Lab3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "27043757-19f9-48b5-96ae-17141a7d6489",
   "metadata": {},
   "source": [
    "# 1 A & B"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3456dce-e713-428b-80a3-dd8e85250caf",
   "metadata": {},
   "source": [
    "#####Repo link \n",
    "https://github.com/JackBeerman/Lab3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33f01f9d-5528-4438-8323-fb13bae6ad98",
   "metadata": {},
   "source": [
    "# 2 A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7f8836eb-17a3-4b28-a685-0e7242f72d62",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import requests\n",
    "import os\n",
    "import zipfile\n",
    "import io\n",
    "POSTGRES_PASSWORD = os.getenv('POSTGRES_PASSWORD')\n",
    "import psycopg2\n",
    "from sqlalchemy import create_engine"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d0afa743-8862-479f-966c-1056c7715856",
   "metadata": {},
   "source": [
    "# 2 B"
   ]
  },
  {
   "cell_type": "raw",
   "id": "bc3ee93d-ff69-4769-bb8c-4240de59e403",
   "metadata": {},
   "source": [
    "url = 'https://databank.worldbank.org/data/download/ESG_CSV.zip'\n",
    "r = requests.get(url)\n",
    "z = zipfile.ZipFile(io.BytesIO(r.content))\n",
    "z.extractall()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "b60c43fc-2247-462f-9a2e-d781e7d4ded8",
   "metadata": {},
   "source": [
    "url = 'https://v-dem.net/media/datasets/V-Dem-CY-Core_csv_v13.zip'\n",
    "r = requests.get(url)\n",
    "z = zipfile.ZipFile(io.BytesIO(r.content))\n",
    "z.extractall()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4b2ac2ff-cefa-45a0-a94f-88e548998ae7",
   "metadata": {},
   "outputs": [],
   "source": [
    "wb = pd.read_csv(\"ESGData.csv\")\n",
    "vdem = pd.read_csv('V-Dem-CY-Core-v13.csv')\n",
    "country = pd.read_csv('ESGCountry.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c72b5de-6320-484a-85e7-165f6b0f94bf",
   "metadata": {},
   "source": [
    "# 2 C"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3f91bdde-7037-4fe5-8807-4d547453b3c7",
   "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_text_id</th>\n",
       "      <th>country_name</th>\n",
       "      <th>year</th>\n",
       "      <th>v2x_polyarchy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MEX</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>1789</td>\n",
       "      <td>0.028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MEX</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>1790</td>\n",
       "      <td>0.028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MEX</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>1791</td>\n",
       "      <td>0.028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MEX</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>1792</td>\n",
       "      <td>0.028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MEX</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>1793</td>\n",
       "      <td>0.028</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>27550</th>\n",
       "      <td>SPD</td>\n",
       "      <td>Piedmont-Sardinia</td>\n",
       "      <td>1857</td>\n",
       "      <td>0.207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27551</th>\n",
       "      <td>SPD</td>\n",
       "      <td>Piedmont-Sardinia</td>\n",
       "      <td>1858</td>\n",
       "      <td>0.210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27552</th>\n",
       "      <td>SPD</td>\n",
       "      <td>Piedmont-Sardinia</td>\n",
       "      <td>1859</td>\n",
       "      <td>0.210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27553</th>\n",
       "      <td>SPD</td>\n",
       "      <td>Piedmont-Sardinia</td>\n",
       "      <td>1860</td>\n",
       "      <td>0.213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27554</th>\n",
       "      <td>SPD</td>\n",
       "      <td>Piedmont-Sardinia</td>\n",
       "      <td>1861</td>\n",
       "      <td>0.213</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>27555 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country_text_id       country_name  year  v2x_polyarchy\n",
       "0                 MEX             Mexico  1789          0.028\n",
       "1                 MEX             Mexico  1790          0.028\n",
       "2                 MEX             Mexico  1791          0.028\n",
       "3                 MEX             Mexico  1792          0.028\n",
       "4                 MEX             Mexico  1793          0.028\n",
       "...               ...                ...   ...            ...\n",
       "27550             SPD  Piedmont-Sardinia  1857          0.207\n",
       "27551             SPD  Piedmont-Sardinia  1858          0.210\n",
       "27552             SPD  Piedmont-Sardinia  1859          0.210\n",
       "27553             SPD  Piedmont-Sardinia  1860          0.213\n",
       "27554             SPD  Piedmont-Sardinia  1861          0.213\n",
       "\n",
       "[27555 rows x 4 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vdem = vdem[['country_text_id', 'country_name','year', 'v2x_polyarchy']]\n",
    "vdem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a098d2bd-4dd1-4f6f-87ce-a20645a560f8",
   "metadata": {},
   "outputs": [],
   "source": [
    "vdem = vdem.query('year >= 1960 and year <= 2021')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6f924746-a9a3-42f2-950d-35cb4efcaeb6",
   "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_text_id</th>\n",
       "      <th>country_name</th>\n",
       "      <th>year</th>\n",
       "      <th>v2x_polyarchy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>MEX</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>1960</td>\n",
       "      <td>0.232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>MEX</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>1961</td>\n",
       "      <td>0.234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>MEX</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>1962</td>\n",
       "      <td>0.233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>MEX</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>1963</td>\n",
       "      <td>0.233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>MEX</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>1964</td>\n",
       "      <td>0.231</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>26150</th>\n",
       "      <td>ZZB</td>\n",
       "      <td>Zanzibar</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26151</th>\n",
       "      <td>ZZB</td>\n",
       "      <td>Zanzibar</td>\n",
       "      <td>2018</td>\n",
       "      <td>0.268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26152</th>\n",
       "      <td>ZZB</td>\n",
       "      <td>Zanzibar</td>\n",
       "      <td>2019</td>\n",
       "      <td>0.266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26153</th>\n",
       "      <td>ZZB</td>\n",
       "      <td>Zanzibar</td>\n",
       "      <td>2020</td>\n",
       "      <td>0.258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26154</th>\n",
       "      <td>ZZB</td>\n",
       "      <td>Zanzibar</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.276</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10371 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country_text_id country_name  year  v2x_polyarchy\n",
       "171               MEX       Mexico  1960          0.232\n",
       "172               MEX       Mexico  1961          0.234\n",
       "173               MEX       Mexico  1962          0.233\n",
       "174               MEX       Mexico  1963          0.233\n",
       "175               MEX       Mexico  1964          0.231\n",
       "...               ...          ...   ...            ...\n",
       "26150             ZZB     Zanzibar  2017          0.267\n",
       "26151             ZZB     Zanzibar  2018          0.268\n",
       "26152             ZZB     Zanzibar  2019          0.266\n",
       "26153             ZZB     Zanzibar  2020          0.258\n",
       "26154             ZZB     Zanzibar  2021          0.276\n",
       "\n",
       "[10371 rows x 4 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vdem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "377afcf8-98bb-4dbf-8867-783f43282218",
   "metadata": {},
   "outputs": [],
   "source": [
    "vdem = vdem.rename(columns={\"country_text_id\": \"country_code\", \"country_name\": \"country_name_vdem\", \"v2x_polyarchy\": 'democracy'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c258e1c4-89b6-4fed-9813-edcf9a496bdd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country_code</th>\n",
       "      <th>country_name_vdem</th>\n",
       "      <th>year</th>\n",
       "      <th>democracy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5433</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>1960</td>\n",
       "      <td>0.080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15884</th>\n",
       "      <td>AGO</td>\n",
       "      <td>Angola</td>\n",
       "      <td>1960</td>\n",
       "      <td>0.009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1810</th>\n",
       "      <td>ALB</td>\n",
       "      <td>Albania</td>\n",
       "      <td>1960</td>\n",
       "      <td>0.176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5667</th>\n",
       "      <td>ARG</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>1960</td>\n",
       "      <td>0.485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10084</th>\n",
       "      <td>AUS</td>\n",
       "      <td>Australia</td>\n",
       "      <td>1960</td>\n",
       "      <td>0.829</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>2272</th>\n",
       "      <td>YEM</td>\n",
       "      <td>Yemen</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1058</th>\n",
       "      <td>ZAF</td>\n",
       "      <td>South Africa</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9241</th>\n",
       "      <td>ZMB</td>\n",
       "      <td>Zambia</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9364</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26154</th>\n",
       "      <td>ZZB</td>\n",
       "      <td>Zanzibar</td>\n",
       "      <td>2021</td>\n",
       "      <td>0.276</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10371 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country_code country_name_vdem  year  democracy\n",
       "5433           AFG       Afghanistan  1960      0.080\n",
       "15884          AGO            Angola  1960      0.009\n",
       "1810           ALB           Albania  1960      0.176\n",
       "5667           ARG         Argentina  1960      0.485\n",
       "10084          AUS         Australia  1960      0.829\n",
       "...            ...               ...   ...        ...\n",
       "2272           YEM             Yemen  2021      0.114\n",
       "1058           ZAF      South Africa  2021      0.702\n",
       "9241           ZMB            Zambia  2021      0.411\n",
       "9364           ZWE          Zimbabwe  2021      0.291\n",
       "26154          ZZB          Zanzibar  2021      0.276\n",
       "\n",
       "[10371 rows x 4 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vdem = vdem.sort_values(by = ['year', 'country_code'], ascending = True)\n",
    "vdem"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "167810c8-d655-4692-84fd-5dc6b43f7e79",
   "metadata": {},
   "source": [
    "# 2 D"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fa0c7741-86e6-4af1-a9c7-2b2bb893ec46",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country Code</th>\n",
       "      <th>Table Name</th>\n",
       "      <th>Long Name</th>\n",
       "      <th>Currency Unit</th>\n",
       "      <th>Region</th>\n",
       "      <th>Income Group</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Islamic State of Afghanistan</td>\n",
       "      <td>Afghan afghani</td>\n",
       "      <td>South Asia</td>\n",
       "      <td>Low income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AGO</td>\n",
       "      <td>Angola</td>\n",
       "      <td>People's Republic of Angola</td>\n",
       "      <td>Angolan kwanza</td>\n",
       "      <td>Sub-Saharan Africa</td>\n",
       "      <td>Lower middle income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ALB</td>\n",
       "      <td>Albania</td>\n",
       "      <td>Republic of Albania</td>\n",
       "      <td>Albanian lek</td>\n",
       "      <td>Europe &amp; Central Asia</td>\n",
       "      <td>Upper middle income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AND</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>Principality of Andorra</td>\n",
       "      <td>Euro</td>\n",
       "      <td>Europe &amp; Central Asia</td>\n",
       "      <td>High income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ARB</td>\n",
       "      <td>Arab World</td>\n",
       "      <td>Arab World</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>234</th>\n",
       "      <td>WSM</td>\n",
       "      <td>Samoa</td>\n",
       "      <td>Samoa</td>\n",
       "      <td>Samoan tala</td>\n",
       "      <td>East Asia &amp; Pacific</td>\n",
       "      <td>Lower middle income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>235</th>\n",
       "      <td>YEM</td>\n",
       "      <td>Yemen, Rep.</td>\n",
       "      <td>Republic of Yemen</td>\n",
       "      <td>Yemeni rial</td>\n",
       "      <td>Middle East &amp; North Africa</td>\n",
       "      <td>Low income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>ZAF</td>\n",
       "      <td>South Africa</td>\n",
       "      <td>Republic of South Africa</td>\n",
       "      <td>South African rand</td>\n",
       "      <td>Sub-Saharan Africa</td>\n",
       "      <td>Upper middle income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>ZMB</td>\n",
       "      <td>Zambia</td>\n",
       "      <td>Republic of Zambia</td>\n",
       "      <td>New Zambian kwacha</td>\n",
       "      <td>Sub-Saharan Africa</td>\n",
       "      <td>Lower middle income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>Republic of Zimbabwe</td>\n",
       "      <td>Zimbabwean Dollar</td>\n",
       "      <td>Sub-Saharan Africa</td>\n",
       "      <td>Lower middle income</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>239 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Country Code    Table Name                     Long Name  \\\n",
       "0            AFG   Afghanistan  Islamic State of Afghanistan   \n",
       "1            AGO        Angola   People's Republic of Angola   \n",
       "2            ALB       Albania           Republic of Albania   \n",
       "3            AND       Andorra       Principality of Andorra   \n",
       "4            ARB    Arab World                    Arab World   \n",
       "..           ...           ...                           ...   \n",
       "234          WSM         Samoa                         Samoa   \n",
       "235          YEM   Yemen, Rep.             Republic of Yemen   \n",
       "236          ZAF  South Africa      Republic of South Africa   \n",
       "237          ZMB        Zambia            Republic of Zambia   \n",
       "238          ZWE      Zimbabwe          Republic of Zimbabwe   \n",
       "\n",
       "          Currency Unit                      Region         Income Group  \n",
       "0        Afghan afghani                  South Asia           Low income  \n",
       "1        Angolan kwanza          Sub-Saharan Africa  Lower middle income  \n",
       "2          Albanian lek       Europe & Central Asia  Upper middle income  \n",
       "3                  Euro       Europe & Central Asia          High income  \n",
       "4                   NaN                         NaN                  NaN  \n",
       "..                  ...                         ...                  ...  \n",
       "234         Samoan tala         East Asia & Pacific  Lower middle income  \n",
       "235         Yemeni rial  Middle East & North Africa           Low income  \n",
       "236  South African rand          Sub-Saharan Africa  Upper middle income  \n",
       "237  New Zambian kwacha          Sub-Saharan Africa  Lower middle income  \n",
       "238   Zimbabwean Dollar          Sub-Saharan Africa  Lower middle income  \n",
       "\n",
       "[239 rows x 6 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country = country[['Country Code', 'Table Name', 'Long Name', 'Currency Unit', 'Region','Income Group']]\n",
    "country"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c3616658-9bc5-47b1-bb80-6ba955fbfc46",
   "metadata": {},
   "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>country_code</th>\n",
       "      <th>country_name_wb</th>\n",
       "      <th>country_longname</th>\n",
       "      <th>currency_unit</th>\n",
       "      <th>region</th>\n",
       "      <th>income_group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Islamic State of Afghanistan</td>\n",
       "      <td>Afghan afghani</td>\n",
       "      <td>South Asia</td>\n",
       "      <td>Low income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AGO</td>\n",
       "      <td>Angola</td>\n",
       "      <td>People's Republic of Angola</td>\n",
       "      <td>Angolan kwanza</td>\n",
       "      <td>Sub-Saharan Africa</td>\n",
       "      <td>Lower middle income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ALB</td>\n",
       "      <td>Albania</td>\n",
       "      <td>Republic of Albania</td>\n",
       "      <td>Albanian lek</td>\n",
       "      <td>Europe &amp; Central Asia</td>\n",
       "      <td>Upper middle income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AND</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>Principality of Andorra</td>\n",
       "      <td>Euro</td>\n",
       "      <td>Europe &amp; Central Asia</td>\n",
       "      <td>High income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ARB</td>\n",
       "      <td>Arab World</td>\n",
       "      <td>Arab World</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>234</th>\n",
       "      <td>WSM</td>\n",
       "      <td>Samoa</td>\n",
       "      <td>Samoa</td>\n",
       "      <td>Samoan tala</td>\n",
       "      <td>East Asia &amp; Pacific</td>\n",
       "      <td>Lower middle income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>235</th>\n",
       "      <td>YEM</td>\n",
       "      <td>Yemen, Rep.</td>\n",
       "      <td>Republic of Yemen</td>\n",
       "      <td>Yemeni rial</td>\n",
       "      <td>Middle East &amp; North Africa</td>\n",
       "      <td>Low income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>ZAF</td>\n",
       "      <td>South Africa</td>\n",
       "      <td>Republic of South Africa</td>\n",
       "      <td>South African rand</td>\n",
       "      <td>Sub-Saharan Africa</td>\n",
       "      <td>Upper middle income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>ZMB</td>\n",
       "      <td>Zambia</td>\n",
       "      <td>Republic of Zambia</td>\n",
       "      <td>New Zambian kwacha</td>\n",
       "      <td>Sub-Saharan Africa</td>\n",
       "      <td>Lower middle income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>Republic of Zimbabwe</td>\n",
       "      <td>Zimbabwean Dollar</td>\n",
       "      <td>Sub-Saharan Africa</td>\n",
       "      <td>Lower middle income</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>239 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    country_code country_name_wb              country_longname  \\\n",
       "0            AFG     Afghanistan  Islamic State of Afghanistan   \n",
       "1            AGO          Angola   People's Republic of Angola   \n",
       "2            ALB         Albania           Republic of Albania   \n",
       "3            AND         Andorra       Principality of Andorra   \n",
       "4            ARB      Arab World                    Arab World   \n",
       "..           ...             ...                           ...   \n",
       "234          WSM           Samoa                         Samoa   \n",
       "235          YEM     Yemen, Rep.             Republic of Yemen   \n",
       "236          ZAF    South Africa      Republic of South Africa   \n",
       "237          ZMB          Zambia            Republic of Zambia   \n",
       "238          ZWE        Zimbabwe          Republic of Zimbabwe   \n",
       "\n",
       "          currency_unit                      region         income_group  \n",
       "0        Afghan afghani                  South Asia           Low income  \n",
       "1        Angolan kwanza          Sub-Saharan Africa  Lower middle income  \n",
       "2          Albanian lek       Europe & Central Asia  Upper middle income  \n",
       "3                  Euro       Europe & Central Asia          High income  \n",
       "4                   NaN                         NaN                  NaN  \n",
       "..                  ...                         ...                  ...  \n",
       "234         Samoan tala         East Asia & Pacific  Lower middle income  \n",
       "235         Yemeni rial  Middle East & North Africa           Low income  \n",
       "236  South African rand          Sub-Saharan Africa  Upper middle income  \n",
       "237  New Zambian kwacha          Sub-Saharan Africa  Lower middle income  \n",
       "238   Zimbabwean Dollar          Sub-Saharan Africa  Lower middle income  \n",
       "\n",
       "[239 rows x 6 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country = country.rename(columns={\"Country Code\": \"country_code\", \"Table Name\": \"country_name_wb\", \"Long Name\": 'country_longname', 'Currency Unit': 'currency_unit', 'Region': 'region', \"Income Group\": 'income_group'})\n",
    "country"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "80e1c488-5e24-4b43-b5ea-2604b3a96a7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "noncountries = [\"Arab World\", \"Central Europe and the Baltics\",\n",
    "\"Caribbean small states\",\n",
    "\"East Asia & Pacific (excluding high income)\",\n",
    "\"Early-demographic dividend\",\"East Asia & Pacific\",\n",
    "\"Europe & Central Asia (excluding high income)\",\n",
    "\"Europe & Central Asia\", \"Euro area\",\n",
    "\"European Union\",\"Fragile and conflict affected situations\",\n",
    "\"High income\",\n",
    "\"Heavily indebted poor countries (HIPC)\",\"IBRD only\",\n",
    "\"IDA & IBRD total\",\n",
    "\"IDA total\",\"IDA blend\",\"IDA only\",\n",
    "\"Latin America & Caribbean (excluding high income)\",\n",
    "\"Latin America & Caribbean\",\n",
    "\"Least developed countries: UN classification\",\n",
    "\"Low income\",\"Lower middle income\",\"Low & middle income\",\n",
    "\"Late-demographic dividend\",\"Middle East & North Africa\",\n",
    "\"Middle income\",\n",
    "\"Middle East & North Africa (excluding high income)\",\n",
    "\"North America\",\"OECD members\",\n",
    "\"Other small states\",\"Pre-demographic dividend\",\n",
    "\"Pacific island small states\",\n",
    "\"Post-demographic dividend\",\n",
    "\"Sub-Saharan Africa (excluding high income)\",\n",
    "\"Sub-Saharan Africa\",\n",
    "\"Small states\",\"East Asia & Pacific (IDA & IBRD)\",\n",
    "\"Europe & Central Asia (IDA & IBRD)\",\n",
    "\"Latin America & Caribbean (IDA & IBRD)\",\n",
    "\"Middle East & North Africa (IDA & IBRD)\",\"South Asia\",\n",
    "\"South Asia (IDA & IBRD)\",\n",
    "\"Sub-Saharan Africa (IDA & IBRD)\",\n",
    "\"Upper middle income\", \"World\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "611ea2ff-817a-4872-b47d-e469c7a28bc2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Arab World',\n",
       " 'Central Europe and the Baltics',\n",
       " 'Caribbean small states',\n",
       " 'East Asia & Pacific (excluding high income)',\n",
       " 'Early-demographic dividend',\n",
       " 'East Asia & Pacific',\n",
       " 'Europe & Central Asia (excluding high income)',\n",
       " 'Europe & Central Asia',\n",
       " 'Euro area',\n",
       " 'European Union',\n",
       " 'Fragile and conflict affected situations',\n",
       " 'High income',\n",
       " 'Heavily indebted poor countries (HIPC)',\n",
       " 'IBRD only',\n",
       " 'IDA & IBRD total',\n",
       " 'IDA total',\n",
       " 'IDA blend',\n",
       " 'IDA only',\n",
       " 'Latin America & Caribbean (excluding high income)',\n",
       " 'Latin America & Caribbean',\n",
       " 'Least developed countries: UN classification',\n",
       " 'Low income',\n",
       " 'Lower middle income',\n",
       " 'Low & middle income',\n",
       " 'Late-demographic dividend',\n",
       " 'Middle East & North Africa',\n",
       " 'Middle income',\n",
       " 'Middle East & North Africa (excluding high income)',\n",
       " 'North America',\n",
       " 'OECD members',\n",
       " 'Other small states',\n",
       " 'Pre-demographic dividend',\n",
       " 'Pacific island small states',\n",
       " 'Post-demographic dividend',\n",
       " 'Sub-Saharan Africa (excluding high income)',\n",
       " 'Sub-Saharan Africa',\n",
       " 'Small states',\n",
       " 'East Asia & Pacific (IDA & IBRD)',\n",
       " 'Europe & Central Asia (IDA & IBRD)',\n",
       " 'Latin America & Caribbean (IDA & IBRD)',\n",
       " 'Middle East & North Africa (IDA & IBRD)',\n",
       " 'South Asia',\n",
       " 'South Asia (IDA & IBRD)',\n",
       " 'Sub-Saharan Africa (IDA & IBRD)',\n",
       " 'Upper middle income',\n",
       " 'World']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "noncountries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e52b6abe-2bd8-4252-830e-4ff196f38ba6",
   "metadata": {},
   "outputs": [],
   "source": [
    "country = country.query('country_name_wb != @noncountries')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4352c6c6-a513-4264-a9a2-98612a259abe",
   "metadata": {},
   "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>country_code</th>\n",
       "      <th>country_name_wb</th>\n",
       "      <th>country_longname</th>\n",
       "      <th>currency_unit</th>\n",
       "      <th>region</th>\n",
       "      <th>income_group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Islamic State of Afghanistan</td>\n",
       "      <td>Afghan afghani</td>\n",
       "      <td>South Asia</td>\n",
       "      <td>Low income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AGO</td>\n",
       "      <td>Angola</td>\n",
       "      <td>People's Republic of Angola</td>\n",
       "      <td>Angolan kwanza</td>\n",
       "      <td>Sub-Saharan Africa</td>\n",
       "      <td>Lower middle income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ALB</td>\n",
       "      <td>Albania</td>\n",
       "      <td>Republic of Albania</td>\n",
       "      <td>Albanian lek</td>\n",
       "      <td>Europe &amp; Central Asia</td>\n",
       "      <td>Upper middle income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AND</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>Principality of Andorra</td>\n",
       "      <td>Euro</td>\n",
       "      <td>Europe &amp; Central Asia</td>\n",
       "      <td>High income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ARE</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>U.A.E. dirham</td>\n",
       "      <td>Middle East &amp; North Africa</td>\n",
       "      <td>High income</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>234</th>\n",
       "      <td>WSM</td>\n",
       "      <td>Samoa</td>\n",
       "      <td>Samoa</td>\n",
       "      <td>Samoan tala</td>\n",
       "      <td>East Asia &amp; Pacific</td>\n",
       "      <td>Lower middle income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>235</th>\n",
       "      <td>YEM</td>\n",
       "      <td>Yemen, Rep.</td>\n",
       "      <td>Republic of Yemen</td>\n",
       "      <td>Yemeni rial</td>\n",
       "      <td>Middle East &amp; North Africa</td>\n",
       "      <td>Low income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>ZAF</td>\n",
       "      <td>South Africa</td>\n",
       "      <td>Republic of South Africa</td>\n",
       "      <td>South African rand</td>\n",
       "      <td>Sub-Saharan Africa</td>\n",
       "      <td>Upper middle income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>ZMB</td>\n",
       "      <td>Zambia</td>\n",
       "      <td>Republic of Zambia</td>\n",
