(Basic)Geospatial_Data_with_Python_1st.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GIS (Geographic Information System or Science)\n",
    "\n",
    "* 지리공간데이터를 생성/편집/저장/분석/시각화하기 위한 모든 Science\n",
    "\n",
    "#### Geographic\n",
    "* 지표상에 있는 모든 지리(地理)적 사상(Feature)\n",
    "\n",
    "#### Information\n",
    "* 디지털화된 데이터\n",
    "\n",
    "#### System / Science\n",
    "* 지리공간데이터를 처리하기 위한 모든 기법/방법"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GeoPandas\n",
    "\n",
    "* `python`으로 지리공간데이터(Geospatial Data)를 다루기 위한 오픈소스 라이브러리\n",
    "* `pandas`를 확장한 라이브러리\n",
    "* `python`에는 다양한 지리공간데이터를 처리할 수 있는 라이브러리들이 존재 (ex:  `GDAL/OGR`, `shapely`, `fiona`, `descrates`)\n",
    "    * `GeoPandas`는 내부적으로 `shapely`, `fiona`, `descrates`, `matplotlib`에 의존"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# GeoPandas설치하기\n",
    "# !pip3 install geopandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# _01 라이브러리 추가하기\n",
    "import geopandas as gpd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reading data\n",
    "- `GeoPandas`는 vector 타입의 대부분 포맷 들을 읽을 수 있습니다.\n",
    "    - `shp`, `geojson`, `GML`, `KML`..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# _02 서울시 행정동 .shp파일\n",
    "file_path = './maps/origin/seoul_h_dong/seoul_h_dong.shp'\n",
    "# file_path = './maps/origin/seoul_h_dong/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# _03 지도 파일을 불러와 GeoDataFrame 생성하기\n",
    "gdf = gpd.read_file(file_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SGG_NM</th>\n",
       "      <th>DONG_NM</th>\n",
       "      <th>SGG_CODE</th>\n",
       "      <th>SEDAE</th>\n",
       "      <th>SEDAE_INGU</th>\n",
       "      <th>TOTAL_POP</th>\n",
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       "      <th>FEMALE_POP</th>\n",
       "      <th>65_OVER</th>\n",
       "      <th>geometry</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>종로구</td>\n",
       "      <td>사직동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4414</td>\n",
       "      <td>2.14</td>\n",
       "      <td>9717</td>\n",
       "      <td>4467</td>\n",
       "      <td>5250</td>\n",
       "      <td>1708</td>\n",
       "      <td>POLYGON ((197958.4491577554 552900.6843211155,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>종로구</td>\n",
       "      <td>삼청동</td>\n",
       "      <td>11110</td>\n",
       "      <td>1414</td>\n",
       "      <td>2.06</td>\n",
       "      <td>3097</td>\n",
       "      <td>1459</td>\n",
       "      <td>1638</td>\n",
       "      <td>634</td>\n",
       "      <td>POLYGON ((198471.2440021661 555055.3898115929,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>종로구</td>\n",
       "      <td>부암동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4325</td>\n",
       "      <td>2.39</td>\n",
       "      <td>10726</td>\n",
       "      <td>5160</td>\n",
       "      <td>5566</td>\n",
       "      <td>1748</td>\n",
       "      <td>POLYGON ((197867.3790096684 555221.862405367, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>종로구</td>\n",
       "      <td>평창동</td>\n",
       "      <td>11110</td>\n",
       "      <td>7510</td>\n",
       "      <td>2.53</td>\n",
       "      <td>19163</td>\n",
       "      <td>9032</td>\n",
       "      <td>10131</td>\n",
       "      <td>3037</td>\n",
       "      <td>POLYGON ((197799.8340111427 559086.752938149, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>종로구</td>\n",
       "      <td>무악동</td>\n",
       "      <td>11110</td>\n",
       "      <td>3024</td>\n",
       "      <td>2.75</td>\n",
       "      <td>8375</td>\n",
       "      <td>3921</td>\n",
       "      <td>4454</td>\n",
       "      <td>1279</td>\n",
       "      <td>POLYGON ((196526.2900434442 553472.4251048469,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>종로구</td>\n",
       "      <td>교남동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4379</td>\n",
       "      <td>2.34</td>\n",
       "      <td>10363</td>\n",
       "      <td>4850</td>\n",
       "      <td>5513</td>\n",
       "      <td>1406</td>\n",
       "      <td>POLYGON ((197265.5793057524 552073.3139507617,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>종로구</td>\n",
       "      <td>가회동</td>\n",
       "      <td>11110</td>\n",
       "      <td>2085</td>\n",
       "      <td>2.17</td>\n",
       "      <td>4657</td>\n",
       "      <td>2194</td>\n",
       "      <td>2463</td>\n",
       "      <td>900</td>\n",
       "      <td>POLYGON ((199040.5083769941 554638.116064481, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>종로구</td>\n",
       "      <td>종로1.2.3.4가동</td>\n",
       "      <td>11110</td>\n",
       "      <td>5378</td>\n",
       "      <td>1.41</td>\n",
       "      <td>8592</td>\n",
       "      <td>5045</td>\n",
       "      <td>3547</td>\n",
       "      <td>1865</td>\n",
       "      <td>POLYGON ((199690.8266258918 553496.6457869865,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>종로구</td>\n",
       "      <td>종로5·6가동</td>\n",
       "      <td>11110</td>\n",
       "      <td>3174</td>\n",
       "      <td>1.69</td>\n",
       "      <td>5690</td>\n",
       "      <td>3096</td>\n",
       "      <td>2594</td>\n",
       "      <td>1089</td>\n",
       "      <td>POLYGON ((200897.5839702621 552447.3517804386,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>종로구</td>\n",
       "      <td>이화동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4462</td>\n",
       "      <td>1.85</td>\n",
       "      <td>8752</td>\n",
       "      <td>4075</td>\n",
       "      <td>4677</td>\n",
       "      <td>1302</td>\n",
       "      <td>POLYGON ((200647.6629528549 553738.7060432669,...</td>\n",
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      ],
      "text/plain": [
       "  SGG_NM      DONG_NM SGG_CODE  SEDAE  SEDAE_INGU  TOTAL_POP  MALE_POP  \\\n",
       "0    종로구          사직동    11110   4414        2.14       9717      4467   \n",
       "1    종로구          삼청동    11110   1414        2.06       3097      1459   \n",
       "2    종로구          부암동    11110   4325        2.39      10726      5160   \n",
       "3    종로구          평창동    11110   7510        2.53      19163      9032   \n",
       "4    종로구          무악동    11110   3024        2.75       8375      3921   \n",
       "5    종로구          교남동    11110   4379        2.34      10363      4850   \n",
       "6    종로구          가회동    11110   2085        2.17       4657      2194   \n",
       "7    종로구  종로1.2.3.4가동    11110   5378        1.41       8592      5045   \n",
       "8    종로구      종로5·6가동    11110   3174        1.69       5690      3096   \n",
       "9    종로구          이화동    11110   4462        1.85       8752      4075   \n",
       "\n",
       "   FEMALE_POP  65_OVER                                           geometry  \n",
       "0        5250     1708  POLYGON ((197958.4491577554 552900.6843211155,...  \n",
       "1        1638      634  POLYGON ((198471.2440021661 555055.3898115929,...  \n",
       "2        5566     1748  POLYGON ((197867.3790096684 555221.862405367, ...  \n",
       "3       10131     3037  POLYGON ((197799.8340111427 559086.752938149, ...  \n",
       "4        4454     1279  POLYGON ((196526.2900434442 553472.4251048469,...  \n",
       "5        5513     1406  POLYGON ((197265.5793057524 552073.3139507617,...  \n",
       "6        2463      900  POLYGON ((199040.5083769941 554638.116064481, ...  \n",
       "7        3547     1865  POLYGON ((199690.8266258918 553496.6457869865,...  \n",
       "8        2594     1089  POLYGON ((200897.5839702621 552447.3517804386,...  \n",
       "9        4677     1302  POLYGON ((200647.6629528549 553738.7060432669,...  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _04 데이터 확인하기\n",
    "gdf.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'geopandas.geodataframe.GeoDataFrame'>\n",
      "RangeIndex: 424 entries, 0 to 423\n",
      "Data columns (total 10 columns):\n",
      "SGG_NM        424 non-null object\n",
      "DONG_NM       424 non-null object\n",
      "SGG_CODE      424 non-null object\n",
      "SEDAE         424 non-null int64\n",
      "SEDAE_INGU    424 non-null float64\n",
      "TOTAL_POP     424 non-null int64\n",
      "MALE_POP      424 non-null int64\n",
      "FEMALE_POP    424 non-null int64\n",
      "65_OVER       424 non-null int64\n",
      "geometry      424 non-null object\n",
      "dtypes: float64(1), int64(5), object(4)\n",
      "memory usage: 33.2+ KB\n"
     ]
    }
   ],
   "source": [
    "# _05 Dataframe 개요정보 확인하기\n",
    "gdf.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'geopandas.geodataframe.GeoDataFrame'>\n",
      "RangeIndex: 424 entries, 0 to 423\n",
      "Data columns (total 10 columns):\n",
      "SGG_NM        424 non-null object\n",
      "DONG_NM       424 non-null object\n",
      "SGG_CODE      424 non-null object\n",
      "SEDAE         424 non-null int64\n",
      "SEDAE_INGU    424 non-null float64\n",
      "TOTAL_POP     424 non-null int64\n",
      "MALE_POP      424 non-null int64\n",
      "FEMALE_POP    424 non-null int64\n",
      "65_OVER       424 non-null int64\n",
      "geometry      424 non-null object\n",
      "dtypes: float64(1), int64(5), object(4)\n",
      "memory usage: 33.2+ KB\n"
     ]
    },
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       "      <th>SGG_CODE</th>\n",
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       "      <th>SEDAE_INGU</th>\n",
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       "      <th>0</th>\n",
       "      <td>종로구</td>\n",
       "      <td>사직동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4414</td>\n",
       "      <td>2.14</td>\n",
       "      <td>9717</td>\n",
       "      <td>4467</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>종로구</td>\n",
       "      <td>삼청동</td>\n",
       "      <td>11110</td>\n",
       "      <td>1414</td>\n",
       "      <td>2.06</td>\n",
       "      <td>3097</td>\n",
       "      <td>1459</td>\n",
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       "      <td>11110</td>\n",
       "      <td>4325</td>\n",
       "      <td>2.39</td>\n",
       "      <td>10726</td>\n",
       "      <td>5160</td>\n",
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       "      <td>1748</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>종로구</td>\n",
       "      <td>평창동</td>\n",
       "      <td>11110</td>\n",
       "      <td>7510</td>\n",
       "      <td>2.53</td>\n",
       "      <td>19163</td>\n",
       "      <td>9032</td>\n",
       "      <td>10131</td>\n",
       "      <td>3037</td>\n",
       "      <td>POLYGON ((197799.8340111427 559086.752938149, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>종로구</td>\n",
       "      <td>무악동</td>\n",
       "      <td>11110</td>\n",
       "      <td>3024</td>\n",
       "      <td>2.75</td>\n",
       "      <td>8375</td>\n",
       "      <td>3921</td>\n",
       "      <td>4454</td>\n",
       "      <td>1279</td>\n",
       "      <td>POLYGON ((196526.2900434442 553472.4251048469,...</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "  SGG_NM DONG_NM SGG_CODE  SEDAE  SEDAE_INGU  TOTAL_POP  MALE_POP  FEMALE_POP  \\\n",
       "0    종로구     사직동    11110   4414        2.14       9717      4467        5250   \n",
       "1    종로구     삼청동    11110   1414        2.06       3097      1459        1638   \n",
       "2    종로구     부암동    11110   4325        2.39      10726      5160        5566   \n",
       "3    종로구     평창동    11110   7510        2.53      19163      9032       10131   \n",
       "4    종로구     무악동    11110   3024        2.75       8375      3921        4454   \n",
       "\n",
       "   65_OVER                                           geometry  \n",
       "0     1708  POLYGON ((197958.4491577554 552900.6843211155,...  \n",
       "1      634  POLYGON ((198471.2440021661 555055.3898115929,...  \n",
       "2     1748  POLYGON ((197867.3790096684 555221.862405367, ...  \n",
       "3     3037  POLYGON ((197799.8340111427 559086.752938149, ...  \n",
       "4     1279  POLYGON ((196526.2900434442 553472.4251048469,...  "
      ]
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     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _06 데이터 확인 요령 info() & head()를 동시에.... 취향대로\n",
    "gdf.info()\n",
    "gdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>SEDAE</th>\n",
       "      <th>SEDAE_INGU</th>\n",
       "      <th>TOTAL_POP</th>\n",
       "      <th>MALE_POP</th>\n",
       "      <th>FEMALE_POP</th>\n",
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       "      <th>count</th>\n",
       "      <td>424.000000</td>\n",
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       "      <td>424.000000</td>\n",
       "      <td>424.000000</td>\n",
       "      <td>424.000000</td>\n",
       "      <td>424.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>9953.023585</td>\n",
       "      <td>2.338137</td>\n",
       "      <td>23878.724057</td>\n",
       "      <td>11693.058962</td>\n",
       "      <td>12185.665094</td>\n",
       "      <td>3219.636792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3889.031075</td>\n",
       "      <td>0.348433</td>\n",
       "      <td>9431.363644</td>\n",
       "      <td>4594.843032</td>\n",
