{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4b6a460b",
   "metadata": {},
   "source": [
    "# 공공데이터를 이용한 카페 상권분석(2021 Ver.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d97c93e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 먼저 필요한 라이브러리를 불러옵니다.\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2f14724",
   "metadata": {},
   "source": [
    "## 1. 데이터 불러오기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e75285ec",
   "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>상가업소번호</th>\n",
       "      <th>상호명</th>\n",
       "      <th>지점명</th>\n",
       "      <th>상권업종대분류코드</th>\n",
       "      <th>상권업종대분류명</th>\n",
       "      <th>상권업종중분류코드</th>\n",
       "      <th>상권업종중분류명</th>\n",
       "      <th>상권업종소분류코드</th>\n",
       "      <th>상권업종소분류명</th>\n",
       "      <th>표준산업분류코드</th>\n",
       "      <th>...</th>\n",
       "      <th>건물관리번호</th>\n",
       "      <th>건물명</th>\n",
       "      <th>도로명주소</th>\n",
       "      <th>구우편번호</th>\n",
       "      <th>신우편번호</th>\n",
       "      <th>동정보</th>\n",
       "      <th>층정보</th>\n",
       "      <th>호정보</th>\n",
       "      <th>경도</th>\n",
       "      <th>위도</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>23498449</td>\n",
       "      <td>츄로하임</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "      <td>음식</td>\n",
       "      <td>Q01</td>\n",
       "      <td>한식</td>\n",
       "      <td>Q01A01</td>\n",
       "      <td>한식/백반/한정식</td>\n",
       "      <td>I56111</td>\n",
       "      <td>...</td>\n",
       "      <td>2826010400109750004000001</td>\n",
       "      <td>청라반도유보라</td>\n",
       "      <td>인천광역시 서구 솔빛로 55</td>\n",
       "      <td>404170.0</td>\n",
       "      <td>22765.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>102</td>\n",
       "      <td>126.626740</td>\n",
       "      <td>37.525163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>22882934</td>\n",
       "      <td>간석미용실</td>\n",
       "      <td>NaN</td>\n",
       "      <td>F</td>\n",
       "      <td>생활서비스</td>\n",
       "      <td>F01</td>\n",
       "      <td>이/미용/건강</td>\n",
       "      <td>F01A01</td>\n",
       "      <td>여성미용실</td>\n",
       "      <td>S96112</td>\n",
       "      <td>...</td>\n",
       "      <td>2820010200101900026021270</td>\n",
       "      <td>NaN</td>\n",
       "      <td>인천광역시 남동구 석촌로14번길 5</td>\n",
       "      <td>405230.0</td>\n",
       "      <td>21545.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>126.709349</td>\n",
       "      <td>37.461969</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 39 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     상가업소번호    상호명  지점명 상권업종대분류코드 상권업종대분류명 상권업종중분류코드 상권업종중분류명 상권업종소분류코드  \\\n",
       "0  23498449   츄로하임  NaN         Q       음식       Q01       한식    Q01A01   \n",
       "1  22882934  간석미용실  NaN         F    생활서비스       F01  이/미용/건강    F01A01   \n",
       "\n",
       "    상권업종소분류명 표준산업분류코드  ...                     건물관리번호      건물명  \\\n",
       "0  한식/백반/한정식   I56111  ...  2826010400109750004000001  청라반도유보라   \n",
       "1      여성미용실   S96112  ...  2820010200101900026021270      NaN   \n",
       "\n",
       "                 도로명주소     구우편번호    신우편번호  동정보  층정보  호정보          경도  \\\n",
       "0      인천광역시 서구 솔빛로 55  404170.0  22765.0  NaN  NaN  102  126.626740   \n",
       "1  인천광역시 남동구 석촌로14번길 5  405230.0  21545.0  NaN  NaN  NaN  126.709349   \n",
       "\n",
       "          위도  \n",
       "0  37.525163  \n",
       "1  37.461969  \n",
       "\n",
       "[2 rows x 39 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 다운로드 받은 데이터중 일부를 열어봅니다.\n",
    "temp = pd.read_csv(\"../my room/data1/소상공인시장진흥공단_상가(상권)정보_인천_202103.csv\"\n",
    "                   ,sep=',',encoding = \"utf-8\")\n",
    "temp.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a3e3257c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['상가업소번호', '상호명', '지점명', '상권업종대분류코드', '상권업종대분류명', '상권업종중분류코드',\n",
       "       '상권업종중분류명', '상권업종소분류코드', '상권업종소분류명', '표준산업분류코드', '표준산업분류명', '시도코드',\n",
       "       '시도명', '시군구코드', '시군구명', '행정동코드', '행정동명', '법정동코드', '법정동명', '지번코드',\n",
       "       '대지구분코드', '대지구분명', '지번본번지', '지번부번지', '지번주소', '도로명코드', '도로명', '건물본번지',\n",
       "       '건물부번지', '건물관리번호', '건물명', '도로명주소', '구우편번호', '신우편번호', '동정보', '층정보',\n",
       "       '호정보', '경도', '위도'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 39개의 변수를 확인해 볼 필요가 있다.\n",
    "temp.columns\n",
    "# 변수가 너무 많다!! \n",
    "# 카페를 분석하는 데 필요한 변수만 추출할 것이다!!\n",
    "#temp.상권업종소분류명.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f0bb6d5",
   "metadata": {},
   "source": [
    "### (1) 일단 여러 csv 파일 한번에 불러오기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b5bc16e5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\work\\envs\\datascience\\lib\\site-packages\\IPython\\core\\interactiveshell.py:3165: DtypeWarning: Columns (35) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  has_raised = await self.run_ast_nodes(code_ast.body, cell_name,\n"
     ]
    },
    {
     "data": {
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "  <thead>\n",
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       "      <th>상가업소번호</th>\n",
       "      <th>상호명</th>\n",
       "      <th>지점명</th>\n",
       "      <th>상권업종대분류코드</th>\n",
       "      <th>상권업종대분류명</th>\n",
       "      <th>상권업종중분류코드</th>\n",
       "      <th>상권업종중분류명</th>\n",
       "      <th>상권업종소분류코드</th>\n",
       "      <th>상권업종소분류명</th>\n",
       "      <th>표준산업분류코드</th>\n",
       "      <th>...</th>\n",
       "      <th>건물관리번호</th>\n",
       "      <th>건물명</th>\n",
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       "      <th>구우편번호</th>\n",
       "      <th>신우편번호</th>\n",
       "      <th>동정보</th>\n",
       "      <th>층정보</th>\n",
       "      <th>호정보</th>\n",
       "      <th>경도</th>\n",
       "      <th>위도</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17174079</td>\n",
       "      <td>평창라마다호텔</td>\n",
       "      <td>NaN</td>\n",
       "      <td>O</td>\n",
       "      <td>숙박</td>\n",
       "      <td>O01</td>\n",
       "      <td>호텔/콘도</td>\n",
       "      <td>O01A01</td>\n",
       "      <td>호텔/콘도</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4276038024102450036000001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>강원도 평창군 대관령면 오목길 107</td>\n",
       "      <td>232954.0</td>\n",
       "      <td>25342.0</td>\n",
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       "      <th>1</th>\n",
       "      <td>17173904</td>\n",
       "      <td>호텔탑스텐스카이라운지</td>\n",
       "      <td>NaN</td>\n",
       "      <td>O</td>\n",
