geopy_test2_공공의료기관 시각화.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ! pip install geopy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from geopy.geocoders import Nominatim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>연번</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",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\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>1</th>\n",
       "      <td>2</td>\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>2</th>\n",
       "      <td>3</td>\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>3</th>\n",
       "      <td>4</td>\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>4</th>\n",
       "      <td>5</td>\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",
       "    <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",
       "      <td>...</td>\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>222</th>\n",
       "      <td>216</td>\n",
       "      <td>청풍호노인사랑병원</td>\n",
       "      <td>시군구립</td>\n",
       "      <td>제천시 노인전문병원 설치및 운영에 관한 조례</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>해당없음</td>\n",
       "      <td>33280576</td>\n",
       "      <td>요양병원</td>\n",
       "      <td>187</td>\n",
       "      <td>27207</td>\n",
       "      <td>충청북도 제천시 금성면 청풍호로 1147</td>\n",
       "      <td>www.cplove.co.kr</td>\n",
       "      <td>043-646-0808</td>\n",
       "      <td>043-648-5827</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>217</td>\n",
       "      <td>충주시 노인전문병원</td>\n",
       "      <td>시군구립</td>\n",
       "      <td>충주시노인전문병원설치 및 운영에관한 조례</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>해당없음</td>\n",
       "      <td>33280088</td>\n",
       "      <td>요양병원</td>\n",
       "      <td>300</td>\n",
       "      <td>27442</td>\n",
       "      <td>충청북도 충주시 동량면 대전리 1686-28</td>\n",
       "      <td>www.hyolife.com</td>\n",
       "      <td>043-855-9393</td>\n",
       "      <td>043-855-8866</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>218</td>\n",
       "      <td>충청북도 충주의료원</td>\n",
       "      <td>특수법인</td>\n",
       "      <td>지방의료원의 설립 및 운영에 관한 법률</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>해당없음</td>\n",
       "      <td>33100063</td>\n",
       "      <td>종합병원</td>\n",
       "      <td>292</td>\n",
       "      <td>27468</td>\n",
       "      <td>충청북도 충주시 안림로 239-50(안림동 134)</td>\n",
       "      <td>www.cjmct.or.kr</td>\n",
       "      <td>043-871-0114</td>\n",
       "      <td>043-843-4231</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>219</td>\n",
       "      <td>영동군립노인전문병원</td>\n",
       "      <td>시군구립</td>\n",
       "      <td>영동군립노인전문병원설치 및    운영조례</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>해당없음</td>\n",
       "      <td>33280681</td>\n",
       "      <td>요양병원</td>\n",
       "      <td>120</td>\n",
       "      <td>29131</td>\n",
       "      <td>충청북도 영동군 영동읍 대학로 290</td>\n",
       "      <td>cmisilveryd.com</td>\n",
       "      <td>043-744-9633</td>\n",
       "      <td>043-742-8275</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>220</td>\n",
       "      <td>단양군노인요양전문병원</td>\n",
       "      <td>시군구립</td>\n",
       "      <td>단양군립노인전문병원설치 및    운영조례</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>해당없음</td>\n",
       "      <td>33280207</td>\n",
       "      <td>요양병원</td>\n",
       "      <td>105</td>\n",
       "      <td>27010</td>\n",
       "      <td>충청북도 단양군 단양읍 별곡6길 10</td>\n",
       "      <td>없음</td>\n",
       "      <td>043-423-8844</td>\n",
       "      <td>043-423-8874</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>227 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      연번         병원 명  설립형태                     근거 법령     관계 행정기관 관계 공공단체  \\\n",
       "0      1     강원도 재활병원   시도립         강원도재활병원설치및운영에관한조례         강원도    해당없음   \n",
       "1      2    강원도 삼척의료원  특수법인     지방의료원의 설립 및 운영에 관한 법률  보건복지부(강원도)   지방의료원   \n",
       "2      3    강원도 영월의료원  특수법인     지방의료원의 설립 및 운영에 관한 법률  보건복지부(강원도)   지방의료원   \n",
       "3      4    강원도 원주의료원  특수법인     지방의료원의 설립 및 운영에 관한 법률  보건복지부(강원도)   지방의료원   \n",
       "4      5    강원도 강릉의료원  특수법인     지방의료원의 설립 및 운영에 관한 법률  보건복지부(강원도)   지방의료원   \n",
       "..   ...          ...   ...                       ...         ...     ...   \n",
       "222  216    청풍호노인사랑병원  시군구립  제천시 노인전문병원 설치및 운영에 관한 조례        충청북도    해당없음   \n",
       "223  217   충주시 노인전문병원  시군구립    충주시노인전문병원설치 및 운영에관한 조례        충청북도    해당없음   \n",
       "224  218   충청북도 충주의료원  특수법인     지방의료원의 설립 및 운영에 관한 법률        충청북도    해당없음   \n",
       "225  219   영동군립노인전문병원  시군구립    영동군립노인전문병원설치 및    운영조례        충청북도    해당없음   \n",
       "226  220  단양군노인요양전문병원  시군구립    단양군립노인전문병원설치 및    운영조례        충청북도    해당없음   \n",
       "\n",
       "     심평원 요양기관번호  종별구분  병상수 소재지 우편번호                            주소  \\\n",
       "0      32200641    병원  165    24227       강원도 춘천시 충열로 142번길 24-16   \n",
       "1      32100060  종합병원  152    25920              강원도 삼척시 오십천로 418   \n",
       "2      32100078  종합병원  214    26234           강원도 영월군 영월읍 중앙1로 59   \n",
       "3      32100086  종합병원  237    26448         강원도 원주시 서원대로 387(개운동)   \n",
       "4      32100159  종합병원  137    25535   강원도 강릉시 경강로 2007(남문동 164-1)   \n",
       "..          ...   ...  ...      ...                           ...   \n",
       "222    33280576  요양병원  187    27207        충청북도 제천시 금성면 청풍호로 1147   \n",
       "223    33280088  요양병원  300    27442      충청북도 충주시 동량면 대전리 1686-28   \n",
       "224    33100063  종합병원  292    27468  충청북도 충주시 안림로 239-50(안림동 134)   \n",
       "225    33280681  요양병원  120    29131          충청북도 영동군 영동읍 대학로 290   \n",
       "226    33280207  요양병원  105    27010          충청북도 단양군 단양읍 별곡6길 10   \n",
       "\n",
       "                        홈페이지          대표전화           FAX   비고  \n",
       "0              www.grh.or.kr  033-248-7700  033-248-7723  NaN  \n",
       "1          http://ksmc.or.kr  033-572-1141  033-573-8424  NaN  \n",
       "2    http://www.youngwol.org  033-370-9117  033-370-9137  NaN  \n",
       "3             www.kwmc.or.kr  033-760-4500  033-761-5121  NaN  \n",
       "4      http://www.gnmc.or.kr  033-646-6910  033-610-1415  NaN  \n",
       "..                       ...           ...           ...  ...  \n",
       "222         www.cplove.co.kr  043-646-0808  043-648-5827  NaN  \n",
       "223          www.hyolife.com  043-855-9393  043-855-8866  NaN  \n",
       "224          www.cjmct.or.kr  043-871-0114  043-843-4231  NaN  \n",
       "225          cmisilveryd.com  043-744-9633  043-742-8275  NaN  \n",
       "226                       없음  043-423-8844  043-423-8874  NaN  \n",
       "\n",
       "[227 rows x 15 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=pd.read_csv('data/보건복지부_공공보건 의료기관 현황_20161231.csv')\n",
