{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Importing the libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Africa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>North Africa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>5280.59</td>\n",
       "      <td>5671.31</td>\n",
       "      <td>8652.24</td>\n",
       "      <td>9326.29</td>\n",
       "      <td>10161.6</td>\n",
       "      <td>9724.38</td>\n",
       "      <td>10412.7</td>\n",
       "      <td>10217.1</td>\n",
       "      <td>10073.4</td>\n",
       "      <td>9583.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Libya</td>\n",
       "      <td>. .</td>\n",
       "      <td>. .</td>\n",
       "      <td>. .</td>\n",
       "      <td>2987.41</td>\n",
       "      <td>3964.69</td>\n",
       "      <td>3755.66</td>\n",
       "      <td>. .</td>\n",
       "      <td>. .</td>\n",
       "      <td>. .</td>\n",
       "      <td>. .</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Morocco</td>\n",
       "      <td>3055.07</td>\n",
       "      <td>3160.8</td>\n",
       "      <td>3342.7</td>\n",
       "      <td>3402.7</td>\n",
       "      <td>4065.55</td>\n",
       "      <td>4048.61</td>\n",
       "      <td>3268.36</td>\n",
       "      <td>3327.03</td>\n",
       "      <td>3461.46</td>\n",
       "      <td>3696.86</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Country     2009     2010     2011     2012     2013     2014  \\\n",
       "0        Africa      NaN      NaN      NaN      NaN      NaN      NaN   \n",
       "1  North Africa      NaN      NaN      NaN      NaN      NaN      NaN   \n",
       "2       Algeria  5280.59  5671.31  8652.24  9326.29  10161.6  9724.38   \n",
       "3         Libya      . .      . .      . .  2987.41  3964.69  3755.66   \n",
       "4       Morocco  3055.07   3160.8   3342.7   3402.7  4065.55  4048.61   \n",
       "\n",
       "      2015     2016     2017     2018  \n",
       "0      NaN      NaN      NaN      NaN  \n",
       "1      NaN      NaN      NaN      NaN  \n",
       "2  10412.7  10217.1  10073.4  9583.72  \n",
       "3      . .      . .      . .      . .  \n",
       "4  3268.36  3327.03  3461.46  3696.86  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#We will see the military spending data of G20 Countries\n",
    "#we took the data from this site \"https://www.sipri.org/databases/milex\"\n",
    "#Among csv,excel and other file formates i took excel which is flexible for me,\n",
    "#based on your convenience you can use better one.\n",
    "\n",
    "militarydata = pd.ExcelFile(\"SIPRI-Milex-data-1949-2018_0.xlsx\")\n",
    "\n",
    "#Excel sheet has 10 sheets but we will be using only three sheets with this information Per capita,Share of GDP, Current USD and Country.\n",
    "\n",
    "#Delete header and footer as they are unnecessary and take the data from 2009 to 2018 as it is recent one.\n",
    "usd = militarydata.parse('Current USD',skip_footer=8,skiprows = 5)\n",
    "usd1 = usd[['Country',2009,2010,2011,2012,2013,2014,2015,2016,2017,2018]]\n",
    "usd1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "    </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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>16352.3</td>\n",
       "      <td>17939.4</td>\n",
       "      <td>17304.9</td>\n",
       "      <td>17958.2</td>\n",
       "      <td>18662.6</td>\n",
       "      <td>17772.2</td>\n",
       "      <td>15880.9</td>\n",
       "      <td>17854</td>\n",
       "      <td>17824</td>\n",
       "      <td>18967.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>3592.69</td>\n",
       "      <td>4188.17</td>\n",
       "      <td>4594.15</td>\n",
       "      <td>4489.59</td>\n",
       "      <td>4118.21</td>\n",
       "      <td>3892.47</td>\n",
       "      <td>3488.87</td>\n",
       "      <td>3169.76</td>\n",
       "      <td>3638.94</td>\n",
       "      <td>3639.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Russia</th>\n",
       "      <td>51532.1</td>\n",
       "      <td>58720.2</td>\n",
       "      <td>70237.5</td>\n",
       "      <td>81469.4</td>\n",
       "      <td>88352.9</td>\n",
       "      <td>84696.5</td>\n",
       "      <td>66418.7</td>\n",
       "      <td>69245.3</td>\n",
       "      <td>66527.3</td>\n",
       "      <td>61387.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>51465.2</td>\n",
       "      <td>54655.5</td>\n",
       "      <td>60762.2</td>\n",
       "      <td>60011.5</td>\n",
       "      <td>49023.9</td>\n",
       "      <td>46881.2</td>\n",
       "      <td>42106.1</td>\n",
       "      <td>46471.3</td>\n",
       "      <td>45387</td>\n",
       "      <td>46618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>3304.46</td>\n",
       "      <td>4663.37</td>\n",
       "      <td>5838.03</td>\n",
       "      <td>6531.1</td>\n",
       "      <td>8384.03</td>\n",
       "      <td>6929.26</td>\n",
       "      <td>7639.1</td>\n",
       "      <td>7385.41</td>\n",
       "      <td>8178.14</td>\n",
       "      <td>7437.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>47470.1</td>\n",
       "      <td>46255.5</td>\n",
       "      <td>48140.3</td>\n",
       "      <td>46470.9</td>\n",
       "      <td>45930.5</td>\n",
       "      <td>46102.7</td>\n",
       "      <td>39812.6</td>\n",
       "      <td>41579.5</td>\n",
       "      <td>45381.7</td>\n",
       "      <td>49470.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>18936.2</td>\n",
       "      <td>19315.7</td>\n",
       "      <td>21393.7</td>\n",
       "      <td>20452.1</td>\n",
       "      <td>18515.7</td>\n",
       "      <td>17853.7</td>\n",
       "      <td>17937.6</td>\n",
       "      <td>17782.8</td>\n",
       "      <td>21343.4</td>\n",
       "      <td>21620.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>18960.1</td>\n",
       "      <td>23217.7</td>\n",
       "      <td>26597.2</td>\n",
       "      <td>26216.6</td>\n",
       "      <td>24825.3</td>\n",
       "      <td>25783.7</td>\n",
       "      <td>24045.6</td>\n",
       "      <td>26382.9</td>\n",
       "      <td>27691.1</td>\n",
       "      <td>26711.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>41267.2</td>\n",
       "      <td>45244.5</td>\n",
       "      <td>48530.9</td>\n",
       "      <td>56497.9</td>\n",
       "      <td>67020</td>\n",
       "      <td>80762.4</td>\n",
       "      <td>87185.9</td>\n",
       "      <td>63672.8</td>\n",
       "      <td>70400</td>\n",
       "      <td>67554.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>4855.51</td>\n",
       "      <td>5897.2</td>\n",
       "      <td>6471.39</td>\n",
       "      <td>6978.78</td>\n",
       "      <td>7837.61</td>\n",
       "      <td>8663.38</td>\n",
       "      <td>7739.52</td>\n",
       "      <td>6019.77</td>\n",
       "      <td>5781.44</td>\n",
       "      <td>6567.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>34054.5</td>\n",
       "      <td>32020.8</td>\n",
       "      <td>33828.8</td>\n",
       "      <td>29781</td>\n",
       "      <td>29957.4</td>\n",
       "      <td>27701</td>\n",
       "      <td>22180.8</td>\n",
       "      <td>25033</td>\n",
       "      <td>26447.9</td>\n",
       "      <td>27807.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>38722.2</td>\n",
       "      <td>46090.4</td>\n",
       "      <td>49633.8</td>\n",
       "      <td>47216.9</td>\n",
       "      <td>47403.5</td>\n",
       "      <td>50914.1</td>\n",
       "      <td>51295.5</td>\n",
       "      <td>56637.6</td>\n",
       "      <td>64559.4</td>\n",
       "      <td>66510.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>66884</td>\n",
       "      <td>61781.7</td>\n",
       "      <td>64600.9</td>\n",
       "      <td>60035.2</td>\n",
       "      <td>62417.1</td>\n",
       "      <td>63613.6</td>\n",
       "      <td>55342.1</td>\n",
       "      <td>57358.4</td>\n",
       "      <td>60417.5</td>\n",
       "      <td>63799.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>China</th>\n",
       "      <td>105644</td>\n",
       "      <td>115712</td>\n",
       "      <td>137967</td>\n",
       "      <td>157390</td>\n",
       "      <td>179880</td>\n",
       "      <td>200772</td>\n",
       "      <td>214093</td>\n",
       "      <td>216031</td>\n",
       "      <td>227829</td>\n",
       "      <td>249997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>25648.8</td>\n",
       "      <td>34002.9</td>\n",
       "      <td>36936.2</td>\n",
       "      <td>33987</td>\n",
       "      <td>32874.8</td>\n",
       "      <td>32659.6</td>\n",
       "      <td>24617.7</td>\n",
       "      <td>24224.7</td>\n",
       "      <td>29283.1</td>\n",
       "      <td>27766.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>2981.85</td>\n",
       "      <td>3475.35</td>\n",
       "      <td>4051.93</td>\n",
       "      <td>4563.22</td>\n",
       "      <td>5137.97</td>\n",
       "      <td>4979.44</td>\n",
       "      <td>5482.62</td>\n",
       "      <td>4509.65</td>\n",
       "      <td>5459.64</td>\n",
       "      <td>4144.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 2009     2010     2011     2012     2013     2014     2015  \\\n",
       "Country                                                                       \n",
       "Turkey        16352.3  17939.4  17304.9  17958.2  18662.6  17772.2  15880.9   \n",
       "South Africa  3592.69  4188.17  4594.15  4489.59  4118.21  3892.47  3488.87   \n",
       "Russia        51532.1  58720.2  70237.5  81469.4  88352.9  84696.5  66418.7   \n",
       "Japan         51465.2  54655.5  60762.2  60011.5  49023.9  46881.2  42106.1   \n",
       "Indonesia     3304.46  4663.37  5838.03   6531.1  8384.03  6929.26   7639.1   \n",
       "Germany       47470.1  46255.5  48140.3  46470.9  45930.5  46102.7  39812.6   \n",
       "Canada        18936.2  19315.7  21393.7  20452.1  18515.7  17853.7  17937.6   \n",
       "Australia     18960.1  23217.7  26597.2  26216.6  24825.3  25783.7  24045.6   \n",
       "Saudi Arabia  41267.2  45244.5  48530.9  56497.9    67020  80762.4  87185.9   \n",
       "Mexico        4855.51   5897.2  6471.39  6978.78  7837.61  8663.38  7739.52   \n",
       "Italy         34054.5  32020.8  33828.8    29781  29957.4    27701  22180.8   \n",
       "India         38722.2  46090.4  49633.8  47216.9  47403.5  50914.1  51295.5   \n",
       "France          66884  61781.7  64600.9  60035.2  62417.1  63613.6  55342.1   \n",
       "China          105644   115712   137967   157390   179880   200772   214093   \n",
       "Brazil        25648.8  34002.9  36936.2    33987  32874.8  32659.6  24617.7   \n",
       "Argentina     2981.85  3475.35  4051.93  4563.22  5137.97  4979.44  5482.62   \n",
       "\n",
       "                 2016     2017     2018  \n",
       "Country                                  \n",
       "Turkey          17854    17824  18967.1  \n",
       "South Africa  3169.76  3638.94  3639.88  \n",
       "Russia        69245.3  66527.3  61387.5  \n",
       "Japan         46471.3    45387    46618  \n",
       "Indonesia     7385.41  8178.14   7437.2  \n",
       "Germany       41579.5  45381.7  49470.6  \n",
       "Canada        17782.8  21343.4  21620.6  \n",
       "Australia     26382.9  27691.1  26711.8  \n",
       "Saudi Arabia  63672.8    70400  67554.7  \n",
       "Mexico        6019.77  5781.44  6567.51  \n",
       "Italy           25033  26447.9  27807.5  \n",
       "India         56637.6  64559.4  66510.3  \n",
       "France        57358.4  60417.5  63799.7  \n",
       "China          216031   227829   249997  \n",
       "Brazil        24224.7  29283.1  27766.4  \n",
       "Argentina     4509.65  5459.64  4144.99  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Remove the data which is not useful and dropping the NAN's\n",
    "usd2 = usd1[usd1!=\". .\"]\n",
    "usd2 = usd2[usd!=\"xxx\"]\n",
    "usd2 = usd2.dropna(how='any',axis=0)\n",
    "\n",
    "#Setting the index name as Country\n",
    "usd3 = usd2.set_index('Country')\n",
    "usd3.head()\n",
    "\n",
    "#Viewing the military data for G20 Nations\n",
    "G20_military_countries = usd3.loc[['Turkey','South Africa','Russia','Japan','Indonesia',  \n",
    "                                    'Germany','Canada','Australia',\n",
    "                                   'Saudi Arabia','Mexico','Italy','India','France','China','Brazil','Argentina',],:]\n",
    "G20_military_countries\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Country\n",
       "Turkey          1.765156e+05\n",
       "South Africa    3.881272e+04\n",
       "Russia          6.985875e+05\n",
       "Japan           5.033819e+05\n",
       "Indonesia       6.629008e+04\n",
       "Germany         4.566144e+05\n",
       "Canada          1.951516e+05\n",
       "Australia       2.504320e+05\n",
       "Saudi Arabia    6.281363e+05\n",
       "Mexico          6.681211e+04\n",
       "Italy           2.888129e+05\n",
       "India           5.189838e+05\n",
       "France          6.162502e+05\n",
       "China           1.805317e+06\n",
       "Brazil          3.020013e+05\n",
       "Argentina       4.478667e+04\n",
       "Name: TOTAL, dtype: float64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Taking the data from 2009 to 2018 and adding a new column 'TOTAL' to it.\n",
    "G20_military_countries['TOTAL'] = np.sum(G20_military_countries, axis =1)\n",
    "G20_military_countries['TOTAL']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>TOTAL</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>China</th>\n",
       "      <td>105644</td>\n",
       "      <td>115712</td>\n",
       "      <td>137967</td>\n",
       "      <td>157390</td>\n",
       "      <td>179880</td>\n",
       "      <td>200772</td>\n",
       "      <td>214093</td>\n",
       "      <td>216031</td>\n",
       "      <td>227829</td>\n",
       "      <td>249997</td>\n",
       "      <td>1.805317e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Russia</th>\n",
       "      <td>51532.1</td>\n",
       "      <td>58720.2</td>\n",
       "      <td>70237.5</td>\n",
       "      <td>81469.4</td>\n",
       "      <td>88352.9</td>\n",
       "      <td>84696.5</td>\n",
       "      <td>66418.7</td>\n",
       "      <td>69245.3</td>\n",
       "      <td>66527.3</td>\n",
       "      <td>61387.5</td>\n",
       "      <td>6.985875e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>41267.2</td>\n",
       "      <td>45244.5</td>\n",
       "      <td>48530.9</td>\n",
       "      <td>56497.9</td>\n",
       "      <td>67020</td>\n",
       "      <td>80762.4</td>\n",
       "      <td>87185.9</td>\n",
       "      <td>63672.8</td>\n",
       "      <td>70400</td>\n",
       "      <td>67554.7</td>\n",
       "      <td>6.281363e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>66884</td>\n",
       "      <td>61781.7</td>\n",
       "      <td>64600.9</td>\n",
       "      <td>60035.2</td>\n",
       "      <td>62417.1</td>\n",
       "      <td>63613.6</td>\n",
       "      <td>55342.1</td>\n",
       "      <td>57358.4</td>\n",
       "      <td>60417.5</td>\n",
       "      <td>63799.7</td>\n",
       "      <td>6.162502e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>38722.2</td>\n",
       "      <td>46090.4</td>\n",
       "      <td>49633.8</td>\n",
       "      <td>47216.9</td>\n",
       "      <td>47403.5</td>\n",
       "      <td>50914.1</td>\n",
       "      <td>51295.5</td>\n",
       "      <td>56637.6</td>\n",
       "      <td>64559.4</td>\n",
       "      <td>66510.3</td>\n",
       "      <td>5.189838e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>51465.2</td>\n",
       "      <td>54655.5</td>\n",
       "      <td>60762.2</td>\n",
       "      <td>60011.5</td>\n",
       "      <td>49023.9</td>\n",
       "      <td>46881.2</td>\n",
       "      <td>42106.1</td>\n",
       "      <td>46471.3</td>\n",
       "      <td>45387</td>\n",
       "      <td>46618</td>\n",
       "      <td>5.033819e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>47470.1</td>\n",
       "      <td>46255.5</td>\n",
       "      <td>48140.3</td>\n",
       "      <td>46470.9</td>\n",
       "      <td>45930.5</td>\n",
       "      <td>46102.7</td>\n",
       "      <td>39812.6</td>\n",
       "      <td>41579.5</td>\n",
       "      <td>45381.7</td>\n",
       "      <td>49470.6</td>\n",
       "      <td>4.566144e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>25648.8</td>\n",
       "      <td>34002.9</td>\n",
       "      <td>36936.2</td>\n",
       "      <td>33987</td>\n",
       "      <td>32874.8</td>\n",
       "      <td>32659.6</td>\n",
       "      <td>24617.7</td>\n",
       "      <td>24224.7</td>\n",
       "      <td>29283.1</td>\n",
       "      <td>27766.4</td>\n",
       "      <td>3.020013e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>34054.5</td>\n",
       "      <td>32020.8</td>\n",
       "      <td>33828.8</td>\n",
       "      <td>29781</td>\n",
       "      <td>29957.4</td>\n",
       "      <td>27701</td>\n",
       "      <td>22180.8</td>\n",
       "      <td>25033</td>\n",
       "      <td>26447.9</td>\n",
       "      <td>27807.5</td>\n",
       "      <td>2.888129e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>18960.1</td>\n",
       "      <td>23217.7</td>\n",
       "      <td>26597.2</td>\n",
       "      <td>26216.6</td>\n",
       "      <td>24825.3</td>\n",
       "      <td>25783.7</td>\n",
       "      <td>24045.6</td>\n",
       "      <td>26382.9</td>\n",
       "      <td>27691.1</td>\n",
       "      <td>26711.8</td>\n",
       "      <td>2.504320e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>18936.2</td>\n",
       "      <td>19315.7</td>\n",
       "      <td>21393.7</td>\n",
       "      <td>20452.1</td>\n",
       "      <td>18515.7</td>\n",
       "      <td>17853.7</td>\n",
       "      <td>17937.6</td>\n",
       "      <td>17782.8</td>\n",
       "      <td>21343.4</td>\n",
       "      <td>21620.6</td>\n",
       "      <td>1.951516e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>16352.3</td>\n",
       "      <td>17939.4</td>\n",
       "      <td>17304.9</td>\n",
       "      <td>17958.2</td>\n",
       "      <td>18662.6</td>\n",
       "      <td>17772.2</td>\n",
       "      <td>15880.9</td>\n",
       "      <td>17854</td>\n",
       "      <td>17824</td>\n",
       "      <td>18967.1</td>\n",
       "      <td>1.765156e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>4855.51</td>\n",
       "      <td>5897.2</td>\n",
       "      <td>6471.39</td>\n",
       "      <td>6978.78</td>\n",
       "      <td>7837.61</td>\n",
