9장_행정구역데이터분석.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 9장. 지리 정보 분석 (2) 행정구역별 데이터 분석 + 블록맵"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. 데이터 준비 및 탐색"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>병원 명</th>\n",
       "      <th>설립형태</th>\n",
       "      <th>근거 법령</th>\n",
       "      <th>관계 행정기관</th>\n",
       "      <th>관계 공공단체</th>\n",
       "      <th>심평원 요양기관번호</th>\n",
       "      <th>종별구분</th>\n",
       "      <th>병상수</th>\n",
       "      <th>소재지 우편번호</th>\n",
       "      <th>주소</th>\n",
       "      <th>홈페이지</th>\n",
       "      <th>대표전화</th>\n",
       "      <th>FAX</th>\n",
       "      <th>비고</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>연번</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>강원도 재활병원</td>\n",
       "      <td>시도립</td>\n",
       "      <td>강원도재활병원설치및운영에관한조례</td>\n",
       "      <td>강원도</td>\n",
       "      <td>해당없음</td>\n",
       "      <td>32200641</td>\n",
       "      <td>병원</td>\n",
       "      <td>165</td>\n",
       "      <td>24227</td>\n",
       "      <td>강원도 춘천시 충열로 142번길 24-16</td>\n",
       "      <td>www.grh.or.kr</td>\n",
       "      <td>033-248-7700</td>\n",
       "      <td>033-248-7723</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>강원도 삼척의료원</td>\n",
       "      <td>특수법인</td>\n",
       "      <td>지방의료원의 설립 및 운영에 관한 법률</td>\n",
       "      <td>보건복지부(강원도)</td>\n",
       "      <td>지방의료원</td>\n",
       "      <td>32100060</td>\n",
       "      <td>종합병원</td>\n",
       "      <td>152</td>\n",
       "      <td>25920</td>\n",
       "      <td>강원도 삼척시 오십천로 418</td>\n",
       "      <td>http://ksmc.or.kr</td>\n",
       "      <td>033-572-1141</td>\n",
       "      <td>033-573-8424</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>강원도 영월의료원</td>\n",
       "      <td>특수법인</td>\n",
       "      <td>지방의료원의 설립 및 운영에 관한 법률</td>\n",
       "      <td>보건복지부(강원도)</td>\n",
       "      <td>지방의료원</td>\n",
       "      <td>32100078</td>\n",
       "      <td>종합병원</td>\n",
       "      <td>214</td>\n",
       "      <td>26234</td>\n",
       "      <td>강원도 영월군 영월읍 중앙1로 59</td>\n",
       "      <td>http://www.youngwol.org</td>\n",
       "      <td>033-370-9117</td>\n",
       "      <td>033-370-9137</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>강원도 원주의료원</td>\n",
       "      <td>특수법인</td>\n",
       "      <td>지방의료원의 설립 및 운영에 관한 법률</td>\n",
       "      <td>보건복지부(강원도)</td>\n",
       "      <td>지방의료원</td>\n",
       "      <td>32100086</td>\n",
       "      <td>종합병원</td>\n",
       "      <td>237</td>\n",
       "      <td>26448</td>\n",
       "      <td>강원도 원주시 서원대로 387(개운동)</td>\n",
       "      <td>www.kwmc.or.kr</td>\n",
       "      <td>033-760-4500</td>\n",
       "      <td>033-761-5121</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>강원도 강릉의료원</td>\n",
       "      <td>특수법인</td>\n",
       "      <td>지방의료원의 설립 및 운영에 관한 법률</td>\n",
       "      <td>보건복지부(강원도)</td>\n",
       "      <td>지방의료원</td>\n",
       "      <td>32100159</td>\n",
       "      <td>종합병원</td>\n",
       "      <td>137</td>\n",
       "      <td>25535</td>\n",
       "      <td>강원도 강릉시 경강로 2007(남문동 164-1)</td>\n",
       "      <td>http://www.gnmc.or.kr</td>\n",
       "      <td>033-646-6910</td>\n",
       "      <td>033-610-1415</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         병원 명  설립형태                  근거 법령     관계 행정기관 관계 공공단체  심평원 요양기관번호  \\\n",
       "연번                                                                           \n",
       "1    강원도 재활병원   시도립      강원도재활병원설치및운영에관한조례         강원도    해당없음    32200641   \n",
       "2   강원도 삼척의료원  특수법인  지방의료원의 설립 및 운영에 관한 법률  보건복지부(강원도)   지방의료원    32100060   \n",
       "3   강원도 영월의료원  특수법인  지방의료원의 설립 및 운영에 관한 법률  보건복지부(강원도)   지방의료원    32100078   \n",
       "4   강원도 원주의료원  특수법인  지방의료원의 설립 및 운영에 관한 법률  보건복지부(강원도)   지방의료원    32100086   \n",
       "5   강원도 강릉의료원  특수법인  지방의료원의 설립 및 운영에 관한 법률  보건복지부(강원도)   지방의료원    32100159   \n",
       "\n",
       "    종별구분  병상수 소재지 우편번호                           주소                     홈페이지  \\\n",
       "연번                                                                             \n",
       "1     병원  165    24227      강원도 춘천시 충열로 142번길 24-16            www.grh.or.kr   \n",
       "2   종합병원  152    25920             강원도 삼척시 오십천로 418        http://ksmc.or.kr   \n",
       "3   종합병원  214    26234          강원도 영월군 영월읍 중앙1로 59  http://www.youngwol.org   \n",
       "4   종합병원  237    26448        강원도 원주시 서원대로 387(개운동)           www.kwmc.or.kr   \n",
       "5   종합병원  137    25535  강원도 강릉시 경강로 2007(남문동 164-1)    http://www.gnmc.or.kr   \n",
       "\n",
       "            대표전화           FAX   비고  \n",
       "연번                                   \n",
       "1   033-248-7700  033-248-7723  NaN  \n",
       "2   033-572-1141  033-573-8424  NaN  \n",
       "3   033-370-9117  033-370-9137  NaN  \n",
       "4   033-760-4500  033-761-5121  NaN  \n",
       "5   033-646-6910  033-610-1415  NaN  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "pd.set_option('mode.chained_assignment',  None) # Warning 방지용\n",
    "import numpy as np\n",
    "\n",
    "data = pd.read_csv('./9장_data/공공보건의료기관현황.csv', index_col=0, encoding='CP949', engine='python')\n",
    "\n",
    "data.head() #작업내용 확인용 출력"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\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>시도</th>\n",
       "      <th>군구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>강원도</td>\n",
       "      <td>춘천시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>강원도</td>\n",
       "      <td>영월군</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>강원도</td>\n",
       "      <td>원주시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    시도   군구\n",
       "0  강원도  춘천시\n",
       "1  강원도  삼척시\n",
       "2  강원도  영월군\n",
       "3  강원도  원주시\n",
       "4  강원도  강릉시"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 주소에서 시도, 군구 정보 분리\n",
    "\n",
    "addr = pd.DataFrame(data['주소'].apply(lambda v: v.split()[:2]).tolist(),columns=('시도', '군구'))\n",
    "\n",
    "addr.head()  #작업내용 확인용 출력"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1) 시도 이름 확인하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['강원도', '경기도', '경기', '경남', '창원시', '경상남도', '경상북도', '경산시', '경북',\n",
       "       '인천광역시', '대구광역시', '전라남도', '대전광역시', '광주광역시', '제주특별자치도', '부산광역시',\n",
       "       '전라북도', '충북', '서울특별시', '서울시', '부산특별시', '대전시', '충남', '전남', '충청남도',\n",
       "       '울산광역시', '전북', '천안시', '충청북도'], dtype=object)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr['시도'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### #잘못된 시도 이름 수정 : 창원시, 경산시, 천안시"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (1) '창원시'를 찾아서 '경상남도 창원시'로 수정"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>시도</th>\n",