    "data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>제천시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>영동군</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>단양군</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>227 rows × 2 columns</p>\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\n",
       "..    ...  ...\n",
       "222  충청북도  제천시\n",
       "223  충청북도  충주시\n",
       "224  충청북도  충주시\n",
       "225  충청북도  영동군\n",
       "226  충청북도  단양군\n",
       "\n",
       "[227 rows x 2 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr=pd.DataFrame(data['주소'].apply(lambda v: v.split()[:2]).tolist(),columns=('시도','군구'))\n",
    "addr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr['시도'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr[addr['시도']=='창원시']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['강원도', '경기도', '경기', '경남', '경상남도', '경상북도', '경산시', '경북', '인천광역시',\n",
       "       '대구광역시', '전라남도', '대전광역시', '광주광역시', '제주특별자치도', '부산광역시', '전라북도',\n",
       "       '충북', '서울특별시', '서울시', '부산특별시', '대전시', '충남', '전남', '충청남도', '울산광역시',\n",
       "       '전북', '천안시', '충청북도'], dtype=object)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr.iloc[27]=['경상남도','창원시']\n",
    "addr.iloc[31]=['경상남도','창원시']\n",
    "addr['시도'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>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": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr[addr['시도']=='경산시']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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",
       "       '천안시', '충청북도'], dtype=object)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr.iloc[47]=['경상북도','경산시']\n",
    "addr['시도'].unique()"
   ]
  },
  {
   "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",
       "    </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": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr[addr['시도']=='천안시']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr.iloc[209]=['충청남도','천안시']\n",
    "addr.iloc[210]=['충청남도','천안시']\n",
    "addr['시도'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr_aliases={'서울':'서울특별시', '서울시':'서울특별시', '경기':'경기도','경남':'경상남도','경북':'경상북도','충북':'충청북도','부산특별시':'부산광역시','대전시':'대전광역시','충남':'충청남도','전남':'전라남도','전북':'전라북도'}\n",
    "addr['시도']=addr['시도'].apply(lambda v: addr_aliases.get(v, v))\n",
    "addr['시도'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr['군구'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         시도     군구\n",
      "75  제주특별자치도  아란13길\n",
      "        시도   군구\n",
      "155  부산광역시  동매로\n"
     ]
    }
   ],
   "source": [
    "print(addr[addr['군구']=='아란13길'])\n",
    "print(addr[addr['군구']=='동매로'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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",
       "       '사하구', '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": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr.iloc[75]=['제주특별자치도','제주시']\n",
    "addr.iloc[155]=['부산광역시','사하구']\n",
    "addr['군구'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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",
       "      <th>count</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",
       "      <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",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>제천시</td>\n",
       "      <td>충청북도 제천시</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "      <td>충청북도 충주시</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "      <td>충청북도 충주시</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>영동군</td>\n",
       "      <td>충청북도 영동군</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>단양군</td>\n",
       "      <td>충청북도 단양군</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>227 rows × 4 columns</p>\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\n",
       "..    ...  ...       ...    ...\n",
       "222  충청북도  제천시  충청북도 제천시      0\n",
       "223  충청북도  충주시  충청북도 충주시      0\n",
       "224  충청북도  충주시  충청북도 충주시      0\n",
       "225  충청북도  영동군  충청북도 영동군      0\n",
       "226  충청북도  단양군  충청북도 단양군      0\n",
       "\n",
       "[227 rows x 4 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr['시도군구']=addr.apply(lambda r: r['시도']+' '+r['군구'], axis=1)\n",
    "addr['count']=0\n",
    "addr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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",
       "      <th>count</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",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>강원도</td>\n",
       "      <td>춘천시</td>\n",
       "      <td>강원도 춘천시</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>강원도</td>\n",
       "      <td>춘천시</td>\n",
       "      <td>강원도 춘천시</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>강원도</td>\n",
       "      <td>춘천시</td>\n",
       "      <td>강원도 춘천시</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>강원도</td>\n",
       "      <td>춘천시</td>\n",
       "      <td>강원도 춘천시</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",
       "6    강원도  춘천시  강원도 춘천시      0\n",
       "69   강원도  춘천시  강원도 춘천시      0\n",
       "105  강원도  춘천시  강원도 춘천시      0\n",
       "142  강원도  춘천시  강원도 춘천시      0"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr.loc[addr['시도군구']=='강원도 춘천시']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>영동군</td>\n",
       "      <td>충청북도 영동군</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>제천시</td>\n",
       "      <td>충청북도 제천시</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>청원군</td>\n",
       "      <td>충청북도 청원군</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>청주시</td>\n",
       "      <td>충청북도 청주시</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "      <td>충청북도 충주시</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>140 rows × 4 columns</p>\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\n",
       "..    ...  ...       ...    ...\n",
       "135  충청북도  영동군  충청북도 영동군      1\n",
       "136  충청북도  제천시  충청북도 제천시      1\n",
       "137  충청북도  청원군  충청북도 청원군      1\n",
       "138  충청북도  청주시  충청북도 청주시      4\n",
       "139  충청북도  충주시  충청북도 충주시      2\n",
       "\n",
       "[140 rows x 4 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr_group=pd.DataFrame(addr.groupby(['시도','군구','시도군구'], as_index=False).count())\n",
    "addr_group"
   ]
  },
  {
   "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>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",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 영동군</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>영동군</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 제천시</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>제천시</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 청원군</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>청원군</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 청주시</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>청주시</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 충주시</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>140 rows × 3 columns</p>\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\n",