       "      <td>New Zambian kwacha</td>\n",
       "      <td>Sub-Saharan Africa</td>\n",
       "      <td>Lower middle income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>Republic of Zimbabwe</td>\n",
       "      <td>Zimbabwean Dollar</td>\n",
       "      <td>Sub-Saharan Africa</td>\n",
       "      <td>Lower middle income</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>193 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    country_code       country_name_wb              country_longname  \\\n",
       "0            AFG           Afghanistan  Islamic State of Afghanistan   \n",
       "1            AGO                Angola   People's Republic of Angola   \n",
       "2            ALB               Albania           Republic of Albania   \n",
       "3            AND               Andorra       Principality of Andorra   \n",
       "5            ARE  United Arab Emirates          United Arab Emirates   \n",
       "..           ...                   ...                           ...   \n",
       "234          WSM                 Samoa                         Samoa   \n",
       "235          YEM           Yemen, Rep.             Republic of Yemen   \n",
       "236          ZAF          South Africa      Republic of South Africa   \n",
       "237          ZMB                Zambia            Republic of Zambia   \n",
       "238          ZWE              Zimbabwe          Republic of Zimbabwe   \n",
       "\n",
       "          currency_unit                      region         income_group  \n",
       "0        Afghan afghani                  South Asia           Low income  \n",
       "1        Angolan kwanza          Sub-Saharan Africa  Lower middle income  \n",
       "2          Albanian lek       Europe & Central Asia  Upper middle income  \n",
       "3                  Euro       Europe & Central Asia          High income  \n",
       "5         U.A.E. dirham  Middle East & North Africa          High income  \n",
       "..                  ...                         ...                  ...  \n",
       "234         Samoan tala         East Asia & Pacific  Lower middle income  \n",
       "235         Yemeni rial  Middle East & North Africa           Low income  \n",
       "236  South African rand          Sub-Saharan Africa  Upper middle income  \n",
       "237  New Zambian kwacha          Sub-Saharan Africa  Lower middle income  \n",
       "238   Zimbabwean Dollar          Sub-Saharan Africa  Lower middle income  \n",
       "\n",
       "[193 rows x 6 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b5741e82-c8cf-4ff7-b771-17973eaac4f9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Country Name', 'Country Code', 'Indicator Name', 'Indicator Code',\n",
      "       '1960', '1961', '1962', '1963', '1964', '1965', '1966', '1967', '1968',\n",
      "       '1969', '1970', '1971', '1972', '1973', '1974', '1975', '1976', '1977',\n",
      "       '1978', '1979', '1980', '1981', '1982', '1983', '1984', '1985', '1986',\n",
      "       '1987', '1988', '1989', '1990', '1991', '1992', '1993', '1994', '1995',\n",
      "       '1996', '1997', '1998', '1999', '2000', '2001', '2002', '2003', '2004',\n",
      "       '2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013',\n",
      "       '2014', '2015', '2016', '2017', '2018', '2019', '2020', '2021', '2022',\n",
      "       'Unnamed: 67'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(wb.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7a13fade-9dd3-485a-9918-eef0f0bb2872",
   "metadata": {},
   "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>Country Name</th>\n",
       "      <th>Country Code</th>\n",
       "      <th>Indicator Name</th>\n",
       "      <th>Indicator Code</th>\n",
       "      <th>1960</th>\n",
       "      <th>1961</th>\n",
       "      <th>1962</th>\n",
       "      <th>1963</th>\n",
       "      <th>1964</th>\n",
       "      <th>1965</th>\n",
       "      <th>...</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "      <th>Unnamed: 67</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Arab World</td>\n",
       "      <td>ARB</td>\n",
       "      <td>Access to clean fuels and technologies for coo...</td>\n",
       "      <td>EG.CFT.ACCS.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>86.705717</td>\n",
       "      <td>86.942778</td>\n",
       "      <td>87.228705</td>\n",
       "      <td>87.390856</td>\n",
       "      <td>87.617862</td>\n",
       "      <td>87.798740</td>\n",
       "      <td>87.948264</td>\n",
       "      <td>88.092536</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Arab World</td>\n",
       "      <td>ARB</td>\n",
       "      <td>Access to electricity (% of population)</td>\n",
       "      <td>EG.ELC.ACCS.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>88.832276</td>\n",
       "      <td>89.053852</td>\n",
       "      <td>89.539016</td>\n",
       "      <td>90.662754</td>\n",
       "      <td>89.176939</td>\n",
       "      <td>90.352802</td>\n",
       "      <td>90.635050</td>\n",
       "      <td>90.845661</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Arab World</td>\n",
       "      <td>ARB</td>\n",
       "      <td>Adjusted savings: natural resources depletion ...</td>\n",
       "      <td>NY.ADJ.DRES.GN.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>10.263684</td>\n",
       "      <td>6.217421</td>\n",
       "      <td>5.190735</td>\n",
       "      <td>6.458100</td>\n",
       "      <td>8.451699</td>\n",
       "      <td>7.351742</td>\n",
       "      <td>4.347213</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Arab World</td>\n",
       "      <td>ARB</td>\n",
       "      <td>Adjusted savings: net forest depletion (% of GNI)</td>\n",
       "      <td>NY.ADJ.DFOR.GN.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.084113</td>\n",
       "      <td>0.098458</td>\n",
       "      <td>0.093562</td>\n",
       "      <td>0.095137</td>\n",
       "      <td>0.050799</td>\n",
       "      <td>0.061584</td>\n",
       "      <td>0.077949</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Arab World</td>\n",
       "      <td>ARB</td>\n",
       "      <td>Agricultural land (% of land area)</td>\n",
       "      <td>AG.LND.AGRI.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30.981414</td>\n",
       "      <td>30.982663</td>\n",
       "      <td>31.007054</td>\n",
       "      <td>31.018001</td>\n",
       "      <td>31.042466</td>\n",
       "      <td>...</td>\n",
       "      <td>39.834421</td>\n",
       "      <td>39.872575</td>\n",
       "      <td>39.937814</td>\n",
       "      <td>39.984452</td>\n",
       "      <td>39.969738</td>\n",
       "      <td>39.907031</td>\n",
       "      <td>39.973290</td>\n",
       "      <td>39.970742</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\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>16964</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>Terrestrial and marine protected areas (% of t...</td>\n",
       "      <td>ER.PTD.TOTL.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.214542</td>\n",
       "      <td>27.214585</td>\n",
       "      <td>27.214585</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16965</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>Tree Cover Loss (hectares)</td>\n",
       "      <td>AG.LND.FRLS.HA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16966</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>Unemployment, total (% of total labor force) (...</td>\n",
       "      <td>SL.UEM.TOTL.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.770000</td>\n",
       "      <td>5.282000</td>\n",
       "      <td>5.796000</td>\n",
       "      <td>6.279000</td>\n",
       "      <td>6.784000</td>\n",
       "      <td>7.370000</td>\n",
       "      <td>7.898000</td>\n",
       "      <td>8.067000</td>\n",
       "      <td>7.945000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16967</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>Unmet need for contraception (% of married wom...</td>\n",
       "      <td>SP.UWT.TFRT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>10.382129</td>\n",
       "      <td>10.400000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16968</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>Voice and Accountability: Estimate</td>\n",
       "      <td>VA.EST</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.256889</td>\n",
       "      <td>-1.166087</td>\n",
       "      <td>-1.178460</td>\n",
       "      <td>-1.195905</td>\n",
       "      <td>-1.136798</td>\n",
       "      <td>-1.163669</td>\n",
       "      <td>-1.113408</td>\n",
       "      <td>-1.135830</td>\n",
       "      <td>-1.102206</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16969 rows × 68 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Country Name Country Code  \\\n",
       "0       Arab World          ARB   \n",
       "1       Arab World          ARB   \n",
       "2       Arab World          ARB   \n",
       "3       Arab World          ARB   \n",
       "4       Arab World          ARB   \n",
       "...            ...          ...   \n",
       "16964     Zimbabwe          ZWE   \n",
       "16965     Zimbabwe          ZWE   \n",
       "16966     Zimbabwe          ZWE   \n",
       "16967     Zimbabwe          ZWE   \n",
       "16968     Zimbabwe          ZWE   \n",
       "\n",
       "                                          Indicator Name     Indicator Code  \\\n",
       "0      Access to clean fuels and technologies for coo...     EG.CFT.ACCS.ZS   \n",
       "1                Access to electricity (% of population)     EG.ELC.ACCS.ZS   \n",
       "2      Adjusted savings: natural resources depletion ...  NY.ADJ.DRES.GN.ZS   \n",
       "3      Adjusted savings: net forest depletion (% of GNI)  NY.ADJ.DFOR.GN.ZS   \n",
       "4                     Agricultural land (% of land area)     AG.LND.AGRI.ZS   \n",
       "...                                                  ...                ...   \n",
       "16964  Terrestrial and marine protected areas (% of t...     ER.PTD.TOTL.ZS   \n",
       "16965                         Tree Cover Loss (hectares)     AG.LND.FRLS.HA   \n",
       "16966  Unemployment, total (% of total labor force) (...     SL.UEM.TOTL.ZS   \n",
       "16967  Unmet need for contraception (% of married wom...        SP.UWT.TFRT   \n",
       "16968                 Voice and Accountability: Estimate             VA.EST   \n",
       "\n",
       "       1960       1961       1962       1963       1964       1965  ...  \\\n",
       "0       NaN        NaN        NaN        NaN        NaN        NaN  ...   \n",
       "1       NaN        NaN        NaN        NaN        NaN        NaN  ...   \n",
       "2       NaN        NaN        NaN        NaN        NaN        NaN  ...   \n",
       "3       NaN        NaN        NaN        NaN        NaN        NaN  ...   \n",
       "4       NaN  30.981414  30.982663  31.007054  31.018001  31.042466  ...   \n",
       "...     ...        ...        ...        ...        ...        ...  ...   \n",
       "16964   NaN        NaN        NaN        NaN        NaN        NaN  ...   \n",
       "16965   NaN        NaN        NaN        NaN        NaN        NaN  ...   \n",
       "16966   NaN        NaN        NaN        NaN        NaN        NaN  ...   \n",
       "16967   NaN        NaN        NaN        NaN        NaN        NaN  ...   \n",
       "16968   NaN        NaN        NaN        NaN        NaN        NaN  ...   \n",
       "\n",
       "            2014       2015       2016       2017       2018       2019  \\\n",
       "0      86.705717  86.942778  87.228705  87.390856  87.617862  87.798740   \n",
       "1      88.832276  89.053852  89.539016  90.662754  89.176939  90.352802   \n",
       "2      10.263684   6.217421   5.190735   6.458100   8.451699   7.351742   \n",
       "3       0.084113   0.098458   0.093562   0.095137   0.050799   0.061584   \n",
       "4      39.834421  39.872575  39.937814  39.984452  39.969738  39.907031   \n",
       "...          ...        ...        ...        ...        ...        ...   \n",
       "16964        NaN        NaN  27.214542  27.214585  27.214585  27.214747   \n",
       "16965        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "16966   4.770000   5.282000   5.796000   6.279000   6.784000   7.370000   \n",
       "16967  10.382129  10.400000        NaN        NaN        NaN        NaN   \n",
       "16968  -1.256889  -1.166087  -1.178460  -1.195905  -1.136798  -1.163669   \n",
       "\n",
       "            2020       2021       2022  Unnamed: 67  \n",
       "0      87.948264  88.092536        NaN          NaN  \n",
       "1      90.635050  90.845661        NaN          NaN  \n",
       "2       4.347213        NaN        NaN          NaN  \n",
       "3       0.077949        NaN        NaN          NaN  \n",
       "4      39.973290  39.970742        NaN          NaN  \n",
       "...          ...        ...        ...          ...  \n",
       "16964  27.214747  27.214747  27.214747          NaN  \n",
       "16965        NaN        NaN        NaN          NaN  \n",
       "16966   7.898000   8.067000   7.945000          NaN  \n",
       "16967        NaN        NaN        NaN          NaN  \n",
       "16968  -1.113408  -1.135830  -1.102206          NaN  \n",
       "\n",
       "[16969 rows x 68 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wb"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7edfcf2a-4b09-43bb-ace1-76f05f0d2c35",
   "metadata": {},
   "source": [
    "# 2 E"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "642f8303-3b35-4ba4-901e-51b276b4ad5e",
   "metadata": {},
   "outputs": [],
   "source": [
    "wb = wb.drop(columns=['Indicator Name', 'Unnamed: 67'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7c3a39d5-d5bc-49be-b660-f88a9e156c5c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Country Name', 'Country Code', 'Indicator Code', '1960', '1961',\n",
       "       '1962', '1963', '1964', '1965', '1966', '1967', '1968', '1969', '1970',\n",
       "       '1971', '1972', '1973', '1974', '1975', '1976', '1977', '1978', '1979',\n",
       "       '1980', '1981', '1982', '1983', '1984', '1985', '1986', '1987', '1988',\n",
       "       '1989', '1990', '1991', '1992', '1993', '1994', '1995', '1996', '1997',\n",
       "       '1998', '1999', '2000', '2001', '2002', '2003', '2004', '2005', '2006',\n",
       "       '2007', '2008', '2009', '2010', '2011', '2012', '2013', '2014', '2015',\n",
       "       '2016', '2017', '2018', '2019', '2020', '2021', '2022'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wb.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0d864fe2-dfb5-41be-8f56-f8c5d45917dd",
   "metadata": {},
   "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>country_name_wb</th>\n",
       "      <th>country_code</th>\n",
       "      <th>feature</th>\n",
       "      <th>1960</th>\n",
       "      <th>1961</th>\n",
       "      <th>1962</th>\n",
       "      <th>1963</th>\n",
       "      <th>1964</th>\n",
       "      <th>1965</th>\n",
       "      <th>1966</th>\n",
       "      <th>...</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Arab World</td>\n",
       "      <td>ARB</td>\n",
       "      <td>EG.CFT.ACCS.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>86.406487</td>\n",
       "      <td>86.705717</td>\n",
       "      <td>86.942778</td>\n",
       "      <td>87.228705</td>\n",
       "      <td>87.390856</td>\n",
       "      <td>87.617862</td>\n",
       "      <td>87.798740</td>\n",
       "      <td>87.948264</td>\n",
       "      <td>88.092536</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Arab World</td>\n",
       "      <td>ARB</td>\n",
       "      <td>EG.ELC.ACCS.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>89.340705</td>\n",
       "      <td>88.832276</td>\n",
       "      <td>89.053852</td>\n",
       "      <td>89.539016</td>\n",
       "      <td>90.662754</td>\n",
       "      <td>89.176939</td>\n",
       "      <td>90.352802</td>\n",
       "      <td>90.635050</td>\n",
       "      <td>90.845661</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Arab World</td>\n",
       "      <td>ARB</td>\n",
       "      <td>NY.ADJ.DRES.GN.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>11.598544</td>\n",
       "      <td>10.263684</td>\n",
       "      <td>6.217421</td>\n",
       "      <td>5.190735</td>\n",
       "      <td>6.458100</td>\n",
       "      <td>8.451699</td>\n",
       "      <td>7.351742</td>\n",
       "      <td>4.347213</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Arab World</td>\n",
       "      <td>ARB</td>\n",
       "      <td>NY.ADJ.DFOR.GN.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.062081</td>\n",
       "      <td>0.084113</td>\n",
       "      <td>0.098458</td>\n",
       "      <td>0.093562</td>\n",
       "      <td>0.095137</td>\n",
       "      <td>0.050799</td>\n",
       "      <td>0.061584</td>\n",
       "      <td>0.077949</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Arab World</td>\n",
       "      <td>ARB</td>\n",
       "      <td>AG.LND.AGRI.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30.981414</td>\n",
       "      <td>30.982663</td>\n",
       "      <td>31.007054</td>\n",
       "      <td>31.018001</td>\n",
       "      <td>31.042466</td>\n",
       "      <td>31.0504</td>\n",
       "      <td>...</td>\n",
       "      <td>39.838650</td>\n",
       "      <td>39.834421</td>\n",
       "      <td>39.872575</td>\n",
       "      <td>39.937814</td>\n",
       "      <td>39.984452</td>\n",
       "      <td>39.969738</td>\n",
       "      <td>39.907031</td>\n",
       "      <td>39.973290</td>\n",
       "      <td>39.970742</td>\n",
       "      <td>NaN</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\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>16964</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>ER.PTD.TOTL.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.214542</td>\n",
       "      <td>27.214585</td>\n",
       "      <td>27.214585</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>27.214747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16965</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>AG.LND.FRLS.HA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16966</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>SL.UEM.TOTL.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.994000</td>\n",
       "      <td>4.770000</td>\n",
       "      <td>5.282000</td>\n",
       "      <td>5.796000</td>\n",
       "      <td>6.279000</td>\n",
       "      <td>6.784000</td>\n",
       "      <td>7.370000</td>\n",
       "      <td>7.898000</td>\n",
       "      <td>8.067000</td>\n",
       "      <td>7.945000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16967</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>SP.UWT.TFRT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.382129</td>\n",
       "      <td>10.400000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16968</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>VA.EST</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.386220</td>\n",
       "      <td>-1.256889</td>\n",
       "      <td>-1.166087</td>\n",
       "      <td>-1.178460</td>\n",
       "      <td>-1.195905</td>\n",
       "      <td>-1.136798</td>\n",
       "      <td>-1.163669</td>\n",
       "      <td>-1.113408</td>\n",
       "      <td>-1.135830</td>\n",
       "      <td>-1.102206</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16969 rows × 66 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country_name_wb country_code            feature  1960       1961  \\\n",
       "0          Arab World          ARB     EG.CFT.ACCS.ZS   NaN        NaN   \n",
       "1          Arab World          ARB     EG.ELC.ACCS.ZS   NaN        NaN   \n",
       "2          Arab World          ARB  NY.ADJ.DRES.GN.ZS   NaN        NaN   \n",
       "3          Arab World          ARB  NY.ADJ.DFOR.GN.ZS   NaN        NaN   \n",
       "4          Arab World          ARB     AG.LND.AGRI.ZS   NaN  30.981414   \n",
       "...               ...          ...                ...   ...        ...   \n",
       "16964        Zimbabwe          ZWE     ER.PTD.TOTL.ZS   NaN        NaN   \n",
       "16965        Zimbabwe          ZWE     AG.LND.FRLS.HA   NaN        NaN   \n",
       "16966        Zimbabwe          ZWE     SL.UEM.TOTL.ZS   NaN        NaN   \n",
       "16967        Zimbabwe          ZWE        SP.UWT.TFRT   NaN        NaN   \n",
       "16968        Zimbabwe          ZWE             VA.EST   NaN        NaN   \n",
       "\n",
       "            1962       1963       1964       1965     1966  ...       2013  \\\n",
       "0            NaN        NaN        NaN        NaN      NaN  ...  86.406487   \n",
       "1            NaN        NaN        NaN        NaN      NaN  ...  89.340705   \n",
       "2            NaN        NaN        NaN        NaN      NaN  ...  11.598544   \n",
       "3            NaN        NaN        NaN        NaN      NaN  ...   0.062081   \n",
       "4      30.982663  31.007054  31.018001  31.042466  31.0504  ...  39.838650   \n",
       "...          ...        ...        ...        ...      ...  ...        ...   \n",
       "16964        NaN        NaN        NaN        NaN      NaN  ...        NaN   \n",
       "16965        NaN        NaN        NaN        NaN      NaN  ...        NaN   \n",
       "16966        NaN        NaN        NaN        NaN      NaN  ...   4.994000   \n",
       "16967        NaN        NaN        NaN        NaN      NaN  ...        NaN   \n",
       "16968        NaN        NaN        NaN        NaN      NaN  ...  -1.386220   \n",
       "\n",
       "            2014       2015       2016       2017       2018       2019  \\\n",
       "0      86.705717  86.942778  87.228705  87.390856  87.617862  87.798740   \n",
       "1      88.832276  89.053852  89.539016  90.662754  89.176939  90.352802   \n",
       "2      10.263684   6.217421   5.190735   6.458100   8.451699   7.351742   \n",
       "3       0.084113   0.098458   0.093562   0.095137   0.050799   0.061584   \n",
       "4      39.834421  39.872575  39.937814  39.984452  39.969738  39.907031   \n",
       "...          ...        ...        ...        ...        ...        ...   \n",
       "16964        NaN        NaN  27.214542  27.214585  27.214585  27.214747   \n",
       "16965        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "16966   4.770000   5.282000   5.796000   6.279000   6.784000   7.370000   \n",
       "16967  10.382129  10.400000        NaN        NaN        NaN        NaN   \n",
       "16968  -1.256889  -1.166087  -1.178460  -1.195905  -1.136798  -1.163669   \n",
       "\n",
       "            2020       2021       2022  \n",
       "0      87.948264  88.092536        NaN  \n",
       "1      90.635050  90.845661        NaN  \n",
       "2       4.347213        NaN        NaN  \n",
       "3       0.077949        NaN        NaN  \n",
       "4      39.973290  39.970742        NaN  \n",
       "...          ...        ...        ...  \n",
       "16964  27.214747  27.214747  27.214747  \n",
       "16965        NaN        NaN        NaN  \n",
       "16966   7.898000   8.067000   7.945000  \n",
       "16967        NaN        NaN        NaN  \n",
       "16968  -1.113408  -1.135830  -1.102206  \n",
       "\n",
       "[16969 rows x 66 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wb = wb.rename(columns={\"Country Code\": \"country_code\", \"Country Name\": \"country_name_wb\", \"Indicator Code\": 'feature'})\n",
    "wb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "283fe757-3971-4502-bb62-d4d5b1c2cf6b",
   "metadata": {},
   "outputs": [],
   "source": [
    "noncountries.remove('World')\n",
    "wb = wb.query('country_name_wb != @noncountries')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "83a6f047-5a04-425d-8e10-fb0adc6c34b4",
   "metadata": {},
   "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",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country_name_wb</th>\n",
       "      <th>country_code</th>\n",
       "      <th>feature</th>\n",
       "      <th>1960</th>\n",
       "      <th>1961</th>\n",
       "      <th>1962</th>\n",
       "      <th>1963</th>\n",
       "      <th>1964</th>\n",
       "      <th>1965</th>\n",
       "      <th>1966</th>\n",
       "      <th>...</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3195</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>EG.CFT.ACCS.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>61.095607</td>\n",
       "      <td>62.372600</td>\n",
       "      <td>63.662869</td>\n",
       "      <td>65.005668</td>\n",
       "      <td>66.321819</td>\n",
       "      <td>67.696517</td>\n",
       "      <td>68.921601</td>\n",
       "      <td>70.184805</td>\n",
       "      <td>71.331487</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3196</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>EG.ELC.ACCS.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>85.817366</td>\n",
       "      <td>86.306969</td>\n",
       "      <td>87.025241</td>\n",
       "      <td>88.192385</td>\n",
       "      <td>89.019548</td>\n",
       "      <td>89.893733</td>\n",
       "      <td>90.194716</td>\n",
       "      <td>90.483629</td>\n",
       "      <td>91.413941</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3197</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>NY.ADJ.DRES.GN.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.778802</td>\n",
       "      <td>1.520162</td>\n",
       "      <td>0.820341</td>\n",
       "      <td>0.717655</td>\n",
       "      <td>0.919547</td>\n",
       "      <td>1.246028</td>\n",
       "      <td>1.087624</td>\n",
       "      <td>0.790953</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3198</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>NY.ADJ.DFOR.GN.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.061422</td>\n",
       "      <td>0.069023</td>\n",
       "      <td>0.071087</td>\n",
       "      <td>0.073026</td>\n",
       "      <td>0.069027</td>\n",
       "      <td>0.048838</td>\n",
       "      <td>0.049834</td>\n",
       "      <td>0.058687</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3199</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>AG.LND.AGRI.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.879317</td>\n",
       "      <td>35.95247</td>\n",
       "      <td>36.035383</td>\n",
       "      <td>36.117043</td>\n",
       "      <td>36.213941</td>\n",
       "      <td>36.294321</td>\n",
       "      <td>...</td>\n",
       "      <td>36.790232</td>\n",
       "      <td>36.789051</td>\n",
       "      <td>36.620496</td>\n",
       "      <td>36.587014</td>\n",
       "      <td>36.834001</td>\n",
       "      <td>36.738458</td>\n",
       "      <td>36.762648</td>\n",
       "      <td>36.730920</td>\n",
       "      <td>36.841665</td>\n",
       "      <td>NaN</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\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>16964</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>ER.PTD.TOTL.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.214542</td>\n",
       "      <td>27.214585</td>\n",
       "      <td>27.214585</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>27.214747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16965</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>AG.LND.FRLS.HA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16966</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>SL.UEM.TOTL.ZS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.994000</td>\n",
       "      <td>4.770000</td>\n",
       "      <td>5.282000</td>\n",
       "      <td>5.796000</td>\n",
       "      <td>6.279000</td>\n",
       "      <td>6.784000</td>\n",
       "      <td>7.370000</td>\n",
       "      <td>7.898000</td>\n",
       "      <td>8.067000</td>\n",
       "      <td>7.945000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16967</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>SP.UWT.TFRT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.382129</td>\n",
       "      <td>10.400000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16968</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>VA.EST</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.386220</td>\n",
