2_shapefile.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install tqdm -q"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from tqdm import tqdm\n",
    "\n",
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "from shapely.geometry import Point, Polygon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "shapefile = 'data/M2/dis_sampa_23s.shp'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "geopandas.geodataframe.GeoDataFrame"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dis_sampa = gpd.read_file(shapefile)\n",
    "type(dis_sampa)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds_codigo</th>\n",
       "      <th>ds_nome</th>\n",
       "      <th>sp_codigo</th>\n",
       "      <th>sp_nome</th>\n",
       "      <th>area_km2</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>51</td>\n",
       "      <td>MANDAQUI</td>\n",
       "      <td>05</td>\n",
       "      <td>SANTANA-TUCURUVI</td>\n",
       "      <td>13.246426</td>\n",
       "      <td>POLYGON ((330995.449 7407882.882, 330997.253 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>52</td>\n",
       "      <td>MARSILAC</td>\n",
       "      <td>20</td>\n",
       "      <td>PARELHEIROS</td>\n",
       "      <td>208.184737</td>\n",
       "      <td>POLYGON ((336169.148 7355348.052, 336166.813 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>32</td>\n",
       "      <td>MOEMA</td>\n",
       "      <td>12</td>\n",
       "      <td>VILA MARIANA</td>\n",
       "      <td>9.078676</td>\n",
       "      <td>POLYGON ((331287.247 7392208.050, 331289.654 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>57</td>\n",
       "      <td>PARQUE DO CARMO</td>\n",
       "      <td>27</td>\n",
       "      <td>ITAQUERA</td>\n",
       "      <td>15.451409</td>\n",
       "      <td>POLYGON ((352642.665 7390165.168, 352633.278 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>60</td>\n",
       "      <td>PERDIZES</td>\n",
       "      <td>08</td>\n",
       "      <td>LAPA</td>\n",
       "      <td>6.337240</td>\n",
       "      <td>POLYGON ((330226.820 7396102.561, 330220.609 7...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  ds_codigo          ds_nome sp_codigo           sp_nome    area_km2  \\\n",
       "0        51         MANDAQUI        05  SANTANA-TUCURUVI   13.246426   \n",
       "1        52         MARSILAC        20       PARELHEIROS  208.184737   \n",
       "2        32            MOEMA        12      VILA MARIANA    9.078676   \n",
       "3        57  PARQUE DO CARMO        27          ITAQUERA   15.451409   \n",
       "4        60         PERDIZES        08              LAPA    6.337240   \n",
       "\n",
       "                                            geometry  \n",
       "0  POLYGON ((330995.449 7407882.882, 330997.253 7...  \n",
       "1  POLYGON ((336169.148 7355348.052, 336166.813 7...  \n",
       "2  POLYGON ((331287.247 7392208.050, 331289.654 7...  \n",
       "3  POLYGON ((352642.665 7390165.168, 352633.278 7...  \n",
       "4  POLYGON ((330226.820 7396102.561, 330220.609 7...  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dis_sampa.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'geopandas.geodataframe.GeoDataFrame'>\n",
      "RangeIndex: 96 entries, 0 to 95\n",
      "Data columns (total 6 columns):\n",
      " #   Column     Non-Null Count  Dtype   \n",
      "---  ------     --------------  -----   \n",
      " 0   ds_codigo  96 non-null     object  \n",
      " 1   ds_nome    96 non-null     object  \n",
      " 2   sp_codigo  96 non-null     object  \n",
      " 3   sp_nome    96 non-null     object  \n",
      " 4   area_km2   96 non-null     float64 \n",
      " 5   geometry   96 non-null     geometry\n",
      "dtypes: float64(1), geometry(1), object(4)\n",
      "memory usage: 4.6+ KB\n"
     ]
    }
   ],
   "source": [
    "dis_sampa.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10,10))\n",
    "\n",
    "dis_sampa.plot(ax=ax);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10,10))\n",
    "\n",
    "dis_sampa.plot(ax=ax)\n",
    "\n",
    "ax.set_ylabel('Norte - Sur')\n",
    "ax.set_xlabel('Oeste - Este')\n",
    "\n",
    "ax.ticklabel_format(style='plain')\n",
    "\n",
    "plt.yticks(rotation=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Seleccionar Geometrias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>ds_codigo</th>\n",
       "      <th>ds_nome</th>\n",
       "      <th>sp_codigo</th>\n",
       "      <th>sp_nome</th>\n",
       "      <th>area_km2</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>32</td>\n",
       "      <td>MOEMA</td>\n",
       "      <td>12</td>\n",
       "      <td>VILA MARIANA</td>\n",
