlTgHRCHmwe8G8KqEpOSoo9SEycOYqn0QPh8xHQj8PQGaAdxPYTw7cz3E+uOfi/5okwnl++WSoBKR3KzJ3MnhWg3QT+L3QEVGDqko0C4uag6Ry68WWY+x69eoxY8aMMu3XX389119/fdHf3bp1Y/Xq1RWRLmwIWRU5NKuImlzSPlwc/O8Q17e6y+9utKIqnN6nE+O+HwnAxhWbK1yA7c0Vz5PSvB6PX/o8m1dtK7IcaJqGIzKCB98fjlAUMg5nktK8Hk2Pb8x9PR4nN9Plc8F/07ODGDzKKOK2+9+93NNtVJm+hdWsx0x7hO79Sxfh+uHDn3h12LsoiiildCmKQvMTm7Bj/a6A13P0eb4QQoAwFuRnXnoaj31+TymFKistm+WzVpGTkUuTto3o3PNkn2l4M1OzuL/HEwFdrgpRbQpXPdiPm58bXMrfEmD1z38zoudYP2fWTMprNbHZdb74YwPT3qvPhVem0erEPDQNVBV0HZRwp7BwXmWkdPWsxagw3RMiB0PO++D+NsyT+UIYMuQvA91PJeqKjq82Q9SbX2TVkJ5NyCP9yjlcHEqD4uruetr9hptRZRZVtJ2ESHgDYQs9L7yUXiNzkuevck0tkqYiIgK7jErP38gjV+NbIVRBSUDUW4BQqr8+lMz9Cpn5NEZMSbD3TIGILojEjwz3QguLMFGT12uFsrX44EmUKN9FPcOBnutm523P1Mh7EE4sRaMW8s6Dn/Dt67PLaMOKIlDtKm8se442p7Yqar++1Z0c2Hmo3PO9+OOTvP/IZ+xYvyvg7n/hwtLusKF5NL+LedWmMGnXe0WxB7s372PiY1+wdMbKop32E89sy03PDuLUC0rvJKYdzGBQs9v9WgiEIsKyWx8VG8mQ0VdzxiWdaX5Ck3KP89rt7zHno59NBZEXMmjkAG4eN7hUW2ZqFtc0us10/YnaTrM2Lu5+bg8nn5mDWiV215KBvCrGl6uqUm2rYDsRvMH8/CuGqL8IoRq1dqTUkIfOBf1gkLP8jJU0BRFxKlLPRR48jUpVMpImIeydK1Q4Tuq5yKxx4PqWYllNpEwWUYj6yxBKVPA5XLOQGSMw3kO9eHwlGZH4McJe1tpZ1cj8lcjU6/wcPep+iGiIvBYRe5/fCuoWFuWlJq/XCmVr/v5Tla5o/DdsbI28B+HEcp2qhdw+fijOKAdT//c9HnexG0PDVik88vFdpZQMgL7DevHxk5PKtwAXcHhvGlvXBM/cUqizevICpwnSdclPXy7hqgeNHdWmbRsxetojpB/K4PDuVGKTYmjQor7Pc3/85JeAi/ZwuQQVWhcqQk5mLj9+vigkJQNg6ivfc9WD/YhLjiU7PYestGwSUuK58PpzmP9Z6OPVNhRFYo+QdDortCQAFePolKRViQbedZU/jSy+LiFUiB5mPptVKRRk7leIiFMLCvVV4v0SkRVWMgCEEoWIH4eMfQjyVwM60nYKpN9mVP32eQ0KRF5jSskwRL0UIs4A11Rk/loQEQjHOeDsa3qMykbmTMS/25oEBETdjIi8BGxtECKyagW0sLA45rAUjVqIoijc9Owgrn74MlbO/YvczFyatmvst+he32E9+W7CD2QcygxpkaqoCqdf1JF1Szai2lRT9Q/MoKoKh3YdKdOeUD++TGXyo9m5cVeFrRYRzgg0r9evdUZRFY7r1LLc4xeyb+uBUoqgWbweL9++PpvNf27j9zmrQYItwsY5V55JvabJHKyAdao2YLMbSoaugVL5ReHrCHZjkRl1TfHOetQQ0HZD7icULz4Dp2g10AusLxgFErERQg7iEFDBOaDCSkZJhJIETiO5hQBkwpvI1EFGrYii6y64BxFdELEPhDa+mgIxd9W4iixF5C0lqGKobUcEi0mxsKgrHDM+P9WHpWjUYmISojn/2h5B+8Ulx/K/X55m9ICX+G/jnqI0qZpXp0mbhhzYeQhdl6WUENWmEB0fzd1v3GJYQ8LoYafrEtWuMvfjheiaTvtux9PypGbkZrlYPPU39u84SFxyLOdc3Y16jUunr4yMdiIq+Bhv2q4R2wJYaHRNp/9dF1doDjCqYJcHIQSTni/IdFRw2735Xn75etkxb80AyM9TUFRZqWkF6x4ecE1Gur5ERt2MiH0UIQQibhQy8nKkayp4/zMUh/wVoAdTZg13AiEikc6+4J5F2C0bItIoBliJCFtzqDcLcqcgXd8ZKYBtzRGR10Jkv2MwLiHY74cEWRlKo4WFRV3FUjTqCE2Pb8yH615l7aINrF28wagWeUEHTurejs1/buPzp6eyYvafSCmxRdi4YNBZDBl9NQ1bptCifTOQy8Imi67pTB1fukJlk7aNOLT7CPnufFSbiq7pvPvQpwy49xKGvTykKND67CvPrFCaV0UVtO7UknOu7MYnT00uZR0pjDFJbJjAJ09NZsHni7jktp506dOpTHC2GZoe34hGxzVg37YDIZ1XmB72aOWuLigZYFhv/lkVVUWxGbUcEW9kRjJFYRaqj5BqU4i8HIQNYW+PsI8u6qVnjYecD/G/KBVga4ae/gBIj5E+VkSBzCV8ykYMIulLQxGoZISSCDHDETHDK32uasfeKUjNE8Wos2JhYYGUAikrzz5ZmWPXJKxgcIsistNzyErNJqFBPJHRxQFQR/alcV2L4UHTwFYKAq5+6DKGvTQEMBbfd5w2gq1/7Sj3kP9bNJaTzz6RX79bwdcvz2Dj8s2AscA1al5gxHCqCrqm02PAGTwx+YGiSt+hMPWVmbz/yOflljWcqDaF+HpxpB/ORK+O99IkPYecw8JJi3lr3iaatXVj83HbpTRVmuTYxnklRA2G1CvLcXIJP3376Yjo24rSr0ptH/LwxQVpT4/+nCgU53ws/L8wXkr9gqxZYcB5NUrCuPCMZVGEdP+ITL/bz1EB2BD1f0GovmPkLCzCRU1erxXK1uy90SiRlRgM7nKz6/ana+Q9CCfhThRpUYuJSYim0XENSikZAMmNErnnzVsBY/FtClFcV6EQ1V4Oh3sJ3742m4zDmQDkufKLCgyGihCC867pToezDB/1swZ05Y1lzzE790s69DihuOJ6gepdaEFYNn0lX4z9plxzph/MNO1jXpjSN5w+6cWDG4vzBz+8g/pNks2/jyXOr9e0HOeFiFAE1z56OarNzrjbm5OVZkMrsUmua5VbqbVWkTcfXNMpn2G6xE31/IlMvx2Z8wkAQm2ESPwIRGxBB7XgVUjh51OnODuXdpSSoZboVw7yF5b/XAv/OHpBVKE7Wsn31HiPRcJrlpJhYVGIrIJXHcBSNCxM0XdYLx774l7qNUkK3hljifHKL2MZv3AM970zjJFf3Eun808qlwuSpmksnb4SgF8mL+Xgf4dDHiMyxsk1j17OY5/fW2Yhv2vTXtYt/cfvLr+UkulvziHfHXq16kVfLzMd39KmUyuuuL9vpVTsFkCn804ioX4cb//xItc9fiXJjZNQVIUIpz34mlDC2BkjSGqUaIxXoBSFO+o1MsZJi/bNePHHJ8nOTmH4hcczeUIKB3bZyclUOLA7gny3sKwZYGR8Ml1VOxDG515mPY/0GrFLIqIzImUxIu45w8XKeTk4elOcujUYGsVPUZUiZUjEgdrGhEipoVyAhUmEEEZ8TuIHENHDcL1T6kHklYjk6Qhnr+oW0cLC4hjD8oK2MMXPXy3h5ZveMp3tSVFVTuzaFoCO554EwLRXZxVbDUJAURRyMnIBWPzNbyFnnep/Vx9ueeG6MpaaQtYsXB90zJyMXLat3ckJZ7QNOp+maSybvpLZHyzg4K7gSlGTto147odRNG7dkLSDGcx4c0653dQinHbyfWS6khL++mU9d3cdSf+7+nDby0M464qurP7pbxZ/8xv/rNiCLgPPOePNudz2wnXMem8+//y+GV3TiYyJpNXJzWnarjFSlxzac4RV89aUS3aAc67qBkCHs05k0n8f8Nv3i9i6ci6/zPyHrj1TadnOqPuQcUTh37XRCAEnnJpDTHzNdQWrXMIZgK0gXVMQsSMAI9CbqKvAHY3MehW0HaEPKeIh6gYgH2FrC87eRrE41/bAsivJ5bkACxMIIcBxLsJxbnWLYmFRwylwC63U8Y99LEXDIigblv/LC0MnhLS4d0SVzbjUoGUKW/7aEXJQs67pbFu7gw9GfM7uTXtNyyEUgTPKwY3PXOtXyQDQdd1M6a5SBQj3bNnHbzP/IM+VT6uTm9P1ks6oNhVPvocxV47n99l/oqhKUFlVm0L77sfTuHVDABJT4ul3x0XMeHNuuSwbvpSMIvkL7vuMt+Yy4625Re1mK3j/+OkvzPt4Yan+2ek5/L1kI38v2YgjKoLHPr+XHX//x5G9aSHLDtC4dQM0TUNVVRRVwRmdzOZ1SWz6PYWZnzZm+JhNrPhRYeF3CXg9hnXMHqFz0aBUhj21F0dkHbFFVwoaeDaWapG5U5CZT1LuB6LMQEScYtSTKCRyANIVyBVRgciB5ZvPwsLCwqJGYSkaFkH55pXvURSBZtaaoQjOvvLMMu19br6AJdOWl0uGn75cYshgcqdfURVsdhtPTx9BTEJ0wL4n9TjBbxXzQpzRDlp1aIYrx834m99i8dTlCEWgKAqaVyO5cSKjvrqflXNWs3LOasBclijNq9Nv+EWl2oa/cgN5rnzmfPgTiqoY163pKIrgpnGDsEfY+XDkl+Wq0eELswpNodLkr39ebj5jB76C1Mq/2P/o8UnMfGceAx/pz+qf/ua3mX+g2pSi9/2TF2LYu92BrhUvfD35Cj98nsyuLQ6en7TNylZVboSRPaoAqWchMwsL+lVAgdOPsurZTzdiBfIW+BhXBSUFET2k/PNZWFhYhIPKjqOoI/ti1iPZIijLZ68KyZVH1yWdLuhQpv30izrS9dLT+P2HP81ZJUqYGaQuTSs68fXj6D30XPrdeRGNWjUI2v+EM9rQ9rTj2LZmh+/rFNDqlBZkHM7i+eteZ8Pyf0vIZLh/pO1P59GLnsFmU0Oy/Fww6KwiF7NCVJvKg+8P55oR/Vk4aSl7t+3n4M5DaJrO30v+oUP3dmFTMsKOLhGiYgHbh3en8vZ9Hxf9XfiexCd52L3Fga/ddV0XrFkay7J58Zzd12y617pGsGJ8ElFQzA4A92wg9LikstM2LPWnEAISXkVmvQy5k0rPEdENEf+cUVivipCe9UjX9yDTEWoTiLzC+NfCwsLCosJYikYdZu3iDXz3xg/8vXhDQRXwTgy49xLadj6uVD/NE5ofuKIIfp22gp7XnXNUu8JTUx/io1FfMevdH8lzGQsM1abStW9ndE1nRUklJMTFqlAEXS4+lbHfjUC1mc9wJYTgya8f5MFznuLIvrSyioKEjb/9y5Dj7vI7hq5L8Gq488wXuxKKCHiJTdo0IiYhmvmfLUJRjFS7QghWzFpleo6qpjIzQnm9AqGAv1ASRZXM/TLJUjTKhQpKA3BeUtQitd1Ge0WqfisNIaJrmWYhIhBxjyNj7oH83wEP2E6qkroZhUiZh0x/GPLmUZiBSSIh+01k9J2ImOLEEdL7H7i/R+qpCLUROC8zqoBbWFhYWATEUjTqKJNfnM7EkV+Wckv5+aslLPhiMY98dBe9hhYHCrbu2IItf+0wvVOv65Lls/5ASlkmw1OEw87wV25gyOir+WeFEVDcpvNxJKbEA5BxOJNDu42A4g9HfRmSsnHto5czdMzAkJSMQhq1asB7a8Yz58Of+eGD+ezdGlqRPQA9RJchqUv+XbnF7/E/flzDW/d9VDB2QWagOpzbNTdbRer+YwV0TXBwz7FWyTmcHK2hFX5PNFAbIxI/RojiWCahJCBNZZgC/EU5KSmgp4Faz/dZShw4e5qcI7zIjDFGimCgTGB6zlug1kdGDkRmjgXXZApT9kp0yBoPMfdB9PDKSUddy5F6JuQtBpkDtuOMWi3WfbKobViuU2HBSm9bB1m7eAMTR34JUMpVSPPqSF0y/ua32L15X1H7gHv7huQOVDhWoBiF6LgoTuvVkS59Ti1SMgDi68XRplMrFJsacirctqe1LldRvULikmK5ZkR/GppwtwoXdqf/hfGUl6ZXet2K2oRhySj7ORRCcmbvDJ79YisT5myucrlqHwpEnA/Oy4y0pglvIurNK2tNcF5M4CehAvbTIGFiqdiOUnjXI1OvReo1y8oktf3g/o5ArmQy+23Dvcs1paBFw7DuGCl+ZfarBQqIRSFSauhZryAPdkdmPIjMfBKZeh3y8EXI/NXVLZ6FhUU1YK1i6iDTJ8xBtQV464Vg1jvziv688PqzufC6s41DioldKQFN2zUul2WhkKbHNwo5O1U4/HaklKz++e9yn2932M3dIwABe7ce4Irkmxg94CXW/LK+6JDm1fjr53Wh34NjmrL3VVElI9/ZydOf7OC087JxRtWRLaJCRCyhZ4TSAS9Kwoso8c8inL0RoqyCbsQrDPIzfkFxydgHEEq0sXPtEw203ZD7ZYgyVjJ5vxB0O1E/CLmfBewnsycgZQVcy44xZOZzkPMeZWJ7tP+QqUORnn+qRS4Li3IhReW/6gCWolEH+XvJxoDB3bqms3ZJcZpLRVEY8endPPLxXbTu2DKoCVwguPzuiysk4xkXn0piw4SQqmqfeGbwGhfB8OR7Q7beFAsB/e+6iNN6dSySKSAS8l35ZKVls2L2Kh6+YAyTX/gOgPSCSujlwRZxbHtEKkrx+3P1HQc5+9KMgvbqkqgakVkYP+MhPrDyl6Bnjffpiie9W9EznkA/cGrBjn0cxfnkCzYPRAIi4R1ExBkFqWoDbSroyNwatvMvXZi7Z0Hi0/TD4Cl/3ZhjCendBa4v/Bw1lFuZ/UZVimRhYVEDOLZXJBY+MeOOc3QfRVHofcN59L7hPKSU/PjpL4y/5e2iIGWgSCk4o29nLr29YhVmVZvKiE/u5olLn0NKEXBnX1EVzr6iK/WaVLzIlz3ChqIq5bIkxCXFMmjUFUTHR/HrtBXMen8+O9btIvNwZtD0uYWK38RRX9HhrBNYv+zfcskP4M0/lndYRdG9VG2SAbcdrpsKRklEDMh8wI2xeDb52c1536gKHX1jUZPM/x2ZejPGArtwkZ0JSFBbQeQAhO04cJyPEHak1CF/NcEX5IdCu6YKIKXLCDCXbrC1Q9halu1kO57g98lMdR1A5oYu5LGIexaB75kGeT8j9SyEEluFgllYlA8pKzfBSV0JubQUjTpIlz6dWPD5Ir9WDUVR6HJRJ7/nCyG46Mbzadgqha9fnsHKuX8hdUnjNg24/O5L6HdH7wq5TRVyeu+OvPLLWD55ajJ//bzOb7/IGCcIwdLpv3Pmpaf5nPu/f/Yw690f2bRyC3anne79utD7xvPK1NgQQtChxwmsXbwhJFkVVfDqkmeISzIeoOcO7M65A7ujeTUe7/scq+avNTeOIpjy0nT2bAk9GL2uIBSYMHsTB3Y5SKx/LCtVJpEZkDQN4fkL6fnDCL7ON1evRma/g4y8GiGzkNgg7W6K4xCKehn/aDsReBHO3karlMiMR0HbGnwiJcEIEPb8DQiwdzACwYPJJzXIW4DM/dpwwVKSEZEDILJfqcD1wr4y+y3I/ajU4l/auyLin0XYWhR3jugGahPQ9uFb4VDB3hk8K4Nfm9oqeJ9KQnrWIXMngWcdCCfC2cuIu1ESq14W/QjBUyjroKeDpWhYWNQZhDyG0thkZmYSHx9PRkYGcXHBH2J1la1rdnDHaSN8uggJRWB32Pn03zdMWwg0TUPz6kQ4Ki/jT9rBDA7vSWXtL+v4edJSdv+7l9xMl5EiVsoiy0rLk5rxwo9Pktyo+EE7fcIc3rr/I8NS4S22vsQkRvPS/Kdoc2rphcKUl6bz4WPmfMqFKlBVhbEzHvOpnC34YjEvDp0Q8vXaImzHuGWi/ETF6Xz3T/njaI5FRL05CFtrpHcXMucDcE0DzNZacQB55roqSYj6vyKEDd01BzLuMyMd2E4E7xaKffcjIPJqRNwIhIj0eZaUeci0OyD/V4oXsAU75rY2iMTPEWrxb5SeMRpck3yMpIISj0iejlCLa3rI/L+QqUMx7pN2VP8USJoMadeDtge/ykjEmShJH/s4VvnI7LeR2a8ZchTJL0DEIZI+RdjbV608OR8is8YTWNGwIVJWGnE9FnWamrxeK5St6YSnUSKdwU8oJ7rLze57RtfIexBO6rrTQZ2kdceWPPrpPUbV6RIuUoqqYHfYGTt9REhuSKqqVpqSoWkaK2av4pvxM/ll0q80aduYQaMGkJvpAgqqVcvi9K+7Nu3hiUufL/I9//Onv40UsZIiJQOM3dicjFweu+hZXDnuovYFXywOqGRERNo5rXdHkhsn0qBlfQbcfQkfrnvVrwXo+3fmUZ6sjpaS4Z+oGBsyYExAHUNEg9oc6fkXeeRycE3FvJIBppUMAD0Vqe1F5nwGGY+YPEkF7z+UDhDOB9ckZOptSOlbVpn1CuQvK5y4sNX4x7sdmfFwcV/vFj9KBoAGegYy571SrSKiEyJ5WkF2rQLjvoiCqOsRydNQbI0Q8S8XHDv686aCiEXEjQlw3ZWHdM8vUDKgtJIkQWYh025BSrePMysR52VBOqjgvMRSMiws6hiW61Qd5cLrzubEM9sy690fWbt4A4qqcnrvjlwyrCf1Ggevyrv7373MfHseq35cg65LOp53Ev3vuohWJ7fA6/GyfNYqdq7fjTPaQff+XWh0XOgpY3du3M2T/V5g37YDqHbjQf/1+JnYHTbDkuHDIqN5dbas3s5fC9dx6gUnM3X8TL8xF7qmk3E4k4Vf/colt/Vky+rtvHzjmwFl0jXJqC/vIy7ZnOl/16a9dcYP82ian9iE/zbuCfu4aQclB3crNGhavMDavDaSmZ8ks/73aFSbpOuFWVx6wxEaNg9DZeuajohHShUyHi5wGQqtwGbIZI5F5i/BXBL4CPxXF9fB8zu450HkpaWOSD0bcifjf3dcg/ylSO9Ww5Lj+o7Abjsa5H6LjH0CIYqVBmFvi0j4H1K+YGTOErGlMnCJiM6Q/DUy+03I+6ngmm1Gwb6YuxG2pibuQfiROR/i/3p10I+A6weIuqLKZBJqCsTcg8x+3cdRFUQ0IubeKpPHwqLCVHZmqDqSdcpSNOowjVs3ZNjLQ0M+b8m05Ywb9BpSyqIF/L5t+/nhgwVccX9ffvpyCekHM1BtKrqu8+7Dn3L+tT146MM7cEQ6TM2ReSSLh88fQ+aRLKB0dXJPkOrbqk1l+fer6HR+B1b/tDZgYLdQBKsWrOX8QT14pOfTQYO2vflels1YSZ+bLzB1HY4oB1mp2ab6VhdCiEopBFgZSgaA5pUMv7AdU9auR1EkMz+px3ujm6CqEk0zfrh3b3UyfWI9Rn+0gy4XZFWKHDUGfS+k31ZgNahkRArkLw7hhGCWJwWZ+zXiKEUD7waM4PYg5K8AW2vj36DB3S5DEROlNwmMmhrzkHoGwtYc6byolDuXsLdHJL6N1LNAzzDcxxQ/dUOqACk94AlWk0JF5v+GqEJFA4DoOxEiDpnzFuipxe0RpyPixlRp5XcLC4uagaVoWITEvm0HGDfoNTRNK7WhWRhYPu3VWUVZIzVvsXKwaMoy8nLzefq7EabmmTPxZzIOZ5Yv1awAT57hjhFMcUBKNK/GT1/+Snaav1oAxSiqQnZ68H6FdOjejl++Xha8YzXwzMxHOaFrW6aOn8nXL8+sbnFCIjdLZeDJ7XFG6qQdigAoUjLAqBIudRh7S0s+XbGRpJRj3BUtf0kVTaQTPOC3JK7g4+m7yzabUnwFMu9XZPb7hrIVlIhShQWl9Bp1H1xfFbQoSLyQ+TTEjUVE9is9mxJb4SBmKaWRWldE+KxdYnIUk32q3pQqhIDoIRB1LXj+Aj0bbMeVDsS3sKglCGm8KnP8uoClaFiExKx3fyx4WAbo5OOYrkuWzVjJltXbywRf+2Lh5F/LXc9C82i0ObUVQgiOP601m1dt9a9wCMGJXY/nj3mrTe3s65ru1w1M13X++nkdK+f+RU56DmqESnSC70DX6iYqLpKufU/jyL40QzmsdUhc2SqubBuKItH1siZoKQUeD8z5MonrHjhYDTIeg8gjmFvAmkwNizBS7B6NvT2B3a4wxi9yZzKBkgzaXrA1M87OfB5cX5Y4v0B5kjlG/IeIQTjPNzd2EKSeA7kfIXO/MtyaUJGOXoiY2xH2k0IaS4gIpO0E8P6Lf4VPN9y+qgkh7BDRpdrmt7CwqDlYweAWIbFqQWBXpECoNpWFk3411bcw2Lu885w/qAcAV9x3iV8lQwijbkafm88n7WCmKfeh2KQYzrjk1DLtB3cdZvipj/Bo72f45tXvmfPRz8x6dz6z3/+p3NdRmZzWsyO5mbnMnfhz+QsUViuClie4Ad9KRiFShzVLY6pOrGMesz7FZvtJRGRZ9x6hxELUVfh/RBWOH8JnV9+HPHwhevrD6N6dRykZPiQrCrauGFLPRqYONlLv6kcKWjXIm488cjUyL3RrlIi+Cf9KhmIkCAganG1hYREQWQWvOoBl0bCoUvy5HR387xA/fPATW/7aToTTTlRsZLkL52lejasa3Irm1ajfzH/2LKEInpjyIFtWb2fjcnMF8k45tz32iNIZtvLzPIzoOZa92/YbDbXgx2PJt8v5dfoKEhskoNfKaHXJaedlsXurA68n0KJW1JJg/FDckaoTEzI6+4H7exNjCVCPg8j+vo/GjEB6NoFnFaXvj1lriR/cs8Dzb5AxJHg3Ir3/VTiuQGZPAO8myt47DRDI9AcgZSlCmItfk/l/GFm/fKICNqNqu2Ip2BYWFtWPpWhYhMSpF5zM9r//K5cCIHXfbkc/fLCA1+94H4RRAdxfRqlQyHcZLhf7t/l3mZESGrSsz2MXPWt6vqXf/c5v3//B6Rd1LFI4fp22nD2b91VI3upA6pLU/Wm1QjHyRZ/BR9ix0cmfS2KRfqwaiiLp2MN8TE31URuUjGCooDSA6OHmFA2lCSLpC791NIQSBUmfgnt2qYJ9RJwBuZ9UQE4dtH8oXX/CDzKzAvMYtUBwfY3/91cac7jn+lW4SvXO/x2ZeqP/8RznI2Ifs4KuLSzCgZV1KixYrlMWIdHvjt7lqgsBgBD0vvG8Uk1/LVzHq7e/h64XZ7CqKlceRRFMHPklafvTQzrvqf4vMrDhbUwc9RV5rjwWf7McodTSH4xaqmTEJnpZvTiWgXcf9KtkCCFRbZKLBx/xedwiHCgUZZZSmyCSPkPYjgOlftAzRfyYUgX3pJRIPR2ppxW5MQoRgYgcgJI8CSVlCUq96YjIy8MgtyB4GmAF1MYVm0bbZ6TNDYgN6d0UdCijEvsYDCXDl6IhwLMe1OpJuWthYWHhC0vRsAiJxq0bMvKL+0oV+jPLrS9cT1LDxFJtU16aEXQsu6PY8JbUKCHkef2heXU2rdxarmvJTs/h65emM7LPOLIzcmppnEPtxRml0++GI3TsnsNtTxkZh1S1+D1QVEPJePLDHSQ3PMYzTlUn9lMh8ipEwpuIenMRtuYIoRbEEARQvkU00mYEK0spkbnfIA9fgjx4BvJgV+ThPsjcKb7jpmzH+w4gDwkFsAeQUQVHT4QSvKbQ0UjPBvSs8egZTxXU9wh6BkZ19iB414G2hYDWEX0f5P9uXlgLCwv/WDEaYcFSNCxC5tyB3Rn5RWiFlxRVoUX7puzbdqAo7a2maayavyaoG5Ynz8v5g3rw5Y63mbTrPXrfcF7YLAhCEeh6+dxWdF2y7teNSE2i2KyvUvjx9Sts/Dpfc/dBdGkE9F81/BCvz/6X8wak0bB5Hk2Oc3P5rYf4YNEmuvY8xmtoVDeevxGRlyGcvUuna426CRwX+j9P5kL6neiePciMp5CZo0DbVnxc24HMfBKZ+VQZZUMIGyJ6WAUFl+DoUzjiUcdUEHGIWHOpuItGlG70tLuN6uw5E40K7TnvmDhTQzgD3KuibmZS+IbQz8LCwqIKsGI0LMqFmRS1JdE1ncf7PgdAdHwkXfuezq0vXmfaErBw8lJuemYQiqJw/3vDkFIy/7NFIctdEtWm0PXizsz/fFG5M2lJCQd2HUL3Hgs+9jWNwqBfYyFos+sFgd+C08/L4q9fY1kyKx5XtkKT4/K4YcR+GjT1VKfAxwa20yDiNMh930RnDzL1Vqj3fam4ACFUpBroN0KCZzkcOb9029H/d00BZ29wnF369KgbwLsLXJ9THGtR8K9IAJlB4O1CgYgbCd7+yKzXDGsBAIphyYgdgShIg2sWmfE45C0o+MtsdXYV7F0Q9g7Bu5q1riiJwftYWFgEp7KtDpZFw8LCP03aNuK4U1qUy7KQk+Hi56+WMLjZcGz2YJWDDRRF4eeC1Lg2u42cjFyjOFQFkBKufuSygriT8o91cMchhjx1dYVksfBH8fsSGVO8eHvm1pY8Pvg45k9JYvGsBCZPaMANXU9k6jvBYwMsguBdBRE9QG1D8DS1EshH5n5R9pDr2zAIoyJzv0TK0gt3IQRK/JOI5OlGcbiIs8HZF5HwHiLlN6j3C4iGlH3EGdcjYkcg1HoIxzmIxHcg6lZw9IaoIYiYexC2Zkg9F+lZj/T8W2b+o5He/4xsVqaD+gv2+OynIBInmDvF3tkItg+EiEMikO75SO9Wk7JYWFhYVB6WomFRLoQQ3DxukOHWUIH1vtdjbudPUQSZhw03mNU//c2yGStN1b3whWpTUFSFEZ/cTYsTmzL8lRvKBKmHgpTQulNLRn55H6pJxckidLLSin3qt643MhVpmkDqwqgELgUfPtOYRTPjq1HKYwEVXJ8jYu7C3JabBu4fyjbL1DDIokHeQuSBE9EPnI6e+QJSK84kJ+ztUeJGoyRNREkYj3CejxAqiq0Rot40I9VuScO92hwRP74ghgRk9rvIQ+dC7keQ9zPkfoE8cin6od7Ig2cijwxAHrkUeehcZM6n/n9z8hYQ0g+h43xE4qeIpMkIxdznVQg1uDuXzIf0Ycj0u5CHL0Y/ci3Su8W8XBYWFhZhJiRFY8OGDbz77rtMmjSJ7OzsMsdvu+22sAlmUfPp2vc0Rn15P9FxUZU+l6bpNGhp7FbP/fjnkAO4I5x24uvH0aRtI/oO68X7a1/hwuvORtM0lnyznGUzVpZfOAEz357LBYPOKhW4blGZ+Mk0pUi+er1BLamdUVPRwLMaKaLNnyLdxj9SIvNXomc+T/j8AgrGkZmQ+ynyyOWGBSEIQq2PkvAyIuU3RPI0RL0fEPV+REQahexk7tfI7P9RnMXJS5HLk7YDcBcPph9EZo1DZj7rR0QX5h+nKtiORzi6hWxJFZH9EHEvgIgtaCmcs7C2j7v0CZ41yCPXIL07Q5rHwsICKxg8TJherU2dOpWzzjqL+fPn884779C2bVtWriy9OPvpp5pZBdmi8jj/2h5M2fs+t78ytFLnUVWFC68z/LQP7jwcckxFfp6HzMNZJDVMYNjLQ2h6fCOmjp/JNY2H8dx1r5OVWlZxNo2ErWuMB3lebn75x6ljFC6ywpkaWOqCHRsjObinuKiipXSUoGiBGgwbZD5usq8CtuOR2n7DApB6HeR+Wl4Jg6CBnobMeMz0GUKJR9hPRtjaFH3mpNSMSt2h4voc6Vlftt3WBkNRMSURUP7fCRF1BSJlGSJhAiJ2FMSOCTC3BjIXmf1GueezsLCwqAimFY0xY8awYMECpk2bxuLFi3n33XcZMGAAu3btqkz5LGoBjkgHVz3Qj+YnNKnQOIGsFG06H0dcsrFISmyUEHpKWmnstq5b+g+Tnv+O569/g/dHfE7GoYoV5CpEL8ik5asgoYV/Ehsm0OmCDiSkxIV13DlfJJF2yIYrRyHtkGVlKkKazMKlNAb9kMlBdYi6Bpk6tKACdkFbpaGB54+KuQR5/zFSwYaMisydWrbZcUFBsLYZpdmLsJ9SjrmLEcKBcF6EiB6KkNlB5tXAPQep14bClRYWNYjCgn2V+aoDmH4Cu1wuOnfuXPR3//792b59O4MGDWLJkiUVDsy1qP289NNobj7xPnIzXeU6X1EEup+QjX9WbGbWe/PpN7w3vYacy6/TVpRrDqlLvn1tNq5sd/DOISE4sPMQjsiIMI977CKlJO1AOvH140g/GB6Fr5BJbzRk0hsNUVTJdfcf4PqHDoR1/GMe71/m+zr7GmYjbUeYJi/MNhYY6f4JEdOm+G/pAekBERn8eSRzyymbBlpZNyQh7BD/CjLtNqOPX/kVo7q544Jyzl8WqR8wxg2o3HlBTwMlBHc4CwuLY54hQ4b4/L1s2LAhN998M+PGjSt1XAjBp5+GZrE2rWgkJyezf/9+GjZsWNR2//33s2jRIm699Vbee++9kCa2qN1sXbODHz/5hSP7UklskECvoedy/GmtmbTrPd4f8TkLJ/2KOyfPqFFh0nUlWGD4509P5cLrz6Zr386cfM6JrF+6qYwLlRAiaJB4+JUMyHPlc3fXkWQeseo2hISEHX8H97cv9/A69L4mHEHJdQ2TX1qRBDEPQOYYzCoIAQYzMl2pjSB/cfDuOROR0bcY8STZ7xecI4EopK0lOC9GRF3tu+ie2orgi3M/SN+/H8LRA5InI7MmQL6v1NsqiAhEwluGYhImhFIPGfQ6FFASwjanhUVdQEjjVZnjVzc9e/b02R4XF0dSUhIXXXQR9957L2+++Sa6rnPvvaHVUAMQ0mTqnm+++YZ58+bxwQcflGp3uVwMHDiQRYsWkZ+fj9sd/kWcWTIzM4mPjycjI4O4uPC6YlgYaJrGa8PfZ+7En1FtCrouURQFzatx/qCzGPHJXdjsxfrrvu0HGNlnHHs2B3ZTsEXYkLosKubnD2e0g5vHDaZBy/q8cus7RZmoClHtKprJTFbhJDLGSZ4736qnUWMw6m/c+Ng+Bt17MGhvi/LiAPLCM5TzCkT8MyDzkAe7mRs36gbI/QxDyfH13bMh4l9CRF5a5oiedjfk/YT5mhclxqy/BKEm++2ha+mQOwlcM0H/D0QURF6KiLoJYWuOlF7Q0w3rixKNzP8DmfMFeFaDsIHjAkTUdQhby6DSSO9u5OEL8a/kqeC4ECXxzRCv08Ki8qjJ67VC2Zq/9CxKpLPS5tFdbv4b8USNvAcladSoEfv27Svzf7OYVjSCsXnzZrZs2cLFF18cjuHKRU3+4B4rfPzEJCY9/63PAFshBAPuu4Q7/ndjqXYpJT99sZh3HviETB9B19HxUZzW6xSWzlhpXkkQoAiBbrLgX6UijDof5S36VzSMMB+4nJAST/rBjArNdyzTqEUe1z1wgF4D06pblFpMOXf8QyXiLETcEwjbcUVNevpT4J4c5EQVY3EdfDdfJH2FiOhsLPBlJohoI6j8yFWgHyE0ZUMgYh5ExNwewjkGUs9AZr9rFCIsjK1Qmxe4YxUWHiy8NgWR+BbCcV7QcfXMZwsUrqNRAAcieSrCfnzI8lpYVBY1eb1WpGi8WAWKxqPVr2jcd999vP7660V/r127lq+//ppnnzWy7DVu3Ji9e/eW+b9ZwlZHQ1VVli5dGq7hLGogrmwX374+2+9iWErJ9+/MIyuttDIhhKDnkHOZdvhjXv5pND0GnEGrk5vT6YIO3PG/G/l821ucO7B7aJYISc1QMjAKCFZYyVAEx5/emutNFv6LTogKa7amY4VGLd18sOgfPl72j6VkVBjdKGRHJdaGieiBSJxYpGRIKZG5kyFvoYmTzSgZBT2z3zZqcBw8w6iPcaCjkao2/gWIvAYoXEyYeSRKZO5X6JnjkPmrTdfzkXo68shAyP2kQMkouIaimI+Sv38a4EWm3YPUDgcdW8SOgui7SlxHAepxiOTPLSXDwsLCL5MmTSr6v9vt5o477uDss88uaquoPaJC6Vjy8vL45ptv+PDDD1mxYgWXXHJJhYSxqLloXo3X7/wQd05gdwZPnpc/F/zNuVd383m80/kd6HR+hzLt3ft3oV6TJFL3p1d40V7VePPNprX0z0vzn6LT+R3IOJzJF2N9ZLU5iiZtGrLn3/JkzTm26Tc0lcYt87ByU4QJ1zdQ/3dwTQbPKsMFKO83kEfCMryIvMyIq/LuRLq+Afdcn8HWvtExFxeiG/Eb+UspXszrhttU3kJE4kSIGwV6ulE75GAXgqaq1fcbxf1yP4WI7pDwJkKJCXiKzH4DtP8wbz2RgAdcUyHmjoA9hVAQsfcZMSv5v4KeC7bWRuVx68tgYWFhgr1793LDDTdw8cUXc9FFF4Vt3HJZNFatWsWdd95Jw4YNueGGG7juuuvYu3cv33zzTdgEs6g56LrO89e9zk9fmAjQBPLdoeeIt9ltjJs9iuj4qFr5YGzZoVnoKXcLUG0qK2b/CWAumFxAdnouUbGR5ZrvWCapgaeOKxlhvniZjsibi4i+AeG8GLSDYVMyQCDtXdCzXkMe7gU5H4SgZKiG0hPSI+zoBb4GaMiMBwGBUFNQlGiI6EFwK44sHi9/OTLjocC9pQtyp/mQIRg6Mv93072FEoNw9jFqbUR0rJW/pRYWFlVLZmYm55xzDm3btqVXr1488cQTpY5X9HfE9K90WloaEyZMoGPHjvTv35/ExESWL1+O3W7n1ltvJSEhoUKCWNRcVs79i0VTfzPdv02nluWa57hTWvDxP69z+b3VF+dTXrr371L+NZ6UZBw20rsmNjBRI0TChmWbyM0qXxrhY5nUg7a6XaBPaQzqyYTT3UnmLUWmXo/MeAQ8f4RtXGztEPm/Qs7bBQ0hWDJFZEHxwYomftBBP4zM+RCppxtDR98S4rg65C1Eev7130XbD5T3+2opCxYW1YGgOPNUpbyq+wILcDqdDB8+nKuuuooPPviADRs2ALB161YeeOABMjMzefDBB3nggQfIygo9s6Zp16lGjRrRoUMHXnrpJXr16oWiGIsha8fk2OeHDxagqMGDnRVVod3prWl1cotyzxVfL447X72JdUv+YfOf28o9TlXz1bhvi74ToSKBlGb1ACMgvGWH5mxbsyN8woWZ+PpxYSt0GG4WTE3iytuD+7Qfc0RcDPlLQN8D7Anv2Pl/gCy8p2F0a/T+g8x6LfTz1NagbQUZxgJ02a8isycgnf0QcSMRcaORmWMx9uLMKB2q4YpVEAshpQfyfkK6FwJ5oJS3mKlARPh2Qz1WkdILeUsM65aIBecFCCWxusWysDhmiYiIYPDgwQwePJhFixZx6aWXMn/+fJxOJy1btmTcuHFFfQsDxEPBtKLx/PPP8/HHH/PAAw9w4403MnTo0FI1NSyOXXZv2msqbiImIZoH3g89E4sv7nrjZh44+8kKByFVJbpevkWYrun0vvE8tvy1nUd7PUNWas2uxVFTlQyAbRsi+XFKIj2vTqOcel/tJH9O5Y0tD1Gx+hj+UECWo8aJtrXgP+GWyQvumUjPWkTy14iIbkZgev5yo5J4QARSuoyIEe9uZNpNJTJJlVdOYVhuoq4s5/m1D5m3GJnxGOiHKcp6lmlDRt9kZPoSlZiYwMLiaCq7encNqQxecp117rnnMmHCBK655hpWrlzJfffdV+HxTT+KH3jgAdauXcunn37Ktm3b6NChAxdffDG6rqNpVV+3wKLqiKsXG9TvXbWrZKZmMazjw9xw/D1MnzAnaE2MQJzUvR1d+3YO3vEYYODDl5HYMIHHLnqW7PScuu36EwZefbgZ37xTn3x3zfgRr/1U1geyvNaRUDXIUD4HGmjbIfczhO04lLhRiKTJlMnmVAYvwnY8UnoKlIzdxeOhE/q1FqSlTXjHd8HBYxCZvxKZNqwg3TAU3zMv5HyAzHqpukSzsDimmTFjRqm/+/btyyOPPBI2j6WQ9/y6dOnCu+++y+7du7nuuuvo1q0bKSkp3HjjjcyePTssQlnULC4YfHbwvC7e4grg+7Ye4O37P2b0gJf44pmpDGl9F32jr+PyxBt4YegbbPlru6l5r3ygbJGtY4m45FiGvTyUW1+8noWTlpJxKLPWZdyqieiaYOK4xgzpekJ1i1L7ETUrv71hhA/1OxKqoqQblowChBIFkVfgP+5FgIgHZ2/I+7nAklGBzTelKUQPR9T/EeGoO25TMuvVwv/57pD7KVI7UGXyWFggq+BVA+jevXuZtmuuuSZs45fbucDpdHL99dezcOFCVq5cSZMmTbjzzjvDJphFzaHn9WfTqFUDVJv/j0tJ05uUEiklK2b/yaejv2b/9oPku/LJycjlpy+WcOdpjzL/80VB5+143kl07nmyz+DocNWQUFTFsNZU4ea3UASn9+nE5D3vcfVD/RBC8MePf1l1McJM+iEb/22OsCxEFUHWJDc5FeynEMbyT/7RD5T6TROx94PawsfcKqAiEl5BiAik+2cqGogvYh9Gib0fodYd12Sp7S9INBBEiXRXooughYVFESkpKWEby/QvttvtxuPx+Dx23HHH8dRTT7F58+awCWZRc4iMieSVX56mzamtAGNxXt5UrmAoIi/f9Ba7NweuAyGEYMx3Izjn6m7GpqEoVjASUkzutIoSrxIoqtHQ8qRmPDf3CTqee1KIV1F+pC75Y+5fPHz+mKKAd92r1ap4lNrAsNH7aN429FTLFr6ozoAXARHnGnETUddSJdXKRUwptwGhJCCSv4boW0pYeRRwnI9InoJwnFPQlk+FtyntwX+LpHYQmf0+esaT6FkvIz0bKjZndVOQ8SswSlFmMAuLKqGOWDSys7PJzc0ttcb3tx6ZN29eyOMLaXJ10717d15++WV69Ojh8/isWbOYNGkSX375ZchChIuaXNL+WEBKycYVm1mzcD1SSlbN/4u1izaWaywhBJcO70Wzdk349bsV5OXm0ebU47h0eC/adGpVpv/+HQf5/Yc/2bF+N3HJMWSlZfP9Oz8ig1QHf3zyA2QcysSV5UKNUNm9aR97t+wnNimG867pTvf+XbDZbUVzfPnsNBZO+pU8V+UvUBVVwR5h47Vfn+WPH9fw0eNfBb0eC3PUb5zHF38EC+C1MI1IKgjcNlMgLxgqoIGIDpI5SgF7Z0TiewglFgAp85CHLwFtLxVPbRtg3qjBKHFP+TwqpQYyC0QkQjhKH8t+H5n9P8qnDKkQcQZK0qcBe8mcicisl4tlLazp4bgIkfAyQgSLJ6l5SD0NebAbge+bQMQ9g4gaWFViWVQiNXm9Vihbi+fGoTgr7/uku93sHPV4td8DVVWJiopC0zR0XSciIgKn08nBgwfL9E1JSfHZHgjTikbDhg3Zv3+/3+OaptG2bVu2bau+lKQ1+YN7LPLCkDdYOHlpueMKFJuC1CQSCRJUm4Lm1blx7LVc90TpTCs/f7WEdx/+jLT96abHF0Lw1X/vUK9JcpljUkrW/LKexd8sx53jplm7JvS+8TySGyXiynax+ud1jLv2VfLdvq144UJRFU45pz2jJt3PdS2G48mreJVxCwDJa7M2c2Jnq9ZIWLCdjIgajHR9Dd59INMo9+59xNmgJIJ7ZtCuIn48IvKyUm1S24NMvbVE9qlwE4GoNxdhaxrymVI7gjx0DhDgd0PEgMyl9KJaBaWeYbVRG/kf3zUdmTHCz1EFnJeiJIwPWe6agJ52t5Ei2K8C6UCk/Ba0ArtF7aAmr9fqmqLRqFEj9u0r9jDJy8ujWbNmPhWK+vXrc+jQoZDGN20Pj46ODnhcVa20c3WNMy89rULBy7pXN8xzBWsVzWuM9clTk1ny7Yqifgu+WMzz178RkpKhqApdL+3sU8nITM3i/rOe4JELn+aHDxbw05dL+OTJSQxuPpyZb88jMiaS7pd1oUHL+uW+NrPoms5fC9eRk5HDuQPLBmRZlBfBy/c2t+IzwoV+GBF1JUryFJQGixHJUwyLRLlcqhQTSoYCthPA2afMEaE2QdSbDbZTyjG3CURMuZQMAKEmI+Kfx7D8lHwmFvhvRpwH9X6A6GGgJBttSjJE34ZInh5YyZASmT0hwOw6uL9HencH6FNzEbEPF1R7972WEHGjLCXDokqp1GJ9Ba+awNHZpRwOh5+e5audZ7qOhtPpJCsri9jYWJ/HPR6P3xgOi2OTHgPOoNFxDTjw3yEj61SYUBTB1y9P5+wruuLJ9/Dug5+EPEaE086NY68t0y6lZOxV4/nn9y0AR6XglUy4+0PqNU2iW7/T2bul6jKcPDf4dbasNpeNy8Ice7Y5mflxMv1vPhK88zGHDZRGoCSAdx0Vdnc6yh1H2NtD8nSjqF3+4tDGyl9EUY0Efyj1EEmfIkSE7+MyHbzrQ5vXLDKtQqeLyMtAbYzM+RDyfgF0UJsjooZC1LUIYYfYByH2QaSU5h/c2lbQdgWb3bAK2G6o0DVUB8LWEpK/RmY+C/lLiw+oTRExDyAi+1WbbBYWdY2cnByeeqrYfTQ5OZn77ruvXLGkprejLr/8cl5//XW/x7/66ivOPPPMkAWwqL3YI+y8OP9JGrY0shMoNgVFERXOvazrkn9WbCHPlcef89eScTj0AnZ5rnyevnI8qftLLxo2rdzCml82+LXEKIrgq3HfMvn57ypUByRUNv+5zYrPqAS+eq0BdbPMjxf0XUAeRN9jVFiuCErZnXZha46IG1nOAYNsTAhn4GrQ7nnBxygvouJVqEXE6SiJ7yIarEc0WIdSfz4ieoihZJTsF8pvpcw1M7PJfjUTYWuNkvQxov4viMTPEMnfIeotsJQMi+qhjgSD+0IIgdPpxOFwFL3Ki2mLxqOPPkq3bt2IiIjg/vvvJyLC2GmSUvLuu+8yZswYfv7553ILYlE7adSqARPXv8pv369i+aw/8OR5aNOpFe4cN5+P/cb/iSZiSnVNJzUEd6mSSF1y8L9DvHHnh4z59pGi9qXTVxbFgvicU5dsWrmFTSu3lGveUBGKQFVVvB4rNqMySD9sZ8c/Tlqf5K5uUaoH72bwboGEdyDrWRM74n7w/I6e9hCQD2oTRNRVCFsbhK010n4qeNYQ1oW/CPJQ01MxXGzC/b1Rw1qJ26hkHSa3YrU5xiM70DVrYGsbnvmqEaE2BrVxdYthYVFniYqKYtSoUWXaK9V1Ki4ujoULFzJs2DCee+45TjnlFDRNY9OmTSQnJ/Ptt99y0klVlyLUouZgs9s4+4qunH1F11LtbU9rzedjp7J5lZEgwO6w0/Hc9nQ4+0Q+eWqyr6EAI41tw1YN2LN5P9EJgWODAqF5dZbNWMnhPUeKYjXyXfmmvihCEZVvYSgQw1IyKpdFMxNo2Owgzigd1fQv3rFCwWc4axxEDYOsJ8s5jhfyZhX8X0HmfoSMuhEROxIRNxaZei1IN+HJBKWAo3fgLmpjKkXJUBIRUTeGedzwIJQEpPMScM/G931WQEkCx3lVLJmFxTFKZVsdarBFI5yE9NhVVZWbb76ZK664AqfTia7rtG7dmtNPPz1spcpdLhf33Xcf8+bNQ9M0Bg8ezIsvvhi28S2qjm79Tqdbv9Nx5+ahazqRMU6EELiyXXz98gxc2W6fi3kpYd+2A9xx2gjsDhsRTnu5sz9JKZn3yS8MGjkARVFodXJzvJ7gi6FQlAy7w44nL3T5BILHJ93PuEGvWW5TlciUCSnM+iSZXtemMuypfdS9vBUStP/A1hxsJ4F3I+WzPhR+Rgu+P7mfgNoQEX0zJH9jVHbOm0/Fnp4KCAciKkhVWkdvYAzgL6uYCmrTgird/jjKrGo/BRH/MkKt/CQQ5UXEPorM/wP0A5RWNlRAMbJ0iTqnTVtYWFSAQHEXv//+O3379kUIgZSStLTQY9hM/yKtXLmSSy65hDZt2pCVlYXD4WDhwoVhT8n10EMPoes6W7duJScnh549e/Lmm29yzz33hHUei6rDGVXaDSIyJpKnvxvB432fx+v1FgWSF36QS+LJ81JRHfOTJyfz54K1jJ3xKOde0523H/gEd7bLZ0Yis5aM1qe2ZOBDl5HcOImlM35nxltzQw6Il1LizdfocvGp/DH3rwpl8Kpr+Pqs+CIyWmPIw/s5qUsOmibIcwkio2WFP1O1EaEfgaRPkRljSlgnKobMfh+ihiBsrSHhNaT7R8j72VTq2hKSUbzg14EocE1HRl3vM8uQ1LNB2w0xwyH7VR/jKSAiIP4NcH9nKESl3Jc0iLwaou9BeFaC9ID9JIS9XQgyVw9CrQ/J05A5b4PrG5AuQBiFA2PuRNg7VLeIFhbHDJWdGaqmZJ36+++//R7r3Lkz69atq9D4puto9OzZk+HDh3PVVVcB8Nxzz5GRkcGLL75YIQFKkp2dTYMGDdi1axdJSUkAfPvttzzzzDOsXr066Pk1OS+zRVn2bt3Pd2/8wJJpy3Hn5JGTUXlBjIqqcOalp/H0dyP47fs/ePpKo+BVyVgNRRG0OqUF3nwv//2zJ6DCcdFN53Pj2Guo1ySZnRt3c+tJD4Qsk82uctWD/Ti15yk82ntsnTGjViV3jdtF3yGpqDbDUiYlKNVZ5LoaEYkfIxw9kPkrkanXhW/gxK8R8ggy80nQD5djAF8ZqATY2iCSvkIo8QBIPRWZ9T9wTceo4QGIFMBbUEywAPvpiLinEPYTjPO8O5Cu6YYVQKmHiOyPsLUph5zhR8p8cM9F5i0GPAhbB4i6EqEkmTtXzzDSDGtbkTlfgucPwAaO8xBRgxG25pV+DRYW5aEmr9cKZWs1tvLraGx/qvrraPiiPPUy/GFa0WjRogU7dxaboXNzcznzzDNZu3ZtWAQBWLRoEXfddVcp7WnPnj20bNkSt9tdplZHXl4eeXl5RX9nZmbSrFmzGvmmWQTm/Uc+49vXZ/sN0g4XH//zOk2Pb8zGFZuZ/MJ3LP/+D3RdElcvltYdW7Lrnz0c3pMafKACTjyzLc/MfIwZb87l87FTEQLTtRsUVWHQYwP48+e/2bj8X0vRCDOqTaf/zYe58dH9LJmdwH//OnBGaVx6wxHiEuuY9Uiph6i/GPRUZM7nkPte+MZ29i+wYIT7AyzAeQVKwvNIPR15ZGBBMLtWug8Som5EOM41UqHaWoRZjspBerchU28CfR+GxaXwM2lDJLyC8FFDxOc4OR8js56nqOI6UORKlfgWworZKEJ6d0LeIpB5YG8PEd0Qoo7uPFQztULRePq5ylc0Ro+qkfdg9+7dNG1avnpCR2PaderoRX5UVBTZ2dlhEaKQffv20aBBg1JtKSkpeL1eMjIyiqwchTz//PM8/fTTYZXBonrYu+1ApbsOCUXw+w+raXp8Y07s2panvxuBJ99D5uEsxlw5nr8Wrgs5VmLj8s1cf9xdfLXzHRod14Cvnv+W3Zv2AoaFRA8wnq7p5Lnz+WfFZkvJqAyk4OCeCK7teBK52SqqTUdKwbT36vP0Jzs46YzcuuNC5eiFTL0BPCvDP7Z7RvjHBECCewZSfxSZ/a4PJaOgD0DuZ0bRuxocX1ESKV3G+1FkASp5XV5k+v2QPBVhPznwOPkrC5SMo8fQAB2ZdjfU/xmhpoRN9tqI1LORGSMhbx6GcqoAGqjNIOG1oPfZwqKuES4lA0JQNNLT03nppZeCto0YMaLcwni93jJ+11pBEnxfweAjR47kwQcfLPq70KJhUfuITYhGUf2nnQ1Gn5vPZ+5HCwP2kVKSn+dB0zS2rdmJOyePpsc3Yubb8/j3j63lDsh2Z7t5+qrxjP9pDD2HnMOhXYfx5HvZ/Mc2xg1+zec5iqpwWu+OLJ3+uxUIXklomuDX2fEUpvfSvArtOufw8tSt2B116Z4LcE2qbiHKiRfp2QSurwma0cr1LcTcXiVSVRjXDwUB3b6QgILM+RiR8L+Aw8icjyltyTh6HK9x72LurpC4tRkpJTL9Tsj/vbCFovul7UGmDoHkGbXGEmZRhVhZp8KCaUWjf//+bNy4MWBbRTNDJSUlcfhwaR/fQ4cO4XQ6iY+PL9O/okVELGoO513bg7kfB1YU/CGEYOuaQNllCpCwbslGpr85hyOF7lECFEWpsDVlzcL1PDPwFVS7Svtu7eg15BzOu7YHaQczePehT0FKhCIAgebVOPmcExn11X0MSLyxQvOWJCYxmuz0nDrz4xUYXzdBsunPaGZ8VI+Bd4XH97R2UNs/EPkgg1nPBVLbSW0xUMm8hQQuJqSB+6fgA+WvILACpiPzlyOou4oG+cuNl090kHnInA8R8c9UqVgWFnUF04rGxx9/XJlyAEZ0+6ZNm0hLSyMx0ajOumzZMrp27YpSVyM46winXngyHc46gQ2//Rvyol9KyZY/t5vqu+KHP486mbC5bC3+xniYLZy0lIkjv2TsjEcZcO8lnHN1N3785Bd2b95LVGwk5w7szknd2yGEwBHlIC83L8jI5vB6NBzOCPJc+WEZr3bja8lptE0c15gze2fSvG147rtFZWIz/OmDIipe/bwcSD0Vcr9GuueAzAHb8YiowRDRI/DGm8wjuAJofY/DgXTPwr/VB6PdNQMZN9ZKo29RirqSdaqyqVGr94YNG9KnTx9GjRqF1+vl8OHDjBs3jvvvv7+6RbOoZBRF4dnvH6NLn05A6NYxkzkNqgx3Th6j+j7H3q37SW6UyKCRA3jko7u487WbSNufzkPnj6Zv1GC8+eWrD+Jzzmy3pWSYQFElP3yRXN1iWJghojtkvWKioxcR2bfSxSmJ9GxCHroYmf2aUZtE+w/yFiLTbkZmPhX4N8nensCPXwVsJwSeX7rBfhqBK48riIgzA45zzKNnELxujJvwF4C0sLCAGqZoAEycOJG9e/fSqFEjTj/9dIYNG8bll19e3WJZVAHR8dE8+/1Inv3+sRqnOJQHb56XGW/OLfpbSsnb93/M2KtfYf3STeS7PZWeZcuiLLom2Lq+8jKJ1A2qYudXhcgbQdtqomt7hP0UU6NKPRuZvwbp2YCU5VtcSulBpg0DefQitmDX3DUFXJP9ni+iBgaZQUdED/E9d/7v6Kk3IQ90hPxf8L9TLwA7RAab6xhHbUrQpY6SjBD2KhHHohYhq+BVB6hxJUTr1avHjBmVlcXEojaw+qe/UWxKyAXwaiILJ//K7a8MJTs9h5++XML0CXOA8LlrWYSOEBJnpHX/K4YkcIxBONAgy2RyEXvroF2kno3MHg+504ACdyylHkTfioy8AUEuCBtCRAafL+/ngrS0/hDInI8g8lqf1lmhNoG4sUbtkcIMSAXngQRnX3BeXvYaXDOQGSMKzgl07wvT206o8xmnRNRVyNyPAvRQIHJQlcljYVHXqHGKhoXF5j+3HxNKBkDagQwuix1Cnju/UtZkZiuZWxQjJfS4OLO6xbAwg37EXL/8wAVdjXSy14P3H0pZIPTDyKwXIOsNJEbBUGk/DRFze8D6EzJ/Jcbj059FRIK2E+meg8xfbLjvqE0QkVcVFRIUUQNBbYHM+QDyfzXkUtsgom+AyKvK1HeQeioyYxSlsiYdjUgAJckq2FcCYWuDjL4Vcj70cVQFtQUi+qYql8uiFlDJMRqWRcPCoppwRDsQQhwT7lNApcZNHHdycw7vSSXjcFalzXFsIYmO0zinf1p1C3IMUBXfT5Nz6LuRUkMIP/EKuZOMOAq/4+UW/9ez2nCLin0CET20YnJl3E9xILKKzP0MGTUUEfs4QgiEoyvC0RUpdUBHiACPZNd3BI0jEBGIenPqbFCzlDrk/4Z0zQQ91VDuoq5ExDwCSkNkznugF2acs4PzMkTcCIRS9YkELCzqCjUuRsPCovtlXZBBHuT+nqNGCtm6gyPaSffLz0BRra+yOQQ5mTZWL7IWFscWhquQP2TuV5hXjAyLh8wah/T+57OHiOiC+eBhrfS/uZ9B7ielxxNKYCUDI/g86CNbP2giFfBR48p8pAxfUorqQuo5yLQbkWk3GZXq8xeBawryyJXIzCcg6jpE/UWI5OmIpCmIlGUoCc8jlMTqFt2ipmLFaIQFa3ViUeO48LqzSGqQ4HPxLIRAtSk0bNXAyGhZoFcUKhiNWjUoc86xzD8rNrPwq1+JjHFaykYIfPhsI7y1f21lAYAKjnMD7+Jre8sxroJ0TfF9yHEhKA0InPHJPzJ7Anr+6tCstiKS4EH4AkRE8Pmljsz9Bv3wpcgDHZAHTkI/MhjpLl8to5qAzHyyRFG+o5Q711TIeQ8hbAh7e0TEqQilbG0uCwuL8GOtTCxqHJExkbz002iSGhk7TYqqoKgKQggiIiN4evqjvLdmPPe+eSttT2tNvaZJnNi1LQ9NvJMJy8fhjK47RRx1TSc/z0Obzq2ISYiubnFqDXt3OBDWr18tw98iW0dE3xLk1PJYsDTwbPI9nLAjEj8oGLfkB8mk4iGzIfUa5OGLkXn+iskdNaezJ4GtKCpEnIUQgX//pJTIjFHIzFHg3Vx8wPMnMv12ZPYHpuSpSUhtL7hnEyiNrcz5CGmqJouFhUU4sWI0LGokLU5symdbJvDrt7+zct5qdK9Ouy5t6DX03KIFdb87LqLfHReVOffaxwbwyZP+U0sea+iazpqF66tbjFqGQNdAUfy74VmYpbKzT/mbw1jgi7hnClyZAhDZH3I/J3AV7aNRCqwIfiSynwD15oDra6R7Nug5YG8HSjK4vvEhrw+07YarT9Jnwa8hogfYTgTvv36uQ0fE3A4YGbbI+wVkFqjNIaJbcXB53jxwf1twjix1PoDMftmwENmPDy5/TSFvCUHvt8wEz1oIdp8tLAqpbPemOuI6ZSkaFjUWe4Sd86/twfnX9jB9jubVaN2xBaf16siq+WsQwsgyVBdQFIFuZaAyRVyiF9VmKRnlRwF0iLyuYFFd2TvFR32uRSJEXYuIGmikig2CiL4R6ZoGMhfzyoaOcPYKPK6aDDF3IGLuKJY07zeka6rJOYyVjMwch6g3PfBcQoHED5FptxYEttsKztcBGyL+ebB3QWa/hcx+D6MIXQFKI4h/DuHogcz5gqL3zycq0jUZYX/K5DXUAKQHUwrvMRCLYmFR27AUDYsazaHdR5j9/nz+WrgOIQSnXnAyl9x2IfWalK3svHT677x+x/ukHcgoaqsrSgZgKRkhcEbPzCKLhkU5sHdERA9DOC9EV2Ig572qnV+mIZy9TCkZAEJtDElfItPvAW0nhouTjv+FqQpqQ3D2CV22iDNBbQHabswpNTp4NyC9WxC2NgF7CrU+JH8H+cuQ7gWAG2E7HiIHIJRE9KzXIOdtH1PsR6bdBkmfg3cDgStla+BZZ0Lu0kjtoGE1UFIQSlzI51cIeweCbw+rYGtXFdJYHCOISk5vW6mpc2sQlqJhUaPQNI01C9dzeE8q+7YdYPKL09E1vajA3Ybf/mXyi98x+puH6dr3tKLzfp+zmqevHH/MpMS1qFxan+SqbhFqKQpE3YwSV6KQXv5vYZ7DjCuWinTPQdg7mB/VfgLU+9GQ1/M3CDsSB2S9hLH7rxTM7QW1KSLxI4SJwOoy8wgBCa8bdTukC9MWFO0ABFE0jPEVcJyFcJxVql1qRyDnfT9nGZYPmfU/EI4gmalEQJexMiPn/47Meg08fxS0qEjnxYiYBxG2pqbHqRD2joYS4d2C7/utgvNiwwJlYWFRpViKhkWNYcm3K3jr3okc2eu/xoGu6UhdZ8yV4/lo42s0atUAKSXvP/JZFUpqUdtZOieeK4Ydrm4xaif6nqP+DnfxQzObBcKIiQgRIQQ4uiMjugGgCIGMvAxcM5DedYAd4TjXKHgXJN1swHns7SF5hlGROncapdyY/KHUK/d8ALh/ILBSo4NnpVFx3P19wL7C0dPUlNK9EJl+x1GtGrjnIPOWQvI3CFszU2NVBEO5exV5ZLARl1Lq2hRQmyHinqh0OSwsLMpiOQ5Y1AiWzVjJ2KvHc2Rf8EJqUhoKx6x3fgRgx/pd7Nyw27JmWJjA8IlftyKadSui0MyWQrAoQIA4KruZrTXlTfPqn2CZ4zSErWWpFqkdRs96Df3g2ej7T0E/dBEy52OkXlyMT+atQE8dVpDStT36kashbzFEXYcS/wJK/DMIZ88KKRmFCFszlLjRiAYryt6z0j3BdrzxqgBST8XU++DsWdDPV4CSAkoiRF4efD6Zj8x4jOI4kZJoIDORWc8HlydMCFsbRL2ZEHUDiHhAgNIQEXMvInkaQkmqMlksLCyKsRQNi2pH13XefuBj4w+zhYA1nRU//AlAxqFw76haHLuIotfoG1uxfqWxAKweHbU2RqJrCGffUi0iahChZXMKhkLw4HKbkUmqAOndiTxyGeS8C/oBwA3aDmTWC8jUa5B6JjL3K2TaEMhfAngMmT1/IzMeQGY+U2kbFUJEImJH+DsKCETsyApX8xZqI4K/DwJh74xIfLdEXQ6FIgVFSUYkfmauUnbeQpBp+P/R1iDvZ6RWdZZDoTZEiXsMpcFKRIN/UFIWI2LutCp/W5QPq2BfWLBcpyyqnY3LN3Ngx6GQz9O8xi5a/WZ1x+9WtatonnAu6uou2Rk2HrmyNSeensOwp/bR/vRcv31zshSyMxRSmnjDmKmqtj1lFLCdgMz/E5n7JYgIhOM8pKMPOPuDe0aY5gkUqGxkSxJxo4sqOkspken3g5521LkF99e7CZl6C3jXFrSX/P4U9Hd9AY7uBbv94cdQxhRk1isg04sPKI0Q8WMQDvOZ9fzivBgyn8G/kqZCxNkItR6oZ0H9JeCajvT8BaiGDM6LzceleHcYYwZz19J2gVpBt7ByUFHFzcLCIjxYioZFtaHrOoqikHYgPeRzVZvCyWefAECTNo1ofWpLtq3ZiTzGMy9ZSka4EWz8I5o3RzXh7R83I2VhyluV1IMw/cN6LPgmiSP7jcXXWX3TePKD/6pV4mpDRIN3E3j/wVigK0j3D6CMh+g7QdjB/QvI8uxgm6zFoR6HiH0Y4byguM37N3iD1JHxrgk2MDL3s4KieJWDiLoGIgdA/jLQU0FpAhFdiutbVHR8JRZiRyCznvFxVDEUw9iHi5u0XUjP2gLLhBep7UKICKSjj7lFuhJLYKWwZD8Li9qHlXUqPFiKhkWVcvC/Q0x95Xvmf7aInIxcEhsm0PWSziGPo3l1LruzD7Pem89no6eQdjAj+EkWFj4R5GYZriNCAAlvkpp6Ovf2vZcj+93oWvGiq9NZOXg9YLNXk6jVicw6qqFgkakfhKwxBW12sHUEkQyen82PLRqC3E9gZUMBZ6/SSgZA/hoqXjSwfCldQ0WICHCcF/ZxpXYE3DOMCtmOXuD5E/QjxR3sHRFxY4qK8En3XMMKhKDIIuFZjUxfBZFXQ9yzwZUNR09gLP7vuwC1FaitK3RtFhYWtRtL0bCoMrav28l93R/HlZNX9GxK25/OvE8WmnYJUm0Kmlfnthev55Vb3mbLXztMzW25HFn4R5J6yMZ7Tzfi1HNyaHeO4MvRI8soGQD1GnlQrV/NAHhMWA98EP8CpN8QpJMEzYeLZRgCtw1qp/Yocz40XLKQGK5lEtAg4gKIGmgEzatNwT0f3T0bpA65n1A2iLvQjWyqUQsksl/AeYWagowcDK4v8a1sSETs/ZYLk0Xtpo5YHSoT65FpUSW4ctzc2+1x3Dll/YelLtGloQQIIXwGZTqjndgdNjr3PJnL77mET56cHFTJiE2O4aEP78BmU1n09TLmf7G4yn80hCqQmvVLVbMR5OWqTP+wPt++X58bHnma+V81QNcUHJEa1z94gLYdXbhyBIoCmreOWjQqDSfC0dmoaREwCFwaheqkt3RWqIgeVPyLrYLjwgqOUfXI3KnIrJdKtJRQHPIXgtoEhBN5ZFBB4LYNw4IR2HIkcz5FBFE0AETcKCRecE2hOLBcAyIQcU8gylPw0MLC4pjCUjQsqoRx17zqU8koREoQiiCleb1SgeEpLeoz/JUbOPuKrkVtG1dsZs0vQXyygawj2TijHJzWqyNv3PVhDS1eKwAArClJREFUtexMWEpG7aHQevHpS40AuPrOA9w8aj+KUpyVytqcrQRsLRHCgYwcULBgDfCd0fdC3nwj8LkAYWuOdPSEvJ8Cn+uXgsxP0cEsKjULKTVk9oRAPcD1JdI1GSjM42wmn7MO3nVIKYNaI4SwIeLHIqOHGbUzZDpCbQbOSxFKjMkrsbCooVR2Zqg6sjywFA2LSid1fxq/z10dtJ/UJQ+8dzuRsZEc2ZNKYoN42ndvh6KUDpb89dsVKKpSVC08EAd2GoGpum4iaNHCAhCK5KQu2dzy+P7ithLrLUvpCDP2TgCImLuQrqkEzmKkIHOnIUooGgAi/gXkkStB2xni5AKwIxJeRdjbhXiub6SeDZ7VIL1gb49QG4Rl3DJ414O+P0inwt+9UFc0akguT8LWFGJuq5UJmy0sLCoXS9GwqHTW/LLBdDaoCGcE7c8MXLjKneM2vciLr2dkPOl47kn8MmVpUUpcCwt/SF1wzd2GVc3X56ywrThDlUWFcE1FOnshHGcjRWzp9K9l0H0uroUSh0yeAYfOARlCXZ2YexCRgxBqxVNkS5mPzHoVcr+kuBK4gnT0NlLYhrtgnO4/HfNRHUMcWAXH2aFKY2FxzGFlnQoPVsE+i0pH85oLwnZGOWh3Rpug/Vqe1AzNhDUjKi6SLn06AdD/7ostJcPCFFGxGl3OzwqoRFhKRjjRkRmPI6UGakMCFzJUQGnk+4gShUj6EkSiiTlVcPREibk7TEqGRKY/BLkfUaxkAOiQNx955FrD0hFObC2pnKKPOiL6lkoYt3Yg9Syk5x+k979KK+JoYVGXsBQNi0qnXRdz6Q373dmbCEfwKNsLrjsbhzN4Uambxw0moqDfiV3bcserN5qSw6JuEx3nJUylDSxMIQ0rRf4yROTVQfrqiKir/B4V9naI+vMg5lEQ/mIECmIyYoaXV+Cy5P8OefPw7aKkgfYf5H4VvvkwqmATcS5FVb3L9iC0R7wKCETcWERElwrLV9uQ2iH09MeQB89EHrkMebgn8kg/pHt+dYtmUV1YlcHDgvU4tah0mrVrQqcLOqCo/j9uDVrU59YXrjc1XnRcFA9/dCdCEQil7I6eUAS3vXg9/e8qnfHkivv6cvXDl4UmvEWdIzPVhhYkZtayZoQbYSzGI68EWxt8L54VsHcJmh1KKAkoMbcg6i8uUbNCpchTWMQhEt9B2E8Jm/TSNY3Aj1Md6ZoStvkKEXFPgIij7P0quN7Iy4PIJcB+hpHONvpmRL35RmHBOobUDiOPXF1Q3d5TfMC7GZl+FzJ3crXJZmFR27EUDYsqYcQnd1OvSRLK0YqBgJTm9Ziw4vkyQd+BOO+aHrz802hOvaBDUZsjMoLul53OpF3vMfCR/j7PGzL6apqf2CSg0mNRNxHC2GLq2D3HUiSqHGkoAEoUIumLgmJwJd8EGzivQCR+UDq1bQCEEoOS+D4i+XtEzD0QfQsi/hVEyq8Ix7nhk9y7BdzzCRoLoR0IfWw9A5m3Apm/EindZY4LW3NEve/A2Z/iOiACHOcgkqcgYp8AW1vKKiLGvRWxj6Akf4GS9BlK7CMIW/OQZTwWkNlvgn6AsokIjC1nmfkMUk+varEsLI4JhDyGnBAzMzOJj48nIyODuLi46hbH4igyU7OY+dY85n70M+kHM0hqlMglt15Ivzt6Ex0fXe5xc7Nc5OXmEZcci2rz50ZQTPqhDF668S1WzgmeCcvi2EYIiWqXSF3Q5Dg3V9x2mN7XpFpF+aocByLlt1IpUaW2HzwFVb/tp4UlliLcSO9u5JHLzQWgKw1RUhabG1fPRmY9D67pFO2wi2iIGoqIuRshyrqYSj3XqAauxCOUuNJjZb8Orq9BuoxGtTUi5i5E5KWm5DmWkdKNPHAGpWNrjkYgYh9HRA+tKrGOeWryeq1QtuMffg7V4ay0ebQ8N/+OH1Uj70E4sR6nFlVGXFIs1z95Fdc/6d/HujxExUYSFRtpun9C/Xiemz2KPVv2se7XfxBCcGLXtnz+zFQWTloaVtksai4Nm+fx2swtxCV5UVTQdTi8z86Mj+qRk6nStlMOZ1yQTQiGNotyImKGlam7INSGBcHh5pH5a5C5X4LnbxAOhPNCiLwWodYPp7jF8+W8DzLHRE8FHOcjZR5COAKPKd3I1CHg3UgpK4nMgZx3kd7tkPB6mfSzQokCJarMeEKJQcQ9jox9CLQ9gAPUJlbF7kK0wwRWMgBUpPaflb7XwqIcWIqGRZ2lSZtGNGlTnMGmxYlNq1Eai6rk1HMyeWHydgAyjqhs2xDJtx/U4/cFcQgFFEWieRWi47yMfHsnXS4Ic8YgCwz3HRWib4Xouyo8msx+G5n9mjFmgQuMzP4Hcj6CxI8QEadWeI5S80kNXN8RuO5HITq4JiHdM5FRgxEx9yCEn53S3Kng3YDvSFEJeXMhfzk4uoUkrxBOsJlLzFGnMFVYUIKIrXRRLGoYVsG+sGDt1VnUaUp6Du7ZHKz4lcWxwg0jDpB6SOWle5ox6NSTeOya1vy+IB4QSF2geY2fxpwslSeHHsdfS8vv2mfhB6URov4SlNgHERVM8yXdCwuUDCi98NdBupBpt4Y/vax0AXkhnpMDORORqbcgZb6fYYMFHqsFhQ0twoFQEiCiO4GXQxrCeUkVSWRh4R+Xy8WwYcNo0aIFTZs2ZcSIEQHTMOfk5FC/fn1eeOGFKpSyNJZFw6LOkZ2ew3ev/8DsD+ZzZG8aMQnR9L7hPDyeIKmGLI4JouM0mrdxc2/ftuzd4UDXAhXMEAgh+ezlhnTqsbXqhKwL6HsxU0xO6jngnofUdhuLQufFoNQDbSvo6aA2QeZMxFgo+hpPB5kF7pkQNTh88otI41UY92AaHTwrwfUtRF1b9rC2l8BbnQXpck0itT3gXgjkga0dRHSvsGJ3rCFi7kamLsewsh197xVw9EbY21aDZBbVSg20aDz00EPous7WrVvJycmhZ8+evPnmm9xzzz0++7/11lukpaVVUNCKYSkaFnWKtIMZ3H/WE+zfdgC9oFp5dnoO09+cg91hfR3qAqpN593RjdmzzYGUwb2uVbskIdlLTpZCdKxV9DGsBFmky9ypyKxnC/rZkGiQNQ5EAshQHp4KMn8FIoyKhhAqMvJKyJ2EOfepUmcjc79C+FI0RGKQuA/FULSCIKUbmfEEuL8vmhN0UJtA/KuIiE4hynzsIiJOh4S3kRkjCgL7bRhKqw7OSxDxz1WzhBYWkJ2dzaeffsquXbuw2WzEx8czcuRInnnmGZ+Kxt69e5k4cSL9+/vOwllVWCsrizrDqvlreGHIBNIPZpQ5pms6njzLolEXyEy18eMUcxmM+gw+wm1P7iUmXqfW5Odz9IW8H6jxDsAiCtQGpZqk1CBvMTJvAXi3gWdViaMlvp8hKRkAksp4A0X0MKR7jmFZCUnZkH6tEiLqCiPdql9rj46IvDzw6FIi0++HvF8o/hwU/KvtQ6beAPWmIWxtQpD52EY4LwDHUnD/iPRuQ4gocPZG2FpUt2gW1YSQxqsyxwcjy1VJHA4HDkfZpBGrVq2iVatWJCUlFbV17dqVdevWoWkaqlo66+b999/PqFGjWLhwYfiFDwHLfmpRJ5jx1lweu+hZn0pGIbpW/GAvU+/D4hjC3Htbv3E+D4zfTUy88bmoNUl6bO0wp2Q4wHm1kTa1yh8FKkQOLJWBSWoHkEf6I9NvN9yKSikZFUdEnO6zXepZSO9/5YrhEGpDSHgb1FblEMhPcHHUYFCS8V20UAXbSUGLFuJZC3k/49eVjHxk9nshiVsXEMKBiOyHEnsfIuY2S8mwqBKaNWtGfHx80ev555/32W/fvn00aFB6cyYlJQWv10tGRum1zVdffcWRI0cYOrT6UzJbFg2LY569W/fz1n0fmeorBPS74yI2r97Gxt82V7JkFjUXSYeuOUhZixSMQuQh/McrlCByAEr8WKTnGmOHW7oJ3QWoPChga20U0StASh2Zdit4C+NgwimHMGIpjrICSM8mo75E0YJcRTouQsTej7C1DDqq1HORmWOM2A8TsSalUSDyMt/SKkmQNAmZ/gB4/6ZYMZZGIb74l3zW0Sglm/t7SmbfKosG7h+Q8nnTBRAtLOocVRSjsWvXrlJ1NHxZMwC8Xm+ZwG9NM77jJdNVb9++nccff5zFixfXiDTW1i+MxTHP7PcXIIRAmvjFkBLanNoKTdP5Z8UWpF7D3U8sKglB/5sP1z4lQ0kBkYwpq03kIACE/RRInonM/QxcM434ABFRECcQ7s9/HEQPQkTfjlBiDCuCaxoy9/OQApwDU1LJUgEbIuGd0kXsPGuRR67HKIZX2FeDvHnI/CWQNDlg8K+UOjJ9OOT/TuhKhgoiBhE1xG8Po+L3NKTnb8j/C4QNIrqZUoCAAleuYHgM5VKYSe9qYWFRWcTFxZkq2JeUlMThw4dLtR06dAin00l8fDxgZKW64oorePHFF2nWrFmlyBsqlqJhccyz9a/tpdyiAiEUQdvOrXj9jvctJaMOk5SSzwmdc6tbjNCxd0I4uiNzXgvcTySXWkgLWzNE3OMQ9zgA0vUDMuP+8MpmOxEizkFEDjSUDG0f8si1oO8L7zz2bkZGKuEAZy9E5GCErbhGjhG/8CiQT1klQQOZi8x8EpEcIM1s/hKjlkVIFGQ0UhsjEt4y3K6CnWE/GewnhzgPRsB30MFjjTgZCwsL39SwrFOdO3dm06ZNpKWlkZiYCMCyZcvo2rUrSkFl2Z9++ol//vmHYcOGMWzYMAByc3NRVZWffvqJ+fPnh/USzGApGhbHPF6POTcMRVE4f1APtq/bhea1sgvVZc6/Iq32WTMAsCG1g0ATYI/fXiLmFvD+i577FXhWA3ZwnG/ETeh7kZ7Vxk63T6uGrxSgwRBGpWvvRmTue0i1LeAJs5IhwNYWkfRRYHcBz1+GIuIXDTx/Ir1b/AZLy9zpBHZN8oGShIh/uUrSy4rIK5E57wboURgjY4VpWljUFho2bEifPn0YNWoUEyZMID09nXHjxjF27NiiPpdeeikuV+lsfjfeeCMnnHACjz32WFWLDFjB4BbHODs37mbj8n9N9e10wUnc9+6wKsk+5Yxx0u+O3jw9/VE6XdAhaH+hCtp1aVMj/C3rAvGJWu3JMlWSvB8g424CKRk4LkFKFXnkcnBNA+9moxJ1zttw+Hxk6iDI/aIgpWzhTVAwFtYCiEAkvIlIWQUxDxQcLxm4XPhYiaVUfEFJtM2g7Sj3ZZbFmEfEPhz8O+Ldbm7IQP30g4QcR6I0QDjOqpLFvbA1h/+zd97hUVRdHH7vzO6md3qR3qsovYMIggiiAioioKJiLx92sSAoNsSODRQQRRHBgqKCFEEFFQvSpXfSe3bmfn9MErJkW5JNgdz3eVaTmTv3nt0su/fMKb+wmzyc1UGvgQi/odTtUCjOZPK6TpXmo6i88847HDp0iJo1a3L++eczceJEhg8fzrx587jjjjsC/yIEABXRUFQYDv93lG/eXcmBHYcIiwyl98hutO/XOj8kWBxmT/7Ad0RDwJ1v3EjrHs1594EFbPgysN1u3GE6DW5/1fqiX/rq1whNeE3Vkoak1xVd2fbrzlK3TQESgWmAftZ9QgowDua2vwXXzXLBPIHT/82YYO+OCO4LIcMQmpUPLMJvRjo6I9Peg+y1ueM6QFA/SHmydJ6CVh3Mk1jtbnOjCiISIh4C4zhm4n0gBMLR2dJAEKcVVmp+qrwLL+P0mpBTlIiGBkG9/BwbIELGgLBD2oe5DQIAdAi+CBHxoFV0rlAoziiqVKnC559/Xuj4mDFjGDNmjNtr5syZU8pWeees+xpVnJksfPoz3nloAZqmIaVE0wRfvf09Lbs1Y+qy+4mIKXrBYvyRBH756jefWR6X3j6Y4NAgJra5G6GJMkmbEgWcpz3/7PerHmTek4voNPhcNn6z2e+aE0Xx+Gt9GKPdC62e4UhwbsavrlQuaCCciLDCrRKFowPC0cF1ldRXkUVNLfKIAPu5EHE/Qq+K0GsjzQTIXAFmEtjqIEUsJN6KlEnkRVdkxmJImQExbyPsrU7Zpp3jx5IR4KEdLuSmJmUu9d9+bIjQK/0cXzJk1mpLhyPnj9wjIRA8BIKHIxxtlIOhUPhLBavROFNRqVOKcuf7+Wt458EFIC0tC2nK/M3+1p938OSoF4o17/ED8T7/Ies2HSPH4JlrX8YssG5p0/S8hvk/B4cF+3VNRkomXYeez7n9reJQ3aYjlN5HqbDpxwiOHbSfmelTflHU97kJ2T8jzRS/RkuZhb96Jd6JQUT8DxH7PpqjPSK3yFloMYjQkVb6j709JN4IMs82g3wHx0xAxl+LNONPTZm5xLdttpYI4fB83tEFgi7wPQ8a4EDEvIbQa/oYW3JkxmJkwg2WjkY+GZC5HFKm4V6bQ6FQKEoP5WgoyhUpJfOf+sRj4a1pmPz+3V/s/MPPvOoCRMb5joKYhsl/f+71S6AvKNR9b+vicN30q/J/7jOym1+Fxza7zvH9J5n+9UPMWj+N4bcOsq5VzkbAERoEhyql+ELIDKQ0MbP/wEyagnm8P+axnpgJtyKzfs4fJmzNcVHyLhY2qLYSEXa9102/TF8AMguP4nQyFdIXnTrkopbtAeOY19NCCET0TAgdBxT8XBCg17dE9eztIexmRNUVCDdpUzLnX2Ta+9Yj51/v9viBNJOQSY9iPTc33bSMfcjU10q8juLsRMqcQhoNlZ2KWKNxJqJSpxTlytG9x9m/9ZDXMZqusX7pRhq3L5r6bs0G1WnWsTHbN+3ymJqk6RrH9p/0Gcmo07QWul1j35aDJf4wbnJeQ1p1a57/++Ab+jN/2qc+rzMMk7CoUIQQtOjchBadrfakQaFBfDNnpWrHG0A6D0gmMka9ni6IcGTG55D2NsgE13NZ3yOzvkWG3YQWcTcEXwApsVAwklBUQiegaX60X81cjvcULROZ+Q0i/Mbc3/1I5xK+xwjhQEQ+gAy/zVIxlwbYW/psWyuNo5YYX85GChbLS/v5iOgXEXp1b5d7JuNzLF0QTxiQ8TEy4h7v0RpFpUGaSci0OZCx0Kp7EiHI4EsRYROshgIKRQBQEQ1FuZKd6e2L0ULThF/j3FEwcuCOi28agKb7/mdgSpO9/xwIyB2fHZt289PSX/N/d+YYfuVqSlPS8/IuhY7f+vIEzh/YHgDdZj0XTVdRjpLQY3BSBU2bCqbc0l9kKqQ+W9jJAPI372lvIDNXWJvwqJmAdwVrjwQNRkTc6addmX6MKdDu0X4+3l9DPXeMfwgtHBHUGxHcz7eTYaYh48fkthQGlyTwnN+R8WOQZprfa7vMbfyHz/eGTCuZ86c4a5BmPPLk5ZD2em5zBax/JxkfIU8OR+ZsKV8DKwKyDB6VAOVoKMoMKSV/rPybxS99yZezV3Di4Emq16tCcLj3GgVnjkHj9vWLtea5/drw8MK70O2Fv4CFgNWL1tPkvIb5G3R36DaNdr1beTxfHN68d26+0+KPowNQv8051Gxg3e3ctXkPM298k+ta38VtXR6kYdt6PLjgDvpd3ZPzLmzHeQPaBdTeykbTdhVIrE+rh4h+AxE7H1H9N0S1DSXbxAekdsITmnWHFBBBXRBxi31s2k+3RYeIR607+8LPgLu9Fb4dh1P/fkXY1XiPahhgb40ZPwHzSGvrET8OmfWjf/Z4I+OzXAV0d+tb6U1WDUkxEGH4tXNRIn0KQCY/BcYB3ItWZiAT71KpVIqAoFKnFGXCto27mH71SxzccTi/lavQBBde24cLx/bmizdXuO2kJDRBZGwE3YZ3LPbaW3/egXQzt5SQdCKFnb//5zV1yjQll905hG2/7OS/v/cFJEXp0M6j3NN3Ck8uvZ9q51Shev2qHN1z3Os1E5+xWtd9/upyXrn9HXRdy7d775YD6DaNx5fcR8eB7Xntzvf47bu/MJyB6PpT+YiMcVYcwT4tEmznINPnQ/LjgJ7bKrW4NRCluXkwLbE7Ka06BnszRNwCTOchSF9odUIyD4Ox14MtElJfhtCRgH/pPSL0amTWD15GGIjQU5FNYW8DEQ8gU6bjKrqX+7OjL6Q84Xou+2dk9k8Qfgci/Ba/7HKHzPjMrzEi9Ooizy2CByLTZnsZoYGjE0KL9Gs+aabmFpVLKyVMiymyTYqKiTTjIfMrPDvcBhj/Wel9juJ/9yoUoCIaijLgwPZD3Nt3Cod3HwXI36hLU/Lt3FUc3XeCBq3rFirI1m0aNrvOwx/dhd1RvLu3melZfDF7BaYH58A0TA7tPMLI/w1DCOES2dBtGkIT3PvOJA7uOEJmepZfTkZM9Si/bPt77VYeG/EsQghG3jvM4zihCarWjSM5PpV1S37mldveAYmLc2QaJs5sg8dGPEv8kYRip5opLFZ8EkNOdnlbAaCBFos8McTaqDu3WwrbaW8Xby6A4MsCaqFfK9tqoUXejYh9D6S3aJFppWZlLvd/ckcPCMnbmBf8DMl9vmETC7XfFWHjEbHzLb0PEWE9gvpD5BOQvTJ3VMFNmPWzTH0JmV0CnR2ZgHdHTxY7tUnY24CjJ+6/1i01dxHm20mSMgszeRryWFdkwjhkwnjkse6YiQ9azofizMe5C9+1Shrk/FMW1lRcVOpUQFCOhqLU+XD6Z+Rk5biNWEhT8vMXm5g0czzXTBlJTI1owOqw1GdUd1795Wna9y2snC2lZO+/B9j6yw4Sjyd5XHvfvwfISPGew63pGhExYbz+2wwuHNeX6vWrUqNBNQaN78ebvz9LwtEkplw6g0O7jnicQ2iC9v1a88y3jzBp5niv6xV87n/88Df//LSNoTdfyLBbBgGn6izyFI6lKTm+/yRPj5nFYyOe85j5IqUkOyObm8+7j12b96hoRgl4+4najOnYkl9/iChnSwRk/4j1jXT6xreI31IiwtKjsDfHtVNSgNGqeT5nngDTe+QObMiczX4vJ4RARD6KiHoabE0LTNMSEfUiIvwe99c5OqLFvIpWfZP1iHkFsn/HVxqWTJ/vt22FL6+L969dLXdM8RDRL+U6G2A9j9ykBRGMiJ6JCOrs9XopDWTCJEh/H8gqcMYJmYuR8eNyWxcrzmz8iRZKOF3sUqEoBip1SlGqGE6DHz5c6zU1SbfprP3sFybNHM/VD19GTlYONofNoyL4j4vWM+fRhRzYZnWr0nSN7sM7cdPzY6l2TlWXsf6qimu6RqN29bl79k0ux/du2c/b98+zfvGwr+t1eVdufeU6YqpZkYzsrBzCY8JITfBd1KnbdH78+Cdad2/OrS9fR5/R3fly9gr2/L2fA9sOkZWRXThP1sf+Mv5wAglHEn2urfBO0gkbj17bgGc/2UXrzsUr0C0ZdssxyNlEyYXvNJBJVupSzu+UqqNhHobMpRDiLkrn71dO4c2+NA6Bcy9oEbk6F6f+bQshIGQEImQEUmYAAiH806dxIed3fNZvZP/u5bx3RMgoZPZ6LyNMRMjI4s+vhSNi30LmbEFmrgCZhrA1guCLEf4oomethOw1Hm3D+afV3Sq0+DYqKgD2liBiPDR2KEBZq9lXMASlW9FWUbJzSxsV0VCUKpnpWTizveeSSylJPmmJbQkhcAQ7PDoIX7y5gqmjXuDg9lMtcU3DZN2SX7i18wMc23/CZXy9VnWIjPN+V9o0zHwRPHfraV4KxTVNcGzf8XwnA8ARZOeuN2/0eI0rkvSUUx1xWndvzn1zb2Pg+L5kZmQVuxhPFfGVHCkFUsLcZ2vgzAHDmXe8DBYPHoGo8g0Y/qQ4+EOeo59nfOnmhcnUV9yf0GLB1gTvX7FORFDP/N+k8z/M+AnI432QCdciT45AHm2FeXwgMuMzpHR9LkKEFM/JAPCn7asobhE+EHwhOLrj/qtXs84FDyz+/LkIe0u0iDvQIh9EhI7yz8kAZPr7HmzLnxmZ/lGJ7VOUL0LYEeETvYzQIHhIvkCmQlESlKOhKFVCwoMJi/Ld5aTaOVV8jklJSOW1O98FCm/2TMMk+WQKcx5Z6HLc7rAz4o4hHgt7dZtGq+7NadKhodvzuzbvwfRRKL7nn/2Fjve6vCtTv3jAZ0cpaUpqNy6sGPzNeyvdjFaUNdIU/PlTOPOer86ns6vy2Lh6vD6lJtmltU8XcYiY99Gin0bY6pSiV1PK3pKxF2kWrsUQQiDCJnpZXwe9Ue5mHKRzL/LkFZD90+kLgPEfMuk+5Mkr/VYs90lQf7x/LeqWRkgxEcKGiHnDEvoTIQVOhEDotYiYN/zvthVAZPZGzJMjIXsD3lXjJZjedY8UZwihEyB0bO4vOpbznxtJdHRFRE4tJ8MqEKpGIyAoR0NRqmiaxkXX9fe64TYNk4Hj+/qca+WH63Bme767azhNVi5c5xIhABh9/3D6jLI2LuI0j6Nmoxo88vHdHucMCQsudM3pOILd3+HsPLgDI/83zLvquBAEhTi4o/tDXFHzeq5rdScfzVjC8YMnK/6HkIC6zWtz0XX9adfHah96tqqUfzirBu9MrcX6b6P5/O1qXNGqNUveroKZvyeLC8xCkY8gggpopTg6cuZ+THt4AwdfAvlFyXkpUrnvG70mIuat/LQomfICyDS8bn6d/yCTHw+EwYjQK7Hy1929j62NmAi5smRriCC0yPsRVX9CxH5oPar+hBb5AKIccuJl1k/I+GtyO0z5gRZbugYpygQhBFrkw4i4LyH0GggaACGXWW20Y95F+COWqVD4wZn6DaY4gxh13zCq1I71qFUxavIwt3f1T+fw7qNe9S4AnNlO4g+75p1qukbNRpb+xOkpRVVrxxIa4TnNovvwTl7TkHSbRs/Luno8P/q+YdRtXtujo2V32HjjnrlsWb+dxKNJ7Pv3IG/fP5+UEwG6Q1uaSNi/9SAtuzbluR8e49Vfn+aCMb2ILpBGdraSmabz+qO1ef6e85Bh/4PgAOUyJz/qqtcQeg3e7zBXYDzoNQgh0CLuQMR9DiGjLJ0NR29E5NOIKl8hbHWQ0sDM/huyfKl+A5iQ+SXS8FVk7ofJeg1EzOzcaENBZ0MAQVbEwVb8Ym2XtbQwhOM80Gsi097EPHEZ5okRmMnPIJ37ArKGL6Q0kckPY73H/HmfCURI2XctU5Qewt4ELfJBtJhX0KKmIhwdfd5cqywIWfqPyoByNBSlTnTVKGatn0a3YZ1cNtzR1aK4+cVxXDfdv57x4TFhHtvUFiQs2jUf+cvZ37HgqcVux27+cQvPXfeax7n6XtWDuFoxbu/UC02g6Roj7hzi2ZaoMF5c8yT9ruzh9nxWhvscHH+eZ0XhhRte5/B/R6nfqi7NOzUhploUNsfZ32ciJMxg4/cZ/LL0dcj8OjCTymRkwg3IdCsFUMjyKEIPAMJKhZSZP2DGj8c82gnzWA/M5CeQzj3WEHsLtKjH0OIWoMXORoSOAGzI1NnI4z0hfgT+h/UMyPktMKYHdUFUXYWImAyOPpYTFH4votoqRJD7f8fFRWauRB4fAGmzwfkXOP+G9DnIEwORGV8GdC235GzMFW3z53XWQa8NIVeUtlUKheIs4uzfDSgqBHE1Y3h00T3EH0lg/9ZDOEIcNOnQAJvd/7dgn1HdCtVgFETTNdr2aulSmG0YBgumferxGtMwWb1oA4emHaFWoxqFzv+1+l80XXern+EIcfDEZ5M5p7n3grmImHCSTqag6ZrbFr9esdrfu6BpghZdm3Jg2yGST6aUTXGyFySWiOA/67ay7Zed1rEzx08qMm26pHLVnUfp0MvSFMjKdPNHKiEy+XEI6ovM+RPrY7q44nzlhK0JMvkRyPj41DEJpH+ITP8YYt4otGmX0kQm3pMbxSjfN5DQoiHsOkTYdaW2hnQeQCbeivW3Lfh8czU7ku4BW1OEvUmp2YDzgP9j7echop9DaOXd8lmhKCNKu47iLP6eLIiKaCjKlNgaMbTr04oWnZsUyckAqN24JgPH93Ub1hVCgIBrH3dtu7j3nwMc33/S67xCE2xYVliE69flv/Pw0OkcP62TVR5ZaVn8uXqLzw5Px/af4NflvxfdycBqf1swmqLbdC4c14fpyx/mqS8fpELIV0v4ft5qtv6yEykLOxlCE9RsWI3Jc28tH/sCSK+hicz4ZBftup0SLgsKLo1vCwkZnyKEjn/fRhXgfVAQM8HVycjHAHKQibcizWTXU1nfQ9bXFO/bV7NaAZ9ByIwPsdKVPD1fgUyfV7pGaH6mOUZOR4ubh9AL34xRKBQKb6iIhuKM4o7Xb8DmsPHVW98BVrG54TSIiA1n8pxbaN2jhct4T6lJBRGaIDvTdZyUktfufM/nnmf+1E+JqR6dL7bnjgPbDxf7zoWRY/DuvzPZ9+9BhBC07NaU6KrW5qBZx8aERoSQluRNablsSDyW7PGcNCWHdx9j7z9FuHtaAQkNN7jnRSt3Xi+DT07p3IkIvRaY5WNk4CMqJcbY6uWkBJkBGUsgbOypo+kfYhWHF7WdrwbBgxG6F6HAikjWanxqdmStLl0bgrqDCAfpRfFbq4Jwq4miUFQCKthH65mIcjQUZxR2h507X5/I1Q9dxrolv5CenEGdpjXpesn52B2Fuz/VaVoTm13HmeP5C910mjRsV9/l2PaNuywHwQ8WTFvMxTcOQLe5VxT2VmzuD9XOqUJ4TDhfvrmCt+77gNTEdGo3qcnQmy4kulqk346GbtPLTS1caIKlr39TLmsHir6XJhAULBFlFQcWIWBvmyva9yeeN6Vn4jehROZsQnDK0cBZTM0QW3NEZGC6TpUt/kQ4S7cRgBDBEH47MmWa5zHhd5dLy12FQnF2oD49FGckVevEMfzWi3yOi4gJp99VPflu/mq3ehiarlGldiznXdjW5fiJg/F+2xJ/OIGdv/9Hs46N848d3n2UL974lr/WbkXTBaERIYXa7vrDuf1bc3TvCe7u/SgpJ1Pyi8STTyTzz7qt1GlWE6EJtzUkBRFClJuTAVZUI6MYz7+iEBRi0rxDOk4n2P3QdCs5JiL4QoQQyKhZkDAGjL1UyOhFsTnNMdfCi7evjph8ZtYNODqBczeenSvdGlPahF6LkDnI1JewhBzzokohiIj/IUIvL30bFIoKSGl3hqosXaeUo6EoM0zTxDTMItdmlJSJz17DPz9t4/Duoy51ErpNw+aw89DCu9B1101PTI3oIq2RmZ6V//P389cwY5yljJy3XnHbBR7adZR7+02xir4LOBN5DseB7YcJiwz1GdVQSuHFo8Y5WYy55yh9hiVid8iyK3IXsUh7d0h7H9LeATMvumYDcsrIiFLG4doWWgQPRabOpKjexpl6t12EXo1MX+BlhIEIHVP6dggB4TdA6GjI/AbM46DXgKAL/VYUVygUCk+cmZ/QijOKv9b8y0czlvDr179jmpK6zWtx6W2DGTzxgkIb/NIgqkokL2+YxqLnlvLl7O9IPpmCzWGj7+jujLpvOHWa1iQjNYPgAuJ8LTo3oWaj6hzeddTn/EIT1G1WC4Cdv//HM9e+XCjCIKU8dTNagM2mY5oS0zDRbRqGB/XxY3uPe9/cSus/IRHBZKRk+n4xFH5Tp1EmM5ftJCTcwJb7SVlmtfch10LCtcicX087cZY4GeiIkItdD4WOhPS5YCbifwpVENhaBti2skHYGkPkU8jkh7D6suQ9ZyuiICIeRjjalZ09WgSo6IVCcQrVdSogKEdDUaqseP9Hnh3/KkITp+7CbzvErFvfZuOKzTz68T0eaxsCSURMOBOeuorxU68kMz2LoBAHB7YfZuHTn7Fy4Tqc2U7CY8IYcsMFjPzfMCLjIrj5hXE8OuwZr/PqNo2ul3QktkYMh/87ytTRL3hOY5KWU3L+he2o1bgGm1f9w56/93ud35876GlJGVz5wKV8OP0z34MVfnP7MwcIDTfKpPDbFRukv1jWi5YtYTchRIjLIaHFQuwHyISbwNiH77a+GoRegdDCA2KSlE7I+h6ZuQJkutVaNvQKhO69fXVJEKGXg705Mu19yF4LSHB0QYRei3C0L7V1FQqFoqxQjoai1DhxKJ7nr38NKSXSOLVjzts8//T5r3z9zg9cfOOAMrNJCEFIWDD//ryD//V/HGd2Tn40ITUhjUXPL2P1Jxt46aen6Dr0fB7/bDIvTHyDpOOFuyppukZMjRhueWk8e7fs586ej5Ca4F1gTZqS9JQMbHZbfhcmT9GMopCekmHl87vxTDRdQwgwDLNU7qB4WvdMplaDLNp1Ky+xvIqmmVHUTlAa2NqC88/c3097fwddiAi/ze2VwtYYqnwL2WuR2b9aG/7M5VY6T8H5MS1dh4j/FcEuz0jjCDJ+HBi7sZ6vCVk/INNeh4iHEAW6YwUaYW+NiJ5RavMrFIrioWo0AoPS0VCUGt+8u9JrkbIAPptVBuq3p2GaJk9d+SI5WdmFNvmmYXJ033HevGcuAN2GdeSjQ7O5951JtOjSNF/ZPCQ8mGG3DOK1X5+mSu04Zox7lfRk/4qdszNzWPraNwHbnAeFBfH5K8s9zlftnCpc+/ioEjsZoZEhdL+0E5FxEURViaDvlT14aOFdhMeEodlcP0qEJiqctENRqNtYpaGdwl8nIzcy6eiEiH0PEfcxBA0CgqxztpaIqKcR0bMQblp3yZw/MVNeQqY+D2YqIvw2tMhHEFW+QUQ8BLYWoFUH+7mIqBnWGgWiIjJnBzJ9ATJ9PjJnu9/PTkoTmXB9brF93vOV5GlcyJSpyMyVfs+nUCgUilOoiIai1Ni1+T+vqT9Swr5/D2IYRpnUauTx23d/cXTPcY/nTafJqo9+YtLM8UTGRaDrOgPH92Xg+L7kZOeQkZJJWFRofsrXrs172L5xl19r53W52rFpd0CeC1jCgZ4QmiAzLZN3H/rQ5ZivLlXuSE/O4JevfmPANb0Zff+l1GxYHYCWXZrw0YzP+XbuKjLTsgiLCqVu89ps/XlH0Z9MBSEzzb/3o5SBqNvIK95xYHX9OQMR0RDUFxFyCTi6Wo6E1hYRM9PnpdKMRybcCjkbsZwVgcQJyTEQ8zLC0QnCrkWEXev+euO4pSiesyHPGEAi7Z0R0c/71tfIXgdOb46Jhkx7AxHc1+dzORuQ0gnGHusX/RyEKJM2awqF4iylQkU0pJS89tprtGvXjnr16tGhQwd++OGH8jZLUUzsQXYXVWt36DYNTSv8NjTN0usfv3vznvzIhCcMp8H+bYcKHbc77JbzUaCu5L+/9hVp/XP7tS7S+ILkFavruRGEhu3qeX0u0pSFxPSkKQmNCKFq3bgir5+T5eSbOSu5+bzJ7P7TugNc7Zyq3PbK9SxN/oAv0uax8OBs9v17ZovzbdkYSnKCd2cjOxM+nFWN1KSSfoxKCBpOyZyMoBLaUBIE2NuiRT+DCOruNlrhCSkNZPz1kPN77hGD/NQxmYSMn4B07vR8vZmOjB8DLkXzuU50zkZk/Bik6SOdMWsV3u+5mZDzO9L0Imp3FiClgUydjTzeE3lisPU41h0zZRZSni1NCBSKIiDL4FEJqFCORlpaGn/88QerVq1i7969TJ06lcsuu4xjx46Vt2mKYtDl4vNd2smejm7T6HLx+fmb5+zMbD598QvGNrmVgbZRXBx2Nc+Of5U9/3gvmC4qjhCHX3f0HcGFBQDdERTq3yZPCLj3nUl0HHSuX+MLEh4Txk3PX0vrns1p0OYcug/vxKSXJpCVluX1NfZEekoGE2dcw6SZ44t8reE0yUjNZPqYl1zStYQQBIUEsWPTbr/TyCoqOdkaC2ZW93hemrB4djXmPlODcV2bk5VRkrCGgKySphB6jmqVBSKoV/EuzF4Dzr9xn55lAgYy9W3P12d+DsZ/Hq43rHSoDB9NEqS/Dt4ZGm3yAyklMmkyMvU5ME8WOJEEaa8iE29FyvLT4VEoFGcuFcrRCA8PZ/bs2cTExAAwePBgGjRowMaNG8vZMkVx6DGiEzUaVMu/+346pikZ+b9LAMjKyGLygCd4897381vKZmVks+KDH5l03mR+/+GvgNnVeUgHpI9bCXG1YmjYrp5f83Xo3xq7D6dEs2m8sPpJBoztTZ2mtWjfrzWa7v/mNDsjm/MHteeFVU8we/PzNGhTj9fueJdDu3233/XEZy9/TfLJFJ/RHXeYhsmev/fz74bCKSflKQwYSD57qwrzX6yGaYDhhJxs6//ShGVz45g7ozogmPDQEYJCSnJrSlJmbWtFBIWE8kqEZs0ZMrxYV8uMr33YY0Dml4Xqj6SZjHTuRqYvwlcxkMxY7PW8sLfEZwG+VtVKDztbyV4Lmcs8nJSQtdIqylcoKhF5xeCl+agMVChH43SklJw8eZKoqCi357OyskhOTnZ5KCoOdoedZ759hKp1qwC53Y80gdAENrvO/e/fRsuuzQBY8NRitqzf7mZDIcnJdjJl+AyyMwNzRzGuVizNOzX2OubKB0b4XTcSFhXGiNsHe83Vv/rBy2jdvXn+7/e+M4mIWP/VjHOynbz7oCXuteGLTcyd8hFAsWot8tj5224Ol8BRAdi1eW+hYw3b1kPzkTJXHMpMw+LUirz/bE2u6dSCuTNq8PWCOOa/WJ2xnZvz6kN10HQ7kTEGa7+I4qevIynFbD8/zY3xMSACYudZYmxAXj1ECRYEEY6IfRehRRZvCpmKb4G+LPIiFtL5H2bCHchjnZAnBuVGQ3wIzZjx3qcPHgoiFM+vhUCEXlOklLAzDZm+EO8On4ZM/9DLeYVCoXBPhS4GnzVrFuHh4XTt2tXt+enTp/P444+XsVWKolCrUQ3e/XcmPy35lfVfbCQny0nj9g0YdF0/YqpZDqQzx8my17/xumnOSM3k0xe/4MoHRpTInrSkNCZf8ATbvRRjX/nApVwyaWCR5h0/9UqS41P5+u3v0W1ani4fhtOk9xVdSUlI5YmRzxNTLYoBY3vTvFMTnv1+ChPb3uPX/NKUrF+6kcTjSXzywjI0XStWylRBDKdJWFRosVXLAVISCuetH9p1JF8zJVDoNo0+o7vz0+e/lrkw4YnDDj56pXAalTPHIDlB5/e1EWz6MZLelyRw36v7KMO+Bq6EXArp73o5PxzN3gJZZQUy5RlLHK9I5BWtFyDiIYS9bVEtPYWtPmQVFKtzg1YTIWxI507kyVFWy1u/1cM10Ot4HSG0cIh6EZl4C9bzy7Ml99+FowuETfBzvTMU5268dxczTxWIKxSVBSXYFxAqpKPhdDp5+OGHWbRoEcuXL3dbLAzwwAMPcPfdd+f/npycTN26dcvKTIWf2B12eo/sRu+R3dyeP3EwnhQf+hMA3y9YU2JH46Wb32LnH3vcnxTQeXAHJjx1VZHn1W06d8++icvuHMKK938k/mgisTWiObjjCD8uWo9u0zANiaYLlr72Db1HdmP0/cOLtIaUkhMH4/lrzb8ldjIAdLtO39HdWfraN8We4++1/xY6tuSVr9F0gWmU/FM0unoUoycPZ8DY3kTGRfDOgwv4aMaSEkVyAo1pWBvS1cuiadwmg5G3eO5oVqpkfuf9fMZiZOS94NwL6R/4N6eoBjKvRs7Na578MDKoJ0KvUiRT86cPGYlMe8vLCA0RerW1etJjuU5GUVLzTAgZjszZAiII9IZuHWsR3BfiPkGmvQOZ3wDZVsel0GsgdPTZ33lJiwLDjSNZEOF/BFahUCjyKDdHo379+vk/t23blqVLlwJw/Phxhg8fTlxcHL/88gtxcZ474wQFBREUVJ7dVhSBwObw7214aOeREq1z4lA8qz7+yaty96/L/+DEoXiq1Iot1hr1Wtbl+qfHADDnkYWs++xn4JQon+G01l79yXqCw4q+eYmqGumfXLgfVKkdS0pCGiERIWSkFK94e+M3m0k+mUJk3KlNyJaftgfEyQBIOp7MG7maJl0vOR/TMIiuGknC0aSAzB9IpITFb1XlshuPl4OaOGD66n6WBhlfI3M24T1lSoOQqyC4DyR6E8TLvfufsQjCby6qtQAIWz0IvxOZOpPCERMNbK0g7Bqkcy/k/FLU2UFUgeTHkHmF3Po5ED4JEVL4hoWwt0REP4+UzwHyrE6VOh0RMhSZ3/nLHZrVulihqEyoiEZAKDdHY8+ePYWOOZ1OBg4cyODBg5k6dWrZG6UoF+JqxhAcFkSmFz0IoMQCd1t+2ubzTrhpmGz5aRu9LnefrucvGakZfDrzC48+gTQl332wxu/5NE3QpldLqtaOo1WP5vyzbluJohpCCBq1q8+jw57x2YLYG9KUxB9JdHE07EGB+1jJ+3u9cc9c3rhnbkBSxkoPQcIxO0f2O6jdoGJ2KJI5/0LWWnymyWTMsx4+MZE5m0tW6RE+CfTayNTXc5W5AREOIaMQ4bciRAiyyGk7DhDBIONxea7GPmTS/WAcRXhwjqyIxxmsNlkcgodB6ttgHqHwe0MHLQZCR5WHZQqF4gynQt2yWblyJenp6crJqGQIIWjXu5XPcQ3b+tcFyhMBCgT4xV9rtvp0nAyn4d9+RoDQNMZPvRKAy+8aWjInQxPE1oxm/TKrm1tJ05CiqrimVHS5+PxidbLyh4rrZJyi7IvWi4BMJrC30QSBuF8lQoYhqnyNqLrSUgKvth4t8j6EFpY7IMy/icImIWI+gNCrcwvN3TtUMnUm0jhYYrvPFoQWjoibB7amuUd08ovD9XMQsfMQWvGivArFmYrqOhUYKpSjsWPHDvbt20f9+vVdHlOmTClv0xSlzE0vjvM5Zvhtg0u0RqtuTX3evReaoGXXpl7H+ENOln/tSj3VHxUkploU0756kFbdrA5d3YZ15OqHLgNwaR3s7wa3dpOaDJrQr8RtaDVd47wBbYmsEsHPX25iwbTFLHp+GecPbIvNrpcoUnJmIomrnkP1ugWjGcFAVQ/j7ZT5R7C9PTg6E7gWtxIR1CMgMwkhEHpthK0BQpyWEmtvD5qvOhAHImwCODpCxmK8F4xryPRPS2bwWYbQayPiliBi51tRprCbETHvIaosR9galrd5CoXiDKVCFYNPmjSJSZMmlbcZinKgTpOa3PziOF6/a47b5ja9R3al/9U9S7RGldpx9L6iK6s/2eD2zrima/S8rDNVahddMft0/I2++LpDbw+y8d62WYRFhrocH/fkaM67sB2fv/I1W3/ZiT3YTp2mNdmwbJPPNQ9sO8Tnr5asJ77QBJqu0WdUd8Y0uIUTB05a3bZMiWlKmnRowO6/9mFII/9vKTQBUpZpZKmgvciSp995XwRG3Hj8tK5TmRA9EyHCkGnvgbEDRBQi9DKk8wCkv1N69rgzMXgAOFohM5cGYDYNRBQEl37uvhA2CL8dmfyo50Fh1yG0SEvBW/pRw2P4qmmpfAghLEfN0bGyJY8pFIVRNRoBoUI5GorKzYg7hlCnaS0+fvZzNq/6B4A6zWox4o4hDL6hv193/31xx+sTObD9MDt//w+hCaQp8//fsG097nzjxhKvAVCzYXXOG9CW33/426MzUb91XZKOJ5N0PNltO1hN17jouv6FnIw82vRsQZueLfJ/z87K4co6N5KakOqzvWyqH12+vFG9XlXGPjaSl25+i5xMK3qTV/AOsOO3/wBr4yKR6DadqnViObKnfDoylWaXKqFJpCnoNyKBERNPf34apL2OiFuECOp8yh7nf5A8rIQrxwJp+K0KHnSh1R1KrwIRjyBTnsCKbBQzsiUiEbHvITT3789AI0JHg5mcWzhuYkWDTEBC6LWI8DtyBwbj+3kJKK72h0KhUCj8RshSvcVXtiQnJxMVFUVSUhKRkepL5EwmOysH0zAJCnGUSOfB7dyZ2fzw4TqWv/M9Jw7GU6V2LIOu60+/K7vjCA5cG8vDu48yvsUdGDnuNzyhESHc/c7NPDP2ZUyn4bJRF5ogqkoEbXu3IqpKJH1GdaNNzxY+X4u/1vzL/QOnYjidLvOVlJga0UyYOhrTkNRuUpM2vVrwwvWv89281QFd58xD0qBlBtc9eITz+6Z4TF8T1Ta45LibSQ/lpvcUN31Nh9CrQOZYXZ98bar1cxCxCxH6qWidmbEY0t4H5z6gsB6KV0KuRETci9DKvuWpNOMh4wukcdh6PsFDEHpNlzFm4l25StaeXxcR+yHCcV4pW6tQKNxRkfdreba1v+YpdEdwqa1jZGfyxwcPVcjXIJCoiIaiQuIIspfe3MEOBo3vy6DxfUttDYDdf+716GQAZKZnsXXDDl795Wk+mrGEHz/6CWeOQUh4MBlpmSSfTGXt4p8RQrDs9W9o27slTyyZTFiU58LYNj1b8MbvM/j0xS/5fv5qnwXp/jBgbG9ue+U6QsJD8o9JKVm5cF0ldzKsupghY+Lp2C/F+0B5SmRQSgkZyyi+k6EBdkToWBDByKwfwDzpfj4RjggbD6FjEZolkCmNI8jE2yBnM0WvEdFBr42InFLi9q9SmuDcCWSCXt9vdXGhxULYWK+pPSLsJmTmCqzchNPfo5olwmfvUDzDFQqFQuE3FaoYXKE4m1i5cJ3X7kumYbLigx9p0Poc7n//dr7MWMDkubeSkZoJ0jpvGmZ+0fbfa7fy1JUzfa5bt1lt7nxjIpfeXrLieYDbX72eyXNudXEyAHKynWRn+lfwXqoICA4LQitQeK7pGnWb1Wb4bYN5bLE3HYiSI6Wg2bnpPmyMOK2Q2QBKoG4uQiDmZdDiEHp1RNwiCLoAl49zvTZETker/hsi/LZTToaZjowfAzl/5w40KZLKtghHRL9aIidDSolMX4Q83g958mLkycuRx7piJj5gRSsCgLA3Q8S+C/lRJBv5r09Qf0T0KwGPlCoUirMMWQaPSoCKaCgUpUTyyRSfxd5piadqJYQQLHz6M6uuwU1Go2mY/Lr8D3b/udevYvP//vKv2LVavaoc23uqtiBP1XvU5GFcfNOFbq9xBNmJrhZF4rHyE84TmuD5VY/TpkcLpJQc2H6I7MwcajasTmiE5RhlZZQ8ouMJTZc0apVB03bexA6FpRFxfCASCY4uiLAxIKqCLGa9ioiEhBus7ym9MSJsAiJ6lhXVMPaCCAVbM/fOQObnxSyCFhB2PTh6Qc5GZPbP4DgXYW9T9KnSXkWmzjrtYA5kLrHEBOMW5TtGJUE4OkHVHyFrJTi3W7UbQf1UByWFQqEoQ5SjoVCUErUaVufPH//xnF4krKLqPI7sOca+f7339td0jfVLN/rlaIRGhvgcA5Cd4Soup+k6o+67hAm5uh2eGDLxAhY8tbh0Ozl54drHRtGmh1UML4SgbrPahcYEhQRRs1F1Du86GtjFhSQqzsmDb+z1NgiQ4NxBflpT5ufIzM/Afj7kFNPRMI+c+tnYhUx+EHL+QkQ+ZhV7e0FmfH7KrqIgYiBnK6TNRuYnLUmkrQ0ieibCVtf9esZhZPp8yPwaZDro9SHHU2c0wxLUS3sbEXFP0exzWfM4GAdBiwC9ISL4QsC9w6xQKBSeKG2tC6WjoVAoSsRF1/f3WsMgEC4Rg9M3/G6v0YRfd+lN0yQ8JtwvO0+PSjiznXw4bTH39nuMw7vdb9ANw+DA9kPl4mSERoYw8dmxXPXQCL/G3/jc2MAbIWHagt3Uqp+XPnZaGo6ILvCLcdrPEnJ+Ldnip/+c8SFkuyrNSymRZrLV7jUPM5Gix+s1wIDsdQXWzJ3DuQUZfxXSTChsZfZm5InBkPY2GPutiEvObz7WMiH9o2K9r6RzL2bCTcjjPZDxI5EnLkKeGILM/K7IcykUCoUiMKiIhkJRCkgpOadFbYbceAFfvll4o6PpGo3a1XdxNKrXr0ZQaBBZ6Z4dCSPHoEEb79GMnz7/lTfumcPh3ceK/wSAzav+YULLO3ls8f/oPNi1cHbxi1/y48frSzR/Ubjqocuo06QmYdGhnDegLUEhQb4vwvo7CARhUaGkJfmopSgCQmj88+cVNGz7h7WB1usgQkchg/ohMJEpMyFjPmWXhKsj0+cjgnohpQHp85Hpc60NPiDt7RBhN4CtvpVeVaRCdOlFl8IA8zikL4Twm09dIbOQCRNBZuBaA+LH6yETreiHv2rggHTuQ568PFcNvMAaxi5k4iSIegYRcqnf8ykUCoXS0QgMytFQKAJIekoGnzy/jGVvfEvisSQ0XaNBm3M4fiCe1ATrzrIj2M7A8f24/umrCQ49tWEODg1i0Pi+LHvjW7e1HUIThEeH0f3STh7XX/PpBp4Y+XzAno8z28kTlz/H+7teJa5mDGBFMz6d+UXA1vCGpmuER4dx9UMj/G49nHA0keXvrmTrrzvY+88BDu44HPDCX00XZGS2RqvyiMvx/KSi7J/wXWSt474rUnEwIOdfpDSQiXdC1je4RFly/kIm3grBw/Hfyci1z9YkN/3Lk50mMmMxooCjQeZykIWjHP5hh9OVwX0gU2bkOhmnPzfrm1wmPw5BA8tM80OhUCgUFsrRUCgCRFpyOvf0fpT//t6f7yiYhsm+fw8ghOC2V66j6fmNOKdFnfxi5dMZ9+Ro/lj1D/u3HnRxNnSbhtA0Hl54l8fWv4Zh8Mrt7wb8Lokz28nXb3/PmEcuB+Dw7mOcPFTcTaT/aLpGUKiDJ5fd77eT8eOi9Tx9zSwMp+Ei0hfoFC/DaVK7aS3PA/xRpgasj2AnAXE2RAhkfpHrZIDrGyF3/swl4OgG2esp/EYRoNUBLcYa7+iECL3Sclx82WeewDSOIYx9IEKQ2Rs59dyKgg5Bg8BMRAoNRIxPJ1Ga8ZD1nXcbZTpkLYcQ/9LtFAqFQhEYlKOhqHTEH0lg3We/kJKQRq1G1ek2rGNAhPo+eOxjFycjD8NpIjTBe48s5KODs/PXykjN4IcFa9myYTuaptHhgrb0GNGJl9ZNZdGzS/nizW9JOpGCbtPocWlnRt9/KY3PbeBx/T9++Jv4w4F3AExTsnnVP/mOBsXctOd1s/KGzaFjD7LjCHbQcWB7Blzbm2rneC9wzmPbxl1Mu2ompmmWakhaCEFkXDhdh3oRexP+3Dk3IGYBpDwJzr99D/eKBsEXIdM/4JRitjt00BtC2LmQ/gHI5Fx7wyH0SkT4HQjh+m9B6nXBuRWvkRCZBsd7FHjZQ7zY4IlchyLnZ+TxbrnmNobwGyB4uGeHwzjix1o2pHO/V+0NhUKhKIgqBg8MytFQVBoMw2D2/z5gyctfI02JpmsYToPw6DDumn0jvS7vWuy5szOz+eqd7z22s5WmJDUhjdWfbOCCMb34Y+XfTLl0BukpGWi6hkCw/N0fqFInjqeXP8S4J0dz7ROjyEjNxBFsx2b3/U/1+IFiaBD42YDo+IET+T/XbFi9yDUPuk0jMi6CxGPJXqMLzmwDZ7ZBRkom381bzXfzVgPQqnszxj95Je36tPJ47ScvLLWUuYv44a3pms82xAXHAvzvvVu8/030+n60kbWhBZ0LQYuROTvAPIRMXwhZ3/tnuAsCQi6DtHfxvuk2rLSmkGEQ817u5t1KjxLCvQKuCB2JzFpeRHu8tfw9ze68YnMcQBaYBWqLjF3IpPvAuRMR4UETxa9WuAZCi/bTJoVCoVAECtV1SlFpePOe9/nspS8xDRMpZb4QXmpiGlNHvcjGbzcXe+5j+0+SkeJdhM1m1/nvz70c3HmYh4ZMPyXM5zwlyhd/OIF7+z1OWnI6QghCI0L8cjIAYqoXXXtA13W/xsUfScQwLBt1m87gGy7wfxFh7f2jqkQWO4Vpy0/b+N8Fj/PTUs/dmjYs21QspXLTMKlev6rvgVhOVpeLz2Pzqn/456dtSCnZvmkXb9w9h2eufZn3Hv6QgzsPI4IH+phJQFCfU7/ZmyCCeoP0oTDuEQMSrsfarPtAnoD0ORB/GTJtDtiae3QyAHB0h6ALKdRZq6SET0ZE3IcIvx1CbwDcNUHIfb+kvYXMdv/vU+i1QcS6PedC8KBim6pQKCohSrAvIChHQ1EpOHEoniWvfO0560fAew9/WOz5g0J8b/CklDhCHCyZ9TVOp9OlhiAP0zBJPJ7Eivd/LLINHS5oQ2SVCP8GC6v97nM/TCEi1ncb3IyUTPZvPZT/+3XTriKmRrTvZYTAEexg+K0XsX+bd40Qb0hp/ef5614nJ9u9Irkzu6j1AKc4fuAk5zSvTbPOjV2OVzunClXqxBISHgwCDu44zIYvN7H4pa+4s8fDXFH9em7peD9LXlnODwvWsvCZJYxrejtvP56KlN6cOAnBQ9wc98/xc4vxH/7XROTpeixDJj/tdaQQAhH9IoTdWKROUN6xQdAAS2ww/GbI2Yz3ryMdme7+36c0jvguPBeRoFUrtrUKhUKhKB7K0VBUCtZ8ssHreWlKtm/cxZE9xWsJW6V2LA3b1vNauGo4TboN68jqTzdg+rjzvnbxz0W2we6wM3HGNT7HhUWFMu7x0dz5xkRa92jBiDuH+NWVyZlzahOr23Re3/QMsW6cDSEgNCKEPiO7MWnmeB744HYWv/RlsaINBZHSUlvfsMy94FvDdvURWvHuuptOk31bD3L9tKuZu+NlJr9/K+ExYZw4GM+JA/H50ae8sXkRqKQTVo2D4TQwDTM/BevjZ7/is7djvKyouRWuE0E9i2X/KYrawldCxodWQbUXhLCjRdwNVdd5HVe0deed+tW5HZ8pX86t7k9lrvBjuSQwdhfFQIVCUcnJq9EozUdlQNVoKCoFKfGpVk2G6b21Z0p8KjXqF/3OpxCCqx++jCdHvuD2vKZrtOvTiiYdGpKd6UOYT0KmFy0Nbwwc1xeA2f/7gOSTp9JwoqtGMviGCzjvwnY079TYpfi9WcfGPlOaQsKDqXNal6W4mrG8++9MvnjzO756+zvijyQSWz2Ki67rz8U3XUh4tHX3+/auDyKECFjnpyWvfM1HM5aQEp9Gnea1uHjiADoP6cDw2y5ixrWvFHteTdeYedNsEo4mkpGSWWJ7F86qziXjTmBz2yTMEqYzzTTLuQi+ECEcSH9SnwKOE7LWWHUbPtC0UEwRnttKtiQYkPkVRD5k/SpCLf0MjwjQPETeZCpWJMhHNMcsqc0FlnTuQ6bPg6wfQBrgOBcROgbh6OD7YoVCoahEKEdDUSmo2bA6Ro53J0Nogqp144q9Rq/Lu3LzC+N489651m19LAfEcBq07NqURz6+G4CGbevx99qtHguQdZtG4/aeu0v5YuC4vvS7qge/rfiT+COJVKkdS4cL2qLb3KflnDegLTUbVufo3uNubdJ0jcHX93fR/MgjLCqMUZOHMWqy+03qiUPx/PvzjmI/F3f8+eOW/J+P7DnGL1/+Ru8runLfB7fx24o/8wvIi4ppmBzaebi4TbUKkXTSxrY/QmnV0VOUIQcylyIzP4OUGsjQUZD6UmAWLyrSe32RC8FDLSXyEq9Z4HUJGQxp7+Gts5UIvsj9Cb0evlPGNNDrFNVCt8isVciEW7AiMHkpaEeQmV9A+F2ueiIKheLMRQn2BQTlaCgqBT0v78LLt73tsWBbt2l0HXo+0VWLXlBdkBF3DqHn5V1Y/u4PHNxxmNCIEHpd0ZV2fVrlpycNu2WQy2b5dAynydCbL/R43h/sDjudh3hpv1oATdOY8um93NN3ChkpmYWcjeCwYJw5Bvu3HaRus9pFsiM92d/uQ8Ujz9bVn6ynYbv6/G/OLbTv15pZt7xNdoaPyJEbAiy3QXamr+zU3I2qeQxSZwV28aJga1qEsQ0DsKDmsqYIHWPVYBRSEgfQQYuDYA8Rl+ALIDkqt1Wvuz+gDkH9EXrxbyLkIY0TyITbsBybgmtZf0eZ+iLY2yKCupd4LYVCoTgbUDUaikpBcGgQt796A0ChegRN1wiNCOUGP+ob/KFqnTiuefQKJs0cz4g7h9CkQwOXNXte1oULrumVa0sBO3LrC659fBSN2tUPiC3+0qhdfWb/8Rwj7hhCRFyBgnIB6cnpLHvjWya0uJOPZnxepHmr1onFHlT69zOkhMW5HcUGjutLs46NAt4kqRhWsf3PYLIy/DHEpPxub+nIhNsxkx9DOnf6Hp65gpK/uCYidEz+b0KvhYh5D/Jb0NrIvw+m10LEfoDwkDolhAMRNZ1TrXILooMWhYi4v4T25pKxCMjB899KR6a9F5i1FApFuaPqM0qOcjQUlYYLxvTi8SWTqdfqVAqFEILOQzrw8s/TqNWoRkDW2b5pFw8OmcZl1SYwvvkdjKgygamjX+DAjsP5a/7vvVu4842J1Gl2qu6hacdGPPrJvaeE8UqZgzsP8/GznzN3ykes+mgd0dWjuf6Zq4mMDUe35X405BVA50YO3r5/HuuW/OL3GiHhIfS/uhearfQ/apKOJ3Nwx2GklJbyegX4IH/3qVrcNawxqUnl9VGr4ftj3gB5FNI/Qp64BJn5nY/hB/DvxRWn/b/A8aCBEDzY9aijPaLqakTU8xA60hIQjH4dUeVbhM17KqEIvgARMwfs7QsctUHwRYi4TxG2AKVNZf+Cz6L1bP//fSgUCsXZjpCBqtCsACQnJxMVFUVSUhKRkZHlbY6igiKl5MD2Q6QmplO9XhVia3jrDlQ0/lrzL/dd+ASG03RJQdJtGsFhwbz001PUa3Fq0yOlJCM1E03X3NZAlAaZ6Vk8N+E1fvz4J0ssUBMYOQYRseFccssg5j/5icdrNU3QtGMjXl4/3e/14o8kcGvnBzh5OMFnt62S8tZfL7Dyw7UsmLbY86C8fa+0Ikph0WGkJqSVmk2aLuk1NJEHXvMl4BdgIh5B5KYiSVsDyPoZMj7Fu5ieAGyIqj8g9OpuR5gnLgXnFnw6G/bzIfhiyFh4qmOUVgsRNg5Cr0GIErTy9YI0joKZDHp1hBbY7wEzfgJkr/U+SISgVS++Jo9CURmoyPu1PNvOu2IqNrsXjaES4szJZNOihyvkaxBIVERDUekQQlC3WW1adG4SUCfDNE1mjHsFZ45RqM7BcJpkpGYya9JbhWwJjQgpMycD4Okxs1jzyXrLZsPML5JPTUhjwdRP8tWv3WGakq0/7yQ9xXWzemDHYd55cAHTx7zEq3e8y9ZfThWAx9aI4ZWfp3Ph2D7YHG42lwVueIdHhXLegLbFel6RcRGA5MPpn3kdp+s6z698jCUJc/gibT4j7x1W7La4/mAagtXLojl5tIxL4hzngxaBzF4HqW9Y3Zli3gF7Zzx/9EvAyE0Rco8IudT32mE3ocUtQAu7Cq3KUoiZByHXgKMrUmaB6UP3ogQIvbolgBhgJwNAOLrgPW1MB0eXgK+rUCgUZyqqGFyhCBB//riFI/951uEwDZM/f9zCwZ2Hqd24Zhladoqdf/znMfVJSmmpeJu+ow55mhpSSt6+fz4fP/t5voMihGDJy1/TbXhHHlpwJ45gB7E1Yrjn7ZupUieWeU+cFjHJvTGu6RrNOjVm2tcP8fSYWaxc6L9mgxCCdn1acnOHyT7b0hpOg7rNahMWZbXfbdiuHkITbgUUA4VpCLb9Fkq3i5JLbY1TaGBrAQk3Ic3DWBtjaUUVMpdgfex7+xubyOyNnrfTISMg/X0wDlK4S5QOel1E2E0ASJmJTLwbslzTsWTqC8jQq9EiHy360ytPQi+H1FeBTNxHdAxE6PgyNkqhUJQGpV1LUVnqNFREQ6EIEAe2H/Zr3MEdR0rZEs/8+PH6U/UX7vCjnV+1elWJiLEKcxfP/JKPn7UKxPME6/LE7NYv3cisW97Ovy4nO4elr37jcV7TMNm04k/2bz3I/fNu59onRvv3pIAWXZuy5tOfcfpoYZxH4vFkpJS888B8Hr54etnUc5RJcboOOMA4BGbe+zHvyeW9Nv6oh3t+jwgtHBE7H+zn5h0h/8nZz0PEzkNoodbKSQ8UcjLybUqfh5n0mB+2VByEFouIeQ1w4PoaWZE6EXE/IkhFNBQKhSIP5WhUQpLjU/jgiUVcXf9mhoRexTUNb2HBtMWkJpZennplIDTCv1zO0MiQUrbEM2mJaX6pgHtKJRICRtw+GCEEzhwnHz7tOU1JmpJv567ixCFLdXr3n/tcRAQ98c6DC9A0jasevJTq9av6tHPy3FsBmd+1yx9ia0SzcuE6Fj6zBMCjpkmg0G2Slh2L8e8r9JaijXd0AXs7kCVJTRKIoG7eR+jV0eIWIOI+R0Q8hIh4GBG3DC1uHkK3BC+lcx9kful9qYwFmMbJEtgaWKR0IrPWIjOWILPWI2Vhx1UEdUdU/RbCJoKtGegNIXg4Iu4zRNiEcrBaoVCUCrIMHpUA5WhUMo4fOMnNHSYz74lFHNt3guzMHI7sOcacRxdyS8f7iD9SernTZzudBnfAHuRWBjqfmBrRtOjcpIwsKkytxjUwfGyq7cF2bHbdJfKR53h0vaQjF980gIRjSfy9bitJx72nAklT8stXvwPkRzp8sX7pRr56+3s0TeP66Vd7HXvt46PoOKg9W37ajlmE1Kdv565i3pOL/K7NEEK43LgvCpquccGVVYmOM8i78+3fR28wIvx6sLX2Mj6vpasOemOwNYecn4tupMt8wRBymX+j7S0QYWMRYdcg7M1czsnM7/1bMu1t32OKgZSZyJwtyJxtSOk7iiMzliKP90ImTEAmTUYmXIs83heZuaLQWKHXRIu4G63KMrSqy9GipyPsrUrjaSgUCsUZjXI0KhnPTXiVk4fiC23KpCk5svc4M2+aXU6WnfmER4dxxT1DvW5Gr31spEeF7rLggmt6eS321nSNIddfwOubZnDhuL6ER4dhD7bTqF19bnr+WqrUiePyatcxssb1TL7gCZ/rCU3kC+fVa1kHR7B3RyyPuVM+wjAM+ozqzj3vTCIkN1qk2zQQYHPYGDtlJFc9OIKM1CKoWucy+38fsH/rIb/qMoQm6DO6O3O2zeK6p66icQf/VNvzIiytujXjltdeRMR9CaHXgKMHiGjfE9jbgghFRE0DEcIpJ6UgknyFamMnpL/jl22ekaBXAz825r6nSvJvnDOwyvFSZmKmzEAe64o8ORx5cijyeE9k6ltI6d7JlhlLkUn3gnnC9YR5FJl4q/9Ok+KMQspMZPbvyOyNSNN3tFVRuRBm6T8qA6oYvBJxYPshfvvuL4/nTafJ+mUbObr3ONXreU9ZUbjn2idGkZmexWcvfYXQBJomMAwTIQTjnhzNkIkDytW+6KpR3PzCOF65zf2G1DRMTCk5p0Ud7p59E3fPtop6TxyK5/auD3LyUEJ+mpE/m3RpShq0PQeAsMhQBk3ox7I3vvV5bfzhBLb+vJNW3ZoxaHxf+ozqxrrPfuHo3uNEV4uix4hORMZawoJxNWMICg0iKz3L79fBX2x2nSe/eIDzB7QDYPT9lyIl/PfnXgwfrXqbnt+Iy++5hB6Xdsp1Lpsg7A9iJtzk3yY85xdIex0RPgniFiNTX4XMr/CvxsIHIgZkIm5j98YBZMIEiPscIUpwL8rmZ+ROC1znNymzkfHXQ85GXArezZPI1GfBuQuiprukD0qZg0yZ5mlGQCBTnoKgviV7PRQVBimd1r+n9LlWNzYAHMiQyxER/0NoYeVqn0JxNqE+NSsR2zfu8j1IwvZNu0vfmLMUTdO4+YVxzNvzGhOeuorOQ86jViNLj2DOIwu5u/ejRRK8CxTpKRl8M2clHzyxCCEEtZt47nq19NXlfDnbtYD3jXvmujgZ/qDpGnWa1qRtr5b5x65/+mqq1a3in83J6fk/B4cG0f/qnlz14AgGX98/38kAcAQ7GDS+r9dITXExnCbTrpzpUltSpU6sTycD4JFF99D7iq4uESzp3AlZP1C4W5N7ZOospHEUYWuAFv0cotpGsLX0faEvtFg8f/wb4NyGzFpVoiVE8IWA7wiWOE24ryBSZll3m7PWI81434tmLLEcNE9dtTIXQ86vrsey14PXuaUlUpjzh+/1FRUeKSUy8R5Ie62AkwGQDRkLkQnjrBbMCoUiIChHoxLhb8qO165ECr+oVrcKzhwn65b8wuHdx/I7Mv3z0zYeG/Es7z38YZnZ8tVb3zGy5g08d91rzJ/6Ka/c9jYHd3jvkLXwmc8wc9vcJh5PYs2nG4roZAiCQhw8MP8Ol7vHIeEh3Pbq9X7N4c0ZOp2xj43M1dEILFJKUhPT+Oa9lfnHug/v6LNWw+6wEVfLzZ36rFUU+WM3Y2kBg9LB+W/Rrj8dcQ4Yu/Dp7CQ9gDRdIy/SuR8zZQbmiUswTwzBTH7ccp7cLSPsEHG39zW0+hDUq9BhKQ1k6svIY92Q8VdZ9RLHemAm/g9pJnqcTqYvxJfOhUz/2PWQccL90NMxj/s3TlGxyf4Jsr7GfSWuCTmbIcOL4Kei8qCKwQOCSp2qRLTt0wrdpnm9G2sPstGmZ4sytOrsZOsvO5jzyELAtaNR3s8Lpi2mw4C2tOtdugWkP3y4lhdvfDP/d38Lso/uOc6hnUeo07QWB3ccKbKid5MODbl/3h3UceMsdBzUnmr1qnJ8/wm3KVSartGmZwtqNarhdu7E40l8+eZ3fL9gDamJaZzTvBYX33gh1etXJfGYn3UBRUCakjWLf+aKey8BYMX7q31+QeRkO3njnvdJS0xj5x//kZmaRd0WtRkyNodO3QWa376GiTT2ndo6Z/9Myb6dgkDY/ZtCJiIT70bEWml2MvN7ZOJt5Iv6ATh3I9MXQOQ0RGjhAnIt7DpMMx3SXilst1YfEfd+IYVwKSUy6UHIPL2jmRMyv0A6/4HYjxFaeGGbjb2F13EdAM7/XA/ldsnyieZeKV1xZiHTF2HVO3n6LBTI9IWI0CvL0CqF4uxFORqViJhqUQwY24dv5qx0u8ETmmDwDRfkayQois/S177x6tTpNo3PX1keMEdjzz/7+WvNvwghaNu7Jec0r41pmrz70IJiz5mT7eTA9kMsefmrIl97fP9JYqpHuT2naRqT59zC/QOn5kd68s/pGiHhwR6jHnv/PcA9faaQfDIl/z2ceCyJzau2lErqVB6Z6VbBuZSSRc8t9THaYsks19ftyJ5j/PKlpNfQ2tz/6j50fz99zYIikP45ilbUxOTUR7wTtDgIuRzS3vRyXUEkZK+xIhYiBJl4e+76BT87LHtk8oNgb4GwF07r0iJuQ4ZeZUUbnFtARCCCB0JQr0JOBmClKBVyMgqs59wN6R9C+A2FT4tIkN6KejXQol0PObqAVqVwIfipSUE/x2obrDjzMfbh/d9RbqqcotKjBPsCg3I0Khm3vjyB4/tPsGnFn2i6hmmY+RvizoM7MPHZseVt4lnB1p93eI0cGU6Tbb+4TzkpCicPJzB9zEtsXvmPy/HzLmzH5XcP5eie4qV7hEQEc3TPMZ644nm/oyAFiT+SyKiaN3D53UMZ+/hItNNu4bfr3YqZa55kziML2bhiM0jLyeg5ojPjpl7pNhJimiZThs8gJT7VxVHO+7m0tDB0m0bjc61OU4nHkzm6t3ivaZ6da76IpmGrLK68/ah/FxZMFbK38XM1OwT1tv6vhSMcHSF4EPLkleQrhfuFBllrcusjTC/Xaci09xHRT7s9K/Q4RIR/miAyw9cdZxOZsRDhztEIGQZpb+BZ+dxEhFzsapuwQeQjyMQ73Flu/TfyYb/0ZxRnAPn1SV4+L053RhUKRbFRjkYlIygkiGlfP8SmFX+yIldMrWqdOAaO78e5/VqrL9MA4UtPAyy9ipKQnpLB3b0f5ch/xwqd+/2Hv9i/9WCx5tV0jQFje/PUlTNx5hh+dZdyR1ZGNvOnfUpacjq3vFRYyKxZx8ZMX/4wiceTSD6ZSmyNaMKjPXd7+e27v3zWlpQGhtPkkpsHWr/Ikt+CklKw5O0qXHHzUWx+vQVObbiFrQHS0S03hcqbA5gFWd9aPwZdCEH9EcKBNI9Q5NQr6YSstT7WMyB7bdHm9TjVQR9rAYb794EIvRqZ/iHIZDdz6KDXAzfF5yL4IogWyOTpBRTVAb0OIvIRRFDvIj0FRcVFhAxDZq/2MkJDhIwoM3sUFRgpA/KZ73X+SoByNCohmqbRcWB7Og5sX96mnLV0G9aRPf/s93iXXdM1ug/rWKI1vp2zisO7jiLdfFiZTpNj+/wscs1DWMJ0Tc9rSI161chKz3Y7d5GQsOSVrxlxxxBqNnSf4x5dNYroqu7TrAry99p/0W16sSIsYEVpMlJ8aG4UuNmvaQLTlFx6x2DWLv7ZiqYkpJbIhjwST9g4vNdB3cbZPkZqlvp0QROjnkaeHOW6IfZG1nfIxEkQMwe0qrkpQv7+XU0riuJL4RuKMKcPtDi8RzQAzf37RehVIW4+MuEWMP7LnSdXa8TeDhH9MkIEub82eJDllOVssl4jrTrYz1U3X842ggdC2lu5+i1unFEtDlR9hkIRMFR7IYWiFBhy4wCCQhz5om0FEZrA5rAxdNLAEq3x7dyVSC+bO6EJQiNDPNYuCCEICg3KH1OrUQ1ufHYsz618jB2/7yZQ+ytN0/h+/poSz1OSDV+zjo3oO7oHmu55DiEgKMSR/3uT8xpx0wvX8v28NSx6fhnxRxLJyXKW2MnII6aqP3oYJggHMv2j/PauQq8BkVOLsJJptXDN2YgIuRz/HQId9Abg6GzVMbgVDMxDyx1TckTIJXiPaGjg5Y6zsDVGVFmOiJmLCL8NEX4nIu5TtLiFliPibW2hIRwdEcEXIRwdlJNxFiKEAxE7Fxzd8o6Q36nM1hwRuwChxZaXeYoKRF6NRmk+KgMqoqFQlAJVasUy7asHeeji6aSnZCDyb5VbbV+f+Pw+atT3s9uNBxKPJXvdM0pTEh4VijQlWRnZLtEVoQmEEDzy8d10Htyh0LWarlk77wDcpRaaIP5IYonnad+vNfOe/KRY127buAvTlJiG5+cjpeUULUudhxCWPsf1re8iJT4l4BHuuk0yCYv0s6YkfSESE5IfR4bdgAi/A6FFFPEvoyMzvoDwyZDyNOArkqKDCM+NAAgIvQqZPsfLeBNsAeqg5ugFtvbg/MPLWt5rVYQQENTVeigUpyG0GETsO7m6NusBA+zngr2tci4VigCjIhoKRSnRukcLFux9nVtmTqD7pZ3oNrwTNz1/LR/uf5Nz+/lb1OuZ6g2quY2Y5KHpGnWb12bW+mmcP7Cdi7xA885NmLHiUbdOBkCH/m29FldrukabXi146+8XfHZ7kqakSu2S3yFs26slDdvWQyuGzoumaSSfTPG5iXCEOAgODSIoJIh/1m1l378HA+5kCCEZf9/hIkSM8jo9OSHtdWTqLLA3A1EU9WIDMj6Ek0Px7WQAwVcgqixD2JtaNtvOgYgHvF+T+jzSua8INrlHCA3szb2NgJTHkNKP56FQeEHYGiPCrkGEjUM42iknQ+GK0tEICCqioVCUImFRYQy/7SKG33ZRwOcefF1//l7jWbzNNEwuuv4C6reqy1NfPEj8kQSOH4gnqkqEz2hK75Fdefv+eSSdSHHrcJiGych7h1G/ZV36XtmdVQvXeeyyJU3JBdcUFmUrKkIIHl8ymXv6TCly/YlpmNiD7F5TzXSbRq/LT90B/2X578W21RvdLkqi68Dk4k+Q9haEjYPQq62fi/JtZfrXtlOE9LdStFyuPYr3bj0mMn0BIvJ+/+1xg5QZkPG5txGWknfW9xAc+H9XCoVCoQgcKqKhUAQIw2mw9rOfmTHuFZ4Y+TwfPL6I4wdOltp6fUZ3o03PFm4jCkITnNu/DT0u7ZR/LLZGDM3Ob+RXylZQSBDTlz9MeHSYy12+PNX466ZfTZeLzwNg7JSRBIcHe4xsjLpvONXqVinSc/NEjfrVeOuvF7jlpQkIL9Gc0xFCULNBNeJqxnh8vTSbzqW3n9q47v0nsL30dbvOwPFdefCNw2jeyh18kgOZ3yHCb4egPrnHAn0n1k3BdOZKvLYExYCslSVf2jgIZPgYZEPmbC35WgqFQuEBVaMRGJSjoVAEgBMHTzKx3T08ftlz/LBgDWs//Zl5Uz9hTINJfPHmilJZ0+6wM+3rhxgycYBLq9ygEAfDb72IqcvuR7cVf0fbqF195u54mZteuJa2vVrSrGMjBl9/AW/+8Ryj7xueP65Woxq8tO4pGrWv73J9cFgQ1z99NROeCmwHl9CIEIbfdhGX3Xmx386GlJKel3Xh2e+nULVOHGA5TbpNAwEh4cFMXfYAdZvVzr8mb1ygMHIMvpmznpn3Vsu1qbgzaSCTrKLW6NcR0a+BvRsBC1CLcHCc6+aEP8Xr/ozxhcP3EKTH7lEKhUKhqDio1CmFooSYpskDFz2Vr/GQl0IkcwuPX7p5NtXrVy2VdsLBoUHc/ur1THjqSnb8thshBE3Oa0hYZGhA5g+PDmPEHUMYcccQr+N+/mKTtb4mkKZEaILMtCy+n7+GC6/tQ0z16IDYU5ArH7yUdZ//wuFdvoXvbHadqKqR1G1WmznbZ7F+6UY2fvMHhtOkRZcm9LuqByHhIS7XtOzWjM9fXR5YoyWs+DiOjDQbNz9xiCo1i1NnYCJFDMgsa7MdfAEi+AKkmYBMfhYyPwdyim2iCLve/Sbefl6uYrKnjlC6Naak6HWtblfGHjynhRkQ1LfkaykUCoUnlI5GQFARDYWihGz8ZjN7/t7vsUZB0zUWPv1ZqdoQHh3Guf3a0L5v64A5Gf7y46L1vHXfPJCn1K/z/r/33wM8csnTJdfjcENkbAQ9hnfyPRAwDJPHLn2WHz5ci81uo+dlXbhr9k3c++4khkwcgG7T2bJ+G3+t+ZeUhFQAelzaiZCI4IDbDbD2yyjGdm7Jl4uugZDLQasFItTaYOv18P7RLCD5fuTRdpgJk5A5f1pHtRi06GmIaush6CK8t6PNQ7fmyxsbMhrCbnK/atgYfIn2WWNKhhACET4Jz06GDo4eCHuLEq+lUCgUitJFRTQUihKy4YtNXkXcTMPkzx+3kJGWSUhY6Wxci0pqYhq/Lv+DjNRMzmlei1bdmxer44qUkg+nfZofyTgd02my7ddd/L12K216BnZj6Mxxsvw9/2oCpClBwIsT36DrJefn/x0Mw2DB1MV8OvML0pLSAbAH2bhgTC9ufG4sk+fcyuOXPRdQu/MwnJIPpu1j6G1vudqaswMZfwXILNxv7PNeZxOyViKzVkHM6/nq1UKLhNDLkFlfe1ldgN4IHJ3APAl6TUTICISXbk/C3hoiHkCmTMdVUM/6WUTch7C39eep+0SEDAPjMDL1RSynS+b+35krvDczIOsoFAqFJ0q7jqKy1GgoR0OhKCE5WTn40/knJyun3B0NwzCY8/BCPp35Za7dFnWa1WLynFtp0blJkeZLPJbErs17vY7RbTobvtgUcEfj2L4TpMSn+n+BhMz0LH786CcGTeiHlJJnx73KDwvWuESwc7KcfP3ODyx/byU1GlRnyMQB/Pb9Zg7vOhZQ+wFSEwvbL+xNIHaRtaHPXof395YBCGTiPVBtXX7Kk8z+08fKEhFxNyL4giLZK8LGg70VMm0OZG+wDjo6I0LHIYI6F2kun2uF3wTBFyMzPrVUvkUEIngwOLqoNqQKhUJxhqBSpxSKEtKofX2vQnAAVWrHEh5dFN2D0uH1O+ewcMYSFycD4NDOw9zb7zF2/+ndaTid0+dxh0Sye/MeVn+yPj8tKRAUp9DdZtM5sP0QAH+v3cr389d4TJOVpuTwriN89fZ36LrODc9eUxJz3VKtnnulamFvghb7LqLqjxAzF7ddoE5ZCjIZMr+xfsveCGmzvC8cOq7ITka+bY5OaDGvoVX/zXrEvB5wJyN/LVsdtIg70KJnokU9iQjqqpwMhUJRNigdjYCgHA2FooRcMKYXjhC7xw6jQhMMu/UiNK18/7kd/u8on7+23O2Hm2lInNlO3n/84yLNGVszhojYcK9jTKfJxm838+TIFxhV6wZeu+s9nDkl705U7Zwq1GpUvUidXQ3D5OShBJJOJPP1O9/nt+v1hjQlh3YfZdXCdX6toTv8d4A8CSbmIfQaCL0akOVjJhvSuR0AmTYP7/UZGpiBc/gUCoVCofCEcjQUihISHh3GA/PuQNM0V40GYRW2tu/bmsvu8t61qSz4+u3vvd5BMQ2Tnz7/lbTkdJ9zSSnZsmE77zywgOr1qvqtcp2T5WTJrK95ZuzLflrtGSEEo+67tEh3haQp+W7eakbXnsivuV2n/MF0muz87T+/xhrZBpru3wsSFuVH4b4I8T0Gicgbl/M73ou2zdwxCoVCofCE0tEIDKpGQ6EoIYbTYPvGXdgcNrIzTrUrDQoJYtR9wxh933DsDruXGcqG3777y+cYaUpS4lO9dq5KS0rj8cuf5/fv/0K36Uhkkbr0SSlZ9dFPXH73UJp1bOz/hW646Lp+HNxxmI+f/RzdpvntODhzDBKPJhVpLSklVevGcfJgPKabwveC+Eqly+OfddusjlzmUcAArTpCnPaxrNUEW1Nw7sB7u9f+1o/Cj/eaP2M8IJ37kOnzc8X5DLB3QISOQTjaFXtOBUgzBTI+Q2Z9bzUCsLdBhI5G2BqVt2kKhUJRbFREQ6EoAVJKnpvwGh9OX+ziZADkZOfw7ZxVZKRmlpN1ruz717fStdAEUVUjvY55ctSLbF71D2A5Waafm/uC6DaNFe//WOTrTkcIwQ3PjOH1TTO46Lr+tO3VksYdGmBzWJt1fyML/nLpbYOxB9k9qqAXld+++5PDmwYhj/dCHu+LPN4Tmfo6Up6qfbHavd6K93avvU51jArqh8/UqTynpIjIzJXIExdB+vuWzoWxHzK/QMZfgUx7p1hznulIKZFmOlL6Sm/zMkfOv8jjFyBTnrKK7HN+g/R5yBODkWnvB9BahUKhKFuUo6FQlIBtv+7ku3mr3d7RN50mx/adYMksb21GywbTNP1yeOJqxXjtjLV90y42fbsZ03DvXAhN0Kyj7zuwpiGJP5Lgc5y/ND63AXe8PpHnVz3O6xtnsPjEu9z91k2WUGCAfA17kI1B1/Vj1vppdBp8bkCKkoUm+XpexqkD5klk6kxkwi1IeaqORQQPQkQ8jPWRrWE5ErnOhL2jS7tXEXp17hh39gnAgQgdVWRbpXEMmXg7lvp3wdQs62eZ8gzm0S6Y8eORmd8iZdEd0DMJKU1k+kLkiYuQx9ojj7bBPDkKmfldEefJQCZMAJmEa4WoAUhkylRkln/1QQqFIoCYsvQflQDlaCgUJWD5uyu9FhSbhsmXb60oQ4vco2maX/UALbs083p+3We/eH2+0pRs+3UXoZHe6wo0XRBXM9anPcUlJDyEi67rj9CEzxqO4FBvHZ0shBAMmtCPiJhwGratx5Of388nx9/h4psuLFb3q3wkHNh1+voSsldB5lJXG8LGIqquRoTfBSHDIXQMInYhInYuQjtVkC9s9RAxrwEOXD/iBYgQRMybCL1G0W3N+BhLcdzLCyrjIXsDMvFWZOJdLs7S2YSUJjJpMjL5Uav1bh45m5GJk5Cpb/o/WcaXlpYJnhwzHZn2dknMVSgUinJDORoKRQk4ceCkz7qAhCOJpaKMXVQGjO1tbby9cMmkgV7PZ6Zl+XUnv/fIbl7TiwynyYXj+vicp6TE1ojxWqguNEHTjo14b+tL3Pj8WGo3dr8Bl1Ky8ZvN7Nt6MP9YZGwE1etVLdHfVtMgJMzd+0cgU99EmsmuR/VqiPAb0aKmo0U+hHB0cPv3EEG9EVVXIcLvAEcPcPRERPwPUXUlIqhrsWyV2T/jeTNckNxoR9ZySHu3WGtVeDKXF3AEC/79rddHpj6PzNnu11Qyew3ev4oNyF5/1keIFIoKh2pvGxCUo6FQlIDoalE+W6RGxEZUiN7/V9wzlPCoULcOgKZrnDegLW17t/Q6R71WdXF6UEDPIyQimKseuszzayPggmt60aRDQ7/sPrr3ODv/+I/kkyl+jS/IoPF9vX6WS1MyaHw/6jStxeV3DWXWhmlExoW7zTo6uvc4d/d+lKQTpzb/PS7t5DGNzB8MQ9BraKI7y8D4D3msG2bS40iZ4WaMm6tytmAmPYp5fDDyxMXItLesInK9DgT1QWgxxba16DloEpk+56yMasj0eXj/+tSRGR/6OZmJ7x1HJdqVKBSKswrlaCgUJWDA2N5eIxqarjFofN8ytMgz1c6pyotrnuScFrUB8p0fIQR9R3dnyuL/+XSI+o7uRnBokMdxmq4x+Lr+1KhXlVk/PUXb3q1czgeFOBg9eTj3vjMJgOMHTvLewx9ya5cHuKXjfbx57/sc2nUEsAqlb+38AGMaTOLmDpO5osb1PHHF8xzefdTv5zzg2j7Ua1HHo3PV+NwG9B7VLf/Ydx+sJiU+zYPWiEnyyRS+euv7/GN1mtai9xXFixBouqRxm3TO6+PNgcqGjA+RCRN9btjNlJeQJ4dDxkdg7AR5EmSq1dEq42PkiaHIXFG/4iAcXSjyV4Z5AoyDvsedaTj/xXt0x4CcLX5NJRztfYzQwNYKIUqQoqdQKIqMoJTb25b3EywjlKOhUJSAtr1bWoXBblKSNF0jMi6CS+8sfw2NPOq1rMvszc/z0rqp3DJrAnfNvol5e17j/g9u91oEnkdIeAiT59wKgkKbd03XqNusFmMevQKAKnViadenFaERp+o1crKdnDycQFpyOj9/9RvXNrmVhc8sYdsvO9m+aTeLX/qS8c3v4PW753D/wKls37Qr/1pL5+MXbul0Pwd3Hvbr+QaHBvH8qsfpdNG5Lp/qQgi6DTufGd89iiPoVKvXlQvXeU2Fkqbk+/mrXY6NvG+4X7acTvMOaTy1YDe6z/2jCdk/Q+a3nu3K+ALSXs37zc0IAzCtugnjSLHsJeQKwE7Rvx7Pxq9TX3U9wk/9EyBkBFY9jafXyUSEXeu/aQqFQlGBUDoaCkUJEELw6KJ7eOW2d/l27iqXNJqm5zXkvg9up0qt0it6Lg5CCFp2bUbLrt4Lvz3R87IuPL/ycRY89SkbV2wGaQnPDZk4gCsfuJTw6DAAZt40m+Xv/uCy7zUNk+/nr2HL+m0c23sCZ47TpWNX3uu3eOaX1oHT9syG0yQtKZ3Z//uAxz+b7Je9UVUieXLp/RzefZS/121FCEGbni2oXq9qobGpCWk+50tLchU03LFxl4eR7qnfui53vTmeZo3uQPiddaUhMz5GhAwudEZKiUybjbVR9ZooBpjI9I8QEXcUyWYAoVeFmFeRCZOwHBfvKXSW2dVBr13ktSo8IYMg/SO8vQYi+EK/phJaDETPQibegvU3yptTA0wIGQXBl5TQYIVCUWSkpEgiUcWZvxKgHA2FooQEhQRxz9s3M37qaH777i9ysnJocl5DGrdvUN6mlRpterZg+vKHyUjNICM1k6gqkS7dl7b9upPl7/zg9lrTMDm44whCiGJ9zpqGyfqlG4k/kkBsjVM1B5npWfwwfw3fzV9N8slU6jSpyeAbLqDjoPYIIajZsDo1G1b3One9lnU4tPuIR20QTdeo29x141yU+pvIKhG8tG4qoRGhSOMDMg7eyIavjnHyqI2Yqk66DUomONTd2iYYHnRQZBI4t/ppgQk5v3odIY0TkPkV0oy3ulMFD0ZolraKCOoFVZZb9QeZKy0tDTyndImw8Wdlyo8IvRaZ/glW+tTpb2IdtNgiOQciuC/EfY5MnwuZK4AcK10qbAwEXVgharwUCoWiOChHQ6EIELE1YrhgTK/yNqNMCQkPISS8cIrI1+/84FOpuyTdmqSUHN17It/ROHHwJPf2e5yDOw8jEEgp2b/1IOuW/EKvy7vw4II7/WpDO2TiBaxb8ovH86ZhMvRm185cbXq18Mvmc/u34bHF9xIaYbUZ/uqdLcyeHEt6cgiaJjFNQXCowYQHDzNswsnTrhagFY7A5Frl1/qncJ8xK6WJTJ0JaW/lzqkjMSB5KkRMRoSNtSyx1UFE/A8i/od07kXGXw3mcU5tuHXAgOBhEDquiLadGQhbA4h5E5l4K8h0TumWOEGrioh916XlsF9z2psgoqZC1NTSMFmhUBSRvFqK0py/MqAcDYVCEXCO7j3ms+1vSQmPPqUL8uTIFzj831GQIHM3vHlpWGs+/ZkFTy3mmilX+Jzz/IHtuWBML76bv9ptFpJu09i9eQ9dhnZg0zd/svzdHzi69ziRVSJIiU9FuhNgEjD0pgu5/dUb8g99O3cVM2+anf+7aVp3rDPTdV57uA42u2TINfEFJpGIkBHujRYxoNUC85DP5wcawtHd/am01yDtjQIH8iIV2ciUqSDCEaGuNghbPajyFWQsRmYsA5kCtsaI0CvB0eOsvhMvgrpD1TWQuRSZ/QcIm/XaBg9ACIdfc0gzHbKWI537rahR8EXF0zhRKBSKCooqBlcoFG6RUpKWnE5Odk6Rr42qGonmQ7OjuAghqN+6LnWa1gIstfIt67d7THeSUvLZrC/JzvL9PIQQ3PveJMZPvdJta17DaTLvyU8YU/8WHrnkadYv28jO3/8jNT7tlJOR+7TziuXb9W7Fjc+NLTCHwdsPzPdqx3vTa5KT7fr6SUc3t2OFEIiwcXguJs4fCQRBaGGHS5qpPkXmZOqLSFm4JkFokYiwcWhVPkWr+i1azGuIoJ4VzsmQzp3IjCXIjC+RZrzvC/xAaOGI0KvQomegRU1DhAzx38nIWII83g2ZdD+kvYlMeQZ5vA9m0mNnZUtgheKMowLqaGRkZDBx4kTq1atHnTp1mDx5cqHsgJycHJ544gnatGlD3bp16dmzJ3/88UfRFwsQytFQKBQuZKZnMe/JTxhVeyLDo69lSOjVPHLJ02xZv83vOToOao/p7u5+AJBSMv7JK/M3sr9//7dPIcKUhDT2/rPfr/l1Xcdut2F40ceIP5wAnIqamKb1f6EJImMjqNmwOu36tOLhhXfxzLePEBRyqkvRX2v+JeFIond7E238sdY19Ubk/O75gtBrICiv+Njda2E5GSLmDYTmpjlB1iogy6tNmEchZ7P3MRUQ6dyPefIq5InBlpp30l3IYz0wk6YgpY/nXFo2Zf6ATJqcm3YFVvTItB4ZHyKTp5eLXQqFomJzzz33YJomu3bt4p9//mHlypW88sorLmO2b9+O0+lkw4YN7N+/nzFjxjB06FBycop+0zAQKEdDoVDkk5GWyf/6Pcb7j3+cvxmWpuSXr3/nrl6Psmbxz37Nc3jnMZ9jGrSuixDCJXKQ9/PEZ69h+G0XITSB0AS6XQcBIeHBTJ5zK92GdQTAMAzWfvaz+5Sl0yiK4/PF7BXFutskTUlKfCrPrXyMGSsepfdIKwpx/MBJEo4lAZB0wj/hwaT40zNbsz2OFUJHRM9ERD0P9vZAKBBspVXpTSHsFkTVFZ5VwaWfYoj+jqsgSOMEMn40FHLSnJDxETLxjhLVChXLJimRqS/gOQIlIWM+0vBfL0ahUAQeIWWpP4pCamoqc+fOZcaMGdhsNqKionjggQd49913Xca1atWKJ554grAwqwPkjTfeSFpaGjt27AjYa1MUVI2GQqHI56Onl7B9465CG3fTMBFC8MzYWXS44C3CIkM9zGDxx49/+1zr2P6TvPrr03w26ys2rdiMNCVt+7Ri+K0X0bp7cwBGTR7G6kUbSI5PoVajGvS8vIuL3sf7Uz5m68/+fXgaHhTNc7JzWPfZL2z9eYelkH5hO47tP+HXnO6QUrJ51T/0vqIrC59ewtLXluc7F43PbZDvfPiiet3THAt7W6/jhdAhZCgiZGjRjdbPCey4CoJMfw/MeNy3oTUh6wfI2QiOjmVnlLEHnNt9DJKWbkrYNWVhkUKhKEeSk5Ndfg8KCiIoqLBWz6ZNm2jQoAGxsaei0p07d+bvv//GMAx0D6JM6enppKenExUVFVjD/aTCOhpSStq0aUOPHj144403fF+gUChKhOE0WPbGtx7v/EspycrI5of5awp1Xio01o/ogZSSJh0aWgKAHqhSO44RHgQP01My+PTFL3yuAyAEbFi2kZZdmroc//fnHUwZ/gwJR5OsqImERc8vQ3NTn1EUsrNyuH/QVP5Zu9Xl9dy1eQ87f/+P6GpRJJ1Idvs6CSGpXjebVh3zND10sJ+LsDUukU1ecXTNLSg/jPtQjgb29la3JR9IaSJEBQmWp3+Kd70PHZnxGaIsHQ0z2fcYdEvVvYyQZgLk/A0IsLfNb2esUFRqcrMZS3V+oG7dui6Hp0yZwmOPPVZo+OHDh6le3bVFe7Vq1XA6nSQlJbk4IAV56KGH6NOnD7Vrl4+mUYV1NBYtWsTWrVvp0aNHeZuiqAQcP3CSHz/+iaQTKVSvV5U+o7rlC89VFhKPJ5N80ntqjG7T+e+vfT7nat+nNX+v3eoiYOg6j0a7Pq2KZWcev3//F1kZntOJCqLpGunJGS7Hjuw5xn0Dnsifw8g5tSGVRsnSaY7sPsbfa7YWSsvJcywSjyWh2zRLhaGAsyE0iRBw+9MH0DQADbQ4RNSMEtnjCyE0iJqGTLiewt+uOoggRORjHq+XZhqkf4BMXwDmEaQIheChiLDrELb6pWq7R5ukBJngY5QBxvEysScfvQ75YnwecYJe18v5wCDNVGTKdMj4jFNdxhzIkMsRkfcjRLC3yxUKRQDYv38/kZGnnHt30QwAp9NZ6DvFMKzvLXfNN9LS0pg0aRJ//fUX33zzTQAtLhoV0tFIT09nypQpjB071vdghaIEGIbBm/e+z5KXv0ZgbUgNp8lrd73HTc9dyyWTvN+5d8ff67ay9LVv2L5xF45gOz0u7cyQGwcQVzPG98XlSFCIH91yJDj8GHfRDf358OnFVpG0mz274TQZcYf7SIW/ZKX7X8hrGjK/S1Uen730FVkZ2W6dobwPc0tU0H+nQ7dptO3dih8X/ZTfZtcdmq7RZ3QPDm4/xNZfduYfb9QmgomP7qdd10zQqkHI5YjQaxB6nN82FBcR1A1i5yNTXoCcvFocAUG9ERH3eoyoSDPF0tJwbid/8yzTIeMTZOZSiHkf4WhX6vafjhACqcWCebomSUF0KON2skKPQwb1t9K2PEVbRAQEDyhVO6TMRiZMgJw/cXV6siFjIdLYDTHvIkSF3CYoFKVOceooijo/QGRkpIuj4YnY2FhOnHBN6z1+/DjBwcGF0qJ27drF0KFD6datG2vXriU01Hu6c2lSIT9BHnvsMUaPHo2UkiNHjngcl5WVRVbWqc3G6XluCoUv3n3wQz6b9VWu/gKYpvXFn5OZw8u3vk1YVCj9r+7p93xzHlnI/Kc+dRGr27vlAJ+8uIynlz9My67NSuNpBITw6DBadW/Gv+t35HdROh3DaeQXYnujSq1YHvn4Hp64/DlMKfNbz+a9Ljc8M4b2fVuXyN76rf2vF7A5dPqPcf07rvponceIC1gb1ZDwYNJTMqxNa67j0HlwB47sOc6+LQesY3ldbTVBtXOqcu+7N3N1vUle7TENk8zUDF7eMJ0D2w9x8lACMTWiOad5+YS28xCOcxFxH1iFyGY86NXdd6kqgEx9AZw7KHyH3gCZhUy8Har+UD4K4SGjcrVBPP2dDc/6JKWIiLgPmb0RZDKuzoYGSETUUwjh/q5mwMj4AnL+8HDShOwNkPUdBA8qXTsUCoVfdOjQgW3btpGQkEBMjHXj8qeffqJz585o2ql01cTERPr168fDDz/MDTfc4Gm6MqPCORpr167l66+/5tdff+Xpp5/2Onb69Ok8/vjjZWSZ4mwj6UQyi2d+4bW70HuPfEjfK7u7/CP2xJrFPzP/qU8BXMTqTMMkKy2LB4dMY8HeNwiNKKykXVG4+qHLeHDwNLfnNJtGs/Ma0aanf0rYXYeez9v/vMjSV79hw5ebMHIMWvdozrBbL6JF5yZ+zXFo1xE+f2U56z7/hZysHJqe34hht1zE+Re2o2HbejTr2Jgdv+326jAA3P7qDUTEuLaLzUzzHhGRUlK/dV1ufnEc237dhc2u02FAW2o2qE5GWibfvLeSr97+jhP7TxJdPZpB4/syZOIFhEaG4gi2k53puZWgpmsEh1tpKXWa1ioUbSlvhF4d9Oo+x1kpU97qIEyr7iNrNQT3LbFd0kyBjCXIrLWAgXCcCyFXIPRqbseLsGuRGUus1ryFbBQQPDi3S1fZImznQNwnyJRnIetb8h0hW2tExF2WGGApIzM+wup85ekDUEOmf4RQjoZCUSGoUaMGgwYN4sEHH+Tll18mMTGRp556iieeeMJl3KJFi2jevHmFcDKggjkaCQkJTJgwgYULFxIc7Ds39IEHHuDuu+/O/z05OblQUY1C4Yn1yzbhzPFWKApH9xxn5+//0fS8Rj7n++T5pWiacFtMbZqStKR0fliwlotvLN2UiJLQcdC53DX7Jmbd8hYyt9MUQmA4DZqc25Anlt5XJCG22o1rcvOL47j5xXFFtuW37/7k4Uuexsgx8h2JX77+nQ3LNnH53UOZ+Ow1/O+9SdzZ4xEyUjPcKpE3aHMO1027is5Dzit0rm7zWmzfuNtjapRu06jfqi7NOzWheSdXxygkLJjht17E8Fsvcnttz8u7sGrhOo/q6KZh0nNEF6/P/4zA2Atk+hikg3MLUDJHQ2ZvRiZcV6DFrkRmr4XU1yD6BURw4TRHocVA3EJk0iOQvZpTm+pgCBuDCL+r3IQFha0uImaWVYhtHAEtEqGXYUTLOIT3Hs4mGAfLyhqFouJRTFG9Is1fRN555x2uu+46atasSVhYGPfeey/Dhw9n3rx5/Prrr7z00kvs2LGD9evXU79+fZdrH3rooXJxPsrN0Sj4ArRt25YlS5Zw1VVXcf3119OhQwe/5vDUAkyh8If0pHSPjoHLuNOKiN1hGAZb1ntvWakJweYf/6nQjgbA4Ov703XoeXzz3kr2/nuA4NAgel7WhXP7tymzTVlKQipTLp2BM8u1+C0vBeuTF5bRvHMTel/Rldc2PsOCaYv5fv5qcrKc2IJsdB16PpffPbRQl6mCxFSP9lp/YThNhhTzbzXy3mH8+PF6hCYLdZbSbRp1m9emy8WFnR9vSJkJMgdEeAVS3bb7MUYC/qlle5zBTLTqCWQart/OJiCRiXdC3BKEvXBqotBrIGLfQjoP5Do8dnB0RGjhhcaWB0KLAa0c6re0KmAew/NuR4BWtSwtUigUPqhSpQqff/55oeNjxoxhzJgxAMyYMYMZM0q3gUhRKDdHY8+ePS6///XXX6xcuZL169czbZqVupGZmYmUkpUrV7Jtm/+qxAqFP9RuUsO3iJuAWo18p5D4gwQoY3Gw4hJTPZrR919abuuvmPsjWenZHh0BTdf4dOYX9L6iKzUbVueet2/m9teuJz05g7CoUGx27x9tO//4jw1fbPI6ptPgDn5FstzRsG09pi67nydHvkBaUjo2u46UVo1Lw7b1eHLZA+g2/2oWZNY6ZNqbVs48gFYDwsZC6FiEKNkGvsTYGoFWM7ctridMCOpTsnUyPs1t9+ru/WAdk2lzEdHu0/4AhK0O2OqUzI6zCBEyApmyxcsIiQi5rMzsUSgqHFKW7nf2GbIfKCkVJnWqTZs2ZGa6huAfe+wxjhw5onQ0FKXC+QPbE1szhoQjiW43tJqu0aF/G6qd4/uunq7rtOjchG2/7vSqQ9G2V8sS210Z+PunrV7Pm4bJ1g3bMU0zv37G7rATVcWfO+zw5ZsrXAr2CyEg8VhiUUwuxHkD2rHw4Gx+/Pgndv72H/YgG50vPo+2vVr6HZGQ6R8jkx/GKhLOxTySm9u/FmJml6uzIYQG4Tchk6d4GKGDoxvC7l9Njidk1iq85xkYkPV9idaodISMgPQPwNhP4foVHWyNIaRkneEUCoWigqgqKRRlj27TuffdSWi6QNNd/yloukZIRDCTXhrv93yX3T3Uo5OhaYKwyFD6j+lVIpsrC1ZtiB9jisl/f+/37GQASNi39VD+rwd2HOa1O99jbONbuarezUy98kX+XufdGQIIDg1i4Li+3DJrAhOfHUu73q38dzKMowU28KfbKiF7PaR/6NdcpUrIaAibmPuL7vp/e1tE9IslX0P6o5fi9D1EkY/QwhCxC8DhplYoqCci9v3S73ylUFRghCz9R2WgwkQ03OFOGVGhCCQdB7bnuR8e471HFvLnj1YagaZrdB/eieumX0XtxjX9nqvX5V0YNXkYH8343OVuuaZrOILtPLn0/grdcaoi0b5va1Z/st7jeU3XaNOzhV/dwNwRGhGM0IRXBfPgUGuT9fOXm3jssucwTTO/RmTtp/H8+NFPjHtyNFc/VErpJRmf4KtaUKZ/gAi7tnTWd7de5kpk+nuQ/RugQVBXROgEtIh7kSHDkemLwNgHIhIRMgQcPQKjEm5vl6v34Kl5gw72tiVfp5Ih9CqI2PeQzt2QvQkQ4OhkdcVSKBSKAFChHQ2Foixo3aMFz698nJOHE0g+mUJcrRgiYyOKPI8QguufHkPHi85l6avL2fbrLhwhDnqO6MzFN11I1TqlL7p2ttD/6p689/CHpCWmu9X0MA2TK+69pNjz97q8K78u/8Pjec2m0Xd0d+KPJPDEFc9j5Dhd0mnznMg5jyykWcfGnH/hKUG6jLRMVi1cx7ZfdmJz2Oh40bmcP7Adul40HQnp3I53R0OCsQ8ps8skfcpMeSFXk0Inf8OftRqZtRIiHkaEjUVEPlAqa4vQK5Hpc72MMBChSuC1uAhbQ7A1LG8zFIqKharRCAjK0VAocomrGRMQ9e52vVvRrnerAFhUeQmNCOGpLx/kgUFTSU/JyI885EWKrpt2FZ0H+9edzh19Rndn3pOfcPzgyfwoRR5CE9gddi69fTBfv/0DOdlOj98Hmq6x+KUv8x2N3777kyeueJ60pHSr2FvA568up27z2kz76kFq1Hev9+CeYKzsVm8tmHXK4mNcZq3PdTI4zR7rZ5nyFDg6u+36VOK1c7ZA9kYIGgRZX+Pi6KABJoSOK3nBuUKhUCgCjqrRUCgUFZIWnZvw3rZZjHtiNM06NqJBm3MYMLYPr218psQdsYJDg3j2hyn5qXG6XcdmtyIOETHhPP3Nw9RsWJ0/V//jNb3KNEz+Wm2l3O399wAPD51OeorVDtlwGhi5Oi0Hdx5m8gVPkJ3pT62BhQjuj08nI6h/YFKTfCDTP+BU/YU7NGSA60WkcQTz5FXIk8MtRyZruXVChANBgB3sHRDRLyMiHqhALX8VCsXZgDBL/1EZUBENheIMITM9i3Wf/cLRvceJjIug52WdiaoSWd5m+UVWRhZC03AE+dcVKo+YalFc9eAIrnpwRMBtqtmgOm///QKbvt3Mxm82YzgNWnRpSs/Lu+Tb6dfmNXfMpy8swzRMt46J6TQ5vPsoqz/ZwAX+NgQI6gd6w1xRPDeq1khEWBmJL+X87saGghiQ81vAlpNmGjL+GjAO5B0pcDIV9NqIuCUVRgtDoVAoFO5RjoZCcQaw4v0fefm2t8lIyUS36ZiGyau3v8PI/w3j2idGFbsoujQxTZNv3lvJpy9+wd4t1oaxVfdmjPzfMLpd0rGcrbPQNI2Og86l46Bz3Z5v368Nv33/l8eohm7TOLdfawBWf7LBeycrAYueX8oXb3xL8skU6jSrxZAbLqDjRee6/fsJYYPYOcj468DYgfVxLbE6UDkQ0c8hHO0KXVc6+FEDEsg6kYzPrKJytzUqhtWSNWMJhI0J3JoKhUJREFWjERAq3u5EoVC4sObTDcwY9woZKZbOjOE0kFLizDFYMG0xHzy+qJwtLIyUkueve50XbniDff8ezD/+74YdTBk+g4VPf1aO1vnPoAl9CQp2IDT3kQ3DaXLZnRcDkJXhIy1Kwu7Ne9myfhv7tx3i5y9/4+GhTzN11AsYTvfRAqHXQFRZioiZDSFXQMgwRMSDiGprEcEDS/TcikRwX3ylTomgfgFbTmYu8T0m48x4DykUCkVlRjkaCkUFRkrJOw8u8Kop8dGMJaQkpJadUX6wdvHPfDt3FYCLGKJpWHf833lwAf/9tbc8TCsS0VWjePzz+3AE2V20VnSb9fPNL4yjXR+r8P+cFrU9OiQFyXs58l6LtYt/YcG0xR7HC6EjgvqgRT2OFvU0IuxahBZV3KdULEToNVhvQnfPTwMRbDlCgcKMx2fHLZkQuPUUCoXidGQZPCoBytFQKCowuzbv4eCOw14/kHKynKxfurHsjPKDz19dXkgEsSC6TWPZGyvK0KLi06F/G97bNosr77+URu3qcU7LOlx4bR9e3zSDEXeeUk4edstFXgvHPSGl5LNZX5GTnRNIswOKsDVCRL8C2HH92hAgQhAxbyP0qoFbUD8H719PGuh1AreeQqFQKEoFVaOhUFRgUhPSfI7RNEFKfMWKaOz847/8O/buMJwmO37bXYYWlYyqdeIY9+Roxj052uOYgeP68NPSX/nly99cojhC+E7FTYlPZe8/B2h8boNAmRxwRHA/qLoKMhYhszdhpUt1hZARAY+wiJCRyOyfvIwwESGjArqmQqFQFERIiSjFOorSnLsioRwNhaICU6OBb90F05TUbFi9DKzxH0ewgzTSPQ8QEBRS+iJzZYlu03ns03v57KWvWDzrK04cOAlAXO04Th6K9xntkGfAl47Qq0D4zd4y+QJD8IWQ0R2y12MVvxdEA0cXKMsaFYVCoVAUC5U6pVBUYGrUr0b7vq09piEJAVFVI+k02H3XpPKi54jOaDbPHy8CQY9LO5ehRWWDzW7jinsvYf6e11h09G2WJMzhoQV3+HQywqJCqddSpQLlIYQNEfOGJcQnQgqcCIHQcYiYN62uXAqFQlFa5HWdKs1HJUA5GgpFBWfSS+MJCnEUcjaswmPBXW/eiM1esTZdl94+GN2muy2O1nSNyCoRDBjrp57EGYimaURXjSIsKoxW3ZvTsG29/ALy0xGaYOjNA3EEn10RnpIiRBBa5P2IqusRsQutR9X11jERVN7mKRQKhcIPlKOhUFRwGrQ+h1nrp9HhgrYuTX8an9uA6csfovvwTuVnnAfqNK3F1KX3ExwaBMJyLvIcpZjqUTz7/RTCosLK2cqyQQjBlE/vJbpalIvjlfd6nDegHddMCWDHprMMoYUiHB2shxZa3uYoFAqFoggIeSYkBvtJcnIyUVFRJCUlERl5ZigmKxRF4cTBkxzbf5KoKhHUblyzvM3xSVpyOt/PW8OWDdvQbTod+rd1Ud6uyMQfSSAtOYMTB+PZsXEXQgja9W1F0/MaFWu+5PgUlr/zAys++JGU+FRqN6nJxTdeSK/Lu6DbvGlUKBQKxdlFRd6v5dnWt8MD2PTgUlvHaWSy8rfpFfI1CCTK0VAoFIoCbPx2M+8//jH/rt9+6qCwIhPSlLTo0pRHF91Nldpx5WKfNE5A1kqQ6WBrBI5uCKGC0wqF4syhIu/XlKMRWCpWYrdCoVCUIz8sWMP0a2YV7qokT3WF2r5xJ/f0mcIbfzxHSFjpfQkVMkHmIJOnQ8aHgIGVRydBqwXRzyIcHcvMFoVCoTjbUe1tA4O6DaZQKBRAekoGL0x8M9ep8DzOcJoc2n2U7z5YXXbGATJ5CmTMx3IyIF/F0TyCjB+PzPmnTO1RKBQKhcIXytFQKBQKYNXCdWRlZPk1ViD47oMfS9miU0jnf5DxCe4l4k3AQKa+Umb2KBQKxVmPpJTb25b3EywblKOhUCgUwP5th7D5WZQtpSTpZEopW1SAzC8Ab7YZkPUD0qxYCvEKhUKhqNyoGg2FQqEAQiNDMH0I6+Wh6Rq1m5Rd1y9pJoBPPW4JMgkILwOLFAqF4iyntEX1VI2GQqFQVB56Xd4F0zD9GmsaJkNuuKCULTqF0GtjpUh5wwFabFmYo1AoFAqFXyhHQ6FQKIB6LevS47LOaG7UzAsihKDbsI50ufi8MrIMCL7ExwAdgi9BiJAyMUehUCjOeswyeFQClKOhUCgUudw39za6j+gMgNCEi5I3QFhUKFc9NIJHPr4bTSu7j0+hV0WE3+3hrA5aFCLi1jKzR6FQKBQKf1A1GgqFQpFLcGgQj358D3u37GfNpz+TnpxO9frVqN+qLsHhwTRoXRdHsKNcbBPhE0GLRqa+DObRvKMQ1AsR8TBCr1UudikUCsXZiNLRCAzK0VAoFIrTqNeyLvVa1i1vMwohQkdCyGXg/AfMdLDVR+g1ytsshUKhUCjcohwNhUJRIuKPJLDn7/3Yg+w069QYR5C9vE06qxFCB3vb8jZDoVAozm5U16mAoBwNhUJRLBKOJvLq7e+yZvHP+d2aImLCuPyeSxh9//AyrWFQKBQKhUJR8VCOhkKhKDLJ8Snc0f1hju497tISNiUhjfce/pDjB05yx2s3lKOFCoVCoVCUABXRCAjqlqNCoSgyi1/8spCTUZAv3viWXZv3lK1RCoVCoVAoKhTK0VAoKin//ryD6WNeYnTdG7mq3k28cMPr7P5zr1/XfvnWd17F7XSbzvJ3fwiUqQqFQqFQlC15EY3SfFQCVOqUQlEJWfzSl7x+1xx0m4bhtByGb+euYvl7K7lv7m30v7qnx2sNwyDxWJLX+Q2nwfH9JwJqs0KhUCgUijML5WgoFJWMLRu28/pdcwDynYyCP88Y9wrNOjWmTpOabq/XdZ2QiGAyUjI9rqHbdKKqRAbOaIVPpDQgazUy82uQaVbr25CRCFu98jZNoVAozjxMQPgcVbL5KwEqdUqhqGQsefkrdJv3f/pfvP6N1/MXju3jdQ7DadB/TK9i2acoOtKMR568HJl4I2Qug6wVkPYu8sQAZOrr5W2eQqFQKCopytFQKCoZf/64xSWScTqmYfLHqn+8znHFvZcQEhGCphf+CNE0wfkD29OmZ4sS26rwjZQSmXArOLfmHjFc/i9TX0RmfF4utikUCoWicqMcDYWikiGE71iw0LyPqV6vKi+ufpJzWtR2mVNogn5X92TKp/f6tY4iAOT8CTkbOeVgnI5Apr6BrCSFhwqFQhEIhJSl/qgMqBoNhaKScd6F7fjugx89RjU0XeP8Ae18zlO/VV1mb36efzdsZ+fve7AH2Th/YHuq1okLtMkKL8isVYCOZ0dDgrELzEOg1y47wxQKhUJR6VGOhkJRybj09sF8O3eV23NCWI7GxTdd6NdcQghadm1Gy67NAmihomhk41fFoswudUsUCoXirEEJ9gUElTqlUFQyGrWrz//euwVNEy41FpquodttTPnkXqrXq1qOFiqKgrC1BJw+BoWraIZCoVAoyhwV0VAoKiEDrulN806NWfb6t2z+8R80TeP8C9tx8U0XKifjTCN4ACTHgEzCfb9EDUKvRAhHWVumUCgUZy6mBFGKUQezckQ0lKOhUFRS6jarzaSZ48vbDEUJEcIB0bOQCddh1WkUrNUQYGuNCLulnKxTKBQKRWVGpU4pFArFGY4I6oyosgSChwFB1kGtFiLif4i4DxBaaHmap1AoFGceeTUapfmoBKiIhkKhUJwFCFtjRPTTSDkdMBFCL2+TFAqFQlHJUY6GQqFQnEVY+iXKyVAoFIqSUdpRh8oR0VCpUwqFQqFQKBQKhSLgqIiGQqFQKBQKhUJREKWjERCUo6FQKCo8WRlZLHv9W5a9/i2H/ztKSHgI/a7szuX3DKV245rlbZ5CoVAoFAo3KEdDoVBUaDLSMpnc/3G2/boLiQQJ6cnpfP3O93w3bzXPrHiUll2alreZCoVCoTibMCWlWkdRSXQ0VI2GQnGWYxgG8gwO0b4/5WO2b9ptPYcCT8NwmmRn5vDE5c9hOA3PEygUCoVCoSgXlKOhUJyFZKZn8dGMz7m6wc0Mso9maPgYnpvwKnu37C9v04pEdmY2X761AtNwp3gNpmFy8lACG77YVMaWKRQKheKsRpql/6gEKEdDoTjLyEjL5N6+j/HOg/M5tvcEAFkZ2Xw3bzU3n38ff67eUs4W+s/h3UfJSMn0Oka362zfuKuMLFIoFAqFQuEvytFQKM4yPnjsY3b8tht5Wv6n4TQxsp08ccXz5GTnlJN1RcPm8F1GJk3p1ziFQqFQKPxGKYMHBOVoKBRnEVaq0XeeU41MSdLxZH5a8msZW1Y8ajasTs2G1UB4HmMaJp2HdCg7oxQKhUKhUPiFcjQUirOIY/tOkJ6c4XWMza6z47fdZWRRydA0jdH3j/DY+EOzabTp2YKm5zUqW8MUCoVCoVD4ROUbKBRnEfYgu88xUkq/xp3OiUPxfPf+jxzZc5zIuHD6XdWT+q3qFsfMInHRdf04vPsoC5/+DN2mYThNNF3DNEwatqnHo5/cU+o2KBQKhaKSodrbBgTlaCgUZxHVzqlCnWa1OLj9kMf0T8Np0uXi84o074Jpi5k75SMAhCZAyv+3d+/BUZV5Gsef7kDSIENMYEMICbkQxOGmG0KFGERBhtsUDLuExUXk4gUFR82ACAR3wqyJgtY4CqyoS8IQUgMjgpIgYClkFDasUQsonJKgXCTLZQ0hlw50CH3ZP1gjMR0Q7fQ5pr+fqlMFJ6dPP3mrc7p//Z73fbXh+bc1YupQPZU3V+2Db7xw+aEsFosefG6q7rnvTm3/zw906quz6nRzR901+Q6l/DpJQe2CWu25AQDAj0ehAbQhFotFUzP/WS/MWOX159Ygq/rd0Ud9Bif+4HNuX7NLa5/Z8N2Oq5asKN74X+rQyaaM1x75sZF/sLh+MZr78qxWfx4AAFp9wDaDwQH8HP3q/rs04w9TJF0ZwyCLFNTuyp96r9vjlLX5qR98LpfLpfX/vqnFn3vcHu3I3a3KM1U/LTQAAGhz6NEA2qBp/5auu+9N0441u3Tqy9Pq2Lmj7vqXO5Q8+jYFBf3wW42OHjihc/9Tec1j3G63/rvoU/169q9+amwAAMzBo1bu0Wi9U5sJhQbQRkX37q6Hl0/7Seeov3DpusdYrVY56q69qB4AAAg8FBoAWhR9S3dZrJZmi/9dze1yK9YPs08BAOA3jNHwCcZoAGhReGSY7pgwuHGMx/dZrBZF9OyqQb8a6OdkAADA7Cg0AFzT3FdmKfQfQmUNanq5sAZZ1S64nRatf0JWK5cSAEAb4na3/hYA+HQA4JoiYrrqPz5ZpnEP3aOQDsGSJKvVojsmJGtFSY4G3PlLgxMCAAAzYowGgOvqGhWuJ1fP1pyXZ8l+vk4dO3dQh5tsRscCAKB1MEbDJ0zZo7F+/XoNGDBAPXv2VGxsrE6ePGl0JACSgkPaq0v3MIoMAABwXabr0SgoKNDy5ctVWFiohIQEnT9/XjYbH2oAAADgJ/Ro+ISpCg2n06kFCxZoy5YtSkhIkCSFh4cbnAoAAADAjTJVobFnzx6FhoYqNTXV6CgAAsTlhsvas/ljHSz+XG63R/3SbtXdU+6QrWOI0dEAAEZxe9Sqy3dfY32qtsRUhcahQ4d0yy23KDMzU2+++aZCQkI0c+ZMPfXUU7JYLM2Ov3Tpki5d+m7l4traWn/GBfAzd/zQ11o8NkeVp6sU1C5Ikkc783brjQX5erZwkfrd0cfoiAAA/GyZajC43W7X3r171b9/fx05ckRFRUVas2aN8vPzvR7//PPPKzQ0tHGLiWF1YgA/jL2qTgvu+YOq/rdGkuRyuuRyXpnX/EL1BS0ek61vTlYYGREAYBCPx93qWyAwrNCIi4tr3CZMmCBJ6tq1q26//XZNnTpVVqtVCQkJeuyxx1RYWOj1HIsXL1ZNTU3jVl5e7s9fAcDP2M68YtWer5Pb1fxi73Z7dMnRoMJX3zMgGQAAbYNht06dOHGi2b6+ffvKbrc32We1WlucdSokJEQhIdxHDeDG7dny3/Jc4x5Zt8utDzft00PLpvkxFQDAFDye1h1HESCzTpnq1qmhQ4fK4XA03ip16tQprVy5UtOm8UYPwLfq6+qve8wlR4MfkgAA0DaZqtCwWCzavHmz1qxZo6ioKI0aNUpLlizR2LFjjY4GoI1J/Md4BbVr+RJoDbIqYWCsHxMBANC2mGrWKUnq06ePPvroI6NjAGjjxs8ZrffzP2zx526XWxPmjvZjIgCAaXhaeXpbbp0CgLbrlym9de+if5IkWazfTZ/97UzaYx4codTxyUZEAwCgTTBdjwYA+MsDOf+qhIGxevPFrfpq/3FJUnSfHkqfN15jHxzhdf0eAEAAcLslSytOQRsg09tSaAAIWBaLRcPvTdPwe9PkqHPI7fao4y86UGAAAOADFBoAIKlDpw5GRwAAmAVjNHyCMRoAAAAAfI4eDQAAAOAqHrdbnlYco+EJkDEa9GgAAAAA8Dl6NAAAAICrMUbDJ+jRAAAAAOBz9GgAAAAAV3N7JAs9Gj8VPRoAAAAAfI4eDQAAAOBqHo+k1lwZnB4NAAAAAPhR6NEAAAAAruJxe+RpxTEaHno0AAAAAODHoUcDAAAAuJrHrdYdo8HK4AAAAADwo1BoAAAAACbncDg0e/ZsxcbGKjo6Wk8//bTXsR779+/XkCFDFBsbq759++r99983IO0VFBoAAADAVTxuT6tvN2r+/Plyu906evSo/v73v6u4uFirVq1qcozdbtf48eOVnZ2tr7/+WqtXr9bkyZN19uxZXzXNDaHQAAAAAEysrq5O69at0wsvvKB27dopNDRUixcvVl5eXpPjNmzYoMGDB2vkyJGSpLvuukvDhg3TX//6VyNiMxgcAAAAaMJkg8E/++wzxcfHKzw8vHFfSkqKPv/8c7lcLgUFBUmS9u3bp7S0tCaPTUlJ0YEDB35y5B+jTRUa396nVltba3ASAAAAePPt5zQzryXh1GWpFeM5dVlS88+sISEhCgkJaXb8mTNn1K1btyb7IiIi5HQ6VVNT01iAnDlzRiNGjGh23Mcff+zL+D9Ymyo07Ha7JCkmJsbgJAAAALgWu92u0NBQo2M0ERwcrMjISO09u73Vn6tTp07NPrNmZWVp6dKlzY51Op3NCjOXyyVJslgs1z3u6mP8qU0VGlFRUSovL9cvfvELwxrUl2praxUTE6Py8nJ17tzZ6DimQbt4R7t4R7t4R7t4R7u0jLbxjnbx7lrt4vF4ZLfbFRUVZVC6ltlsNh0/flwNDQ2t/lwej6fZ51VvvRmSFB4ernPnzjXZV1FRIZvN1qRYa+m4yMhIH6W+MW2q0LBarYqOjjY6hs917tyZi5cXtIt3tIt3tIt3tIt3tEvLaBvvaBfvWmoXs/VkXM1ms8lmsxkdo4mkpCSVlZWpqqpKYWFhkqSSkhKlpKTIav1ubqdBgwappKRE8+bNa9xXUlKiKVOm+D2zxKxTAAAAgKlFRkZqzJgxyszMlNPp1Llz55STk6OMjIwmx913333atWuXdu/eLUnavn27vvjiC02ePNmA1BQaAAAAgOnl5ubq9OnT6t69u5KTkzV79mxNnDhRBQUFevLJJyVJ0dHR2rhxo+bOnauIiAhlZ2erqKhIN910kyGZ29StU21NSEiIsrKyWrxfL1DRLt7RLt7RLt7RLt7RLi2jbbyjXbyjXXyva9eu2rp1a7P906ZN07Rp0xr/P3r0aB0+fNif0Vpk8Zh5bjEAAAAAP0vcOgUAAADA5yg0AAAAAPgchQYAAAAAn6PQ+BlYv369BgwYoJ49eyo2NlYnT540OpJpeDwe9e/fX48++qjRUQzn8Xj06quv6rbbblNsbKySkpIap7cLVA6HQ7Nnz1ZsbKyio6P19NNPN1sxNRDt3r1baWlpSkxMVK9evbRy5UqjI5nOnDlzdOuttxodw1RKS0s1bNgwxcbGKioqSlu2bDE6kuFOnTql8ePHq0ePHkpISNCzzz5rdCTDeDwe5efnKzU1tcn+/fv3a8iQIYqNjVXfvn31/vvvG5QQRmDWKZMrKCjQ8uXLVVhYqISEBJ0/f950i8gYadOmTTp8+LCGDh1qdBTDXbhwQQcOHNDf/vY3hYWFafv27Zo0aZLKysoUERFhdDxDzJ8/X263W0ePHtWFCxc0cuRIrVq1So8//rjR0Qy1detW5eXlqU+fPjp27JiGDRum3r17a8yYMUZHM4Xy8nLl5+crJibG6CimcfjwYU2cOFH5+fkaOXKkGhoaVF1dbXQsw02fPl3JyckqLCxUVVWVRowYoZiYGM2cOdPoaH61c+dOLViwQA6HQ+3afffR0m63a/z48frzn/+skSNH6sMPP9RvfvMbHT582LCVquFfzDplYk6nUzExMdqyZUuzbwggXbx4UYMGDVJqaqqCg4P12muvGR3JdJKSkpSdna1x48YZHcXv6urq1K1bN5WXlys8PFyStGXLFj377LPav3+/wenMZd68eWrXrp1eeOEFo6OYQnp6uiIjI/XBBx+YZopIo02aNEnJyclavHix0VFMJTw8XB999JH69+8vSXrmmWdUXV2tVatWGZzMvzZv3qwOHTqoY8eOevTRRxv/bt544w3t2LFDb7/9duOxEyZM0D333NO47gPaNm6dMrE9e/YoNDSUIqMFS5cu1b333quePXsaHcWUPB6PKisrFRoaanQUQ3z22WeKj49vLDIkKSUlRZ9//rlcLpeBycynoqIiYF8n3/fuu++qsrJS6enpRkcxjfr6em3btk2zZs0yOorppKena9WqVWpoaNDXX3+trVu3BuRrZ9KkSV6/0Nq3b5/S0tKa7EtJSdGBAwf8lAxGo9AwsUOHDumWW25RZmamEhMT1a9fP7344ovcYy5p79692rFjhxYuXGh0FNNasWKFOnXqFLCF6pkzZ9StW7cm+yIiIuR0OlVTU2NQKvMpLS3Vtm3bNHXqVKOjGK6yslJPPPGEVq9ebXQUUzly5Ig6dOig4uJiDRw4UAkJCXrkkUdUW1trdDTD5eTkaOfOnQoLC1N8fLyGDx+uu+++2+hYptHSdbiystKgRPA3Cg0Ts9vt2rt3r/r3768jR46oqKhIa9asUX5+vtHRDFVVVaUHHnhA69atY7yKF06nU4sWLdKKFSv0zjvvyGoNzD9zp9PZrCj/tifDYrEYEcl0Nm7cqAkTJmjdunWKj483Oo6hPB6PHnzwQWVkZDAI/HvsdrucTqc+/fRTlZaW6uDBg6qoqAj4W19cLpfGjRunjIwM1dTU6NSpUzp48KBeeeUVo6OZRkvXYa7BgYPB4CYRFxfX+O+BAweqsLBQXbt21e233974TWNCQoIee+wxFRYWasaMGQYl9a/vt8s777yjqVOn6qGHHlJSUpJxwQzm7fUiXbkFZuLEierSpYtKS0vVpUsXgxIaLzw8XOfOnWuyr6KiQjabLeBvE3K5XHr88cdVXFys9957T7fddpvRkQy3bNkyXb58Wb/97W+NjmI6Xbt21eXLl7Vs2TK1b99eNptNS5cu1fDhw42OZqjdu3eroaFBGRkZkqTu3bvrpZde0oQJEwK+CPtWS9dhBoIHDgoNkzhx4kSzfX379pXdbm+yz2q1BtS3+N9vl0OHDqm4uFj79u3Tc889J+nK/cMej0fFxcUqKyszIKX/eXu9OJ1OjR49WuPGjVN2drb/Q5lMUlKSysrKVFVVpbCwMElSSUmJUlJSAraX51sZGRk6duyYPv30U910001GxzGFFStW6MKFC42vFafTKYfDoZtvvlmffPKJevfubXBC48TGxio4OFj19fVq3769pMB7L/KmoaGhyQxLktS+fXs1NDQYlMh8Bg0apJKSEs2bN69xX0lJiaZMmWJgKvhTYL/bmtzQoUPlcDgab5U6deqUVq5cqWnTphmczDgDBgxQfX29qqurG7dFixZp1qxZAVNktKS4uFgXL16kyPh/kZGRGjNmjDIzM+V0OnXu3Dnl5OQ0fvsYqOrr67V69WqtXbuWIuMqZ86cUW1tbeN1Zdu2berdu7eqq6sDusiQJJvNpunTp2v+/PlyOp26dOmSsrKyAvq9SLryHn327Flt2LBB0pWZ7pYsWRKQg8Fbct9992nXrl2Nazpt375dX3zxhSZPnmxwMvgLhYaJWSwWbd68WWvWrFFUVJRGjRqlJUuWaOzYsUZHgwl9+eWXOnnypOLi4ppsWVlZRkczTG5urk6fPq3u3bsrOTlZs2fP1sSJE42OZahjx47J7XYrNTW1yetk9OjRRkeDiS1fvlwOh0M9evRQv379lJiYGNCL00lSaGio3nvvPa1du1ZxcXEaOHCgEhMT9cc//tHoaKYRHR2tjRs3au7cuYqIiFB2draKior4kiOAsI4GAAAAAJ+jRwMAAACAz1FoAAAAAPA5Cg0AAAAAPkehAQAAAMDnKDQAAAAA+ByFBgAAAACfo9AAAAAA4HMUGgAAAAB8jkIDAFrZzJkzFRYWpri4OMXExGjEiBEqLS1t/HlNTY0yMzPVt29fxcfHq1u3bhoyZIguXrzY5Dx/+tOfFBISosrKSq/P43Q69dJLLwX86ucAAHOg0AAAP1i4cKFOnDih8vJyzZkzR+PGjVNFRYW++eYbpaamymazad++fTp+/LjOnj2rF198UUFBQU3OkZeXp379+qmgoKDZ+QsKCtS7d2+9+uqrqq+v99evBQBAiyg0AMDPJk+erF69eqmkpEQPP/yw7r//fv3+979XaGioJMlisejOO+9USEhI42NKS0t1+fJl5eTkKDc3t9k5GxoaVFBQoGeeecZvvwcAANdCoQEABqirq1N1dbWKi4v1u9/97rrH5+bmasaMGRo1apQqKyv1ySefNPn5Aw88oLS0tNaKCwDADWtndAAACCQXLlzQyy+/rODgYNlsNg0cOFA2m+2aj3E4HNq0aZMOHTqkoKAgTZ8+Xbm5uRo8eLCfUgMAcOPo0QAAP1i+fLni4uKUkpLS2JPhdrvlcrmu+9i33npLgwcPVo8ePSRdGVy+ceNGORyO1o4NAMCPRo8GAPjBwoULtWjRoib7evXqpbKyMrlcrmYDv6+Wm5urkpKSJj0fDQ0Neuutt3T//fe3WmYAAH4KejQAwCDJycnq0qWLXn/99RaPOXr0qA4ePKi6ujrV19c3bq+//rrXQeEAAJgFhQYAGMRqtWrt2rXKysrS2rVr1dDQIOnKehhFRUWqr69XXl6exo8fr+Dg4CaPTU9P18cff6yvvvrKiOgAAFwXhQYAGGjo0KHavXu33n33XSUkJCguLk6JiYn6y1/+IovFovz8fKWnpzd7XFhYmMaOHau8vDwDUgMAcH0Wj8fjMToEAAAAgLaFHg0AAAAAPkehAQAAAMDnKDQAAAAA+ByFBgAAAACfo9AAAAAA4HMUGgAAAAB8jkIDAAAAgM9RaAAAAADwOQoNAAAAAD5HoQEAAADA5yg0AAAAAPjc/wEaW3vxXpOwoQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 2일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
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       "      <th class=\"blank level0\" >&nbsp;</th>\n",
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       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
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       "      <td id=\"T_98089_row1_col1\" class=\"data row1 col1\" >0.656875</td>\n",
       "      <td id=\"T_98089_row1_col2\" class=\"data row1 col2\" >21.418875</td>\n",
       "      <td id=\"T_98089_row1_col3\" class=\"data row1 col3\" >2529.167168</td>\n",
       "      <td id=\"T_98089_row1_col4\" class=\"data row1 col4\" >0.252449</td>\n",
       "      <td id=\"T_98089_row1_col5\" class=\"data row1 col5\" >0.052705</td>\n",
       "      <td id=\"T_98089_row1_col6\" class=\"data row1 col6\" >0.184400</td>\n",
       "      <td id=\"T_98089_row1_col7\" class=\"data row1 col7\" >0.078168</td>\n",
       "      <td id=\"T_98089_row1_col8\" class=\"data row1 col8\" >0.086311</td>\n",
       "      <td id=\"T_98089_row1_col9\" class=\"data row1 col9\" >0.168766</td>\n",
       "      <td id=\"T_98089_row1_col10\" class=\"data row1 col10\" >0.160137</td>\n",
       "      <td id=\"T_98089_row1_col11\" class=\"data row1 col11\" >0.220656</td>\n",
       "      <td id=\"T_98089_row1_col12\" class=\"data row1 col12\" >0.097723</td>\n",
       "      <td id=\"T_98089_row1_col13\" class=\"data row1 col13\" >0.103289</td>\n",
       "      <td id=\"T_98089_row1_col14\" class=\"data row1 col14\" >0.231280</td>\n",
       "      <td id=\"T_98089_row1_col15\" class=\"data row1 col15\" >0.256491</td>\n",
       "      <td id=\"T_98089_row1_col16\" class=\"data row1 col16\" >0.237352</td>\n",
       "      <td id=\"T_98089_row1_col17\" class=\"data row1 col17\" >0.231541</td>\n",
       "      <td id=\"T_98089_row1_col18\" class=\"data row1 col18\" >0.361571</td>\n",
       "      <td id=\"T_98089_row1_col19\" class=\"data row1 col19\" >0.338567</td>\n",
       "      <td id=\"T_98089_row1_col20\" class=\"data row1 col20\" >0.071169</td>\n",
       "      <td id=\"T_98089_row1_col21\" class=\"data row1 col21\" >0.068307</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x14b242bf990>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 3일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_20452_row0_col0, #T_20452_row0_col5, #T_20452_row0_col11, #T_20452_row0_col14, #T_20452_row0_col15, #T_20452_row0_col16, #T_20452_row0_col17, #T_20452_row1_col4, #T_20452_row1_col6, #T_20452_row1_col9, #T_20452_row1_col12, #T_20452_row1_col13, #T_20452_row2_col1, #T_20452_row2_col2, #T_20452_row2_col3, #T_20452_row2_col7, #T_20452_row2_col8, #T_20452_row2_col10, #T_20452_row2_col18, #T_20452_row2_col19, #T_20452_row2_col20, #T_20452_row2_col21 {\n",
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       "#T_20452_row0_col1, #T_20452_row0_col6, #T_20452_row0_col7, #T_20452_row0_col9, #T_20452_row0_col13, #T_20452_row0_col18, #T_20452_row0_col19, #T_20452_row0_col20, #T_20452_row0_col21, #T_20452_row1_col2, #T_20452_row1_col3, #T_20452_row1_col8, #T_20452_row1_col10, #T_20452_row1_col16, #T_20452_row1_col17, #T_20452_row2_col0, #T_20452_row2_col4, #T_20452_row2_col5, #T_20452_row2_col11, #T_20452_row2_col12, #T_20452_row2_col14, #T_20452_row2_col15 {\n",
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       "<table id=\"T_20452\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_20452_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_20452_level0_col1\" class=\"col_heading level0 col1\" >남성고객비율</th>\n",
       "      <th id=\"T_20452_level0_col2\" class=\"col_heading level0 col2\" >평균이용시간</th>\n",
       "      <th id=\"T_20452_level0_col3\" class=\"col_heading level0 col3\" >평균이용거리</th>\n",
       "      <th id=\"T_20452_level0_col4\" class=\"col_heading level0 col4\" >주말대여비율</th>\n",
       "      <th id=\"T_20452_level0_col5\" class=\"col_heading level0 col5\" >새벽대여비율</th>\n",
       "      <th id=\"T_20452_level0_col6\" class=\"col_heading level0 col6\" >출근시간대여비율</th>\n",
       "      <th id=\"T_20452_level0_col7\" class=\"col_heading level0 col7\" >오전대여비율</th>\n",
       "      <th id=\"T_20452_level0_col8\" class=\"col_heading level0 col8\" >점심대여비율</th>\n",
       "      <th id=\"T_20452_level0_col9\" class=\"col_heading level0 col9\" >오후대여비율</th>\n",
       "      <th id=\"T_20452_level0_col10\" class=\"col_heading level0 col10\" >퇴근시간대여비율</th>\n",
       "      <th id=\"T_20452_level0_col11\" class=\"col_heading level0 col11\" >야간대여비율</th>\n",
       "      <th id=\"T_20452_level0_col12\" class=\"col_heading level0 col12\" >주중청소년고객비율</th>\n",
       "      <th id=\"T_20452_level0_col13\" class=\"col_heading level0 col13\" >주말청소년고객비율</th>\n",
       "      <th id=\"T_20452_level0_col14\" class=\"col_heading level0 col14\" >주중청년1고객비율</th>\n",
       "      <th id=\"T_20452_level0_col15\" class=\"col_heading level0 col15\" >주말청년1고객비율</th>\n",
       "      <th id=\"T_20452_level0_col16\" class=\"col_heading level0 col16\" >주중청년2고객비율</th>\n",
       "      <th id=\"T_20452_level0_col17\" class=\"col_heading level0 col17\" >주말청년2고객비율</th>\n",
       "      <th id=\"T_20452_level0_col18\" class=\"col_heading level0 col18\" >주중장년고객비율</th>\n",
       "      <th id=\"T_20452_level0_col19\" class=\"col_heading level0 col19\" >주말장년고객비율</th>\n",
       "      <th id=\"T_20452_level0_col20\" class=\"col_heading level0 col20\" >주중노인고객비율</th>\n",
       "      <th id=\"T_20452_level0_col21\" class=\"col_heading level0 col21\" >주말노인고객비율</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "      <th class=\"blank col8\" >&nbsp;</th>\n",
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       "      <td id=\"T_20452_row1_col17\" class=\"data row1 col17\" >0.196196</td>\n",
       "      <td id=\"T_20452_row1_col18\" class=\"data row1 col18\" >0.312957</td>\n",
       "      <td id=\"T_20452_row1_col19\" class=\"data row1 col19\" >0.293623</td>\n",
       "      <td id=\"T_20452_row1_col20\" class=\"data row1 col20\" >0.053545</td>\n",
       "      <td id=\"T_20452_row1_col21\" class=\"data row1 col21\" >0.050725</td>\n",
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       "      <th id=\"T_20452_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
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       "      <td id=\"T_20452_row2_col1\" class=\"data row2 col1\" >0.659060</td>\n",
       "      <td id=\"T_20452_row2_col2\" class=\"data row2 col2\" >23.018267</td>\n",
       "      <td id=\"T_20452_row2_col3\" class=\"data row2 col3\" >2706.572233</td>\n",
       "      <td id=\"T_20452_row2_col4\" class=\"data row2 col4\" >0.238969</td>\n",
       "      <td id=\"T_20452_row2_col5\" class=\"data row2 col5\" >0.046677</td>\n",
       "      <td id=\"T_20452_row2_col6\" class=\"data row2 col6\" >0.175029</td>\n",
       "      <td id=\"T_20452_row2_col7\" class=\"data row2 col7\" >0.081563</td>\n",
       "      <td id=\"T_20452_row2_col8\" class=\"data row2 col8\" >0.089387</td>\n",
