var_grid_bike.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import folium\n",
    "import json\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import geopandas as gpd\n",
    "import fiona\n",
    "import os\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from shapely.geometry import Polygon, LineString, Point\n",
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "           gid  2030val           layer  \\\n",
       "0     다사579454     77.0  강남구 20,30대 인구수   \n",
       "1     다사613448     66.0  강남구 20,30대 인구수   \n",
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       "...        ...      ...             ...   \n",
       "9128  다사559438      NaN  서초구 20,30대 인구수   \n",
       "9129  다사618387      NaN  서초구 20,30대 인구수   \n",
       "9130  다사559464      NaN  서초구 20,30대 인구수   \n",
       "9131  다사585417      NaN  서초구 20,30대 인구수   \n",
       "9132  다사548430      NaN  서초구 20,30대 인구수   \n",
       "\n",
       "                                               geometry  \n",
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       "1     MULTIPOLYGON (((127.06216 37.50166, 127.06215 ...  \n",
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       "3     MULTIPOLYGON (((127.02817 37.50874, 127.02817 ...  \n",
       "4     MULTIPOLYGON (((127.03849 37.48714, 127.03848 ...  \n",
       "...                                                 ...  \n",
       "9128  MULTIPOLYGON (((127.00113 37.49240, 127.00112 ...  \n",
       "9129  MULTIPOLYGON (((127.06813 37.44669, 127.06813 ...  \n",
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       "\n",
       "[9133 rows x 4 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
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   ],
   "source": [
    "data = gpd.read_file('data/서울시 격자 인구 데이터/강남서초2030대인구수 - 복사본.geojson')\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0.0</td>\n",
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       "      <td>MULTIPOLYGON (((127.00097 37.51583, 127.00097 ...</td>\n",
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       "    <tr>\n",
       "      <th>9131</th>\n",
       "      <td>다사585417</td>\n",
       "      <td>0.0</td>\n",
       "      <td>서초구 20,30대 인구수</td>\n",
       "      <td>MULTIPOLYGON (((127.03066 37.47359, 127.03065 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9132</th>\n",
       "      <td>다사548430</td>\n",
       "      <td>0.0</td>\n",
       "      <td>서초구 20,30대 인구수</td>\n",
       "      <td>MULTIPOLYGON (((126.98873 37.48514, 126.98873 ...</td>\n",
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      ],
      "text/plain": [
       "           gid  2030val           layer  \\\n",
       "0     다사579454     77.0  강남구 20,30대 인구수   \n",
       "1     다사613448     66.0  강남구 20,30대 인구수   \n",
       "2     다사585452      0.0  강남구 20,30대 인구수   \n",
       "3     다사583456    227.0  강남구 20,30대 인구수   \n",
       "4     다사592432     85.0  강남구 20,30대 인구수   \n",
       "...        ...      ...             ...   \n",
       "9128  다사559438      0.0  서초구 20,30대 인구수   \n",
       "9129  다사618387      0.0  서초구 20,30대 인구수   \n",
       "9130  다사559464      0.0  서초구 20,30대 인구수   \n",
       "9131  다사585417      0.0  서초구 20,30대 인구수   \n",
       "9132  다사548430      0.0  서초구 20,30대 인구수   \n",
       "\n",
       "                                               geometry  \n",
       "0     MULTIPOLYGON (((127.02366 37.50691, 127.02365 ...  \n",
       "1     MULTIPOLYGON (((127.06216 37.50166, 127.06215 ...  \n",
       "2     MULTIPOLYGON (((127.03046 37.50514, 127.03045 ...  \n",
       "3     MULTIPOLYGON (((127.02817 37.50874, 127.02817 ...  \n",
       "4     MULTIPOLYGON (((127.03849 37.48714, 127.03848 ...  \n",
       "...                                                 ...  \n",
       "9128  MULTIPOLYGON (((127.00113 37.49240, 127.00112 ...  \n",
       "9129  MULTIPOLYGON (((127.06813 37.44669, 127.06813 ...  \n",
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       "9131  MULTIPOLYGON (((127.03066 37.47359, 127.03065 ...  \n",
       "9132  MULTIPOLYGON (((126.98873 37.48514, 126.98873 ...  \n",
       "\n",
       "[9133 rows x 4 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
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    }
   ],
   "source": [