       "      <td>9.078676</td>\n",
       "      <td>POLYGON ((331287.247 7392208.050, 331289.654 7...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  ds_codigo ds_nome sp_codigo       sp_nome  area_km2  \\\n",
       "2        32   MOEMA        12  VILA MARIANA  9.078676   \n",
       "\n",
       "                                            geometry  \n",
       "2  POLYGON ((331287.247 7392208.050, 331289.654 7...  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "moema = dis_sampa[dis_sampa['ds_nome'] == 'MOEMA']\n",
    "moema.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "out = 'output/moema.shp'\n",
    "\n",
    "moema.to_file(out)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    POLYGON ((330995.449 7407882.882, 330997.253 7...\n",
       "1    POLYGON ((336169.148 7355348.052, 336166.813 7...\n",
       "2    POLYGON ((331287.247 7392208.050, 331289.654 7...\n",
       "3    POLYGON ((352642.665 7390165.168, 352633.278 7...\n",
       "4    POLYGON ((330226.820 7396102.561, 330220.609 7...\n",
       "Name: geometry, dtype: geometry"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dis_sampa['geometry'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "área de MANDAQUI es 13246425.63 \n",
      "área de MARSILAC es 208184736.92 \n",
      "área de MOEMA es 9078676.33 \n",
      "área de PARQUE DO CARMO es 15451408.61 \n",
      "área de PERDIZES es 6337239.72 \n"
     ]
    }
   ],
   "source": [
    "for index, row in dis_sampa[:5].iterrows():\n",
    "    plg_area = row['geometry'].area\n",
    "    \n",
    "    print('área de {0} es {1:.2f} '.format(row['ds_nome'], plg_area))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>ds_codigo</th>\n",
       "      <th>ds_nome</th>\n",
       "      <th>sp_codigo</th>\n",
       "      <th>sp_nome</th>\n",
       "      <th>area_km2</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>51</td>\n",
       "      <td>MANDAQUI</td>\n",
       "      <td>05</td>\n",
       "      <td>SANTANA-TUCURUVI</td>\n",
       "      <td>13.246426</td>\n",
       "      <td>POLYGON ((330995.449 7407882.882, 330997.253 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>52</td>\n",
       "      <td>MARSILAC</td>\n",
       "      <td>20</td>\n",
       "      <td>PARELHEIROS</td>\n",
       "      <td>208.184737</td>\n",
       "      <td>POLYGON ((336169.148 7355348.052, 336166.813 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>32</td>\n",
       "      <td>MOEMA</td>\n",
       "      <td>12</td>\n",
       "      <td>VILA MARIANA</td>\n",
       "      <td>9.078676</td>\n",
       "      <td>POLYGON ((331287.247 7392208.050, 331289.654 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>57</td>\n",
       "      <td>PARQUE DO CARMO</td>\n",
       "      <td>27</td>\n",
       "      <td>ITAQUERA</td>\n",
       "      <td>15.451409</td>\n",
       "      <td>POLYGON ((352642.665 7390165.168, 352633.278 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>60</td>\n",
       "      <td>PERDIZES</td>\n",
       "      <td>08</td>\n",
       "      <td>LAPA</td>\n",
       "      <td>6.337240</td>\n",
       "      <td>POLYGON ((330226.820 7396102.561, 330220.609 7...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  ds_codigo          ds_nome sp_codigo           sp_nome    area_km2  \\\n",
       "0        51         MANDAQUI        05  SANTANA-TUCURUVI   13.246426   \n",
       "1        52         MARSILAC        20       PARELHEIROS  208.184737   \n",
       "2        32            MOEMA        12      VILA MARIANA    9.078676   \n",
       "3        57  PARQUE DO CARMO        27          ITAQUERA   15.451409   \n",
       "4        60         PERDIZES        08              LAPA    6.337240   \n",
       "\n",
       "                                            geometry  \n",
       "0  POLYGON ((330995.449 7407882.882, 330997.253 7...  \n",
       "1  POLYGON ((336169.148 7355348.052, 336166.813 7...  \n",
       "2  POLYGON ((331287.247 7392208.050, 331289.654 7...  \n",
       "3  POLYGON ((352642.665 7390165.168, 352633.278 7...  \n",
       "4  POLYGON ((330226.820 7396102.561, 330220.609 7...  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dis_sampa['area_km2'] = dis_sampa.area/10**6\n",
    "dis_sampa.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "área de MANDAQUI es 13.25 \n",
      "área de MARSILAC es 208.18 \n",
      "área de MOEMA es 9.08 \n",
      "área de PARQUE DO CARMO es 15.45 \n",
      "área de PERDIZES es 6.34 \n"
     ]
    }
   ],
   "source": [
    "for index, row in dis_sampa[:5].iterrows():\n",
    "    \n",
    "    print('área de {0} es {1:.2f} '.format(row['ds_nome'], row['area_km2']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "208.18 2.19 15.91\n"