       "...        ...  ...    ...\n",
       "충청북도 영동군  충청북도  영동군      1\n",
       "충청북도 제천시  충청북도  제천시      1\n",
       "충청북도 청원군  충청북도  청원군      1\n",
       "충청북도 청주시  충청북도  청주시      4\n",
       "충청북도 충주시  충청북도  충주시      2\n",
       "\n",
       "[140 rows x 3 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr_group=addr_group.set_index('시도군구')\n",
    "addr_group"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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>행정구역시도</th>\n",
       "      <th>행정구역군구</th>\n",
       "      <th>총인구수</th>\n",
       "      <th>남자인구수</th>\n",
       "      <th>여자인구수</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>전국</td>\n",
       "      <td>소계</td>\n",
       "      <td>51392745</td>\n",
       "      <td>25607244</td>\n",
       "      <td>25785501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>소계</td>\n",
       "      <td>9414093</td>\n",
       "      <td>4557609</td>\n",
       "      <td>4856484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>종로구</td>\n",
       "      <td>140397</td>\n",
       "      <td>67834</td>\n",
       "      <td>72563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>중구</td>\n",
       "      <td>121441</td>\n",
       "      <td>58857</td>\n",
       "      <td>62584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>용산구</td>\n",
       "      <td>217288</td>\n",
       "      <td>104357</td>\n",
       "      <td>112931</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  행정구역시도 행정구역군구      총인구수     남자인구수     여자인구수\n",
       "0     전국     소계  51392745  25607244  25785501\n",
       "1  서울특별시     소계   9414093   4557609   4856484\n",
       "2  서울특별시    종로구    140397     67834     72563\n",
       "3  서울특별시     중구    121441     58857     62584\n",
       "4  서울특별시    용산구    217288    104357    112931"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population=pd.read_csv('data/행정구역_시군구_별__성별_인구수_20230717102236.csv')\n",
    "population.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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>총인구수</th>\n",
       "      <th>남자</th>\n",
       "      <th>여자</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>전국</td>\n",
       "      <td>소계</td>\n",
       "      <td>51392745</td>\n",
       "      <td>25607244</td>\n",
       "      <td>25785501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>소계</td>\n",
       "      <td>9414093</td>\n",
       "      <td>4557609</td>\n",
       "      <td>4856484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>종로구</td>\n",
       "      <td>140397</td>\n",
       "      <td>67834</td>\n",
       "      <td>72563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>중구</td>\n",
       "      <td>121441</td>\n",
       "      <td>58857</td>\n",
       "      <td>62584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>용산구</td>\n",
       "      <td>217288</td>\n",
       "      <td>104357</td>\n",
       "      <td>112931</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      시도   군구      총인구수        남자        여자\n",
       "0     전국   소계  51392745  25607244  25785501\n",
       "1  서울특별시   소계   9414093   4557609   4856484\n",
       "2  서울특별시  종로구    140397     67834     72563\n",
       "3  서울특별시   중구    121441     58857     62584\n",
       "4  서울특별시  용산구    217288    104357    112931"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population=population.rename(columns={'행정구역시도':'시도','행정구역군구':'군구','남자인구수':'남자','여자인구수':'여자'})\n",
    "population.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['전국', '서울특별시', '부산광역시', '대구광역시', '인천광역시', '광주광역시', '대전광역시',\n",
       "       '울산광역시', '세종특별자치시', '경기도', '강원도', '충청북도', '충청남도', '전라북도', '전라남도',\n",
       "       '경상북도', '경상남도', '제주특별자치도'], dtype=object)"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population['시도'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['소계', '종로구', '중구', '용산구', '성동구', '광진구', '동대문구', '중랑구', '성북구',\n",
       "       '강북구', '도봉구', '노원구', '은평구', '서대문구', '마포구', '양천구', '강서구', '구로구',\n",
       "       '금천구', '영등포구', '동작구', '관악구', '서초구', '강남구', '송파구', '강동구', '서구',\n",
       "       '동구', '영도구', '부산진구', '동래구', '남구', '북구', '해운대구', '사하구', '금정구',\n",
       "       '연제구', '수영구', '사상구', '기장군', '수성구', '달서구', '달성군', '미추홀구', '연수구',\n",
       "       '남동구', '부평구', '계양구', '강화군', '옹진군', '광산구', '유성구', '대덕구', '울주군',\n",
       "       '세종시', '수원시', '장안구', '권선구', '팔달구', '영통구', '성남시', '수정구', '중원구',\n",
       "       '분당구', '의정부시', '안양시', '만안구', '동안구', '부천시', '광명시', '평택시', '동두천시',\n",
       "       '안산시', '상록구', '단원구', '고양시', '덕양구', '일산동구', '일산서구', '과천시', '구리시',\n",
       "       '남양주시', '오산시', '시흥시', '군포시', '의왕시', '하남시', '용인시', '처인구', '기흥구',\n",
       "       '수지구', '파주시', '이천시', '안성시', '김포시', '화성시', '광주시', '양주시', '포천시',\n",
       "       '여주시', '연천군', '가평군', '양평군', '춘천시', '원주시', '강릉시', '동해시', '태백시',\n",
       "       '속초시', '삼척시', '홍천군', '횡성군', '영월군', '평창군', '정선군', '철원군', '화천군',\n",
       "       '양구군', '인제군', '고성군', '양양군', '청주시', '서원구', '청원구', '상당구', '흥덕구',\n",
       "       '충주시', '제천시', '보은군', '옥천군', '영동군', '증평군', '진천군', '괴산군', '음성군',\n",
       "       '단양군', '당진시', '천안시', '동남구', '서북구', '공주시', '보령시', '아산시', '서산시',\n",
       "       '논산시', '계룡시', '금산군', '부여군', '서천군', '청양군', '홍성군', '예산군', '태안군',\n",
       "       '전주시', '완산구', '덕진구', '군산시', '익산시', '정읍시', '남원시', '김제시', '완주군',\n",
       "       '진안군', '무주군', '장수군', '임실군', '순창군', '고창군', '부안군', '목포시', '여수시',\n",
       "       '순천시', '나주시', '광양시', '담양군', '곡성군', '구례군', '고흥군', '보성군', '화순군',\n",
       "       '장흥군', '강진군', '해남군', '영암군', '무안군', '함평군', '영광군', '장성군', '완도군',\n",
       "       '진도군', '신안군', '포항시', '경주시', '김천시', '안동시', '구미시', '영주시', '영천시',\n",
       "       '상주시', '문경시', '경산시', '군위군', '의성군', '청송군', '영양군', '영덕군', '청도군',\n",
       "       '고령군', '성주군', '칠곡군', '예천군', '봉화군', '울진군', '울릉군', '창원시', '의창구',\n",
       "       '성산구', '마산합포구', '마산회원구', '진해구', '진주시', '통영시', '사천시', '김해시', '밀양시',\n",
       "       '거제시', '양산시', '의령군', '함안군', '창녕군', '남해군', '하동군', '산청군', '함양군',\n",
       "       '거창군', '합천군', '제주시', '서귀포시'], dtype=object)"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population['군구'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "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>총인구수</th>\n",
       "      <th>남자</th>\n",
       "      <th>여자</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>140397</td>\n",
       "      <td>67834</td>\n",
       "      <td>72563</td>\n",
       "      <td>서울특별시 종로구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>중구</td>\n",