       "      <td>4866.509822</td>\n",
       "      <td>1279.225377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>365.000000</td>\n",
       "      <td>1.350000</td>\n",
       "      <td>905.000000</td>\n",
       "      <td>450.000000</td>\n",
       "      <td>455.000000</td>\n",
       "      <td>114.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>7358.250000</td>\n",
       "      <td>2.127500</td>\n",
       "      <td>17607.250000</td>\n",
       "      <td>8669.750000</td>\n",
       "      <td>9028.500000</td>\n",
       "      <td>2340.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>9723.000000</td>\n",
       "      <td>2.330000</td>\n",
       "      <td>23178.000000</td>\n",
       "      <td>11361.500000</td>\n",
       "      <td>11732.500000</td>\n",
       "      <td>3107.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>12395.000000</td>\n",
       "      <td>2.542500</td>\n",
       "      <td>29671.000000</td>\n",
       "      <td>14559.000000</td>\n",
       "      <td>14998.000000</td>\n",
       "      <td>3965.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>25214.000000</td>\n",
       "      <td>3.420000</td>\n",
       "      <td>55569.000000</td>\n",
       "      <td>26975.000000</td>\n",
       "      <td>29079.000000</td>\n",
       "      <td>7244.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              SEDAE  SEDAE_INGU     TOTAL_POP      MALE_POP    FEMALE_POP  \\\n",
       "count    424.000000  424.000000    424.000000    424.000000    424.000000   \n",
       "mean    9953.023585    2.338137  23878.724057  11693.058962  12185.665094   \n",
       "std     3889.031075    0.348433   9431.363644   4594.843032   4866.509822   \n",
       "min      365.000000    1.350000    905.000000    450.000000    455.000000   \n",
       "25%     7358.250000    2.127500  17607.250000   8669.750000   9028.500000   \n",
       "50%     9723.000000    2.330000  23178.000000  11361.500000  11732.500000   \n",
       "75%    12395.000000    2.542500  29671.000000  14559.000000  14998.000000   \n",
       "max    25214.000000    3.420000  55569.000000  26975.000000  29079.000000   \n",
       "\n",
       "           65_OVER  \n",
       "count   424.000000  \n",
       "mean   3219.636792  \n",
       "std    1279.225377  \n",
       "min     114.000000  \n",
       "25%    2340.750000  \n",
       "50%    3107.000000  \n",
       "75%    3965.500000  \n",
       "max    7244.000000  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _07 Dataframe 통계정보 확인하기\n",
    "gdf.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "23878.724056603773"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _08 평균값 가져오기\n",
    "gdf.TOTAL_POP.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0            사직동\n",
       "1            삼청동\n",
       "2            부암동\n",
       "3            평창동\n",
       "4            무악동\n",
       "5            교남동\n",
       "6            가회동\n",
       "7    종로1.2.3.4가동\n",
       "8        종로5·6가동\n",
       "9            이화동\n",
       "Name: DONG_NM, dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _09 Serise 데이터 가져오기\n",
    "# seoul_h_dong_gdf.DONG_NM\n",
    "gdf['DONG_NM'][:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'geopandas.geodataframe.GeoDataFrame'>\n",
      "<class 'pandas.core.series.Series'>\n",
      "<class 'geopandas.geoseries.GeoSeries'>\n"
     ]
    }
   ],
   "source": [
    "# _10 GeoPandas 데이터구조 확인하기\n",
    "# GeoPandas Data Structure - GeoDataFrame / Series / GeoSeries\n",
    "print(type(gdf))\n",
    "print(type(gdf['DONG_NM']))\n",
    "print(type(gdf['geometry']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GeoSeries 알아보기\n",
    "* Pandas의 Series + Geometry"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## GeoSeries 속성(Attributes)\n",
    "* geom_type\n",
    "    * Points / Multi-Points\n",
    "    * Lines / Multi-Lines\n",
    "    * Polygons / Multi-Polygons\n",
    "* area\n",
    "* bounds\n",
    "* total_bounds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    Polygon\n",
       "1    Polygon\n",
       "2    Polygon\n",
       "3    Polygon\n",
       "4    Polygon\n",
       "5    Polygon\n",
       "6    Polygon\n",
       "7    Polygon\n",
       "8    Polygon\n",
       "9    Polygon\n",
       "dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _11 geometry type 확인하기\n",
    "gdf['geometry'].geom_type[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"300\" height=\"300\" viewBox=\"196664.33708650593 552022.669678184 1357.447911933501 1367.395359597751\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,1105412.7347159656)\"><path fill-rule=\"evenodd\" fill=\"#66cc99\" stroke=\"#555555\" stroke-width=\"9.115969063985006\" opacity=\"0.6\" d=\"M 197958.4491577554,552900.6843211155 L 197971.14072586174,552184.1123524397 L 197877.52059645994,552199.8705089501 L 197824.51220588048,552197.5831753515 L 197732.38809654687,552191.6403721836 L 197265.57930575244,552073.3139507617 L 197221.11211223912,552099.2180676005 L 197053.74292993586,552217.3646784354 L 197021.22235715218,552240.5816862687 L 197004.936064223,552257.8767512648 L 196972.3686070026,552294.229088402 L 196989.90730560425,552309.1916655769 L 196997.37230805957,552445.6591680065 L 196789.77468437853,552848.2103652554 L 196739.19582296166,552993.764776159 L 196717.56019392892,553013.2702196955 L 196714.9813590836,553322.6210887851 L 197122.54122677125,553339.420765204 L 197122.30272344803,553301.9049769004 L 197123.03289744144,553294.0308140318 L 197125.41214778746,553269.9091362057 L 197179.17518955146,553189.0388562792 L 197257.69806532306,553154.4376006247 L 197280.46389781,553154.4342124134 L 197298.28710881426,553175.0528147675 L 197320.37520449125,553220.5523418686 L 197320.62921799783,553243.3125067883 L 197320.77571780758,553271.8003177046 L 197320.84409618835,553285.0798237997 L 197341.61544250924,553306.0751599241 L 197469.4742792764,553329.5119628768 L 197687.4089091411,553313.783708161 L 197696.04747293313,553215.5489861605 L 197698.00586750783,553188.1738929916 L 197732.54971459124,552911.7448990903 L 197862.59972573962,552900.5629869966 L 197958.4491577554,552900.6843211155 z\" /></g></svg>"
      ],
      "text/plain": [
       "<shapely.geometry.polygon.Polygon at 0x11f525438>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _12 Polygon(Geometry) 확인하기 \n",
    "gdf['geometry'][0]\n",
    "# gdf['geometry'][0:10].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1.165780e+06\n",
       "1    1.361445e+06\n",
       "2    2.202073e+06\n",
       "3    9.017316e+06\n",
       "4    4.675752e+05\n",
       "dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _13 GeoSeries 면적 계산하기\n",
    "gdf['geometry'].area[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1165779.6434216234\n",
      "<class 'numpy.float64'>\n"
     ]
    }
   ],
   "source": [
    "# 사직동 면적 1.23 km2 \n",
    "area = gdf['geometry'].area[0]\n",
    "print(area)\n",
    "print(type(area))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     4747.313027\n",
       "1     6396.687286\n",
       "2     8181.111555\n",
       "3    13537.740440\n",
       "4     2793.127231\n",
       "dtype: float64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _14 길이 확인하기\n",
    "gdf['geometry'].length[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{}"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _15 좌표체계 확인하기\n",
    "# 실제 데이터는 중부원점(GRS80) / EPSG:5186 입니다.\n",
    "gdf.crs"
   ]
  },
  {
   "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>minx</th>\n",
       "      <th>miny</th>\n",
       "      <th>maxx</th>\n",
       "      <th>maxy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>196714.981359</td>\n",
       "      <td>552073.313951</td>\n",
       "      <td>197971.140726</td>\n",
       "      <td>553339.420765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>197667.350764</td>\n",
       "      <td>552886.757958</td>\n",
       "      <td>199070.532651</td>\n",
       "      <td>555221.862405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>195827.437507</td>\n",
       "      <td>553807.003187</td>\n",
       "      <td>197867.379010</td>\n",
       "      <td>556387.087748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>195583.723664</td>\n",
       "      <td>555055.371189</td>\n",
       "      <td>198917.474288</td>\n",
       "      <td>559186.620547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>195897.493788</td>\n",
       "      <td>552602.691416</td>\n",
       "      <td>196717.560194</td>\n",
       "      <td>553572.333845</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            minx           miny           maxx           maxy\n",
       "0  196714.981359  552073.313951  197971.140726  553339.420765\n",
       "1  197667.350764  552886.757958  199070.532651  555221.862405\n",
       "2  195827.437507  553807.003187  197867.379010  556387.087748\n",
       "3  195583.723664  555055.371189  198917.474288  559186.620547\n",
       "4  195897.493788  552602.691416  196717.560194  553572.333845"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _16 GeoSeries bbox가져오기\n",
    "gdf['geometry'].bounds[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([179171.58071505, 536627.30404374, 216220.74149712, 566821.94693283])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _17 지도 전체 bbox가져오기\n",
    "gdf['geometry'].total_bounds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## GeoSeries Method\n",
    "* Basic Method\n",
    "    * centroid\n",
    "    * distance()\n",
    "    * representative_point()\n",
    "    * to_crs()\n",
    "    * plot()\n",
    "* Relationship Test\n",
    "    * geom_almost_equals()\n",
    "    * contains()\n",
    "    * intersects()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     POINT (197362.5622298564 552729.621167927)\n",
       "1    POINT (198331.9449764204 554272.6763917576)\n",
       "2    POINT (196693.3447557241 555237.1494030188)\n",
       "3    POINT (197287.2225161952 557153.2680252423)\n",
       "4    POINT (196377.3555106968 553133.1854231888)\n",
       "dtype: object"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _18 폴리곤 중심점 \n",
    "gdf['geometry'].centroid[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    POINT (197428.2584702565 552646.9347666309)\n",
       "1    POINT (198437.8098259113 554051.7878601849)\n",
       "2    POINT (196966.9525517866 555083.6930316656)\n",
       "3    POINT (197247.5400351976 557169.9326852214)\n",
       "4     POINT (196364.6265732131 553114.950885898)\n",
       "dtype: object"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _19 폴리곤 내 Point \n",
    "gdf['geometry'].representative_point()[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1822.2849209513395"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _20 두 포인트 사이 거리 계산하기\n",
    "start_point = gdf['geometry'].centroid[0]\n",
    "end_point = gdf['geometry'].centroid[1]\n",
    "\n",
    "start_point.distance(end_point)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### GeoDataFrame 알아보기"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### GeoDataFrame Method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11fc81be0>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# _21 지도 그리기\n",
    "%matplotlib inline\n",
    "gdf.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'geometry'"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _22 현재 위치정보(좌표)가 저장된 GeoSeries명 확인하기 - gemetry name확인\n",
    "gdf.geometry.name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# _23 컬럼명 변경하기\n",
    "gdf = gdf.rename(columns={'geometry': 'geom'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "No geometry data set yet (expected in column 'geometry'.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-26-7e7db0b69f71>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# _24 GeoDataFrame의 gemetry 확인하기\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mgdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgeometry\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m   5065\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_info_axis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_can_hold_identifiers_and_holds_name\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5066\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5067\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   5068\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5069\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/geopandas/geodataframe.py\u001b[0m in \u001b[0;36m_get_geometry\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     68\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_geometry_column_name\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     69\u001b[0m             raise AttributeError(\"No geometry data set yet (expected in\"\n\u001b[0;32m---> 70\u001b[0;31m                                  \" column '%s'.\" % self._geometry_column_name)\n\u001b[0m\u001b[1;32m     71\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_geometry_column_name\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     72\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mAttributeError\u001b[0m: No geometry data set yet (expected in column 'geometry'."