     ]
    }
   ],
   "source": [
    "max_area = dis_sampa['area_km2'].max()\n",
    "min_area = dis_sampa['area_km2'].min()\n",
    "avg_area = dis_sampa['area_km2'].mean()\n",
    "\n",
    "print(round(max_area,2), round(min_area,2), round(avg_area,2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creando Geometrias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty GeoDataFrame\n",
       "Columns: []\n",
       "Index: []"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data = gpd.GeoDataFrame()\n",
    "\n",
    "new_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty GeoDataFrame\n",
       "Columns: [geometry]\n",
       "Index: []"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data['geometry'] = None\n",
    "\n",
    "new_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"100.0\" height=\"100.0\" viewBox=\"-23.563601163999998 -46.658423664000004 0.002097227999996676 0.00252352800000466\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,-93.31432380000001)\"><path fill-rule=\"evenodd\" fill=\"#66cc99\" stroke=\"#555555\" stroke-width=\"5.04705600000932e-05\" opacity=\"0.6\" d=\"M -23.5615974,-46.6573198 L -23.5626145,-46.6583302 L -23.5635077,-46.6572431 L -23.5635077,-46.6572431 L -23.5635077,-46.6572431 L -23.5624905,-46.6559936 L -23.5615974,-46.6573198 z\" /></g></svg>"
      ],
      "text/plain": [
       "<POLYGON ((-23.562 -46.657, -23.563 -46.658, -23.564 -46.657, -23.564 -46.65...>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coordenadas = [(-23.5615974,-46.6573198), (-23.5626145,-46.6583302), (-23.5635077,-46.6572431), (-23.5635077,-46.6572431), (-23.5635077,-46.6572431), (-23.5624905,-46.6559936)]\n",
    "\n",
    "trianon_plg = Polygon(coordenadas)\n",
    "trianon_plg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "POLYGON ((-23.5615974 -46.6573198, -23.5626145 -46.6583302, -23.5635077 -46.6572431, -23.5635077 -46.6572431, -23.5635077 -46.6572431, -23.5624905 -46.6559936, -23.5615974 -46.6573198))\n"
     ]
    }
   ],
   "source": [
    "print(trianon_plg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POLYGON ((-23.56160 -46.65732, -23.56261 -46.6...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            geometry\n",
       "0  POLYGON ((-23.56160 -46.65732, -23.56261 -46.6..."
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data.loc[0, 'geometry'] = trianon_plg\n",
    "new_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "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>geometry</th>\n",
       "      <th>lugar</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POLYGON ((-23.56160 -46.65732, -23.56261 -46.6...</td>\n",
       "      <td>Trianon</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            geometry    lugar\n",
       "0  POLYGON ((-23.56160 -46.65732, -23.56261 -46.6...  Trianon"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data.loc[0, 'lugar'] = 'Trianon'\n",
    "new_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CRS: Coordinate Reference System\n",
    "\n",
    "EPSG es un sistema de coordenadas Mercator, bastante comun que permite aproximar a una esfera"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "None\n"
     ]
    }
   ],
   "source": [
    "print(new_data.crs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "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>geometry</th>\n",
       "      <th>lugar</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POLYGON ((-23.562 -46.657, -23.563 -46.658, -2...</td>\n",
       "      <td>Trianon</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            geometry    lugar\n",
       "0  POLYGON ((-23.562 -46.657, -23.563 -46.658, -2...  Trianon"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data = new_data.set_crs('epsg:3857')\n",
    "new_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epsg:3857\n"
     ]
    }
   ],
   "source": [
    "print(new_data.crs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Projected CRS: EPSG:3857>\n",
       "Name: WGS 84 / Pseudo-Mercator\n",
       "Axis Info [cartesian]:\n",
       "- X[east]: Easting (metre)\n",
       "- Y[north]: Northing (metre)\n",
       "Area of Use:\n",
       "- name: World between 85.06°S and 85.06°N.\n",
       "- bounds: (-180.0, -85.06, 180.0, 85.06)\n",
       "Coordinate Operation:\n",
       "- name: Popular Visualisation Pseudo-Mercator\n",
       "- method: Popular Visualisation Pseudo Mercator\n",
       "Datum: World Geodetic System 1984 ensemble\n",
       "- Ellipsoid: WGS 84\n",
       "- Prime Meridian: Greenwich"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "out_shapefile = 'output/trianon_mercator.shp'\n",
