Cleaning_Happiness_Index.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data on Happiness Index for years 2015-2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.stats as st"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Study data files\n",
    "happiness_2015_path = \"Data_Sources/Happiness 2015.csv\"\n",
    "happiness_2016_path = \"Data_Sources/Happiness 2016.csv\"\n",
    "happiness_2017_path = \"Data_Sources/Happiness 2017.csv\"\n",
    "happiness_2018_path = \"Data_Sources/Happiness 2018.csv\"\n",
    "happiness_2019_path = \"Data_Sources/Happiness 2019.csv\"\n",
    "\n",
    "# Read the happiness data\n",
    "happiness_2015 = pd.read_csv(happiness_2015_path)\n",
    "happiness_2016 = pd.read_csv(happiness_2016_path)\n",
    "happiness_2017 = pd.read_csv(happiness_2017_path)\n",
    "happiness_2018 = pd.read_csv(happiness_2018_path)\n",
    "happiness_2019 = pd.read_csv(happiness_2019_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Region</th>\n",
       "      <th>Happiness Rank</th>\n",
       "      <th>Happiness Score</th>\n",
       "      <th>Standard Error</th>\n",
       "      <th>Economy (GDP per Capita)</th>\n",
       "      <th>Family</th>\n",
       "      <th>Health (Life Expectancy)</th>\n",
       "      <th>Freedom</th>\n",
       "      <th>Trust (Government Corruption)</th>\n",
       "      <th>Generosity</th>\n",
       "      <th>Dystopia Residual</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>1</td>\n",
       "      <td>7.587</td>\n",
       "      <td>0.03411</td>\n",
       "      <td>1.39651</td>\n",
       "      <td>1.34951</td>\n",
       "      <td>0.94143</td>\n",
       "      <td>0.66557</td>\n",
       "      <td>0.41978</td>\n",
       "      <td>0.29678</td>\n",
       "      <td>2.51738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>2</td>\n",
       "      <td>7.561</td>\n",
       "      <td>0.04884</td>\n",
       "      <td>1.30232</td>\n",
       "      <td>1.40223</td>\n",
       "      <td>0.94784</td>\n",
       "      <td>0.62877</td>\n",
       "      <td>0.14145</td>\n",
       "      <td>0.43630</td>\n",
       "      <td>2.70201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>3</td>\n",
       "      <td>7.527</td>\n",
       "      <td>0.03328</td>\n",
       "      <td>1.32548</td>\n",
       "      <td>1.36058</td>\n",
       "      <td>0.87464</td>\n",
       "      <td>0.64938</td>\n",
       "      <td>0.48357</td>\n",
       "      <td>0.34139</td>\n",
       "      <td>2.49204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Norway</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>4</td>\n",
       "      <td>7.522</td>\n",
       "      <td>0.03880</td>\n",
       "      <td>1.45900</td>\n",
       "      <td>1.33095</td>\n",
       "      <td>0.88521</td>\n",
       "      <td>0.66973</td>\n",
       "      <td>0.36503</td>\n",
       "      <td>0.34699</td>\n",
       "      <td>2.46531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Canada</td>\n",
       "      <td>North America</td>\n",
       "      <td>5</td>\n",
       "      <td>7.427</td>\n",
       "      <td>0.03553</td>\n",
       "      <td>1.32629</td>\n",
       "      <td>1.32261</td>\n",
       "      <td>0.90563</td>\n",
       "      <td>0.63297</td>\n",
       "      <td>0.32957</td>\n",
       "      <td>0.45811</td>\n",
       "      <td>2.45176</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Country          Region  Happiness Rank  Happiness Score  \\\n",
       "0  Switzerland  Western Europe               1            7.587   \n",
       "1      Iceland  Western Europe               2            7.561   \n",
       "2      Denmark  Western Europe               3            7.527   \n",
       "3       Norway  Western Europe               4            7.522   \n",
       "4       Canada   North America               5            7.427   \n",
       "\n",
       "   Standard Error  Economy (GDP per Capita)   Family  \\\n",
       "0         0.03411                   1.39651  1.34951   \n",
       "1         0.04884                   1.30232  1.40223   \n",
       "2         0.03328                   1.32548  1.36058   \n",
       "3         0.03880                   1.45900  1.33095   \n",
       "4         0.03553                   1.32629  1.32261   \n",
       "\n",
       "   Health (Life Expectancy)  Freedom  Trust (Government Corruption)  \\\n",
       "0                   0.94143  0.66557                        0.41978   \n",
       "1                   0.94784  0.62877                        0.14145   \n",
       "2                   0.87464  0.64938                        0.48357   \n",
       "3                   0.88521  0.66973                        0.36503   \n",
       "4                   0.90563  0.63297                        0.32957   \n",
       "\n",
       "   Generosity  Dystopia Residual  \n",
       "0     0.29678            2.51738  \n",
       "1     0.43630            2.70201  \n",
       "2     0.34139            2.49204  \n",
       "3     0.34699            2.46531  \n",
       "4     0.45811            2.45176  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "happiness_2015.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Happiness Rank</th>\n",
       "      <th>Happiness Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>1</td>\n",
       "      <td>7.587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>2</td>\n",
       "      <td>7.561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>3</td>\n",
       "      <td>7.527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Norway</td>\n",
       "      <td>4</td>\n",
       "      <td>7.522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Canada</td>\n",
       "      <td>5</td>\n",
       "      <td>7.427</td>\n",
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      ],
      "text/plain": [
       "       Country  Happiness Rank  Happiness Score\n",
       "0  Switzerland               1            7.587\n",
       "1      Iceland               2            7.561\n",
       "2      Denmark               3            7.527\n",
       "3       Norway               4            7.522\n",
       "4       Canada               5            7.427"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove columns and only keep countries, year, ranking, and score.\n",
    "columns_to_drop_1 = ['Region', 'Standard Error', 'Economy (GDP per Capita)', 'Family', 'Health (Life Expectancy)', \n",
    "                     'Freedom', 'Trust (Government Corruption)', 'Generosity', 'Dystopia Residual']\n",
    "happiness_2015 = happiness_2015.drop(columns_to_drop_1, axis=1)\n",
    "happiness_2015.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Region</th>\n",
       "      <th>Happiness Rank</th>\n",
       "      <th>Happiness Score</th>\n",
       "      <th>Lower Confidence Interval</th>\n",
       "      <th>Upper Confidence Interval</th>\n",
       "      <th>Economy (GDP per Capita)</th>\n",
       "      <th>Family</th>\n",
       "      <th>Health (Life Expectancy)</th>\n",