       "      <td>-1.256889</td>\n",
       "      <td>-1.166087</td>\n",
       "      <td>-1.178460</td>\n",
       "      <td>-1.195905</td>\n",
       "      <td>-1.136798</td>\n",
       "      <td>-1.163669</td>\n",
       "      <td>-1.113408</td>\n",
       "      <td>-1.135830</td>\n",
       "      <td>-1.102206</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13774 rows × 66 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country_name_wb country_code            feature  1960       1961  \\\n",
       "3195            World          WLD     EG.CFT.ACCS.ZS   NaN        NaN   \n",
       "3196            World          WLD     EG.ELC.ACCS.ZS   NaN        NaN   \n",
       "3197            World          WLD  NY.ADJ.DRES.GN.ZS   NaN        NaN   \n",
       "3198            World          WLD  NY.ADJ.DFOR.GN.ZS   NaN        NaN   \n",
       "3199            World          WLD     AG.LND.AGRI.ZS   NaN  35.879317   \n",
       "...               ...          ...                ...   ...        ...   \n",
       "16964        Zimbabwe          ZWE     ER.PTD.TOTL.ZS   NaN        NaN   \n",
       "16965        Zimbabwe          ZWE     AG.LND.FRLS.HA   NaN        NaN   \n",
       "16966        Zimbabwe          ZWE     SL.UEM.TOTL.ZS   NaN        NaN   \n",
       "16967        Zimbabwe          ZWE        SP.UWT.TFRT   NaN        NaN   \n",
       "16968        Zimbabwe          ZWE             VA.EST   NaN        NaN   \n",
       "\n",
       "           1962       1963       1964       1965       1966  ...       2013  \\\n",
       "3195        NaN        NaN        NaN        NaN        NaN  ...  61.095607   \n",
       "3196        NaN        NaN        NaN        NaN        NaN  ...  85.817366   \n",
       "3197        NaN        NaN        NaN        NaN        NaN  ...   1.778802   \n",
       "3198        NaN        NaN        NaN        NaN        NaN  ...   0.061422   \n",
       "3199   35.95247  36.035383  36.117043  36.213941  36.294321  ...  36.790232   \n",
       "...         ...        ...        ...        ...        ...  ...        ...   \n",
       "16964       NaN        NaN        NaN        NaN        NaN  ...        NaN   \n",
       "16965       NaN        NaN        NaN        NaN        NaN  ...        NaN   \n",
       "16966       NaN        NaN        NaN        NaN        NaN  ...   4.994000   \n",
       "16967       NaN        NaN        NaN        NaN        NaN  ...        NaN   \n",
       "16968       NaN        NaN        NaN        NaN        NaN  ...  -1.386220   \n",
       "\n",
       "            2014       2015       2016       2017       2018       2019  \\\n",
       "3195   62.372600  63.662869  65.005668  66.321819  67.696517  68.921601   \n",
       "3196   86.306969  87.025241  88.192385  89.019548  89.893733  90.194716   \n",
       "3197    1.520162   0.820341   0.717655   0.919547   1.246028   1.087624   \n",
       "3198    0.069023   0.071087   0.073026   0.069027   0.048838   0.049834   \n",
       "3199   36.789051  36.620496  36.587014  36.834001  36.738458  36.762648   \n",
       "...          ...        ...        ...        ...        ...        ...   \n",
       "16964        NaN        NaN  27.214542  27.214585  27.214585  27.214747   \n",
       "16965        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "16966   4.770000   5.282000   5.796000   6.279000   6.784000   7.370000   \n",
       "16967  10.382129  10.400000        NaN        NaN        NaN        NaN   \n",
       "16968  -1.256889  -1.166087  -1.178460  -1.195905  -1.136798  -1.163669   \n",
       "\n",
       "            2020       2021       2022  \n",
       "3195   70.184805  71.331487        NaN  \n",
       "3196   90.483629  91.413941        NaN  \n",
       "3197    0.790953        NaN        NaN  \n",
       "3198    0.058687        NaN        NaN  \n",
       "3199   36.730920  36.841665        NaN  \n",
       "...          ...        ...        ...  \n",
       "16964  27.214747  27.214747  27.214747  \n",
       "16965        NaN        NaN        NaN  \n",
       "16966   7.898000   8.067000   7.945000  \n",
       "16967        NaN        NaN        NaN  \n",
       "16968  -1.113408  -1.135830  -1.102206  \n",
       "\n",
       "[13774 rows x 66 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b8ceba0a-a711-4e19-a064-8a4aacb74e0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "replace_map = {\n",
    "\"AG.LND.AGRI.ZS\": \"agricultural_land\",\n",
    "\"AG.LND.FRST.ZS\": \"forest_area\",\n",
    "\"AG.PRD.FOOD.XD\": \"food_production_index\",\n",
    "\"CC.EST\": \"control_of_corruption\",\n",
    "\"EG.CFT.ACCS.ZS\": \"access_to_clean_fuels_and_technologies_for_cooking\",\n",
    "\"EG.EGY.PRIM.PP.KD\": \"energy_intensity_level_of_primary_energy\",\n",
    "\"EG.ELC.ACCS.ZS\": \"access_to_electricity\",\n",
    "\"EG.ELC.COAL.ZS\": \"electricity_production_from_coal_sources\",\n",
    "\"EG.ELC.RNEW.ZS\": \"renewable_electricity_output\",\n",
    "\"EG.FEC.RNEW.ZS\": \"renewable_energy_consumption\",\n",
    "\"EG.IMP.CONS.ZS\": \"energy_imports\",\n",
    "\"EG.USE.COMM.FO.ZS\": \"fossil_fuel_energy_consumption\",\n",
    "\"EG.USE.PCAP.KG.OE\": \"energy_use\",\n",
    "\"EN.ATM.CO2E.PC\": \"co2_emissions\",\n",
    "\"EN.ATM.METH.PC\": \"methane_emissions\",\n",
    "\"EN.ATM.NOXE.PC\": \"nitrous_oxide_emissions\",\n",
    "\"EN.ATM.PM25.MC.M3\": \"pm2_5_air_pollution\",\n",
    "\"EN.CLC.CDDY.XD\": \"cooling_degree_days\",\n",
    "\"EN.CLC.GHGR.MT.CE\": \"ghg_net_emissions\",\n",
    "\"EN.CLC.HEAT.XD\": \"heat_index_35\",\n",
    "\"EN.CLC.MDAT.ZS\": \"droughts\",\n",
    "\"EN.CLC.PRCP.XD\": \"maximum_5-day_rainfall\",\n",
    "\"EN.CLC.SPEI.XD\": \"mean_drought_index\",\n",
    "\"EN.MAM.THRD.NO\":\"mammal_species\",\n",
    "\"EN.POP.DNST\":\"population_density\",\n",
    "\"ER.H2O.FWTL.ZS\":\"annual_freshwater_withdrawals\",\n",
    "\"ER.PTD.TOTL.ZS\":\"terrestrial_and_marine_protected_areas\",\n",
    "\"GB.XPD.RSDV.GD.ZS\":\"research_and_development_expenditure\",\n",
    "\"GE.EST\":\"government_effectiveness\",\n",
    "\"IC.BUS.EASE.XQ\":\"ease_of_doing_business_rank\",\n",
    "\"IC.LGL.CRED.XQ\":\"strength_of_legal_rights_index\",\n",
    "\"IP.JRN.ARTC.SC\":\"scientific_and_technical_journal_articles\",\n",
    "\"IP.PAT.RESD\":\"patent_applications\",\n",
    "\"IT.NET.USER.ZS\":\"individuals_using_the_internet\",\n",
    "\"NV.AGR.TOTL.ZS\":\"agriculture\",\n",
    "\"NY.ADJ.DFOR.GN.ZS\":\"net_forest_depletion\",\n",
    "\"NY.ADJ.DRES.GN.ZS\":\"natural_resources_depletion\",\n",
    "\"NY.GDP.MKTP.KD.ZG\":\"gdp_growth\",\n",
    "\"PV.EST\":\"political_stability_and_absence_of_violence\",\n",
    "\"RL.EST\":\"rule_of_law\",\n",
    "\"RQ.EST\":\"regulatory_quality\",\n",
    "\"SE.ADT.LITR.ZS\":\"literacy_rate\",\n",
    "\"SE.ENR.PRSC.FM.ZS\":\"gross_school_enrollment\",\n",
    "\"SE.PRM.ENRR\":\"primary_school_enrollment\",\n",
    "\"SE.XPD.TOTL.GB.ZS\":\"government_expenditure_on_education\",\n",
    "\"SG.GEN.PARL.ZS\":\"proportion_of_seats_held_by_women_in_national_parliament\",\n",
    "\"SH.DTH.COMM.ZS\":\"cause_of_death\",\n",
    "\"SH.DYN.MORT\":\"mortality_rate\",\n",
    "\"SH.H2O.SMDW.ZS\":\"people_using_safely_managed_drinking_water_services\",\n",
    "\"SH.MED.BEDS.ZS\":\"hospital_beds\",\n",
    "\"SH.STA.OWAD.ZS\":\"prevalence_of_overweight\",\n",
    "\"SH.STA.SMSS.ZS\":\"people_using_safely_managed_sanitation_services\",\n",
    "\"SI.DST.FRST.20\":\"income_share_held_by_lowest_20pct\",\n",
    "\"SI.POV.GINI\":\"gini_index\",\n",
    "\"SI.POV.NAHC\":\"poverty_headcount_ratio_at_national_poverty_lines\",\n",
    "\"SI.SPR.PCAP.ZG\":\"annualized_average_growth_rate_in_per_capita_real_survey\",\n",
    "\"SL.TLF.0714.ZS\":\"children_in_employment\",\n",
    "\"SL.TLF.ACTI.ZS\":\"labor_force_participation_rate\",\n",
    "\"SL.TLF.CACT.FM.ZS\":\"ratio_of_female_to_male_labor_force_participation_rate\",\n",
    "\"SL.UEM.TOTL.ZS\":\"unemployment\",\n",
    "\"SM.POP.NETM\":\"net_migration\",\n",
    "\"SN.ITK.DEFC.ZS\":\"prevalence_of_undernourishment\",\n",
    "\"SP.DYN.LE00.IN\":\"life_expectancy_at_birth\",\n",
    "\"SP.DYN.TFRT.IN\":\"fertility_rate\",\n",
    "\"SP.POP.65UP.TO.ZS\":\"population_ages_65_and_above\",\n",
    "\"SP.UWT.TFRT\":\"unmet_need_for_contraception\",\n",
    "\"VA.EST\":\"voice_and_accountability\",\n",
    "\"EN.CLC.CSTP.ZS\":\"coastal_protection\",\n",
    "\"SD.ESR.PERF.XQ\":\"economic_and_social_rights_performance_score\",\n",
    "\"EN.CLC.HDDY.XD\":\"heating_degree_days\",\n",
    "\"EN.LND.LTMP.DC\":\"land_surface_temperature\",\n",
    "\"ER.H2O.FWST.ZS\":\"freshwater_withdrawal\",\n",
    "\"EN.H2O.BDYS.ZS\":\"water_quality\",\n",
    "\"AG.LND.FRLS.HA\":\"tree_cover_loss\"\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a9a12172-a95b-4102-a672-aff625eecbd6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'AG.LND.AGRI.ZS': 'agricultural_land',\n",
       " 'AG.LND.FRST.ZS': 'forest_area',\n",
       " 'AG.PRD.FOOD.XD': 'food_production_index',\n",
       " 'CC.EST': 'control_of_corruption',\n",
       " 'EG.CFT.ACCS.ZS': 'access_to_clean_fuels_and_technologies_for_cooking',\n",
       " 'EG.EGY.PRIM.PP.KD': 'energy_intensity_level_of_primary_energy',\n",
       " 'EG.ELC.ACCS.ZS': 'access_to_electricity',\n",
       " 'EG.ELC.COAL.ZS': 'electricity_production_from_coal_sources',\n",
       " 'EG.ELC.RNEW.ZS': 'renewable_electricity_output',\n",
       " 'EG.FEC.RNEW.ZS': 'renewable_energy_consumption',\n",
       " 'EG.IMP.CONS.ZS': 'energy_imports',\n",
       " 'EG.USE.COMM.FO.ZS': 'fossil_fuel_energy_consumption',\n",
       " 'EG.USE.PCAP.KG.OE': 'energy_use',\n",
       " 'EN.ATM.CO2E.PC': 'co2_emissions',\n",
       " 'EN.ATM.METH.PC': 'methane_emissions',\n",
       " 'EN.ATM.NOXE.PC': 'nitrous_oxide_emissions',\n",
       " 'EN.ATM.PM25.MC.M3': 'pm2_5_air_pollution',\n",
       " 'EN.CLC.CDDY.XD': 'cooling_degree_days',\n",
       " 'EN.CLC.GHGR.MT.CE': 'ghg_net_emissions',\n",
       " 'EN.CLC.HEAT.XD': 'heat_index_35',\n",
       " 'EN.CLC.MDAT.ZS': 'droughts',\n",
       " 'EN.CLC.PRCP.XD': 'maximum_5-day_rainfall',\n",
       " 'EN.CLC.SPEI.XD': 'mean_drought_index',\n",
       " 'EN.MAM.THRD.NO': 'mammal_species',\n",
       " 'EN.POP.DNST': 'population_density',\n",
       " 'ER.H2O.FWTL.ZS': 'annual_freshwater_withdrawals',\n",
       " 'ER.PTD.TOTL.ZS': 'terrestrial_and_marine_protected_areas',\n",
       " 'GB.XPD.RSDV.GD.ZS': 'research_and_development_expenditure',\n",
       " 'GE.EST': 'government_effectiveness',\n",
       " 'IC.BUS.EASE.XQ': 'ease_of_doing_business_rank',\n",
       " 'IC.LGL.CRED.XQ': 'strength_of_legal_rights_index',\n",
       " 'IP.JRN.ARTC.SC': 'scientific_and_technical_journal_articles',\n",
       " 'IP.PAT.RESD': 'patent_applications',\n",
       " 'IT.NET.USER.ZS': 'individuals_using_the_internet',\n",
       " 'NV.AGR.TOTL.ZS': 'agriculture',\n",
       " 'NY.ADJ.DFOR.GN.ZS': 'net_forest_depletion',\n",
       " 'NY.ADJ.DRES.GN.ZS': 'natural_resources_depletion',\n",
       " 'NY.GDP.MKTP.KD.ZG': 'gdp_growth',\n",
       " 'PV.EST': 'political_stability_and_absence_of_violence',\n",
       " 'RL.EST': 'rule_of_law',\n",
       " 'RQ.EST': 'regulatory_quality',\n",
       " 'SE.ADT.LITR.ZS': 'literacy_rate',\n",
       " 'SE.ENR.PRSC.FM.ZS': 'gross_school_enrollment',\n",
       " 'SE.PRM.ENRR': 'primary_school_enrollment',\n",
       " 'SE.XPD.TOTL.GB.ZS': 'government_expenditure_on_education',\n",
       " 'SG.GEN.PARL.ZS': 'proportion_of_seats_held_by_women_in_national_parliament',\n",
       " 'SH.DTH.COMM.ZS': 'cause_of_death',\n",
       " 'SH.DYN.MORT': 'mortality_rate',\n",
       " 'SH.H2O.SMDW.ZS': 'people_using_safely_managed_drinking_water_services',\n",
       " 'SH.MED.BEDS.ZS': 'hospital_beds',\n",
       " 'SH.STA.OWAD.ZS': 'prevalence_of_overweight',\n",
       " 'SH.STA.SMSS.ZS': 'people_using_safely_managed_sanitation_services',\n",
       " 'SI.DST.FRST.20': 'income_share_held_by_lowest_20pct',\n",
       " 'SI.POV.GINI': 'gini_index',\n",
       " 'SI.POV.NAHC': 'poverty_headcount_ratio_at_national_poverty_lines',\n",
       " 'SI.SPR.PCAP.ZG': 'annualized_average_growth_rate_in_per_capita_real_survey',\n",
       " 'SL.TLF.0714.ZS': 'children_in_employment',\n",
       " 'SL.TLF.ACTI.ZS': 'labor_force_participation_rate',\n",
       " 'SL.TLF.CACT.FM.ZS': 'ratio_of_female_to_male_labor_force_participation_rate',\n",
       " 'SL.UEM.TOTL.ZS': 'unemployment',\n",
       " 'SM.POP.NETM': 'net_migration',\n",
       " 'SN.ITK.DEFC.ZS': 'prevalence_of_undernourishment',\n",
       " 'SP.DYN.LE00.IN': 'life_expectancy_at_birth',\n",
       " 'SP.DYN.TFRT.IN': 'fertility_rate',\n",
       " 'SP.POP.65UP.TO.ZS': 'population_ages_65_and_above',\n",
       " 'SP.UWT.TFRT': 'unmet_need_for_contraception',\n",
       " 'VA.EST': 'voice_and_accountability',\n",
       " 'EN.CLC.CSTP.ZS': 'coastal_protection',\n",
       " 'SD.ESR.PERF.XQ': 'economic_and_social_rights_performance_score',\n",
       " 'EN.CLC.HDDY.XD': 'heating_degree_days',\n",
       " 'EN.LND.LTMP.DC': 'land_surface_temperature',\n",
       " 'ER.H2O.FWST.ZS': 'freshwater_withdrawal',\n",
       " 'EN.H2O.BDYS.ZS': 'water_quality',\n",
       " 'AG.LND.FRLS.HA': 'tree_cover_loss'}"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "replace_map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "48356ea9-c609-44b8-8223-082b79cc2c7c",
   "metadata": {},
   "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country_name_wb</th>\n",
       "      <th>country_code</th>\n",
       "      <th>feature</th>\n",
       "      <th>1960</th>\n",
       "      <th>1961</th>\n",
       "      <th>1962</th>\n",
       "      <th>1963</th>\n",
       "      <th>1964</th>\n",
       "      <th>1965</th>\n",
       "      <th>1966</th>\n",
       "      <th>...</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3195</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>access_to_clean_fuels_and_technologies_for_coo...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>61.095607</td>\n",
       "      <td>62.372600</td>\n",
       "      <td>63.662869</td>\n",
       "      <td>65.005668</td>\n",
       "      <td>66.321819</td>\n",
       "      <td>67.696517</td>\n",
       "      <td>68.921601</td>\n",
       "      <td>70.184805</td>\n",
       "      <td>71.331487</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3196</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>access_to_electricity</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>85.817366</td>\n",
       "      <td>86.306969</td>\n",
       "      <td>87.025241</td>\n",
       "      <td>88.192385</td>\n",
       "      <td>89.019548</td>\n",
       "      <td>89.893733</td>\n",
       "      <td>90.194716</td>\n",
       "      <td>90.483629</td>\n",
       "      <td>91.413941</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3197</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>natural_resources_depletion</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.778802</td>\n",
       "      <td>1.520162</td>\n",
       "      <td>0.820341</td>\n",
       "      <td>0.717655</td>\n",
       "      <td>0.919547</td>\n",
       "      <td>1.246028</td>\n",
       "      <td>1.087624</td>\n",
       "      <td>0.790953</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3198</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>net_forest_depletion</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.061422</td>\n",
       "      <td>0.069023</td>\n",
       "      <td>0.071087</td>\n",
       "      <td>0.073026</td>\n",
       "      <td>0.069027</td>\n",
       "      <td>0.048838</td>\n",
       "      <td>0.049834</td>\n",
       "      <td>0.058687</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3199</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>agricultural_land</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.879317</td>\n",
       "      <td>35.95247</td>\n",
       "      <td>36.035383</td>\n",
       "      <td>36.117043</td>\n",
       "      <td>36.213941</td>\n",
       "      <td>36.294321</td>\n",
       "      <td>...</td>\n",
       "      <td>36.790232</td>\n",
       "      <td>36.789051</td>\n",
       "      <td>36.620496</td>\n",
       "      <td>36.587014</td>\n",
       "      <td>36.834001</td>\n",
       "      <td>36.738458</td>\n",
       "      <td>36.762648</td>\n",
       "      <td>36.730920</td>\n",
       "      <td>36.841665</td>\n",
       "      <td>NaN</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\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>16964</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>terrestrial_and_marine_protected_areas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.214542</td>\n",
       "      <td>27.214585</td>\n",
       "      <td>27.214585</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>27.214747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16965</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>tree_cover_loss</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16966</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>unemployment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>4.994000</td>\n",
       "      <td>4.770000</td>\n",
       "      <td>5.282000</td>\n",
       "      <td>5.796000</td>\n",
       "      <td>6.279000</td>\n",
       "      <td>6.784000</td>\n",
       "      <td>7.370000</td>\n",
       "      <td>7.898000</td>\n",
       "      <td>8.067000</td>\n",
       "      <td>7.945000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16967</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>unmet_need_for_contraception</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.382129</td>\n",
       "      <td>10.400000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16968</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>voice_and_accountability</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.386220</td>\n",
       "      <td>-1.256889</td>\n",
       "      <td>-1.166087</td>\n",
       "      <td>-1.178460</td>\n",
       "      <td>-1.195905</td>\n",
       "      <td>-1.136798</td>\n",
       "      <td>-1.163669</td>\n",
       "      <td>-1.113408</td>\n",
       "      <td>-1.135830</td>\n",
       "      <td>-1.102206</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13774 rows × 66 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country_name_wb country_code  \\\n",
       "3195            World          WLD   \n",
       "3196            World          WLD   \n",
       "3197            World          WLD   \n",
       "3198            World          WLD   \n",
       "3199            World          WLD   \n",
       "...               ...          ...   \n",
       "16964        Zimbabwe          ZWE   \n",
       "16965        Zimbabwe          ZWE   \n",
       "16966        Zimbabwe          ZWE   \n",
       "16967        Zimbabwe          ZWE   \n",
       "16968        Zimbabwe          ZWE   \n",
       "\n",
       "                                                 feature  1960       1961  \\\n",
       "3195   access_to_clean_fuels_and_technologies_for_coo...   NaN        NaN   \n",
       "3196                               access_to_electricity   NaN        NaN   \n",
       "3197                         natural_resources_depletion   NaN        NaN   \n",
       "3198                                net_forest_depletion   NaN        NaN   \n",
       "3199                                   agricultural_land   NaN  35.879317   \n",
       "...                                                  ...   ...        ...   \n",
       "16964             terrestrial_and_marine_protected_areas   NaN        NaN   \n",
       "16965                                    tree_cover_loss   NaN        NaN   \n",
       "16966                                       unemployment   NaN        NaN   \n",
       "16967                       unmet_need_for_contraception   NaN        NaN   \n",
       "16968                           voice_and_accountability   NaN        NaN   \n",
       "\n",
       "           1962       1963       1964       1965       1966  ...       2013  \\\n",
       "3195        NaN        NaN        NaN        NaN        NaN  ...  61.095607   \n",
       "3196        NaN        NaN        NaN        NaN        NaN  ...  85.817366   \n",
       "3197        NaN        NaN        NaN        NaN        NaN  ...   1.778802   \n",
       "3198        NaN        NaN        NaN        NaN        NaN  ...   0.061422   \n",
       "3199   35.95247  36.035383  36.117043  36.213941  36.294321  ...  36.790232   \n",
       "...         ...        ...        ...        ...        ...  ...        ...   \n",
       "16964       NaN        NaN        NaN        NaN        NaN  ...        NaN   \n",
       "16965       NaN        NaN        NaN        NaN        NaN  ...        NaN   \n",
       "16966       NaN        NaN        NaN        NaN        NaN  ...   4.994000   \n",
       "16967       NaN        NaN        NaN        NaN        NaN  ...        NaN   \n",
       "16968       NaN        NaN        NaN        NaN        NaN  ...  -1.386220   \n",
       "\n",
       "            2014       2015       2016       2017       2018       2019  \\\n",
       "3195   62.372600  63.662869  65.005668  66.321819  67.696517  68.921601   \n",
       "3196   86.306969  87.025241  88.192385  89.019548  89.893733  90.194716   \n",
       "3197    1.520162   0.820341   0.717655   0.919547   1.246028   1.087624   \n",
       "3198    0.069023   0.071087   0.073026   0.069027   0.048838   0.049834   \n",
       "3199   36.789051  36.620496  36.587014  36.834001  36.738458  36.762648   \n",
       "...          ...        ...        ...        ...        ...        ...   \n",
       "16964        NaN        NaN  27.214542  27.214585  27.214585  27.214747   \n",
       "16965        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "16966   4.770000   5.282000   5.796000   6.279000   6.784000   7.370000   \n",
       "16967  10.382129  10.400000        NaN        NaN        NaN        NaN   \n",
       "16968  -1.256889  -1.166087  -1.178460  -1.195905  -1.136798  -1.163669   \n",
       "\n",
       "            2020       2021       2022  \n",
       "3195   70.184805  71.331487        NaN  \n",
       "3196   90.483629  91.413941        NaN  \n",
       "3197    0.790953        NaN        NaN  \n",
       "3198    0.058687        NaN        NaN  \n",
       "3199   36.730920  36.841665        NaN  \n",
       "...          ...        ...        ...  \n",
       "16964  27.214747  27.214747  27.214747  \n",
       "16965        NaN        NaN        NaN  \n",
       "16966   7.898000   8.067000   7.945000  \n",
       "16967        NaN        NaN        NaN  \n",
       "16968  -1.113408  -1.135830  -1.102206  \n",
       "\n",
       "[13774 rows x 66 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wb = wb.replace(replace_map)\n",
    "wb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c9dbc733-f8ee-42f2-9168-12b4bffc0a2c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['country_name_wb', 'country_code', 'feature', '1960', '1961', '1962',\n",
       "       '1963', '1964', '1965', '1966', '1967', '1968', '1969', '1970', '1971',\n",
       "       '1972', '1973', '1974', '1975', '1976', '1977', '1978', '1979', '1980',\n",
       "       '1981', '1982', '1983', '1984', '1985', '1986', '1987', '1988', '1989',\n",
       "       '1990', '1991', '1992', '1993', '1994', '1995', '1996', '1997', '1998',\n",
       "       '1999', '2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007',\n",
       "       '2008', '2009', '2010', '2011', '2012', '2013', '2014', '2015', '2016',\n",
       "       '2017', '2018', '2019', '2020', '2021', '2022'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wb.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cdf74e94-3771-492a-8c14-d272a6255a01",
   "metadata": {},
   "source": [
    "# 2 F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "ed8e4b57-8b86-4fa1-bd30-3f1dff0a08b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "wb = pd.melt(wb, id_vars=['country_name_wb', 'country_code'\n",
    "                         ,'feature'], var_name='year', value_name='value')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "1bce5e25-17d4-4920-a940-646049f243aa",
   "metadata": {},
   "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>country_name_wb</th>\n",
       "      <th>country_code</th>\n",
       "      <th>feature</th>\n",
       "      <th>year</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>access_to_clean_fuels_and_technologies_for_coo...</td>\n",
       "      <td>1960</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>access_to_electricity</td>\n",
       "      <td>1960</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>natural_resources_depletion</td>\n",
       "      <td>1960</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>net_forest_depletion</td>\n",
       "      <td>1960</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>agricultural_land</td>\n",
       "      <td>1960</td>\n",
       "      <td>NaN</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>867757</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>terrestrial_and_marine_protected_areas</td>\n",
       "      <td>2022</td>\n",
       "      <td>27.214747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>867758</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>tree_cover_loss</td>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>867759</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>unemployment</td>\n",
       "      <td>2022</td>\n",
       "      <td>7.945000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>867760</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>unmet_need_for_contraception</td>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>867761</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>voice_and_accountability</td>\n",
       "      <td>2022</td>\n",
       "      <td>-1.102206</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>867762 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       country_name_wb country_code  \\\n",
       "0                World          WLD   \n",
       "1                World          WLD   \n",
       "2                World          WLD   \n",
       "3                World          WLD   \n",
       "4                World          WLD   \n",
       "...                ...          ...   \n",
       "867757        Zimbabwe          ZWE   \n",
       "867758        Zimbabwe          ZWE   \n",
       "867759        Zimbabwe          ZWE   \n",
       "867760        Zimbabwe          ZWE   \n",
       "867761        Zimbabwe          ZWE   \n",
       "\n",
       "                                                  feature  year      value  \n",
       "0       access_to_clean_fuels_and_technologies_for_coo...  1960        NaN  \n",
       "1                                   access_to_electricity  1960        NaN  \n",
       "2                             natural_resources_depletion  1960        NaN  \n",
       "3                                    net_forest_depletion  1960        NaN  \n",
       "4                                       agricultural_land  1960        NaN  \n",
       "...                                                   ...   ...        ...  \n",
       "867757             terrestrial_and_marine_protected_areas  2022  27.214747  \n",
       "867758                                    tree_cover_loss  2022        NaN  \n",
       "867759                                       unemployment  2022   7.945000  \n",
       "867760                       unmet_need_for_contraception  2022        NaN  \n",
       "867761                           voice_and_accountability  2022  -1.102206  \n",
       "\n",
       "[867762 rows x 5 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9282a5c1-de34-4af1-8149-d76440a574ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>country_name_wb</th>\n",
       "      <th>country_code</th>\n",
       "      <th>year</th>\n",
       "      <th>access_to_clean_fuels_and_technologies_for_cooking</th>\n",
       "      <th>access_to_electricity</th>\n",
       "      <th>agricultural_land</th>\n",
       "      <th>agriculture</th>\n",
       "      <th>annual_freshwater_withdrawals</th>\n",
       "      <th>annualized_average_growth_rate_in_per_capita_real_survey</th>\n",
       "      <th>cause_of_death</th>\n",
