Done.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. Loading & cleaning the datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "sns.set(style=\"whitegrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['adultliteracy.csv',\n",
       " 'badteeth.csv',\n",
       " 'gdp.csv',\n",
       " 'healthexpend.csv',\n",
       " 'population.csv',\n",
       " 'sugar_consumption.csv']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(\"Data\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.1. Adult Literacy Rate (%)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "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>X1975</th>\n",
       "      <th>X1976</th>\n",
       "      <th>X1977</th>\n",
       "      <th>X1978</th>\n",
       "      <th>X1979</th>\n",
       "      <th>X1980</th>\n",
       "      <th>X1981</th>\n",
       "      <th>X1982</th>\n",
       "      <th>X1983</th>\n",
       "      <th>X1984</th>\n",
       "      <th>...</th>\n",
       "      <th>X2002</th>\n",
       "      <th>X2003</th>\n",
       "      <th>X2004</th>\n",
       "      <th>X2005</th>\n",
       "      <th>X2006</th>\n",
       "      <th>X2007</th>\n",
       "      <th>X2008</th>\n",
       "      <th>X2009</th>\n",
       "      <th>X2010</th>\n",
       "      <th>X2011</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.157681</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>39.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\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",
       "      <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>95.93864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>96.845299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\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",
       "      <td>...</td>\n",
       "      <td>69.8735</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>72.648679</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>Andorra</th>\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",
       "      <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>Angola</th>\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",
       "      <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>70.362420</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 37 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             X1975  X1976  X1977  X1978      X1979  X1980  X1981  X1982  \\\n",
       "Country                                                                   \n",
       "Afghanistan    NaN    NaN    NaN    NaN  18.157681    NaN    NaN    NaN   \n",
       "Albania        NaN    NaN    NaN    NaN        NaN    NaN    NaN    NaN   \n",
       "Algeria        NaN    NaN    NaN    NaN        NaN    NaN    NaN    NaN   \n",
       "Andorra        NaN    NaN    NaN    NaN        NaN    NaN    NaN    NaN   \n",
       "Angola         NaN    NaN    NaN    NaN        NaN    NaN    NaN    NaN   \n",
       "\n",
       "             X1983  X1984  ...    X2002  X2003  X2004  X2005      X2006  \\\n",
       "Country                    ...                                            \n",
       "Afghanistan    NaN    NaN  ...      NaN    NaN    NaN    NaN        NaN   \n",
       "Albania        NaN    NaN  ...      NaN    NaN    NaN    NaN        NaN   \n",
       "Algeria        NaN    NaN  ...  69.8735    NaN    NaN    NaN  72.648679   \n",
       "Andorra        NaN    NaN  ...      NaN    NaN    NaN    NaN        NaN   \n",
       "Angola         NaN    NaN  ...      NaN    NaN    NaN    NaN        NaN   \n",
       "\n",
       "             X2007     X2008  X2009  X2010      X2011  \n",
       "Country                                                \n",
       "Afghanistan    NaN       NaN    NaN    NaN  39.000000  \n",
