01 - Descarga de geometrias (IGN, Censo CONICET).ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ">> Click en Run All ^^"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Descarga de geometrías (IGN, Censo CONICET)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Este notebook se encarga de descargar los datos geográficos oficiales. fuentes: el Instituto Geográfico Nacional (IGN). Fuente alternativa, Rodriguez CEUR CONICET. Aquí están los pasos que sigue este notebook:\n",
    "\n",
    "**Descarga de los datos del Censo CONICET**: El notebook descarga archivos .rar que contienen los datos del censo para diferentes años si no existen ya en tu sistema.\n",
    "\n",
    "**Extracción de los datos**: Una vez descargados los archivos .rar, el notebook los extrae automáticamente. ¡Ya tines todo listo para trabajar con los datos!\n",
    "\n",
    "Este notebook es perfecto para descargar y preparar los datos geográficos necesarios para trabajar con los datos del censo. ¡No tenes que ser un experto en Python! El notebook hace todo el trabajo."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from urllib.request import urlretrieve\n",
    "\n",
    "# Attempt to import pyunpack, if it fails, install pyunpack and patool\n",
    "try:\n",
    "    from pyunpack import Archive\n",
    "except ModuleNotFoundError:\n",
    "    os.system('pip install pyunpack')\n",
    "    os.system('pip install patool')\n",
    "    from pyunpack import Archive"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Descarga de geometrias de CENSO de CONICET (Gonzalo Rodriguez)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Obtaining the data from the URL's\n",
    "url_front = 'http://ceur-conicet.gov.ar/archivos/transferencia/'\n",
    "\n",
    "## Carpeta donde quedaran los shp\n",
    "extract_dir = './censos_shp_CONICET'\n",
    "\n",
    "for year in ['1991', '2001', '2010']:\n",
    "    file_name = year+'_RADIOS_ARGENTINA.rar'\n",
    "    full_file = os.path.join(os.getcwd(), extract_dir, file_name)\n",
    "    extracted_folder_path = os.path.join(extract_dir, year+'_RADIOS ARGENTINA')\n",
    "\n",
    "    # Descarga el rar solo si no existe.\n",
    "    if not os.path.isfile(full_file):\n",
    "\n",
    "        # Si no esta el directorio lo crea\n",
    "        if not os.path.exists(extract_dir):\n",
    "            os.makedirs(extract_dir)\n",
    "\n",
    "        # Toma data del URL\n",
    "        urlretrieve(url_front + file_name, full_file)\n",
    "        \n",
    "    # Extracts files only if the extracted folder does not exist.\n",
    "    if not os.path.isdir(extracted_folder_path):\n",
    "        Archive(full_file).extractall(extract_dir)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Descarga de geometrias de IGN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/matias/anaconda3/envs/base2/lib/python3.11/site-packages/urllib3/connectionpool.py:1095: InsecureRequestWarning: Unverified HTTPS request is being made to host 'ign.gob.ar'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/latest/advanced-usage.html#tls-warnings\n",
      "  warnings.warn(\n",
      "/home/matias/anaconda3/envs/base2/lib/python3.11/site-packages/urllib3/connectionpool.py:1095: InsecureRequestWarning: Unverified HTTPS request is being made to host 'www.ign.gob.ar'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/latest/advanced-usage.html#tls-warnings\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "import geopandas as gpd\n",
    "import requests\n",
    "import zipfile\n",
    "import os\n",
    "from io import BytesIO\n",
    "\n",
    "# URL of the ZIP file\n",
    "url = \"http://www.ign.gob.ar/descargas/geodatos/SHAPES/ign_departamento.zip\"\n",
    "\n",
    "# Download the ZIP file with SSL certificate verification disabled\n",
    "response = requests.get(url, verify=False)\n",
    "\n",
    "# Specify the target directory for extraction\n",
    "target_directory = \"./IGN_shp/\"\n",
    "\n",
    "# Create the target directory if it doesn't exist\n",
    "os.makedirs(target_directory, exist_ok=True)\n",
    "\n",
    "# Extract the shapefile files from the ZIP archive to the target directory\n",
    "with zipfile.ZipFile(BytesIO(response.content)) as zip_file:\n",
    "    zip_file.extractall(target_directory)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'./IGN_shp/ign_departamento'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Listo, ya tenes los departamentos.\n",
    "# Load the shapefile into a GeoDataFrame\n",
    "shapefile_path = os.path.join(target_directory, \"ign_departamento\")\n",
    "gdf = gpd.read_file(shapefile_path)\n",
    "shapefile_path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gdf.plot(color = 'w', edgecolor = 'k')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'./IGN_shp/ign_departamento'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shapefile_path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "### ALTERNATIVA DIRECTO DE IGN, TIENE ERORRES ESE DATASET. NO USAR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Obtaining the data from the URL's\n",
    "url_front = 'https://www.ign.gob.ar/descargas/geodatos/SHAPES/'\n",
    "\n",
    "## Carpeta donde quedaran los shp\n",
    "extract_dir = 'IGN_shp'\n",
    "\n",
    "for file_name in ['ign_provincia.zip', 'ign_departamento.zip']:\n",
    "    full_file = os.path.join(os.getcwd(), extract_dir, file_name)\n",
    "\n",
    "    # Descarga el rar solo si no existe.\n",
    "    if not os.path.isfile(full_file):\n",
    "        # Si no esta el directorio lo crea\n",
    "        if not os.path.exists(extract_dir):\n",
    "            os.makedirs(extract_dir)\n",
    "\n",
    "        # Toma data del URL\n",
    "        urlretrieve(url_front + file_name, full_file)\n",
    "\n",
    "    Archive(full_file).extractall(extract_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'IGN_shp'"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "extract_dir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/matias/repos/IGN_INDEC_georef/IGN_shp/ign_departamento.zip'"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_file"
   ]
  },
  {
   "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": "3.11.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}