caitlin_locations.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "%config InlineBackend.figure_formats = ['svg']\n",
    "sns.set_style(\"white\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "United States of America\n",
      "England\n",
      "Australia\n",
      "Canada\n",
      "Germany\n",
      "Spain\n",
      "France\n",
      "Italy\n",
      "Ireland\n",
      "Netherlands\n",
      "Brazil\n",
      "Hong Kong\n",
      "New Zealand\n",
      "Poland\n",
      "China\n",
      "Finland\n",
      "Mexico\n",
      "Denmark\n",
      "Sweden\n",
      "Scotland\n",
      "Argentina\n",
      "Malaysia\n",
      "South Korea\n",
      "Belgium\n",
      "Switzerland\n",
      "Czech Republic\n",
      "Austria\n",
      "Norway\n",
      "Taiwan\n",
      "Northern Ireland\n",
      "Hungary\n",
      "Japan\n",
      "Portugal\n",
      "Singapore\n",
      "Thailand\n",
      "Russia\n",
      "India\n",
      "South Africa\n",
      "Chile\n",
      "Turkey\n",
      "Wales\n",
      "Indonesia\n",
      "Greece\n",
      "Colombia\n",
      "Israel\n",
      "Romania\n",
      "Vietnam\n",
      "Slovenia\n",
      "Trinidad And Tobago\n",
      "Ukraine\n",
      "American Samoa\n",
      "Costa Rica\n",
      "Slovakia\n",
      "Lithuania\n",
      "Latvia\n",
      "Philippines\n",
      "Guatemala\n",
      "Puerto Rico\n",
      "Croatia\n",
      "Peru\n",
      "Serbia\n",
      "Bangladesh\n",
      "Venezuela\n",
      "Bulgaria\n",
      "Tunisia\n",
      "Belarus\n",
      "Dominican Republic\n",
      "Uruguay\n",
      "Brunei\n",
      "Luxembourg\n",
      "Egypt\n",
      "Estonia\n",
      "Iceland\n",
      "Paraguay\n",
      "Malta\n",
      "Iraq\n",
      "Bosnia And Herzegovina\n",
      "Armenia\n",
      "Mauritius\n",
      "Morocco\n",
      "Kyrgyzstan\n",
      "Kazakhstan\n",
      "Bouvet Island\n",
      "Jamaica\n",
      "Botswana\n",
      "Ecuador\n",
      "British Virgin Islands\n",
      "Pakistan\n",
      "Congo\n",
      "Iran\n",
      "Jordan\n"
     ]
    }
   ],
   "source": [
    "## Bing map locators http://bingmapslocators.cloudapp.net/\n",
    "# https://geopy.readthedocs.io/en/1.10.0/\n",
    "from geopy.geocoders import Bing\n",
    "\n",
    "countries = ['United States of America', 'England', 'Australia', 'Canada', 'Germany', 'Spain', 'France', 'Italy', 'Ireland', \n",
    "          'Netherlands','Brazil',\n",
    "             'Hong Kong', 'New Zealand', 'Poland', 'China', 'Finland', 'Mexico', 'Denmark', 'Sweden', 'Scotland', \n",
    "             'Argentina',\n",
    "            'Malaysia', 'South Korea', 'Belgium', 'Switzerland', 'Czech Republic', 'Austria', 'Norway', 'Taiwan', \n",
    "             'Northern Ireland',\n",
    "            'Hungary', 'Japan', 'Portugal', 'Singapore', 'Thailand', 'Russia', 'India', 'South Africa', 'Chile', 'Turkey', \n",
    "             'Wales', 'Indonesia',\n",
    "            'Greece', 'Colombia', 'Israel', 'Romania', 'Vietnam', 'Slovenia', 'Trinidad And Tobago', 'Ukraine', \n",
    "             'American Samoa',\n",
    "            'Costa Rica', 'Slovakia', 'Lithuania', 'Latvia', 'Philippines', 'Guatemala', 'Puerto Rico', 'Croatia', \n",
    "             'Peru', 'Serbia',\n",
    "            'Bangladesh', 'Venezuela', 'Bulgaria', 'Tunisia', 'Belarus', 'Dominican Republic', 'Uruguay', \n",
    "             'Brunei', 'Luxembourg',\n",
    "            'Egypt', 'Estonia', 'Iceland', 'Paraguay', 'Malta', 'Iraq', 'Bosnia And Herzegovina', 'Armenia', 'Mauritius', \n",
    "             'Morocco',\n",