     ]
    }
   ],
   "source": [
    "# _24 GeoDataFrame의 gemetry 확인하기\n",
    "gdf.geometry.name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'geom'"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _25 GeoDataFrame에 geometry 등록하기\n",
    "gdf = gdf.set_geometry('geom')\n",
    "gdf.geometry.name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>SGG_NM</th>\n",
       "      <th>DONG_NM</th>\n",
       "      <th>SGG_CODE</th>\n",
       "      <th>SEDAE</th>\n",
       "      <th>SEDAE_INGU</th>\n",
       "      <th>TOTAL_POP</th>\n",
       "      <th>MALE_POP</th>\n",
       "      <th>FEMALE_POP</th>\n",
       "      <th>65_OVER</th>\n",
       "      <th>geom</th>\n",
       "      <th>centoroid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>종로구</td>\n",
       "      <td>사직동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4414</td>\n",
       "      <td>2.14</td>\n",
       "      <td>9717</td>\n",
       "      <td>4467</td>\n",
       "      <td>5250</td>\n",
       "      <td>1708</td>\n",
       "      <td>POLYGON ((197958.4491577554 552900.6843211155,...</td>\n",
       "      <td>POINT (197362.5622298564 552729.621167927)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>종로구</td>\n",
       "      <td>삼청동</td>\n",
       "      <td>11110</td>\n",
       "      <td>1414</td>\n",
       "      <td>2.06</td>\n",
       "      <td>3097</td>\n",
       "      <td>1459</td>\n",
       "      <td>1638</td>\n",
       "      <td>634</td>\n",
       "      <td>POLYGON ((198471.2440021661 555055.3898115929,...</td>\n",
       "      <td>POINT (198331.9449764204 554272.6763917576)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>종로구</td>\n",
       "      <td>부암동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4325</td>\n",
       "      <td>2.39</td>\n",
       "      <td>10726</td>\n",
       "      <td>5160</td>\n",
       "      <td>5566</td>\n",
       "      <td>1748</td>\n",
       "      <td>POLYGON ((197867.3790096684 555221.862405367, ...</td>\n",
       "      <td>POINT (196693.3447557241 555237.1494030188)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>종로구</td>\n",
       "      <td>평창동</td>\n",
       "      <td>11110</td>\n",
       "      <td>7510</td>\n",
       "      <td>2.53</td>\n",
       "      <td>19163</td>\n",
       "      <td>9032</td>\n",
       "      <td>10131</td>\n",
       "      <td>3037</td>\n",
       "      <td>POLYGON ((197799.8340111427 559086.752938149, ...</td>\n",
       "      <td>POINT (197287.2225161952 557153.2680252423)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>종로구</td>\n",
       "      <td>무악동</td>\n",
       "      <td>11110</td>\n",
       "      <td>3024</td>\n",
       "      <td>2.75</td>\n",
       "      <td>8375</td>\n",
       "      <td>3921</td>\n",
       "      <td>4454</td>\n",
       "      <td>1279</td>\n",
       "      <td>POLYGON ((196526.2900434442 553472.4251048469,...</td>\n",
       "      <td>POINT (196377.3555106968 553133.1854231888)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  SGG_NM DONG_NM SGG_CODE  SEDAE  SEDAE_INGU  TOTAL_POP  MALE_POP  FEMALE_POP  \\\n",
       "0    종로구     사직동    11110   4414        2.14       9717      4467        5250   \n",
       "1    종로구     삼청동    11110   1414        2.06       3097      1459        1638   \n",
       "2    종로구     부암동    11110   4325        2.39      10726      5160        5566   \n",
       "3    종로구     평창동    11110   7510        2.53      19163      9032       10131   \n",
       "4    종로구     무악동    11110   3024        2.75       8375      3921        4454   \n",
       "\n",
       "   65_OVER                                               geom  \\\n",
       "0     1708  POLYGON ((197958.4491577554 552900.6843211155,...   \n",
       "1      634  POLYGON ((198471.2440021661 555055.3898115929,...   \n",
       "2     1748  POLYGON ((197867.3790096684 555221.862405367, ...   \n",
       "3     3037  POLYGON ((197799.8340111427 559086.752938149, ...   \n",
       "4     1279  POLYGON ((196526.2900434442 553472.4251048469,...   \n",
       "\n",
       "                                     centoroid  \n",
       "0   POINT (197362.5622298564 552729.621167927)  \n",
       "1  POINT (198331.9449764204 554272.6763917576)  \n",
       "2  POINT (196693.3447557241 555237.1494030188)  \n",
       "3  POINT (197287.2225161952 557153.2680252423)  \n",
       "4  POINT (196377.3555106968 553133.1854231888)  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _26 GeoDataFrame의 새로운 컬럼에 폴리곤 중심점 값을 할당하기\n",
    "gdf['centoroid'] = gdf.centroid\n",
    "gdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'centoroid'"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _27 해당 Dataframe의 geometry컬럼 변경하기\n",
    "gdf = gdf.set_geometry('centoroid')\n",
    "gdf.geometry.name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x121e15668>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# _28 plot\n",
    "gdf.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.series.Series'>\n",
      "<class 'geopandas.geoseries.GeoSeries'>\n"
     ]
    }
   ],
   "source": [
    "print(type(gdf['geom']))\n",
    "print(type(gdf['centoroid']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Map Projection\n",
    "* https://www.osgeo.kr/17?fbclid=IwAR0pm8EkkCvsIKAXumPfkv5dmfgcF71WrmONkIpHBhWqbVxnF1_l0t-BntU"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# _01 GeoDataFrame Projection확인하기\n",
    "gdf.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'init': 'epsg:5186'}\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SGG_NM</th>\n",
       "      <th>DONG_NM</th>\n",
       "      <th>SGG_CODE</th>\n",
       "      <th>SEDAE</th>\n",
       "      <th>SEDAE_INGU</th>\n",
       "      <th>TOTAL_POP</th>\n",
       "      <th>MALE_POP</th>\n",
       "      <th>FEMALE_POP</th>\n",
       "      <th>65_OVER</th>\n",
       "      <th>geom</th>\n",
       "      <th>centoroid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>종로구</td>\n",
       "      <td>사직동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4414</td>\n",
       "      <td>2.14</td>\n",
       "      <td>9717</td>\n",
       "      <td>4467</td>\n",
       "      <td>5250</td>\n",
       "      <td>1708</td>\n",
       "      <td>POLYGON ((197958.4491577554 552900.6843211155,...</td>\n",
       "      <td>POINT (197362.5622298564 552729.621167927)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>종로구</td>\n",
       "      <td>삼청동</td>\n",
       "      <td>11110</td>\n",
       "      <td>1414</td>\n",
       "      <td>2.06</td>\n",
       "      <td>3097</td>\n",
       "      <td>1459</td>\n",
       "      <td>1638</td>\n",
       "      <td>634</td>\n",
       "      <td>POLYGON ((198471.2440021661 555055.3898115929,...</td>\n",
       "      <td>POINT (198331.9449764204 554272.6763917576)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>종로구</td>\n",
       "      <td>부암동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4325</td>\n",
       "      <td>2.39</td>\n",
       "      <td>10726</td>\n",
       "      <td>5160</td>\n",
       "      <td>5566</td>\n",
       "      <td>1748</td>\n",
       "      <td>POLYGON ((197867.3790096684 555221.862405367, ...</td>\n",
       "      <td>POINT (196693.3447557241 555237.1494030188)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>종로구</td>\n",
       "      <td>평창동</td>\n",
       "      <td>11110</td>\n",
       "      <td>7510</td>\n",
       "      <td>2.53</td>\n",
       "      <td>19163</td>\n",
       "      <td>9032</td>\n",
       "      <td>10131</td>\n",
       "      <td>3037</td>\n",
       "      <td>POLYGON ((197799.8340111427 559086.752938149, ...</td>\n",
       "      <td>POINT (197287.2225161952 557153.2680252423)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>종로구</td>\n",
       "      <td>무악동</td>\n",
       "      <td>11110</td>\n",
       "      <td>3024</td>\n",
       "      <td>2.75</td>\n",
       "      <td>8375</td>\n",
       "      <td>3921</td>\n",
       "      <td>4454</td>\n",
       "      <td>1279</td>\n",
       "      <td>POLYGON ((196526.2900434442 553472.4251048469,...</td>\n",
       "      <td>POINT (196377.3555106968 553133.1854231888)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  SGG_NM DONG_NM SGG_CODE  SEDAE  SEDAE_INGU  TOTAL_POP  MALE_POP  FEMALE_POP  \\\n",
       "0    종로구     사직동    11110   4414        2.14       9717      4467        5250   \n",
       "1    종로구     삼청동    11110   1414        2.06       3097      1459        1638   \n",
       "2    종로구     부암동    11110   4325        2.39      10726      5160        5566   \n",
       "3    종로구     평창동    11110   7510        2.53      19163      9032       10131   \n",
       "4    종로구     무악동    11110   3024        2.75       8375      3921        4454   \n",
       "\n",
       "   65_OVER                                               geom  \\\n",
       "0     1708  POLYGON ((197958.4491577554 552900.6843211155,...   \n",
       "1      634  POLYGON ((198471.2440021661 555055.3898115929,...   \n",
       "2     1748  POLYGON ((197867.3790096684 555221.862405367, ...   \n",
       "3     3037  POLYGON ((197799.8340111427 559086.752938149, ...   \n",
       "4     1279  POLYGON ((196526.2900434442 553472.4251048469,...   \n",
       "\n",
       "                                     centoroid  \n",
       "0   POINT (197362.5622298564 552729.621167927)  \n",
       "1  POINT (198331.9449764204 554272.6763917576)  \n",
       "2  POINT (196693.3447557241 555237.1494030188)  \n",
       "3  POINT (197287.2225161952 557153.2680252423)  \n",
       "4  POINT (196377.3555106968 553133.1854231888)  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _02 좌표체계 입력하기 1\n",
    "gdf.crs = {'init': 'epsg:5186'}\n",
    "print(gdf.crs)\n",
    "gdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{}"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf.crs = {}\n",
    "gdf.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'init': 'epsg:5186', 'no_defs': True}"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _02 좌표체계 입력하기 2\n",
    "from fiona.crs import from_epsg\n",
    "gdf.crs = from_epsg(5186)\n",
    "gdf.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'+proj=tmerc +lat_0=38 +lon_0=127 +k=1 +x_0=200000 +y_0=600000 +ellps=GRS80 +units=m +no_defs'"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _02 좌표체계 입력하기 3\n",
    "gdf.crs = '+proj=tmerc +lat_0=38 +lon_0=127 +k=1 +x_0=200000 +y_0=600000 +ellps=GRS80 +units=m +no_defs'\n",
    "gdf.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'init': 'epsg:4326', 'no_defs': True}\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SGG_NM</th>\n",
       "      <th>DONG_NM</th>\n",
       "      <th>SGG_CODE</th>\n",
       "      <th>SEDAE</th>\n",
       "      <th>SEDAE_INGU</th>\n",
       "      <th>TOTAL_POP</th>\n",
       "      <th>MALE_POP</th>\n",
       "      <th>FEMALE_POP</th>\n",
       "      <th>65_OVER</th>\n",
       "      <th>geom</th>\n",
       "      <th>centoroid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>종로구</td>\n",
       "      <td>사직동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4414</td>\n",
       "      <td>2.14</td>\n",
       "      <td>9717</td>\n",
       "      <td>4467</td>\n",
       "      <td>5250</td>\n",
       "      <td>1708</td>\n",
       "      <td>POLYGON ((197958.4491577554 552900.6843211155,...</td>\n",
       "      <td>POINT (126.9701437848048 37.57410799640894)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>종로구</td>\n",
       "      <td>삼청동</td>\n",
       "      <td>11110</td>\n",
       "      <td>1414</td>\n",
       "      <td>2.06</td>\n",
       "      <td>3097</td>\n",
       "      <td>1459</td>\n",
       "      <td>1638</td>\n",
       "      <td>634</td>\n",
       "      <td>POLYGON ((198471.2440021661 555055.3898115929,...</td>\n",
       "      <td>POINT (126.9811138394541 37.58801309167354)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>종로구</td>\n",
       "      <td>부암동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4325</td>\n",
       "      <td>2.39</td>\n",
       "      <td>10726</td>\n",
       "      <td>5160</td>\n",
       "      <td>5566</td>\n",
       "      <td>1748</td>\n",
       "      <td>POLYGON ((197867.3790096684 555221.862405367, ...</td>\n",
       "      <td>POINT (126.9625568232872 37.59669848799677)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>종로구</td>\n",
       "      <td>평창동</td>\n",
       "      <td>11110</td>\n",
       "      <td>7510</td>\n",
       "      <td>2.53</td>\n",
       "      <td>19163</td>\n",
       "      <td>9032</td>\n",
       "      <td>10131</td>\n",
       "      <td>3037</td>\n",