       "      <th>Freedom</th>\n",
       "      <th>Trust (Government Corruption)</th>\n",
       "      <th>Generosity</th>\n",
       "      <th>Dystopia Residual</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>1</td>\n",
       "      <td>7.526</td>\n",
       "      <td>7.460</td>\n",
       "      <td>7.592</td>\n",
       "      <td>1.44178</td>\n",
       "      <td>1.16374</td>\n",
       "      <td>0.79504</td>\n",
       "      <td>0.57941</td>\n",
       "      <td>0.44453</td>\n",
       "      <td>0.36171</td>\n",
       "      <td>2.73939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>2</td>\n",
       "      <td>7.509</td>\n",
       "      <td>7.428</td>\n",
       "      <td>7.590</td>\n",
       "      <td>1.52733</td>\n",
       "      <td>1.14524</td>\n",
       "      <td>0.86303</td>\n",
       "      <td>0.58557</td>\n",
       "      <td>0.41203</td>\n",
       "      <td>0.28083</td>\n",
       "      <td>2.69463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>3</td>\n",
       "      <td>7.501</td>\n",
       "      <td>7.333</td>\n",
       "      <td>7.669</td>\n",
       "      <td>1.42666</td>\n",
       "      <td>1.18326</td>\n",
       "      <td>0.86733</td>\n",
       "      <td>0.56624</td>\n",
       "      <td>0.14975</td>\n",
       "      <td>0.47678</td>\n",
       "      <td>2.83137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Norway</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>4</td>\n",
       "      <td>7.498</td>\n",
       "      <td>7.421</td>\n",
       "      <td>7.575</td>\n",
       "      <td>1.57744</td>\n",
       "      <td>1.12690</td>\n",
       "      <td>0.79579</td>\n",
       "      <td>0.59609</td>\n",
       "      <td>0.35776</td>\n",
       "      <td>0.37895</td>\n",
       "      <td>2.66465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Finland</td>\n",
       "      <td>Western Europe</td>\n",
       "      <td>5</td>\n",
       "      <td>7.413</td>\n",
       "      <td>7.351</td>\n",
       "      <td>7.475</td>\n",
       "      <td>1.40598</td>\n",
       "      <td>1.13464</td>\n",
       "      <td>0.81091</td>\n",
       "      <td>0.57104</td>\n",
       "      <td>0.41004</td>\n",
       "      <td>0.25492</td>\n",
       "      <td>2.82596</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Country          Region  Happiness Rank  Happiness Score  \\\n",
       "0      Denmark  Western Europe               1            7.526   \n",
       "1  Switzerland  Western Europe               2            7.509   \n",
       "2      Iceland  Western Europe               3            7.501   \n",
       "3       Norway  Western Europe               4            7.498   \n",
       "4      Finland  Western Europe               5            7.413   \n",
       "\n",
       "   Lower Confidence Interval  Upper Confidence Interval  \\\n",
       "0                      7.460                      7.592   \n",
       "1                      7.428                      7.590   \n",
       "2                      7.333                      7.669   \n",
       "3                      7.421                      7.575   \n",
       "4                      7.351                      7.475   \n",
       "\n",
       "   Economy (GDP per Capita)   Family  Health (Life Expectancy)  Freedom  \\\n",
       "0                   1.44178  1.16374                   0.79504  0.57941   \n",
       "1                   1.52733  1.14524                   0.86303  0.58557   \n",
       "2                   1.42666  1.18326                   0.86733  0.56624   \n",
       "3                   1.57744  1.12690                   0.79579  0.59609   \n",
       "4                   1.40598  1.13464                   0.81091  0.57104   \n",
       "\n",
       "   Trust (Government Corruption)  Generosity  Dystopia Residual  \n",
       "0                        0.44453     0.36171            2.73939  \n",
       "1                        0.41203     0.28083            2.69463  \n",
       "2                        0.14975     0.47678            2.83137  \n",
       "3                        0.35776     0.37895            2.66465  \n",
       "4                        0.41004     0.25492            2.82596  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "happiness_2016.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Happiness Rank</th>\n",
       "      <th>Happiness Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>1</td>\n",
       "      <td>7.526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>2</td>\n",
       "      <td>7.509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>3</td>\n",
       "      <td>7.501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Norway</td>\n",
       "      <td>4</td>\n",
       "      <td>7.498</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Finland</td>\n",
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      "text/plain": [
       "       Country  Happiness Rank  Happiness Score\n",
       "0      Denmark               1            7.526\n",
       "1  Switzerland               2            7.509\n",
       "2      Iceland               3            7.501\n",
       "3       Norway               4            7.498\n",
       "4      Finland               5            7.413"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove columns and only keep countries, year, ranking, and score.\n",
    "columns_to_drop_2 = ['Region', 'Lower Confidence Interval', 'Upper Confidence Interval', 'Economy (GDP per Capita)', \n",
    "                     'Family', 'Health (Life Expectancy)', 'Freedom', 'Trust (Government Corruption)', 'Generosity', 'Dystopia Residual']\n",
    "happiness_2016 = happiness_2016.drop(columns_to_drop_2, axis=1)\n",
    "happiness_2016.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Happiness.Rank</th>\n",
       "      <th>Happiness.Score</th>\n",
       "      <th>Whisker.high</th>\n",
       "      <th>Whisker.low</th>\n",
       "      <th>Economy..GDP.per.Capita.</th>\n",
       "      <th>Family</th>\n",
       "      <th>Health..Life.Expectancy.</th>\n",
       "      <th>Freedom</th>\n",
       "      <th>Generosity</th>\n",
       "      <th>Trust..Government.Corruption.</th>\n",
       "      <th>Dystopia.Residual</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Norway</td>\n",
       "      <td>1</td>\n",
       "      <td>7.537</td>\n",
       "      <td>7.594445</td>\n",
       "      <td>7.479556</td>\n",
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       "      <td>2.277027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>2</td>\n",
       "      <td>7.522</td>\n",
       "      <td>7.581728</td>\n",
       "      <td>7.462272</td>\n",
       "      <td>1.482383</td>\n",
       "      <td>1.551122</td>\n",
       "      <td>0.792566</td>\n",
       "      <td>0.626007</td>\n",
       "      <td>0.355280</td>\n",
       "      <td>0.400770</td>\n",
       "      <td>2.313707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>3</td>\n",
       "      <td>7.504</td>\n",