    "data.loc[data['2030val'].apply(pd.isna), '2030val'] = 0\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_gid = data[['gid', 'geometry']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "      <th>9131</th>\n",
       "      <td>다사585417</td>\n",
       "      <td>MULTIPOLYGON (((127.03066 37.47359, 127.03065 ...</td>\n",
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       "           gid                                           geometry\n",
       "0     다사579454  MULTIPOLYGON (((127.02366 37.50691, 127.02365 ...\n",
       "1     다사613448  MULTIPOLYGON (((127.06216 37.50166, 127.06215 ...\n",
       "2     다사585452  MULTIPOLYGON (((127.03046 37.50514, 127.03045 ...\n",
       "3     다사583456  MULTIPOLYGON (((127.02817 37.50874, 127.02817 ...\n",
       "4     다사592432  MULTIPOLYGON (((127.03849 37.48714, 127.03848 ...\n",
       "...        ...                                                ...\n",
       "9128  다사559438  MULTIPOLYGON (((127.00113 37.49240, 127.00112 ...\n",
       "9129  다사618387  MULTIPOLYGON (((127.06813 37.44669, 127.06813 ...\n",
       "9130  다사559464  MULTIPOLYGON (((127.00097 37.51583, 127.00097 ...\n",
       "9131  다사585417  MULTIPOLYGON (((127.03066 37.47359, 127.03065 ...\n",
       "9132  다사548430  MULTIPOLYGON (((126.98873 37.48514, 126.98873 ...\n",
       "\n",
       "[9133 rows x 2 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_gid"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## 강남구서초구 출근 자전거"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('output/그리드 전처리 완료/자전거이용/강남서초출근자전거교차2 - 복사본.json',encoding='UTF-8') as json_file:\n",
    "    json_data = json.load(json_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [],
   "source": [
    "전처리전 = json_data[\"features\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'properties': {'COUNT': 0, 'gid': '다사605367'},\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'COUNT': 0, 'gid': '다사605367'}"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_data[\"features\"][0][\"properties\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'COUNT': 64, 'gid': '다사590486'}"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "json_data[\"features\"][16546][\"properties\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
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       " {'COUNT': 0, 'gid': '다사621388'},\n",
       " {'COUNT': 0, 'gid': '다사619389'},\n",
       " {'COUNT': 0, 'gid': '다사618388'},\n",
       " {'COUNT': 0, 'gid': '다사620388'},\n",
       " {'COUNT': 0, 'gid': '다사621386'},\n",
       " {'COUNT': 0, 'gid': '다사620389'},\n",
       " {'COUNT': 0, 'gid': '다사622388'},\n",
       " {'COUNT': 0, 'gid': '다사621387'},\n",
       " {'COUNT': 0, 'gid': '다사620387'},\n",
       " {'COUNT': 0, 'gid': '다사619386'},\n",
       " {'COUNT': 0, 'gid': '다사621389'},\n",
       " {'COUNT': 0, 'gid': '다사619387'},\n",
       " {'COUNT': 0, 'gid': '다사620386'},\n",
       " {'COUNT': 0, 'gid': '다사618387'},\n",
       " {'COUNT': 0, 'gid': '다사625389'},\n",
       " {'COUNT': 0, 'gid': '다사628389'},\n",
       " {'COUNT': 0, 'gid': '다사626388'},\n",
       " ...]"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "countgid = []\n",
    "for i in range(0,16547) :\n",
    "    a = json_data[\"features\"][i][\"properties\"]\n",
    "    countgid.append(a)\n",
    "    \n",
    "countgid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>COUNT</th>\n",
       "      <th>gid</th>\n",
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       "    <tr>\n",
       "      <th>16542</th>\n",
       "      <td>22</td>\n",
       "      <td>다사586486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16543</th>\n",
       "      <td>22</td>\n",
       "      <td>다사585486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16544</th>\n",
       "      <td>64</td>\n",
       "      <td>다사592486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16545</th>\n",
       "      <td>64</td>\n",
       "      <td>다사591486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16546</th>\n",
       "      <td>64</td>\n",
       "      <td>다사590486</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16547 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       COUNT       gid\n",
       "0          0  다사605367\n",
       "1          0  다사606367\n",
       "2          0  다사604366\n",
       "3          0  다사603366\n",
       "4          0  다사604367\n",