    "\n",
    "new_data.to_file(out_shapefile)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Formato de Sistemas de Coordenadas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "shapefile = 'data/a__031_001_americaDoSul.shp'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "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>fid</th>\n",
       "      <th>ScaleRank</th>\n",
       "      <th>LabelRank</th>\n",
       "      <th>FeatureCla</th>\n",
       "      <th>SOVEREIGNT</th>\n",
       "      <th>SOV_A3</th>\n",
       "      <th>ADM0_DIF</th>\n",
       "      <th>LEVEL</th>\n",
       "      <th>TYPE</th>\n",
       "      <th>ADMIN</th>\n",
       "      <th>...</th>\n",
       "      <th>TERR_</th>\n",
       "      <th>NAME_SORT</th>\n",
       "      <th>MAP_COLOR</th>\n",
       "      <th>POP_EST</th>\n",
       "      <th>GDP_MD_EST</th>\n",
       "      <th>FIPS_10_</th>\n",
       "      <th>ISO_A2</th>\n",
       "      <th>ISO_A3</th>\n",
       "      <th>ISO_N3</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Adm-0 country</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>ARG</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Sovereign country</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>13.0</td>\n",
       "      <td>40913584.0</td>\n",
       "      <td>573900.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>AR</td>\n",
       "      <td>ARG</td>\n",
       "      <td>32.0</td>\n",
       "      <td>MULTIPOLYGON (((-68.56752 -54.87835, -68.58653...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Adm-0 country</td>\n",
       "      <td>Bolivia</td>\n",
       "      <td>BOL</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Sovereign country</td>\n",
       "      <td>Bolivia</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>Bolivia</td>\n",
       "      <td>3.0</td>\n",
       "      <td>9775246.0</td>\n",
       "      <td>43270.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>BO</td>\n",
       "      <td>BOL</td>\n",
       "      <td>68.0</td>\n",
       "      <td>POLYGON ((-60.24640 -15.47828, -60.23797 -15.5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Adm-0 country</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>BRA</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Sovereign country</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>7.0</td>\n",
       "      <td>198739269.0</td>\n",
       "      <td>1993000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>BR</td>\n",
       "      <td>BRA</td>\n",
       "      <td>76.0</td>\n",
       "      <td>MULTIPOLYGON (((-48.54186 -27.81670, -48.55117...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Adm-0 country</td>\n",
       "      <td>Chile</td>\n",
       "      <td>CHL</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Sovereign country</td>\n",
       "      <td>Chile</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>Chile</td>\n",
       "      <td>9.0</td>\n",
       "      <td>16601707.0</td>\n",
       "      <td>244500.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>CL</td>\n",
       "      <td>CHL</td>\n",
       "      <td>152.0</td>\n",
       "      <td>MULTIPOLYGON (((-67.49094 -55.83303, -67.52205...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Adm-0 country</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>COL</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Sovereign country</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>1.0</td>\n",
       "      <td>45644023.0</td>\n",
       "      <td>395400.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>CO</td>\n",
       "      <td>COL</td>\n",
       "      <td>170.0</td>\n",
       "      <td>MULTIPOLYGON (((-78.10657 2.51230, -78.13370 2...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   fid  ScaleRank  LabelRank     FeatureCla SOVEREIGNT SOV_A3  ADM0_DIF  \\\n",
       "0    1        1.0        2.0  Adm-0 country  Argentina    ARG       0.0   \n",
       "1    2        1.0        2.0  Adm-0 country    Bolivia    BOL       0.0   \n",
       "2    3        1.0        2.0  Adm-0 country     Brazil    BRA       0.0   \n",
       "3    4        1.0        2.0  Adm-0 country      Chile    CHL       0.0   \n",
       "4    5        1.0        2.0  Adm-0 country   Colombia    COL       0.0   \n",
       "\n",
       "   LEVEL               TYPE      ADMIN  ... TERR_  NAME_SORT MAP_COLOR  \\\n",
       "0    2.0  Sovereign country  Argentina  ...  None  Argentina      13.0   \n",
       "1    2.0  Sovereign country    Bolivia  ...  None    Bolivia       3.0   \n",
       "2    2.0  Sovereign country     Brazil  ...  None     Brazil       7.0   \n",