       "      <td>7.622030</td>\n",
       "      <td>7.385970</td>\n",
       "      <td>1.480633</td>\n",
       "      <td>1.610574</td>\n",
       "      <td>0.833552</td>\n",
       "      <td>0.627163</td>\n",
       "      <td>0.475540</td>\n",
       "      <td>0.153527</td>\n",
       "      <td>2.322715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>4</td>\n",
       "      <td>7.494</td>\n",
       "      <td>7.561772</td>\n",
       "      <td>7.426227</td>\n",
       "      <td>1.564980</td>\n",
       "      <td>1.516912</td>\n",
       "      <td>0.858131</td>\n",
       "      <td>0.620071</td>\n",
       "      <td>0.290549</td>\n",
       "      <td>0.367007</td>\n",
       "      <td>2.276716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Finland</td>\n",
       "      <td>5</td>\n",
       "      <td>7.469</td>\n",
       "      <td>7.527542</td>\n",
       "      <td>7.410458</td>\n",
       "      <td>1.443572</td>\n",
       "      <td>1.540247</td>\n",
       "      <td>0.809158</td>\n",
       "      <td>0.617951</td>\n",
       "      <td>0.245483</td>\n",
       "      <td>0.382612</td>\n",
       "      <td>2.430182</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Country  Happiness.Rank  Happiness.Score  Whisker.high  Whisker.low  \\\n",
       "0       Norway               1            7.537      7.594445     7.479556   \n",
       "1      Denmark               2            7.522      7.581728     7.462272   \n",
       "2      Iceland               3            7.504      7.622030     7.385970   \n",
       "3  Switzerland               4            7.494      7.561772     7.426227   \n",
       "4      Finland               5            7.469      7.527542     7.410458   \n",
       "\n",
       "   Economy..GDP.per.Capita.    Family  Health..Life.Expectancy.   Freedom  \\\n",
       "0                  1.616463  1.533524                  0.796667  0.635423   \n",
       "1                  1.482383  1.551122                  0.792566  0.626007   \n",
       "2                  1.480633  1.610574                  0.833552  0.627163   \n",
       "3                  1.564980  1.516912                  0.858131  0.620071   \n",
       "4                  1.443572  1.540247                  0.809158  0.617951   \n",
       "\n",
       "   Generosity  Trust..Government.Corruption.  Dystopia.Residual  \n",
       "0    0.362012                       0.315964           2.277027  \n",
       "1    0.355280                       0.400770           2.313707  \n",
       "2    0.475540                       0.153527           2.322715  \n",
       "3    0.290549                       0.367007           2.276716  \n",
       "4    0.245483                       0.382612           2.430182  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "happiness_2017.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .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</th>\n",
       "      <th>Happiness.Rank</th>\n",
       "      <th>Happiness.Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Norway</td>\n",
       "      <td>1</td>\n",
       "      <td>7.537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>2</td>\n",
       "      <td>7.522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>3</td>\n",
       "      <td>7.504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>4</td>\n",
       "      <td>7.494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Finland</td>\n",
       "      <td>5</td>\n",
       "      <td>7.469</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Country  Happiness.Rank  Happiness.Score\n",
       "0       Norway               1            7.537\n",
       "1      Denmark               2            7.522\n",
       "2      Iceland               3            7.504\n",
       "3  Switzerland               4            7.494\n",
       "4      Finland               5            7.469"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove columns and only keep countries, year, ranking, and score.\n",
    "columns_to_drop_3 = ['Whisker.high', 'Whisker.low', 'Economy..GDP.per.Capita.',\n",
    "                     'Family', 'Health..Life.Expectancy.', 'Freedom', 'Generosity', 'Trust..Government.Corruption.', 'Dystopia.Residual']\n",
    "happiness_2017 = happiness_2017.drop(columns_to_drop_3, axis=1)\n",
    "happiness_2017.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Overall rank</th>\n",
       "      <th>Country or region</th>\n",
       "      <th>Score</th>\n",
       "      <th>GDP per capita</th>\n",
       "      <th>Social support</th>\n",
       "      <th>Healthy life expectancy</th>\n",
       "      <th>Freedom to make life choices</th>\n",
       "      <th>Generosity</th>\n",
       "      <th>Perceptions of corruption</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Finland</td>\n",
       "      <td>7.632</td>\n",
       "      <td>1.305</td>\n",
       "      <td>1.592</td>\n",
       "      <td>0.874</td>\n",
       "      <td>0.681</td>\n",
       "      <td>0.202</td>\n",
       "      <td>0.393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Norway</td>\n",
       "      <td>7.594</td>\n",
       "      <td>1.456</td>\n",
       "      <td>1.582</td>\n",
       "      <td>0.861</td>\n",
       "      <td>0.686</td>\n",
       "      <td>0.286</td>\n",
       "      <td>0.340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>7.555</td>\n",
       "      <td>1.351</td>\n",
       "      <td>1.590</td>\n",
       "      <td>0.868</td>\n",
       "      <td>0.683</td>\n",
       "      <td>0.284</td>\n",
       "      <td>0.408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Iceland</td>\n",
       "      <td>7.495</td>\n",
       "      <td>1.343</td>\n",
       "      <td>1.644</td>\n",
       "      <td>0.914</td>\n",
       "      <td>0.677</td>\n",
       "      <td>0.353</td>\n",
       "      <td>0.138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>7.487</td>\n",
       "      <td>1.420</td>\n",
       "      <td>1.549</td>\n",
       "      <td>0.927</td>\n",
       "      <td>0.660</td>\n",
       "      <td>0.256</td>\n",
       "      <td>0.357</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Overall rank Country or region  Score  GDP per capita  Social support  \\\n",
       "0             1           Finland  7.632           1.305           1.592   \n",
       "1             2            Norway  7.594           1.456           1.582   \n",
       "2             3           Denmark  7.555           1.351           1.590   \n",
       "3             4           Iceland  7.495           1.343           1.644   \n",
       "4             5       Switzerland  7.487           1.420           1.549   \n",
       "\n",
       "   Healthy life expectancy  Freedom to make life choices  Generosity  \\\n",
       "0                    0.874                         0.681       0.202   \n",
       "1                    0.861                         0.686       0.286   \n",
       "2                    0.868                         0.683       0.284   \n",
