lecture_2_exercise_2_solution.ipynb

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   "source": [
    "# Lecture 2 exercise 2 solution\n",
    "\n",
    "Using [\"International migrants and refugees\" from the UN](https://data.un.org/)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
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    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Region/Country/Area</th>\n",
       "      <th>Unnamed: 1</th>\n",
       "      <th>Year</th>\n",
       "      <th>Series</th>\n",
       "      <th>Value</th>\n",
       "      <th>Footnotes</th>\n",
       "      <th>Source</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2005</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>191,446,828</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United Nations Population Division, New York, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2005</td>\n",
       "      <td>International migrant stock: Both sexes (% tot...</td>\n",
       "      <td>2.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United Nations Population Division, New York, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2005</td>\n",
       "      <td>International migrant stock: Male (% total Pop...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United Nations Population Division, New York, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2005</td>\n",
       "      <td>International migrant stock: Female (% total P...</td>\n",
       "      <td>2.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United Nations Population Division, New York, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2010</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>220,983,187</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United Nations Population Division, New York, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7228</th>\n",
       "      <td>716</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2020</td>\n",
       "      <td>Total population of concern to UNHCR (number)</td>\n",
       "      <td>292,147</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United Nations High Commissioner for Refugees ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7229</th>\n",
       "      <td>716</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2023</td>\n",
       "      <td>Total refugees and people in refugee-like situ...</td>\n",
       "      <td>10,181</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United Nations High Commissioner for Refugees ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7230</th>\n",
       "      <td>716</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2023</td>\n",
       "      <td>Asylum seekers, including pending cases (number)</td>\n",
       "      <td>11,986</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United Nations High Commissioner for Refugees ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7231</th>\n",
       "      <td>716</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2023</td>\n",
       "      <td>Other of concern to UNHCR (number)</td>\n",
       "      <td>972</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United Nations High Commissioner for Refugees ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7232</th>\n",
       "      <td>716</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2023</td>\n",
       "      <td>Total population of concern to UNHCR (number)</td>\n",
       "      <td>23,139</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United Nations High Commissioner for Refugees ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7233 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Region/Country/Area                     Unnamed: 1  Year  \\\n",
       "0                       1  Total, all countries or areas  2005   \n",
       "1                       1  Total, all countries or areas  2005   \n",
       "2                       1  Total, all countries or areas  2005   \n",
       "3                       1  Total, all countries or areas  2005   \n",
       "4                       1  Total, all countries or areas  2010   \n",
       "...                   ...                            ...   ...   \n",
       "7228                  716                       Zimbabwe  2020   \n",
       "7229                  716                       Zimbabwe  2023   \n",
       "7230                  716                       Zimbabwe  2023   \n",
       "7231                  716                       Zimbabwe  2023   \n",
       "7232                  716                       Zimbabwe  2023   \n",
       "\n",
       "                                                 Series        Value  \\\n",
       "0      International migrant stock: Both sexes (number)  191,446,828   \n",
       "1     International migrant stock: Both sexes (% tot...          2.9   \n",
       "2     International migrant stock: Male (% total Pop...          3.0   \n",
       "3     International migrant stock: Female (% total P...          2.9   \n",
       "4      International migrant stock: Both sexes (number)  220,983,187   \n",
       "...                                                 ...          ...   \n",
       "7228      Total population of concern to UNHCR (number)      292,147   \n",
       "7229  Total refugees and people in refugee-like situ...       10,181   \n",
       "7230   Asylum seekers, including pending cases (number)       11,986   \n",
       "7231                 Other of concern to UNHCR (number)          972   \n",
       "7232      Total population of concern to UNHCR (number)       23,139   \n",
       "\n",
       "     Footnotes                                             Source  \n",
       "0          NaN  United Nations Population Division, New York, ...  \n",
       "1          NaN  United Nations Population Division, New York, ...  \n",
       "2          NaN  United Nations Population Division, New York, ...  \n",
       "3          NaN  United Nations Population Division, New York, ...  \n",
       "4          NaN  United Nations Population Division, New York, ...  \n",
       "...        ...                                                ...  \n",
       "7228       NaN  United Nations High Commissioner for Refugees ...  \n",
       "7229       NaN  United Nations High Commissioner for Refugees ...  \n",
       "7230       NaN  United Nations High Commissioner for Refugees ...  \n",
       "7231       NaN  United Nations High Commissioner for Refugees ...  \n",
       "7232       NaN  United Nations High Commissioner for Refugees ...  \n",
       "\n",
       "[7233 rows x 7 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "migrants = pd.read_csv(\n",
    "    \"https://data.un.org/_Docs/SYB/CSV/SYB67_327_202411_International%20Migrants%20and%20Refugees.csv\",\n",
    "    skiprows=1,\n",
    ")\n",
    "migrants"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "Clean up the columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
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   "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>Region/Country/Area</th>\n",
       "      <th>Year</th>\n",
       "      <th>Series</th>\n",
       "      <th>Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2005</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>191,446,828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2005</td>\n",
       "      <td>International migrant stock: Both sexes (% tot...</td>\n",
       "      <td>2.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2005</td>\n",
       "      <td>International migrant stock: Male (% total Pop...</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2005</td>\n",