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       "      <td>O01</td>\n",
       "      <td>호텔/콘도</td>\n",
       "      <td>O01A01</td>\n",
       "      <td>호텔/콘도</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4215035029100920001000002</td>\n",
       "      <td>NaN</td>\n",
       "      <td>강원도 강릉시 옥계면 헌화로 455-34</td>\n",
       "      <td>210831.0</td>\n",
       "      <td>25633.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>129.052902</td>\n",
       "      <td>37.654680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>25033300</td>\n",
       "      <td>동그라미중고타이어</td>\n",
       "      <td>NaN</td>\n",
       "      <td>D</td>\n",
       "      <td>소매</td>\n",
       "      <td>D23</td>\n",
       "      <td>자동차/자동차용품</td>\n",
       "      <td>D23A04</td>\n",
       "      <td>타이어판매</td>\n",
       "      <td>G45211</td>\n",
       "      <td>...</td>\n",
       "      <td>4215011100110960006010791</td>\n",
       "      <td>NaN</td>\n",
       "      <td>강원도 강릉시 가작로 270</td>\n",
       "      <td>210110.0</td>\n",
       "      <td>25488.0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>128.904472</td>\n",
       "      <td>37.770252</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>17174549</td>\n",
       "      <td>세인트존스호텔Ohcrab</td>\n",
       "      <td>NaN</td>\n",
       "      <td>O</td>\n",
       "      <td>숙박</td>\n",
       "      <td>O01</td>\n",
       "      <td>호텔/콘도</td>\n",
       "      <td>O01A01</td>\n",
       "      <td>호텔/콘도</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4215011300100010001017124</td>\n",
       "      <td>세인트존스호텔</td>\n",
       "      <td>강원도 강릉시 창해로 307</td>\n",
       "      <td>210120.0</td>\n",
       "      <td>25467.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>37.791299</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17175358</td>\n",
       "      <td>국수나루</td>\n",
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       "      <td>Q01</td>\n",
       "      <td>한식</td>\n",
       "      <td>Q01A01</td>\n",
       "      <td>한식/백반/한정식</td>\n",
       "      <td>I56111</td>\n",
       "      <td>...</td>\n",
       "      <td>4215010900101730002015569</td>\n",
       "      <td>NaN</td>\n",
       "      <td>강원도 강릉시 토성로 193</td>\n",
       "      <td>210934.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>128.896783</td>\n",
       "      <td>37.757642</td>\n",
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       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2233992</th>\n",
       "      <td>17433055</td>\n",
       "      <td>더:예쁨</td>\n",
       "      <td>NaN</td>\n",
       "      <td>F</td>\n",
       "      <td>생활서비스</td>\n",
       "      <td>F01</td>\n",
       "      <td>이/미용/건강</td>\n",
       "      <td>F01A01</td>\n",
       "      <td>여성미용실</td>\n",
       "      <td>S96112</td>\n",
       "      <td>...</td>\n",
       "      <td>4313011800116250000000008</td>\n",
       "      <td>연수세영리첼1단지아파트상가</td>\n",
       "      <td>충청북도 충주시 연수동산로 35</td>\n",
       "      <td>380100.0</td>\n",
       "      <td>27352.0</td>\n",
       "      <td>상가</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104</td>\n",
       "      <td>127.941797</td>\n",
       "      <td>36.985736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2233993</th>\n",
       "      <td>17451070</td>\n",
       "      <td>우리집밥상</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "      <td>음식</td>\n",
       "      <td>Q01</td>\n",
       "      <td>한식</td>\n",
       "      <td>Q01A01</td>\n",
       "      <td>한식/백반/한정식</td>\n",
       "      <td>I56111</td>\n",
       "      <td>...</td>\n",
       "      <td>4377025021103370004010973</td>\n",
       "      <td>NaN</td>\n",
       "      <td>충청북도 음성군 음성읍 시장로 68</td>\n",
       "      <td>369807.0</td>\n",
       "      <td>27702.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>127.693937</td>\n",
       "      <td>36.933781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2233994</th>\n",
       "      <td>17433002</td>\n",
       "      <td>빅스타</td>\n",
       "      <td>서충주점</td>\n",
       "      <td>Q</td>\n",
       "      <td>음식</td>\n",
       "      <td>Q01</td>\n",
       "      <td>한식</td>\n",
       "      <td>Q01A01</td>\n",
       "      <td>한식/백반/한정식</td>\n",
       "      <td>I56111</td>\n",
       "      <td>...</td>\n",
       "      <td>4313033531110450000000001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>충청북도 충주시 대소원면 첨단산업4로 13</td>\n",
       "      <td>380871.0</td>\n",
       "      <td>27466.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>104</td>\n",
       "      <td>127.829923</td>\n",
       "      <td>36.985799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2233995</th>\n",
       "      <td>17389939</td>\n",
       "      <td>무한닭발</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "      <td>음식</td>\n",
       "      <td>Q05</td>\n",
       "      <td>닭/오리요리</td>\n",
       "      <td>Q05A10</td>\n",
       "      <td>닭내장/닭발요리</td>\n",
       "      <td>I56111</td>\n",
       "      <td>...</td>\n",
       "      <td>4311311500104920003016198</td>\n",
       "      <td>NaN</td>\n",
       "      <td>충청북도 청주시 흥덕구 직지대로639번길 75</td>\n",
       "      <td>361817.0</td>\n",
       "      <td>28475.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105</td>\n",
       "      <td>127.465799</td>\n",
       "      <td>36.646244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2233996</th>\n",
       "      <td>17433391</td>\n",
       "      <td>모아모아플레이</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "      <td>음식</td>\n",
       "      <td>Q01</td>\n",
       "      <td>한식</td>\n",
       "      <td>Q01A01</td>\n",
       "      <td>한식/백반/한정식</td>\n",
       "      <td>I56111</td>\n",
       "      <td>...</td>\n",
       "      <td>4311110800100190005048885</td>\n",
       "      <td>NaN</td>\n",
       "      <td>충청북도 청주시 상당구 탑동로1번길 25</td>\n",
       "      <td>360050.0</td>\n",
       "      <td>28716.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>101</td>\n",
       "      <td>127.494822</td>\n",
       "      <td>36.628995</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2233997 rows × 39 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           상가업소번호            상호명   지점명 상권업종대분류코드 상권업종대분류명 상권업종중분류코드  \\\n",
       "0        17174079        평창라마다호텔   NaN         O       숙박       O01   \n",
       "1        17173904    호텔탑스텐스카이라운지   NaN         O       숙박       O01   \n",
       "2        25033300      동그라미중고타이어   NaN         D       소매       D23   \n",