       "      <td>8663.38</td>\n",
       "      <td>7739.52</td>\n",
       "      <td>6019.77</td>\n",
       "      <td>5781.44</td>\n",
       "      <td>6567.51</td>\n",
       "      <td>6.681211e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>3304.46</td>\n",
       "      <td>4663.37</td>\n",
       "      <td>5838.03</td>\n",
       "      <td>6531.1</td>\n",
       "      <td>8384.03</td>\n",
       "      <td>6929.26</td>\n",
       "      <td>7639.1</td>\n",
       "      <td>7385.41</td>\n",
       "      <td>8178.14</td>\n",
       "      <td>7437.2</td>\n",
       "      <td>6.629008e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>2981.85</td>\n",
       "      <td>3475.35</td>\n",
       "      <td>4051.93</td>\n",
       "      <td>4563.22</td>\n",
       "      <td>5137.97</td>\n",
       "      <td>4979.44</td>\n",
       "      <td>5482.62</td>\n",
       "      <td>4509.65</td>\n",
       "      <td>5459.64</td>\n",
       "      <td>4144.99</td>\n",
       "      <td>4.478667e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>3592.69</td>\n",
       "      <td>4188.17</td>\n",
       "      <td>4594.15</td>\n",
       "      <td>4489.59</td>\n",
       "      <td>4118.21</td>\n",
       "      <td>3892.47</td>\n",
       "      <td>3488.87</td>\n",
       "      <td>3169.76</td>\n",
       "      <td>3638.94</td>\n",
       "      <td>3639.88</td>\n",
       "      <td>3.881272e+04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 2009     2010     2011     2012     2013     2014     2015  \\\n",
       "Country                                                                       \n",
       "China          105644   115712   137967   157390   179880   200772   214093   \n",
       "Russia        51532.1  58720.2  70237.5  81469.4  88352.9  84696.5  66418.7   \n",
       "Saudi Arabia  41267.2  45244.5  48530.9  56497.9    67020  80762.4  87185.9   \n",
       "France          66884  61781.7  64600.9  60035.2  62417.1  63613.6  55342.1   \n",
       "India         38722.2  46090.4  49633.8  47216.9  47403.5  50914.1  51295.5   \n",
       "Japan         51465.2  54655.5  60762.2  60011.5  49023.9  46881.2  42106.1   \n",
       "Germany       47470.1  46255.5  48140.3  46470.9  45930.5  46102.7  39812.6   \n",
       "Brazil        25648.8  34002.9  36936.2    33987  32874.8  32659.6  24617.7   \n",
       "Italy         34054.5  32020.8  33828.8    29781  29957.4    27701  22180.8   \n",
       "Australia     18960.1  23217.7  26597.2  26216.6  24825.3  25783.7  24045.6   \n",
       "Canada        18936.2  19315.7  21393.7  20452.1  18515.7  17853.7  17937.6   \n",
       "Turkey        16352.3  17939.4  17304.9  17958.2  18662.6  17772.2  15880.9   \n",
       "Mexico        4855.51   5897.2  6471.39  6978.78  7837.61  8663.38  7739.52   \n",
       "Indonesia     3304.46  4663.37  5838.03   6531.1  8384.03  6929.26   7639.1   \n",
       "Argentina     2981.85  3475.35  4051.93  4563.22  5137.97  4979.44  5482.62   \n",
       "South Africa  3592.69  4188.17  4594.15  4489.59  4118.21  3892.47  3488.87   \n",
       "\n",
       "                 2016     2017     2018         TOTAL  \n",
       "Country                                                \n",
       "China          216031   227829   249997  1.805317e+06  \n",
       "Russia        69245.3  66527.3  61387.5  6.985875e+05  \n",
       "Saudi Arabia  63672.8    70400  67554.7  6.281363e+05  \n",
       "France        57358.4  60417.5  63799.7  6.162502e+05  \n",
       "India         56637.6  64559.4  66510.3  5.189838e+05  \n",
       "Japan         46471.3    45387    46618  5.033819e+05  \n",
       "Germany       41579.5  45381.7  49470.6  4.566144e+05  \n",
       "Brazil        24224.7  29283.1  27766.4  3.020013e+05  \n",
       "Italy           25033  26447.9  27807.5  2.888129e+05  \n",
       "Australia     26382.9  27691.1  26711.8  2.504320e+05  \n",
       "Canada        17782.8  21343.4  21620.6  1.951516e+05  \n",
       "Turkey          17854    17824  18967.1  1.765156e+05  \n",
       "Mexico        6019.77  5781.44  6567.51  6.681211e+04  \n",
       "Indonesia     7385.41  8178.14   7437.2  6.629008e+04  \n",
       "Argentina     4509.65  5459.64  4144.99  4.478667e+04  \n",
       "South Africa  3169.76  3638.94  3639.88  3.881272e+04  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "#keeping the data in descending order by making ascending order as 'False' and \n",
    "#checking the military expenditure of 10 years.\n",
    "#this gives military data in millions\n",
    "\n",
    "G20_military_countries.sort_values(ascending = False,by = 'TOTAL')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
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       "    <tr>\n",
       "      <th>Country</th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>0.0253659</td>\n",
       "      <td>0.0232413</td>\n",
       "      <td>0.0207854</td>\n",
       "      <td>0.0205476</td>\n",
       "      <td>0.0196325</td>\n",
       "      <td>0.0190246</td>\n",
       "      <td>0.0184706</td>\n",
       "      <td>0.0206754</td>\n",
       "      <td>0.0206814</td>\n",
       "      <td>0.0250436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>0.01214</td>\n",
       "      <td>0.0111581</td>\n",
       "      <td>0.0110326</td>\n",
       "      <td>0.0113279</td>\n",
       "      <td>0.0112327</td>\n",
       "      <td>0.0110944</td>\n",
       "      <td>0.0109918</td>\n",
       "      <td>0.0107553</td>\n",
       "      <td>0.0104366</td>\n",
       "      <td>0.0098171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Russia</th>\n",
       "      <td>0.0392273</td>\n",
       "      <td>0.0358386</td>\n",
       "      <td>0.0342345</td>\n",
       "      <td>0.0368597</td>\n",
       "      <td>0.0384623</td>\n",
       "      <td>0.0410418</td>\n",
       "      <td>0.0486276</td>\n",
       "      <td>0.0545241</td>\n",
       "      <td>0.0423341</td>\n",
       "      <td>0.0392951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>0.00983777</td>\n",
       "      <td>0.00958851</td>\n",
       "      <td>0.00986806</td>\n",
       "      <td>0.00967427</td>\n",
       "      <td>0.00950866</td>\n",
       "      <td>0.00966999</td>\n",
       "      <td>0.0095805</td>\n",
       "      <td>0.00939583</td>\n",
       "      <td>0.00930768</td>\n",
       "      <td>0.0092384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>0.00612411</td>\n",
       "      <td>0.00617587</td>\n",
       "      <td>0.00653777</td>\n",
       "      <td>0.00711549</td>\n",
       "      <td>0.0091877</td>\n",
       "      <td>0.00777855</td>\n",
       "      <td>0.00886971</td>\n",
       "      <td>0.00790695</td>\n",
       "      <td>0.00804337</td>\n",
       "      <td>0.00716443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>0.0138891</td>\n",
       "      <td>0.0135365</td>\n",
       "      <td>0.0128111</td>\n",
       "      <td>0.0131126</td>\n",
       "      <td>0.0122399</td>\n",
       "      <td>0.0118251</td>\n",
       "      <td>0.0117746</td>\n",
       "      <td>0.011899</td>\n",
       "      <td>0.0123414</td>\n",
       "      <td>0.0123377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>0.0138104</td>\n",
       "      <td>0.0119715</td>\n",
       "      <td>0.0119608</td>\n",
       "      <td>0.011211</td>\n",
       "      <td>0.0100486</td>\n",
       "      <td>0.00992271</td>\n",
       "      <td>0.0115013</td>\n",
       "      <td>0.0115846</td>\n",
       "      <td>0.012934</td>\n",
       "      <td>0.0125263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>0.0192918</td>\n",
       "      <td>0.018624</td>\n",
       "      <td>0.0176939</td>\n",
       "      <td>0.0167992</td>\n",
       "      <td>0.0164953</td>\n",
       "      <td>0.0178129</td>\n",
       "      <td>0.0195845</td>\n",
       "      <td>0.0209285</td>\n",
       "      <td>0.0200797</td>\n",
       "      <td>0.0189156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>0.096172</td>\n",
       "      <td>0.0856568</td>\n",
       "      <td>0.0723005</td>\n",
       "      <td>0.076766</td>\n",
       "      <td>0.0897613</td>\n",
       "      <td>0.106779</td>\n",
       "      <td>0.133257</td>\n",
       "      <td>0.0987274</td>\n",
       "      <td>0.102514</td>\n",
       "      <td>0.0877472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>0.00539474</td>\n",
       "      <td>0.00557496</td>\n",
       "      <td>0.00548195</td>\n",
       "      <td>0.00581037</td>\n",
       "      <td>0.00614983</td>\n",
       "      <td>0.0065912</td>\n",
       "      <td>0.0066171</td>\n",
       "      <td>0.0055923</td>\n",
       "      <td>0.00502372</td>\n",
       "      <td>0.00538884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>0.0155854</td>\n",
       "      <td>0.0150682</td>\n",
       "      <td>0.0148614</td>\n",
       "      <td>0.0143674</td>\n",
       "      <td>0.0140613</td>\n",
       "      <td>0.0128738</td>\n",
       "      <td>0.0121062</td>\n",
       "      <td>0.0133961</td>\n",
       "      <td>0.0136653</td>\n",
       "      <td>0.013327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>0.028935</td>\n",
       "      <td>0.0270746</td>\n",
       "      <td>0.026515</td>\n",
       "      <td>0.0253735</td>\n",
       "      <td>0.0247273</td>\n",
       "      <td>0.0249677</td>\n",
       "      <td>0.0240513</td>\n",
       "      <td>0.0250647</td>\n",
       "      <td>0.0250962</td>\n",
       "      <td>0.0241903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>0.0248634</td>\n",
       "      <td>0.0233791</td>\n",
       "      <td>0.0225766</td>\n",
       "      <td>0.0223693</td>\n",
       "      <td>0.022204</td>\n",
       "      <td>0.0223036</td>\n",
       "      <td>0.0226989</td>\n",
       "      <td>0.0232732</td>\n",
       "      <td>0.0234968</td>\n",
       "      <td>0.0229394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>China</th>\n",
       "      <td>0.0206269</td>\n",
       "      <td>0.0190744</td>\n",
       "      <td>0.0183416</td>\n",
       "      <td>0.0183645</td>\n",
       "      <td>0.0186694</td>\n",
       "      <td>0.0190585</td>\n",
       "      <td>0.0190709</td>\n",
       "      <td>0.0192495</td>\n",
       "      <td>0.0189651</td>\n",
       "      <td>0.0186594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>0.0153863</td>\n",
       "      <td>0.0153941</td>\n",
       "      <td>0.0141185</td>\n",
       "      <td>0.0137866</td>\n",
       "      <td>0.0132945</td>\n",
       "      <td>0.0133024</td>\n",
       "      <td>0.0136552</td>\n",
       "      <td>0.0135015</td>\n",
       "      <td>0.0141953</td>\n",
       "      <td>0.014749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>0.00886509</td>\n",
       "      <td>0.00814878</td>\n",
       "      <td>0.00764287</td>\n",
       "      <td>0.00784825</td>\n",
       "      <td>0.00837736</td>\n",
       "      <td>0.00878101</td>\n",
       "      <td>0.00850129</td>\n",
       "      <td>0.0081314</td>\n",
       "      <td>0.00856138</td>\n",
       "      <td>0.00854561</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    2009        2010        2011        2012        2013  \\\n",
       "Country                                                                    \n",
       "Turkey         0.0253659   0.0232413   0.0207854   0.0205476   0.0196325   \n",
       "South Africa     0.01214   0.0111581   0.0110326   0.0113279   0.0112327   \n",
       "Russia         0.0392273   0.0358386   0.0342345   0.0368597   0.0384623   \n",
       "Japan         0.00983777  0.00958851  0.00986806  0.00967427  0.00950866   \n",
       "Indonesia     0.00612411  0.00617587  0.00653777  0.00711549   0.0091877   \n",
       "Germany        0.0138891   0.0135365   0.0128111   0.0131126   0.0122399   \n",
       "Canada         0.0138104   0.0119715   0.0119608    0.011211   0.0100486   \n",
       "Australia      0.0192918    0.018624   0.0176939   0.0167992   0.0164953   \n",
       "Saudi Arabia    0.096172   0.0856568   0.0723005    0.076766   0.0897613   \n",
       "Mexico        0.00539474  0.00557496  0.00548195  0.00581037  0.00614983   \n",
       "Italy          0.0155854   0.0150682   0.0148614   0.0143674   0.0140613   \n",
       "India           0.028935   0.0270746    0.026515   0.0253735   0.0247273   \n",
       "France         0.0248634   0.0233791   0.0225766   0.0223693    0.022204   \n",
       "China          0.0206269   0.0190744   0.0183416   0.0183645   0.0186694   \n",
       "Brazil         0.0153863   0.0153941   0.0141185   0.0137866   0.0132945   \n",
       "Argentina     0.00886509  0.00814878  0.00764287  0.00784825  0.00837736   \n",
       "\n",
       "                    2014        2015        2016        2017        2018  \n",
       "Country                                                                   \n",
       "Turkey         0.0190246   0.0184706   0.0206754   0.0206814   0.0250436  \n",
       "South Africa   0.0110944   0.0109918   0.0107553   0.0104366   0.0098171  \n",
       "Russia         0.0410418   0.0486276   0.0545241   0.0423341   0.0392951  \n",
       "Japan         0.00966999   0.0095805  0.00939583  0.00930768   0.0092384  \n",
       "Indonesia     0.00777855  0.00886971  0.00790695  0.00804337  0.00716443  \n",
       "Germany        0.0118251   0.0117746    0.011899   0.0123414   0.0123377  \n",
       "Canada        0.00992271   0.0115013   0.0115846    0.012934   0.0125263  \n",
       "Australia      0.0178129   0.0195845   0.0209285   0.0200797   0.0189156  \n",
       "Saudi Arabia    0.106779    0.133257   0.0987274    0.102514   0.0877472  \n",
       "Mexico         0.0065912   0.0066171   0.0055923  0.00502372  0.00538884  \n",
       "Italy          0.0128738   0.0121062   0.0133961   0.0136653    0.013327  \n",
       "India          0.0249677   0.0240513   0.0250647   0.0250962   0.0241903  \n",
       "France         0.0223036   0.0226989   0.0232732   0.0234968   0.0229394  \n",
       "China          0.0190585   0.0190709   0.0192495   0.0189651   0.0186594  \n",
       "Brazil         0.0133024   0.0136552   0.0135015   0.0141953    0.014749  \n",
       "Argentina     0.00878101  0.00850129   0.0081314  0.00856138  0.00854561  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#This gives Share of GDp data with respect to country and year.\n",
    "\n",
    "GDPdata = militarydata.parse('Share of GDP',skip_footer=8,skiprows=5)\n",
    "GDPdata1 = GDPdata[['Country',2009,2010,2011,2012,2013,2014,2015,2016,2017,2018]]\n",
    "\n",
    "#Remove the data which is not useful and dropping the NAN's\n",
    "GDPdata2 = GDPdata1[GDPdata1!=\". .\"]\n",
    "GDPdata2 = GDPdata2[GDPdata!=\"xxx\"]\n",
    "GDPdata2 = GDPdata2.dropna(how='any',axis=0)\n",
    "GDPdata2.head()\n",
    "#Choicing the index name as 'Country'\n",
    "GDPdata3 = GDPdata2.set_index('Country')\n",
    "GDPdata3.head()\n",
    "\n",
    "#Selecting the military spending of all G20 countries with respect to Share of GDP\n",
    "GDP_G20 = GDPdata3.loc[['Turkey','South Africa','Russia','Japan','Indonesia',  \n",
    "                         'Germany','Canada','Australia','Saudi Arabia','Mexico',\n",
    "                        'Italy','India','France','China','Brazil','Argentina',],:]\n",
    "\n",
    "\n",
    "GDP_G20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "    </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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>2.53659</td>\n",
       "      <td>2.32413</td>\n",
       "      <td>2.07854</td>\n",
       "      <td>2.05476</td>\n",
       "      <td>1.96325</td>\n",
       "      <td>1.90246</td>\n",
       "      <td>1.84706</td>\n",
       "      <td>2.06754</td>\n",
       "      <td>2.06814</td>\n",
       "      <td>2.50436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>1.214</td>\n",
       "      <td>1.11581</td>\n",
       "      <td>1.10326</td>\n",
       "      <td>1.13279</td>\n",
       "      <td>1.12327</td>\n",
       "      <td>1.10944</td>\n",
       "      <td>1.09918</td>\n",
       "      <td>1.07553</td>\n",
       "      <td>1.04366</td>\n",
       "      <td>0.98171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Russia</th>\n",
       "      <td>3.92273</td>\n",
       "      <td>3.58386</td>\n",
       "      <td>3.42345</td>\n",
       "      <td>3.68597</td>\n",
       "      <td>3.84623</td>\n",
       "      <td>4.10418</td>\n",
       "      <td>4.86276</td>\n",
       "      <td>5.45241</td>\n",
       "      <td>4.23341</td>\n",
       "      <td>3.92951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>0.983777</td>\n",
       "      <td>0.958851</td>\n",
       "      <td>0.986806</td>\n",
       "      <td>0.967427</td>\n",
       "      <td>0.950866</td>\n",
       "      <td>0.966999</td>\n",
       "      <td>0.95805</td>\n",
       "      <td>0.939583</td>\n",
       "      <td>0.930768</td>\n",
       "      <td>0.92384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>0.612411</td>\n",
       "      <td>0.617587</td>\n",
       "      <td>0.653777</td>\n",
       "      <td>0.711549</td>\n",
       "      <td>0.91877</td>\n",
       "      <td>0.777855</td>\n",
       "      <td>0.886971</td>\n",
       "      <td>0.790695</td>\n",
       "      <td>0.804337</td>\n",
       "      <td>0.716443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>1.38891</td>\n",
       "      <td>1.35365</td>\n",
       "      <td>1.28111</td>\n",
       "      <td>1.31126</td>\n",
       "      <td>1.22399</td>\n",
       "      <td>1.18251</td>\n",
       "      <td>1.17746</td>\n",
       "      <td>1.1899</td>\n",
       "      <td>1.23414</td>\n",
       "      <td>1.23377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>1.38104</td>\n",
       "      <td>1.19715</td>\n",
       "      <td>1.19608</td>\n",
       "      <td>1.1211</td>\n",
       "      <td>1.00486</td>\n",
       "      <td>0.992271</td>\n",
       "      <td>1.15013</td>\n",
       "      <td>1.15846</td>\n",
       "      <td>1.2934</td>\n",
       "      <td>1.25263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>1.92918</td>\n",
       "      <td>1.8624</td>\n",
       "      <td>1.76939</td>\n",
       "      <td>1.67992</td>\n",
       "      <td>1.64953</td>\n",
       "      <td>1.78129</td>\n",
       "      <td>1.95845</td>\n",
       "      <td>2.09285</td>\n",
       "      <td>2.00797</td>\n",
       "      <td>1.89156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>9.6172</td>\n",
       "      <td>8.56568</td>\n",
       "      <td>7.23005</td>\n",
       "      <td>7.6766</td>\n",
       "      <td>8.97613</td>\n",