       "Albania        NaN  95.93864    NaN    NaN  96.845299  \n",
       "Algeria        NaN       NaN    NaN    NaN        NaN  \n",
       "Andorra        NaN       NaN    NaN    NaN        NaN  \n",
       "Angola         NaN       NaN    NaN    NaN  70.362420  \n",
       "\n",
       "[5 rows x 37 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load adult literacy and set index\n",
    "literacy_full = pd.read_csv(\"Data/adultliteracy.csv\")\n",
    "literacy_full.rename(columns={literacy_full.columns[0]:\"Country\"}, inplace=True)\n",
    "literacy_full.set_index(\"Country\", inplace=True)\n",
    "literacy_full.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "106 countries with no data\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Country\n",
       "Afghanistan           39.000000\n",
       "Albania               98.712978\n",
       "Algeria               72.648679\n",
       "Angola                70.362420\n",
       "Anguilla              95.407098\n",
       "                        ...    \n",
       "West Bank and Gaza    95.267242\n",
       "Vietnam               93.359470\n",
       "Yemen, Rep.           65.261950\n",
       "Zambia                69.149218\n",
       "Zimbabwe              83.582714\n",
       "Name: literacy, Length: 156, dtype: float64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Using max instead of mean here is a better choice (why?)\n",
    "literacy = literacy_full.max(axis=1)\n",
    "print(sum(literacy.isna()), \"countries with no data\")\n",
    "literacy.dropna(inplace=True)\n",
    "literacy.name = \"literacy\"\n",
    "literacy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24fb944b160>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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P3v0HHe79gMdH8ZvCS3p6WrF8Gee9+ZNDmfaN7103lOk+3bgGIEmVsgAkqVIWgCRVygKQpEoV3QkcEc8EvgC8MjPvi4hzgU3AKmBrZm4sOX1pUPbs3c+K5cuKTmOho2vm9u5nsvC09fRUrAAi4kXA+4ET289XAZuBs4EHgJsjYm1m3loqgzQowz4iZhjT9kic8VdyE9DFwBuB3e3nZwI7M3NXZu4DtgDnF5y+JOkQiq0BZOZFABExP+hYYLbjJbPAcb2Od2Zm5ilne6JWq9X3cZYyLlnHJSf0J6snP2kQ+v13NcgTwQ4DDnQ8nwAe63UkU1NTTE5O9i1Uq9Uamz/ecck6LjlhvLJKS/ldnZubW3DBeZBHAT0IHNPxfDXf2zwkSRqwQa4B3AlERKwBdgHraXYK62nmpJNfOLRp93pEjEv/qtnACiAzH42IDcB2YCVwC7BtUNPX4Bx5xEqPiJHGQPECyMzndzzeAZxaepqSpMV5JrAkVcoCkKRKWQCSVCkLQJIqZQFIUqUsAEmqVDUFMMwbWC80bUkapmpuCj/sy/VK0qipZg1AkvR4FoAkVcoCkKRKWQCSVCkLQJIqZQFIUqUsAEmqlAUgSZWyACSpUhaAJFXKAhiAfl0LqNfrFs15DSJJh1DNtYCGaVjXIfIG6ZIOxTUASarUUNYAImI9sBFYDvx+Zr5vGDkkqWYDXwOIiH8PvBM4CzgNeENE/NCgc0hS7YaxBnAu8NnM/CZARGwDXgNcvcj7lgHs2bNnyRM+6shlS37vUzE3NzeUadc23WFO2//nOqY97P/npej4znxS8IkDBw48hUi9i4hfA47MzI3t5xcBZ2bmGw71vlardRbwVwOIKElPRy+Znp6+vXPAMNYADgM6W2cCeKyL930JeAkwC3h8oyR1ZxlwDM136OMMowAepPkin7ca2L3Ym6anp+eA2xd7nSTpSf7hYAOHUQCfAd4eEc8BHgH+E3DIzT+SpP4b+FFAmflPwG8AnwPuAj6cmX896BySVLuB7wSWJI0GzwSWpEpZAJJUKQtAkiplAUhSpaq6HHREXE1z2YkDwHWZuSkizgU2AauArfNnKI+KiPhd4NmZuWEUs0bE54DnAnvbgy4BnsGI5QSIiPOAq4Ajgdsy8/IRnacXAZd1DHoB8CHgE4xYVoCI+Dng19pPb83MK0Z0vl4JvB6Yo8n0zlHLGRHPBL4AvDIz71soX0ScBnwAeCbwv4FLM3Nfr9Or5iigiDib5iJ0L6W5CundwKuAG4GzgQeAm2muTnrrkGI+TkScA9xAk+u/AskIZY2ICZoT+46f/+WLiFWjlrOd6wSaS4m8CPgX4LPAu4BrGbGsnSLihTRf/C8HPs+IZY2II2h+B04EvkWT8b8B72OEsnZ8kZ5Fc/7Rx4GtwG+PSs6IeBHwfuAkmvn5LyzwtxQRM8BFmXlHRFwHfDkzr+l1mtVsAsrMvwRe1v6iei7N2s9RwM7M3NUevgU4f4gx/01EHE1TWO9qDzqT0csa7f/eFhF/GxGXMZo5AV5NswT1YGbuBS4AvstoZu10DfDrwAmMZtZlNN8jR9IsWC0HvsPoZf0R4NOZ+Z3M3A/8L+AiRivnxcAb+d6VEQ76txQRxwOrMvOO9uuuZ4m5qykAgMzcGxHvoFn63wEcS3NtoXmzwHHDyHYQ19KcMPd/289HMeuzaObjq4FzgEuBH2D0cgKsAZZFxKci4i7glxjNefpv2kutqzLzo4xo1sx8GHgbcA/NmsB9jGbWvwF+MiKOjoiVwM/QrA2MTM7MvCgzOy94udB87Nv8raoAADLzKuA5wPNoVrOWcmG6otrbgB/IzB0dg5d6Eb1iMvOLmfnzmfntzPw6cB3NZb1HKmfb4TSXIv9F4MdoNgWdwGhmnXcJzWYLGMHPHyAiTgF+ATie5otpPyP4d9X+W7oe+Auapf/baX4nRirnEyz0mfftd6GancARcRKwMjPvyszvRsTHaHYId15ZtKsL0w3ABcAx7SXVo