       "3    2.0  Sovereign country      Chile  ...  None      Chile       9.0   \n",
       "4    2.0  Sovereign country   Colombia  ...  None   Colombia       1.0   \n",
       "\n",
       "       POP_EST GDP_MD_EST FIPS_10_ ISO_A2 ISO_A3  ISO_N3  \\\n",
       "0   40913584.0   573900.0      0.0     AR    ARG    32.0   \n",
       "1    9775246.0    43270.0      0.0     BO    BOL    68.0   \n",
       "2  198739269.0  1993000.0      0.0     BR    BRA    76.0   \n",
       "3   16601707.0   244500.0      0.0     CL    CHL   152.0   \n",
       "4   45644023.0   395400.0      0.0     CO    COL   170.0   \n",
       "\n",
       "                                            geometry  \n",
       "0  MULTIPOLYGON (((-68.56752 -54.87835, -68.58653...  \n",
       "1  POLYGON ((-60.24640 -15.47828, -60.23797 -15.5...  \n",
       "2  MULTIPOLYGON (((-48.54186 -27.81670, -48.55117...  \n",
       "3  MULTIPOLYGON (((-67.49094 -55.83303, -67.52205...  \n",
       "4  MULTIPOLYGON (((-78.10657 2.51230, -78.13370 2...  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "brasil = gpd.read_file(shapefile)\n",
    "brasil.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Bound CRS: GEOGCS[\"SIRGAS 2000\",DATUM[\"Sistema_de_Referencia_ ...>\n",
       "Name: SIRGAS 2000\n",
       "Axis Info [ellipsoidal]:\n",
       "- lon[east]: Longitude (degree)\n",
       "- lat[north]: Latitude (degree)\n",
       "Area of Use:\n",
       "- undefined\n",
       "Coordinate Operation:\n",
       "- name: Transformation from SIRGAS 2000 to WGS84\n",
       "- method: Position Vector transformation (geog2D domain)\n",
       "Datum: Sistema de Referencia Geocentrico para las AmericaS 2000\n",
       "- Ellipsoid: GRS 1980\n",
       "- Prime Meridian: Greenwich\n",
       "Source CRS: SIRGAS 2000"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "brasil.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    MULTIPOLYGON (((-68.56752 -54.87835, -68.58653...\n",
       "1    POLYGON ((-60.24640 -15.47828, -60.23797 -15.5...\n",
       "2    MULTIPOLYGON (((-48.54186 -27.81670, -48.55117...\n",
       "3    MULTIPOLYGON (((-67.49094 -55.83303, -67.52205...\n",
       "4    MULTIPOLYGON (((-78.10657 2.51230, -78.13370 2...\n",
       "Name: geometry, dtype: geometry"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "brasil['geometry'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Projected CRS: EPSG:3395>\n",
       "Name: WGS 84 / World Mercator\n",
       "Axis Info [cartesian]:\n",
       "- E[east]: Easting (metre)\n",
       "- N[north]: Northing (metre)\n",
       "Area of Use:\n",
       "- name: World between 80°S and 84°N.\n",
       "- bounds: (-180.0, -80.0, 180.0, 84.0)\n",
       "Coordinate Operation:\n",
       "- name: World Mercator\n",
       "- method: Mercator (variant A)\n",
       "Datum: World Geodetic System 1984 ensemble\n",
       "- Ellipsoid: WGS 84\n",
       "- Prime Meridian: Greenwich"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bra_wgs84 = brasil.to_crs(epsg=3395)\n",
    "bra_wgs84.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    MULTIPOLYGON (((-7632900.902 -7303316.834, -76...\n",
       "1    POLYGON ((-6706598.061 -1732985.779, -6705660....\n",
       "2    MULTIPOLYGON (((-5403655.625 -3205948.989, -54...\n",
       "3    MULTIPOLYGON (((-7513057.108 -7489864.851, -75...\n",
       "4    MULTIPOLYGON (((-8694783.757 277886.287, -8697...\n",
       "Name: geometry, dtype: geometry"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bra_wgs84['geometry'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Projected CRS: ESRI:102033>\n",
       "Name: South_America_Albers_Equal_Area_Conic\n",
       "Axis Info [cartesian]:\n",
       "- E[east]: Easting (metre)\n",
       "- N[north]: Northing (metre)\n",
       "Area of Use:\n",
       "- name: South America\n",
       "- bounds: (-90.0, -60.0, -30.0, 15.0)\n",
       "Coordinate Operation:\n",
       "- name: South_America_Albers_Equal_Area_Conic\n",
       "- method: Albers Equal Area\n",
       "Datum: South American Datum 1969\n",
       "- Ellipsoid: GRS 1967 Modified\n",
       "- Prime Meridian: Greenwich"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bra_albers = brasil.to_crs(crs='esri:102033')\n",
    "bra_albers.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    MULTIPOLYGON (((-633098.193 -2505557.779, -634...\n",
       "1    POLYGON ((-25349.139 1922291.478, -24476.537 1...\n",
       "2    MULTIPOLYGON (((1071381.054 446268.182, 107048...\n",
       "3    MULTIPOLYGON (((-549076.510 -2592766.934, -551...\n",
       "4    MULTIPOLYGON (((-2100204.193 3795190.587, -210...\n",