       "      <td>10.6779</td>\n",
       "      <td>13.3257</td>\n",
       "      <td>9.87274</td>\n",
       "      <td>10.2514</td>\n",
       "      <td>8.77472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>0.539474</td>\n",
       "      <td>0.557496</td>\n",
       "      <td>0.548195</td>\n",
       "      <td>0.581037</td>\n",
       "      <td>0.614983</td>\n",
       "      <td>0.65912</td>\n",
       "      <td>0.66171</td>\n",
       "      <td>0.55923</td>\n",
       "      <td>0.502372</td>\n",
       "      <td>0.538884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>1.55854</td>\n",
       "      <td>1.50682</td>\n",
       "      <td>1.48614</td>\n",
       "      <td>1.43674</td>\n",
       "      <td>1.40613</td>\n",
       "      <td>1.28738</td>\n",
       "      <td>1.21062</td>\n",
       "      <td>1.33961</td>\n",
       "      <td>1.36653</td>\n",
       "      <td>1.3327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>2.8935</td>\n",
       "      <td>2.70746</td>\n",
       "      <td>2.6515</td>\n",
       "      <td>2.53735</td>\n",
       "      <td>2.47273</td>\n",
       "      <td>2.49677</td>\n",
       "      <td>2.40513</td>\n",
       "      <td>2.50647</td>\n",
       "      <td>2.50962</td>\n",
       "      <td>2.41903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>2.48634</td>\n",
       "      <td>2.33791</td>\n",
       "      <td>2.25766</td>\n",
       "      <td>2.23693</td>\n",
       "      <td>2.2204</td>\n",
       "      <td>2.23036</td>\n",
       "      <td>2.26989</td>\n",
       "      <td>2.32732</td>\n",
       "      <td>2.34968</td>\n",
       "      <td>2.29394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>China</th>\n",
       "      <td>2.06269</td>\n",
       "      <td>1.90744</td>\n",
       "      <td>1.83416</td>\n",
       "      <td>1.83645</td>\n",
       "      <td>1.86694</td>\n",
       "      <td>1.90585</td>\n",
       "      <td>1.90709</td>\n",
       "      <td>1.92495</td>\n",
       "      <td>1.89651</td>\n",
       "      <td>1.86594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>1.53863</td>\n",
       "      <td>1.53941</td>\n",
       "      <td>1.41185</td>\n",
       "      <td>1.37866</td>\n",
       "      <td>1.32945</td>\n",
       "      <td>1.33024</td>\n",
       "      <td>1.36552</td>\n",
       "      <td>1.35015</td>\n",
       "      <td>1.41953</td>\n",
       "      <td>1.4749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>0.886509</td>\n",
       "      <td>0.814878</td>\n",
       "      <td>0.764287</td>\n",
       "      <td>0.784825</td>\n",
       "      <td>0.837736</td>\n",
       "      <td>0.878101</td>\n",
       "      <td>0.850129</td>\n",
       "      <td>0.81314</td>\n",
       "      <td>0.856138</td>\n",
       "      <td>0.854561</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  2009      2010      2011      2012      2013      2014  \\\n",
       "Country                                                                    \n",
       "Turkey         2.53659   2.32413   2.07854   2.05476   1.96325   1.90246   \n",
       "South Africa     1.214   1.11581   1.10326   1.13279   1.12327   1.10944   \n",
       "Russia         3.92273   3.58386   3.42345   3.68597   3.84623   4.10418   \n",
       "Japan         0.983777  0.958851  0.986806  0.967427  0.950866  0.966999   \n",
       "Indonesia     0.612411  0.617587  0.653777  0.711549   0.91877  0.777855   \n",
       "Germany        1.38891   1.35365   1.28111   1.31126   1.22399   1.18251   \n",
       "Canada         1.38104   1.19715   1.19608    1.1211   1.00486  0.992271   \n",
       "Australia      1.92918    1.8624   1.76939   1.67992   1.64953   1.78129   \n",
       "Saudi Arabia    9.6172   8.56568   7.23005    7.6766   8.97613   10.6779   \n",
       "Mexico        0.539474  0.557496  0.548195  0.581037  0.614983   0.65912   \n",
       "Italy          1.55854   1.50682   1.48614   1.43674   1.40613   1.28738   \n",
       "India           2.8935   2.70746    2.6515   2.53735   2.47273   2.49677   \n",
       "France         2.48634   2.33791   2.25766   2.23693    2.2204   2.23036   \n",
       "China          2.06269   1.90744   1.83416   1.83645   1.86694   1.90585   \n",
       "Brazil         1.53863   1.53941   1.41185   1.37866   1.32945   1.33024   \n",
       "Argentina     0.886509  0.814878  0.764287  0.784825  0.837736  0.878101   \n",
       "\n",
       "                  2015      2016      2017      2018  \n",
       "Country                                               \n",
       "Turkey         1.84706   2.06754   2.06814   2.50436  \n",
       "South Africa   1.09918   1.07553   1.04366   0.98171  \n",
       "Russia         4.86276   5.45241   4.23341   3.92951  \n",
       "Japan          0.95805  0.939583  0.930768   0.92384  \n",
       "Indonesia     0.886971  0.790695  0.804337  0.716443  \n",
       "Germany        1.17746    1.1899   1.23414   1.23377  \n",
       "Canada         1.15013   1.15846    1.2934   1.25263  \n",
       "Australia      1.95845   2.09285   2.00797   1.89156  \n",
       "Saudi Arabia   13.3257   9.87274   10.2514   8.77472  \n",
       "Mexico         0.66171   0.55923  0.502372  0.538884  \n",
       "Italy          1.21062   1.33961   1.36653    1.3327  \n",
       "India          2.40513   2.50647   2.50962   2.41903  \n",
       "France         2.26989   2.32732   2.34968   2.29394  \n",
       "China          1.90709   1.92495   1.89651   1.86594  \n",
       "Brazil         1.36552   1.35015   1.41953    1.4749  \n",
       "Argentina     0.850129   0.81314  0.856138  0.854561  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Military Percentage value is given by multiplying the Share of GDP to military spending\n",
    "military_percent_GDP = GDP_G20 * 100\n",
    "military_percent_GDP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "    </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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>229.219</td>\n",
       "      <td>248.032</td>\n",
       "      <td>235.731</td>\n",
       "      <td>240.824</td>\n",
       "      <td>246.249</td>\n",
       "      <td>230.716</td>\n",
       "      <td>202.895</td>\n",
       "      <td>224.543</td>\n",
       "      <td>220.744</td>\n",
       "      <td>231.541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>70.4852</td>\n",
       "      <td>81.1902</td>\n",
       "      <td>87.9037</td>\n",
       "      <td>84.7121</td>\n",
       "      <td>76.593</td>\n",
       "      <td>71.3696</td>\n",
       "      <td>63.0998</td>\n",
       "      <td>56.5872</td>\n",
       "      <td>64.1594</td>\n",
       "      <td>63.4143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Russia</th>\n",
       "      <td>360.131</td>\n",
       "      <td>410.19</td>\n",
       "      <td>490.266</td>\n",
       "      <td>568.045</td>\n",
       "      <td>615.283</td>\n",
       "      <td>589.146</td>\n",
       "      <td>461.6</td>\n",
       "      <td>480.989</td>\n",
       "      <td>462.028</td>\n",
       "      <td>426.407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>400.299</td>\n",
       "      <td>425.163</td>\n",
       "      <td>472.838</td>\n",
       "      <td>467.283</td>\n",
       "      <td>382.065</td>\n",
       "      <td>365.794</td>\n",
       "      <td>329.018</td>\n",
       "      <td>363.772</td>\n",
       "      <td>356.02</td>\n",
       "      <td>366.536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>13.8065</td>\n",
       "      <td>19.2285</td>\n",
       "      <td>23.7601</td>\n",
       "      <td>26.2416</td>\n",
       "      <td>33.2657</td>\n",
       "      <td>27.1596</td>\n",
       "      <td>29.5903</td>\n",
       "      <td>28.2841</td>\n",
       "      <td>30.9788</td>\n",
       "      <td>27.8761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>586.299</td>\n",
       "      <td>571.799</td>\n",
       "      <td>594.81</td>\n",
       "      <td>573.246</td>\n",
       "      <td>565.194</td>\n",
       "      <td>565.749</td>\n",
       "      <td>487.256</td>\n",
       "      <td>507.595</td>\n",
       "      <td>552.666</td>\n",
       "      <td>601.149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>560.412</td>\n",
       "      <td>565.304</td>\n",
       "      <td>619.414</td>\n",
       "      <td>586.008</td>\n",
       "      <td>525.187</td>\n",
       "      <td>501.442</td>\n",
       "      <td>498.965</td>\n",
       "      <td>490.021</td>\n",
       "      <td>582.767</td>\n",
       "      <td>585.072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>872.17</td>\n",
       "      <td>1049.62</td>\n",
       "      <td>1183.16</td>\n",
       "      <td>1148.75</td>\n",
       "      <td>1072.33</td>\n",
       "      <td>1098.36</td>\n",
       "      <td>1010.34</td>\n",
       "      <td>1093.56</td>\n",
       "      <td>1132.53</td>\n",
       "      <td>1078.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>1547.82</td>\n",
       "      <td>1649.71</td>\n",
       "      <td>1718.64</td>\n",
       "      <td>1942.42</td>\n",
       "      <td>2238.14</td>\n",
       "      <td>2624.14</td>\n",
       "      <td>2762.79</td>\n",
       "      <td>1972.78</td>\n",
       "      <td>2137.34</td>\n",
       "      <td>2013.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>42.0372</td>\n",
       "      <td>50.2664</td>\n",
       "      <td>54.3403</td>\n",
       "      <td>57.7578</td>\n",
       "      <td>63.9617</td>\n",
       "      <td>69.7413</td>\n",
       "      <td>61.478</td>\n",
       "      <td>47.1989</td>\n",
       "      <td>44.7607</td>\n",
       "      <td>50.226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>570.983</td>\n",
       "      <td>536.094</td>\n",
       "      <td>566.078</td>\n",
       "      <td>498.562</td>\n",
       "      <td>502.069</td>\n",
       "      <td>464.894</td>\n",
       "      <td>372.761</td>\n",
       "      <td>421.219</td>\n",
       "      <td>445.552</td>\n",
       "      <td>469.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>31.8892</td>\n",
       "      <td>37.4421</td>\n",
       "      <td>39.795</td>\n",
       "      <td>37.3828</td>\n",
       "      <td>37.0757</td>\n",
       "      <td>39.3506</td>\n",
       "      <td>39.1852</td>\n",
       "      <td>42.7721</td>\n",
       "      <td>48.2082</td>\n",
       "      <td>49.1195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>1066.94</td>\n",
       "      <td>980.247</td>\n",
       "      <td>1019.85</td>\n",
       "      <td>943.358</td>\n",
       "      <td>976.489</td>\n",
       "      <td>991.01</td>\n",
       "      <td>858.587</td>\n",
       "      <td>886.245</td>\n",
       "      <td>929.793</td>\n",
       "      <td>978.024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>China</th>\n",
       "      <td>78.1353</td>\n",
       "      <td>85.0975</td>\n",
       "      <td>100.892</td>\n",
       "      <td>114.449</td>\n",
       "      <td>130.085</td>\n",
       "      <td>144.429</td>\n",
       "      <td>153.249</td>\n",
       "      <td>153.923</td>\n",
       "      <td>161.636</td>\n",
       "      <td>176.671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>131.603</td>\n",
       "      <td>172.782</td>\n",
       "      <td>185.902</td>\n",
       "      <td>169.46</td>\n",
       "      <td>162.418</td>\n",
       "      <td>159.929</td>\n",
       "      <td>119.525</td>\n",
       "      <td>116.66</td>\n",
       "      <td>139.917</td>\n",
       "      <td>131.677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>73.0857</td>\n",
       "      <td>84.3042</td>\n",
       "      <td>97.2692</td>\n",
       "      <td>108.398</td>\n",
       "      <td>120.78</td>\n",
       "      <td>115.851</td>\n",
       "      <td>126.276</td>\n",
       "      <td>102.849</td>\n",
       "      <td>123.323</td>\n",
       "      <td>92.7522</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 2009     2010     2011     2012     2013     2014     2015  \\\n",
       "Country                                                                       \n",
       "Turkey        229.219  248.032  235.731  240.824  246.249  230.716  202.895   \n",
       "South Africa  70.4852  81.1902  87.9037  84.7121   76.593  71.3696  63.0998   \n",
       "Russia        360.131   410.19  490.266  568.045  615.283  589.146    461.6   \n",
       "Japan         400.299  425.163  472.838  467.283  382.065  365.794  329.018   \n",
       "Indonesia     13.8065  19.2285  23.7601  26.2416  33.2657  27.1596  29.5903   \n",
       "Germany       586.299  571.799   594.81  573.246  565.194  565.749  487.256   \n",
       "Canada        560.412  565.304  619.414  586.008  525.187  501.442  498.965   \n",
       "Australia      872.17  1049.62  1183.16  1148.75  1072.33  1098.36  1010.34   \n",
       "Saudi Arabia  1547.82  1649.71  1718.64  1942.42  2238.14  2624.14  2762.79   \n",
       "Mexico        42.0372  50.2664  54.3403  57.7578  63.9617  69.7413   61.478   \n",
       "Italy         570.983  536.094  566.078  498.562  502.069  464.894  372.761   \n",
       "India         31.8892  37.4421   39.795  37.3828  37.0757  39.3506  39.1852   \n",
       "France        1066.94  980.247  1019.85  943.358  976.489   991.01  858.587   \n",
       "China         78.1353  85.0975  100.892  114.449  130.085  144.429  153.249   \n",
       "Brazil        131.603  172.782  185.902   169.46  162.418  159.929  119.525   \n",
       "Argentina     73.0857  84.3042  97.2692  108.398   120.78  115.851  126.276   \n",
       "\n",
       "                 2016     2017     2018  \n",
       "Country                                  \n",
       "Turkey        224.543  220.744  231.541  \n",
       "South Africa  56.5872  64.1594  63.4143  \n",
       "Russia        480.989  462.028  426.407  \n",
       "Japan         363.772   356.02  366.536  \n",
       "Indonesia     28.2841  30.9788  27.8761  \n",
       "Germany       507.595  552.666  601.149  \n",
       "Canada        490.021  582.767  585.072  \n",
       "Australia     1093.56  1132.53   1078.3  \n",
       "Saudi Arabia  1972.78  2137.34  2013.29  \n",
       "Mexico        47.1989  44.7607   50.226  \n",
       "Italy         421.219  445.552  469.001  \n",
       "India         42.7721  48.2082  49.1195  \n",
       "France        886.245  929.793  978.024  \n",
       "China         153.923  161.636  176.671  \n",
       "Brazil         116.66  139.917  131.677  \n",
       "Argentina     102.849  123.323  92.7522  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "\n",
    "#Per capita military spending data for 10 countries .\n",
    "##Delete header and footer as they are unnecessary and take the data from 2009 to 2018 as it is recent one\n",
    "\n",
    "\n",
    "military_Per_Capita = militarydata.parse('Per capita',skip_footer=8,skiprows=6)\n",
    "military_Per_Capita_1 = military_Per_Capita[['Country',2009,2010,2011,2012,2013,2014,2015,2016,2017,2018]]\n",
    "\n",
    "#Remove the data which is not useful and dropping the NAN's\n",
    "military_Per_Capita_2 = military_Per_Capita_1[military_Per_Capita_1!=\". .\"]\n",
    "military_Per_Capita_2 = military_Per_Capita_2[military_Per_Capita!=\"xxx\"]\n",
    "military_Per_Capita_2 = military_Per_Capita_2.dropna(how='any',axis=0)\n",
    "military_Per_Capita_2.head()\n",
    "\n",
    "#Setting the index name as Country\n",
    "military_Per_Capita3= military_Per_Capita_2.set_index('Country')\n",
    "military_Per_Capita3.head()\n",
    "\n",
    "#We need to choose the Per Capita for the countries mentioned below\n",
    "military_Per_Capita_G20countries = military_Per_Capita3.loc[['Turkey','South Africa','Russia','Japan','Indonesia',  \n",
    "                         'Germany','Canada','Australia','Saudi Arabia','Mexico',\n",
    "                        'Italy','India','France','China','Brazil','Argentina',],:]\n",
    "\n",
    "military_Per_Capita_G20countries\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country Name</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",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>6.446399e+05</td>\n",
       "      <td>7.719018e+05</td>\n",
       "      <td>8.325237e+05</td>\n",
       "      <td>8.739822e+05</td>\n",
       "      <td>9.505794e+05</td>\n",
       "      <td>9.341859e+05</td>\n",
       "      <td>8.597969e+05</td>\n",
       "      <td>8.637216e+05</td>\n",
       "      <td>8.515492e+05</td>\n",
       "      <td>7.665091e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>2.959365e+05</td>\n",
       "      <td>3.753494e+05</td>\n",
       "      <td>4.164189e+05</td>\n",
       "      <td>3.963279e+05</td>\n",
       "      <td>3.666432e+05</td>\n",
       "      <td>3.506362e+05</td>\n",
       "      <td>3.175368e+05</td>\n",
       "      <td>2.957466e+05</td>\n",
       "      <td>3.488716e+05</td>\n",
       "      <td>3.662982e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>5.231383e+06</td>\n",
       "      <td>5.700098e+06</td>\n",
       "      <td>6.157460e+06</td>\n",
       "      <td>6.203213e+06</td>\n",
       "      <td>5.155717e+06</td>\n",
       "      <td>4.850414e+06</td>\n",
       "      <td>4.389476e+06</td>\n",
       "      <td>4.926667e+06</td>\n",
       "      <td>4.859951e+06</td>\n",
       "      <td>4.970916e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>5.395801e+05</td>\n",
       "      <td>7.550942e+05</td>\n",
       "      <td>8.929691e+05</td>\n",
       "      <td>9.178699e+05</td>\n",
       "      <td>9.125241e+05</td>\n",
       "      <td>8.908148e+05</td>\n",
       "      <td>8.608542e+05</td>\n",
       "      <td>9.318774e+05</td>\n",
       "      <td>1.015423e+06</td>\n",
       "      <td>1.042173e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>3.418005e+06</td>\n",
       "      <td>3.417095e+06</td>\n",
       "      <td>3.757698e+06</td>\n",
       "      <td>3.543984e+06</td>\n",
       "      <td>3.752514e+06</td>\n",
       "      <td>3.898727e+06</td>\n",
       "      <td>3.381389e+06</td>\n",
       "      <td>3.495163e+06</td>\n",
       "      <td>3.693204e+06</td>\n",
       "      <td>3.996759e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>1.371153e+06</td>\n",
       "      <td>1.613543e+06</td>\n",
       "      <td>1.789141e+06</td>\n",
       "      <td>1.823967e+06</td>\n",
       "      <td>1.842018e+06</td>\n",
       "      <td>1.801480e+06</td>\n",
       "      <td>1.552900e+06</td>\n",
       "      <td>1.526706e+06</td>\n",
       "      <td>1.646867e+06</td>\n",
       "      <td>1.709327e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>9.278052e+05</td>\n",
       "      <td>1.146138e+06</td>\n",