       "      <td>POLYGON ((197799.8340111427 559086.752938149, ...</td>\n",
       "      <td>POINT (126.9692745447589 37.61396446471238)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>종로구</td>\n",
       "      <td>무악동</td>\n",
       "      <td>11110</td>\n",
       "      <td>3024</td>\n",
       "      <td>2.75</td>\n",
       "      <td>8375</td>\n",
       "      <td>3921</td>\n",
       "      <td>4454</td>\n",
       "      <td>1279</td>\n",
       "      <td>POLYGON ((196526.2900434442 553472.4251048469,...</td>\n",
       "      <td>POINT (126.9589890961927 37.57774073986884)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  SGG_NM DONG_NM SGG_CODE  SEDAE  SEDAE_INGU  TOTAL_POP  MALE_POP  FEMALE_POP  \\\n",
       "0    종로구     사직동    11110   4414        2.14       9717      4467        5250   \n",
       "1    종로구     삼청동    11110   1414        2.06       3097      1459        1638   \n",
       "2    종로구     부암동    11110   4325        2.39      10726      5160        5566   \n",
       "3    종로구     평창동    11110   7510        2.53      19163      9032       10131   \n",
       "4    종로구     무악동    11110   3024        2.75       8375      3921        4454   \n",
       "\n",
       "   65_OVER                                               geom  \\\n",
       "0     1708  POLYGON ((197958.4491577554 552900.6843211155,...   \n",
       "1      634  POLYGON ((198471.2440021661 555055.3898115929,...   \n",
       "2     1748  POLYGON ((197867.3790096684 555221.862405367, ...   \n",
       "3     3037  POLYGON ((197799.8340111427 559086.752938149, ...   \n",
       "4     1279  POLYGON ((196526.2900434442 553472.4251048469,...   \n",
       "\n",
       "                                     centoroid  \n",
       "0  POINT (126.9701437848048 37.57410799640894)  \n",
       "1  POINT (126.9811138394541 37.58801309167354)  \n",
       "2  POINT (126.9625568232872 37.59669848799677)  \n",
       "3  POINT (126.9692745447589 37.61396446471238)  \n",
       "4  POINT (126.9589890961927 37.57774073986884)  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _03 좌표 변환하기 \n",
    "# 반드시 좌표 변환이 되는 타켓 좌표체계(원본 데이터)가 존재해야 하고 변환 된 GeoDataFrame이 새롭게 생성되어야 한다.\n",
    "gdf = gdf.to_crs(epsg=4326)\n",
    "print(gdf.crs)\n",
    "gdf.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 실습 \n",
    "## 1. 변환된 GeoDataFrame의 geometry 컬럼을 `centroid`컬럼에서 `geom`컬럼으로 변경한다.\n",
    "## 2. `geom` 컬럼의 좌표 체계를 EPSG:5183 -> EPSG:4326으로 좌표변환한다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'geom'"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# geometry 컬럼 변경하기\n",
    "gdf = gdf.set_geometry('geom')\n",
    "gdf.geometry.name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'init': 'epsg:4326', 'no_defs': True}\n",
      "{'init': 'epsg:5186', 'no_defs': True}\n"
     ]
    }
   ],
   "source": [
    "# GeoDataFrame의 정확한 좌표체계 정보 입력하기\n",
    "print(gdf.crs)\n",
    "gdf.crs = from_epsg(5186)\n",
    "print(gdf.crs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>SGG_NM</th>\n",
       "      <th>DONG_NM</th>\n",
       "      <th>SGG_CODE</th>\n",
       "      <th>SEDAE</th>\n",
       "      <th>SEDAE_INGU</th>\n",
       "      <th>TOTAL_POP</th>\n",
       "      <th>MALE_POP</th>\n",
       "      <th>FEMALE_POP</th>\n",
       "      <th>65_OVER</th>\n",
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       "      <th>0</th>\n",
       "      <td>종로구</td>\n",
       "      <td>사직동</td>\n",
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       "      <td>4414</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>종로구</td>\n",
       "      <td>삼청동</td>\n",
       "      <td>11110</td>\n",
       "      <td>1414</td>\n",
       "      <td>2.06</td>\n",
       "      <td>3097</td>\n",
       "      <td>1459</td>\n",
       "      <td>1638</td>\n",
       "      <td>634</td>\n",
       "      <td>POLYGON ((198471.2440021661 555055.3898115929,...</td>\n",
       "      <td>POINT (126.9811138394541 37.58801309167354)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>종로구</td>\n",
       "      <td>부암동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4325</td>\n",
       "      <td>2.39</td>\n",
       "      <td>10726</td>\n",
       "      <td>5160</td>\n",
       "      <td>5566</td>\n",
       "      <td>1748</td>\n",
       "      <td>POLYGON ((197867.3790096684 555221.862405367, ...</td>\n",
       "      <td>POINT (126.9625568232872 37.59669848799677)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>종로구</td>\n",
       "      <td>평창동</td>\n",
       "      <td>11110</td>\n",
       "      <td>7510</td>\n",
       "      <td>2.53</td>\n",
       "      <td>19163</td>\n",
       "      <td>9032</td>\n",
       "      <td>10131</td>\n",
       "      <td>3037</td>\n",
       "      <td>POLYGON ((197799.8340111427 559086.752938149, ...</td>\n",
       "      <td>POINT (126.9692745447589 37.61396446471238)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>종로구</td>\n",
       "      <td>무악동</td>\n",
       "      <td>11110</td>\n",
       "      <td>3024</td>\n",
       "      <td>2.75</td>\n",
       "      <td>8375</td>\n",
       "      <td>3921</td>\n",
       "      <td>4454</td>\n",
       "      <td>1279</td>\n",
       "      <td>POLYGON ((196526.2900434442 553472.4251048469,...</td>\n",
       "      <td>POINT (126.9589890961927 37.57774073986884)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  SGG_NM DONG_NM SGG_CODE  SEDAE  SEDAE_INGU  TOTAL_POP  MALE_POP  FEMALE_POP  \\\n",
       "0    종로구     사직동    11110   4414        2.14       9717      4467        5250   \n",
       "1    종로구     삼청동    11110   1414        2.06       3097      1459        1638   \n",
       "2    종로구     부암동    11110   4325        2.39      10726      5160        5566   \n",
       "3    종로구     평창동    11110   7510        2.53      19163      9032       10131   \n",
       "4    종로구     무악동    11110   3024        2.75       8375      3921        4454   \n",
       "\n",
       "   65_OVER                                               geom  \\\n",
       "0     1708  POLYGON ((197958.4491577554 552900.6843211155,...   \n",
       "1      634  POLYGON ((198471.2440021661 555055.3898115929,...   \n",
       "2     1748  POLYGON ((197867.3790096684 555221.862405367, ...   \n",
       "3     3037  POLYGON ((197799.8340111427 559086.752938149, ...   \n",
       "4     1279  POLYGON ((196526.2900434442 553472.4251048469,...   \n",
       "\n",
       "                                     centoroid  \n",
       "0  POINT (126.9701437848048 37.57410799640894)  \n",
       "1  POINT (126.9811138394541 37.58801309167354)  \n",
       "2  POINT (126.9625568232872 37.59669848799677)  \n",
       "3  POINT (126.9692745447589 37.61396446471238)  \n",
       "4  POINT (126.9589890961927 37.57774073986884)  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 원본 파일을 복사해 새로운 변수에 할당하기\n",
    "_gdf = gdf.copy()\n",
    "_gdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>SGG_CODE</th>\n",
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       "      <th>SEDAE_INGU</th>\n",
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       "      <th>0</th>\n",
       "      <td>종로구</td>\n",
       "      <td>사직동</td>\n",
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       "      <td>2.14</td>\n",
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       "      <td>삼청동</td>\n",
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       "      <td>3097</td>\n",
       "      <td>1459</td>\n",
       "      <td>1638</td>\n",
       "      <td>634</td>\n",
       "      <td>POLYGON ((126.982689386493 37.5950655194224, 1...</td>\n",
       "      <td>POINT (126.9811138394541 37.58801309167354)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>종로구</td>\n",
       "      <td>부암동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4325</td>\n",
       "      <td>2.39</td>\n",
       "      <td>10726</td>\n",
       "      <td>5160</td>\n",
       "      <td>5566</td>\n",
       "      <td>1748</td>\n",
       "      <td>POLYGON ((126.9758511377569 37.59656422224408,...</td>\n",
       "      <td>POINT (126.9625568232872 37.59669848799677)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>종로구</td>\n",
       "      <td>평창동</td>\n",
       "      <td>11110</td>\n",
       "      <td>7510</td>\n",
       "      <td>2.53</td>\n",
       "      <td>19163</td>\n",
       "      <td>9032</td>\n",
       "      <td>10131</td>\n",
       "      <td>3037</td>\n",
       "      <td>POLYGON ((126.9750746678809 37.631386286513, 1...</td>\n",
       "      <td>POINT (126.9692745447589 37.61396446471238)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>종로구</td>\n",
       "      <td>무악동</td>\n",
       "      <td>11110</td>\n",
       "      <td>3024</td>\n",
       "      <td>2.75</td>\n",
       "      <td>8375</td>\n",
       "      <td>3921</td>\n",
       "      <td>4454</td>\n",
       "      <td>1279</td>\n",
       "      <td>POLYGON ((126.960673532739 37.58079784202972, ...</td>\n",
       "      <td>POINT (126.9589890961927 37.57774073986884)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  SGG_NM DONG_NM SGG_CODE  SEDAE  SEDAE_INGU  TOTAL_POP  MALE_POP  FEMALE_POP  \\\n",
       "0    종로구     사직동    11110   4414        2.14       9717      4467        5250   \n",
       "1    종로구     삼청동    11110   1414        2.06       3097      1459        1638   \n",
       "2    종로구     부암동    11110   4325        2.39      10726      5160        5566   \n",
       "3    종로구     평창동    11110   7510        2.53      19163      9032       10131   \n",
       "4    종로구     무악동    11110   3024        2.75       8375      3921        4454   \n",
       "\n",
       "   65_OVER                                               geom  \\\n",
       "0     1708  POLYGON ((126.9768888427482 37.57565077944879,...   \n",
       "1      634  POLYGON ((126.982689386493 37.5950655194224, 1...   \n",
       "2     1748  POLYGON ((126.9758511377569 37.59656422224408,...   \n",
       "3     3037  POLYGON ((126.9750746678809 37.631386286513, 1...   \n",
       "4     1279  POLYGON ((126.960673532739 37.58079784202972, ...   \n",
       "\n",
       "                                     centoroid  \n",
       "0  POINT (126.9701437848048 37.57410799640894)  \n",
       "1  POINT (126.9811138394541 37.58801309167354)  \n",
       "2  POINT (126.9625568232872 37.59669848799677)  \n",
       "3  POINT (126.9692745447589 37.61396446471238)  \n",
       "4  POINT (126.9589890961927 37.57774073986884)  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 좌표 변환된 GeoDataFrame생성 후 _gdf변수에 할당하기\n",
    "_gdf = gdf.to_crs(from_epsg(4326))\n",
    "_gdf.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  Writing data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mkdir: ./maps/output: File exists\r\n"
     ]
    }
   ],
   "source": [
    "# 폴더생성\n",