       "      <td id=\"T_20452_row2_col9\" class=\"data row2 col9\" >0.166143</td>\n",
       "      <td id=\"T_20452_row2_col10\" class=\"data row2 col10\" >0.185774</td>\n",
       "      <td id=\"T_20452_row2_col11\" class=\"data row2 col11\" >0.211764</td>\n",
       "      <td id=\"T_20452_row2_col12\" class=\"data row2 col12\" >0.040389</td>\n",
       "      <td id=\"T_20452_row2_col13\" class=\"data row2 col13\" >0.051421</td>\n",
       "      <td id=\"T_20452_row2_col14\" class=\"data row2 col14\" >0.224201</td>\n",
       "      <td id=\"T_20452_row2_col15\" class=\"data row2 col15\" >0.257535</td>\n",
       "      <td id=\"T_20452_row2_col16\" class=\"data row2 col16\" >0.285092</td>\n",
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      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x14acb87b990>"
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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 4일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
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       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_76929_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_76929_level0_col1\" class=\"col_heading level0 col1\" >남성고객비율</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
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       "      <th id=\"T_76929_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_76929_row1_col0\" class=\"data row1 col0\" >2414.575492</td>\n",
       "      <td id=\"T_76929_row1_col1\" class=\"data row1 col1\" >0.656653</td>\n",
       "      <td id=\"T_76929_row1_col2\" class=\"data row1 col2\" >17.810825</td>\n",
       "      <td id=\"T_76929_row1_col3\" class=\"data row1 col3\" >2046.672445</td>\n",
       "      <td id=\"T_76929_row1_col4\" class=\"data row1 col4\" >0.249090</td>\n",
       "      <td id=\"T_76929_row1_col5\" class=\"data row1 col5\" >0.048666</td>\n",
       "      <td id=\"T_76929_row1_col6\" class=\"data row1 col6\" >0.188544</td>\n",
       "      <td id=\"T_76929_row1_col7\" class=\"data row1 col7\" >0.072761</td>\n",
       "      <td id=\"T_76929_row1_col8\" class=\"data row1 col8\" >0.083006</td>\n",
       "      <td id=\"T_76929_row1_col9\" class=\"data row1 col9\" >0.173694</td>\n",
       "      <td id=\"T_76929_row1_col10\" class=\"data row1 col10\" >0.144934</td>\n",
       "      <td id=\"T_76929_row1_col11\" class=\"data row1 col11\" >0.238546</td>\n",
       "      <td id=\"T_76929_row1_col12\" class=\"data row1 col12\" >0.195088</td>\n",
       "      <td id=\"T_76929_row1_col13\" class=\"data row1 col13\" >0.190543</td>\n",
       "      <td id=\"T_76929_row1_col14\" class=\"data row1 col14\" >0.245020</td>\n",
       "      <td id=\"T_76929_row1_col15\" class=\"data row1 col15\" >0.275551</td>\n",
       "      <td id=\"T_76929_row1_col16\" class=\"data row1 col16\" >0.198827</td>\n",
       "      <td id=\"T_76929_row1_col17\" class=\"data row1 col17\" >0.195116</td>\n",
       "      <td id=\"T_76929_row1_col18\" class=\"data row1 col18\" >0.311186</td>\n",
       "      <td id=\"T_76929_row1_col19\" class=\"data row1 col19\" >0.290988</td>\n",
       "      <td id=\"T_76929_row1_col20\" class=\"data row1 col20\" >0.049065</td>\n",
       "      <td id=\"T_76929_row1_col21\" class=\"data row1 col21\" >0.046849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76929_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "      <td id=\"T_76929_row2_col0\" class=\"data row2 col0\" >1868.454031</td>\n",
       "      <td id=\"T_76929_row2_col1\" class=\"data row2 col1\" >0.670387</td>\n",
       "      <td id=\"T_76929_row2_col2\" class=\"data row2 col2\" >20.306824</td>\n",
       "      <td id=\"T_76929_row2_col3\" class=\"data row2 col3\" >2278.375440</td>\n",
       "      <td id=\"T_76929_row2_col4\" class=\"data row2 col4\" >0.199986</td>\n",
       "      <td id=\"T_76929_row2_col5\" class=\"data row2 col5\" >0.034474</td>\n",
       "      <td id=\"T_76929_row2_col6\" class=\"data row2 col6\" >0.179187</td>\n",
       "      <td id=\"T_76929_row2_col7\" class=\"data row2 col7\" >0.083323</td>\n",
       "      <td id=\"T_76929_row2_col8\" class=\"data row2 col8\" >0.089216</td>\n",
       "      <td id=\"T_76929_row2_col9\" class=\"data row2 col9\" >0.159346</td>\n",
       "      <td id=\"T_76929_row2_col10\" class=\"data row2 col10\" >0.216953</td>\n",
       "      <td id=\"T_76929_row2_col11\" class=\"data row2 col11\" >0.199891</td>\n",
       "      <td id=\"T_76929_row2_col12\" class=\"data row2 col12\" >0.030388</td>\n",
       "      <td id=\"T_76929_row2_col13\" class=\"data row2 col13\" >0.043736</td>\n",
       "      <td id=\"T_76929_row2_col14\" class=\"data row2 col14\" >0.222959</td>\n",
       "      <td id=\"T_76929_row2_col15\" class=\"data row2 col15\" >0.273279</td>\n",
       "      <td id=\"T_76929_row2_col16\" class=\"data row2 col16\" >0.337050</td>\n",
       "      <td id=\"T_76929_row2_col17\" class=\"data row2 col17\" >0.327159</td>\n",
       "      <td id=\"T_76929_row2_col18\" class=\"data row2 col18\" >0.357878</td>\n",
       "      <td id=\"T_76929_row2_col19\" class=\"data row2 col19\" >0.305836</td>\n",
       "      <td id=\"T_76929_row2_col20\" class=\"data row2 col20\" >0.051050</td>\n",
       "      <td id=\"T_76929_row2_col21\" class=\"data row2 col21\" >0.048047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76929_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "      <td id=\"T_76929_row3_col0\" class=\"data row3 col0\" >1419.019316</td>\n",
       "      <td id=\"T_76929_row3_col1\" class=\"data row3 col1\" >0.639889</td>\n",
       "      <td id=\"T_76929_row3_col2\" class=\"data row3 col2\" >25.763734</td>\n",
       "      <td id=\"T_76929_row3_col3\" class=\"data row3 col3\" >3144.470853</td>\n",
       "      <td id=\"T_76929_row3_col4\" class=\"data row3 col4\" >0.280588</td>\n",
       "      <td id=\"T_76929_row3_col5\" class=\"data row3 col5\" >0.060746</td>\n",
       "      <td id=\"T_76929_row3_col6\" class=\"data row3 col6\" >0.164215</td>\n",
       "      <td id=\"T_76929_row3_col7\" class=\"data row3 col7\" >0.075233</td>\n",
       "      <td id=\"T_76929_row3_col8\" class=\"data row3 col8\" >0.086062</td>\n",
       "      <td id=\"T_76929_row3_col9\" class=\"data row3 col9\" >0.169923</td>\n",
       "      <td id=\"T_76929_row3_col10\" class=\"data row3 col10\" >0.157017</td>\n",
       "      <td id=\"T_76929_row3_col11\" class=\"data row3 col11\" >0.236713</td>\n",
       "      <td id=\"T_76929_row3_col12\" class=\"data row3 col12\" >0.056250</td>\n",
       "      <td id=\"T_76929_row3_col13\" class=\"data row3 col13\" >0.065377</td>\n",
       "      <td id=\"T_76929_row3_col14\" class=\"data row3 col14\" >0.244568</td>\n",
       "      <td id=\"T_76929_row3_col15\" class=\"data row3 col15\" >0.261241</td>\n",
       "      <td id=\"T_76929_row3_col16\" class=\"data row3 col16\" >0.238447</td>\n",
       "      <td id=\"T_76929_row3_col17\" class=\"data row3 col17\" >0.236673</td>\n",
       "      <td id=\"T_76929_row3_col18\" class=\"data row3 col18\" >0.371754</td>\n",
       "      <td id=\"T_76929_row3_col19\" class=\"data row3 col19\" >0.352629</td>\n",
       "      <td id=\"T_76929_row3_col20\" class=\"data row3 col20\" >0.087891</td>\n",
       "      <td id=\"T_76929_row3_col21\" class=\"data row3 col21\" >0.082834</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x14b244db510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 2일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   0\n",
      "1     ST-1000   1\n",
      "2     ST-1002   1\n",
      "3     ST-1003   1\n",
      "4     ST-1004   1\n",
      "5     ST-1005   1\n",
      "6     ST-1006   1\n",
      "7     ST-1007   1\n",
      "8     ST-1008   1\n",
      "9     ST-1010   1\n",
      "10    ST-1011   1\n",
      "11    ST-1012   1\n",
      "12    ST-1013   0\n",
      "13    ST-1014   1\n",
      "14    ST-1015   1\n",
      "15    ST-1016   1\n",
      "16    ST-1017   1\n",
      "17    ST-1018   1\n",
      "18    ST-1019   0\n",
      "19     ST-102   0\n",
      "20    ST-1020   0\n",
      "21    ST-1023   1\n",
      "22    ST-1024   1\n",
      "23    ST-1025   0\n",
      "24    ST-1027   1\n",
      "25    ST-1028   1\n",
      "26    ST-1029   0\n",
      "27     ST-103   0\n",
      "28    ST-1031   1\n",
      "29    ST-1032   1\n",
      "30    ST-1033   0\n",
      "31    ST-1034   0\n",
      "32    ST-1035   0\n",
      "33    ST-1036   1\n",
      "34    ST-1038   0\n",
      "35    ST-1039   0\n",
      "36    ST-1040   1\n",
      "37    ST-1041   0\n",
      "38    ST-1042   1\n",
      "39    ST-1044   0\n",
      "40    ST-1045   0\n",
      "41    ST-1046   0\n",
      "42    ST-1047   0\n",
      "43    ST-1048   1\n",
      "44    ST-1049   1\n",
      "45     ST-105   0\n",
      "46    ST-1050   1\n",
      "47    ST-1051   1\n",
      "48    ST-1053   1\n",
      "49    ST-1054   1\n",
      "50    ST-1055   1\n",
      "51    ST-1056   1\n",
      "52    ST-1058   1\n",
      "53    ST-1059   1\n",
      "54     ST-106   0\n",
      "55    ST-1061   0\n",
      "56    ST-1062   0\n",
      "57    ST-1063   1\n",
      "58    ST-1064   0\n",
      "59    ST-1065   0\n",
      "60    ST-1067   0\n",
      "61    ST-1069   0\n",
      "62     ST-107   0\n",
      "63    ST-1070   0\n",
      "64    ST-1072   0\n",
      "65    ST-1075   0\n",
      "66    ST-1076   0\n",
      "67    ST-1077   1\n",
      "68    ST-1078   0\n",
      "69    ST-1079   0\n",
      "70     ST-108   0\n",
      "71    ST-1081   0\n",
      "72    ST-1082   1\n",
      "73    ST-1083   0\n",
      "74    ST-1084   0\n",
      "75    ST-1085   0\n",
      "76    ST-1086   1\n",
      "77    ST-1087   0\n",
      "78    ST-1088   0\n",
      "79    ST-1089   1\n",
      "80     ST-109   0\n",
      "81    ST-1092   0\n",
      "82    ST-1093   1\n",
      "83    ST-1095   1\n",
      "84    ST-1096   1\n",
      "85    ST-1097   0\n",
      "86    ST-1098   0\n",
      "87    ST-1099   0\n",
      "88      ST-11   0\n",
      "89     ST-110   0\n",
      "90    ST-1100   0\n",
      "91    ST-1101   1\n",
      "92    ST-1102   1\n",
      "93    ST-1103   1\n",
      "94    ST-1104   0\n",
      "95    ST-1105   0\n",
      "96    ST-1106   1\n",
      "97    ST-1107   1\n",
      "98    ST-1109   0\n",
      "99     ST-111   0\n",
      "100   ST-1110   1\n",
      "101   ST-1111   0\n",
      "102   ST-1114   1\n",
      "103   ST-1118   1\n",
      "104   ST-1119   1\n",
      "105    ST-112   0\n",
      "106   ST-1120   1\n",
      "107   ST-1121   0\n",
      "108   ST-1122   1\n",
      "109   ST-1123   1\n",
      "110   ST-1124   0\n",
      "111   ST-1125   1\n",
      "112   ST-1127   1\n",
      "113   ST-1128   1\n",
      "114   ST-1129   0\n",
      "115    ST-113   0\n",
      "116   ST-1130   1\n",
      "117   ST-1131   1\n",
      "118   ST-1132   1\n",
      "119   ST-1133   1\n",
      "120   ST-1135   1\n",
      "121   ST-1136   1\n",
      "122   ST-1137   1\n",
      "123    ST-114   0\n",
      "124   ST-1140   0\n",
      "125   ST-1141   0\n",
      "126   ST-1142   0\n",
      "127   ST-1143   0\n",
      "128   ST-1144   0\n",
      "129   ST-1146   0\n",
      "130   ST-1147   0\n",
      "131   ST-1148   1\n",
      "132   ST-1149   0\n",
      "133   ST-1150   0\n",
      "134   ST-1151   0\n",
      "135   ST-1152   0\n",
      "136   ST-1153   1\n",
      "137   ST-1154   1\n",
      "138   ST-1156   0\n",
      "139   ST-1158   0\n",
      "140    ST-116   1\n",
      "141   ST-1160   0\n",
      "142   ST-1161   0\n",
      "143   ST-1162   1\n",
      "144   ST-1163   1\n",
      "145   ST-1164   1\n",
      "146   ST-1165   0\n",
      "147   ST-1166   0\n",
      "148   ST-1167   1\n",
      "149   ST-1168   0\n",
      "150   ST-1169   1\n",
      "151    ST-117   0\n",
      "152   ST-1171   0\n",
      "153   ST-1172   0\n",
      "154   ST-1173   0\n",
      "155   ST-1174   0\n",
      "156   ST-1177   1\n",
      "157   ST-1178   1\n",
      "158   ST-1179   1\n",
      "159    ST-118   0\n",
      "160   ST-1180   1\n",
      "161   ST-1181   1\n",
      "162   ST-1182   1\n",
      "163   ST-1184   1\n",
      "164   ST-1185   1\n",
      "165   ST-1186   1\n",
      "166   ST-1188   0\n",
      "167   ST-1189   1\n",
      "168    ST-119   1\n",
      "169   ST-1190   0\n",
      "170   ST-1191   0\n",
      "171   ST-1192   0\n",
      "172   ST-1193   0\n",
      "173   ST-1194   0\n",
      "174   ST-1195   1\n",
      "175   ST-1197   0\n",
      "176   ST-1198   0\n",
      "177   ST-1199   0\n",
      "178     ST-12   0\n",
      "179   ST-1200   1\n",
      "180   ST-1201   0\n",
      "181   ST-1202   0\n",
      "182   ST-1203   1\n",
      "183   ST-1204   0\n",
      "184   ST-1206   1\n",
      "185   ST-1207   0\n",
      "186   ST-1208   1\n",
      "187    ST-121   1\n",
      "188   ST-1210   1\n",
      "189   ST-1211   1\n",
      "190   ST-1212   1\n",
      "191   ST-1213   1\n",
      "192   ST-1215   0\n",
      "193   ST-1216   1\n",
      "194   ST-1217   1\n",
      "195   ST-1218   1\n",
      "196   ST-1219   1\n",
      "197   ST-1220   0\n",
      "198   ST-1221   0\n",
      "199   ST-1222   0\n",
      "200   ST-1223   0\n",
      "201   ST-1224   0\n",
      "202   ST-1226   1\n",
      "203   ST-1227   1\n",
      "204   ST-1228   1\n",
      "205   ST-1229   1\n",
      "206    ST-123   1\n",
      "207   ST-1230   1\n",
      "208   ST-1231   1\n",
      "209   ST-1233   0\n",
      "210   ST-1235   1\n",
      "211   ST-1236   1\n",
      "212   ST-1237   0\n",
      "213   ST-1238   0\n",
      "214   ST-1239   1\n",
      "215    ST-124   1\n",
      "216   ST-1241   1\n",
      "217   ST-1243   1\n",
      "218   ST-1245   1\n",
      "219   ST-1246   0\n",
      "220   ST-1247   0\n",
      "221   ST-1248   1\n",
      "222   ST-1249   0\n",
      "223    ST-125   0\n",
      "224   ST-1250   1\n",
      "225   ST-1251   0\n",
      "226   ST-1252   1\n",
      "227   ST-1253   1\n",
      "228   ST-1254   1\n",
      "229   ST-1259   0\n",
      "230    ST-126   0\n",
      "231   ST-1260   0\n",
      "232   ST-1262   0\n",
      "233   ST-1263   0\n",
      "234   ST-1264   0\n",
      "235   ST-1265   0\n",
      "236   ST-1266   0\n",
      "237   ST-1267   1\n",
      "238   ST-1268   0\n",
      "239   ST-1269   0\n",
      "240   ST-1270   0\n",
      "241   ST-1271   1\n",
      "242   ST-1273   0\n",
      "243   ST-1274   0\n",
      "244   ST-1275   0\n",
      "245   ST-1276   0\n",
      "246   ST-1277   0\n",
      "247   ST-1278   1\n",
      "248   ST-1279   0\n",
      "249   ST-1280   0\n",
      "250   ST-1281   1\n",
      "251   ST-1282   1\n",
      "252   ST-1283   1\n",
      "253   ST-1284   1\n",
      "254   ST-1285   0\n",
      "255   ST-1286   1\n",
      "256   ST-1287   1\n",
      "257   ST-1288   1\n",
      "258   ST-1289   1\n",
      "259   ST-1291   0\n",
      "260   ST-1292   1\n",
      "261   ST-1293   1\n",
      "262   ST-1295   1\n",
      "263   ST-1296   0\n",
      "264   ST-1297   1\n",
      "265   ST-1298   0\n",
      "266   ST-1299   0\n",
      "267    ST-130   0\n",
      "268   ST-1300   1\n",
      "269   ST-1302   0\n",
      "270   ST-1305   0\n",
      "271   ST-1306   1\n",
      "272   ST-1307   1\n",
      "273   ST-1309   0\n",
      "274   ST-1310   0\n",
      "275   ST-1311   1\n",
      "276   ST-1312   1\n",
      "277   ST-1313   1\n",
      "278   ST-1314   1\n",
      "279   ST-1315   1\n",
      "280   ST-1317   0\n",
      "281    ST-132   0\n",
      "282   ST-1320   0\n",
      "283   ST-1321   0\n",
      "284   ST-1323   0\n",
      "285   ST-1324   1\n",
      "286   ST-1325   0\n",
      "287   ST-1326   0\n",
      "288   ST-1327   1\n",
      "289   ST-1328   0\n",
      "290   ST-1329   1\n",
      "291   ST-1331   1\n",
      "292   ST-1332   0\n",
      "293   ST-1333   1\n",
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      "295   ST-1335   1\n",
      "296   ST-1337   0\n",
      "297   ST-1338   1\n",
      "298   ST-1339   1\n",
      "299    ST-134   0\n",
      "300   ST-1341   0\n",
      "301   ST-1342   0\n",
      "302   ST-1343   1\n",
      "303   ST-1344   0\n",
      "304   ST-1345   1\n",
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      "336   ST-1383   1\n",
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      "338   ST-1386   1\n",
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      "344   ST-1392   1\n",
      "345   ST-1394   0\n",
      "346   ST-1395   0\n",
      "347   ST-1396   0\n",
      "348   ST-1397   1\n",
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      "2464   ST-694   1\n",
      "2465   ST-695   0\n",
      "2466   ST-696   0\n",
      "2467   ST-697   1\n",
      "2468   ST-699   0\n",
      "2469     ST-7   0\n",
      "2470    ST-70   1\n",
      "2471   ST-700   0\n",
      "2472   ST-701   1\n",
      "2473   ST-702   0\n",
      "2474   ST-703   0\n",
      "2475   ST-704   0\n",
      "2476   ST-705   1\n",
      "2477   ST-707   1\n",
      "2478   ST-709   1\n",
      "2479    ST-71   0\n",
      "2480   ST-712   0\n",
      "2481   ST-713   0\n",
      "2482   ST-714   0\n",
      "2483   ST-715   0\n",
      "2484   ST-717   0\n",
      "2485   ST-719   0\n",
      "2486    ST-72   0\n",
      "2487   ST-720   0\n",
      "2488   ST-721   0\n",
      "2489   ST-722   0\n",
      "2490   ST-723   0\n",
      "2491   ST-724   0\n",
      "2492   ST-725   0\n",
      "2493   ST-726   0\n",
      "2494   ST-727   1\n",
      "2495   ST-728   0\n",
      "2496   ST-729   0\n",
      "2497    ST-73   0\n",
      "2498   ST-731   0\n",
      "2499   ST-732   1\n",
      "2500   ST-733   1\n",
      "2501   ST-735   0\n",
      "2502   ST-736   1\n",
      "2503   ST-737   0\n",
      "2504   ST-738   1\n",
      "2505   ST-740   0\n",
      "2506   ST-741   1\n",
      "2507   ST-742   1\n",
      "2508   ST-743   1\n",
      "2509   ST-744   1\n",
      "2510   ST-745   1\n",
      "2511   ST-746   1\n",
      "2512   ST-747   1\n",
      "2513   ST-748   1\n",
      "2514   ST-749   1\n",
      "2515   ST-750   0\n",
      "2516   ST-752   1\n",
      "2517   ST-753   0\n",
      "2518   ST-754   1\n",
      "2519   ST-755   1\n",
      "2520   ST-756   1\n",
      "2521   ST-757   1\n",
      "2522   ST-758   0\n",
      "2523   ST-759   0\n",
      "2524    ST-76   1\n",
      "2525   ST-760   0\n",
      "2526   ST-761   0\n",
      "2527   ST-762   1\n",
      "2528   ST-763   1\n",
      "2529   ST-764   1\n",
      "2530   ST-765   0\n",
      "2531   ST-766   1\n",
      "2532   ST-767   0\n",
      "2533   ST-768   0\n",
      "2534   ST-769   0\n",
      "2535    ST-77   1\n",
      "2536   ST-770   1\n",
      "2537   ST-771   1\n",
      "2538   ST-772   1\n",
      "2539   ST-773   1\n",
      "2540   ST-774   1\n",
      "2541   ST-775   1\n",
      "2542   ST-776   0\n",
      "2543   ST-777   0\n",
      "2544   ST-778   1\n",
      "2545   ST-779   1\n",
      "2546    ST-78   0\n",
      "2547   ST-780   1\n",
      "2548   ST-781   0\n",
      "2549   ST-782   1\n",
      "2550   ST-783   0\n",
      "2551   ST-784   0\n",
      "2552   ST-786   1\n",
      "2553   ST-787   0\n",
      "2554   ST-788   0\n",
      "2555   ST-789   1\n",
      "2556   ST-790   1\n",
      "2557   ST-791   0\n",
      "2558   ST-792   0\n",
      "2559   ST-793   1\n",
      "2560   ST-794   0\n",
      "2561   ST-795   1\n",
      "2562   ST-796   1\n",
      "2563   ST-797   0\n",
      "2564   ST-798   1\n",
      "2565   ST-799   1\n",
      "2566     ST-8   0\n",
      "2567    ST-80   1\n",
      "2568   ST-801   1\n",
      "2569   ST-802   0\n",
      "2570   ST-803   1\n",
      "2571   ST-804   1\n",
      "2572   ST-806   1\n",
      "2573   ST-807   1\n",
      "2574   ST-808   1\n",
      "2575   ST-809   1\n",
      "2576    ST-81   1\n",
      "2577   ST-810   0\n",
      "2578   ST-811   0\n",
      "2579   ST-812   0\n",
      "2580   ST-813   0\n",
      "2581   ST-814   1\n",
      "2582   ST-815   1\n",
      "2583   ST-816   0\n",
      "2584   ST-817   1\n",
      "2585   ST-818   1\n",
      "2586   ST-819   1\n",
      "2587    ST-82   0\n",
      "2588   ST-820   1\n",
      "2589   ST-821   0\n",
      "2590   ST-822   1\n",
      "2591   ST-823   1\n",
      "2592   ST-824   1\n",
      "2593   ST-825   0\n",
      "2594   ST-826   1\n",
      "2595   ST-827   0\n",
      "2596   ST-828   1\n",
      "2597   ST-829   0\n",
      "2598    ST-83   1\n",
      "2599   ST-830   1\n",
      "2600   ST-831   1\n",
      "2601   ST-834   0\n",
      "2602   ST-835   1\n",
      "2603   ST-838   0\n",
      "2604   ST-839   0\n",
      "2605    ST-84   1\n",
      "2606   ST-840   0\n",
      "2607   ST-842   0\n",
      "2608   ST-847   0\n",
      "2609   ST-849   0\n",
      "2610    ST-85   1\n",
      "2611   ST-850   0\n",
      "2612   ST-852   0\n",
      "2613   ST-853   1\n",
      "2614   ST-854   1\n",
      "2615   ST-855   1\n",
      "2616   ST-856   1\n",
      "2617   ST-857   0\n",
      "2618   ST-859   1\n",
      "2619    ST-86   0\n",
      "2620   ST-860   1\n",
      "2621   ST-861   1\n",
      "2622   ST-862   0\n",
      "2623   ST-863   0\n",
      "2624   ST-866   1\n",
      "2625   ST-867   1\n",
      "2626   ST-868   1\n",
      "2627   ST-869   1\n",
      "2628    ST-87   1\n",
      "2629   ST-870   1\n",
      "2630   ST-871   0\n",
      "2631   ST-872   1\n",
      "2632   ST-873   0\n",
      "2633   ST-874   1\n",
      "2634   ST-875   1\n",
      "2635   ST-876   0\n",
      "2636   ST-877   0\n",
      "2637   ST-879   1\n",
      "2638    ST-88   1\n",
      "2639   ST-880   1\n",
      "2640   ST-881   1\n",
      "2641   ST-882   0\n",
      "2642   ST-883   0\n",
      "2643   ST-884   0\n",
      "2644   ST-885   1\n",
      "2645   ST-886   0\n",
      "2646   ST-887   0\n",
      "2647   ST-889   1\n",
      "2648    ST-89   1\n",
      "2649   ST-890   1\n",
      "2650   ST-891   0\n",
      "2651   ST-892   1\n",
      "2652   ST-894   1\n",
      "2653   ST-895   1\n",
      "2654   ST-896   1\n",
      "2655   ST-897   1\n",
      "2656   ST-899   0\n",
      "2657     ST-9   0\n",
      "2658    ST-90   0\n",
      "2659   ST-900   0\n",
      "2660   ST-901   0\n",
      "2661   ST-902   0\n",
      "2662   ST-903   0\n",
      "2663   ST-904   0\n",
      "2664   ST-905   0\n",
      "2665   ST-906   1\n",
      "2666   ST-907   1\n",
      "2667   ST-908   1\n",
      "2668    ST-91   0\n",
      "2669   ST-910   0\n",
      "2670   ST-912   0\n",
      "2671   ST-913   0\n",
      "2672   ST-914   1\n",
      "2673   ST-915   1\n",
      "2674   ST-916   1\n",
      "2675   ST-918   0\n",
      "2676   ST-919   0\n",
      "2677    ST-92   1\n",
      "2678   ST-920   1\n",
      "2679   ST-923   0\n",
      "2680   ST-924   0\n",
      "2681   ST-925   1\n",
      "2682   ST-926   1\n",
      "2683   ST-927   1\n",
      "2684   ST-928   1\n",
      "2685   ST-929   1\n",
      "2686    ST-93   0\n",
      "2687   ST-930   1\n",
      "2688   ST-931   1\n",
      "2689   ST-932   0\n",
      "2690   ST-933   0\n",
      "2691   ST-935   0\n",
      "2692   ST-936   0\n",
      "2693   ST-937   1\n",
      "2694   ST-938   1\n",
      "2695   ST-939   1\n",
      "2696    ST-94   0\n",
      "2697   ST-941   1\n",
      "2698   ST-942   0\n",
      "2699   ST-943   1\n",
      "2700   ST-944   0\n",
      "2701   ST-946   0\n",
      "2702   ST-947   1\n",
      "2703   ST-948   0\n",
      "2704   ST-949   0\n",
      "2705    ST-95   0\n",
      "2706   ST-950   0\n",
      "2707   ST-951   0\n",
      "2708   ST-952   0\n",
      "2709   ST-953   1\n",
      "2710   ST-954   1\n",
      "2711   ST-956   0\n",
      "2712   ST-957   1\n",
      "2713   ST-958   1\n",
      "2714   ST-959   0\n",
      "2715    ST-96   0\n",
      "2716   ST-960   1\n",
      "2717   ST-961   1\n",
      "2718   ST-962   1\n",
      "2719   ST-963   0\n",
      "2720   ST-964   0\n",
      "2721   ST-965   0\n",
      "2722   ST-966   0\n",
      "2723   ST-967   1\n",
      "2724   ST-968   1\n",
      "2725    ST-97   0\n",
      "2726   ST-970   1\n",
      "2727   ST-971   1\n",
      "2728   ST-972   0\n",
      "2729   ST-973   0\n",
      "2730   ST-974   0\n",
      "2731   ST-975   1\n",
      "2732   ST-977   1\n",
      "2733   ST-978   1\n",
      "2734   ST-979   1\n",
      "2735    ST-98   0\n",
      "2736   ST-980   0\n",
      "2737   ST-981   0\n",
      "2738   ST-983   0\n",
      "2739   ST-984   0\n",
      "2740   ST-985   0\n",
      "2741   ST-986   0\n",
      "2742   ST-987   0\n",
      "2743   ST-988   0\n",
      "2744    ST-99   0\n",
      "2745   ST-990   0\n",
      "2746   ST-991   1\n",
      "2747   ST-992   1\n",
      "2748   ST-993   1\n",
      "2749   ST-994   0\n",
      "2750   ST-995   1\n",
      "2751   ST-996   0\n",
      "2752   ST-997   1\n",
      "n_clusters = 3일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   0\n",
      "1     ST-1000   1\n",
      "2     ST-1002   1\n",
      "3     ST-1003   1\n",
      "4     ST-1004   1\n",
      "5     ST-1005   1\n",
      "6     ST-1006   1\n",
      "7     ST-1007   1\n",
      "8     ST-1008   1\n",
      "9     ST-1010   1\n",
      "10    ST-1011   1\n",
      "11    ST-1012   1\n",
      "12    ST-1013   0\n",
      "13    ST-1014   1\n",
      "14    ST-1015   1\n",
      "15    ST-1016   1\n",
      "16    ST-1017   1\n",
      "17    ST-1018   1\n",
      "18    ST-1019   1\n",
      "19     ST-102   0\n",
      "20    ST-1020   0\n",
      "21    ST-1023   2\n",
      "22    ST-1024   1\n",
      "23    ST-1025   0\n",
      "24    ST-1027   2\n",
      "25    ST-1028   2\n",
      "26    ST-1029   0\n",
      "27     ST-103   0\n",
      "28    ST-1031   1\n",
      "29    ST-1032   1\n",
      "30    ST-1033   0\n",
      "31    ST-1034   0\n",
      "32    ST-1035   0\n",
      "33    ST-1036   0\n",
      "34    ST-1038   0\n",
      "35    ST-1039   0\n",
      "36    ST-1040   2\n",
      "37    ST-1041   0\n",
      "38    ST-1042   2\n",
      "39    ST-1044   2\n",
      "40    ST-1045   0\n",
      "41    ST-1046   0\n",
      "42    ST-1047   0\n",
      "43    ST-1048   2\n",
      "44    ST-1049   2\n",
      "45     ST-105   0\n",
      "46    ST-1050   1\n",
      "47    ST-1051   1\n",
      "48    ST-1053   1\n",
      "49    ST-1054   2\n",
      "50    ST-1055   2\n",
      "51    ST-1056   1\n",
      "52    ST-1058   1\n",
      "53    ST-1059   1\n",
      "54     ST-106   0\n",
      "55    ST-1061   0\n",
      "56    ST-1062   0\n",
      "57    ST-1063   1\n",
      "58    ST-1064   0\n",
      "59    ST-1065   0\n",
      "60    ST-1067   1\n",
      "61    ST-1069   0\n",
      "62     ST-107   0\n",
      "63    ST-1070   0\n",
      "64    ST-1072   0\n",
      "65    ST-1075   0\n",
      "66    ST-1076   2\n",
      "67    ST-1077   2\n",
      "68    ST-1078   0\n",
      "69    ST-1079   0\n",
      "70     ST-108   0\n",
      "71    ST-1081   0\n",
      "72    ST-1082   2\n",
      "73    ST-1083   0\n",
      "74    ST-1084   2\n",
      "75    ST-1085   0\n",
      "76    ST-1086   2\n",
      "77    ST-1087   0\n",
      "78    ST-1088   2\n",
      "79    ST-1089   2\n",
      "80     ST-109   0\n",
      "81    ST-1092   1\n",
      "82    ST-1093   1\n",
      "83    ST-1095   2\n",
      "84    ST-1096   2\n",
      "85    ST-1097   0\n",
      "86    ST-1098   0\n",
      "87    ST-1099   0\n",
      "88      ST-11   0\n",
      "89     ST-110   0\n",
      "90    ST-1100   0\n",
      "91    ST-1101   2\n",
      "92    ST-1102   1\n",
      "93    ST-1103   0\n",
      "94    ST-1104   0\n",
      "95    ST-1105   0\n",
      "96    ST-1106   2\n",
      "97    ST-1107   0\n",
      "98    ST-1109   0\n",
      "99     ST-111   0\n",
      "100   ST-1110   2\n",
      "101   ST-1111   0\n",
      "102   ST-1114   2\n",
      "103   ST-1118   1\n",
      "104   ST-1119   1\n",
      "105    ST-112   0\n",
      "106   ST-1120   1\n",
      "107   ST-1121   0\n",
      "108   ST-1122   1\n",
      "109   ST-1123   2\n",
      "110   ST-1124   0\n",
      "111   ST-1125   2\n",
      "112   ST-1127   1\n",
      "113   ST-1128   1\n",
      "114   ST-1129   1\n",
      "115    ST-113   0\n",
      "116   ST-1130   2\n",
      "117   ST-1131   2\n",
      "118   ST-1132   2\n",
      "119   ST-1133   2\n",
      "120   ST-1135   2\n",
      "121   ST-1136   2\n",
      "122   ST-1137   1\n",
      "123    ST-114   0\n",
      "124   ST-1140   0\n",
      "125   ST-1141   0\n",
      "126   ST-1142   0\n",
      "127   ST-1143   0\n",
      "128   ST-1144   0\n",
      "129   ST-1146   2\n",
      "130   ST-1147   0\n",
      "131   ST-1148   2\n",
      "132   ST-1149   0\n",
      "133   ST-1150   0\n",
      "134   ST-1151   0\n",
      "135   ST-1152   0\n",
      "136   ST-1153   2\n",
      "137   ST-1154   2\n",
      "138   ST-1156   0\n",
      "139   ST-1158   2\n",
      "140    ST-116   2\n",
      "141   ST-1160   0\n",
      "142   ST-1161   0\n",
      "143   ST-1162   2\n",
      "144   ST-1163   2\n",
      "145   ST-1164   2\n",
      "146   ST-1165   2\n",
      "147   ST-1166   2\n",
      "148   ST-1167   2\n",
      "149   ST-1168   2\n",
      "150   ST-1169   2\n",
      "151    ST-117   2\n",
      "152   ST-1171   0\n",
      "153   ST-1172   2\n",
      "154   ST-1173   0\n",
      "155   ST-1174   0\n",
      "156   ST-1177   2\n",
      "157   ST-1178   2\n",
      "158   ST-1179   1\n",
      "159    ST-118   0\n",
      "160   ST-1180   2\n",
      "161   ST-1181   2\n",
      "162   ST-1182   0\n",
      "163   ST-1184   2\n",
      "164   ST-1185   2\n",
      "165   ST-1186   2\n",
      "166   ST-1188   0\n",
      "167   ST-1189   2\n",
      "168    ST-119   2\n",
      "169   ST-1190   0\n",
      "170   ST-1191   0\n",
      "171   ST-1192   0\n",
      "172   ST-1193   0\n",
      "173   ST-1194   0\n",
      "174   ST-1195   2\n",
      "175   ST-1197   0\n",
      "176   ST-1198   0\n",
      "177   ST-1199   0\n",
      "178     ST-12   0\n",
      "179   ST-1200   0\n",
      "180   ST-1201   0\n",
      "181   ST-1202   0\n",
      "182   ST-1203   1\n",
      "183   ST-1204   2\n",
      "184   ST-1206   2\n",
      "185   ST-1207   0\n",
      "186   ST-1208   2\n",
      "187    ST-121   2\n",
      "188   ST-1210   1\n",
      "189   ST-1211   2\n",
      "190   ST-1212   1\n",
      "191   ST-1213   2\n",
      "192   ST-1215   0\n",
      "193   ST-1216   2\n",
      "194   ST-1217   0\n",
      "195   ST-1218   1\n",
      "196   ST-1219   1\n",
      "197   ST-1220   0\n",
      "198   ST-1221   0\n",
      "199   ST-1222   0\n",
      "200   ST-1223   0\n",
      "201   ST-1224   0\n",
      "202   ST-1226   1\n",
      "203   ST-1227   1\n",
      "204   ST-1228   1\n",
      "205   ST-1229   1\n",
      "206    ST-123   2\n",
      "207   ST-1230   1\n",
      "208   ST-1231   1\n",
      "209   ST-1233   0\n",
      "210   ST-1235   1\n",
      "211   ST-1236   1\n",
      "212   ST-1237   0\n",
      "213   ST-1238   2\n",
      "214   ST-1239   1\n",
      "215    ST-124   2\n",
      "216   ST-1241   2\n",
      "217   ST-1243   2\n",
      "218   ST-1245   2\n",
      "219   ST-1246   2\n",
      "220   ST-1247   0\n",
      "221   ST-1248   2\n",
      "222   ST-1249   0\n",
      "223    ST-125   2\n",
      "224   ST-1250   2\n",
      "225   ST-1251   0\n",
      "226   ST-1252   2\n",
      "227   ST-1253   1\n",
      "228   ST-1254   1\n",
      "229   ST-1259   0\n",
      "230    ST-126   2\n",
      "231   ST-1260   0\n",
      "232   ST-1262   0\n",
      "233   ST-1263   0\n",
      "234   ST-1264   0\n",
      "235   ST-1265   0\n",
      "236   ST-1266   0\n",
      "237   ST-1267   2\n",
      "238   ST-1268   0\n",
      "239   ST-1269   0\n",
      "240   ST-1270   0\n",
      "241   ST-1271   1\n",
      "242   ST-1273   0\n",
      "243   ST-1274   0\n",
      "244   ST-1275   0\n",
      "245   ST-1276   0\n",
      "246   ST-1277   0\n",
      "247   ST-1278   2\n",
      "248   ST-1279   0\n",
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      "2362   ST-580   0\n",
      "2363   ST-583   1\n",
      "2364   ST-584   1\n",
      "2365   ST-585   1\n",
      "2366   ST-586   1\n",
      "2367   ST-587   2\n",
      "2368   ST-588   1\n",
      "2369   ST-589   0\n",
      "2370    ST-59   2\n",
      "2371   ST-590   0\n",
      "2372   ST-593   1\n",
      "2373   ST-594   0\n",
      "2374   ST-595   2\n",
      "2375   ST-596   1\n",
      "2376   ST-599   0\n",
      "2377     ST-6   0\n",
      "2378    ST-60   2\n",
      "2379   ST-600   0\n",
      "2380   ST-602   0\n",
      "2381   ST-603   0\n",
      "2382   ST-604   0\n",
      "2383   ST-605   2\n",
      "2384   ST-608   2\n",
      "2385   ST-609   2\n",
      "2386   ST-610   0\n",
      "2387   ST-611   0\n",
      "2388   ST-612   1\n",
      "2389   ST-613   0\n",
      "2390   ST-614   2\n",
      "2391   ST-615   1\n",
      "2392   ST-616   2\n",
      "2393   ST-619   2\n",
      "2394    ST-62   2\n",
      "2395   ST-620   0\n",
      "2396   ST-621   2\n",
      "2397   ST-622   2\n",
      "2398   ST-623   2\n",
      "2399   ST-624   0\n",
      "2400   ST-625   0\n",
      "2401   ST-626   2\n",
      "2402   ST-628   2\n",
      "2403   ST-629   1\n",
      "2404    ST-63   2\n",
      "2405   ST-630   2\n",
      "2406   ST-631   0\n",
      "2407   ST-632   2\n",
      "2408   ST-633   2\n",
      "2409   ST-634   2\n",
      "2410   ST-635   0\n",
      "2411   ST-636   0\n",
      "2412   ST-637   0\n",
      "2413   ST-638   0\n",
      "2414   ST-639   0\n",
      "2415    ST-64   2\n",
      "2416   ST-640   2\n",
      "2417   ST-641   2\n",
      "2418   ST-642   2\n",
      "2419   ST-643   0\n",
      "2420   ST-644   2\n",
      "2421   ST-645   2\n",
      "2422   ST-646   0\n",
      "2423   ST-647   2\n",
      "2424   ST-648   2\n",
      "2425   ST-650   0\n",
      "2426   ST-651   2\n",
      "2427   ST-652   2\n",
      "2428   ST-654   2\n",
      "2429   ST-655   0\n",
      "2430   ST-657   2\n",
      "2431   ST-658   0\n",
      "2432    ST-66   2\n",
      "2433   ST-660   2\n",
      "2434   ST-661   0\n",
      "2435   ST-662   1\n",
      "2436   ST-663   1\n",
      "2437   ST-664   0\n",
      "2438   ST-665   1\n",
      "2439   ST-666   1\n",
      "2440   ST-667   0\n",
      "2441   ST-668   0\n",
      "2442   ST-669   1\n",
      "2443    ST-67   2\n",
      "2444   ST-670   1\n",
      "2445   ST-671   1\n",
      "2446   ST-673   0\n",
      "2447   ST-674   0\n",
      "2448   ST-675   0\n",
      "2449   ST-676   1\n",
      "2450   ST-677   0\n",
      "2451   ST-678   1\n",
      "2452   ST-679   2\n",
      "2453    ST-68   2\n",
      "2454   ST-683   0\n",
      "2455   ST-685   0\n",
      "2456   ST-686   0\n",
      "2457   ST-687   0\n",
      "2458   ST-688   0\n",
      "2459    ST-69   2\n",
      "2460   ST-690   0\n",
      "2461   ST-691   0\n",
      "2462   ST-692   0\n",
      "2463   ST-693   0\n",
      "2464   ST-694   2\n",
      "2465   ST-695   2\n",
      "2466   ST-696   0\n",
      "2467   ST-697   2\n",
      "2468   ST-699   0\n",
      "2469     ST-7   0\n",
      "2470    ST-70   2\n",
      "2471   ST-700   0\n",
      "2472   ST-701   2\n",
      "2473   ST-702   0\n",
      "2474   ST-703   0\n",
      "2475   ST-704   0\n",
      "2476   ST-705   2\n",
      "2477   ST-707   2\n",
      "2478   ST-709   2\n",
      "2479    ST-71   2\n",
      "2480   ST-712   0\n",
      "2481   ST-713   0\n",
      "2482   ST-714   0\n",
      "2483   ST-715   0\n",
      "2484   ST-717   0\n",
      "2485   ST-719   0\n",
      "2486    ST-72   2\n",
      "2487   ST-720   0\n",
      "2488   ST-721   0\n",
      "2489   ST-722   0\n",
      "2490   ST-723   0\n",
      "2491   ST-724   2\n",
      "2492   ST-725   0\n",
      "2493   ST-726   0\n",
      "2494   ST-727   2\n",
      "2495   ST-728   0\n",
      "2496   ST-729   0\n",
      "2497    ST-73   0\n",
      "2498   ST-731   0\n",
      "2499   ST-732   2\n",
      "2500   ST-733   1\n",
      "2501   ST-735   0\n",
      "2502   ST-736   1\n",
      "2503   ST-737   2\n",
      "2504   ST-738   2\n",
      "2505   ST-740   0\n",
      "2506   ST-741   2\n",
      "2507   ST-742   2\n",
      "2508   ST-743   2\n",
      "2509   ST-744   2\n",
      "2510   ST-745   2\n",
      "2511   ST-746   2\n",
      "2512   ST-747   2\n",
      "2513   ST-748   2\n",
      "2514   ST-749   2\n",
      "2515   ST-750   0\n",
      "2516   ST-752   2\n",
      "2517   ST-753   0\n",
      "2518   ST-754   2\n",
      "2519   ST-755   2\n",
      "2520   ST-756   2\n",
      "2521   ST-757   2\n",
      "2522   ST-758   0\n",
      "2523   ST-759   2\n",
      "2524    ST-76   1\n",
      "2525   ST-760   0\n",
      "2526   ST-761   2\n",
      "2527   ST-762   2\n",
      "2528   ST-763   2\n",
      "2529   ST-764   2\n",
      "2530   ST-765   0\n",
      "2531   ST-766   2\n",
      "2532   ST-767   2\n",
      "2533   ST-768   2\n",
      "2534   ST-769   2\n",
      "2535    ST-77   1\n",
      "2536   ST-770   2\n",
      "2537   ST-771   2\n",
      "2538   ST-772   2\n",
      "2539   ST-773   2\n",
      "2540   ST-774   2\n",
      "2541   ST-775   2\n",
      "2542   ST-776   0\n",
      "2543   ST-777   0\n",
      "2544   ST-778   2\n",
      "2545   ST-779   1\n",
      "2546    ST-78   2\n",
      "2547   ST-780   2\n",
      "2548   ST-781   2\n",
      "2549   ST-782   2\n",
      "2550   ST-783   2\n",
      "2551   ST-784   2\n",
      "2552   ST-786   2\n",
      "2553   ST-787   0\n",
      "2554   ST-788   0\n",
      "2555   ST-789   2\n",
      "2556   ST-790   2\n",
      "2557   ST-791   2\n",
      "2558   ST-792   0\n",
      "2559   ST-793   2\n",
      "2560   ST-794   0\n",
      "2561   ST-795   2\n",
      "2562   ST-796   2\n",
      "2563   ST-797   2\n",
      "2564   ST-798   2\n",
      "2565   ST-799   2\n",
      "2566     ST-8   0\n",
      "2567    ST-80   2\n",
      "2568   ST-801   2\n",
      "2569   ST-802   2\n",
      "2570   ST-803   2\n",
      "2571   ST-804   2\n",
      "2572   ST-806   2\n",
      "2573   ST-807   2\n",
      "2574   ST-808   1\n",
      "2575   ST-809   2\n",
      "2576    ST-81   2\n",
      "2577   ST-810   2\n",
      "2578   ST-811   2\n",
      "2579   ST-812   2\n",
      "2580   ST-813   2\n",
      "2581   ST-814   2\n",
      "2582   ST-815   2\n",
      "2583   ST-816   2\n",
      "2584   ST-817   2\n",
      "2585   ST-818   2\n",
      "2586   ST-819   2\n",
      "2587    ST-82   2\n",
      "2588   ST-820   2\n",
      "2589   ST-821   2\n",
      "2590   ST-822   2\n",
      "2591   ST-823   2\n",
      "2592   ST-824   1\n",
      "2593   ST-825   0\n",
      "2594   ST-826   2\n",
      "2595   ST-827   0\n",
      "2596   ST-828   1\n",
      "2597   ST-829   0\n",
      "2598    ST-83   1\n",
      "2599   ST-830   1\n",
      "2600   ST-831   1\n",
      "2601   ST-834   0\n",
      "2602   ST-835   1\n",
      "2603   ST-838   2\n",
      "2604   ST-839   2\n",
      "2605    ST-84   2\n",
      "2606   ST-840   0\n",
      "2607   ST-842   0\n",
      "2608   ST-847   1\n",
      "2609   ST-849   0\n",
      "2610    ST-85   2\n",
      "2611   ST-850   0\n",
      "2612   ST-852   0\n",
      "2613   ST-853   1\n",
      "2614   ST-854   1\n",
      "2615   ST-855   1\n",
      "2616   ST-856   1\n",
      "2617   ST-857   1\n",
      "2618   ST-859   2\n",
      "2619    ST-86   2\n",
      "2620   ST-860   2\n",
      "2621   ST-861   2\n",
      "2622   ST-862   0\n",
      "2623   ST-863   0\n",
      "2624   ST-866   1\n",
      "2625   ST-867   1\n",
      "2626   ST-868   2\n",
      "2627   ST-869   2\n",
      "2628    ST-87   2\n",
      "2629   ST-870   1\n",
      "2630   ST-871   0\n",
      "2631   ST-872   1\n",
      "2632   ST-873   0\n",
      "2633   ST-874   1\n",
      "2634   ST-875   1\n",
      "2635   ST-876   1\n",
      "2636   ST-877   0\n",
      "2637   ST-879   2\n",
      "2638    ST-88   1\n",
      "2639   ST-880   2\n",
      "2640   ST-881   2\n",
      "2641   ST-882   0\n",
      "2642   ST-883   0\n",
      "2643   ST-884   0\n",
      "2644   ST-885   2\n",
      "2645   ST-886   0\n",
      "2646   ST-887   0\n",
      "2647   ST-889   2\n",
      "2648    ST-89   2\n",
      "2649   ST-890   2\n",
      "2650   ST-891   0\n",
      "2651   ST-892   1\n",
      "2652   ST-894   2\n",
      "2653   ST-895   2\n",
      "2654   ST-896   2\n",
      "2655   ST-897   1\n",
      "2656   ST-899   2\n",
      "2657     ST-9   0\n",
      "2658    ST-90   2\n",
      "2659   ST-900   0\n",
      "2660   ST-901   0\n",
      "2661   ST-902   2\n",
      "2662   ST-903   0\n",
      "2663   ST-904   0\n",
      "2664   ST-905   0\n",
      "2665   ST-906   2\n",
      "2666   ST-907   2\n",
      "2667   ST-908   2\n",
      "2668    ST-91   2\n",
      "2669   ST-910   0\n",
      "2670   ST-912   0\n",
      "2671   ST-913   0\n",
      "2672   ST-914   1\n",
      "2673   ST-915   2\n",
      "2674   ST-916   2\n",
      "2675   ST-918   0\n",
      "2676   ST-919   0\n",
      "2677    ST-92   2\n",
      "2678   ST-920   1\n",
      "2679   ST-923   0\n",
      "2680   ST-924   0\n",
      "2681   ST-925   2\n",
      "2682   ST-926   2\n",
      "2683   ST-927   2\n",
      "2684   ST-928   2\n",
      "2685   ST-929   2\n",
      "2686    ST-93   2\n",
      "2687   ST-930   1\n",
      "2688   ST-931   0\n",
      "2689   ST-932   2\n",
      "2690   ST-933   0\n",
      "2691   ST-935   0\n",
      "2692   ST-936   0\n",
      "2693   ST-937   2\n",
      "2694   ST-938   2\n",
      "2695   ST-939   2\n",
      "2696    ST-94   0\n",
      "2697   ST-941   2\n",
      "2698   ST-942   0\n",
      "2699   ST-943   2\n",
      "2700   ST-944   0\n",
      "2701   ST-946   2\n",
      "2702   ST-947   2\n",
      "2703   ST-948   0\n",
      "2704   ST-949   2\n",
      "2705    ST-95   0\n",
      "2706   ST-950   0\n",
      "2707   ST-951   2\n",
      "2708   ST-952   0\n",
      "2709   ST-953   2\n",
      "2710   ST-954   2\n",
      "2711   ST-956   2\n",
      "2712   ST-957   2\n",
      "2713   ST-958   2\n",
      "2714   ST-959   2\n",
      "2715    ST-96   2\n",
      "2716   ST-960   2\n",
      "2717   ST-961   2\n",
      "2718   ST-962   2\n",
      "2719   ST-963   2\n",
      "2720   ST-964   0\n",
      "2721   ST-965   0\n",
      "2722   ST-966   2\n",
      "2723   ST-967   2\n",
      "2724   ST-968   2\n",
      "2725    ST-97   0\n",
      "2726   ST-970   2\n",
      "2727   ST-971   2\n",
      "2728   ST-972   0\n",
      "2729   ST-973   0\n",
      "2730   ST-974   0\n",
      "2731   ST-975   1\n",
      "2732   ST-977   2\n",
      "2733   ST-978   2\n",
      "2734   ST-979   2\n",
      "2735    ST-98   0\n",
      "2736   ST-980   0\n",
      "2737   ST-981   2\n",
      "2738   ST-983   0\n",
      "2739   ST-984   0\n",
      "2740   ST-985   2\n",
      "2741   ST-986   0\n",
      "2742   ST-987   0\n",
      "2743   ST-988   0\n",
      "2744    ST-99   0\n",
      "2745   ST-990   2\n",
      "2746   ST-991   2\n",
      "2747   ST-992   2\n",
      "2748   ST-993   1\n",
      "2749   ST-994   0\n",
      "2750   ST-995   2\n",
      "2751   ST-996   1\n",
      "2752   ST-997   1\n",
      "n_clusters = 4일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   0\n",
      "1     ST-1000   1\n",
      "2     ST-1002   1\n",
      "3     ST-1003   1\n",
      "4     ST-1004   1\n",
      "5     ST-1005   1\n",
      "6     ST-1006   1\n",
      "7     ST-1007   1\n",
      "8     ST-1008   1\n",
      "9     ST-1010   1\n",
      "10    ST-1011   3\n",
      "11    ST-1012   1\n",
      "12    ST-1013   0\n",
      "13    ST-1014   1\n",
      "14    ST-1015   1\n",
      "15    ST-1016   1\n",
      "16    ST-1017   1\n",
      "17    ST-1018   1\n",
      "18    ST-1019   1\n",
      "19     ST-102   0\n",
      "20    ST-1020   0\n",
      "21    ST-1023   3\n",
      "22    ST-1024   3\n",
      "23    ST-1025   2\n",
      "24    ST-1027   2\n",
      "25    ST-1028   1\n",
      "26    ST-1029   2\n",
      "27     ST-103   2\n",
      "28    ST-1031   1\n",
      "29    ST-1032   3\n",
      "30    ST-1033   0\n",
      "31    ST-1034   2\n",
      "32    ST-1035   0\n",
      "33    ST-1036   3\n",
      "34    ST-1038   0\n",
      "35    ST-1039   0\n",
      "36    ST-1040   2\n",
      "37    ST-1041   0\n",
      "38    ST-1042   2\n",
      "39    ST-1044   2\n",
      "40    ST-1045   0\n",
      "41    ST-1046   0\n",
      "42    ST-1047   0\n",
      "43    ST-1048   3\n",
      "44    ST-1049   3\n",
      "45     ST-105   2\n",
      "46    ST-1050   1\n",
      "47    ST-1051   1\n",
      "48    ST-1053   1\n",
      "49    ST-1054   3\n",
      "50    ST-1055   3\n",
      "51    ST-1056   1\n",
      "52    ST-1058   1\n",
      "53    ST-1059   1\n",
      "54     ST-106   2\n",
      "55    ST-1061   0\n",
      "56    ST-1062   0\n",
      "57    ST-1063   1\n",
      "58    ST-1064   0\n",
      "59    ST-1065   0\n",
      "60    ST-1067   1\n",
      "61    ST-1069   0\n",
      "62     ST-107   0\n",
      "63    ST-1070   0\n",
      "64    ST-1072   0\n",
      "65    ST-1075   0\n",
      "66    ST-1076   2\n",
      "67    ST-1077   3\n",
      "68    ST-1078   0\n",
      "69    ST-1079   0\n",
      "70     ST-108   0\n",
      "71    ST-1081   0\n",
      "72    ST-1082   3\n",
      "73    ST-1083   0\n",
      "74    ST-1084   2\n",
      "75    ST-1085   2\n",
      "76    ST-1086   3\n",
      "77    ST-1087   3\n",
      "78    ST-1088   3\n",
      "79    ST-1089   3\n",
      "80     ST-109   0\n",
      "81    ST-1092   1\n",
      "82    ST-1093   1\n",
      "83    ST-1095   3\n",
      "84    ST-1096   2\n",
      "85    ST-1097   0\n",
      "86    ST-1098   0\n",
      "87    ST-1099   0\n",
      "88      ST-11   0\n",
      "89     ST-110   0\n",
      "90    ST-1100   0\n",
      "91    ST-1101   3\n",
      "92    ST-1102   1\n",
      "93    ST-1103   3\n",
      "94    ST-1104   0\n",
      "95    ST-1105   0\n",
      "96    ST-1106   3\n",
      "97    ST-1107   3\n",
      "98    ST-1109   0\n",
      "99     ST-111   0\n",
      "100   ST-1110   3\n",
      "101   ST-1111   0\n",
      "102   ST-1114   3\n",
      "103   ST-1118   1\n",
      "104   ST-1119   1\n",
      "105    ST-112   0\n",
      "106   ST-1120   3\n",
      "107   ST-1121   0\n",
      "108   ST-1122   1\n",
      "109   ST-1123   3\n",
      "110   ST-1124   0\n",
      "111   ST-1125   2\n",
      "112   ST-1127   1\n",
      "113   ST-1128   1\n",
      "114   ST-1129   0\n",
      "115    ST-113   0\n",
      "116   ST-1130   2\n",
      "117   ST-1131   3\n",
      "118   ST-1132   3\n",
      "119   ST-1133   3\n",
      "120   ST-1135   3\n",
      "121   ST-1136   3\n",
      "122   ST-1137   1\n",
      "123    ST-114   0\n",
      "124   ST-1140   0\n",
      "125   ST-1141   2\n",
      "126   ST-1142   0\n",
      "127   ST-1143   0\n",
      "128   ST-1144   2\n",
      "129   ST-1146   2\n",
      "130   ST-1147   2\n",