       "      <td>1.396650e+06</td>\n",
       "      <td>1.546152e+06</td>\n",
       "      <td>1.576184e+06</td>\n",
       "      <td>1.467484e+06</td>\n",
       "      <td>1.351520e+06</td>\n",
       "      <td>1.210028e+06</td>\n",
       "      <td>1.330803e+06</td>\n",
       "      <td>1.432195e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>4.290979e+05</td>\n",
       "      <td>5.282072e+05</td>\n",
       "      <td>6.712388e+05</td>\n",
       "      <td>7.359748e+05</td>\n",
       "      <td>7.466471e+05</td>\n",
       "      <td>7.563503e+05</td>\n",
       "      <td>6.542699e+05</td>\n",
       "      <td>6.449355e+05</td>\n",
       "      <td>6.885861e+05</td>\n",
       "      <td>7.824835e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>9.000454e+05</td>\n",
       "      <td>1.057801e+06</td>\n",
       "      <td>1.180490e+06</td>\n",
       "      <td>1.201090e+06</td>\n",
       "      <td>1.274443e+06</td>\n",
       "      <td>1.314564e+06</td>\n",
       "      <td>1.170565e+06</td>\n",
       "      <td>1.077828e+06</td>\n",
       "      <td>1.158071e+06</td>\n",
       "      <td>1.223809e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>2.185160e+06</td>\n",
       "      <td>2.125058e+06</td>\n",
       "      <td>2.276292e+06</td>\n",
       "      <td>2.072823e+06</td>\n",
       "      <td>2.130491e+06</td>\n",
       "      <td>2.151733e+06</td>\n",
       "      <td>1.832273e+06</td>\n",
       "      <td>1.869202e+06</td>\n",
       "      <td>1.946570e+06</td>\n",
       "      <td>2.073902e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>1.341887e+06</td>\n",
       "      <td>1.675615e+06</td>\n",
       "      <td>1.823050e+06</td>\n",
       "      <td>1.827638e+06</td>\n",
       "      <td>1.856722e+06</td>\n",
       "      <td>2.039127e+06</td>\n",
       "      <td>2.103588e+06</td>\n",
       "      <td>2.290432e+06</td>\n",
       "      <td>2.652551e+06</td>\n",
       "      <td>2.726323e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>2.690222e+06</td>\n",
       "      <td>2.642610e+06</td>\n",
       "      <td>2.861408e+06</td>\n",
       "      <td>2.683825e+06</td>\n",
       "      <td>2.811078e+06</td>\n",
       "      <td>2.852166e+06</td>\n",
       "      <td>2.438208e+06</td>\n",
       "      <td>2.471286e+06</td>\n",
       "      <td>2.586285e+06</td>\n",
       "      <td>2.777535e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>China</th>\n",
       "      <td>5.101702e+06</td>\n",
       "      <td>6.087165e+06</td>\n",
       "      <td>7.551500e+06</td>\n",
       "      <td>8.532231e+06</td>\n",
       "      <td>9.570406e+06</td>\n",
       "      <td>1.043853e+07</td>\n",
       "      <td>1.101554e+07</td>\n",
       "      <td>1.113795e+07</td>\n",
       "      <td>1.214349e+07</td>\n",
       "      <td>1.360815e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>1.667020e+06</td>\n",
       "      <td>2.208872e+06</td>\n",
       "      <td>2.616202e+06</td>\n",
       "      <td>2.465189e+06</td>\n",
       "      <td>2.472806e+06</td>\n",
       "      <td>2.455994e+06</td>\n",
       "      <td>1.802214e+06</td>\n",
       "      <td>1.796275e+06</td>\n",
       "      <td>2.053595e+06</td>\n",
       "      <td>1.868626e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>3.329765e+05</td>\n",
       "      <td>4.236274e+05</td>\n",
       "      <td>5.301633e+05</td>\n",
       "      <td>5.459824e+05</td>\n",
       "      <td>5.520251e+05</td>\n",
       "      <td>5.263197e+05</td>\n",
       "      <td>5.947493e+05</td>\n",
       "      <td>5.575314e+05</td>\n",
       "      <td>6.426959e+05</td>\n",
       "      <td>5.184751e+05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      2009          2010          2011          2012  \\\n",
       "Country Name                                                           \n",
       "Turkey        6.446399e+05  7.719018e+05  8.325237e+05  8.739822e+05   \n",
       "South Africa  2.959365e+05  3.753494e+05  4.164189e+05  3.963279e+05   \n",
       "Japan         5.231383e+06  5.700098e+06  6.157460e+06  6.203213e+06   \n",
       "Indonesia     5.395801e+05  7.550942e+05  8.929691e+05  9.178699e+05   \n",
       "Germany       3.418005e+06  3.417095e+06  3.757698e+06  3.543984e+06   \n",
       "Canada        1.371153e+06  1.613543e+06  1.789141e+06  1.823967e+06   \n",
       "Australia     9.278052e+05  1.146138e+06  1.396650e+06  1.546152e+06   \n",
       "Saudi Arabia  4.290979e+05  5.282072e+05  6.712388e+05  7.359748e+05   \n",
       "Mexico        9.000454e+05  1.057801e+06  1.180490e+06  1.201090e+06   \n",
       "Italy         2.185160e+06  2.125058e+06  2.276292e+06  2.072823e+06   \n",
       "India         1.341887e+06  1.675615e+06  1.823050e+06  1.827638e+06   \n",
       "France        2.690222e+06  2.642610e+06  2.861408e+06  2.683825e+06   \n",
       "China         5.101702e+06  6.087165e+06  7.551500e+06  8.532231e+06   \n",
       "Brazil        1.667020e+06  2.208872e+06  2.616202e+06  2.465189e+06   \n",
       "Argentina     3.329765e+05  4.236274e+05  5.301633e+05  5.459824e+05   \n",
       "\n",
       "                      2013          2014          2015          2016  \\\n",
       "Country Name                                                           \n",
       "Turkey        9.505794e+05  9.341859e+05  8.597969e+05  8.637216e+05   \n",
       "South Africa  3.666432e+05  3.506362e+05  3.175368e+05  2.957466e+05   \n",
       "Japan         5.155717e+06  4.850414e+06  4.389476e+06  4.926667e+06   \n",
       "Indonesia     9.125241e+05  8.908148e+05  8.608542e+05  9.318774e+05   \n",
       "Germany       3.752514e+06  3.898727e+06  3.381389e+06  3.495163e+06   \n",
       "Canada        1.842018e+06  1.801480e+06  1.552900e+06  1.526706e+06   \n",
       "Australia     1.576184e+06  1.467484e+06  1.351520e+06  1.210028e+06   \n",
       "Saudi Arabia  7.466471e+05  7.563503e+05  6.542699e+05  6.449355e+05   \n",
       "Mexico        1.274443e+06  1.314564e+06  1.170565e+06  1.077828e+06   \n",
       "Italy         2.130491e+06  2.151733e+06  1.832273e+06  1.869202e+06   \n",
       "India         1.856722e+06  2.039127e+06  2.103588e+06  2.290432e+06   \n",
       "France        2.811078e+06  2.852166e+06  2.438208e+06  2.471286e+06   \n",
       "China         9.570406e+06  1.043853e+07  1.101554e+07  1.113795e+07   \n",
       "Brazil        2.472806e+06  2.455994e+06  1.802214e+06  1.796275e+06   \n",
       "Argentina     5.520251e+05  5.263197e+05  5.947493e+05  5.575314e+05   \n",
       "\n",
       "                      2017          2018  \n",
       "Country Name                              \n",
       "Turkey        8.515492e+05  7.665091e+05  \n",
       "South Africa  3.488716e+05  3.662982e+05  \n",
       "Japan         4.859951e+06  4.970916e+06  \n",
       "Indonesia     1.015423e+06  1.042173e+06  \n",
       "Germany       3.693204e+06  3.996759e+06  \n",
       "Canada        1.646867e+06  1.709327e+06  \n",
       "Australia     1.330803e+06  1.432195e+06  \n",
       "Saudi Arabia  6.885861e+05  7.824835e+05  \n",
       "Mexico        1.158071e+06  1.223809e+06  \n",
       "Italy         1.946570e+06  2.073902e+06  \n",
       "India         2.652551e+06  2.726323e+06  \n",
       "France        2.586285e+06  2.777535e+06  \n",
       "China         1.214349e+07  1.360815e+07  \n",
       "Brazil        2.053595e+06  1.868626e+06  \n",
       "Argentina     6.426959e+05  5.184751e+05  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#In millions we have GDP data of G20 Countries\n",
    "#we took the data from world bank website and url is \"https://data.worldbank.org/indicator/NY.GDP.MKTP.CD\"\n",
    "\n",
    "GDPdata = pd.read_excel(\"Until2018_GDP_US$.xls\",index_col=0,sheet_name='Data',skiprows=3)\n",
    "GDP_G20 = GDPdata.loc[['Turkey','South Africa','Japan','Indonesia',  \n",
    "                         'Germany','Canada','Australia','Saudi Arabia','Mexico',\n",
    "                        'Italy','India','France','China','Brazil','Argentina'],\n",
    "                  ['2009','2010','2011','2012','2013','2014','2015','2016','2017','2018']]\n",
    "GDP_G20_Millions = GDP_G20/1000000\n",
    "GDP_G20_Millions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country Name</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>Turkey</th>\n",
       "      <td>10850.871936</td>\n",
       "      <td>9036.268076</td>\n",
       "      <td>10672.400365</td>\n",
       "      <td>11340.822270</td>\n",
       "      <td>11720.313014</td>\n",
       "      <td>12542.720926</td>\n",
       "      <td>12127.461458</td>\n",
       "      <td>10984.802882</td>\n",
       "      <td>10862.726426</td>\n",
       "      <td>10546.152563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>5688.508806</td>\n",
       "      <td>5805.998362</td>\n",
       "      <td>7276.376756</td>\n",
       "      <td>7967.678159</td>\n",
       "      <td>7478.136578</td>\n",
       "      <td>6819.062302</td>\n",
       "      <td>6429.023950</td>\n",
       "      <td>5742.987800</td>\n",
       "      <td>5279.730472</td>\n",
       "      <td>6151.077955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>39339.297573</td>\n",
       "      <td>40855.175635</td>\n",
       "      <td>44507.676386</td>\n",
       "      <td>48167.997268</td>\n",
       "      <td>48603.476650</td>\n",
       "      <td>40454.447458</td>\n",
       "      <td>38109.412113</td>\n",
       "      <td>34567.745675</td>\n",
       "      <td>38972.340639</td>\n",
       "      <td>38428.097317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>2160.527605</td>\n",
       "      <td>2254.445592</td>\n",
       "      <td>3113.480635</td>\n",
       "      <td>3634.276805</td>\n",
       "      <td>3687.953996</td>\n",
       "      <td>3620.663981</td>\n",
       "      <td>3491.595887</td>\n",
       "      <td>3334.549075</td>\n",
       "      <td>3570.284615</td>\n",
       "      <td>3846.864323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>45699.198323</td>\n",
       "      <td>41732.707253</td>\n",
       "      <td>41785.556913</td>\n",
       "      <td>46810.327959</td>\n",
       "      <td>44065.248908</td>\n",
       "      <td>46530.911428</td>\n",
       "      <td>48042.563435</td>\n",
       "      <td>41323.921502</td>\n",
       "      <td>42232.574208</td>\n",
       "      <td>44469.909061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>46596.335991</td>\n",
       "      <td>40773.454364</td>\n",
       "      <td>47447.476024</td>\n",
       "      <td>52082.210760</td>\n",
       "      <td>52496.694870</td>\n",
       "      <td>52418.315062</td>\n",
       "      <td>50633.208822</td>\n",
       "      <td>43525.370187</td>\n",
       "      <td>42348.945461</td>\n",
       "      <td>45032.119908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>49535.257874</td>\n",
       "      <td>42709.803303</td>\n",
       "      <td>51936.888712</td>\n",
       "      <td>62411.785447</td>\n",
       "      <td>67864.689862</td>\n",
       "      <td>67990.290030</td>\n",
       "      <td>62327.555939</td>\n",
       "      <td>56561.412382</td>\n",
       "      <td>49896.681101</td>\n",
       "      <td>53799.938090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>20037.832339</td>\n",
       "      <td>16094.293098</td>\n",
       "      <td>19259.587257</td>\n",
       "      <td>23770.747386</td>\n",
       "      <td>25303.094621</td>\n",
       "      <td>24934.386142</td>\n",
       "      <td>24575.403038</td>\n",
       "      <td>20732.861722</td>\n",
       "      <td>19982.085631</td>\n",
       "      <td>20849.291369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>9765.717028</td>\n",
       "      <td>7792.247730</td>\n",
       "      <td>9016.457927</td>\n",
       "      <td>9912.582362</td>\n",
       "      <td>9940.468561</td>\n",
       "      <td>10400.563158</td>\n",
       "      <td>10582.410526</td>\n",
       "      <td>9298.242878</td>\n",
       "      <td>8450.494010</td>\n",
       "      <td>8910.333177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>40640.183858</td>\n",
       "      <td>36976.845534</td>\n",
       "      <td>35849.373198</td>\n",
       "      <td>38334.683850</td>\n",
       "      <td>34814.125117</td>\n",
       "      <td>35370.275258</td>\n",
       "      <td>35396.665724</td>\n",
       "      <td>30180.321515</td>\n",
       "      <td>30668.981429</td>\n",
       "      <td>31952.975921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>991.484630</td>\n",
       "      <td>1090.317765</td>\n",
       "      <td>1345.770153</td>\n",
       "      <td>1461.671957</td>\n",
       "      <td>1446.985410</td>\n",
       "      <td>1452.195373</td>\n",
       "      <td>1576.004018</td>\n",
       "      <td>1606.038285</td>\n",
       "      <td>1717.473878</td>\n",
       "      <td>1942.097401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>45334.110915</td>\n",
       "      <td>41575.416178</td>\n",
       "      <td>40638.334004</td>\n",
       "      <td>43790.735399</td>\n",
       "      <td>40874.715956</td>\n",
       "      <td>42592.951519</td>\n",
       "      <td>43008.652570</td>\n",
       "      <td>36613.375216</td>\n",
       "      <td>36870.219134</td>\n",
       "      <td>38476.658636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>8787.610658</td>\n",
       "      <td>8553.381368</td>\n",
       "      <td>11224.154083</td>\n",
       "      <td>13167.472892</td>\n",
       "      <td>12291.466852</td>\n",
       "      <td>12216.904464</td>\n",
       "      <td>12026.619391</td>\n",
       "      <td>8750.222996</td>\n",
       "      <td>8639.365743</td>\n",
       "      <td>9821.407686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>8953.359275</td>\n",
       "      <td>8161.306966</td>\n",
       "      <td>10276.260498</td>\n",
       "      <td>12726.908359</td>\n",
       "      <td>12969.707124</td>\n",
       "      <td>12976.636425</td>\n",
       "      <td>12245.256449</td>\n",
       "      <td>13698.293438</td>\n",
       "      <td>12654.354999</td>\n",
       "      <td>14398.358771</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      2008          2009          2010          2011  \\\n",
       "Country Name                                                           \n",
       "Turkey        10850.871936   9036.268076  10672.400365  11340.822270   \n",
       "South Africa   5688.508806   5805.998362   7276.376756   7967.678159   \n",
       "Japan         39339.297573  40855.175635  44507.676386  48167.997268   \n",
       "Indonesia      2160.527605   2254.445592   3113.480635   3634.276805   \n",
       "Germany       45699.198323  41732.707253  41785.556913  46810.327959   \n",
       "Canada        46596.335991  40773.454364  47447.476024  52082.210760   \n",
       "Australia     49535.257874  42709.803303  51936.888712  62411.785447   \n",
       "Saudi Arabia  20037.832339  16094.293098  19259.587257  23770.747386   \n",
       "Mexico         9765.717028   7792.247730   9016.457927   9912.582362   \n",
       "Italy         40640.183858  36976.845534  35849.373198  38334.683850   \n",
       "India           991.484630   1090.317765   1345.770153   1461.671957   \n",
       "France        45334.110915  41575.416178  40638.334004  43790.735399   \n",
       "Brazil         8787.610658   8553.381368  11224.154083  13167.472892   \n",
       "Argentina      8953.359275   8161.306966  10276.260498  12726.908359   \n",
       "\n",
       "                      2012          2013          2014          2015  \\\n",
       "Country Name                                                           \n",
       "Turkey        11720.313014  12542.720926  12127.461458  10984.802882   \n",
       "South Africa   7478.136578   6819.062302   6429.023950   5742.987800   \n",
       "Japan         48603.476650  40454.447458  38109.412113  34567.745675   \n",
       "Indonesia      3687.953996   3620.663981   3491.595887   3334.549075   \n",
       "Germany       44065.248908  46530.911428  48042.563435  41323.921502   \n",
       "Canada        52496.694870  52418.315062  50633.208822  43525.370187   \n",
       "Australia     67864.689862  67990.290030  62327.555939  56561.412382   \n",
       "Saudi Arabia  25303.094621  24934.386142  24575.403038  20732.861722   \n",
       "Mexico         9940.468561  10400.563158  10582.410526   9298.242878   \n",
       "Italy         34814.125117  35370.275258  35396.665724  30180.321515   \n",
       "India          1446.985410   1452.195373   1576.004018   1606.038285   \n",
       "France        40874.715956  42592.951519  43008.652570  36613.375216   \n",
       "Brazil        12291.466852  12216.904464  12026.619391   8750.222996   \n",
       "Argentina     12969.707124  12976.636425  12245.256449  13698.293438   \n",
       "\n",
       "                      2016          2017  \n",
       "Country Name                              \n",
       "Turkey        10862.726426  10546.152563  \n",
       "South Africa   5279.730472   6151.077955  \n",
       "Japan         38972.340639  38428.097317  \n",
       "Indonesia      3570.284615   3846.864323  \n",
       "Germany       42232.574208  44469.909061  \n",
       "Canada        42348.945461  45032.119908  \n",
       "Australia     49896.681101  53799.938090  \n",
       "Saudi Arabia  19982.085631  20849.291369  \n",
       "Mexico         8450.494010   8910.333177  \n",
       "Italy         30668.981429  31952.975921  \n",
       "India          1717.473878   1942.097401  \n",
       "France        36870.219134  38476.658636  \n",
       "Brazil         8639.365743   9821.407686  \n",
       "Argentina     12654.354999  14398.358771  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#GDP Per Person of G20 countries\n",
    "#we took the data from world bank website and url is \"https://data.worldbank.org/indicator/NY.GDP.MKTP.CD\"\n",
    "\n",
    "GDP_Per_Person = pd.read_excel(\"Until2018_GDP_PC_US$.xls\",index_col=0,sheet_name='Data',skiprows=3)\n",
    "\n",
    "GDP_Per_Person_20 = GDP_Per_Person.loc[['Turkey','South Africa','Japan','Indonesia',  \n",
    "                         'Germany','Canada','Australia','Saudi Arabia','Mexico',\n",
    "                        'Italy','India','France','Brazil','Argentina'],\n",
    "                  ['2008','2009','2010','2011','2012','2013','2014','2015','2016','2017']]\n",
    "\n",
    "GDP_Per_Person_20\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country Name</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>Turkey</th>\n",
       "      <td>7.133918e+07</td>\n",