    "!mkdir ./maps/output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Invalid field type <class 'shapely.geometry.point.Point'>",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-42-cdaf1d70ea85>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# _29 shp파일 저장하기 (에러발생)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0m_gdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_file\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'./maps/output/seoul_h_dong'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencoding\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'utf-8'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/geopandas/geodataframe.py\u001b[0m in \u001b[0;36mto_file\u001b[0;34m(self, filename, driver, schema, **kwargs)\u001b[0m\n\u001b[1;32m    427\u001b[0m         \"\"\"\n\u001b[1;32m    428\u001b[0m         \u001b[0;32mfrom\u001b[0m \u001b[0mgeopandas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfile\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mto_file\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 429\u001b[0;31m         \u001b[0mto_file\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfilename\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdriver\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mschema\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    430\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    431\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mto_crs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcrs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mepsg\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/geopandas/io/file.py\u001b[0m in \u001b[0;36mto_file\u001b[0;34m(df, filename, driver, schema, **kwargs)\u001b[0m\n\u001b[1;32m    129\u001b[0m         with fiona.open(filename, 'w', driver=driver, crs=df.crs,\n\u001b[1;32m    130\u001b[0m                         schema=schema, **kwargs) as colxn:\n\u001b[0;32m--> 131\u001b[0;31m             \u001b[0mcolxn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwriterecords\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miterfeatures\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    132\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    133\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.7/site-packages/fiona/collection.py\u001b[0m in \u001b[0;36mwriterecords\u001b[0;34m(self, records)\u001b[0m\n\u001b[1;32m    345\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmode\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m'a'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'w'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    346\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mIOError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"collection not open for writing\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 347\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msession\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwriterecs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrecords\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    348\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_len\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msession\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_length\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    349\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_bounds\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msession\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_extent\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mfiona/ogrext.pyx\u001b[0m in \u001b[0;36mfiona.ogrext.WritingSession.writerecs\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mfiona/ogrext.pyx\u001b[0m in \u001b[0;36mfiona.ogrext.OGRFeatureBuilder.build\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Invalid field type <class 'shapely.geometry.point.Point'>"
     ]
    }
   ],
   "source": [
    "# _29 shp파일 저장하기 (에러발생)\n",
    "_gdf.to_file('./maps/output/seoul_h_dong', encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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>SGG_NM</th>\n",
       "      <th>DONG_NM</th>\n",
       "      <th>SGG_CODE</th>\n",
       "      <th>SEDAE</th>\n",
       "      <th>SEDAE_INGU</th>\n",
       "      <th>TOTAL_POP</th>\n",
       "      <th>MALE_POP</th>\n",
       "      <th>FEMALE_POP</th>\n",
       "      <th>65_OVER</th>\n",
       "      <th>geom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>종로구</td>\n",
       "      <td>사직동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4414</td>\n",
       "      <td>2.14</td>\n",
       "      <td>9717</td>\n",
       "      <td>4467</td>\n",
       "      <td>5250</td>\n",
       "      <td>1708</td>\n",
       "      <td>POLYGON ((126.9768888427482 37.57565077944879,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>종로구</td>\n",
       "      <td>삼청동</td>\n",
       "      <td>11110</td>\n",
       "      <td>1414</td>\n",
       "      <td>2.06</td>\n",
       "      <td>3097</td>\n",
       "      <td>1459</td>\n",
       "      <td>1638</td>\n",
       "      <td>634</td>\n",
       "      <td>POLYGON ((126.982689386493 37.5950655194224, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>종로구</td>\n",
       "      <td>부암동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4325</td>\n",
       "      <td>2.39</td>\n",
       "      <td>10726</td>\n",
       "      <td>5160</td>\n",
       "      <td>5566</td>\n",
       "      <td>1748</td>\n",
       "      <td>POLYGON ((126.9758511377569 37.59656422224408,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>종로구</td>\n",
       "      <td>평창동</td>\n",
       "      <td>11110</td>\n",
       "      <td>7510</td>\n",
       "      <td>2.53</td>\n",
       "      <td>19163</td>\n",
       "      <td>9032</td>\n",
       "      <td>10131</td>\n",
       "      <td>3037</td>\n",
       "      <td>POLYGON ((126.9750746678809 37.631386286513, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>종로구</td>\n",
       "      <td>무악동</td>\n",
       "      <td>11110</td>\n",
       "      <td>3024</td>\n",
       "      <td>2.75</td>\n",
       "      <td>8375</td>\n",
       "      <td>3921</td>\n",
       "      <td>4454</td>\n",
       "      <td>1279</td>\n",
       "      <td>POLYGON ((126.960673532739 37.58079784202972, ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  SGG_NM DONG_NM SGG_CODE  SEDAE  SEDAE_INGU  TOTAL_POP  MALE_POP  FEMALE_POP  \\\n",
       "0    종로구     사직동    11110   4414        2.14       9717      4467        5250   \n",
       "1    종로구     삼청동    11110   1414        2.06       3097      1459        1638   \n",
       "2    종로구     부암동    11110   4325        2.39      10726      5160        5566   \n",
       "3    종로구     평창동    11110   7510        2.53      19163      9032       10131   \n",
       "4    종로구     무악동    11110   3024        2.75       8375      3921        4454   \n",
       "\n",
       "   65_OVER                                               geom  \n",
       "0     1708  POLYGON ((126.9768888427482 37.57565077944879,...  \n",
       "1      634  POLYGON ((126.982689386493 37.5950655194224, 1...  \n",
       "2     1748  POLYGON ((126.9758511377569 37.59656422224408,...  \n",
       "3     3037  POLYGON ((126.9750746678809 37.631386286513, 1...  \n",
       "4     1279  POLYGON ((126.960673532739 37.58079784202972, ...  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _30 불필요한 컬럼 제거하기\n",
    "# 파일 저장 시 GeoDataFrame에는 좌표정보가 반드시 하나만 있어야 한다.\n",
    "columns = ['SGG_NM', 'DONG_NM','SGG_CODE', 'SEDAE', 'SEDAE_INGU', 'TOTAL_POP', 'MALE_POP', 'FEMALE_POP', '65_OVER','geom']\n",
    "_gdf = gpd.GeoDataFrame(_gdf[columns], geometry='geom', crs=from_epsg(4326))\n",
    "_gdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "geopandas.geodataframe.GeoDataFrame"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _31 Dataframe 타입 확인\n",
    "type(gdf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# _32 shp파일로 저장하기\n",
    "_gdf.to_file('./maps/output/seoul_h_dong', encoding='euc-kr')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# _33 geojson으로 저장하기\n",
    "_gdf.to_file('./maps/output/seoul_h_dong.geojson', driver='GeoJSON')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  특정 컬럼만 선택 해 파일 저장하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SGG_NM</th>\n",
       "      <th>DONG_NM</th>\n",
       "      <th>SGG_CODE</th>\n",
       "      <th>SEDAE</th>\n",
       "      <th>SEDAE_INGU</th>\n",
       "      <th>TOTAL_POP</th>\n",
       "      <th>MALE_POP</th>\n",
       "      <th>FEMALE_POP</th>\n",
       "      <th>65_OVER</th>\n",
       "      <th>geom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>종로구</td>\n",
       "      <td>사직동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4414</td>\n",
       "      <td>2.14</td>\n",
       "      <td>9717</td>\n",
       "      <td>4467</td>\n",
       "      <td>5250</td>\n",
       "      <td>1708</td>\n",
       "      <td>POLYGON ((126.9768888427482 37.57565077944879,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>종로구</td>\n",
       "      <td>삼청동</td>\n",
       "      <td>11110</td>\n",
       "      <td>1414</td>\n",
       "      <td>2.06</td>\n",
       "      <td>3097</td>\n",
       "      <td>1459</td>\n",
       "      <td>1638</td>\n",
       "      <td>634</td>\n",
       "      <td>POLYGON ((126.982689386493 37.5950655194224, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>종로구</td>\n",
       "      <td>부암동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4325</td>\n",
       "      <td>2.39</td>\n",
       "      <td>10726</td>\n",
       "      <td>5160</td>\n",
       "      <td>5566</td>\n",
       "      <td>1748</td>\n",
       "      <td>POLYGON ((126.9758511377569 37.59656422224408,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>종로구</td>\n",
       "      <td>평창동</td>\n",
       "      <td>11110</td>\n",
       "      <td>7510</td>\n",
       "      <td>2.53</td>\n",
       "      <td>19163</td>\n",
       "      <td>9032</td>\n",
       "      <td>10131</td>\n",
       "      <td>3037</td>\n",
       "      <td>POLYGON ((126.9750746678809 37.631386286513, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>종로구</td>\n",
       "      <td>무악동</td>\n",
       "      <td>11110</td>\n",
       "      <td>3024</td>\n",
       "      <td>2.75</td>\n",
       "      <td>8375</td>\n",
       "      <td>3921</td>\n",
       "      <td>4454</td>\n",
       "      <td>1279</td>\n",
       "      <td>POLYGON ((126.960673532739 37.58079784202972, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>종로구</td>\n",
       "      <td>교남동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4379</td>\n",
       "      <td>2.34</td>\n",
       "      <td>10363</td>\n",
       "      <td>4850</td>\n",
       "      <td>5513</td>\n",
       "      <td>1406</td>\n",
       "      <td>POLYGON ((126.9690483700185 37.56819441770832,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>종로구</td>\n",
       "      <td>가회동</td>\n",
       "      <td>11110</td>\n",
       "      <td>2085</td>\n",
       "      <td>2.17</td>\n",
       "      <td>4657</td>\n",
       "      <td>2194</td>\n",
       "      <td>2463</td>\n",
       "      <td>900</td>\n",
       "      <td>POLYGON ((126.9891359030894 37.59130668631862,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>종로구</td>\n",
       "      <td>종로1.2.3.4가동</td>\n",
       "      <td>11110</td>\n",
       "      <td>5378</td>\n",
       "      <td>1.41</td>\n",
       "      <td>8592</td>\n",
       "      <td>5045</td>\n",
       "      <td>3547</td>\n",
       "      <td>1865</td>\n",
       "      <td>POLYGON ((126.9964997845193 37.5810225677299, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>종로구</td>\n",
       "      <td>종로5·6가동</td>\n",
       "      <td>11110</td>\n",
       "      <td>3174</td>\n",
       "      <td>1.69</td>\n",
       "      <td>5690</td>\n",
       "      <td>3096</td>\n",
       "      <td>2594</td>\n",
       "      <td>1089</td>\n",
       "      <td>POLYGON ((127.0101604483956 37.57156810157084,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>종로구</td>\n",
       "      <td>이화동</td>\n",
       "      <td>11110</td>\n",
       "      <td>4462</td>\n",
       "      <td>1.85</td>\n",
       "      <td>8752</td>\n",
       "      <td>4075</td>\n",
       "      <td>4677</td>\n",
       "      <td>1302</td>\n",
       "      <td>POLYGON ((127.0073325396313 37.58320333921623,...</td>\n",
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      ],
      "text/plain": [
       "  SGG_NM      DONG_NM SGG_CODE  SEDAE  SEDAE_INGU  TOTAL_POP  MALE_POP  \\\n",
       "0    종로구          사직동    11110   4414        2.14       9717      4467   \n",
       "1    종로구          삼청동    11110   1414        2.06       3097      1459   \n",
       "2    종로구          부암동    11110   4325        2.39      10726      5160   \n",
       "3    종로구          평창동    11110   7510        2.53      19163      9032   \n",
       "4    종로구          무악동    11110   3024        2.75       8375      3921   \n",
       "5    종로구          교남동    11110   4379        2.34      10363      4850   \n",
       "6    종로구          가회동    11110   2085        2.17       4657      2194   \n",
       "7    종로구  종로1.2.3.4가동    11110   5378        1.41       8592      5045   \n",
       "8    종로구      종로5·6가동    11110   3174        1.69       5690      3096   \n",
       "9    종로구          이화동    11110   4462        1.85       8752      4075   \n",
       "\n",
       "   FEMALE_POP  65_OVER                                               geom  \n",
       "0        5250     1708  POLYGON ((126.9768888427482 37.57565077944879,...  \n",
       "1        1638      634  POLYGON ((126.982689386493 37.5950655194224, 1...  \n",
       "2        5566     1748  POLYGON ((126.9758511377569 37.59656422224408,...  \n",
       "3       10131     3037  POLYGON ((126.9750746678809 37.631386286513, 1...  \n",
       "4        4454     1279  POLYGON ((126.960673532739 37.58079784202972, ...  \n",
       "5        5513     1406  POLYGON ((126.9690483700185 37.56819441770832,...  \n",
       "6        2463      900  POLYGON ((126.9891359030894 37.59130668631862,...  \n",
       "7        3547     1865  POLYGON ((126.9964997845193 37.5810225677299, ...  \n",
       "8        2594     1089  POLYGON ((127.0101604483956 37.57156810157084,...  \n",
       "9        4677     1302  POLYGON ((127.0073325396313 37.58320333921623,...  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _34 select_by_attribute\n",