       "      <th>군구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>창원시</td>\n",
       "      <td>의창구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>창원시</td>\n",
       "      <td>마산합포구3.15대로</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     시도           군구\n",
       "27  창원시          의창구\n",
       "31  창원시  마산합포구3.15대로"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr[addr['시도'] == '창원시']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "## 표준 행정구역 이름으로 수정 : 창원시-> 경상남도 창원시\n",
    "addr.iloc[27] = ['경상남도', '창원시']\n",
    "addr.iloc[31] = ['경상남도', '창원시']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "시도    경상남도\n",
       "군구     창원시\n",
       "Name: 27, dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr.iloc[27]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "시도    경상남도\n",
       "군구     창원시\n",
       "Name: 31, dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr.iloc[31]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (2) '경산시'를 찾아서 '경상북도 경산시'로 수정"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\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>시도</th>\n",
       "      <th>군구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>경산시</td>\n",
       "      <td>경안로</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     시도   군구\n",
       "47  경산시  경안로"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr[addr['시도'] == '경산시']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "시도    경상북도\n",
       "군구     경산시\n",
       "Name: 47, dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr.iloc[47] = ['경상북도', '경산시']\n",
    "\n",
    "addr.iloc[47]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (3) '천안시'를 찾아서 '충청남도 천안시'로 수정"
   ]
  },
  {
   "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>시도</th>\n",
       "      <th>군구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>천안시</td>\n",
       "      <td>동남구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>천안시</td>\n",
       "      <td>동남구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      시도   군구\n",
       "209  천안시  동남구\n",
       "210  천안시  동남구"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr[addr['시도'] == '천안시']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "## 표준 행정구역 이름으로 수정 : 천안시-> 충청남도 천안시\n",
    "addr.iloc[209] = ['충청남도', '천안시']\n",
    "addr.iloc[210] = ['충청남도', '천안시']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "시도    충청남도\n",
       "군구     천안시\n",
       "Name: 209, dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr.iloc[209]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "시도    충청남도\n",
       "군구     천안시\n",
       "Name: 210, dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr.iloc[210]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['강원도', '경기도', '경기', '경남', '경상남도', '경상북도', '경북', '인천광역시', '대구광역시',\n",
       "       '전라남도', '대전광역시', '광주광역시', '제주특별자치도', '부산광역시', '전라북도', '충북',\n",
       "       '서울특별시', '서울시', '부산특별시', '대전시', '충남', '전남', '충청남도', '울산광역시', '전북',\n",
       "       '충청북도'], dtype=object)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 작업 결과 확인하기\n",
    "addr['시도'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### # 시도 이름을 표준이름으로 수정"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "## 표준 행정구역 이름으로 수정 :  경기 -> 경기도, 경남 -> 경상남도, ...\n",
    "addr_aliases = {'경기':'경기도', '경남':'경상남도', '경북':'경상북도', '충북':'충청북도', '서울시':'서울특별시', '부산특별시':'부산광역시', '대전시':'대전광역시', '충남':'충청남도', '전남':'전라남도', '전북':'전라북도'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "addr['시도']= addr['시도'].apply(lambda v: addr_aliases.get(v, v))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['강원도', '경기도', '경상남도', '경상북도', '인천광역시', '대구광역시', '전라남도', '대전광역시',\n",
       "       '광주광역시', '제주특별자치도', '부산광역시', '전라북도', '충청북도', '서울특별시', '충청남도',\n",
       "       '울산광역시'], dtype=object)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 작업 결과 확인하기\n",
    "addr['시도'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2) 군구 이름 확인하기 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['춘천시', '삼척시', '영월군', '원주시', '강릉시', '속초시', '정선군', '수원시', '이천시',\n",
       "       '안성시', '의정부시', '포천시', '파주시', '용인시', '평택시', '시흥시', '여주시', '남양주시',\n",
       "       '동두천시', '안산시', '부천시', '통영시', '사천시', '창원시', '김해시', '양산시', '거창군',\n",
       "       '남해군', '의령군', '포항시', '김천시', '안동시', '울진군', '경주시', '구미시', '영주시',\n",
       "       '상주시', '문경시', '경산시', '의성군', '청도군', '고령군', '칠곡군', '봉화군', '울릉군',\n",
       "       '부평구', '북구', '순천시', '대덕구', '태백시', '동해시', '화성시', '광산구', '남구', '중구',\n",
       "       '아란13길', '서구', '전주시', '진주시', '청주시', '종로구', '성남시', '동구', '화순군',\n",
       "       '강동구', '사상구', '달서구', '해운대구', '유성구', '가평군', '양주시', '고양시', '홍천군',\n",
       "       '양구군', '청원군', '계룡시', '논산시', '함평군', '양평군', '수성구', '달성군', '연수구',\n",
       "       '노원구', '기장군', '공주시', '강북구', '광진구', '나주시', '창녕군', '목포시', '고흥군',\n",
       "       '연제구', '동매로', '서초구', '은평구', '중랑구', '강남구', '동작구', '동대문구', '양천구',\n",
       "       '성동구', '송파구', '울주군', '계양구', '옹진군', '보성군', '광양시', '영광군', '무안군',\n",
       "       '진도군', '강진군', '곡성군', '여수시', '신안군', '장성군', '완주군', '부안군', '정읍시',\n",
       "       '남원시', '군산시', '고창군', '진안군', '제주시', '서귀포시', '천안시', '보령시', '서산시',\n",
       "       '서천군', '홍성군', '제천시', '충주시', '영동군', '단양군'], dtype=object)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr['군구'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### # 잘못된 군구 이름 수정하기 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### (1) '아란13길' 을 '제주특별자치도'  '제주시'로 수정"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>시도</th>\n",
       "      <th>군구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>제주특별자치도</td>\n",
       "      <td>아란13길</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         시도     군구\n",
       "75  제주특별자치도  아란13길"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr[addr['군구'] == '아란13길']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "시도    제주특별자치도\n",
       "군구        제주시\n",
       "Name: 75, dtype: object"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr.iloc[75] = ['제주특별자치도', '제주시']\n",
    "\n",
    "addr.iloc[75]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['춘천시', '삼척시', '영월군', '원주시', '강릉시', '속초시', '정선군', '수원시', '이천시',\n",
       "       '안성시', '의정부시', '포천시', '파주시', '용인시', '평택시', '시흥시', '여주시', '남양주시',\n",
       "       '동두천시', '안산시', '부천시', '통영시', '사천시', '창원시', '김해시', '양산시', '거창군',\n",
       "       '남해군', '의령군', '포항시', '김천시', '안동시', '울진군', '경주시', '구미시', '영주시',\n",
       "       '상주시', '문경시', '경산시', '의성군', '청도군', '고령군', '칠곡군', '봉화군', '울릉군',\n",