       "      <td>7.232691e+07</td>\n",
       "      <td>7.340946e+07</td>\n",
       "      <td>7.456987e+07</td>\n",
       "      <td>7.578733e+07</td>\n",
       "      <td>7.703063e+07</td>\n",
       "      <td>7.827147e+07</td>\n",
       "      <td>7.951243e+07</td>\n",
       "      <td>8.074502e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>5.097082e+07</td>\n",
       "      <td>5.158466e+07</td>\n",
       "      <td>5.226352e+07</td>\n",
       "      <td>5.299821e+07</td>\n",
       "      <td>5.376740e+07</td>\n",
       "      <td>5.453957e+07</td>\n",
       "      <td>5.529122e+07</td>\n",
       "      <td>5.601547e+07</td>\n",
       "      <td>5.671716e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>1.280470e+08</td>\n",
       "      <td>1.280700e+08</td>\n",
       "      <td>1.278330e+08</td>\n",
       "      <td>1.276290e+08</td>\n",
       "      <td>1.274450e+08</td>\n",
       "      <td>1.272760e+08</td>\n",
       "      <td>1.271410e+08</td>\n",
       "      <td>1.269945e+08</td>\n",
       "      <td>1.267858e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>2.393405e+08</td>\n",
       "      <td>2.425241e+08</td>\n",
       "      <td>2.457075e+08</td>\n",
       "      <td>2.488832e+08</td>\n",
       "      <td>2.520323e+08</td>\n",
       "      <td>2.551311e+08</td>\n",
       "      <td>2.581621e+08</td>\n",
       "      <td>2.611155e+08</td>\n",
       "      <td>2.639914e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>8.190231e+07</td>\n",
       "      <td>8.177693e+07</td>\n",
       "      <td>8.027498e+07</td>\n",
       "      <td>8.042582e+07</td>\n",
       "      <td>8.064560e+07</td>\n",
       "      <td>8.098250e+07</td>\n",
       "      <td>8.168661e+07</td>\n",
       "      <td>8.234867e+07</td>\n",
       "      <td>8.269500e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>3.362857e+07</td>\n",
       "      <td>3.400527e+07</td>\n",
       "      <td>3.434278e+07</td>\n",
       "      <td>3.475054e+07</td>\n",
       "      <td>3.515237e+07</td>\n",
       "      <td>3.553535e+07</td>\n",
       "      <td>3.583251e+07</td>\n",
       "      <td>3.626460e+07</td>\n",
       "      <td>3.670808e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>2.169170e+07</td>\n",
       "      <td>2.203175e+07</td>\n",
       "      <td>2.234002e+07</td>\n",
       "      <td>2.274248e+07</td>\n",
       "      <td>2.314590e+07</td>\n",
       "      <td>2.350414e+07</td>\n",
       "      <td>2.385078e+07</td>\n",
       "      <td>2.421081e+07</td>\n",
       "      <td>2.459893e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>2.666149e+07</td>\n",
       "      <td>2.742568e+07</td>\n",
       "      <td>2.823802e+07</td>\n",
       "      <td>2.908636e+07</td>\n",
       "      <td>2.994448e+07</td>\n",
       "      <td>3.077672e+07</td>\n",
       "      <td>3.155714e+07</td>\n",
       "      <td>3.227569e+07</td>\n",
       "      <td>3.293821e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>1.155052e+08</td>\n",
       "      <td>1.173189e+08</td>\n",
       "      <td>1.190900e+08</td>\n",
       "      <td>1.208283e+08</td>\n",
       "      <td>1.225360e+08</td>\n",
       "      <td>1.242216e+08</td>\n",
       "      <td>1.258909e+08</td>\n",
       "      <td>1.275404e+08</td>\n",
       "      <td>1.291633e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>5.909536e+07</td>\n",
       "      <td>5.927742e+07</td>\n",
       "      <td>5.937945e+07</td>\n",
       "      <td>5.953972e+07</td>\n",
       "      <td>6.023395e+07</td>\n",
       "      <td>6.078914e+07</td>\n",
       "      <td>6.073058e+07</td>\n",
       "      <td>6.062750e+07</td>\n",
       "      <td>6.055142e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>1.214270e+09</td>\n",
       "      <td>1.230981e+09</td>\n",
       "      <td>1.247236e+09</td>\n",
       "      <td>1.263066e+09</td>\n",
       "      <td>1.278562e+09</td>\n",
       "      <td>1.293859e+09</td>\n",
       "      <td>1.309054e+09</td>\n",
       "      <td>1.324171e+09</td>\n",
       "      <td>1.339180e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>6.470704e+07</td>\n",
       "      <td>6.502751e+07</td>\n",
       "      <td>6.534278e+07</td>\n",
       "      <td>6.565979e+07</td>\n",
       "      <td>6.599866e+07</td>\n",
       "      <td>6.631609e+07</td>\n",
       "      <td>6.659337e+07</td>\n",
       "      <td>6.685977e+07</td>\n",
       "      <td>6.711865e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>1.948960e+08</td>\n",
       "      <td>1.967963e+08</td>\n",
       "      <td>1.986867e+08</td>\n",
       "      <td>2.005610e+08</td>\n",
       "      <td>2.024086e+08</td>\n",
       "      <td>2.042131e+08</td>\n",
       "      <td>2.059621e+08</td>\n",
       "      <td>2.076529e+08</td>\n",
       "      <td>2.092883e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>4.079941e+07</td>\n",
       "      <td>4.122389e+07</td>\n",
       "      <td>4.165688e+07</td>\n",
       "      <td>4.209674e+07</td>\n",
       "      <td>4.253992e+07</td>\n",
       "      <td>4.298152e+07</td>\n",
       "      <td>4.341776e+07</td>\n",
       "      <td>4.384743e+07</td>\n",
       "      <td>4.427104e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      2009          2010          2011          2012  \\\n",
       "Country Name                                                           \n",
       "Turkey        7.133918e+07  7.232691e+07  7.340946e+07  7.456987e+07   \n",
       "South Africa  5.097082e+07  5.158466e+07  5.226352e+07  5.299821e+07   \n",
       "Japan         1.280470e+08  1.280700e+08  1.278330e+08  1.276290e+08   \n",
       "Indonesia     2.393405e+08  2.425241e+08  2.457075e+08  2.488832e+08   \n",
       "Germany       8.190231e+07  8.177693e+07  8.027498e+07  8.042582e+07   \n",
       "Canada        3.362857e+07  3.400527e+07  3.434278e+07  3.475054e+07   \n",
       "Australia     2.169170e+07  2.203175e+07  2.234002e+07  2.274248e+07   \n",
       "Saudi Arabia  2.666149e+07  2.742568e+07  2.823802e+07  2.908636e+07   \n",
       "Mexico        1.155052e+08  1.173189e+08  1.190900e+08  1.208283e+08   \n",
       "Italy         5.909536e+07  5.927742e+07  5.937945e+07  5.953972e+07   \n",
       "India         1.214270e+09  1.230981e+09  1.247236e+09  1.263066e+09   \n",
       "France        6.470704e+07  6.502751e+07  6.534278e+07  6.565979e+07   \n",
       "Brazil        1.948960e+08  1.967963e+08  1.986867e+08  2.005610e+08   \n",
       "Argentina     4.079941e+07  4.122389e+07  4.165688e+07  4.209674e+07   \n",
       "\n",
       "                      2013          2014          2015          2016  \\\n",
       "Country Name                                                           \n",
       "Turkey        7.578733e+07  7.703063e+07  7.827147e+07  7.951243e+07   \n",
       "South Africa  5.376740e+07  5.453957e+07  5.529122e+07  5.601547e+07   \n",
       "Japan         1.274450e+08  1.272760e+08  1.271410e+08  1.269945e+08   \n",
       "Indonesia     2.520323e+08  2.551311e+08  2.581621e+08  2.611155e+08   \n",
       "Germany       8.064560e+07  8.098250e+07  8.168661e+07  8.234867e+07   \n",
       "Canada        3.515237e+07  3.553535e+07  3.583251e+07  3.626460e+07   \n",
       "Australia     2.314590e+07  2.350414e+07  2.385078e+07  2.421081e+07   \n",
       "Saudi Arabia  2.994448e+07  3.077672e+07  3.155714e+07  3.227569e+07   \n",
       "Mexico        1.225360e+08  1.242216e+08  1.258909e+08  1.275404e+08   \n",
       "Italy         6.023395e+07  6.078914e+07  6.073058e+07  6.062750e+07   \n",
       "India         1.278562e+09  1.293859e+09  1.309054e+09  1.324171e+09   \n",
       "France        6.599866e+07  6.631609e+07  6.659337e+07  6.685977e+07   \n",
       "Brazil        2.024086e+08  2.042131e+08  2.059621e+08  2.076529e+08   \n",
       "Argentina     4.253992e+07  4.298152e+07  4.341776e+07  4.384743e+07   \n",
       "\n",
       "                      2017  \n",
       "Country Name                \n",
       "Turkey        8.074502e+07  \n",
       "South Africa  5.671716e+07  \n",
       "Japan         1.267858e+08  \n",
       "Indonesia     2.639914e+08  \n",
       "Germany       8.269500e+07  \n",
       "Canada        3.670808e+07  \n",
       "Australia     2.459893e+07  \n",
       "Saudi Arabia  3.293821e+07  \n",
       "Mexico        1.291633e+08  \n",
       "Italy         6.055142e+07  \n",
       "India         1.339180e+09  \n",
       "France        6.711865e+07  \n",
       "Brazil        2.092883e+08  \n",
       "Argentina     4.427104e+07  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Population of G20 Countries\n",
    "##we took the data from world bank website and url is \"https://data.worldbank.org/indicator/NY.GDP.MKTP.CD\"\n",
    "\n",
    "Populationdata = pd.read_excel(\"Until2018_Total_Population.xls\",index_col=0,sheet_name='Data',skiprows=3)\n",
    "Population_G20 = Populationdata.loc[['Turkey','South Africa','Japan','Indonesia',  \n",
    "                         'Germany','Canada','Australia','Saudi Arabia','Mexico',\n",
    "                        'Italy','India','France','Brazil','Argentina'],\n",
    "                  ['2009','2010','2011','2012','2013','2014','2015','2016','2017']]\n",
    "Population_G20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country Name</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>Turkey</th>\n",
       "      <td>71.339185</td>\n",
       "      <td>72.326914</td>\n",
       "      <td>73.409455</td>\n",
       "      <td>74.569867</td>\n",
       "      <td>75.787333</td>\n",
       "      <td>77.030628</td>\n",
       "      <td>78.271472</td>\n",
       "      <td>79.512426</td>\n",
       "      <td>80.745020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>50.970818</td>\n",
       "      <td>51.584663</td>\n",
       "      <td>52.263516</td>\n",
       "      <td>52.998213</td>\n",
       "      <td>53.767396</td>\n",
       "      <td>54.539571</td>\n",
       "      <td>55.291225</td>\n",
       "      <td>56.015473</td>\n",
       "      <td>56.717156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>128.047000</td>\n",
       "      <td>128.070000</td>\n",
       "      <td>127.833000</td>\n",
       "      <td>127.629000</td>\n",
       "      <td>127.445000</td>\n",
       "      <td>127.276000</td>\n",
       "      <td>127.141000</td>\n",
       "      <td>126.994511</td>\n",
       "      <td>126.785797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>239.340478</td>\n",
       "      <td>242.524123</td>\n",
       "      <td>245.707511</td>\n",
       "      <td>248.883232</td>\n",
       "      <td>252.032263</td>\n",
       "      <td>255.131116</td>\n",
       "      <td>258.162113</td>\n",
       "      <td>261.115456</td>\n",
       "      <td>263.991379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>81.902307</td>\n",
       "      <td>81.776930</td>\n",
       "      <td>80.274983</td>\n",
       "      <td>80.425823</td>\n",
       "      <td>80.645605</td>\n",
       "      <td>80.982500</td>\n",
       "      <td>81.686611</td>\n",
       "      <td>82.348669</td>\n",
       "      <td>82.695000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>33.628571</td>\n",
       "      <td>34.005274</td>\n",
       "      <td>34.342780</td>\n",
       "      <td>34.750545</td>\n",
       "      <td>35.152370</td>\n",
       "      <td>35.535348</td>\n",
       "      <td>35.832513</td>\n",
       "      <td>36.264604</td>\n",
       "      <td>36.708083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>21.691700</td>\n",
       "      <td>22.031750</td>\n",
       "      <td>22.340024</td>\n",
       "      <td>22.742475</td>\n",
       "      <td>23.145901</td>\n",
       "      <td>23.504138</td>\n",
       "      <td>23.850784</td>\n",
       "      <td>24.210809</td>\n",
       "      <td>24.598933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>26.661492</td>\n",
       "      <td>27.425676</td>\n",
       "      <td>28.238020</td>\n",
       "      <td>29.086357</td>\n",
       "      <td>29.944476</td>\n",
       "      <td>30.776722</td>\n",
       "      <td>31.557144</td>\n",
       "      <td>32.275687</td>\n",
       "      <td>32.938213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>115.505228</td>\n",
       "      <td>117.318941</td>\n",
       "      <td>119.090017</td>\n",
       "      <td>120.828307</td>\n",
       "      <td>122.535969</td>\n",
       "      <td>124.221600</td>\n",
       "      <td>125.890949</td>\n",
       "      <td>127.540423</td>\n",
       "      <td>129.163276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>59.095365</td>\n",
       "      <td>59.277417</td>\n",
       "      <td>59.379449</td>\n",
       "      <td>59.539717</td>\n",
       "      <td>60.233948</td>\n",
       "      <td>60.789140</td>\n",
       "      <td>60.730582</td>\n",
       "      <td>60.627498</td>\n",
       "      <td>60.551416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>1214.270132</td>\n",
       "      <td>1230.980691</td>\n",
       "      <td>1247.236029</td>\n",
       "      <td>1263.065852</td>\n",
       "      <td>1278.562207</td>\n",
       "      <td>1293.859294</td>\n",
       "      <td>1309.053980</td>\n",
       "      <td>1324.171354</td>\n",
       "      <td>1339.180127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>64.707044</td>\n",
       "      <td>65.027507</td>\n",
       "      <td>65.342775</td>\n",
       "      <td>65.659789</td>\n",
       "      <td>65.998660</td>\n",
       "      <td>66.316092</td>\n",
       "      <td>66.593366</td>\n",
       "      <td>66.859768</td>\n",
       "      <td>67.118648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>194.895996</td>\n",
       "      <td>196.796269</td>\n",
       "      <td>198.686688</td>\n",
       "      <td>200.560983</td>\n",
       "      <td>202.408632</td>\n",
       "      <td>204.213133</td>\n",
       "      <td>205.962108</td>\n",
       "      <td>207.652865</td>\n",
       "      <td>209.288278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>40.799407</td>\n",
       "      <td>41.223889</td>\n",
       "      <td>41.656879</td>\n",
       "      <td>42.096739</td>\n",
       "      <td>42.539925</td>\n",
       "      <td>42.981515</td>\n",
       "      <td>43.417765</td>\n",
       "      <td>43.847430</td>\n",
       "      <td>44.271041</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     2009         2010         2011         2012         2013  \\\n",
       "Country Name                                                                    \n",
       "Turkey          71.339185    72.326914    73.409455    74.569867    75.787333   \n",
       "South Africa    50.970818    51.584663    52.263516    52.998213    53.767396   \n",
       "Japan          128.047000   128.070000   127.833000   127.629000   127.445000   \n",
       "Indonesia      239.340478   242.524123   245.707511   248.883232   252.032263   \n",
       "Germany         81.902307    81.776930    80.274983    80.425823    80.645605   \n",
       "Canada          33.628571    34.005274    34.342780    34.750545    35.152370   \n",
       "Australia       21.691700    22.031750    22.340024    22.742475    23.145901   \n",
       "Saudi Arabia    26.661492    27.425676    28.238020    29.086357    29.944476   \n",
       "Mexico         115.505228   117.318941   119.090017   120.828307   122.535969   \n",
       "Italy           59.095365    59.277417    59.379449    59.539717    60.233948   \n",
       "India         1214.270132  1230.980691  1247.236029  1263.065852  1278.562207   \n",
       "France          64.707044    65.027507    65.342775    65.659789    65.998660   \n",
       "Brazil         194.895996   196.796269   198.686688   200.560983   202.408632   \n",
       "Argentina       40.799407    41.223889    41.656879    42.096739    42.539925   \n",
       "\n",
       "                     2014         2015         2016         2017  \n",
       "Country Name                                                      \n",
       "Turkey          77.030628    78.271472    79.512426    80.745020  \n",
       "South Africa    54.539571    55.291225    56.015473    56.717156  \n",
       "Japan          127.276000   127.141000   126.994511   126.785797  \n",
       "Indonesia      255.131116   258.162113   261.115456   263.991379  \n",
       "Germany         80.982500    81.686611    82.348669    82.695000  \n",
       "Canada          35.535348    35.832513    36.264604    36.708083  \n",
       "Australia       23.504138    23.850784    24.210809    24.598933  \n",
       "Saudi Arabia    30.776722    31.557144    32.275687    32.938213  \n",
       "Mexico         124.221600   125.890949   127.540423   129.163276  \n",
       "Italy           60.789140    60.730582    60.627498    60.551416  \n",
       "India         1293.859294  1309.053980  1324.171354  1339.180127  \n",
       "France          66.316092    66.593366    66.859768    67.118648  \n",
       "Brazil         204.213133   205.962108   207.652865   209.288278  \n",
       "Argentina       42.981515    43.417765    43.847430    44.271041  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#In millions we have Population data of G20 Countries\n",
    "PopulationData_Millions = Population_G20/1000000\n",
    "PopulationData_Millions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country Name</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>Turkey</th>\n",
       "      <td>416.884706</td>\n",
       "      <td>512.734525</td>\n",
       "      <td>570.680980</td>\n",
       "      <td>500.071604</td>\n",
       "      <td>539.328806</td>\n",
       "      <td>531.659655</td>\n",
       "      <td>524.817836</td>\n",
       "      <td>552.405481</td>\n",
       "      <td>527.202842</td>\n",
       "      <td>454.608292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>362.463642</td>\n",
       "      <td>385.999993</td>\n",
       "      <td>372.355113</td>\n",
       "      <td>413.074083</td>\n",
       "      <td>539.567615</td>\n",
       "      <td>597.359448</td>\n",
       "      <td>579.748563</td>\n",
       "      <td>526.499575</td>\n",
       "      <td>509.833261</td>\n",
       "      <td>470.796993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>2754.157447</td>\n",
       "      <td>2772.455448</td>\n",
       "      <td>3213.398809</td>\n",
       "      <td>3685.825237</td>\n",
       "      <td>4060.190083</td>\n",
       "      <td>5087.102201</td>\n",
       "      <td>5212.069380</td>\n",
       "      <td>4336.149947</td>\n",
       "      <td>4099.465080</td>\n",
       "      <td>3732.562266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>45.361829</td>\n",