    "            'Kyrgyzstan', 'Kazakhstan', 'Bouvet Island', 'Jamaica', 'Botswana', 'Ecuador', 'British Virgin Islands', \n",
    "             'Pakistan',\n",
    "            'Congo', 'Iran', 'Jordan']\n",
    "# 'UK', \n",
    "\n",
    "locations = []\n",
    "\n",
    "geolocator  = Bing(\"AqbMqgChvhrcKHPnavY2dmbyTP9L7XQG1iKCnZ61KXFOwcZbMABDNlyNnFnYGJvY\")\n",
    "for i in countries:\n",
    "    print i\n",
    "    geocode = geolocator.geocode(i)\n",
    "    locations.append([i, geocode[1][0], geocode[1][1]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 91 entries, 0 to 90\n",
      "Data columns (total 3 columns):\n",
      "country      91 non-null object\n",
      "latitude     91 non-null object\n",
      "longitude    91 non-null object\n",
      "dtypes: object(3)\n",
      "memory usage: 2.2+ KB\n",
      "None\n",
      "\n",
      "=======\n",
      "                    country        latitude       longitude\n",
      "0  United States of America   39.4432563782  -98.9573364258\n",
      "1                   England   52.5988769531  -1.46688139439\n",
      "2                 Australia  -25.5852413177   134.504119873\n",
      "3                    Canada   62.8329086304  -95.9133224487\n",
      "4                   Germany   51.2024650574   10.3822031021\n",
      "5                     Spain   40.3960266113  -3.55069255829\n",
      "6                    France   46.6372795105   2.33826231956\n",
      "7                     Italy   42.7669792175   12.4938230515\n",
      "8                   Ireland   53.1827278137  -8.19610214233\n",
      "\n",
      "=======\n",
      "                   country        latitude       longitude\n",
      "82           Bouvet Island  -54.4342041016   3.41025114059\n",
      "83                 Jamaica   18.1434440613  -77.3465499878\n",
      "84                Botswana  -22.1867523193   23.8149414062\n",
      "85                 Ecuador  -1.42152893543  -78.8710403442\n",
      "86  British Virgin Islands   18.4430713654  -64.5713043213\n",
      "87                Pakistan   29.9232196808   69.3577423096\n",
      "88                   Congo   -2.8798661232   23.6563777924\n",
      "89                    Iran   32.5007781982   54.2942008972\n",
      "90                  Jordan    31.275762558   36.8283882141\n"
     ]
    }
   ],
   "source": [
    "locations = np.array(locations)\n",
    "locations = pd.DataFrame(locations, columns=['country','latitude','longitude'])\n",
    "print locations.info()\n",
    "print '\\n======='\n",
    "print locations.head(9)\n",
    "print '\\n======='\n",
    "print locations.tail(9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import cPickle\n",
    "f = open('locations.save', 'wb')\n",
    "cPickle.dump(locations,f)\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "f = open('locations.save', 'rb')\n",
    "locations = cPickle.load(f)\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>United States of America</td>\n",
       "      <td>39.4432563782</td>\n",
       "      <td>-98.9573364258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>England</td>\n",
       "      <td>52.5988769531</td>\n",
       "      <td>-1.46688139439</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    country       latitude       longitude\n",
       "0  United States of America  39.4432563782  -98.9573364258\n",
       "1                   England  52.5988769531  -1.46688139439"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "locations.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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