       "3                    0.914                         0.677       0.353   \n",
       "4                    0.927                         0.660       0.256   \n",
       "\n",
       "   Perceptions of corruption  \n",
       "0                      0.393  \n",
       "1                      0.340  \n",
       "2                      0.408  \n",
       "3                      0.138  \n",
       "4                      0.357  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "happiness_2018.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove columns and only keep countries, year, ranking, and score.\n",
    "columns_to_drop_4 = ['GDP per capita', 'Social support', 'Healthy life expectancy',\n",
    "                    'Freedom to make life choices', 'Generosity', 'Perceptions of corruption']\n",
    "happiness_2018 = happiness_2018.drop(columns_to_drop_4, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Overall rank</th>\n",
       "      <th>Country</th>\n",
       "      <th>Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Finland</td>\n",
       "      <td>7.632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Norway</td>\n",
       "      <td>7.594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>7.555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Iceland</td>\n",
       "      <td>7.495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Switzerland</td>\n",
       "      <td>7.487</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Overall rank      Country  Score\n",
       "0             1      Finland  7.632\n",
       "1             2       Norway  7.594\n",
       "2             3      Denmark  7.555\n",
       "3             4      Iceland  7.495\n",
       "4             5  Switzerland  7.487"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Renaming 'country or region' column to 'Country' \n",
    "happiness_2018 = happiness_2018.rename(columns={'Country or region': 'Country'})\n",
    "happiness_2018.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Overall rank</th>\n",
       "      <th>Country or region</th>\n",
       "      <th>Score</th>\n",
       "      <th>GDP per capita</th>\n",
       "      <th>Social support</th>\n",
       "      <th>Healthy life expectancy</th>\n",
       "      <th>Freedom to make life choices</th>\n",
       "      <th>Generosity</th>\n",
       "      <th>Perceptions of corruption</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Finland</td>\n",
       "      <td>7.769</td>\n",
       "      <td>1.340</td>\n",
       "      <td>1.587</td>\n",
       "      <td>0.986</td>\n",
       "      <td>0.596</td>\n",
       "      <td>0.153</td>\n",
       "      <td>0.393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>7.600</td>\n",
       "      <td>1.383</td>\n",
       "      <td>1.573</td>\n",
       "      <td>0.996</td>\n",
       "      <td>0.592</td>\n",
       "      <td>0.252</td>\n",
       "      <td>0.410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Norway</td>\n",
       "      <td>7.554</td>\n",
       "      <td>1.488</td>\n",
       "      <td>1.582</td>\n",
       "      <td>1.028</td>\n",
       "      <td>0.603</td>\n",
       "      <td>0.271</td>\n",
       "      <td>0.341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Iceland</td>\n",
       "      <td>7.494</td>\n",
       "      <td>1.380</td>\n",
       "      <td>1.624</td>\n",
       "      <td>1.026</td>\n",
       "      <td>0.591</td>\n",
       "      <td>0.354</td>\n",
       "      <td>0.118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>7.488</td>\n",
       "      <td>1.396</td>\n",
       "      <td>1.522</td>\n",
       "      <td>0.999</td>\n",
       "      <td>0.557</td>\n",
       "      <td>0.322</td>\n",
       "      <td>0.298</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Overall rank Country or region  Score  GDP per capita  Social support  \\\n",
       "0             1           Finland  7.769           1.340           1.587   \n",
       "1             2           Denmark  7.600           1.383           1.573   \n",
       "2             3            Norway  7.554           1.488           1.582   \n",
       "3             4           Iceland  7.494           1.380           1.624   \n",
       "4             5       Netherlands  7.488           1.396           1.522   \n",
       "\n",
       "   Healthy life expectancy  Freedom to make life choices  Generosity  \\\n",
       "0                    0.986                         0.596       0.153   \n",
       "1                    0.996                         0.592       0.252   \n",
       "2                    1.028                         0.603       0.271   \n",
       "3                    1.026                         0.591       0.354   \n",
       "4                    0.999                         0.557       0.322   \n",
       "\n",
       "   Perceptions of corruption  \n",
       "0                      0.393  \n",
       "1                      0.410  \n",
       "2                      0.341  \n",
       "3                      0.118  \n",
       "4                      0.298  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "happiness_2019.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>Overall rank</th>\n",
       "      <th>Country or region</th>\n",
       "      <th>Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Finland</td>\n",
       "      <td>7.769</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>7.600</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Norway</td>\n",
       "      <td>7.554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Iceland</td>\n",
       "      <td>7.494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>7.488</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Overall rank Country or region  Score\n",
       "0             1           Finland  7.769\n",
       "1             2           Denmark  7.600\n",
       "2             3            Norway  7.554\n",
       "3             4           Iceland  7.494\n",
       "4             5       Netherlands  7.488"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "columns_to_drop_5 = ['GDP per capita', 'Social support', 'Healthy life expectancy', 'Freedom to make life choices', 'Generosity', 'Perceptions of corruption']\n",
    "happiness_2019 = happiness_2019.drop(columns_to_drop_5, axis=1)\n",
    "happiness_2019.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>Overall rank</th>\n",
       "      <th>Country</th>\n",
       "      <th>Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Finland</td>\n",
       "      <td>7.769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>7.600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Norway</td>\n",
       "      <td>7.554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Iceland</td>\n",
       "      <td>7.494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>7.488</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Overall rank      Country  Score\n",
       "0             1      Finland  7.769\n",