       "      <td>International migrant stock: Female (% total P...</td>\n",
       "      <td>2.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2010</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>220,983,187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7228</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2020</td>\n",
       "      <td>Total population of concern to UNHCR (number)</td>\n",
       "      <td>292,147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7229</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2023</td>\n",
       "      <td>Total refugees and people in refugee-like situ...</td>\n",
       "      <td>10,181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7230</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2023</td>\n",
       "      <td>Asylum seekers, including pending cases (number)</td>\n",
       "      <td>11,986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7231</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2023</td>\n",
       "      <td>Other of concern to UNHCR (number)</td>\n",
       "      <td>972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7232</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2023</td>\n",
       "      <td>Total population of concern to UNHCR (number)</td>\n",
       "      <td>23,139</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7233 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                Region/Country/Area  Year  \\\n",
       "0     Total, all countries or areas  2005   \n",
       "1     Total, all countries or areas  2005   \n",
       "2     Total, all countries or areas  2005   \n",
       "3     Total, all countries or areas  2005   \n",
       "4     Total, all countries or areas  2010   \n",
       "...                             ...   ...   \n",
       "7228                       Zimbabwe  2020   \n",
       "7229                       Zimbabwe  2023   \n",
       "7230                       Zimbabwe  2023   \n",
       "7231                       Zimbabwe  2023   \n",
       "7232                       Zimbabwe  2023   \n",
       "\n",
       "                                                 Series        Value  \n",
       "0      International migrant stock: Both sexes (number)  191,446,828  \n",
       "1     International migrant stock: Both sexes (% tot...          2.9  \n",
       "2     International migrant stock: Male (% total Pop...          3.0  \n",
       "3     International migrant stock: Female (% total P...          2.9  \n",
       "4      International migrant stock: Both sexes (number)  220,983,187  \n",
       "...                                                 ...          ...  \n",
       "7228      Total population of concern to UNHCR (number)      292,147  \n",
       "7229  Total refugees and people in refugee-like situ...       10,181  \n",
       "7230   Asylum seekers, including pending cases (number)       11,986  \n",
       "7231                 Other of concern to UNHCR (number)          972  \n",
       "7232      Total population of concern to UNHCR (number)       23,139  \n",
       "\n",
       "[7233 rows x 4 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "migrants = migrants.drop(columns=[\"Region/Country/Area\", \"Footnotes\", \"Source\"])\n",
    "migrants = migrants.rename(columns={\"Unnamed: 1\": \"Region/Country/Area\"})\n",
    "migrants"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['International migrant stock: Both sexes (number)',\n",
       "       'International migrant stock: Both sexes (% total population)',\n",
       "       'International migrant stock: Male (% total Population)',\n",
       "       'International migrant stock: Female (% total Population)',\n",
       "       'Total refugees and people in refugee-like situations (number)',\n",
       "       'Asylum seekers, including pending cases (number)',\n",
       "       'Other of concern to UNHCR (number)',\n",
       "       'Total population of concern to UNHCR (number)'], dtype=object)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "migrants[\"Series\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "editable": true,
    "slideshow": {
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   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Region/Country/Area</th>\n",
       "      <th>Year</th>\n",
       "      <th>Series</th>\n",
       "      <th>Value</th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2005</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>191,446,828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2010</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>220,983,187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2015</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>247,958,644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2020</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>280,598,105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Africa</td>\n",
       "      <td>2005</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>16,040,087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7186</th>\n",
       "      <td>Zambia</td>\n",
       "      <td>2020</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>187,955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7198</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2005</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>402,226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7206</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2010</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>398,307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7213</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2015</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>400,482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7221</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2020</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>416,141</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1045 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                Region/Country/Area  Year  \\\n",
       "0     Total, all countries or areas  2005   \n",
       "4     Total, all countries or areas  2010   \n",
       "8     Total, all countries or areas  2015   \n",
       "16    Total, all countries or areas  2020   \n",
       "28                           Africa  2005   \n",
       "...                             ...   ...   \n",
       "7186                         Zambia  2020   \n",
       "7198                       Zimbabwe  2005   \n",
       "7206                       Zimbabwe  2010   \n",
       "7213                       Zimbabwe  2015   \n",
       "7221                       Zimbabwe  2020   \n",
       "\n",
       "                                                Series        Value  \n",
       "0     International migrant stock: Both sexes (number)  191,446,828  \n",
       "4     International migrant stock: Both sexes (number)  220,983,187  \n",
       "8     International migrant stock: Both sexes (number)  247,958,644  \n",
       "16    International migrant stock: Both sexes (number)  280,598,105  \n",
       "28    International migrant stock: Both sexes (number)   16,040,087  \n",
       "...                                                ...          ...  \n",
       "7186  International migrant stock: Both sexes (number)      187,955  \n",
       "7198  International migrant stock: Both sexes (number)      402,226  \n",
       "7206  International migrant stock: Both sexes (number)      398,307  \n",