       "3        17174549  세인트존스호텔Ohcrab   NaN         O       숙박       O01   \n",
       "4        17175358           국수나루   NaN         Q       음식       Q01   \n",
       "...           ...            ...   ...       ...      ...       ...   \n",
       "2233992  17433055           더:예쁨   NaN         F    생활서비스       F01   \n",
       "2233993  17451070          우리집밥상   NaN         Q       음식       Q01   \n",
       "2233994  17433002            빅스타  서충주점         Q       음식       Q01   \n",
       "2233995  17389939           무한닭발   NaN         Q       음식       Q05   \n",
       "2233996  17433391        모아모아플레이   NaN         Q       음식       Q01   \n",
       "\n",
       "          상권업종중분류명 상권업종소분류코드   상권업종소분류명 표준산업분류코드  ...  \\\n",
       "0            호텔/콘도    O01A01      호텔/콘도      NaN  ...   \n",
       "1            호텔/콘도    O01A01      호텔/콘도      NaN  ...   \n",
       "2        자동차/자동차용품    D23A04      타이어판매   G45211  ...   \n",
       "3            호텔/콘도    O01A01      호텔/콘도      NaN  ...   \n",
       "4               한식    Q01A01  한식/백반/한정식   I56111  ...   \n",
       "...            ...       ...        ...      ...  ...   \n",
       "2233992    이/미용/건강    F01A01      여성미용실   S96112  ...   \n",
       "2233993         한식    Q01A01  한식/백반/한정식   I56111  ...   \n",
       "2233994         한식    Q01A01  한식/백반/한정식   I56111  ...   \n",
       "2233995     닭/오리요리    Q05A10   닭내장/닭발요리   I56111  ...   \n",
       "2233996         한식    Q01A01  한식/백반/한정식   I56111  ...   \n",
       "\n",
       "                            건물관리번호             건물명                      도로명주소  \\\n",
       "0        4276038024102450036000001             NaN       강원도 평창군 대관령면 오목길 107   \n",
       "1        4215035029100920001000002             NaN     강원도 강릉시 옥계면 헌화로 455-34   \n",
       "2        4215011100110960006010791             NaN            강원도 강릉시 가작로 270   \n",
       "3        4215011300100010001017124         세인트존스호텔            강원도 강릉시 창해로 307   \n",
       "4        4215010900101730002015569             NaN            강원도 강릉시 토성로 193   \n",
       "...                            ...             ...                        ...   \n",
       "2233992  4313011800116250000000008  연수세영리첼1단지아파트상가          충청북도 충주시 연수동산로 35   \n",
       "2233993  4377025021103370004010973             NaN        충청북도 음성군 음성읍 시장로 68   \n",
       "2233994  4313033531110450000000001             NaN    충청북도 충주시 대소원면 첨단산업4로 13   \n",
       "2233995  4311311500104920003016198             NaN  충청북도 청주시 흥덕구 직지대로639번길 75   \n",
       "2233996  4311110800100190005048885             NaN     충청북도 청주시 상당구 탑동로1번길 25   \n",
       "\n",
       "            구우편번호    신우편번호  동정보  층정보  호정보          경도         위도  \n",
       "0        232954.0  25342.0  NaN  NaN  NaN  128.717971  37.660051  \n",
       "1        210831.0  25633.0  NaN  NaN  NaN  129.052902  37.654680  \n",
       "2        210110.0  25488.0    1  NaN  NaN  128.904472  37.770252  \n",
       "3        210120.0  25467.0  NaN  NaN  NaN  128.920908  37.791299  \n",
       "4        210934.0  25531.0  NaN  NaN  NaN  128.896783  37.757642  \n",
       "...           ...      ...  ...  ...  ...         ...        ...  \n",
       "2233992  380100.0  27352.0   상가  NaN  104  127.941797  36.985736  \n",
       "2233993  369807.0  27702.0  NaN  NaN  NaN  127.693937  36.933781  \n",
       "2233994  380871.0  27466.0  NaN  1.0  104  127.829923  36.985799  \n",
       "2233995  361817.0  28475.0  NaN  NaN  105  127.465799  36.646244  \n",
       "2233996  360050.0  28716.0  NaN  1.0  101  127.494822  36.628995  \n",
       "\n",
       "[2233997 rows x 39 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data 폴더에 있는 모든 csv 파일을 읽어오기 위해 glob을 사용합니다.\n",
    "from glob import glob\n",
    "\n",
    "# csv 목록 불러오기\n",
    "file_names = glob(\"../my room/data1/*.csv\")\n",
    "total = pd.DataFrame()\n",
    "\n",
    "# 모든 csv 병합하기\n",
    "for file_name in file_names:\n",
    "    temp = pd.read_csv(file_name,sep=',',encoding='utf-8')\n",
    "    total = pd.concat([total,temp])\n",
    "# reset index로 인덱스를 새로 지정할 수 있다.\n",
    "total.reset_index(inplace=True, drop=True) #기존 index 제거하고 싶을땐 drop=True\n",
    "total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "91d1775a",
   "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>상호명</th>\n",
       "      <th>지점명</th>\n",
       "      <th>상권업종대분류명</th>\n",
       "      <th>상권업종중분류명</th>\n",
       "      <th>시도명</th>\n",
       "      <th>시군구명</th>\n",
       "      <th>행정동명</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>평창라마다호텔</td>\n",
       "      <td>NaN</td>\n",
       "      <td>숙박</td>\n",
       "      <td>호텔/콘도</td>\n",
       "      <td>강원도</td>\n",
       "      <td>평창군</td>\n",
       "      <td>대관령면</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>호텔탑스텐스카이라운지</td>\n",
       "      <td>NaN</td>\n",
       "      <td>숙박</td>\n",
       "      <td>호텔/콘도</td>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>옥계면</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>동그라미중고타이어</td>\n",
       "      <td>NaN</td>\n",
       "      <td>소매</td>\n",
       "      <td>자동차/자동차용품</td>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>포남1동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>세인트존스호텔Ohcrab</td>\n",
       "      <td>NaN</td>\n",
       "      <td>숙박</td>\n",
       "      <td>호텔/콘도</td>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>초당동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>국수나루</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>한식</td>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>옥천동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2233992</th>\n",
       "      <td>더:예쁨</td>\n",
       "      <td>NaN</td>\n",
       "      <td>생활서비스</td>\n",
       "      <td>이/미용/건강</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "      <td>연수동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2233993</th>\n",
       "      <td>우리집밥상</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>한식</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>음성군</td>\n",
       "      <td>음성읍</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2233994</th>\n",
       "      <td>빅스타</td>\n",
       "      <td>서충주점</td>\n",
       "      <td>음식</td>\n",
       "      <td>한식</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "      <td>대소원면</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2233995</th>\n",
       "      <td>무한닭발</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>닭/오리요리</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>청주시 흥덕구</td>\n",