       "       '부평구', '북구', '순천시', '대덕구', '태백시', '동해시', '화성시', '광산구', '남구', '중구',\n",
       "       '제주시', '서구', '전주시', '진주시', '청주시', '종로구', '성남시', '동구', '화순군', '강동구',\n",
       "       '사상구', '달서구', '해운대구', '유성구', '가평군', '양주시', '고양시', '홍천군', '양구군',\n",
       "       '청원군', '계룡시', '논산시', '함평군', '양평군', '수성구', '달성군', '연수구', '노원구',\n",
       "       '기장군', '공주시', '강북구', '광진구', '나주시', '창녕군', '목포시', '고흥군', '연제구',\n",
       "       '동매로', '서초구', '은평구', '중랑구', '강남구', '동작구', '동대문구', '양천구', '성동구',\n",
       "       '송파구', '울주군', '계양구', '옹진군', '보성군', '광양시', '영광군', '무안군', '진도군',\n",
       "       '강진군', '곡성군', '여수시', '신안군', '장성군', '완주군', '부안군', '정읍시', '남원시',\n",
       "       '군산시', '고창군', '진안군', '서귀포시', '천안시', '보령시', '서산시', '서천군', '홍성군',\n",
       "       '제천시', '충주시', '영동군', '단양군'], dtype=object)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr['군구'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3) 행정구역별 공공보건의료기관의 수 구하기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (1) '시도' 와 '군구' 컬럼 결합하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>시도</th>\n",
       "      <th>군구</th>\n",
       "      <th>시도군구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>강원도</td>\n",
       "      <td>춘천시</td>\n",
       "      <td>강원도 춘천시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "      <td>강원도 삼척시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>강원도</td>\n",
       "      <td>영월군</td>\n",
       "      <td>강원도 영월군</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>강원도</td>\n",
       "      <td>원주시</td>\n",
       "      <td>강원도 원주시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>강원도 강릉시</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    시도   군구     시도군구\n",
       "0  강원도  춘천시  강원도 춘천시\n",
       "1  강원도  삼척시  강원도 삼척시\n",
       "2  강원도  영월군  강원도 영월군\n",
       "3  강원도  원주시  강원도 원주시\n",
       "4  강원도  강릉시  강원도 강릉시"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr['시도군구'] = addr.apply(lambda r: r['시도'] + ' ' + r['군구'], axis=1)\n",
    "\n",
    "addr.head() #작업 확인용 출력"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "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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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>시도</th>\n",
       "      <th>군구</th>\n",
       "      <th>시도군구</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>강원도</td>\n",
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       "      <td>강원도 춘천시</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "      <td>강원도 삼척시</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>강원도</td>\n",
       "      <td>영월군</td>\n",
       "      <td>강원도 영월군</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>강원도</td>\n",
       "      <td>원주시</td>\n",
       "      <td>강원도 원주시</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>강원도 강릉시</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    시도   군구     시도군구  count\n",
       "0  강원도  춘천시  강원도 춘천시      0\n",
       "1  강원도  삼척시  강원도 삼척시      0\n",
       "2  강원도  영월군  강원도 영월군      0\n",
       "3  강원도  원주시  강원도 원주시      0\n",
       "4  강원도  강릉시  강원도 강릉시      0"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr['count'] = 0  # 의료기관수 합계를 저장할 컬럼 만들기\n",
    "\n",
    "addr.head() #작업 확인용 출력"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (2) '시도군구' 를 기준으로 그룹을 만들고, 그룹별 의료기관수 합계 구하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "\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>시도</th>\n",
       "      <th>군구</th>\n",
       "      <th>시도군구</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>강원도 강릉시</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>강원도</td>\n",
       "      <td>동해시</td>\n",
       "      <td>강원도 동해시</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "      <td>강원도 삼척시</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "      <td>강원도 속초시</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>강원도</td>\n",
       "      <td>양구군</td>\n",
       "      <td>강원도 양구군</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    시도   군구     시도군구  count\n",
       "0  강원도  강릉시  강원도 강릉시      4\n",
       "1  강원도  동해시  강원도 동해시      1\n",
       "2  강원도  삼척시  강원도 삼척시      1\n",
       "3  강원도  속초시  강원도 속초시      1\n",
       "4  강원도  양구군  강원도 양구군      1"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr_group =pd.DataFrame(addr.groupby(['시도', '군구', '시도군구'], as_index=False).count())\n",
    "\n",
    "addr_group.head()  #작업 확인용 출력"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (3) 데이터 병합에 사용할 인덱스 설정하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>시도</th>\n",
       "      <th>군구</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>시도군구</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>강원도 강릉시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 동해시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>동해시</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 삼척시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 속초시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 양구군</th>\n",
       "      <td>강원도</td>\n",
       "      <td>양구군</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          시도   군구  count\n",
       "시도군구                    \n",
       "강원도 강릉시  강원도  강릉시      4\n",
       "강원도 동해시  강원도  동해시      1\n",
       "강원도 삼척시  강원도  삼척시      1\n",
       "강원도 속초시  강원도  속초시      1\n",
       "강원도 양구군  강원도  양구군      1"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr_group = addr_group.set_index(\"시도군구\")\n",
    "\n",
    "addr_group.head()   #작업 확인용 출력"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4) 행정구역 인구수 컬럼 추가하기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####   (1) 행정구역 이름 데이터 불러오기 : 행정구역_시군구_별__성별_인구수_2.xlsx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>행정구역(시군구)별(1)</th>\n",
       "      <th>행정구역(시군구)별(2)</th>\n",
       "      <th>총인구수 (명)</th>\n",
       "      <th>남자인구수 (명)</th>\n",
       "      <th>여자인구수 (명)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>전국</td>\n",
       "      <td>소계</td>\n",
       "      <td>51847509</td>\n",
       "      <td>25862863</td>\n",
       "      <td>25984646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>소계</td>\n",
       "      <td>9733509</td>\n",
       "      <td>4745088</td>\n",
       "      <td>4988421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>종로구</td>\n",
       "      <td>151215</td>\n",
       "      <td>73688</td>\n",
       "      <td>77527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>중구</td>\n",
       "      <td>126201</td>\n",
       "      <td>61946</td>\n",
       "      <td>64255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>용산구</td>\n",
       "      <td>229385</td>\n",