       "7213  International migrant stock: Both sexes (number)      400,482  \n",
       "7221  International migrant stock: Both sexes (number)      416,141  \n",
       "\n",
       "[1045 rows x 4 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "migrants_total = migrants[migrants[\"Series\"] == \"International migrant stock: Both sexes (number)\"]\n",
    "migrants_total"
   ]
  },
  {
   "cell_type": "code",
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Total, all countries or areas',\n",
       " 'Africa',\n",
       " 'Northern Africa',\n",
       " 'Sub-Saharan Africa',\n",
       " 'Eastern Africa',\n",
       " 'Middle Africa',\n",
       " 'Southern Africa',\n",
       " 'Western Africa',\n",
       " 'Northern America',\n",
       " 'Latin America & the Caribbean',\n",
       " 'Caribbean',\n",
       " 'Central America',\n",
       " 'South America',\n",
       " 'Asia',\n",
       " 'Central Asia',\n",
       " 'Eastern Asia',\n",
       " 'South-central Asia',\n",
       " 'South-eastern Asia',\n",
       " 'Southern Asia',\n",
       " 'Western Asia',\n",
       " 'Europe',\n",
       " 'Eastern Europe',\n",
       " 'Northern Europe',\n",
       " 'Southern Europe',\n",
       " 'Western Europe',\n",
       " 'Oceania',\n",
       " 'Australia and New Zealand',\n",
       " 'Melanesia',\n",
       " 'Micronesia',\n",
       " 'Polynesia',\n",
       " 'Afghanistan',\n",
       " 'Albania',\n",
       " 'Algeria',\n",
       " 'American Samoa',\n",
       " 'Andorra',\n",
       " 'Angola',\n",
       " 'Anguilla',\n",
       " 'Antigua and Barbuda',\n",
       " 'Argentina',\n",
       " 'Armenia',\n",
       " 'Aruba',\n",
       " 'Australia',\n",
       " 'Austria',\n",
       " 'Azerbaijan',\n",
       " 'Bahamas',\n",
       " 'Bahrain',\n",
       " 'Bangladesh',\n",
       " 'Barbados',\n",
       " 'Belarus',\n",
       " 'Belgium',\n",
       " 'Belize',\n",
       " 'Benin',\n",
       " 'Bermuda',\n",
       " 'Bhutan',\n",
       " 'Bolivia (Plurin. State of)',\n",
       " 'Bonaire, St. Eustatius & Saba',\n",
       " 'Bosnia and Herzegovina',\n",
       " 'Botswana',\n",
       " 'Brazil',\n",
       " 'British Virgin Islands',\n",
       " 'Brunei Darussalam',\n",
       " 'Bulgaria',\n",
       " 'Burkina Faso',\n",
       " 'Burundi',\n",
       " 'Cabo Verde',\n",
       " 'Cambodia',\n",
       " 'Cameroon',\n",
       " 'Canada',\n",
       " 'Cayman Islands',\n",
       " 'Central African Republic',\n",
       " 'Chad',\n",
       " 'Channel Islands',\n",
       " 'Chile',\n",
       " 'China',\n",
       " 'China, Hong Kong SAR',\n",
       " 'China, Macao SAR',\n",
       " 'Colombia',\n",
       " 'Comoros',\n",
       " 'Congo',\n",
       " 'Cook Islands',\n",
       " 'Costa Rica',\n",
       " 'Côte d’Ivoire',\n",
       " 'Croatia',\n",
       " 'Cuba',\n",
       " 'Curaçao',\n",
       " 'Cyprus',\n",
       " 'Czechia',\n",
       " \"Dem. People's Rep. Korea\",\n",
       " 'Dem. Rep. of the Congo',\n",
       " 'Denmark',\n",
       " 'Djibouti',\n",
       " 'Dominica',\n",
       " 'Dominican Republic',\n",
       " 'Ecuador',\n",
       " 'Egypt',\n",
       " 'El Salvador',\n",
       " 'Equatorial Guinea',\n",
       " 'Eritrea',\n",
       " 'Estonia',\n",
       " 'Eswatini',\n",
       " 'Ethiopia',\n",
       " 'Falkland Islands (Malvinas)',\n",
       " 'Faroe Islands',\n",
       " 'Fiji',\n",
       " 'Finland',\n",
       " 'France',\n",
       " 'French Guiana',\n",
       " 'French Polynesia',\n",
       " 'Gabon',\n",
       " 'Gambia',\n",
       " 'Georgia',\n",
       " 'Germany',\n",
       " 'Ghana',\n",
       " 'Gibraltar',\n",
       " 'Greece',\n",
       " 'Greenland',\n",
       " 'Grenada',\n",
       " 'Guadeloupe',\n",
       " 'Guam',\n",
       " 'Guatemala',\n",
       " 'Guinea',\n",
       " 'Guinea-Bissau',\n",
       " 'Guyana',\n",
       " 'Haiti',\n",
       " 'Holy See',\n",
       " 'Honduras',\n",
       " 'Hungary',\n",
       " 'Iceland',\n",
       " 'India',\n",
       " 'Indonesia',\n",
       " 'Iran (Islamic Republic of)',\n",
       " 'Iraq',\n",
       " 'Ireland',\n",
       " 'Isle of Man',\n",
       " 'Israel',\n",
       " 'Italy',\n",
       " 'Jamaica',\n",
       " 'Japan',\n",
       " 'Jordan',\n",
       " 'Kazakhstan',\n",
       " 'Kenya',\n",
       " 'Kiribati',\n",
       " 'Kuwait',\n",
       " 'Kyrgyzstan',\n",
       " \"Lao People's Dem. Rep.\",\n",
       " 'Latvia',\n",
       " 'Lebanon',\n",
       " 'Lesotho',\n",
       " 'Liberia',\n",
       " 'Libya',\n",
       " 'Liechtenstein',\n",
       " 'Lithuania',\n",
       " 'Luxembourg',\n",
       " 'Madagascar',\n",
       " 'Malawi',\n",
       " 'Malaysia',\n",
       " 'Maldives',\n",
       " 'Mali',\n",
       " 'Malta',\n",
       " 'Marshall Islands',\n",
       " 'Martinique',\n",
       " 'Mauritania',\n",
       " 'Mauritius',\n",
       " 'Mayotte',\n",
       " 'Mexico',\n",
       " 'Micronesia (Fed. States of)',\n",
       " 'Monaco',\n",
       " 'Mongolia',\n",
       " 'Montenegro',\n",
       " 'Montserrat',\n",
       " 'Morocco',\n",
       " 'Mozambique',\n",
       " 'Myanmar',\n",
       " 'Namibia',\n",
       " 'Nauru',\n",
       " 'Nepal',\n",
       " 'Netherlands (Kingdom of the)',\n",
       " 'New Caledonia',\n",
       " 'New Zealand',\n",
       " 'Nicaragua',\n",
       " 'Niger',\n",
       " 'Nigeria',\n",
       " 'Niue',\n",
       " 'North Macedonia',\n",
       " 'Northern Mariana Islands',\n",
       " 'Norway',\n",
       " 'Oman',\n",
       " 'Pakistan',\n",
       " 'Palau',\n",
       " 'Panama',\n",
       " 'Papua New Guinea',\n",
       " 'Paraguay',\n",
       " 'Peru',\n",
       " 'Philippines',\n",
       " 'Poland',\n",
       " 'Portugal',\n",
       " 'Puerto Rico',\n",
       " 'Qatar',\n",
       " 'Republic of Korea',\n",
       " 'Republic of Moldova',\n",
       " 'Réunion',\n",
       " 'Romania',\n",
       " 'Russian Federation',\n",
       " 'Rwanda',\n",
       " 'Saint Helena',\n",
       " 'Saint Kitts and Nevis',\n",
       " 'Saint Lucia',\n",
       " 'Saint Pierre and Miquelon',\n",
       " 'Saint Vincent & Grenadines',\n",
       " 'Samoa',\n",
       " 'San Marino',\n",
       " 'Sao Tome and Principe',\n",
       " 'Saudi Arabia',\n",
       " 'Senegal',\n",
       " 'Serbia',\n",
       " 'Seychelles',\n",
       " 'Sierra Leone',\n",
       " 'Singapore',\n",
       " 'Sint Maarten (Dutch part)',\n",
       " 'Slovakia',\n",
       " 'Slovenia',\n",
       " 'Solomon Islands',\n",
       " 'Somalia',\n",
       " 'South Africa',\n",
       " 'South Sudan',\n",
       " 'Spain',\n",
       " 'Sri Lanka',\n",
       " 'State of Palestine',\n",
       " 'Sudan',\n",
       " 'Suriname',\n",
       " 'Sweden',\n",
       " 'Switzerland',\n",
       " 'Syrian Arab Republic',\n",
       " 'Tajikistan',\n",
       " 'Thailand',\n",
       " 'Timor-Leste',\n",
       " 'Togo',\n",
       " 'Tokelau',\n",
       " 'Tonga',\n",
       " 'Trinidad and Tobago',\n",
       " 'Tunisia',\n",
       " 'Türkiye',\n",
       " 'Turkmenistan',\n",
       " 'Turks and Caicos Islands',\n",
       " 'Tuvalu',\n",
       " 'Uganda',\n",
       " 'Ukraine',\n",
       " 'United Arab Emirates',\n",
       " 'United Kingdom',\n",
       " 'United Rep. of Tanzania',\n",
       " 'United States of America',\n",
       " 'United States Virgin Islands',\n",
       " 'Uruguay',\n",
       " 'Uzbekistan',\n",
       " 'Vanuatu',\n",
       " 'Venezuela (Boliv. Rep. of)',\n",
       " 'Viet Nam',\n",
       " 'Wallis and Futuna Islands',\n",
       " 'Western Sahara',\n",
       " 'Yemen',\n",
       " 'Zambia',\n",