       "Name: geometry, dtype: geometry"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bra_albers['geometry'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyproj import CRS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Texto extraido de [aqui](https://github.com/OSGeo/spatialreference.org/blob/master/scripts/sr-org.json)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc = CRS('PROJCS[\\\"Brazil / Albers Equal Area Conic (WGS84)\\\",GEOGCS[\\\"WGS 84\\\",DATUM[\\\"WGS_1984\\\",SPHEROID[\\\"WGS 84\\\",6378137,298.257223563,AUTHORITY[\\\"EPSG\\\",\\\"7030\\\"]],AUTHORITY[\\\"EPSG\\\",\\\"6326\\\"]],PRIMEM[\\\"Greenwich\\\",0,AUTHORITY[\\\"EPSG\\\",\\\"8901\\\"]],UNIT[\\\"degree\\\",0.01745329251994328,AUTHORITY[\\\"EPSG\\\",\\\"9122\\\"]],AUTHORITY[\\\"EPSG\\\",\\\"4326\\\"]],PROJECTION[\\\"Albers_Conic_Equal_Area\\\"],PARAMETER[\\\"longitude_of_center\\\",-50.0],PARAMETER[\\\"standard_parallel_1\\\",10.0],PARAMETER[\\\"standard_parallel_2\\\",-40.0],PARAMETER[\\\"latitude_of_center\\\",-25.0],UNIT[\\\"Meter\\\",1.0]]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Projected CRS: PROJCS[\"Brazil / Albers Equal Area Conic (WGS84)\", ...>\n",
       "Name: Brazil / Albers Equal Area Conic (WGS84)\n",
       "Axis Info [cartesian]:\n",
       "- E[east]: Easting (Meter)\n",
       "- N[north]: Northing (Meter)\n",
       "Area of Use:\n",
       "- undefined\n",
       "Coordinate Operation:\n",
       "- name: unnamed\n",
       "- method: Albers Equal Area\n",
       "Datum: World Geodetic System 1984\n",
       "- Ellipsoid: WGS 84\n",
       "- Prime Meridian: Greenwich"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Projected CRS: PROJCS[\"Brazil / Albers Equal Area Conic (WGS84)\", ...>\n",
       "Name: Brazil / Albers Equal Area Conic (WGS84)\n",
       "Axis Info [cartesian]:\n",
       "- E[east]: Easting (Meter)\n",
       "- N[north]: Northing (Meter)\n",
       "Area of Use:\n",
       "- undefined\n",
       "Coordinate Operation:\n",
       "- name: unnamed\n",
       "- method: Albers Equal Area\n",
       "Datum: World Geodetic System 1984\n",
       "- Ellipsoid: WGS 84\n",
       "- Prime Meridian: Greenwich"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bra_bralbers = brasil.to_crs(crs=sc)\n",
    "bra_bralbers.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    MULTIPOLYGON (((-1469039.509 -3319468.382, -14...\n",
       "1    POLYGON ((-996955.716 1137737.099, -996011.753...\n",
       "2    MULTIPOLYGON (((132961.996 -339227.720, 132111...\n",
       "3    MULTIPOLYGON (((-1377900.091 -3398261.160, -13...\n",
       "4    MULTIPOLYGON (((-2977188.445 3141275.661, -297...\n",
       "Name: geometry, dtype: geometry"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bra_bralbers['geometry'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Usando proj4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Projected CRS: +proj=cea +lon_0=0 +lat_ts=45 +x_0=0 +y_0=0 +ellps ...>\n",
       "Name: unknown\n",
       "Axis Info [cartesian]:\n",
       "- E[east]: Easting (metre)\n",
       "- N[north]: Northing (metre)\n",
       "Area of Use:\n",
       "- undefined\n",
       "Coordinate Operation:\n",
       "- name: unknown\n",
       "- method: Lambert Cylindrical Equal Area\n",
       "Datum: Unknown based on WGS 84 ellipsoid\n",
       "- Ellipsoid: WGS 84\n",
       "- Prime Meridian: Greenwich"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sc = CRS('+proj=cea +lon_0=0 +lat_ts=45 +x_0=0 +y_0=0 +ellps=WGS84 +units=m +no_defs')\n",
    "sc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Projected CRS: +proj=cea +lon_0=0 +lat_ts=45 +x_0=0 +y_0=0 +ellps ...>\n",
       "Name: unknown\n",
       "Axis Info [cartesian]:\n",
       "- E[east]: Easting (metre)\n",
       "- N[north]: Northing (metre)\n",
       "Area of Use:\n",
       "- undefined\n",
       "Coordinate Operation:\n",
       "- name: unknown\n",
       "- method: Lambert Cylindrical Equal Area\n",
       "Datum: Unknown based on WGS 84 ellipsoid\n",
       "- Ellipsoid: WGS 84\n",
       "- Prime Meridian: Greenwich"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bra_gall = brasil.to_crs(crs=sc)\n",
    "bra_gall.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    MULTIPOLYGON (((-5406331.581 -7338057.459, -54...\n",
       "1    POLYGON ((-4750237.605 -2387846.827, -4749573....\n",
       "2    MULTIPOLYGON (((-3827372.376 -4178036.030, -38...\n",
       "3    MULTIPOLYGON (((-5321447.041 -7423554.100, -53...\n",
       "4    MULTIPOLYGON (((-6158455.956 392082.572, -6160...\n",