       "1             2      Denmark  7.600\n",
       "2             3       Norway  7.554\n",
       "3             4      Iceland  7.494\n",
       "4             5  Netherlands  7.488"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Renaming 'country or region' column to 'Country' \n",
    "happiness_2019 = happiness_2019.rename(columns={'Country or region': 'Country'})\n",
    "happiness_2019.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine the data into a single DataFrame\n",
    "combined_dataframe1 = pd.merge(happiness_2015, happiness_2016,\n",
    "                              how='left', on='Country')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         Country  Happiness Rank_x  Happiness Score_x  Happiness Rank_y  \\\n",
      "0    Switzerland                 1              7.587               2.0   \n",
      "1        Iceland                 2              7.561               3.0   \n",
      "2        Denmark                 3              7.527               1.0   \n",
      "3         Norway                 4              7.522               4.0   \n",
      "4         Canada                 5              7.427               6.0   \n",
      "..           ...               ...                ...               ...   \n",
      "153       Rwanda               154              3.465             152.0   \n",
      "154        Benin               155              3.340             153.0   \n",
      "155        Syria               156              3.006             156.0   \n",
      "156      Burundi               157              2.905             157.0   \n",
      "157         Togo               158              2.839             155.0   \n",
      "\n",
      "     Happiness Score_y  \n",
      "0                7.509  \n",
      "1                7.501  \n",
      "2                7.526  \n",
      "3                7.498  \n",
      "4                7.404  \n",
      "..                 ...  \n",
      "153              3.515  \n",
      "154              3.484  \n",
      "155              3.069  \n",
      "156              2.905  \n",
      "157              3.303  \n",
      "\n",
      "[158 rows x 5 columns]\n"
     ]
    }
   ],
   "source": [
    "# check the merged dataframe\n",
    "print(combined_dataframe1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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</th>\n",
       "      <th>Rank 2015</th>\n",
       "      <th>Score 2015</th>\n",
       "      <th>Rank 2016</th>\n",
       "      <th>Score 2016</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>1</td>\n",
       "      <td>7.587</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>2</td>\n",
       "      <td>7.561</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>3</td>\n",
       "      <td>7.527</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Norway</td>\n",
       "      <td>4</td>\n",
       "      <td>7.522</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Canada</td>\n",
       "      <td>5</td>\n",
       "      <td>7.427</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.404</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Country  Rank 2015  Score 2015  Rank 2016  Score 2016\n",
       "0  Switzerland          1       7.587        2.0       7.509\n",
       "1      Iceland          2       7.561        3.0       7.501\n",
       "2      Denmark          3       7.527        1.0       7.526\n",
       "3       Norway          4       7.522        4.0       7.498\n",
       "4       Canada          5       7.427        6.0       7.404"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#rename columns in first merger\n",
    "combined_dataframe1.rename(columns={'Country': 'Country', 'Happiness Rank_x': 'Rank 2015', 'Happiness Score_x': 'Score 2015', 'Happiness Rank_y': 'Rank 2016', 'Happiness Score_y': 'Score 2016'}, inplace=True)\n",
    "combined_dataframe1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         Country  Rank 2015  Score 2015  Rank 2016  Score 2016\n",
      "0    Switzerland          1       7.587        2.0       7.509\n",
      "1        Iceland          2       7.561        3.0       7.501\n",
      "2        Denmark          3       7.527        1.0       7.526\n",
      "3         Norway          4       7.522        4.0       7.498\n",
      "4         Canada          5       7.427        6.0       7.404\n",
      "..           ...        ...         ...        ...         ...\n",
      "153       Rwanda        154       3.465      152.0       3.515\n",
      "154        Benin        155       3.340      153.0       3.484\n",
      "155        Syria        156       3.006      156.0       3.069\n",
      "156      Burundi        157       2.905      157.0       2.905\n",
      "157         Togo        158       2.839      155.0       3.303\n",
      "\n",
      "[158 rows x 5 columns]\n"
     ]
    }
   ],
   "source": [
    "# Check to see renamed columns in first merger\n",
    "print(combined_dataframe1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine the data into a single DataFrame again incorporating the next year, being 2017.\n",
    "combined_dataframe2 = pd.merge(combined_dataframe1, happiness_2017,\n",
    "                              how='left', on='Country')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         Country  Rank 2015  Score 2015  Rank 2016  Score 2016  \\\n",
      "0    Switzerland          1       7.587        2.0       7.509   \n",
      "1        Iceland          2       7.561        3.0       7.501   \n",
      "2        Denmark          3       7.527        1.0       7.526   \n",
      "3         Norway          4       7.522        4.0       7.498   \n",
      "4         Canada          5       7.427        6.0       7.404   \n",
      "..           ...        ...         ...        ...         ...   \n",
      "153       Rwanda        154       3.465      152.0       3.515   \n",
      "154        Benin        155       3.340      153.0       3.484   \n",
      "155        Syria        156       3.006      156.0       3.069   \n",
      "156      Burundi        157       2.905      157.0       2.905   \n",
      "157         Togo        158       2.839      155.0       3.303   \n",
      "\n",
      "     Happiness.Rank  Happiness.Score  \n",
      "0               4.0            7.494  \n",
      "1               3.0            7.504  \n",
      "2               2.0            7.522  \n",
      "3               1.0            7.537  \n",
      "4               7.0            7.316  \n",
      "..              ...              ...  \n",
      "153           151.0            3.471  \n",
      "154           143.0            3.657  \n",
      "155           152.0            3.462  \n",
      "156           154.0            2.905  \n",
      "157           150.0            3.495  \n",
      "\n",
      "[158 rows x 7 columns]\n"
     ]
    }
   ],
   "source": [
    "# check the merge\n",
    "print(combined_dataframe2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "#rename columns\n",