       " 'Zimbabwe']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(migrants_total[\"Region/Country/Area\"].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "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>Region/Country/Area</th>\n",
       "      <th>Unnamed: 1</th>\n",
       "      <th>Year</th>\n",
       "      <th>Series</th>\n",
       "      <th>Value</th>\n",
       "      <th>Footnotes</th>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2010</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>7,021.73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United Nations Population Division, New York, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2010</td>\n",
       "      <td>Population mid-year estimates for males (milli...</td>\n",
       "      <td>3,533.14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United Nations Population Division, New York, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2010</td>\n",
       "      <td>Population mid-year estimates for females (mil...</td>\n",
       "      <td>3,488.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United Nations Population Division, New York, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2010</td>\n",
       "      <td>Sex ratio (males per 100 females)</td>\n",
       "      <td>101.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>United Nations Population Division, New York, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2010</td>\n",
       "      <td>Population aged 0 to 14 years old (percentage)</td>\n",
       "      <td>27.3</td>\n",
       "      <td>Calculated by the UN Statistics Division.</td>\n",
       "      <td>United Nations Population Division, New York, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7705</th>\n",
       "      <td>722</td>\n",
       "      <td>SIDS</td>\n",
       "      <td>2024</td>\n",
       "      <td>Population mid-year estimates for females (mil...</td>\n",
       "      <td>36.77</td>\n",
       "      <td>Projected estimate (medium fertility variant).</td>\n",
       "      <td>United Nations Population Division, New York, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7706</th>\n",
       "      <td>722</td>\n",
       "      <td>SIDS</td>\n",
       "      <td>2024</td>\n",
       "      <td>Sex ratio (males per 100 females)</td>\n",
       "      <td>99.8</td>\n",
       "      <td>Projected estimate (medium fertility variant).</td>\n",
       "      <td>United Nations Population Division, New York, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7707</th>\n",
       "      <td>722</td>\n",
       "      <td>SIDS</td>\n",
       "      <td>2024</td>\n",
       "      <td>Population aged 0 to 14 years old (percentage)</td>\n",
       "      <td>24.5</td>\n",
       "      <td>Projected estimate (medium fertility variant)....</td>\n",
       "      <td>United Nations Population Division, New York, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7708</th>\n",
       "      <td>722</td>\n",
       "      <td>SIDS</td>\n",
       "      <td>2024</td>\n",
       "      <td>Population aged 60+ years old (percentage)</td>\n",
       "      <td>13.8</td>\n",
       "      <td>Projected estimate (medium fertility variant)....</td>\n",
       "      <td>United Nations Population Division, New York, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7709</th>\n",
       "      <td>722</td>\n",
       "      <td>SIDS</td>\n",
       "      <td>2024</td>\n",
       "      <td>Population density</td>\n",
       "      <td>30.8</td>\n",
       "      <td>Projected estimate (medium fertility variant).</td>\n",
       "      <td>United Nations Population Division, New York, ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7710 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Region/Country/Area                     Unnamed: 1  Year  \\\n",
       "0                       1  Total, all countries or areas  2010   \n",
       "1                       1  Total, all countries or areas  2010   \n",
       "2                       1  Total, all countries or areas  2010   \n",
       "3                       1  Total, all countries or areas  2010   \n",
       "4                       1  Total, all countries or areas  2010   \n",
       "...                   ...                            ...   ...   \n",
       "7705                  722                           SIDS  2024   \n",
       "7706                  722                           SIDS  2024   \n",
       "7707                  722                           SIDS  2024   \n",
       "7708                  722                           SIDS  2024   \n",
       "7709                  722                           SIDS  2024   \n",
       "\n",
       "                                                 Series     Value  \\\n",
       "0              Population mid-year estimates (millions)  7,021.73   \n",
       "1     Population mid-year estimates for males (milli...  3,533.14   \n",
       "2     Population mid-year estimates for females (mil...  3,488.59   \n",
       "3                     Sex ratio (males per 100 females)     101.3   \n",
       "4        Population aged 0 to 14 years old (percentage)      27.3   \n",
       "...                                                 ...       ...   \n",
       "7705  Population mid-year estimates for females (mil...     36.77   \n",
       "7706                  Sex ratio (males per 100 females)      99.8   \n",
       "7707     Population aged 0 to 14 years old (percentage)      24.5   \n",
       "7708         Population aged 60+ years old (percentage)      13.8   \n",
       "7709                                 Population density      30.8   \n",
       "\n",
       "                                              Footnotes  \\\n",
       "0                                                   NaN   \n",
       "1                                                   NaN   \n",
       "2                                                   NaN   \n",
       "3                                                   NaN   \n",
       "4             Calculated by the UN Statistics Division.   \n",
       "...                                                 ...   \n",
       "7705     Projected estimate (medium fertility variant).   \n",
       "7706     Projected estimate (medium fertility variant).   \n",
       "7707  Projected estimate (medium fertility variant)....   \n",
       "7708  Projected estimate (medium fertility variant)....   \n",
       "7709     Projected estimate (medium fertility variant).   \n",
       "\n",
       "                                                 Source  \n",
       "0     United Nations Population Division, New York, ...  \n",
       "1     United Nations Population Division, New York, ...  \n",
       "2     United Nations Population Division, New York, ...  \n",
       "3     United Nations Population Division, New York, ...  \n",
       "4     United Nations Population Division, New York, ...  \n",
       "...                                                 ...  \n",
       "7705  United Nations Population Division, New York, ...  \n",
       "7706  United Nations Population Division, New York, ...  \n",
       "7707  United Nations Population Division, New York, ...  \n",
       "7708  United Nations Population Division, New York, ...  \n",
       "7709  United Nations Population Division, New York, ...  \n",
       "\n",
       "[7710 rows x 7 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "demographics = pd.read_csv(\n",
    "    \"https://data.un.org/_Docs/SYB/CSV/SYB67_1_202411_Population,%20Surface%20Area%20and%20Density.csv\",\n",
    "    skiprows=1,\n",
    ")\n",