       "      <td>110701</td>\n",
       "      <td>118684</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  행정구역(시군구)별(1) 행정구역(시군구)별(2)  총인구수 (명)  남자인구수 (명)  여자인구수 (명)\n",
       "0            전국            소계  51847509   25862863   25984646\n",
       "1         서울특별시            소계   9733509    4745088    4988421\n",
       "2         서울특별시        　　　종로구    151215      73688      77527\n",
       "3         서울특별시         　　　중구    126201      61946      64255\n",
       "4         서울특별시        　　　용산구    229385     110701     118684"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population = pd.read_excel('./9장_data/행정구역_시군구_별__성별_인구수_2.xlsx')\n",
    "\n",
    "population.head()    #작업 확인용 출력"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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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       "\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>시도</th>\n",
       "      <th>군구</th>\n",
       "      <th>총인구수 (명)</th>\n",
       "      <th>남자인구수 (명)</th>\n",
       "      <th>여자인구수 (명)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>전국</td>\n",
       "      <td>소계</td>\n",
       "      <td>51847509</td>\n",
       "      <td>25862863</td>\n",
       "      <td>25984646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>소계</td>\n",
       "      <td>9733509</td>\n",
       "      <td>4745088</td>\n",
       "      <td>4988421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>종로구</td>\n",
       "      <td>151215</td>\n",
       "      <td>73688</td>\n",
       "      <td>77527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>중구</td>\n",
       "      <td>126201</td>\n",
       "      <td>61946</td>\n",
       "      <td>64255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>용산구</td>\n",
       "      <td>229385</td>\n",
       "      <td>110701</td>\n",
       "      <td>118684</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      시도      군구  총인구수 (명)  남자인구수 (명)  여자인구수 (명)\n",
       "0     전국      소계  51847509   25862863   25984646\n",
       "1  서울특별시      소계   9733509    4745088    4988421\n",
       "2  서울특별시  　　　종로구    151215      73688      77527\n",
       "3  서울특별시   　　　중구    126201      61946      64255\n",
       "4  서울특별시  　　　용산구    229385     110701     118684"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population = population.rename(columns = {'행정구역(시군구)별(1)': '시도', '행정구역(시군구)별(2)': '군구'}) #컬럼이름 변경\n",
    "\n",
    "population.head()  #작업 확인용 출력"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####   (2) 병합에 사용할 공통 컬럼 '시도군구' 추가하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# '군구' 컬럼에서 공백 제거하기\n",
    "for element in range(0,len(population)):\n",
    "      population['군구'][element] = population['군구'][element].strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>시도</th>\n",
       "      <th>군구</th>\n",
       "      <th>총인구수 (명)</th>\n",
       "      <th>남자인구수 (명)</th>\n",
       "      <th>여자인구수 (명)</th>\n",
       "      <th>시도군구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>전국</td>\n",
       "      <td>소계</td>\n",
       "      <td>51847509</td>\n",
       "      <td>25862863</td>\n",
       "      <td>25984646</td>\n",
       "      <td>전국 소계</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>소계</td>\n",
       "      <td>9733509</td>\n",
       "      <td>4745088</td>\n",
       "      <td>4988421</td>\n",
       "      <td>서울특별시 소계</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>종로구</td>\n",
       "      <td>151215</td>\n",
       "      <td>73688</td>\n",
       "      <td>77527</td>\n",
       "      <td>서울특별시 종로구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>중구</td>\n",
       "      <td>126201</td>\n",
       "      <td>61946</td>\n",
       "      <td>64255</td>\n",
       "      <td>서울특별시 중구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>용산구</td>\n",
       "      <td>229385</td>\n",
       "      <td>110701</td>\n",
       "      <td>118684</td>\n",
       "      <td>서울특별시 용산구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      시도   군구  총인구수 (명)  남자인구수 (명)  여자인구수 (명)       시도군구\n",
       "0     전국   소계  51847509   25862863   25984646      전국 소계\n",
       "1  서울특별시   소계   9733509    4745088    4988421   서울특별시 소계\n",
       "2  서울특별시  종로구    151215      73688      77527  서울특별시 종로구\n",
       "3  서울특별시   중구    126201      61946      64255   서울특별시 중구\n",
       "4  서울특별시  용산구    229385     110701     118684  서울특별시 용산구"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# '시도'와 '군구'를 연결하여 '시도군구' 컬럼 추가\n",
    "population['시도군구']= population.apply(lambda r: r['시도'] + ' ' + r['군구'], axis=1)\n",
    "\n",
    "population.head()  #작업 확인용 출력"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### -  필요없는  '소계' 행 삭제"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\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>시도</th>\n",
       "      <th>군구</th>\n",
       "      <th>총인구수 (명)</th>\n",
       "      <th>남자인구수 (명)</th>\n",
       "      <th>여자인구수 (명)</th>\n",
       "      <th>시도군구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>종로구</td>\n",
       "      <td>151215</td>\n",
       "      <td>73688</td>\n",
       "      <td>77527</td>\n",
       "      <td>서울특별시 종로구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>중구</td>\n",
       "      <td>126201</td>\n",
       "      <td>61946</td>\n",
       "      <td>64255</td>\n",
       "      <td>서울특별시 중구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>용산구</td>\n",
       "      <td>229385</td>\n",
       "      <td>110701</td>\n",
       "      <td>118684</td>\n",
       "      <td>서울특별시 용산구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>성동구</td>\n",
       "      <td>300410</td>\n",
       "      <td>147020</td>\n",
       "      <td>153390</td>\n",
       "      <td>서울특별시 성동구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>광진구</td>\n",
       "      <td>351263</td>\n",
       "      <td>170164</td>\n",
       "      <td>181099</td>\n",
       "      <td>서울특별시 광진구</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      시도   군구  총인구수 (명)  남자인구수 (명)  여자인구수 (명)       시도군구\n",
       "2  서울특별시  종로구    151215      73688      77527  서울특별시 종로구\n",
       "3  서울특별시   중구    126201      61946      64255   서울특별시 중구\n",
       "4  서울특별시  용산구    229385     110701     118684  서울특별시 용산구\n",
       "5  서울특별시  성동구    300410     147020     153390  서울특별시 성동구\n",
       "6  서울특별시  광진구    351263     170164     181099  서울특별시 광진구"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population = population[population.군구 != '소계']\n",
    "\n",