       "      <td>121441</td>\n",
       "      <td>58857</td>\n",
       "      <td>62584</td>\n",
       "      <td>서울특별시 중구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>용산구</td>\n",
       "      <td>217288</td>\n",
       "      <td>104357</td>\n",
       "      <td>112931</td>\n",
       "      <td>서울특별시 용산구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>성동구</td>\n",
       "      <td>279374</td>\n",
       "      <td>135723</td>\n",
       "      <td>143651</td>\n",
       "      <td>서울특별시 성동구</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>광진구</td>\n",
       "      <td>336169</td>\n",
       "      <td>161755</td>\n",
       "      <td>174414</td>\n",
       "      <td>서울특별시 광진구</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>273</th>\n",
       "      <td>경상남도</td>\n",
       "      <td>함양군</td>\n",
       "      <td>37294</td>\n",
       "      <td>18105</td>\n",
       "      <td>19189</td>\n",
       "      <td>경상남도 함양군</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>274</th>\n",
       "      <td>경상남도</td>\n",
       "      <td>거창군</td>\n",
       "      <td>60356</td>\n",
       "      <td>29704</td>\n",
       "      <td>30652</td>\n",
       "      <td>경상남도 거창군</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>275</th>\n",
       "      <td>경상남도</td>\n",
       "      <td>합천군</td>\n",
       "      <td>41741</td>\n",
       "      <td>20339</td>\n",
       "      <td>21402</td>\n",
       "      <td>경상남도 합천군</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>277</th>\n",
       "      <td>제주특별자치도</td>\n",
       "      <td>제주시</td>\n",
       "      <td>492546</td>\n",
       "      <td>246132</td>\n",
       "      <td>246414</td>\n",
       "      <td>제주특별자치도 제주시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>278</th>\n",
       "      <td>제주특별자치도</td>\n",
       "      <td>서귀포시</td>\n",
       "      <td>184286</td>\n",
       "      <td>92725</td>\n",
       "      <td>91561</td>\n",
       "      <td>제주특별자치도 서귀포시</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>261 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          시도    군구    총인구수      남자      여자          시도군구\n",
       "2      서울특별시   종로구  140397   67834   72563     서울특별시 종로구\n",
       "3      서울특별시    중구  121441   58857   62584      서울특별시 중구\n",
       "4      서울특별시   용산구  217288  104357  112931     서울특별시 용산구\n",
       "5      서울특별시   성동구  279374  135723  143651     서울특별시 성동구\n",
       "6      서울특별시   광진구  336169  161755  174414     서울특별시 광진구\n",
       "..       ...   ...     ...     ...     ...           ...\n",
       "273     경상남도   함양군   37294   18105   19189      경상남도 함양군\n",
       "274     경상남도   거창군   60356   29704   30652      경상남도 거창군\n",
       "275     경상남도   합천군   41741   20339   21402      경상남도 합천군\n",
       "277  제주특별자치도   제주시  492546  246132  246414   제주특별자치도 제주시\n",
       "278  제주특별자치도  서귀포시  184286   92725   91561  제주특별자치도 서귀포시\n",
       "\n",
       "[261 rows x 6 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population['시도군구']=population.apply(lambda r: r['시도']+' '+r['군구'], axis=1)\n",
    "population=population[population.군구 !='소계']\n",
    "population"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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>총인구수</th>\n",
       "      <th>남자</th>\n",
       "      <th>여자</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>140397</td>\n",
       "      <td>67834</td>\n",
       "      <td>72563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>서울특별시 중구</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>중구</td>\n",
       "      <td>121441</td>\n",
       "      <td>58857</td>\n",
       "      <td>62584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>서울특별시 용산구</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>용산구</td>\n",
       "      <td>217288</td>\n",
       "      <td>104357</td>\n",
       "      <td>112931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>서울특별시 성동구</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>성동구</td>\n",
       "      <td>279374</td>\n",
       "      <td>135723</td>\n",
       "      <td>143651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>서울특별시 광진구</th>\n",
       "      <td>서울특별시</td>\n",
       "      <td>광진구</td>\n",
       "      <td>336169</td>\n",
       "      <td>161755</td>\n",
       "      <td>174414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>경상남도 함양군</th>\n",
       "      <td>경상남도</td>\n",
       "      <td>함양군</td>\n",
       "      <td>37294</td>\n",
       "      <td>18105</td>\n",
       "      <td>19189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>경상남도 거창군</th>\n",
       "      <td>경상남도</td>\n",
       "      <td>거창군</td>\n",
       "      <td>60356</td>\n",
       "      <td>29704</td>\n",
       "      <td>30652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>경상남도 합천군</th>\n",
       "      <td>경상남도</td>\n",
       "      <td>합천군</td>\n",
       "      <td>41741</td>\n",
       "      <td>20339</td>\n",
       "      <td>21402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>제주특별자치도 제주시</th>\n",
       "      <td>제주특별자치도</td>\n",
       "      <td>제주시</td>\n",
       "      <td>492546</td>\n",
       "      <td>246132</td>\n",
       "      <td>246414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>제주특별자치도 서귀포시</th>\n",
       "      <td>제주특별자치도</td>\n",
       "      <td>서귀포시</td>\n",
       "      <td>184286</td>\n",
       "      <td>92725</td>\n",
       "      <td>91561</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>261 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   시도    군구    총인구수      남자      여자\n",
       "시도군구                                               \n",
       "서울특별시 종로구       서울특별시   종로구  140397   67834   72563\n",
       "서울특별시 중구        서울특별시    중구  121441   58857   62584\n",
       "서울특별시 용산구       서울특별시   용산구  217288  104357  112931\n",
       "서울특별시 성동구       서울특별시   성동구  279374  135723  143651\n",
       "서울특별시 광진구       서울특별시   광진구  336169  161755  174414\n",
       "...               ...   ...     ...     ...     ...\n",
       "경상남도 함양군         경상남도   함양군   37294   18105   19189\n",
       "경상남도 거창군         경상남도   거창군   60356   29704   30652\n",
       "경상남도 합천군         경상남도   합천군   41741   20339   21402\n",
       "제주특별자치도 제주시   제주특별자치도   제주시  492546  246132  246414\n",
       "제주특별자치도 서귀포시  제주특별자치도  서귀포시  184286   92725   91561\n",
       "\n",
       "[261 rows x 5 columns]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population=population.set_index('시도군구')\n",
    "population"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2개 데이터 테이블 병합하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>시도</th>\n",
       "      <th>군구</th>\n",
       "      <th>count</th>\n",
       "      <th>총인구수</th>\n",
       "      <th>남자</th>\n",