    "demographics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Region/Country/Area</th>\n",
       "      <th>Year</th>\n",
       "      <th>Series</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
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       "      <td>7,021.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2010</td>\n",
       "      <td>Population mid-year estimates for males (milli...</td>\n",
       "      <td>3,533.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2010</td>\n",
       "      <td>Population mid-year estimates for females (mil...</td>\n",
       "      <td>3,488.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2010</td>\n",
       "      <td>Sex ratio (males per 100 females)</td>\n",
       "      <td>101.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2010</td>\n",
       "      <td>Population aged 0 to 14 years old (percentage)</td>\n",
       "      <td>27.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>7705</th>\n",
       "      <td>SIDS</td>\n",
       "      <td>2024</td>\n",
       "      <td>Population mid-year estimates for females (mil...</td>\n",
       "      <td>36.77</td>\n",
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       "    <tr>\n",
       "      <th>7706</th>\n",
       "      <td>SIDS</td>\n",
       "      <td>2024</td>\n",
       "      <td>Sex ratio (males per 100 females)</td>\n",
       "      <td>99.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7707</th>\n",
       "      <td>SIDS</td>\n",
       "      <td>2024</td>\n",
       "      <td>Population aged 0 to 14 years old (percentage)</td>\n",
       "      <td>24.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7708</th>\n",
       "      <td>SIDS</td>\n",
       "      <td>2024</td>\n",
       "      <td>Population aged 60+ years old (percentage)</td>\n",
       "      <td>13.8</td>\n",
       "    </tr>\n",
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       "      <th>7709</th>\n",
       "      <td>SIDS</td>\n",
       "      <td>2024</td>\n",
       "      <td>Population density</td>\n",
       "      <td>30.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7710 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                Region/Country/Area  Year  \\\n",
       "0     Total, all countries or areas  2010   \n",
       "1     Total, all countries or areas  2010   \n",
       "2     Total, all countries or areas  2010   \n",
       "3     Total, all countries or areas  2010   \n",
       "4     Total, all countries or areas  2010   \n",
       "...                             ...   ...   \n",
       "7705                           SIDS  2024   \n",
       "7706                           SIDS  2024   \n",
       "7707                           SIDS  2024   \n",
       "7708                           SIDS  2024   \n",
       "7709                           SIDS  2024   \n",
       "\n",
       "                                                 Series     Value  \n",
       "0              Population mid-year estimates (millions)  7,021.73  \n",
       "1     Population mid-year estimates for males (milli...  3,533.14  \n",
       "2     Population mid-year estimates for females (mil...  3,488.59  \n",
       "3                     Sex ratio (males per 100 females)     101.3  \n",
       "4        Population aged 0 to 14 years old (percentage)      27.3  \n",
       "...                                                 ...       ...  \n",
       "7705  Population mid-year estimates for females (mil...     36.77  \n",
       "7706                  Sex ratio (males per 100 females)      99.8  \n",
       "7707     Population aged 0 to 14 years old (percentage)      24.5  \n",
       "7708         Population aged 60+ years old (percentage)      13.8  \n",
       "7709                                 Population density      30.8  \n",
       "\n",
       "[7710 rows x 4 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "demographics = demographics.drop(columns=[\"Region/Country/Area\", \"Footnotes\", \"Source\"])\n",
    "demographics = demographics.rename(columns={\"Unnamed: 1\": \"Region/Country/Area\"})\n",
    "demographics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Population mid-year estimates (millions)',\n",
       "       'Population mid-year estimates for males (millions)',\n",
       "       'Population mid-year estimates for females (millions)',\n",
       "       'Sex ratio (males per 100 females)',\n",
       "       'Population aged 0 to 14 years old (percentage)',\n",
       "       'Population aged 60+ years old (percentage)', 'Population density',\n",
       "       'Surface area (thousand km2)'], dtype=object)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "demographics[\"Series\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "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>Region/Country/Area</th>\n",
       "      <th>Year</th>\n",
       "      <th>Series</th>\n",
       "      <th>Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2010</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>7,021.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2015</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>7,470.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2022</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>8,021.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2024</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>8,161.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Africa</td>\n",
       "      <td>2010</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>1,072.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7675</th>\n",
       "      <td>LDC§</td>\n",
       "      <td>2015</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>962.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7682</th>\n",
       "      <td>LDC§</td>\n",
       "      <td>2024</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>1,188.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7689</th>\n",
       "      <td>SIDS</td>\n",
       "      <td>2010</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>64.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7696</th>\n",
       "      <td>SIDS</td>\n",
       "      <td>2015</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>68.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7703</th>\n",
       "      <td>SIDS</td>\n",
       "      <td>2024</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>73.46</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1065 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                Region/Country/Area  Year  \\\n",
       "0     Total, all countries or areas  2010   \n",
       "7     Total, all countries or areas  2015   \n",
       "14    Total, all countries or areas  2022   \n",
       "22    Total, all countries or areas  2024   \n",
       "29                           Africa  2010   \n",
       "...                             ...   ...   \n",
       "7675                           LDC§  2015   \n",
       "7682                           LDC§  2024   \n",
       "7689                           SIDS  2010   \n",
       "7696                           SIDS  2015   \n",
       "7703                           SIDS  2024   \n",
       "\n",
       "                                        Series     Value  \n",
       "0     Population mid-year estimates (millions)  7,021.73  \n",
       "7     Population mid-year estimates (millions)  7,470.49  \n",
       "14    Population mid-year estimates (millions)  8,021.41  \n",
       "22    Population mid-year estimates (millions)  8,161.97  \n",
       "29    Population mid-year estimates (millions)  1,072.22  \n",