       "      <td>57.050494</td>\n",
       "      <td>60.666738</td>\n",
       "      <td>63.904085</td>\n",
       "      <td>107.491965</td>\n",
       "      <td>121.471749</td>\n",
       "      <td>124.473534</td>\n",
       "      <td>122.041519</td>\n",
       "      <td>120.079190</td>\n",
       "      <td>111.761744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>3746.156110</td>\n",
       "      <td>4240.497982</td>\n",
       "      <td>4730.123037</td>\n",
       "      <td>4742.252717</td>\n",
       "      <td>4696.737702</td>\n",
       "      <td>5030.805251</td>\n",
       "      <td>4761.253315</td>\n",
       "      <td>5103.486548</td>\n",
       "      <td>5293.384484</td>\n",
       "      <td>4591.846096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>3710.006373</td>\n",
       "      <td>4125.389372</td>\n",
       "      <td>4389.263347</td>\n",
       "      <td>4290.851273</td>\n",
       "      <td>4987.548682</td>\n",
       "      <td>5292.441914</td>\n",
       "      <td>5343.612160</td>\n",
       "      <td>5286.740903</td>\n",
       "      <td>5028.982333</td>\n",
       "      <td>4507.550519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>3177.485519</td>\n",
       "      <td>3794.238045</td>\n",
       "      <td>4088.804277</td>\n",
       "      <td>3997.509689</td>\n",
       "      <td>4952.776147</td>\n",
       "      <td>5876.878483</td>\n",
       "      <td>6047.020069</td>\n",
       "      <td>5838.389894</td>\n",
       "      <td>5637.559721</td>\n",
       "      <td>4934.047418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>544.327217</td>\n",
       "      <td>574.455256</td>\n",
       "      <td>575.125565</td>\n",
       "      <td>657.687624</td>\n",
       "      <td>670.962495</td>\n",
       "      <td>859.550351</td>\n",
       "      <td>991.667674</td>\n",
       "      <td>1091.317588</td>\n",
       "      <td>1248.805293</td>\n",
       "      <td>1194.100455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>501.037570</td>\n",
       "      <td>542.785954</td>\n",
       "      <td>556.534658</td>\n",
       "      <td>477.648850</td>\n",
       "      <td>538.744767</td>\n",
       "      <td>565.129192</td>\n",
       "      <td>580.748407</td>\n",
       "      <td>617.874698</td>\n",
       "      <td>593.398448</td>\n",
       "      <td>534.810930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>2830.181814</td>\n",
       "      <td>3088.470097</td>\n",
       "      <td>3489.985726</td>\n",
       "      <td>3324.373620</td>\n",
       "      <td>3214.546282</td>\n",
       "      <td>3387.575618</td>\n",
       "      <td>3125.611468</td>\n",
       "      <td>3195.553285</td>\n",
       "      <td>3190.088143</td>\n",
       "      <td>2700.425800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>29.651600</td>\n",
       "      <td>35.963478</td>\n",
       "      <td>37.993600</td>\n",
       "      <td>38.412412</td>\n",
       "      <td>45.250772</td>\n",
       "      <td>48.722833</td>\n",
       "      <td>49.051403</td>\n",
       "      <td>56.218824</td>\n",
       "      <td>57.151140</td>\n",
       "      <td>63.317742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>3693.584291</td>\n",
       "      <td>4168.034547</td>\n",
       "      <td>4614.265430</td>\n",
       "      <td>4523.594551</td>\n",
       "      <td>4385.429864</td>\n",
       "      <td>4725.351304</td>\n",
       "      <td>4447.746434</td>\n",
       "      <td>4679.114650</td>\n",
       "      <td>4779.179428</td>\n",
       "      <td>4026.147179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>484.001823</td>\n",
       "      <td>600.408660</td>\n",
       "      <td>704.905757</td>\n",
       "      <td>719.961527</td>\n",
       "      <td>894.941419</td>\n",
       "      <td>1029.311397</td>\n",
       "      <td>960.783780</td>\n",
       "      <td>975.935405</td>\n",
       "      <td>1014.092105</td>\n",
       "      <td>780.395982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>380.102685</td>\n",
       "      <td>465.151885</td>\n",
       "      <td>567.328010</td>\n",
       "      <td>576.811181</td>\n",
       "      <td>698.603496</td>\n",
       "      <td>806.859949</td>\n",
       "      <td>864.505354</td>\n",
       "      <td>920.812880</td>\n",
       "      <td>845.054687</td>\n",
       "      <td>997.931375</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     2006         2007         2008         2009         2010  \\\n",
       "Country Name                                                                    \n",
       "Turkey         416.884706   512.734525   570.680980   500.071604   539.328806   \n",
       "South Africa   362.463642   385.999993   372.355113   413.074083   539.567615   \n",
       "Japan         2754.157447  2772.455448  3213.398809  3685.825237  4060.190083   \n",
       "Indonesia       45.361829    57.050494    60.666738    63.904085   107.491965   \n",
       "Germany       3746.156110  4240.497982  4730.123037  4742.252717  4696.737702   \n",
       "Canada        3710.006373  4125.389372  4389.263347  4290.851273  4987.548682   \n",
       "Australia     3177.485519  3794.238045  4088.804277  3997.509689  4952.776147   \n",
       "Saudi Arabia   544.327217   574.455256   575.125565   657.687624   670.962495   \n",
       "Mexico         501.037570   542.785954   556.534658   477.648850   538.744767   \n",
       "Italy         2830.181814  3088.470097  3489.985726  3324.373620  3214.546282   \n",
       "India           29.651600    35.963478    37.993600    38.412412    45.250772   \n",
       "France        3693.584291  4168.034547  4614.265430  4523.594551  4385.429864   \n",
       "Brazil         484.001823   600.408660   704.905757   719.961527   894.941419   \n",
       "Argentina      380.102685   465.151885   567.328010   576.811181   698.603496   \n",
       "\n",
       "                     2011         2012         2013         2014         2015  \n",
       "Country Name                                                                   \n",
       "Turkey         531.659655   524.817836   552.405481   527.202842   454.608292  \n",
       "South Africa   597.359448   579.748563   526.499575   509.833261   470.796993  \n",
       "Japan         5087.102201  5212.069380  4336.149947  4099.465080  3732.562266  \n",
       "Indonesia      121.471749   124.473534   122.041519   120.079190   111.761744  \n",
       "Germany       5030.805251  4761.253315  5103.486548  5293.384484  4591.846096  \n",
       "Canada        5292.441914  5343.612160  5286.740903  5028.982333  4507.550519  \n",
       "Australia     5876.878483  6047.020069  5838.389894  5637.559721  4934.047418  \n",
       "Saudi Arabia   859.550351   991.667674  1091.317588  1248.805293  1194.100455  \n",
       "Mexico         565.129192   580.748407   617.874698   593.398448   534.810930  \n",
       "Italy         3387.575618  3125.611468  3195.553285  3190.088143  2700.425800  \n",
       "India           48.722833    49.051403    56.218824    57.151140    63.317742  \n",
       "France        4725.351304  4447.746434  4679.114650  4779.179428  4026.147179  \n",
       "Brazil        1029.311397   960.783780   975.935405  1014.092105   780.395982  \n",
       "Argentina      806.859949   864.505354   920.812880   845.054687   997.931375  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Health Per Person of G20 Countries spending amount in US dollars.\n",
    "###we took the data from world bank website and url is \"https://data.worldbank.org/indicator/NY.GDP.MKTP.CD\"\n",
    "\n",
    "\n",
    "Health_Per_Person = pd.read_excel(\"Until2018_Health_PC.xls\",index_col=0,sheet_name='Data',skiprows=3)\n",
    "Health_Per_Person_G20 = Health_Per_Person.loc[['Turkey','South Africa','Japan','Indonesia',  \n",
    "                         'Germany','Canada','Australia','Saudi Arabia','Mexico',\n",
    "                        'Italy','India','France','Brazil','Argentina'],\n",
    "                  ['2006','2007','2008','2009','2010','2011','2012','2013','2014','2015']]\n",
    "Health_Per_Person_G20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\n",
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       "        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>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country Name</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>Turkey</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35674.700637</td>\n",
       "      <td>39007.988161</td>\n",
       "      <td>39028.845551</td>\n",
       "      <td>39135.596250</td>\n",
       "      <td>41865.338108</td>\n",
       "      <td>40610.765980</td>\n",
       "      <td>35582.860204</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21054.723890</td>\n",
       "      <td>27833.413574</td>\n",
       "      <td>31220.105060</td>\n",
       "      <td>30725.637827</td>\n",
       "      <td>28308.511152</td>\n",
       "      <td>27806.087334</td>\n",
       "      <td>26030.942487</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>471958.864145</td>\n",
       "      <td>519988.543989</td>\n",
       "      <td>650299.535599</td>\n",
       "      <td>665211.202905</td>\n",
       "      <td>552620.629974</td>\n",
       "      <td>521763.517499</td>\n",
       "      <td>474561.699040</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15294.834135</td>\n",
       "      <td>26069.394570</td>\n",
       "      <td>29846.521020</td>\n",
       "      <td>30979.375532</td>\n",
       "      <td>30758.400100</td>\n",
       "      <td>30635.937858</td>\n",
       "      <td>28852.647942</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>388401.437899</td>\n",
       "      <td>384084.790313</td>\n",
       "      <td>403847.805990</td>\n",
       "      <td>382927.716389</td>\n",
       "      <td>411573.760287</td>\n",
       "      <td>428671.508942</td>\n",
       "      <td>375092.345811</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>144295.196693</td>\n",
       "      <td>169602.959503</td>\n",
       "      <td>181757.168320</td>\n",
       "      <td>185693.434813</td>\n",
       "      <td>185841.472314</td>\n",
       "      <td>178706.637278</td>\n",
       "      <td>161516.862568</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>86712.780916</td>\n",
       "      <td>109118.325885</td>\n",
       "      <td>131289.606354</td>\n",
       "      <td>137524.202744</td>\n",
       "      <td>135134.794482</td>\n",
       "      <td>132505.981660</td>\n",
       "      <td>117680.899223</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17534.933333</td>\n",
       "      <td>18401.600000</td>\n",
       "      <td>24272.000000</td>\n",
       "      <td>28844.000000</td>\n",
       "      <td>32678.933333</td>\n",
       "      <td>38434.133333</td>\n",
       "      <td>37682.400000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55170.939377</td>\n",
       "      <td>63204.965524</td>\n",
       "      <td>67301.245037</td>\n",
       "      <td>70170.846818</td>\n",
       "      <td>75711.874858</td>\n",
       "      <td>73712.904694</td>\n",
       "      <td>67327.855468</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>196455.072444</td>\n",
       "      <td>190550.000451</td>\n",
       "      <td>201152.373663</td>\n",
       "      <td>186098.022242</td>\n",
       "      <td>192480.790375</td>\n",
       "      <td>193922.714760</td>\n",
       "      <td>163998.430498</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46643.045112</td>\n",
       "      <td>55702.826117</td>\n",
       "      <td>60768.872304</td>\n",
       "      <td>61955.151970</td>\n",
       "      <td>71879.263982</td>\n",
       "      <td>73945.533406</td>\n",
       "      <td>82886.341554</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>292708.431641</td>\n",
       "      <td>285173.571171</td>\n",
       "      <td>308767.567069</td>\n",
       "      <td>292038.092366</td>\n",
       "      <td>308815.296857</td>\n",
       "      <td>316936.502632</td>\n",
       "      <td>268114.692674</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140317.618912</td>\n",
       "      <td>176121.132221</td>\n",
       "      <td>204510.472428</td>\n",
       "      <td>192695.739449</td>\n",
       "      <td>197537.750236</td>\n",
       "      <td>207090.925902</td>\n",
       "      <td>160732.001560</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23533.554154</td>\n",
       "      <td>28799.152959</td>\n",
       "      <td>33611.267285</td>\n",
       "      <td>36392.856254</td>\n",
       "      <td>39171.310835</td>\n",
       "      <td>36321.730720</td>\n",
       "      <td>43327.949940</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              2006  2007  2008           2009           2010           2011  \\\n",
       "Country Name                                                                  \n",
       "Turkey         NaN   NaN   NaN   35674.700637   39007.988161   39028.845551   \n",
       "South Africa   NaN   NaN   NaN   21054.723890   27833.413574   31220.105060   \n",
       "Japan          NaN   NaN   NaN  471958.864145  519988.543989  650299.535599   \n",
       "Indonesia      NaN   NaN   NaN   15294.834135   26069.394570   29846.521020   \n",
       "Germany        NaN   NaN   NaN  388401.437899  384084.790313  403847.805990   \n",
       "Canada         NaN   NaN   NaN  144295.196693  169602.959503  181757.168320   \n",
       "Australia      NaN   NaN   NaN   86712.780916  109118.325885  131289.606354   \n",
       "Saudi Arabia   NaN   NaN   NaN   17534.933333   18401.600000   24272.000000   \n",
       "Mexico         NaN   NaN   NaN   55170.939377   63204.965524   67301.245037   \n",
       "Italy          NaN   NaN   NaN  196455.072444  190550.000451  201152.373663   \n",
       "India          NaN   NaN   NaN   46643.045112   55702.826117   60768.872304   \n",
       "France         NaN   NaN   NaN  292708.431641  285173.571171  308767.567069   \n",
       "Brazil         NaN   NaN   NaN  140317.618912  176121.132221  204510.472428   \n",
       "Argentina      NaN   NaN   NaN   23533.554154   28799.152959   33611.267285   \n",
       "\n",
       "                       2012           2013           2014           2015  \\\n",
       "Country Name                                                               \n",
       "Turkey         39135.596250   41865.338108   40610.765980   35582.860204   \n",
       "South Africa   30725.637827   28308.511152   27806.087334   26030.942487   \n",
       "Japan         665211.202905  552620.629974  521763.517499  474561.699040   \n",
       "Indonesia      30979.375532   30758.400100   30635.937858   28852.647942   \n",
       "Germany       382927.716389  411573.760287  428671.508942  375092.345811   \n",
       "Canada        185693.434813  185841.472314  178706.637278  161516.862568   \n",
       "Australia     137524.202744  135134.794482  132505.981660  117680.899223   \n",
       "Saudi Arabia   28844.000000   32678.933333   38434.133333   37682.400000   \n",
       "Mexico         70170.846818   75711.874858   73712.904694   67327.855468   \n",
       "Italy         186098.022242  192480.790375  193922.714760  163998.430498   \n",
       "India          61955.151970   71879.263982   73945.533406   82886.341554   \n",
       "France        292038.092366  308815.296857  316936.502632  268114.692674   \n",
       "Brazil        192695.739449  197537.750236  207090.925902  160732.001560   \n",
       "Argentina      36392.856254   39171.310835   36321.730720   43327.949940   \n",
       "\n",
       "              2016  2017  \n",
       "Country Name              \n",
       "Turkey         NaN   NaN  \n",
       "South Africa   NaN   NaN  \n",
       "Japan          NaN   NaN  \n",
       "Indonesia      NaN   NaN  \n",
       "Germany        NaN   NaN  \n",
       "Canada         NaN   NaN  \n",
       "Australia      NaN   NaN  \n",
       "Saudi Arabia   NaN   NaN  \n",
       "Mexico         NaN   NaN  \n",
       "Italy          NaN   NaN  \n",
       "India          NaN   NaN  \n",
       "France         NaN   NaN  \n",
       "Brazil         NaN   NaN  \n",
       "Argentina      NaN   NaN  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Health Expenditure data of all G20 countries in million dollars\n",
    "\n",
    "HealthExpenditureData = Health_Per_Person_G20 * Population_G20\n",
    "HealthExpenditureData1_Millions = HealthExpenditureData/1000000\n",
    "HealthExpenditureData1_Millions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'HealthExpenditureData_Millions' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-24-ee2912898d69>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m#Formatting the countries in order based on Health Expenditure data in Millions\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mHealthExpenditureData_Millions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Total'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mHealthExpenditureData_Millions\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0mHealthExpenditureData_Millions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Total'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mHealthExpenditureData_Millions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mascending\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mby\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Total'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'HealthExpenditureData_Millions' is not defined"
     ]
    }
   ],
   "source": [
    "#Formatting the countries in order based on Health Expenditure data in Millions\n",
    "HealthExpenditureData_Millions['Total'] = np.sum(HealthExpenditureData_Millions,axis=1)\n",
    "HealthExpenditureData_Millions['Total']\n",
    "HealthExpenditureData_Millions.sort_values(ascending=False,by='Total')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
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       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>5.188443</td>\n",
       "      <td>5.280757</td>\n",
       "      <td>5.259400</td>\n",
       "      <td>5.533908</td>\n",
       "      <td>5.053656</td>\n",
       "      <td>4.687890</td>\n",
       "      <td>4.477850</td>\n",
       "      <td>4.404118</td>\n",
       "      <td>4.347266</td>\n",
       "      <td>4.138533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>6.587062</td>\n",
       "      <td>6.431316</td>\n",
       "      <td>6.545761</td>\n",
       "      <td>7.114587</td>\n",
       "      <td>7.415357</td>\n",
       "      <td>7.497317</td>\n",