       "      <th>여자</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>4</td>\n",
       "      <td>210456</td>\n",
       "      <td>104324</td>\n",
       "      <td>106132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>강원도</td>\n",
       "      <td>동해시</td>\n",
       "      <td>1</td>\n",
       "      <td>89058</td>\n",
       "      <td>45253</td>\n",
       "      <td>43805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "      <td>1</td>\n",
       "      <td>63270</td>\n",
       "      <td>32093</td>\n",
       "      <td>31177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "      <td>1</td>\n",
       "      <td>82474</td>\n",
       "      <td>40873</td>\n",
       "      <td>41601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>강원도</td>\n",
       "      <td>양구군</td>\n",
       "      <td>1</td>\n",
       "      <td>21315</td>\n",
       "      <td>11197</td>\n",
       "      <td>10118</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>단양군</td>\n",
       "      <td>1</td>\n",
       "      <td>27699</td>\n",
       "      <td>14096</td>\n",
       "      <td>13603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>영동군</td>\n",
       "      <td>1</td>\n",
       "      <td>44617</td>\n",
       "      <td>22353</td>\n",
       "      <td>22264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>제천시</td>\n",
       "      <td>1</td>\n",
       "      <td>131231</td>\n",
       "      <td>65990</td>\n",
       "      <td>65241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>청주시</td>\n",
       "      <td>4</td>\n",
       "      <td>850168</td>\n",
       "      <td>429590</td>\n",
       "      <td>420578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "      <td>2</td>\n",
       "      <td>207893</td>\n",
       "      <td>105400</td>\n",
       "      <td>102493</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>139 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       시도   군구  count    총인구수      남자      여자\n",
       "0     강원도  강릉시      4  210456  104324  106132\n",
       "1     강원도  동해시      1   89058   45253   43805\n",
       "2     강원도  삼척시      1   63270   32093   31177\n",
       "3     강원도  속초시      1   82474   40873   41601\n",
       "4     강원도  양구군      1   21315   11197   10118\n",
       "..    ...  ...    ...     ...     ...     ...\n",
       "134  충청북도  단양군      1   27699   14096   13603\n",
       "135  충청북도  영동군      1   44617   22353   22264\n",
       "136  충청북도  제천시      1  131231   65990   65241\n",
       "137  충청북도  청주시      4  850168  429590  420578\n",
       "138  충청북도  충주시      2  207893  105400  102493\n",
       "\n",
       "[139 rows x 6 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr_poplulation=pd.merge(addr_group,population,how='inner')\n",
    "addr_poplulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "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_x</th>\n",
       "      <th>군구_x</th>\n",
       "      <th>count</th>\n",
       "      <th>시도_y</th>\n",
       "      <th>군구_y</th>\n",
       "      <th>총인구수</th>\n",
       "      <th>남자</th>\n",
       "      <th>여자</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",
       "      <td>강릉시</td>\n",
       "      <td>4</td>\n",
       "      <td>강원도</td>\n",
       "      <td>강릉시</td>\n",
       "      <td>210456</td>\n",
       "      <td>104324</td>\n",
       "      <td>106132</td>\n",
       "    </tr>\n",
       "    <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>89058</td>\n",
       "      <td>45253</td>\n",
       "      <td>43805</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>63270</td>\n",
       "      <td>32093</td>\n",
       "      <td>31177</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>82474</td>\n",
       "      <td>40873</td>\n",
       "      <td>41601</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>21315</td>\n",
       "      <td>11197</td>\n",
       "      <td>10118</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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 단양군</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>단양군</td>\n",
       "      <td>1</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>단양군</td>\n",
       "      <td>27699</td>\n",
       "      <td>14096</td>\n",
       "      <td>13603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 영동군</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>영동군</td>\n",
       "      <td>1</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>영동군</td>\n",
       "      <td>44617</td>\n",
       "      <td>22353</td>\n",
       "      <td>22264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 제천시</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>제천시</td>\n",
       "      <td>1</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>제천시</td>\n",
       "      <td>131231</td>\n",
       "      <td>65990</td>\n",
       "      <td>65241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 청주시</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>청주시</td>\n",
       "      <td>4</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>청주시</td>\n",
       "      <td>850168</td>\n",
       "      <td>429590</td>\n",
       "      <td>420578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 충주시</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "      <td>2</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "      <td>207893</td>\n",
       "      <td>105400</td>\n",
       "      <td>102493</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>139 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          시도_x 군구_x  count  시도_y 군구_y    총인구수      남자      여자\n",
       "시도군구                                                         \n",
       "강원도 강릉시    강원도  강릉시      4   강원도  강릉시  210456  104324  106132\n",
       "강원도 동해시    강원도  동해시      1   강원도  동해시   89058   45253   43805\n",
       "강원도 삼척시    강원도  삼척시      1   강원도  삼척시   63270   32093   31177\n",
       "강원도 속초시    강원도  속초시      1   강원도  속초시   82474   40873   41601\n",
       "강원도 양구군    강원도  양구군      1   강원도  양구군   21315   11197   10118\n",
       "...        ...  ...    ...   ...  ...     ...     ...     ...\n",
       "충청북도 단양군  충청북도  단양군      1  충청북도  단양군   27699   14096   13603\n",
       "충청북도 영동군  충청북도  영동군      1  충청북도  영동군   44617   22353   22264\n",
       "충청북도 제천시  충청북도  제천시      1  충청북도  제천시  131231   65990   65241\n",
       "충청북도 청주시  충청북도  청주시      4  충청북도  청주시  850168  429590  420578\n",
       "충청북도 충주시  충청북도  충주시      2  충청북도  충주시  207893  105400  102493\n",
       "\n",
       "[139 rows x 8 columns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr_poplulation=pd.merge(addr_group,population,how='inner', left_index=True, right_index=True)\n",
    "addr_poplulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "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_x</th>\n",