       "...                                        ...       ...  \n",
       "7675  Population mid-year estimates (millions)    962.71  \n",
       "7682  Population mid-year estimates (millions)  1,188.01  \n",
       "7689  Population mid-year estimates (millions)     64.59  \n",
       "7696  Population mid-year estimates (millions)     68.19  \n",
       "7703  Population mid-year estimates (millions)     73.46  \n",
       "\n",
       "[1065 rows x 4 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pop = demographics[demographics[\"Series\"] == \"Population mid-year estimates (millions)\"]\n",
    "pop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>Region/Country/Area</th>\n",
       "      <th>Year</th>\n",
       "      <th>Series_x</th>\n",
       "      <th>Value_x</th>\n",
       "      <th>Series_y</th>\n",
       "      <th>Value_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2010</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>220,983,187</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>7,021.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2015</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>247,958,644</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>7,470.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Africa</td>\n",
       "      <td>2010</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>17,806,677</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>1,072.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Africa</td>\n",
       "      <td>2015</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>22,860,792</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>1,220.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Northern Africa</td>\n",
       "      <td>2010</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>1,952,040</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>210.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>515</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>2015</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>379,882</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>31.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>Zambia</td>\n",
       "      <td>2010</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>149,962</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>13.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>517</th>\n",
       "      <td>Zambia</td>\n",
       "      <td>2015</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>132,107</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>16.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>518</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2010</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>398,307</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>13.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>519</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2015</td>\n",
       "      <td>International migrant stock: Both sexes (number)</td>\n",
       "      <td>400,482</td>\n",
       "      <td>Population mid-year estimates (millions)</td>\n",
       "      <td>14.40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>520 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Region/Country/Area  Year  \\\n",
       "0    Total, all countries or areas  2010   \n",
       "1    Total, all countries or areas  2015   \n",
       "2                           Africa  2010   \n",
       "3                           Africa  2015   \n",
       "4                  Northern Africa  2010   \n",
       "..                             ...   ...   \n",
       "515                          Yemen  2015   \n",
       "516                         Zambia  2010   \n",
       "517                         Zambia  2015   \n",
       "518                       Zimbabwe  2010   \n",
       "519                       Zimbabwe  2015   \n",
       "\n",
       "                                             Series_x      Value_x  \\\n",
       "0    International migrant stock: Both sexes (number)  220,983,187   \n",
       "1    International migrant stock: Both sexes (number)  247,958,644   \n",
       "2    International migrant stock: Both sexes (number)   17,806,677   \n",
       "3    International migrant stock: Both sexes (number)   22,860,792   \n",
       "4    International migrant stock: Both sexes (number)    1,952,040   \n",
       "..                                                ...          ...   \n",
       "515  International migrant stock: Both sexes (number)      379,882   \n",
       "516  International migrant stock: Both sexes (number)      149,962   \n",
       "517  International migrant stock: Both sexes (number)      132,107   \n",
       "518  International migrant stock: Both sexes (number)      398,307   \n",
       "519  International migrant stock: Both sexes (number)      400,482   \n",
       "\n",
       "                                     Series_y   Value_y  \n",
       "0    Population mid-year estimates (millions)  7,021.73  \n",
       "1    Population mid-year estimates (millions)  7,470.49  \n",
       "2    Population mid-year estimates (millions)  1,072.22  \n",
       "3    Population mid-year estimates (millions)  1,220.08  \n",
       "4    Population mid-year estimates (millions)    210.94  \n",
       "..                                        ...       ...  \n",
       "515  Population mid-year estimates (millions)     31.16  \n",
       "516  Population mid-year estimates (millions)     13.97  \n",
       "517  Population mid-year estimates (millions)     16.40  \n",
       "518  Population mid-year estimates (millions)     13.36  \n",
       "519  Population mid-year estimates (millions)     14.40  \n",
       "\n",
       "[520 rows x 6 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged = pd.merge(migrants_total, pop, on=[\"Region/Country/Area\", \"Year\"])\n",
    "merged"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "Clean up columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "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>Region/Country/Area</th>\n",
       "      <th>Year</th>\n",
       "      <th>Migrants</th>\n",
       "      <th>Population</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2010</td>\n",
       "      <td>220,983,187</td>\n",
       "      <td>7,021.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2015</td>\n",
       "      <td>247,958,644</td>\n",
       "      <td>7,470.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Africa</td>\n",
       "      <td>2010</td>\n",
       "      <td>17,806,677</td>\n",
       "      <td>1,072.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Africa</td>\n",
       "      <td>2015</td>\n",
       "      <td>22,860,792</td>\n",
       "      <td>1,220.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Northern Africa</td>\n",
       "      <td>2010</td>\n",
       "      <td>1,952,040</td>\n",
       "      <td>210.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>515</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>2015</td>\n",
       "      <td>379,882</td>\n",
       "      <td>31.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>Zambia</td>\n",
       "      <td>2010</td>\n",
       "      <td>149,962</td>\n",
       "      <td>13.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>517</th>\n",
       "      <td>Zambia</td>\n",
       "      <td>2015</td>\n",
       "      <td>132,107</td>\n",
       "      <td>16.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>518</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2010</td>\n",