       "      <th>...</th>\n",
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       "      <th>scientific_and_technical_journal_articles</th>\n",
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       "      <th>terrestrial_and_marine_protected_areas</th>\n",
       "      <th>tree_cover_loss</th>\n",
       "      <th>unemployment</th>\n",
       "      <th>unmet_need_for_contraception</th>\n",
       "      <th>voice_and_accountability</th>\n",
       "      <th>water_quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1960</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1961</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>57.878356</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1962</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>57.955016</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1963</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.031676</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1964</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.116002</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 74 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  country_name_wb country_code  year  \\\n",
       "0     Afghanistan          AFG  1960   \n",
       "1     Afghanistan          AFG  1961   \n",
       "2     Afghanistan          AFG  1962   \n",
       "3     Afghanistan          AFG  1963   \n",
       "4     Afghanistan          AFG  1964   \n",
       "\n",
       "   access_to_clean_fuels_and_technologies_for_cooking  access_to_electricity  \\\n",
       "0                                                NaN                     NaN   \n",
       "1                                                NaN                     NaN   \n",
       "2                                                NaN                     NaN   \n",
       "3                                                NaN                     NaN   \n",
       "4                                                NaN                     NaN   \n",
       "\n",
       "   agricultural_land  agriculture  annual_freshwater_withdrawals  \\\n",
       "0                NaN          NaN                            NaN   \n",
       "1          57.878356          NaN                            NaN   \n",
       "2          57.955016          NaN                            NaN   \n",
       "3          58.031676          NaN                            NaN   \n",
       "4          58.116002          NaN                            NaN   \n",
       "\n",
       "   annualized_average_growth_rate_in_per_capita_real_survey  cause_of_death  \\\n",
       "0                                                NaN                    NaN   \n",
       "1                                                NaN                    NaN   \n",
       "2                                                NaN                    NaN   \n",
       "3                                                NaN                    NaN   \n",
       "4                                                NaN                    NaN   \n",
       "\n",
       "   ...  research_and_development_expenditure  rule_of_law  \\\n",
       "0  ...                                   NaN          NaN   \n",
       "1  ...                                   NaN          NaN   \n",
       "2  ...                                   NaN          NaN   \n",
       "3  ...                                   NaN          NaN   \n",
       "4  ...                                   NaN          NaN   \n",
       "\n",
       "   scientific_and_technical_journal_articles  strength_of_legal_rights_index  \\\n",
       "0                                        NaN                             NaN   \n",
       "1                                        NaN                             NaN   \n",
       "2                                        NaN                             NaN   \n",
       "3                                        NaN                             NaN   \n",
       "4                                        NaN                             NaN   \n",
       "\n",
       "   terrestrial_and_marine_protected_areas  tree_cover_loss  unemployment  \\\n",
       "0                                     NaN              NaN           NaN   \n",
       "1                                     NaN              NaN           NaN   \n",
       "2                                     NaN              NaN           NaN   \n",
       "3                                     NaN              NaN           NaN   \n",
       "4                                     NaN              NaN           NaN   \n",
       "\n",
       "   unmet_need_for_contraception  voice_and_accountability  water_quality  \n",
       "0                           NaN                       NaN            NaN  \n",
       "1                           NaN                       NaN            NaN  \n",
       "2                           NaN                       NaN            NaN  \n",
       "3                           NaN                       NaN            NaN  \n",
       "4                           NaN                       NaN            NaN  \n",
       "\n",
       "[5 rows x 74 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wb = wb.pivot_table(index=['country_name_wb','country_code', 'year'], columns='feature', values='value').reset_index()\n",
    " \n",
    " \n",
    "wb.columns.name = None\n",
    " \n",
    " \n",
    "wb = wb.reset_index(drop=True)\n",
    " \n",
    "wb.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e939216-c20b-4ff5-9d56-6f9d191ad13d",
   "metadata": {},
   "source": [
    "# 2 G"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "701c12ec-4d7a-493d-a2f1-b4b8aed6f60a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "country_name_wb                                        object\n",
       "country_code                                           object\n",
       "year                                                    int64\n",
       "access_to_clean_fuels_and_technologies_for_cooking    float64\n",
       "access_to_electricity                                 float64\n",
       "                                                       ...   \n",
       "tree_cover_loss                                       float64\n",
       "unemployment                                          float64\n",
       "unmet_need_for_contraception                          float64\n",
       "voice_and_accountability                              float64\n",
       "water_quality                                         float64\n",
       "Length: 74, dtype: object"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wb['year'] = pd.to_numeric(wb['year'])\n",
    "wb.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f780fdba-ea09-499d-83e3-60123dd0c37d",
   "metadata": {},
   "source": [
    "# 2 H"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "235e4228-db07-4ead-8106-f33c9798381f",
   "metadata": {},
   "outputs": [],
   "source": [
    "newdf = wb[wb['country_name_wb'] == 'World']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "99664b97-5726-4c2a-bc5a-96ebd99df90f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>WLD</td>\n",
       "      <td>1963</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>1964</td>\n",
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       "      <th>12028</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
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       "      <td>67.696517</td>\n",
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       "      <td>3.951747</td>\n",
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       "      <td>2.565871e+06</td>\n",
       "      <td>5.507853</td>\n",
       "      <td>14.337515</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.699076</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12029</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>2019</td>\n",
       "      <td>68.921601</td>\n",
       "      <td>90.194716</td>\n",
       "      <td>36.762648</td>\n",
       "      <td>4.013242</td>\n",
       "      <td>9.167900</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.40885</td>\n",
       "      <td>...</td>\n",
       "      <td>2.331934</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.734962e+06</td>\n",
       "      <td>5.685864</td>\n",
       "      <td>14.599801</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.543161</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12030</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>2020</td>\n",
       "      <td>70.184805</td>\n",
       "      <td>90.483629</td>\n",
       "      <td>36.730920</td>\n",
       "      <td>4.352489</td>\n",
       "      <td>9.109511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>2.627081</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.933011e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.787111</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.898273</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12031</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>2021</td>\n",
       "      <td>71.331487</td>\n",
       "      <td>91.413941</td>\n",
       "      <td>36.841665</td>\n",
       "      <td>4.304093</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.552260</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.201871</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12032</th>\n",
       "      <td>World</td>\n",
       "      <td>WLD</td>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.329327</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.772710</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>63 rows × 74 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country_name_wb country_code  year  \\\n",
       "11970           World          WLD  1960   \n",
       "11971           World          WLD  1961   \n",
       "11972           World          WLD  1962   \n",
       "11973           World          WLD  1963   \n",
       "11974           World          WLD  1964   \n",
       "...               ...          ...   ...   \n",
       "12028           World          WLD  2018   \n",
       "12029           World          WLD  2019   \n",
       "12030           World          WLD  2020   \n",
       "12031           World          WLD  2021   \n",
       "12032           World          WLD  2022   \n",
       "\n",
       "       access_to_clean_fuels_and_technologies_for_cooking  \\\n",
       "11970                                                NaN    \n",
       "11971                                                NaN    \n",
       "11972                                                NaN    \n",
       "11973                                                NaN    \n",
       "11974                                                NaN    \n",
       "...                                                  ...    \n",
       "12028                                          67.696517    \n",
       "12029                                          68.921601    \n",
       "12030                                          70.184805    \n",
       "12031                                          71.331487    \n",
       "12032                                                NaN    \n",
       "\n",
       "       access_to_electricity  agricultural_land  agriculture  \\\n",
       "11970                    NaN                NaN          NaN   \n",
       "11971                    NaN          35.879317          NaN   \n",
       "11972                    NaN          35.952470          NaN   \n",
       "11973                    NaN          36.035383          NaN   \n",
       "11974                    NaN          36.117043          NaN   \n",
       "...                      ...                ...          ...   \n",
       "12028              89.893733          36.738458     3.951747   \n",
       "12029              90.194716          36.762648     4.013242   \n",
       "12030              90.483629          36.730920     4.352489   \n",
       "12031              91.413941          36.841665     4.304093   \n",
       "12032                    NaN                NaN     4.329327   \n",
       "\n",
       "       annual_freshwater_withdrawals  \\\n",
       "11970                            NaN   \n",
       "11971                            NaN   \n",
       "11972                            NaN   \n",
       "11973                            NaN   \n",
       "11974                            NaN   \n",
       "...                              ...   \n",
       "12028                       9.137864   \n",
       "12029                       9.167900   \n",
       "12030                       9.109511   \n",
       "12031                            NaN   \n",
       "12032                            NaN   \n",
       "\n",
       "       annualized_average_growth_rate_in_per_capita_real_survey  \\\n",
       "11970                                                NaN          \n",
       "11971                                                NaN          \n",
       "11972                                                NaN          \n",
       "11973                                                NaN          \n",
       "11974                                                NaN          \n",
       "...                                                  ...          \n",
       "12028                                                NaN          \n",
       "12029                                                NaN          \n",
       "12030                                                NaN          \n",
       "12031                                                NaN          \n",
       "12032                                                NaN          \n",
       "\n",
       "       cause_of_death  ...  research_and_development_expenditure  rule_of_law  \\\n",
       "11970             NaN  ...                                   NaN          NaN   \n",
       "11971             NaN  ...                                   NaN          NaN   \n",
       "11972             NaN  ...                                   NaN          NaN   \n",
       "11973             NaN  ...                                   NaN          NaN   \n",
       "11974             NaN  ...                                   NaN          NaN   \n",
       "...               ...  ...                                   ...          ...   \n",
       "12028             NaN  ...                              2.196050          NaN   \n",
       "12029        18.40885  ...                              2.331934          NaN   \n",
       "12030             NaN  ...                              2.627081          NaN   \n",
       "12031             NaN  ...                                   NaN          NaN   \n",
       "12032             NaN  ...                                   NaN          NaN   \n",
       "\n",
       "       scientific_and_technical_journal_articles  \\\n",
       "11970                                        NaN   \n",
       "11971                                        NaN   \n",
       "11972                                        NaN   \n",
       "11973                                        NaN   \n",
       "11974                                        NaN   \n",
       "...                                          ...   \n",
       "12028                               2.565871e+06   \n",
       "12029                               2.734962e+06   \n",
       "12030                               2.933011e+06   \n",
       "12031                                        NaN   \n",
       "12032                                        NaN   \n",
       "\n",
       "       strength_of_legal_rights_index  terrestrial_and_marine_protected_areas  \\\n",
       "11970                             NaN                                     NaN   \n",
       "11971                             NaN                                     NaN   \n",
       "11972                             NaN                                     NaN   \n",
       "11973                             NaN                                     NaN   \n",
       "11974                             NaN                                     NaN   \n",
       "...                               ...                                     ...   \n",
       "12028                        5.507853                               14.337515   \n",
       "12029                        5.685864                               14.599801   \n",
       "12030                             NaN                               14.787111   \n",
       "12031                             NaN                               14.552260   \n",
       "12032                             NaN                                     NaN   \n",
       "\n",
       "       tree_cover_loss  unemployment  unmet_need_for_contraception  \\\n",
       "11970              NaN           NaN                           NaN   \n",
       "11971              NaN           NaN                           NaN   \n",
       "11972              NaN           NaN                           NaN   \n",
       "11973              NaN           NaN                           NaN   \n",
       "11974              NaN           NaN                           NaN   \n",
       "...                ...           ...                           ...   \n",
       "12028              NaN      5.699076                           NaN   \n",
       "12029              NaN      5.543161                           NaN   \n",
       "12030              NaN      6.898273                           NaN   \n",
       "12031              NaN      6.201871                           NaN   \n",
       "12032              NaN      5.772710                           NaN   \n",
       "\n",
       "       voice_and_accountability  water_quality  \n",
       "11970                       NaN            NaN  \n",
       "11971                       NaN            NaN  \n",
       "11972                       NaN            NaN  \n",
       "11973                       NaN            NaN  \n",
       "11974                       NaN            NaN  \n",
       "...                         ...            ...  \n",
       "12028                       NaN            NaN  \n",
       "12029                       NaN            NaN  \n",
       "12030                       NaN            NaN  \n",
       "12031                       NaN            NaN  \n",
       "12032                       NaN            NaN  \n",
       "\n",
       "[63 rows x 74 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "7df9d0cc-bac7-40bf-9217-4ef79308c8ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "test = wb[wb['country_name_wb'] != 'World']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "503766fd-b9f7-4d75-9154-11c0d3671078",
   "metadata": {},
   "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>country_name_wb</th>\n",
       "      <th>country_code</th>\n",
       "      <th>year</th>\n",
       "      <th>access_to_clean_fuels_and_technologies_for_cooking</th>\n",
       "      <th>access_to_electricity</th>\n",
       "      <th>agricultural_land</th>\n",
       "      <th>agriculture</th>\n",
       "      <th>annual_freshwater_withdrawals</th>\n",
       "      <th>annualized_average_growth_rate_in_per_capita_real_survey</th>\n",
       "      <th>cause_of_death</th>\n",
       "      <th>...</th>\n",
       "      <th>research_and_development_expenditure</th>\n",
       "      <th>rule_of_law</th>\n",
       "      <th>scientific_and_technical_journal_articles</th>\n",
       "      <th>strength_of_legal_rights_index</th>\n",
       "      <th>terrestrial_and_marine_protected_areas</th>\n",
       "      <th>tree_cover_loss</th>\n",
       "      <th>unemployment</th>\n",
       "      <th>unmet_need_for_contraception</th>\n",
       "      <th>voice_and_accountability</th>\n",
       "      <th>water_quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1960</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1961</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>57.878356</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1962</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>57.955016</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1963</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.031676</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1964</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.116002</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\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>12217</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>2018</td>\n",
       "      <td>30.0</td>\n",
       "      <td>45.400288</td>\n",
       "      <td>41.876696</td>\n",
       "      <td>7.319375</td>\n",
       "      <td>30.761677</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.292463</td>\n",
       "      <td>406.23</td>\n",
       "      <td>5.0</td>\n",
       "      <td>27.214585</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.784</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.136798</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12218</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>2019</td>\n",
       "      <td>30.2</td>\n",
       "      <td>46.682095</td>\n",
       "      <td>41.876696</td>\n",
       "      <td>9.819262</td>\n",
       "      <td>30.761677</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47.647301</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.303515</td>\n",
       "      <td>431.62</td>\n",
       "      <td>6.0</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.370</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.163669</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12219</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>2020</td>\n",
       "      <td>30.3</td>\n",
       "      <td>52.747667</td>\n",
       "      <td>41.876696</td>\n",
       "      <td>8.772859</td>\n",
       "      <td>30.761677</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.329611</td>\n",
       "      <td>480.16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.898</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.113408</td>\n",
       "      <td>83.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12220</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>2021</td>\n",
       "      <td>30.3</td>\n",
       "      <td>48.979927</td>\n",
       "      <td>41.876696</td>\n",
       "      <td>8.849899</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.277202</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.067</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.135830</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12221</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.236284</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.945</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.102206</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12159 rows × 74 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country_name_wb country_code  year  \\\n",
       "0         Afghanistan          AFG  1960   \n",
       "1         Afghanistan          AFG  1961   \n",
       "2         Afghanistan          AFG  1962   \n",
       "3         Afghanistan          AFG  1963   \n",
       "4         Afghanistan          AFG  1964   \n",
       "...               ...          ...   ...   \n",
       "12217        Zimbabwe          ZWE  2018   \n",
       "12218        Zimbabwe          ZWE  2019   \n",
       "12219        Zimbabwe          ZWE  2020   \n",
       "12220        Zimbabwe          ZWE  2021   \n",
       "12221        Zimbabwe          ZWE  2022   \n",
       "\n",
       "       access_to_clean_fuels_and_technologies_for_cooking  \\\n",
       "0                                                    NaN    \n",
       "1                                                    NaN    \n",
       "2                                                    NaN    \n",
       "3                                                    NaN    \n",
       "4                                                    NaN    \n",
       "...                                                  ...    \n",
       "12217                                               30.0    \n",
       "12218                                               30.2    \n",
       "12219                                               30.3    \n",
       "12220                                               30.3    \n",
       "12221                                                NaN    \n",
       "\n",
       "       access_to_electricity  agricultural_land  agriculture  \\\n",
       "0                        NaN                NaN          NaN   \n",
       "1                        NaN          57.878356          NaN   \n",
       "2                        NaN          57.955016          NaN   \n",
       "3                        NaN          58.031676          NaN   \n",
       "4                        NaN          58.116002          NaN   \n",
       "...                      ...                ...          ...   \n",
       "12217              45.400288          41.876696     7.319375   \n",
       "12218              46.682095          41.876696     9.819262   \n",
       "12219              52.747667          41.876696     8.772859   \n",
       "12220              48.979927          41.876696     8.849899   \n",
       "12221                    NaN                NaN          NaN   \n",
       "\n",
       "       annual_freshwater_withdrawals  \\\n",
       "0                                NaN   \n",
       "1                                NaN   \n",
       "2                                NaN   \n",
       "3                                NaN   \n",
       "4                                NaN   \n",
       "...                              ...   \n",
       "12217                      30.761677   \n",
       "12218                      30.761677   \n",
       "12219                      30.761677   \n",
       "12220                            NaN   \n",
       "12221                            NaN   \n",
       "\n",
       "       annualized_average_growth_rate_in_per_capita_real_survey  \\\n",
       "0                                                    NaN          \n",
       "1                                                    NaN          \n",
       "2                                                    NaN          \n",
       "3                                                    NaN          \n",
       "4                                                    NaN          \n",
       "...                                                  ...          \n",
       "12217                                                NaN          \n",
       "12218                                                NaN          \n",
       "12219                                                NaN          \n",
       "12220                                                NaN          \n",
       "12221                                                NaN          \n",
       "\n",
       "       cause_of_death  ...  research_and_development_expenditure  rule_of_law  \\\n",
       "0                 NaN  ...                                   NaN          NaN   \n",
       "1                 NaN  ...                                   NaN          NaN   \n",
       "2                 NaN  ...                                   NaN          NaN   \n",
       "3                 NaN  ...                                   NaN          NaN   \n",
       "4                 NaN  ...                                   NaN          NaN   \n",
       "...               ...  ...                                   ...          ...   \n",
       "12217             NaN  ...                                   NaN    -1.292463   \n",
       "12218       47.647301  ...                                   NaN    -1.303515   \n",
       "12219             NaN  ...                                   NaN    -1.329611   \n",
       "12220             NaN  ...                                   NaN    -1.277202   \n",
       "12221             NaN  ...                                   NaN    -1.236284   \n",
       "\n",
       "       scientific_and_technical_journal_articles  \\\n",
       "0                                            NaN   \n",
       "1                                            NaN   \n",
       "2                                            NaN   \n",
       "3                                            NaN   \n",