       "Name: geometry, dtype: geometry"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bra_gall['geometry'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Proyectamos usando la estereografica del polo sur"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc = CRS('+proj=stere +lat_0=-90 +lat_ts=-90 +lon_0=-63 +k=1 +x_0=0 +y_0=0 +ellps=WGS84 +datum=WGS84 +units=m +no_defs')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Projected CRS: +proj=stere +lat_0=-90 +lat_ts=-90 +lon_0=-63 +k=1 ...>\n",
       "Name: unknown\n",
       "Axis Info [cartesian]:\n",
       "- E[north]: Easting (metre)\n",
       "- N[north]: Northing (metre)\n",
       "Area of Use:\n",
       "- undefined\n",
       "Coordinate Operation:\n",
       "- name: unknown\n",
       "- method: Polar Stereographic (variant B)\n",
       "Datum: World Geodetic System 1984\n",
       "- Ellipsoid: WGS 84\n",
       "- Prime Meridian: Greenwich"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bra_stereo = brasil.to_crs(crs=sc)\n",
    "bra_stereo.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    MULTIPOLYGON (((-392493.673 4026465.033, -3937...\n",
       "1    POLYGON ((465456.772 9677559.852, 466674.581 9...\n",
       "2    MULTIPOLYGON (((1920183.234 7447241.343, 19188...\n",
       "3    MULTIPOLYGON (((-307641.653 3916875.960, -3096...\n",
       "4    MULTIPOLYGON (((-3460907.107 12820845.269, -34...\n",
       "Name: geometry, dtype: geometry"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bra_stereo['geometry'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2, 3, figsize=(10,10))\n",
    "\n",
    "brasil.plot(ax=ax[0,0], facecolor='gray')\n",
    "bra_wgs84.plot(ax=ax[0,1], facecolor='gray')\n",
    "bra_albers.plot(ax=ax[0,2], facecolor='gray')\n",
    "bra_bralbers.plot(ax=ax[1,0], facecolor='gray')\n",
    "bra_gall.plot(ax=ax[1,1], facecolor='gray')\n",
    "bra_stereo.plot(ax=ax[1,2], facecolor='gray')\n",
    "\n",
    "ax[0,0].set_title('SIRGAS 2000')\n",
    "ax[0,1].set_title('Mercator')\n",
    "ax[0,2].set_title('Albers')\n",
    "ax[1,0].set_title('Brazil Albers')\n",
    "ax[1,1].set_title('Gall Stereographic')\n",
    "ax[1,2].set_title('Stereographic')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Estereogafo:  2    2.508907e+07\n",
      "dtype: float64\n",
      "Albers:  2    8.470775e+06\n",
      "dtype: float64\n",
      "Mercator:  2    8.959530e+06\n",
      "dtype: float64\n",
      "SIRGAS 2000:  2    706.950022\n",
      "dtype: float64\n",
      "Brazil Albers:  2    8.470782e+06\n",
      "dtype: float64\n",
      "Gall Stereographic:  2    8.470780e+06\n",
      "dtype: float64\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/pc/mkcyyvhd0vggcpltg8x7prb80000gn/T/ipykernel_50269/3040182418.py:5: UserWarning: Geometry is in a geographic CRS. Results from 'area' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n",
      "\n",
      "  print('SIRGAS 2000: ', brasil[brasil.NAME_SORT == 'Brazil'].area)\n"
     ]
    }
   ],
   "source": [
    "# En SIRGAS da error porque necesita ser proyectado\n",
    "print('Estereogafo: ', bra_stereo[bra_stereo.NAME_SORT == 'Brazil'].area/10**6)\n",
    "print('Albers: ', bra_albers[bra_albers.NAME_SORT == 'Brazil'].area/10**6)\n",
    "print('Mercator: ', bra_wgs84[bra_wgs84.NAME_SORT == 'Brazil'].area/10**6)\n",
    "print('SIRGAS 2000: ', brasil[brasil.NAME_SORT == 'Brazil'].area)\n",
    "print('Brazil Albers: ', bra_bralbers[bra_bralbers.NAME_SORT == 'Brazil'].area/10**6)\n",
    "print('Gall Stereographic: ', bra_gall[bra_gall.NAME_SORT == 'Brazil'].area/10**6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Automatizacion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "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>ds_codigo</th>\n",
       "      <th>ds_nome</th>\n",
       "      <th>sp_codigo</th>\n",
       "      <th>sp_nome</th>\n",
       "      <th>area_km2</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>51</td>\n",
       "      <td>MANDAQUI</td>\n",
       "      <td>05</td>\n",
       "      <td>SANTANA-TUCURUVI</td>\n",
       "      <td>13.246426</td>\n",
       "      <td>POLYGON ((330995.449 7407882.882, 330997.253 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>52</td>\n",
       "      <td>MARSILAC</td>\n",
       "      <td>20</td>\n",
       "      <td>PARELHEIROS</td>\n",
       "      <td>208.184737</td>\n",
       "      <td>POLYGON ((336169.148 7355348.052, 336166.813 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>32</td>\n",
       "      <td>MOEMA</td>\n",
       "      <td>12</td>\n",
       "      <td>VILA MARIANA</td>\n",
       "      <td>9.078676</td>\n",
       "      <td>POLYGON ((331287.247 7392208.050, 331289.654 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>57</td>\n",
       "      <td>PARQUE DO CARMO</td>\n",
       "      <td>27</td>\n",