       "      <td>398,307</td>\n",
       "      <td>13.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>519</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2015</td>\n",
       "      <td>400,482</td>\n",
       "      <td>14.40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>520 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Region/Country/Area  Year     Migrants Population\n",
       "0    Total, all countries or areas  2010  220,983,187   7,021.73\n",
       "1    Total, all countries or areas  2015  247,958,644   7,470.49\n",
       "2                           Africa  2010   17,806,677   1,072.22\n",
       "3                           Africa  2015   22,860,792   1,220.08\n",
       "4                  Northern Africa  2010    1,952,040     210.94\n",
       "..                             ...   ...          ...        ...\n",
       "515                          Yemen  2015      379,882      31.16\n",
       "516                         Zambia  2010      149,962      13.97\n",
       "517                         Zambia  2015      132,107      16.40\n",
       "518                       Zimbabwe  2010      398,307      13.36\n",
       "519                       Zimbabwe  2015      400,482      14.40\n",
       "\n",
       "[520 rows x 4 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged = merged.rename(columns={\n",
    "    \"Value_x\": \"Migrants\",\n",
    "    \"Value_y\": \"Population\",\n",
    "})\n",
    "merged = merged.drop(columns=[\"Series_x\", \"Series_y\"])\n",
    "merged"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      7,021.737,021.737,021.737,021.737,021.737,021....\n",
       "1      7,470.497,470.497,470.497,470.497,470.497,470....\n",
       "2      1,072.221,072.221,072.221,072.221,072.221,072....\n",
       "3      1,220.081,220.081,220.081,220.081,220.081,220....\n",
       "4      210.94210.94210.94210.94210.94210.94210.94210....\n",
       "                             ...                        \n",
       "515    31.1631.1631.1631.1631.1631.1631.1631.1631.163...\n",
       "516    13.9713.9713.9713.9713.9713.9713.9713.9713.971...\n",
       "517    16.4016.4016.4016.4016.4016.4016.4016.4016.401...\n",
       "518    13.3613.3613.3613.3613.3613.3613.3613.3613.361...\n",
       "519    14.4014.4014.4014.4014.4014.4014.4014.4014.401...\n",
       "Name: Population, Length: 520, dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged[\"Population\"] * 1000000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 520 entries, 0 to 519\n",
      "Data columns (total 4 columns):\n",
      " #   Column               Non-Null Count  Dtype \n",
      "---  ------               --------------  ----- \n",
      " 0   Region/Country/Area  520 non-null    object\n",
      " 1   Year                 520 non-null    int64 \n",
      " 2   Migrants             520 non-null    object\n",
      " 3   Population           520 non-null    object\n",
      "dtypes: int64(1), object(3)\n",
      "memory usage: 16.4+ KB\n"
     ]
    }
   ],
   "source": [
    "merged.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 520 entries, 0 to 519\n",
      "Data columns (total 4 columns):\n",
      " #   Column               Non-Null Count  Dtype  \n",
      "---  ------               --------------  -----  \n",
      " 0   Region/Country/Area  520 non-null    object \n",
      " 1   Year                 520 non-null    int64  \n",
      " 2   Migrants             520 non-null    float64\n",
      " 3   Population           520 non-null    float64\n",
      "dtypes: float64(2), int64(1), object(1)\n",
      "memory usage: 16.4+ KB\n"
     ]
    }
   ],
   "source": [
    "pop_float = merged[\"Population\"].str.replace(\",\", \"\").astype(float)\n",
    "merged[\"Population\"] = pop_float * 1000000\n",
    "\n",
    "merged[\"Migrants\"] = merged[\"Migrants\"].str.replace(\",\", \"\").astype(float)\n",
    "\n",
    "merged.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "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>Region/Country/Area</th>\n",
       "      <th>Year</th>\n",
       "      <th>Migrants</th>\n",
       "      <th>Population</th>\n",
       "      <th>Migrant %</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2010</td>\n",
       "      <td>220983187.0</td>\n",
       "      <td>7.021730e+09</td>\n",
       "      <td>0.031471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Total, all countries or areas</td>\n",
       "      <td>2015</td>\n",
       "      <td>247958644.0</td>\n",
       "      <td>7.470490e+09</td>\n",
       "      <td>0.033192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Africa</td>\n",
       "      <td>2010</td>\n",
       "      <td>17806677.0</td>\n",
       "      <td>1.072220e+09</td>\n",
       "      <td>0.016607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Africa</td>\n",
       "      <td>2015</td>\n",
       "      <td>22860792.0</td>\n",
       "      <td>1.220080e+09</td>\n",
       "      <td>0.018737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Northern Africa</td>\n",
       "      <td>2010</td>\n",
       "      <td>1952040.0</td>\n",
       "      <td>2.109400e+08</td>\n",
       "      <td>0.009254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>515</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>2015</td>\n",
       "      <td>379882.0</td>\n",
       "      <td>3.116000e+07</td>\n",
       "      <td>0.012191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>Zambia</td>\n",
       "      <td>2010</td>\n",
       "      <td>149962.0</td>\n",
       "      <td>1.397000e+07</td>\n",
       "      <td>0.010735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>517</th>\n",
       "      <td>Zambia</td>\n",
       "      <td>2015</td>\n",
       "      <td>132107.0</td>\n",
       "      <td>1.640000e+07</td>\n",
       "      <td>0.008055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>518</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2010</td>\n",
       "      <td>398307.0</td>\n",
       "      <td>1.336000e+07</td>\n",
       "      <td>0.029813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>519</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2015</td>\n",
       "      <td>400482.0</td>\n",
       "      <td>1.440000e+07</td>\n",
       "      <td>0.027811</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>520 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Region/Country/Area  Year     Migrants    Population  Migrant %\n",
       "0    Total, all countries or areas  2010  220983187.0  7.021730e+09   0.031471\n",
       "1    Total, all countries or areas  2015  247958644.0  7.470490e+09   0.033192\n",
       "2                           Africa  2010   17806677.0  1.072220e+09   0.016607\n",
       "3                           Africa  2015   22860792.0  1.220080e+09   0.018737\n",
       "4                  Northern Africa  2010    1952040.0  2.109400e+08   0.009254\n",
       "..                             ...   ...          ...           ...        ...\n",
       "515                          Yemen  2015     379882.0  3.116000e+07   0.012191\n",
       "516                         Zambia  2010     149962.0  1.397000e+07   0.010735\n",
       "517                         Zambia  2015     132107.0  1.640000e+07   0.008055\n",
       "518                       Zimbabwe  2010     398307.0  1.336000e+07   0.029813\n",
       "519                       Zimbabwe  2015     400482.0  1.440000e+07   0.027811\n",
       "\n",
       "[520 rows x 5 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged[\"Migrant %\"] = merged[\"Migrants\"] / merged[\"Population\"]\n",