       "...      ...       ...\n",
       "16542     22  다사586486\n",
       "16543     22  다사585486\n",
       "16544     64  다사592486\n",
       "16545     64  다사591486\n",
       "16546     64  다사590486\n",
       "\n",
       "[16547 rows x 2 columns]"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(countgid)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>COUNT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gid</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>다사540449</th>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>다사540450</th>\n",
       "      <td>150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>다사540451</th>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>다사540452</th>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>다사540453</th>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>다사666409</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>다사666410</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>다사666411</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>다사667408</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>다사667409</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8942 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          COUNT\n",
       "gid            \n",
       "다사540449     38\n",
       "다사540450    150\n",
       "다사540451     81\n",
       "다사540452     81\n",
       "다사540453     81\n",
       "...         ...\n",
       "다사666409      7\n",
       "다사666410      5\n",
       "다사666411     10\n",
       "다사667408      5\n",
       "다사667409      7\n",
       "\n",
       "[8942 rows x 1 columns]"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result1 = df[['COUNT', 'gid']].groupby(['gid']).sum()\n",
    "result1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "result1.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>gid</th>\n",
       "      <th>COUNT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>다사540449</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>다사540450</td>\n",
       "      <td>150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>다사540451</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>다사540452</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>다사540453</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8937</th>\n",
       "      <td>다사666409</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8938</th>\n",
       "      <td>다사666410</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8939</th>\n",
       "      <td>다사666411</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8940</th>\n",
       "      <td>다사667408</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8941</th>\n",
       "      <td>다사667409</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8942 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           gid  COUNT\n",
       "0     다사540449     38\n",
       "1     다사540450    150\n",
       "2     다사540451     81\n",
       "3     다사540452     81\n",
       "4     다사540453     81\n",
       "...        ...    ...\n",
       "8937  다사666409      7\n",
       "8938  다사666410      5\n",
       "8939  다사666411     10\n",
       "8940  다사667408      5\n",
       "8941  다사667409      7\n",
       "\n",
       "[8942 rows x 2 columns]"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [],
   "source": [
    "result1.to_csv(\"output/그리드 전처리 완료/서초강남출근시간자전거.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 강남구서초구 퇴근 자전거"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('output/그리드 전처리 완료/자전거이용/강남서초퇴근자전거교차2 - 복사본.json',encoding='UTF-8') as json_file:\n",
    "    json_data2 = json.load(json_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "json_data2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       " {'COUNT': 0, 'gid': '다사601373'},\n",
       " {'COUNT': 0, 'gid': '다사601374'},\n",
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       " {'COUNT': 0, 'gid': '다사595387'},\n",
       " {'COUNT': 0, 'gid': '다사594387'},\n",
       " {'COUNT': 0, 'gid': '다사594388'},\n",
       " {'COUNT': 0, 'gid': '다사598388'},\n",
       " {'COUNT': 0, 'gid': '다사598387'},\n",
       " {'COUNT': 0, 'gid': '다사598389'},\n",
       " {'COUNT': 0, 'gid': '다사596386'},\n",
       " {'COUNT': 0, 'gid': '다사622387'},\n",
       " {'COUNT': 0, 'gid': '다사622386'},\n",