      "131   ST-1148   3\n",
      "132   ST-1149   2\n",
      "133   ST-1150   0\n",
      "134   ST-1151   0\n",
      "135   ST-1152   0\n",
      "136   ST-1153   3\n",
      "137   ST-1154   3\n",
      "138   ST-1156   0\n",
      "139   ST-1158   2\n",
      "140    ST-116   2\n",
      "141   ST-1160   2\n",
      "142   ST-1161   2\n",
      "143   ST-1162   3\n",
      "144   ST-1163   2\n",
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     ]
    }
   ],
   "source": [
    "# 변수 초기화\n",
    "cluster_results = {}\n",
    "\n",
    "# n_clusters 값을 2, 3, 4로 설정하여 K-means 군집분석 및 시각화\n",
    "for n_clusters in [2, 3, 4]:\n",
    "    # K-means 군집분석\n",
    "    kmeans = KMeans(n_clusters=n_clusters, random_state=42)\n",
    "    grouped['군집'] = kmeans.fit_predict(scaled_features)\n",
    "\n",
    "    # PCA 적용\n",
    "    pca = PCA(n_components=2)\n",
    "    pca_features = pca.fit_transform(scaled_features)\n",
    "\n",
    "    # PCA 결과를 데이터프레임에 추가\n",
    "    grouped['PCA1'] = pca_features[:, 0]\n",
    "    grouped['PCA2'] = pca_features[:, 1]\n",
    "\n",
    "    # 군집 시각화\n",
    "    plt.figure(figsize=(10, 7))\n",
    "    plt.scatter(grouped['PCA1'], grouped['PCA2'], c=grouped['군집'], cmap='viridis')\n",
    "    plt.xlabel('PCA1')\n",
    "    plt.ylabel('PCA2')\n",
    "    plt.title(f'대여소 군집 결과 (PCA, n_clusters={n_clusters})')\n",
    "    plt.colorbar(label='군집')\n",
    "    plt.show()\n",
    "    \n",
    "    # 각 군집의 평균 값 계산 (대여대여소ID 제외)\n",
    "    grouped_means = grouped.drop(columns=['대여대여소ID', 'PCA1', 'PCA2']).groupby('군집').mean()\n",
    "\n",
    "    # # 컬럼 별로 가장 높은 값을 가진 군집의 셀에 파란색 배경 추가\n",
    "    # def highlight_max(s):\n",
    "    #     is_max = s == s.max()\n",
    "    #     return ['background-color: #ccffcc' if v else '' for v in is_max]\n",
    "\n",
    "    # styled_means = grouped_means.style.apply(highlight_max)\n",
    "    \n",
    "    # 컬럼 별로 가장 높은 값을 가진 군집의 셀에 연한 초록색 배경 추가\n",
    "    def highlight_max(s):\n",
    "        is_max = s == s.max()\n",
    "        return ['background-color: #ccffcc' if v else '' for v in is_max]\n",
    "\n",
    "    # 컬럼 별로 가장 낮은 값을 가진 군집의 셀에 연한 노랑색 배경 추가\n",
    "    def highlight_min(s):\n",
    "        is_min = s == s.min()\n",
    "        return ['background-color: #fffff0' if v else '' for v in is_min]\n",
    "\n",
    "    styled_means = grouped_means.style.apply(highlight_max).apply(highlight_min)\n",
    "\n",
    "    \n",
    "    # 결과 출력\n",
    "    print(f\"n_clusters = {n_clusters}일 때 각 군집의 평균 값:\")\n",
    "    display(styled_means)\n",
    "    \n",
    "    # 각 대여소가 속한 군집 저장\n",
    "    cluster_results[f'cluster_{n_clusters}'] = grouped[['대여대여소ID', '군집']].copy()\n",
    "\n",
    "# 결과 데이터프레임 확인\n",
    "df_ins_2 = cluster_results['cluster_2']\n",
    "df_ins_3 = cluster_results['cluster_3']\n",
    "df_ins_4 = cluster_results['cluster_4']\n",
    "\n",
    "print(\"n_clusters = 2일 때 각 대여소가 속한 군집:\")\n",
    "print(df_ins_2)\n",
    "\n",
    "print(\"n_clusters = 3일 때 각 대여소가 속한 군집:\")\n",
    "print(df_ins_3)\n",
    "\n",
    "print(\"n_clusters = 4일 때 각 대여소가 속한 군집:\")\n",
    "print(df_ins_4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(마스터 정보와 조인해서 저장하기)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대여소ID</th>\n",
       "      <th>군집</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "      <th>구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ST-10</td>\n",
       "      <td>0</td>\n",
       "      <td>37.55275</td>\n",
       "      <td>126.91862</td>\n",
       "      <td>마포구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ST-1000</td>\n",
       "      <td>1</td>\n",
       "      <td>37.51038</td>\n",
       "      <td>126.86680</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ST-1002</td>\n",
       "      <td>1</td>\n",
       "      <td>37.52990</td>\n",
       "      <td>126.87654</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ST-1003</td>\n",
       "      <td>1</td>\n",
       "      <td>37.53955</td>\n",
       "      <td>126.82830</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ST-1004</td>\n",
       "      <td>1</td>\n",
       "      <td>37.51410</td>\n",
       "      <td>126.83100</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     대여소ID  군집        위도         경도    구\n",
       "0    ST-10   0  37.55275  126.91862  마포구\n",
       "1  ST-1000   1  37.51038  126.86680  양천구\n",
       "2  ST-1002   1  37.52990  126.87654  양천구\n",
       "3  ST-1003   1  37.53955  126.82830  양천구\n",
       "4  ST-1004   1  37.51410  126.83100  양천구"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in_k_2 = pd.merge(df_ins_2, ll_join, how='left', left_on='대여대여소ID', right_on='대여소_ID')\n",
    "in_k_2 = in_k_2.drop(columns=['대여소_ID'])\n",
    "in_k_2.columns = ['대여소ID', '군집', '위도', '경도', '구']\n",
    "in_k_2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "in_k_2.to_csv('./(군집_내국인_k=2_청12복) 서울시 따릉이 대여소 별 군집결과_마스터 조인.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대여소ID</th>\n",
       "      <th>군집</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "      <th>구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ST-10</td>\n",
       "      <td>0</td>\n",
       "      <td>37.55275</td>\n",
       "      <td>126.91862</td>\n",
       "      <td>마포구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ST-1000</td>\n",
       "      <td>1</td>\n",
       "      <td>37.51038</td>\n",
       "      <td>126.86680</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ST-1002</td>\n",
       "      <td>1</td>\n",
       "      <td>37.52990</td>\n",
       "      <td>126.87654</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ST-1003</td>\n",
       "      <td>1</td>\n",
       "      <td>37.53955</td>\n",
       "      <td>126.82830</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ST-1004</td>\n",
       "      <td>1</td>\n",
       "      <td>37.51410</td>\n",
       "      <td>126.83100</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     대여소ID  군집        위도         경도    구\n",
       "0    ST-10   0  37.55275  126.91862  마포구\n",
       "1  ST-1000   1  37.51038  126.86680  양천구\n",
       "2  ST-1002   1  37.52990  126.87654  양천구\n",
       "3  ST-1003   1  37.53955  126.82830  양천구\n",
       "4  ST-1004   1  37.51410  126.83100  양천구"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in_k_3 = pd.merge(df_ins_3, ll_join, how='left', left_on='대여대여소ID', right_on='대여소_ID')\n",
    "in_k_3 = in_k_3.drop(columns=['대여소_ID'])\n",
    "in_k_3.columns = ['대여소ID', '군집', '위도', '경도', '구']\n",
    "in_k_3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [],
   "source": [
    "in_k_3.to_csv('./(군집_내국인_k=3_청12복) 서울시 따릉이 대여소 별 군집결과_마스터 조인.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대여소ID</th>\n",
       "      <th>군집</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "      <th>구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ST-10</td>\n",
       "      <td>0</td>\n",
       "      <td>37.55275</td>\n",
       "      <td>126.91862</td>\n",
       "      <td>마포구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ST-1000</td>\n",
       "      <td>1</td>\n",
       "      <td>37.51038</td>\n",
       "      <td>126.86680</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ST-1002</td>\n",
       "      <td>1</td>\n",
       "      <td>37.52990</td>\n",
       "      <td>126.87654</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ST-1003</td>\n",
       "      <td>1</td>\n",
       "      <td>37.53955</td>\n",
       "      <td>126.82830</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ST-1004</td>\n",
       "      <td>1</td>\n",
       "      <td>37.51410</td>\n",
       "      <td>126.83100</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     대여소ID  군집        위도         경도    구\n",
       "0    ST-10   0  37.55275  126.91862  마포구\n",
       "1  ST-1000   1  37.51038  126.86680  양천구\n",
       "2  ST-1002   1  37.52990  126.87654  양천구\n",
       "3  ST-1003   1  37.53955  126.82830  양천구\n",
       "4  ST-1004   1  37.51410  126.83100  양천구"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in_k_4 = pd.merge(df_ins_4, ll_join, how='left', left_on='대여대여소ID', right_on='대여소_ID')\n",
    "in_k_4 = in_k_4.drop(columns=['대여소_ID'])\n",
    "in_k_4.columns = ['대여소ID', '군집', '위도', '경도', '구']\n",
    "in_k_4.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "in_k_4.to_csv('./(군집_내국인_k=4_청12복) 서울시 따릉이 대여소 별 군집결과_마스터 조인.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 비율..인데 좀 덜 세분화한..버전으로다가..  \n",
    "주중/주말 연령대 컬럼 세분화하지 말고 그냥 연령대 별 청소년, 청년, 장년, 노인만 나눠보기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      대여대여소ID  총대여횟수    남성고객비율     평균이용시간       평균이용거리    주말대여비율    새벽대여비율  \\\n",
      "0       ST-10   2764  0.641823  30.027135  2896.118784  0.308249  0.099493   \n",
      "1     ST-1000   3074  0.625895  19.268705  2427.495573  0.265777  0.036760   \n",
      "2     ST-1002   5895  0.658863  20.319932  2289.621218  0.298049  0.013740   \n",
      "3     ST-1003   1914  0.641066  17.774817  2121.170564  0.269592  0.060084   \n",
      "4     ST-1004   1543  0.736876  15.806870  1868.960045  0.288399  0.038885   \n",
      "...       ...    ...       ...        ...          ...       ...       ...   \n",
      "2748   ST-993   2288  0.677885  18.303759  1884.028086  0.255682  0.042832   \n",
      "2749   ST-994   4450  0.640225  20.783820  2037.581463  0.224045  0.014607   \n",
      "2750   ST-995    467  0.698073  18.715203  2259.101649  0.241970  0.008565   \n",
      "2751   ST-996   1075  0.709767  20.463256  1966.129544  0.279070  0.097674   \n",
      "2752   ST-997   6979  0.640923  18.015618  1877.363578  0.252472  0.028084   \n",
      "\n",
      "      출근시간대여비율    오전대여비율    점심대여비율    오후대여비율  퇴근시간대여비율    야간대여비율     청소년비율  \\\n",
      "0     0.045224  0.061867  0.099855  0.183792  0.184877  0.295224  0.027135   \n",
      "1     0.307417  0.080677  0.093689  0.143136  0.155172  0.145413  0.256018   \n",
      "2     0.079389  0.058015  0.087532  0.188126  0.233927  0.318405  0.205259   \n",
      "3     0.142111  0.063218  0.096134  0.153083  0.166667  0.286311  0.129572   \n",
      "4     0.263772  0.059624  0.088788  0.154893  0.149060  0.207388  0.467920   \n",
      "...        ...       ...       ...       ...       ...       ...       ...   \n",
      "2748  0.194493  0.077797  0.092220  0.165210  0.152535  0.208479  0.144668   \n",
      "2749  0.076854  0.061124  0.087865  0.161348  0.276854  0.293708  0.082921   \n",
      "2750  0.233405  0.085653  0.100642  0.171306  0.175589  0.211991  0.102784   \n",
      "2751  0.042791  0.049302  0.083721  0.191628  0.236279  0.247442  0.120000   \n",
      "2752  0.260496  0.077948  0.082533  0.186130  0.156183  0.178106  0.275971   \n",
      "\n",
      "          청년비율      장년비율      노인비율  \n",
      "0     0.780753  0.176194  0.015919  \n",
      "1     0.357840  0.345153  0.040664  \n",
      "2     0.423070  0.335369  0.034266  \n",
      "3     0.517764  0.311390  0.040752  \n",
      "4     0.274141  0.232016  0.025924  \n",
      "...        ...       ...       ...  \n",
      "2748  0.501311  0.308566  0.045455  \n",
      "2749  0.523146  0.366067  0.027865  \n",
      "2750  0.449679  0.370450  0.077088  \n",
      "2751  0.548837  0.266047  0.065116  \n",
      "2752  0.344319  0.339160  0.037398  \n",
      "\n",
      "[2753 rows x 17 columns]\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "df1_ins['대여일자'] = pd.to_datetime(df1_ins['대여일자'])\n",
    "\n",
    "# 주중/주말 구분\n",
    "df1_ins['주말여부'] = df1_ins['대여요일'].isin(['Saturday', 'Sunday'])\n",
    "\n",
    "# 시간대 구분\n",
    "df1_ins['새벽시간'] = (df1_ins['대여시간'] >= 0) & (df1_ins['대여시간'] < 6)\n",
    "df1_ins['출근시간'] = (df1_ins['대여시간'] >= 7) & (df1_ins['대여시간'] < 10)\n",
    "df1_ins['오전시간'] = (df1_ins['대여시간'] >= 10) & (df1_ins['대여시간'] < 12)\n",
    "df1_ins['점심시간'] = (df1_ins['대여시간'] >= 12) & (df1_ins['대여시간'] < 14)\n",
    "df1_ins['오후시간'] = (df1_ins['대여시간'] >= 14) & (df1_ins['대여시간'] < 17)\n",
    "df1_ins['퇴근시간'] = (df1_ins['대여시간'] >= 17) & (df1_ins['대여시간'] < 19)\n",
    "df1_ins['야간시간'] = (df1_ins['대여시간'] >= 19) & (df1_ins['대여시간'] < 24)\n",
    "\n",
    "# 연령대 구분\n",
    "df1_ins['청소년'] = (df1_ins['연령대'] == 10)\n",
    "df1_ins['청년'] = (df1_ins['연령대'] == 20) | (df1_ins['연령대'] == 30)\n",
    "df1_ins['장년'] = (df1_ins['연령대'] == 40) | (df1_ins['연령대'] == 50)\n",
    "df1_ins['노인'] = (df1_ins['연령대'] == 60) | (df1_ins['연령대'] == 70)\n",
    "\n",
    "# 대여대여소ID 기준 그룹화하여 통계 피처 생성\n",
    "total_counts = df1_ins.groupby('대여대여소ID')['대여일자'].count()\n",
    "\n",
    "grouped = df1_ins.groupby('대여대여소ID').agg({\n",
    "    '대여일자': 'count',  # 총 대여 횟수\n",
    "    '성별_M': 'mean',  # 남성 방문고객 비율\n",
    "    '이용시간(분)': 'mean',  # 평균 이용시간\n",
    "    '이용거리(M)': 'mean',  # 평균 이용거리\n",
    "    '주말여부': lambda x: x.sum() / x.count(),  # 주말 대여 비율\n",
    "    '새벽시간': lambda x: x.sum() / x.count(),  # 새벽 대여 비율\n",
    "    '출근시간': lambda x: x.sum() / x.count(),  # 출근 시간대 대여 비율\n",
    "    '오전시간': lambda x: x.sum() / x.count(),  # 오전 대여 비율\n",
    "    '점심시간': lambda x: x.sum() / x.count(),  # 점심시간 대여 비율\n",
    "    '오후시간': lambda x: x.sum() / x.count(),  # 오후시간 대여 비율\n",
    "    '퇴근시간': lambda x: x.sum() / x.count(),  # 퇴근 시간대 대여 비율\n",
    "    '야간시간': lambda x: x.sum() / x.count(),   # 야간 대여 비율\n",
    "    '청소년' : lambda x: x.sum() / x.count(),   # 청소년 비율\n",
    "    '청년' : lambda x: x.sum() / x.count(),     # 청년 비율\n",
    "    '장년' : lambda x: x.sum() / x.count(),     # 장년 비율\n",
    "    '노인' : lambda x: x.sum() / x.count()      # 노인 비율\n",
    "}).reset_index()\n",
    "\n",
    "# 컬럼 이름 변경\n",
    "grouped.columns = [\n",
    "    '대여대여소ID', '총대여횟수', '남성고객비율', '평균이용시간', '평균이용거리',\n",
    "    '주말대여비율', '새벽대여비율', '출근시간대여비율', '오전대여비율', '점심대여비율', '오후대여비율',\n",
    "    '퇴근시간대여비율', '야간대여비율', '청소년비율', '청년비율', '장년비율', '노인비율'\n",
    "]\n",
    "\n",
    "print(grouped)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "grouped = grouped.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "\n",
    "# # 군집분석에 사용할 피처 선택\n",
    "features = grouped.drop(columns=['대여대여소ID'])\n",
    "\n",
    "sum_of_squared_distances = []\n",
    "K = range(1, 15)\n",
    "for k in K:\n",
    "    km = KMeans(n_clusters = k)\n",
    "    km = km.fit(features)\n",
    "    sum_of_squared_distances.append(km.inertia_)\n",
    "    \n",
    "# 시각화\n",
    "\n",
    "plt.plot(K, sum_of_squared_distances, 'bx-')\n",
    "plt.xlabel('k')\n",
    "plt.ylabel('Sum_of_squared_distances')\n",
    "plt.title('Elbow Method For Optimal k')\n",
    "plt.axvline(2,c= 'r',alpha =0.4)\n",
    "plt.axvline(3,c= 'r',alpha =0.4)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "k : 2 score : 0.5859813545786464\n",
      "k : 3 score : 0.4626715228955522\n",
      "k : 4 score : 0.4262747450091651\n",
      "k : 5 score : 0.43963908555833203\n",
      "k : 6 score : 0.42642627285678675\n",
      "k : 7 score : 0.38862466454525346\n",
      "k : 8 score : 0.3786767302673371\n",
      "k : 9 score : 0.3617073796403045\n",
      "k : 10 score : 0.36252520196377197\n",
      "k : 11 score : 0.3736200781240138\n",
      "k : 12 score : 0.3613642190710511\n",
      "k : 13 score : 0.3617205101689882\n",
      "best n : 2 best score : 0.5859813545786464\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import silhouette_score\n",
    "k_range = range(2,14)\n",
    "\n",
    "best_n = -1\n",
    "best_silhouette_score = -1\n",
    "\n",
    "for k in k_range:\n",
    "\n",
    "  kmeans = KMeans(n_clusters=k, random_state=200)\n",
    "  kmeans.fit(features)\n",
    "  clusters = kmeans.predict(features)\n",
    "\n",
    "  score = silhouette_score(features, clusters)\n",
    "  print('k :',  k, 'score :', score)\n",
    "\n",
    "  if score > best_silhouette_score:\n",
    "    best_n = k\n",
    "    best_silhouette_score = score\n",
    "\n",
    "print('best n :', best_n, 'best score :', best_silhouette_score )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      대여대여소ID  총대여횟수    남성고객비율     평균이용시간       평균이용거리    주말대여비율    새벽대여비율  \\\n",
      "0       ST-10   2764  0.641823  30.027135  2896.118784  0.308249  0.099493   \n",
      "1     ST-1000   3074  0.625895  19.268705  2427.495573  0.265777  0.036760   \n",
      "2     ST-1002   5895  0.658863  20.319932  2289.621218  0.298049  0.013740   \n",
      "3     ST-1003   1914  0.641066  17.774817  2121.170564  0.269592  0.060084   \n",
      "4     ST-1004   1543  0.736876  15.806870  1868.960045  0.288399  0.038885   \n",
      "...       ...    ...       ...        ...          ...       ...       ...   \n",
      "2748   ST-993   2288  0.677885  18.303759  1884.028086  0.255682  0.042832   \n",
      "2749   ST-994   4450  0.640225  20.783820  2037.581463  0.224045  0.014607   \n",
      "2750   ST-995    467  0.698073  18.715203  2259.101649  0.241970  0.008565   \n",
      "2751   ST-996   1075  0.709767  20.463256  1966.129544  0.279070  0.097674   \n",
      "2752   ST-997   6979  0.640923  18.015618  1877.363578  0.252472  0.028084   \n",
      "\n",
      "      출근시간대여비율    오전대여비율    점심대여비율    오후대여비율  퇴근시간대여비율    야간대여비율     청소년비율  \\\n",
      "0     0.045224  0.061867  0.099855  0.183792  0.184877  0.295224  0.027135   \n",
      "1     0.307417  0.080677  0.093689  0.143136  0.155172  0.145413  0.256018   \n",
      "2     0.079389  0.058015  0.087532  0.188126  0.233927  0.318405  0.205259   \n",
      "3     0.142111  0.063218  0.096134  0.153083  0.166667  0.286311  0.129572   \n",
      "4     0.263772  0.059624  0.088788  0.154893  0.149060  0.207388  0.467920   \n",
      "...        ...       ...       ...       ...       ...       ...       ...   \n",
      "2748  0.194493  0.077797  0.092220  0.165210  0.152535  0.208479  0.144668   \n",
      "2749  0.076854  0.061124  0.087865  0.161348  0.276854  0.293708  0.082921   \n",
      "2750  0.233405  0.085653  0.100642  0.171306  0.175589  0.211991  0.102784   \n",
      "2751  0.042791  0.049302  0.083721  0.191628  0.236279  0.247442  0.120000   \n",
      "2752  0.260496  0.077948  0.082533  0.186130  0.156183  0.178106  0.275971   \n",
      "\n",
      "          청년비율      장년비율      노인비율  군집      PCA1      PCA2  \n",
      "0     0.780753  0.176194  0.015919   0  3.274340  0.714850  \n",
      "1     0.357840  0.345153  0.040664   1 -2.146758 -0.170314  \n",
      "2     0.423070  0.335369  0.034266   0  0.660402  0.181680  \n",
      "3     0.517764  0.311390  0.040752   0  0.328941 -0.271689  \n",
      "4     0.274141  0.232016  0.025924   1 -1.943081 -0.699624  \n",
      "...        ...       ...       ...  ..       ...       ...  \n",
      "2748  0.501311  0.308566  0.045455   1 -0.979848 -0.605732  \n",
      "2749  0.523146  0.366067  0.027865   0  0.436059 -0.517604  \n",
      "2750  0.449679  0.370450  0.077088   1 -2.190447  0.224377  \n",
      "2751  0.548837  0.266047  0.065116   0  0.588077  0.420539  \n",
      "2752  0.344319  0.339160  0.037398   1 -1.702630 -0.910421  \n",
      "\n",
      "[2753 rows x 20 columns]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.decomposition import PCA\n",
    "\n",
    "# 군집분석에 사용할 피처 선택\n",
    "features = grouped.drop(columns=['대여대여소ID'])\n",
    "\n",
    "# 표준화\n",
    "scaler = StandardScaler()\n",
    "scaled_features = scaler.fit_transform(features)\n",
    "\n",
    "# K-means 군집분석\n",
    "kmeans = KMeans(n_clusters=4, random_state=42)\n",
    "grouped['군집'] = kmeans.fit_predict(scaled_features)\n",
    "\n",
    "# PCA 적용\n",
    "pca = PCA(n_components=2)\n",
    "pca_features = pca.fit_transform(scaled_features)\n",
    "\n",
    "# PCA 결과를 데이터프레임에 추가\n",
    "grouped['PCA1'] = pca_features[:, 0]\n",
    "grouped['PCA2'] = pca_features[:, 1]\n",
    "\n",
    "# 결과 출력\n",
    "print(grouped)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 2일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
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       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_bfd95_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_bfd95_level0_col1\" class=\"col_heading level0 col1\" >남성고객비율</th>\n",
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       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
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       "      <td id=\"T_bfd95_row1_col8\" class=\"data row1 col8\" >0.088676</td>\n",
       "      <td id=\"T_bfd95_row1_col9\" class=\"data row1 col9\" >0.170886</td>\n",
       "      <td id=\"T_bfd95_row1_col10\" class=\"data row1 col10\" >0.170763</td>\n",
       "      <td id=\"T_bfd95_row1_col11\" class=\"data row1 col11\" >0.201611</td>\n",
       "      <td id=\"T_bfd95_row1_col12\" class=\"data row1 col12\" >0.083792</td>\n",
       "      <td id=\"T_bfd95_row1_col13\" class=\"data row1 col13\" >0.489808</td>\n",
       "      <td id=\"T_bfd95_row1_col14\" class=\"data row1 col14\" >0.356834</td>\n",
       "      <td id=\"T_bfd95_row1_col15\" class=\"data row1 col15\" >0.068649</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x24ee0293790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 3일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "#T_f2180_row0_col0, #T_f2180_row0_col5, #T_f2180_row0_col11, #T_f2180_row0_col13, #T_f2180_row1_col1, #T_f2180_row1_col6, #T_f2180_row1_col7, #T_f2180_row1_col8, #T_f2180_row1_col12, #T_f2180_row1_col14, #T_f2180_row2_col2, #T_f2180_row2_col3, #T_f2180_row2_col4, #T_f2180_row2_col9, #T_f2180_row2_col10, #T_f2180_row2_col15 {\n",
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       "#T_f2180_row0_col2, #T_f2180_row0_col3, #T_f2180_row0_col8, #T_f2180_row0_col9, #T_f2180_row0_col14, #T_f2180_row0_col15, #T_f2180_row1_col0, #T_f2180_row1_col4, #T_f2180_row1_col5, #T_f2180_row1_col10, #T_f2180_row1_col11, #T_f2180_row1_col13, #T_f2180_row2_col1, #T_f2180_row2_col6, #T_f2180_row2_col7, #T_f2180_row2_col12 {\n",
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       "</style>\n",
       "<table id=\"T_f2180\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_f2180_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_f2180_level0_col1\" class=\"col_heading level0 col1\" >남성고객비율</th>\n",
       "      <th id=\"T_f2180_level0_col2\" class=\"col_heading level0 col2\" >평균이용시간</th>\n",
       "      <th id=\"T_f2180_level0_col3\" class=\"col_heading level0 col3\" >평균이용거리</th>\n",
       "      <th id=\"T_f2180_level0_col4\" class=\"col_heading level0 col4\" >주말대여비율</th>\n",
       "      <th id=\"T_f2180_level0_col5\" class=\"col_heading level0 col5\" >새벽대여비율</th>\n",
       "      <th id=\"T_f2180_level0_col6\" class=\"col_heading level0 col6\" >출근시간대여비율</th>\n",
       "      <th id=\"T_f2180_level0_col7\" class=\"col_heading level0 col7\" >오전대여비율</th>\n",
       "      <th id=\"T_f2180_level0_col8\" class=\"col_heading level0 col8\" >점심대여비율</th>\n",
       "      <th id=\"T_f2180_level0_col9\" class=\"col_heading level0 col9\" >오후대여비율</th>\n",
       "      <th id=\"T_f2180_level0_col10\" class=\"col_heading level0 col10\" >퇴근시간대여비율</th>\n",
       "      <th id=\"T_f2180_level0_col11\" class=\"col_heading level0 col11\" >야간대여비율</th>\n",
       "      <th id=\"T_f2180_level0_col12\" class=\"col_heading level0 col12\" >청소년비율</th>\n",
       "      <th id=\"T_f2180_level0_col13\" class=\"col_heading level0 col13\" >청년비율</th>\n",
       "      <th id=\"T_f2180_level0_col14\" class=\"col_heading level0 col14\" >장년비율</th>\n",
       "      <th id=\"T_f2180_level0_col15\" class=\"col_heading level0 col15\" >노인비율</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "      <th class=\"blank col8\" >&nbsp;</th>\n",
       "      <th class=\"blank col9\" >&nbsp;</th>\n",
       "      <th class=\"blank col10\" >&nbsp;</th>\n",
       "      <th class=\"blank col11\" >&nbsp;</th>\n",
       "      <th class=\"blank col12\" >&nbsp;</th>\n",
       "      <th class=\"blank col13\" >&nbsp;</th>\n",
       "      <th class=\"blank col14\" >&nbsp;</th>\n",
       "      <th class=\"blank col15\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_f2180_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_f2180_row0_col0\" class=\"data row0 col0\" >2978.683698</td>\n",
       "      <td id=\"T_f2180_row0_col1\" class=\"data row0 col1\" >0.630206</td>\n",
       "      <td id=\"T_f2180_row0_col2\" class=\"data row0 col2\" >19.628613</td>\n",
       "      <td id=\"T_f2180_row0_col3\" class=\"data row0 col3\" >2173.422678</td>\n",
       "      <td id=\"T_f2180_row0_col4\" class=\"data row0 col4\" >0.244127</td>\n",
       "      <td id=\"T_f2180_row0_col5\" class=\"data row0 col5\" >0.054716</td>\n",
       "      <td id=\"T_f2180_row0_col6\" class=\"data row0 col6\" >0.149427</td>\n",
       "      <td id=\"T_f2180_row0_col7\" class=\"data row0 col7\" >0.069318</td>\n",
       "      <td id=\"T_f2180_row0_col8\" class=\"data row0 col8\" >0.084702</td>\n",
       "      <td id=\"T_f2180_row0_col9\" class=\"data row0 col9\" >0.152825</td>\n",
       "      <td id=\"T_f2180_row0_col10\" class=\"data row0 col10\" >0.172800</td>\n",
       "      <td id=\"T_f2180_row0_col11\" class=\"data row0 col11\" >0.270423</td>\n",
       "      <td id=\"T_f2180_row0_col12\" class=\"data row0 col12\" >0.059185</td>\n",
       "      <td id=\"T_f2180_row0_col13\" class=\"data row0 col13\" >0.645490</td>\n",
       "      <td id=\"T_f2180_row0_col14\" class=\"data row0 col14\" >0.253374</td>\n",
       "      <td id=\"T_f2180_row0_col15\" class=\"data row0 col15\" >0.041475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f2180_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_f2180_row1_col0\" class=\"data row1 col0\" >1562.726876</td>\n",
       "      <td id=\"T_f2180_row1_col1\" class=\"data row1 col1\" >0.671629</td>\n",
       "      <td id=\"T_f2180_row1_col2\" class=\"data row1 col2\" >19.943785</td>\n",
       "      <td id=\"T_f2180_row1_col3\" class=\"data row1 col3\" >2288.325208</td>\n",
       "      <td id=\"T_f2180_row1_col4\" class=\"data row1 col4\" >0.229613</td>\n",
       "      <td id=\"T_f2180_row1_col5\" class=\"data row1 col5\" >0.048129</td>\n",
       "      <td id=\"T_f2180_row1_col6\" class=\"data row1 col6\" >0.198622</td>\n",
       "      <td id=\"T_f2180_row1_col7\" class=\"data row1 col7\" >0.083473</td>\n",
       "      <td id=\"T_f2180_row1_col8\" class=\"data row1 col8\" >0.087747</td>\n",
       "      <td id=\"T_f2180_row1_col9\" class=\"data row1 col9\" >0.167217</td>\n",
       "      <td id=\"T_f2180_row1_col10\" class=\"data row1 col10\" >0.167568</td>\n",
       "      <td id=\"T_f2180_row1_col11\" class=\"data row1 col11\" >0.199470</td>\n",
       "      <td id=\"T_f2180_row1_col12\" class=\"data row1 col12\" >0.089539</td>\n",
       "      <td id=\"T_f2180_row1_col13\" class=\"data row1 col13\" >0.487512</td>\n",
       "      <td id=\"T_f2180_row1_col14\" class=\"data row1 col14\" >0.355638</td>\n",
       "      <td id=\"T_f2180_row1_col15\" class=\"data row1 col15\" >0.066382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_f2180_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "      <td id=\"T_f2180_row2_col0\" class=\"data row2 col0\" >1876.593583</td>\n",
       "      <td id=\"T_f2180_row2_col1\" class=\"data row2 col1\" >0.618279</td>\n",
       "      <td id=\"T_f2180_row2_col2\" class=\"data row2 col2\" >30.814294</td>\n",
       "      <td id=\"T_f2180_row2_col3\" class=\"data row2 col3\" >3882.758013</td>\n",
       "      <td id=\"T_f2180_row2_col4\" class=\"data row2 col4\" >0.305884</td>\n",
       "      <td id=\"T_f2180_row2_col5\" class=\"data row2 col5\" >0.050838</td>\n",
       "      <td id=\"T_f2180_row2_col6\" class=\"data row2 col6\" >0.124945</td>\n",
       "      <td id=\"T_f2180_row2_col7\" class=\"data row2 col7\" >0.067267</td>\n",
       "      <td id=\"T_f2180_row2_col8\" class=\"data row2 col8\" >0.085237</td>\n",
       "      <td id=\"T_f2180_row2_col9\" class=\"data row2 col9\" >0.182400</td>\n",
       "      <td id=\"T_f2180_row2_col10\" class=\"data row2 col10\" >0.184218</td>\n",
       "      <td id=\"T_f2180_row2_col11\" class=\"data row2 col11\" >0.265852</td>\n",
       "      <td id=\"T_f2180_row2_col12\" class=\"data row2 col12\" >0.052239</td>\n",
       "      <td id=\"T_f2180_row2_col13\" class=\"data row2 col13\" >0.542349</td>\n",
       "      <td id=\"T_f2180_row2_col14\" class=\"data row2 col14\" >0.337071</td>\n",
       "      <td id=\"T_f2180_row2_col15\" class=\"data row2 col15\" >0.067441</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x24ee64e2690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 4일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_76572_row0_col0, #T_76572_row0_col11, #T_76572_row0_col13, #T_76572_row1_col5, #T_76572_row1_col6, #T_76572_row1_col12, #T_76572_row2_col2, #T_76572_row2_col3, #T_76572_row2_col4, #T_76572_row2_col15, #T_76572_row3_col1, #T_76572_row3_col7, #T_76572_row3_col8, #T_76572_row3_col9, #T_76572_row3_col10, #T_76572_row3_col14 {\n",
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       "}\n",
       "#T_76572_row0_col3, #T_76572_row0_col9, #T_76572_row0_col14, #T_76572_row0_col15, #T_76572_row1_col0, #T_76572_row1_col2, #T_76572_row1_col8, #T_76572_row1_col10, #T_76572_row1_col13, #T_76572_row2_col1, #T_76572_row2_col6, #T_76572_row2_col7, #T_76572_row3_col4, #T_76572_row3_col5, #T_76572_row3_col11, #T_76572_row3_col12 {\n",
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       "<table id=\"T_76572\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_76572_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_76572_level0_col1\" class=\"col_heading level0 col1\" >남성고객비율</th>\n",
       "      <th id=\"T_76572_level0_col2\" class=\"col_heading level0 col2\" >평균이용시간</th>\n",
       "      <th id=\"T_76572_level0_col3\" class=\"col_heading level0 col3\" >평균이용거리</th>\n",
       "      <th id=\"T_76572_level0_col4\" class=\"col_heading level0 col4\" >주말대여비율</th>\n",
       "      <th id=\"T_76572_level0_col5\" class=\"col_heading level0 col5\" >새벽대여비율</th>\n",
       "      <th id=\"T_76572_level0_col6\" class=\"col_heading level0 col6\" >출근시간대여비율</th>\n",
       "      <th id=\"T_76572_level0_col7\" class=\"col_heading level0 col7\" >오전대여비율</th>\n",
       "      <th id=\"T_76572_level0_col8\" class=\"col_heading level0 col8\" >점심대여비율</th>\n",
       "      <th id=\"T_76572_level0_col9\" class=\"col_heading level0 col9\" >오후대여비율</th>\n",
       "      <th id=\"T_76572_level0_col10\" class=\"col_heading level0 col10\" >퇴근시간대여비율</th>\n",
       "      <th id=\"T_76572_level0_col11\" class=\"col_heading level0 col11\" >야간대여비율</th>\n",
       "      <th id=\"T_76572_level0_col12\" class=\"col_heading level0 col12\" >청소년비율</th>\n",
       "      <th id=\"T_76572_level0_col13\" class=\"col_heading level0 col13\" >청년비율</th>\n",
       "      <th id=\"T_76572_level0_col14\" class=\"col_heading level0 col14\" >장년비율</th>\n",
       "      <th id=\"T_76572_level0_col15\" class=\"col_heading level0 col15\" >노인비율</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "      <th class=\"blank col8\" >&nbsp;</th>\n",
       "      <th class=\"blank col9\" >&nbsp;</th>\n",
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       "      <th class=\"blank col11\" >&nbsp;</th>\n",
       "      <th class=\"blank col12\" >&nbsp;</th>\n",
       "      <th class=\"blank col13\" >&nbsp;</th>\n",
       "      <th class=\"blank col14\" >&nbsp;</th>\n",
       "      <th class=\"blank col15\" >&nbsp;</th>\n",
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       "      <th id=\"T_76572_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_76572_row0_col0\" class=\"data row0 col0\" >3152.038690</td>\n",
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       "      <td id=\"T_76572_row0_col2\" class=\"data row0 col2\" >19.749949</td>\n",
       "      <td id=\"T_76572_row0_col3\" class=\"data row0 col3\" >2179.826534</td>\n",
       "      <td id=\"T_76572_row0_col4\" class=\"data row0 col4\" >0.250350</td>\n",
       "      <td id=\"T_76572_row0_col5\" class=\"data row0 col5\" >0.055096</td>\n",
       "      <td id=\"T_76572_row0_col6\" class=\"data row0 col6\" >0.150279</td>\n",
       "      <td id=\"T_76572_row0_col7\" class=\"data row0 col7\" >0.068604</td>\n",
       "      <td id=\"T_76572_row0_col8\" class=\"data row0 col8\" >0.084357</td>\n",
       "      <td id=\"T_76572_row0_col9\" class=\"data row0 col9\" >0.150319</td>\n",
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       "      <td id=\"T_76572_row0_col11\" class=\"data row0 col11\" >0.278628</td>\n",
       "      <td id=\"T_76572_row0_col12\" class=\"data row0 col12\" >0.054549</td>\n",
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       "      <th id=\"T_76572_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_76572_row1_col0\" class=\"data row1 col0\" >1660.481855</td>\n",
       "      <td id=\"T_76572_row1_col1\" class=\"data row1 col1\" >0.663343</td>\n",
       "      <td id=\"T_76572_row1_col2\" class=\"data row1 col2\" >19.447675</td>\n",
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       "      <td id=\"T_76572_row1_col4\" class=\"data row1 col4\" >0.248459</td>\n",
       "      <td id=\"T_76572_row1_col5\" class=\"data row1 col5\" >0.058949</td>\n",
       "      <td id=\"T_76572_row1_col6\" class=\"data row1 col6\" >0.212154</td>\n",
       "      <td id=\"T_76572_row1_col7\" class=\"data row1 col7\" >0.075312</td>\n",
       "      <td id=\"T_76572_row1_col8\" class=\"data row1 col8\" >0.080046</td>\n",
       "      <td id=\"T_76572_row1_col9\" class=\"data row1 col9\" >0.158145</td>\n",
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       "      <td id=\"T_76572_row1_col12\" class=\"data row1 col12\" >0.112146</td>\n",
       "      <td id=\"T_76572_row1_col13\" class=\"data row1 col13\" >0.481233</td>\n",
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       "      <td id=\"T_76572_row1_col15\" class=\"data row1 col15\" >0.066682</td>\n",
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       "    <tr>\n",
       "      <th id=\"T_76572_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
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       "      <td id=\"T_76572_row2_col2\" class=\"data row2 col2\" >31.501212</td>\n",
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       "      <td id=\"T_76572_row2_col4\" class=\"data row2 col4\" >0.314889</td>\n",
       "      <td id=\"T_76572_row2_col5\" class=\"data row2 col5\" >0.050260</td>\n",
       "      <td id=\"T_76572_row2_col6\" class=\"data row2 col6\" >0.126211</td>\n",
       "      <td id=\"T_76572_row2_col7\" class=\"data row2 col7\" >0.066851</td>\n",
       "      <td id=\"T_76572_row2_col8\" class=\"data row2 col8\" >0.085326</td>\n",
       "      <td id=\"T_76572_row2_col9\" class=\"data row2 col9\" >0.183544</td>\n",
       "      <td id=\"T_76572_row2_col10\" class=\"data row2 col10\" >0.178754</td>\n",
       "      <td id=\"T_76572_row2_col11\" class=\"data row2 col11\" >0.269320</td>\n",
       "      <td id=\"T_76572_row2_col12\" class=\"data row2 col12\" >0.051851</td>\n",
       "      <td id=\"T_76572_row2_col13\" class=\"data row2 col13\" >0.538255</td>\n",
       "      <td id=\"T_76572_row2_col14\" class=\"data row2 col14\" >0.341463</td>\n",
       "      <td id=\"T_76572_row2_col15\" class=\"data row2 col15\" >0.067464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_76572_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "      <td id=\"T_76572_row3_col0\" class=\"data row3 col0\" >1730.002309</td>\n",
       "      <td id=\"T_76572_row3_col1\" class=\"data row3 col1\" >0.679261</td>\n",
       "      <td id=\"T_76572_row3_col2\" class=\"data row3 col2\" >21.482156</td>\n",
       "      <td id=\"T_76572_row3_col3\" class=\"data row3 col3\" >2362.686619</td>\n",
       "      <td id=\"T_76572_row3_col4\" class=\"data row3 col4\" >0.182347</td>\n",
       "      <td id=\"T_76572_row3_col5\" class=\"data row3 col5\" >0.026644</td>\n",
       "      <td id=\"T_76572_row3_col6\" class=\"data row3 col6\" >0.129948</td>\n",
       "      <td id=\"T_76572_row3_col7\" class=\"data row3 col7\" >0.094762</td>\n",
       "      <td id=\"T_76572_row3_col8\" class=\"data row3 col8\" >0.104231</td>\n",
       "      <td id=\"T_76572_row3_col9\" class=\"data row3 col9\" >0.187403</td>\n",
       "      <td id=\"T_76572_row3_col10\" class=\"data row3 col10\" >0.253010</td>\n",
       "      <td id=\"T_76572_row3_col11\" class=\"data row3 col11\" >0.179104</td>\n",
       "      <td id=\"T_76572_row3_col12\" class=\"data row3 col12\" >0.028400</td>\n",
       "      <td id=\"T_76572_row3_col13\" class=\"data row3 col13\" >0.571204</td>\n",
       "      <td id=\"T_76572_row3_col14\" class=\"data row3 col14\" >0.345952</td>\n",
       "      <td id=\"T_76572_row3_col15\" class=\"data row3 col15\" >0.053777</td>\n",
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       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x24eba8e4d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 2일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   0\n",
      "1     ST-1000   1\n",
      "2     ST-1002   0\n",
      "3     ST-1003   0\n",
      "4     ST-1004   1\n",
      "...       ...  ..\n",
      "2748   ST-993   1\n",
      "2749   ST-994   0\n",
      "2750   ST-995   1\n",
      "2751   ST-996   0\n",
      "2752   ST-997   1\n",
      "\n",
      "[2753 rows x 2 columns]\n",
      "n_clusters = 3일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   0\n",
      "1     ST-1000   1\n",
      "2     ST-1002   0\n",
      "3     ST-1003   0\n",
      "4     ST-1004   1\n",
      "...       ...  ..\n",
      "2748   ST-993   1\n",
      "2749   ST-994   0\n",
      "2750   ST-995   1\n",
      "2751   ST-996   0\n",
      "2752   ST-997   1\n",
      "\n",
      "[2753 rows x 2 columns]\n",
      "n_clusters = 4일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   0\n",
      "1     ST-1000   1\n",
      "2     ST-1002   0\n",
      "3     ST-1003   0\n",
      "4     ST-1004   1\n",
      "...       ...  ..\n",
      "2748   ST-993   1\n",
      "2749   ST-994   0\n",
      "2750   ST-995   1\n",
      "2751   ST-996   0\n",
      "2752   ST-997   1\n",
      "\n",
      "[2753 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "# 변수 초기화\n",
    "cluster_results = {}\n",
    "\n",
    "# n_clusters 값을 2, 3, 4로 설정하여 K-means 군집분석 및 시각화\n",
    "for n_clusters in [2, 3, 4]:\n",
    "    # K-means 군집분석\n",
    "    kmeans = KMeans(n_clusters=n_clusters, random_state=42)\n",
    "    grouped['군집'] = kmeans.fit_predict(scaled_features)\n",
    "\n",
    "    # PCA 적용\n",
    "    pca = PCA(n_components=2)\n",
    "    pca_features = pca.fit_transform(scaled_features)\n",
    "\n",
    "    # PCA 결과를 데이터프레임에 추가\n",
    "    grouped['PCA1'] = pca_features[:, 0]\n",
    "    grouped['PCA2'] = pca_features[:, 1]\n",
    "\n",
    "    # 군집 시각화\n",
    "    plt.figure(figsize=(10, 7))\n",
    "    plt.scatter(grouped['PCA1'], grouped['PCA2'], c=grouped['군집'], cmap='viridis')\n",
    "    plt.xlabel('PCA1')\n",
    "    plt.ylabel('PCA2')\n",
    "    plt.title(f'대여소 군집 결과 (PCA, n_clusters={n_clusters})')\n",
    "    plt.colorbar(label='군집')\n",
    "    plt.show()\n",
    "    \n",
    "    # 각 군집의 평균 값 계산 (대여대여소ID 제외)\n",
    "    grouped_means = grouped.drop(columns=['대여대여소ID', 'PCA1', 'PCA2']).groupby('군집').mean()\n",
    "\n",
    "    # # 컬럼 별로 가장 높은 값을 가진 군집의 셀에 파란색 배경 추가\n",
    "    # def highlight_max(s):\n",
    "    #     is_max = s == s.max()\n",
    "    #     return ['background-color: #ccffcc' if v else '' for v in is_max]\n",
    "\n",
    "    # styled_means = grouped_means.style.apply(highlight_max)\n",
    "    \n",
    "    # 컬럼 별로 가장 높은 값을 가진 군집의 셀에 연한 초록색 배경 추가\n",
    "    def highlight_max(s):\n",
    "        is_max = s == s.max()\n",
    "        return ['background-color: #ccffcc' if v else '' for v in is_max]\n",
    "\n",
    "    # 컬럼 별로 가장 낮은 값을 가진 군집의 셀에 연한 노랑색 배경 추가\n",
    "    def highlight_min(s):\n",
    "        is_min = s == s.min()\n",
    "        return ['background-color: #fffff0' if v else '' for v in is_min]\n",
    "\n",
    "    styled_means = grouped_means.style.apply(highlight_max).apply(highlight_min)\n",
    "\n",
    "    \n",
    "    # 결과 출력\n",
    "    print(f\"n_clusters = {n_clusters}일 때 각 군집의 평균 값:\")\n",
    "    display(styled_means)\n",
    "    \n",
    "    # 각 대여소가 속한 군집 저장\n",
    "    cluster_results[f'cluster_{n_clusters}'] = grouped[['대여대여소ID', '군집']].copy()\n",
    "\n",
    "# 결과 데이터프레임 확인\n",
    "df_ins_2 = cluster_results['cluster_2']\n",
    "df_ins_3 = cluster_results['cluster_3']\n",
    "df_ins_4 = cluster_results['cluster_4']\n",
    "\n",
    "print(\"n_clusters = 2일 때 각 대여소가 속한 군집:\")\n",
    "print(df_ins_2)\n",
    "\n",
    "print(\"n_clusters = 3일 때 각 대여소가 속한 군집:\")\n",
    "print(df_ins_3)\n",
    "\n",
    "print(\"n_clusters = 4일 때 각 대여소가 속한 군집:\")\n",
    "print(df_ins_4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대여소ID</th>\n",
       "      <th>군집</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "      <th>구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ST-10</td>\n",
       "      <td>0</td>\n",
       "      <td>37.55275</td>\n",
       "      <td>126.91862</td>\n",
       "      <td>마포구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ST-1000</td>\n",
       "      <td>1</td>\n",
       "      <td>37.51038</td>\n",
       "      <td>126.86680</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ST-1002</td>\n",
       "      <td>0</td>\n",
       "      <td>37.52990</td>\n",
       "      <td>126.87654</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ST-1003</td>\n",
       "      <td>0</td>\n",
       "      <td>37.53955</td>\n",
       "      <td>126.82830</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ST-1004</td>\n",
       "      <td>1</td>\n",
       "      <td>37.51410</td>\n",
       "      <td>126.83100</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     대여소ID  군집        위도         경도    구\n",
       "0    ST-10   0  37.55275  126.91862  마포구\n",
       "1  ST-1000   1  37.51038  126.86680  양천구\n",
       "2  ST-1002   0  37.52990  126.87654  양천구\n",
       "3  ST-1003   0  37.53955  126.82830  양천구\n",
       "4  ST-1004   1  37.51410  126.83100  양천구"
      ]
     },
     "execution_count": 155,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in_k_2_ = pd.merge(df_ins_2, ll_join, how='left', left_on='대여대여소ID', right_on='대여소_ID')\n",
    "in_k_2_ = in_k_2_.drop(columns=['대여소_ID'])\n",
    "in_k_2_.columns = ['대여소ID', '군집', '위도', '경도', '구']\n",
    "in_k_2_.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "in_k_2_.to_csv('./(군집_내국인_k=2_청합간) 서울시 따릉이 대여소 별 군집결과_마스터 조인.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>대여소ID</th>\n",
       "      <th>군집</th>\n",
       "      <th>위도</th>\n",
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       "      <td>마포구</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ST-1000</td>\n",
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       "      <td>양천구</td>\n",
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       "      <td>ST-1002</td>\n",
       "      <td>0</td>\n",
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       "</div>"
      ],
      "text/plain": [
       "     대여소ID  군집        위도         경도    구\n",
       "0    ST-10   0  37.55275  126.91862  마포구\n",
       "1  ST-1000   1  37.51038  126.86680  양천구\n",
       "2  ST-1002   0  37.52990  126.87654  양천구\n",
       "3  ST-1003   0  37.53955  126.82830  양천구\n",
       "4  ST-1004   1  37.51410  126.83100  양천구"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in_k_3_ = pd.merge(df_ins_3, ll_join, how='left', left_on='대여대여소ID', right_on='대여소_ID')\n",
    "in_k_3_ = in_k_3_.drop(columns=['대여소_ID'])\n",
    "in_k_3_.columns = ['대여소ID', '군집', '위도', '경도', '구']\n",
    "in_k_3_.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [],
   "source": [
    "in_k_3_.to_csv('./(군집_내국인_k=3_청합간) 서울시 따릉이 대여소 별 군집결과_마스터 조인.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대여소ID</th>\n",
       "      <th>군집</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "      <th>구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ST-10</td>\n",
       "      <td>0</td>\n",
       "      <td>37.55275</td>\n",
       "      <td>126.91862</td>\n",
       "      <td>마포구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ST-1000</td>\n",
       "      <td>1</td>\n",
       "      <td>37.51038</td>\n",
       "      <td>126.86680</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ST-1002</td>\n",
       "      <td>0</td>\n",
       "      <td>37.52990</td>\n",
       "      <td>126.87654</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ST-1003</td>\n",
       "      <td>0</td>\n",
       "      <td>37.53955</td>\n",
       "      <td>126.82830</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ST-1004</td>\n",
       "      <td>1</td>\n",
       "      <td>37.51410</td>\n",
       "      <td>126.83100</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     대여소ID  군집        위도         경도    구\n",
       "0    ST-10   0  37.55275  126.91862  마포구\n",
       "1  ST-1000   1  37.51038  126.86680  양천구\n",
       "2  ST-1002   0  37.52990  126.87654  양천구\n",
       "3  ST-1003   0  37.53955  126.82830  양천구\n",
       "4  ST-1004   1  37.51410  126.83100  양천구"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in_k_4_ = pd.merge(df_ins_4, ll_join, how='left', left_on='대여대여소ID', right_on='대여소_ID')\n",
    "in_k_4_ = in_k_4_.drop(columns=['대여소_ID'])\n",
    "in_k_4_.columns = ['대여소ID', '군집', '위도', '경도', '구']\n",
    "in_k_4_.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [],
   "source": [