    "combined_dataframe2.rename(columns={'Happiness.Rank': 'Rank 2017', 'Happiness.Score': 'Score 2017'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         Country  Rank 2015  Score 2015  Rank 2016  Score 2016  Rank 2017  \\\n",
      "0    Switzerland          1       7.587        2.0       7.509        4.0   \n",
      "1        Iceland          2       7.561        3.0       7.501        3.0   \n",
      "2        Denmark          3       7.527        1.0       7.526        2.0   \n",
      "3         Norway          4       7.522        4.0       7.498        1.0   \n",
      "4         Canada          5       7.427        6.0       7.404        7.0   \n",
      "..           ...        ...         ...        ...         ...        ...   \n",
      "153       Rwanda        154       3.465      152.0       3.515      151.0   \n",
      "154        Benin        155       3.340      153.0       3.484      143.0   \n",
      "155        Syria        156       3.006      156.0       3.069      152.0   \n",
      "156      Burundi        157       2.905      157.0       2.905      154.0   \n",
      "157         Togo        158       2.839      155.0       3.303      150.0   \n",
      "\n",
      "     Score 2017  \n",
      "0         7.494  \n",
      "1         7.504  \n",
      "2         7.522  \n",
      "3         7.537  \n",
      "4         7.316  \n",
      "..          ...  \n",
      "153       3.471  \n",
      "154       3.657  \n",
      "155       3.462  \n",
      "156       2.905  \n",
      "157       3.495  \n",
      "\n",
      "[158 rows x 7 columns]\n"
     ]
    }
   ],
   "source": [
    "#check the merged data frame after renaming columns\n",
    "print(combined_dataframe2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Country', 'Rank 2015', 'Score 2015', 'Rank 2016', 'Score 2016',\n",
      "       'Rank 2017', 'Score 2017'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(combined_dataframe2.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine the data into a single DataFrame again, but merging with 2018\n",
    "combined_dataframe3 = pd.merge(combined_dataframe2, happiness_2018, \n",
    "                               how='left', on='Country')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         Country  Rank 2015  Score 2015  Rank 2016  Score 2016  Rank 2017  \\\n",
      "0    Switzerland          1       7.587        2.0       7.509        4.0   \n",
      "1        Iceland          2       7.561        3.0       7.501        3.0   \n",
      "2        Denmark          3       7.527        1.0       7.526        2.0   \n",
      "3         Norway          4       7.522        4.0       7.498        1.0   \n",
      "4         Canada          5       7.427        6.0       7.404        7.0   \n",
      "..           ...        ...         ...        ...         ...        ...   \n",
      "153       Rwanda        154       3.465      152.0       3.515      151.0   \n",
      "154        Benin        155       3.340      153.0       3.484      143.0   \n",
      "155        Syria        156       3.006      156.0       3.069      152.0   \n",
      "156      Burundi        157       2.905      157.0       2.905      154.0   \n",
      "157         Togo        158       2.839      155.0       3.303      150.0   \n",
      "\n",
      "     Score 2017  Overall rank  Score  \n",
      "0         7.494           5.0  7.487  \n",
      "1         7.504           4.0  7.495  \n",
      "2         7.522           3.0  7.555  \n",
      "3         7.537           2.0  7.594  \n",
      "4         7.316           7.0  7.328  \n",
      "..          ...           ...    ...  \n",
      "153       3.471         151.0  3.408  \n",
      "154       3.657         136.0  4.141  \n",
      "155       3.462         150.0  3.462  \n",
      "156       2.905         156.0  2.905  \n",
      "157       3.495         139.0  3.999  \n",
      "\n",
      "[158 rows x 9 columns]\n"
     ]
    }
   ],
   "source": [
    "#check the column names of merged df\n",
    "print(combined_dataframe3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .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</th>\n",
       "      <th>Rank 2015</th>\n",
       "      <th>Score 2015</th>\n",
       "      <th>Rank 2016</th>\n",
       "      <th>Score 2016</th>\n",
       "      <th>Rank 2017</th>\n",
       "      <th>Score 2017</th>\n",
       "      <th>Overall rank</th>\n",
       "      <th>Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>1</td>\n",
       "      <td>7.587</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.509</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.494</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>2</td>\n",
       "      <td>7.561</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.501</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.504</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>3</td>\n",
       "      <td>7.527</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.526</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.522</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Norway</td>\n",
       "      <td>4</td>\n",
       "      <td>7.522</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.498</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.537</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Canada</td>\n",
       "      <td>5</td>\n",
       "      <td>7.427</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.404</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.316</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.328</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Country  Rank 2015  Score 2015  Rank 2016  Score 2016  Rank 2017  \\\n",
       "0  Switzerland          1       7.587        2.0       7.509        4.0   \n",
       "1      Iceland          2       7.561        3.0       7.501        3.0   \n",
       "2      Denmark          3       7.527        1.0       7.526        2.0   \n",
       "3       Norway          4       7.522        4.0       7.498        1.0   \n",
       "4       Canada          5       7.427        6.0       7.404        7.0   \n",
       "\n",
       "   Score 2017  Overall rank  Score  \n",
       "0       7.494           5.0  7.487  \n",
       "1       7.504           4.0  7.495  \n",
       "2       7.522           3.0  7.555  \n",
       "3       7.537           2.0  7.594  \n",
       "4       7.316           7.0  7.328  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined_dataframe3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "#rename columns\n",
    "combined_dataframe3.rename(columns={'Overall rank': 'Rank 2018', 'Score': 'Score 2018'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         Country  Rank 2015  Score 2015  Rank 2016  Score 2016  Rank 2017  \\\n",
      "0    Switzerland          1       7.587        2.0       7.509        4.0   \n",
      "1        Iceland          2       7.561        3.0       7.501        3.0   \n",
      "2        Denmark          3       7.527        1.0       7.526        2.0   \n",