       "4                                            NaN   \n",
       "...                                          ...   \n",
       "12217                                     406.23   \n",
       "12218                                     431.62   \n",
       "12219                                     480.16   \n",
       "12220                                        NaN   \n",
       "12221                                        NaN   \n",
       "\n",
       "       strength_of_legal_rights_index  terrestrial_and_marine_protected_areas  \\\n",
       "0                                 NaN                                     NaN   \n",
       "1                                 NaN                                     NaN   \n",
       "2                                 NaN                                     NaN   \n",
       "3                                 NaN                                     NaN   \n",
       "4                                 NaN                                     NaN   \n",
       "...                               ...                                     ...   \n",
       "12217                             5.0                               27.214585   \n",
       "12218                             6.0                               27.214747   \n",
       "12219                             NaN                               27.214747   \n",
       "12220                             NaN                               27.214747   \n",
       "12221                             NaN                               27.214747   \n",
       "\n",
       "       tree_cover_loss  unemployment  unmet_need_for_contraception  \\\n",
       "0                  NaN           NaN                           NaN   \n",
       "1                  NaN           NaN                           NaN   \n",
       "2                  NaN           NaN                           NaN   \n",
       "3                  NaN           NaN                           NaN   \n",
       "4                  NaN           NaN                           NaN   \n",
       "...                ...           ...                           ...   \n",
       "12217              NaN         6.784                           NaN   \n",
       "12218              NaN         7.370                           NaN   \n",
       "12219              NaN         7.898                           NaN   \n",
       "12220              NaN         8.067                           NaN   \n",
       "12221              NaN         7.945                           NaN   \n",
       "\n",
       "       voice_and_accountability  water_quality  \n",
       "0                           NaN            NaN  \n",
       "1                           NaN            NaN  \n",
       "2                           NaN            NaN  \n",
       "3                           NaN            NaN  \n",
       "4                           NaN            NaN  \n",
       "...                         ...            ...  \n",
       "12217                 -1.136798            NaN  \n",
       "12218                 -1.163669            NaN  \n",
       "12219                 -1.113408           83.3  \n",
       "12220                 -1.135830            NaN  \n",
       "12221                 -1.102206            NaN  \n",
       "\n",
       "[12159 rows x 74 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "930edcb9-41c0-4458-80c8-71c5e99025dc",
   "metadata": {},
   "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",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>access_to_clean_fuels_and_technologies_for_cooking</th>\n",
       "      <th>access_to_electricity</th>\n",
       "      <th>agricultural_land</th>\n",
       "      <th>agriculture</th>\n",
       "      <th>annual_freshwater_withdrawals</th>\n",
       "      <th>annualized_average_growth_rate_in_per_capita_real_survey</th>\n",
       "      <th>cause_of_death</th>\n",
       "      <th>children_in_employment</th>\n",
       "      <th>co2_emissions</th>\n",
       "      <th>...</th>\n",
       "      <th>research_and_development_expenditure</th>\n",
       "      <th>rule_of_law</th>\n",
       "      <th>scientific_and_technical_journal_articles</th>\n",
       "      <th>strength_of_legal_rights_index</th>\n",
       "      <th>terrestrial_and_marine_protected_areas</th>\n",
       "      <th>tree_cover_loss</th>\n",
       "      <th>unemployment</th>\n",
       "      <th>unmet_need_for_contraception</th>\n",
       "      <th>voice_and_accountability</th>\n",
       "      <th>water_quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>11970</th>\n",
       "      <td>1960</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11971</th>\n",
       "      <td>1961</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.879317</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11972</th>\n",
       "      <td>1962</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.952470</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11973</th>\n",
       "      <td>1963</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.035383</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11974</th>\n",
       "      <td>1964</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.117043</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\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>12028</th>\n",
       "      <td>2018</td>\n",
       "      <td>67.696517</td>\n",
       "      <td>89.893733</td>\n",
       "      <td>36.738458</td>\n",
       "      <td>3.951747</td>\n",
       "      <td>9.137864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.641294</td>\n",
       "      <td>...</td>\n",
       "      <td>2.196050</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.565871e+06</td>\n",
       "      <td>5.507853</td>\n",
       "      <td>14.337515</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.699076</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12029</th>\n",
       "      <td>2019</td>\n",
       "      <td>68.921601</td>\n",
       "      <td>90.194716</td>\n",
       "      <td>36.762648</td>\n",
       "      <td>4.013242</td>\n",
       "      <td>9.167900</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.40885</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.582036</td>\n",
       "      <td>...</td>\n",
       "      <td>2.331934</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.734962e+06</td>\n",
       "      <td>5.685864</td>\n",
       "      <td>14.599801</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.543161</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12030</th>\n",
       "      <td>2020</td>\n",
       "      <td>70.184805</td>\n",
       "      <td>90.483629</td>\n",
       "      <td>36.730920</td>\n",
       "      <td>4.352489</td>\n",
       "      <td>9.109511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.291853</td>\n",
       "      <td>...</td>\n",
       "      <td>2.627081</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.933011e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.787111</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.898273</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12031</th>\n",
       "      <td>2021</td>\n",
       "      <td>71.331487</td>\n",
       "      <td>91.413941</td>\n",
       "      <td>36.841665</td>\n",
       "      <td>4.304093</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.552260</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.201871</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12032</th>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.329327</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.772710</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>63 rows × 72 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       year  access_to_clean_fuels_and_technologies_for_cooking  \\\n",
       "11970  1960                                                NaN    \n",
       "11971  1961                                                NaN    \n",
       "11972  1962                                                NaN    \n",
       "11973  1963                                                NaN    \n",
       "11974  1964                                                NaN    \n",
       "...     ...                                                ...    \n",
       "12028  2018                                          67.696517    \n",
       "12029  2019                                          68.921601    \n",
       "12030  2020                                          70.184805    \n",
       "12031  2021                                          71.331487    \n",
       "12032  2022                                                NaN    \n",
       "\n",
       "       access_to_electricity  agricultural_land  agriculture  \\\n",
       "11970                    NaN                NaN          NaN   \n",
       "11971                    NaN          35.879317          NaN   \n",
       "11972                    NaN          35.952470          NaN   \n",
       "11973                    NaN          36.035383          NaN   \n",
       "11974                    NaN          36.117043          NaN   \n",
       "...                      ...                ...          ...   \n",
       "12028              89.893733          36.738458     3.951747   \n",
       "12029              90.194716          36.762648     4.013242   \n",
       "12030              90.483629          36.730920     4.352489   \n",
       "12031              91.413941          36.841665     4.304093   \n",
       "12032                    NaN                NaN     4.329327   \n",
       "\n",
       "       annual_freshwater_withdrawals  \\\n",
       "11970                            NaN   \n",
       "11971                            NaN   \n",
       "11972                            NaN   \n",
       "11973                            NaN   \n",
       "11974                            NaN   \n",
       "...                              ...   \n",
       "12028                       9.137864   \n",
       "12029                       9.167900   \n",
       "12030                       9.109511   \n",
       "12031                            NaN   \n",
       "12032                            NaN   \n",
       "\n",
       "       annualized_average_growth_rate_in_per_capita_real_survey  \\\n",
       "11970                                                NaN          \n",
       "11971                                                NaN          \n",
       "11972                                                NaN          \n",
       "11973                                                NaN          \n",
       "11974                                                NaN          \n",
       "...                                                  ...          \n",
       "12028                                                NaN          \n",
       "12029                                                NaN          \n",
       "12030                                                NaN          \n",
       "12031                                                NaN          \n",
       "12032                                                NaN          \n",
       "\n",
       "       cause_of_death  children_in_employment  co2_emissions  ...  \\\n",
       "11970             NaN                     NaN            NaN  ...   \n",
       "11971             NaN                     NaN            NaN  ...   \n",
       "11972             NaN                     NaN            NaN  ...   \n",
       "11973             NaN                     NaN            NaN  ...   \n",
       "11974             NaN                     NaN            NaN  ...   \n",
       "...               ...                     ...            ...  ...   \n",
       "12028             NaN                     NaN       4.641294  ...   \n",
       "12029        18.40885                     NaN       4.582036  ...   \n",
       "12030             NaN                     NaN       4.291853  ...   \n",
       "12031             NaN                     NaN            NaN  ...   \n",
       "12032             NaN                     NaN            NaN  ...   \n",
       "\n",
       "       research_and_development_expenditure  rule_of_law  \\\n",
       "11970                                   NaN          NaN   \n",
       "11971                                   NaN          NaN   \n",
       "11972                                   NaN          NaN   \n",
       "11973                                   NaN          NaN   \n",
       "11974                                   NaN          NaN   \n",
       "...                                     ...          ...   \n",
       "12028                              2.196050          NaN   \n",
       "12029                              2.331934          NaN   \n",
       "12030                              2.627081          NaN   \n",
       "12031                                   NaN          NaN   \n",
       "12032                                   NaN          NaN   \n",
       "\n",
       "       scientific_and_technical_journal_articles  \\\n",
       "11970                                        NaN   \n",
       "11971                                        NaN   \n",
       "11972                                        NaN   \n",
       "11973                                        NaN   \n",
       "11974                                        NaN   \n",
       "...                                          ...   \n",
       "12028                               2.565871e+06   \n",
       "12029                               2.734962e+06   \n",
       "12030                               2.933011e+06   \n",
       "12031                                        NaN   \n",
       "12032                                        NaN   \n",
       "\n",
       "       strength_of_legal_rights_index  terrestrial_and_marine_protected_areas  \\\n",
       "11970                             NaN                                     NaN   \n",
       "11971                             NaN                                     NaN   \n",
       "11972                             NaN                                     NaN   \n",
       "11973                             NaN                                     NaN   \n",
       "11974                             NaN                                     NaN   \n",
       "...                               ...                                     ...   \n",
       "12028                        5.507853                               14.337515   \n",
       "12029                        5.685864                               14.599801   \n",
       "12030                             NaN                               14.787111   \n",
       "12031                             NaN                               14.552260   \n",
       "12032                             NaN                                     NaN   \n",
       "\n",
       "       tree_cover_loss  unemployment  unmet_need_for_contraception  \\\n",
       "11970              NaN           NaN                           NaN   \n",
       "11971              NaN           NaN                           NaN   \n",
       "11972              NaN           NaN                           NaN   \n",
       "11973              NaN           NaN                           NaN   \n",
       "11974              NaN           NaN                           NaN   \n",
       "...                ...           ...                           ...   \n",
       "12028              NaN      5.699076                           NaN   \n",
       "12029              NaN      5.543161                           NaN   \n",
       "12030              NaN      6.898273                           NaN   \n",
       "12031              NaN      6.201871                           NaN   \n",
       "12032              NaN      5.772710                           NaN   \n",
       "\n",
       "       voice_and_accountability  water_quality  \n",
       "11970                       NaN            NaN  \n",
       "11971                       NaN            NaN  \n",
       "11972                       NaN            NaN  \n",
       "11973                       NaN            NaN  \n",
       "11974                       NaN            NaN  \n",
       "...                         ...            ...  \n",
       "12028                       NaN            NaN  \n",
       "12029                       NaN            NaN  \n",
       "12030                       NaN            NaN  \n",
       "12031                       NaN            NaN  \n",
       "12032                       NaN            NaN  \n",
       "\n",
       "[63 rows x 72 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "worlddf = newdf.drop(columns=['country_code', 'country_name_wb'])\n",
    "worlddf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7d91f516-18d7-498b-87cb-82853c4ce574",
   "metadata": {},
   "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>year</th>\n",
       "      <th>world_access_to_clean_fuels_and_technologies_for_cooking</th>\n",
       "      <th>world_access_to_electricity</th>\n",
       "      <th>world_agricultural_land</th>\n",
       "      <th>world_agriculture</th>\n",
       "      <th>world_annual_freshwater_withdrawals</th>\n",
       "      <th>world_annualized_average_growth_rate_in_per_capita_real_survey</th>\n",
       "      <th>world_cause_of_death</th>\n",
       "      <th>world_children_in_employment</th>\n",
       "      <th>world_co2_emissions</th>\n",
       "      <th>...</th>\n",
       "      <th>world_research_and_development_expenditure</th>\n",
       "      <th>world_rule_of_law</th>\n",
       "      <th>world_scientific_and_technical_journal_articles</th>\n",
       "      <th>world_strength_of_legal_rights_index</th>\n",
       "      <th>world_terrestrial_and_marine_protected_areas</th>\n",
       "      <th>world_tree_cover_loss</th>\n",
       "      <th>world_unemployment</th>\n",
       "      <th>world_unmet_need_for_contraception</th>\n",
       "      <th>world_voice_and_accountability</th>\n",
       "      <th>world_water_quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>11970</th>\n",
       "      <td>1960</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11971</th>\n",
       "      <td>1961</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.879317</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11972</th>\n",
       "      <td>1962</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.952470</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11973</th>\n",
       "      <td>1963</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.035383</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11974</th>\n",
       "      <td>1964</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.117043</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\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>12028</th>\n",
       "      <td>2018</td>\n",
       "      <td>67.696517</td>\n",
       "      <td>89.893733</td>\n",
       "      <td>36.738458</td>\n",
       "      <td>3.951747</td>\n",
       "      <td>9.137864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.641294</td>\n",
       "      <td>...</td>\n",
       "      <td>2.196050</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.565871e+06</td>\n",
       "      <td>5.507853</td>\n",
       "      <td>14.337515</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.699076</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12029</th>\n",
       "      <td>2019</td>\n",
       "      <td>68.921601</td>\n",
       "      <td>90.194716</td>\n",
       "      <td>36.762648</td>\n",
       "      <td>4.013242</td>\n",
       "      <td>9.167900</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.40885</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.582036</td>\n",
       "      <td>...</td>\n",
       "      <td>2.331934</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.734962e+06</td>\n",
       "      <td>5.685864</td>\n",
       "      <td>14.599801</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.543161</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12030</th>\n",
       "      <td>2020</td>\n",
       "      <td>70.184805</td>\n",
       "      <td>90.483629</td>\n",
       "      <td>36.730920</td>\n",
       "      <td>4.352489</td>\n",
       "      <td>9.109511</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.291853</td>\n",
       "      <td>...</td>\n",
       "      <td>2.627081</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.933011e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.787111</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.898273</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12031</th>\n",
       "      <td>2021</td>\n",
       "      <td>71.331487</td>\n",
       "      <td>91.413941</td>\n",
       "      <td>36.841665</td>\n",
       "      <td>4.304093</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.552260</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.201871</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12032</th>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.329327</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.772710</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>63 rows × 72 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       year  world_access_to_clean_fuels_and_technologies_for_cooking  \\\n",
       "11970  1960                                                NaN          \n",
       "11971  1961                                                NaN          \n",
       "11972  1962                                                NaN          \n",
       "11973  1963                                                NaN          \n",
       "11974  1964                                                NaN          \n",
       "...     ...                                                ...          \n",
       "12028  2018                                          67.696517          \n",
       "12029  2019                                          68.921601          \n",
       "12030  2020                                          70.184805          \n",
       "12031  2021                                          71.331487          \n",
       "12032  2022                                                NaN          \n",
       "\n",
       "       world_access_to_electricity  world_agricultural_land  \\\n",
       "11970                          NaN                      NaN   \n",
       "11971                          NaN                35.879317   \n",
       "11972                          NaN                35.952470   \n",
       "11973                          NaN                36.035383   \n",
       "11974                          NaN                36.117043   \n",
       "...                            ...                      ...   \n",
       "12028                    89.893733                36.738458   \n",
       "12029                    90.194716                36.762648   \n",
       "12030                    90.483629                36.730920   \n",
       "12031                    91.413941                36.841665   \n",
       "12032                          NaN                      NaN   \n",
       "\n",
       "       world_agriculture  world_annual_freshwater_withdrawals  \\\n",
       "11970                NaN                                  NaN   \n",
       "11971                NaN                                  NaN   \n",
       "11972                NaN                                  NaN   \n",
       "11973                NaN                                  NaN   \n",
       "11974                NaN                                  NaN   \n",
       "...                  ...                                  ...   \n",
       "12028           3.951747                             9.137864   \n",
       "12029           4.013242                             9.167900   \n",
       "12030           4.352489                             9.109511   \n",
       "12031           4.304093                                  NaN   \n",
       "12032           4.329327                                  NaN   \n",
       "\n",
       "       world_annualized_average_growth_rate_in_per_capita_real_survey  \\\n",
       "11970                                                NaN                \n",
       "11971                                                NaN                \n",
       "11972                                                NaN                \n",
       "11973                                                NaN                \n",
       "11974                                                NaN                \n",
       "...                                                  ...                \n",
       "12028                                                NaN                \n",
       "12029                                                NaN                \n",
       "12030                                                NaN                \n",
       "12031                                                NaN                \n",
       "12032                                                NaN                \n",
       "\n",
       "       world_cause_of_death  world_children_in_employment  \\\n",
       "11970                   NaN                           NaN   \n",
       "11971                   NaN                           NaN   \n",
       "11972                   NaN                           NaN   \n",
       "11973                   NaN                           NaN   \n",
       "11974                   NaN                           NaN   \n",
       "...                     ...                           ...   \n",
       "12028                   NaN                           NaN   \n",
       "12029              18.40885                           NaN   \n",
       "12030                   NaN                           NaN   \n",
       "12031                   NaN                           NaN   \n",
       "12032                   NaN                           NaN   \n",
       "\n",
       "       world_co2_emissions  ...  world_research_and_development_expenditure  \\\n",
       "11970                  NaN  ...                                         NaN   \n",
       "11971                  NaN  ...                                         NaN   \n",
       "11972                  NaN  ...                                         NaN   \n",
       "11973                  NaN  ...                                         NaN   \n",
       "11974                  NaN  ...                                         NaN   \n",
       "...                    ...  ...                                         ...   \n",
       "12028             4.641294  ...                                    2.196050   \n",
       "12029             4.582036  ...                                    2.331934   \n",
       "12030             4.291853  ...                                    2.627081   \n",
       "12031                  NaN  ...                                         NaN   \n",
       "12032                  NaN  ...                                         NaN   \n",
       "\n",
       "       world_rule_of_law  world_scientific_and_technical_journal_articles  \\\n",
       "11970                NaN                                              NaN   \n",
       "11971                NaN                                              NaN   \n",
       "11972                NaN                                              NaN   \n",
       "11973                NaN                                              NaN   \n",
       "11974                NaN                                              NaN   \n",
       "...                  ...                                              ...   \n",
       "12028                NaN                                     2.565871e+06   \n",
       "12029                NaN                                     2.734962e+06   \n",
       "12030                NaN                                     2.933011e+06   \n",
       "12031                NaN                                              NaN   \n",
       "12032                NaN                                              NaN   \n",
       "\n",
       "       world_strength_of_legal_rights_index  \\\n",
       "11970                                   NaN   \n",