    "selection_1 = _gdf[0:10]\n",
    "selection_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SGG_NM</th>\n",
       "      <th>DONG_NM</th>\n",
       "      <th>SGG_CODE</th>\n",
       "      <th>SEDAE</th>\n",
       "      <th>SEDAE_INGU</th>\n",
       "      <th>TOTAL_POP</th>\n",
       "      <th>MALE_POP</th>\n",
       "      <th>FEMALE_POP</th>\n",
       "      <th>65_OVER</th>\n",
       "      <th>geom</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>357</th>\n",
       "      <td>강남구</td>\n",
       "      <td>신사동</td>\n",
       "      <td>11680</td>\n",
       "      <td>7633</td>\n",
       "      <td>2.34</td>\n",
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       "      <th>358</th>\n",
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       "      <td>11680</td>\n",
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       "      <td>1.68</td>\n",
       "      <td>24186</td>\n",
       "      <td>11192</td>\n",
       "      <td>12994</td>\n",
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       "      <td>11146</td>\n",
       "      <td>2.00</td>\n",
       "      <td>22573</td>\n",
       "      <td>10587</td>\n",
       "      <td>11986</td>\n",
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       "      <td>POLYGON ((127.0391780751905 37.52290539552295,...</td>\n",
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       "    <tr>\n",
       "      <th>360</th>\n",
       "      <td>강남구</td>\n",
       "      <td>삼성1동</td>\n",
       "      <td>11680</td>\n",
       "      <td>5811</td>\n",
       "      <td>2.56</td>\n",
       "      <td>15193</td>\n",
       "      <td>7650</td>\n",
       "      <td>7543</td>\n",
       "      <td>1900</td>\n",
       "      <td>POLYGON ((127.0669618590224 37.52508139275426,...</td>\n",
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       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>강남구</td>\n",
       "      <td>삼성2동</td>\n",
       "      <td>11680</td>\n",
       "      <td>12815</td>\n",
       "      <td>2.29</td>\n",
       "      <td>29628</td>\n",
       "      <td>14130</td>\n",
       "      <td>15498</td>\n",
       "      <td>2867</td>\n",
       "      <td>POLYGON ((127.05669182524 37.50685502947763, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>강남구</td>\n",
       "      <td>대치1동</td>\n",
       "      <td>11680</td>\n",
       "      <td>7374</td>\n",
       "      <td>3.42</td>\n",
       "      <td>25262</td>\n",
       "      <td>12666</td>\n",
       "      <td>12596</td>\n",
       "      <td>2061</td>\n",
       "      <td>POLYGON ((127.0655300172321 37.49006958228259,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>강남구</td>\n",
       "      <td>대치4동</td>\n",
       "      <td>11680</td>\n",
       "      <td>10080</td>\n",
       "      <td>2.08</td>\n",
       "      <td>21193</td>\n",
       "      <td>9995</td>\n",
       "      <td>11198</td>\n",
       "      <td>1806</td>\n",
       "      <td>POLYGON ((127.0608606032655 37.49887322207154,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>강남구</td>\n",
       "      <td>역삼1동</td>\n",
       "      <td>11680</td>\n",
       "      <td>22689</td>\n",
       "      <td>1.57</td>\n",
       "      <td>36534</td>\n",
       "      <td>17618</td>\n",
       "      <td>18916</td>\n",
       "      <td>3266</td>\n",
       "      <td>POLYGON ((127.0471782349514 37.50397402969755,...</td>\n",
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       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>강남구</td>\n",
       "      <td>역삼2동</td>\n",
       "      <td>11680</td>\n",
       "      <td>14910</td>\n",
       "      <td>2.47</td>\n",
       "      <td>37103</td>\n",
       "      <td>17499</td>\n",
       "      <td>19604</td>\n",
       "      <td>3330</td>\n",
       "      <td>POLYGON ((127.0525102427596 37.4970538815509, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>366</th>\n",
       "      <td>강남구</td>\n",
       "      <td>도곡1동</td>\n",
       "      <td>11680</td>\n",
       "      <td>8491</td>\n",
       "      <td>2.68</td>\n",
       "      <td>22882</td>\n",
       "      <td>10877</td>\n",
       "      <td>12005</td>\n",
       "      <td>2455</td>\n",
       "      <td>POLYGON ((127.0413458460977 37.48557052780573,...</td>\n",
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       "    <tr>\n",
       "      <th>367</th>\n",
       "      <td>강남구</td>\n",
       "      <td>도곡2동</td>\n",
       "      <td>11680</td>\n",
       "      <td>11943</td>\n",
       "      <td>2.91</td>\n",
       "      <td>34884</td>\n",
       "      <td>16203</td>\n",
       "      <td>18681</td>\n",
       "      <td>3938</td>\n",
       "      <td>POLYGON ((127.0565591748036 37.48768150139139,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368</th>\n",
       "      <td>강남구</td>\n",
       "      <td>개포1동</td>\n",
       "      <td>11680</td>\n",
       "      <td>7925</td>\n",
       "      <td>2.53</td>\n",
       "      <td>20111</td>\n",
       "      <td>9682</td>\n",
       "      <td>10429</td>\n",
       "      <td>2861</td>\n",
       "      <td>POLYGON ((127.0764100074407 37.48370494677163,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>369</th>\n",
       "      <td>강남구</td>\n",
       "      <td>개포4동</td>\n",
       "      <td>11680</td>\n",
       "      <td>7735</td>\n",
       "      <td>2.38</td>\n",
       "      <td>18525</td>\n",
       "      <td>9091</td>\n",
       "      <td>9434</td>\n",
       "      <td>1946</td>\n",
       "      <td>POLYGON ((127.0625318878364 37.47284246894814,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>강남구</td>\n",
       "      <td>일원본동</td>\n",
       "      <td>11680</td>\n",
       "      <td>8321</td>\n",
       "      <td>3.00</td>\n",
       "      <td>25027</td>\n",
       "      <td>12292</td>\n",
       "      <td>12735</td>\n",
       "      <td>2285</td>\n",
       "      <td>POLYGON ((127.0929906751923 37.47726100304872,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>강남구</td>\n",
       "      <td>일원1동</td>\n",
       "      <td>11680</td>\n",
       "      <td>7496</td>\n",
       "      <td>2.26</td>\n",
       "      <td>17108</td>\n",
       "      <td>8358</td>\n",
       "      <td>8750</td>\n",
       "      <td>2692</td>\n",
       "      <td>POLYGON ((127.096740694648 37.49583086240225, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>강남구</td>\n",
       "      <td>일원2동</td>\n",
       "      <td>11680</td>\n",
       "      <td>6589</td>\n",
       "      <td>2.49</td>\n",
       "      <td>16467</td>\n",
       "      <td>7895</td>\n",
       "      <td>8572</td>\n",
       "      <td>2452</td>\n",
       "      <td>POLYGON ((127.08362899995 37.49926446356682, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>강남구</td>\n",
       "      <td>수서동</td>\n",
       "      <td>11680</td>\n",
       "      <td>7864</td>\n",
       "      <td>2.12</td>\n",
       "      <td>16787</td>\n",
       "      <td>7712</td>\n",
       "      <td>9075</td>\n",
       "      <td>3644</td>\n",
       "      <td>POLYGON ((127.1081396454639 37.48930959967124,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>강남구</td>\n",
       "      <td>세곡동</td>\n",
       "      <td>11680</td>\n",
       "      <td>16878</td>\n",
       "      <td>2.65</td>\n",
       "      <td>44921</td>\n",
       "      <td>21497</td>\n",
       "      <td>23424</td>\n",
       "      <td>5376</td>\n",
       "      <td>POLYGON ((127.1110354206454 37.48293504402488,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>375</th>\n",
       "      <td>강남구</td>\n",
       "      <td>압구정동</td>\n",
       "      <td>11680</td>\n",
       "      <td>10677</td>\n",
       "      <td>2.61</td>\n",
       "      <td>28050</td>\n",
       "      <td>12977</td>\n",
       "      <td>15073</td>\n",
       "      <td>4494</td>\n",
       "      <td>POLYGON ((127.0459616923422 37.53250292666626,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>376</th>\n",
       "      <td>강남구</td>\n",
       "      <td>청담동</td>\n",
       "      <td>11680</td>\n",
       "      <td>12155</td>\n",
       "      <td>2.47</td>\n",
       "      <td>30269</td>\n",
       "      <td>14290</td>\n",
       "      <td>15979</td>\n",
       "      <td>3760</td>\n",
       "      <td>POLYGON ((127.0565665637636 37.52910117290872,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>377</th>\n",
       "      <td>강남구</td>\n",
       "      <td>대치2동</td>\n",
       "      <td>11680</td>\n",
       "      <td>13659</td>\n",
       "      <td>3.03</td>\n",
       "      <td>41566</td>\n",
       "      <td>21142</td>\n",
       "      <td>20424</td>\n",
       "      <td>4077</td>\n",
       "      <td>POLYGON ((127.0688034980296 37.51000278936197,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>378</th>\n",
       "      <td>강남구</td>\n",
       "      <td>개포2동</td>\n",
       "      <td>11680</td>\n",
       "      <td>5331</td>\n",
       "      <td>2.75</td>\n",
       "      <td>14678</td>\n",
       "      <td>7168</td>\n",
       "      <td>7510</td>\n",
       "      <td>1705</td>\n",
       "      <td>POLYGON ((127.0774490637626 37.48712375233896,...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    SGG_NM DONG_NM SGG_CODE  SEDAE  SEDAE_INGU  TOTAL_POP  MALE_POP  \\\n",
       "357    강남구     신사동    11680   7633        2.34      18105      8420   \n",
       "358    강남구    논현1동    11680  14090        1.68      24186     11192   \n",
       "359    강남구    논현2동    11680  11146        2.00      22573     10587   \n",
       "360    강남구    삼성1동    11680   5811        2.56      15193      7650   \n",
       "361    강남구    삼성2동    11680  12815        2.29      29628     14130   \n",
       "362    강남구    대치1동    11680   7374        3.42      25262     12666   \n",
       "363    강남구    대치4동    11680  10080        2.08      21193      9995   \n",
       "364    강남구    역삼1동    11680  22689        1.57      36534     17618   \n",
       "365    강남구    역삼2동    11680  14910        2.47      37103     17499   \n",
       "366    강남구    도곡1동    11680   8491        2.68      22882     10877   \n",
       "367    강남구    도곡2동    11680  11943        2.91      34884     16203   \n",
       "368    강남구    개포1동    11680   7925        2.53      20111      9682   \n",
       "369    강남구    개포4동    11680   7735        2.38      18525      9091   \n",
       "370    강남구    일원본동    11680   8321        3.00      25027     12292   \n",
       "371    강남구    일원1동    11680   7496        2.26      17108      8358   \n",
       "372    강남구    일원2동    11680   6589        2.49      16467      7895   \n",
       "373    강남구     수서동    11680   7864        2.12      16787      7712   \n",
       "374    강남구     세곡동    11680  16878        2.65      44921     21497   \n",
       "375    강남구    압구정동    11680  10677        2.61      28050     12977   \n",
       "376    강남구     청담동    11680  12155        2.47      30269     14290   \n",
       "377    강남구    대치2동    11680  13659        3.03      41566     21142   \n",
       "378    강남구    개포2동    11680   5331        2.75      14678      7168   \n",
       "\n",
       "     FEMALE_POP  65_OVER                                               geom  \n",
       "357        9685     2691  POLYGON ((127.0280781532315 37.519584003369, 1...  \n",
       "358       12994     2672  POLYGON ((127.0338873528466 37.5073920313264, ...  \n",
       "359       11986     2782  POLYGON ((127.0391780751905 37.52290539552295,...  \n",
       "360        7543     1900  POLYGON ((127.0669618590224 37.52508139275426,...  \n",
       "361       15498     2867  POLYGON ((127.05669182524 37.50685502947763, 1...  \n",
       "362       12596     2061  POLYGON ((127.0655300172321 37.49006958228259,...  \n",
       "363       11198     1806  POLYGON ((127.0608606032655 37.49887322207154,...  \n",
       "364       18916     3266  POLYGON ((127.0471782349514 37.50397402969755,...  \n",
       "365       19604     3330  POLYGON ((127.0525102427596 37.4970538815509, ...  \n",
       "366       12005     2455  POLYGON ((127.0413458460977 37.48557052780573,...  \n",
       "367       18681     3938  POLYGON ((127.0565591748036 37.48768150139139,...  \n",
       "368       10429     2861  POLYGON ((127.0764100074407 37.48370494677163,...  \n",
       "369        9434     1946  POLYGON ((127.0625318878364 37.47284246894814,...  \n",
       "370       12735     2285  POLYGON ((127.0929906751923 37.47726100304872,...  \n",
       "371        8750     2692  POLYGON ((127.096740694648 37.49583086240225, ...  \n",
       "372        8572     2452  POLYGON ((127.08362899995 37.49926446356682, 1...  \n",
