04_country_names.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Country name dictionary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will be using a clickable map to select countries (in addition to giving users the ability to click on a country name from a list)\n",
    "\n",
    "Since the map we're using, `mapael` uses `ISO 3166-1 alpha-2` (two letters) to identify a country, while the dataset we have uses `ISO 3166-2 alpha-3` (three letters) to identify a country, we'll need a way to convert between the two, and to translate those into readable names.\n",
    "\n",
    "Huge thank you to `tadast` for saving us from having to figure out the mapping:\n",
    "\n",
    "https://gist.github.com/tadast/8827699"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I downloaded and renamed it: `countries_codes_and_coordinates.csv` -> `iso2_iso3.csv`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.io.stata.read_stata('./DATA/ventile_2011_for_release_LCU.dta')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "country_codes = df['contcod'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['ALB', 'ARG', 'ARM', 'AUS', 'AUT', 'BEN', 'BGD', 'BGR', 'BLR',\n",
       "       'BOL', 'BRA', 'BTN', 'BWA', 'CAN', 'CHL', 'CHN-R', 'CHN-U', 'COG',\n",
       "       'COL', 'CRI'], dtype=object)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country_codes[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "ISO = pd.read_csv('./data/iso2_iso3.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Alpha-2 code</th>\n",
       "      <th>Alpha-3 code</th>\n",
       "      <th>Numeric code</th>\n",
       "      <th>Latitude (average)</th>\n",
       "      <th>Longitude (average)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>\"AF\"</td>\n",
       "      <td>\"AFG\"</td>\n",
       "      <td>\"4\"</td>\n",
       "      <td>\"33\"</td>\n",
       "      <td>\"65\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>\"AL\"</td>\n",
       "      <td>\"ALB\"</td>\n",
       "      <td>\"8\"</td>\n",
       "      <td>\"41\"</td>\n",
       "      <td>\"20\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>\"DZ\"</td>\n",
       "      <td>\"DZA\"</td>\n",
       "      <td>\"12\"</td>\n",
       "      <td>\"28\"</td>\n",
       "      <td>\"3\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>American Samoa</td>\n",
       "      <td>\"AS\"</td>\n",
       "      <td>\"ASM\"</td>\n",
       "      <td>\"16\"</td>\n",
       "      <td>\"-14.3333\"</td>\n",
       "      <td>\"-170\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>\"AD\"</td>\n",
       "      <td>\"AND\"</td>\n",
       "      <td>\"20\"</td>\n",
       "      <td>\"42.5\"</td>\n",
       "      <td>\"1.6\"</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Country Alpha-2 code Alpha-3 code Numeric code Latitude (average)  \\\n",
       "0     Afghanistan         \"AF\"        \"AFG\"          \"4\"               \"33\"   \n",
       "1         Albania         \"AL\"        \"ALB\"          \"8\"               \"41\"   \n",
       "2         Algeria         \"DZ\"        \"DZA\"         \"12\"               \"28\"   \n",
       "3  American Samoa         \"AS\"        \"ASM\"         \"16\"         \"-14.3333\"   \n",
       "4         Andorra         \"AD\"        \"AND\"         \"20\"             \"42.5\"   \n",
       "\n",
       "  Longitude (average)  \n",
       "0                \"65\"  \n",
       "1                \"20\"  \n",
       "2                 \"3\"  \n",
       "3              \"-170\"  \n",
       "4               \"1.6\"  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ISO.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "ISO.columns = ['country', 'iso2', 'iso3', 'u0', 'u1', 'u2']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>iso2</th>\n",
       "      <th>iso3</th>\n",
       "      <th>u0</th>\n",
       "      <th>u1</th>\n",
       "      <th>u2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>\"AF\"</td>\n",
       "      <td>\"AFG\"</td>\n",
       "      <td>\"4\"</td>\n",
       "      <td>\"33\"</td>\n",
       "      <td>\"65\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>\"AL\"</td>\n",
       "      <td>\"ALB\"</td>\n",
       "      <td>\"8\"</td>\n",
       "      <td>\"41\"</td>\n",
       "      <td>\"20\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>\"DZ\"</td>\n",
       "      <td>\"DZA\"</td>\n",
       "      <td>\"12\"</td>\n",
       "      <td>\"28\"</td>\n",
       "      <td>\"3\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>American Samoa</td>\n",
       "      <td>\"AS\"</td>\n",
       "      <td>\"ASM\"</td>\n",
       "      <td>\"16\"</td>\n",
       "      <td>\"-14.3333\"</td>\n",
       "      <td>\"-170\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>\"AD\"</td>\n",
       "      <td>\"AND\"</td>\n",
       "      <td>\"20\"</td>\n",
       "      <td>\"42.5\"</td>\n",
       "      <td>\"1.6\"</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          country   iso2    iso3     u0           u1       u2\n",
       "0     Afghanistan   \"AF\"   \"AFG\"    \"4\"         \"33\"     \"65\"\n",
       "1         Albania   \"AL\"   \"ALB\"    \"8\"         \"41\"     \"20\"\n",
       "2         Algeria   \"DZ\"   \"DZA\"   \"12\"         \"28\"      \"3\"\n",
       "3  American Samoa   \"AS\"   \"ASM\"   \"16\"   \"-14.3333\"   \"-170\"\n",
       "4         Andorra   \"AD\"   \"AND\"   \"20\"       \"42.5\"    \"1.6\""
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ISO.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "countries = ISO[['country', 'iso2', 'iso3']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>iso2</th>\n",
       "      <th>iso3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>\"AF\"</td>\n",
       "      <td>\"AFG\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>\"AL\"</td>\n",