       "11971                                   NaN   \n",
       "11972                                   NaN   \n",
       "11973                                   NaN   \n",
       "11974                                   NaN   \n",
       "...                                     ...   \n",
       "12028                              5.507853   \n",
       "12029                              5.685864   \n",
       "12030                                   NaN   \n",
       "12031                                   NaN   \n",
       "12032                                   NaN   \n",
       "\n",
       "       world_terrestrial_and_marine_protected_areas  world_tree_cover_loss  \\\n",
       "11970                                           NaN                    NaN   \n",
       "11971                                           NaN                    NaN   \n",
       "11972                                           NaN                    NaN   \n",
       "11973                                           NaN                    NaN   \n",
       "11974                                           NaN                    NaN   \n",
       "...                                             ...                    ...   \n",
       "12028                                     14.337515                    NaN   \n",
       "12029                                     14.599801                    NaN   \n",
       "12030                                     14.787111                    NaN   \n",
       "12031                                     14.552260                    NaN   \n",
       "12032                                           NaN                    NaN   \n",
       "\n",
       "       world_unemployment  world_unmet_need_for_contraception  \\\n",
       "11970                 NaN                                 NaN   \n",
       "11971                 NaN                                 NaN   \n",
       "11972                 NaN                                 NaN   \n",
       "11973                 NaN                                 NaN   \n",
       "11974                 NaN                                 NaN   \n",
       "...                   ...                                 ...   \n",
       "12028            5.699076                                 NaN   \n",
       "12029            5.543161                                 NaN   \n",
       "12030            6.898273                                 NaN   \n",
       "12031            6.201871                                 NaN   \n",
       "12032            5.772710                                 NaN   \n",
       "\n",
       "       world_voice_and_accountability  world_water_quality  \n",
       "11970                             NaN                  NaN  \n",
       "11971                             NaN                  NaN  \n",
       "11972                             NaN                  NaN  \n",
       "11973                             NaN                  NaN  \n",
       "11974                             NaN                  NaN  \n",
       "...                               ...                  ...  \n",
       "12028                             NaN                  NaN  \n",
       "12029                             NaN                  NaN  \n",
       "12030                             NaN                  NaN  \n",
       "12031                             NaN                  NaN  \n",
       "12032                             NaN                  NaN  \n",
       "\n",
       "[63 rows x 72 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "worlddf.columns = ['world_' + column if column != 'year' else column for column in worlddf.columns]\n",
    "worlddf"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e968a22-4b07-4fe8-b6fa-21bec4569645",
   "metadata": {},
   "source": [
    "# 2 I"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "9462fe76-2fcb-4c24-9357-c7ad053e5dc2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# I believe that the merge is going to many to many\n",
    "\n",
    "merge = pd.merge(test, vdem, on = ['country_code', 'year'],\n",
    "                  how = 'outer', validate = 'many_to_many', indicator= 'matched')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d14726be-716d-482f-a7c9-5fdfa39daf7a",
   "metadata": {},
   "source": [
    "# 2 J"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "ce679dbd-2045-44e0-982b-24d13707a854",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matched\n",
       "both          9976\n",
       "left_only     2183\n",
       "right_only     395\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merge.value_counts('matched')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "920dbd44-a2e7-43f8-882a-e9b8267b7aa3",
   "metadata": {},
   "outputs": [],
   "source": [
    "wb_only = merge.query('matched == \"left_only\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "140d5d9e-5d0e-4eb7-b0cc-610a7f93d999",
   "metadata": {},
   "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>country_name_wb</th>\n",
       "      <th>country_code</th>\n",
       "      <th>year</th>\n",
       "      <th>access_to_clean_fuels_and_technologies_for_cooking</th>\n",
       "      <th>access_to_electricity</th>\n",
       "      <th>agricultural_land</th>\n",
       "      <th>agriculture</th>\n",
       "      <th>annual_freshwater_withdrawals</th>\n",
       "      <th>annualized_average_growth_rate_in_per_capita_real_survey</th>\n",
       "      <th>cause_of_death</th>\n",
       "      <th>...</th>\n",
       "      <th>strength_of_legal_rights_index</th>\n",
       "      <th>terrestrial_and_marine_protected_areas</th>\n",
       "      <th>tree_cover_loss</th>\n",
       "      <th>unemployment</th>\n",
       "      <th>unmet_need_for_contraception</th>\n",
       "      <th>voice_and_accountability</th>\n",
       "      <th>water_quality</th>\n",
       "      <th>country_name_vdem</th>\n",
       "      <th>democracy</th>\n",
       "      <th>matched</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.637257</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.751587</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>left_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>Albania</td>\n",
       "      <td>ALB</td>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.628032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.175197</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.808</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.139466</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>left_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>DZA</td>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.384084</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.400036</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.550</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.003874</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>left_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>AND</td>\n",
       "      <td>1960</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>left_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>AND</td>\n",
       "      <td>1961</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55.319149</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>left_only</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\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>11906</th>\n",
       "      <td>Venezuela, RB</td>\n",
       "      <td>VEN</td>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.000859</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.328</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.533926</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>left_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11969</th>\n",
       "      <td>Vietnam</td>\n",
       "      <td>VNM</td>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.877108</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.929507</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.923</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.288703</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>left_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12032</th>\n",
       "      <td>Yemen, Rep.</td>\n",
       "      <td>YEM</td>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.605801</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.590</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.618616</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>left_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12095</th>\n",
       "      <td>Zambia</td>\n",
       "      <td>ZMB</td>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.388658</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41.259399</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.131</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.089141</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>left_only</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12158</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.945</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.102206</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>left_only</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2183 rows × 77 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country_name_wb country_code  year  \\\n",
       "62        Afghanistan          AFG  2022   \n",
       "125           Albania          ALB  2022   \n",
       "188           Algeria          DZA  2022   \n",
       "189           Andorra          AND  1960   \n",
       "190           Andorra          AND  1961   \n",
       "...               ...          ...   ...   \n",
       "11906   Venezuela, RB          VEN  2022   \n",
       "11969         Vietnam          VNM  2022   \n",
       "12032     Yemen, Rep.          YEM  2022   \n",
       "12095          Zambia          ZMB  2022   \n",
       "12158        Zimbabwe          ZWE  2022   \n",
       "\n",
       "       access_to_clean_fuels_and_technologies_for_cooking  \\\n",
       "62                                                   NaN    \n",
       "125                                                  NaN    \n",
       "188                                                  NaN    \n",
       "189                                                  NaN    \n",
       "190                                                  NaN    \n",
       "...                                                  ...    \n",
       "11906                                                NaN    \n",
       "11969                                                NaN    \n",
       "12032                                                NaN    \n",
       "12095                                                NaN    \n",
       "12158                                                NaN    \n",
       "\n",
       "       access_to_electricity  agricultural_land  agriculture  \\\n",
       "62                       NaN                NaN          NaN   \n",
       "125                      NaN                NaN    18.628032   \n",
       "188                      NaN                NaN    11.384084   \n",
       "189                      NaN                NaN          NaN   \n",
       "190                      NaN          55.319149          NaN   \n",
       "...                      ...                ...          ...   \n",
       "11906                    NaN                NaN          NaN   \n",
       "11969                    NaN                NaN    11.877108   \n",
       "12032                    NaN                NaN          NaN   \n",
       "12095                    NaN                NaN     3.388658   \n",
       "12158                    NaN                NaN          NaN   \n",
       "\n",
       "       annual_freshwater_withdrawals  \\\n",
       "62                               NaN   \n",
       "125                              NaN   \n",
       "188                              NaN   \n",
       "189                              NaN   \n",
       "190                              NaN   \n",
       "...                              ...   \n",
       "11906                            NaN   \n",
       "11969                            NaN   \n",
       "12032                            NaN   \n",
       "12095                            NaN   \n",
       "12158                            NaN   \n",
       "\n",
       "       annualized_average_growth_rate_in_per_capita_real_survey  \\\n",
       "62                                                   NaN          \n",
       "125                                                  NaN          \n",
       "188                                                  NaN          \n",
       "189                                                  NaN          \n",
       "190                                                  NaN          \n",
       "...                                                  ...          \n",
       "11906                                                NaN          \n",
       "11969                                                NaN          \n",
       "12032                                                NaN          \n",
       "12095                                                NaN          \n",
       "12158                                                NaN          \n",
       "\n",
       "       cause_of_death  ...  strength_of_legal_rights_index  \\\n",
       "62                NaN  ...                             NaN   \n",
       "125               NaN  ...                             NaN   \n",
       "188               NaN  ...                             NaN   \n",
       "189               NaN  ...                             NaN   \n",
       "190               NaN  ...                             NaN   \n",
       "...               ...  ...                             ...   \n",
       "11906             NaN  ...                             NaN   \n",
       "11969             NaN  ...                             NaN   \n",
       "12032             NaN  ...                             NaN   \n",
       "12095             NaN  ...                             NaN   \n",
       "12158             NaN  ...                             NaN   \n",
       "\n",
       "       terrestrial_and_marine_protected_areas  tree_cover_loss  unemployment  \\\n",
       "62                                   3.637257              NaN           NaN   \n",
       "125                                 14.175197              NaN        11.808   \n",
       "188                                  4.400036              NaN        11.550   \n",
       "189                                       NaN              NaN           NaN   \n",
       "190                                       NaN              NaN           NaN   \n",
       "...                                       ...              ...           ...   \n",
       "11906                               39.000859              NaN         5.328   \n",
       "11969                                2.929507              NaN         1.923   \n",
       "12032                                0.605801              NaN        13.590   \n",
       "12095                               41.259399              NaN         6.131   \n",
       "12158                               27.214747              NaN         7.945   \n",
       "\n",
       "       unmet_need_for_contraception  voice_and_accountability  water_quality  \\\n",
       "62                              NaN                 -1.751587            NaN   \n",
       "125                             NaN                  0.139466            NaN   \n",
       "188                             NaN                 -1.003874            NaN   \n",
       "189                             NaN                       NaN            NaN   \n",
       "190                             NaN                       NaN            NaN   \n",
       "...                             ...                       ...            ...   \n",
       "11906                           NaN                 -1.533926            NaN   \n",
       "11969                           NaN                 -1.288703            NaN   \n",
       "12032                           NaN                 -1.618616            NaN   \n",
       "12095                           NaN                 -0.089141            NaN   \n",
       "12158                           NaN                 -1.102206            NaN   \n",
       "\n",
       "       country_name_vdem  democracy    matched  \n",
       "62                   NaN        NaN  left_only  \n",
       "125                  NaN        NaN  left_only  \n",
       "188                  NaN        NaN  left_only  \n",
       "189                  NaN        NaN  left_only  \n",
       "190                  NaN        NaN  left_only  \n",
       "...                  ...        ...        ...  \n",
       "11906                NaN        NaN  left_only  \n",
       "11969                NaN        NaN  left_only  \n",
       "12032                NaN        NaN  left_only  \n",
       "12095                NaN        NaN  left_only  \n",
       "12158                NaN        NaN  left_only  \n",
       "\n",
       "[2183 rows x 77 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wb_only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "2e6c4539-d588-4e7c-99da-0477c20e7a31",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = wb_only.groupby(['country_code', 'country_name_wb'])['year'].agg(['min', 'max'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "3737ee99-0489-4fa4-8566-0fd33e71d25f",
   "metadata": {},
   "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></th>\n",
       "      <th>min</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_code</th>\n",
       "      <th>country_name_wb</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AFG</th>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>2022</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AGO</th>\n",
       "      <th>Angola</th>\n",
       "      <td>2022</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALB</th>\n",
       "      <th>Albania</th>\n",
       "      <td>2022</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AND</th>\n",
       "      <th>Andorra</th>\n",
       "      <td>1960</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ARE</th>\n",
       "      <th>United Arab Emirates</th>\n",
       "      <td>1960</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WSM</th>\n",
       "      <th>Samoa</th>\n",
       "      <td>1960</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YEM</th>\n",
       "      <th>Yemen, Rep.</th>\n",
       "      <td>2022</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZAF</th>\n",
       "      <th>South Africa</th>\n",
       "      <td>2022</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZMB</th>\n",
       "      <th>Zambia</th>\n",
       "      <td>2022</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZWE</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>2022</td>\n",
       "      <td>2022</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>193 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    min   max\n",
       "country_code country_name_wb                 \n",
       "AFG          Afghanistan           2022  2022\n",
       "AGO          Angola                2022  2022\n",
       "ALB          Albania               2022  2022\n",
       "AND          Andorra               1960  2022\n",
       "ARE          United Arab Emirates  1960  2022\n",
       "...                                 ...   ...\n",
       "WSM          Samoa                 1960  2022\n",
       "YEM          Yemen, Rep.           2022  2022\n",
       "ZAF          South Africa          2022  2022\n",
       "ZMB          Zambia                2022  2022\n",
       "ZWE          Zimbabwe              2022  2022\n",
       "\n",
       "[193 rows x 2 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.head(200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "4872d3e3-3045-4987-bfa5-64929739abdb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                              min   max\n",
      "country_code country_name_wb                           \n",
      "AFG          Afghanistan                     2022  2022\n",
      "AGO          Angola                          2022  2022\n",
      "ALB          Albania                         2022  2022\n",
      "AND          Andorra                         1960  2022\n",
      "ARE          United Arab Emirates            1960  2022\n",
      "ARG          Argentina                       2022  2022\n",
      "ARM          Armenia                         1960  2022\n",
      "ATG          Antigua and Barbuda             1960  2022\n",
      "AUS          Australia                       2022  2022\n",
      "AUT          Austria                         2022  2022\n",
      "AZE          Azerbaijan                      1960  2022\n",
      "BDI          Burundi                         2022  2022\n",
      "BEL          Belgium                         2022  2022\n",
      "BEN          Benin                           2022  2022\n",
      "BFA          Burkina Faso                    2022  2022\n",
      "BGD          Bangladesh                      1960  2022\n",
      "BGR          Bulgaria                        2022  2022\n",
      "BHR          Bahrain                         2022  2022\n",
      "BHS          Bahamas, The                    1960  2022\n",
      "BIH          Bosnia and Herzegovina          1960  2022\n",
      "BLR          Belarus                         1960  2022\n",
      "BLZ          Belize                          1960  2022\n",
      "BOL          Bolivia                         2022  2022\n",
      "BRA          Brazil                          2022  2022\n",
      "BRB          Barbados                        2022  2022\n",
      "BRN          Brunei Darussalam               1960  2022\n",
      "BTN          Bhutan                          2022  2022\n",
      "BWA          Botswana                        2022  2022\n",
      "CAF          Central African Republic        2022  2022\n",
      "CAN          Canada                          2022  2022\n",
      "CHE          Switzerland                     2022  2022\n",
      "CHL          Chile                           2022  2022\n",
      "CHN          China                           2022  2022\n",
      "CIV          Cote d'Ivoire                   2022  2022\n",
      "CMR          Cameroon                        1960  2022\n",
      "COD          Congo, Dem. Rep.                2022  2022\n",
      "COG          Congo, Rep.                     2022  2022\n",
      "COL          Colombia                        2022  2022\n",
      "COM          Comoros                         2022  2022\n",
      "CPV          Cabo Verde                      2022  2022\n",
      "CRI          Costa Rica                      2022  2022\n",
      "CUB          Cuba                            2022  2022\n",
      "CYP          Cyprus                          2022  2022\n",
      "CZE          Czechia                         2022  2022\n",
      "DEU          Germany                         2022  2022\n",
      "DJI          Djibouti                        2022  2022\n",
      "DMA          Dominica                        1960  2022\n",
      "DNK          Denmark                         2022  2022\n",
      "DOM          Dominican Republic              2022  2022\n",
      "DZA          Algeria                         2022  2022\n",
      "ECU          Ecuador                         2022  2022\n",
      "EGY          Egypt, Arab Rep.                2022  2022\n",
      "ERI          Eritrea                         2022  2022\n",
      "ESP          Spain                           2022  2022\n",
      "EST          Estonia                         1960  2022\n",
      "ETH          Ethiopia                        2022  2022\n",
      "FIN          Finland                         2022  2022\n",
      "FJI          Fiji                            2022  2022\n",
      "FRA          France                          2022  2022\n",
      "FSM          Micronesia, Fed. Sts.           1960  2022\n",
      "GAB          Gabon                           2022  2022\n",
      "GBR          United Kingdom                  2022  2022\n",
      "GEO          Georgia                         1960  2022\n",
      "GHA          Ghana                           2022  2022\n",
      "GIN          Guinea                          2022  2022\n",
      "GMB          Gambia, The                     2022  2022\n",
      "GNB          Guinea-Bissau                   2022  2022\n",
      "GNQ          Equatorial Guinea               2022  2022\n",
      "GRC          Greece                          2022  2022\n",
      "GRD          Grenada                         1960  2022\n",
      "GTM          Guatemala                       2022  2022\n",
      "GUY          Guyana                          2022  2022\n",
      "HND          Honduras                        2022  2022\n",
      "HRV          Croatia                         1960  2022\n",
      "HTI          Haiti                           2022  2022\n",
      "HUN          Hungary                         2022  2022\n",
      "IDN          Indonesia                       2022  2022\n",
      "IND          India                           2022  2022\n",
      "IRL          Ireland                         2022  2022\n",
      "IRN          Iran, Islamic Rep.              2022  2022\n",
      "IRQ          Iraq                            2022  2022\n",
      "ISL          Iceland                         2022  2022\n",
      "ISR          Israel                          2022  2022\n",
      "ITA          Italy                           2022  2022\n",
      "JAM          Jamaica                         2022  2022\n",
      "JOR          Jordan                          2022  2022\n",
      "JPN          Japan                           2022  2022\n",
      "KAZ          Kazakhstan                      1960  2022\n",
      "KEN          Kenya                           2022  2022\n",
      "KGZ          Kyrgyz Republic                 1960  2022\n",
      "KHM          Cambodia                        2022  2022\n",
      "KIR          Kiribati                        1960  2022\n",
      "KNA          St. Kitts and Nevis             1960  2022\n",
      "KOR          Korea, Rep.                     2022  2022\n",
      "KWT          Kuwait                          2022  2022\n",
      "LAO          Lao PDR                         2022  2022\n",
      "LBN          Lebanon                         2022  2022\n",
      "LBR          Liberia                         2022  2022\n",
      "LBY          Libya                           2022  2022\n",
      "LCA          St. Lucia                       1960  2022\n",
      "LIE          Liechtenstein                   1960  2022\n",
      "LKA          Sri Lanka                       2022  2022\n",
      "LSO          Lesotho                         2022  2022\n",
      "LTU          Lithuania                       1960  2022\n",
      "LUX          Luxembourg                      2022  2022\n",
      "LVA          Latvia                          1960  2022\n",
      "MAR          Morocco                         2022  2022\n",
      "MCO          Monaco                          1960  2022\n",
      "MDA          Moldova                         1960  2022\n",
      "MDG          Madagascar                      2022  2022\n",
      "MDV          Maldives                        2022  2022\n",
      "MEX          Mexico                          2022  2022\n",
      "MHL          Marshall Islands                1960  2022\n",
      "MKD          North Macedonia                 1960  2022\n",
      "MLI          Mali                            2022  2022\n",
      "MLT          Malta                           2022  2022\n",
      "MMR          Myanmar                         2022  2022\n",
      "MNE          Montenegro                      1960  2022\n",
      "MNG          Mongolia                        2022  2022\n",
      "MOZ          Mozambique                      2022  2022\n",
      "MRT          Mauritania                      2022  2022\n",
      "MUS          Mauritius                       2022  2022\n",
      "MWI          Malawi                          2022  2022\n",
      "MYS          Malaysia                        2022  2022\n",