4Hvo/kDG6msEXEWMNlRVBM0S4DHdLxs6Dnb/hn4TGZ+DSAiPk6z2jxS83ReRKyg2fa7oT3oQUZzvv4ksCMzHwKIiOuBKxix+RoRzwC2Z+am9vO30JTBKM7TeQt95n37XaimAGiW9t7R/tI6AKyj2czyOxGxBtgFrAc2Dy9iIzNfMf84IjbQ7Li+FNg5YlmPAq6OiBfTbPt9HU3Oj4xYToCbgA9GxFHAw8BaYBtw5QhmBTgFuDczH2k/vxOIEcz6t8B7IuJImn0q59FkvXDEsr4A+POIOJ1mf8Uvtv/dMGI5Ox30M8/M+yPi0Yj48cz8PPBfgCXtuK5mE1Bm3kKzF/0rQAv4QmbeQLOEtZ1mv8A9NF8KIyczH2XEsmbmTTx+nm7OzC8yYjkBMvNO4D00q/53A/fT7GDdwIhlbTuBZkkPGM3PHyAzbwP+J83n/1WaBYG3M2JZM/Or7TxfBf6a5miazzNiOTst8plfCPxeRNxDs4XgD5YyjWoOA5UkPV41awCSpMezACSpUhaAJFXKApCkSlkAklQpC0CSKmUBSFKlLABJqtT/BxNJK3haRUTYAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "literacy.plot.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1.2. Bad Teeth (# of bad teeth per child)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Country\n",
       "Afghanistan    2.90\n",
       "Albania        3.02\n",
       "Algeria        2.30\n",
       "Angola         1.70\n",
       "Anguilla       2.50\n",
       "               ... \n",
       "Venezuela      2.10\n",
       "Vietnam        1.90\n",
       "Yemen, Rep.    3.10\n",
       "Zambia         2.30\n",
       "Zimbabwe       1.30\n",
       "Name: bad_teeth, Length: 190, dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bad_teeth_full = pd.read_csv(\"Data/badteeth.csv\")\n",
    "bad_teeth_full.rename(columns={bad_teeth_full.columns[0]:\"Country\"}, inplace=True)\n",
    "bad_teeth_full.set_index(\"Country\", inplace=True)\n",
    "bad_teeth = bad_teeth_full.X2004.dropna()\n",
    "bad_teeth.name = \"bad_teeth\"\n",
    "bad_teeth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24fb9708d30>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bad_teeth.plot.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.3. GDP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Country\n",
       "Albania                 1454.022854\n",
       "Algeria                 2043.135713\n",
       "Andorra                20254.346287\n",
       "Angola                   353.231466\n",
       "Antigua and Barbuda    10599.284668\n",
       "                           ...     \n",
       "West Bank and Gaza      1029.051966\n",
       "Vietnam                  506.938950\n",
       "Yemen                    559.999172\n",
       "Zambia                   349.085472\n",
       "Zimbabwe                 383.707665\n",
       "Name: gdp, Length: 194, dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdp_full = pd.read_csv(\"Data/gdp.csv\")\n",
    "gdp_full.rename(columns={gdp_full.columns[0]:\"Country\"}, inplace=True)\n",
    "gdp_full.set_index(\"Country\", inplace=True)\n",
    "gdp = gdp_full.X2004.dropna()\n",
    "gdp.name = \"gdp\"\n",
    "gdp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24fb984d710>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "gdp.plot.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.4. Healthcare Spending (US$ per person)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Country\n",
       "Afghanistan       1.614160\n",
       "Albania          63.935601\n",
       "Algeria          63.229395\n",
       "Andorra        1517.211905\n",
       "Angola           19.664783\n",
       "                  ...     \n",
       "Vanuatu          45.755352\n",
       "Venezuela        99.022717\n",
       "Vietnam           8.373131\n",
       "Yemen            14.460323\n",
       "Zambia           18.407207\n",
       "Name: health_spend, Length: 190, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "health_spend_full = pd.read_csv(\"Data/healthexpend.csv\")\n",
    "health_spend_full.rename(columns={health_spend_full.columns[0]:\"Country\"}, inplace=True)\n",
    "health_spend_full.set_index(\"Country\", inplace=True)\n",
    "health_spend = health_spend_full.X2004.dropna()\n",