       "      <td>봉명2.송정동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2233996</th>\n",
       "      <td>모아모아플레이</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>한식</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>청주시 상당구</td>\n",
       "      <td>성안동</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2233997 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   상호명   지점명 상권업종대분류명   상권업종중분류명   시도명     시군구명     행정동명\n",
       "0              평창라마다호텔   NaN       숙박      호텔/콘도   강원도      평창군     대관령면\n",
       "1          호텔탑스텐스카이라운지   NaN       숙박      호텔/콘도   강원도      강릉시      옥계면\n",
       "2            동그라미중고타이어   NaN       소매  자동차/자동차용품   강원도      강릉시     포남1동\n",
       "3        세인트존스호텔Ohcrab   NaN       숙박      호텔/콘도   강원도      강릉시      초당동\n",
       "4                 국수나루   NaN       음식         한식   강원도      강릉시      옥천동\n",
       "...                ...   ...      ...        ...   ...      ...      ...\n",
       "2233992           더:예쁨   NaN    생활서비스    이/미용/건강  충청북도      충주시      연수동\n",
       "2233993          우리집밥상   NaN       음식         한식  충청북도      음성군      음성읍\n",
       "2233994            빅스타  서충주점       음식         한식  충청북도      충주시     대소원면\n",
       "2233995           무한닭발   NaN       음식     닭/오리요리  충청북도  청주시 흥덕구  봉명2.송정동\n",
       "2233996        모아모아플레이   NaN       음식         한식  충청북도  청주시 상당구      성안동\n",
       "\n",
       "[2233997 rows x 7 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 분석에 필요한 column을 고릅니다. ## 자유롭게 하셔도 상관없습니다.\n",
    "data=total[['상호명','지점명','상권업종대분류명','상권업종중분류명','시도명','시군구명','행정동명']]\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "859edbdf",
   "metadata": {},
   "source": [
    "## 2. 데이터 구경하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "2b22400e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2233997 entries, 0 to 2233996\n",
      "Data columns (total 7 columns):\n",
      " #   Column    Dtype \n",
      "---  ------    ----- \n",
      " 0   상호명       object\n",
      " 1   지점명       object\n",
      " 2   상권업종대분류명  object\n",
      " 3   상권업종중분류명  object\n",
      " 4   시도명       object\n",
      " 5   시군구명      object\n",
      " 6   행정동명      object\n",
      "dtypes: object(7)\n",
      "memory usage: 119.3+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "a06a8c44",
   "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>상호명</th>\n",
       "      <th>지점명</th>\n",
       "      <th>상권업종대분류명</th>\n",
       "      <th>상권업종중분류명</th>\n",
       "      <th>시도명</th>\n",
       "      <th>시군구명</th>\n",
       "      <th>행정동명</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2233994</td>\n",
       "      <td>327569</td>\n",
       "      <td>2233997</td>\n",
       "      <td>2233997</td>\n",
       "      <td>2233997</td>\n",
       "      <td>2233997</td>\n",
       "      <td>2233997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>1273411</td>\n",
       "      <td>111919</td>\n",
       "      <td>8</td>\n",
       "      <td>95</td>\n",
       "      <td>17</td>\n",
       "      <td>234</td>\n",
       "      <td>3221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>CU</td>\n",
       "      <td>본점</td>\n",
       "      <td>음식</td>\n",
       "      <td>한식</td>\n",
       "      <td>경기도</td>\n",
       "      <td>서구</td>\n",
       "      <td>중앙동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>11208</td>\n",
       "      <td>2371</td>\n",
       "      <td>845782</td>\n",
       "      <td>324746</td>\n",
       "      <td>508845</td>\n",
       "      <td>66428</td>\n",
       "      <td>40277</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            상호명     지점명 상권업종대분류명 상권업종중분류명      시도명     시군구명     행정동명\n",
       "count   2233994  327569  2233997  2233997  2233997  2233997  2233997\n",
       "unique  1273411  111919        8       95       17      234     3221\n",
       "top          CU      본점       음식       한식      경기도       서구      중앙동\n",
       "freq      11208    2371   845782   324746   508845    66428    40277"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "4ad893f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'PC/오락/당구/볼링등',\n",
       " '가구소매',\n",
       " '가방/신발/액세서리',\n",
       " '가전제품소매',\n",
       " '가정/주방/인테리어',\n",
       " '개인/가정용품수리',\n",
       " '개인서비스',\n",
       " '건강/미용식품',\n",
       " '경마/경륜/성인오락',\n",
       " '광고/인쇄',\n",
       " '기타교육기관',\n",
       " '기타서비스업',\n",
       " '기타음식업',\n",
       " '기타판매업',\n",
       " '놀이/여가/취미',\n",
       " '닭/오리요리',\n",
       " '대중목욕탕/휴게',\n",
       " '대행업',\n",
       " '도서관/독서실',\n",
       " '모텔/여관/여인숙',\n",
       " '무도/유흥/가무',\n",
       " '물품기기대여',\n",
       " '민박/하숙',\n",
       " '법무세무회계',\n",
       " '별식/퓨전요리',\n",
       " '부동산관련서비스',\n",
       " '부동산임대',\n",
       " '부동산중개',\n",
       " '부페',\n",
       " '분식',\n",
       " '분양',\n",
       " '사무/문구/컴퓨터',\n",
       " '사진',\n",
       " '사진/광학/정밀기기소매',\n",
       " '선물/팬시/기념품',\n",
       " '세탁/가사서비스',\n",
       " '스포츠/운동',\n",
       " '시계/귀금속소매',\n",
       " '실내운동시설',\n",
       " '실외운동시설',\n",
       " '애견/애완/동물',\n",
       " '양식',\n",
       " '연구소',\n",
       " '연극/영화/극장',\n",
       " '예술품/골동품/수석/분재',\n",
       " '예식/의례/관혼상제',\n",
       " '요가/단전/마사지',\n",
       " '운동/경기용품소매',\n",
       " '운송/배달/택배',\n",
       " '운영관리시설',\n",
       " '유스호스텔',\n",
       " '유아교육',\n",
       " '유아용품',\n",
       " '유흥주점',\n",
       " '음/식료품소매',\n",
       " '음식배달서비스',\n",
       " '의복의류',\n",
       " '의약/의료품소매',\n",
       " '이/미용/건강',\n",
       " '인력/고용/용역알선',\n",
       " '일식/수산물',\n",
       " '자동차/이륜차',\n",
       " '자동차/자동차용품',\n",
       " '장례/묘지',\n",
       " '전시/관람',\n",
       " '제과제빵떡케익',\n",
       " '종교용품판매',\n",
       " '종합소매점',\n",
       " '주유소/충전소',\n",
       " '주택수리',\n",
       " '중고품소매/교환',\n",
       " '중식',\n",
       " '책/서적/도서',\n",
       " '철물/난방/건설자재소매',\n",
       " '취미/오락관련소매',\n",
       " '캠프/별장/펜션',\n",
       " '커피점/카페',\n",
       " '특수교육기관',\n",
       " '패스트푸드',\n",
       " '페인트/유리제품소매',\n",
       " '평가/개발/관리',\n",
       " '학교',\n",
       " '학문교육기타',\n",
       " '학원-보습교습입시',\n",
       " '학원-어학',\n",
       " '학원-예능취미체육',\n",
       " '학원-음악미술무용',\n",
       " '학원-자격/국가고시',\n",
       " '학원-창업취업취미',\n",
       " '학원-컴퓨터',\n",
       " '학원기타',\n",
       " '한식',\n",
       " '행사/이벤트',\n",
       " '호텔/콘도',\n",
       " '화장품소매'}"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set(data[\"상권업종중분류명\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "e2954378",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "전국 커피 전문점 점포 수 :  106710\n"
     ]
    },
    {
     "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>상호명</th>\n",
