get_metro_pos.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 3,
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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import requests\n",
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "metro_data = pd.read_csv('data/metro.csv', header=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "metro_names = metro_data[0]"
   ]
  },
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   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error con TOBALABA L1\n",
      "Error con FRANKLIN\n",
      "Error con LA CISTERNA L4A\n",
      "Error con LA GRANJA\n",
      "Error con LOS ORIENTALES\n",
      "Error con SANTA JULIA\n",
      "Error con HERNANDO DE MAGALLANES\n",
      "Error con LOS HEROES L2\n",
      "Error con LO PRADO\n",
      "Error con TOBALABA L4\n",
      "Error con BAQUEDANO L5\n"
     ]
    }
   ],
   "source": [
    "data = []\n",
    "for metro_name in metro_names:\n",
    "    params = {\n",
    "        'query': 'metro {}'.format(metro_name),\n",
    "        'key': 'AIzaSyAbZD-Lsr0ZkujnShZDCO7OIgB2DiFUemo'\n",
    "    }\n",
    "    r = requests.get('https://maps.googleapis.com/maps/api/place/textsearch/json', params=params)\n",
    "    response = r.json()\n",
    "    try:\n",
    "        location = response['results'][0]['geometry']['location']\n",
    "        data.append((metro_name, location['lat'], location['lng']))\n",
    "    except:\n",
    "        print('Error con', metro_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.columns = ['metro', 'latitude', 'longitude']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('data/metro_pos_new.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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