       " {'COUNT': 0, 'gid': '다사622389'},\n",
       " {'COUNT': 0, 'gid': '다사619388'},\n",
       " {'COUNT': 0, 'gid': '다사621388'},\n",
       " {'COUNT': 0, 'gid': '다사619389'},\n",
       " {'COUNT': 0, 'gid': '다사618388'},\n",
       " {'COUNT': 0, 'gid': '다사620388'},\n",
       " {'COUNT': 0, 'gid': '다사621386'},\n",
       " {'COUNT': 0, 'gid': '다사620389'},\n",
       " {'COUNT': 0, 'gid': '다사622388'},\n",
       " {'COUNT': 0, 'gid': '다사621387'},\n",
       " {'COUNT': 0, 'gid': '다사620387'},\n",
       " {'COUNT': 0, 'gid': '다사619386'},\n",
       " {'COUNT': 0, 'gid': '다사621389'},\n",
       " {'COUNT': 0, 'gid': '다사619387'},\n",
       " {'COUNT': 0, 'gid': '다사620386'},\n",
       " {'COUNT': 0, 'gid': '다사618387'},\n",
       " {'COUNT': 0, 'gid': '다사625389'},\n",
       " {'COUNT': 0, 'gid': '다사628389'},\n",
       " {'COUNT': 0, 'gid': '다사626388'},\n",
       " ...]"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "countgid2 = []\n",
    "for i in range(0,16547) :\n",
    "    a = json_data2[\"features\"][i][\"properties\"]\n",
    "    countgid2.append(a)\n",
    "    \n",
    "countgid2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>16543</th>\n",
       "      <td>135</td>\n",
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       "      <th>16544</th>\n",
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       "      <td>416</td>\n",
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       "      <th>16546</th>\n",
       "      <td>416</td>\n",
       "      <td>다사590486</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16547 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       COUNT       gid\n",
       "0          0  다사605367\n",
       "1          0  다사606367\n",
       "2          0  다사604366\n",
       "3          0  다사603366\n",
       "4          0  다사604367\n",
       "...      ...       ...\n",
       "16542    135  다사586486\n",
       "16543    135  다사585486\n",
       "16544    416  다사592486\n",
       "16545    416  다사591486\n",
       "16546    416  다사590486\n",
       "\n",
       "[16547 rows x 2 columns]"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.DataFrame(countgid2)\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>gid</th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
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       "      <th>다사540449</th>\n",
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       "      <th>다사540452</th>\n",
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       "      <th>다사667408</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>다사667409</th>\n",
       "      <td>8</td>\n",
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       "</table>\n",
       "<p>8942 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          COUNT\n",
       "gid            \n",
       "다사540449    217\n",
       "다사540450    951\n",
       "다사540451    530\n",
       "다사540452    530\n",
       "다사540453    530\n",
       "...         ...\n",
       "다사666409      8\n",
       "다사666410      7\n",
       "다사666411     21\n",
       "다사667408      4\n",
       "다사667409      8\n",
       "\n",
       "[8942 rows x 1 columns]"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result2 = df2[['COUNT', 'gid']].groupby(['gid']).sum()\n",
    "result2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "result2.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>8938</th>\n",
       "      <td>다사666410</td>\n",
       "      <td>7</td>\n",
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       "      <td>4</td>\n",
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       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8942 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           gid  COUNT\n",
       "0     다사540449    217\n",
       "1     다사540450    951\n",
       "2     다사540451    530\n",
       "3     다사540452    530\n",
       "4     다사540453    530\n",
       "...        ...    ...\n",
       "8937  다사666409      8\n",
       "8938  다사666410      7\n",
       "8939  다사666411     21\n",
       "8940  다사667408      4\n",
       "8941  다사667409      8\n",
       "\n",
       "[8942 rows x 2 columns]"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "result2.to_csv(\"output/그리드 전처리 완료/서초강남퇴근시간자전거.csv\")"
   ]
  }
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