       "      <th>군구_x</th>\n",
       "      <th>count</th>\n",
       "      <th>총인구수</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>210456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 동해시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>동해시</td>\n",
       "      <td>1</td>\n",
       "      <td>89058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 삼척시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "      <td>1</td>\n",
       "      <td>63270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 속초시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "      <td>1</td>\n",
       "      <td>82474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 양구군</th>\n",
       "      <td>강원도</td>\n",
       "      <td>양구군</td>\n",
       "      <td>1</td>\n",
       "      <td>21315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 단양군</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>단양군</td>\n",
       "      <td>1</td>\n",
       "      <td>27699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 영동군</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>영동군</td>\n",
       "      <td>1</td>\n",
       "      <td>44617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 제천시</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>제천시</td>\n",
       "      <td>1</td>\n",
       "      <td>131231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 청주시</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>청주시</td>\n",
       "      <td>4</td>\n",
       "      <td>850168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 충주시</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "      <td>2</td>\n",
       "      <td>207893</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>139 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          시도_x 군구_x  count    총인구수\n",
       "시도군구                              \n",
       "강원도 강릉시    강원도  강릉시      4  210456\n",
       "강원도 동해시    강원도  동해시      1   89058\n",
       "강원도 삼척시    강원도  삼척시      1   63270\n",
       "강원도 속초시    강원도  속초시      1   82474\n",
       "강원도 양구군    강원도  양구군      1   21315\n",
       "...        ...  ...    ...     ...\n",
       "충청북도 단양군  충청북도  단양군      1   27699\n",
       "충청북도 영동군  충청북도  영동군      1   44617\n",
       "충청북도 제천시  충청북도  제천시      1  131231\n",
       "충청북도 청주시  충청북도  청주시      4  850168\n",
       "충청북도 충주시  충청북도  충주시      2  207893\n",
       "\n",
       "[139 rows x 4 columns]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr_population2=addr_poplulation[['시도_x','군구_x','count','총인구수']]\n",
    "addr_population2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "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>210456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 동해시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>동해시</td>\n",
       "      <td>1</td>\n",
       "      <td>89058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 삼척시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "      <td>1</td>\n",
       "      <td>63270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 속초시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "      <td>1</td>\n",
       "      <td>82474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 양구군</th>\n",
       "      <td>강원도</td>\n",
       "      <td>양구군</td>\n",
       "      <td>1</td>\n",
       "      <td>21315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 단양군</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>단양군</td>\n",
       "      <td>1</td>\n",
       "      <td>27699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 영동군</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>영동군</td>\n",
       "      <td>1</td>\n",
       "      <td>44617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 제천시</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>제천시</td>\n",
       "      <td>1</td>\n",
       "      <td>131231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 청주시</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>청주시</td>\n",
       "      <td>4</td>\n",
       "      <td>850168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 충주시</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "      <td>2</td>\n",
       "      <td>207893</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>139 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            시도   군구  count     인구수\n",
       "시도군구                              \n",
       "강원도 강릉시    강원도  강릉시      4  210456\n",
       "강원도 동해시    강원도  동해시      1   89058\n",
       "강원도 삼척시    강원도  삼척시      1   63270\n",
       "강원도 속초시    강원도  속초시      1   82474\n",
       "강원도 양구군    강원도  양구군      1   21315\n",
       "...        ...  ...    ...     ...\n",
       "충청북도 단양군  충청북도  단양군      1   27699\n",
       "충청북도 영동군  충청북도  영동군      1   44617\n",
       "충청북도 제천시  충청북도  제천시      1  131231\n",
       "충청북도 청주시  충청북도  청주시      4  850168\n",
       "충청북도 충주시  충청북도  충주시      2  207893\n",
       "\n",
       "[139 rows x 4 columns]"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "addr_population2=addr_population2.rename(columns={'시도_x':'시도','군구_x':'군구','총인구수':'인구수'})\n",
    "addr_population2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "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>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>210456</td>\n",
       "      <td>1.900635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 동해시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>동해시</td>\n",
       "      <td>1</td>\n",
       "      <td>89058</td>\n",
       "      <td>1.122864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 삼척시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>삼척시</td>\n",
       "      <td>1</td>\n",
       "      <td>63270</td>\n",
       "      <td>1.580528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 속초시</th>\n",
       "      <td>강원도</td>\n",
       "      <td>속초시</td>\n",
       "      <td>1</td>\n",
       "      <td>82474</td>\n",
       "      <td>1.212503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>강원도 양구군</th>\n",
       "      <td>강원도</td>\n",
       "      <td>양구군</td>\n",
       "      <td>1</td>\n",
       "      <td>21315</td>\n",
       "      <td>4.691532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 단양군</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>단양군</td>\n",
       "      <td>1</td>\n",
       "      <td>27699</td>\n",
       "      <td>3.610239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 영동군</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>영동군</td>\n",
       "      <td>1</td>\n",
       "      <td>44617</td>\n",
       "      <td>2.241298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 제천시</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>제천시</td>\n",