       "373        9075     3644  POLYGON ((127.1081396454639 37.48930959967124,...  \n",
       "374       23424     5376  POLYGON ((127.1110354206454 37.48293504402488,...  \n",
       "375       15073     4494  POLYGON ((127.0459616923422 37.53250292666626,...  \n",
       "376       15979     3760  POLYGON ((127.0565665637636 37.52910117290872,...  \n",
       "377       20424     4077  POLYGON ((127.0688034980296 37.51000278936197,...  \n",
       "378        7510     1705  POLYGON ((127.0774490637626 37.48712375233896,...  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _35 select_by_attribute\n",
    "selection_2 = _gdf[_gdf['SGG_NM'] == '강남구']\n",
    "selection_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1222e6e80>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# _36 선택된 GeoDataFrame plot()으로 확인하기\n",
    "selection_2.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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>SGG_NM</th>\n",
       "      <th>DONG_NM</th>\n",
       "      <th>SGG_CODE</th>\n",
       "      <th>SEDAE</th>\n",
       "      <th>SEDAE_INGU</th>\n",
       "      <th>TOTAL_POP</th>\n",
       "      <th>MALE_POP</th>\n",
       "      <th>FEMALE_POP</th>\n",
       "      <th>65_OVER</th>\n",
       "      <th>geom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>339</th>\n",
       "      <td>서초구</td>\n",
       "      <td>서초1동</td>\n",
       "      <td>11650</td>\n",
       "      <td>9035</td>\n",
       "      <td>2.35</td>\n",
       "      <td>21532</td>\n",
       "      <td>10420</td>\n",
       "      <td>11112</td>\n",
       "      <td>2611</td>\n",
       "      <td>POLYGON ((127.0270147928412 37.48050810722698,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>340</th>\n",
       "      <td>서초구</td>\n",
       "      <td>서초2동</td>\n",
       "      <td>11650</td>\n",
       "      <td>7216</td>\n",
       "      <td>2.28</td>\n",
       "      <td>16766</td>\n",
       "      <td>7999</td>\n",
       "      <td>8767</td>\n",
       "      <td>1771</td>\n",
       "      <td>POLYGON ((127.0316232575204 37.48954007672874,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>341</th>\n",
       "      <td>서초구</td>\n",
       "      <td>서초3동</td>\n",
       "      <td>11650</td>\n",
       "      <td>12541</td>\n",
       "      <td>2.40</td>\n",
       "      <td>30439</td>\n",
       "      <td>14965</td>\n",
       "      <td>15474</td>\n",
       "      <td>4050</td>\n",
       "      <td>POLYGON ((127.0157623700279 37.49431858110463,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>342</th>\n",
       "      <td>서초구</td>\n",
       "      <td>서초4동</td>\n",
       "      <td>11650</td>\n",
       "      <td>10553</td>\n",
       "      <td>2.94</td>\n",
       "      <td>31285</td>\n",
       "      <td>15178</td>\n",
       "      <td>16107</td>\n",
       "      <td>3552</td>\n",
       "      <td>POLYGON ((127.0276351080783 37.49796430342112,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>343</th>\n",
       "      <td>서초구</td>\n",
       "      <td>잠원동</td>\n",
       "      <td>11650</td>\n",
       "      <td>13837</td>\n",
       "      <td>2.51</td>\n",
       "      <td>34940</td>\n",
       "      <td>16572</td>\n",
       "      <td>18368</td>\n",
       "      <td>3520</td>\n",
       "      <td>POLYGON ((127.0194410495604 37.51598724164066,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>344</th>\n",
       "      <td>서초구</td>\n",
       "      <td>반포본동</td>\n",
       "      <td>11650</td>\n",
       "      <td>4235</td>\n",
       "      <td>3.02</td>\n",
       "      <td>12826</td>\n",
       "      <td>6054</td>\n",
       "      <td>6772</td>\n",
       "      <td>1766</td>\n",
       "      <td>POLYGON ((126.9893793179576 37.5127079765066, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>345</th>\n",
       "      <td>서초구</td>\n",
       "      <td>반포1동</td>\n",
       "      <td>11650</td>\n",
       "      <td>12906</td>\n",
       "      <td>2.20</td>\n",
       "      <td>28665</td>\n",
       "      <td>13753</td>\n",
       "      <td>14912</td>\n",
       "      <td>2577</td>\n",
       "      <td>POLYGON ((127.0244700492047 37.50457187505761,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>346</th>\n",
       "      <td>서초구</td>\n",
       "      <td>반포2동</td>\n",
       "      <td>11650</td>\n",
       "      <td>7878</td>\n",
       "      <td>3.09</td>\n",
       "      <td>24506</td>\n",
       "      <td>11740</td>\n",
       "      <td>12766</td>\n",
       "      <td>2699</td>\n",
       "      <td>POLYGON ((127.0009280362828 37.50527051031399,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>347</th>\n",
       "      <td>서초구</td>\n",
       "      <td>반포3동</td>\n",
       "      <td>11650</td>\n",
       "      <td>6453</td>\n",
       "      <td>2.89</td>\n",
       "      <td>18721</td>\n",
       "      <td>8931</td>\n",
       "      <td>9790</td>\n",
       "      <td>2044</td>\n",
       "      <td>POLYGON ((127.0116219296791 37.50830799626219,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>348</th>\n",
       "      <td>서초구</td>\n",
       "      <td>반포4동</td>\n",
       "      <td>11650</td>\n",
       "      <td>7327</td>\n",
       "      <td>2.72</td>\n",
       "      <td>20443</td>\n",
       "      <td>9715</td>\n",
       "      <td>10728</td>\n",
       "      <td>2368</td>\n",
       "      <td>POLYGON ((127.0123823067712 37.49937041702919,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>349</th>\n",
       "      <td>서초구</td>\n",
       "      <td>방배본동</td>\n",
       "      <td>11650</td>\n",
       "      <td>7852</td>\n",
       "      <td>2.75</td>\n",
       "      <td>21805</td>\n",
       "      <td>10198</td>\n",
       "      <td>11607</td>\n",
       "      <td>2621</td>\n",
       "      <td>POLYGON ((126.9877476109485 37.4982352340315, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>350</th>\n",
       "      <td>서초구</td>\n",
       "      <td>방배1동</td>\n",
       "      <td>11650</td>\n",
       "      <td>7366</td>\n",
       "      <td>2.33</td>\n",
       "      <td>17293</td>\n",
       "      <td>8133</td>\n",
       "      <td>9160</td>\n",
       "      <td>2344</td>\n",
       "      <td>POLYGON ((127.0021516263079 37.48229539968449,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>351</th>\n",
       "      <td>서초구</td>\n",
       "      <td>방배2동</td>\n",
       "      <td>11650</td>\n",
       "      <td>11088</td>\n",
       "      <td>2.44</td>\n",
       "      <td>27221</td>\n",
       "      <td>12969</td>\n",
       "      <td>14252</td>\n",
       "      <td>3956</td>\n",
       "      <td>POLYGON ((126.9936378461754 37.48018051362616,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>352</th>\n",
       "      <td>서초구</td>\n",
       "      <td>방배3동</td>\n",
       "      <td>11650</td>\n",
       "      <td>8567</td>\n",
       "      <td>2.62</td>\n",
       "      <td>22584</td>\n",
       "      <td>10873</td>\n",
       "      <td>11711</td>\n",
       "      <td>3270</td>\n",
       "      <td>POLYGON ((127.0103100761861 37.47226020215308,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>353</th>\n",
       "      <td>서초구</td>\n",
       "      <td>방배4동</td>\n",
       "      <td>11650</td>\n",
       "      <td>10370</td>\n",
       "      <td>2.51</td>\n",
       "      <td>26392</td>\n",
       "      <td>12135</td>\n",
       "      <td>14257</td>\n",
       "      <td>3235</td>\n",
       "      <td>POLYGON ((127.0002678936836 37.491946693102, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>354</th>\n",
       "      <td>서초구</td>\n",
       "      <td>양재1동</td>\n",
       "      <td>11650</td>\n",
       "      <td>18225</td>\n",
       "      <td>2.57</td>\n",
       "      <td>47275</td>\n",
       "      <td>22634</td>\n",
       "      <td>24641</td>\n",
       "      <td>5668</td>\n",
       "      <td>POLYGON ((127.0439421898421 37.47971047664745,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>355</th>\n",
       "      <td>서초구</td>\n",
       "      <td>양재2동</td>\n",
       "      <td>11650</td>\n",
       "      <td>10947</td>\n",
       "      <td>2.15</td>\n",
       "      <td>23836</td>\n",
       "      <td>11939</td>\n",
       "      <td>11897</td>\n",
       "      <td>2438</td>\n",
       "      <td>POLYGON ((127.0495805879957 37.47048749255598,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356</th>\n",
       "      <td>서초구</td>\n",
       "      <td>내곡동</td>\n",
       "      <td>11650</td>\n",
       "      <td>7198</td>\n",
       "      <td>2.61</td>\n",
       "      <td>18872</td>\n",
       "      <td>9214</td>\n",
       "      <td>9658</td>\n",
       "      <td>2715</td>\n",
       "      <td>POLYGON ((127.0851618267097 37.47527333765135,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>357</th>\n",
       "      <td>강남구</td>\n",
       "      <td>신사동</td>\n",
       "      <td>11680</td>\n",
       "      <td>7633</td>\n",
       "      <td>2.34</td>\n",
       "      <td>18105</td>\n",
       "      <td>8420</td>\n",
       "      <td>9685</td>\n",
       "      <td>2691</td>\n",
       "      <td>POLYGON ((127.0280781532315 37.519584003369, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>358</th>\n",
       "      <td>강남구</td>\n",
       "      <td>논현1동</td>\n",
       "      <td>11680</td>\n",
       "      <td>14090</td>\n",
       "      <td>1.68</td>\n",
       "      <td>24186</td>\n",
       "      <td>11192</td>\n",
       "      <td>12994</td>\n",
       "      <td>2672</td>\n",
       "      <td>POLYGON ((127.0338873528466 37.5073920313264, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>359</th>\n",
       "      <td>강남구</td>\n",
       "      <td>논현2동</td>\n",
       "      <td>11680</td>\n",
       "      <td>11146</td>\n",
       "      <td>2.00</td>\n",
       "      <td>22573</td>\n",
       "      <td>10587</td>\n",
       "      <td>11986</td>\n",
       "      <td>2782</td>\n",
       "      <td>POLYGON ((127.0391780751905 37.52290539552295,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>360</th>\n",
       "      <td>강남구</td>\n",
       "      <td>삼성1동</td>\n",
       "      <td>11680</td>\n",
       "      <td>5811</td>\n",
       "      <td>2.56</td>\n",
       "      <td>15193</td>\n",
       "      <td>7650</td>\n",
       "      <td>7543</td>\n",
       "      <td>1900</td>\n",
       "      <td>POLYGON ((127.0669618590224 37.52508139275426,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>강남구</td>\n",
       "      <td>삼성2동</td>\n",
       "      <td>11680</td>\n",
       "      <td>12815</td>\n",
       "      <td>2.29</td>\n",
       "      <td>29628</td>\n",
       "      <td>14130</td>\n",
       "      <td>15498</td>\n",
       "      <td>2867</td>\n",
       "      <td>POLYGON ((127.05669182524 37.50685502947763, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>강남구</td>\n",
       "      <td>대치1동</td>\n",
       "      <td>11680</td>\n",
       "      <td>7374</td>\n",
       "      <td>3.42</td>\n",
       "      <td>25262</td>\n",
       "      <td>12666</td>\n",
       "      <td>12596</td>\n",
       "      <td>2061</td>\n",
       "      <td>POLYGON ((127.0655300172321 37.49006958228259,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>강남구</td>\n",
       "      <td>대치4동</td>\n",
       "      <td>11680</td>\n",
       "      <td>10080</td>\n",
       "      <td>2.08</td>\n",
       "      <td>21193</td>\n",
       "      <td>9995</td>\n",
       "      <td>11198</td>\n",
       "      <td>1806</td>\n",
       "      <td>POLYGON ((127.0608606032655 37.49887322207154,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>강남구</td>\n",
       "      <td>역삼1동</td>\n",
       "      <td>11680</td>\n",
       "      <td>22689</td>\n",
       "      <td>1.57</td>\n",
       "      <td>36534</td>\n",
       "      <td>17618</td>\n",
       "      <td>18916</td>\n",
       "      <td>3266</td>\n",
       "      <td>POLYGON ((127.0471782349514 37.50397402969755,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>강남구</td>\n",
       "      <td>역삼2동</td>\n",
       "      <td>11680</td>\n",
       "      <td>14910</td>\n",
       "      <td>2.47</td>\n",
       "      <td>37103</td>\n",
       "      <td>17499</td>\n",
       "      <td>19604</td>\n",
       "      <td>3330</td>\n",
       "      <td>POLYGON ((127.0525102427596 37.4970538815509, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>366</th>\n",
       "      <td>강남구</td>\n",
       "      <td>도곡1동</td>\n",
       "      <td>11680</td>\n",
       "      <td>8491</td>\n",
       "      <td>2.68</td>\n",
       "      <td>22882</td>\n",
       "      <td>10877</td>\n",