    "population.head()  #작업 확인용 출력"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####   (3) 병합의 기준이 될 인덱스를 '시도군구'로 설정"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>시도</th>\n",
       "      <th>군구</th>\n",
       "      <th>총인구수 (명)</th>\n",
       "      <th>남자인구수 (명)</th>\n",
       "      <th>여자인구수 (명)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>시도군구</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>서울특별시 종로구</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>종로구</td>\n",
       "      <td>151215</td>\n",
       "      <td>73688</td>\n",
       "      <td>77527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>서울특별시 중구</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>중구</td>\n",
       "      <td>126201</td>\n",
       "      <td>61946</td>\n",
       "      <td>64255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>서울특별시 용산구</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>용산구</td>\n",
       "      <td>229385</td>\n",
       "      <td>110701</td>\n",
       "      <td>118684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>서울특별시 성동구</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>성동구</td>\n",
       "      <td>300410</td>\n",
       "      <td>147020</td>\n",
       "      <td>153390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>서울특별시 광진구</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>광진구</td>\n",
       "      <td>351263</td>\n",
       "      <td>170164</td>\n",
       "      <td>181099</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              시도   군구  총인구수 (명)  남자인구수 (명)  여자인구수 (명)\n",
       "시도군구                                                 \n",
       "서울특별시 종로구  서울특별시  종로구    151215      73688      77527\n",
       "서울특별시 중구   서울특별시   중구    126201      61946      64255\n",
       "서울특별시 용산구  서울특별시  용산구    229385     110701     118684\n",
       "서울특별시 성동구  서울특별시  성동구    300410     147020     153390\n",
       "서울특별시 광진구  서울특별시  광진구    351263     170164     181099"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population = population.set_index(\"시도군구\")\n",
    "\n",
    "population.head()  #작업 확인용 출력"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5) '의료기관' 데이터프레임과 '시도군구별 인구수' 데이터프레임 병합하기 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>시도_x</th>\n",
       "      <th>군구_x</th>\n",
       "      <th>count</th>\n",
       "      <th>시도_y</th>\n",
       "      <th>군구_y</th>\n",
       "      <th>총인구수 (명)</th>\n",
       "      <th>남자인구수 (명)</th>\n",
       "      <th>여자인구수 (명)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>시도군구</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>강원도 강릉시</th>\n",
       "      <td>강원도</td>\n",
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       "      <td>4</td>\n",
       "      <td>강원도</td>\n",
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       "      <td>213328</td>\n",
       "      <td>105775</td>\n",
       "      <td>107553</td>\n",
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       "    <tr>\n",
       "      <th>강원도 동해시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>동해시</td>\n",
       "      <td>1</td>\n",
       "      <td>강원도</td>\n",
       "      <td>동해시</td>\n",
       "      <td>90417</td>\n",
       "      <td>45782</td>\n",
       "      <td>44635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 삼척시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "      <td>1</td>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "      <td>66806</td>\n",
       "      <td>33811</td>\n",
       "      <td>32995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 속초시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "      <td>1</td>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "      <td>81840</td>\n",
       "      <td>40470</td>\n",
       "      <td>41370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 양구군</th>\n",
       "      <td>강원도</td>\n",
       "      <td>양구군</td>\n",
       "      <td>1</td>\n",
       "      <td>강원도</td>\n",
       "      <td>양구군</td>\n",
       "      <td>22526</td>\n",
       "      <td>11937</td>\n",
       "      <td>10589</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        시도_x 군구_x  count 시도_y 군구_y  총인구수 (명)  남자인구수 (명)  여자인구수 (명)\n",
       "시도군구                                                              \n",
       "강원도 강릉시  강원도  강릉시      4  강원도  강릉시    213328     105775     107553\n",
       "강원도 동해시  강원도  동해시      1  강원도  동해시     90417      45782      44635\n",
       "강원도 삼척시  강원도  삼척시      1  강원도  삼척시     66806      33811      32995\n",
       "강원도 속초시  강원도  속초시      1  강원도  속초시     81840      40470      41370\n",
       "강원도 양구군  강원도  양구군      1  강원도  양구군     22526      11937      10589"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr_population_merge = pd.merge(addr_group,population,  how='inner',  left_index=True, right_index=True)\n",
    "\n",
    "addr_population_merge.head()   #작업 확인용 출력"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### -필요한 컬럼만 추출하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>강원도 강릉시</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 삼척시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "      <td>1</td>\n",
       "      <td>66806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 속초시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "      <td>1</td>\n",
       "      <td>81840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 양구군</th>\n",
       "      <td>강원도</td>\n",
       "      <td>양구군</td>\n",
       "      <td>1</td>\n",
       "      <td>22526</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        시도_x 군구_x  count  총인구수 (명)\n",
       "시도군구                              \n",
       "강원도 강릉시  강원도  강릉시      4    213328\n",
       "강원도 동해시  강원도  동해시      1     90417\n",
       "강원도 삼척시  강원도  삼척시      1     66806\n",
       "강원도 속초시  강원도  속초시      1     81840\n",
       "강원도 양구군  강원도  양구군      1     22526"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "local_MC_Population = addr_population_merge[['시도_x', '군구_x',  'count', '총인구수 (명)']]\n",
    "\n",
    "local_MC_Population.head()   #작업 확인용 출력  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>시도</th>\n",
       "      <th>군구</th>\n",
       "      <th>count</th>\n",
       "      <th>인구수</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>시도군구</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>강원도 강릉시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>4</td>\n",
       "      <td>213328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 동해시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>동해시</td>\n",
       "      <td>1</td>\n",
       "      <td>90417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 삼척시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "      <td>1</td>\n",