       "      <td>7.752553</td>\n",
       "      <td>7.721369</td>\n",
       "      <td>7.925304</td>\n",
       "      <td>8.201155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>7.807843</td>\n",
       "      <td>7.890461</td>\n",
       "      <td>8.199514</td>\n",
       "      <td>9.058297</td>\n",
       "      <td>9.156773</td>\n",
       "      <td>10.616718</td>\n",
       "      <td>10.790653</td>\n",
       "      <td>10.791594</td>\n",
       "      <td>10.835803</td>\n",
       "      <td>10.898156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>2.859771</td>\n",
       "      <td>3.075343</td>\n",
       "      <td>2.807959</td>\n",
       "      <td>2.834581</td>\n",
       "      <td>3.452469</td>\n",
       "      <td>3.342391</td>\n",
       "      <td>3.375138</td>\n",
       "      <td>3.370694</td>\n",
       "      <td>3.440357</td>\n",
       "      <td>3.347431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>10.128486</td>\n",
       "      <td>9.984562</td>\n",
       "      <td>10.180502</td>\n",
       "      <td>11.167144</td>\n",
       "      <td>11.034898</td>\n",
       "      <td>10.747211</td>\n",
       "      <td>10.805037</td>\n",
       "      <td>10.968000</td>\n",
       "      <td>11.050367</td>\n",
       "      <td>11.151569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>9.207055</td>\n",
       "      <td>9.298435</td>\n",
       "      <td>9.465102</td>\n",
       "      <td>10.574113</td>\n",
       "      <td>10.562243</td>\n",
       "      <td>10.219664</td>\n",
       "      <td>10.222931</td>\n",
       "      <td>10.115272</td>\n",
       "      <td>9.987017</td>\n",
       "      <td>10.435622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>7.983217</td>\n",
       "      <td>8.057317</td>\n",
       "      <td>8.261526</td>\n",
       "      <td>8.587602</td>\n",
       "      <td>8.467782</td>\n",
       "      <td>8.585724</td>\n",
       "      <td>8.725502</td>\n",
       "      <td>8.805844</td>\n",
       "      <td>9.079250</td>\n",
       "      <td>9.445333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</th>\n",
       "      <td>3.549651</td>\n",
       "      <td>3.487430</td>\n",
       "      <td>2.870199</td>\n",
       "      <td>4.086465</td>\n",
       "      <td>3.493014</td>\n",
       "      <td>3.625356</td>\n",
       "      <td>3.929937</td>\n",
       "      <td>4.390346</td>\n",
       "      <td>5.098504</td>\n",
       "      <td>5.833172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>5.714462</td>\n",
       "      <td>5.819359</td>\n",
       "      <td>5.743962</td>\n",
       "      <td>6.175593</td>\n",
       "      <td>6.019952</td>\n",
       "      <td>5.755392</td>\n",
       "      <td>5.924072</td>\n",
       "      <td>6.014017</td>\n",
       "      <td>5.691027</td>\n",
       "      <td>5.864490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>8.459687</td>\n",
       "      <td>8.162836</td>\n",
       "      <td>8.561831</td>\n",
       "      <td>8.976537</td>\n",
       "      <td>8.953612</td>\n",
       "      <td>8.834643</td>\n",
       "      <td>8.956061</td>\n",
       "      <td>8.952267</td>\n",
       "      <td>9.011441</td>\n",
       "      <td>8.996320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>3.634778</td>\n",
       "      <td>3.517542</td>\n",
       "      <td>3.514679</td>\n",
       "      <td>3.485380</td>\n",
       "      <td>3.272121</td>\n",
       "      <td>3.246450</td>\n",
       "      <td>3.328474</td>\n",
       "      <td>3.748426</td>\n",
       "      <td>3.629525</td>\n",
       "      <td>3.888257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>10.045368</td>\n",
       "      <td>9.961600</td>\n",
       "      <td>10.102235</td>\n",
       "      <td>10.806621</td>\n",
       "      <td>10.713047</td>\n",
       "      <td>10.725864</td>\n",
       "      <td>10.827697</td>\n",
       "      <td>10.929331</td>\n",
       "      <td>11.100077</td>\n",
       "      <td>11.066443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>8.259312</td>\n",
       "      <td>8.209353</td>\n",
       "      <td>8.021441</td>\n",
       "      <td>8.417393</td>\n",
       "      <td>7.973474</td>\n",
       "      <td>7.817211</td>\n",
       "      <td>7.816547</td>\n",
       "      <td>7.988362</td>\n",
       "      <td>8.431892</td>\n",
       "      <td>8.911484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>6.415635</td>\n",
       "      <td>6.419172</td>\n",
       "      <td>6.270604</td>\n",
       "      <td>6.997006</td>\n",
       "      <td>6.755996</td>\n",
       "      <td>6.343036</td>\n",
       "      <td>6.257964</td>\n",
       "      <td>6.387981</td>\n",
       "      <td>6.407625</td>\n",
       "      <td>6.834533</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   2006      2007       2008       2009       2010       2011  \\\n",
       "Country Name                                                                    \n",
       "Turkey         5.188443  5.280757   5.259400   5.533908   5.053656   4.687890   \n",
       "South Africa   6.587062  6.431316   6.545761   7.114587   7.415357   7.497317   \n",
       "Japan          7.807843  7.890461   8.199514   9.058297   9.156773  10.616718   \n",
       "Indonesia      2.859771  3.075343   2.807959   2.834581   3.452469   3.342391   \n",
       "Germany       10.128486  9.984562  10.180502  11.167144  11.034898  10.747211   \n",
       "Canada         9.207055  9.298435   9.465102  10.574113  10.562243  10.219664   \n",
       "Australia      7.983217  8.057317   8.261526   8.587602   8.467782   8.585724   \n",
       "Saudi Arabia   3.549651  3.487430   2.870199   4.086465   3.493014   3.625356   \n",
       "Mexico         5.714462  5.819359   5.743962   6.175593   6.019952   5.755392   \n",
       "Italy          8.459687  8.162836   8.561831   8.976537   8.953612   8.834643   \n",
       "India          3.634778  3.517542   3.514679   3.485380   3.272121   3.246450   \n",
       "France        10.045368  9.961600  10.102235  10.806621  10.713047  10.725864   \n",
       "Brazil         8.259312  8.209353   8.021441   8.417393   7.973474   7.817211   \n",
       "Argentina      6.415635  6.419172   6.270604   6.997006   6.755996   6.343036   \n",
       "\n",
       "                   2012       2013       2014       2015  \n",
       "Country Name                                              \n",
       "Turkey         4.477850   4.404118   4.347266   4.138533  \n",
       "South Africa   7.752553   7.721369   7.925304   8.201155  \n",
       "Japan         10.790653  10.791594  10.835803  10.898156  \n",
       "Indonesia      3.375138   3.370694   3.440357   3.347431  \n",
       "Germany       10.805037  10.968000  11.050367  11.151569  \n",
       "Canada        10.222931  10.115272   9.987017  10.435622  \n",
       "Australia      8.725502   8.805844   9.079250   9.445333  \n",
       "Saudi Arabia   3.929937   4.390346   5.098504   5.833172  \n",
       "Mexico         5.924072   6.014017   5.691027   5.864490  \n",
       "Italy          8.956061   8.952267   9.011441   8.996320  \n",
       "India          3.328474   3.748426   3.629525   3.888257  \n",
       "France        10.827697  10.929331  11.100077  11.066443  \n",
       "Brazil         7.816547   7.988362   8.431892   8.911484  \n",
       "Argentina      6.257964   6.387981   6.407625   6.834533  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Health Percent Data of G20 countries and removing header and footer.\n",
    "#we took the data from world bank website and url is \"https://data.worldbank.org/indicator/NY.GDP.MKTP.CD\"\n",
    "\n",
    "\n",
    "HealthPercentData = pd.read_excel(\"Until2018_Health_%GDP.xls\",index_col=0,sheet_name='Data',skiprows=3)\n",
    "HealthPercentData_G20 = HealthPercentData.loc [['Turkey','South Africa','Japan','Indonesia',  \n",
    "                         'Germany','Canada','Australia','Saudi Arabia','Mexico',\n",
    "                        'Italy','India','France','Brazil','Argentina'],\n",
    "                  ['2006','2007','2008','2009','2010','2011','2012','2013','2014','2015']]\n",
    "HealthPercentData_G20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country Name</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>Turkey</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.41900</td>\n",
       "      <td>4.36410</td>\n",
       "      <td>4.37116</td>\n",
       "      <td>4.29187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>5.24869</td>\n",
       "      <td>5.72174</td>\n",
       "      <td>5.96275</td>\n",
       "      <td>6.37164</td>\n",
       "      <td>6.01354</td>\n",
       "      <td>6.04662</td>\n",
       "      <td>5.95619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.63950</td>\n",
       "      <td>3.64258</td>\n",
       "      <td>3.69226</td>\n",
       "      <td>3.66538</td>\n",
       "      <td>3.59059</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>3.52513</td>\n",
       "      <td>2.81228</td>\n",
       "      <td>3.18944</td>\n",
       "      <td>3.40748</td>\n",
       "      <td>3.35904</td>\n",
       "      <td>3.28801</td>\n",
       "      <td>3.58360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>4.88048</td>\n",
       "      <td>4.91368</td>\n",
       "      <td>4.80780</td>\n",
       "      <td>4.93331</td>\n",
       "      <td>4.93497</td>\n",
       "      <td>4.93113</td>\n",
       "      <td>4.81341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>4.85264</td>\n",
       "      <td>5.36993</td>\n",
       "      <td>5.27444</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>5.09327</td>\n",
       "      <td>5.55917</td>\n",
       "      <td>5.08313</td>\n",
       "      <td>4.87765</td>\n",
       "      <td>5.23801</td>\n",
       "      <td>5.17368</td>\n",
       "      <td>5.32175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>5.18794</td>\n",
       "      <td>5.15922</td>\n",
       "      <td>5.10565</td>\n",
       "      <td>5.10310</td>\n",
       "      <td>4.69605</td>\n",
       "      <td>5.26134</td>\n",
       "      <td>5.23946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>4.53631</td>\n",
       "      <td>4.35239</td>\n",
       "      <td>4.14407</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.16472</td>\n",
       "      <td>4.07525</td>\n",
       "      <td>4.08036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>3.31124</td>\n",
       "      <td>3.42347</td>\n",
       "      <td>3.83972</td>\n",
       "      <td>3.86750</td>\n",
       "      <td>3.84467</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>5.74618</td>\n",
       "      <td>5.69251</td>\n",
       "      <td>5.51830</td>\n",
       "      <td>5.45642</td>\n",
       "      <td>5.50028</td>\n",
       "      <td>5.51206</td>\n",
       "      <td>5.46424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>5.46355</td>\n",
       "      <td>5.64880</td>\n",
       "      <td>5.73741</td>\n",
       "      <td>5.85510</td>\n",
       "      <td>5.83885</td>\n",
       "      <td>5.94848</td>\n",
       "      <td>6.24106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>5.53105</td>\n",
       "      <td>5.01971</td>\n",
       "      <td>5.29063</td>\n",
       "      <td>5.34583</td>\n",
       "      <td>5.43661</td>\n",
       "      <td>5.36144</td>\n",
       "      <td>5.77611</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 2009     2010     2011     2012     2013     2014     2015\n",
       "Country Name                                                               \n",
       "Turkey            NaN      NaN      NaN  4.41900  4.36410  4.37116  4.29187\n",
       "South Africa  5.24869  5.72174  5.96275  6.37164  6.01354  6.04662  5.95619\n",
       "Japan             NaN  3.63950  3.64258  3.69226  3.66538  3.59059      NaN\n",
       "Indonesia     3.52513  2.81228  3.18944  3.40748  3.35904  3.28801  3.58360\n",
       "Germany       4.88048  4.91368  4.80780  4.93331  4.93497  4.93113  4.81341\n",
       "Canada        4.85264  5.36993  5.27444      NaN      NaN      NaN      NaN\n",
       "Australia     5.09327  5.55917  5.08313  4.87765  5.23801  5.17368  5.32175\n",
       "Mexico        5.18794  5.15922  5.10565  5.10310  4.69605  5.26134  5.23946\n",
       "Italy         4.53631  4.35239  4.14407      NaN  4.16472  4.07525  4.08036\n",
       "India         3.31124  3.42347  3.83972  3.86750  3.84467      NaN      NaN\n",
       "France        5.74618  5.69251  5.51830  5.45642  5.50028  5.51206  5.46424\n",
       "Brazil        5.46355  5.64880  5.73741  5.85510  5.83885  5.94848  6.24106\n",
       "Argentina     5.53105  5.01971  5.29063  5.34583  5.43661  5.36144  5.77611"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#EducationPercentageData to check which country has good percentage of education with respect to GDP share\n",
    "##we took the data from world bank website and url is \"https://data.worldbank.org/indicator/NY.GDP.MKTP.CD\"\n",
    "\n",
    "\n",
    "\n",
    "EducationPercentData = pd.read_excel(\"Until2018_Education_%GDP.xls\",index_col=0,sheet_name='Data',skiprows=3)\n",
    "EducationPercentData_G20 = EducationPercentData.loc[['Turkey','South Africa','Japan','Indonesia',  \n",
    "                         'Germany','Canada','Australia','Mexico',\n",
    "                        'Italy','India','France','Brazil','Argentina'],\n",
    "                  ['2009','2010','2011','2012','2013','2014','2015']]\n",
    "EducationPercentData_G20\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country Name</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>Turkey</th>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>4.41900</td>\n",
       "      <td>4.36410</td>\n",
       "      <td>4.37116</td>\n",
       "      <td>4.29187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>5.24869</td>\n",
       "      <td>5.72174</td>\n",
       "      <td>5.96275</td>\n",
       "      <td>6.37164</td>\n",
       "      <td>6.01354</td>\n",
       "      <td>6.04662</td>\n",
       "      <td>5.95619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>0.00000</td>\n",
       "      <td>3.63950</td>\n",
       "      <td>3.64258</td>\n",
       "      <td>3.69226</td>\n",
       "      <td>3.66538</td>\n",
       "      <td>3.59059</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>3.52513</td>\n",
       "      <td>2.81228</td>\n",
       "      <td>3.18944</td>\n",
       "      <td>3.40748</td>\n",
       "      <td>3.35904</td>\n",
       "      <td>3.28801</td>\n",
       "      <td>3.58360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>4.88048</td>\n",
       "      <td>4.91368</td>\n",
       "      <td>4.80780</td>\n",
       "      <td>4.93331</td>\n",
       "      <td>4.93497</td>\n",
       "      <td>4.93113</td>\n",
       "      <td>4.81341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>4.85264</td>\n",
       "      <td>5.36993</td>\n",
       "      <td>5.27444</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>5.09327</td>\n",
       "      <td>5.55917</td>\n",
       "      <td>5.08313</td>\n",
       "      <td>4.87765</td>\n",
       "      <td>5.23801</td>\n",
       "      <td>5.17368</td>\n",
       "      <td>5.32175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>5.18794</td>\n",
       "      <td>5.15922</td>\n",
       "      <td>5.10565</td>\n",
       "      <td>5.10310</td>\n",
       "      <td>4.69605</td>\n",
       "      <td>5.26134</td>\n",
       "      <td>5.23946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>4.53631</td>\n",
       "      <td>4.35239</td>\n",
       "      <td>4.14407</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>4.16472</td>\n",
       "      <td>4.07525</td>\n",
       "      <td>4.08036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>3.31124</td>\n",
       "      <td>3.42347</td>\n",
       "      <td>3.83972</td>\n",
       "      <td>3.86750</td>\n",
       "      <td>3.84467</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>5.74618</td>\n",
       "      <td>5.69251</td>\n",
       "      <td>5.51830</td>\n",
       "      <td>5.45642</td>\n",
       "      <td>5.50028</td>\n",
       "      <td>5.51206</td>\n",
       "      <td>5.46424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>5.46355</td>\n",
       "      <td>5.64880</td>\n",
       "      <td>5.73741</td>\n",
       "      <td>5.85510</td>\n",
       "      <td>5.83885</td>\n",
       "      <td>5.94848</td>\n",
       "      <td>6.24106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>5.53105</td>\n",
       "      <td>5.01971</td>\n",
       "      <td>5.29063</td>\n",
       "      <td>5.34583</td>\n",
       "      <td>5.43661</td>\n",
       "      <td>5.36144</td>\n",
       "      <td>5.77611</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 2009     2010     2011     2012     2013     2014     2015\n",
       "Country Name                                                               \n",
       "Turkey        0.00000  0.00000  0.00000  4.41900  4.36410  4.37116  4.29187\n",
       "South Africa  5.24869  5.72174  5.96275  6.37164  6.01354  6.04662  5.95619\n",
       "Japan         0.00000  3.63950  3.64258  3.69226  3.66538  3.59059  0.00000\n",
       "Indonesia     3.52513  2.81228  3.18944  3.40748  3.35904  3.28801  3.58360\n",
       "Germany       4.88048  4.91368  4.80780  4.93331  4.93497  4.93113  4.81341\n",
       "Canada        4.85264  5.36993  5.27444  0.00000  0.00000  0.00000  0.00000\n",
       "Australia     5.09327  5.55917  5.08313  4.87765  5.23801  5.17368  5.32175\n",
       "Mexico        5.18794  5.15922  5.10565  5.10310  4.69605  5.26134  5.23946\n",
       "Italy         4.53631  4.35239  4.14407  0.00000  4.16472  4.07525  4.08036\n",
       "India         3.31124  3.42347  3.83972  3.86750  3.84467  0.00000  0.00000\n",
       "France        5.74618  5.69251  5.51830  5.45642  5.50028  5.51206  5.46424\n",
       "Brazil        5.46355  5.64880  5.73741  5.85510  5.83885  5.94848  6.24106\n",
       "Argentina     5.53105  5.01971  5.29063  5.34583  5.43661  5.36144  5.77611"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#We need to replace NAN's by Zero\n",
    "EducationPercentData_G20[np.isnan(EducationPercentData_G20)]=0\n",
    "EducationPercentData_G20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>18417.095850</td>\n",
       "      <td>21264.868070</td>\n",
       "      <td>28048.977624</td>\n",
       "      <td>29187.289635</td>\n",
       "      <td>30011.453977</td>\n",
       "      <td>28218.313515</td>\n",
       "      <td>34353.372950</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>47255.623061</td>\n",