    "in_k_4_.to_csv('./(군집_내국인_k=4_청합간) 서울시 따릉이 대여소 별 군집결과_마스터 조인.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 방사형 그래프"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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IIYQQQ0CCtxBCCCGEEENAgrcQQgghhBBDQIK3EEIIIYQQQ0CCtxBCCCGEEENAgrcQQgghhBBDQIK3EEIIIYQQQ8Ba7QKEEGIk0ul0tLa20tLSQktLywk/bm1tpb29HYPB0OdNr9djMBh4++23GT9+PDNmzECr1R73Zm1tjbOzM87Ozri4uJjeH/uxo6MjWq2MwwghxGCT4C2EEOdIr9dTXV1NeXk5FRUVprfy8nLKysqoqanpE6bb2tro6uoyfb+jo6PpzcnJCQcHB5ycnHB0dMTe3h4rKys0Gk2fUK3RaNDr9dTV1VFWVgZwXEDX6XS0t7fT0dFBW1sb7e3tfd56a9BoNKb7PjqQ+/n5ERgYSEBAAP7+/qa3gIAA3N3d0Wg0qjzeQghhqTSKoihqFyGEEOaqra2N/Px8ioqKTMG6N1CXl5dTWVlJbW0tBoMBDw8PRo0ahbe3N15eXvj5+eHv74+Pjw9ubm64uLjg7u6Om5sbbm5ueHh44OLigpWV1VnV1tPTw/fff89FF12EjY3NGX9/V1cXzc3NNDY20tTUZHrfe1llZSUVFRVUV1dTU1NDbW0tNTU1dHR0YGtri6+vL/7+/qZw3hvQAwICiIyMJDQ0FGtrGd8RQohe8owohBjxenp6KCoqIjc3l9zcXHJycsjOziYvL4/y8nKcnZ0JDAzE29sbb29vfH19mTZtGkFBQQQFBREaGkpoaCj29vZq/yhnxM7OzvQznYn6+nqKi4s5cuQIpaWllJWVUVFRwbZt26itraW6uprS0lI0Gg1hYWHExMSY3qKjo4mOjsbPz09GzIUQI44EbyHEiKAoCmVlZX3Cde/bkSNH0Gg0hISEEBoaSnh4OBdffDFjxoxh/PjxBAYGSg/0UTw9PfH09GTSpEknvU53dze5ubkcOHCArKws8vLy2LZtG8XFxVRWVuLo6Mjo0aOJiYkhNjbWFMijo6Nxd3cfuh9GCCGGkLSaCCGGHUVROHz4MHv27CEtLY3du3eTkZFBc3Mz/v7+hIWFERYWRlRUFGPGjGHcuHFERUVZXFvEubaaqKW1tZWDBw9y8OBBsrOzTa08R44coaGhgZCQEBITE5k8eTKJiYkkJiYyatQotcsWQohzJsFbCGHRFEWhoKCgT8jeu3cvbW1tREZGMmbMGCZNmsS0adNITk7G2dlZ7ZIHjKUG71MpKysjNTWVnTt3sm/fPrKysigrKyM4OPi4MO7l5aV2uUIIcUYkeAshLEZvyE5LS+sTsjs6OkwhOyEhgenTpzNlyhQcHR3VLnlQDcfgfSJVVVVs3brVFMYzMzMpLS0lKCioTxhPSkqSMC6EMGsSvIUQZktRFHJycti4cSMbNmxg48aNNDY2Eh0dTVxcnClkJycnW9zExoEwUoL3idTU1LBlyxZ27tzJ/v37yczMpKSkhJiYGObNm8fcuXNJSUk544mjQggxmCR4CyHMxomCdnNzM+PHj2fatGmcd955zJs3b9iPZPfXSA7eJ1JRUcH333/Pzz//zK5du8jPzyc2NtYUxGfPni1BXAihKgneQgjVKIpCbm7ucSPavUH7/PPPl6B9ChK8T62srIwffvjBFMQLCgokiAshVCXBWwgxpMrLy1m9ejXr1q07LmgvWLCA+fPn4+TkpHaZFkGC95npDeIbNmxg165dHD582BTEzz//fBYsWCAHeUKIQSXBWwgxqBRFYd++faxatYoVK1awf/9+xo4dy6xZs1iwYAELFiyQoH2WJHifm9LSUlMQ37JlC7W1tSxYsIDLLruMRYsW4e/vr3aJKIrCJ598wltvvcX27dtPeJ2MjAzuueceKioqcHJy4rXXXuO8884b4kqFEP0hwVsIMeC6urrYuHEjq1atYuXKldTX1zNt2jQuvvhirrnmGoKCgtQucViQ4D1wDAYDaWlpfPHFF6xbt46DBw8yceJELrvsMi677DLGjRs35Dtt/vjjjzzyyCN0dHRgbW1Ndnb2cddpaWkhLi6Ojz76iAULFrBp0yYuu+wysrOz8fPzG9J6hRCnJ8FbCDEgamtr+f7771m5ciU//fQTzs7OpKSkcPnll3PppZfKqPYgkOA9eEpKSvjiiy9YvXo1O3bsYNSoUaYQnpKSgq2t7aDX8PXXX+Pg4ICjoyN33333CYP3u+++yw8//MA333xjuuzSSy9l/vz5/OEPfxj0GoUQZ8aytmkTQpiVnJwcUwvJzp07iY6OZsGCBXz//ffMnDlTtlkXFis4OJiHHnqIhx56iLa2NlauXMmKFSu44YYbaG9vZ+HChVx++eVceOGFg7ar5pVXXgnAxo0bT3qd7du3M2PGjD6XJScns3fv3kGpSQhxbuRVUQhxRkpKSnj55ZeJj49n/PjxrFq1iosvvpjs7GwyMzP597//zezZsyV0i2HDycmJ6667ji+++IKKigq+++47/Pz8eP755/Hz8+PCCy/kf//7H+3t7UNeW0VFBb6+vn0u8/Hxoa6ubshrEUKcnrwyCiFOq7Gxkffff5+UlBQiIiJYsWIFv/vd76ioqGDLli08+eSTREZGql2mEINOq9WSkpLCG2+8QVZWFvv372fMmDE89dRTeHt7c8MNN7BmzRp0Ot2Q1KPT6Ti2Y1Sv1w95P7oQon8keAshTqirq4tvvvmGxYsX4+vryyuvvMLs2bPJy8sjNTWVBx98EE9PT7XLFEJVcXFx/POf/yQ/P58ffvgBa2trrr/+egICAnjwwQdJS0s7LhgPJE9PT2pra/tcVlNTIxMrhTBTEryFECYGg4HNmzdz55134uvrywMPPICfnx/bt2/n0KFDPPfcc4SFhaldphBmR6vVMnv2bD766CMqKir4z3/+Q2FhIXPmzCE6Oppnn32Ww4cPD/j9JiYmkpqa2uey1NRUpk2bNuD3JYQ4dxK8hRAcOnSIxx9/nNDQUC677DKam5tZtmwZR44c4c033yQhIUHtEoWwGNbW1lx99dWsXLmSyspKHnroIdavX09MTAzJycm8+eabx41Sn63rr7+e9evXs2HDBgC+//57srKyuPrqqwfk9oUQA0uCtxAjVGtrK++99x4JCQkkJiaSkZHBCy+8QEVFBZ9//jkLFy6UCZJCnCNnZ2fuvvtuNm3aRFFREYsWLeKdd94hICCAxYsXs27dOgwGwxnd5tKlS01LBQYFBfH5559z77334uPjw1//+le+/fZbWb5TCDMl63gLMcLs37+ft99+m08++YSAgABuvPFG7rnnnkFbEk0MHlnH23IdOHCA1157jeXLl+Ph4cHdd9/NrbfeipeXl9qlCSEGkQxnCTECdHR0sGTJEqZOnUpycjLl5eV88803ZGVl8ec//1lCtxBDbNy4cbz33nuUlpby8MMPs2zZMgIDA/ntb3/Lli1bBnVCphBCPRK8hRjGiouLefTRRwkICOAvf/kLCxcu5MiRI6xYsYIFCxZIK4kQKnN0dOSee+4hLS2N1NRUbG1tueSSSxg7dizvvvsubW1tapcohBhA8qorxDCjKArr16/n0ksvJSoqivT0dD766CPy8vL4y1/+gre3t9olCiFOIDExkY8//pjS0lJuueUW/vnPfxIYGMif/vQnCgoK1C5PCDEAJHgLMUy0trby5ptvEhcXx1VXXYW/vz+HDh1i3bp1XHbZZTK6LYSFcHZ25pFHHiErK4vPPvuMzMxM4uLiuOiii/jxxx/PeDKmEMJ8yCuxEBautraWZ555hqCgIN544w3uuusuSktLeeedd4iKilK7PCHEWdJqtaawnZWVRUREBDfccAPjxo3j008/HbLdMYUQA0eCtxAWqrS0lAcffJCQkBDWrFnDhx9+yMGDB/njH/8oS4kJMcyMHj2aN954g+LiYq6//noee+wxIiMjeeutt+js7FS7PCFEP0nwFsLC5ObmcttttzF69GgOHjzId999x44dO7jiiiuknUSIYc7JyYknn3ySw4cP8/DDD/Ovf/2LkJAQXnzxRZqbm9UuTwhxGvIqLYSFSE9P58orr2TcuHHU19eTmprKunXrmDdvntqlCSGGmK2tLffffz/Z2dm88sorfP755wQHB/Pkk09SXV2tdnlCiJOQ4C2EGVMUhY0bN3Leeecxc+ZMHB0dOXjwICtWrCAxMVHt8oQQKtNqtdxwww3s3buXTz/9lM2bNxMaGsr9999PcXGx2uUJIY4hwVsIM2QwGFi1ahVTp07l0ksvJTIyktzcXD755BOZMCmEOKFFixaxdetW1qxZQ15eHtHR0dx0001kZWWpXZoQ4hcSvIUwI4qisHz5csaNG8dtt93GnDlzKCws5K233iIoKEjt8oQQFmDWrFn89NNP7Ny5k7a2NiZOnMgVV1zBoUOH1C5NiBFPgrcQZuLnn39mypQp3HnnnVx77bUUFxfz0ksvyXbuQoizMnHiRL7++msOHTqEg4MDiYmJ3HLLLZSUlKhdmhAjlgRvIVSWkZHB+eefz6WXXsqsWbMoKCjgmWeekSUBhRADIjIyks8++4y0tDSqq6uJjo7moYceoq6uTu3ShBhxJHgLoZKCggJ+85vfMH36dIKCgsjNzeWVV17Bzc1N7dKEEMPQ2LFj+f7771mzZg07duwgPDycv/71r7S1taldmhAjhgRvIYZYVVUV9913H/Hx8XR1dbF//34++OAD/P391S5NCDECzJo1i23btvHJJ5+wbNkyIiIieOutt+jp6VG7NCGGPQneQgyR5uZmnn76aSIiIsjKymLz5s188803skqJEEIVl112Gfv27eOFF17g5ZdfJjY2lmXLlmEwGNQuTYhhS4K3EIOsq6uLV155hbCwML7//nuWL1/Ohg0bmDJlitqlCSFGOK1Wy+23305OTg533XUXv//970lMTGTt2rVqlybEsCTBW4hBoigKn332GZGRkbz99tu88cYb7N69m4ULF6pdmhBC9GFra8ujjz5KQUEBCxcu5KqrrmLevHns27dP7dKEGFYkeAsxCA4cOMDs2bN58MEHefjhh8nKyuK6665Dq5V/OSGE+XJ2dubFF18kPz+f8PBwpk6dyu9//3saGxvVLk2IYUFSgBADqKmpiQcffJApU6YQFRVFdnY2f/jDH7CyslK7NCGE6Ddvb2/ef/99tm3bxq5du4iKimLJkiUoiqJ2aUJYNAneQgwARVFYunQp0dHRpKamsmXLFj744AM8PT3VLk0IIc5aQkICqampPP/88zz66KPMmDFD2k+EOAcSvIU4RwcOHGDWrFk89NBD/OUvf2HHjh0kJSWpXZYQQgwIrVbLnXfeSU5ODvHx8UydOpUHHnhA2k+EOAsSvIU4S0e3lcTExJCTk8Pdd98tfdxCiGHJzc2N//73v2zbto3du3cTFRXFxx9/LMsPCnEGJCEIcYZ620qioqJMbSXvv/8+7u7uapcmhBCDrrf95IUXXuCxxx5jxowZ7N27V+2yhLAIEryFOAP79+83tZU8++yz0lYihBiRtFotv/vd78jJyWHs2LFMnTqV+++/X9pPhDgNCd5C9ENHRwcPP/ywtJUIIcRRettPUlNTSUtLIzIyki+++ELtsoQwW5IahDiN7du3M2HCBH766Sc2b94sbSVCCHGM3vaT5557jrvuuosrr7yS6upqtcsSwuxI8BbiJHpHuefPn8/ll19ORkaGbPMuhBAnodVqueeee9i/fz9NTU3ExcXx5Zdfql2WEGbFWu0ChDBHO3bs4Oabb8bGxobNmzdLH7cQQvRTcHAwa9as4Z133uHOO+9k2bJlvPXWW3h7e6tdmhCqkxFvIY7S2dnJo48+yrx587j00ktJT0+X0C2EEGeod/R77969NDQ0EBcXx1dffaV2WUKoTka8hfjFrl27uOmmm7CysmLjxo3SViKEEOcoNDSUtWvX8tZbb/G73/3ONPrt5eWldmlCqEJGvMWI19nZyWOPPcacOXNYtGiR9HILIcQA0mq13Hfffezdu5e6ujpiY2P5+uuv1S5LCFXIiLcY0XpHubVaLT///DPJyclqlySEEMNSaGgo69at48033+T222/niy++4D//+Y+MfosRRUa8xYjU3d3NE088wZw5c7j44ovZu3evhG4hhBhkWq2W+++/n71791JdXU1cXBwrV65UuywhhoyMeIsR5/Dhw1xzzTW0tLSwYcMGpk6dqnZJQggxooSFhbF+/Xr+85//cMMNN3DzzTfzj3/8A3t7e7VLE2JQyYi3GFG++uorJk2aRExMDBkZGRK6hRBCJVqtlgceeIAdO3awceNGpk6dSl5entplCTGoJHiLEaGzs5N77rmH2267jX/+8598+umnODo6ql2WEEKMePHx8aSlpTFx4kQSEhL47LPP1C5JiEEjrSZi2MvJyeHqq69GURR27txJXFyc2iUJIYQ4ir29PR999BHz58/n3nvvZf369bz++usyQCKGHRnxFsPaJ598QmJiIklJSaSlpUnoFkIIM3bjjTeye/duMjIySExM5NChQ2qXJMSA0iiKoqhdhBADra2tjXvvvZdVq1bxn//8h+uuu07tksQIZzAY6Orqoquri87OTnp6etDr9eh0utO+6fV6DAYDAIqimN70ej0A1tbGk5cajcb0ptVqsba2xtraGisrK9PHJ3uzsbHB3t4ee3t7bGxs0Gg0qj1WQnR3d/OHP/yBJUuW8O9//5vbbrtN/ibFsCDBWww7Bw4c4KqrrsLJyYkvvviCyMhItUsSw5iiKHR2dtLR0WEK1b1vR3/e1dUFgK2tLXZ2dtjY2Jw0BJ8oKGu1xhOUvcEaoLW1ld27dzNr1iysra37hHKDwXDaMH/0593d3XR2dqLX69FqtdjZ2ZmCuL29/XGfOzo6YmNjo9rjLkaGL7/8knvuuYfzzjuPd999FxcXF7VLEuKcSPAWw4aiKLz33ns8+OCD3HLLLfzrX//C1tZW7bLEMNHd3U1rayutra20tbX1+Viv15uC6ekCa2+AHgg9PT18//33XHTRRQMWgnt6ek55ANH7ptPpsLW1xdnZGWdnZ5ycnPp8bGVlNSD1CFFUVMQ111xDXV2daWUqISyVTK4Uw0JLSwt33HEH69ev55NPPmHx4sVqlyQskKIotLe309TUZArWveG6u7sbOzs7U7B0d3cnKCgIJyenYRU0bWxssLGxwdnZ+ZTX6+7u7nMA0tzcTHl5Oa2trej1ehwcHPoEcVdXV9zc3ORgWJyxsLAwUlNTeeSRR5gxYwYvv/wy9913n7SeCIskwVtYvMOHD7No0SKcnZ3Zs2cPoaGhapckLEBvyG5sbKSxsZGmpiYaGxvR6XS4uLjg4uKCs7MzPj4+ptFcaa34la2tLba2tnh4ePS5vLf15uhQXlNTQ0FBAR0dHTg6OuLu7o6bmxvu7u64u7tLGBenZW1tzb/+9S/mz5/PrbfeSnp6Om+99RZ2dnZqlybEGZFWE2HRfv75Z6688kouvvhi3n//fXkBFyd0bMjuDdo6nc40EtsbAl1dXS1m9HowWk0GU1dXl+kAp/d30N7ejqOjY5/fgYRxcSr5+flceumluLm5sWLFCnx9fdUuSYh+k+AtLNZ//vMfHnnkEf7f//t/PProo2qXI8yIoii0tLRQW1tLbW0tdXV19PT04Orqagp2bm5uFhWyT8TSgveJdHd39znj0NjYSHt7O87Oznh5eTFq1Ci8vLxkK3HRR2trK9dccw379u3j22+/JSEhQe2ShOgXaTURFqe7u5vf//73fPnll3z11VdcdNFFapckVHaioK3X6/H09MTLy4vIyEjc3NwsOmQPV7a2tvj4+ODj42O6rLu7m/r6empra8nPz2fPnj2mIN4bxs0liHd0dPCHP/yBn376Cb1ez3XXXcdLL710XP/xihUreOqpp2hpacHPz49XXnmFmTNnqlS15XN2dua7777jscceY9asWXz44Ydcc801apclxGlJ8BYWpba2lsWLF1NVVUVqaioxMTFqlyRUcHTQrquro7a29rig7e7uPqAriIihY2tri5+fH35+foBxZL/395yXl0daWprZBPGHHnoIg8FAQUEBbW1tLFiwgDfeeIMHHnjAdJ3CwkJuuukmNmzYQFJSEmvXruXSSy+lsLAQNzc3VeoeDrRaLX//+98ZP348t99+O/v37+fZZ5+V/3th1qTVRFiM/fv3c8kllxAdHc1XX30lL1gjjF6vp7a2lsrKSiorK+np6TEFbS8vrxEZtIdDq8nZ6O7upq6uzhTGm5qacHNzw9/fH19fX9zc3IZkxYvW1lZ8fX0pKSnB09MTgOXLl/Pcc8+RkZFhut6qVat49tlnSUtLM10WFBTEihUrSEpKGvQ6R4Jdu3Zx5ZVXkpCQwKeffnraVXmEUIuMeAuLsGLFCm688UZuu+02/vWvf424gDVSdXV1UVVVRWVlJdXV1aaR0EmTJjFq1ChpHRmhbG1t8ff3x9/fHzD+nVRXV1NZWUleXh62trb4+vri5+eHl5fXoP2d7Nmzh/DwcFPoBkhOTubgwYPo9XrT/c6aNYvq6mrWrl3Leeedx//+9z88PT0ZP378oNQ1Ek2ZMoXdu3dz6aWXMnXqVL799lvCw8PVLkuI40jwFmZNURT++te/8uKLL/Lvf/+b22+/Xe2SxCDqbSGprKykqqqKhoYG3Nzc8PPzIyYmBldXV1m7VxzHzs6O4OBggoOD0ev11NXVUVlZyb59++ju7sbHxwc/Pz98fX0HdPm5ioqK41bU8PHxQafT0dTUZArkHh4e/OMf/+D888/HycmJ7u5utmzZIiu3DDA/Pz+2bt3KbbfdRmJiIsuXL2fOnDlqlyVEHxK8hdlqa2vj5ptvJjU1lTVr1jBjxgy1SxKDQFEUGhsbKSsro7Kyko6ODnx8fAgJCWHy5MlmM4lOWAYrKyvTZM1x48bR3NxMZWUlhYWF7N27Fw8PD/z9/QkMDMTBweGc7kun03Fst6Zerwfoc4C4a9cunnzySTIyMpgwYQLr16/nyiuvZOvWrYSFhZ1TDaIvW1tbli5dyksvvcRFF13EP//5T+655x61yxLCRIK3MEuVlZVceOGFaDQadu3aRVBQkNoliQHW1tZGaWkpJSUldHV14e/vz9ixY/Hy8sLaWp6axLnTaDS4ubnh5uZGTEwMHR0dVFVVUV5eTmZmJqNGjSIoKIiAgICz6pH39PSktra2z2U1NTXY29v3mYPy2muvcd999zFx4kQAFixYwBVXXMF///tfnn/++XP6GcWJPfbYY4wdO5Ybb7yRzMxMXn31VWlNE2ZBXt2E2cnPz+e8884jPj6er776SkY8h5Guri7KysooLS2lsbERX19f4uLi8PPzkxdFMegcHBwICwsjLCyMjo4OysrKKCwsZP/+/fj5+REUFISvr2+/55AkJCSQk5NDQ0ODaQfP1NRUkpOT+9xGd3f3cQeTNjY2dHd3D9wPJ45z8cUXs23bNi688EIqKytZunSp7HQpVCermgizkp6ezsKFC007UUoYs3w6nY7KykpKS0uprq7Gw8ODoKAgAgMDpcf1HI3UVU0GWnNzM6WlpZSWlqLT6QgMDCQoKAhPT8/Tzim47LLLCAgI4PXXX6exsZF58+bx7LPPcvnll5uu88UXX/DnP/+ZdevWERISwt69e1mwYAGrVq1i+vTpg/zTibKyMhYuXIi3tzcrV67E1dVV7ZLECCbBW5iNdevWccUVV3Dffffx4osvql2OOAeKolBXV8eRI0coLy/HwcGBoKAggoKCcHJyUru8YUOC98BSFIX6+npKS0spKyvDxsaGoKAgQkJCTvp3W1tby+23305qaipOTk48/PDD3H///SxdupTdu3fz2muvAfDee+/xyiuv0NbWhoeHB8888wyLFy8eyh9vRGtsbOSiiy6ivb2dn376SbaZF6qR4C3MwrJly7j11lt54YUXePDBB9UuR5yl7u5uSkpKKCoqoqury7TSxFCtqzzSSPAePHq9nurqakpKSqisrMTb25uwsLAzakUR5qWrq4srr7ySzMxM1q5dy+jRo9UuSYxAEryF6v7973/zxBNP8N///pfrrrtO7XLEGVIUhYaGBoqKiigrK8Pd3Z2wsDACAgKkVWiQSfAeGh0dHRw5coTi4mIURSE0NJTQ0NBzXhVFDD29Xs/tt9/O6tWrWbNmDZMmTVK7JDHCSPAWqlEUhaeeeoq33nqLZcuWcf7556tdkjgDer2e0tJSCgsLaWtrIzg4mLCwMOmfHEISvIeWoihUVVVRVFRETU0Nvr6+REREMGrUKDmjY2Eef/xx3nzzTVasWMG8efPULkeMILKqiVCFTqfjrrvu4vvvv2fdunUkJiaqXZLop/b2dgoLCykuLsbe3p7w8HCCg4NlCUAx7Gk0Gvz8/PDz86OtrY2ioiJ27dqFvb09ERERBAUFyf+BhXjxxRfx9fVl0aJFfPTRR1xzzTVqlyRGCHmGEEOuvb2da6+9lqysLLZs2UJkZKTaJYl+aGhoIC8vj8rKSvz8/Jg8eTJeXl4y0idGJCcnJ+Lj44mJiaGsrIzDhw9z6NAhwsPDiYiIkGVQLcAf//hHfHx8uPXWW6mqquKBBx5QuyQxAkjwFkOqoaGBiy++mPb2drZt2yYzy82coijU1taSl5dHfX09oaGhLFiwAEdHR7VLE8IsWFtbExoaSkhICHV1deTn57Nu3TqCg4OJioqS/xUzd/311+Pl5cW1115LVVUVzz33nAwmiEElwVsMmYqKCubPn4+Pjw9r1qzB2dlZ7ZLESSiKQmVlJXl5ebS2thIREUFiYqJsPiHESWg0Gry8vPDy8qKpqYm8vDzWr19PQEAAUVFRMvfBjC1cuJB169axaNEiqqqqeOedd2TlGjFoZHKlGBJlZWXMmTOH2NhYvv76a9k4xUwZDAbKysrIy8uju7ubyMhIQkNDZeKemZLJleattbWV/Px8SkpK8PHxISoqCk9PT7XLEieRl5fHggULSElJ4cMPP5RVmcSgkOAtBl1JSQkpKSlMmDCBL7/8UiYfmSG9Xs+RI0fIz89Ho9EQGRlJcHCwvPCYOQnelqGjo4OCggKKiorw8PAgKioKb29vaWkwQ4WFhcybN49p06axZMkSeb0SA06CtxhUxcXFpKSkkJSUxLJlyyTImRm9Xk9hYSH5+fnY2dkRFRVFQECAnGa1EBK8LUt3dzeFhYUcPnwYR0dHYmNj8fHxkQBuZoqLi5k7dy6TJ0/m008/lfAtBpQEbzFoCgsLSUlJYfr06Xz66acSus2IwWCgpKSE7Oxs7OzsiI2NxdfXVwKAhZHgbZl0Oh1FRUXk5eXh4uLCmDFjpAXFzJSWljJ37lzGjRvHsmXL5P9LDBgJ3mJQFBQUkJKSwpw5c1iyZImMoJoJRVGoqKggKysLRVGIjY0lMDBQAreFkuBt2Xp6esjPz6egoABvb2/GjBmDi4uL2mWJX5SVlTFv3jxiY2P58ssvZW6SGBASvMWAKywsZNasWcybN4+PPvpIQreZqK2tJTMzk/b2dmJiYggNDZXfjYWT4D08dHZ2kpOTw5EjRwgKCiI2Nla2ozcTlZWVzJ07l5iYGL788kv5PxPnTIK3GFDFxcXMmjWL2bNny0i3mWhqaiIzM5P6+noiIyMZPXq09CwOExK8h5fW1lays7OprKwkPDycqKgoGWU1A5WVlaSkpDB27FiWLVsmz5/inEjwFgOmpKSEWbNmMXXqVD777DMJ3Spra2sjOzub8vJy04u4rMM9vEjwHp4aGxvJysqivr6eqKgoIiIiJOyprHdJ3MTERJYuXSq/D3HWJHiLAVFWVsasWbNISkrif//7n0ykVJFOpyMnJ4fDhw8TGBhIbGys7J43TEnwHt5qamrIzMyks7OT+Ph4mY+hstLSUlJSUkhOTuaTTz6R1zlxViR4i3NWUVHBrFmzGD9+PF9++aU8GalEURTKy8s5ePAgjo6OjB8/Hjc3N7XLEoNIgvfwpygKpaWlHDp0CBcXF8aNGye7YKqouLiYOXPmMGvWLJnDJM6KBG9xTurq6pgxYwbR0dF88803ErpV0tLSwv79+2lpaSE+Pp6goCAZGRsBJHiPHD09PeTk5FBYWEh4eDgxMTHyO1dJYWEhc+bM4YILLuDtt9+W51pxRqRJSZy1trY2LrroIgIDA1m+fLmEbhUc3VYSFhbGlClT5MVYiGHIxsaGsWPHEhISwv79+1m/fj1jx46V9hMVhIeHs27dOmbNmoWfnx9/+ctf1C5JWBAJ3uKs9PT0cPXVV9PT08OqVatkoskQO7atZPbs2dJWIsQI4OrqyowZMygrK+PgwYMUFRUxfvx4aT8ZYlFRUaxcuZLzzz8fX19f7r33XrVLEhZC0pI4Y4qicPvtt5OXl0dqaipOTk5qlzSiSFuJECObRqMhKCgIX19fcnJy2LRpk7SfqCA5OZlly5axePFifHx8uOqqq9QuSVgA6fEWZ+yxxx5j6dKlbN68mdGjR6tdzoih1+vJycmhoKCAsLAwYmNj5UV2BNPpDVz/3g4cO+t4994L5G9hBGtubmb//v20trYyfvx4AgIC1C5pRFmyZAl3330333//PXPmzFG7HGHmJHiLM/LKK6/w3HPPsWHDBiZNmqR2OSNGQ0MDGRkZaLVaJk2aJG0lgrDHV5s+/v3c0fxpYayK1Qi19a5+cuDAAXx8fBg/frxsvjOE/v73v/Pcc8+xefNmJk6cqHY5woxJq4not08//ZRnnnmGlStXSugeIr2j3IcPHyYqKoqoqChZvkrQ0Nbd5/OCmjaVKhHmQqPREBwcjLe3N/v27WPDhg1MmDABf39/tUsbER555BGqqqpYuHAh27dvJyIiQu2ShJmS4C36Zc2aNfzud7/jo48+Yv78+WqXMyIcPco9e/ZsmTwlTF7+KbvP582dPSpVIsyNvb09U6ZMobS0lIyMDMrLyxk3bpyMfg+Bl19+maqqKs477zy2b9+Oj4+P2iUJMyStJuK0du/ezbx583jhhRd44IEH1C5n2JNRbnEqGUcaWPxWKkc/c9tYadjz9Hm42kuft/hVZ2cn+/bto6GhQUa/h4her2fRokVUVVWxadMmXFxc1C5JmBkJ3uKUcnNzmTZtGvfccw9//etf1S5n2GtsbCQ9PV16ucUJ6Q0Kl/9nGwfKmo772uu/ncQlE2RSnehLURRKSko4ePAgvr6+Mvo9BDo7O0lJScHZ2ZkffvhBHm/RhwyjiZMqLy9nwYIFLF68WEL3IDMYDGRlZbF161YCAwNlXW5xQv/bdcQUuoM9HXn0/CjT19ZmVqlVljBjGo2GkJAQ5s6dS09PDxs2bKCiokLtsoY1e3t7fvjhB8rLy7npppswGAxqlyTMiARvcUItLS0sXLiQiRMn8s4776hdzrDW2trK5s2bqaqqYtasWcTExEhriThOXWsXf/8px/T5bdPDiA9wwcHKeNLy55xqunXyAi9OzMHBgeTkZMaMGUNGRgZ79+5Fp9OpXdaw5enpyZo1a0hNTeXhhx9WuxxhRuTVXRzHYDBw/fXX4+joyJdffikhcBCVlpayadMmvLy8ZJRbnNLLP+bQ1GGcRDkr0otYf1estVrGeBiDd0unjp2FdWqWKMxc7+j3nDlzaGlpYfPmzTQ3N6td1rAVHBzM6tWr+eCDD/jggw/ULkeYCUlU4jjPPPMMe/fuZeXKldjZ2aldzrCk0+nIyMhg//79JCYmMnbsWDnAESeVfqSBZWklADjYWHFdcojpa+M8fp2mI+0moj8cHR2ZMWMGfn5+bN68mSNHjiDTvQbHuHHj+OCDD7j//vvZtm2b2uUIMyCv9KKPZcuW8dprr7F8+XL8/PzULmdYam5uZvPmzbS2tjJ37lx5nMUp6Q0KT684aPr8mqQg3B1/nawV565gpdUAsC6zSgKU6BetVsuYMWOYMmUKhw4dIj09XVpPBsnixYt57LHHuPzyyzly5Ija5QiVSfAWJunp6dx222289dZbJCUlqV3OsKMoCsXFxWzevBl/f39mzJiBg4OD2mUJM/fpzmIOlRvbAUI9HTlvTN8DNXtriPc3LllW3tRpuq4Q/eHj48OcOXPo7Oxk48aNNDUdv2KOOHdPP/00c+bM4dJLL6W9vV3tcoSKJHgLACorK7nkkku47777uOGGG9QuZ9jp6ekhPT2drKwspkyZQlxcnLSWiNOqPWZC5a0zwk2j20dLDHU3fbzmUOVQlCaGEQcHB6ZPn05wcDBbtmyhsLBQzpwMMK1WyyeffIJWq+Xmm2+Wx3cEk1d+QVdXF5dffjkTJ07kxRdfVLucYaexsZFNmzbR2dnJnDlzZDcz0W8v/pBNS6fx9H9KtDcxfifejCMxxN308Rrp8xZnQaPREBMTw9SpU8nJySEtLY2eHtkRdSDZ29uzatUqtm3bxvPPP692OUIlErxHOEVRuOuuu2hpaWHZsmUyCjvAiouL2bp1K8HBwUyfPh17e3u1SxIWIq2onq/2lALgaGvFb6eEnPS6Ho62jPZ2AiC7soWSejmVLc6Ol5cXc+fORafTSevJIAgKCuKLL77gb3/7GytXrlS7HKECSVkj3Kuvvsrq1atZuXIlzs7OapczbBgMBg4cOMChQ4dITk4mJiYGjeb4FgEhTkSnN/D0ykOmz69NCsbN4dTbwSeFepo+ltVNxLmws7Nj6tSpBAcHs3XrVtlwZ4DNnDmTV199lRtuuIEDBw6oXY4YYhK8R7A1a9bw1FNP8emnnxIZGal2OcNGd3c3O3bsoKamhpSUFLy9vdUuSViYpTuKyaowTpIMG+XIgjjf035PYqiH6WMJ3uJcaTQaYmNjmTRpEnv27CEnJ0f6kgfQ7373O2655RYuueQSamtr1S5HDCEJ3iNUbm4u11xzDS+88ALnn3++2uUMG71LBVpZWTFr1iycnJzULklYmOqWTv65Jtf0+a0zwtGeYELlsYI8HPB1Na67v6uonsb27kGrUYwcAQEBzJo1i+LiYtLS0mTJwQH06quvEhUVxZVXXin99COIBO8RqKmpiUWLFrF48WIefPBBtcsZNiorK9myZQuBgYFMmTIFG5tTtwYIcSIvfp9NS5cx3MyN8Sba98QTKo+l0WhI/KXdRG9Q2JBdPWg1ipHFzc2NlJQUurq62Lp1qyyHN0CsrKz46quvqKio4A9/+IPa5YghIsF7hFEUhRtuuAFvb2/effddtcsZFhRFIS8vj7S0NCZOnEhcXJz0c4uzsvNwHcszygBwsrPiN5NPPqHyRCZLu4kYJHZ2dkyfPh0PDw82b95MXV2d2iUNC25ubqxatYrPP/+cDz/8UO1yxBCQ4D3CvPrqq+zevZuvv/4aa2trtcuxeHq9nvT0dA4fPszMmTMJDAxUuyRhoXr0Bp7pM6EyBNfTTKg8VrSvCy72xv/rTbk1dPboB7RGMbJptVomTJhATEwM27dvp7i4WO2ShoXY2Fjeeecd7r//fjIzM9UuRwwyCd4jSFpaGk899RQfffSRbFM+ADo6Oti6dSttbW2kpKTg7u6udknCgi3ZXkxOVQsA4V5OzI898/XetVoNCSHGUe/2bj2pBTJpSwy88PBwkpOTyczM5MCBAxgMBrVLsnhXX301119/PVdddZW08gxzErxHiKamJq6++mruvfdeLrjgArXLsXi9kyhdXFyYMWOGrM8tzkl1cyf/WmucUKkBbuvnhMoTkdVNxFDw9vZm9uzZ1NTUsHv3bpl0OQDeeOMNbG1tpd97mJPgPQIoisIdd9yBn58fL730ktrlWLz6+nq2bt1KaGgokyZNwsrKSu2ShIV74fssWn+ZUDknxpvRXg4YdN3ouzvp6Wilu62ZrpYGOptqf3mrobOxhpbyAgC6ei9rqiXGVY+tlTG0rz1USWtbG93d3TIqKQack5MTs2bNoqenh+3bt9PdLSvpnAtbW1u+/PJLvvzyS/73v/+pXY4YJBpFFuYc9t5++23+/Oc/k5GRQXBwsNrlWLTKykrS0tKIj48nPDxc7XKEhTAYDHR2dtLZ2UlXV5fp487OTtJLW3lum3HNbkdrhacm6nE2tXZr0FhZodH2vmkxjokbVzHpaTd+n7VD78onCigKb+/v5kCd8an9j2N1hP3yZa1Wi7W1NdbW1tjZ2WFvb4+9vX2fj3vfbG1tZZKw6Be9Xk9aWhptbW1MmzYNBwcHtUuyaEuWLOG+++4jPT2dqKgotcsRA0yC9zC3f/9+pk2bxtKlS7niiivULseiHTlyhP3795OQkEBAQIDa5QgzYzAYaG9vp7W1lba2NlpbW01vnZ2dAMeFXWtbO+7/rpzihi4AbpsayLwYb1PQRqM5Zfg16HXUZu3AK24qWqtfJ0v/nFPNu5sPA3B3SgQPnxeFTqfr83aig4DeN51Oh0ajwcnJCWdnZ5ydnft8bGdnJ6Fc9KEoCvv27aO6uppp06bh4tK/ZTDFid18883s27ePnTt3Ymdnp3Y5YgBJ8B7GWltbSUxM5LzzzuONN95QuxyLpSgK+fn55ObmkpycjJeXl9olCRUpikJHRweNjY00NjbS3NxMa2sr7e3tprB6dEh1dnbG0dEROzs7tNq+3X3/3XyY57/PAmC0txPPXjYW7RkE2pMF76aOHu5Zugfll9td/9CcM/oZ9Xo9HR0dfQ4gej/u6OjAysrK9LO5ubnh7u6Ou7u7Wa5d39HRwR/+8Ad++ukn9Ho91113HS+99NJxBw6KovCvf/2Ld955h46ODmxtbcnKyjLLn8lcKYpCTk4Ohw8fZurUqXh6eqpdksXq7OwkISGB+fPn8/rrr6tdjhhAsp7cMHbvvffi4uLCq6++qnYpFktRFA4ePEhZWRkzZ87Ezc1N7ZLEEFIUhfb2dpqamkxBu6mpiZ6eHlxcXHBzc8Pb25uIiAicnJxwdHTs90hwZVMnr677dULlrTPCzyh0n4qbgw3Rvi7kVLVQUNPG4ZpWIryd+/39RwdrX9++29XrdDrTyH5LSwsNDQ0UFhbS0dGBk5NTnyDu5uaGra3tgPxMZ+uhhx7CYDBQUFBAW1sbCxYs4I033uCBBx7oc73nn3+edevWsWXLFnx8fCgvL5f5G2eod5t5Ozs7UlNTSUpKkhW0zpK9vT3Lli1j+vTpzJs3T85YDyMy4j1MLVmyhD/84Q+kpaUxevRotcuxSAaDgfT0dBobG5k2bZps/z4CKIpCc3MztbW11NbWUl9fbwrZR4dJNze3cw5lD/wvg2/3lQOwIM6H22dGnPFtnGzEG+C7/eV8uvMIAE9cGMtdKYP7PNDV1dXnAKWxsdEUxkeNGoWXlxdeXl5D2v/b2tqKr68vJSUlptHX5cuX89xzz5GRkWG6Xk1NDeHh4WRlZck8mAFSXl5Oeno648ePJyTkzDaCEr96++23efzxx9m3bx+hoaFqlyMGgIx4D0PZ2dnce++9/Pe//5XQfZZ6enrYvXs33d3dzJo1S3rshqljg3ZdXR2KojBq1ChGjRpFVFTUgITsY6Xm15pCt7OdNdcmDXwwSQz1MAXvNZlVgx687ezs8PHxwcfn1/XHu7q6aGxspLa2lsOHD5ORkYGjo+OQBfE9e/YQHh7ep+UhOTmZgwcPotfrTb/X7777jpkzZ0roHkABAQHY2Niwa9cuurq6iIyMlHkBZ+Huu+9mw4YNXHPNNWzdulVan4YBCd7DTEdHB1dffTXXXnstv/3tb9UuxyL1Lo1lbW3NjBkz5IlumOns7KSqqorKysrjgnZ0dDRubm7H9WIPpG6dgWdW/bpD5XVTQnC2H/inYn83BwLdHShr7CD9SAM1LV14uwztAaSdnR2+vr6mdpWenh7q6+uPC+Le3t74+vri7e09oAc5FRUVx7XK+Pj4oNPpaGpqMgXyAwcOEBoayl133cWaNWtwc3PjT3/6EzfddNOA1TISeXt7M2PGDHbs2EFPTw9xcXESvs/CBx98wKRJk3jqqad4+eWX1S5HnCMJ3sPMI488AsCbb76pciWWqbu7m+3bt2NnZ8fkyZOlx3MYUBSFlpYWKisrqayspLGxEXd3d/z8/IYkaB/rg22F5Fe3AhDl40xKjPeg3VdSmAdleztQFNiQXcW1k9U95W9jY3PCIF5dXc2BAwfo6urC29sbPz8/fH19z3ljKp1Ox7HdlHq9HqBPAGxpaWH16tUsWbKEt99+m3379nH++ecTGhpKSkrKOdUw0rm7uzNz5ky2bduGoiiMGTNGwvcZcnZ25vPPP2f27Nmcd955nHfeeWqXJM6BBO9h5Oeff+bDDz+U5YfOUnd3N6mpqTg4ODB58uQhDWNiYBkMBurq6kxhuzfQhYaGkpycrNr/R3ljB/9enweARjOwEypPJCnUg5V7jS0tazPVD97HOjqIjx071nSAVFxczL59+0wHSH5+fri4uJxxYPP09KS2trbPZTU1Ndjb2/eZKO3l5cUFF1zAggULAJg4cSI33HADq1atkuA9AJydnZkxYwbbtm3DYDAwduxYCd9nKDExkSeeeIJbb72VzMxMXF1d1S5JnCUJ3sNEa2srt9xyC4888ghjx45VuxyL09XVRWpqKk5OTiQlJUnotkCKolBfX09paSllZWVYWVnh5+fHuHHjBryF4Ww9vzqL9m7jiOt5cb6Eew3uhN0Ib2fcHW1obO9hS14t7d06HG3N82lfo9Hg6uqKq6sr0dHRfVqCcnNzcXBwICgoiKCgoH5PdE5ISCAnJ4eGhgY8PDwASE1NJTk5uc//+JgxY8jPz+/zvVqtVgYwBpCzs3Ofke9x48ZJ+D5DTz75JN9++y0PPfQQ//3vf9UuR5wlWdVkmLj33nvZtWsXO3fuNIuAYUm6urrYtm0bLi4uJCYmSui2MC0tLZSUlFBWVkZPTw+BgYEEBQXh6elpVi/sW/JquPH9XQC42lvzz2sm4mx3biH4VKua9Hpvy2HWZ1cD8PYNiVww1vKWd9PpdFRWVlJaWkp1dTUeHh4EBQURGBh42uUKL7vsMgICAnj99ddpbGxk3rx5PPvss1x++eWm63R0dDB69GiWLFnCggULyMrKYv78+fz444+MHz9+kH+6kaW9vZ1t27bh4+PD+PHjzep/1BJkZ2eTlJTE8uXLOf/889UuR5wF8xz6EGdkw4YNfPzxxxK6z0Jve4mEbsvS0dFBWVkZpaWltLS04Ofnx9ixY/H19TXL32GXTs//rTxqQmVyyDmH7v5KCvMwBe+1mVUWGbytra1No91dXV2UlZVRUlLCgQMH8PX1JSgoCD8/vxM+/73//vvcfvvt+Pv74+TkxMMPP8zll1/O0qVL2b17N6+99hoODg58/fXX3HvvvdTU1ODt7c37778voXsQODo6mtpODhw4ICPfZyg2NpYnn3yS2267jUOHDsneEhZIRrwtXGtrK/Hx8dx222383//9n9rlWJTe0O3o6CjtJRZAURSqqqooKiqiurqaUaNGERQUZFq2zJy9uTGfl3/MASDa15n/uyR+QHq7+zPi3aM3cOcnaXT2GPBwtGH3Uwuwthoef+utra2mEN7V1UVwcDBhYWHS/2oB2tvb2bp1K/7+/tLzfYYMBgPTpk1j3LhxvPfee2qXI86QBG8Ld88997B7924Z7T5DPT09bNu2TSZSWoDOzk6Ki4spLi5GURRCQ0MJDQ0d0o1YzkVZYwcL/rmJjh49Gg28cMU4wkYNTG93f4I3wKvrctlZWA/A53dOZWrEqAG5f3OhKAoNDQ0UFRVRVlaGu7s7YWFhBAQEyPOiGWtra2Pr1q0EBQXJaidnqLfl5Ouvv2bhwoVqlyPOgLSaWLD169ezZMkSdu3aJS8uZ6Cnp4fU1FTs7e0ldJup3iB1+PBhKioq8PLyYty4cWbbSnIqz32bSUePcULl+WP8Bix0n4nEUA9T8F6bWTXsgrdGo8HT0xNPT0/Gjh1LSUkJubm5HDx4kNDQUMLDwy3mQG0kcXJyMrWdaDQaxowZo3ZJFuPolpPMzExpObEgMuJtoVpaWoiPj+eOO+7gmWeeUbsci6HX69mxYwcajYbk5GQ5YDEzBoOB0tJSDh8+TFtbGyEhIYSHh+Ps7Kx2aWdlY041t3y4GwA3Bxv+efUEnAawt7u/I96tXTru+iQNgwIhno5semTOsB9dVBSFmpoaCgsLqa6uxtfXl8jIyD67WArz0NLSwtatW4mKiiIyMlLtciyGwWBg+vTpxMfH8/7776tdjugnGfG2UA8//DC+vr489dRTapdiMRRFIT09HZ1Ox4wZMyR0mxGdTseRI0fIz89Hq9UyevRogoODsba23KeoLp2e/3fUDpXXJ4cMaOg+E8521sT5u3KovJkj9e3kVrUS4+eiSi1DRaPRmLawb2tro7CwkNTUVNzd3YmOjsbb23vYH3xYChcXF6ZNm8a2bduws7MjODhY7ZIsglar5eOPPyYpKYmrr76aCy64QO2SRD9Y7qvaCLZu3TqWLl0qLSZnQFEUDhw4QFNTE7NmzbLoQDec9PT0UFhYSEFBAQ4ODsTHxxMQEDAsAtF/Nx+mqK4dgBhfF2ZGeqlaT1KoB4fKmwFYc6hy2Afvozk5OTF27Fiio6MpLCxkz549ODg4EB0djb+//7D4e7N07u7uTJ48mV27dmFra2va3VScWkxMDE8++SS33367tJxYCGk1sTDNzc3Ex8dz55138vTTT6tdjsXIzc3l8OHDzJ49G0dHR7XLGfE6OzspKCigqKgINzc3oqKi8PHxGTYBqKS+nfP+tYnOHgPaXyZUhg5Cb3d/W00Aalq6+P3nGQCMD3Jj1f0zB7weS6HT6SguLqagoACtVktUVBTBwcEWN39gOCotLWXv3r1Mnz5d2oL6yWAwMGPGDOLi4vjggw/ULkechgz7WZiHH34YPz8/nnzySbVLsRjFxcXk5eUxc+ZMCd0q6+zsJDc3l+LiYry9vZk2bdqwfHF97rtMOnsMACyM9xuU0H2mvF3sCB3lSHFdO/tLm6hs6sTPzV7tslRhbW3N6NGjCQ8Pp7S0lLy8PLKzs4mKiiIsLEwCuIp612rfuXMnM2fOxMVl5JyZOVtarZaPPvrI1HJy4YUXql2SOAUJ3hZk27ZtLF26lD179kiLST9VVFRw4MABpk6dKqfgVNTT00N+fj4FBQX4+Pgwe/bsYfv7+Dm7mjWZVQC4O9hwVWKQyhX9KinUg+Jf2l/WZlVx49RQlStSl1arJSQkhODgYCoqKsjOzqagoIC4uDgCAwOHzRkYSzN69Gi6urrYvn07s2bNkhVp+iEmJoYnnniCu+66i+zsbBlkMmNyWG8hdDod99xzD/fccw9xcXFql2MR6urq2LNnDwkJCXh5qdtfO1Lp9Xry8/NZu3Yt9fX1TJ8+nSlTpgzb0N3Zo+f/fXvUhMqpoTjams/4RmLor2cX1hyqVLES86LRaAgICGDu3LlER0eTmZnJpk2bqK6uRrox1REXF4e3tzfbt2+np6dH7XIswmOPPYarqyt/+9vf1C5FnIIEbwvx1ltv0dTUxHPPPad2KRahubmZnTt3MnbsWAICAtQuZ8RRFIXi4mLWr19PaWkpiYmJI6Jn851Nh00jynH+LswYbV7rZYeNcsTL2RaAHYfraO6UQHM0jUZDaGgo8+fPJygoiLS0NFJTU2loaFC7tBFHo9EwYcIEHB0d2blzJ3q9Xu2SzJ6VlRX//ve/+cc//kF+fr7a5YiTkOBtAaqqqvjzn//Myy+/LKeP+qG9vZ3t27czevRowsLC1C5nRFEUhcrKSn7++Wdyc3MZM2YMKSkp+Pr6DvvT9kfq2nlzo/HFTquBW6eHm93PrNFoTKPePXqFTTk1KldknqysrIiMjOS8887D09OTbdu2sWvXLlpbW9UubUTRarUkJSWhKAppaWly9qEf5s2bxyWXXMIDDzwgj5eZkuBtAR599FGSkpK49tpr1S7F7Ol0Onbt2oWvry/R0dFqlzOitLa2smPHDjIyMggLCzONGppb+Bwsz353iC6dcULlhWP9CfY0z4PkpFAP08drf+lFFydmY2NDXFwcCxYswM7Ojo0bN5KZmYlOp1O7tBHD2tqa5ORkWlpayMzMVLsci/Dvf/+bHTt28O2336pdijgBCd5mLjU1lS+//JI333xT7VLMnqIoZGRkYG1tzfjx40dM4FObTqcjKyuLjRs34ujoyPz584mIiBhRK0Osy6xiXVY1AB6ONlyZYD4TKo8V6++Ck61xcvbPOdV0/3KwIE7O3t6eCRMmMGvWLOrq6tiwYQPl5eUyojhEbG1tSU5Opri4mJKSErXLMXt+fn48/vjjPPDAA3R0dKhdjjjGyHlltEB6vZ577rmHu+++m5iYGLXLMXu5ubk0NjYyefLkERX61KIoChUVFWzYsIGamhpmzpzJhAkTsLW1Vbu0IdXZo+cv3/06ofKGqaE42JrvqkPWWi0Tg90BaOnUsbOwTt2CLIibmxszZ84kNjaWffv2sX37dmk/GSIuLi4kJSWxb98+6bnvh4cffhgXFxeZaGmGJJ2YsbfeeovGxkb++te/ql2K2SsvLycvL48pU6ZgZ2endjnDXm9byd69e4mJiWHWrFm4u7urXZYq3tpYQEm9cVRpjL8r0yLMa0LliSSF/TrJVdpNzoxGoyEkJIQFCxbg7Ows7SdDyMfHh7i4OHbt2iUjuafRO9Hy73//OwUFBWqXI44iwdtMVVdXy4TKfmpqaiI9PZ2EhIRhu0yduTAYDGRnZ/dpKwkNDR2xbT3FdW28tcn4omal0XDbDPObUHkiE4LcsdYa61yXWSUtE2fBxsaG8ePH92k/qayUJRoHW0REBN7e3uzatUtWOjmNoydaCvMhwdtMPfrooyQmJsqEytPo3eEsKipKlg0cZE1NTWzatImKiooR21ZyNEVR+H+rDpl6pC8a50egh2Vs9OFga0V8gCsA5U2dHCpvVrkiy9XbfhITE8OePXtIT0+XdacHUe8ygxqNhr1798pB42m89tprbN++XSZamhEJ3mZo+/btfPHFFzKh8jQMBgO7d+/Gw8NDVjAZRL2j3Fu2bMHf35+UlJQR21ZytLWZVfz8y3J8nk62LDbjCZUnIpvpDJze9b/nzZtHV1cXGzZsoKpKWngGi5WVFVOmTKG2tlbWqz4Nf39/Hn30Ue6//35pzzETErzNjF6v5+6775YJlaehKAr79+9Hp9MxadIkizi9b4mOHeWOjY2ViatAR7eev3z769JmN04Nxd7GfCdUnkjiUcsKrpE+7wHh4ODA1KlTiY2NJS0tTUa/B5G9vT3Jycnk5OTIQc5pPProo7i4uPDiiy+qXYpAgrfZefvtt2VCZT8UFRVRUVHBlClTsLY2ny25hwsZ5T61NzfmU9ZoHD0aG+hGcrjl7cjp6WTLaG8nALIrWyipb1e5ouFBRr+Hjru7OxMnTiQtLY2Wlha1yzFbvRMtX375ZZloaQYkeJuRpqYmnn76aZ5//nmZUHkK9fX1HDp0iClTpsjjNAhaWlrYvHmzjHKfRGFtG+9sOgyAlVbDLdPDLPaMS1KorG4yWI4d/c7IyJCVTwZBUFAQ4eHh7Nq1Sx7fU5g3bx4XXXQRjz/+uNqljHjyampG/v73vxMeHs51112ndilmq7u7m7S0NGJjYxk1yvyXbbM0R44cYdOmTXh7e8so9wkoisL/rTpEt944ofLicf4EulvGhMoT6dtuIn3eA+3o0e+2tjY2bdpEc7NMZB1ocXFx2Nvbs3//frVLMWsvvfQSq1evZs+ePWqXMqJJ8DYTlZWV/Otf/+KFF16Q0cWT6N2Z0tXVldGjR6tdzrCi0+nYs2eP6UxCfHy8/B2ewE+Hqtica5xQOcrJlismBapc0bkJ8nDAz9UegN1FDTS2d6tc0fDk4ODA9OnTCQwMZPPmzRQVFclqHANIo9GQkJBAVVUVR44cUbscsxUZGcl1113Ho48+qnYpI5q8spqJZ599luTkZBYuXKh2KWarsLCQxsZGEhISLPbUvjnqnUDZ2dnJnDlz8PHxUbsks9TerePZb3/dofKmaWEWN6HyWBqNxjTqrTcobMiuVrmi4Uur1RIbG0tycjLZ2dns2bNHJl4OIAcHBxISEti/f7/0e5/C888/z+7du1m3bp3apYxYErzNQH5+Pu+//z4vv/yy2qWYrcbGRjIzM0lKShrRa0cPJEVRKCwsZMuWLQQFBTF9+nQcHCy3bWKwvbEhn/KmTgDGB7kxOczjNN9hGZKOajeRPu/B5+3tzZw5c+ju7mbjxo2y/fkA8vX1JTw8nLS0NNlc5yR8fX25++67efTRRzEYDGqXMyJJ8DYDTz31FBdddBFJSUlql2KWenp6SEtLIzo6Wvq6B0jvY5qTk8PUqVOJiYmRswinUFDTyn+3GCdUWlv4hMpjRfu64GJvXBloU24NnT0SWAabvb0906ZNIzQ0lG3btlFQUCCtJwMkLi4OKysrDh48qHYpZuuZZ56hrKyMr776Su1SRiQJ3ipLT09n1apVMtp9EoqisG/fPhwdHYmKilK7nGGhtbWVzZs309PTw9y5c/Hy8lK7JLPWu0Nlj94YjBaND8DfbficGdBqNSSEGEe927v1pBbUqlzRyKDRaIiOjmbatGnk5+eTnp4uo7QDQKvVkpSURFlZGWVlZWqXY5acnZ3505/+xBNPPCHtTiqQ4K2yxx9/nN/+9rcSKk/iyJEj1NbWSl/3AKmurmbz5s34+fkxbdo07Ozs1C7J7P1wsJItecYw6uVsy+WTAlSuaOBJu4l6Ro0aRUpKCm1tbWzdulV2FxwAjo6OTJo0ib1799LW1qZ2OWbpj3/8I3q9ng8++EDtUkYcCd4q+vnnn9m+fTsvvPCC2qWYpebmZg4cOEBCQgL29vZql2PRFEWhoKCAXbt2MW7cOOLj4+VAph/aunQ8992vO1TeNC0MO2vLnlB5IuOC3LC1Mr4crM2sxmCQtoehZG9vz4wZM3BxcWHTpk3U19erXZLF8/f3Jzg4mN27d8uZhBOwtbXlqaee4v/+7/9ob5fNs4aSBG+VKIrCo48+yu9+9zv8/PzULsfs6HQ6du/ezejRo2WVjXOk1+vZu3cveXl5TJ8+neDgYLVLshivb8in4pcJlROD3fuMDA8ndtZWjAtyA6C2tYuMkkZ1CxqBrKysmDRpElFRUaSmplJSUqJ2SRYvPj4egMzMzNNcc2S6/fbb8fLy4tVXX1W7lBFFgrdKli9fTmFhIf/3f/+ndilmKSsrC1tbW2JiYtQuxaJ1dnaybds2mpubSUlJwdPT8rY2V0t+dQvv/TKh0sZqeE2oPBFpN1GfRqNh9OjRTJkyhQMHDnDo0CGZdHkOrKysSEpKori4mJqaGrXLMTtarZbnnnuOl156Sc6yDCEJ3irQ6XQ88cQTPPjgg7i5ualdjtmpra2luLiYSZMmySYu56B3fW4nJydmzpwpSwWeAUVReGblIXS/tFxcMiEAX9fh3e6UEOJB73HFWtnFUlU+Pj7Mnj2byspKduzYIRPgzoGzszNjxoxh7969sqX8CVxxxRXEx8dLy+sQklSjgg8//JCuri4eeeQRtUsxOzqdjoyMDOLi4nB2dla7HItVU1PD1q1bCQsLIyEhASur4deXPJi+219BakEdAN7Odlw2wbJ3qOwPVwcbon1cACioaaOgplXlikY2Z2dnZs+ejaIobNu2ja6uLrVLsljh4eE4ODhw6NCh0195BHrxxRf5z3/+I+1NQ0SC9xDr7u7m//2//8fjjz8uK0qcQGZmJvb29kRERKhdisUqKytj586djBs3TtbnPgutXTr+uvrXntCbp4dhaz0yniqTwqTdxJzY2NgwdepUnJ2d2bJli6zQcZY0Gg2TJk2ipKREWk5OYPbs2aSkpPDcc8+pXcqIMDJeTczIJ598go2NDXfeeafapZid2tpajhw5wqRJkyQsnqXCwkIyMjJISkoiJCRE7XIs0r/X51HVbBxdTAhxN22pPhIkSp+32dFqtSQmJuLr68uWLVtoampSuySL5OTkxJgxY8jIyJDWnRP4y1/+wpIlSygvL1e7lGFPgvcQ0uv1/O1vf+O+++6TU//HkBaTc6MoCllZWWRlZTF9+nRZKecs5Va18MHWQsA4ofKmaWHqFjTE/N0cCHQ3zgVIP9JATYu0N5gDjUbD2LFjGT16NFu3bpVR27MUHh6Ok5OTrHJyAsnJyUydOpVXXnlF7VKGPQneQ2j58uW0trbywAMPqF2K2cnMzMTBwUFaTM6CwWBg3759HDlyhJkzZ8rKJWfJOKHyoGlC5WUTA4f9hMoT6W03URTYkC2j3uZCo9EQFRXF2LFj2blzp4xMngWNRsPEiROl5eQknnjiCd5++20aGhrULmVYk+A9RBRF4fnnn+fOO++UzWCO0dtiMnHiRGkxOUN6vZ7du3dTX1/P7NmzcXV1Vbski7VqXzk7DhuX1PJxseOS8cNvh8r+OHpZwTWHJHibm9DQUJKSkkhPT6ewsFDtciyOk5MT8fHx0nJyAgsXLiQ2NpbXX39d7VKGNQneQ2TNmjUUFxfz8MMPq12KWZEWk7On1+vZtWsXXV1dslzgOWrp7OGvq7NMn4+kCZXHivB2xt3RBoCt+bW0d8sSbObGz8+P6dOnk5WVRUFBgdrlWJywsDBpOTmJRx99lFdffVUm8g6ikfnKooLnn3+em2++WUYkjyEtJmdHp9Oxc+dOdDod06ZNw9bWVu2SLNqr6/JM/cxJoR4khIycCZXH0mo0JP7y83fpDGzOrVW5InEinp6eTJs2jZycHPLz89Uux6Ic3XJSXV2tdjlm5aqrrsLPz4/33ntP7VKGLQneQ2D79u3s2bOHJ554Qu1SzEpDQ4O0mJyF3tBtMBiYNm0aNjY2apdk0bIrm/kotQjonVAZqm5BZkCWFbQMHh4eTJ8+ndzcXHJzc9Uux6L0rnKyf/9+9Hq92uWYDa1Wyx//+Edefvlluru71S5nWJLgPQSef/55rr32Wnx9fdUuxWwoisL+/fuJjIyUFpMz0Bu6AaZOnYq1tbXKFVk2RVF4ZsUh9L9MqLx8YiDeLjIHIz7ADXsb48vDhuwqdHqDyhWJk3F3d2fGjBkUFBRI+D5D4eHhWFtbyxmDY9x2223Y2NiwdOlStUsZliR4D7KDBw+ybt06nn76abVLMSvFxcV0d3cTFRWldikWQ6/Xs3PnThRFITk5WUL3AFixt4xdRcYJlX6u9iwaoRMqj2VjpWVCkDsADe09pBXLKgfmzM3NjenTp5Ofny8h8gxoNBrGjx9PXl4e7e3tapdjNqysrLjvvvv429/+JmcDBoEE70H2wgsvcOmllxIeHq52KWaju7ubzMxMxo0bJ+uZ91Nv6DYYDDLSPUCaO3t4fnW26fORPKHyRJLCfl2WUtpNzF9v+M7NzZUJl2fA09OTwMBADhw4oHYpZuWBBx6gpaWFb775Ru1Shh15lRlEhYWFfP311zzzzDNql2JWMjMz8fT0lE1e+slgMJCWloZOp5PQPYBeWZNLbatxQuWUME8mBrurW5CZmRjsjvaXqRdrM6tQFEXdgsRpubu7M23aNLKzsykqKlK7HIsxZswY6urqqKqSA8xe9vb2/O53v+P555+X//0BJsF7EL388svMnz+fsWPHql2K2WhoaKC0tJRx48apXYpFUBSFffv20dbWxtSpU2Ui5QDJLG9myfYiAGyttNwoEyqP42xnTZy/cRWmI/Xt5Fa1qlyR6A8PDw+mTp3KwYMHZZOdfrKzsyMuLo4DBw5Ia8VRHn74YYqKili7dq3apQwrErwHSWVlJR9++KH0dh/l6AmVTk5OapdjEbKysqipqZElAweQwWDcofKX+ZRckRCIl7OdukWZqb6b6VQO2v10dHRw5513EhoaSlBQEI8++ugpR9na2trw9vbmxRdfHLSaLNmoUaNITEwkPT2d2lpZDrI/wsLCZKLlMdzc3Ljpppt4/vnn1S5lWJHgPUjefPNNkpKSmDZtmtqlmA2ZUHlmCgoKKC4uZtq0abI5zgBanlFmmizo72bPxeP8Va7IfCWGHtXnnTV4p+EfeughDAYDBQUFHDp0iJ9//pk33njjpNf/z3/+I9tan4a/vz/jxo1j586dNDc3q12O2ZOJlif25JNPsmvXLtLT09UuZdjQKNK8M+C6u7sJCgritdde47e//a3a5ZiF7u5u1q1bR0JCgvR290NpaSl79+5l+vTpeHp6nv4bRL80dfQw7x8bqWszrk/7xIWxjP9l9Q5zoBj06Hu6Meh+eTvqY8Vg+GUUWAFFQVEUetqaALBxckOj0YIGQINGo0VjZYXW2hYrG1u01r+82diitbYxXrefHl++n+I6YxDZ8cR8/NwGdrnF1tZWfH19KSkpMf2tL1++nOeee46MjIzjrl9eXs7cuXMZO3YskydP5vHHHx/QeoabnJwcCgsLmT17No6OjmqXY/Z6t5KfMmWK2qWYjauuugoXFxc+/PBDtUsZFmSW1iD46quvcHBw4JprrlG7FLMhEyr7r7q6mr179zJ58mQJ3QPslTU5ptCdHO455KHboNej62xF19mGvrvruICtGPSg0ZiCcm9otrJ1QKO1Ao0GY7DWmK7X1VSDnesoNBrtUcHcgEGvx9DTja6jFYOuG31PN4q+BwCNlc1RgdwGrY0dVrb22Dg4Y2Xn2GdDq6RQD1PwXptVxY1TB7Yffs+ePYSHh/f5W09OTubgwYPo9frjVj568MEHefLJJ/n5558HtI7hKjo6mq6uLlJTU5k1axZ2dtJWdSpjxoxh/fr1VFVVyd4bv3jooYeYO3cu//jHPxg1apTa5Vg8Cd6D4LXXXuOmm26SpfJ+0dTURGlpKXPnzlW7FLPX2NjI7t27mTBhgjzpD7CDZU18sqMYADtr7YAHyGMZ9Dp0nW3oOlrp6WhF19mKvqsDrbUN1vbOWNnaY23viNbavU/I1lhZ93snVzvXUXQ11WDv7oPW6vRP54piwKDr6TOS3jvC3tPWREu5cRk6a3snbBycsXZwZqK/A1//8v1rDlUO+ONWUVFx3N+6j48POp2OpqamPoH8s88+o66ujptuukmCdz9pNBrGjRtHWloaO3bsYMaMGbIy0inY2dkRGxvLgQMH8Pb2RquVjtxp06YxduxY/vvf/8oZpgEg/30DLC0tjQMHDrB69Wq1SzEbmZmZhIWFyYTK0+jo6GDHjh1ER0cTHBysdjnDisGg8PRREyoXJwQxagAnVJpGsntDdkcr+u4OtNa2WDs4Y+PgjL2bN9YOTljZqDfiqNFosbKxO2kNiqKg7+pA12n8OTobqnDtaMPDFhq6NWwvqOVQ7mGCfEfh6ura7wOEU9HpdMdNpOxdWeLo2y8sLOSpp55i8+bNA3K/I4lGoyEhIYEdO3awZ88epkyZIo/hKYSFhXH48GGOHDlCWFiY2uWYhbvuuotnn32WRx55RAYVz5EE7wH2+uuvc8kll+Dl5aV2KWahtraW+vp6EhMT1S7FrOn1enbt2oWvry+RkZFqlzPsfLWnlIwjjQAEuNtz0dhzb3nSd3fR1VJPd0s93W2NaK1sfg3Z7t7GUW0by1qJRqPRYG3viLW9I/buPoAxjCfV57M2uw6dAX7YW0ScUxZarRZfX1/8/Pzw8fE561FUT0/P41beqKmpwd7eHjc3N8B4ULp48WJeeuklOSg9S1ZWVkyePJnNmzeTnZ1NXFyc2iWZLa1Wa1peMCgoSM4QADfffDNPP/003333HZdddpna5Vg0+WsaQLW1tSxbtoxNmzapXYpZUBSFQ4cOERkZKUvhnYKiKOzduxetVsv48eNlJGqANbZ38+KPv+5Qeev0cKytzvz0saIo6Drb6Gquo7ulHl1nGzaOrti5jsLZPwJru+G58oxGo2FKhA9rs+sAOKL34E8XzqGhoYHKykqysrLYs2cPXl5e+Pn54efnd0ar8CQkJJCTk0NDQwMeHsblC1NTU0lOTjad5l+/fj3Z2dnceeed3HnnnQC0t7djZWXF+vXrZZ3hfrK1tWXKlCls2bIFV1dXAgMD1S7JbAUEBJCfn8/hw4eJjo5WuxzV2dract111/Haa69J8D5HErwH0Pvvv8/YsWNJTk5WuxSzUFFRQUdHB6NHj1a7FLOWn59PbW0tKSkpcgpvEPxjTQ71v0yonBYxirGBbv3+XsVgoLutka5m48i2YtBj6+yBo1cgts4eaK1HxoZGsf4uONla0dat5+fsanQG41rRo0aNIj4+npaWFqqqqigrK+PAgQO4urqaQribm9spDyb9/Py44IILePLJJ3n99ddpbGzk+eef59lnnzVdZ9GiRXR0dPT5vltuuYXY2FjpOT1Drq6uJCYmkpaWhpOTE+7u7mqXZJY0Gg1jxoxh165dhIWFyeAR8Kc//YmIiAhycnKIiYlRuxyLJbMGBojBYOCdd97hjjvuULsUs2AwGMjKyiImJkZO051CZWUlOTk5JCcnY28/sMu0CThQ2sSnO48AxgmVN/RjYqCiGOhsqqXpSBY1WTtoKS9Ao9HgGhSNV2wybiGxxsmMIyR0A1hrtUwMMY5Gt3Tp2FlY1+frLi4uREZGMnPmTC644AJGjx5NS0sL27ZtY82aNezfv5/GxsaT3v77779PeXk5/v7+JCUlceedd3L55ZezdOlS/vCHPwzmjzYi+fn5ER0dza5du+js7FS7HLPl7e2Nh4cHeXl5apdiFoKCgpg/fz7vvPOO2qVYNFnHe4CsXbuW3/zmN5SVlUmAwrhZTl5eHvPmzZNZ4SfR0tLC5s2bmThxopzyHQQGg8IVb6Wyr6QRgOuTQ1g0PuCk19d1ddDZUEVnYxVotDh4+GLnOuq45fXMiUGvozZrB15xU/u1qsm52HG4jtfWGwPITdNCefaysaf9Hr1eT11dHWVlZZSVleHs7GzandLGZuQcuJgjRVHYs2cPHR0dTJ8+Xc62nURjYyNbt25l/vz5spEZsHLlSm655RYqKiok65wlSUQD5M0332Tx4sXyh4jxxTY7O5vY2FgJ3SfR3d3Nzp07iYiIkNA9SL5IKzGF7kB3By44wYRK4+h2DQ2FB6jPT0ff3YFLYDSjopNw8gnB2t7JbEP3UJsQ5I611vhYrM2sOuWW7r2srKzw8fFh0qRJLFy4kLCwMI4cOcJPP/1ERkaG7D6pIo1Gw6RJk9Dr9ezfv79fv8+RyN3dHV9fX3JyctQuxSxccskluLu789VXX6ldisWSVDQAysvLWb16tZwS/cXhw4exs7OTQHkSiqKQnp6Oi4sLsbGxapczLDW0dfPSURMqb5sRhvVRB4EGXQ9t1SXU5aTRWlmMrbMHXjGTcQuJw87FQ8L2CTjYWhEf4ApARVMnB8vObBtyGxsbwsLCSElJYdasWWi1WrZt28bmzZspLS3FYDAMRtniFKysrEhOTqaqqoojR46oXY7ZiouLo6SkhJaWFrVLUZ1Wq+X666/nzTffVLsUiyXBewC8//77TJ48mbFjT3/qdbjr6ekhLy+PMWPGSHg5icOHD9Pc3MykSZPkMRokL/+UQ0O7cZfGGaNHMSbAOKFS19lGc1ketTm76W5rxCVgNKOiE3HyDkJrLZOnTicp7NfNbNZmVp717bi5uTFhwgQWLlxIYGAgWVlZrF27ltzcXLq6ugaiVNFPDg4OJCQkcODAAZqbz+xgaqRwdnYmJCSErKwstUsxC/fffz/p6ekcPHhQ7VIskgTvc6TX63n33Xe5/fbb1S7FLOTl5eHm5oa3t7fapZilhoYGsrKySEpKklnyg2RvSSOf7zaO3jnYWHFdcii6zjYaiw9RX7APAM/RE/AIH/fLVuty8NNfCb9MsARYk1l1zrdnY2PD6NGjWbBgAePHj6empoa1a9dy6NAhuru7z/n2Rf/4+PgwevRo0tLS0Ol0apdjlmJiYqiurqa+vl7tUlTn5+fHeeedx9tvv612KRZJgvc52rBhA52dndxwww1ql6K67u5uDh8+TFxcnISZE+jp6SEtLY2YmJg+22CLgaM3KDyz8iC97aqLJ/hi3VBIfcE+rGwd8IqZjGtgFNb2sovq2fB0smW0t/Gxy65soaS+fUBuV6PR4O/vz4wZM5g5cyZNTU2sW7eO3NxcCYJDJCYmBhsbGw4cOKB2KWbJ3t7etJSegLvvvpulS5fKAfJZkOB9jj755BMuuugiGb3E2ELh4eEhofIEejfJcXZ2lp0pB9Hnu4+wv7QJgAAXKxKtSwENo6IScPGPGFFLAA6WpNBf/78HYtT7WO7u7kyfPp3JkydTUVHB+vXrKSoqkh7wQabVaklKSqKyspKSkhK1yzFLo0ePpq6ujqamJrVLUd2FF16Ik5MTP/zwg9qlWBwJ3uegvb2d5cuXc+utt6pdiup0Op3s8HUKRUVF1NfXk5CQIGcDBkl9WzcvHzWh8jcxdnhHTcA1KBorW1ltaKAkhf3abnIufd6n4+3tzezZsxk3bhz5+fls2LCB8vJyWX1jEDk4ODBp0iT2799Pa2ur2uWYHTs7O0JCQmRdb4wHapdccglLlixRuxSLI8H7HHz77bemF4eRrqioCCcnJ7y8vNQuxew0NTVx6NAhEhMTsbOzU7ucYUmv1/PnL3fT1GFsS5ge5sbkSeOlpWQQBLo74OdqPJDZXdRAY/vgnWrWaDQEBAQwb948IiMj2b9/P5s3b6ampmbQ7nOk8/PzIzQ0lLS0NPR6vdrlmJ3IyEgqKirkwAS44447+O677+QMwBmyuOC9b9++fl2vrKyMoqKifl23tbWVioqK4y6vrq7mp59+4vPPP2fZsmWsWbOG2tpa09eXLFnC5ZdfPuLXqtbr9RQUFBAVFSWjucfQ6/WkpaURGRkpByWDQFEUSkpK+O836/g+uxEwTqi8ccZodQsbxjQaDYmhxlFvvUFhQ3b1oN+nVqslLCyMBQsW4O/vz65du0hNTZUX/EHSuypVZmam2qWYHUdHRwICAsjPz1e7lAGzY8eOs2rlSkpKYvTo0Xz99denvF5HR0e/25fy8/Opqup/C1tRUVG/+8zP5ExFQUHBcY+JXq8nPT2d5cuX89lnn/HNN9+QkZFxxo+dWe7l/dlnn9He3k5jYyNOTk7Y2NiQkJBAQkIC27dvZ8KECabrvv3229x9992AcZvy3ok4FRUV6HQ6wsLCAMjOzqayspI5c+YAxt2ofvzxR37zm99QW1tLbm4u/v7+ptutq6vjm2++4cILL8Tf3x9FUSgvL+err77iN7/5DTqdjrVr1/Lyyy8PzYNixkpLS7G2tu7z+AmjrKwsbGxsiImJUbuUYae9vZ29e/fS1NzM10U2gPF//5qkINwdZc7FYEoK9WD1AeNgxZpDVSxOCBqS+7W2tiY6OpqwsDDy8vLYsmULERERxMTEyM6LA0ir1ZKYmMjGjRsJCAhg1KhRapdkVqKioti0aRMxMTEWuZtlW1sb//vf/0yfl5WVkZGRYdpNdt68eURERACQnp5Oenr6cbdRU1PDww8/zBVXXMGSJUu47bbbAGMQzs7O5oILLjBdt6mpiT179hAcHAwY89fRG/C0tLQwbdo0pk6dSmlpKX5+fvj6+gLGRRv++c9/mlZK02q13Hbbbbz77rvceeed7NixgwsuuMA0z667u5vVq1dTW1uLRqPhkksuMd3W+vXriYqKMt3v0fkRYMWKFUydOhU/Pz+2bNlCcHBwn/l7q1evxsXFhQULFuDk5ERbWxs7d+7kxx9/5KKLLur342+Wwfu6664D4IsvviAxMZHRo/s3elVSUsK2bdsAaG5uZuLEiWddQ319PUFBQYSEhJguCwsLw9/fn4aGBn744QfGjBlDfHz8Wd/HcKAoCnl5eURHR8to9zHq6+spKioiJSVFHpsBpCgKxcXFHDp0iMDAQHINvuTVGnu7QzwdOW/M8TtUioEV7euCi701LZ06NufV0Nmjx95m6IKvra0t8fHxBAcHk56eTmVlJZMmTcLDw+P03yz6xdnZmbi4ODIyMpgzZw7W1mYZF1Th6uqKj48PBQUFFrl/h5OTE3fccQc6nY7169djMBhwdHTk8ssvx9nZuc91ewc9j/X++++j0Wi44447ePnllyktLSUoKAhFUU47D8Pd3Z077rjD9PnXX3/dJ2sdy9/fn1tuuaVfP9vmzZsJCgriiiuuoKamhq+++oq4uDgAOjs7+3UbJ1NdXc38+fNxcjK2MLq6ujJ58mRWrFhxRrdjtv9JHR0dtLS0cODAgT7Bu6uri/fee++EfwxBQUFcfvnlABw8ePC44f+mpibT7lyn688aPXo0OTk5fP3113h5eaEoCtXV1Tg7OxMaGsrHH3/MlVdeOQA/qWUrLy/HYDAQFDQ0I16WoveUVExMDC4uLmqXM2z0jnK3tLQwefJktI5u3PSPjaav3zojDCutHOQMNq1WQ0KIB5tya2jv1pNaUMu8WN8hr8PV1ZXZs2eTl5fHtm3bZPR7gEVERFBeXk5WVhbjxo1TuxyzEhUVRWpqKtHR0Ra3qlleXh5ZWVk0NTUxZswYzj//fAoLC1m5ciXW1taEh4czZcqUU96GwWDAysqK8PBwEhMT+d///scjjzxCa2vrGfW/NzQ00NjYSEBAgOmy7u5uurq6zmpO1OHDh02h3tvbG29vb9zd3fH09OTQoUPHXf/oHVvb2tpOedvnn38+y5cvx8fHB0dHR9ra2qiqqmLBggVnVKNZBm+DwcDq1au54IILKC4uZuvWrcycORMwzio++kjpaGVlZaSmpgLGkH10SwoYRyB7+7JOd+Sj1WpZtGgR3d3dpt28XF1dsbW15fDhw6Snp5/xUc5woygKubm5REZGjvg+92NlZWVha2srSwcOEEVROHLkCAcPHiQgIIDJkydjY2PDI1/uo7nT2GIyO8qLWD9XlSsdOZJCjcEbYG1mlSrBG4zP1TExMfj5+ZGRkUFlZSUJCQm4u7urUs9wotFomDRpEhs3bsTf31/mqRzF09MTDw8PDh8+TGxsrNrlnJHAwEB8fX1xdf31+TIiIoKIiAg6Ojr6tXusoiimM7nXXnstH3zwAY888gilpaWmAbnT5YLOzk6WL1/epy0FIDU1lby8vNMObh48eJCWlpY+l2k0mj736+7ubtp59EQH5Ef36h97W8cKCQnhxhtvpLm5mY6ODhwcHPo8hv1ldsG7s7OTZcuWMXHiRAIDAwkMDGTnzp1s2bKFWbNmnfB7DAYDiqLg4+PDwoULsbW1JS8v77hwHR4eflyP94l89dVXtLa2oigK7e3tptMKra2tODk58e233zJp0qQR39NcXV1NZ2fnKU8RjUR1dXXSYjKAOjo62Lt3L83NzSQlJZn69fYU1/PlnlIAHG2t+O0U+TscSuOC3LC10tKtN7A2s5rnL1fQqni2wc3NzTT6vXXrVkaPHk1MTIwMCpyjo1tO5s6dKy0nR4mKijJNnreUx6WiooLVq1f3uay6uhofH58+l02ePJndu3ef9Hbq6+t57733iIuL4+abb+bJJ59kz549lJeXM2HCBPbt28ekSZNO+f1ff/01c+bMITAwsM/X5syZ06+DmebmZnp6ek55nd6AfDLz5s3rc3snkp+fz9atW023Z2tri5WVFTqdjp6eHtPtp6SkEB4eftq6ze4vxd7enkWLFvWZzJGcnGz6uHeyZC8HBwc++eQTrKyssLGxMa1Dei6uuuoquru7qa6uZu3atSxatAiAb775hvPOO48XXniBhx566JzuYzjIy8tj9OjRFvOEMxR0Oh0ZGRnExsZKi8k5OnaUOykpyTT5R6c38PSKX08bXpsULBMqh5idtRXjg9xIK26gtrWLjJJG02onajnR6PekSZNk9PscRUREUFFRQWZmJuPHj1e7HLPh7e2Nk5MTxcXF/Z6LpjZ/f3/uuOMOqqurTS0h33//PSkpKVhZWWFtbW0aTDu2a+BUUlJS+Otf/8o///lPQkJC+PjjjwkKCjJNijzarl272LdvHxdddNFxoftMTJ8+vU+rCICHhwdlZWUEBgbS09NDYWEhDQ0NaLXa07aSnExkZCSRkZE0NjayYcMGoqOj8fPzo6ysjMLCQubOnYubm1u/b88sE9OoUaPo6elhw4YNlJaWotVq0Wg02Nramkase9188820tbWZRqV71dXVHXe7Bw8epLLSuOFDT0+P6UX8RNrb2ykvLyc+Pp7Dhw8Dxj/C999/n/Ly8hG/RXxvX9bRB0XCuHqOra2txTwJm6uuri7S09OPG+XutXRHMZkVxtGJsFGOLIhTp81hpEsM9SCtuAEwtpuoHbx7HTv6HRkZSUxMjJyBOksajYaJEyeaVjmRlhMjjUZDVFQUBw8eJCIiwqL+vtra2mhsbASMAba3zWLnzp3cc889puuVlJSg1WpPGZAVRSExMZH33nuPsLAwtFotixcv5vPPPzctlnG0cePGkZiYSENDQ79qbWxsZOPGjRgMBrq7u085Gj537ly++eYbRo8eTWFhITNnzjTNB3z77bePu/7nn39u+riiooKpU6ee9LbLysoICgqivb3dlAv9/Pz4+uuvTau69IdZBm8wLvvi4eHBwoULTZc1NDTw6aefcs899/Tp1fnkk0/6LAkDHLeiSXR0tGl5nF6nOgXZ2tpKdnb2cZdv2LCBlJSU42b+jjSFhYUEBwef8uBlpGlsbJQWkwHQ1NTEzp078fDwYN68ecf9jdW0dPHPNbmmz2+dEa5qi8NIlhDigUYDimLcxfLxC82n1/Xo0e/du3fT1NREQkKCPGedpd6Wk3379jF37lxp4fmFn58fBw4coLKy0qLaT4uLi03h8Wi9SzL3qqiowNra+pTBW6PRcNddd/Hmm2+yZcsWUlJS8PDw4NZbb8Xe3p6Ojo4+13dwcKCzs5PvvvvuuNVKjh1ctba2ZtGiRWi1WqysrLCzszvl6kWjRo3ipptuoqKi4rRnu26//fbjVmA51fNDUVHRcYO6Z7OTrtkG76Mb93udS5jRarVnNPO4vb2dkJCQPn8EOp2Ohx9+mLfeeuus6xgOurq6KCsrIyUlRe1SzIaiKOzfv5+IiAhpMTkH5eXlpKenExUVddIlKv/2QxYtXcYXhznR3kT7yuOtFlcHG6J9XMipaqGgpo2CmlZGe5vXoETv6HdaWhpbtmwhOTn5uDOkon/Cw8M5cuSIacM0YcwW4eHhFBYWWlTwrq2t5fLLL8fT03NAbi8kJIQLLriApUuXmrKBvb39Od+uVqs940UKbG1tCQ0NPe31zvQgvKysjDvvvPOMvudEzDZ4z58/n3Xr1vHBBx+YRretra254oorjpuZ2tvkfyxPT08WL1581jXs3bu3z+6XmZmZ9PT09Fn2ZiQqLi7G09PzrGbzDlclJSV0dnYSHR2tdikWSVEUcnJyKCgoIDEx8aQvYLsK61meXgaAk0yoNAtJYR7kVBlPU6/NrGJ0inkFbzC+EE+dOpXMzEw2bdrE5MmTT9h7Kk5Nq9Uybtw4duzYQVBQkEVuHjMYQkNDycnJoaWlxaIGXr788ssTrvRxzTXX9Hl937p16wk30bniiiv6zMe7+eab+c1vfsObb77Zr1BbUVFxwuwWExNz0sU01PbRRx+d8PLrr7++30Feo5zNOPkI9cADD1BUVMQHH3zAqFGjRuSpNoPBwLp16xg7duyIPwDp1dPTw7p165gwYYI8JmdBp9ORnp5OU1MTycnJJz2g0+kNLHp9K9mVxpB324ywEb9ZjkGvozZrB15xU9FaqTOOUtnUyR+/2AsYe76/vme6KnX0V3FxMQcOHCA+Pp6wsDBpCzsLe/bsQVEUkpKS1C7FbKSnp2NtbT1iJ5/29PRQVlZGQkICy5cvP65lRPxq5CXHs6QoCqtWrSIlJYU9e/bw008/sXfvXqqrq4/bqGc4652c6uc3sgPP0bKysnBzc7Oo04zmor29nS1bttDT08Ps2bNPeRZlyfZiU+gO93JivkrrRou+/NzsCXQ3jnymH2mgpuX0awCrKTQ0lOnTp5OTk8P+/ftH1PP3QImPj6eqqoqamhq1SzEbvW04p1vebjjp7u6muLiYHTt28OOPP1JYWMj06dNZuXKl2qWZNQne/XTo0CGqq6u5++67WbhwoXHXPK2WjIwMfvzxR9LT06moqECv16td6qAqKioyzVoWv+6GOn78eBk5O0N1dXVs2rQJT09Ppk2bdspdyqqbO/nXWuOESg1wm0yoNCtJYcbJTooCG7KrVK7m9Dw9PUlJSaGhoYHU1NR+bRgifmVvb09sbKwcuBzFw8MDFxcXSktL1S5lUHV2dlJYWEhqaio//vgjRUVFeHp6MnfuXObOnctVV13FypUrz2rS4Ugh6amfvv32W6ZOnYqzszMajQYvLy/Gjx/P+eefz9SpU7G1teXgwYP88MMPpKWlUV5eftzsYEvX1tZGXV2dbJjzi6MnVI70VW7OVFFREdu3byc2NpYJEyac9kDuhe9/nVA5N9aHSB95vM1JUuivE7TWHDL/4A3GlRVmzpyJnZ0dmzZtoqmpSe2SLEp4eDgajYaCggK1SzEbYWFhFBUVDbvQ2dHRQUFBAVu3bmXNmjWUlpbi6+vLggULSElJITo62vQauHjxYsrLy0+4KpwwMtvJlebmm2++4aqrrjruco1Gg6enJ56ensTHx9PU1ER5eTmZmZmkp6fj4+NDQEAAvr6+Fr+MVVFREX5+fgMyU3k4KCkpoaOjQyZUngFFUcjMzOTIkSNMnTq1X+sB7zhcx4q95QA421lz7eTgwS5TnKEIbyfcHW1obO9ha34t7d06HG3N/+XF2tqapKQkcnNz2bJlC1OmTDluBz9xYlqtlvHjx8tEy6MEBgZy8OBBGhoaBmy1ELW0tbVRXl5ORUUFjY2NjBo1ioCAABITE0/5u3Z1dWXKlCl8++23xMXFDWHFlsP8nxnNQFVVFenp6Xz55ZenvJ5Go8Hd3R13d3fi4uJoaWmhvLycvLw8MjIy8Pb2xt/fH39//zNa2tAcGAwGjhw5QmJiotqlmAW9Xk92djZjxoyRnTv7SVEU03q3s2bN6tdZgh69gWdWHjR9/pvJwbjaW/YB7HCk1WhIDPFgfXY1XToDm3NruWCsZcwD0Wg0xMTE4OTkxK5du0hKSpI5LP3k5eWFr68vOTk5x+2dMRJZW1sTHBxsar+wNL2ZpaKigubmZry9vQkJCSE5OfmUrYDHuvDCC/nmm2949NFHB7FayyWJoR9Wr17NmDFj+rUuZC+NRoOrqyuurq7ExsbS2tpKeXk5hYWF7Nu3Dy8vLwICAixmBLmiogIbGxtZgusXhYWF2NrantN2tyOJoijs27ePmpoaZs6ciaOjY7++7+PUInKrjNsaj/Z2Ym6MjEaaq6QwY/AG47KClhK8ewUFBaHVaklLSyMhIUFWKOqnuLg4fv75Z0aPHm1RS+kNlrCwMDZv3szYsWPNfoBNURSam5tNYbutrQ0fHx8iIiLw8/M76/p/85vf8PTTT1NTUyOZ4QQkePfDihUrWLBgwTndhrOzM9HR0URHR5u2oy8pKWH//v14enri7+9PQECA2Z6uKy4uJjQ0VCYQYlw2KTc3l6SkJHk8+sFgMJCRkUFDQwMzZ87s99941TETKmWHSvMWH+CGvY2Wzh4D67Or0OkNWFtZ1jSigIAAU/g2GAwEBQWpXZLZc3Z2JiQkhOzsbCZPnqx2OarrHXArKysjPDxc7XKOoygKjY2NprDd2dmJr68v0dHRA9YSGx4eTmxsLN9//z0333zzAFQ9vEjwPo2Ojg7WrVvHk08+OWC36ejoSGRkJJGRkXR0dFBRUUFFRQWHDh3C3d2dgIAA/P39zWZ3tc7OTmpra5k0aZLapZiFvLw83Nzc5Ei+HwwGA+np6TQ3NzNz5swzOrvz/Oos2rqNqwTNi/Uxux0RRV82VlomBLmzs7CexvYe0oobmBox6vTfaGb8/PyYMmUKu3btQlEUgoNlTsHpREdHs379ehoaGk65nfdIERwcTGlpqdkEb0VRqK+vN4Xtnp4e/Pz8GDNmDD4+PoPSLjl//nxWrFghwfsEJHifxoYNG/Dw8GDKlCmDcvsODg5EREQQERFBV1eXKYRnZmbi6upqGglX8xReWVkZo0aNMtvR+KHU2dnJ4cOHmTFjhox2n4aiKGRkZNDc3MyMGTPOqEcwtaCWVft+nVD5m8myko4lSArzZGdhPWBsN7HE4A3g4+NDcnIyO3fuRKvVSkvZafS+jmVmZjJ9+vQR/9wYEBDAgQMHaGtrU20AzWAwUFdXZwrbBoMBf39/xo8fj7e39wl3rBxIV199NQsXLqSzs9Mi2mmHkgTv01i1ahVz584dknWr7ezsCAsLIywsjO7ubiorK6moqCA3NxcnJyfTSLirq+uQPrGVlJSYzZG72nJycvDx8ZFRndPo7enubS85k9DdrTPwzMpDps+vmxKCs708VVmCicHuaDVgUIzB+88Xx1lsCPP29mby5Mns3r0bjUYjPd+nERUVxdq1a6mpqRnxK8PY2dnh6+tLaWkpMTExQ3a/BoOBmpoaysvLqaysRKPR4O/vT0JCAl5eXkO6/8b06dNxdXVl48aNXHDBBUN2v5ZAXs1OwWAwsGrVKt54440hv29bW1tCQkIICQmhp6eHqqoqKioqyM/Px97e3jQS7u7uPqgvbC0tLbS0tMiLDtDa2sqRI0dkK9zT6F29pHci5ZmOdny4rZD8auOEykgfZ1JipKXHUjjbWTPG35WD5c0cqW8np6qFWL+T70Zq7nx9fUlMTGTPnj1YWVnh6yu7pZ6MjY0N0dHRZGZm4u3tbbEHXAMlKCiI7OxsoqOjB/Wx0Ov1VFdXm8K2tbU1AQEBTJ48mVGjRqn2e9BqtcyZM4eVK1dK8D6GBO9TSE9Pp7W1lYsvvljVOmxsbAgKCiIoKAidTkd1dTUVFRWkpqZiY2NjGgn39PQc8H+y0tJS/Pz8LH4N8oGQnZ1NcHCwzNw/BUVROHToEJWVlWc0kbJXRVMHr63PA47aoXKEv4BbmsRQTw6WNwOw9lCVRQdvAH9/fyZNmsTu3btlne/TCA8Pp6CggPLy8hHfnuPr68vevXtpamrC3d19QG9bp9OZBuMqKyuxs7MjICCAadOm4eHhYTYHPVdccQV//OMfefPNN82mJnMgwfsUVq1axfTp082qP6n3aDYgIAC9Xk9NTQ0VFRWmXsTeED5q1KhzPq2kKAqlpaWMHTt2gKq3XC0tLVRUVDB//ny1SzFrhYWFlJaWntGSgUf76+os2n+ZULlgjC/hXuYxwVj0X2KoBx9vLwJgbVYVD8yPUregARAYGIjBYGD37t3MmjULV1fLPpgYLFZWVkRHR5Obm0tAQMCIDlvW1tb4+/tTUlIyIMG7p6eHyspKysvLqa6uxtHRkYCAAGbOnImbm5tZPtaLFi3itttuY+/evbI4w1EkeJ/C2rVrWbx4sdplnJSVlRV+fn74+fkxYcIEamtrqaioYM+ePSiKYtqsx9vb+6xCeH19PT09PXJ6FcjPzycoKOiswuRIUVNTY5pc1Z/NcY61Na+W1fsrAHCxt+aaJFlNwhJ5u9gROsqR4rp29pc2UdHUgb+b5U/MDg4OprW1lV27djF79myzX6NZLSEhIeTk5FBVVTXiNyIKCgoiPT2d+Pj4s3oN7u7uNi24UFNTg7OzMwEBAcTFxVnEwZ+joyNJSUmsX79egvdRJHifRFtbG3v27OG9995Tu5R+0Wq1+Pj44OPjw/jx46mrq6OiooK9e/ei1+vx8/PD398fHx+ffs9mLi0tJTAwcEgnZJijjo4OSktLpbf7FNra2ti9ezfjxo07qx3bunUGnln16w6V100JwdlOnp4sVVKoJ8V17QCsy6z6/+y9d3hj93Xm/1703kkUggR7J4dtOF3UjIpjO5YtuW/klmQTb7L5reMkjm0lXpfYWsdOHMdxNi5Zx042WUe2Zcu22kgzmsYpYpth7x2FBEj0DtzfHxxAnNEUVlwA3/t5nnk04pDAe0nw4r3nvuccfOhIKbOC9oja2lp4vV68/vrrOHLkCPHnxjvB5XJRUVGByclJ6PX6rKzEZorUyFmn07nliFI4HIbNZoPVaoXL5YJSqYTJZEJjY+OOChpMc+zYMZw5cwZ/+qd/yrSUrIF9Z7sLly9fhlarRV1dHdNStg1FUdDpdNDpdGhsbMT6+jpsNhuGhoYQiUTSJlyv1991fmcymcTy8jIOHTqUYfXZx9TUFPR6PZvtvguxWAxXr15FcXHxtra7buafL85iZjUAAKjWy/BANdtQmct0lKrx074lAMDLeWS8KYpCW1sbLly4gOHhYTQ1NTEtKSspLS3F5OQkXC4XdDod03IYg6IomM1mLC4u3tN4h0Kh9Ni/tbU1qNVqmEwmtLa25vxd1re85S341re+hXg8vi/zwnMR9rtwF86cOYOOjo6cr2hQFAWNRgONRoP6+np4PB7YbDaMjY2hr68Per0eRqPxTQ2UDocDfD5/R9XLfCISiWB+fh7Hjx9nWkpWQtM0ent7IRKJ0NDQsKPHWHaH8Pephkrq5oZKgqtk+YBFI4FOJoDTH8WVGRe84RgUovxo0Obz+Th06BDOnz8PhUKx44vNfIbP56OsrAyTk5NEG29gI25y8eLFNxnPQCAAq9UKq9UKj8cDrVaLoqIidHR0ZFVf2W45evQoAGBgYAAdHR0Mq8kOWON9F86cOYP3vve9TMvYUyiKgkqlgkqlQm1tbbphcGpqCgMDAygoKEjnwpeXl1FUVET0bUIAmJmZgUaj2fOu9HxhdHQUfr8fDzzwwI4vUv/qVyMIxTYaKh+tN6BUyzZU5joURaHdosFLw3bEEjTOja/iHQfyZySpVCrFwYMHceXKFchkMmi1ubkoaD8pLy/H6dOn4Xa7iT5/KpVKiMVi2O12KJXKdGXb6/WioKAApaWlMBgM29p1kEvweDy0tbXhtddeY433TXK7nLtPpPLdb3vb25iWsm9QFAWFQoGamhqcPHkSJ0+ehFarxdzcHF544QVYrRtbA8PhMMNKmSMWi2F2dhZVVbk/lWE/WFpawuzsLA4dOrTjRrNzE6t4YcgOAFCI+Xhvu3kvJbIwSIfljSVTL484GFSyP+h0OjQ0NODatWsIBoNMy8k6hEIhLBYLJicnmZbCGDRNw+v1QiAQ4Pr163jttdfgdrtRUVGBt771rThy5AgsFkvemu4UqZw3ywZsxfsOdHd3o6CgICfz3TtFJpOhqqoKVVVVWFxcxI0bN+B0OjE1NQWNRpNe2EPS2vj5+XnIZDLib5XeifX1dQwMDODgwYM7zr5H4gl8/rk3NlT+VmcJpGxDZd5Qa5RDKuAiEE3gtbEVRONJCHj5VespKyuD1+vFtWvXcPz4cTbDehsVFRV49dVX4ff7c7IxcCfQNA23252ubIfDYajVatA0jUcffTTvTfad+I3f+A02572J/DoL7hFnz54l+pbI+vo6zGYzHnjgATz66KMoKiqC3W7H6dOncf78eUxOTiIQCDAtc19JJpOYmZlBZWUl8XGb2wmHw7h27Rpqa2t3NWry+xdmMevceB3V6OU4UcVe4OQTPA4HLSUbVW9fJI6rsy6GFe0PTU1N4PP56O/vB03TTMvJKlKzpmdmZpiWsq/QNA2Xy4XBwUGcPn0a3d3dCIfDaGhowFvf+lYcPXoUPB4PXq+XaamMcPToUVAUhf7+fqalZAXspccdyMd891ahaRp2ux0HDhwAAIhEIpSVlaGsrAyRSCQ9wH90dBQKhSJdCc+3iR92+0b8gfQ5tLdD0zR6enqg0+lQUVGx48dZWg/iW2c2bkFzKOBjx0rZC5w8pMOixqUpJwDg9IgDJ6ryb1oNh8NBR0cHzp8/j+npaVRWVjItKasoLy/HpUuXUFdXl1cbkJPJJFwuV7qyTdN0eqeGTqd709heg8EAu92eHjFIElwuN53zPnjwINNyGIc13reRynf/4Ac/YFoKI3i9XkSj0TvGK1KZPYvFgmg0CrvdDpvNhomJCUil0rQJVygUOW+iZmdnUVpamvNTbfaamZkZhMNhHD58eFc/4y/9agThWBIA8JYGAyxsQ2VecsCsAo9DIZ6kcXrEgS881pDz54Y7IRQK0d7eju7ubnb06G2o1WrI5XIsLi6ivLycaTm7IplMYnV1FVarFXa7HRRFwWg0or29/b7bog0GAwYHB9HY2JiXvwP3I5Xz/rM/+zOmpTAOa7xv49KlSygsLCQq370Zu92+pSU7AoEAJSUlKCkpQSwWw8rKCqxWKy5cuACRSJQ24SqVKudOMl6vF2tra0THje6E3+/H6OgoDh8+vKuc3tnxFbw0vNFspxLz8R62oTJvEQu4aCxSYmDRDZsnjKFlL5rMSqZl7QsajQalpaXo7+/HiRMncu68t5+Ul5djfHwcZWVlOfd9SSQS6fc3u90OHo8Hk8mEzs5OaDSaLR9PQUEBIpEIfD5fTmyd3Gve8pa34Jvf/Cab8wZrvN8E6fluu92OsrKybX0Nn89HUVERioqKEI/HsbKyApvNhu7ubvD5/LQJ385JiklmZ2dRVFREZBPM3aBpGv39/bBYLLtqNg3HbmuoPGyBRMCehvKZdosaA4tuAMDpEXveGm8AqKurw2uvvYapqSl2GtImTCYThoaGsLq6uuUNjkwSj8fhcDhgtVrhcDggFAphMplw9OjRHReTuFwuCgoKYLfbiTTeR48eBYfDQX9/P/FxE/Yd7zbOnDmD97///UzLYIRwOAyPx7OrhrlUNcBkMiGRSMDpdMJqteLq1avgcDhpE36/23JMEY/HsbS0hCNHjjAtJauYmZlBJBLZ9Z2g756fSa8SrzXIcayCnX+c77SVqPHPmAWwMVbwk4/WMKxo/+ByuWhtbUV3dzcMBgMbObkJl8tFSUkJ5ufns9Z4x2KxdA/TyspKujG0urp6z+KTBoMB8/PzqK6u3gPFuQWb834D1nhvwu/3o6+vD//yL//CtBRGsNvtUKvVe1bp5XK50Ov10Ov1OHDgAJxOJ2w2G3p7e9ONKCaTCQUFBVljwpeXlyGRSKBWq+//yYSQipgcOXJkV7cIF9eC+PbZKQAbDZW/fSz3bjuTSiQcwje+9FlcvXAWyUQCjz72bvzBp/7nLT+/eCyGH/3T3+HMC8/B7/XAaC7BH3/uaVTXN6GyUIapFT/G7D4srgVRrMntNdj3QqPRoKysDH19fThx4kTWnNuYprS0FGfOnEE4HM6azYybBwasrq5CLpfDZDKhrq5uX6rSer0eAwMDWfU9yCRsznsD9oywiStXrhA3v3szDodj36Z4cDgcFBYW4sCBA3jLW96Czs5O8Hg8DAwM4IUXXkBvby9sNhsSicS+PP9WmZubQ2kpO2EjxeaIyW63833hlyOIxDcaKn+j0ZjX5ivf+PuvfA50MolnzvTg/754Cb1XLuIn//r9Wz5nYXYaiUQc3/vJi/j5xRt4yzvfg0/93m8hHouhPc+X6dxObW0t4vE4pqenmZaSNUilUmi1WiwsLDCqIxwOY3Z2FpcuXcJLL72Eubk56HQ6nDp1CidPnkRNTc2+RUFEIhHUajUcjvz/HbgTjz76KC5evIhkMsm0FEZhjfcmenp60NjYyLQMRkhlszMxPo+iKGi1WjQ1NeHRRx/FkSNHIBKJMDQ0hBdeeAGvv/46lpeXEY/H913LZjweD3w+H8xmttkvxfT09J5ETF4ddeCV0ZsNlRI+3t1WtBfyWDJAMODHC8/+GH/4558Hj8eDTK7Ahz/+CfzqmX+/5fPKq2vxXz/xGYglGxNq3vXBjyIUCmJxbuaWLZanR+wZ1c8EqcjJ+Pg4sbOb70RpaSnm5+czPu88GAxienoaFy5cwMsvv4ylpSUYDAY8/PDD6OrqQlVVVcYW/KTGCpLI4cOHEYvFiN5mCrBRk1t4/fXX0dzczLQMRnC5XBCJRBnfLkZRFDQaDTQaDerr6+H1emG1WjE2Noa+vj4UFhbCZDLBYDDs+wzYxcVFGI3GvJo1uxt8Ph/GxsZ2HTEJxxL4/C/faKj8ENtQmVOMD12H0VwCheoN89xwoB0zk6NIJBJ3nYAUDgURCYUgkyugU4lhUIhg94bx+tw63MEoVBJBpg6BEVKRk9SUEzZysmE6BwYGsLa2tus7aPcjEAjAarXCarXC4/FAq9XCbDbj4MGDjMY89Ho9JiYmkEwmiXtNCAQCVFVVobe3FzU1+dvrcT/I+qnfh56eHhw6dIhpGYzgdDqh0+kYjVhQFAWlUom6ujo89NBD6OrqgkqlwtTUFF544QVcvnwZ8/PziEaje/7cNE1jeXkZxcXFe/7YucheRkz+92vTWFwLAQDqjQocKWcbKnMJ56oDGt2tSz/UWh0S8TgCvrtXc7/zN19G66FjKDAYQVEUOko3jHsiSePM2Mq+as4WUpGTqakppqVkBRwOB0VFRVhaWtqXx/d6vRgfH8fZs2fx6quvwul0orS0FG95y1tw7NgxlJWVMZ6tVigU4HK5cLvdjOpgivr6evT09DAtg1HYstNN1tbWsLCwgOPHjzMthRGcTmfWLTdQKBRQKBSoqamB3++HzWbD3Nwcrl+/Dq1WC5PJBKPRuCcnUqfTCZqmdzUqL5+YnZ1FNBrddcRk3hXA/z63kXPlUhS7oTIHScTjb4oGJJI3ezHu8LMMBQP4+v/8FKbHR/CNHzyT/ni7RY1f3bABAF4eduCJtvyPdG2eclJUVASplF0UZTabcfXqVTQ1Ne264kvTdPouqdVqRTAYRGFhISorKzNyl3QnpKKWTqcTGo2GaTkZp729Hb/85S+ZlsEorPG+SV9fX9rIkUYsFoPH48lq0ymTyVBVVYWqqioEg0HYbDYsLS1hcHAQGo0mPaZQLBbv6PEXFxdRVFRE3K2/OxGLxTA+Po7W1tZdRUxomsbnnxtG9GZD5VubDDCr2YbK3UDTNOhEHHQyAZqmEY9sjGZMRMOguXxQXC443L09rStUanjW1275mNvlgkAogkx+axPa0vwsPvV7v4WmtoP4px//GiLxGz/v6kI5FCIevOE4zk+uIhxLQMS/96KufECj0aCoqAijo6NE74hIodFowOPx4HA4dvR+S9M03G53elV7OByGXq9HbW0t9Hp9Tixn0el0sNvtRI4VPHLkCL70pS8RGbVJkf2v0AzR29tL7DSTtbU1SCSSHZvWTCORSFBRUYGKigqEw2HYbDZYrVYMDw9DqVSm54hvtbqUSCRgs9lw9OjRfVaeG0xPT0Mmk+1qnjsAvDK6grPjqwAAjVSAJ1rzv8K5FyTjMcTDfsRCASRjYSRiUSTjUSRjUSQTMSBVfaao9N/Xp68D2Pg7xeGAwxNs/OFv/JcnFIMnkoEnkoLa5ptdTUMzFmam4PW4oVCqAACD/dfQcKDtljdOn9eDP/rQ4/joH3wS7/zAh9/0OBwOhdYSNc5NrCIYTaB72olTtbt7jeUKtbW1ePXVV+F2u6FSqZiWwygURcFsNmNpaWnLxpumaaytraXNdiwWg8FgQENDw5Y2LWcbOp0OIyMjRJrPzs5ORKNRTE1NEXnhAbDGO01PTw8OHDjAtAxGcDqd+97osl+IRCKUlZWhrKzslpmso6OjUCgU6Ur4vRZZ2O12CIVC4t8QgY25tlNTUzhy5MiuIiGh6K0bKp88ZIFYkFtvjpmApmnEgl7Egl7EQ37EQn4kYxFw+ELwxTJwBWIIpGJw+EJweHxweAJw+QJQnI3vZTIRh3P0CnR1h0BxuKCTCSRjESTjsTcMezyCsMeFuGMedCIBnkgCnlgGnkgGgUwJnvDedyG0BXoceuAUvvM3f4U//tz/gt/rwQ//8Rv43U98+pbPO/P8L2Apr7qj6U7RUbphvAHg9IiDGOMtFotRVlaWnodPOmazGefOnUMsFrtrHCSZTMLlcqXNdmr3w4EDB7Jq98NOkMvl6Zw3aXEToVCYbrBkjTfh9PT04L3vfS/TMhghG/PdO0EoFMJiscBisdyyhWxiYiK9hcxkMr1pC9nS0hKKi4vZ7DGAiYkJFBQU7EFD5RSW3RsNlY1FShwuJ+vN5V4kE3FE/euIeNcQ9a8DoCCQKsETyyHWGMETScHhbT+bSlEUKC7vrlETmqaRjEUQC/kRD/kR8brgt8+AyxdCINdCqNCAL7nzhr7PPv1NfOUz/wOPHWmASCLBf/mdP0TXI2/Diz//T4wODuCP//IrWJqfwVD/63iiq/WWr/3If/vjtBlvKlJCwOUgmkji9MgKvvwuGhwOGb93VVVVOH36NFZXV1FQUHD/L8hjFAoF5HI5rFYrLBZL+uPJZBKrq6uwWq2w2+2gKApGoxHt7e1Zu+14J5Ce8041WH7wgx9kWgojUHSmB2pmIW63G2q1GlarlbiMdywWw/PPP49HH300Z6Im2yUej8PhcMBqtcLhcEAkEqUr4RKJBC+99BIeeugh4hufAoEAzpw5g66url0tkJhzBvDoN84jmkiCy6Hw1Xc3o0iVn6+trZJMxBHxOBH2rCIW9IIrEEOo0EAo14Anlu/4ou+NivfhHWW76WQCUb8bEa8LEd86ABoCmRpidSH4UtW+XIz+zcvj6JlfBwD89L8dvWW5Tr4zMTEBm82GBx54gPgL/ampKTgcDhw+fBgrKytps83n89PnZ41Gk7ffp5mZGdjtdiIjjl/96lfx61//GufPn2daCiOwFW9sNFYajUbiTDewke+WSqV5a7oBgMfjoaioCEVFRUgkEumTfHd3NyiKgkAgQDgchkQiyduT/FYYGxtDUVHRrkw3TdP4n88NI5rYaKh8e5ORaNMdC/kRWrMh4nGCKxBBpCqEoqgKXEF2rIumOFwIFVoIFdqNZs2QDxGvC57FCVAcDsRqA8Qaw44q8Hej3aJOG+/TIw6ijHd5eTlmZmZgs9lgMpmYlsMY8XgcXC4XTqcTzz//PMRiMYxGI44ePQqVan8u+LINknPeR44cwZe//GUijx1gjTcAshsrcznfvRO4XG76IiuZTOLSpUtIJBK4du1a+ramyWTKq9uaW8Hj8cBqteKhhx7a1eO8NOxIZ3i1UgEebyVvQyVN04j6XAg6rYiF/BCpCqAqawJfnNnlVNuFoijwJQrwJQpICy2I+NYQWrMjsLoIkVIHia4IPNHu7wq1lajTfaGnR+z49Ftr90B9bsDj8VBTU4PR0VEYDAaizjGb438rKyuQSqUQCoUoKytDdXU1EWZ7MyTnvDs7OxEOhzE9PY2qqiqm5WQc1niD7I2V+ZLv3gk0TcPj8eDEiROQy+XpRp7e3t50I4/JZMr5Rp6tMDo6irKyMkgkOx/3F4zG8aVfjaT//0NHLESMi0tB0zSifjcCjjkk4zGItSYoS+r2tFqcKSgOByKlDiKlDvFwAEGXDWvT1yFUaCHTW3ZVsVeI+ajRyzFm92F6NYDpVT8qCrL7omQvsVgsmJ6exuLi4i355nxkc8P76upquuG9vr4ecrkcY2Nj8Hq9xJlugOyct0gkQmVlJXp7e1njTSo9PT14/PHHmZaRcWKxGNxud1bP795PnE4nBAJButmyoKAABQUFaG5uTo+uun79enp0lclkysnRVffD6XTC5XKhtbX1/p98D7599o2GyuYiJTpLyXkziQV98DvmEA8HIC0wQ6wxpieP5Do8kRSKokpIC8wIrCzANdkHsVoPaWExOLydrX1vt6gxZvcB2IibVHSRY7w5HA7q6uowNDQEs9mcd+eTzSNeXS5XesRrc3Pzm/poDAYDpqenkUgk8u77sBVInuedarD8wAc+wLSUjEO88fZ4PJidncWJEyeYlpJx3G43xGJxXue774XdbofBYHhTtSVVidBqtWhsbEwvaxgaGkIkEoFer4fJZMqZZQ33gqZpjIyMoLKyEkKhcMePM7Pqx3fPzwAAeBwKHz1KxobKRDQMv30WEd86JKkK9x4vsMkWuAIRFOZqSHRF8Dvm4ZrohVhrgrTAvO2LjA6LBv/36gKADeP98a6K/ZCctZhMJkxOTmJmZiYvKn6ppWZWqxXr6+vppWZtbW33fH9RKpXg8XhwuVwoLCzMoOLsQKPRYHR0FDRNE3G+3ExbWxteeuklpmUwQn6+Q2yDGzduoKCgAGYzecs9SF7mQNM07Hb7fau8FEVBrVZDrVajvr4+vZ54bGwMfX19KCwshMlkytr1xPdjdXUVgUAAFRU7Nz6phspYYmNA0m82m2DM84ZKmqYRWrMh4JiHUKmDtroDXP7Oqr+5Bk8khcpSj1jQC59tBhGPEwpzFfiSrTflGpQimNViLK2H0LewjlVfBAXynV/45RoURaG+vh69vb0oLy/PyWqv3+9Pm22PxwOtVguz2YyDBw9CJNpaFImiKBgMBtjtdiKNt0KhQDKZRCAQgExGzl0fADh06BC+9rWvMS2DEYg33hMTEygtLWVaBiO43W4olUqmZTCCx+NBPB7fVmMpRVFQKpVQKpWoq6uDz+eD1WrF1NQU+vv7UVBQkDbhu6keZ5KZmRmUlpbuqnL/4pAdFyadAACdTIB3teb3tIZENAzv8iQS0TCUJXUQyFRMS2IEvkQBdfkBBJ3LWJ8dgkRrhLSwZMvV7w6LGkvrIdA08OqoAx/oLNlnxdlFQUEBhEIhlpaWcibr7fV602bb7/ejoKAApaWluzrnGQwGXL9+HU1NTcRVfTkcDhQKBdxuN3HGu6WlBW63Gy6Xi6gBDwBrvDE+Pk6s8fZ4PCgpIevNLkWqwrKbSpNcLkdNTQ1qamoQCARgtVoxNzeH69evQ6vVwmQywWg0brn6k2n8fj9WV1d3tbE1EInji5saKj98pBRCXu5V77bCRpXbjoBjDiJVQV7HSrYKRVGQFpghlGvgXZ5AZHoAiqKtVb/bLRr8fMAKYCNuQprxpigqPV6wpKQkK01nqgE9ZbaDwSAKCwtRWVm5Z3f5dDodotEovF4vkYUglUoFj8dD3F13rVYLnU6HiYkJ4ra5kv2ugQ3j3djYyLSMjBOLxRAIBIiNmtjt9l3FK25HKpWiqqoKVVVVCIVCsFqtWFpawuDgINRqddqE72ZqyF4zOzsLo9G4q4z/t85MweYJAwBailXoyNOZzMlEHN6lCcTDAaKr3HeDJ5LcUv2W6S0Qa033NJPlBVKoJHy4gzFcnHIiGI1DIiDrLclsNmNkZAQulytrmtxpmsb6+nrabEciERgMBtTW1u5LXwuXy0VhYSHsdjuRxlupVGJ5eZlpGYxQUlLCGm8SGR8fJ3JVfKqxMlciEXtJNBqFx+PZt7XNYrEYFRUVqKiouKXDf3h4ON3hbzKZGN2UGYvFsLCwsKsT3tSKD9+/8EZD5UeO5GdDZTwSgmdhFByeAJrKVuKr3HcjVf0WSJXwLIwiHg5AbqoEdZdRnByKQodFjVdGVxCJJ3F+wonfaDRkWDWz8Hi89HhBJo03TdPpSU5WqxXxeBwGgwGNjY0ZmeRUUFAAq9WKmpqafX2ebESlUmF4eJjIBsvS0lJMTEwwLSPjEP0OkkgkMDs7S2TFm+R8t8vlgkwmy0gERCQSoaysDGVlZbfMtB0dHYVcLk9XwnezLXInLCwsQC6X73h+bKqhMp7caKh87IAJBmV2Rmp2Q9TvhmdxDCJVIWSGMuLeGHcCXyKHuuIAPAujWJ8dhLKk7q6Np+0WDV4ZXQEAvDxiJ854AxvbLF955RUEAoGMXownk0k4nU7YbDbYbDbQNA2j0YiWlpaM7y7Q6XQYGhoicqwgyQ2WlZWVGBsbY1pGxiHaeC8sLCCZTBK5tdLj8RAbM2Hqtq5QKITFYoHFYrlli9vExAQkEkm6Ep6aK75f0DSNubm5Xc2O/fWgDZemXACAApkQj7XkX0Nl0GWF3z4HuakcYjV5hnA3cPlCqMua4F2ewvr0AJSW+jtu7mwwKSDmcxGKJXBmbAXxRBI8bn4vq7odsVgMvV6P+fl51NfX7+tzJRIJOJ1OWK1W2Gw2cDgcGI1GtLe3M7qtVyaTgc/nw+12E9dox+FwIJfL4fF4iDPetbW1eP7555mWkXGINt4TExMoKioiMm7hdrtRXFzMtAxGcDqdjM/O5fP5KC4uRnFxMeLxOBwOB6xWKy5cuAChUJiuhKvV6j034Wtra4hEIjCZdmaW/ZFbN1R+5Gh+NVTSNI3AygJCazaoShshkGb2bkS+QHG4UJirEXQuwz07CKWlHgLprXfZ+FwOms1KXJ1dgzsYQ8/8Og6Xk2W8gI1tlv39/aitrd1z85tIJOBwOGCz2WC328Hn82EymXDo0CFoNJqsuItDURR0Oh2cTidxxhvYiJu43W4UFRUxLSWjNDU1YXp6GslkMu+3Q2+GeOOdK2Oc9hKSGytT+e5sOrnzeDwUFRWhqKgIiUQCKysrsFqtuHz5Mvh8PoxGI0wm0569Sc7Pz+9qY963Xp2EwxsBALSVqNCeRw2VNE0j4JhD2L0KdVkzeKLsaYbNRVK5bw6PB8/88M3G1FtfLwdLNbg6uwZgY7oJica7sLAQHA4HDocDRqNx148Xi8XS5xGHwwGRSASj0YijR49CpVJlhdm+Ha1WS3TOm8QGy/r6ekQiEVitVqKmuhBtvMfHx1FWVsa0jIzj8XggEomIrPRnMt+9E7hcLoxGI4xGI5LJJFZXV2G1WnHt2jVQFJX+N51Ot6MKQSwWg9Vq3fGm1gmHD/98cRYAwOdS+PCR0h09Tjay2XSryprAE+b3EqBMIlYbQFEcuOdHobLU3zIVpqVYBS5FIUHTeHnEjr94e11WGsP9hKIoWCwWzM/P79h4R6NR2O122Gw2rKysQCqVwmg0orq6et/ja3sByTlvlUqFkZER4hosUxHLiYkJ1niTwtjYGE6dOsW0jIxD8sbKbBrbdT84HA70ej30ej2SySRcLhesViv6+vpA0zQMBgNMJtO2GqGWlpYgl8t31FhL0zQ+94uhTQ2VRdArsvMCZicEVhZY072PiFQbmwk9C6O3xE6kQh7qjHIMWb1YXAth3OFDrYG8eE9JSQnGx8cRCoW2POJzc8P26uoqFAoFjEYj6uvrIZfL91nx3kJyzlsulyMejyMYDDI67YoJUiMFSfJiRBvviYkJ/OEf/iHTMjKOz+fL+BSNbCEb8t07gcPhoKCgAAUFBWhubk6P/rp+/TpisVjahN9v9NfCwsKO41XPXbfiysxGJKBQLsRjB/KnoTLoXEZozQ41a7r3FZGqEHQyCc/8CNTlzeCJNkxGu0WDIasXAHB62EGk8RaLxSgsLMTi4uI9G583jyh1uVxQqVQwGo1obm7OadNGcs6by+VCJpPB5/Pl9M9wJ5SVlWF8fJxpGRmFWOMdDoextLSEpqYmpqVknEAgQNyJDdiIWWRbvnsnUBQFrVYLrVaLxsZGuN3u9Jzw3t5e6PV6mEymNy27CIVC8Hg8O7qV7QvH8OVfj6b//yNHSyHg5UczTMS3Dr9jfsN0s5nufUesMSAZj8I9PwJNRQs4PD46StX44eU5AMDpUQf+6KHcuzjeC4xGI+bn599kvIPBYNpsr6+vQ6PRwGg0oq2tbVcLsLINknPeMpkMgUCAaRkZp6qqCleuXGFaRkYh1nhPT09DKBSivLycaSkZx+/3Eze2CNiI2IhEoqzNd+8EiqKgVquhVqtRX18Pr9cLq9WK8fFx9PX1obCwECaTCQaDAQ6HA2q1ekfZ/m++MokV30ZDZbtFjbaS/GiojEeC8C6OQVFUCb4kt27N5zKSgmLEwwF4FkahKm2ETiZEqVaCOVcQN5Y8sHlCMCrzx1BuFb1ej+vXryMcDiMej6fNtsfjgU6ng9lsxsGDB/PqHLYZtVqN0dFR4rLOwMb2Y7/fz7SMjFNfX48f/ehHTMvIKMQa79REE5JG2AAbVd9IJEKk8c732eUURUGpVEKpVKKurg4+nw9WqxXT09Po7+8Hn8+HVqtFJBLZlvket/vwg+45ABsNlR85kh+TgJKJODzzoxBrjOn8MUtmoCgKCnM11mduwG+fgdxUiXaLBnOuIADglREHPpRHjbtbgaZpRKNRCIVCnDt3DtFoFAUFBSgtLYXRaIRAcOclRPkEyVlnmUyGpaUlpmVknKamJszPzyMWi4HP5zMtJyMQa7xnZmaIm5kJbFS7BQIBESfx2yGtqVQul6OmpgY1NTXwer147bXXEAgE8NJLL0Gr1aZnhd+rekbTNP7yF0NI3GyofFdLEQrkuV9to2ka3sVxcIUiSPX5cSGRa1AcLpQldVibvg6uUIqOUjV+2rdhPF4mxHjTNA2Px5OubIdCIUgkEnA4HJw6dYoYI5KCy+VCoVDA7XYTabxJrHhXVVWBoigsLCygoqKCaTkZgVjjvby8DIOBvG10mV5LnE2QvDQoEAhAIpHgwQcfRDgchtVqxfLyMgYHB6FWq9MmXCK5NeP884FlXLs5Y9mgEOE3m/OjoTLoXEYiGoa64gBxt7SzCa5ABGVJLdxzwygqb4ZOJoDTH8WVGRe84RgUovwznjRNY319PW22I5EIDAYD6urqUFhYiGAwiPPnzxN3NzYFqctkZDJZOmK0uTcn3+FyudDpdLDZbKzxznesVitxv9gAufnu1NKgnYzRywfsdjsMBgMoioJYLEZFRQUqKirSExJsNhuGh4ehVCrTJjzJE+LLvx5LP0a+NFTGw0EEVhagLmsCh0vsKTBrEEiVkOhM8C1Pot2ixkvDDsQSNM6Nr+IdeTI5h6ZpuFyutNlOJBIwGAxobGx80yQiuVwOoVCI1dVVIotDKpUKVquVaRkZRyAQgMfjEfk+lTLepEDsu47VasXBgweZlpFx/H4/kaMEU0uD8rUp6V7QNA2Hw4GOjo43/ZtIJEJZWRnKysoQjUbTJnxsbAyv2oVw+mMAgKpCGQ6Yc//NgKZpeJcnINEa2WbKLEJaUIKIdw2Nyjheuvmxl0ccOW28k8kknE5n+neKpmkYjUa0trbecwEWRVEwGAzpi2XSUCqVRC6ToSgqHTdhjXd+Q6zxttlsRG1KSuH3+2Ey5e6b2U4hLd+9mfX1dSSTSWg0mnt+nkAggMVigcViQSwWw2v/2QvABQCYXPHj6V8O4GNHLDDo1Dn7hhh0LoFOJiAtZHPd2QTF4UBhrkbR1A1IBDwEo0m8NraCaDyZU3dZEokEVldX02abw+HAZDKhvb0dWq12y/ERg8GA3t5e4swnACgUCqIbLEnMeRcUFBB1l4NY422321FSUsK0jIxC0zSxGe98n2hyL+x2O/R6/bYyo3w+H597vB3exHWcHnEAAAYdEXz6uXG8vZSLt9TpIFEVgCeW5YwxiIcDCKwsQl3WBIrQ/Gw2wxfLIC8sQoPagdcdgC8Sx9VZF05UFTAt7Z7E43GsrKzAZrPBbreDz+fDZDLh8OHDUKt3dpGq1WqRSCTgdruhVufH6M6tkmqw9Hg8xL1XSaVSImd5G41GLC8vMy0jYxBpvAOBAPx+P3HGOxKJIB6PE3cyAzaMN4mVfmDDeO9kIYVSwsf3PtyBF4fs+J/PDcHhjSCapPDsTBK9ThfeX+ZAiYILoVILoUIHvkSRtSacpmn4bDNsxCTLkRYUo1m7itcdSQDA6RFHVhrvWCwGh8MBm80Gh8MBkUgEk8mEo0ePQqVS7fr3gMPhQK/Xw263E2e8gY24CYnnbJlMhpWVFaZlZByTyYShoSGmZWQMIo23zWYDj8fb0Qa/XMbv90MkEhHVMQ28UemXy8kzXKmLzMLCnc+p/o1GA45WavG1F8fxb1fnQdPAgjeBr9+g8Gi1Em8TJxBeGAVFURAqbppwqQIUlT1V5ajfjXg4AGVJHdNSWO4BxeGgo9aCfxmdRoLeMN5feKwhKy7ootEo7HY7bDYbVlZWIJVKYTKZUFNTA7lcvucaDQYDJicnUVdH3mtWJpPB7XYzLSPjkBo1KSoqYqMm+Y7NZrtnc0u+kpoRSxrBYBA0TRN57C6XC2q1etfzgBUiPr70rka8q7UIn/3ZIMYdPtA08NL4OnqXBfjYsRo0aihEvC54lyZA00kI5RoIlToIpCpGox00TSPgmIO0wMxOMckBlBodajWzGHYlYfOEMbTsRRNDjb2RSCSd115dXYVCoYDJZEJ9ff2+X8gXFBSgt7eXqMUiKUhdJiMWixGLxYgbKVhcXAy73c60jIxBzk92E1arFTqdjmkZGScSiRA51SM1w5q0Cy1g75tK2y1q/Or/O47vnp/BN1+dRDSehNMfxddeGseRci0+fMQCrbEcsaAPEa8TPus06EQcArkGIqUWApkaFId7/yfaQyIeJ5LxGMQasm5b5yoUReFghR7Dro0pB6dH7Bk13qFQKG22XS4XVCoVTCYTmpubMxrTEwqFEIvFcLvdKCjIvrjNfiKTyRAIBIhrLhUIBKAoCpFIhCjjbbFY4Ha7t71VOVch5ye7CZvNRtyJDADC4TARL+rbIXV2ObCRbbdY9naCB5/LwR+erMTbm4x46ueDuDS1Mfnk8owLN5bc+OChEpysKYRAqoDMUIZ42I+IxwW/fQ6J2ASEcvVGJVym3vcKNJ1Mwu+Yh1RfwjZU5hCdVUb8y7UN4/3yiAOffHT7PQrbIRgMwmq1wmazYX19HRqNBiaTCW1tbRCLxfv63PdCqVQSabwlEgkSiQTC4TCj3/9MQ1EURCIRwuEwUb1YZrMZHA4Hdrt9z9+vshHWeBNEOBwmcoY3qcY7tY56v6a5lOqk+LffOYSf9S3jr349gvVgDIFoAt+/MIsLE0781xPlKFKLwRfLwRfLIdVbkIgEEfY4EVhZhHdpAgKZ+mYuXLsvJjzsXgHFoSBS6ff8sVn2D7VEgAqdGNPOEMbsPiyuBVGs2duomN/vT5ttj8cDnU6H4uJiHDx4MGvuDKpUKng8HqZlZBwulwuJRAK/30+U8QY27nSEw2GmZWQUHo8HrVYLq9XKGu98hdR18eFweFdNdrkKqbPLfT4fAOxrFpWiKLy73YyTtYX4q1+P4Gd9GyOhxh0+/PnPbuBdLSa8s6UIfC4HFEWBJ5JCJpJCprcgHgki4nEh5LLCZ52CQKp6w4Tzdp9ppWkaQdcyJDozUber84WOMh2mnYsANqrev3O8bFePR9M0fD5f2mz7/X4UFBSgrKwMBoMBAoFgL2TvKSqVCouLi0zLYIRUoyFpRbJUxZs0tFotMUt0iDTeVqsVzc3NTMvIOOFwOGsqOZmE5NnlSqUyI6ZTIxXgb9/XgidazXjq54OYdwWRSNL4ad8yLk+78DsnylFvvPVuC08oAa9QAmlhMRLRMCJeJ0LrDvis0+BLFWkTzuXvLB4V9buRjMchUpL1xp0vHLRo8OPXbxrvYduOjHfqrk/KbIdCIRQWFqKqqgp6vT7rmxZVKhUCgQCRDZakzrQm1XgXFhayxjufsVqtKCoqYlpGxiGxuTKRSCAYDBIZNXG73RlfPXy8SoeXPvEAvnVmEt85N4N4kobVE8aXfjWCkzUF+C+dFshEbz7tcAUiSHRmSHRmJGIRRLwuRDxO+G0z4Es2mXDB1l+/oTUbxBoDm+3OUUwqEQwKEezeMHrm1rEeiEItvX9VmqZprK+vp812JBKBwWBAXV0dCgsLc6ppTSgUQiQSpaMwJEHqTGuRSETkBQdJ2ytz5wy0hzidTuJmeMfjccTjceKaK4PBIDgcDnEXHMCG8WYiLyfic/Fnb6nFOw6Y8JmfDaJ/wQ0AODu+it4FNz582IKjFdq7VuK5fCEkWhMkWhOS8SgiXhfCN5szeWJpelY4T3j37GciFkHUvw65sXw/DpElA1AUhY5SNX51w4YEDZwZW8G72813/FyapuFyudJmO5FIwGAwoKmpCQUFBeByMztJZy9RqVRwu93EGW+SK94ul4tpGRmnoKAADoeDaRkZgUjj7ff7idsGFg6HQVFUVuYY95NUvIa0jO9+N1ZuhVqDAj/9+FH836vz+OqL4/BH4vCGYviHs1O4MLmK3z5WhkLFvS+IODwBxBojxBojkvEYIr41RLxOBFYWwBOKIVToNirhQsktP+PwugMCqWpbFXKW7KPdsmG8AeD5G0u3GO9kMgmn0wmr1Qq73Q6apmE0GtHa2ppXexpSxps0SI1ckNhcCWz0Is3PzzMtIyMQZ7zj8TgikQhx0z1INaCk5tpT28+YjthwOBQ+dKQUj9Qb8PnnhvHi8MaShOtLHvzZT27gvR1mvLXRCC7n/q9LDo8PsVoPsVqPZCKOqG8NEa8LgdUlcPnC9Op6nkiKsHsVUn3+d8fnO9WFcihEPHjDcVyaXkMwHIXXvZY221wuF0ajER0dHdBq734XJZdRKpVENliKRKL0ndpcigftFlIvOGQyGbxeL9MyMgI5r+abpCY9kFbxJjHfDZB73G63GwqFImuqfgalCP/0oXa8PGzH534xDLs3jGgiif97dQEXpzZGD1YUbP0igcPlQaQqhEhVCDqZQMS3jojXCffsIMDhgI7HwOFyiVvAkW9wOBSqCmXoXXAjHKfxD8+cRoueD5PJhMOHD0OtVuf9z5fUBktSl8mIRCLEYjEkEomcjkhtF4VCkS4Y5TvkvJpvkvrBZrrpjGlIXZ5DasWb6ZjJ3Xi0wYAjFVr8zcsT+OHlOdA0MO8K4i9/MYTfaDDgfR3FEPG392ZDcbgQKXUQKXWgk0n4rFOI+t3wLIyB4nDTlXC+RJH3Ji1fSCbiiHjX8Nz1ZfQuRNIfr6qqxCOHqon6OYpEIiIbLEldJiMUCtMXHBLJ3s6uz2YUCkW6MJrvEGe8fT4fxGIxUVeSABCLxYjLdwPkLg0KBAJZ+yYtF/Hx+cca8M6WjebLMbsPNA28MGTHtdk1fOxYGdotO7sjRXE4SETDkBQUQ6zWIxrwIOJ1wrMwBgAQKrQQKbXgS5WgqOy4G8CywYbZdm388a3juUU+ziwl0//+tnIhmnRcokx3CplMhmAwyLSMjENi3pmiKPB4PMRiMaalZBS5XM4a73zF5/MRdfWcgrScXApSlwblQqW/tUSNX/7RcfzzxVn83SsTCMeScAWi+PrL4zhUpsFHjpZCLdnexWIyHkMs6IXCXAOKw9lYTy9XgzbRiAU8iHhd8C5NgqaTEMo1G6vrpSp25CBDbEyt2WiYjQY8G7Pd5Vr8dJqLC0vr6c/71G/U4C3FFOx2OyorKxlUzAwkGlCA3Lwzj8dDPB5nWkZGUSqVxEyxIc6J+f1+om7fpCBxlCCQGwZ0P8iV4+ZzOfh4VwXe1mjEUz8fxIVJJwDg6uwabix58MHOEjxUVwjOFqucUf86eCIpuIJbX+sURUEgU0EgU0FmLEc85EPY44TPOg06EYdArtkYUyhXg+KQdTcs06TntHtdiAW84IllECm1kJsqkeAI8K0zk+iZ3zDdHAr48uNN+GBnCYLBIIaHh4nLOgPkGlBSj5tU481mvPMUn89HrPEmsdKfKwZ0L6FpOueaSku0EvzotzvxiwErvvirEawFogjFEvg/l2ZxcWoVv3u8HMWa+//eRgNeCGSqe34ORVHgSxTgSxSQGcoQD/sR8bgQcMzBuzSxUSVX6CCQq8HhEneK3BdSm0nDHhfiId/GUiSlDgpzdXozaTAax9dfHMWobeN2s4DLwTc/0IK3Nm3sXJBIJJBIJFhbW4Ner2fsWJhAJBJhbW2NaRkZRyQSEWPGNkOi8VapVAgGg0gmk1kzFGC/IO5dheSKN2m59kQigUQiQVylPxqNgqbpnDLewIYhfldrEbqqC/CV50fxTO8SAGDC4cdnnh3EYwdMeFdLEQS8u5+U4yE/JAVb30pLURT4Yjn4YjmkegsSkSDCHicCq4vwLk9AIFOnt2ayJnx7xCMhRLxORDwuxCMBCKRKiNV6CC114PBujRB5QjH8rxdGMefayDFLBVx898MdOFZ5a59CaqY1icY7Eonc/xPzDKFQSOQyGRKNt1KpBE3TRGyaJu6dhM14k0PqxEXacYfDYfB4vJy90FJLBfjaew/g8bYiPPXsEGadASSSNJ7tX8blaRd+90QZGkxvnkpEJ5OIRwLgiXZ20qYoCjyRFDKRFDK9BfFIEBGPCyGXFT7rFARSZXphD4dHVtRhK9A0jUQkeHPTqBOJaAgCmQpirRFCueau37NVXxhfeX4Mdu9GpEAt4eNfPtaJA8WqN32uUqnE+vr6mz6e75AcuUgkEkzLyDgkGu/UiGe/388a73yD5KgJaQY0Ho+Doqi8v211O/kSrzlaocML/+MEvn12Cv90bhqxBA27N4y/+vUouqoL8FuHSiAXvWHm4pEgKIqzZ9sqeUIJeIUSSAuL01GJ0LoDPus0+FJFuhKeikqQCE3TiIcDiHiciHhdSMQiEMrVkBYUbymqs7gWxNMvjGI9uDHBwagU4V9/pxOVhfI7fr5KpcLs7OyeH0e2k2quJG0uPYkGFCDzuIVCIQQCAXw+HwwGA9Ny9hWynBg2rqbYijcZpI6ZpDcqIH+MNwCI+Fz8yaM1eMeBjdGDvTeb7s5NrKJvYR0fOmzB8UodKIpCPOQHTyzbl583VyCCRGeGRGd+oznQ44TfNgu+RPbG6noCVtTTNH2zOdWFiNeZbk6V6i3bak6ddPjw1ZfGEIhsVDTLC6T41985hCKV+K5fo1KpEAqFEIlEiIqQiUQiJJNJ4sbCkmhAAYDL5RJ53BKJhIhMP1lODIDX62WNNyGQeMxAfhnvFNV6OZ75/SP4j9cX8L9eGIMvHIcvHMc/vjaNC5NO/M7xMkjCfvDF+3+LkssXQqI1QaI13TIOz2+fA08kfWN1vfDuBjLXoOk3xjFGvK70OEa5sQIC2fbHMV5fdOMbr0wgEt+Y091sVuIHHz0IrezeZprP50MqlcLj8RA1JjQVHQuHw6zxJgBSj1sikRAxy5s4V0JCfuhOJBIJ4kwoqcY71yaabBUOh8JvHbLgkTo9vvDLEfx60AYAGFz24M9+ch1vL+PjbTcnYGRME08AscYAscaAZDyGiG/DhAdWFsAViCFS3qyECyU5d+eFppOI+t8w28DGAiKFuWpXC4guTzvx7demkUjSAICjFVp898MdkAm39rsqk8mImfebIrXFkbQGS1INKI/HI+5nDbAV77zF7/ejuLiYaRkZhaZpIk0oiccMbFS8NRoN0zL2jUKFCN/+rTY8PuLA534xBKsnjFiCxs+nouh12vB7XbK7ZoT3Ew6PD7FaD7Faj2QijqhvDRGvC4HVJXD5wjcq4SJp1ppwOplE1L9+c3vkGiiKA6FCC2VJLfgSxa51nx6x4weX5kDf/P/faDDg7z7QAhF/643A7DIZcuDxeEgmk0SMmNsMqRccpIyPJM6VkFj5TXWFk3bcJI5QBPIzanInHq7X40iFFn/z8gT+pXsWSRpYdEfxuV8M49EGA97XYYZEwMxrnsPlQaQqhEhVCDqZQMS3YWbds4OguDwIFTqIlFrwxHLGTfhmfVHfWlqfylK/Z/poemMqTWpEJAC8v6MYX3miCVzO9h6fRAMKkHnBkTp/x+NxNmJDAKkLrXyHLCcGEHflDCD9QibtuEmteMfjcWI2+0mFPHzuHfV4R7MB//2H3VgOUqABvDRsx+tza/jo0VIcLGW2+k9xuBApdRApdbdUlN3zI+mKslCp25OK8lbZqMivb8zZ9q2nK/KqsqY9r8gnaRr/emUeLw7Z0x/7eFcF/vw3anb0PCKRCG63e8/05Qp8Pp84M5Y6f5NmvDkcDhEG9HYoiiLiuIlzJSQab5reuLHLdGUt05B4dwMAcSPHAKCmQIQ/aU5gVd2Iv3tlEqFYAmuBKP729AQOlqrx0aNl0EiZf+OmOJz0GMLNGWrPwhiAjQy1SKndVYb6bmzOoEf97nQGXVpYsm8Z9Hgyie+cm8HFKWf6Y599Wy1+74GKHT8miVlnYOP8nTqXkwJFUeByucTN8ibxZw2Qc8FBnCtJJBLEGW9SIdGAAmQedzgchkQkxO93VeBtTUb8xc+HcG5iFQDw+tw6hpa9+MDBYjxcpwdnm9GG/YKiOBvr6eVq0KaK9NQQ79JkemqIUKHb0dSQFJunrkT9nvTUFZmhfN+nrkTiCXzzlUn0L7oBABwK+F/vbsb7OnbXY0Nq1IRUM0bicZN2/k7BGu88haZp4ow3qRVvgMxjJvE1vjleU6yR4F8+dhC/vGHDF385DKc/ilAsgR90z+HilBO/e6IcJZrsWqJFURQEMhUEMhVkxvL0nGyfbTo9J1uo0G5pTvbmOeOxoC89Z1xuqszYnPFAJI6vvTSOccfGaDABj4NvfbAVb2nY/WIMUvOvpJiS2yHReAMg8pjZqEmeQmLFm1TjTeKJC9iIU5H4s958zBRF4bEDJjxQpcPTz4/hxz2LAIDJFT8++7NB/OYBI55oNUPAy75zAUVR4EsU4EsUkBlK05shA455eJcmNqrkCh0EcnX6axLRMMIBN8IeF+Ih/8ZmTaUOiuKajG/WdAejePqFMSysBQEAMiEP3/1wO45W6Pbk8TkcDpG/26SYEhZyLzZIubgkzngnk0kiJ12QCImRC4DM475b74ZKIsBX39OMJ9qK8JlnBzGzGkCCpvGLASuuzLjwO8fL0VSkZEDx1qAoCnyxDHyxDFK9BYlI8OaIwkV4lyeAmz/n9enrEMiUEKv1EFrqwOExk2d3eMN4+oVROLwbGWytVIAf/nYnGvfwe0yqASXVjJF63CQeM4fDISLPn33lHhYWFpY95lC5Fi/8jxP4Hw9Vgc/dMKsObwRfeX4U/3h2Ct5QjGGF94eiKPBEUkgLS6CtaoOiqBq4aUDVlS1QlTZCrDEwZrrnXQF8/rnhtOkuUonxzMeP7KnpZmFhYcl1iDPepFxRsZBbKSHxuLdyi1LI4+KPH6nGC//jBDo3jRi8MOXEnzxzHecmVnPm+5ZMxOF3zEGqLwVfokDQucyonnG7D1/61QjcNy9gKgtl+Ml/O4Lygr3fEkxiDwNA5p0sgNzjJvGYSUkkEHf24nK5xN2mTP0C54qp2CtIPHEBZGZgt3OxUVkox//7vcN4+okmKEQbaTt/JI5/OjeNLz8/Crsnuydm0DQN3/IUeEIJJLoiKIprEPWtIexeYURP/8I6vvL8KALRjYJGS7EKz/z+ERiV+zM1hcQeBoBcA0oipP6sSRn3nP9HeBsk5gNJNd4AmcdM4mucx+MhFtt6XITDofDBzhK88idd+M1mY/rjw1YvPvXT6/h5/zLiiez8HobXHYgFPVCYqzbmHPOFUBRVwWedRiKa2YuGS1NO/M3LE4je/F6dqNLh//7uIaj3cWY6qYuxSDElt0OqCSXxmEm5m5X/R3gbJFa8SYXEyAVA5nGnlqps97gL5SL8w39pww8+ehBFqo0KbSxB48c9i/jss4OYuDkOL1uIh4Pw22egMFffkuUWKrQQqQrhWRwDTWfm/PbSsB3/cHYKiZvf87c3GfH9j3RAKtxfUxwOhyESZWYsYjZBqgEl8bhJO3+nIOXiMv+P8DZIGVezGVIr3lwul8h5vyQab6FwY2TeTjcanqwtxOlPPoD/eqIMqf06i+shfP65YfyfS7MIRpl/HdHJJLxL4xBrjBDI1G/6d5mhDHQyiYBjYX910DR+0ruIf+meS3/svxwqwd9/sBVC3v7nM8PhcPrnTRKkGtBEIkFE7nczJP6sAdZ45y0kGu/UC5m04yZ10cZ2Yxf5AJfLBZ/P39VGQ4mAh6feXo/n/vvx9IhBGsDpEQf+9JnruDa7xugFjd8xC1AUpIWWO/47xeFAWVyL0JoVUb97XzQkaRr/0j2Hn/a90cz5R6cq8eV3NYKboY2gpFa8Y7EYcRGb1PmbtOMmxYDeDhs1yVNIrIKmqgWkHTePxyNygg2pK7X36rgbi5R49g+O4i/eXgcxf+N3Zz0YwzdemcDfnJ6Ay7+zqvpuiHhdCK+vQGGuuef6eJ5IApmhHN6lcSTje3vxFU8k8e2zU3h5xJH+2F/+Zj3+5NGajFbnSDXekUiEuONOnb9JM96k9jHE43HWeOcjMpkMgUCAaRkZhaIoIqu/JB4z8EbemTT28rh5XA5+90Q5Tn/yAZyqLUx/vHd+HX/6k+t4cciGZDIz1e9ELALv8iTkpgrwhPefFCJS68GXKOBdmtizCn04lsDXXx5H97QLAMDlUPib9x7A7xwv25PH3w4kGlCAzAuOlBEjwYxthlTjHQ6HIZPt/QjSbIOsVzM2jLff72daRsYhsdJPqvEWCoVEVrylUume/26b1RL880c68A//pRU62UauOBxL4oeX5/G554Yw79rfi3iapm+uiddApCq8/xdg40JbXlSFeCSIkMu6aw3+cBxfeX4U15c8AAAhj4PvPNmOd7ebd/3YO9Lj90MqlTLy3ExB0zSR2XZSDWg8Hicu1w4AwWCQNd75iEKhIK7iDZBpQkk8ZoDcqIlSqYTb7d7zx6UoCr/ZbMKrn+zCBztL0h+fXg3gs88O4t+vziMS359IU9C5hGQsApmxfFtfx+HyoDDXwO+YRyy084uRtUAUX/zVMCZXNh5DLuThX3/nEB6u1+/4MXdDLBZDIBCAUknWNsx4PI5EIkFkxZtU403icQeDQcjlcqZl7DvEGW8SoyYAmSY0dcykTfgg1XirVCq43e59+3krJXw8/UQTnvn4EVQWblRlkjTwyxs2fOonN3B90b2nzxcLehFYWYSiuBYc7vbfhAVSBaQFZngXx5HcQa+D3RPG558bxuJ6CACgkwnx/37/MDrLNPf5yv3D7XZDLBYTV/kNh8PgcDjg8/lMS8kopBrQRCJB5HGzFe88RS6XIxgMMi0j45BqvGmaJm6aC6nGW6FQIJlM7vuF9cFSDX79/x3HJx+phoC7cQpd8UXwv14cwz+cnYIntPumxmQiDs/iOGT6EvDFO38jkhQUg8Pjw2+b2dbXzbkC+Pwvh7F6s5HUrBbjJx8/ggYTs5Vmt9sNlUrFqAYmSOXaSRsxR6rxJvG4I5EIotEoW/HOR+RyOVvxJoTUiYu04xaJROlb0yTB4XAgl8vh8Xj2/bmEPC7+v4eq8MInTuDQpgrwpSkn/vSZ63htfGXHlXeapuGzToEnFEOsLdqVToqioCiuQcTnQti9uqWvGbV58cVfjqQvIGr0cvz0vx1FqY75XLXH4yEuZgKQ2VgJkJt1JtF4r6+vAwBb8c5HZDIZsRVv0owYl8sFl8slbsKHQCAARVFEVr1TcZNMUVEgw//7vcP463c3QyneiAH4I3F85/wM/urXo7C5Q9t+zLB7BVG/Bwpz9Z5UON9YKT9135XyvfPrePqFUYRiG+eKthIV/vP3j0CvyA7TR2rFm8TGSmCjCkricZNovD0eDyiKgkQiYVrKvkOc8WajJmRBYuyCoihiJ5totVqsrm6tsrtXUBSF9x0sxqt/0oV3tpjSHx+xefHnP7uBn/UtIZ7YWtwpHgnCb3vzSvjd8sZK+fG7rpQ/P7GKvz09jlhio1LfVV2Af/vdQ1BKsiNXHAwGEQwGodEwlzFnClIr3qQeN4nG2+12QyKREDE6Mv+P8DZIrnizxpscSD1uvV4Pr9eLUGj7lebdopMJ8c0PtOKHv92JYs3GvO1YgsYzvUv49M8GMW733fPr6WQS3sVxiDUGCOVvXgm/W2SGUtDJBAIrb14p//ygDf/73DRSo8kfO2DC9z7cAYkge9787XY7tFotcQ2GALkGlNTjJtF4ezweImImAIHGm814kwWpBpTU4xYIBNBoNLDb7Yxp6KouwMuf6MLvd5Wn16gvu0P4/C+H8f0LMwhE7vx76HfMAbj7SvjdQnG4UBbXIOR6Y6U8TdP48euL+Ncr8+nP+8gRC/7u/S0Q8LLr7cFut8NgMDAtgxHYpUFkQarxJmU+f3adWTOAXC5HKBQiLu/M5/MRjUaZlpFxSN3iKJVKibzABACDwcCo8QYAsYCLz7y1Ds/992NoNr/RDPjq2Ar+9JnruDLjuqX5MuJbQ3jdAUXxvVfC7xaeSAqZoQzepQnEo1H888VZ/HxgOf3vn3i4Cp9/rAEcTnZNz4jFYnA6ncQab7/fT0T29XZIvOCgaRrxeJy4Ozs+n4+IiSYAQNYlFd7omPV4PERlBUk1oCKRKN0tTRJKpRKzs7NMy2AEg8GA0dFRxGIxxt+8GkxKPPsHx/Cjy3P4+kvjCEQTcIdi+Oark2grUeFjx8qgFlLwLk1AZtzaSnjg5ptzkkY0nkQ0kUQ0nkTs5n+jm/4bi9O3/vvNv/vXeVgcvo6xtTcKEF94rAEfOVq6T9+J3bGysgKZTEZMRWwz4XAY4XCYuGkuqW2dpBnvSCQCmqaJayr1er2s8c5XUj/Y9fV1oow3qc12pB63SqWC1+tFMpkkolllMzKZDBKJBCsrKygq2t04vr2Ay6HwsWNleEuDAZ/7xRBeGV0BAPQtuDFsvY5OAwccjhBY8SGa8CB2BzMdS7xhoFMf36s1QTwOhb953wG8s4X579XdIDlm4na7IZVKGb+IzDTRaJRIAxoOh8Hn84kbo+j1eonJeBNnvHk8HoRCIbxeL9NSMkoq80vTNFFLGEjNOqdOYH6/HwqFgmE1mcdsNmNhYSErjHcKk0qM7324Ay8O2fE/nxvGii+CSDyJC0tJAHEAmZ3GAgBiLo2vv7seb89i0x2NRmG1WtHV1cW0FEbweDzEjlDk8XjEZZ1JrPIDZL1XkfWKvolMJiMufiASiUDTNKLRKFEVBFIvOCiKglKphNvtJuZktpmSkhKMj48jGAxmVTaWoii8tcmIY1U6fOnn1/GTATto3Pt1KeJzIOJzIeJxIeRzIOJxIeJzIORzIeJzIeSl/v3mf/kcCG9+jojP3fg8Hif9X9HNrxPxOUisW7G2MoN4vDhrDc7S0hKUSiWRr2Ngo+Kt1WqZlpFxSDWgJObaATbjnffodDrYbDamZWSUVOWAtIUEEokEyWQS4XAYYvHW8rP5QmqZTElJCdNSMo5YLIZer8f8/Dzq6uqYlvMmxFzgUe063vX+cvBVhlvMdco4C/kcCHmcfb1gTJoU6PasYWhoCC0tLfv2PDuFpmnMz8+jvLycaSmM4Xa7UVFRwbSMjBMIBIjN9JNovFdXV1FTU8O0jIxAVvjzJiaTCcvLy/f/xDyDxLwzl8uFRCKB3+9nWkrGUalUGVmfnq2UlZVhbm4u6yYY0TSN69evQyqV4mhLHTrLNGg2q1Ctl6NEK0GhQgSlhA8Rn7vvd2k4HA7a2tpgtVqz8pzodDoRCoWyKjKUSSKRCJGNlcBG9ICUzO9mSN1Surq6CpPJdP9PzANY400QpOadSR2tp1Qq4fF4bhlbRxIFBQUQCARZ97u+uLiI1dVVtLW1ZUX8SSKRoKWlBQMDA1m3XGxmZgalpaVZG4PZb0htrATYijdprKyswGg0Mi0jIxBpvIuKihif88sEpBpvmUxGZMU7lZfz+e69MTFfoSgKFRUVmJycRDK5tZXt+43f78eNGzfQ1taWVW+uJpMJZrMZPT09WfO98nq9WFlZQVlZGdNSGMPtdhPZWAmQXfHOpnNDpnC5XKzxzmeMRiNWVzM/QYBpWONNFpsbLEmlpKQENE1jcXGRaSlIJBLo6elBaWkp9Ho903LeRGNjI+LxOMbHx5mWAgAYHR1FaWkpcb0Zm3G73UTGTBKJBILBIJHGm8Tmyng8DpfLxUZN8hmSjTeJS3RINd7AG3ETUuFwOKitrcXY2BjjWe/R0VEAyMpmT2CjH6KjowPT09NwOp2ManG5XFhdXUV1dTWjOpiG1FGCwWAQXC6XOANK6tKgpaUlJJNJYmb1E2m8TSYT428sTEBicyWwkfEOBoNZcws9k6Qmm5BMUVERhEIho5s8HQ4H5ubm0NHRkdWLMRQKBRoaGtDb28vYRTpN0xgZGUFlZSWRTWYpIpEIQqEQkcbb7/dDKpVmRQ9EJiF1adD8/DxUKhUxx02k8TYajXA6ncQZMbFYnHXNU5lAIpGAoigij12n02F9fR2xWIxpKYxBURTq6+sxMTHByPchHA6jr68Pzc3NOXHrvLS0FCqVCgMDA4w05jocDvj9fiJH6G1mdXUVCoWCyMZKUvPdoVAIfD6fuGbixcVFYqrdAMHGOx6PEzfLWyaTIRwOIx6PMy0lo1AUBalUSmSToUQigUwmw8rKCtNSGKWgoABKpRITExMZfV6aptHX14fCwkIUFxdn9Ll3CkVRaG1thdvtzvhdgkQigeHhYVRXVxNpODdjt9uJMiObIdV4k3rcy8vLxOS7AUKNt1QqhUwmw8LCAtNSMopQKASPxyN2tJ7X62VaBiMYDAYip/hshqIoNDU1YXZ2Fmtraxl73qmpKQQCATQ3N+fUbXOBQID29naMjIxktEdgYmICXC6X6EkmAJBMJuFwOIg13h6Ph8imUlKNt9VqZY03CRgMBuKMd6ryS6rxJjXrbDAY4HA4iItW3Y5CoUB1dTX6+/sz0mi5vr6O8fFxtLe352T1VqfTobKyEj09PRm5S7a+vo7p6Wm0traCwyH2rQnARnMpl8slMt+dSCTg9XqJNN6kzi632WxELcki9uxmNBqxtLTEtIyMQ+qED5KbDNVqNTgcTkYrvdlKZWUleDwexsbG9vV5YrEYent7UVNTA41Gs6/PtZ9UV1dDIBBgaGhoX58nkUigv78fVVVVRBqu20nFTHLpLsle4fV6wePxIJFImJaScUiteJO0tRIg2HibTCZYrVamZWQcUo23UqlEOBwmcqoLRVHQ6/XEx02AjfGCra2t+x45uXHjBiQSCSorK/ftOTIBh8NBe3s7rFbrvp4vx8fHweFwUFVVtW/PkSvQNE10vjs1QpG0iw6apok13k6nk5jlOQDhxptEI0Kq8ebz+ZBKpcTOtE7lvEldH78ZhUKBmpoa9PX17cuUk8XFRaysrGTNSvjdst8r5V0uF2ZmZtDW1kZ8xATY2DQbiURQUFDAtBRGIHVpUDQaRTweJzJqwhpvQiB1bTypGW+A7LhJQUEBQqEQkRddd6KyshJSqRS9vb17ejGSrSvhd4vJZILJZEJvb++e9goEg0Fcu3YNDQ0NUCgUe/a4uYzdbkdBQUFWz3vfT9xuN5HZdr/fD5FIRNwowUQiwRpvUigvL8fy8jLTMjKOTCZDNBpFNBplWkrGIdl483g8FBQUEHmxeScoikJHRwf8fj9GRkb25DGTySR6enpQUlKSlSvhd0tjYyOi0eiejWSMx+O4du0aTCYT8VNMNkNyzCTVWEmq8SYxZjI5OQmaplFSUsK0lIxBrPGurq7G/Pw8cZMe+Hw+hEIhkZVPkiebAOxYwdvh8/k4dOgQ5ufnsbi4uOvHS62Er6+v3/VjZSM8Hg8dHR2Ympra9eZfmqbR398PHo+HpqamPVKY+4TDYbjd7ry8cNsKPp+PbawkjMHBQVgslpyc/LRTiDXeFRUViEQimJmZYVpKxiE1561SqYhtsAQAvV6P9fV1xlaBZyNyuRwdHR24fv061tfXd/w4KysrmJ2dRXt7e15HBJRKJerr69Hb27uru2YTExNwu904ePAgm+vehMPhgEqlyquY0nZYX1+HUqnMi96I7RIIBIg03iMjI6iurmZaRkYh9ownEolgNpsxODjItJSMQ2rOm8/nQ6lUwuVyMS2FEcRiMZRKJXEbW+9HYWEh6urqcOXKlR1tN02thG9qaoJcLt8HhdlFWVkZVCoV+vv7d5SPn5+fx9TUFDo7OyEUCvdBYe5is9mIjZkAG422Op2OaRmM4Pf7iWysnJycRG1tLdMyMgqxxhvYiJukbg+ThFwuJ3aLo06n2/Vt8lympKQE8/PzTMvIOioqKlBaWopLly5t625QKjKh0+mIyShuXik/Nze3ra9dXFzE4OAgDh06ROTkinsRCoWwsrKC4uJipqUwAk3TcDqdRBrvRCIBv99PxIX77czOzqKmpoZpGRmFaONdW1u7Z41CuQTJTYZarZZo4202m+Hz+Ygdq3gvamtrUVxcvC3zPT09Db/fjwMHDhB1ezy1Un54eHjLF/GLi4u4fv06Ojs7iTRX92NhYQGFhYUQi8VMS2EEv9+PWCxGZGMlydn2hYUFNmpCEjU1NZidnWVaRsZJLZMhMeur1Wrh9/uJzXnz+XyYTCa26n0HKIpCfX09zGYzLl68eF9Dub6+jrGxsZxdCb9bdDodKioqtrRSfn5+Pm26CwsLM6Qwd6BpGvPz87BYLExLYQyn0wmNRpPXPRJ3IzW7nKSLd2BjnKjVamWNN0mkJpuQRmqZDIlVb4FAQHTOGwAsFguWlpaQSCSYlpJ1pMy3xWLBpUuX7vo6Sa2Er66uzumV8LulpqYGPB4Pw8PDd/x3mqYxOTmJoaEhHD58mDXdd2FlZQXJZJLYaSYA2fluUmeXj4yMQCgUErUuHmCNN5aXl4ms/JIcNyE9563RaCAUCvd1BXguQ1EU6urqUFNTg8uXL9/x4nxwcBBisZj4FeccDgcdHR1YWlp60+spkUigr68PMzMzOHbsGLGmaivMz8+jpKSE2AkvJOe7AXKN9+DgICoqKoh73ZN1tLeROtGR2GBJ8kxr0nPeFEWhtLSUyJjVdigvL8ehQ4cwPDyMwcHB9Mz/xcVFOByOvFkJv1vutFI+FArh4sWLCAQC6OrqItJUbJVQKASHw0F0zITkfHcymYTP5yOy2XhsbIy4mAlAuPHmcrkoKyvD0NAQ01IyjkqlIrbBjvScN7Bx0enz+bC2tsa0lKymoKAAXV1dWF1dxZUrV+B2u3Hjxg20trYS2wR3J4qKimAymdDX1weXy4Vz585BLpfj2LFjxM6k3iozMzMoLCwkcpRcCpLz3V6vFxwOh8if/9TUFHGjBAHCjTewkVEkseKtUqkQCoWIjNmkct6rq6tMS2EMPp+PkpISIhdIbRepVIoTJ06Aw+Hg/Pnz0Ol0RM9avhv19fXw+Xy4dOkSqqqq0NraSqSR2g7xeBzz8/OoqKhgWgqjrK6uEh8zIfHu2dzcHFvxJpGamhpMTk4yLSPjkNxgCbDr04GNRSg2mw2hUIhpKVkPn8+HTCaDUCjE6uoqrl+/jlgsxrSsrMHr9eLy5cvg8XigKIpYI7FdlpaWIBaLodVqmZbCGIlEAisrK8RezHo8HiIjNgCZowQB1nijpqZm20sg8gWSc94GgwErKytET/aQyWQoKCgg9vW/HVZWVjA3N4ejR4/i5MmT8Pv9OHv2LNF3TYCNfOrk5GT6TsCpU6fQ0NCw65XyJEDTNGZmZlBeXk70RYrT6YRAIIBCoWBaCiOkRgmShsvlgtPpZI03iVRXVxNrPEjOeSuVSvB4PKLHCgIbDYRzc3P3ncNMMpFI5JaV8FKpFEePHkVVVRWuXr2KgYEBIu8auFwuXLhwAQsLCzh69CgaGhrSfTMKhQIDAwM7WilPCqurq4hEIjCbzUxLYRS73Q6DwUDkxUcymYTX6yWy4j0wMACVSkXk3R7ijXdzczNWV1extLTEtJSMQ/JIQYqi2LgJNpoHpVIppqenmZaSldA0jb6+Pmi12ltWwlMUhbKyMpw8eRKxWAyvvvoqRkZGiIifeL1eXL16FZcvX4Zer8eDDz54yyzz1Er5tbU1IvckbAWapjEyMoLKykqic/A0TaeNN4mQ3Fh59epVNDc3My2DEYg33kqlEmVlZbhw4QLTUjJOqsGSxGod8EbOm+SqXGphzNTUFJGNtvdjZmYGPp8PLS0td6zISaVSHDx4EMeOHcP6+jpOnz6NycnJvIwwBYNB9PX14dy5cxCLxXjkkUdQW1t7R+MoFArR3t6OoaGhLa+UJwmr1YpIJILy8nKmpTCKx+NBPB4nsuoJAGtra1Cr1URW+/v6+nDw4EGmZTAC8cYbADo6OnDt2jWmZWQcPp8PlUpF7ExrnU6HaDRKvDHQ6XTQarVENhnfC7fbjdHRUXR0dNx3JbxarcbRo0fR0dGB5eVlvPLKK5icnMyLnLPX68XAwABeffVV0DSNU6dOobm5GUKh8J5fV1BQgPLycvT09OTlhchOSSaTGB0dvetFC0nY7XYUFhYS+30geWnQyMgIOjo6mJbBCKzxBnDw4EHcuHGDaRmMQPIWRy6Xi8LCQuLjJgBQV1eH2dnZ9AIU0onH4+jp6UFVVdWWV8JTFIXCwkJ0dXWhqakJDocDL7/8MgYGBrC+vp5Td1aSySSsVisuXbqEc+fOgaZpdHV1ob29fVu3xWtra8Hj8YjclXA35ufnQVEUiouLmZbCOCTHTGiahsvlItJ4h8NhTE1Nob29nWkpjMAabwDt7e1EzvIGNow3yQ2GbM57A6VSCZPJhLGxMaalZAU3btyAWCzeUcc9RVEwmUw4fvw4Tpw4AQBpAzs9PY1AILDXcvcEmqaxtraG4eFhvPzyyxgeHkZBQQEeffRRtLa27mjqBIfDQXt7O5aWlmCz2fZBdW4Rj8cxPj6Ouro64tZk304oFILX64Ver2daCiP4fD4kEgkiGyuvXbsGkUhE7Px6HtMCsoG2tjbYbDbYbDYYjUam5WQUjUaDQCCAUChE5CY+g8GAgYEBBAIBIhtcNlNbW4szZ86gsrKS2NFewMZsZYfDgQcffHDX2UulUomWlhY0NjZieXkZy8vLGB4ehkwmg8FggMFgYDTjGY/HsbKyArvdDofDAZqmodfr0dbWhoKCgj3RJZVK0dLSgv7+fqhUKiLPMylmZmYgkUiIe5+5E8vLy9BqtRAIBExLYYTUtk4SL8AuX76MlpYWIo8dYI03gI0mw9LSUly4cAHve9/7mJaTUTbnvEm89SkQCKDX67G0tISamhqm5TCKVCpFaWkpRkdHcejQIablMEIgEMD169fR1ta2pwaRx+PBYrHAYrEgFoulze6VK1fA4XCg1WqhVCqhUqmgUqn2xYzQNI1gMAi3253+s7a2BrFYDKPRiIMHD+6bESgqKsLKygp6e3tx7NgxIpvJotEoJicncejQISKP/3aWlpZQVlbGtAzGIDnf3dvbS2xjJcAa7zQdHR24evUqccYbeCPnTaLxBgCz2YzR0VFUV1cT/4ZYXV2N06dPw+VyETdpIJlMoqenB8XFxftakeTz+SgqKkJRURGSySTW1tawtrYGj8eD+fl5BINBSCQSKJVKSKVSiESi9B+hUAiRSAQul/um1ypN04jFYgiHw7f8iUQi8Hq96QkSCoUCKpUKJpMJzc3NkMvl+3asm2lqasK5c+cwMTFB5EXu5OQkNBoNsWZrM16vFz6fDyaTiWkpjJDKd1dWVjIthRFGRkbw+OOPMy2DMVjjfZOOjg6cPn2aaRmMoNPpMDg4yLQMxkjFTdxuN9RqNdNyGEUoFKKyshIjIyM4fvw4URciY2NjSCaTaGhoyNhzcjgc6HS6W8xYNBqF2+2Gx+NBMBiE0+lEJBJJG+lUkyZFUemfD03T6Y9zudxbzLpIJEJRURHq6+uhUCgYmyDB4/HQ3t6OixcvpifpkEIoFMLs7CyOHz/OtJSsYGlpCQaD4b7TgvIVkvPdkUgEk5OTxDZWAqzxTtPe3o6///u/Z1oGI2g0GgSDQWJz3lwuF0ajEUtLS8QbbwCoqKjA7OwsHA4HMRMHVlZWMDMzgwceeIDx0WYCgQCFhYUoLCx807/RNI1oNIpEIgGappFMJtMGnMPhgM/ng8fL3tO6SqVCXV0dent78eCDDxKT7x0bG4PBYCDSaN0OTdNYWlpCU1MT01IYg+R897Vr1yAQCIit9gPsVJM0bW1tsFqtRHbe8/l8KJVKYscKAkBxcTGWl5eRTCaZlsI4fD4fNTU1GBoaImKVfGolfGNjY9Y3lVIUBaFQCIlEAqlUCrlcDplMBqlUCrFYnNWmO0V5eTlRK+XX1tawvLyMuro6pqVkBWtra4jH48ROMwHIzneT3lgJsMY7jUajQUlJCS5evMi0FEYgeZ43sHH8FEUR/T3YTFlZGQQCQd6P2aRpGv39/dBqtbBYLEzLIQKSVsonEgn09/ejurqa+KlJKZaWllBUVESs8SJ5fjfANlYCrPG+hVSDJYmkjDcJFag7QVEUioqKsLi4yLSUrCBljubn5/N6zvvMzAy8Xi8OHDhAVJ6daUhZKT82NgYej0f0bfXNJJNJLC8vw2w2My2FMbxeL7H5boDsjZUpWOO9CZI3WGq1WoTDYfj9fqalMEZxcTFsNhtisRjTUrICuVyO2tpa9Pf352XkJLUSvr29nZiscTaRWinf29ublyvl19bWMDs7i9bWVmKru7djt9vB5/O3vA02H3E4HCgoKCDyNRGJRDAxMUF0YyXAGu9b6OjoIHa1MY/HI359ulKphFwux9LSEtNSsoaKigoIhcK8i5xsXglP0nSNbKO2thYcDgfDw8NMS9lTUhGTmpqarO8byCRzc3OwWCxE312y2+3ENK3fztWrVyEQCFBVVcW0FEZhjfcmDh8+jNXV1bwzGVtFr9cTbbwBoLS0FHNzc8RGbm4nXyMng4ODEIlEO1oJz7J3cDgcdHR0YHFxMa8a21MRE1JXYt+JQCAAl8uFkpISpqUwRjgcxvr6OrGNpS+//DKOHz9OZLV/M2Qf/W3IZDK0tbXhhRdeYFoKIxgMBqyvryMSiTAthTGKiooQDAaxvr7OtJSsQSaToa6uLm8iJ0tLS7DZbGhvbye68pYtSKVSHDhwAP39/QiFQkzL2TWpiElbWxvxBmMzc3NzMBgMEIlETEthDIfDAbVaTez34NKlSzh16hTTMhiHPSvcxqlTp3Du3DmmZTCCSCSCUqmEw+FgWgpj8Hg8mM1mzM3NMS0lqygvL8+LyElqJXxrayuRM+uzFbPZDIPBgL6+vpy+25RIJNDX14eampqMbQTNBRKJBBYWFoifHERyzCT1u/Hggw8yLYVxWON9GydPnkRPTw/TMhjDYDAQHzcpKyvD8vIy0ZX/29kcOcnVkYvJZBK9vb0wm837uhKeZWc0NzcjFAphYmKCaSk7ZnR0lPjlIHfCarVCIBCgoKCAaSmMkUgksLq6Sqzx7u7uRjKZRGtrK9NSGIc13rdx7NgxrKys5Hxlb6cYDAasrKzk5ZSBraJQKKDRaPJ+xvB2SUVOBgYGcjJyMjY2hng8jsbGRqalsNwBHo+Hjo4OTE5OYm1tjWk522ZtbQ1zc3NobW1lI0y3MTMzg7KyMqK/L6urqxAKhcTeCXnppZdw/PjxnFjytd+wxvs2pFIp2tvb8fzzzzMthREUCgUEAkHOVjX3irKyMszNzbGbLG+jvLwcIpEI169fz6lIwOrqKmZmZtDR0cH4SniWu6NSqVBbW4uenp6cGusZiUTQ29uL2tpaYo3V3VhfX4fP50NxcTHTUhglFTMh9eKDzXe/AWu87wDJOW+Koti4CZC+HUj69+F2KIpCR0cHnE4npqenmZazJVKmKBdWwrNsjLCUy+U5s1I+mUzi9ddfh0qlYqeY3IGZmRmUlJSAz+czLYUxaJpm891svjsNa7zvAJvz3jDeufCmt19wOByUl5djamqK6O/DnRCJROjs7MTY2FjWN+KmVsJrNBriG7tyhVQ/gcvlwsLCAtNy7svg4CDi8TgbMbkDwWAQVqsV5eXlTEthFLfbjUQiQezOgO7ubtA0zea7b8Ia7ztw9OhRoud5a7VaxONxeDwepqUwisVigd/vJz52cyfUajVaWlrQ09MDn8/HtJy7Mjs7C6/Xi5aWFtYU5RAikQhtbW0YHBzM+teX1WpFZ2cnm129A9PT0zAYDJDJZExLYRS73Q69Xk/seMkXX3yRzXdvgsxXwX0gPefN5XKh1+thtVqZlsIofD4fZWVlmJycZFpKVmI2m1FWVoarV68iGo0yLedNeDwejIyMsCvhc5TCwkKUlZWhp6cnK5u9V1dXMTw8jM7OTkgkEqblZB2RSATz8/PEbymkaRpWq5XYmAnA5rtvhzXed+HUqVN47bXXmJbBGEVFRVheXiY+ZlFeXo61tTW43W6mpWQldXV1kMvl6OnpyapG1NRK+MrKSmJv7+YDdXV14HA4GBkZYVrKLQQCAfT09KCpqYl9fd2FmZkZaLVaqFQqpqUwisfjQSgUItZ4x+NxNt99G6zxvgunTp3KOjORSfR6PWKxWE6O9dpLhEIhLBZLTs8W3k8oikJbWxvC4TCGh4eZlpNmaGgIQqGQXQmf43A4HLS3t2NhYSFrGp1jsRiuXr0Ks9nM9g3chVgshpmZGeKr3cDGplyj0UhszKK7uxsA0NLSwqyQLII13nfhyJEjcLlcxOa8ORwOioqKsLS0xLQUxqmsrITD4cjqrCmT8Pl8HDp0CIuLi1kx+3x5eRlWq5Vd2Z0nyGQyNDc3Z8VKeZqm0dfXB5FIhIaGBka1ZDNzc3NQKBTE3w2gaRpLS0tEj1Jk53e/GfZd6S6QnvMGNjK8y8vLxFb9U4jFYpjNZkxNTTEtJWuRSqU4ePAgBgcH4XK5GNMRDAYxMDCAlpYWNnebRxQXF6OwsJDxlfJjY2Pw+Xzo6OhgL+ruQiKRwPT0NKqqqohvaF5dXQUA6HQ6hpUwB5vvfjPsmeMePPLII3jllVeYlsEYGo0GfD4/60fGZYLKykosLS0hGAwyLSVrKSgoQH19PV5//XX4/f6MP38ymURPTw/MZjNMJlPGn59lf0mtlGeq2XlxcREzMzPo7Oxkm3XvwcLCAoRCIfR6PdNSGGdpaQlFRUXEXqQFg0H09PTgoYceYlpKVkHmq2GLPPbYY+ju7kY4HGZaCiNQFAWz2czGTQDI5XIYjUY2630fysrKYDab0d3dnfGLlPHxcXYlfB7D5/PR3t6OiYmJjPeeLC8v4/r16+js7GSXMN2DRCKBiYkJVFdXE1/tjsfjsNlsRMdMfvWrX0GpVLL57ttgjfc9aGtrg0wmw69//WumpTCG2WyG3W7PqfXN+0VtbS0WFxfZrPc9oCgKDQ0NMBgMuHTpUsYyualNmuxK+PxGrVajtrYWvb29GTsn2Ww29Pf34+DBgygoKMjIc+Yqs7OzEAqF7B0nAA6HAyKRCEqlkmkpjPHss8/iscceI/4i7HZY430POBwOHnvsMTz77LNMS2EMuVwOuVxO/ExvYKPJq6SkhNiG261CURSamppQUFCAS5cu7fsdo9RK+IaGBrYaSQAVFRWQSqW4fv36vue9HQ4Hent70d7ezkYn7kMsFsPExATq6+tZo4WNmInZbCb2e5FMJvHaa6/hne98J9NSsg7WeN+Hxx57DGfPniW6wbC4uJiNm9ykpqYGKysrWF9fZ1pKVkNRFA4cOAC1Wo3u7m5EIpF9eR6apjEwMACVSoXS0tJ9eQ6W7CI1wtLpdO7rSvnV1VW8/vrraG1thdFo3LfnyRcmJyehVCrZuwLYKAY4HA6YzWampTBGd3c3fD4fTp48ybSUrIM13vfh1KlTWF9fx7Vr15iWwhhFRUVwuVyMj/LKBkQiEcrLyzEyMkL8cqH7QVEUWltboVAo9q3yPTs7C7fbjdbWVmIrSyQiEonQ2tq6byvlV1ZWcPXqVRw4cABFRUV7/vj5RigUwszMDFvtvonVaoVarYZUKmVaCmM888wzeOSRRyAUCpmWknWwxvs+iMViPPzww/jP//xPpqUwhkgkgk6nY6veN6mqqoLH40mPimK5O6kFKCqVChcvXtzTizd2JTzZ6PV6lJaWore3d09Xytvtdly7dg0tLS1EN8Zth4mJCej1eqjVaqalZAWLi4tEV7sB4NVXX8W73vUupmVkJazx3gLvete7iB4rCAAWiwXz8/NslRcb0xWqq6vZqvcWSVW+dTodLl68uCfTTjavhCd5Ri7p1NfXA8CerZS3Wq3o6elBW1sb8cZpq/j9fiwsLKCuro5pKVmB1+uF1+sl+k7J9PQ0xsbG8La3vY1pKVkJa7y3wNvf/naMjIxgbm6OaSmMYTQaEYvF2CrvTcrKyhCNRrG8vMy0lJwglfnW6/W4cOHCrud8Dw0NQSAQsCvhCYfD4aCjowPz8/O7Xim/uLiIvr4+dHR0sFM5tsHo6CiKi4shk8mYlpIVzM3NwWQyEX0X7j//8z/ZKUD3gDXeW0Cv16OtrY3ouAmHw0FJSUlWrATPBrhcLmprazEyMoJ4PM60nJwgNe3EbDbjwoULcDqdO3ocq9UKq9WK9vZ2YhdTsLzB5pXyO+kjoGka4+Pj6TndBoNhH1TmJ06nEw6HAzU1NUxLyQri8TgWFxeJb/R+4YUX8PjjjzMtI2th37W2yOOPP44XXniBaRmMUlpaCrvdTuxCodspLi6GWCxml+psg9Sc77q6Oly5cgWzs7Pb+np2JTzLnUitlO/t7d1W/CsVWZqfn8eJEydQWFi4jyrzi2QyiRs3bqCmpgZisZhpOVnB8vIypFIp0Vl3r9eLa9eu4R3veAfTUrIW1nhvkXe84x24cuUKI6uwswWpVAqtVruvI7xyCYqi0NzcjJmZGaJfFzuhtLQUR44cwdjYGK5fv76lcZ3JZBK9vb0wmUxsFIDlFlK/i8FgEFNTU1v6mlAohIsXLyISiaCrq4voRSc7YXZ2FjRNo6KigmkpWcPc3BwsFgvRk11+9rOfwWQyoba2lmkpWQtrvLdIQ0MD9Ho9fv7znzMthVFKS0sxNzdH9FzzzSiVSpSUlODGjRtso+U20Wq16OrqwtraGi5fvnzfWd8TExOIRqPsSniWO8Ln89HR0YHx8fH7ztlfW1vDuXPnoFarcfToUXbk2TYJh8MYGxtDc3MzG/e6yfr6Onw+H/FNuc899xze9a53EX3xcT/Y35gtQlEUHnvsMeKNdyr/uNtGpnyirq4OHo8HNpuNaSk5h0QiwYkTJ8Dn83H+/Hl4vd47fp7T6cTU1BQ6OjrA4/EyrJIlV1Cr1aipqUFPT89dV8rPz8+ju7sbNTU1OHDgAGscd8Dw8DD0ej3bPLeJ2dlZlJSUgM/nMy2FMRKJBM6fP4/HHnuMaSlZDXvG2QbvfOc7ce7cOaKb6TgcDkpLS7edzc1n+Hw+GhoaMDQ0RPRrY6fweDwcPHgQJSUluHDhwpsuYKLRKHp7e1FfX8/GAVjuS2VlJaRS6ZvuQiWTSQwODmJkZASHDh1CWVkZgypzF6fTCZvNhoaGBqalZA2RSATLy8vEv6ZOnz6NeDyOY8eOMS0lq2GN9zbo6uoCRVH4xS9+wbQURrFYLFhbW7trdZJEiouLIRKJ2EbLHUJRFGpqatDa2ore3l6Mj4+DpulbVsKT/qbGsjVSK+VXVlawuLgIYOPi7cqVK1hdXcUDDzzAVmp3CNtQeWfm5+eh1Wohl8uZlsIoP/zhD/He976X6Kr/VmCN9zbg8Xj44Ac/iB/96EdMS2EUoVCIoqIituq9ic2NlvuxwpoUTCYTTpw4gfn5efT09GB6ehrr6+vsSniWbSESidDW1oYbN27AZrPh/Pnz4HK5OHHiBNFrvHcL21D5ZpLJJGZnZ4kvDEQiEbz44ot48sknmZaS9bDGe5t86EMfwquvvkr8FIvy8nIsLi7eNUdJIiqVCqWlpejv72cbLXeBUqlEV1cXwuEwhoeHUVZWRvQyCpadUVBQAIVCgWvXrsFsNqOzs5OtxO0Cv9+P0dFRNhd/G3a7HRRFET///ZlnnoFUKsWJEyeYlpL1sL8926S9vR1GoxH/9m//xrQURlGpVFCpVGzV+zZqa2sRjUYxPT3NtJSchsfjIRqNQq/XY3JyEn19fexFHsuW8Xg8OH/+POLxOGQyGeLxOHvHZBekIl8lJSXQ6XRMy8kaaJrG5OQkKioqiH99/du//RuefPJJ9qJsC7DfoW1CURQ+9KEP4T/+4z+YlsI4VVVVmJ6eZhsKN8Hj8dDa2oqxsTE2crILhoaGwOfz0dnZiVOnTiESieDMmTNwOBxMS2PJYpLJJMbHx3HhwgXo9Xo8+OCDOHToEObm5tjXzi6YmZlBOBxGfX0901KyitXVVQQCAVgsFqalMEpqPCcbM9karPHeAU8++SS6u7uxvLzMtBRGKSwshFgsZhfq3IZWq2UjJ7vAarViaWkJHR0d4HA4EIvFOHz4MGpra9HT04P+/n62+s3yJlJV7uXlZRw/fhx1dXXgcDi7XilPOqmISUtLCzvK8zYmJydRXl5O/Pflhz/8ISorK9kdC1uENd47oLy8HG1tbfg//+f/MC2FUSiKQlVVFaamptiFOrdRV1eHaDS65S16LBuEQqE7roSnKAoWiwWnTp1CKBTCmTNnsLKywqBSlmzh9ip3V1cXVCrVLZ9TXFwMnU6Hvr4+9mJ4G9A0jf7+flgsFjZichtra2tYX19HeXk501IY58c//jE+/OEPMy0jZ2CN9w75yEc+gp/+9KdMy2Ack8kEDoeDpaUlpqVkFVwuF21tbRgfH2cjJ1uEpun0SviioqI7fo5YLMaRI0dQW1uL119/na1+E47X601XuY8dO4a6ujpwudw3fR5FUThw4AACgQDbf7ENZmZmEIlEUFdXx7SUrGNychKlpaXEN37Pzs6it7cXH/zgB5mWkjOwxnuHvO9978PIyAiGh4eZlsIoqar35OQkW0m6DY1Gw0ZOtsHExAQikch9b1emqt8nT55MV78XFhbY7zFBRKNRDA8P4/z58+kqt1qtvufX8Pl8tLe3Y2xs7L4r5VneiJi0trYSH6W4Ha/Xi5WVFXasIoDvf//7OHbsGMxmM9NScgbWeO8QnU6HRx55BN///veZlsI4ZrMZ8XicXZl+B+rq6hCLxTA+Ps60lKzG5XJhcnJyWyvhJRIJjhw5goaGBoyPj+Ps2bOw2+2sAc9j4vE4JiYmcPr0aXi9Xpw4ceKuVe47odFoUF1djd7eXvZOyT1IJpPo7e2FxWKBVqtlWk7WMTk5ieLiYnaJEIBnn32WjZlsE9Z474IPf/jD+PnPf058vpnL5aKiooKtet8BLpeLjo4OTE1Nwel0Mi0nK9nNSniKomA2m/HQQw+htLQUAwMDuHjxIlwu1z6pZWGCZDKJubk5vPLKK7DZbOjs7MSRI0e2/XoBNqYxicVi3LhxYx+U5gcjIyOgaZqdYnIHgsEgrFYrKisrmZbCOKklZ+9+97uZlpJTsMZ7F7zjHe/A6uoqzp8/z7QUxiktLUUgEGDN5R1QKpVoaGhAb28vIpEI03KyitR8YIVCsavNbxwOB+Xl5XjooYdQWFiIK1eu4MqVK/B6vXuoliXT0DSN5eVlnDlzBlNTU2hubt71yvc7rZRneQO73Y75+Xl0dHRs+U4CSUxNTcFoNEImkzEthXG+//3v4zd/8zd3dAFMMqzx3gUSiQRPPPEEfvCDHzAthXF4PB7Ky8sxMTHBtJSspLS0FBqNhp2qcBvz8/NYW1vbs5XwfD4fNTU1ePjhhyGVSnHu3Dn09fUhGAzugVqWTLKysoJz585haGgIlZWVOHXqFEwm0568TsRiMVpbW3Hjxg3itxBvJhQKoa+vD83NzayxvAPhcBgLCwuoqqpiWgrjJJNJ/PKXv2RjJjuANd675EMf+hCef/55RKNRpqUwTnl5OdbX17G2tsa0lKyDoii0tLTA7/ezIwZv4vV6MTQ0hPb2dgiFwj19bKFQiKamJjz00EMAgFdffRWDg4PsHYccwO12o7u7Gz09PSgqKkrHiPZ6I57BYEBJSQl6e3uJjwsCG0aqp6cHRqMRxcXFTMvJSmZmZqDVatkKL4AXXngBgUAAb33rW5mWknOwxnuXnDp1CiKRiPgV8gAgEAhQXl6O0dFRtqp7B/h8Pjo6OjA+Pk78xUkikUBvby/Ky8t3FRu4HxKJBG1tbejq6kIgEMDLL7+MgYEBNoKSZdA0DZvNhkuXLuHixYtQKpV4+OGHUVVVta8TNerr60HTNEZHR/ftOXKF8fFxxGIxNDU1MS0lKwmHw5iZmUFNTQ3TUrKCf/qnf8KTTz5J/DjFnUDRrEPaNV/60pfw4osv4tKlS0xLYZxYLIbTp0+jo6MDhYWFTMvJSqanpzE9PY0HH3yQ2JPWjRs34Ha7cfz48T2vZN4Lr9eLmZkZLC4uQqPRoLy8HAaDYU/iCyzbJxaLYWFhATMzM0gmkygrK4PFYtnzOyD3wufz4dy5c+js7CT2nLWysoJr167hgQcegEKhYFpOVnL9+nVEIhF0dnYyLYVx7HY7SktL0dPTw26r3AGs8d4DbDYbLBYL+vr62BchNkYtLS8vo6urizU0d4CmaVy9ehUURaGzs5O475HNZkNfXx8efPBBSKVSRjREIhHMz89jdnYWHA4HpaWlKC4uhkgkYkQPabjdbszPz2NxcREKhQIVFRUwGo0ZvQjbzPz8PEZHR/Hggw8S9xoIhUI4d+4c6urqYLFYmJaTlfj9fpw9exYPPvgg5HI503IY5y/+4i9w5swZdHd3My0lJ2GN9x7x+OOPQ6fT4Xvf+x7TUhgnkUjglVdeQUNDAztU/y5Eo1GcP38eRUVFRG2FC4VCOHv2LA4cOHDX7ZSZJJlMwmazYW5uDmtra9Dr9SgtLUVBQQFxF0T7TSwWw/LyMubm5uD3+1FUVITS0tL7Lr7JBKmtqbFYDIcPHybmZ59IJHDhwgUolUq0tLQQc9zb5fXXXwefz0dLSwvTUhgnmUyioqICX/rSl/Dkk08yLScnYY33HnH69Gl84AMfwPLyMnEVkzsxPz+PyclJnDp1irEqVrbj8/lw/vx5tLS0ZIUJ3W9omsalS5cglUrR2trKtJw34ff7sbCwgIWFBXA4HJSUlMBoNEKhULCGZIckEgm4XC4sLy9jeXkZMpkMpaWlKCoqAp/PZ1reLcRiMbz22msoKysjYkZz6mIjFArh6NGj7OjAu+B2u3Hx4kU89NBD7MIcAL/4xS/w0Y9+FDabjfU6O4Q13ntEMplEZWUlPvWpT+HjH/8403IYJ5lM4uzZsygvL9/VfOZ8x263o6enB8ePH4dKZmYaxwAAWLJJREFUpWJazr4yPj6OpaUldHV1ZfUK6mQyCbvdjqWlJaysrEAgEMBgMMBgMECn07EXkvchEonA4XCk//D5fBiNRpSUlGT9a3xtbQ3d3d1E/D5OTExgbm4ODzzwAGug7kF3d3d6FwML8Na3vhV1dXX427/9W6al5Cys8d5DvvrVr+KZZ55BT08P01KyAqvVihs3buDhhx/OaqPFNJOTk5iZmUFXV1fevgG6XC5cvnw55wxNIpGA0+mE3W6H3W5HPB5HYWEhDAYD9Ho9sc2xt+Pz+WC32+FwOLC2tgaFQgGj0Qi9Xg+lUplTdwwmJiawsLCArq6urKvK7xUkXfDvhtXVVbz++ut4+OGH2d91AEtLSygvL8fg4CA73WUXsMZ7D3E6nTCbzTh37hwOHTrEtBzGoWkaFy5cgF6vZ39J7wFN0+klL/l4yzcWi+Hs2bOoqKhARUUF03J2DE3T8Hg8aRPu9Xqh0WjS1XCSFo4kk0msra2lvxehUAgFBQXpC5JcviVP0zS6u7shFovR1tbGtJw9x+v14sKFC8RE3HYKTdM4f/48jEYjqqurmZaTFXzyk5/EwMAAzpw5w7SUnIY13nvMRz7yEYTDYfz4xz9mWkpW4HQ6cfXqVTzyyCNsxeAeJBIJXLx4EQqFIq+anGiaRk9PDxKJBA4dOpQ3xwVsNIqmjKfT6YRAIIBKpYJSqYRKpYJKpcqLOxg0TcPv98PtdsPtdsPj8cDtdoPL5aYvOgoKCvLqrlYoFMJrr72GxsbGvFomE41Gce7cOZjNZqKaunfC8vIyhoaG8NBDD+XVa3unRKNRlJSU4Dvf+Q7e+c53Mi0np2GN9x7T29uLEydOYGFhATqdjmk5WcHly5chl8vZUYv3ITXWq6KiIm9WEqfGtJ08eTKjs5kzTTwev8WUut1u+P1+CIXCtAlPmXKRSJS1FyA0TcPn891yHB6PBwCgUChuubDI96ZTu92O3t5eRsde7iWJRAJXrlwBj8cjcozpdkgmkzhz5gwqKytRWlrKtJys4Hvf+x6++MUvYm5uLu/uymYa1njvA4cOHcKjjz6KL33pS0xLyQo8Hg8uXLiAkydP5sUb2H7idrtx6dIlNDc353ylLbWY5NChQ/u6nTJbicVi8Hq9txhYn8+XNuMSiQQikSj9RygUQiQSQSAQ7JspSiaTiEQiCIfDt/yJRCJpww0ASqXylsq9TCYjsqn0xo0bWF9fx4kTJ3L6+FN3noLBII4dO8ZWcO/DzMwMZmZm2Klcm+jo6MB73vMefPrTn2ZaSs7DGu994N///d/xmc98BjMzM+yV4U0GBgYQDodx+PBhpqVkPaktcgcPHoRer2dazo5IJBI4f/489Ho96uvrmZaTNcTjcXg8Hng8HoRCoTcZ4Hg8DoqibjHiqT9cLhcURYHD4YCiqPTfaZpO/0kmk+m/R6PRN5nsaDQKAOnH3vwcUqkUKpUKcrmcrYbeJPU6LiwszNmpFjRNY3BwEKurqzh+/Hhe33naCyKRCF555RV0dHTk7Pl3r7l8+TJOnjyJ5eVlaLVapuXkPKzx3gei0SjMZjO++c1v4oMf/CDTcrKCaDSKV155BW1tbTAYDEzLyXqWl5fR39+Po0ePQqPRMC1n2+RLpTDTxOPxu1akE4nELcY6ZbRTJvx2U87n899UTU/9nf2ZbJ1cXyk/Pj6Oubk5nDhxAhKJhGk5WU9/fz9isRi7Gn4T73nPeyCXy/GDH/yAaSl5AWu894nPfe5zOHPmDC5evMi0lKxhbm4uvVSHvRNwf2ZmZjA+Po7jx4/n1JrifMvGsrDkaq/C/Pw8hoeHcfz4cSgUCqblZD2pOe6nTp1iL1Ju4nA4UFpaikuXLuXllB8mYMse+8Qf/MEfoKenB5cvX2ZaStZgsVggEAgwOTnJtJScoLy8HBaLBZcvX0YoFGJazpYIhULo7+/HgQMHWNPNkjeUlJRAq9Wir68PuVKrstlsGBwcRGdnJ2u6twBN07hx4waqqqpY072Jr3zlK+js7GRN9x7CGu99wmAw4GMf+xjbYLkJiqLQ3NyMqakpBAIBpuXkBHV1dSgoKMDly5fT+dxsJTWPXK/Xw2w2My2HhWXPoCgKLS0t8Pl8mJmZYVrOfXG5XOjt7UV7ezs7XWuLzM3NIR6Po7KykmkpWYPH48GPfvQjPPXUU0xLyStY472PfOpTn8Krr76KoaEhpqVkDWq1GmazGYODg0xLyQkoikpXj69cuYJYLMa0pLsyOTmJUCiE5uZmpqWwsOw5fD4fHR0dGB0dhdvtZlrOXVlfX8eVK1fQ2NgIo9HItJycIBKJYHR0FE1NTWwMchNf//rXUVpaikceeYRpKXkFa7z3kbKyMrz73e/GF7/4RaalZBX19fXprXcs94fD4aCjowM8Hg9XrlxBPB5nWtKbWFtbw8TERFonC0s+otFoUFVVhZ6enqz8PXS73bh8+TJqa2vZ+dPbYGRkBFqtlp1isolwOIzvfe97eOqpp9gpR3sMa7z3mc9+9rN47rnnMDs7y7SUrEEgEKC+vh6Dg4NIJBJMy8kJuFwuDh06BA6Hk3XmOxaLoaenB3V1dVCpVEzLYWHZV6qrqyESibLurp3H40F3dzeqq6tRUVHBtJycYW1tDcvLy2hqamJaSlbxrW99C3K5HI8//jjTUvIO1njvM42NjXj44YfZrPdtsI2W2ydlvimKwtWrV7PCfNM0jevXr0Mul6O8vJxpOSws+w5FUWhvb4fNZsPS0hLTcgC8YbqrqqrYjPI2YBsq70w8Hse3v/1tfOYzn2GjN/sAa7wzwFNPPYUf//jHcDgcTEvJGjY3Wvr9fqbl5Aw8Hg+HDh0CgKzIfC8sLMDpdKKtrY29HclCDGKxGK2trbh+/TrjjeKpbbcVFRWoqqpiVEuuMTs7yzZU3oEf/OAHiMViePLJJ5mWkpewxjsDHDlyBO3t7Xj66aeZlpJVqNVqlJSUYGBgIGdGdGUDKfOdip0wZb59Ph8GBwfR1taWU7ONWVj2AqPRiOLiYvT29iKZTDKiYX19PR0vqa6uZkRDrhIIBDAyMoLm5ma2qruJZDKJb3zjG/jUpz4FgUDAtJy8hDXeGeKpp57CD3/4Q3i9XqalZBX19fUIhUI5MaIrm0iZbx6Px8iowUQigZ6eHpSVleXkNj8Wlr2goaEBiUQCY2NjGX/utbU1XL58GTU1NWzFdpvQNI2BgQEUFxez56/b+MlPfgK73Y7f/d3fZVpK3sIa7wzx6KOPwmKx4Otf/zrTUrIKHo+H1tZWjI6OspGTbcLlctHZ2QmRSIQLFy5kdMnOyMgIOBwO6urqMvacLCzZBpfLRXt7O2ZmZrC6upqx57Xb7eju7kZdXR3bSLkD5ubmEAgEUF9fz7SUrOOv//qv8YlPfIJdgLaPsMY7Q1AUhaeeegrf/e53EQ6HmZaTVeh0OjZyskO4XC4OHjwIrVaL8+fPZ+SOit1ux8LCAjo6OsDhsKcQFrJRKBRobGxEb28vIpHIvj/f/Pw8enp60NbWhrKysn1/vnwjEAhgeHgYra2t4PP5TMvJKl566SWMjY3hj/7oj5iWktew75oZ5IknnoBcLse3vvUtpqVkHWzkZOekluxYLBZcvHgRa2tr+/ZcqZXwzc3NbEWEheUmFosFGo0G/f39+1Y8oGkaExMTGBoawuHDh2EymfblefKZzRGTgoICpuVkHU8//TQ+/vGPQ61WMy0lr2GNdwbhcrn49Kc/jW9/+9tZMQoum2AjJ7uDoijU1tairq4O3d3d+7KcaPNK+OLi4j1/fBaWXCW1Ut7r9e5L8YCmaQwNDWFmZgbHjx9n18DvkNnZWTZicheuXLmCK1eu4JOf/CTTUvIe1nhnmA996EOIxWL43ve+x7SUrCMVOdnPqlG+U1ZWhra2NvT09GB+fn5PHzu1Ep5dNMHC8mYEAgHa29sxOjoKj8ezZ4+bTCbR29sLh8OBEydOQKlU7tljk0RqigkbMbkzn//85/HhD3+YvZOSAVjjnWEEAgE+//nP4+mnn85IHjDXqK+vRyQSYSMnu8BkMuHQoUMYGhrC+Pj4nlzEbF4Jz75psbDcGa1Wu6cr5WOxGK5cuQK/348TJ06w8a4dQtM0+vv72YjJXTh//jzOnTuHv/zLv2RaChGwxpsBPvaxj0EkEuFrX/sa01KyDh6Ph5aWFjZysksKCgpw/PhxzM3Noa+vD4lEYsePFYvF0Nvbi9raWnYlPAvLfaiuroZQKNz1Snm/34/z58+DoigcO3aMnZW/C2ZnZxEKhdDQ0MC0lKzk05/+NP7wD/+QjRBmCNZ4MwCPx8PTTz+Nv/u7v9vTW5L5gk6ng8ViQX9/P2OLKfIBpVKJrq4uBINBXLx4cUfjBlMr4WUyGTu2jIVlC2xeKb+8vLyjx1hZWcH58+dhMBhw+PBh9i7TLvD7/RgZGUFLSwt4PB7TcrKOZ599FsPDw/jsZz/LtBRiYI03QzzxxBMoKyvDF77wBaalZCV1dXWIRqMYHx9nWkpOIxKJcPToUSgUCpw7d27bE08WFxfhdDrR2trKroRnYdkiYrEYLS0tGBgY2NZKeZqmMT09jWvXrqGpqQkNDQ3s790uSC36slgsbMTkDiSTSfzlX/4l/vzP/xwajYZpOcTAGm+GoCgKf/3Xf43vfe97sNlsTMvJOng8Hg4ePIjp6WmsrKwwLSen4XK5aGlpQVVVFbq7u7GwsLClr/P5fLhx4wba2togEon2WSULS35hMplgNpu3vFI+kUigv78fk5OTOHbsGHvbfw8YHh4GRVFsxOQu/PM//zOcTic+8YlPMC2FKFjjzSAnT57EkSNH8NRTTzEtJStRKBRoampCX18fu3Rol1AUhYqKCnR2dmJoaAjDw8P3bLpMJBLo7e1lV8KzsOyCxsZGxOPx+965C4fDuHTpEnw+H7q6utg5ynuAzWbD4uIiu+jrLkSjUXz5y1/GF77wBUgkEqblEAX7amSYr371q/iP//gPTE5OMi0lKykpKYFOp0NfXx87YnAPKCwsxAMPPAC73Y7Lly/fdbLO6OgoALAr4VlYdgGXy0VHRwemp6fvulLe5XLh3LlzkEqlOH78OMRicYZV5h/BYBD9/f1oaWlhJ8HchW984xvg8Xj47d/+baalEAdFs26Gcd7//vcjGo3i2WefZVpKVhKLxXDu3DmUlJSgurqaaTl5QSwWw8DAAFwuFzo6Om5ZyOFwONDT04Ouri7IZDIGVbKw5Aezs7OYmJjAgw8+mJ5OQtM0JicnMTExgbq6OpSXl7N57j0gmUzi4sWLUCqVOHDgANNyshK/34+Kigp861vfwvve9z6m5RAHa7yzgKmpKTQ2NuL8+fPo7OxkWk5W4na7cfHiRRw5cgRarZZpOXkBTdOYn5/H0NAQKisrUVNTg0gkgrNnz6KxsZHNmLKw7BE0TeP1118HTdPo7OxEJBJBX18fgsEg2tvb2WjJHjI8PIyVlRU88MAD4HK5TMvJSj71qU/hlVdeQU9PDxvDYQDWeGcJf/AHf4CxsTGcOXOGaSlZy8zMDCYnJ2+pGrHsHo/Hg56eHgiFQtA0DYlEgvb2dqZlsbDkFdFoFGfPnoXRaITVaoVOp8OBAwfYUYF7iMPhwOuvv46uri7I5XKm5WQlDocDVVVV+NnPfoaHH36YaTlEwl7qZAmf+9zncPXqVbz00ktMS8laysrKoFKp2JXye0xq3nc8Hsfa2hqMRiPTklhY8g4ejwedTofZ2VlYLBa0t7ezpnsPCYVC6OvrQ3NzM2u678FTTz2FgwcPsqabQVjjnSUYDAb88R//MT772c+yS2PuAkVRaG1thdfrxfT0NNNy8gqfzwe/34/q6mr09fVheHh4V9suWVhY3iAUCqG7uxtutxulpaWwWq3s79ceQtM0ent7odfrUVJSwrScrGVqagr//u//jr/+679mWgrRsFGTLMLr9aK0tBR///d/jyeffJJpOVnL2toauru72bz3HhGLxfDaa6+htLQUVVVV8Pl86O3tBU3TaG1tZdfEs7DsEJqmsbCwgKGhIZhMJjQ1NYHD4eDSpUuQy+VoaWlhWmJeMDIyApvNhq6uLnY75T1497vfDQ6Hg2eeeYZpKUTDGu8s49vf/ja++tWvYmxsjJ2teQ9mZ2cxNjaGrq4u9vu0C2iaRl9fHyKRCI4cOZKeqpBMJjE5OYnJyUlUVFSgpqaGbcJhYdkGoVAIAwMD8Hq9aGlpgV6vT/9bMBjEa6+9hgMHDqCoqIhBlbnP0tISrl+/jgceeICNmNyDM2fO4O1vfzuGhoZQUVHBtByiYY13lpFIJNDe3o5Tp07hb//2b5mWk7XQNI0bN25gfX0dx48fZ6scO2RhYQHDw8M4efLkHbdTejyedKaerX6zsNyf26vcjY2Nd8xyW61WDAwM4MEHH2SLBzskNe3q4MGDt1zYsNxKIpFAc3Mz3vOe9+ALX/gC03KIhzXeWcjly5fx0EMPoa+vD7W1tUzLyVqSySS6u7shFArR0dHBzsDdJn6/H+fOnUNHR8c937SSySQmJiYwNTWFyspKVFdXs9VvFpY7cK8q9524fv06vF4vjh07xv5ObZNwOIxz586hvLwcVVVVTMvJap5++ml85zvfwejoKLugKQtgjXeW8tGPfhSLi4t49dVXmZaS1UQiEZw/fx4lJSWoqalhWk7OkEwmcf78eeh0OjQ2Nm7pazweD/r6+gCArX6zsGxic5XbaDSiqalpSxNL4vE4zp8/D6PRyG6J3QaJRAKXLl2CVCpFW1sbW3S5BzabDfX19fjRj36Ed7zjHUzLYQFrvLOWlZUVVFdX4zvf+Q7e//73My0nq/F4PLhw4QLa2tpgMpmYlpMTDA0Nwel04sSJE9taMrG5+l1cXIy6ujoIBIJ9VMrCkt243W7cuHED4XAYzc3NMBgM2/p6r9eL8+fP4/Dhw7dskGW5MzRNo7+/Hz6fD8ePH2eX5NyH973vffD7/Xj++eeZlsJyE9Z4ZzH/8A//gK997WsYHR1lM4D3wWq1oq+vDydOnIBSqWRaTlaTWjLx4IMP7nglvN/vx+DgINxuN+rr61FSUsJWnViIIhqNYmxsDAsLCygvL0d1dfWOe01SK+VPnjzJXsjeh+npaUxNTeGBBx5gYxP3gW2ozE5Y453FJBIJtLW14aGHHmIbLbfA+Pg45ufn0dXVxW62vAvhcBivvfZa2izvBpqmYbfbMTg4CJFIhObmZjZ+wpL30DSNxcVFDA8PQ6lUorm5eccXsJsf89q1awCAzs5O9iL2LqysrODatWs4duwY1Go103KymkQigQMHDuCJJ57AF7/4RablsGyCNd5ZTnd3Nx5++GH09/ezGeb7QNM0enp6EIlEcPToUbZZ6TZomsbly5chFAr3NBcZj8cxOTmJ6elpNn7CktdsjpU0NjbCaDTu2e9RaqV8dXU1ysrK9uQx8wmfz4fz58+jubkZxcXFTMvJer761a/iH//xHzE2NsbeGcgyWOOdA3zkIx/B0tIS22i5BeLxOC5evAiVSoUDBw6wlaNNTE1NYXZ2Fg8++OC+rKreHD+pqalBaWkpe/HDkheEw2GMj49jcXFx17GSe+F0OnHlyhU88MADUCgUe/74uUo0Gk03oTY0NDAtJ+ux2+2oq6vDD3/4Qzz22GNMy2G5DdZ45wArKyuoqqrCd7/7XbbRcgsEg0FcuHABpaWl7F2Cm6yvr+PSpUs4+v+3d+dxUZb7//hfbLLv+w4KyC6yKCACbmhprkmlpVZmaaeO55zOp85psTrHyk5Wx8xMSy3UXNJwSbOjAQqyCCigsm+yDfsAM8w+9++PvjM/yQ1kuWd5Px+PeQg4zLzZ5n7d131d1zs2FjY2NqP2PAzDoLW1FTdv3oRMJkNAQABcXV3pBIioJYlEgsrKStTU1MDBwQGBgYHDnlbyIKWlpWhpaUF8fDz1J8DvgynZ2dkYN24cTcMZpOTkZPT19eHMmTP0/VJBFLzVxBdffIFPPvmEFloOUm9vLzIzMxEYGAgvLy+2y2GVRCJBRkYGPDw84OfnNybPqZgHW1ZWBgMDAwQGBsLBwYEOAkQtyGQy5YJHS0tLBAYGjtmcYrlcjqysLFhYWGDSpElj8pyqSi6XIy8vD1KpFDExMbSDySDQgkrVR8FbTUilUoSHh2POnDnYunUr2+Wohc7OTmRnZ2v9NoMFBQUQCoWIjY0d8+B7e4CxsLBAYGDgqI64EzIccrlcecJoaGiIwMBA2Nvbj/nfjaKlfFhYmNa+djEMg2vXroHL5SIuLm5UpsdpGsWCyiVLluBf//oX2+WQe6DgrUaysrIwZ84cFBQUULOFQWppaUFBQYHW7pHb0NCA69evIzExkdUFNhKJBFVVVaiuroaDgwMmTpxI2z4SlcEwDFpaWlBaWgqGYeDv78/6FKmmpiYUFRVpbUv5mzdvorGxEdOnT6fFgYP0wQcfKDtUauPvjLqg4K1m1q1bh6tXryInJ4cuuw1SfX09rl+/jri4OK0Ke4qW8BEREUNu6jFahEIhKioqcOvWLdjZ2cHX1xe2trZsl0W0lGKEu6qqClKpFH5+fvD09FSZRcHXrl1DX1+f1rWUr66uRkVFBeLi4mBubs52OWqhvLwckZGROHLkCB555BG2yyH3QcFbzfT29iIoKAjr1q3D22+/zXY5aqOiogI1NTWIj4/XipEAuVyOS5cuwcbGBiEhIWyXcwehUIiamhrU1tbC0tISvr6+NAecjBmpVIr6+npUVVVBX18fPj4+cHd3V7lwK5VKkZGRAVdXV/j7+7NdzphobGzEtWvXaK/uIZDL5YiNjUVgYCD27NnDdjnkASh4q6Hz589j0aJFyMvLo62VBolhGJSUlKCtrQ3Tp0/X+AY7N27cQHt7+5Bbwo81iUSC2tpaVFdXw9jYGL6+vnBxcaEATkaFWCxGbW0tampqYGxsDD8/vxHdi3s09PT04NKlS1oxXU7RICcqKgqOjo5sl6M2PvzwQ2zfvh03b97Uqqu66oqCt5p68cUXUVhYSFNOhkDRYKe/vx/Tpk3T2K26FAevhIQEtblMK5PJlCOQurq6mDBhAtzd3TX2Z0TGFp/PR21tLerq6mBtbQ1fX19WFk0+rJqaGlRWVmp0S3kul4usrCxqkDNE5eXliIiIwLFjxzB37ly2yyGDQMFbTfX19SEoKAhr167FO++8w3Y5akMmkyEnJwc6OjqYOnWqxp20KFrCBwQEwNPTk+1yhkwul6OpqQnV1dXg8/nw8PCAt7f3qO+dTDQPwzBob29HbW0t2tra4OTkhAkTJqjlrjqKlvI6OjqIiopSmxOGwerr60NmZiZ8fX3h4+PDdjlqQzHFJCgoCN9++y3b5ZBBouCtxi5cuICFCxfSlJMhkkgkuHz5MgwNDTFlyhSVm9f5sBiGQU5ODgwMDBAREaHWB2eGYdDd3Y2amhq0tLTAzs4OXl5ecHR01JifFxkdYrEYDQ0NqKurg1gshpeXF7y8vNR+ZwyRSIT09HSNaynP4/GQlZUFd3d3BAYGsl2OWvnggw/w5Zdf0hQTNUPBW82tX78eV65cQW5ursaN3o4miUSCrKwsGBsbIyoqSiPC3Gi3hGeLUChEfX096uvrwTAMPD094enpqfZBiowcxYlabW0tmpubYWVlBS8vL7i4uGjU62J7eztyc3M1pqU8n89HZmYm3NzcEBgYqNaDBWOtrKwMkZGRNMVEDVHwVnM8Hg9BQUF47rnnsGnTJrbLUStisRiXL1+GiYkJIiMj1Tp8c7lcZGZmjnpLeDYp2tHX19ejtbUVtra2cHNzg4uLi0adaJDB4/F4aGxsRGNjI0QiEdzd3eHl5aURofReFC3lExIS1Pqkor+/H5mZmXB2dkZwcDCF7iGQy+WIiYlBSEgIvvnmG7bLIUNEwVsDpKWlYcGCBcjNzUVwcDDb5agVsViMrKwsmJmZISIiQi3DNxst4dkmFArR1NSEhoYG9PX1wcnJCW5ubjQVRQuIRCI0NTWhsbERXC4Xjo6OcHd3h6Ojo1oH0cGSy+XIzMyEpaWl2raU7+/vR1ZWFhwdHRESEkKhe4g++OAD7NixAzdv3tTok0xNRcFbQ2zYsAG5ubnIy8vTioPPSBKJRMjKyoK5ublahu/CwkIIBAJWWsKrgr6+PuWop0QigaurK9zc3GBjY6OV3w9NJJVKweFw0NjYiLa2NlhbW8Pd3R0uLi4au8vH/fT39yMtLQ2TJ09Wu5byitDt4OCA0NBQ+hsdotLSUkRFReH48eNISkpiuxzyECh4awgej4fg4GCsWbMG7777LtvlqB2RSITLly/D1NRUraadqEpLeFXAMAy6urrQ2NiIpqYm6OrqwsnJCU5OTrC3t6cTUjUjFArR2toKDoeD9vZ2GBsbw93dHW5ublrRBOtBFC3lZ8yYoTZ/+3w+H1lZWXBycqKR7oegmGISGhqK3bt3s10OeUgUvDVIeno65s+fj5ycHJXsVqjqFHO+1WXBJZ/PR3p6ukq1hFcVcrkcnZ2d4HA44HA4EIlEsLe3h5OTExwdHWFkZMR2ieQPGIZBX18fWlpawOFw0NPTAysrK+XJk7m5OQW1P7h69Sr4fD6mTZum8t8bxe4lLi4uNKf7If373//G119/jRs3btAUEzVGwVvD/OlPf0JGRgby8/M1vjvjaBCLxcjOzoahoSGioqJUdpRU0RLe2toaoaGhbJej0hSBThHCuVyuMtDZ29vD0tJS5U+yNJVEIkFXVxdaW1vR2to64ATJycmJXsMeQNFS3s3NDRMnTmS7nHtShG7aveThFRQUID4+HqmpqZgzZw7b5ZBhoOCtYQQCAaZMmYIpU6bQhvoPSSKRIDs7G/r6+oiKilLJHTNu3LiBtrY2xMfHq+zJgapSTGFobW1FR0cH5HI5bG1tYWdnBzs7Owrio0gRtDs6OtDR0YGenh6YmJgow7adnR39Pg+RoqV8TEwMbG1t2S7nDlwuFzk5OfDw8EBAQACF7ofA4/EwefJkLFmyBB9//DHb5ZBhouCtgRT7e+7atQsrVqxguxy1JJVKkZeXB7FYjJiYGJUaeVPHlvCqimEY9Pb2KoNgZ2fngCBua2sLS0tLCoMPSSQSobu7G52dnQOCtuJ7a2dnpzbzk1VZdXU1qqurkZiYqFKLTdvb25GXlwc/Pz/4+vqyXY7aSk5ORn19PTIzM1VyIIgMDQVvDfX999/jz3/+M/Lz8zFhwgS2y1FLcrkcV69eRXd3N2JiYmBqasp2SRCJREhLS1PblvCq7o9BvKurCxKJBObm5rCysoKlpaXyXwrjA4lEInC5XHC5XPT09IDL5UIgEMDU1JSC9ihjGAa5ubnQ1dVVmZbyTU1NuHr1KkJDQ+Hh4cF2OWpr586deOONN1BUVESv+RqCgrcGW7VqFW7cuIHc3Fzo6+uzXY5aYhgG169fR1NTE2JiYlhty6toCa+vr4/IyEiVOLhqOoZhIBAI7giUijBuaWkJS0tLmJmZwczMDCYmJhr/c5FKpeDz+eDz+ejr61N+XxQh+48nKKo0AqvJFCfl/v7+8PLyYrWW2tpa3LhxA1FRUXB0dGS1FnVWUlKC2NhYpKSkYPHixWyXQ0YIBW8NxuPxEBERgTlz5mD79u1sl6O2GIZBVVUVKioqMGXKFNjb27NSh+Jy8owZM+hyI4tuD+M9PT3o6elRBlEdHR2YmJgog7iZmRlMTU1hamoKQ0NDtZk7LpVKIRQKwefzwePxlDc+nw+BQAB9fX2YmpoOOPmwsrKi30uWsd1SnmEYlJWVoba2FtHR0RrbRXcsCIVChIeHY9asWfjiiy/YLoeMIAreGq64uBgxMTFISUnB0qVL2S5Hrd26dQvFxcUIDw8f86YV2tASXt3J5XL09/ffM6wCgKGhIYyMjJT/Km6GhoYwNDSEvr7+gJuuru6wR9AZhoFMJoNUKlXeJBIJRCIRhEIhhELhgLeFQiGkUil0dXXvehJhZmYGQ0NDjR/ZV1c3b95Ea2vrmC+8lsvlKC4uRltbG2JiYmj9yTCtXr0axcXFyMnJUak1RmT4KHhrgZ07d+Ktt97C1atX4e7uznY5ao3D4SA/Px9BQUHw9vYek+eUSqVIT0+Hu7u7Sm8ZRu5NLpffEW7/GHhFIpEyICtelnV0dKCvrw89PT3lvzo6OgNuivsyDKO83R6yZTKZsg5dXV1lqP9j+L/9JMDIyAjjxo2jcK2GFC3lraysxmyrUZlMhvz8fPD5fMTExNA8/mHat28fXn31VRQWFsLHx4ftcsgIo+CtBRiGQXJyMhobG5GZmUmLwoapq6sLOTk58Pb2hr+//6iHE3VqkkGGj2EYyOXyO8Kz4m3FfRQ3RQAHoHz79rBuYGCgfFtdprqQ4VE01woPD4ezs/OoPpdEIkFubi4YhsHUqVNpTv8wlZeXY+rUqdi5cyeefPJJtssho4CCt5bo6elBWFgYli1bhk8++YTtctReb28vsrOzYW9vj0mTJo3ayUxjYyOKi4vVqi00IYR9Y/HawefzkZubC1NTU0RERNAi/mESiUTKPhzUEl5zUfDWIvn5+YiPj8fx48cxb948tstRewKBAHl5edDR0cGUKVNGvA35WI5aEUI0z2heLWtvb8eVK1fg7u6OoKAgupoyAtatW4fMzEzk5+fDxMSE7XLIKKG/FC0SGRmJzZs3Y82aNeBwOGyXo/aMjY0RFxcHU1NTZGRkgMvljthjy+VyFBQUwN3dnUI3IeShhISEQCgUoqKiYsQek2EY1NbWIjc3F0FBQQgJCaHQPQKOHDmCAwcO4Mcff6TQreFoxFvLMAyDhQsXoqurCxkZGXRpcAQothssLy9HWFgY3Nzchv2YbO1MQAjRLIodkUaipbxcLkdJSQlaWloQFRWlki3q1VFZWRliY2OxdetWPPvss2yXQ0YZBW8t1NPTg6ioKMTFxWHPnj1sl6MxOBwOCgoK4O3tjYCAgIe+tMv2XryEEM0yEj0ARCIRrly5AqlUiilTptCo7AhRHI9nz56NHTt2sF0OGQMUvLWUohnMu+++i40bN7Jdjsbo6+tDbm4uzM3NER4ePuSDnCp1nyOEaAZFS3k9Pb2H6nrb09OD3NxcWFtbY/LkyXSldITIZDLMnTsXEokE58+fpwZUWoImZmkpPz8/HDlyBP/85z/x66+/sl2OxjA3N0d8fDxkMhkuXboEPp8/6M9lGAZXr16FjY0NPD09R7FKQog20dHRweTJk9HZ2Ylbt24N6XObm5tx6dIleHp6IjIykkL3CNq4cSOqqqpw7NgxCt1ahIK3FktKSsLmzZuxcuVKVFVVsV2Oxhg3bhyio6Nhb2+PjIwMtLe3D+rzampq0Nvbi7CwMNqvmxAyogwNDREeHo6SkhL09fU98P6K9u9Xr15FREQEJk6cSK9LI2j37t3Yt28fTp8+DTs7O7bLIWOIpppoOYZh8NxzzyEvLw+5ubkwMzNjuySNUl9fj5KSEvj6+sLPz++eB66enh5cunRpRBZAEULIvdy4cQNtbW33XbgtEolQWFgIHo+HqVOn0lqTEZaZmYm5c+fi4MGDWLRoEdvlkDFGwZtAJBIhISEBtra2OHXqFG0NNcK4XC7y8/NhbGyMiIiIO/b7lkqlyMjIgJubG7WEJ4SMKrlcjkuXLsHa2vquLeU7OjqQn58PW1tbhIWF0RSIEdbQ0IApU6bg5ZdfxltvvcV2OYQFFLwJgN935IiIiMDKlSvx8ccfs12OxpFIJCguLkZ7ezvCw8Ph4OCg/D9qCU8IGUuK5lwRERFwcnIC8PvVz/LyclRVVSEoKAheXl70ejTChEIhYmNj4ePjg8OHD9P3V0tR8CZKhYWFiI+Px86dO/H000+zXY7GYRgGt27dQklJCcaPHw9/f3+0tLSgqKiIWsITQsZUY2MjSkpKkJiYCOD313+hUIjIyEhYWlqyW5wGksvlSE5ORlVVFS5fvkzbMWoxCt5kgCNHjuD5559HWloaIiMj2S5HI/X29iI/Px+6urrg8XgIDw+Hi4sL22URQrRMYWEhenp6IBQK4eDggEmTJtGuJaPkvffew/bt21FYWAh3d3e2yyEsosm8ZIDk5GT8+c9/xtKlS6mt/CixsLBAXFwcBAIBGIahOfWEkDEnl8thYGCA3t5e2NraIiIigkL3KDl+/Di2bNmCEydOUOgmFLzJnd5//32EhYVh0aJFEIlEbJejkaqrq2FoaIhJkyahoKAA169fh1wuZ7ssQogW6O/vR2ZmJtrb2xEZGYm2tjZ0dXWxXZZGKikpwXPPPYft27cjNjaW7XKICqCpJuSu+vr6EBsbC29vb6SmptKo7Aj6Y0t4Ho+H/Px8MAyD8PBwml9JCBkVDMOgoaEB169fh4uLC0JCQqCnp4eqqirU1NQMq6U8uVN9fT3i4uKwfPlyfPrpp2yXQ1QEBW9yT83NzYiJiUFSUhJ2797NdjkaQSQSIT09HX5+fvD29lZ+XC6Xo7y8HNXV1fDx8YGfnx+d7BBCRoxAIEBRURG4XC7CwsKUu5kAvwfynJwcGBgYICIignbbGAFdXV2YNm0awsLCcODAAXo9J0oUvMl9VVRUICYmBi+99BI2b97MdjlqjWEY5OXlQUdHB1FRUXc9uHG5XBQWFkJXVxeTJ0+m0W9CyLDcPsrt6OiIkJAQjBs37o77CYVCpKenIyAgAJ6enixUqjmEQiESEhJgZmaGs2fP3vX7TbQXBW/yQFeuXMHMmTOxefNmvPrqq2yXo7ZqampQWVmJGTNm3PeFWCaToaKiAtXV1fD19YWvry+NlhBChuz2Ue5JkybB2dn5vvdva2tDXl4eEhISYG5uPkZVahaZTIb58+ejra0NGRkZ9H0kd6DgTQbl119/xeLFi7Fv3z4kJyezXY7aUbSEj46Ohp2d3aA+p7u7G1evXoWuri7Cw8OpbTMhZFAYhlHu032/Ue67GUxLeXJ3crkcq1atQnZ2NrKzswc0SiNEgYI3GbSDBw9i3bp1OHHiBGbNmsV2OWpD0RLe1dUV/v7+Q/pcGv0mhAyFUChEUVERuru7BzXK/UeKlvI2NjYICQkZpSo102uvvYaUlBTk5OQMWMNDyO1o004yaCtWrEBraysef/xx/Pbbb5g8eTLbJamF69evY9y4cfDz8xvy5+rp6SEgIABOTk64evUqWlpaaO43IeQOfxzlnjlz5kPNLdbV1UVERAQyMjJgb28/YBEmubf//Oc/2L17NzIyMih0k/uiEW8yZK+//jpSUlJw6dIlTJgwge1yVFpTUxOKioqQmJg47BbBMplMufOJl5cX/P39aesvQgh6e3tRXFwMHo/3UKPcd6NYkJmYmAhjY+MRqFJzff/993jppZdw5swZJCYmsl0OUXEUvMmQMQyD1atXIzs7G5cvX4a9vT3bJamk/v5+pKenIywsbERbwvf19aG4uBh9fX0ICgqCm5sbbf9FiBaSSCQoLy9HbW0tvL29MXHixBE9GS8oKIBQKERsbCy9xtzDL7/8gqVLlyIlJQXLli1juxyiBih4k4cikUiwaNEicDgcXLp0CaampmyXpFLkcjmysrJgYWGBSZMmjfjjMwyD5uZmXL9+HSYmJggNDaXpJ4RoCcW0khs3bsDc3BwhISGjsvhaIpEgIyMDHh4eDzVVTtPl5uYiKSkJH330EdavX892OURNUPAmD62/vx8zZsyAqakpfv31V+jr05IBhdLSUrS0tCA+Pn5Uvy9SqRTl5eWoqamh6SeEaIHbp5UEBwfD1dV1VEeju7u7kZWVhdjYWNjY2Iza86ibyspKTJ8+HS+++CLee+89tsshaoSCNxmWzs5OxMXFwdfXFz/99BNtPwWgo6MDOTk5ypbwY6Gvrw8lJSXo7e1FYGAg3N3d6dIwIRrk9mkl48ePh5+f35idZFdWVqKurg6JiYl0Yg+gtrYWiYmJmDdvHnbu3EmvtWRIKHiTYVOM7IaEhODo0aNaHb7FYjHS0tLuaAk/Fmj6CSGaZ6ymlTyohuzsbIwbN07rW8rX19cjMTER8fHx2Lt3L23vSoaMgjcZEU1NTZg+fTrCw8Nx+PBhrQzfipbwADBlyhTWDk63Tz9R7B0+3B1VCCFjr729HTdv3oRQKERwcDBcXFxYe10RCoVIS0tDUFAQPDw8WKmBbQ0NDUhISEB0dDRSUlK08jhHho+CNxkxDQ0NmD59OqKjo3Hw4EGtGwmora1FRUXFA1vCjxU+n4+ysjI0NzfDy8sLfn5+MDQ0ZLssQsgDcLlc3Lx5E93d3fD19cX48eNVYg1Na2srrly5opUt5ZuampCYmIiIiAjs379fJX4eRD1R8CYjqr6+HtOnT0d8fDy+//57rQnfvb29uHjx4pBawo+Vnp4elJaWorOzEz4+PpgwYQIdNAhRQTweD2VlZeBwOPD29oavr69KnMTf7vr16+jo6MD06dO1ZsSXw+EgPj4eoaGhOHToEL1+kmGh4E1GXG1tLaZPn46ZM2di3759Gh++pVIpLl68CGdnZwQEBLBdzj11dHTg5s2b6O/vh5+fH7y8vDT+Z0OIOhAKhSgvL8etW7fg5uYGf39/lW1aI5PJcOnSJdjZ2SE4OJjtckYdh8PBjBkzMHHiRBw9epQWl5Jho+BNRkV1dTUSEhKQkJCAlJQUjQ54RUVF6O3txbRp01T+62QYBhwOBzdv3oRcLkdAQMCob0dGCLk7iUSCqqoqVFdXw8HBAQEBAWoxhYPH4yE9PR1RUVFwdHRku5xR09TUhJkzZ8Lf3x9Hjx5VuasPRD1R8Cajpra2FgkJCYiJicHBgwc18rJkc3Mzrl27NiIt4ccSwzC4desWysvLMW7cOPj7+8PR0ZECOCFjQCqVoq6uDpWVlbCwsEBAQIDa7ZF969Yt3LhxAzNmzICRkRHb5Yy4hoYGzJw5Uzm9hEa6yUih4E1GlWLrpYiICI3b7UTREn7SpElwdXVlu5yHIpPJUFtbi6qqKhgaGsLX1xcuLi4qP3JPiDoSi8WoqalBTU0NTE1N4e/vDwcHB7U84WUYBoWFhRCJRIiJiVHLr+Fe6uvrMWPGDEyZMoUWUpIRR8GbjLqGhgYkJiYiNDQUR48e1YgXMUVLeHNzc4SFhbFdzrDJZDLcunULVVVVAABfX1+4u7tr1IkSIWwRCASorq5GXV0drK2t4evrC3t7e7UPqxKJBOnp6fDy8oKvry/b5YyI2tpazJw5EzExMfj+++814nhFVAsFbzImFFsx+fv749ixY2o/V66srAxNTU1ISEjQqBdmuVyOpqYmVFZWQiwWw8fHB56ennSZlZCHwOPxUFVVhYaGBjg4OMDPzw/W1tZslzWiurq6cPnyZUybNk3tv7bKykrMnj0bCQkJ2Lt3Lw08kFFBwZuMmZaWFsyaNQsODg44ffo0zMzM2C7poShawk+fPl1jO0MqFmFWVlaCx+PB29sb48ePp33ACRmEnp4eVFZWoqWlBa6urvDx8RnzbpNjSRNayufn52PBggVYuHAhdu7cSdPtyKih4E3GVHd3N+bPnw+BQIBffvlF7VbEK1rCK5paaDqGYdDR0YHKykp0dXXB09MTEyZMUKuFpISMBYZh0NnZicrKSnR2dsLDwwM+Pj5a8beiaClvaGiI8PBwtZtCc+7cOTzxxBN45ZVX8P7776td/US9UPAmY04gECA5ORmlpaX45Zdf4OPjw3ZJg8IwDK5cuQKGYVhtCc+W7u5uVFZWgsPhwMnJCd7e3rCzs9O67wMht5NKpWhqakJNTQ36+/uVV4c0caeP+1HXlvIHDhzAunXrsGXLFvzpT39iuxyiBSh4E1ZIpVK8+OKLOHPmDE6fPo2IiAi2S3ogRUv4xMRErZ5y0d/fj9raWtTX18PIyAje3t5wd3fXqLnuhDwIn89HXV0d6uvrYWxsDG9vb7i5uWn134GipXxiYqJaTCX87LPP8Oabb+K7777D8uXL2S6HaAkK3oQ1DMPgrbfewo4dO3D48GEkJSWxXdI9KVrCT506Ffb29myXoxJkMhkaGxtRW1sLPp8Pd3d3eHl5afRcVqLdGIZBa2sr6urq0N7errzyY2trS1d+/p+SkhJ0dnYiPj5epedJv/766/jqq6+QmpqKmTNnsl0O0SIUvAnrtm3bhn/84x/YvXs3VqxYwXY5d5DJZMjIyFD5lvBsYRgG3d3dqKurQ1NTE6ysrODl5QUXFxfaFYBoBIFAgFu3bqG+vh4Mw8DT0xOenp4q29adTareUl4mk+H555/HmTNncO7cOUyePJntkoiWoeBNVMKRI0ewZs0abN68GX/5y1/YLmeAoqIi9PT0IC4uTqVHcFSBWCxGQ0MD6urqIBKJ4O7uDnd3d1haWtKIIFErMpkMbW1taGhoAIfDgb29Pby8vODo6EivAw/Q19eHjIwMlWspLxQKsWzZMpSWluJ///sfJkyYwHZJRAtR8CYq48KFC1iyZAk2bNiAjz76iO1yAPzeEv7q1auYMWOGVuxOMFIUOzzcunULzc3NMDY2hpubG9zc3GBqasp2eYTcFcMw6OrqQkNDA5qbm2FgYAA3Nzd4eHjQ7+0Q1dfXo7S0FImJiSqx0JTL5eLRRx9Ff38/zp07p1InBES7UPAmKqWwsBBz587F/Pnz8e2337I6VUEgECAtLU2tW8KrAqlUitbWVjQ0NKCtrQ3W1tZwc3ODq6ur2jdSIpqht7cXjY2NaGxshEwmg4uLC9zd3WFtbU1Xah4SwzAoKCiAWCxmvaV8Y2Mj5s6dC0dHR6SmptI6FMIqCt5E5VRVVWHOnDkIDAzEsWPHWBktYRgGWVlZMDU1pTmAI0gkEqG5uRmNjY3o7u6Go6Mj3Nzc4OTkRPPByZgSCARoampCY2Mj+vr64OzsDDc3Nzg4ONBUkhGiaCnv7e3N2raxpaWlmDdvHqZMmYL9+/dr9Y5URDVQ8CYqicPh4JFHHoGOjg5OnjwJNze3MX3+8vJyNDY2alxLeFXC5/OVo4xCoRDOzs5wdnaGvb09fc/JqBAIBGhtbUVTUxM6OzthZ2cHNzc3ODs7q23HRVXHZkv5n3/+Gc888wyefvppfP7553RCRVQCBW+isvr7+7F69WpkZWXh6NGjmDZt2pg8b2dnJ7KzszW6JbwqYRgGXC4XTU1N4HA4EAgEsLe3h5OTE5ycnFRifihRTwzDoLe3FxwOBxwOBz09PbC2toazszNcXV1pV5IxUlFRgVu3biEhIWHMTnC2bNmC9957D1u3bsX69evH5DkJGQwK3kSlMQyDzZs348MPP8R///tfrF27dlSfTywWIz09HRMmTKAV7yxgGAY8Hk8ZlLq7u2FpaakM4RYWFjTnltyXTCZDZ2cnWlpa0NraCrFYDAcHBzg5OcHR0ZGmGrCAYRhcvnwZRkZGo94sTSwW49lnn8XZs2fx008/ISEhYVSfj5ChouBN1EJqaiqeeeYZPPvss/jss89GZT6woiW8XC7H1KlTKeCpAJFIhNbWVnA4HLS1tWHcuHHKEG5ra0vzwgkA+j1RBwKBAOnp6QgODoa7u/uoPAeHw8HChQvR39+PU6dOwdvbe1Seh5DhoOBN1EZJSQkWLFgAPz8//PjjjyM+DaSurg5lZWWYMWMGjYqpIJlMho6ODuVouEQigY2NDWxtbWFnZwdra2uaw6klxGIxOjs70dHRgc7OTvT09MDKyoqujKg4DoeDgoICJCQkjHhL+by8PCxbtgwRERHYv3+/WrSsJ9qJgjdRKx0dHVi6dClaW1tx8uRJTJw4cUQel1rCqxeGYdDX16cMXx0dHZDJZLCxsYGdnR3s7OxgZWVFQVxDKIK24ufd09MDMzMz5c/a1taW1gKoiZKSEnR1dWH69Okj9veZkpKCDRs2YOPGjXjvvffo756oNAreRO1IJBK88sorOHLkCFJSUjB//vxhPZ5MJsPFixfh6OiIwMDAEaqSjCVFEFeMgN4tiFtaWtKUAzVBQVtzKV5vHRwcEBQUNKzHksvleP311/HVV19hz549SE5OHqEqCRk9FLyJ2tqxYwdee+01vPvuu/i///u/h36c4uJicLlcagmvQe4WxCUSCSwsLGBlZQVLS0tYWVnBwsKCwjjLxGIxuFwuuFwuenp6wOVy0d/fT0Fbgylayk+ZMgUODg4P9Rg8Hg/JyckoLi7GqVOnqN8CURsUvIlaS0tLw7Jly/Doo49iz549Q+6E2NLSgsLCQiQmJlJLaA3GMAz6+/vvCHhSqRQWFhbKIG5paUkj46NIJBIpv/eKn0N/fz9MTEwGnBBZWVlRV1MNN5yW8lVVVVi4cCEsLS2RmppK7d+JWqHgTdReTU0NHnvsMZiamuLo0aPw9PQc1OcpWsKHhoaOeYMewj5FGL89CCrCuLm5OczNzWFmZgZTU1OYmZnBzMyMmqwMAsMwEAqF4PF44PP54PF44PF46O3thUAgUIbs24M2hWztwzAM8vPzIZVKER0dPejFsKdPn8aaNWuwcOFCfPXVV7QQnqgdCt5EI/T19WHt2rW4cOECvv76ayxbtuy+96eW8ORuGIaBQCAAl8tVBkZFeBSLxTA0NBwQxBVvm5qaat0ouVgsviNcK96WyWQwMTEZ8L0yNzeHpaUlhWyiJJFIkJaWhvHjxz+wpbxUKsVrr72GXbt24eOPP8bLL79MO9cQtUTBm2gMhmHw7bff4s9//jNWr16Nzz///J4H+fLycjQ0NCAxMZHak5NBeVDQNDQ0hKGhIYyMjJS3u72vygGdYRhIpVIIhUKIRCIIhULl7Y/vS6VSOhEhw6ZoKR8XFwcrK6u73qeurg7Jycno6urC0aNHabCEqDUK3kTjlJSUYPny5TAxMcGRI0fuGElRtIS/3ws9IYOlmFrxx9vdgisAGBgYwMjICAYGBtDX11fe9PT0Brz/x5uOjo7yBkD5tuIl/PZ/GYaBXC6HVCp94E0mk0EqlUIsFkMoFEImk0FXV/eeJw+Kj5mYmNDUGzIiFAMhd2spf/ToUbz00ktISkrCrl27YG5uzlKVhIwMCt5EI/H5fLz88ss4ceIEtm/fjpUrVwL4/y9tUkt4MtYYhhkQxh8UhP94UwRqxU3xmADuGsh1dXXvGuDvFfAVJwSKkwK6jE/GiqKlvLGxMcLDwwH8foXp1VdfRUpKCr744gs8++yz9DtJNAIFb6LR9u/fj/Xr12P58uXYsWMHSkpKIJPJqCU8IYSokNtbyguFQiQnJ0MkEuHo0aPD3u+bEFVCmxYTjfb0008jPz8f+fn5iIiIwI0bNzB58mQK3YQQokKMjY0RFhaG3bt3IyoqChEREcjPz6fQTTQOjXgTrSAUCrFx40YcPHgQn376KdauXct2SYQQQv4foVCIl156CT/++CN27dqFFStWsF0SIaOCgjfRKj/++COef/55zJ8/H7t376amOYQQwrIbN24gOTkZBgYGOHr0KHx9fdkuiZBRQ1NNiFZ5/PHHce3aNVRWViI8PBw5OTlsl0QIIVpJLpdj27ZtiI6OxsyZM5Gbm0uhm2i8IY94y2QySCSS0aqHPCQDAwPaN3cIxGIxNm3ahM8//xzr16/HRx99RI09CCFkjNTV1WHNmjW4ceMGvvnmGyxatIjtkggZE4MO3gzDgMPhgMvljnJJ5GFZWVnBycmJFg4OQV5eHlatWgVdXV3s3bsXU6dOZbskQgjRWHK5HF9++SXefvttzJs3D19++SVsbW3ZLouQMTPo4N3S0gIulwsHBweYmJhQuFMhDMOgv78fbW1tsLKygrOzM9slqRWhUIh3330X27Ztw/r16/Hhhx/S6DchhIyw+vp6rFmzBtevX8fXX3+NpUuXsl0SIWNuUMFbJpOhoqICDg4OdGaqwjo7O9HW1gY/Pz+advIQFKPfenp62Lt3L6ZMmcJ2SYQQovbkcjl27NiBt956C0lJSdixYwfs7OzYLosQVgxqcaViTreJicmoFkOGR/HzoTn4D2fKlCm4du0aFixYgMTERLz22msQi8Vsl0UIIWqrvr4ec+bMwbvvvotvv/0WR44codBNtNqQdjWh6SWqjX4+w2dkZIQtW7YgLS0Np06dQnh4OPLy8tguixBC1IpiLndYWBhsbGxQWlqKZcuWsV0WIayj7QQJuYupU6eiqKgIjzzyCBITE/H3v/+dRr8JIWQQGhoaMGfOHLzzzjvYvXs3jh49Cnt7e7bLIkQlUPAmo6qhoQFdXV0PvB+Xyx3U/RQqKysHdT+xWIy6urqHelwjIyP85z//wc8//4zDhw8jODgY//nPf3Dq1CnU1NQM+jEJIUQbyOVyfPXVVwgNDYW1tTXKysrw+OOPD+pzu7u70dHRMejnGotjgAKfz8elS5dw9OhRHDx4kI4BZFj02S5gtPX09GDLli1ITU2FQCBAf38/vL298dtvv6GtrQ3+/v4QCoVsl3lPUqkU27Ztw8WLF5Gamsp2OXd16tQptLa2oq+vD/r6+jA2Noavry8SEhJQXV0NJycn2NjYKO9/7do1SKVSREZGKj9WU1MDqVSqXNBYUVGB06dPw8LCAgDg6uqKWbNm4eDBg1izZg0uXLgwoNFCV1cXTp06BaFQCAsLCyxZsgRGRkbo7+9HTk4OvLy8APy+g8mhQ4ewZs0a5efu3LkTL730EgAgLS1twOMyDIOKigocO3YMBw8exNtvv43k5GS0trZCIBAgKChoxL+fhBCibvLy8vDiiy+iuroaK1euRGRkJLKysjBz5kzl63h6ejqqqqogFAohkUhgbm4OZ2dnzJ8/H/X19RAKhcr536p0DNi/fz9iY2MRGRkJAwMDdHV14X//+x8dA8hD0ejg3dbWhsTERDz55JPIzs6GpaUlGIZBZmbmiO76ce7cOXz33Xc4ePDgiD0mAOzfvx9vv/029PT04OPjM6KPPZIee+wxAMCvv/4Ka2trREVF3ff+AoFgUAtAw8PDkZiYqHz/flM9Tpw4gUceeQROTk64evUqjhw5Ag8Pj2GfVEkkEjAMg8jISERFReG5557D+vXrcebMGaxbtw7//ve/oatLF44IIdqJy+XitddeQ0pKCh577DFcuHBBOdBSXl6Ow4cP44UXXgAAJCYmIjExEUVFRejo6MCsWbPu+9iqdAwIDg5WrqNycHBAUFAQ2traKHiTIdPo4P3CCy/gmWeewT/+8Q/lx3R0dDB9+vQRfZ6WlpYhTZO4nVwuv2dwE4vF2L9/PyorK3Ho0KHhlDjq5HI5amtr0dzcjKioKOzbtw9SqRS9vb149NFHB9y3qqoKYrEYcXFxIxJae3p6YGRkBCcnJwBAWFgYMjMzMX78ePB4vDuaPolEIty6dUv5vkwmu+djjxs3DhERETh48CCcnZ1hYGCA1157DefPn8c333yD8+fPY8eOHQNG7wkhRNPJ5XJ88803eOeddzB+/Hj89a9/xQcffDBgkf/EiRORlZUFPp8PU1NT5ccbGxvR0tICADh58iQ6OjrA5/MfOGhzL2N9DOjq6oJAIFAOOhEyFMMK3o99kYn2PtFI1TIo9uaGOPVK3APvV19fj7S0NBw+fHjQj+3l5YVDhw4hOjoawO8tbW+fivLzzz/jnXfeQWdnJ3R0dHDhwgXs2rUL33zzDfh8Pry8vPDKK6/gb3/7G0pKSvDqq6+itrYWFhYW+PjjjzFv3jwAv5/1L1iwAMePH0d7e/s956o999xzAAY/l41NaWlpCA4OhkQiwf/+9z/lZbz09PQB98vLy4OrqytsbGxw+vRpLFiwYEjhm8/n4/r165DL5cqP9fX1wdLSUvm+jo4OTExM4OLiAh6Ph+Li4gGPIRAIUFVVpXz/QaPvUVFRCA8PR09PD6RSKczMzLB48WJ88MEH2LRpE6ZPn46nnnoKn3zyyYApNYQQookKCgqwYcMG1NTUYOvWrXjmmWdw5MgRVFdXD7g6293dDaFQOGAr4p6eHnR0dMDd3R1FRUVYuHAhgN+nIA5mdFpVjgG0vTJ5WMMK3u19InB6VXN+dEFBAUJDQ2FkZDQij9ff34/HH38cRUVF8PPzQ2trK4yMjPDRRx/B398fhw4dwi+//AIAaG9vx5w5c7Bv3z7MmzcPxcXFmDlzJoqLi+Hi4gIAOHjwIM6cOQMHB4cRqY8tDMPg5MmTMDExwbRp0wAAWVlZylB9u3PnzkEqleLRRx+Fjo4OdHV18dNPPw1piymZTIbe3l7c3vfJ2NgYItHAE0CpVAp9/bv/eltZWWHmzJnK9ysqKu56v8zMTOWLM4/Hg5mZGYDf5wjq6enBwMAAkyZNwsWLF/HXv/4V/v7+eO+99/Diiy/S9BNCiMbhcrn4+9//jv379+OFF17AuXPnYGVlBQCYP38+zpw5g7y8PFhYWCjXVC1ZskQ5Cs7n83H8+HEsWLAA1tbWOHToEHR1dRESEjLoGlTtGAAATzzxBIyNjQf9NRDtNqzgbW9uOFJ1jPhzikSi+14+GiodHR0YGBjgypUr8PX1haOj4z3v+91332Hu3LnKEe7Q0FAkJibi3LlzePbZZwEAy5cvV14WU2c6OjpISEhQvvgCwLRp05Qvir6+vsqRgZiYGOVCGeD370toaCgAwMPDY8AIxr1YWFggNjZ2wAiGtbU12traIJFIYGBgAA6Hg76+Puzfvx9SqfShT77i4uIwbdo0dHZ24siRI8oTiby8PNjZ2SE4OFj5tV28eBEHDx7EX//6V+zduxfbt2+nzpeEEI0gl8uxe/dubNq0CRMmTEBOTg4mTZo04D5mZmZITk6GVCrF7t27sWrVqgHTS4DfB19mzJih3FrwiSeewNWrVzGIBtpKqnoMIGSwhhW8BzPlgy0TJkxAeXk5ZDLZiCykNDY2xoULF/CPf/wDmzZtwhtvvIG1a9fe9b41NTU4efKkchU18PulralTpyrf9/T0HHZNqsLKygpdXV345ptv7uhI1tvbi3nz5sHa2hoWFhYQi8X49NNP7xjp5/P5mDp16oCP19XVIT09HTKZDEKhEDExMXd9fl1dXcTHx2P//v3w8vJCWVkZVq5cCWdnZ3C5XOWVCIW2trYBc+b5fP49vza5XI6amhpERkYqt4+ys7NDe3s7cnJylKMmOjo6WLlyJR577DFs2rQJCQkJNP2EEKL2FNNKamtrsXXrVjz99NP3bdamr68PPT09GBreOUi2dOlSAEBRUREmTZoEAwOD+w5QqNMxgJDB0tjFlZGRkbC1tcXXX3+NDRs2DOpzzM3NwePxlO//ccFkVFQUzp8/j5KSEixZsgTm5uZ44okn7ngcFxcXrF69Gp9//vk9n0sTpyJ4eXkhOTl5wMcuXrx4x/2cnJwGbOUE/D6/7/YV666ursrFlwYGBjA0NLzvpbyAgAC4u7ujvb0d0dHR97yvkZERNm7cOOiviWEYlJWV3fFxgUAwYMspBQsLC3z22Wd4/vnnsX79evj7++Of//wnXnnllRHdSYcQQkZTe3s7Xn/9dfzwww9Yt24dfv311wHzqBVaWlpw9uzZAR/r7OzE999/P+BjkZGRyiuc2dnZd4yYh4WFDXhfXY8BhDyIxgZvXV1d7N27F0uWLIGxsTFWrlyJcePGQSqV4uzZs5gzZ84dnxMZGYnU1FTMnj0bDMPgyy+/VP5fd3c3qqurERkZicDAQHh7eytDuo2NDerr6yGTycAwDJ588klMmzYNTz31FKZOnQq5XI7Tp0/j0UcfveecMzKQqanpHVsoPqhzpJmZmXIO3v2MGzdu0HXI5XLI5fI7ThQeJDg4GBcvXsQPP/yAN954Azt27MCmTZvw1FNPaeRJFyFEM/B4PPzrX//Czp07ERERgdzcXGVgvhtnZ2flRgAjSd2PAYTci0anwLi4OPz2229477338PbbbytDb0xMDJKSku64/+bNm7F69WpMmzYN5ubmePTRR3HgwAEAv696fuGFF9DS0gJLS0vMnz8fq1evBgAkJSVh27Zt8PLywv/93//hlVdeQUpKCtavX4+Ojg4YGhoiKSnpjsWGmqaurg579uwZ8DHFVJPbcTicO+6nmGqiijgcDvbt23fHx21tbe+7nZSOjg5WrFiBZcuWYceOHXj11VexdetWfPjhh5g7d+4oVkwIIUMjFovx2Wef4dNPP4WrqyuOHTuG2bNnj8pzdXV13XEMAAA3N7e7HpvZ9rDHAELuRocZxKoGoVCI2tpaeHt7j9guIWTk0c9JtfX29uKTTz7Bp59+isjISHz88ce0AJMQwiq5XI49e/Zg8+bN0NXVxYcffojHH3+crswRMkroL4uQMWJhYYH3338f1dXVCA4ORnx8PBYvXqwW+7QTQjTPTz/9hNDQULz55pt4/fXXUVZWhuTkZArdhIwi+usiZIw5Ojpi+/btuHnzJoyNjREaGoo1a9YoO7kRQshounjxImJjY7F69Wo89dRTqKmpwUsvvaTcl5oQMnooeBPCkvHjx+OHH35AdnY2Wlpa4Ofnh7/85S/o6elhuzRCiAYqKSnBI488grlz5yI2Nha1tbV4880379hvmxAyeih4E8KysLAwnDt3DqdOnUJmZiZ8fHzw/vvv33dvWUIIGayqqio89dRTiIqKgpOTEyoqKvDJJ5/A1taW7dII0TpDCt6D6SxI2EM/H/WWmJiIvLw87Nq1C4cPH1buktPZ2cl2aYQQNXTt2jUsXboUQUFBEAqFKCwsxN69e+Hu7s52aYRorUHtaiKXy1FZWQk9PT3Y29tj3Lhx9+1cRcYWwzAQi8Vob2+HTCaDr68vLY5Rc3K5HD///DM2b96MmzdvYsWKFXjrrbfg5ubGdmmEEBV38eJFbN68Genp6XjyySfxxhtvICAggO2yCCEYZPAGft/js6WlBf39/aNdE3lIJiYmcHZ2HlJzAKLaGIZRHkQzMzOxdOlSvP3225g4cSLbpRFCVIiiUduWLVtQWFiItWvX4u9//zs8PDzYLo0QcptBB2/g9xAglUohk8lGsybyEPT09KCvr09XIjRYYWEhPvjgA5w6dQrz5s3DO++8g4iICLbLIoSwSC6X48CBA/jkk09QV1eHP/3pT9i4cSPs7e3ZLo0QchdDCt6EEPZVVFRgy5Yt2L9/P+Li4vDmm29i5syZbJdFCBlDYrEYX3/9NbZt24aenh787W9/w/r162FhYcF2aYSQ+6DgTYiaamxsxNatW/H1118jJCQEr7/+OhYvXkzz+wnRYHw+H5999hl27twJfX19vPHGG1izZg11KyZETVDwJkTNdXR04IsvvsB///tfuLi4YO3atXjxxRdpb15CNEh1dTU+/fRTHD58GE5OTvjnP/+J5ORk6Ovrs10aIWQIKHgToiF4PB5SUlKwbds2cDgcLF++HH/7299oISYhakoul+Ps2bPYtm0b0tLSMGfOHLz66qtISkqi9TyEqCm6Jk2IhjAzM8P69etx8+ZNHDt2DK2trQgJCcGsWbPw008/0T7vhKgJHo+Hjz/+GAEBAVi5ciWCg4NRWlqKn3/+GXPnzqXQTYgaoxFvQjRYfX09duzYgV27dsHGxgYrV67Eyy+/DEdHR7ZLI4T8QUFBAf773//ixIkTcHNzw8aNG7FixQqaNkaIBqHgTYgWEAgE+PHHH7Fjxw5cu3YNSUlJePnllzF79mxajEkIi/r7+7F3717s2bMH169fx7Jly7B+/XrExcXRyDYhGoiCNyFapqSkBDt37kRKSgqcnZ3x9NNPY8OGDbC1tWW7NEK0RlFREbZt24bjx4/DxsYG69evx5o1a2BnZ8d2aYSQUUTBmxAtxefzcejQIXz55Ze4efMmEhISsHLlSiQnJ9PWZISMgqamJnz77bc4duwYSktL8dhjj2HDhg2YMWMGXXkiREtQ8CaE4MaNG9i/fz8OHDiA3t5ezJ07F88++yySkpIoEBAyDL29vThw4AB++OEHZGdnIzIyEqtWrcLy5ctpdJsQLUTBmxCiJJfLkZWVhf379+Pw4cMwMzPDY489hrVr11J7ekIGSSqV4qeffkJKSgouXLgAV1dXPPPMM1i5ciXGjx/PdnmEEBZR8CaE3JVIJMLZs2eRkpKC06dPY8KECVi6dCnWrl0LLy8vtssjRKXI5XJcunQJe/fuxc8//wxdXV2sWLECTz/9NMLDw2mhJCEEAAVvQsggcLlcHD9+HN9//z2ysrIQGRmJ5ORkrF69GjY2NmyXRwhrSktLsXv3bqSmpqKtrQ1LlizBqlWrMGPGDOoqSQi5AwVvQsiQNDY24ocffsB3332HyspKREVFYd68eXjiiSfg6+vLdnmEjCq5XI6LFy/i6NGjuHDhAqqrqzFnzhysWrUKCxcuhImJCdslEkJUGAVvQshDKy8vx6lTp5CamoqcnBz4+vpi9uzZePzxxzF9+nRamEk0Ap/PR2pqKlJTU3Hx4kX09/dj3rx5WLx4MR555BG66kMIGTQK3oSQEdHZ2YkzZ87gxIkTOHfuHExNTREfH4/Fixdj0aJF1H2PqJWGhgYcOnQIZ8+eRXZ2Nuzt7bFo0SIsWrQI8fHxGDduHNslEkLUEAVvQsiIE4lEyMjIwMmTJ3HixAl0dnYiOjoa8+fPxxNPPAE3Nze2SyRkALlcjitXruDIkSM4f/48bty4gcmTJyvDdnBwMC2QJIQMGwVvQsioYhgGxcXFOHnyJFJTU1FUVITg4GDExcVhzpw5mD17No2GE1Y0NjbizJkzSEtLw6VLl9DZ2YnZs2dj0aJFmD9/PpydndkukRCiYSh4E0LGVHNzM86cOYPz588jLS0NXC4XISEhiImJwezZsymIk1HT2NiIs2fP4rfffsOVK1dQU1ODgIAAzJw5E0lJSZg1axYtjiSEjCoK3oQQ1jAMg8rKSqSnp+O33367I4grRsQpDJGH0dTUpBzRzsvLGxC0Z8yYgfj4eOoeSQgZUxS8CSEqg2EYVFRUKIN4eno6enp67hgRpyBO7qapqQlnz55VBu3q6moK2oQQlULBmxCisu4WxLu7u+Hr64uAgACEh4cjNjYW0dHRMDIyYrtcMoZaW1uRmZmJ3NxcFBUVobS0FI2NjfD39x8QtO3t7dkulRBClCh4E0LUBsMwqK6uRkFBAfLz83HlyhVcu3YNfD4fPj4+CAoKQnh4OKKjoxEdHU0j4xqCw+Hg0qVLyMvLGxCy3d3dERERgaioKERERCAiIoJGtAkhKo2CNyFErTEMg5qamgFh/OrVq8owHhAQgMmTJyMmJgbR0dEwMzNju2RyH01NTcjKyhowkt3c3AwPD48BITs8PJxCNiFE7VDwJoRoHIZhUFtbOyCMFxYWore3F05OTvDy8oKXlxd8fX0RGBiI4OBgTJw4Efr6+myXrhV4PB5KSkpw/fp1lJWVoaqqCnV1dbh16xa4XC48PDwQGRk5IGTb2tqyXTYhhAwbBW9CiFZgGAZNTU2orKxERUUFysvLlbf6+nro6OjA3d0dnp6e8Pb2xsSJExEYGIiQkBC4u7tDV1eX7S9BrYjFYpSXl6OkpASlpaWorKxEXV0d6uvrweFwYGpqCh8fH0ycOBH+/v7w8/NT3iwtLdkunxBCRgUFb0KI1pNIJKivr0dFRYUylJeVlaGyshJNTU0wMzODi4sL7O3tYW9vD0dHRzg7O8PNzQ1ubm7w9PSEh4eHVswpl8vl6O7uRn19PRoaGtDQ0ICmpia0tLSgra0NHR0daGtrQ1NTE3R0dJQnMYqbIlw7OjpSJ0hCiNah4E0IIffR39+Pqqoq1NbWoqWlBS0tLWhubkZTUxOam5vB4XDQ3t4OuVwOKysr2NnZKW9OTk5wdnaGg4MDLC0tYWFhAUtLS+Xb1tbWsLS0hJ6eHitfm0gkApfLBZfLRU9Pj/Lfvr4+9PT0KL/etrY2tLe3o6OjAx0dHRAIBDA0NFSegLi6usLFxQUuLi5wdnaGi4sLfHx84OHhQdN3CCHkNhS8CSFkmGQyGdrb29Hc3KwMq4qA3tjYiI6ODvB4PPT19YHH44HP50MoFCo/39jYGCYmJjAxMYGpqSmMjY1hamoKExMTGBkZQU9PD7q6utDR0YGuru6AG8MwYBgGcrn8jptUKkV/fz8EAgH4fP4d/4rFYgCAjo4OTE1NYWpqCjMzM5ibm8Pc3BxOTk7KUO3s7Ky8ubi4wNLSkkasCSFkiCh4E0IIC6RSKfh8Pvr6+pSB/I9v83g89Pf3DwjTMplswNt/DOK33/T19WFmZqYM07eH6tvfNjY2pjnshBAyBih4E0IIIYQQMgZoiIMQQgghhJAxQMGbEEIIIYSQMUDBmxBCCCGEkDFAwZsQQgghhJAxQMGbEEIIIYSQMUDBmxBCCCGEkDFAwZsQQgghhJAxQMGbEEIIIYSQMfD/Aekf73RgQqhYAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# k=3일 때 군집 정보를 사용하기 위해 군집 평균값 계산\n",
    "kmeans = KMeans(n_clusters=3, random_state=42)\n",
    "grouped['군집'] = kmeans.fit_predict(scaled_features)\n",
    "\n",
    "# 군집별 평균 값 계산 (대여대여소ID, PCA1, PCA2 제외)\n",
    "grouped_means = grouped.drop(columns=['대여대여소ID', 'PCA1', 'PCA2']).groupby('군집').mean()\n",
    "\n",
    "# 방사형 그래프 그리기 위한 설정\n",
    "cluster_features = {\n",
    "    0: ['총대여횟수', '새벽대여비율', '퇴근시간대여비율', '야간대여비율', '청년비율'],\n",
    "    1: ['남성고객비율', '출근시간대여비율', '오전대여비율', '점심대여비율', '장년비율'],\n",
    "    2: ['평균이용시간', '평균이용거리', '주말대여비율', '오후대여비율', '퇴근시간대여비율']\n",
    "}\n",
    "\n",
    "# 방사형 그래프 그리기\n",
    "for cluster, features in cluster_features.items():\n",
    "    values = grouped_means.loc[cluster, features].values.flatten().tolist()\n",
    "    values += values[:1]\n",
    "    \n",
    "    num_vars = len(features)\n",
    "    angles = [n / float(num_vars) * 2 * np.pi for n in range(num_vars)]\n",
    "    angles += angles[:1]\n",
    "    \n",
    "    fig, ax = plt.subplots(figsize=(8, 8), subplot_kw=dict(polar=True))\n",
    "    \n",
    "    ax.set_theta_offset(np.pi / 2)\n",
    "    ax.set_theta_direction(-1)\n",
    "    \n",
    "    plt.xticks(angles[:-1], features, color='grey', size=8)\n",
    "    \n",
    "    ax.plot(angles, values, linewidth=2, linestyle='solid', label=f'Cluster {cluster}')\n",
    "    ax.fill(angles, values, alpha=0.25)\n",
    "    \n",
    "    # 각도 축의 범위를 조정하여 더 낮은 값을 기준으로 설정\n",
    "    ax.set_ylim(0, 1)  # 0에서 1 사이의 값으로 스케일을 조정\n",
    "    \n",
    "    plt.title(f'Cluster {cluster}', size=20, color='blue', y=1.1)\n",
    "    plt.legend(loc='upper right', bbox_to_anchor=(0.1, 0.1))\n",
    "    plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.cluster import KMeans\n",
    "\n",
    "# 데이터 로드 및 전처리\n",
    "df1_ins['대여일자'] = pd.to_datetime(df1_ins['대여일자'])\n",
    "\n",
    "# 주중/주말 구분\n",
    "df1_ins['주말여부'] = df1_ins['대여요일'].isin(['Saturday', 'Sunday'])\n",
    "\n",
    "# 시간대 구분\n",
    "df1_ins['새벽시간'] = (df1_ins['대여시간'] >= 0) & (df1_ins['대여시간'] < 6)\n",
    "df1_ins['출근시간'] = (df1_ins['대여시간'] >= 7) & (df1_ins['대여시간'] < 10)\n",
    "df1_ins['오전시간'] = (df1_ins['대여시간'] >= 10) & (df1_ins['대여시간'] < 12)\n",
    "df1_ins['점심시간'] = (df1_ins['대여시간'] >= 12) & (df1_ins['대여시간'] < 14)\n",
    "df1_ins['오후시간'] = (df1_ins['대여시간'] >= 14) & (df1_ins['대여시간'] < 17)\n",
    "df1_ins['퇴근시간'] = (df1_ins['대여시간'] >= 17) & (df1_ins['대여시간'] < 19)\n",
    "df1_ins['야간시간'] = (df1_ins['대여시간'] >= 19) & (df1_ins['대여시간'] < 24)\n",
    "\n",
    "# 연령대 구분\n",
    "df1_ins['청소년'] = (df1_ins['연령대'] == 10)\n",
    "df1_ins['청년'] = (df1_ins['연령대'] == 20) | (df1_ins['연령대'] == 30)\n",
    "df1_ins['장년'] = (df1_ins['연령대'] == 40) | (df1_ins['연령대'] == 50)\n",
    "df1_ins['노인'] = (df1_ins['연령대'] == 60) | (df1_ins['연령대'] == 70)\n",
    "\n",
    "# 대여대여소ID 기준 그룹화하여 통계 피처 생성\n",
    "total_counts = df1_ins.groupby('대여대여소ID')['대여일자'].count()\n",
    "\n",
    "grouped = df1_ins.groupby('대여대여소ID').agg({\n",
    "    '대여일자': 'count',  # 총 대여 횟수\n",
    "    '성별_M': 'mean',  # 남성 방문고객 비율\n",
    "    '이용시간(분)': 'mean',  # 평균 이용시간\n",
    "    '이용거리(M)': 'mean',  # 평균 이용거리\n",
    "    '주말여부': lambda x: x.sum() / x.count(),  # 주말 대여 비율\n",
    "    '새벽시간': lambda x: x.sum() / x.count(),  # 새벽 대여 비율\n",
    "    '출근시간': lambda x: x.sum() / x.count(),  # 출근 시간대 대여 비율\n",
    "    '오전시간': lambda x: x.sum() / x.count(),  # 오전 대여 비율\n",
    "    '점심시간': lambda x: x.sum() / x.count(),  # 점심시간 대여 비율\n",
    "    '오후시간': lambda x: x.sum() / x.count(),  # 오후시간 대여 비율\n",
    "    '퇴근시간': lambda x: x.sum() / x.count(),  # 퇴근 시간대 대여 비율\n",
    "    '야간시간': lambda x: x.sum() / x.count(),   # 야간 대여 비율\n",
    "    '청소년' : lambda x: x.sum() / x.count(),   # 청소년 비율\n",
    "    '청년' : lambda x: x.sum() / x.count(),     # 청년 비율\n",
    "    '장년' : lambda x: x.sum() / x.count(),     # 장년 비율\n",
    "    '노인' : lambda x: x.sum() / x.count()      # 노인 비율\n",
    "}).reset_index()\n",
    "\n",
    "# 컬럼 이름 변경\n",
    "grouped.columns = [\n",
    "    '대여대여소ID', '총대여횟수', '남성고객비율', '평균이용시간', '평균이용거리',\n",
    "    '주말대여비율', '새벽대여비율', '출근시간대여비율', '오전대여비율', '점심대여비율', '오후대여비율',\n",
    "    '퇴근시간대여비율', '야간대여비율', '청소년비율', '청년비율', '장년비율', '노인비율'\n",
    "]\n",
    "\n",
    "# 군집분석에 사용할 피처 선택\n",
    "features = grouped.drop(columns=['대여대여소ID'])\n",
    "\n",
    "# 표준화\n",
    "scaler = StandardScaler()\n",
    "scaled_features = scaler.fit_transform(features)\n",
    "\n",
    "# K-means 군집분석\n",
    "kmeans = KMeans(n_clusters=3, random_state=42)\n",
    "grouped['군집'] = kmeans.fit_predict(scaled_features)\n",
    "\n",
    "# 군집별 평균 값 계산 (대여대여소ID 제외)\n",
    "grouped_means = grouped.drop(columns=['대여대여소ID']).groupby('군집').mean()\n",
    "\n",
    "# 총대여횟수, 평균이용시간, 평균이용거리 비율로 변환\n",
    "grouped_means['총대여횟수'] = grouped_means['총대여횟수'] / grouped_means['총대여횟수'].max()\n",
    "grouped_means['평균이용시간'] = grouped_means['평균이용시간'] / grouped_means['평균이용시간'].max()\n",
    "grouped_means['평균이용거리'] = grouped_means['평균이용거리'] / grouped_means['평균이용거리'].max()\n",
    "\n",
    "# 방사형 그래프 그리기 위한 설정\n",
    "cluster_features = {\n",
    "    0: ['총대여횟수', '새벽대여비율', '퇴근시간대여비율', '야간대여비율', '청년비율'],\n",
    "    1: ['남성고객비율', '출근시간대여비율', '오전대여비율', '점심대여비율', '장년비율'],\n",
    "    2: ['평균이용시간', '평균이용거리', '주말대여비율', '오후대여비율', '퇴근시간대여비율']\n",
    "}\n",
    "\n",
    "# 방사형 그래프 그리기\n",
    "for cluster, features in cluster_features.items():\n",
    "    values = grouped_means.loc[cluster, features].values.flatten().tolist()\n",
    "    values += values[:1]\n",
    "    \n",
    "    num_vars = len(features)\n",
    "    angles = [n / float(num_vars) * 2 * np.pi for n in range(num_vars)]\n",
    "    angles += angles[:1]\n",
    "    \n",
    "    fig, ax = plt.subplots(figsize=(8, 8), subplot_kw=dict(polar=True))\n",
    "    \n",
    "    ax.set_theta_offset(np.pi / 2)\n",
    "    ax.set_theta_direction(-1)\n",
    "    \n",
    "    plt.xticks(angles[:-1], features, color='grey', size=8)\n",
    "    \n",
    "    ax.plot(angles, values, linewidth=2, linestyle='solid', label=f'Cluster {cluster}')\n",
    "    ax.fill(angles, values, alpha=0.25)\n",
    "    \n",
    "    #plt.title(f'Cluster {cluster}', size=20, color='blue', y=1.1)\n",
    "    #plt.legend(loc='upper right', bbox_to_anchor=(0.1, 0.1))\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 한 번만 더.. 20대랑 30대는 좀 다른 양상이니까!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      대여대여소ID  총대여횟수    남성고객비율     평균이용시간       평균이용거리    주말대여비율    새벽대여비율  \\\n",
      "0       ST-10   2764  0.641823  30.027135  2896.118784  0.308249  0.099493   \n",
      "1     ST-1000   3074  0.625895  19.268705  2427.495573  0.265777  0.036760   \n",
      "2     ST-1002   5895  0.658863  20.319932  2289.621218  0.298049  0.013740   \n",
      "3     ST-1003   1914  0.641066  17.774817  2121.170564  0.269592  0.060084   \n",
      "4     ST-1004   1543  0.736876  15.806870  1868.960045  0.288399  0.038885   \n",
      "...       ...    ...       ...        ...          ...       ...       ...   \n",
      "2748   ST-993   2288  0.677885  18.303759  1884.028086  0.255682  0.042832   \n",
      "2749   ST-994   4450  0.640225  20.783820  2037.581463  0.224045  0.014607   \n",
      "2750   ST-995    467  0.698073  18.715203  2259.101649  0.241970  0.008565   \n",
      "2751   ST-996   1075  0.709767  20.463256  1966.129544  0.279070  0.097674   \n",
      "2752   ST-997   6979  0.640923  18.015618  1877.363578  0.252472  0.028084   \n",
      "\n",
      "      출근시간대여비율    오전대여비율    점심대여비율    오후대여비율  퇴근시간대여비율    야간대여비율     청소년비율  \\\n",
      "0     0.045224  0.061867  0.099855  0.183792  0.184877  0.295224  0.027135   \n",
      "1     0.307417  0.080677  0.093689  0.143136  0.155172  0.145413  0.256018   \n",
      "2     0.079389  0.058015  0.087532  0.188126  0.233927  0.318405  0.205259   \n",
      "3     0.142111  0.063218  0.096134  0.153083  0.166667  0.286311  0.129572   \n",
      "4     0.263772  0.059624  0.088788  0.154893  0.149060  0.207388  0.467920   \n",
      "...        ...       ...       ...       ...       ...       ...       ...   \n",
      "2748  0.194493  0.077797  0.092220  0.165210  0.152535  0.208479  0.144668   \n",
      "2749  0.076854  0.061124  0.087865  0.161348  0.276854  0.293708  0.082921   \n",
      "2750  0.233405  0.085653  0.100642  0.171306  0.175589  0.211991  0.102784   \n",
      "2751  0.042791  0.049302  0.083721  0.191628  0.236279  0.247442  0.120000   \n",
      "2752  0.260496  0.077948  0.082533  0.186130  0.156183  0.178106  0.275971   \n",
      "\n",
      "         청년1비율     청년2비율      장년비율      노인비율  \n",
      "0     0.420043  0.360709  0.176194  0.015919  \n",
      "1     0.231620  0.126220  0.345153  0.040664  \n",
      "2     0.228159  0.194911  0.335369  0.034266  \n",
      "3     0.245559  0.272205  0.311390  0.040752  \n",
      "4     0.198963  0.075178  0.232016  0.025924  \n",
      "...        ...       ...       ...       ...  \n",
      "2748  0.302885  0.198427  0.308566  0.045455  \n",
      "2749  0.280225  0.242921  0.366067  0.027865  \n",
      "2750  0.224839  0.224839  0.370450  0.077088  \n",
      "2751  0.295814  0.253023  0.266047  0.065116  \n",
      "2752  0.237140  0.107179  0.339160  0.037398  \n",
      "\n",
      "[2753 rows x 18 columns]\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "df1_ins['대여일자'] = pd.to_datetime(df1_ins['대여일자'])\n",
    "\n",
    "# 주중/주말 구분\n",
    "df1_ins['주말여부'] = df1_ins['대여요일'].isin(['Saturday', 'Sunday'])\n",
    "\n",
    "# 시간대 구분\n",
    "df1_ins['새벽시간'] = (df1_ins['대여시간'] >= 0) & (df1_ins['대여시간'] < 6)\n",
    "df1_ins['출근시간'] = (df1_ins['대여시간'] >= 7) & (df1_ins['대여시간'] < 10)\n",
    "df1_ins['오전시간'] = (df1_ins['대여시간'] >= 10) & (df1_ins['대여시간'] < 12)\n",
    "df1_ins['점심시간'] = (df1_ins['대여시간'] >= 12) & (df1_ins['대여시간'] < 14)\n",
    "df1_ins['오후시간'] = (df1_ins['대여시간'] >= 14) & (df1_ins['대여시간'] < 17)\n",
    "df1_ins['퇴근시간'] = (df1_ins['대여시간'] >= 17) & (df1_ins['대여시간'] < 19)\n",
    "df1_ins['야간시간'] = (df1_ins['대여시간'] >= 19) & (df1_ins['대여시간'] < 24)\n",
    "\n",
    "# 연령대 구분\n",
    "df1_ins['청소년'] = (df1_ins['연령대'] == 10)\n",
    "df1_ins['청년1'] = (df1_ins['연령대'] == 20)\n",
    "df1_ins['청년2'] = (df1_ins['연령대'] == 30)\n",
    "df1_ins['장년'] = (df1_ins['연령대'] == 40) | (df1_ins['연령대'] == 50)\n",
    "df1_ins['노인'] = (df1_ins['연령대'] == 60) | (df1_ins['연령대'] == 70)\n",
    "\n",
    "# 대여대여소ID 기준 그룹화하여 통계 피처 생성\n",
    "total_counts = df1_ins.groupby('대여대여소ID')['대여일자'].count()\n",
    "\n",
    "grouped = df1_ins.groupby('대여대여소ID').agg({\n",
    "    '대여일자': 'count',  # 총 대여 횟수\n",
    "    '성별_M': 'mean',  # 남성 방문고객 비율\n",
    "    '이용시간(분)': 'mean',  # 평균 이용시간\n",
    "    '이용거리(M)': 'mean',  # 평균 이용거리\n",
    "    '주말여부': lambda x: x.sum() / x.count(),  # 주말 대여 비율\n",
    "    '새벽시간': lambda x: x.sum() / x.count(),  # 새벽 대여 비율\n",
    "    '출근시간': lambda x: x.sum() / x.count(),  # 출근 시간대 대여 비율\n",
    "    '오전시간': lambda x: x.sum() / x.count(),  # 오전 대여 비율\n",
    "    '점심시간': lambda x: x.sum() / x.count(),  # 점심시간 대여 비율\n",
    "    '오후시간': lambda x: x.sum() / x.count(),  # 오후시간 대여 비율\n",
    "    '퇴근시간': lambda x: x.sum() / x.count(),  # 퇴근 시간대 대여 비율\n",
    "    '야간시간': lambda x: x.sum() / x.count(),   # 야간 대여 비율\n",
    "    '청소년' : lambda x: x.sum() / x.count(),   # 청소년 비율\n",
    "    '청년1' : lambda x: x.sum() / x.count(),    # 청년1 비율\n",
    "    '청년2' : lambda x: x.sum() / x.count(),    # 청년2 비율\n",
    "    '장년' : lambda x: x.sum() / x.count(),     # 장년 비율\n",
    "    '노인' : lambda x: x.sum() / x.count()      # 노인 비율\n",
    "}).reset_index()\n",
    "\n",
    "# 컬럼 이름 변경\n",
    "grouped.columns = [\n",
    "    '대여대여소ID', '총대여횟수', '남성고객비율', '평균이용시간', '평균이용거리',\n",
    "    '주말대여비율', '새벽대여비율', '출근시간대여비율', '오전대여비율', '점심대여비율', '오후대여비율',\n",
    "    '퇴근시간대여비율', '야간대여비율', '청소년비율', '청년1비율', '청년2비율', '장년비율', '노인비율'\n",
    "]\n",
    "\n",
    "print(grouped)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대여대여소ID</th>\n",
       "      <th>총대여횟수</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ST-10</td>\n",
       "      <td>2764</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  대여대여소ID  총대여횟수\n",
       "0   ST-10   2764"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#g = grouped[['대여대여소ID', '총대여횟수']]\n",
    "#g.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#g.to_csv('./대여소ID와 대여건수.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [],
   "source": [
    "grouped = grouped.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "\n",
    "# # 군집분석에 사용할 피처 선택\n",
    "# features = grouped.drop(columns=['대여대여소ID'])\n",
    "\n",
    "sum_of_squared_distances = []\n",
    "K = range(1, 15)\n",
    "for k in K:\n",
    "    km = KMeans(n_clusters = k)\n",
    "    km = km.fit(features)\n",
    "    sum_of_squared_distances.append(km.inertia_)\n",
    "    \n",
    "# 시각화\n",
    "\n",
    "plt.plot(K, sum_of_squared_distances, 'bx-')\n",
    "plt.xlabel('k')\n",
    "plt.ylabel('Sum_of_squared_distances')\n",
    "plt.title('Elbow Method For Optimal k')\n",
    "plt.axvline(2,c= 'r',alpha =0.4)\n",
    "plt.axvline(3,c= 'r',alpha =0.4)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "k : 2 score : 0.5859813635394627\n",
      "k : 3 score : 0.46252571202880305\n",
      "k : 4 score : 0.4262747653528918\n",
      "k : 5 score : 0.4396391089804624\n",
      "k : 6 score : 0.42642630167356094\n",
      "k : 7 score : 0.3886247007710414\n",
      "k : 8 score : 0.37863545604351945\n",
      "k : 9 score : 0.36149340589077517\n",
      "k : 10 score : 0.3625252556573451\n",
      "k : 11 score : 0.3732543464652768\n",
      "k : 12 score : 0.3613642817997847\n",
      "k : 13 score : 0.36172057289848064\n",
      "best n : 2 best score : 0.5859813635394627\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import silhouette_score\n",
    "k_range = range(2,14)\n",
    "\n",
    "best_n = -1\n",
    "best_silhouette_score = -1\n",
    "\n",
    "for k in k_range:\n",
    "\n",
    "  kmeans = KMeans(n_clusters=k, random_state=200)\n",
    "  kmeans.fit(features)\n",
    "  clusters = kmeans.predict(features)\n",
    "\n",
    "  score = silhouette_score(features, clusters)\n",
    "  print('k :',  k, 'score :', score)\n",
    "\n",
    "  if score > best_silhouette_score:\n",
    "    best_n = k\n",
    "    best_silhouette_score = score\n",
    "\n",
    "print('best n :', best_n, 'best score :', best_silhouette_score )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 2일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
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       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_a9b62_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_a9b62_level0_col1\" class=\"col_heading level0 col1\" >남성고객비율</th>\n",
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       "      <th id=\"T_a9b62_level0_col5\" class=\"col_heading level0 col5\" >새벽대여비율</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
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       "      <td id=\"T_a9b62_row1_col2\" class=\"data row1 col2\" >21.091691</td>\n",
       "      <td id=\"T_a9b62_row1_col3\" class=\"data row1 col3\" >2458.956388</td>\n",
       "      <td id=\"T_a9b62_row1_col4\" class=\"data row1 col4\" >0.236947</td>\n",
       "      <td id=\"T_a9b62_row1_col5\" class=\"data row1 col5\" >0.047603</td>\n",
       "      <td id=\"T_a9b62_row1_col6\" class=\"data row1 col6\" >0.191775</td>\n",
       "      <td id=\"T_a9b62_row1_col7\" class=\"data row1 col7\" >0.082208</td>\n",
       "      <td id=\"T_a9b62_row1_col8\" class=\"data row1 col8\" >0.088676</td>\n",
       "      <td id=\"T_a9b62_row1_col9\" class=\"data row1 col9\" >0.170886</td>\n",
       "      <td id=\"T_a9b62_row1_col10\" class=\"data row1 col10\" >0.170763</td>\n",
       "      <td id=\"T_a9b62_row1_col11\" class=\"data row1 col11\" >0.201611</td>\n",
       "      <td id=\"T_a9b62_row1_col12\" class=\"data row1 col12\" >0.083792</td>\n",
       "      <td id=\"T_a9b62_row1_col13\" class=\"data row1 col13\" >0.234311</td>\n",
       "      <td id=\"T_a9b62_row1_col14\" class=\"data row1 col14\" >0.255497</td>\n",
       "      <td id=\"T_a9b62_row1_col15\" class=\"data row1 col15\" >0.356834</td>\n",
       "      <td id=\"T_a9b62_row1_col16\" class=\"data row1 col16\" >0.068649</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x14acb92b3d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 3일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_cabda_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_cabda_level0_col1\" class=\"col_heading level0 col1\" >남성고객비율</th>\n",
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       "      <th id=\"T_cabda_level0_col3\" class=\"col_heading level0 col3\" >평균이용거리</th>\n",
       "      <th id=\"T_cabda_level0_col4\" class=\"col_heading level0 col4\" >주말대여비율</th>\n",
       "      <th id=\"T_cabda_level0_col5\" class=\"col_heading level0 col5\" >새벽대여비율</th>\n",
       "      <th id=\"T_cabda_level0_col6\" class=\"col_heading level0 col6\" >출근시간대여비율</th>\n",
       "      <th id=\"T_cabda_level0_col7\" class=\"col_heading level0 col7\" >오전대여비율</th>\n",
       "      <th id=\"T_cabda_level0_col8\" class=\"col_heading level0 col8\" >점심대여비율</th>\n",
       "      <th id=\"T_cabda_level0_col9\" class=\"col_heading level0 col9\" >오후대여비율</th>\n",
       "      <th id=\"T_cabda_level0_col10\" class=\"col_heading level0 col10\" >퇴근시간대여비율</th>\n",
       "      <th id=\"T_cabda_level0_col11\" class=\"col_heading level0 col11\" >야간대여비율</th>\n",
       "      <th id=\"T_cabda_level0_col12\" class=\"col_heading level0 col12\" >청소년비율</th>\n",
       "      <th id=\"T_cabda_level0_col13\" class=\"col_heading level0 col13\" >청년1비율</th>\n",
       "      <th id=\"T_cabda_level0_col14\" class=\"col_heading level0 col14\" >청년2비율</th>\n",
       "      <th id=\"T_cabda_level0_col15\" class=\"col_heading level0 col15\" >장년비율</th>\n",
       "      <th id=\"T_cabda_level0_col16\" class=\"col_heading level0 col16\" >노인비율</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "      <th class=\"blank col8\" >&nbsp;</th>\n",
       "      <th class=\"blank col9\" >&nbsp;</th>\n",
       "      <th class=\"blank col10\" >&nbsp;</th>\n",
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       "      <th class=\"blank col13\" >&nbsp;</th>\n",
       "      <th class=\"blank col14\" >&nbsp;</th>\n",
       "      <th class=\"blank col15\" >&nbsp;</th>\n",
       "      <th class=\"blank col16\" >&nbsp;</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
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       "      <td id=\"T_cabda_row0_col1\" class=\"data row0 col1\" >0.630206</td>\n",
       "      <td id=\"T_cabda_row0_col2\" class=\"data row0 col2\" >19.628613</td>\n",
       "      <td id=\"T_cabda_row0_col3\" class=\"data row0 col3\" >2173.422678</td>\n",
       "      <td id=\"T_cabda_row0_col4\" class=\"data row0 col4\" >0.244127</td>\n",
       "      <td id=\"T_cabda_row0_col5\" class=\"data row0 col5\" >0.054716</td>\n",
       "      <td id=\"T_cabda_row0_col6\" class=\"data row0 col6\" >0.149427</td>\n",
       "      <td id=\"T_cabda_row0_col7\" class=\"data row0 col7\" >0.069318</td>\n",
       "      <td id=\"T_cabda_row0_col8\" class=\"data row0 col8\" >0.084702</td>\n",
       "      <td id=\"T_cabda_row0_col9\" class=\"data row0 col9\" >0.152825</td>\n",
       "      <td id=\"T_cabda_row0_col10\" class=\"data row0 col10\" >0.172800</td>\n",
       "      <td id=\"T_cabda_row0_col11\" class=\"data row0 col11\" >0.270423</td>\n",
       "      <td id=\"T_cabda_row0_col12\" class=\"data row0 col12\" >0.059185</td>\n",
       "      <td id=\"T_cabda_row0_col13\" class=\"data row0 col13\" >0.346218</td>\n",
       "      <td id=\"T_cabda_row0_col14\" class=\"data row0 col14\" >0.299272</td>\n",
       "      <td id=\"T_cabda_row0_col15\" class=\"data row0 col15\" >0.253374</td>\n",
       "      <td id=\"T_cabda_row0_col16\" class=\"data row0 col16\" >0.041475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_cabda_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_cabda_row1_col0\" class=\"data row1 col0\" >1562.726876</td>\n",
       "      <td id=\"T_cabda_row1_col1\" class=\"data row1 col1\" >0.671629</td>\n",
       "      <td id=\"T_cabda_row1_col2\" class=\"data row1 col2\" >19.943785</td>\n",
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       "      <td id=\"T_cabda_row1_col4\" class=\"data row1 col4\" >0.229613</td>\n",
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       "      <td id=\"T_cabda_row1_col16\" class=\"data row1 col16\" >0.066382</td>\n",
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       "      <th id=\"T_cabda_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
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       "      <td id=\"T_cabda_row2_col6\" class=\"data row2 col6\" >0.124945</td>\n",
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       "      <td id=\"T_cabda_row2_col11\" class=\"data row2 col11\" >0.265852</td>\n",
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       "      <td id=\"T_cabda_row2_col13\" class=\"data row2 col13\" >0.271613</td>\n",
       "      <td id=\"T_cabda_row2_col14\" class=\"data row2 col14\" >0.270736</td>\n",
       "      <td id=\"T_cabda_row2_col15\" class=\"data row2 col15\" >0.337071</td>\n",
       "      <td id=\"T_cabda_row2_col16\" class=\"data row2 col16\" >0.067441</td>\n",
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       "  </tbody>\n",
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      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x14aca9da650>"
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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 4일 때 각 군집의 평균 값:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
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       "#T_2d389_row0_col3, #T_2d389_row0_col9, #T_2d389_row0_col15, #T_2d389_row0_col16, #T_2d389_row1_col0, #T_2d389_row1_col2, #T_2d389_row1_col8, #T_2d389_row1_col10, #T_2d389_row1_col13, #T_2d389_row1_col14, #T_2d389_row2_col1, #T_2d389_row2_col6, #T_2d389_row2_col7, #T_2d389_row3_col4, #T_2d389_row3_col5, #T_2d389_row3_col11, #T_2d389_row3_col12 {\n",
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       "<table id=\"T_2d389\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_2d389_level0_col0\" class=\"col_heading level0 col0\" >총대여횟수</th>\n",
       "      <th id=\"T_2d389_level0_col1\" class=\"col_heading level0 col1\" >남성고객비율</th>\n",
       "      <th id=\"T_2d389_level0_col2\" class=\"col_heading level0 col2\" >평균이용시간</th>\n",
       "      <th id=\"T_2d389_level0_col3\" class=\"col_heading level0 col3\" >평균이용거리</th>\n",
       "      <th id=\"T_2d389_level0_col4\" class=\"col_heading level0 col4\" >주말대여비율</th>\n",
       "      <th id=\"T_2d389_level0_col5\" class=\"col_heading level0 col5\" >새벽대여비율</th>\n",
       "      <th id=\"T_2d389_level0_col6\" class=\"col_heading level0 col6\" >출근시간대여비율</th>\n",
       "      <th id=\"T_2d389_level0_col7\" class=\"col_heading level0 col7\" >오전대여비율</th>\n",
       "      <th id=\"T_2d389_level0_col8\" class=\"col_heading level0 col8\" >점심대여비율</th>\n",
       "      <th id=\"T_2d389_level0_col9\" class=\"col_heading level0 col9\" >오후대여비율</th>\n",
       "      <th id=\"T_2d389_level0_col10\" class=\"col_heading level0 col10\" >퇴근시간대여비율</th>\n",
       "      <th id=\"T_2d389_level0_col11\" class=\"col_heading level0 col11\" >야간대여비율</th>\n",
       "      <th id=\"T_2d389_level0_col12\" class=\"col_heading level0 col12\" >청소년비율</th>\n",
       "      <th id=\"T_2d389_level0_col13\" class=\"col_heading level0 col13\" >청년1비율</th>\n",
       "      <th id=\"T_2d389_level0_col14\" class=\"col_heading level0 col14\" >청년2비율</th>\n",
       "      <th id=\"T_2d389_level0_col15\" class=\"col_heading level0 col15\" >장년비율</th>\n",
       "      <th id=\"T_2d389_level0_col16\" class=\"col_heading level0 col16\" >노인비율</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >군집</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "      <th class=\"blank col8\" >&nbsp;</th>\n",
       "      <th class=\"blank col9\" >&nbsp;</th>\n",
       "      <th class=\"blank col10\" >&nbsp;</th>\n",
       "      <th class=\"blank col11\" >&nbsp;</th>\n",
       "      <th class=\"blank col12\" >&nbsp;</th>\n",
       "      <th class=\"blank col13\" >&nbsp;</th>\n",
       "      <th class=\"blank col14\" >&nbsp;</th>\n",
       "      <th class=\"blank col15\" >&nbsp;</th>\n",
       "      <th class=\"blank col16\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_2d389_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_2d389_row0_col0\" class=\"data row0 col0\" >3152.038690</td>\n",
       "      <td id=\"T_2d389_row0_col1\" class=\"data row0 col1\" >0.623735</td>\n",
       "      <td id=\"T_2d389_row0_col2\" class=\"data row0 col2\" >19.749949</td>\n",
       "      <td id=\"T_2d389_row0_col3\" class=\"data row0 col3\" >2179.826534</td>\n",
       "      <td id=\"T_2d389_row0_col4\" class=\"data row0 col4\" >0.250350</td>\n",
       "      <td id=\"T_2d389_row0_col5\" class=\"data row0 col5\" >0.055096</td>\n",
       "      <td id=\"T_2d389_row0_col6\" class=\"data row0 col6\" >0.150279</td>\n",
       "      <td id=\"T_2d389_row0_col7\" class=\"data row0 col7\" >0.068604</td>\n",
       "      <td id=\"T_2d389_row0_col8\" class=\"data row0 col8\" >0.084357</td>\n",
       "      <td id=\"T_2d389_row0_col9\" class=\"data row0 col9\" >0.150319</td>\n",
       "      <td id=\"T_2d389_row0_col10\" class=\"data row0 col10\" >0.166229</td>\n",
       "      <td id=\"T_2d389_row0_col11\" class=\"data row0 col11\" >0.278628</td>\n",
       "      <td id=\"T_2d389_row0_col12\" class=\"data row0 col12\" >0.054549</td>\n",
       "      <td id=\"T_2d389_row0_col13\" class=\"data row0 col13\" >0.350644</td>\n",
       "      <td id=\"T_2d389_row0_col14\" class=\"data row0 col14\" >0.304575</td>\n",
       "      <td id=\"T_2d389_row0_col15\" class=\"data row0 col15\" >0.248665</td>\n",
       "      <td id=\"T_2d389_row0_col16\" class=\"data row0 col16\" >0.041084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2d389_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_2d389_row1_col0\" class=\"data row1 col0\" >1660.481855</td>\n",
       "      <td id=\"T_2d389_row1_col1\" class=\"data row1 col1\" >0.663343</td>\n",
       "      <td id=\"T_2d389_row1_col2\" class=\"data row1 col2\" >19.447675</td>\n",
       "      <td id=\"T_2d389_row1_col3\" class=\"data row1 col3\" >2277.739927</td>\n",
       "      <td id=\"T_2d389_row1_col4\" class=\"data row1 col4\" >0.248459</td>\n",
       "      <td id=\"T_2d389_row1_col5\" class=\"data row1 col5\" >0.058949</td>\n",
       "      <td id=\"T_2d389_row1_col6\" class=\"data row1 col6\" >0.212154</td>\n",
       "      <td id=\"T_2d389_row1_col7\" class=\"data row1 col7\" >0.075312</td>\n",
       "      <td id=\"T_2d389_row1_col8\" class=\"data row1 col8\" >0.080046</td>\n",
       "      <td id=\"T_2d389_row1_col9\" class=\"data row1 col9\" >0.158145</td>\n",
       "      <td id=\"T_2d389_row1_col10\" class=\"data row1 col10\" >0.140806</td>\n",
       "      <td id=\"T_2d389_row1_col11\" class=\"data row1 col11\" >0.218609</td>\n",
       "      <td id=\"T_2d389_row1_col12\" class=\"data row1 col12\" >0.112146</td>\n",
       "      <td id=\"T_2d389_row1_col13\" class=\"data row1 col13\" >0.244500</td>\n",
       "      <td id=\"T_2d389_row1_col14\" class=\"data row1 col14\" >0.236733</td>\n",
       "      <td id=\"T_2d389_row1_col15\" class=\"data row1 col15\" >0.339028</td>\n",
       "      <td id=\"T_2d389_row1_col16\" class=\"data row1 col16\" >0.066682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2d389_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "      <td id=\"T_2d389_row2_col0\" class=\"data row2 col0\" >1849.700000</td>\n",
       "      <td id=\"T_2d389_row2_col1\" class=\"data row2 col1\" >0.615893</td>\n",
       "      <td id=\"T_2d389_row2_col2\" class=\"data row2 col2\" >31.501212</td>\n",
       "      <td id=\"T_2d389_row2_col3\" class=\"data row2 col3\" >3983.049648</td>\n",
       "      <td id=\"T_2d389_row2_col4\" class=\"data row2 col4\" >0.314889</td>\n",
       "      <td id=\"T_2d389_row2_col5\" class=\"data row2 col5\" >0.050260</td>\n",
       "      <td id=\"T_2d389_row2_col6\" class=\"data row2 col6\" >0.126211</td>\n",
       "      <td id=\"T_2d389_row2_col7\" class=\"data row2 col7\" >0.066851</td>\n",
       "      <td id=\"T_2d389_row2_col8\" class=\"data row2 col8\" >0.085326</td>\n",
       "      <td id=\"T_2d389_row2_col9\" class=\"data row2 col9\" >0.183544</td>\n",
       "      <td id=\"T_2d389_row2_col10\" class=\"data row2 col10\" >0.178754</td>\n",
       "      <td id=\"T_2d389_row2_col11\" class=\"data row2 col11\" >0.269320</td>\n",
       "      <td id=\"T_2d389_row2_col12\" class=\"data row2 col12\" >0.051851</td>\n",
       "      <td id=\"T_2d389_row2_col13\" class=\"data row2 col13\" >0.270179</td>\n",
       "      <td id=\"T_2d389_row2_col14\" class=\"data row2 col14\" >0.268076</td>\n",
       "      <td id=\"T_2d389_row2_col15\" class=\"data row2 col15\" >0.341463</td>\n",
       "      <td id=\"T_2d389_row2_col16\" class=\"data row2 col16\" >0.067464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_2d389_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "      <td id=\"T_2d389_row3_col0\" class=\"data row3 col0\" >1730.002309</td>\n",
       "      <td id=\"T_2d389_row3_col1\" class=\"data row3 col1\" >0.679261</td>\n",
       "      <td id=\"T_2d389_row3_col2\" class=\"data row3 col2\" >21.482156</td>\n",
       "      <td id=\"T_2d389_row3_col3\" class=\"data row3 col3\" >2362.686619</td>\n",
       "      <td id=\"T_2d389_row3_col4\" class=\"data row3 col4\" >0.182347</td>\n",
       "      <td id=\"T_2d389_row3_col5\" class=\"data row3 col5\" >0.026644</td>\n",
       "      <td id=\"T_2d389_row3_col6\" class=\"data row3 col6\" >0.129948</td>\n",
       "      <td id=\"T_2d389_row3_col7\" class=\"data row3 col7\" >0.094762</td>\n",
       "      <td id=\"T_2d389_row3_col8\" class=\"data row3 col8\" >0.104231</td>\n",
       "      <td id=\"T_2d389_row3_col9\" class=\"data row3 col9\" >0.187403</td>\n",
       "      <td id=\"T_2d389_row3_col10\" class=\"data row3 col10\" >0.253010</td>\n",
       "      <td id=\"T_2d389_row3_col11\" class=\"data row3 col11\" >0.179104</td>\n",
       "      <td id=\"T_2d389_row3_col12\" class=\"data row3 col12\" >0.028400</td>\n",
       "      <td id=\"T_2d389_row3_col13\" class=\"data row3 col13\" >0.262644</td>\n",
       "      <td id=\"T_2d389_row3_col14\" class=\"data row3 col14\" >0.308561</td>\n",
       "      <td id=\"T_2d389_row3_col15\" class=\"data row3 col15\" >0.345952</td>\n",
       "      <td id=\"T_2d389_row3_col16\" class=\"data row3 col16\" >0.053777</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x14aca9607d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_clusters = 2일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   0\n",
      "1     ST-1000   1\n",
      "2     ST-1002   0\n",
      "3     ST-1003   0\n",
      "4     ST-1004   1\n",
      "5     ST-1005   1\n",
      "6     ST-1006   1\n",
      "7     ST-1007   1\n",
      "8     ST-1008   1\n",
      "9     ST-1010   1\n",
      "10    ST-1011   1\n",
      "11    ST-1012   1\n",
      "12    ST-1013   0\n",
      "13    ST-1014   1\n",
      "14    ST-1015   1\n",
      "15    ST-1016   1\n",
      "16    ST-1017   0\n",
      "17    ST-1018   1\n",
      "18    ST-1019   0\n",
      "19     ST-102   0\n",
      "20    ST-1020   0\n",
      "21    ST-1023   1\n",
      "22    ST-1024   1\n",
      "23    ST-1025   0\n",
      "24    ST-1027   1\n",
      "25    ST-1028   1\n",
      "26    ST-1029   1\n",
      "27     ST-103   0\n",