       "      <td>66806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 속초시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "      <td>1</td>\n",
       "      <td>81840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 양구군</th>\n",
       "      <td>강원도</td>\n",
       "      <td>양구군</td>\n",
       "      <td>1</td>\n",
       "      <td>22526</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          시도   군구  count     인구수\n",
       "시도군구                            \n",
       "강원도 강릉시  강원도  강릉시      4  213328\n",
       "강원도 동해시  강원도  동해시      1   90417\n",
       "강원도 삼척시  강원도  삼척시      1   66806\n",
       "강원도 속초시  강원도  속초시      1   81840\n",
       "강원도 양구군  강원도  양구군      1   22526"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " #컬럼이름 변경\n",
    "local_MC_Population = local_MC_Population.rename(columns = {'시도_x': '시도', '군구_x': '군구','총인구수 (명)': '인구수' })\n",
    "\n",
    "local_MC_Population.head()  #작업 확인용 출력"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6) 시도군구의 인구대비 의료기관수 비율 구하기"
   ]
  },
  {
   "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>시도</th>\n",
       "      <th>군구</th>\n",
       "      <th>count</th>\n",
       "      <th>인구수</th>\n",
       "      <th>MC_ratio</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>시도군구</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>강원도 강릉시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>4</td>\n",
       "      <td>213328</td>\n",
       "      <td>1.875047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 동해시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>동해시</td>\n",
       "      <td>1</td>\n",
       "      <td>90417</td>\n",
       "      <td>1.105987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 삼척시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "      <td>1</td>\n",
       "      <td>66806</td>\n",
       "      <td>1.496872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 속초시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "      <td>1</td>\n",
       "      <td>81840</td>\n",
       "      <td>1.221896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 양구군</th>\n",
       "      <td>강원도</td>\n",
       "      <td>양구군</td>\n",
       "      <td>1</td>\n",
       "      <td>22526</td>\n",
       "      <td>4.439315</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          시도   군구  count     인구수  MC_ratio\n",
       "시도군구                                      \n",
       "강원도 강릉시  강원도  강릉시      4  213328  1.875047\n",
       "강원도 동해시  강원도  동해시      1   90417  1.105987\n",
       "강원도 삼척시  강원도  삼척시      1   66806  1.496872\n",
       "강원도 속초시  강원도  속초시      1   81840  1.221896\n",
       "강원도 양구군  강원도  양구군      1   22526  4.439315"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MC_count = local_MC_Population['count']\n",
    "local_MC_Population['MC_ratio'] = MC_count.div(local_MC_Population['인구수'], axis=0)*100000\n",
    "\n",
    "local_MC_Population.head()   #작업 확인용 출력"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. 분석 모델 구축 및 시각화"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  1) 바 차트 그리기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "from matplotlib import rcParams, style\n",
    "style.use('ggplot')\n",
    "\n",
    "from matplotlib import font_manager, rc\n",
    "font_name = font_manager.FontProperties(fname=\"/System/Library/Fonts/AppleSDGothicNeo.ttc\").get_name()\n",
    "rc('font', family=font_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####   (1) 행정구역별 공공보건의료기관수에 대한 바 차트 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1800x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "MC_ratio = local_MC_Population[['count']]\n",
    "MC_ratio = MC_ratio.sort_values('count', ascending = False)\n",
    "plt.rcParams[\"figure.figsize\"] = (25,5)\n",
    "MC_ratio.plot(kind='bar', rot=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####   (2) 행정구역별 인구수 대비 공공보건의료기관 비율에 대한 바 차트 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "MC_ratio = local_MC_Population[['MC_ratio']]\n",
    "MC_ratio = MC_ratio.sort_values('MC_ratio', ascending = False)\n",
    "plt.rcParams[\"figure.figsize\"] = (25,5)\n",
    "MC_ratio.plot(kind='bar', rot=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2) 블록맵 시각화"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###   (1) 블록맵 데이터 파일 열기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "path = os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "scrolled": true
   },
   "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>인구수</th>\n",
       "      <th>shortName</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>면적</th>\n",
       "      <th>광역시도</th>\n",
       "      <th>행정구역</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>202520</td>\n",
       "      <td>강릉</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>1040.07</td>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>25589</td>\n",
       "      <td>고성(강원)</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>664.19</td>\n",
       "      <td>강원도</td>\n",
       "      <td>고성군</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86747</td>\n",
       "      <td>동해</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>180.01</td>\n",
       "      <td>강원도</td>\n",
       "      <td>동해시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>63986</td>\n",
       "      <td>삼척</td>\n",
       "      <td>11</td>\n",
       "      <td>8</td>\n",
       "      <td>1185.80</td>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>76733</td>\n",
       "      <td>속초</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>105.25</td>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      인구수 shortName   x  y       면적 광역시도 행정구역\n",
       "0  202520        강릉  11  4  1040.07  강원도  강릉시\n",
       "1   25589    고성(강원)   9  0   664.19  강원도  고성군\n",
       "2   86747        동해  11  5   180.01  강원도  동해시\n",
       "3   63986        삼척  11  8  1185.80  강원도  삼척시\n",
       "4   76733        속초   9  1   105.25  강원도  속초시"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_draw_korea = pd.read_csv(path+'/9장_data/data_draw_korea.csv', index_col=0, encoding='UTF-8', engine='python')\n",
    "\n",
    "data_draw_korea.head()   #작업 확인용 출력"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###   (2) 블록맵 데이터 파일에 '시도군구' 컬럼 만들기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>인구수</th>\n",
       "      <th>shortName</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>면적</th>\n",
       "      <th>광역시도</th>\n",
       "      <th>행정구역</th>\n",
       "      <th>시도군구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>202520</td>\n",