    "health_spend.name = \"health_spend\"\n",
    "health_spend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24fb989a898>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "health_spend.plot.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.5. Sugar Consumption (g per day, per person)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Country\n",
       "Albania                 65.75\n",
       "Algeria                 84.93\n",
       "Angola                  35.62\n",
       "Antigua and Barbuda     95.89\n",
       "Argentina              112.33\n",
       "                        ...  \n",
       "West Bank and Gaza      90.41\n",
       "Vietnam                 35.62\n",
       "Yemen, Rep.             65.75\n",
       "Zambia                  46.58\n",
       "Zimbabwe               104.11\n",
       "Name: sugar, Length: 175, dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sugar_full = pd.read_csv(\"Data/sugar_consumption.csv\")\n",
    "sugar_full.rename(columns={sugar_full.columns[0]:\"Country\"}, inplace=True)\n",
    "sugar_full.set_index(\"Country\", inplace=True)\n",
    "sugar = sugar_full.X2004.dropna()\n",
    "sugar.name = \"sugar\"\n",
    "sugar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24fb994b550>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sugar.plot.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Merging datasets & basic correlations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "119 countries remaining\n"
     ]
    },
    {
     "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>bad_teeth</th>\n",
       "      <th>sugar</th>\n",
       "      <th>gdp</th>\n",
       "      <th>literacy</th>\n",
       "      <th>health_spend</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>3.02</td>\n",
       "      <td>65.75</td>\n",
       "      <td>1454.022854</td>\n",
       "      <td>98.712978</td>\n",
       "      <td>63.935601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>2.30</td>\n",
       "      <td>84.93</td>\n",
       "      <td>2043.135713</td>\n",
       "      <td>72.648679</td>\n",
       "      <td>63.229395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Angola</th>\n",
       "      <td>1.70</td>\n",
       "      <td>35.62</td>\n",
       "      <td>353.231466</td>\n",
       "      <td>70.362420</td>\n",
       "      <td>19.664783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Antigua and Barbuda</th>\n",
       "      <td>0.70</td>\n",
       "      <td>95.89</td>\n",
       "      <td>10599.284668</td>\n",
       "      <td>98.950000</td>\n",
       "      <td>290.616312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>3.40</td>\n",
       "      <td>112.33</td>\n",
       "      <td>7492.249508</td>\n",
       "      <td>97.858770</td>\n",
       "      <td>173.801947</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     bad_teeth   sugar           gdp   literacy  health_spend\n",
       "Country                                                                      \n",
       "Albania                   3.02   65.75   1454.022854  98.712978     63.935601\n",
       "Algeria                   2.30   84.93   2043.135713  72.648679     63.229395\n",
       "Angola                    1.70   35.62    353.231466  70.362420     19.664783\n",
       "Antigua and Barbuda       0.70   95.89  10599.284668  98.950000    290.616312\n",
       "Argentina                 3.40  112.33   7492.249508  97.858770    173.801947"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.merge(bad_teeth, sugar, left_index=True, right_index=True)\\\n",
    "    .merge(gdp, left_index=True, right_index=True)\\\n",
    "    .merge(literacy, left_index=True, right_index=True)\\\n",
    "    .merge(health_spend, left_index=True, right_index=True)\n",