    "merged"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\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>Region/Country/Area</th>\n",
       "      <th>Year</th>\n",
       "      <th>Migrants</th>\n",
       "      <th>Population</th>\n",
       "      <th>Migrant %</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>360</th>\n",
       "      <td>Niue</td>\n",
       "      <td>2010</td>\n",
       "      <td>589.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>470</th>\n",
       "      <td>Tokelau</td>\n",
       "      <td>2010</td>\n",
       "      <td>1128.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>471</th>\n",
       "      <td>Tokelau</td>\n",
       "      <td>2015</td>\n",
       "      <td>1185.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>Niue</td>\n",
       "      <td>2015</td>\n",
       "      <td>588.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>Falkland Islands (Malvinas)</td>\n",
       "      <td>2010</td>\n",
       "      <td>1436.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508</th>\n",
       "      <td>Viet Nam</td>\n",
       "      <td>2010</td>\n",
       "      <td>61756.0</td>\n",
       "      <td>8.746000e+07</td>\n",
       "      <td>0.000706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>China</td>\n",
       "      <td>2015</td>\n",
       "      <td>978046.0</td>\n",
       "      <td>1.396130e+09</td>\n",
       "      <td>0.000701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>Cuba</td>\n",
       "      <td>2010</td>\n",
       "      <td>7373.0</td>\n",
       "      <td>1.130000e+07</td>\n",
       "      <td>0.000652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>China</td>\n",
       "      <td>2010</td>\n",
       "      <td>849861.0</td>\n",
       "      <td>1.351560e+09</td>\n",
       "      <td>0.000629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>Cuba</td>\n",
       "      <td>2015</td>\n",
       "      <td>4649.0</td>\n",
       "      <td>1.128000e+07</td>\n",
       "      <td>0.000412</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>520 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Region/Country/Area  Year  Migrants    Population  Migrant %\n",
       "360                         Niue  2010     589.0  0.000000e+00        inf\n",
       "470                      Tokelau  2010    1128.0  0.000000e+00        inf\n",
       "471                      Tokelau  2015    1185.0  0.000000e+00        inf\n",
       "361                         Niue  2015     588.0  0.000000e+00        inf\n",
       "200  Falkland Islands (Malvinas)  2010    1436.0  0.000000e+00        inf\n",
       "..                           ...   ...       ...           ...        ...\n",
       "508                     Viet Nam  2010   61756.0  8.746000e+07   0.000706\n",
       "145                        China  2015  978046.0  1.396130e+09   0.000701\n",
       "164                         Cuba  2010    7373.0  1.130000e+07   0.000652\n",
       "144                        China  2010  849861.0  1.351560e+09   0.000629\n",
       "165                         Cuba  2015    4649.0  1.128000e+07   0.000412\n",
       "\n",
       "[520 rows x 5 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged.sort_values(\"Migrant %\", ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        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>Region/Country/Area</th>\n",
       "      <th>Year</th>\n",
       "      <th>Migrants</th>\n",
       "      <th>Population</th>\n",
       "      <th>Migrant %</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>Bonaire, St. Eustatius &amp; Saba</td>\n",
       "      <td>2015</td>\n",
       "      <td>24571.0</td>\n",
       "      <td>2.000000e+04</td>\n",
       "      <td>1.228550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491</th>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>2015</td>\n",
       "      <td>7995126.0</td>\n",
       "      <td>8.670000e+06</td>\n",
       "      <td>0.922160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>281</th>\n",
       "      <td>Kuwait</td>\n",
       "      <td>2015</td>\n",
       "      <td>2866136.0</td>\n",
       "      <td>3.830000e+06</td>\n",
       "      <td>0.748338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>391</th>\n",
       "      <td>Qatar</td>\n",
       "      <td>2015</td>\n",
       "      <td>1687640.0</td>\n",
       "      <td>2.430000e+06</td>\n",
       "      <td>0.694502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>Sint Maarten (Dutch part)</td>\n",
       "      <td>2015</td>\n",
       "      <td>27295.0</td>\n",
       "      <td>4.000000e+04</td>\n",
       "      <td>0.682375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>Indonesia</td>\n",
       "      <td>2015</td>\n",
       "      <td>338124.0</td>\n",
       "      <td>2.618000e+08</td>\n",
       "      <td>0.001292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>303</th>\n",
       "      <td>Madagascar</td>\n",
       "      <td>2015</td>\n",
       "      <td>32075.0</td>\n",
       "      <td>2.543000e+07</td>\n",
       "      <td>0.001261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>Viet Nam</td>\n",
       "      <td>2015</td>\n",
       "      <td>72793.0</td>\n",
       "      <td>9.282000e+07</td>\n",
       "      <td>0.000784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>China</td>\n",
       "      <td>2015</td>\n",
       "      <td>978046.0</td>\n",
       "      <td>1.396130e+09</td>\n",
       "      <td>0.000701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>Cuba</td>\n",
       "      <td>2015</td>\n",
       "      <td>4649.0</td>\n",
       "      <td>1.128000e+07</td>\n",
       "      <td>0.000412</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>256 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Region/Country/Area  Year   Migrants    Population  Migrant %\n",
       "111  Bonaire, St. Eustatius & Saba  2015    24571.0  2.000000e+04   1.228550\n",
       "491           United Arab Emirates  2015  7995126.0  8.670000e+06   0.922160\n",
       "281                         Kuwait  2015  2866136.0  3.830000e+06   0.748338\n",
       "391                          Qatar  2015  1687640.0  2.430000e+06   0.694502\n",
       "433      Sint Maarten (Dutch part)  2015    27295.0  4.000000e+04   0.682375\n",
       "..                             ...   ...        ...           ...        ...\n",
       "255                      Indonesia  2015   338124.0  2.618000e+08   0.001292\n",
       "303                     Madagascar  2015    32075.0  2.543000e+07   0.001261\n",
       "509                       Viet Nam  2015    72793.0  9.282000e+07   0.000784\n",
       "145                          China  2015   978046.0  1.396130e+09   0.000701\n",
       "165                           Cuba  2015     4649.0  1.128000e+07   0.000412\n",
       "\n",
       "[256 rows x 5 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "has_pop = merged[\"Population\"] > 0\n",
    "pop_2015 = merged[\"Year\"] == 2015\n",
    "merged_2015 = merged[has_pop & pop_2015]\n",
    "\n",
    "merged_2015.sort_values(\"Migrant %\", ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "Save the data to a file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# merged_2015.to_csv(\"data/migrants_by_country.csv\", index=False)"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "kernelspec": {
   "display_name": "Python [conda env:python-public-policy] *",
   "language": "python",
   "name": "conda-env-python-public-policy-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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