       "      <td>강릉</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>1040.07</td>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>강원도 강릉시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>25589</td>\n",
       "      <td>고성(강원)</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>664.19</td>\n",
       "      <td>강원도</td>\n",
       "      <td>고성군</td>\n",
       "      <td>강원도 고성군</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86747</td>\n",
       "      <td>동해</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>180.01</td>\n",
       "      <td>강원도</td>\n",
       "      <td>동해시</td>\n",
       "      <td>강원도 동해시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>63986</td>\n",
       "      <td>삼척</td>\n",
       "      <td>11</td>\n",
       "      <td>8</td>\n",
       "      <td>1185.80</td>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "      <td>강원도 삼척시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>76733</td>\n",
       "      <td>속초</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>105.25</td>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "      <td>강원도 속초시</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      인구수 shortName   x  y       면적 광역시도 행정구역     시도군구\n",
       "0  202520        강릉  11  4  1040.07  강원도  강릉시  강원도 강릉시\n",
       "1   25589    고성(강원)   9  0   664.19  강원도  고성군  강원도 고성군\n",
       "2   86747        동해  11  5   180.01  강원도  동해시  강원도 동해시\n",
       "3   63986        삼척  11  8  1185.80  강원도  삼척시  강원도 삼척시\n",
       "4   76733        속초   9  1   105.25  강원도  속초시  강원도 속초시"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_draw_korea['시도군구']= data_draw_korea.apply(lambda r: r['광역시도'] + ' ' + r['행정구역'], axis=1)\n",
    "\n",
    "data_draw_korea.head()  #작업 확인용 출력"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###   (3) 블록맵 데이터에서 병합에 사용할 '시도군구' 컬럼을 인덱스로 설정하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <th></th>\n",
       "      <th>인구수</th>\n",
       "      <th>shortName</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>면적</th>\n",
       "      <th>광역시도</th>\n",
       "      <th>행정구역</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>시도군구</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>강원도 강릉시</th>\n",
       "      <td>202520</td>\n",
       "      <td>강릉</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>1040.07</td>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 고성군</th>\n",
       "      <td>25589</td>\n",
       "      <td>고성(강원)</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>664.19</td>\n",
       "      <td>강원도</td>\n",
       "      <td>고성군</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 동해시</th>\n",
       "      <td>86747</td>\n",
       "      <td>동해</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>180.01</td>\n",
       "      <td>강원도</td>\n",
       "      <td>동해시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 삼척시</th>\n",
       "      <td>63986</td>\n",
       "      <td>삼척</td>\n",
       "      <td>11</td>\n",
       "      <td>8</td>\n",
       "      <td>1185.80</td>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 속초시</th>\n",
       "      <td>76733</td>\n",
       "      <td>속초</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>105.25</td>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            인구수 shortName   x  y       면적 광역시도 행정구역\n",
       "시도군구                                               \n",
       "강원도 강릉시  202520        강릉  11  4  1040.07  강원도  강릉시\n",
       "강원도 고성군   25589    고성(강원)   9  0   664.19  강원도  고성군\n",
       "강원도 동해시   86747        동해  11  5   180.01  강원도  동해시\n",
       "강원도 삼척시   63986        삼척  11  8  1185.80  강원도  삼척시\n",
       "강원도 속초시   76733        속초   9  1   105.25  강원도  속초시"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_draw_korea = data_draw_korea.set_index(\"시도군구\")\n",
    "\n",
    "data_draw_korea.head()  #작업 확인용 출력"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###   (4) 블록맵 데이터프레임과 local_MC_Population을 병합하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "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>인구수_x</th>\n",
       "      <th>shortName</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>면적</th>\n",
       "      <th>광역시도</th>\n",
       "      <th>행정구역</th>\n",
       "      <th>시도</th>\n",
       "      <th>군구</th>\n",
       "      <th>count</th>\n",
       "      <th>인구수_y</th>\n",
       "      <th>MC_ratio</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>시도군구</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>강원도 강릉시</th>\n",
       "      <td>202520</td>\n",
       "      <td>강릉</td>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>1040.07</td>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>4.0</td>\n",
       "      <td>213328.0</td>\n",
       "      <td>1.875047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 고성군</th>\n",
       "      <td>25589</td>\n",
       "      <td>고성(강원)</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>664.19</td>\n",
       "      <td>강원도</td>\n",
       "      <td>고성군</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 동해시</th>\n",
       "      <td>86747</td>\n",
       "      <td>동해</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>180.01</td>\n",
       "      <td>강원도</td>\n",
       "      <td>동해시</td>\n",
       "      <td>강원도</td>\n",
       "      <td>동해시</td>\n",
       "      <td>1.0</td>\n",
       "      <td>90417.0</td>\n",
       "      <td>1.105987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 삼척시</th>\n",
       "      <td>63986</td>\n",
       "      <td>삼척</td>\n",
       "      <td>11</td>\n",
       "      <td>8</td>\n",
       "      <td>1185.80</td>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "      <td>1.0</td>\n",
       "      <td>66806.0</td>\n",
       "      <td>1.496872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 속초시</th>\n",
       "      <td>76733</td>\n",
       "      <td>속초</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>105.25</td>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "      <td>1.0</td>\n",
       "      <td>81840.0</td>\n",
       "      <td>1.221896</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          인구수_x shortName   x  y       면적 광역시도 행정구역   시도   군구  count  \\\n",
       "시도군구                                                                   \n",
       "강원도 강릉시  202520        강릉  11  4  1040.07  강원도  강릉시  강원도  강릉시    4.0   \n",
       "강원도 고성군   25589    고성(강원)   9  0   664.19  강원도  고성군  NaN  NaN    NaN   \n",
       "강원도 동해시   86747        동해  11  5   180.01  강원도  동해시  강원도  동해시    1.0   \n",