       "      <th>지점명</th>\n",
       "      <th>상권업종대분류명</th>\n",
       "      <th>상권업종중분류명</th>\n",
       "      <th>시도명</th>\n",
       "      <th>시군구명</th>\n",
       "      <th>행정동명</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>키즈까페아이사랑</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>성덕동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>카페마실</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>원주시</td>\n",
       "      <td>단계동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>힐링</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>원주시</td>\n",
       "      <td>단구동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>드롭탑</td>\n",
       "      <td>속초엑스포점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "      <td>조양동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>상유재카페</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>정선군</td>\n",
       "      <td>정선읍</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         상호명     지점명 상권업종대분류명 상권업종중분류명  시도명 시군구명 행정동명\n",
       "16  키즈까페아이사랑     NaN       음식   커피점/카페  강원도  강릉시  성덕동\n",
       "43      카페마실     NaN       음식   커피점/카페  강원도  원주시  단계동\n",
       "51        힐링     NaN       음식   커피점/카페  강원도  원주시  단구동\n",
       "67       드롭탑  속초엑스포점       음식   커피점/카페  강원도  속초시  조양동\n",
       "89     상유재카페     NaN       음식   커피점/카페  강원도  정선군  정선읍"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 카페만 뽑아냅니다.\n",
    "df_coffee = data[data[\"상권업종중분류명\"]=='커피점/카페']\n",
    "print(\"전국 커피 전문점 점포 수 : \", len(df_coffee))\n",
    "df_coffee.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "d75bd118",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'강원도',\n",
       " '경기도',\n",
       " '경상남도',\n",
       " '경상북도',\n",
       " '광주광역시',\n",
       " '대구광역시',\n",
       " '대전광역시',\n",
       " '부산광역시',\n",
       " '서울특별시',\n",
       " '세종특별자치시',\n",
       " '울산광역시',\n",
       " '인천광역시',\n",
       " '전라남도',\n",
       " '전라북도',\n",
       " '제주특별자치도',\n",
       " '충청남도',\n",
       " '충청북도'}"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set(data['시도명'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "8b3f338b",
   "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>상호명</th>\n",
       "      <th>지점명</th>\n",
       "      <th>상권업종대분류명</th>\n",
       "      <th>상권업종중분류명</th>\n",
       "      <th>시도명</th>\n",
       "      <th>시군구명</th>\n",
       "      <th>행정동명</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>커피빈</td>\n",
       "      <td>코리아대학로대명거리점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>서울특별시</td>\n",
       "      <td>종로구</td>\n",
       "      <td>혜화동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>요거프레소</td>\n",
       "      <td>쌍문점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>서울특별시</td>\n",
       "      <td>도봉구</td>\n",
       "      <td>쌍문2동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>메머드커피</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>서울특별시</td>\n",
       "      <td>마포구</td>\n",
       "      <td>서교동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>버블베어</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>서울특별시</td>\n",
       "      <td>강서구</td>\n",
       "      <td>방화3동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>우성커피숍</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>서울특별시</td>\n",
       "      <td>양천구</td>\n",
       "      <td>신월4동</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     상호명          지점명 상권업종대분류명 상권업종중분류명    시도명 시군구명  행정동명\n",
       "0    커피빈  코리아대학로대명거리점       음식   커피점/카페  서울특별시  종로구   혜화동\n",
       "1  요거프레소          쌍문점       음식   커피점/카페  서울특별시  도봉구  쌍문2동\n",
       "2  메머드커피          NaN       음식   커피점/카페  서울특별시  마포구   서교동\n",
       "3   버블베어          NaN       음식   커피점/카페  서울특별시  강서구  방화3동\n",
       "4  우성커피숍          NaN       음식   커피점/카페  서울특별시  양천구  신월4동"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 시도별로 구분하는 데이터 만들기\n",
    "df_coffee_seoul = df_coffee[df_coffee['시도명']=='서울특별시']\n",
    "df_coffee_seoul.index = range(len(df_coffee_seoul)) # index 재설정\n",
    "# df_coffee_seoul.reset_index(inplace=True, drop=True)\n",
    "df_coffee_seoul.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "abcfb9e3",
   "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>상호명</th>\n",
       "      <th>지점명</th>\n",
       "      <th>상권업종대분류명</th>\n",
       "      <th>상권업종중분류명</th>\n",
       "      <th>시도명</th>\n",
       "      <th>시군구명</th>\n",
       "      <th>행정동명</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>브라운</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>대구광역시</td>\n",
       "      <td>수성구</td>\n",
       "      <td>고산2동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>커피명가</td>\n",
       "      <td>2호점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>대구광역시</td>\n",
       "      <td>중구</td>\n",
       "      <td>삼덕동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>대림다방</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>대구광역시</td>\n",
       "      <td>수성구</td>\n",
       "      <td>수성2.3가동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>카페머그</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>대구광역시</td>\n",
       "      <td>중구</td>\n",
       "      <td>성내2동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>샌디버블</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>대구광역시</td>\n",
       "      <td>남구</td>\n",
       "      <td>대명2동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5108</th>\n",
       "      <td>카페</td>\n",
       "      <td>이루다스터디</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>대구광역시</td>\n",
       "      <td>달서구</td>\n",
       "      <td>월성1동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5109</th>\n",
       "      <td>커피지상주의</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>대구광역시</td>\n",
       "      <td>달서구</td>\n",
       "      <td>용산1동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5110</th>\n",
       "      <td>그린바스켓</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>대구광역시</td>\n",
       "      <td>수성구</td>\n",
       "      <td>만촌3동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5111</th>\n",
       "      <td>티앤오T.N.O</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>대구광역시</td>\n",
       "      <td>북구</td>\n",
       "      <td>침산2동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5112</th>\n",
       "      <td>커피가득</td>\n",
       "      <td>NaN</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>대구광역시</td>\n",
       "      <td>서구</td>\n",
       "      <td>비산2.3동</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5113 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           상호명     지점명 상권업종대분류명 상권업종중분류명    시도명 시군구명     행정동명\n",