      "NAM          Namibia                         2022  2022\n",
      "NER          Niger                           2022  2022\n",
      "NGA          Nigeria                         2022  2022\n",
      "NIC          Nicaragua                       2022  2022\n",
      "NLD          Netherlands                     2022  2022\n",
      "NOR          Norway                          2022  2022\n",
      "NPL          Nepal                           2022  2022\n",
      "NRU          Nauru                           1960  2022\n",
      "NZL          New Zealand                     2022  2022\n",
      "OMN          Oman                            2022  2022\n",
      "PAK          Pakistan                        2022  2022\n",
      "PAN          Panama                          2022  2022\n",
      "PER          Peru                            2022  2022\n",
      "PHL          Philippines                     2022  2022\n",
      "PLW          Palau                           1960  2022\n",
      "PNG          Papua New Guinea                2022  2022\n",
      "POL          Poland                          2022  2022\n",
      "PRK          Korea, Dem. People's Rep.       2022  2022\n",
      "PRT          Portugal                        2022  2022\n",
      "PRY          Paraguay                        2022  2022\n",
      "QAT          Qatar                           2022  2022\n",
      "ROU          Romania                         2022  2022\n",
      "RUS          Russian Federation              2022  2022\n",
      "RWA          Rwanda                          2022  2022\n",
      "SAU          Saudi Arabia                    2022  2022\n",
      "SDN          Sudan                           2022  2022\n",
      "SEN          Senegal                         2022  2022\n",
      "SGP          Singapore                       2022  2022\n",
      "SLB          Solomon Islands                 2022  2022\n",
      "SLE          Sierra Leone                    2022  2022\n",
      "SLV          El Salvador                     2022  2022\n",
      "SMR          San Marino                      1960  2022\n",
      "SOM          Somalia                         2022  2022\n",
      "SRB          Serbia                          2022  2022\n",
      "SSD          South Sudan                     1960  2022\n",
      "STP          Sao Tome and Principe           2022  2022\n",
      "SUR          Suriname                        2022  2022\n",
      "SVK          Slovak Republic                 1960  2022\n",
      "SVN          Slovenia                        1960  2022\n",
      "SWE          Sweden                          2022  2022\n",
      "SWZ          Eswatini                        2022  2022\n",
      "SYC          Seychelles                      2022  2022\n",
      "SYR          Syrian Arab Republic            2022  2022\n",
      "TCD          Chad                            2022  2022\n",
      "TGO          Togo                            2022  2022\n",
      "THA          Thailand                        2022  2022\n",
      "TJK          Tajikistan                      1960  2022\n",
      "TKM          Turkmenistan                    1960  2022\n",
      "TLS          Timor-Leste                     2022  2022\n",
      "TON          Tonga                           1960  2022\n",
      "TTO          Trinidad and Tobago             2022  2022\n",
      "TUN          Tunisia                         2022  2022\n",
      "TUR          Turkiye                         2022  2022\n",
      "TUV          Tuvalu                          1960  2022\n",
      "TZA          Tanzania                        2022  2022\n",
      "UGA          Uganda                          2022  2022\n",
      "UKR          Ukraine                         1960  2022\n",
      "URY          Uruguay                         2022  2022\n",
      "USA          United States                   2022  2022\n",
      "UZB          Uzbekistan                      1960  2022\n",
      "VCT          St. Vincent and the Grenadines  1960  2022\n",
      "VEN          Venezuela, RB                   2022  2022\n",
      "VNM          Vietnam                         2022  2022\n",
      "VUT          Vanuatu                         2022  2022\n",
      "WSM          Samoa                           1960  2022\n",
      "YEM          Yemen, Rep.                     2022  2022\n",
      "ZAF          South Africa                    2022  2022\n",
      "ZMB          Zambia                          2022  2022\n",
      "ZWE          Zimbabwe                        2022  2022\n"
     ]
    }
   ],
   "source": [
    "with pd.option_context('display.max_rows', None,):\n",
    "    print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "65773fb2-3e49-4b3c-8a95-d62e0e2fe8ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "vdem_only = merge.query('matched == \"right_only\"')\n",
    "y = vdem_only.groupby(['country_code', 'country_name_vdem'])['year'].agg(['min', 'max'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "57694c08-b081-49eb-ba4e-cd5121995f58",
   "metadata": {},
   "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></th>\n",
       "      <th>min</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_code</th>\n",
       "      <th>country_name_vdem</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DDR</th>\n",
       "      <th>German Democratic Republic</th>\n",
       "      <td>1960</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HKG</th>\n",
       "      <th>Hong Kong</th>\n",
       "      <td>1960</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PSE</th>\n",
       "      <th>Palestine/West Bank</th>\n",
       "      <td>1967</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PSG</th>\n",
       "      <th>Palestine/Gaza</th>\n",
       "      <td>1960</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SML</th>\n",
       "      <th>Somaliland</th>\n",
       "      <td>1991</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TWN</th>\n",
       "      <th>Taiwan</th>\n",
       "      <td>1960</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VDR</th>\n",
       "      <th>Republic of Vietnam</th>\n",
       "      <td>1960</td>\n",
       "      <td>1975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XKX</th>\n",
       "      <th>Kosovo</th>\n",
       "      <td>1999</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YMD</th>\n",
       "      <th>South Yemen</th>\n",
       "      <td>1960</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZZB</th>\n",
       "      <th>Zanzibar</th>\n",
       "      <td>1960</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          min   max\n",
       "country_code country_name_vdem                     \n",
       "DDR          German Democratic Republic  1960  1990\n",
       "HKG          Hong Kong                   1960  2021\n",
       "PSE          Palestine/West Bank         1967  2021\n",
       "PSG          Palestine/Gaza              1960  2021\n",
       "SML          Somaliland                  1991  2021\n",
       "TWN          Taiwan                      1960  2021\n",
       "VDR          Republic of Vietnam         1960  1975\n",
       "XKX          Kosovo                      1999  2021\n",
       "YMD          South Yemen                 1960  1990\n",
       "ZZB          Zanzibar                    1960  2021"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05e3e15a-efae-4447-a4bc-4a0d3190e8c3",
   "metadata": {},
   "source": [
    "# 2 K"
   ]
  },
  {
   "cell_type": "raw",
   "id": "348c6277-e534-4e37-bd29-48445f788bb9",
   "metadata": {},
   "source": [
    "# k\n",
    "Yes Vietnam and Republic of Vietnam, Palestine, German Democractic Republic, Hong Kong. The pattern is clear that they vdem has countries that are not always reconginized as a country dependingon national stances and political views."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36d8e205-404a-4020-927c-cf2eea989945",
   "metadata": {},
   "source": [
    "# 2 L"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "63a0c73a-3383-4fb5-b4d5-7d0531f8ec07",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_merge = pd.merge(test, vdem, on = ['country_code', 'year'],\n",
    "                  how = 'inner')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "faf2be87-69c5-4cfd-b1a6-08459748579f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>country_name_wb</th>\n",
       "      <th>country_code</th>\n",
       "      <th>year</th>\n",
       "      <th>access_to_clean_fuels_and_technologies_for_cooking</th>\n",
       "      <th>access_to_electricity</th>\n",
       "      <th>agricultural_land</th>\n",
       "      <th>agriculture</th>\n",
       "      <th>annual_freshwater_withdrawals</th>\n",
       "      <th>annualized_average_growth_rate_in_per_capita_real_survey</th>\n",
       "      <th>cause_of_death</th>\n",
       "      <th>...</th>\n",
       "      <th>scientific_and_technical_journal_articles</th>\n",
       "      <th>strength_of_legal_rights_index</th>\n",
       "      <th>terrestrial_and_marine_protected_areas</th>\n",
       "      <th>tree_cover_loss</th>\n",
       "      <th>unemployment</th>\n",
       "      <th>unmet_need_for_contraception</th>\n",
       "      <th>voice_and_accountability</th>\n",
       "      <th>water_quality</th>\n",
       "      <th>country_name_vdem</th>\n",
       "      <th>democracy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1960</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>0.080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1961</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>57.878356</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>0.083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1962</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>57.955016</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>0.082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1963</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.031676</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>0.085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "      <td>1964</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.116002</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>0.137</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\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>9971</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>2017</td>\n",
       "      <td>29.8</td>\n",
       "      <td>43.979065</td>\n",
       "      <td>41.876696</td>\n",
       "      <td>8.340969</td>\n",
       "      <td>27.234910</td>\n",
       "      <td>-3.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>334.71</td>\n",
       "      <td>5.0</td>\n",
       "      <td>27.214585</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.279</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.195905</td>\n",
       "      <td>76.5</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>0.295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9972</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>2018</td>\n",
       "      <td>30.0</td>\n",
       "      <td>45.400288</td>\n",
       "      <td>41.876696</td>\n",
       "      <td>7.319375</td>\n",
       "      <td>30.761677</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>406.23</td>\n",
       "      <td>5.0</td>\n",
       "      <td>27.214585</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.784</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.136798</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>0.305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9973</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>2019</td>\n",
       "      <td>30.2</td>\n",
       "      <td>46.682095</td>\n",
       "      <td>41.876696</td>\n",
       "      <td>9.819262</td>\n",
       "      <td>30.761677</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47.647301</td>\n",
       "      <td>...</td>\n",
       "      <td>431.62</td>\n",
       "      <td>6.0</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.370</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.163669</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>0.293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9974</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>2020</td>\n",
       "      <td>30.3</td>\n",
       "      <td>52.747667</td>\n",
       "      <td>41.876696</td>\n",
       "      <td>8.772859</td>\n",
       "      <td>30.761677</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>480.16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.898</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.113408</td>\n",
       "      <td>83.3</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>0.293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9975</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>2021</td>\n",
       "      <td>30.3</td>\n",
       "      <td>48.979927</td>\n",
       "      <td>41.876696</td>\n",
       "      <td>8.849899</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27.214747</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.067</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.135830</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>0.291</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9976 rows × 76 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     country_name_wb country_code  year  \\\n",
       "0        Afghanistan          AFG  1960   \n",
       "1        Afghanistan          AFG  1961   \n",
       "2        Afghanistan          AFG  1962   \n",
       "3        Afghanistan          AFG  1963   \n",
       "4        Afghanistan          AFG  1964   \n",
       "...              ...          ...   ...   \n",
       "9971        Zimbabwe          ZWE  2017   \n",
       "9972        Zimbabwe          ZWE  2018   \n",
       "9973        Zimbabwe          ZWE  2019   \n",
       "9974        Zimbabwe          ZWE  2020   \n",
       "9975        Zimbabwe          ZWE  2021   \n",
       "\n",
       "      access_to_clean_fuels_and_technologies_for_cooking  \\\n",
       "0                                                   NaN    \n",
       "1                                                   NaN    \n",
       "2                                                   NaN    \n",
       "3                                                   NaN    \n",
       "4                                                   NaN    \n",
       "...                                                 ...    \n",
       "9971                                               29.8    \n",
       "9972                                               30.0    \n",
       "9973                                               30.2    \n",
       "9974                                               30.3    \n",
       "9975                                               30.3    \n",
       "\n",
       "      access_to_electricity  agricultural_land  agriculture  \\\n",
       "0                       NaN                NaN          NaN   \n",
       "1                       NaN          57.878356          NaN   \n",
       "2                       NaN          57.955016          NaN   \n",
       "3                       NaN          58.031676          NaN   \n",
       "4                       NaN          58.116002          NaN   \n",
       "...                     ...                ...          ...   \n",
       "9971              43.979065          41.876696     8.340969   \n",
       "9972              45.400288          41.876696     7.319375   \n",
       "9973              46.682095          41.876696     9.819262   \n",
       "9974              52.747667          41.876696     8.772859   \n",
       "9975              48.979927          41.876696     8.849899   \n",
       "\n",
       "      annual_freshwater_withdrawals  \\\n",
       "0                               NaN   \n",
       "1                               NaN   \n",
       "2                               NaN   \n",
       "3                               NaN   \n",
       "4                               NaN   \n",
       "...                             ...   \n",
       "9971                      27.234910   \n",
       "9972                      30.761677   \n",
       "9973                      30.761677   \n",
       "9974                      30.761677   \n",
       "9975                            NaN   \n",
       "\n",
       "      annualized_average_growth_rate_in_per_capita_real_survey  \\\n",
       "0                                                   NaN          \n",
       "1                                                   NaN          \n",
       "2                                                   NaN          \n",
       "3                                                   NaN          \n",
       "4                                                   NaN          \n",
       "...                                                 ...          \n",
       "9971                                               -3.5          \n",
       "9972                                                NaN          \n",
       "9973                                                NaN          \n",
       "9974                                                NaN          \n",
       "9975                                                NaN          \n",
       "\n",
       "      cause_of_death  ...  scientific_and_technical_journal_articles  \\\n",
       "0                NaN  ...                                        NaN   \n",
       "1                NaN  ...                                        NaN   \n",
       "2                NaN  ...                                        NaN   \n",
       "3                NaN  ...                                        NaN   \n",
       "4                NaN  ...                                        NaN   \n",
       "...              ...  ...                                        ...   \n",
       "9971             NaN  ...                                     334.71   \n",
       "9972             NaN  ...                                     406.23   \n",
       "9973       47.647301  ...                                     431.62   \n",
       "9974             NaN  ...                                     480.16   \n",
       "9975             NaN  ...                                        NaN   \n",
       "\n",
       "      strength_of_legal_rights_index  terrestrial_and_marine_protected_areas  \\\n",
       "0                                NaN                                     NaN   \n",
       "1                                NaN                                     NaN   \n",
       "2                                NaN                                     NaN   \n",
       "3                                NaN                                     NaN   \n",
       "4                                NaN                                     NaN   \n",
       "...                              ...                                     ...   \n",
       "9971                             5.0                               27.214585   \n",
       "9972                             5.0                               27.214585   \n",
       "9973                             6.0                               27.214747   \n",
       "9974                             NaN                               27.214747   \n",
       "9975                             NaN                               27.214747   \n",
       "\n",
       "      tree_cover_loss  unemployment  unmet_need_for_contraception  \\\n",
       "0                 NaN           NaN                           NaN   \n",
       "1                 NaN           NaN                           NaN   \n",
       "2                 NaN           NaN                           NaN   \n",
       "3                 NaN           NaN                           NaN   \n",
       "4                 NaN           NaN                           NaN   \n",
       "...               ...           ...                           ...   \n",
       "9971              NaN         6.279                           NaN   \n",
       "9972              NaN         6.784                           NaN   \n",
       "9973              NaN         7.370                           NaN   \n",
       "9974              NaN         7.898                           NaN   \n",
       "9975              NaN         8.067                           NaN   \n",
       "\n",
       "      voice_and_accountability  water_quality  country_name_vdem  democracy  \n",
       "0                          NaN            NaN        Afghanistan      0.080  \n",
       "1                          NaN            NaN        Afghanistan      0.083  \n",
       "2                          NaN            NaN        Afghanistan      0.082  \n",
       "3                          NaN            NaN        Afghanistan      0.085  \n",
       "4                          NaN            NaN        Afghanistan      0.137  \n",
       "...                        ...            ...                ...        ...  \n",
       "9971                 -1.195905           76.5           Zimbabwe      0.295  \n",
       "9972                 -1.136798            NaN           Zimbabwe      0.305  \n",
       "9973                 -1.163669            NaN           Zimbabwe      0.293  \n",
       "9974                 -1.113408           83.3           Zimbabwe      0.293  \n",
       "9975                 -1.135830            NaN           Zimbabwe      0.291  \n",
       "\n",
       "[9976 rows x 76 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_merge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "cc0959cd-57c8-49a8-a53e-4dac12287156",
   "metadata": {},
   "outputs": [],
   "source": [
    "# newmerge, worlddf, country\n",
    "new_merge.to_csv(\"timeseries.csv\")\n",
    "worlddf.to_csv(\"world.csv\")\n",
    "country.to_csv(\"country.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e24a18a6-4650-4845-8965-1a67505cfb9b",
   "metadata": {},
   "source": [
    "# 3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79762811-80b2-45b0-a87f-3c764648b4b3",
   "metadata": {},
   "source": [
    "###### \n",
    "timeseries has country name twice, fails timeseries is all atomic, PK will be country code and year world is all atomic, PK is just the year country is all atomic, PK is country code. This data is not in third normal form because of timeseries having country name twice. Once this is removed it will be in third normal form because everything is atomic and there are no transitive dependencies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "d0923922-6637-4db9-8d8c-84dc11d05f6d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "timeseries = new_merge.drop(columns = ['country_name_vdem'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ab3329c-1518-4e37-b4c6-ce0b9913def2",
   "metadata": {},
   "source": [
    "# 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "eb2aeb1e-a2da-471d-a66e-663e3ee38f62",
   "metadata": {},
   "outputs": [],
   "source": [
    "dbserver = psycopg2.connect(\n",
    "    host = 'postgres',\n",
    "    user = 'postgres',\n",
    "    password = POSTGRES_PASSWORD,\n",
    "    port = 5432\n",
    ")\n",
    "dbserver.autocommit = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "187fb80d-a800-4ac8-b651-91aeb23f5dbb",
   "metadata": {},
   "outputs": [],
   "source": [
    "cursor = dbserver.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "3e38f50b-80ef-4d21-ad51-4b720098415b",
   "metadata": {},
   "outputs": [],
   "source": [
    "try:\n",
    "    cursor.execute('CREATE DATABASE cardib')\n",
    "except:\n",
    "    cursor.execute('DROP DATABASE cardib')\n",
    "    cursor.execute('CREATE DATABASE cardib')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "4eb6e67c-6431-4646-bdd8-df6db643c067",
   "metadata": {},
   "outputs": [],
   "source": [
    "engine = create_engine('postgresql+psycopg2://{user}:{password}@{host}:{port}/{db}'.format(\n",
    "    user = 'postgres',\n",
    "    password = POSTGRES_PASSWORD,\n",
    "    host = 'postgres',\n",
    "    port = 5432,\n",
    "    db = 'cardib'\n",
    "))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "eb31e147-a5b4-47b0-a394-0525c78cdc73",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1256"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "timeseries.to_sql('timeseries', con=engine, index=False, chunksize=500, if_exists = 'replace')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "41e47505-ecf4-4eae-9b51-952ceee84c82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "63"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "worlddf.to_sql('world', con=engine, index=False, chunksize=1000, if_exists = 'replace')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "623558d3-5e70-46d7-9a8d-e77cb98d35d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "193"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country.to_sql('country', con=engine, index=False, chunksize=1000, if_exists = 'replace')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "6bfce68f-1091-4e9a-a5f1-961571cb46d7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "country_name_wb object\n",
      "country_code object\n",
      "year int64\n",
      "access_to_clean_fuels_and_technologies_for_cooking float64\n",
      "access_to_electricity float64\n",
      "agricultural_land float64\n",
      "agriculture float64\n",
      "annual_freshwater_withdrawals float64\n",
      "annualized_average_growth_rate_in_per_capita_real_survey float64\n",
      "cause_of_death float64\n",
      "children_in_employment float64\n",
      "co2_emissions float64\n",
      "coastal_protection float64\n",
      "control_of_corruption float64\n",
      "cooling_degree_days float64\n",
      "economic_and_social_rights_performance_score float64\n",
      "electricity_production_from_coal_sources float64\n",
      "energy_imports float64\n",
      "energy_intensity_level_of_primary_energy float64\n",
      "energy_use float64\n",
      "fertility_rate float64\n",
      "food_production_index float64\n",
      "forest_area float64\n",
      "fossil_fuel_energy_consumption float64\n",
      "freshwater_withdrawal float64\n",
      "gdp_growth float64\n",
      "ghg_net_emissions float64\n",
      "gini_index float64\n",
      "government_effectiveness float64\n",
      "government_expenditure_on_education float64\n",
      "gross_school_enrollment float64\n",
      "heat_index_35 float64\n",
      "heating_degree_days float64\n",
      "hospital_beds float64\n",
      "income_share_held_by_lowest_20pct float64\n",
      "individuals_using_the_internet float64\n",
      "labor_force_participation_rate float64\n",
      "land_surface_temperature float64\n",
      "life_expectancy_at_birth float64\n",
      "literacy_rate float64\n",
      "mammal_species float64\n",
      "mean_drought_index float64\n",
      "methane_emissions float64\n",
      "mortality_rate float64\n",
      "natural_resources_depletion float64\n",
      "net_forest_depletion float64\n",
      "net_migration float64\n",
      "nitrous_oxide_emissions float64\n",
      "patent_applications float64\n",
      "people_using_safely_managed_drinking_water_services float64\n",
      "people_using_safely_managed_sanitation_services float64\n",
      "pm2_5_air_pollution float64\n",
      "political_stability_and_absence_of_violence float64\n",
      "population_ages_65_and_above float64\n",
      "population_density float64\n",
      "poverty_headcount_ratio_at_national_poverty_lines float64\n",
      "prevalence_of_overweight float64\n",
      "prevalence_of_undernourishment float64\n",
      "primary_school_enrollment float64\n",
      "proportion_of_seats_held_by_women_in_national_parliament float64\n",
      "ratio_of_female_to_male_labor_force_participation_rate float64\n",
      "regulatory_quality float64\n",
      "renewable_electricity_output float64\n",
      "renewable_energy_consumption float64\n",
      "research_and_development_expenditure float64\n",
      "rule_of_law float64\n",
      "scientific_and_technical_journal_articles float64\n",
      "strength_of_legal_rights_index float64\n",
      "terrestrial_and_marine_protected_areas float64\n",
      "tree_cover_loss float64\n",
      "unemployment float64\n",
      "unmet_need_for_contraception float64\n",
      "voice_and_accountability float64\n",
      "water_quality float64\n",