       "      <td>12005</td>\n",
       "      <td>2455</td>\n",
       "      <td>POLYGON ((127.0413458460977 37.48557052780573,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>367</th>\n",
       "      <td>강남구</td>\n",
       "      <td>도곡2동</td>\n",
       "      <td>11680</td>\n",
       "      <td>11943</td>\n",
       "      <td>2.91</td>\n",
       "      <td>34884</td>\n",
       "      <td>16203</td>\n",
       "      <td>18681</td>\n",
       "      <td>3938</td>\n",
       "      <td>POLYGON ((127.0565591748036 37.48768150139139,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368</th>\n",
       "      <td>강남구</td>\n",
       "      <td>개포1동</td>\n",
       "      <td>11680</td>\n",
       "      <td>7925</td>\n",
       "      <td>2.53</td>\n",
       "      <td>20111</td>\n",
       "      <td>9682</td>\n",
       "      <td>10429</td>\n",
       "      <td>2861</td>\n",
       "      <td>POLYGON ((127.0764100074407 37.48370494677163,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>369</th>\n",
       "      <td>강남구</td>\n",
       "      <td>개포4동</td>\n",
       "      <td>11680</td>\n",
       "      <td>7735</td>\n",
       "      <td>2.38</td>\n",
       "      <td>18525</td>\n",
       "      <td>9091</td>\n",
       "      <td>9434</td>\n",
       "      <td>1946</td>\n",
       "      <td>POLYGON ((127.0625318878364 37.47284246894814,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>강남구</td>\n",
       "      <td>일원본동</td>\n",
       "      <td>11680</td>\n",
       "      <td>8321</td>\n",
       "      <td>3.00</td>\n",
       "      <td>25027</td>\n",
       "      <td>12292</td>\n",
       "      <td>12735</td>\n",
       "      <td>2285</td>\n",
       "      <td>POLYGON ((127.0929906751923 37.47726100304872,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>강남구</td>\n",
       "      <td>일원1동</td>\n",
       "      <td>11680</td>\n",
       "      <td>7496</td>\n",
       "      <td>2.26</td>\n",
       "      <td>17108</td>\n",
       "      <td>8358</td>\n",
       "      <td>8750</td>\n",
       "      <td>2692</td>\n",
       "      <td>POLYGON ((127.096740694648 37.49583086240225, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>강남구</td>\n",
       "      <td>일원2동</td>\n",
       "      <td>11680</td>\n",
       "      <td>6589</td>\n",
       "      <td>2.49</td>\n",
       "      <td>16467</td>\n",
       "      <td>7895</td>\n",
       "      <td>8572</td>\n",
       "      <td>2452</td>\n",
       "      <td>POLYGON ((127.08362899995 37.49926446356682, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>강남구</td>\n",
       "      <td>수서동</td>\n",
       "      <td>11680</td>\n",
       "      <td>7864</td>\n",
       "      <td>2.12</td>\n",
       "      <td>16787</td>\n",
       "      <td>7712</td>\n",
       "      <td>9075</td>\n",
       "      <td>3644</td>\n",
       "      <td>POLYGON ((127.1081396454639 37.48930959967124,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>강남구</td>\n",
       "      <td>세곡동</td>\n",
       "      <td>11680</td>\n",
       "      <td>16878</td>\n",
       "      <td>2.65</td>\n",
       "      <td>44921</td>\n",
       "      <td>21497</td>\n",
       "      <td>23424</td>\n",
       "      <td>5376</td>\n",
       "      <td>POLYGON ((127.1110354206454 37.48293504402488,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>375</th>\n",
       "      <td>강남구</td>\n",
       "      <td>압구정동</td>\n",
       "      <td>11680</td>\n",
       "      <td>10677</td>\n",
       "      <td>2.61</td>\n",
       "      <td>28050</td>\n",
       "      <td>12977</td>\n",
       "      <td>15073</td>\n",
       "      <td>4494</td>\n",
       "      <td>POLYGON ((127.0459616923422 37.53250292666626,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>376</th>\n",
       "      <td>강남구</td>\n",
       "      <td>청담동</td>\n",
       "      <td>11680</td>\n",
       "      <td>12155</td>\n",
       "      <td>2.47</td>\n",
       "      <td>30269</td>\n",
       "      <td>14290</td>\n",
       "      <td>15979</td>\n",
       "      <td>3760</td>\n",
       "      <td>POLYGON ((127.0565665637636 37.52910117290872,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>377</th>\n",
       "      <td>강남구</td>\n",
       "      <td>대치2동</td>\n",
       "      <td>11680</td>\n",
       "      <td>13659</td>\n",
       "      <td>3.03</td>\n",
       "      <td>41566</td>\n",
       "      <td>21142</td>\n",
       "      <td>20424</td>\n",
       "      <td>4077</td>\n",
       "      <td>POLYGON ((127.0688034980296 37.51000278936197,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>378</th>\n",
       "      <td>강남구</td>\n",
       "      <td>개포2동</td>\n",
       "      <td>11680</td>\n",
       "      <td>5331</td>\n",
       "      <td>2.75</td>\n",
       "      <td>14678</td>\n",
       "      <td>7168</td>\n",
       "      <td>7510</td>\n",
       "      <td>1705</td>\n",
       "      <td>POLYGON ((127.0774490637626 37.48712375233896,...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    SGG_NM DONG_NM SGG_CODE  SEDAE  SEDAE_INGU  TOTAL_POP  MALE_POP  \\\n",
       "339    서초구    서초1동    11650   9035        2.35      21532     10420   \n",
       "340    서초구    서초2동    11650   7216        2.28      16766      7999   \n",
       "341    서초구    서초3동    11650  12541        2.40      30439     14965   \n",
       "342    서초구    서초4동    11650  10553        2.94      31285     15178   \n",
       "343    서초구     잠원동    11650  13837        2.51      34940     16572   \n",
       "344    서초구    반포본동    11650   4235        3.02      12826      6054   \n",
       "345    서초구    반포1동    11650  12906        2.20      28665     13753   \n",
       "346    서초구    반포2동    11650   7878        3.09      24506     11740   \n",
       "347    서초구    반포3동    11650   6453        2.89      18721      8931   \n",
       "348    서초구    반포4동    11650   7327        2.72      20443      9715   \n",
       "349    서초구    방배본동    11650   7852        2.75      21805     10198   \n",
       "350    서초구    방배1동    11650   7366        2.33      17293      8133   \n",
       "351    서초구    방배2동    11650  11088        2.44      27221     12969   \n",
       "352    서초구    방배3동    11650   8567        2.62      22584     10873   \n",
       "353    서초구    방배4동    11650  10370        2.51      26392     12135   \n",
       "354    서초구    양재1동    11650  18225        2.57      47275     22634   \n",
       "355    서초구    양재2동    11650  10947        2.15      23836     11939   \n",
       "356    서초구     내곡동    11650   7198        2.61      18872      9214   \n",
       "357    강남구     신사동    11680   7633        2.34      18105      8420   \n",
       "358    강남구    논현1동    11680  14090        1.68      24186     11192   \n",
       "359    강남구    논현2동    11680  11146        2.00      22573     10587   \n",
       "360    강남구    삼성1동    11680   5811        2.56      15193      7650   \n",
       "361    강남구    삼성2동    11680  12815        2.29      29628     14130   \n",
       "362    강남구    대치1동    11680   7374        3.42      25262     12666   \n",
       "363    강남구    대치4동    11680  10080        2.08      21193      9995   \n",
       "364    강남구    역삼1동    11680  22689        1.57      36534     17618   \n",
       "365    강남구    역삼2동    11680  14910        2.47      37103     17499   \n",
       "366    강남구    도곡1동    11680   8491        2.68      22882     10877   \n",
       "367    강남구    도곡2동    11680  11943        2.91      34884     16203   \n",
       "368    강남구    개포1동    11680   7925        2.53      20111      9682   \n",
       "369    강남구    개포4동    11680   7735        2.38      18525      9091   \n",
       "370    강남구    일원본동    11680   8321        3.00      25027     12292   \n",
       "371    강남구    일원1동    11680   7496        2.26      17108      8358   \n",
       "372    강남구    일원2동    11680   6589        2.49      16467      7895   \n",
       "373    강남구     수서동    11680   7864        2.12      16787      7712   \n",
       "374    강남구     세곡동    11680  16878        2.65      44921     21497   \n",
       "375    강남구    압구정동    11680  10677        2.61      28050     12977   \n",
       "376    강남구     청담동    11680  12155        2.47      30269     14290   \n",
       "377    강남구    대치2동    11680  13659        3.03      41566     21142   \n",
       "378    강남구    개포2동    11680   5331        2.75      14678      7168   \n",
       "\n",
       "     FEMALE_POP  65_OVER                                               geom  \n",
       "339       11112     2611  POLYGON ((127.0270147928412 37.48050810722698,...  \n",
       "340        8767     1771  POLYGON ((127.0316232575204 37.48954007672874,...  \n",
       "341       15474     4050  POLYGON ((127.0157623700279 37.49431858110463,...  \n",
       "342       16107     3552  POLYGON ((127.0276351080783 37.49796430342112,...  \n",
       "343       18368     3520  POLYGON ((127.0194410495604 37.51598724164066,...  \n",
       "344        6772     1766  POLYGON ((126.9893793179576 37.5127079765066, ...  \n",
       "345       14912     2577  POLYGON ((127.0244700492047 37.50457187505761,...  \n",
       "346       12766     2699  POLYGON ((127.0009280362828 37.50527051031399,...  \n",
       "347        9790     2044  POLYGON ((127.0116219296791 37.50830799626219,...  \n",
       "348       10728     2368  POLYGON ((127.0123823067712 37.49937041702919,...  \n",
       "349       11607     2621  POLYGON ((126.9877476109485 37.4982352340315, ...  \n",
       "350        9160     2344  POLYGON ((127.0021516263079 37.48229539968449,...  \n",
       "351       14252     3956  POLYGON ((126.9936378461754 37.48018051362616,...  \n",
       "352       11711     3270  POLYGON ((127.0103100761861 37.47226020215308,...  \n",
       "353       14257     3235  POLYGON ((127.0002678936836 37.491946693102, 1...  \n",
       "354       24641     5668  POLYGON ((127.0439421898421 37.47971047664745,...  \n",
       "355       11897     2438  POLYGON ((127.0495805879957 37.47048749255598,...  \n",
       "356        9658     2715  POLYGON ((127.0851618267097 37.47527333765135,...  \n",
       "357        9685     2691  POLYGON ((127.0280781532315 37.519584003369, 1...  \n",
       "358       12994     2672  POLYGON ((127.0338873528466 37.5073920313264, ...  \n",
       "359       11986     2782  POLYGON ((127.0391780751905 37.52290539552295,...  \n",
       "360        7543     1900  POLYGON ((127.0669618590224 37.52508139275426,...  \n",
       "361       15498     2867  POLYGON ((127.05669182524 37.50685502947763, 1...  \n",
       "362       12596     2061  POLYGON ((127.0655300172321 37.49006958228259,...  \n",
       "363       11198     1806  POLYGON ((127.0608606032655 37.49887322207154,...  \n",
       "364       18916     3266  POLYGON ((127.0471782349514 37.50397402969755,...  \n",
       "365       19604     3330  POLYGON ((127.0525102427596 37.4970538815509, ...  \n",
       "366       12005     2455  POLYGON ((127.0413458460977 37.48557052780573,...  \n",
       "367       18681     3938  POLYGON ((127.0565591748036 37.48768150139139,...  \n",
       "368       10429     2861  POLYGON ((127.0764100074407 37.48370494677163,...  \n",
       "369        9434     1946  POLYGON ((127.0625318878364 37.47284246894814,...  \n",
       "370       12735     2285  POLYGON ((127.0929906751923 37.47726100304872,...  \n",
       "371        8750     2692  POLYGON ((127.096740694648 37.49583086240225, ...  \n",
       "372        8572     2452  POLYGON ((127.08362899995 37.49926446356682, 1...  \n",
       "373        9075     3644  POLYGON ((127.1081396454639 37.48930959967124,...  \n",
       "374       23424     5376  POLYGON ((127.1110354206454 37.48293504402488,...  \n",
       "375       15073     4494  POLYGON ((127.0459616923422 37.53250292666626,...  \n",
       "376       15979     3760  POLYGON ((127.0565665637636 37.52910117290872,...  \n",
       "377       20424     4077  POLYGON ((127.0688034980296 37.51000278936197,...  \n",
       "378        7510     1705  POLYGON ((127.0774490637626 37.48712375233896,...  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# _35 select_by_attribute \n",
    "# pandas의 and/or operator는 `&`, `\\` 이다\n",
    "selection_3 = _gdf[(_gdf['SGG_NM'] == '강남구') | (_gdf['SGG_NM'] == '서초구')]\n",
    "# selection_3 = _gdf[(_gdf['SGG_NM'] == '서초구')]\n",
    "selection_3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x122366be0>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "selection_3.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "# _37 선택된 파일 GeoJson으로 저장하기\n",
    "selection_2.to_file('./maps/output/gangnamgu.geojson', driver='GeoJSON')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}