      "3         Norway          4       7.522        4.0       7.498        1.0   \n",
      "4         Canada          5       7.427        6.0       7.404        7.0   \n",
      "..           ...        ...         ...        ...         ...        ...   \n",
      "153       Rwanda        154       3.465      152.0       3.515      151.0   \n",
      "154        Benin        155       3.340      153.0       3.484      143.0   \n",
      "155        Syria        156       3.006      156.0       3.069      152.0   \n",
      "156      Burundi        157       2.905      157.0       2.905      154.0   \n",
      "157         Togo        158       2.839      155.0       3.303      150.0   \n",
      "\n",
      "     Score 2017  Rank 2018  Score 2018  \n",
      "0         7.494        5.0       7.487  \n",
      "1         7.504        4.0       7.495  \n",
      "2         7.522        3.0       7.555  \n",
      "3         7.537        2.0       7.594  \n",
      "4         7.316        7.0       7.328  \n",
      "..          ...        ...         ...  \n",
      "153       3.471      151.0       3.408  \n",
      "154       3.657      136.0       4.141  \n",
      "155       3.462      150.0       3.462  \n",
      "156       2.905      156.0       2.905  \n",
      "157       3.495      139.0       3.999  \n",
      "\n",
      "[158 rows x 9 columns]\n"
     ]
    }
   ],
   "source": [
    "#check df of merged df\n",
    "print(combined_dataframe3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine the data into a single DataFrame again\n",
    "happiness_index = pd.merge(combined_dataframe3, happiness_2019,\n",
    "                              how='left', on='Country')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "#rename columns one last time\n",
    "happiness_index.rename(columns={'Overall rank': 'Rank 2019', 'Score': 'Score 2019'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Rank 2015</th>\n",
       "      <th>Score 2015</th>\n",
       "      <th>Rank 2016</th>\n",
       "      <th>Score 2016</th>\n",
       "      <th>Rank 2017</th>\n",
       "      <th>Score 2017</th>\n",
       "      <th>Rank 2018</th>\n",
       "      <th>Score 2018</th>\n",
       "      <th>Rank 2019</th>\n",
       "      <th>Score 2019</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>1</td>\n",
       "      <td>7.587</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.509</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.494</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.487</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>2</td>\n",
       "      <td>7.561</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.501</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.504</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.495</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>3</td>\n",
       "      <td>7.527</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.526</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.522</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.555</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Norway</td>\n",
       "      <td>4</td>\n",
       "      <td>7.522</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.498</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.537</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.594</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Canada</td>\n",
       "      <td>5</td>\n",
       "      <td>7.427</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.404</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.316</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.328</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.278</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Country  Rank 2015  Score 2015  Rank 2016  Score 2016  Rank 2017  \\\n",
       "0  Switzerland          1       7.587        2.0       7.509        4.0   \n",
       "1      Iceland          2       7.561        3.0       7.501        3.0   \n",
       "2      Denmark          3       7.527        1.0       7.526        2.0   \n",
       "3       Norway          4       7.522        4.0       7.498        1.0   \n",
       "4       Canada          5       7.427        6.0       7.404        7.0   \n",
       "\n",
       "   Score 2017  Rank 2018  Score 2018  Rank 2019  Score 2019  \n",
       "0       7.494        5.0       7.487        6.0       7.480  \n",
       "1       7.504        4.0       7.495        4.0       7.494  \n",
       "2       7.522        3.0       7.555        2.0       7.600  \n",
       "3       7.537        2.0       7.594        3.0       7.554  \n",
       "4       7.316        7.0       7.328        9.0       7.278  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#check the first five rows of fully merged df\n",
    "happiness_index.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Rank 2015</th>\n",
       "      <th>Score 2015</th>\n",
       "      <th>Rank 2016</th>\n",
       "      <th>Score 2016</th>\n",
       "      <th>Rank 2017</th>\n",
       "      <th>Score 2017</th>\n",
       "      <th>Rank 2018</th>\n",
       "      <th>Score 2018</th>\n",
       "      <th>Rank 2019</th>\n",
       "      <th>Score 2019</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>1</td>\n",
       "      <td>7.587</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.509</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.494</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.487</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>2</td>\n",
       "      <td>7.561</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.501</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.504</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.495</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>3</td>\n",
       "      <td>7.527</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.526</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.522</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.555</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Norway</td>\n",
       "      <td>4</td>\n",
       "      <td>7.522</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.498</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.537</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.594</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Canada</td>\n",
       "      <td>5</td>\n",
       "      <td>7.427</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.404</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.316</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.328</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.278</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Country  Rank 2015  Score 2015  Rank 2016  Score 2016  Rank 2017  \\\n",
       "0  Switzerland          1       7.587        2.0       7.509        4.0   \n",
       "1      Iceland          2       7.561        3.0       7.501        3.0   \n",