       "      <td>\"ALB\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>\"DZ\"</td>\n",
       "      <td>\"DZA\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>American Samoa</td>\n",
       "      <td>\"AS\"</td>\n",
       "      <td>\"ASM\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>\"AD\"</td>\n",
       "      <td>\"AND\"</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          country   iso2    iso3\n",
       "0     Afghanistan   \"AF\"   \"AFG\"\n",
       "1         Albania   \"AL\"   \"ALB\"\n",
       "2         Algeria   \"DZ\"   \"DZA\"\n",
       "3  American Samoa   \"AS\"   \"ASM\"\n",
       "4         Andorra   \"AD\"   \"AND\""
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "countries.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I would like a simple dictionary that will take an `iso3` value and return a `country`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When using the map on the webpage, users will click on a country and the map library will give us `iso2`\n",
    "\n",
    "So we'll have another dictionary that will take an `iso2` and return `iso3`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Remove all the `\"` quotes as well as extra spaces!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \n",
      "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/ipykernel_launcher.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    }
   ],
   "source": [
    "for col in countries.columns[1:]:\n",
    "  countries[col] = countries[col].apply(lambda x: x.replace('\"', ''))\n",
    "  countries[col] = countries[col].apply(lambda x: x.replace(' ', ''))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>iso2</th>\n",
       "      <th>iso3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>AL</td>\n",
       "      <td>ALB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>DZ</td>\n",
       "      <td>DZA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>American Samoa</td>\n",
       "      <td>AS</td>\n",
       "      <td>ASM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>AD</td>\n",
       "      <td>AND</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          country iso2 iso3\n",
       "0     Afghanistan   AF  AFG\n",
       "1         Albania   AL  ALB\n",
       "2         Algeria   DZ  DZA\n",
       "3  American Samoa   AS  ASM\n",
       "4         Andorra   AD  AND"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "countries.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Add missing country\n",
    "\n",
    "`South Sudan` was added in 2011 as `SS` and `SSD`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "sudan = { 'country': 'South Sudan', 'iso2': 'SS', 'iso3': 'SSD'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "countries = countries.append(sudan, ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>iso2</th>\n",
       "      <th>iso3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>254</th>\n",
       "      <td>Zambia</td>\n",
       "      <td>ZM</td>\n",
       "      <td>ZMB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZW</td>\n",
       "      <td>ZWE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>South Sudan</td>\n",
       "      <td>SS</td>\n",
       "      <td>SSD</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         country iso2 iso3\n",
       "254       Zambia   ZM  ZMB\n",
       "255     Zimbabwe   ZW  ZWE\n",
       "256  South Sudan   SS  SSD"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "countries.tail(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "iso2_to_iso3 = pd.Series(countries['iso3'].values, index=countries['iso2']).to_dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'DEU'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iso2_to_iso3.get('DE')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "iso3_to_iso2 = pd.Series(countries['iso2'].values, index=countries['iso3']).to_dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'DE'"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iso3_to_iso2.get('DEU')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "iso3_to_name = pd.Series(countries['country'].values, index=countries['iso3']).to_dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Germany'"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iso3_to_name.get('DEU')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's list all the countries not found in our dictionary:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "! NOT FOUND ! --  CHN-R\n",
      "! NOT FOUND ! --  CHN-U\n",
      "! NOT FOUND ! --  KOS\n"
     ]
    }
   ],
   "source": [
    "for country in country_codes:\n",
    "  if not iso3_to_name.get(country):\n",
    "    print('! NOT FOUND ! -- ', country)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "China has been split into two `U` (urban) and `R` (rural)\n",
    "\n",
    "`KOS` is Kosovo\n",
    "\n",
    "Ref: https://en.wikipedia.org/wiki/ISO_3166-1_alpha-3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Romania'"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iso3_to_name.get('ROU')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "output = json.dumps(iso2_to_iso3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"./export/iso2_to_iso3.js\", \"w\") as text_file:\n",
    "    text_file.write(\"var iso2_to_iso3 = \" + output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "output = json.dumps(iso3_to_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"./export/iso3_to_name.js\", \"w\") as text_file:\n",
    "    text_file.write(\"var iso3_to_name = \" + output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "output = json.dumps(iso3_to_iso2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"./export/iso3_to_iso2.js\", \"w\") as text_file:\n",
    "    text_file.write(\"var iso3_to_iso2 = \" + output)"
   ]
  }
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