       "0          브라운     NaN       음식   커피점/카페  대구광역시  수성구     고산2동\n",
       "1         커피명가     2호점       음식   커피점/카페  대구광역시   중구      삼덕동\n",
       "2         대림다방     NaN       음식   커피점/카페  대구광역시  수성구  수성2.3가동\n",
       "3         카페머그     NaN       음식   커피점/카페  대구광역시   중구     성내2동\n",
       "4         샌디버블     NaN       음식   커피점/카페  대구광역시   남구     대명2동\n",
       "...        ...     ...      ...      ...    ...  ...      ...\n",
       "5108        카페  이루다스터디       음식   커피점/카페  대구광역시  달서구     월성1동\n",
       "5109    커피지상주의     NaN       음식   커피점/카페  대구광역시  달서구     용산1동\n",
       "5110     그린바스켓     NaN       음식   커피점/카페  대구광역시  수성구     만촌3동\n",
       "5111  티앤오T.N.O     NaN       음식   커피점/카페  대구광역시   북구     침산2동\n",
       "5112      커피가득     NaN       음식   커피점/카페  대구광역시   서구   비산2.3동\n",
       "\n",
       "[5113 rows x 7 columns]"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# for문으로 전국 시도명별 데이터 만드는 법\n",
    "a=list(set(data['시도명']))\n",
    "import sys\n",
    "mod = sys.modules[__name__]\n",
    "for i in range(len(a)):\n",
    "    setattr(mod, 'df_coffee_{}' .format(a[i]), df_coffee[df_coffee['시도명']==a[i]])\n",
    "# 이건 for문을 돌릴 방법을 못 찾겠네요...\n",
    "df_coffee_강원도.index = range(len(df_coffee_강원도))\n",
    "df_coffee_경기도.index = range(len(df_coffee_경기도))\n",
    "df_coffee_경상남도.index = range(len(df_coffee_경상남도))\n",
    "df_coffee_경상북도.index = range(len(df_coffee_경상북도))\n",
    "df_coffee_광주광역시.index = range(len(df_coffee_광주광역시))\n",
    "df_coffee_대구광역시.index = range(len(df_coffee_대구광역시))\n",
    "df_coffee_대전광역시.index = range(len(df_coffee_대전광역시))\n",
    "df_coffee_부산광역시.index = range(len(df_coffee_부산광역시))\n",
    "df_coffee_서울특별시.index = range(len(df_coffee_서울특별시))\n",
    "df_coffee_세종특별자치시.index = range(len(df_coffee_세종특별자치시))\n",
    "df_coffee_울산광역시.index = range(len(df_coffee_울산광역시))\n",
    "df_coffee_인천광역시.index = range(len(df_coffee_인천광역시))\n",
    "df_coffee_전라남도.index = range(len(df_coffee_전라남도))\n",
    "df_coffee_전라북도.index = range(len(df_coffee_전라북도))\n",
    "df_coffee_제주특별자치도.index = range(len(df_coffee_제주특별자치도))\n",
    "df_coffee_충청남도.index = range(len(df_coffee_충청남도))\n",
    "df_coffee_충청북도.index = range(len(df_coffee_충청북도))\n",
    "\n",
    "df_coffee_대구광역시"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "042b32db",
   "metadata": {},
   "source": [
    "#### 전국 스타벅스"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "13dc9304",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "전국 스타벅스 점포 수 : 1563\n"
     ]
    },
    {
     "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>상호명</th>\n",
       "      <th>지점명</th>\n",
       "      <th>상권업종대분류명</th>\n",
       "      <th>상권업종중분류명</th>\n",
       "      <th>시도명</th>\n",
       "      <th>시군구명</th>\n",
       "      <th>행정동명</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>스타벅스강릉안목항점</td>\n",
       "      <td>강릉안목항점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>송정동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>스타벅스</td>\n",
       "      <td>대명델피노리조트점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>고성군</td>\n",
       "      <td>토성면</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>스타벅스춘천후평DT점</td>\n",
       "      <td>춘천후평DT점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>춘천시</td>\n",
       "      <td>후평3동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>스타벅스</td>\n",
       "      <td>춘천명동점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>춘천시</td>\n",
       "      <td>약사명동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>스타벅스설악워터피아점</td>\n",
       "      <td>설악워터피아점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "      <td>영랑동</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           상호명        지점명 상권업종대분류명 상권업종중분류명  시도명 시군구명  행정동명\n",
       "0   스타벅스강릉안목항점     강릉안목항점       음식   커피점/카페  강원도  강릉시   송정동\n",
       "1         스타벅스  대명델피노리조트점       음식   커피점/카페  강원도  고성군   토성면\n",
       "2  스타벅스춘천후평DT점    춘천후평DT점       음식   커피점/카페  강원도  춘천시  후평3동\n",
       "3         스타벅스      춘천명동점       음식   커피점/카페  강원도  춘천시  약사명동\n",
       "4  스타벅스설악워터피아점    설악워터피아점       음식   커피점/카페  강원도  속초시   영랑동"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_스타벅스 = df_coffee[df_coffee[\"상호명\"].str.contains(\"스타벅스\")]\n",
    "df_스타벅스.index = range(len(df_스타벅스))\n",
    "print('전국 스타벅스 점포 수 :', len(df_스타벅스))\n",
    "df_스타벅스.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2e062bc0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 한글깨짐 해결을 위해 코드\n",
    "import matplotlib.font_manager as fm\n",
    "path = 'C:\\\\Users\\\\설위준\\\\Desktop\\\\my room\\\\NanumBarunGothic.ttf'\n",
    "fontprob=fm.FontProperties(fname=path,size=18)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "6f8eb074",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.axis.XTick at 0x19feba5da30>,\n",
       "  <matplotlib.axis.XTick at 0x19feba5d8e0>,\n",
       "  <matplotlib.axis.XTick at 0x19febd6a850>,\n",
       "  <matplotlib.axis.XTick at 0x19febf0cfd0>,\n",
       "  <matplotlib.axis.XTick at 0x19febf1fa60>,\n",
       "  <matplotlib.axis.XTick at 0x19febe90850>,\n",
       "  <matplotlib.axis.XTick at 0x19febfae910>,\n",
       "  <matplotlib.axis.XTick at 0x19febe74340>,\n",
       "  <matplotlib.axis.XTick at 0x19febe90940>,\n",
       "  <matplotlib.axis.XTick at 0x19febd582e0>,\n",
       "  <matplotlib.axis.XTick at 0x19febe74640>,\n",
       "  <matplotlib.axis.XTick at 0x19febe74a90>,\n",
       "  <matplotlib.axis.XTick at 0x19febd44460>,\n",
       "  <matplotlib.axis.XTick at 0x19febe56610>,\n",
       "  <matplotlib.axis.XTick at 0x19febe56340>,\n",
       "  <matplotlib.axis.XTick at 0x19febe56c70>,\n",
       "  <matplotlib.axis.XTick at 0x19febe50640>],\n",
       " [Text(0, 0, '전라북도'),\n",
       "  Text(1, 0, '부산광역시'),\n",
       "  Text(2, 0, '강원도'),\n",
       "  Text(3, 0, '경기도'),\n",
       "  Text(4, 0, '인천광역시'),\n",
       "  Text(5, 0, '충청북도'),\n",
       "  Text(6, 0, '경상북도'),\n",
       "  Text(7, 0, '전라남도'),\n",
       "  Text(8, 0, '제주특별자치도'),\n",
       "  Text(9, 0, '경상남도'),\n",
       "  Text(10, 0, '울산광역시'),\n",
       "  Text(11, 0, '세종특별자치시'),\n",
       "  Text(12, 0, '광주광역시'),\n",
       "  Text(13, 0, '서울특별시'),\n",
       "  Text(14, 0, '대구광역시'),\n",
       "  Text(15, 0, '대전광역시'),\n",
       "  Text(16, 0, '충청남도')])"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 시도별 스타벅스 분포\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "a = list(set(data['시도명']))\n",
    "v1 = [len(df_스타벅스[df_스타벅스[\"시도명\"]==a[i]]) for i in range(len(a))]\n",
    "index = np.arange(len(a))\n",