       "      <td>1</td>\n",
       "      <td>131231</td>\n",
       "      <td>0.762015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 청주시</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>청주시</td>\n",
       "      <td>4</td>\n",
       "      <td>850168</td>\n",
       "      <td>0.470495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 충주시</th>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "      <td>2</td>\n",
       "      <td>207893</td>\n",
       "      <td>0.962033</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>139 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            시도   군구  count     인구수     ratio\n",
       "시도군구                                        \n",
       "강원도 강릉시    강원도  강릉시      4  210456  1.900635\n",
       "강원도 동해시    강원도  동해시      1   89058  1.122864\n",
       "강원도 삼척시    강원도  삼척시      1   63270  1.580528\n",
       "강원도 속초시    강원도  속초시      1   82474  1.212503\n",
       "강원도 양구군    강원도  양구군      1   21315  4.691532\n",
       "...        ...  ...    ...     ...       ...\n",
       "충청북도 단양군  충청북도  단양군      1   27699  3.610239\n",
       "충청북도 영동군  충청북도  영동군      1   44617  2.241298\n",
       "충청북도 제천시  충청북도  제천시      1  131231  0.762015\n",
       "충청북도 청주시  충청북도  청주시      4  850168  0.470495\n",
       "충청북도 충주시  충청북도  충주시      2  207893  0.962033\n",
       "\n",
       "[139 rows x 5 columns]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "counts=addr_population2['count']\n",
    "addr_population2['ratio']=counts.divide(addr_population2['인구수'],axis=0)*100000\n",
    "# addr_population2['ratio']=counts/addr_population2['인구수']*100000\n",
    "addr_population2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "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</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",
       "    <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>224</th>\n",
       "      <td>127462</td>\n",
       "      <td>제천</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>882.47</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>제천시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>34480</td>\n",
       "      <td>증평</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "      <td>81.84</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>증평군</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>62809</td>\n",
       "      <td>진천</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>406.08</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>진천군</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>790216</td>\n",
       "      <td>청주</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>932.51</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>청주시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>198077</td>\n",
       "      <td>충주</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>983.70</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>229 rows × 7 columns</p>\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\n",
       "..      ...       ...  ..  ..      ...   ...  ...\n",
       "224  127462        제천   8  10   882.47  충청북도  제천시\n",
       "225   34480        증평   6  11    81.84  충청북도  증평군\n",
       "226   62809        진천   5  11   406.08  충청북도  진천군\n",
       "227  790216        청주   6  12   932.51  충청북도  청주시\n",
       "228  198077        충주   6  10   983.70  충청북도  충주시\n",
       "\n",
       "[229 rows x 7 columns]"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_draw_korea=pd.read_csv('data/data_draw_korea.csv',index_col=0)\n",
    "data_draw_korea"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "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</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",
       "    <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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>127462</td>\n",
       "      <td>제천</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>882.47</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>제천시</td>\n",
       "      <td>충청북도 제천시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>34480</td>\n",
       "      <td>증평</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "      <td>81.84</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>증평군</td>\n",
       "      <td>충청북도 증평군</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>62809</td>\n",
       "      <td>진천</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>406.08</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>진천군</td>\n",
       "      <td>충청북도 진천군</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>790216</td>\n",
       "      <td>청주</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>932.51</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>청주시</td>\n",
       "      <td>충청북도 청주시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>198077</td>\n",
       "      <td>충주</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>983.70</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "      <td>충청북도 충주시</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>229 rows × 8 columns</p>\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\n",
       "..      ...       ...  ..  ..      ...   ...  ...       ...\n",
       "224  127462        제천   8  10   882.47  충청북도  제천시  충청북도 제천시\n",
       "225   34480        증평   6  11    81.84  충청북도  증평군  충청북도 증평군\n",
       "226   62809        진천   5  11   406.08  충청북도  진천군  충청북도 진천군\n",
       "227  790216        청주   6  12   932.51  충청북도  청주시  충청북도 청주시\n",
       "228  198077        충주   6  10   983.70  충청북도  충주시  충청북도 충주시\n",
       "\n",
       "[229 rows x 8 columns]"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_draw_korea['시도군구']=data_draw_korea.apply(lambda r:r['광역시도']+ ' '+ r['행정구역'], axis=1)\n",
    "data_draw_korea"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "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</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",
       "    <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>충청북도 제천시</th>\n",
       "      <td>127462</td>\n",
       "      <td>제천</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>882.47</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>제천시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 증평군</th>\n",
       "      <td>34480</td>\n",
       "      <td>증평</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "      <td>81.84</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>증평군</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 진천군</th>\n",
       "      <td>62809</td>\n",
       "      <td>진천</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>406.08</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>진천군</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 청주시</th>\n",
       "      <td>790216</td>\n",
