geopandas3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9163866b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3e2e4531",
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2ceee2fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "boundaries = geopandas.read_file(\"/tmp/data/boundary-polygon-lvl6.shp\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6e213e9e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 4,
     "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": [
    "boundaries.plot(column=\"oktmo\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8df00cd1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 5,
     "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": [
    "(\n",
    "    boundaries[boundaries.NAME_EN == \"Giaginsky District\"]\n",
    "    .to_crs(\"EPSG:3395\")\n",
    "    .buffer(1000)\n",
    ").plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7cb34a7b",
   "metadata": {},
   "outputs": [],
   "source": [
    "boundaries[\"AREA\"] = boundaries.to_crs(\"EPSG:32637\").area / 10 ** 6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ea6d3966",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NAME</th>\n",
       "      <th>AREA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Гиагинский район</td>\n",
       "      <td>798.157228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Майкопский район</td>\n",
       "      <td>3679.852979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Кошехабльский район</td>\n",
       "      <td>602.941652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Тахтамукайский район</td>\n",
       "      <td>467.467497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Шовгеновский район</td>\n",
       "      <td>516.355858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Красногвардейский район</td>\n",
       "      <td>725.687762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>городской округ Майкоп</td>\n",
       "      <td>280.901994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>городской округ Адыгейск</td>\n",
       "      <td>33.496230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Теучежский район</td>\n",
       "      <td>709.741658</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       NAME         AREA\n",
       "0          Гиагинский район   798.157228\n",
       "1          Майкопский район  3679.852979\n",
       "2       Кошехабльский район   602.941652\n",
       "3      Тахтамукайский район   467.467497\n",
       "4        Шовгеновский район   516.355858\n",
       "5   Красногвардейский район   725.687762\n",
       "6    городской округ Майкоп   280.901994\n",
       "7  городской округ Адыгейск    33.496230\n",
       "8          Теучежский район   709.741658"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boundaries[[\"NAME\", \"AREA\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d8ab3752",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  </thead>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Giaginsky District</td>\n",
       "      <td>798.157228</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Maykopsky District</td>\n",
       "      <td>3679.852979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Koshekhablsky District</td>\n",
       "      <td>602.941652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Takhtamukaysky District</td>\n",
       "      <td>467.467497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Shovgenovsky District</td>\n",
       "      <td>516.355858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Krasnogvardeysky District</td>\n",
       "      <td>725.687762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Teuchezhsky District</td>\n",
       "      <td>709.741658</td>\n",
       "    </tr>\n",
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       "</table>\n",
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      "text/plain": [
       "                     NAME_EN         AREA\n",
       "0         Giaginsky District   798.157228\n",
       "1         Maykopsky District  3679.852979\n",
       "2     Koshekhablsky District   602.941652\n",
       "3    Takhtamukaysky District   467.467497\n",
       "4      Shovgenovsky District   516.355858\n",
       "5  Krasnogvardeysky District   725.687762\n",
       "8       Teuchezhsky District   709.741658"
      ]
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     "execution_count": 8,
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    "boundaries[[\"NAME_EN\", \"AREA\"]].dropna()"
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