    "plt.bar(a, v1)\n",
    "plt.xticks(index, a, fontsize=13,fontproperties=fontprob, rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "d3890258",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 시도별 스타벅스 분포\n",
    "plt.barh(index, v1)\n",
    "plt.yticks(index, a, fontsize=13,fontproperties=fontprob, rotation=0)\n",
    "plt.show()\n",
    "#plt.savefig('savefig_200dpi.png', dpi=200)\n",
    "# 대부분의 스타벅스가 서울과 경기도 지역에 분포하는 것을 확인할 수 있다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "74fa2916",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "스타벅스의 전국 대비 전라북도에서의 비율 : 1.663%\n",
      "스타벅스의 전국 대비 부산광역시에서의 비율 : 7.550%\n",
      "스타벅스의 전국 대비 강원도에서의 비율 : 2.687%\n",
      "스타벅스의 전국 대비 경기도에서의 비율 : 22.905%\n",
      "스타벅스의 전국 대비 인천광역시에서의 비율 : 4.351%\n",
      "스타벅스의 전국 대비 충청북도에서의 비율 : 1.983%\n",
      "스타벅스의 전국 대비 경상북도에서의 비율 : 3.711%\n",
      "스타벅스의 전국 대비 전라남도에서의 비율 : 1.536%\n",
      "스타벅스의 전국 대비 제주특별자치도에서의 비율 : 1.727%\n",
      "스타벅스의 전국 대비 경상남도에서의 비율 : 3.967%\n",
      "스타벅스의 전국 대비 울산광역시에서의 비율 : 1.855%\n",
      "스타벅스의 전국 대비 세종특별자치시에서의 비율 : 0.576%\n",
      "스타벅스의 전국 대비 광주광역시에서의 비율 : 3.839%\n",
      "스타벅스의 전국 대비 서울특별시에서의 비율 : 31.158%\n",
      "스타벅스의 전국 대비 대구광역시에서의 비율 : 4.543%\n",
      "스타벅스의 전국 대비 대전광역시에서의 비율 : 3.263%\n",
      "스타벅스의 전국 대비 충청남도에서의 비율 : 2.687%\n"
     ]
    }
   ],
   "source": [
    "# 지역별 스타벅스 비율 \n",
    "sum_star = sum(v1)\n",
    "for i in range(len(a)):\n",
    "    print('스타벅스의 전국 대비 {}에서의 비율 : {:.3f}%' .format(a[i],v1[i]/sum_star*100))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8da5121d",
   "metadata": {},
   "source": [
    "#### 전국 투썸"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "bcf1f867",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "전국 투썸 점포 수 : 1108\n"
     ]
    },
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>상호명</th>\n",
       "      <th>지점명</th>\n",
       "      <th>상권업종대분류명</th>\n",
       "      <th>상권업종중분류명</th>\n",
       "      <th>시도명</th>\n",
       "      <th>시군구명</th>\n",
       "      <th>행정동명</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>투썸플레이스</td>\n",
       "      <td>춘천명동점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>춘천시</td>\n",
       "      <td>조운동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>투썸플레이스</td>\n",
       "      <td>강릉포남점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>포남1동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>투썸플레이스</td>\n",
       "      <td>춘천퇴계점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>춘천시</td>\n",
       "      <td>퇴계동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>투썸플레이스</td>\n",
       "      <td>소양강댐점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>춘천시</td>\n",
       "      <td>신북읍</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>투썸플레이스</td>\n",
       "      <td>용평리조트점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>평창군</td>\n",
       "      <td>대관령면</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      상호명     지점명 상권업종대분류명 상권업종중분류명  시도명 시군구명  행정동명\n",
       "0  투썸플레이스   춘천명동점       음식   커피점/카페  강원도  춘천시   조운동\n",
       "1  투썸플레이스   강릉포남점       음식   커피점/카페  강원도  강릉시  포남1동\n",
       "2  투썸플레이스   춘천퇴계점       음식   커피점/카페  강원도  춘천시   퇴계동\n",
       "3  투썸플레이스   소양강댐점       음식   커피점/카페  강원도  춘천시   신북읍\n",
       "4  투썸플레이스  용평리조트점       음식   커피점/카페  강원도  평창군  대관령면"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_투썸 = df_coffee[df_coffee[\"상호명\"].str.contains(\"투썸\")]\n",
    "df_투썸.index = range(len(df_투썸))\n",
    "print('전국 투썸 점포 수 :', len(df_투썸))\n",
    "df_투썸.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "e9976984",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['전라북도',\n",
       " '부산광역시',\n",
       " '강원도',\n",
       " '경기도',\n",
       " '인천광역시',\n",
       " '충청북도',\n",
       " '경상북도',\n",
       " '전라남도',\n",
       " '제주특별자치도',\n",
       " '경상남도',\n",
       " '울산광역시',\n",
       " '세종특별자치시',\n",
       " '광주광역시',\n",
       " '서울특별시',\n",
       " '대구광역시',\n",
       " '대전광역시',\n",
       " '충청남도']"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = list(set(data['시도명']))\n",
    "a # 이것을 계속 활용한다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "366d12f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.axis.XTick at 0x19febe29640>,\n",
       "  <matplotlib.axis.XTick at 0x19febe295e0>,\n",
       "  <matplotlib.axis.XTick at 0x19febe63bb0>,\n",
       "  <matplotlib.axis.XTick at 0x19febcb8100>,\n",
       "  <matplotlib.axis.XTick at 0x19febcb8cd0>,\n",
       "  <matplotlib.axis.XTick at 0x19febcb8b50>,\n",
       "  <matplotlib.axis.XTick at 0x19febce60a0>,\n",
       "  <matplotlib.axis.XTick at 0x19febcd9190>,\n",
       "  <matplotlib.axis.XTick at 0x19febcd9d60>,\n",
       "  <matplotlib.axis.XTick at 0x19febcd9f10>,\n",
       "  <matplotlib.axis.XTick at 0x19febcb89d0>,\n",
       "  <matplotlib.axis.XTick at 0x19febe38730>,\n",
       "  <matplotlib.axis.XTick at 0x19febcd92e0>,\n",
       "  <matplotlib.axis.XTick at 0x19febc63af0>,\n",
       "  <matplotlib.axis.XTick at 0x19febc63850>,\n",
       "  <matplotlib.axis.XTick at 0x19febc63490>,\n",
       "  <matplotlib.axis.XTick at 0x19febccf700>],\n",
       " [Text(0, 0, '전라북도'),\n",
       "  Text(1, 0, '부산광역시'),\n",
       "  Text(2, 0, '강원도'),\n",
       "  Text(3, 0, '경기도'),\n",
       "  Text(4, 0, '인천광역시'),\n",
       "  Text(5, 0, '충청북도'),\n",
       "  Text(6, 0, '경상북도'),\n",
       "  Text(7, 0, '전라남도'),\n",
       "  Text(8, 0, '제주특별자치도'),\n",
       "  Text(9, 0, '경상남도'),\n",
       "  Text(10, 0, '울산광역시'),\n",
       "  Text(11, 0, '세종특별자치시'),\n",
       "  Text(12, 0, '광주광역시'),\n",
       "  Text(13, 0, '서울특별시'),\n",
       "  Text(14, 0, '대구광역시'),\n",
       "  Text(15, 0, '대전광역시'),\n",
       "  Text(16, 0, '충청남도')])"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "v2 = [len(df_투썸[df_투썸[\"시도명\"]==a[i]]) for i in range(len(a))]\n",
    "index = np.arange(len(a))\n",
    "plt.bar(a, v2)\n",
    "plt.xticks(index, a, fontsize=13,fontproperties=fontprob, rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "77cc5665",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 시도별 투썸 분포\n",
    "plt.barh(index, v2)\n",
    "plt.yticks(index, a, fontsize=13,fontproperties=fontprob, rotation=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "d16a5b61",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "투썸의 전국 대비 전라북도에서의 비율 : 3.159%\n",
      "투썸의 전국 대비 부산광역시에서의 비율 : 5.505%\n",
      "투썸의 전국 대비 강원도에서의 비율 : 3.159%\n",
      "투썸의 전국 대비 경기도에서의 비율 : 21.209%\n",
      "투썸의 전국 대비 인천광역시에서의 비율 : 5.686%\n",
      "투썸의 전국 대비 충청북도에서의 비율 : 3.520%\n",
      "투썸의 전국 대비 경상북도에서의 비율 : 4.422%\n",