      "28    ST-1031   1\n",
      "29    ST-1032   1\n",
      "30    ST-1033   0\n",
      "31    ST-1034   0\n",
      "32    ST-1035   0\n",
      "33    ST-1036   0\n",
      "34    ST-1038   0\n",
      "35    ST-1039   0\n",
      "36    ST-1040   1\n",
      "37    ST-1041   0\n",
      "38    ST-1042   1\n",
      "39    ST-1044   1\n",
      "40    ST-1045   0\n",
      "41    ST-1046   0\n",
      "42    ST-1047   0\n",
      "43    ST-1048   1\n",
      "44    ST-1049   1\n",
      "45     ST-105   0\n",
      "46    ST-1050   1\n",
      "47    ST-1051   1\n",
      "48    ST-1053   0\n",
      "49    ST-1054   1\n",
      "50    ST-1055   1\n",
      "51    ST-1056   1\n",
      "52    ST-1058   1\n",
      "53    ST-1059   1\n",
      "54     ST-106   0\n",
      "55    ST-1061   0\n",
      "56    ST-1062   0\n",
      "57    ST-1063   1\n",
      "58    ST-1064   0\n",
      "59    ST-1065   0\n",
      "60    ST-1067   1\n",
      "61    ST-1069   0\n",
      "62     ST-107   0\n",
      "63    ST-1070   0\n",
      "64    ST-1072   0\n",
      "65    ST-1075   0\n",
      "66    ST-1076   1\n",
      "67    ST-1077   1\n",
      "68    ST-1078   0\n",
      "69    ST-1079   0\n",
      "70     ST-108   0\n",
      "71    ST-1081   0\n",
      "72    ST-1082   1\n",
      "73    ST-1083   0\n",
      "74    ST-1084   0\n",
      "75    ST-1085   0\n",
      "76    ST-1086   1\n",
      "77    ST-1087   0\n",
      "78    ST-1088   0\n",
      "79    ST-1089   1\n",
      "80     ST-109   0\n",
      "81    ST-1092   0\n",
      "82    ST-1093   0\n",
      "83    ST-1095   1\n",
      "84    ST-1096   1\n",
      "85    ST-1097   0\n",
      "86    ST-1098   0\n",
      "87    ST-1099   0\n",
      "88      ST-11   0\n",
      "89     ST-110   0\n",
      "90    ST-1100   0\n",
      "91    ST-1101   1\n",
      "92    ST-1102   1\n",
      "93    ST-1103   0\n",
      "94    ST-1104   0\n",
      "95    ST-1105   0\n",
      "96    ST-1106   1\n",
      "97    ST-1107   0\n",
      "98    ST-1109   0\n",
      "99     ST-111   0\n",
      "100   ST-1110   0\n",
      "101   ST-1111   0\n",
      "102   ST-1114   1\n",
      "103   ST-1118   0\n",
      "104   ST-1119   0\n",
      "105    ST-112   0\n",
      "106   ST-1120   1\n",
      "107   ST-1121   0\n",
      "108   ST-1122   0\n",
      "109   ST-1123   1\n",
      "110   ST-1124   0\n",
      "111   ST-1125   1\n",
      "112   ST-1127   1\n",
      "113   ST-1128   1\n",
      "114   ST-1129   0\n",
      "115    ST-113   0\n",
      "116   ST-1130   1\n",
      "117   ST-1131   1\n",
      "118   ST-1132   1\n",
      "119   ST-1133   1\n",
      "120   ST-1135   1\n",
      "121   ST-1136   1\n",
      "122   ST-1137   0\n",
      "123    ST-114   0\n",
      "124   ST-1140   0\n",
      "125   ST-1141   0\n",
      "126   ST-1142   0\n",
      "127   ST-1143   1\n",
      "128   ST-1144   1\n",
      "129   ST-1146   1\n",
      "130   ST-1147   0\n",
      "131   ST-1148   1\n",
      "132   ST-1149   0\n",
      "133   ST-1150   0\n",
      "134   ST-1151   0\n",
      "135   ST-1152   0\n",
      "136   ST-1153   1\n",
      "137   ST-1154   1\n",
      "138   ST-1156   0\n",
      "139   ST-1158   1\n",
      "140    ST-116   1\n",
      "141   ST-1160   0\n",
      "142   ST-1161   0\n",
      "143   ST-1162   1\n",
      "144   ST-1163   1\n",
      "145   ST-1164   1\n",
      "146   ST-1165   1\n",
      "147   ST-1166   0\n",
      "148   ST-1167   1\n",
      "149   ST-1168   0\n",
      "150   ST-1169   0\n",
      "151    ST-117   0\n",
      "152   ST-1171   0\n",
      "153   ST-1172   0\n",
      "154   ST-1173   0\n",
      "155   ST-1174   0\n",
      "156   ST-1177   1\n",
      "157   ST-1178   1\n",
      "158   ST-1179   0\n",
      "159    ST-118   0\n",
      "160   ST-1180   1\n",
      "161   ST-1181   1\n",
      "162   ST-1182   1\n",
      "163   ST-1184   1\n",
      "164   ST-1185   1\n",
      "165   ST-1186   1\n",
      "166   ST-1188   0\n",
      "167   ST-1189   1\n",
      "168    ST-119   1\n",
      "169   ST-1190   0\n",
      "170   ST-1191   0\n",
      "171   ST-1192   0\n",
      "172   ST-1193   0\n",
      "173   ST-1194   0\n",
      "174   ST-1195   0\n",
      "175   ST-1197   0\n",
      "176   ST-1198   0\n",
      "177   ST-1199   0\n",
      "178     ST-12   0\n",
      "179   ST-1200   0\n",
      "180   ST-1201   0\n",
      "181   ST-1202   0\n",
      "182   ST-1203   0\n",
      "183   ST-1204   1\n",
      "184   ST-1206   1\n",
      "185   ST-1207   0\n",
      "186   ST-1208   1\n",
      "187    ST-121   1\n",
      "188   ST-1210   1\n",
      "189   ST-1211   1\n",
      "190   ST-1212   1\n",
      "191   ST-1213   0\n",
      "192   ST-1215   0\n",
      "193   ST-1216   1\n",
      "194   ST-1217   0\n",
      "195   ST-1218   1\n",
      "196   ST-1219   1\n",
      "197   ST-1220   0\n",
      "198   ST-1221   0\n",
      "199   ST-1222   0\n",
      "200   ST-1223   0\n",
      "201   ST-1224   1\n",
      "202   ST-1226   1\n",
      "203   ST-1227   0\n",
      "204   ST-1228   1\n",
      "205   ST-1229   1\n",
      "206    ST-123   1\n",
      "207   ST-1230   1\n",
      "208   ST-1231   1\n",
      "209   ST-1233   0\n",
      "210   ST-1235   1\n",
      "211   ST-1236   0\n",
      "212   ST-1237   0\n",
      "213   ST-1238   1\n",
      "214   ST-1239   1\n",
      "215    ST-124   1\n",
      "216   ST-1241   1\n",
      "217   ST-1243   1\n",
      "218   ST-1245   1\n",
      "219   ST-1246   0\n",
      "220   ST-1247   0\n",
      "221   ST-1248   1\n",
      "222   ST-1249   0\n",
      "223    ST-125   1\n",
      "224   ST-1250   1\n",
      "225   ST-1251   0\n",
      "226   ST-1252   1\n",
      "227   ST-1253   1\n",
      "228   ST-1254   1\n",
      "229   ST-1259   0\n",
      "230    ST-126   1\n",
      "231   ST-1260   0\n",
      "232   ST-1262   0\n",
      "233   ST-1263   0\n",
      "234   ST-1264   0\n",
      "235   ST-1265   0\n",
      "236   ST-1266   0\n",
      "237   ST-1267   1\n",
      "238   ST-1268   0\n",
      "239   ST-1269   0\n",
      "240   ST-1270   0\n",
      "241   ST-1271   0\n",
      "242   ST-1273   0\n",
      "243   ST-1274   0\n",
      "244   ST-1275   0\n",
      "245   ST-1276   0\n",
      "246   ST-1277   0\n",
      "247   ST-1278   1\n",
      "248   ST-1279   0\n",
      "249   ST-1280   0\n",
      "250   ST-1281   0\n",
      "251   ST-1282   1\n",
      "252   ST-1283   1\n",
      "253   ST-1284   1\n",
      "254   ST-1285   0\n",
      "255   ST-1286   0\n",
      "256   ST-1287   1\n",
      "257   ST-1288   1\n",
      "258   ST-1289   1\n",
      "259   ST-1291   0\n",
      "260   ST-1292   1\n",
      "261   ST-1293   1\n",
      "262   ST-1295   1\n",
      "263   ST-1296   0\n",
      "264   ST-1297   1\n",
      "265   ST-1298   0\n",
      "266   ST-1299   0\n",
      "267    ST-130   1\n",
      "268   ST-1300   0\n",
      "269   ST-1302   0\n",
      "270   ST-1305   0\n",
      "271   ST-1306   1\n",
      "272   ST-1307   1\n",
      "273   ST-1309   1\n",
      "274   ST-1310   0\n",
      "275   ST-1311   1\n",
      "276   ST-1312   1\n",
      "277   ST-1313   1\n",
      "278   ST-1314   1\n",
      "279   ST-1315   1\n",
      "280   ST-1317   0\n",
      "281    ST-132   1\n",
      "282   ST-1320   0\n",
      "283   ST-1321   0\n",
      "284   ST-1323   0\n",
      "285   ST-1324   1\n",
      "286   ST-1325   0\n",
      "287   ST-1326   0\n",
      "288   ST-1327   1\n",
      "289   ST-1328   0\n",
      "290   ST-1329   1\n",
      "291   ST-1331   1\n",
      "292   ST-1332   0\n",
      "293   ST-1333   1\n",
      "294   ST-1334   0\n",
      "295   ST-1335   0\n",
      "296   ST-1337   0\n",
      "297   ST-1338   1\n",
      "298   ST-1339   1\n",
      "299    ST-134   1\n",
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      "2415    ST-64   1\n",
      "2416   ST-640   1\n",
      "2417   ST-641   1\n",
      "2418   ST-642   1\n",
      "2419   ST-643   0\n",
      "2420   ST-644   1\n",
      "2421   ST-645   1\n",
      "2422   ST-646   0\n",
      "2423   ST-647   1\n",
      "2424   ST-648   1\n",
      "2425   ST-650   0\n",
      "2426   ST-651   0\n",
      "2427   ST-652   1\n",
      "2428   ST-654   1\n",
      "2429   ST-655   0\n",
      "2430   ST-657   1\n",
      "2431   ST-658   0\n",
      "2432    ST-66   1\n",
      "2433   ST-660   1\n",
      "2434   ST-661   0\n",
      "2435   ST-662   1\n",
      "2436   ST-663   1\n",
      "2437   ST-664   0\n",
      "2438   ST-665   1\n",
      "2439   ST-666   1\n",
      "2440   ST-667   0\n",
      "2441   ST-668   0\n",
      "2442   ST-669   0\n",
      "2443    ST-67   0\n",
      "2444   ST-670   1\n",
      "2445   ST-671   1\n",
      "2446   ST-673   0\n",
      "2447   ST-674   0\n",
      "2448   ST-675   0\n",
      "2449   ST-676   1\n",
      "2450   ST-677   0\n",
      "2451   ST-678   1\n",
      "2452   ST-679   1\n",
      "2453    ST-68   1\n",
      "2454   ST-683   0\n",
      "2455   ST-685   0\n",
      "2456   ST-686   0\n",
      "2457   ST-687   0\n",
      "2458   ST-688   0\n",
      "2459    ST-69   1\n",
      "2460   ST-690   0\n",
      "2461   ST-691   0\n",
      "2462   ST-692   0\n",
      "2463   ST-693   0\n",
      "2464   ST-694   1\n",
      "2465   ST-695   0\n",
      "2466   ST-696   0\n",
      "2467   ST-697   1\n",
      "2468   ST-699   0\n",
      "2469     ST-7   0\n",
      "2470    ST-70   1\n",
      "2471   ST-700   0\n",
      "2472   ST-701   1\n",
      "2473   ST-702   0\n",
      "2474   ST-703   0\n",
      "2475   ST-704   0\n",
      "2476   ST-705   1\n",
      "2477   ST-707   1\n",
      "2478   ST-709   1\n",
      "2479    ST-71   0\n",
      "2480   ST-712   0\n",
      "2481   ST-713   0\n",
      "2482   ST-714   0\n",
      "2483   ST-715   0\n",
      "2484   ST-717   0\n",
      "2485   ST-719   0\n",
      "2486    ST-72   1\n",
      "2487   ST-720   0\n",
      "2488   ST-721   1\n",
      "2489   ST-722   0\n",
      "2490   ST-723   0\n",
      "2491   ST-724   0\n",
      "2492   ST-725   0\n",
      "2493   ST-726   0\n",
      "2494   ST-727   1\n",
      "2495   ST-728   0\n",
      "2496   ST-729   0\n",
      "2497    ST-73   0\n",
      "2498   ST-731   0\n",
      "2499   ST-732   1\n",
      "2500   ST-733   1\n",
      "2501   ST-735   0\n",
      "2502   ST-736   1\n",
      "2503   ST-737   1\n",
      "2504   ST-738   1\n",
      "2505   ST-740   1\n",
      "2506   ST-741   1\n",
      "2507   ST-742   1\n",
      "2508   ST-743   1\n",
      "2509   ST-744   1\n",
      "2510   ST-745   1\n",
      "2511   ST-746   1\n",
      "2512   ST-747   1\n",
      "2513   ST-748   0\n",
      "2514   ST-749   0\n",
      "2515   ST-750   0\n",
      "2516   ST-752   1\n",
      "2517   ST-753   0\n",
      "2518   ST-754   1\n",
      "2519   ST-755   1\n",
      "2520   ST-756   1\n",
      "2521   ST-757   1\n",
      "2522   ST-758   0\n",
      "2523   ST-759   0\n",
      "2524    ST-76   1\n",
      "2525   ST-760   0\n",
      "2526   ST-761   0\n",
      "2527   ST-762   1\n",
      "2528   ST-763   1\n",
      "2529   ST-764   1\n",
      "2530   ST-765   0\n",
      "2531   ST-766   1\n",
      "2532   ST-767   1\n",
      "2533   ST-768   1\n",
      "2534   ST-769   0\n",
      "2535    ST-77   1\n",
      "2536   ST-770   1\n",
      "2537   ST-771   1\n",
      "2538   ST-772   1\n",
      "2539   ST-773   1\n",
      "2540   ST-774   1\n",
      "2541   ST-775   1\n",
      "2542   ST-776   0\n",
      "2543   ST-777   0\n",
      "2544   ST-778   1\n",
      "2545   ST-779   1\n",
      "2546    ST-78   1\n",
      "2547   ST-780   1\n",
      "2548   ST-781   1\n",
      "2549   ST-782   1\n",
      "2550   ST-783   0\n",
      "2551   ST-784   0\n",
      "2552   ST-786   1\n",
      "2553   ST-787   0\n",
      "2554   ST-788   0\n",
      "2555   ST-789   1\n",
      "2556   ST-790   0\n",
      "2557   ST-791   0\n",
      "2558   ST-792   0\n",
      "2559   ST-793   0\n",
      "2560   ST-794   0\n",
      "2561   ST-795   1\n",
      "2562   ST-796   1\n",
      "2563   ST-797   1\n",
      "2564   ST-798   0\n",
      "2565   ST-799   1\n",
      "2566     ST-8   0\n",
      "2567    ST-80   1\n",
      "2568   ST-801   1\n",
      "2569   ST-802   1\n",
      "2570   ST-803   1\n",
      "2571   ST-804   1\n",
      "2572   ST-806   1\n",
      "2573   ST-807   0\n",
      "2574   ST-808   0\n",
      "2575   ST-809   1\n",
      "2576    ST-81   1\n",
      "2577   ST-810   1\n",
      "2578   ST-811   1\n",
      "2579   ST-812   1\n",
      "2580   ST-813   0\n",
      "2581   ST-814   1\n",
      "2582   ST-815   1\n",
      "2583   ST-816   0\n",
      "2584   ST-817   1\n",
      "2585   ST-818   1\n",
      "2586   ST-819   1\n",
      "2587    ST-82   0\n",
      "2588   ST-820   1\n",
      "2589   ST-821   0\n",
      "2590   ST-822   1\n",
      "2591   ST-823   1\n",
      "2592   ST-824   1\n",
      "2593   ST-825   0\n",
      "2594   ST-826   1\n",
      "2595   ST-827   0\n",
      "2596   ST-828   1\n",
      "2597   ST-829   0\n",
      "2598    ST-83   1\n",
      "2599   ST-830   1\n",
      "2600   ST-831   0\n",
      "2601   ST-834   0\n",
      "2602   ST-835   0\n",
      "2603   ST-838   0\n",
      "2604   ST-839   1\n",
      "2605    ST-84   1\n",
      "2606   ST-840   0\n",
      "2607   ST-842   0\n",
      "2608   ST-847   0\n",
      "2609   ST-849   0\n",
      "2610    ST-85   1\n",
      "2611   ST-850   0\n",
      "2612   ST-852   0\n",
      "2613   ST-853   1\n",
      "2614   ST-854   1\n",
      "2615   ST-855   1\n",
      "2616   ST-856   0\n",
      "2617   ST-857   0\n",
      "2618   ST-859   1\n",
      "2619    ST-86   1\n",
      "2620   ST-860   1\n",
      "2621   ST-861   1\n",
      "2622   ST-862   0\n",
      "2623   ST-863   0\n",
      "2624   ST-866   1\n",
      "2625   ST-867   1\n",
      "2626   ST-868   1\n",
      "2627   ST-869   0\n",
      "2628    ST-87   0\n",
      "2629   ST-870   1\n",
      "2630   ST-871   0\n",
      "2631   ST-872   0\n",
      "2632   ST-873   0\n",
      "2633   ST-874   1\n",
      "2634   ST-875   1\n",
      "2635   ST-876   0\n",
      "2636   ST-877   0\n",
      "2637   ST-879   1\n",
      "2638    ST-88   1\n",
      "2639   ST-880   1\n",
      "2640   ST-881   1\n",
      "2641   ST-882   0\n",
      "2642   ST-883   0\n",
      "2643   ST-884   0\n",
      "2644   ST-885   1\n",
      "2645   ST-886   0\n",
      "2646   ST-887   0\n",
      "2647   ST-889   1\n",
      "2648    ST-89   0\n",
      "2649   ST-890   1\n",
      "2650   ST-891   0\n",
      "2651   ST-892   0\n",
      "2652   ST-894   1\n",
      "2653   ST-895   1\n",
      "2654   ST-896   1\n",
      "2655   ST-897   0\n",
      "2656   ST-899   1\n",
      "2657     ST-9   0\n",
      "2658    ST-90   0\n",
      "2659   ST-900   0\n",
      "2660   ST-901   0\n",
      "2661   ST-902   0\n",
      "2662   ST-903   0\n",
      "2663   ST-904   0\n",
      "2664   ST-905   0\n",
      "2665   ST-906   1\n",
      "2666   ST-907   0\n",
      "2667   ST-908   0\n",
      "2668    ST-91   1\n",
      "2669   ST-910   0\n",
      "2670   ST-912   0\n",
      "2671   ST-913   0\n",
      "2672   ST-914   0\n",
      "2673   ST-915   0\n",
      "2674   ST-916   1\n",
      "2675   ST-918   0\n",
      "2676   ST-919   0\n",
      "2677    ST-92   1\n",
      "2678   ST-920   1\n",
      "2679   ST-923   0\n",
      "2680   ST-924   0\n",
      "2681   ST-925   1\n",
      "2682   ST-926   1\n",
      "2683   ST-927   0\n",
      "2684   ST-928   1\n",
      "2685   ST-929   1\n",
      "2686    ST-93   1\n",
      "2687   ST-930   0\n",
      "2688   ST-931   0\n",
      "2689   ST-932   1\n",
      "2690   ST-933   0\n",
      "2691   ST-935   0\n",
      "2692   ST-936   0\n",
      "2693   ST-937   1\n",
      "2694   ST-938   1\n",
      "2695   ST-939   1\n",
      "2696    ST-94   0\n",
      "2697   ST-941   1\n",
      "2698   ST-942   0\n",
      "2699   ST-943   1\n",
      "2700   ST-944   0\n",
      "2701   ST-946   1\n",
      "2702   ST-947   1\n",
      "2703   ST-948   0\n",
      "2704   ST-949   0\n",
      "2705    ST-95   0\n",
      "2706   ST-950   0\n",
      "2707   ST-951   0\n",
      "2708   ST-952   0\n",
      "2709   ST-953   1\n",
      "2710   ST-954   1\n",
      "2711   ST-956   1\n",
      "2712   ST-957   1\n",
      "2713   ST-958   1\n",
      "2714   ST-959   1\n",
      "2715    ST-96   0\n",
      "2716   ST-960   1\n",
      "2717   ST-961   1\n",
      "2718   ST-962   1\n",
      "2719   ST-963   1\n",
      "2720   ST-964   0\n",
      "2721   ST-965   0\n",
      "2722   ST-966   1\n",
      "2723   ST-967   1\n",
      "2724   ST-968   1\n",
      "2725    ST-97   0\n",
      "2726   ST-970   1\n",
      "2727   ST-971   0\n",
      "2728   ST-972   0\n",
      "2729   ST-973   0\n",
      "2730   ST-974   0\n",
      "2731   ST-975   0\n",
      "2732   ST-977   1\n",
      "2733   ST-978   1\n",
      "2734   ST-979   1\n",
      "2735    ST-98   0\n",
      "2736   ST-980   0\n",
      "2737   ST-981   1\n",
      "2738   ST-983   0\n",
      "2739   ST-984   0\n",
      "2740   ST-985   0\n",
      "2741   ST-986   0\n",
      "2742   ST-987   0\n",
      "2743   ST-988   0\n",
      "2744    ST-99   0\n",
      "2745   ST-990   0\n",
      "2746   ST-991   1\n",
      "2747   ST-992   1\n",
      "2748   ST-993   1\n",
      "2749   ST-994   0\n",
      "2750   ST-995   1\n",
      "2751   ST-996   0\n",
      "2752   ST-997   1\n",
      "n_clusters = 3일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   0\n",
      "1     ST-1000   1\n",
      "2     ST-1002   0\n",
      "3     ST-1003   0\n",
      "4     ST-1004   1\n",
      "5     ST-1005   1\n",
      "6     ST-1006   1\n",
      "7     ST-1007   1\n",
      "8     ST-1008   1\n",
      "9     ST-1010   1\n",
      "10    ST-1011   1\n",
      "11    ST-1012   1\n",
      "12    ST-1013   0\n",
      "13    ST-1014   1\n",
      "14    ST-1015   1\n",
      "15    ST-1016   1\n",
      "16    ST-1017   0\n",
      "17    ST-1018   1\n",
      "18    ST-1019   0\n",
      "19     ST-102   0\n",
      "20    ST-1020   0\n",
      "21    ST-1023   2\n",
      "22    ST-1024   2\n",
      "23    ST-1025   0\n",
      "24    ST-1027   1\n",
      "25    ST-1028   1\n",
      "26    ST-1029   1\n",
      "27     ST-103   0\n",
      "28    ST-1031   1\n",
      "29    ST-1032   1\n",
      "30    ST-1033   0\n",
      "31    ST-1034   0\n",
      "32    ST-1035   0\n",
      "33    ST-1036   0\n",
      "34    ST-1038   0\n",
      "35    ST-1039   0\n",
      "36    ST-1040   1\n",
      "37    ST-1041   0\n",
      "38    ST-1042   1\n",
      "39    ST-1044   1\n",
      "40    ST-1045   0\n",
      "41    ST-1046   0\n",
      "42    ST-1047   0\n",
      "43    ST-1048   1\n",
      "44    ST-1049   1\n",
      "45     ST-105   0\n",
      "46    ST-1050   1\n",
      "47    ST-1051   1\n",
      "48    ST-1053   0\n",
      "49    ST-1054   1\n",
      "50    ST-1055   1\n",
      "51    ST-1056   1\n",
      "52    ST-1058   1\n",
      "53    ST-1059   1\n",
      "54     ST-106   0\n",
      "55    ST-1061   0\n",
      "56    ST-1062   0\n",
      "57    ST-1063   1\n",
      "58    ST-1064   0\n",
      "59    ST-1065   0\n",
      "60    ST-1067   1\n",
      "61    ST-1069   0\n",
      "62     ST-107   2\n",
      "63    ST-1070   0\n",
      "64    ST-1072   0\n",
      "65    ST-1075   0\n",
      "66    ST-1076   0\n",
      "67    ST-1077   1\n",
      "68    ST-1078   0\n",
      "69    ST-1079   0\n",
      "70     ST-108   2\n",
      "71    ST-1081   0\n",
      "72    ST-1082   1\n",
      "73    ST-1083   0\n",
      "74    ST-1084   0\n",
      "75    ST-1085   0\n",
      "76    ST-1086   2\n",
      "77    ST-1087   2\n",
      "78    ST-1088   0\n",
      "79    ST-1089   1\n",
      "80     ST-109   0\n",
      "81    ST-1092   0\n",
      "82    ST-1093   0\n",
      "83    ST-1095   2\n",
      "84    ST-1096   1\n",
      "85    ST-1097   0\n",
      "86    ST-1098   0\n",
      "87    ST-1099   0\n",
      "88      ST-11   2\n",
      "89     ST-110   0\n",
      "90    ST-1100   0\n",
      "91    ST-1101   1\n",
      "92    ST-1102   1\n",
      "93    ST-1103   2\n",
      "94    ST-1104   0\n",
      "95    ST-1105   0\n",
      "96    ST-1106   1\n",
      "97    ST-1107   0\n",
      "98    ST-1109   0\n",
      "99     ST-111   0\n",
      "100   ST-1110   0\n",
      "101   ST-1111   0\n",
      "102   ST-1114   2\n",
      "103   ST-1118   0\n",
      "104   ST-1119   0\n",
      "105    ST-112   0\n",
      "106   ST-1120   1\n",
      "107   ST-1121   0\n",
      "108   ST-1122   0\n",
      "109   ST-1123   1\n",
      "110   ST-1124   0\n",
      "111   ST-1125   1\n",
      "112   ST-1127   1\n",
      "113   ST-1128   1\n",
      "114   ST-1129   0\n",
      "115    ST-113   0\n",
      "116   ST-1130   1\n",
      "117   ST-1131   2\n",
      "118   ST-1132   2\n",
      "119   ST-1133   1\n",
      "120   ST-1135   1\n",
      "121   ST-1136   2\n",
      "122   ST-1137   0\n",
      "123    ST-114   0\n",
      "124   ST-1140   0\n",
      "125   ST-1141   0\n",
      "126   ST-1142   0\n",
      "127   ST-1143   1\n",
      "128   ST-1144   1\n",
      "129   ST-1146   1\n",
      "130   ST-1147   0\n",
      "131   ST-1148   2\n",
      "132   ST-1149   0\n",
      "133   ST-1150   0\n",
      "134   ST-1151   0\n",
      "135   ST-1152   0\n",
      "136   ST-1153   2\n",
      "137   ST-1154   1\n",
      "138   ST-1156   0\n",
      "139   ST-1158   2\n",
      "140    ST-116   1\n",
      "141   ST-1160   0\n",
      "142   ST-1161   0\n",
      "143   ST-1162   2\n",
      "144   ST-1163   1\n",
      "145   ST-1164   1\n",
      "146   ST-1165   1\n",
      "147   ST-1166   0\n",
      "148   ST-1167   1\n",
      "149   ST-1168   2\n",
      "150   ST-1169   2\n",
      "151    ST-117   0\n",
      "152   ST-1171   2\n",
      "153   ST-1172   0\n",
      "154   ST-1173   0\n",
      "155   ST-1174   2\n",
      "156   ST-1177   1\n",
      "157   ST-1178   1\n",
      "158   ST-1179   0\n",
      "159    ST-118   0\n",
      "160   ST-1180   1\n",
      "161   ST-1181   2\n",
      "162   ST-1182   2\n",
      "163   ST-1184   1\n",
      "164   ST-1185   1\n",
      "165   ST-1186   1\n",
      "166   ST-1188   0\n",
      "167   ST-1189   1\n",
      "168    ST-119   1\n",
      "169   ST-1190   0\n",
      "170   ST-1191   0\n",
      "171   ST-1192   0\n",
      "172   ST-1193   0\n",
      "173   ST-1194   0\n",
      "174   ST-1195   2\n",
      "175   ST-1197   0\n",
      "176   ST-1198   0\n",
      "177   ST-1199   2\n",
      "178     ST-12   0\n",
      "179   ST-1200   0\n",
      "180   ST-1201   0\n",
      "181   ST-1202   0\n",
      "182   ST-1203   0\n",
      "183   ST-1204   1\n",
      "184   ST-1206   1\n",
      "185   ST-1207   0\n",
      "186   ST-1208   1\n",
      "187    ST-121   1\n",
      "188   ST-1210   1\n",
      "189   ST-1211   1\n",
      "190   ST-1212   1\n",
      "191   ST-1213   2\n",
      "192   ST-1215   0\n",
      "193   ST-1216   1\n",
      "194   ST-1217   0\n",
      "195   ST-1218   1\n",
      "196   ST-1219   1\n",
      "197   ST-1220   0\n",
      "198   ST-1221   0\n",
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      "2313   ST-522   0\n",
      "2314   ST-523   1\n",
      "2315   ST-524   0\n",
      "2316   ST-525   0\n",
      "2317   ST-526   0\n",
      "2318   ST-528   0\n",
      "2319    ST-53   1\n",
      "2320   ST-530   1\n",
      "2321   ST-531   1\n",
      "2322   ST-532   1\n",
      "2323   ST-533   1\n",
      "2324   ST-534   0\n",
      "2325   ST-535   1\n",
      "2326   ST-536   0\n",
      "2327   ST-538   1\n",
      "2328   ST-539   2\n",
      "2329   ST-540   2\n",
      "2330   ST-541   0\n",
      "2331   ST-542   0\n",
      "2332   ST-543   1\n",
      "2333   ST-544   0\n",
      "2334   ST-545   1\n",
      "2335   ST-546   0\n",
      "2336   ST-547   2\n",
      "2337   ST-548   2\n",
      "2338   ST-549   0\n",
      "2339    ST-55   2\n",
      "2340   ST-550   0\n",
      "2341   ST-551   0\n",
      "2342   ST-553   0\n",
      "2343   ST-555   0\n",
      "2344   ST-558   0\n",
      "2345   ST-559   1\n",
      "2346   ST-560   0\n",
      "2347   ST-561   0\n",
      "2348   ST-562   0\n",
      "2349   ST-563   0\n",
      "2350   ST-564   0\n",
      "2351   ST-565   1\n",
      "2352   ST-566   0\n",
      "2353   ST-567   1\n",
      "2354   ST-568   0\n",
      "2355   ST-570   1\n",
      "2356   ST-571   1\n",
      "2357   ST-572   0\n",
      "2358   ST-573   1\n",
      "2359   ST-574   0\n",
      "2360   ST-578   0\n",
      "2361   ST-579   0\n",
      "2362   ST-580   0\n",
      "2363   ST-583   1\n",
      "2364   ST-584   1\n",
      "2365   ST-585   0\n",
      "2366   ST-586   1\n",
      "2367   ST-587   2\n",
      "2368   ST-588   1\n",
      "2369   ST-589   0\n",
      "2370    ST-59   1\n",
      "2371   ST-590   1\n",
      "2372   ST-593   0\n",
      "2373   ST-594   0\n",
      "2374   ST-595   1\n",
      "2375   ST-596   0\n",
      "2376   ST-599   0\n",
      "2377     ST-6   2\n",
      "2378    ST-60   1\n",
      "2379   ST-600   0\n",
      "2380   ST-602   0\n",
      "2381   ST-603   0\n",
      "2382   ST-604   0\n",
      "2383   ST-605   0\n",
      "2384   ST-608   1\n",
      "2385   ST-609   1\n",
      "2386   ST-610   0\n",
      "2387   ST-611   0\n",
      "2388   ST-612   1\n",
      "2389   ST-613   1\n",
      "2390   ST-614   1\n",
      "2391   ST-615   0\n",
      "2392   ST-616   1\n",
      "2393   ST-619   0\n",
      "2394    ST-62   1\n",
      "2395   ST-620   0\n",
      "2396   ST-621   0\n",
      "2397   ST-622   1\n",
      "2398   ST-623   1\n",
      "2399   ST-624   0\n",
      "2400   ST-625   0\n",
      "2401   ST-626   1\n",
      "2402   ST-628   2\n",
      "2403   ST-629   0\n",
      "2404    ST-63   1\n",
      "2405   ST-630   1\n",
      "2406   ST-631   0\n",
      "2407   ST-632   2\n",
      "2408   ST-633   2\n",
      "2409   ST-634   1\n",
      "2410   ST-635   0\n",
      "2411   ST-636   0\n",
      "2412   ST-637   0\n",
      "2413   ST-638   0\n",
      "2414   ST-639   0\n",
      "2415    ST-64   2\n",
      "2416   ST-640   2\n",
      "2417   ST-641   1\n",
      "2418   ST-642   1\n",
      "2419   ST-643   0\n",
      "2420   ST-644   1\n",
      "2421   ST-645   1\n",
      "2422   ST-646   0\n",
      "2423   ST-647   1\n",
      "2424   ST-648   1\n",
      "2425   ST-650   0\n",
      "2426   ST-651   0\n",
      "2427   ST-652   1\n",
      "2428   ST-654   1\n",
      "2429   ST-655   0\n",
      "2430   ST-657   2\n",
      "2431   ST-658   0\n",
      "2432    ST-66   1\n",
      "2433   ST-660   2\n",
      "2434   ST-661   0\n",
      "2435   ST-662   1\n",
      "2436   ST-663   1\n",
      "2437   ST-664   0\n",
      "2438   ST-665   1\n",
      "2439   ST-666   1\n",
      "2440   ST-667   0\n",
      "2441   ST-668   0\n",
      "2442   ST-669   0\n",
      "2443    ST-67   2\n",
      "2444   ST-670   1\n",
      "2445   ST-671   1\n",
      "2446   ST-673   0\n",
      "2447   ST-674   0\n",
      "2448   ST-675   0\n",
      "2449   ST-676   1\n",
      "2450   ST-677   0\n",
      "2451   ST-678   1\n",
      "2452   ST-679   2\n",
      "2453    ST-68   1\n",
      "2454   ST-683   2\n",
      "2455   ST-685   0\n",
      "2456   ST-686   0\n",
      "2457   ST-687   0\n",
      "2458   ST-688   0\n",
      "2459    ST-69   1\n",
      "2460   ST-690   0\n",
      "2461   ST-691   0\n",
      "2462   ST-692   2\n",
      "2463   ST-693   2\n",
      "2464   ST-694   1\n",
      "2465   ST-695   2\n",
      "2466   ST-696   0\n",
      "2467   ST-697   1\n",
      "2468   ST-699   0\n",
      "2469     ST-7   0\n",
      "2470    ST-70   1\n",
      "2471   ST-700   0\n",
      "2472   ST-701   1\n",
      "2473   ST-702   0\n",
      "2474   ST-703   0\n",
      "2475   ST-704   0\n",
      "2476   ST-705   1\n",
      "2477   ST-707   1\n",
      "2478   ST-709   1\n",
      "2479    ST-71   0\n",
      "2480   ST-712   0\n",
      "2481   ST-713   2\n",
      "2482   ST-714   0\n",
      "2483   ST-715   0\n",
      "2484   ST-717   0\n",
      "2485   ST-719   0\n",
      "2486    ST-72   1\n",
      "2487   ST-720   0\n",
      "2488   ST-721   1\n",
      "2489   ST-722   0\n",
      "2490   ST-723   0\n",
      "2491   ST-724   2\n",
      "2492   ST-725   0\n",
      "2493   ST-726   0\n",
      "2494   ST-727   1\n",
      "2495   ST-728   0\n",
      "2496   ST-729   0\n",
      "2497    ST-73   2\n",
      "2498   ST-731   0\n",
      "2499   ST-732   1\n",
      "2500   ST-733   1\n",
      "2501   ST-735   0\n",
      "2502   ST-736   1\n",
      "2503   ST-737   0\n",
      "2504   ST-738   2\n",
      "2505   ST-740   1\n",
      "2506   ST-741   2\n",
      "2507   ST-742   1\n",
      "2508   ST-743   1\n",
      "2509   ST-744   1\n",
      "2510   ST-745   1\n",
      "2511   ST-746   1\n",
      "2512   ST-747   1\n",
      "2513   ST-748   2\n",
      "2514   ST-749   2\n",
      "2515   ST-750   2\n",
      "2516   ST-752   2\n",
      "2517   ST-753   0\n",
      "2518   ST-754   1\n",
      "2519   ST-755   1\n",
      "2520   ST-756   1\n",
      "2521   ST-757   1\n",
      "2522   ST-758   0\n",
      "2523   ST-759   0\n",
      "2524    ST-76   1\n",
      "2525   ST-760   0\n",
      "2526   ST-761   0\n",
      "2527   ST-762   1\n",
      "2528   ST-763   1\n",
      "2529   ST-764   1\n",
      "2530   ST-765   0\n",
      "2531   ST-766   1\n",
      "2532   ST-767   1\n",
      "2533   ST-768   1\n",
      "2534   ST-769   0\n",
      "2535    ST-77   1\n",
      "2536   ST-770   1\n",
      "2537   ST-771   2\n",
      "2538   ST-772   1\n",
      "2539   ST-773   1\n",
      "2540   ST-774   1\n",
      "2541   ST-775   1\n",
      "2542   ST-776   2\n",
      "2543   ST-777   2\n",
      "2544   ST-778   1\n",
      "2545   ST-779   2\n",
      "2546    ST-78   0\n",
      "2547   ST-780   1\n",
      "2548   ST-781   1\n",
      "2549   ST-782   2\n",
      "2550   ST-783   0\n",
      "2551   ST-784   2\n",
      "2552   ST-786   2\n",
      "2553   ST-787   2\n",
      "2554   ST-788   0\n",
      "2555   ST-789   1\n",
      "2556   ST-790   2\n",
      "2557   ST-791   2\n",
      "2558   ST-792   2\n",
      "2559   ST-793   2\n",
      "2560   ST-794   2\n",
      "2561   ST-795   1\n",
      "2562   ST-796   2\n",
      "2563   ST-797   1\n",
      "2564   ST-798   2\n",
      "2565   ST-799   2\n",
      "2566     ST-8   2\n",
      "2567    ST-80   1\n",
      "2568   ST-801   2\n",
      "2569   ST-802   1\n",
      "2570   ST-803   2\n",
      "2571   ST-804   2\n",
      "2572   ST-806   1\n",
      "2573   ST-807   2\n",
      "2574   ST-808   0\n",
      "2575   ST-809   1\n",
      "2576    ST-81   1\n",
      "2577   ST-810   1\n",
      "2578   ST-811   1\n",
      "2579   ST-812   1\n",
      "2580   ST-813   0\n",
      "2581   ST-814   1\n",
      "2582   ST-815   1\n",
      "2583   ST-816   0\n",
      "2584   ST-817   1\n",
      "2585   ST-818   1\n",
      "2586   ST-819   1\n",
      "2587    ST-82   0\n",
      "2588   ST-820   1\n",
      "2589   ST-821   0\n",
      "2590   ST-822   1\n",
      "2591   ST-823   1\n",
      "2592   ST-824   1\n",
      "2593   ST-825   0\n",
      "2594   ST-826   1\n",
      "2595   ST-827   0\n",
      "2596   ST-828   1\n",
      "2597   ST-829   0\n",
      "2598    ST-83   1\n",
      "2599   ST-830   1\n",
      "2600   ST-831   0\n",
      "2601   ST-834   0\n",
      "2602   ST-835   0\n",
      "2603   ST-838   0\n",
      "2604   ST-839   1\n",
      "2605    ST-84   1\n",
      "2606   ST-840   0\n",
      "2607   ST-842   0\n",
      "2608   ST-847   0\n",
      "2609   ST-849   0\n",
      "2610    ST-85   2\n",
      "2611   ST-850   0\n",
      "2612   ST-852   0\n",
      "2613   ST-853   1\n",
      "2614   ST-854   1\n",
      "2615   ST-855   1\n",
      "2616   ST-856   0\n",
      "2617   ST-857   0\n",
      "2618   ST-859   1\n",
      "2619    ST-86   0\n",
      "2620   ST-860   1\n",
      "2621   ST-861   1\n",
      "2622   ST-862   2\n",
      "2623   ST-863   0\n",
      "2624   ST-866   1\n",
      "2625   ST-867   1\n",
      "2626   ST-868   1\n",
      "2627   ST-869   0\n",
      "2628    ST-87   2\n",
      "2629   ST-870   1\n",
      "2630   ST-871   0\n",
      "2631   ST-872   1\n",
      "2632   ST-873   0\n",
      "2633   ST-874   1\n",
      "2634   ST-875   2\n",
      "2635   ST-876   0\n",
      "2636   ST-877   2\n",
      "2637   ST-879   1\n",
      "2638    ST-88   1\n",
      "2639   ST-880   1\n",
      "2640   ST-881   2\n",
      "2641   ST-882   0\n",
      "2642   ST-883   0\n",
      "2643   ST-884   0\n",
      "2644   ST-885   2\n",
      "2645   ST-886   0\n",
      "2646   ST-887   0\n",
      "2647   ST-889   1\n",
      "2648    ST-89   2\n",
      "2649   ST-890   1\n",
      "2650   ST-891   0\n",
      "2651   ST-892   0\n",
      "2652   ST-894   1\n",
      "2653   ST-895   1\n",
      "2654   ST-896   2\n",
      "2655   ST-897   0\n",
      "2656   ST-899   1\n",
      "2657     ST-9   0\n",
      "2658    ST-90   0\n",
      "2659   ST-900   0\n",
      "2660   ST-901   0\n",
      "2661   ST-902   2\n",
      "2662   ST-903   0\n",
      "2663   ST-904   0\n",
      "2664   ST-905   0\n",
      "2665   ST-906   1\n",
      "2666   ST-907   0\n",
      "2667   ST-908   0\n",
      "2668    ST-91   1\n",
      "2669   ST-910   0\n",
      "2670   ST-912   0\n",
      "2671   ST-913   0\n",
      "2672   ST-914   0\n",
      "2673   ST-915   0\n",
      "2674   ST-916   1\n",
      "2675   ST-918   0\n",
      "2676   ST-919   0\n",
      "2677    ST-92   1\n",
      "2678   ST-920   1\n",
      "2679   ST-923   0\n",
      "2680   ST-924   0\n",
      "2681   ST-925   2\n",
      "2682   ST-926   1\n",
      "2683   ST-927   0\n",
      "2684   ST-928   2\n",
      "2685   ST-929   1\n",
      "2686    ST-93   1\n",
      "2687   ST-930   0\n",
      "2688   ST-931   0\n",
      "2689   ST-932   1\n",
      "2690   ST-933   0\n",
      "2691   ST-935   0\n",
      "2692   ST-936   0\n",
      "2693   ST-937   1\n",
      "2694   ST-938   2\n",
      "2695   ST-939   1\n",
      "2696    ST-94   0\n",
      "2697   ST-941   1\n",
      "2698   ST-942   0\n",
      "2699   ST-943   1\n",
      "2700   ST-944   0\n",
      "2701   ST-946   1\n",
      "2702   ST-947   1\n",
      "2703   ST-948   0\n",
      "2704   ST-949   0\n",
      "2705    ST-95   0\n",
      "2706   ST-950   0\n",
      "2707   ST-951   2\n",
      "2708   ST-952   0\n",
      "2709   ST-953   2\n",
      "2710   ST-954   1\n",
      "2711   ST-956   1\n",
      "2712   ST-957   1\n",
      "2713   ST-958   1\n",
      "2714   ST-959   1\n",
      "2715    ST-96   0\n",
      "2716   ST-960   1\n",
      "2717   ST-961   1\n",
      "2718   ST-962   1\n",
      "2719   ST-963   1\n",
      "2720   ST-964   0\n",
      "2721   ST-965   0\n",
      "2722   ST-966   1\n",
      "2723   ST-967   1\n",
      "2724   ST-968   2\n",
      "2725    ST-97   0\n",
      "2726   ST-970   1\n",
      "2727   ST-971   2\n",
      "2728   ST-972   0\n",
      "2729   ST-973   0\n",
      "2730   ST-974   0\n",
      "2731   ST-975   0\n",
      "2732   ST-977   1\n",
      "2733   ST-978   1\n",
      "2734   ST-979   1\n",
      "2735    ST-98   0\n",
      "2736   ST-980   0\n",
      "2737   ST-981   1\n",
      "2738   ST-983   0\n",
      "2739   ST-984   0\n",
      "2740   ST-985   0\n",
      "2741   ST-986   0\n",
      "2742   ST-987   0\n",
      "2743   ST-988   0\n",
      "2744    ST-99   2\n",
      "2745   ST-990   0\n",
      "2746   ST-991   1\n",
      "2747   ST-992   1\n",
      "2748   ST-993   1\n",
      "2749   ST-994   0\n",
      "2750   ST-995   1\n",
      "2751   ST-996   0\n",
      "2752   ST-997   1\n",
      "n_clusters = 4일 때 각 대여소가 속한 군집:\n",
      "      대여대여소ID  군집\n",
      "0       ST-10   0\n",
      "1     ST-1000   1\n",
      "2     ST-1002   0\n",
      "3     ST-1003   0\n",
      "4     ST-1004   1\n",
      "5     ST-1005   1\n",
      "6     ST-1006   1\n",
      "7     ST-1007   1\n",
      "8     ST-1008   1\n",
      "9     ST-1010   1\n",
      "10    ST-1011   1\n",
      "11    ST-1012   1\n",
      "12    ST-1013   0\n",
      "13    ST-1014   1\n",
      "14    ST-1015   1\n",
      "15    ST-1016   1\n",
      "16    ST-1017   0\n",
      "17    ST-1018   1\n",
      "18    ST-1019   0\n",
      "19     ST-102   0\n",
      "20    ST-1020   1\n",
      "21    ST-1023   2\n",
      "22    ST-1024   2\n",
      "23    ST-1025   0\n",
      "24    ST-1027   3\n",
      "25    ST-1028   1\n",
      "26    ST-1029   3\n",
      "27     ST-103   3\n",
      "28    ST-1031   1\n",
      "29    ST-1032   1\n",
      "30    ST-1033   0\n",
      "31    ST-1034   0\n",
      "32    ST-1035   0\n",
      "33    ST-1036   0\n",
      "34    ST-1038   0\n",
      "35    ST-1039   0\n",
      "36    ST-1040   3\n",
      "37    ST-1041   0\n",
      "38    ST-1042   1\n",
      "39    ST-1044   1\n",
      "40    ST-1045   0\n",
      "41    ST-1046   0\n",
      "42    ST-1047   0\n",
      "43    ST-1048   1\n",
      "44    ST-1049   1\n",
      "45     ST-105   0\n",
      "46    ST-1050   1\n",
      "47    ST-1051   1\n",
      "48    ST-1053   1\n",
      "49    ST-1054   1\n",
      "50    ST-1055   1\n",
      "51    ST-1056   1\n",
      "52    ST-1058   1\n",
      "53    ST-1059   1\n",
      "54     ST-106   0\n",
      "55    ST-1061   0\n",
      "56    ST-1062   0\n",
      "57    ST-1063   1\n",
      "58    ST-1064   0\n",
      "59    ST-1065   0\n",
      "60    ST-1067   1\n",
      "61    ST-1069   0\n",
      "62     ST-107   2\n",
      "63    ST-1070   0\n",
      "64    ST-1072   0\n",
      "65    ST-1075   0\n",
      "66    ST-1076   3\n",
      "67    ST-1077   1\n",
      "68    ST-1078   0\n",
      "69    ST-1079   0\n",
      "70     ST-108   0\n",
      "71    ST-1081   0\n",
      "72    ST-1082   1\n",
      "73    ST-1083   0\n",
      "74    ST-1084   0\n",
      "75    ST-1085   0\n",
      "76    ST-1086   2\n",
      "77    ST-1087   2\n",
      "78    ST-1088   0\n",
      "79    ST-1089   3\n",
      "80     ST-109   0\n",
      "81    ST-1092   0\n",
      "82    ST-1093   1\n",
      "83    ST-1095   1\n",
      "84    ST-1096   1\n",
      "85    ST-1097   0\n",
      "86    ST-1098   0\n",
      "87    ST-1099   0\n",
      "88      ST-11   2\n",
      "89     ST-110   0\n",
      "90    ST-1100   0\n",
      "91    ST-1101   1\n",
      "92    ST-1102   1\n",
      "93    ST-1103   0\n",
      "94    ST-1104   0\n",
      "95    ST-1105   0\n",
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      "2751   ST-996   0\n",
      "2752   ST-997   1\n"
     ]
    }
   ],
   "source": [
    "# 변수 초기화\n",
    "cluster_results = {}\n",
    "\n",
    "# n_clusters 값을 2, 3, 4로 설정하여 K-means 군집분석 및 시각화\n",
    "for n_clusters in [2, 3, 4]:\n",
    "    # K-means 군집분석\n",
    "    kmeans = KMeans(n_clusters=n_clusters, random_state=42)\n",
    "    grouped['군집'] = kmeans.fit_predict(scaled_features)\n",
    "\n",
    "    # PCA 적용\n",
    "    pca = PCA(n_components=2)\n",
    "    pca_features = pca.fit_transform(scaled_features)\n",
    "\n",
    "    # PCA 결과를 데이터프레임에 추가\n",
    "    grouped['PCA1'] = pca_features[:, 0]\n",
    "    grouped['PCA2'] = pca_features[:, 1]\n",
    "\n",
    "    # 군집 시각화\n",
    "    plt.figure(figsize=(10, 7))\n",
    "    plt.scatter(grouped['PCA1'], grouped['PCA2'], c=grouped['군집'], cmap='viridis')\n",
    "    plt.xlabel('PCA1')\n",
    "    plt.ylabel('PCA2')\n",
    "    plt.title(f'대여소 군집 결과 (PCA, n_clusters={n_clusters})')\n",
    "    plt.colorbar(label='군집')\n",
    "    plt.show()\n",
    "    \n",
    "    # 각 군집의 평균 값 계산 (대여대여소ID 제외)\n",
    "    grouped_means = grouped.drop(columns=['대여대여소ID', 'PCA1', 'PCA2']).groupby('군집').mean()\n",
    "\n",
    "    # # 컬럼 별로 가장 높은 값을 가진 군집의 셀에 파란색 배경 추가\n",
    "    # def highlight_max(s):\n",
    "    #     is_max = s == s.max()\n",
    "    #     return ['background-color: #ccffcc' if v else '' for v in is_max]\n",
    "\n",
    "    # styled_means = grouped_means.style.apply(highlight_max)\n",
    "    \n",
    "    # 컬럼 별로 가장 높은 값을 가진 군집의 셀에 연한 초록색 배경 추가\n",
    "    def highlight_max(s):\n",
    "        is_max = s == s.max()\n",
    "        return ['background-color: #ccffcc' if v else '' for v in is_max]\n",
    "\n",
    "    # 컬럼 별로 가장 낮은 값을 가진 군집의 셀에 연한 노랑색 배경 추가\n",
    "    def highlight_min(s):\n",
    "        is_min = s == s.min()\n",
    "        return ['background-color: #fffff0' if v else '' for v in is_min]\n",
    "\n",
    "    styled_means = grouped_means.style.apply(highlight_max).apply(highlight_min)\n",
    "\n",
    "    \n",
    "    # 결과 출력\n",
    "    print(f\"n_clusters = {n_clusters}일 때 각 군집의 평균 값:\")\n",
    "    display(styled_means)\n",
    "    \n",
    "    # 각 대여소가 속한 군집 저장\n",
    "    cluster_results[f'cluster_{n_clusters}'] = grouped[['대여대여소ID', '군집']].copy()\n",
    "\n",
    "# 결과 데이터프레임 확인\n",
    "df_ins_2 = cluster_results['cluster_2']\n",
    "df_ins_3 = cluster_results['cluster_3']\n",
    "df_ins_4 = cluster_results['cluster_4']\n",
    "\n",
    "print(\"n_clusters = 2일 때 각 대여소가 속한 군집:\")\n",
    "print(df_ins_2)\n",
    "\n",
    "print(\"n_clusters = 3일 때 각 대여소가 속한 군집:\")\n",
    "print(df_ins_3)\n",
    "\n",
    "print(\"n_clusters = 4일 때 각 대여소가 속한 군집:\")\n",
    "print(df_ins_4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대여소ID</th>\n",
       "      <th>군집</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "      <th>구</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>ST-10</td>\n",
       "      <td>0</td>\n",
       "      <td>37.55275</td>\n",
       "      <td>126.91862</td>\n",
       "      <td>마포구</td>\n",
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       "      <td>ST-1000</td>\n",
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       "      <td>37.51038</td>\n",
       "      <td>126.86680</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
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       "      <td>ST-1002</td>\n",
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       "      <td>ST-1003</td>\n",
       "      <td>0</td>\n",
       "      <td>37.53955</td>\n",
       "      <td>126.82830</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ST-1004</td>\n",
       "      <td>1</td>\n",
       "      <td>37.51410</td>\n",
       "      <td>126.83100</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     대여소ID  군집        위도         경도    구\n",
       "0    ST-10   0  37.55275  126.91862  마포구\n",
       "1  ST-1000   1  37.51038  126.86680  양천구\n",
       "2  ST-1002   0  37.52990  126.87654  양천구\n",
       "3  ST-1003   0  37.53955  126.82830  양천구\n",
       "4  ST-1004   1  37.51410  126.83100  양천구"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in_k_2 = pd.merge(df_ins_2, ll_join, how='left', left_on='대여대여소ID', right_on='대여소_ID')\n",
    "in_k_2 = in_k_2.drop(columns=['대여소_ID'])\n",
    "in_k_2.columns = ['대여소ID', '군집', '위도', '경도', '구']\n",
    "in_k_2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [],
   "source": [
    "in_k_2.to_csv('./(군집_내국인_k=2_청12간) 서울시 따릉이 대여소 별 군집결과_마스터 조인.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "      <th></th>\n",
       "      <th>대여소ID</th>\n",
       "      <th>군집</th>\n",
       "      <th>위도</th>\n",
       "      <th>경도</th>\n",
       "      <th>구</th>\n",
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       "      <td>126.91862</td>\n",
       "      <td>마포구</td>\n",
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       "      <td>ST-1000</td>\n",
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       "      <td>37.51038</td>\n",
       "      <td>126.86680</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ST-1002</td>\n",
       "      <td>0</td>\n",
       "      <td>37.52990</td>\n",
       "      <td>126.87654</td>\n",
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       "      <td>ST-1003</td>\n",
       "      <td>0</td>\n",
       "      <td>37.53955</td>\n",
       "      <td>126.82830</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ST-1004</td>\n",
       "      <td>1</td>\n",
       "      <td>37.51410</td>\n",
       "      <td>126.83100</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "     대여소ID  군집        위도         경도    구\n",
       "0    ST-10   0  37.55275  126.91862  마포구\n",
       "1  ST-1000   1  37.51038  126.86680  양천구\n",
       "2  ST-1002   0  37.52990  126.87654  양천구\n",
       "3  ST-1003   0  37.53955  126.82830  양천구\n",
       "4  ST-1004   1  37.51410  126.83100  양천구"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in_k_3_ = pd.merge(df_ins_3, ll_join, how='left', left_on='대여대여소ID', right_on='대여소_ID')\n",
    "in_k_3_ = in_k_3_.drop(columns=['대여소_ID'])\n",
    "in_k_3_.columns = ['대여소ID', '군집', '위도', '경도', '구']\n",
    "in_k_3_.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [],
   "source": [
    "in_k_3_.to_csv('./(군집_내국인_k=3_청12간) 서울시 따릉이 대여소 별 군집결과_마스터 조인.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>군집</th>\n",
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       "      <th>0</th>\n",
       "      <td>ST-10</td>\n",
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       "      <td>126.91862</td>\n",
       "      <td>마포구</td>\n",
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       "      <th>1</th>\n",
       "      <td>ST-1000</td>\n",
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       "      <td>37.51038</td>\n",
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       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ST-1002</td>\n",
       "      <td>0</td>\n",
       "      <td>37.52990</td>\n",
       "      <td>126.87654</td>\n",
       "      <td>양천구</td>\n",
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       "      <th>3</th>\n",
       "      <td>ST-1003</td>\n",
       "      <td>0</td>\n",
       "      <td>37.53955</td>\n",
       "      <td>126.82830</td>\n",
       "      <td>양천구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ST-1004</td>\n",
       "      <td>1</td>\n",
       "      <td>37.51410</td>\n",
       "      <td>126.83100</td>\n",
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       "     대여소ID  군집        위도         경도    구\n",
       "0    ST-10   0  37.55275  126.91862  마포구\n",
       "1  ST-1000   1  37.51038  126.86680  양천구\n",
       "2  ST-1002   0  37.52990  126.87654  양천구\n",
       "3  ST-1003   0  37.53955  126.82830  양천구\n",
       "4  ST-1004   1  37.51410  126.83100  양천구"
      ]
     },
     "execution_count": 175,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in_k_4_ = pd.merge(df_ins_4, ll_join, how='left', left_on='대여대여소ID', right_on='대여소_ID')\n",
    "in_k_4_ = in_k_4_.drop(columns=['대여소_ID'])\n",
    "in_k_4_.columns = ['대여소ID', '군집', '위도', '경도', '구']\n",
    "in_k_4_.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [],
   "source": [
    "in_k_4_.to_csv('./(군집_내국인_k=4_청12간) 서울시 따릉이 대여소 별 군집결과_마스터 조인.csv', index=False)"
   ]
  }
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