       "강원도 삼척시   63986        삼척  11  8  1185.80  강원도  삼척시  강원도  삼척시    1.0   \n",
       "강원도 속초시   76733        속초   9  1   105.25  강원도  속초시  강원도  속초시    1.0   \n",
       "\n",
       "            인구수_y  MC_ratio  \n",
       "시도군구                         \n",
       "강원도 강릉시  213328.0  1.875047  \n",
       "강원도 고성군       NaN       NaN  \n",
       "강원도 동해시   90417.0  1.105987  \n",
       "강원도 삼척시   66806.0  1.496872  \n",
       "강원도 속초시   81840.0  1.221896  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_draw_korea_MC_Population_all = pd.merge(data_draw_korea,local_MC_Population,  how='outer',  left_index=True, right_index=True)\n",
    "\n",
    "data_draw_korea_MC_Population_all.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###   (5) 한국지도의 블록맵 경계선 좌표를 리스트로 생성 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "BORDER_LINES = [\n",
    "    [(3, 2), (5, 2), (5, 3), (9, 3), (9, 1)], # 인천\n",
    "    [(2, 5), (3, 5), (3, 4), (8, 4), (8, 7), (7, 7), (7, 9), (4, 9), (4, 7), (1, 7)], # 서울\n",
    "    [(1, 6), (1, 9), (3, 9), (3, 10), (8, 10), (8, 9),\n",
    "     (9, 9), (9, 8), (10, 8), (10, 5), (9, 5), (9, 3)], # 경기도\n",
    "    [(9, 12), (9, 10), (8, 10)], # 강원도\n",
    "    [(10, 5), (11, 5), (11, 4), (12, 4), (12, 5), (13, 5),\n",
    "     (13, 4), (14, 4), (14, 2)], # 충청남도\n",
    "    [(11, 5), (12, 5), (12, 6), (15, 6), (15, 7), (13, 7),\n",
    "     (13, 8), (11, 8), (11, 9), (10, 9), (10, 8)], # 충청북도\n",
    "    [(14, 4), (15, 4), (15, 6)], # 대전시\n",
    "    [(14, 7), (14, 9), (13, 9), (13, 11), (13, 13)], # 경상북도\n",
    "    [(14, 8), (16, 8), (16, 10), (15, 10),\n",
    "     (15, 11), (14, 11), (14, 12), (13, 12)], # 대구시\n",
    "    [(15, 11), (16, 11), (16, 13)], # 울산시\n",
    "    [(17, 1), (17, 3), (18, 3), (18, 6), (15, 6)], # 전라북도\n",
    "    [(19, 2), (19, 4), (21, 4), (21, 3), (22, 3), (22, 2), (19, 2)], # 광주시\n",
    "    [(18, 5), (20, 5), (20, 6)], # 전라남도\n",
    "    [(16, 9), (18, 9), (18, 8), (19, 8), (19, 9), (20, 9), (20, 10)], # 부산시\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###   (6) 블록맵에서 블록에 해당 데이터를 매핑하여 색을 표시하는 함수"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "def draw_blockMap(blockedMap, targetData, title, color ):\n",
    "    whitelabelmin = (max(blockedMap[targetData]) - min(blockedMap[targetData])) * 0.25 + min(blockedMap[targetData])\n",
    "\n",
    "    datalabel = targetData\n",
    "\n",
    "    vmin = min(blockedMap[targetData])\n",
    "    vmax = max(blockedMap[targetData])\n",
    "\n",
    "    mapdata = blockedMap.pivot(index='y', columns='x', values=targetData)\n",
    "    masked_mapdata = np.ma.masked_where(np.isnan(mapdata), mapdata)\n",
    "    \n",
    "    plt.figure(figsize=(8, 13))\n",
    "    plt.title(title)\n",
    "    plt.pcolor(masked_mapdata, vmin=vmin, vmax=vmax, cmap=color, edgecolor='#aaaaaa', linewidth=0.5)\n",
    "\n",
    "    # 지역 이름 표시\n",
    "    for idx, row in blockedMap.iterrows():\n",
    "        annocolor = 'white' if row[targetData] > whitelabelmin else 'black'\n",
    "    \n",
    "        # 광역시는 구 이름이 겹치는 경우가 많아서 시단위 이름도 같이 표시한다. (중구, 서구)\n",
    "        if row['광역시도'].endswith('시') and not row['광역시도'].startswith('세종'):\n",
    "            dispname = '{}\\n{}'.format(row['광역시도'][:2], row['행정구역'][:-1])\n",
    "            if len(row['행정구역']) <= 2:\n",
    "                dispname += row['행정구역'][-1]\n",
    "        else:\n",
    "            dispname = row['행정구역'][:-1]\n",
    "\n",
    "        # 서대문구, 서귀포시 같이 이름이 3자 이상인 경우에 작은 글자로 표시한다.\n",
    "        if len(dispname.splitlines()[-1]) >= 3:\n",
    "            fontsize, linespacing = 9.5, 1.5\n",
    "        else:\n",
    "            fontsize, linespacing = 11, 1.2\n",
    "\n",
    "        plt.annotate(dispname, (row['x']+0.5, row['y']+0.5), weight='bold',\n",
    "                     fontsize=fontsize, ha='center', va='center', color=annocolor,\n",
    "                     linespacing=linespacing)\n",
    "    \n",
    "    # 시도 경계 그린다.\n",
    "    for path in BORDER_LINES:\n",
    "        ys, xs = zip(*path)\n",
    "        plt.plot(xs, ys, c='black', lw=4)\n",
    "\n",
    "    plt.gca().invert_yaxis()\n",
    "    #plt.gca().set_aspect(1)\n",
    "    plt.axis('off')\n",
    "    \n",
    "    cb = plt.colorbar(shrink=.1, aspect=10)\n",
    "    cb.set_label(datalabel)\n",
    "\n",
    "    plt.tight_layout()\n",
    "    \n",
    "    plt.savefig('.\\\\9장_data\\\\' + 'blockMap_' + targetData + '.png')\n",
    "                      \n",
    "    \n",
    "    plt.show()      "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###   (7) 함수를 호출하여 블록맵 생성하기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#####     - 행정구역별 인구에 대한 의료기관 수에 대한 블록맵"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/m0/5pqtbll13p97hjn1mqvl1mwh0000gn/T/ipykernel_3311/770551840.py:14: MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and pcolormesh() is deprecated since 3.5 and will be removed two minor releases later; please call grid(False) first.\n",
      "  plt.pcolor(masked_mapdata, vmin=vmin, vmax=vmax, cmap=color, edgecolor='#aaaaaa', linewidth=0.5)\n",
      "/var/folders/m0/5pqtbll13p97hjn1mqvl1mwh0000gn/T/ipykernel_3311/770551840.py:47: MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and pcolormesh() is deprecated since 3.5 and will be removed two minor releases later; please call grid(False) first.\n",
      "  cb = plt.colorbar(shrink=.1, aspect=10)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x936 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_blockMap(data_draw_korea_MC_Population_all, 'count', '행정구역별 공공보건의료기관 수', 'Blues')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#####     - 행정구역별 인구에 대한 의료기관 비율에 대한 블록맵"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/m0/5pqtbll13p97hjn1mqvl1mwh0000gn/T/ipykernel_3311/770551840.py:14: MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and pcolormesh() is deprecated since 3.5 and will be removed two minor releases later; please call grid(False) first.\n",
      "  plt.pcolor(masked_mapdata, vmin=vmin, vmax=vmax, cmap=color, edgecolor='#aaaaaa', linewidth=0.5)\n",
      "/var/folders/m0/5pqtbll13p97hjn1mqvl1mwh0000gn/T/ipykernel_3311/770551840.py:47: MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and pcolormesh() is deprecated since 3.5 and will be removed two minor releases later; please call grid(False) first.\n",
      "  cb = plt.colorbar(shrink=.1, aspect=10)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x936 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_blockMap(data_draw_korea_MC_Population_all, 'MC_ratio', '행정구역별 인구수 대비 공공보건의료기관 비율', 'Reds' )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}