      "democracy float64\n"
     ]
    }
   ],
   "source": [
    "for col in timeseries.columns:\n",
    "    print(col, timeseries[col].dtype)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "badcc869-91d3-4831-9708-ec502d0cf6d5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "year int64\n",
      "world_access_to_clean_fuels_and_technologies_for_cooking float64\n",
      "world_access_to_electricity float64\n",
      "world_agricultural_land float64\n",
      "world_agriculture float64\n",
      "world_annual_freshwater_withdrawals float64\n",
      "world_annualized_average_growth_rate_in_per_capita_real_survey float64\n",
      "world_cause_of_death float64\n",
      "world_children_in_employment float64\n",
      "world_co2_emissions float64\n",
      "world_coastal_protection float64\n",
      "world_control_of_corruption float64\n",
      "world_cooling_degree_days float64\n",
      "world_economic_and_social_rights_performance_score float64\n",
      "world_electricity_production_from_coal_sources float64\n",
      "world_energy_imports float64\n",
      "world_energy_intensity_level_of_primary_energy float64\n",
      "world_energy_use float64\n",
      "world_fertility_rate float64\n",
      "world_food_production_index float64\n",
      "world_forest_area float64\n",
      "world_fossil_fuel_energy_consumption float64\n",
      "world_freshwater_withdrawal float64\n",
      "world_gdp_growth float64\n",
      "world_ghg_net_emissions float64\n",
      "world_gini_index float64\n",
      "world_government_effectiveness float64\n",
      "world_government_expenditure_on_education float64\n",
      "world_gross_school_enrollment float64\n",
      "world_heat_index_35 float64\n",
      "world_heating_degree_days float64\n",
      "world_hospital_beds float64\n",
      "world_income_share_held_by_lowest_20pct float64\n",
      "world_individuals_using_the_internet float64\n",
      "world_labor_force_participation_rate float64\n",
      "world_land_surface_temperature float64\n",
      "world_life_expectancy_at_birth float64\n",
      "world_literacy_rate float64\n",
      "world_mammal_species float64\n",
      "world_mean_drought_index float64\n",
      "world_methane_emissions float64\n",
      "world_mortality_rate float64\n",
      "world_natural_resources_depletion float64\n",
      "world_net_forest_depletion float64\n",
      "world_net_migration float64\n",
      "world_nitrous_oxide_emissions float64\n",
      "world_patent_applications float64\n",
      "world_people_using_safely_managed_drinking_water_services float64\n",
      "world_people_using_safely_managed_sanitation_services float64\n",
      "world_pm2_5_air_pollution float64\n",
      "world_political_stability_and_absence_of_violence float64\n",
      "world_population_ages_65_and_above float64\n",
      "world_population_density float64\n",
      "world_poverty_headcount_ratio_at_national_poverty_lines float64\n",
      "world_prevalence_of_overweight float64\n",
      "world_prevalence_of_undernourishment float64\n",
      "world_primary_school_enrollment float64\n",
      "world_proportion_of_seats_held_by_women_in_national_parliament float64\n",
      "world_ratio_of_female_to_male_labor_force_participation_rate float64\n",
      "world_regulatory_quality float64\n",
      "world_renewable_electricity_output float64\n",
      "world_renewable_energy_consumption float64\n",
      "world_research_and_development_expenditure float64\n",
      "world_rule_of_law float64\n",
      "world_scientific_and_technical_journal_articles float64\n",
      "world_strength_of_legal_rights_index float64\n",
      "world_terrestrial_and_marine_protected_areas float64\n",
      "world_tree_cover_loss float64\n",
      "world_unemployment float64\n",
      "world_unmet_need_for_contraception float64\n",
      "world_voice_and_accountability float64\n",
      "world_water_quality float64\n"
     ]
    }
   ],
   "source": [
    "for col in worlddf.columns:\n",
    "    print(col, worlddf[col].dtype)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "9b727a9f-c710-4691-93a4-130ae4b43392",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "country_code        object\n",
       "country_name_wb     object\n",
       "country_longname    object\n",
       "currency_unit       object\n",
       "region              object\n",
       "income_group        object\n",
       "dtype: object"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20a9ca57-98fa-4249-bcb2-8ce7d524d1d6",
   "metadata": {},
   "source": [
    "# 5"
   ]
  },
  {
   "cell_type": "raw",
   "id": "e7b63928-5f8f-4e6a-a173-6b7b637291d1",
   "metadata": {},
   "source": [
    "Project World {\n",
    "  database_type: 'PostgreSQL'\n",
    "  Note: '''\n",
    "    # World statistics\n",
    "    This database was created by Jack Beerman. If there are problems it is his fault.\n",
    "  '''\n",
    "}\n",
    "Table country as CY {\n",
    "country_code        varchar [pk]\n",
    "country_name_wb     varchar \n",
    "country_longname    varchar\n",
    "currency_unit       varchar\n",
    "region              varchar\n",
    "income_group        varchar\n",
    "\n",
    "\n",
    "  note: \"Data on countries\"\n",
    "}\n",
    "Table world as WD{\n",
    "year int [pk]\n",
    "world_access_to_clean_fuels_and_technologies_for_cooking float\n",
    "world_access_to_electricity float\n",
    "world_agricultural_land float\n",
    "world_agriculture float\n",
    "world_annual_freshwater_withdrawals float\n",
    "world_annualized_average_growth_rate_in_per_capita_real_survey float\n",
    "world_cause_of_death float\n",
    "world_children_in_employment float\n",
    "world_co2_emissions float\n",
    "world_coastal_protection float\n",
    "world_control_of_corruption float\n",
    "world_cooling_degree_days float\n",
    "world_economic_and_social_rights_performance_score float\n",
    "world_electricity_production_from_coal_sources float\n",
    "world_energy_imports float\n",
    "world_energy_intensity_level_of_primary_energy float\n",
    "world_energy_use float\n",
    "world_fertility_rate float\n",
    "world_food_production_index float\n",
    "world_forest_area float\n",
    "world_fossil_fuel_energy_consumption float\n",
    "world_freshwater_withdrawal float\n",
    "world_gdp_growth float\n",
    "world_ghg_net_emissions float\n",
    "world_gini_index float\n",
    "world_government_effectiveness float\n",
    "world_government_expenditure_on_education float\n",
    "world_gross_school_enrollment float\n",
    "world_heat_index_35 float\n",
    "world_heating_degree_days float\n",
    "world_hospital_beds float\n",
    "world_income_share_held_by_lowest_20pct float\n",
    "world_individuals_using_the_internet float\n",
    "world_labor_force_participation_rate float\n",
    "world_land_surface_temperature float\n",
    "world_life_expectancy_at_birth float\n",
    "world_literacy_rate float\n",
    "world_mammal_species float\n",
    "world_mean_drought_index float\n",
    "world_methane_emissions float\n",
    "world_mortality_rate float\n",
    "world_natural_resources_depletion float\n",
    "world_net_forest_depletion float\n",
    "world_net_migration float\n",
    "world_nitrous_oxide_emissions float\n",
    "world_patent_applications float\n",
    "world_people_using_safely_managed_drinking_water_services float\n",
    "world_people_using_safely_managed_sanitation_services float\n",
    "world_pm2_5_air_pollution float\n",
    "world_political_stability_and_absence_of_violence float\n",
    "world_population_ages_65_and_above float\n",
    "world_population_density float\n",
    "world_poverty_headcount_ratio_at_national_poverty_lines float\n",
    "world_prevalence_of_overweight float\n",
    "world_prevalence_of_undernourishment float\n",
    "world_primary_school_enrollment float\n",
    "world_proportion_of_seats_held_by_women_in_national_parliament float\n",
    "world_ratio_of_female_to_male_labor_force_participation_rate float\n",
    "world_regulatory_quality float\n",
    "world_renewable_electricity_output float\n",
    "world_renewable_energy_consumption float\n",
    "world_research_and_development_expenditure float\n",
    "world_rule_of_law float\n",
    "world_scientific_and_technical_journal_articles float\n",
    "world_strength_of_legal_rights_index float\n",
    "world_terrestrial_and_marine_protected_areas float\n",
    "world_tree_cover_loss float\n",
    "world_unemployment float\n",
    "world_unmet_need_for_contraception float\n",
    "world_voice_and_accountability float\n",
    "world_water_quality float\n",
    "\n",
    "  note: \"Data on world\"\n",
    "}\n",
    "Table timeseries as T{\n",
    "   country_name_wb varchar \n",
    "country_code varchar [pk]\n",
    "year int [pk]\n",
    "access_to_clean_fuels_and_technologies_for_cooking float\n",
    "access_to_electricity float\n",
    "agricultural_land float\n",
    "agriculture float\n",
    "annual_freshwater_withdrawals float\n",
    "annualized_average_growth_rate_in_per_capita_real_survey float\n",
    "cause_of_death float\n",
    "children_in_employment float\n",
    "co2_emissions float\n",
    "coastal_protection float\n",
    "control_of_corruption float\n",
    "cooling_degree_days float\n",
    "economic_and_social_rights_performance_score float\n",
    "electricity_production_from_coal_sources float\n",
    "energy_imports float\n",
    "energy_intensity_level_of_primary_energy float\n",
    "energy_use float\n",
    "fertility_rate float\n",
    "food_production_index float\n",
    "forest_area float\n",
    "fossil_fuel_energy_consumption float\n",
    "freshwater_withdrawal float\n",
    "gdp_growth float\n",
    "ghg_net_emissions float\n",
    "gini_index float\n",
    "government_effectiveness float\n",
    "government_expenditure_on_education float\n",
    "gross_school_enrollment float\n",
    "heat_index_35 float\n",
    "heating_degree_days float\n",
    "hospital_beds float\n",
    "income_share_held_by_lowest_20pct float\n",
    "individuals_using_the_internet float\n",
    "labor_force_participation_rate float\n",
    "land_surface_temperature float\n",
    "life_expectancy_at_birth float\n",
    "literacy_rate float\n",
    "mammal_species float\n",
    "mean_drought_index float\n",
    "methane_emissions float\n",
    "mortality_rate float\n",
    "natural_resources_depletion float\n",
    "net_forest_depletion float\n",
    "net_migration float\n",
    "nitrous_oxide_emissions float\n",
    "patent_applications float\n",
    "people_using_safely_managed_drinking_water_services float\n",
    "people_using_safely_managed_sanitation_services float\n",
    "pm2_5_air_pollution float\n",
    "political_stability_and_absence_of_violence float\n",
    "population_ages_65_and_above float\n",
    "population_density float\n",
    "poverty_headcount_ratio_at_national_poverty_lines float\n",
    "prevalence_of_overweight float\n",
    "prevalence_of_undernourishment float\n",
    "primary_school_enrollment float\n",
    "proportion_of_seats_held_by_women_in_national_parliament float\n",
    "ratio_of_female_to_male_labor_force_participation_rate float\n",
    "regulatory_quality float\n",
    "renewable_electricity_output float\n",
    "renewable_energy_consumption float\n",
    "research_and_development_expenditure float\n",
    "rule_of_law float\n",
    "scientific_and_technical_journal_articles float\n",
    "strength_of_legal_rights_index float\n",
    "terrestrial_and_marine_protected_areas float\n",
    "tree_cover_loss float\n",
    "unemployment float\n",
    "unmet_need_for_contraception float\n",
    "voice_and_accountability float\n",
    "water_quality float\n",
    "democracy float\n",
    "\n",
    "  note: \"Timeseries stats\"\n",
    "}\n",
    "\n",
    "Ref: CY.country_name_wb < T.country_name_wb  \n",
    "Ref: T.year < WD.year\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e2e13d1-23d1-47de-b2e2-37f1e4b93bf7",
   "metadata": {},
   "source": [
    "#### DBDOCS\n",
    "https://dbdocs.io/jacktbeerman/World"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74ec1472-9f94-46c6-adb0-c6c952904f71",
   "metadata": {},
   "source": [
    "# 6 A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "6098e108-8166-4f6b-80ad-026dcd595b30",
   "metadata": {},
   "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>democracy</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.915</td>\n",
       "      <td>Denmark</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.903</td>\n",
       "      <td>Sweden</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.901</td>\n",
       "      <td>Norway</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.898</td>\n",
       "      <td>Switzerland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.898</td>\n",
       "      <td>Costa Rica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.896</td>\n",
       "      <td>Estonia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.895</td>\n",
       "      <td>Ireland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.893</td>\n",
       "      <td>Belgium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.888</td>\n",
       "      <td>Portugal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.883</td>\n",
       "      <td>New Zealand</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.881</td>\n",
       "      <td>Luxembourg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.872</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.872</td>\n",
       "      <td>France</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.867</td>\n",
       "      <td>Finland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.863</td>\n",
       "      <td>Korea, Rep.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    democracy      country\n",
       "0       0.915      Denmark\n",
       "1       0.903       Sweden\n",
       "2       0.901       Norway\n",
       "3       0.898  Switzerland\n",
       "4       0.898   Costa Rica\n",
       "5       0.896      Estonia\n",
       "6       0.895      Ireland\n",
       "7       0.893      Belgium\n",
       "8       0.888     Portugal\n",
       "9       0.883  New Zealand\n",
       "10      0.881   Luxembourg\n",
       "11      0.872      Germany\n",
       "12      0.872       France\n",
       "13      0.867      Finland\n",
       "14      0.863  Korea, Rep."
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "myquery = '''\n",
    "SELECT t.democracy, t.country_name_wb AS country\n",
    "FROM timeseries t\n",
    "INNER JOIN country c\n",
    "    ON t.country_code = c.country_code\n",
    "WHERE year = 2021\n",
    "ORDER BY t.democracy DESC\n",
    "LIMIT 15\n",
    "'''\n",
    "\n",
    "pd.read_sql_query(myquery, con=engine)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e15bceb4-fef2-45fd-8f1f-b7bbfa3924fb",
   "metadata": {},
   "source": [
    "# 6 B"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "d0beccfa-002b-40ca-91b0-c8e2f88d31b5",
   "metadata": {},
   "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>life_expectancy_at_birth</th>\n",
       "      <th>country_name_wb</th>\n",
       "      <th>world_life_expectancy_at_birth</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>57.015</td>\n",
       "      <td>Chile</td>\n",
       "      <td>50.894180</td>\n",
       "      <td>1960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>57.537</td>\n",
       "      <td>Chile</td>\n",
       "      <td>52.846336</td>\n",
       "      <td>1961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>57.771</td>\n",
       "      <td>Chile</td>\n",
       "      <td>55.208684</td>\n",
       "      <td>1962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>57.150</td>\n",
       "      <td>Chile</td>\n",
       "      <td>55.542341</td>\n",
       "      <td>1963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>58.738</td>\n",
       "      <td>Chile</td>\n",
       "      <td>56.034875</td>\n",
       "      <td>1964</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>57</th>\n",
       "      <td>80.350</td>\n",
       "      <td>Chile</td>\n",
       "      <td>72.542776</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>80.133</td>\n",
       "      <td>Chile</td>\n",
       "      <td>72.784090</td>\n",
       "      <td>2018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>80.326</td>\n",
       "      <td>Chile</td>\n",
       "      <td>72.979716</td>\n",
       "      <td>2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>79.377</td>\n",
       "      <td>Chile</td>\n",
       "      <td>72.243822</td>\n",
       "      <td>2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Chile</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2021</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>62 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    life_expectancy_at_birth country_name_wb  world_life_expectancy_at_birth  \\\n",
       "0                     57.015           Chile                       50.894180   \n",
       "1                     57.537           Chile                       52.846336   \n",
       "2                     57.771           Chile                       55.208684   \n",
       "3                     57.150           Chile                       55.542341   \n",
       "4                     58.738           Chile                       56.034875   \n",
       "..                       ...             ...                             ...   \n",
       "57                    80.350           Chile                       72.542776   \n",
       "58                    80.133           Chile                       72.784090   \n",
       "59                    80.326           Chile                       72.979716   \n",
       "60                    79.377           Chile                       72.243822   \n",
       "61                       NaN           Chile                             NaN   \n",
       "\n",
       "    year  \n",
       "0   1960  \n",
       "1   1961  \n",
       "2   1962  \n",
       "3   1963  \n",
       "4   1964  \n",
       "..   ...  \n",
       "57  2017  \n",
       "58  2018  \n",
       "59  2019  \n",
       "60  2020  \n",
       "61  2021  \n",
       "\n",
       "[62 rows x 4 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "myquery = '''\n",
    "SELECT t.life_expectancy_at_birth, t.country_name_wb, w.world_life_expectancy_at_birth, w.year\n",
    "FROM timeseries t\n",
    "FULL JOIN world w\n",
    "    ON t.year = w.year\n",
    "WHERE t.country_code = 'CHL'\n",
    "ORDER BY t.year\n",
    "'''\n",
    "\n",
    "pd.read_sql_query(myquery, con=engine)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "630e3b38-92f7-4dd5-8ec1-c5cdf7f6e113",
   "metadata": {},
   "source": [
    "# 6 C"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "7b738a81-8aea-46a8-a923-02930656b196",
   "metadata": {},
   "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</th>\n",
       "      <th>co2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>South Asia</td>\n",
       "      <td>10.820011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>North America</td>\n",
       "      <td>29.726128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sub-Saharan Africa</td>\n",
       "      <td>43.318399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Latin America &amp; Caribbean</td>\n",
       "      <td>68.692584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>East Asia &amp; Pacific</td>\n",
       "      <td>94.256987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Middle East &amp; North Africa</td>\n",
       "      <td>176.008097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Europe &amp; Central Asia</td>\n",
       "      <td>273.807274</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       region         co2\n",
       "0                  South Asia   10.820011\n",
       "1               North America   29.726128\n",
       "2          Sub-Saharan Africa   43.318399\n",
       "3   Latin America & Caribbean   68.692584\n",
       "4         East Asia & Pacific   94.256987\n",
       "5  Middle East & North Africa  176.008097\n",
       "6       Europe & Central Asia  273.807274"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "myquery = '''\n",
    "SELECT c.region, SUM(t.co2_emissions) AS co2\n",
    "FROM timeseries t\n",
    "FULL JOIN country c\n",
    "    ON t.country_code = c.country_code\n",
    "WHERE year = 2019\n",
    "GROUP BY c.region\n",
    "ORDER BY co2\n",
    "'''\n",
    "pd.read_sql_query(myquery, con=engine)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "219a4597-65d7-4693-a930-77b30959c03b",
   "metadata": {},
   "source": [
    "# 6 D"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "d904c15f-925d-4133-b6c0-e6fe541fd70c",
   "metadata": {},
   "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>country_name_wb</th>\n",
       "      <th>country_code</th>\n",
       "      <th>old_demo</th>\n",
       "      <th>new_demo</th>\n",
       "      <th>difference</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ESP</td>\n",
       "      <td>0.070</td>\n",
       "      <td>0.854</td>\n",
       "      <td>0.784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Portugal</td>\n",
       "      <td>PRT</td>\n",
       "      <td>0.128</td>\n",
       "      <td>0.888</td>\n",
       "      <td>0.760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Cabo Verde</td>\n",
       "      <td>CPV</td>\n",
       "      <td>0.023</td>\n",
       "      <td>0.773</td>\n",
       "      <td>0.750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Vanuatu</td>\n",
       "      <td>VUT</td>\n",
       "      <td>0.080</td>\n",
       "      <td>0.771</td>\n",
       "      <td>0.691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Timor-Leste</td>\n",
       "      <td>TLS</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.680</td>\n",
       "      <td>0.662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>São Tomé and Principe</td>\n",
       "      <td>STP</td>\n",
       "      <td>0.030</td>\n",
       "      <td>0.690</td>\n",
       "      <td>0.660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Romania</td>\n",
       "      <td>ROU</td>\n",
       "      <td>0.158</td>\n",
       "      <td>0.768</td>\n",
       "      <td>0.610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Czechia</td>\n",
       "      <td>CZE</td>\n",
       "      <td>0.196</td>\n",
       "      <td>0.805</td>\n",
       "      <td>0.609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Seychelles</td>\n",
       "      <td>SYC</td>\n",
       "      <td>0.130</td>\n",
       "      <td>0.714</td>\n",
       "      <td>0.584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Malawi</td>\n",
       "      <td>MWI</td>\n",
       "      <td>0.040</td>\n",
       "      <td>0.619</td>\n",
       "      <td>0.579</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         country_name_wb country_code  old_demo  new_demo  difference\n",
       "0                  Spain          ESP     0.070     0.854       0.784\n",
       "1               Portugal          PRT     0.128     0.888       0.760\n",
       "2             Cabo Verde          CPV     0.023     0.773       0.750\n",
       "3                Vanuatu          VUT     0.080     0.771       0.691\n",
       "4            Timor-Leste          TLS     0.018     0.680       0.662\n",
       "5  São Tomé and Principe          STP     0.030     0.690       0.660\n",
       "6                Romania          ROU     0.158     0.768       0.610\n",
       "7                Czechia          CZE     0.196     0.805       0.609\n",
       "8             Seychelles          SYC     0.130     0.714       0.584\n",
       "9                 Malawi          MWI     0.040     0.619       0.579"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "myquery = '''\n",
    "WITH old_democracy AS (\n",
    "  SELECT country_code, democracy\n",
    "  FROM timeseries\n",
    "  WHERE year = 1960\n",
    "),\n",
    "new_democracy AS (\n",
    "  SELECT country_code, democracy\n",
    "  FROM timeseries\n",
    "  WHERE year = 2021\n",
    ")\n",
    "SELECT c.country_name_wb,\n",
    "        c.country_code,\n",
    "       old_democracy.democracy AS old_demo,\n",
    "       new_democracy.democracy AS new_demo,\n",
    "       (new_democracy.democracy - old_democracy.democracy) AS difference\n",
    "FROM country c\n",
    "JOIN old_democracy ON c.country_code = old_democracy.country_code\n",
    "JOIN new_democracy ON c.country_code = new_democracy.country_code\n",
    "ORDER BY difference DESC\n",
    "LIMIT 10;\n",
    "'''\n",
    "\n",
    "pd.read_sql_query(myquery, con=engine)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "239eb0cc-6048-440d-a2cc-aa7d47c50d80",
   "metadata": {},
   "source": [
    "# 6 E"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "3323a130-8183-47d6-8b90-4f5929917aec",
   "metadata": {},
   "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>currency_unit</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Euro</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>West African CFA franc</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>U.S. dollar</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>East Caribbean dollar</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Central African CFA franc</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>Lao kip</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>Czech koruna</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>Iraqi dinar</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>New Zambian kwacha</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>Sierra Leonean leone</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>143 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 currency_unit  count\n",
       "0                         Euro     24\n",
       "1       West African CFA franc      8\n",
       "2                  U.S. dollar      7\n",
       "3        East Caribbean dollar      6\n",
       "4    Central African CFA franc      6\n",
       "..                         ...    ...\n",
       "138                    Lao kip      1\n",
       "139               Czech koruna      1\n",
       "140                Iraqi dinar      1\n",
       "141         New Zambian kwacha      1\n",
       "142       Sierra Leonean leone      1\n",
       "\n",
       "[143 rows x 2 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##### find the most used currency by counting how many countries use it \n",
    "\n",
    "myquery = '''\n",
    "SELECT c.currency_unit, COUNT(c.country_name_wb) AS count\n",
    "FROM country c\n",
    "GROUP BY c.currency_unit\n",
    "ORDER BY count DESC\n",
    "'''\n",
    "\n",
    "pd.read_sql_query(myquery, con=engine)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4758ab11-f590-449d-a53a-d5d19673c2aa",
   "metadata": {},
   "source": [
    "# 6 F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "cdaf2049-7565-42bd-8cf6-b5a4b7379f78",
   "metadata": {},
   "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>avg</th>\n",
       "      <th>income_group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>31.731250</td>\n",
       "      <td>High income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>37.420000</td>\n",
       "      <td>Lower middle income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>43.900000</td>\n",
       "      <td>Low income</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>38.145833</td>\n",
       "      <td>Upper middle income</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         avg         income_group\n",
       "0  31.731250          High income\n",
       "1  37.420000  Lower middle income\n",
       "2  43.900000           Low income\n",
       "3        NaN                 None\n",
       "4  38.145833  Upper middle income"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### income group - country\n",
    "### one country - country\n",
    "### GINI index timeseries\n",
    "## same country multiple times\n",
    "\n",
    "myquery = '''\n",
    "SELECT AVG(t.gini_index), c.income_group\n",
    "\n",
    "FROM country c\n",
    "INNER JOIN timeseries t\n",
    "    ON c.country_code = t.country_code\n",
    "WHERE year =2019\n",
    "GROUP BY c.income_group\n",
    "'''\n",
    "\n",
    "pd.read_sql_query(myquery, con=engine)"
   ]
  }
 ],
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