       "2      Denmark          3       7.527        1.0       7.526        2.0   \n",
       "3       Norway          4       7.522        4.0       7.498        1.0   \n",
       "4       Canada          5       7.427        6.0       7.404        7.0   \n",
       "\n",
       "   Score 2017  Rank 2018  Score 2018  Rank 2019  Score 2019  \n",
       "0       7.494        5.0       7.487        6.0       7.480  \n",
       "1       7.504        4.0       7.495        4.0       7.494  \n",
       "2       7.522        3.0       7.555        2.0       7.600  \n",
       "3       7.537        2.0       7.594        3.0       7.554  \n",
       "4       7.316        7.0       7.328        9.0       7.278  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#print the first five rows again\n",
    "happiness_index.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "#replace na values with 0\n",
    "happiness_index.fillna(0, inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .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</th>\n",
       "      <th>Rank 2015</th>\n",
       "      <th>Score 2015</th>\n",
       "      <th>Rank 2016</th>\n",
       "      <th>Score 2016</th>\n",
       "      <th>Rank 2017</th>\n",
       "      <th>Score 2017</th>\n",
       "      <th>Rank 2018</th>\n",
       "      <th>Score 2018</th>\n",
       "      <th>Rank 2019</th>\n",
       "      <th>Score 2019</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>1</td>\n",
       "      <td>7.587</td>\n",
       "      <td>2</td>\n",
       "      <td>7.509</td>\n",
       "      <td>4</td>\n",
       "      <td>7.494</td>\n",
       "      <td>5</td>\n",
       "      <td>7.487</td>\n",
       "      <td>6</td>\n",
       "      <td>7.480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Iceland</td>\n",
       "      <td>2</td>\n",
       "      <td>7.561</td>\n",
       "      <td>3</td>\n",
       "      <td>7.501</td>\n",
       "      <td>3</td>\n",
       "      <td>7.504</td>\n",
       "      <td>4</td>\n",
       "      <td>7.495</td>\n",
       "      <td>4</td>\n",
       "      <td>7.494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>3</td>\n",
       "      <td>7.527</td>\n",
       "      <td>1</td>\n",
       "      <td>7.526</td>\n",
       "      <td>2</td>\n",
       "      <td>7.522</td>\n",
       "      <td>3</td>\n",
       "      <td>7.555</td>\n",
       "      <td>2</td>\n",
       "      <td>7.600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Norway</td>\n",
       "      <td>4</td>\n",
       "      <td>7.522</td>\n",
       "      <td>4</td>\n",
       "      <td>7.498</td>\n",
       "      <td>1</td>\n",
       "      <td>7.537</td>\n",
       "      <td>2</td>\n",
       "      <td>7.594</td>\n",
       "      <td>3</td>\n",
       "      <td>7.554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Canada</td>\n",
       "      <td>5</td>\n",
       "      <td>7.427</td>\n",
       "      <td>6</td>\n",
       "      <td>7.404</td>\n",
       "      <td>7</td>\n",
       "      <td>7.316</td>\n",
       "      <td>7</td>\n",
       "      <td>7.328</td>\n",
       "      <td>9</td>\n",
       "      <td>7.278</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Country  Rank 2015  Score 2015  Rank 2016  Score 2016  Rank 2017  \\\n",
       "0  Switzerland          1       7.587          2       7.509          4   \n",
       "1      Iceland          2       7.561          3       7.501          3   \n",
       "2      Denmark          3       7.527          1       7.526          2   \n",
       "3       Norway          4       7.522          4       7.498          1   \n",
       "4       Canada          5       7.427          6       7.404          7   \n",
       "\n",
       "   Score 2017  Rank 2018  Score 2018  Rank 2019  Score 2019  \n",
       "0       7.494          5       7.487          6       7.480  \n",
       "1       7.504          4       7.495          4       7.494  \n",
       "2       7.522          3       7.555          2       7.600  \n",
       "3       7.537          2       7.594          3       7.554  \n",
       "4       7.316          7       7.328          9       7.278  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "happiness_index['Rank 2016'] = happiness_index['Rank 2016'].astype(int)\n",
    "happiness_index['Rank 2017'] = happiness_index['Rank 2017'].astype(int)\n",
    "happiness_index['Rank 2018'] = happiness_index['Rank 2018'].astype(int)\n",
    "happiness_index['Rank 2019'] = happiness_index['Rank 2019'].astype(int)\n",
    "happiness_index.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[7.49399996 7.50400019 7.52199984 7.53700018 7.31599998 7.46899986\n",
      " 7.37699986 7.28399992 7.31400013 7.21299982 7.079      7.00600004\n",
      " 6.57800007 6.99300003 6.63500023 6.86299992 6.97700024 6.89099979\n",
      " 6.64799976 6.71400023 0.         5.25       6.57200003 6.45200014\n",
      " 6.95100021 6.65199995 6.375      6.44199991 6.59899998 6.60900021\n",
      " 6.454      6.35699987 6.42399979 6.34399986 6.40299988 6.52699995\n",
      " 6.10500002 6.16800022 6.00299978 5.97100019 6.09800005 5.92000008\n",
      " 5.83799982 6.0079999  6.08699989 5.96400023 5.82299995 5.49300003\n",
      " 5.81899977 5.7579999  5.90199995 6.0710001  5.71500015 5.56899977\n",
      " 5.97300005 6.08400011 5.29300022 5.5250001  5.96299982 5.31099987\n",
      " 5.80999994 5.62099981 5.87200022 5.27899981 5.82200003 5.62900019\n",
      " 5.61100006 5.26200008 5.07399988 5.5        5.00400019 5.01100016\n",
      " 5.23400021 5.26900005 5.33599997 5.23699999 5.27299976 4.51399994\n",
      " 5.82499981 5.39499998 5.19500017 5.8499999  5.42999983 5.23500013\n",
      " 5.17500019 4.55000019 4.64400005 5.18200016 3.80800009 5.23000002\n",
      " 4.95499992 5.22700024 5.2249999  5.32399988 5.18100023 5.04099989\n",
      " 4.80499983 4.7750001  4.6079998  4.69199991 4.09600019 4.49700022\n",
      " 4.829      4.11999989 3.875      3.53299999 4.31500006 4.13899994\n",
      " 3.60299993 4.28000021 4.96199989 4.46000004 4.70900011 4.29199982\n",
      " 4.55299997 4.37599993 3.76600003 4.54500008 4.28599977 3.97000003\n",
      " 4.44000006 4.69500017 4.71400023 4.73500013 3.59299994 3.79500008\n",
      " 4.19000006 4.29099989 4.08099985 4.53499985 4.46500015 4.02799988\n",
      " 4.16800022 3.34899998 3.64400005 2.69300008 3.93600011 3.50699997\n",
      " 4.17999983 4.03200006 3.79399991 3.47099996 3.65700006 3.46199989\n",
      " 2.90499997 3.49499989]\n"
     ]
    }
   ],
   "source": [
    "#look for na values or anything that stands out \n",
    "unique_values = happiness_index['Score 2017'].unique()\n",
    "print(unique_values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "happiness_index['Score 2017'] = happiness_index['Score 2017'].round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "#export file into a cleaned dataset csv file\n",
    "file_path = 'Cleaned_Datasets/cleaned_happiness_index.csv'\n",
    "happiness_index.to_csv(file_path, index=False)"
   ]
  }
 ],
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