       "      <td>청주</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>932.51</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>청주시</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 충주시</th>\n",
       "      <td>198077</td>\n",
       "      <td>충주</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>983.70</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>229 rows × 7 columns</p>\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\n",
       "...          ...       ...  ..  ..      ...   ...  ...\n",
       "충청북도 제천시  127462        제천   8  10   882.47  충청북도  제천시\n",
       "충청북도 증평군   34480        증평   6  11    81.84  충청북도  증평군\n",
       "충청북도 진천군   62809        진천   5  11   406.08  충청북도  진천군\n",
       "충청북도 청주시  790216        청주   6  12   932.51  충청북도  청주시\n",
       "충청북도 충주시  198077        충주   6  10   983.70  충청북도  충주시\n",
       "\n",
       "[229 rows x 7 columns]"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_draw_korea=data_draw_korea.set_index('시도군구')\n",
    "data_draw_korea"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "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>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>210456.0</td>\n",
       "      <td>1.900635</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>89058.0</td>\n",
       "      <td>1.122864</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>63270.0</td>\n",
       "      <td>1.580528</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>82474.0</td>\n",
       "      <td>1.212503</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 제천시</th>\n",
       "      <td>127462</td>\n",
       "      <td>제천</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>882.47</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>제천시</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>제천시</td>\n",
       "      <td>1.0</td>\n",
       "      <td>131231.0</td>\n",
       "      <td>0.762015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 증평군</th>\n",
       "      <td>34480</td>\n",
       "      <td>증평</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "      <td>81.84</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>증평군</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>충청북도 진천군</th>\n",
       "      <td>62809</td>\n",
       "      <td>진천</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>406.08</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>진천군</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>충청북도 청주시</th>\n",
       "      <td>790216</td>\n",
       "      <td>청주</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>932.51</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>청주시</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>청주시</td>\n",
       "      <td>4.0</td>\n",
       "      <td>850168.0</td>\n",
       "      <td>0.470495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>충청북도 충주시</th>\n",
       "      <td>198077</td>\n",
       "      <td>충주</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>983.70</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "      <td>충청북도</td>\n",
       "      <td>충주시</td>\n",
       "      <td>2.0</td>\n",
       "      <td>207893.0</td>\n",
       "      <td>0.962033</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>229 rows × 12 columns</p>\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",
       "충청북도 제천시  127462        제천   8  10   882.47  충청북도  제천시  충청북도  제천시    1.0   \n",
       "충청북도 증평군   34480        증평   6  11    81.84  충청북도  증평군   NaN  NaN    NaN   \n",
       "충청북도 진천군   62809        진천   5  11   406.08  충청북도  진천군   NaN  NaN    NaN   \n",
       "충청북도 청주시  790216        청주   6  12   932.51  충청북도  청주시  충청북도  청주시    4.0   \n",
       "충청북도 충주시  198077        충주   6  10   983.70  충청북도  충주시  충청북도  충주시    2.0   \n",
       "\n",
       "             인구수_y     ratio  \n",
       "시도군구                          \n",
       "강원도 강릉시   210456.0  1.900635  \n",
       "강원도 고성군        NaN       NaN  \n",
       "강원도 동해시    89058.0  1.122864  \n",
       "강원도 삼척시    63270.0  1.580528  \n",
       "강원도 속초시    82474.0  1.212503  \n",
       "...            ...       ...  \n",
       "충청북도 제천시  131231.0  0.762015  \n",
       "충청북도 증평군       NaN       NaN  \n",
       "충청북도 진천군       NaN       NaN  \n",
       "충청북도 청주시  850168.0  0.470495  \n",
       "충청북도 충주시  207893.0  0.962033  \n",
       "\n",
       "[229 rows x 12 columns]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_draw_korea_addr_population=pd.merge(data_draw_korea,addr_population2, how='outer', left_index=True, right_index=True)\n",
    "data_draw_korea_addr_population                                       "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "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": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "from matplotlib import rcParams, style\n",
    "style.use('ggplot')\n",
    "from matplotlib import font_manager, rc\n",
    "font_name = font_manager.FontProperties(fname = \"c:/Windows/Fonts/malgun.ttf\").get_name()\n",
    "rc('font', family = font_name)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [],
   "source": [
    "def draw_blockMap(blockedMap, targetData, title, color):\n",
    "    whitelabelmin=(max(blockedMap[targetData]-min(blockedMap[targetData]))*0.25+min(blockedMap[targetData]))\n",
    "    datalabel=targetData\n",
    "    vmin=min(blockedMap[targetData])\n",
    "    vmax=max(blockedMap[targetData])\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(어노테이션 표기 설정)\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 표시\n",
    "        if row['광역시도'].endswith('시') and not row['광역시도'].startswith('세종'):\n",
    "            dispname='{}\\n{}'.format(row['광역시도'][:2], row['행정구역'][:-1])\n",
    "            \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 이상이면 작은 글자로 표시\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 경계를 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",
    "    # plt.savefig('data/blockMap_' + targetData + '.png')\n",
    "    plt.show()\n",
    "                              "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "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('data/blockMap'+'.png')\n",
    "                    \n",
    "    \n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x1300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_blockMap(data_draw_korea_addr_population,'count','행정구역별 공공보건의료기관 수','Blues')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x1300 with 75 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_blockMap(data_draw_korea_addr_population,'ratio','행정구역별 인구수 대비 공공보건의료기관 비율','Reds')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "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": "3.10.9"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}