    "print(len(data), \"countries remaining\")\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>bad_teeth</th>\n",
       "      <th>sugar</th>\n",
       "      <th>gdp</th>\n",
       "      <th>literacy</th>\n",
       "      <th>health_spend</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>bad_teeth</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.366839</td>\n",
       "      <td>0.084987</td>\n",
       "      <td>0.372845</td>\n",
       "      <td>0.014250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sugar</th>\n",
       "      <td>0.366839</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.394889</td>\n",
       "      <td>0.568284</td>\n",
       "      <td>0.320016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gdp</th>\n",
       "      <td>0.084987</td>\n",
       "      <td>0.394889</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.362225</td>\n",
       "      <td>0.768014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>literacy</th>\n",
       "      <td>0.372845</td>\n",
       "      <td>0.568284</td>\n",
       "      <td>0.362225</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.356778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>health_spend</th>\n",
       "      <td>0.014250</td>\n",
       "      <td>0.320016</td>\n",
       "      <td>0.768014</td>\n",
       "      <td>0.356778</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              bad_teeth     sugar       gdp  literacy  health_spend\n",
       "bad_teeth      1.000000  0.366839  0.084987  0.372845      0.014250\n",
       "sugar          0.366839  1.000000  0.394889  0.568284      0.320016\n",
       "gdp            0.084987  0.394889  1.000000  0.362225      0.768014\n",
       "literacy       0.372845  0.568284  0.362225  1.000000      0.356778\n",
       "health_spend   0.014250  0.320016  0.768014  0.356778      1.000000"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24fb99d21d0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "sns.heatmap(data.corr(), cmap=\"Reds\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. Linear Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24fb9a67630>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x=\"literacy\", y=\"bad_teeth\", data=data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24fb9ad7320>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x=\"sugar\", y=\"bad_teeth\", data=data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24fb9b64710>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x=\"gdp\", y=\"bad_teeth\", data=data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24fb9ad7da0>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x=\"health_spend\", y=\"bad_teeth\", data=data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4. Predictive Modelling\n",
    "## 4.1. Setting Up Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from sklearn.model_selection import KFold\n",
    "from sklearn.metrics import mean_squared_error\n",
    "def get_features(data, target = \"bad_teeth\"):\n",
    "    return [x for x in data.columns if x != target]\n",
    "    \n",
    "def evaluate(model, data, target = \"bad_teeth\"):\n",
    "    features = get_features(data, target)\n",
    "    results = []\n",
    "    kf = KFold(5, shuffle=True) \n",
    "    for train_index, test_index in kf.split(data): \n",
    "        train = data.iloc[train_index]\n",
    "        test = data.iloc[test_index]\n",
    "        \n",
    "        model.fit(train[features], train[target])\n",
    "        predictions = model.predict(test[features])\n",
    "        \n",
    "        error = mean_squared_error(test[target], predictions)\n",
    "        print(\"Fold score:\", error)\n",
    "        results.append(error)\n",
    "    \n",