       "      <td>ITAQUERA</td>\n",
       "      <td>15.451409</td>\n",
       "      <td>POLYGON ((352642.665 7390165.168, 352633.278 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>60</td>\n",
       "      <td>PERDIZES</td>\n",
       "      <td>08</td>\n",
       "      <td>LAPA</td>\n",
       "      <td>6.337240</td>\n",
       "      <td>POLYGON ((330226.820 7396102.561, 330220.609 7...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  ds_codigo          ds_nome sp_codigo           sp_nome    area_km2  \\\n",
       "0        51         MANDAQUI        05  SANTANA-TUCURUVI   13.246426   \n",
       "1        52         MARSILAC        20       PARELHEIROS  208.184737   \n",
       "2        32            MOEMA        12      VILA MARIANA    9.078676   \n",
       "3        57  PARQUE DO CARMO        27          ITAQUERA   15.451409   \n",
       "4        60         PERDIZES        08              LAPA    6.337240   \n",
       "\n",
       "                                            geometry  \n",
       "0  POLYGON ((330995.449 7407882.882, 330997.253 7...  \n",
       "1  POLYGON ((336169.148 7355348.052, 336166.813 7...  \n",
       "2  POLYGON ((331287.247 7392208.050, 331289.654 7...  \n",
       "3  POLYGON ((352642.665 7390165.168, 352633.278 7...  \n",
       "4  POLYGON ((330226.820 7396102.561, 330220.609 7...  "
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dis_sampa.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(96, 6)"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dis_sampa.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pandas.core.groupby.generic.DataFrameGroupBy object at 0x29ab10a30>"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agrupado = dis_sampa.groupby('sp_nome')\n",
    "agrupado"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "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>ds_codigo</th>\n",
       "      <th>ds_nome</th>\n",
       "      <th>sp_codigo</th>\n",
       "      <th>sp_nome</th>\n",
       "      <th>area_km2</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>72</td>\n",
       "      <td>SAO LUCAS</td>\n",
       "      <td>29</td>\n",
       "      <td>VILA PRUDENTE</td>\n",
       "      <td>9.673558</td>\n",
       "      <td>POLYGON ((340533.881 7391295.876, 340546.130 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>93</td>\n",
       "      <td>VILA PRUDENTE</td>\n",
       "      <td>29</td>\n",
       "      <td>VILA PRUDENTE</td>\n",
       "      <td>9.583360</td>\n",
       "      <td>POLYGON ((341776.354 7388505.223, 341768.814 7...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ds_codigo        ds_nome sp_codigo        sp_nome  area_km2  \\\n",
       "29        72      SAO LUCAS        29  VILA PRUDENTE  9.673558   \n",
       "42        93  VILA PRUDENTE        29  VILA PRUDENTE  9.583360   \n",
       "\n",
       "                                             geometry  \n",
       "29  POLYGON ((340533.881 7391295.876, 340546.130 7...  \n",
       "42  POLYGON ((341776.354 7388505.223, 341768.814 7...  "
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for key, values in agrupado:\n",
    "    cod_dis = values\n",
    "\n",
    "cod_dis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'geopandas.geodataframe.GeoDataFrame'>\n"
     ]
    }
   ],
   "source": [
    "print(type(cod_dis))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VILA PRUDENTE\n"
     ]
    }
   ],
   "source": [
    "print(key)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "saida = r'output'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "outdir = os.path.join(saida, 'Distritos')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "if not os.path.exists(outdir):\n",
    "    os.makedirs(outdir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 32/32 [00:00<00:00, 189.53it/s]\n"
     ]
    }
   ],
   "source": [
    "for key, values in tqdm(agrupado):\n",
    "    out = os.path.join(outdir, key.replace(' ', '_') + '.shp')\n",
    "    #print(out)\n",
    "\n",
    "    values.to_file(out)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "160"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shapefiles = os.listdir(outdir)\n",
    "len(shapefiles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [],
   "source": [
    "for shapefile in shapefiles:\n",
    "    if shapefile.endswith('.shp'):\n",
    "        data = gpd.read_file(os.path.join(outdir, shapefile))\n",
    "        data = data.to_crs(epsg=4326)\n",
    "        #print(data.head())\n",
    "\n",
    "        data.to_file(os.path.join(outdir, 'repro_' + shapefile))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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