      "투썸의 전국 대비 전라남도에서의 비율 : 2.347%\n",
      "투썸의 전국 대비 제주특별자치도에서의 비율 : 1.986%\n",
      "투썸의 전국 대비 경상남도에서의 비율 : 4.242%\n",
      "투썸의 전국 대비 울산광역시에서의 비율 : 2.617%\n",
      "투썸의 전국 대비 세종특별자치시에서의 비율 : 0.722%\n",
      "투썸의 전국 대비 광주광역시에서의 비율 : 2.527%\n",
      "투썸의 전국 대비 서울특별시에서의 비율 : 24.639%\n",
      "투썸의 전국 대비 대구광역시에서의 비율 : 6.137%\n",
      "투썸의 전국 대비 대전광역시에서의 비율 : 3.881%\n",
      "투썸의 전국 대비 충청남도에서의 비율 : 4.242%\n"
     ]
    }
   ],
   "source": [
    "sum_star = sum(v2)\n",
    "for i in range(len(a)):\n",
    "    print('투썸의 전국 대비 {}에서의 비율 : {:.3f}%' .format(a[i],v2[i]/sum_star*100))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "68f5f878",
   "metadata": {},
   "source": [
    "#### 전국 이디야"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "97549cd2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "전국 이디야 점포 수 : 2158\n"
     ]
    },
    {
     "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>상호명</th>\n",
       "      <th>지점명</th>\n",
       "      <th>상권업종대분류명</th>\n",
       "      <th>상권업종중분류명</th>\n",
       "      <th>시도명</th>\n",
       "      <th>시군구명</th>\n",
       "      <th>행정동명</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>이디야커피</td>\n",
       "      <td>원주반곡동점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>원주시</td>\n",
       "      <td>반곡관설동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>이디야커피</td>\n",
       "      <td>춘천제일점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>춘천시</td>\n",
       "      <td>강남동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>이디야커피</td>\n",
       "      <td>흥업점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>원주시</td>\n",
       "      <td>흥업면</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>이디야커피</td>\n",
       "      <td>주문진점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>주문진읍</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>이디야커피</td>\n",
       "      <td>강릉입암남부점</td>\n",
       "      <td>음식</td>\n",
       "      <td>커피점/카페</td>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>성덕동</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     상호명      지점명 상권업종대분류명 상권업종중분류명  시도명 시군구명   행정동명\n",
       "0  이디야커피   원주반곡동점       음식   커피점/카페  강원도  원주시  반곡관설동\n",
       "1  이디야커피    춘천제일점       음식   커피점/카페  강원도  춘천시    강남동\n",
       "2  이디야커피      흥업점       음식   커피점/카페  강원도  원주시    흥업면\n",
       "3  이디야커피     주문진점       음식   커피점/카페  강원도  강릉시   주문진읍\n",
       "4  이디야커피  강릉입암남부점       음식   커피점/카페  강원도  강릉시    성덕동"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_이디야 = df_coffee[df_coffee[\"상호명\"].str.contains(\"이디야\")]\n",
    "df_이디야.index = range(len(df_이디야))\n",
    "print('전국 이디야 점포 수 :', len(df_이디야))\n",
    "df_이디야.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "e599adc6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.axis.XTick at 0x19feb95cf10>,\n",
       "  <matplotlib.axis.XTick at 0x19feb95ceb0>,\n",
       "  <matplotlib.axis.XTick at 0x19feba4b2b0>,\n",
       "  <matplotlib.axis.XTick at 0x19feab7efd0>,\n",
       "  <matplotlib.axis.XTick at 0x19feaba5760>,\n",
       "  <matplotlib.axis.XTick at 0x19feaba5250>,\n",
       "  <matplotlib.axis.XTick at 0x19feaba57f0>,\n",
       "  <matplotlib.axis.XTick at 0x19febdf0490>,\n",
       "  <matplotlib.axis.XTick at 0x19febdf0f70>,\n",
       "  <matplotlib.axis.XTick at 0x19febdf0e20>,\n",
       "  <matplotlib.axis.XTick at 0x19feaba59d0>,\n",
       "  <matplotlib.axis.XTick at 0x19feab995e0>,\n",
       "  <matplotlib.axis.XTick at 0x19febdf0c40>,\n",
       "  <matplotlib.axis.XTick at 0x19feb948a00>,\n",
       "  <matplotlib.axis.XTick at 0x19feb9483d0>,\n",
       "  <matplotlib.axis.XTick at 0x19feb948af0>,\n",
       "  <matplotlib.axis.XTick at 0x19feb879a60>],\n",
       " [Text(0, 0, '전라북도'),\n",
       "  Text(1, 0, '부산광역시'),\n",
       "  Text(2, 0, '강원도'),\n",
       "  Text(3, 0, '경기도'),\n",
       "  Text(4, 0, '인천광역시'),\n",
       "  Text(5, 0, '충청북도'),\n",
       "  Text(6, 0, '경상북도'),\n",
       "  Text(7, 0, '전라남도'),\n",
       "  Text(8, 0, '제주특별자치도'),\n",
       "  Text(9, 0, '경상남도'),\n",
       "  Text(10, 0, '울산광역시'),\n",
       "  Text(11, 0, '세종특별자치시'),\n",
       "  Text(12, 0, '광주광역시'),\n",
       "  Text(13, 0, '서울특별시'),\n",
       "  Text(14, 0, '대구광역시'),\n",
       "  Text(15, 0, '대전광역시'),\n",
       "  Text(16, 0, '충청남도')])"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "v3 = [len(df_이디야[df_이디야[\"시도명\"]==a[i]]) for i in range(len(a))]\n",
    "index = np.arange(len(a))\n",
    "plt.bar(a, v3)\n",
    "plt.xticks(index, a, fontsize=13,fontproperties=fontprob, rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "id": "845f1d64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 시도별 이디야 분포\n",
    "plt.barh(index, v3)\n",
    "plt.yticks(index, a, fontsize=13,fontproperties=fontprob, rotation=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "id": "202c89de",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "이디야의 전국 대비 전라북도에서의 비율 : 3.151%\n",
      "이디야의 전국 대비 부산광역시에서의 비율 : 6.024%\n",
      "이디야의 전국 대비 강원도에서의 비율 : 3.939%\n",
      "이디야의 전국 대비 경기도에서의 비율 : 27.108%\n",
      "이디야의 전국 대비 인천광역시에서의 비율 : 6.441%\n",
      "이디야의 전국 대비 충청북도에서의 비율 : 3.105%\n",
      "이디야의 전국 대비 경상북도에서의 비율 : 4.727%\n",
      "이디야의 전국 대비 전라남도에서의 비율 : 3.661%\n",
      "이디야의 전국 대비 제주특별자치도에서의 비율 : 0.649%\n",
      "이디야의 전국 대비 경상남도에서의 비율 : 5.746%\n",
      "이디야의 전국 대비 울산광역시에서의 비율 : 3.475%\n",
      "이디야의 전국 대비 세종특별자치시에서의 비율 : 0.834%\n",
      "이디야의 전국 대비 광주광역시에서의 비율 : 2.688%\n",
      "이디야의 전국 대비 서울특별시에서의 비율 : 20.992%\n",
      "이디야의 전국 대비 대구광역시에서의 비율 : 2.873%\n",
      "이디야의 전국 대비 대전광역시에서의 비율 : 1.483%\n",
      "이디야의 전국 대비 충청남도에서의 비율 : 3.105%\n"
     ]
    }
   ],
   "source": [
    "sum_star = sum(v3)\n",
    "for i in range(len(a)):\n",
    "    print('이디야의 전국 대비 {}에서의 비율 : {:.3f}%' .format(a[i],v3[i]/sum_star*100))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15b54208",
   "metadata": {},
   "source": [
    "## 3대 커피브랜드의 점포 수 비교"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "id": "c1c791c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.axis.XTick at 0x19feb9c1d30>,\n",
       "  <matplotlib.axis.XTick at 0x19fec5df400>,\n",
       "  <matplotlib.axis.XTick at 0x19fec5d2400>],\n",
       " [Text(0, 0, '스타벅스'), Text(1, 0, '투썸'), Text(2, 0, '이디야')])"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "star = sum(v1)\n",
    "two = sum(v2)\n",
    "edia = sum(v3)\n",
    "X=[\"스타벅스\",\"투썸\",\"이디야\"]\n",
    "Y=[star, two, edia]\n",
    "index = [0,1,2]\n",
    "plt.bar(X, Y)\n",
    "plt.xticks(index, X, fontsize=13,fontproperties=fontprob, rotation=90)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}