    "    mean_score = np.mean(results)\n",
    "    print(\"-------------------\")\n",
    "    print(\"AVG:\", mean_score)\n",
    "    return mean_score\n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.2. Evaluating Your First Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fold score: 1.2666931056614592\n",
      "Fold score: 1.3061031609626743\n",
      "Fold score: 0.9732236247543472\n",
      "Fold score: 1.1040711334857796\n",
      "Fold score: 1.6614447191263555\n",
      "-------------------\n",
      "AVG: 1.2623071487981232\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "evaluate(LinearRegression(), data);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fold score: 1.6798514720833333\n",
      "Fold score: 1.7201559912499995\n",
      "Fold score: 1.3139636120833322\n",
      "Fold score: 1.4419775295833333\n",
      "Fold score: 0.9817523134782613\n",
      "-------------------\n",
      "AVG: 1.427540183695652\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "evaluate(RandomForestRegressor(100), data);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.3. Measuring Feature Impact & Importance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_feature_weights(data):\n",
    "    target = \"bad_teeth\"\n",
    "    lr = LinearRegression()\n",
    "    features = get_features(data)\n",
    "    lr.fit(data[features], data[target])\n",
    "    return dict(zip(features, lr.coef_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'sugar': 0.007505667886811191,\n",
       " 'gdp': 6.027750523175565e-06,\n",
       " 'literacy': 0.019269338494403564,\n",
       " 'health_spend': -0.00076063053178074}"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_feature_weights(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_feature_importances(data):\n",
    "    target = \"bad_teeth\"\n",
    "    rf = RandomForestRegressor(100)\n",
    "    features = get_features(data)\n",
    "    rf.fit(data[features], data[target])\n",
    "    importances = pd.DataFrame(index=features, data=rf.feature_importances_, columns=[\"Feature Importance\"])\n",
    "    importances.plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_feature_importances(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.4. Add More Features!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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LTAdOTztnGDATmJa2/wjgPDP7h5lNNbPOra5YREQ2SyZDOr2AFSnbK4B+qSe4+20AZnZ02rUrgNuB+cAtwL1EfxwyUlZWlumpjWrtuhZtpbS0NOkS1BYp1BZtb3t4LSH8XmQS+O2A2pTtPGBDJt/c3YfUfW1m44EPsimuqKiIDh06ZHNJTsqVX6RcoLaot720RWlp6XbzWnJBa9qyoqKi2Y5yJkM65UDPlO0ewMctXWRmnczs8pRdeUB1Bj9PRES2gEwCfw5wvJl1M7MdgaHAixlc9xVwtZkdGW+PAJ7evDJFRKS1Wgx8d18OXA/MAxYBJe6+wMxmm1nfZq6rAc4AJpnZYqJZPle3TdkiIpKtjObhu3sJUJK276RGzjs/bftV4PBW1CciIm1Ed9qKiARCgS8SsBAe6yf19IhDkYCF8Fg/qacevohIIBT4IiKBUOCLiARCgS8iEggFvohIIBT4IiKBUOCLiARCgS8iEggFvohIIBT4IiKBUOCLiARCgS8iEggFvohIIBT4IiKBUOCLiARCgS8iEggFvohIIBT4IiKBUOCLiARCgS8iEggFvohIIBT4IiKBUOCLiARCgS8iEggFvohIINpncpKZnQ2MBAqAie5+XxPnPQrMdfdH4u09galAd8CBYe7+VRvULSIiWWqxh29mvYFxwNHAocBwMzso7ZxeZjYLOD3t8vuB+939AGAhcEObVC0iIlnLZEhnAFGvfbW7rwWm0zDYhwEzgWl1O8ysADg2Ph/gEeAnrS1YREQ2TyZDOr2AFSnbK4B+qSe4+20AZnZ0yu6uwJfuXp1yXZ9siisrK8vm9AaKi4tbdX1bKS0tTboEtUUKtUU9tUW9ENoik8BvB9SmbOcBGzbjOjK8bqOioiI6dOiQzSU5KVd+kXKB2qKe2qKe2qJea9qioqKi2Y5yJkM65UDPlO0ewMcZXLcK6GRm+fF2zwyvExGRLSCTwJ8DHG9m3cxsR2Ao8GJLF7l7FfAqcGa861zghc0tVEREWqfFwHf35cD1wDxgEVDi7gvMbLaZ9W3h8ouJZvW8CxxDNLVTREQSkNE8fHcvAUrS9p3UyHnnp20vBY7b/PJERKSt6E5bEZFAKPBFRAKhwBcRCYQCX0QkEAp8EZFAKPBFRAKhwBcRCYQCX0QkEAp8EZFAKPBFRAKhwBcRCYQCX0QkEAp8EZFAKPBFRAKhwBcRCYQCX0QkEAp8EZFAKPBFRAKhwBcRCYQCX0QkEAp8EZFAKPBFRAKhwBcRCYQCX0QkEAp8EZFAKPBFRAKhwBcRCYQCX0QkEO0zOcnMzgZGAgXARHe/L+34ocBkYFfgz8BF7l5tZucBtwIr41Ofd/fr26p4ERHJXIs9fDPrDYwDjgYOBYab2UFpp00FRrj7/kAe8It4f1/gCnc/NP5PYS8ikpBMhnQGAHPdfbW7rwWmA6fXHTSzvYAd3P31eNcjwE/ir48AzjOzf5jZVDPr3Hali4hINjIJ/F7AipTtFUCfDI+vAG4GDgGWAfdudqUiItIqmYzhtwNqU7bzgA2ZHHf3IXU7zWw88EE2xZWVlWVzegPFxcWtur6tlJaWJl2C2iKF2qKe2qJeCG2RSeCXA8ekbPcAPk473jP9uJl1An7u7hPi/XlAdTbFFRUV0aFDh2wuyUm58ouUC9QW9dQW9dQW9VrTFhUVFc12lDMZ0pkDHG9m3cxsR2Ao8GLdQXdfCqw3s/+Id50DvAB8BVxtZkfG+0cAT2f/EkREpC20GPjuvhy4HpgHLAJK3H2Bmc02s77xacOACWb2T2Bn4G53rwHOACaZ2WKgGLh6S7wIERFpWUbz8N29BChJ23dSytdvAf0aue5V4PBW1igiIm1Ad9qKiARCgS8iEggFvohIIBT4IiKBUOCLiARCgS8iEggFvohIIBT4IiKBUOCLiARCgS8iEggFvohIIBT4IiKBUOCLiARCgS8iEggFvohIIBT4IiKBUOCLiARCgS8iEggFvohIIBT4IiKBUOCLiARCgS8iEggFvohIIBT4IiKBUOCLiARCgS8iEggFvohIIBT4IiKBUOCLiASifSYnmdnZwEigAJjo7velHT8UmAzsCvwZuMjdq81sT2Aq0B1wYJi7f9WG9YuISIZa7OGbWW9gHHA0cCgw3MwOSjttKjDC3fcH8oBfxPvvB+539wOAhcANbVW4iIhkJ5Me/gBgrruvBjCz6cDpwE3x9l7ADu7+enz+I8AYM5sMHAucmrL/FeA3GfzMfIDKysqMXkRzdtspv9XfozUqKioS/fmp1Bb11Bb11Bb1tvW2SMnMRl9IJoHfC1iRsr0C6NfC8T5AV+BLd69O25+JngDvvfdehqc37bLBPVv9PVqjrKws0Z+fSm1RT21RT21Rbztqi57AB+k7Mwn8dkBtynYesCGD4+n7SbuuOW8CxxD9kajJ8BoRkdDlE4X9m40dzCTwy4nCt04P4OO04z0bOb4K6GRm+e5eE5+Tel2TiouLK4DXMjlXREQ20aBnXyeTaZlzgOPNrJuZ7QgMBV6sO+juS4H1ZvYf8a5zgBfcvQp4FTgz3n8u8MJmFC8iIm2gxcB39+XA9cA8YBFQ4u4LzGy2mfWNTxsGTDCzfwI7A3fH+y8mmtXzLtG7hJFt/QJERCQzebW16cPsIiKyPdKdtiIigVDgi4gEQoEvIhIIBb6ISCAU+CIigVDgi4gEIqPlkUNiZr90998lXYfkFjN7h2gBwMfc/ZOEy0mEmZ3b3HF3f3Rr1SKbR4Hf0KWAAh+In2dwD/ADoIroTunL3P3TRAtLxklEd4vPM7MPgYeBmfEd5aH4fvy/3wL2BWYD1cCJwDtAcIFvZr8gWj6+S7wrD6h192SX3WyCbrxKY2YvAB2AN4B1dfvd/abEikqImb0KPAlMIRr++zlwgruflGhhCTOzIUR3k+8IPAbc7O6fJ1vV1mNm84CfuPtn8XZn4Bl3759sZVufmS0BBrn7O0nXkgn18Bt6PeXrvMSqyA27uvu9KdsTzOz8pIpJkpntTPQciHOA3sAk4Ami3u1LQN+mr97u9AJWp2yvZdMFFEOyalsJe1DgN+DuY1K3zSwP2CehcpI238x+6u5TAczsZODvCdeUlCXAc8AYd/9z3U4zmwSckFhVyXgeeNnMZhB1is4geicYjJTPM5aa2UxgJtHwFpC7n2doSCeNmQ0Hbgd2Stm9xN33TaikxJjZSqAb0dBWLdEQRp2cHafcEsxsF2Bfd/+7mXUCit19btJ1JcXMhgLHEf1ezHH3Z5OtaOsys4ebOVzr7j/fasVkQT38hq4FvgOMJVol9CTgP5q9Yjvl7t9IuoYcch1QDPyQ6A/fKDM71t1HJ1pVcv5J9MyLPIC4Lf7c/CXbD3f/GYCZneDuL6ceM7PTkqmqZQr8hla5+xIz+wdwsLvfb2YXJ13U1mRmo5o7HuIH2MApRB0B3H2FmQ0gGt4anWRRSTCz+4jaI/VBG7VEs7mCYGZnEk3uuCnt30t7os7BjEQKa4ECv6G1ZvZ94G3gVDN7E9gh4Zq2troPq/sRPYf4v4nGJ4cAHyVUU9LaE/0efBVvF9LwEZ6h+CFg7r6uxTO3X7sQvfPfhfrpqhD9O7k+kYoyoMBv6L+AC4Ar4/91AuvF1X1wbWZ/AY5y96/j7YlED8IJ0e+AUjObRRT0JwH3JVtSYj4k8Bls7j4ZmGxmv3b325OuJ1MK/DTuXgZcHm8OTbKWHNCNTXuxhcDuCdWSKHefEN+X0J/oJrSfunuoM5ZWA++a2Xxgfd3OXP2gcgsbYGb/B5hLNIvr5boOUi5S4Kcxs/eJnvxep5Zolspi4NfxM3xD8SCw0MxmE914NQiYmGxJyTCzDsAe1H9QeaiZDXH3Zj/v2E69SMpzrUPm7ieaWUeiYZ2BxI96zdWbExX4Db1A9Jb1D/H2MOAIYBbwEDAgobqS8ClRO9T18qcCn5pZUfxOKCR/BDoTLSnwKtE/8NcSrSgh7j7FzPYGvk1009ke7r4k2aqSYWbdiN71HUf03O7VwLtJ1tQcrZbZ0NHuPtHdv4z/mwQc4u5PE95wxo+JHkTfm+jD23OAS4CHzezy5i7cDh1CNAvlaWA80Qd2eydZUFLiGSqzgLuI/k381cx+mmxViVlJtN7UMuA4d+/r7r9OuKYmKfAbqjGzH9VtxF9Xmtk3gILkykpED6IbjK509yuIlg9oBxwFnJ9kYQlY5e61RPPPD3H3D4k+0wjRb4DvAWvcfRVwGNH9KyE6ABgDHE60sF5JvKBaTlLgN/QzYJyZfWZmnwM3ES0aVncHbki6AWtSttcBu7t7NeFNSSwzs3uA/wdcbmbXEO5MlRp33/h74e4rgA0J1pMYd3/P3R8gWjHzMaLh36uTrappGsNPE49N941XAKxx9y/jQzcnWFZSngLmmtk0os7BUOCZeB2RFYlWtvVdTDRF9V0zuxE4Hjg74ZqS8o6ZjQAKzOxQorZZlHBNiTCzJ4iG95xojaFB7u7JVtU0raWTJl76tUGjuHswdxGmMrNBRIuD1RCtmTLbzL4LuLv/O9nqth4z+5u7H550HbnAzHYCRhJNYGhHdG/GmNRefyjiZRT+h+jdXr67f5FwSc1S4Kcxs9Q1vQuAwcC/A51+J7F4aur/BRa4e0XS9STNzLoTzUqpAl4N6Y9/KjP7FtEMrm8Rhf5S4Ex3fy/RwpqgwM+Amb3h7kcmXYckx8w+pf6pRrXk+JONtqR4Rs7tRNNS84mW4PiFu89OtLAEmNnLwO/cfXq8fQZwsbsfl2hhTdAYfpr4sX518oAi6v+hS6DcvVvSNeSQkUSzt5YDmNleRNM0gwt8oGtd2AO4+zQzG5lkQc1R4Df0CvU9uA3AZ8CIRCuSxJlZIfBrwIiee3wZcKu7VyZaWDLWkPKhvbsvNbMQ2wGgwswOd/e/AZhZMaClFbYhZwFHA/cS9Vr0QZ1AtFDap0Rr4lcD+xHdhRziDUdvArPjh4BUEz3xakXdU6By9WlPW8ivgKfMbDVRJ3F34MxkS2qa5uE3dBfwD+A0or/UhxHmlEzZVLG7XwdUxYtjnQscmnBNSdmBqId/ItH6Sl8TvRP+PtESAyHpCuxP9PtwHrC/u7+RbElNUw+/oXbu/j9m9jjwlLsvMzO1k9TGwzp1sxy6Et7NZ0D9054AzGxXorV0tpkHebex8e7+PLBNvH4FWUNfm9mVROumjDCz/2LTu00lTHcBc4Ae8XMBhhDdhR0cM7uAaErmVURP/VpjZo+5+y3JVpaID8zsD8AbRHeiA7k7rKUhnYaGET3AfGg8t7g34d5RKbH4H/BFRLfQfwic4u4PJVtVYi4mWjvnP4GZwMFEQ6Ah+pxo7P67RENaOT2spXn4Ihkws6fcfWjavj+5+/FJ1ZQUMyt192IzexG4O777+h13/3bStUnzNKQj0gwzm0H04WxvM/sw5VB7oiVxQ/SOmT0HfBOYY2ZPAgsSrikR29oDkxT4Is07n2iq3V1EzzuuU020FnqIfk60PHKZu1ea2VSiBwdhZoPc/blEq9u6tqkHJmlIR6QZdTfVxGssNbao3p8TKCtnhbbIXGOv18wWunvfXGwL9fBFmncR0bMQRtP4NMwgV1FtRmjPCKgxsx+5+0uQ+w9MUuCLNG8/M5sbf50eZnp73FBobXI+MCUe1soDPiC6AWs4cFuCdTVKgS/SvNFJFyC5K77hrNEHJpnZ6OQqa5wCX6QZ7v5K0jVI7mvieQA/Jsc6DLrxSkTaUmhj+M3JubZQD19EsmJmBUTTDbuSEmrx3chHJVVXDsq5zzMU+CKSrf8GehLdXFQXarXAo+6+PrGqpEUKfBHJ1gHufkDSRUj2NIYvItn6IO1RoNK4d5MuIJ3utBWRjJjZPKKhm+7AHsBbREtMAODuwd2EFv/hu4foBrwqoqUWLnP3TxMtrAka0hGRTI1OuoAc9DjwJNGjLtsRrTM0BTgpyaKaosAXkYzU3ZNgZve4+6Wpx8xsChDiPQu7uvu9KdsTzOz8pIppiQJfRDJiZpOJlkTua2apa9+3B3ZLpqrEzTezn7r7VAAzO5noKWA5SWP4IpIRM9sb2JvGl4pe7O6rEygrUWa2EuhGtAZ+LbBjyuFad89v9MKEqIcvIpnaQI48qmQAAAJnSURBVPx4x0aO7QwEF/ju/o2ka8iGAl9EMvUK9TdaNbZy6De3bjnJMbNRzR1395x8wL0CX0Qy4u77JF1DDqn7g9cP6EN093E1MAT4KKGaWqQxfBHJipntB4wgGsbJI3qm6z7ufmyihSXAzP4CnODuX8fbHYF57p6TawrpTlsRydYfgS+Aw4BFwJ5AWaIVJacbmy6SVkj0DOScpCEdEclWobvfGK+a+Tfg98DChGtKyoPAQjObTdSBHgRMTLakpqmHLyLZ+trMOgDvAcXuvi7pghL0KfAHYAWwHJgKfGpmRYlW1QT18EUkW1OBWcAw4K9mdiJR2IXox8ChwDNEn2cMImqLnc2sxN0nJFlcOvXwRSQr8VICQ+MFwo4jGtYYkmhRyelB9C7nSne/AuhLlKtHET3gPKco8EUkK2ZWCFxqZo8CXwIHE60UGaJuwJqU7XXA7u5ejZ54JSLbgfuIxq4PJ5p7vi/ROPZPkywqIU8Bc81sGlEHeijwjJmdSzSun1PUwxeRbBW7+3VAVTz//DyicezguPu1wG3A/sA+wHh3v4HoA+2zk6ytMerhi0i2auNhnbohi67k4PDF1uLuzwHPpe17PaFymqUevohk6y5gDtDDzCYSzcHPqdko0jj18EUkW08QLavQFfg3cAcpjzqU3KXAF5FsTQN6AoupH8qpBR5NrCLJiAJfRLJ1gLsfkHQRkj2N4YtItj4wsz2TLkKyp+WRRSQjZjaPaOimO7AH8BYpY/fu/oOESpMMaUhHRDI1OukCpHXUwxcRCYTG8EVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEAvG/tbKtX5zx7xMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# one example here: total growth in gdp over the years\n",
    "gdp_growth = (gdp_full.max(axis=1) - gdp_full.min(axis=1))/gdp_full.min(axis=1)\n",
    "gdp_growth.name = \"gdp_growth\"\n",
    "data_bis = pd.merge(data, gdp_growth, left_index=True, right_index=True)\n",
    "plot_feature_importances(data_bis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# what else can you think of?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 5. Advanced Visualisation (extra)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "sns.set(style=\"whitegrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "population_full = pd.read_csv(\"Data/population.csv\")\n",
    "population_full.set_index(\"Country\", inplace=True)\n",
    "population_full.drop(\"Country_Code\", axis=1, inplace=True)\n",
    "population = population_full.iloc[:,-1]\n",
    "population.name = \"population\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "points = []\n",
    "for i, x in gdp_full.iterrows():\n",
    "    if i not in bad_teeth.index or i not in population.index:\n",
    "        continue\n",
    "    bt = bad_teeth.loc[i]\n",
    "    pop = population.loc[i]\n",
    "    \n",
    "    for column in x.index:\n",
    "        year = int(column[1:])\n",
    "        points.append((year, x[column], bt, np.sqrt(pop)))\n",
    "df = pd.DataFrame(points, columns=[\"year\", \"gdp\", \"bad_teeth\", \"population (sqrt)\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x24fbc9b02e8>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(figsize=(10, 6))\n",
    "\n",
    "sns.scatterplot(data=df, \n",
    "                x=\"year\", \n",
    "                y=\"gdp\", \n",
    "                hue=\"bad_teeth\", \n",
    "                size=\"population (sqrt)\",\n",
    "                palette=\"Reds\", \n",
    "                sizes=(10, 200), \n",
    "                linewidth=0, \n",
    "                alpha=.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}