       "      <td>63715.785738</td>\n",
       "      <td>70993.530384</td>\n",
       "      <td>75415.872486</td>\n",
       "      <td>82560.700001</td>\n",
       "      <td>75922.910956</td>\n",
       "      <td>71924.520559</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>91078.459386</td>\n",
       "      <td>124774.741551</td>\n",
       "      <td>150102.210967</td>\n",
       "      <td>144339.262076</td>\n",
       "      <td>144383.459762</td>\n",
       "      <td>146094.314874</td>\n",
       "      <td>112477.280394</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>66537.119181</td>\n",
       "      <td>86646.119556</td>\n",
       "      <td>94367.150902</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>China</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>154585.014837</td>\n",
       "      <td>150430.812834</td>\n",
       "      <td>157901.087060</td>\n",
       "      <td>146440.776347</td>\n",
       "      <td>154617.145931</td>\n",
       "      <td>157213.088025</td>\n",
       "      <td>133229.531150</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>166815.050492</td>\n",
       "      <td>167905.092106</td>\n",
       "      <td>180662.617960</td>\n",
       "      <td>174835.712588</td>\n",
       "      <td>185185.415633</td>\n",
       "      <td>192251.272249</td>\n",
       "      <td>162760.132566</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>44433.089145</td>\n",
       "      <td>57364.187545</td>\n",
       "      <td>70000.012687</td>\n",
       "      <td>70683.894202</td>\n",
       "      <td>71384.838385</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>19020.899472</td>\n",
       "      <td>21235.362053</td>\n",
       "      <td>28480.713916</td>\n",
       "      <td>31276.233613</td>\n",
       "      <td>30652.050762</td>\n",
       "      <td>29290.078234</td>\n",
       "      <td>30849.572368</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>99125.639915</td>\n",
       "      <td>92490.822517</td>\n",
       "      <td>94331.150651</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>88728.998130</td>\n",
       "      <td>87688.493713</td>\n",
       "      <td>74763.335912</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>207455.070886</td>\n",
       "      <td>224290.391709</td>\n",
       "      <td>229038.756794</td>\n",
       "      <td>188976.621837</td>\n",
       "      <td>174158.463384</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>46693.812764</td>\n",
       "      <td>54574.296002</td>\n",
       "      <td>60271.667362</td>\n",
       "      <td>61292.823127</td>\n",
       "      <td>59848.484480</td>\n",
       "      <td>69163.679844</td>\n",
       "      <td>61331.265035</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>15532.788738</td>\n",
       "      <td>21476.519211</td>\n",
       "      <td>24830.016465</td>\n",
       "      <td>25252.585427</td>\n",
       "      <td>22048.236882</td>\n",
       "      <td>21201.639090</td>\n",
       "      <td>18913.096953</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>38621.275478</td>\n",
       "      <td>41484.236168</td>\n",
       "      <td>40834.761059</td>\n",
       "      <td>36901.364039</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "                       2009           2010           2011           2012  \\\n",
       "Country Name                                                               \n",
       "Argentina      18417.095850   21264.868070   28048.977624   29187.289635   \n",
       "Australia      47255.623061   63715.785738   70993.530384   75415.872486   \n",
       "Brazil         91078.459386  124774.741551  150102.210967  144339.262076   \n",
       "Canada         66537.119181   86646.119556   94367.150902       0.000000   \n",
       "China                   NaN            NaN            NaN            NaN   \n",
       "France        154585.014837  150430.812834  157901.087060  146440.776347   \n",
       "Germany       166815.050492  167905.092106  180662.617960  174835.712588   \n",
       "India          44433.089145   57364.187545   70000.012687   70683.894202   \n",
       "Indonesia      19020.899472   21235.362053   28480.713916   31276.233613   \n",
       "Italy          99125.639915   92490.822517   94331.150651       0.000000   \n",
       "Japan              0.000000  207455.070886  224290.391709  229038.756794   \n",
       "Mexico         46693.812764   54574.296002   60271.667362   61292.823127   \n",
       "Saudi Arabia            NaN            NaN            NaN            NaN   \n",
       "South Africa   15532.788738   21476.519211   24830.016465   25252.585427   \n",
       "Turkey             0.000000       0.000000       0.000000   38621.275478   \n",
       "\n",
       "                       2013           2014           2015  2016  2017  2018  \n",
       "Country Name                                                                 \n",
       "Argentina      30011.453977   28218.313515   34353.372950   NaN   NaN   NaN  \n",
       "Australia      82560.700001   75922.910956   71924.520559   NaN   NaN   NaN  \n",
       "Brazil        144383.459762  146094.314874  112477.280394   NaN   NaN   NaN  \n",
       "Canada             0.000000       0.000000       0.000000   NaN   NaN   NaN  \n",
       "China                   NaN            NaN            NaN   NaN   NaN   NaN  \n",
       "France        154617.145931  157213.088025  133229.531150   NaN   NaN   NaN  \n",
       "Germany       185185.415633  192251.272249  162760.132566   NaN   NaN   NaN  \n",
       "India          71384.838385       0.000000       0.000000   NaN   NaN   NaN  \n",
       "Indonesia      30652.050762   29290.078234   30849.572368   NaN   NaN   NaN  \n",
       "Italy          88728.998130   87688.493713   74763.335912   NaN   NaN   NaN  \n",
       "Japan         188976.621837  174158.463384       0.000000   NaN   NaN   NaN  \n",
       "Mexico         59848.484480   69163.679844   61331.265035   NaN   NaN   NaN  \n",
       "Saudi Arabia            NaN            NaN            NaN   NaN   NaN   NaN  \n",
       "South Africa   22048.236882   21201.639090   18913.096953   NaN   NaN   NaN  \n",
       "Turkey         41484.236168   40834.761059   36901.364039   NaN   NaN   NaN  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Education Expedniture for G20 Countries i million dollars\n",
    "EducationExpenditureData_Millions_G20 = (EducationPercentData_G20 * GDP_G20_Millions)/100\n",
    "EducationExpenditureData_Millions_G20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
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       "      <th>Country Name</th>\n",
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       "      <th>Turkey</th>\n",
       "      <td>0.00000</td>\n",
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       "      <td>0.00000</td>\n",
       "      <td>4.41900</td>\n",
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       "      <th>South Africa</th>\n",
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       "      <td>3.64258</td>\n",
       "      <td>3.69226</td>\n",
       "      <td>3.66538</td>\n",
       "      <td>3.59059</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>3.52513</td>\n",
       "      <td>2.81228</td>\n",
       "      <td>3.18944</td>\n",
       "      <td>3.40748</td>\n",
       "      <td>3.35904</td>\n",
       "      <td>3.28801</td>\n",
       "      <td>3.58360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>4.88048</td>\n",
       "      <td>4.91368</td>\n",
       "      <td>4.80780</td>\n",
       "      <td>4.93331</td>\n",
       "      <td>4.93497</td>\n",
       "      <td>4.93113</td>\n",
       "      <td>4.81341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>4.85264</td>\n",
       "      <td>5.36993</td>\n",
       "      <td>5.27444</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>5.09327</td>\n",
       "      <td>5.55917</td>\n",
       "      <td>5.08313</td>\n",
       "      <td>4.87765</td>\n",
       "      <td>5.23801</td>\n",
       "      <td>5.17368</td>\n",
       "      <td>5.32175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>5.18794</td>\n",
       "      <td>5.15922</td>\n",
       "      <td>5.10565</td>\n",
       "      <td>5.10310</td>\n",
       "      <td>4.69605</td>\n",
       "      <td>5.26134</td>\n",
       "      <td>5.23946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>4.53631</td>\n",
       "      <td>4.35239</td>\n",
       "      <td>4.14407</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>4.16472</td>\n",
       "      <td>4.07525</td>\n",
       "      <td>4.08036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>3.31124</td>\n",
       "      <td>3.42347</td>\n",
       "      <td>3.83972</td>\n",
       "      <td>3.86750</td>\n",
       "      <td>3.84467</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>5.74618</td>\n",
       "      <td>5.69251</td>\n",
       "      <td>5.51830</td>\n",
       "      <td>5.45642</td>\n",
       "      <td>5.50028</td>\n",
       "      <td>5.51206</td>\n",
       "      <td>5.46424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>5.46355</td>\n",
       "      <td>5.64880</td>\n",
       "      <td>5.73741</td>\n",
       "      <td>5.85510</td>\n",
       "      <td>5.83885</td>\n",
       "      <td>5.94848</td>\n",
       "      <td>6.24106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>5.53105</td>\n",
       "      <td>5.01971</td>\n",
       "      <td>5.29063</td>\n",
       "      <td>5.34583</td>\n",
       "      <td>5.43661</td>\n",
       "      <td>5.36144</td>\n",
       "      <td>5.77611</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 2009     2010     2011     2012     2013     2014     2015\n",
       "Country Name                                                               \n",
       "Turkey        0.00000  0.00000  0.00000  4.41900  4.36410  4.37116  4.29187\n",
       "South Africa  5.24869  5.72174  5.96275  6.37164  6.01354  6.04662  5.95619\n",
       "Japan         0.00000  3.63950  3.64258  3.69226  3.66538  3.59059  0.00000\n",
       "Indonesia     3.52513  2.81228  3.18944  3.40748  3.35904  3.28801  3.58360\n",
       "Germany       4.88048  4.91368  4.80780  4.93331  4.93497  4.93113  4.81341\n",
       "Canada        4.85264  5.36993  5.27444  0.00000  0.00000  0.00000  0.00000\n",
       "Australia     5.09327  5.55917  5.08313  4.87765  5.23801  5.17368  5.32175\n",
       "Mexico        5.18794  5.15922  5.10565  5.10310  4.69605  5.26134  5.23946\n",
       "Italy         4.53631  4.35239  4.14407  0.00000  4.16472  4.07525  4.08036\n",
       "India         3.31124  3.42347  3.83972  3.86750  3.84467  0.00000  0.00000\n",
       "France        5.74618  5.69251  5.51830  5.45642  5.50028  5.51206  5.46424\n",
       "Brazil        5.46355  5.64880  5.73741  5.85510  5.83885  5.94848  6.24106\n",
       "Argentina     5.53105  5.01971  5.29063  5.34583  5.43661  5.36144  5.77611"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Select the countries that gives more information and based on them select the percapita \n",
    "#for the 10 military countries\n",
    "EducationPercentData_10Countries = EducationPercentData_G20.loc[['Turkey','South Africa','Japan','Indonesia',  \n",
    "                         'Germany','Canada','Australia','Mexico',\n",
    "                        'Italy','India','France','Brazil','Argentina',],:]\n",
    "EducationPercentData_10Countries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country Name</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>Turkey</th>\n",
       "      <td>6.446399e+05</td>\n",
       "      <td>7.719018e+05</td>\n",
       "      <td>8.325237e+05</td>\n",
       "      <td>8.739822e+05</td>\n",
       "      <td>9.505794e+05</td>\n",
       "      <td>9.341859e+05</td>\n",
       "      <td>8.597969e+05</td>\n",
       "      <td>8.637216e+05</td>\n",
       "      <td>8.515492e+05</td>\n",
       "      <td>7.665091e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>2.959365e+05</td>\n",
       "      <td>3.753494e+05</td>\n",
       "      <td>4.164189e+05</td>\n",
       "      <td>3.963279e+05</td>\n",
       "      <td>3.666432e+05</td>\n",
       "      <td>3.506362e+05</td>\n",
       "      <td>3.175368e+05</td>\n",
       "      <td>2.957466e+05</td>\n",
       "      <td>3.488716e+05</td>\n",
       "      <td>3.662982e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>5.231383e+06</td>\n",
       "      <td>5.700098e+06</td>\n",
       "      <td>6.157460e+06</td>\n",
       "      <td>6.203213e+06</td>\n",
       "      <td>5.155717e+06</td>\n",
       "      <td>4.850414e+06</td>\n",
       "      <td>4.389476e+06</td>\n",
       "      <td>4.926667e+06</td>\n",
       "      <td>4.859951e+06</td>\n",
       "      <td>4.970916e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>5.395801e+05</td>\n",
       "      <td>7.550942e+05</td>\n",
       "      <td>8.929691e+05</td>\n",
       "      <td>9.178699e+05</td>\n",
       "      <td>9.125241e+05</td>\n",
       "      <td>8.908148e+05</td>\n",
       "      <td>8.608542e+05</td>\n",
       "      <td>9.318774e+05</td>\n",
       "      <td>1.015423e+06</td>\n",
       "      <td>1.042173e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>3.418005e+06</td>\n",
       "      <td>3.417095e+06</td>\n",
       "      <td>3.757698e+06</td>\n",
       "      <td>3.543984e+06</td>\n",
       "      <td>3.752514e+06</td>\n",
       "      <td>3.898727e+06</td>\n",
       "      <td>3.381389e+06</td>\n",
       "      <td>3.495163e+06</td>\n",
       "      <td>3.693204e+06</td>\n",
       "      <td>3.996759e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>1.371153e+06</td>\n",
       "      <td>1.613543e+06</td>\n",
       "      <td>1.789141e+06</td>\n",
       "      <td>1.823967e+06</td>\n",
       "      <td>1.842018e+06</td>\n",
       "      <td>1.801480e+06</td>\n",
       "      <td>1.552900e+06</td>\n",
       "      <td>1.526706e+06</td>\n",
       "      <td>1.646867e+06</td>\n",
       "      <td>1.709327e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>9.278052e+05</td>\n",
       "      <td>1.146138e+06</td>\n",
       "      <td>1.396650e+06</td>\n",
       "      <td>1.546152e+06</td>\n",
       "      <td>1.576184e+06</td>\n",
       "      <td>1.467484e+06</td>\n",
       "      <td>1.351520e+06</td>\n",
       "      <td>1.210028e+06</td>\n",
       "      <td>1.330803e+06</td>\n",
       "      <td>1.432195e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>9.000454e+05</td>\n",
       "      <td>1.057801e+06</td>\n",
       "      <td>1.180490e+06</td>\n",
       "      <td>1.201090e+06</td>\n",
       "      <td>1.274443e+06</td>\n",
       "      <td>1.314564e+06</td>\n",
       "      <td>1.170565e+06</td>\n",
       "      <td>1.077828e+06</td>\n",
       "      <td>1.158071e+06</td>\n",
       "      <td>1.223809e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>2.185160e+06</td>\n",
       "      <td>2.125058e+06</td>\n",
       "      <td>2.276292e+06</td>\n",
       "      <td>2.072823e+06</td>\n",
       "      <td>2.130491e+06</td>\n",
       "      <td>2.151733e+06</td>\n",
       "      <td>1.832273e+06</td>\n",
       "      <td>1.869202e+06</td>\n",
       "      <td>1.946570e+06</td>\n",
       "      <td>2.073902e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>1.341887e+06</td>\n",
       "      <td>1.675615e+06</td>\n",
       "      <td>1.823050e+06</td>\n",
       "      <td>1.827638e+06</td>\n",
       "      <td>1.856722e+06</td>\n",
       "      <td>2.039127e+06</td>\n",
       "      <td>2.103588e+06</td>\n",
       "      <td>2.290432e+06</td>\n",
       "      <td>2.652551e+06</td>\n",
       "      <td>2.726323e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>2.690222e+06</td>\n",
       "      <td>2.642610e+06</td>\n",
       "      <td>2.861408e+06</td>\n",
       "      <td>2.683825e+06</td>\n",
       "      <td>2.811078e+06</td>\n",
       "      <td>2.852166e+06</td>\n",
       "      <td>2.438208e+06</td>\n",
       "      <td>2.471286e+06</td>\n",
       "      <td>2.586285e+06</td>\n",
       "      <td>2.777535e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>1.667020e+06</td>\n",
       "      <td>2.208872e+06</td>\n",
       "      <td>2.616202e+06</td>\n",
       "      <td>2.465189e+06</td>\n",
       "      <td>2.472806e+06</td>\n",
       "      <td>2.455994e+06</td>\n",
       "      <td>1.802214e+06</td>\n",
       "      <td>1.796275e+06</td>\n",
       "      <td>2.053595e+06</td>\n",
       "      <td>1.868626e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>3.329765e+05</td>\n",
       "      <td>4.236274e+05</td>\n",
       "      <td>5.301633e+05</td>\n",
       "      <td>5.459824e+05</td>\n",
       "      <td>5.520251e+05</td>\n",
       "      <td>5.263197e+05</td>\n",
       "      <td>5.947493e+05</td>\n",
       "      <td>5.575314e+05</td>\n",
       "      <td>6.426959e+05</td>\n",
       "      <td>5.184751e+05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      2009          2010          2011          2012  \\\n",
       "Country Name                                                           \n",
       "Turkey        6.446399e+05  7.719018e+05  8.325237e+05  8.739822e+05   \n",
       "South Africa  2.959365e+05  3.753494e+05  4.164189e+05  3.963279e+05   \n",
       "Japan         5.231383e+06  5.700098e+06  6.157460e+06  6.203213e+06   \n",
       "Indonesia     5.395801e+05  7.550942e+05  8.929691e+05  9.178699e+05   \n",
       "Germany       3.418005e+06  3.417095e+06  3.757698e+06  3.543984e+06   \n",
       "Canada        1.371153e+06  1.613543e+06  1.789141e+06  1.823967e+06   \n",
       "Australia     9.278052e+05  1.146138e+06  1.396650e+06  1.546152e+06   \n",
       "Mexico        9.000454e+05  1.057801e+06  1.180490e+06  1.201090e+06   \n",
       "Italy         2.185160e+06  2.125058e+06  2.276292e+06  2.072823e+06   \n",
       "India         1.341887e+06  1.675615e+06  1.823050e+06  1.827638e+06   \n",
       "France        2.690222e+06  2.642610e+06  2.861408e+06  2.683825e+06   \n",
       "Brazil        1.667020e+06  2.208872e+06  2.616202e+06  2.465189e+06   \n",
       "Argentina     3.329765e+05  4.236274e+05  5.301633e+05  5.459824e+05   \n",
       "\n",
       "                      2013          2014          2015          2016  \\\n",
       "Country Name                                                           \n",
       "Turkey        9.505794e+05  9.341859e+05  8.597969e+05  8.637216e+05   \n",
       "South Africa  3.666432e+05  3.506362e+05  3.175368e+05  2.957466e+05   \n",
       "Japan         5.155717e+06  4.850414e+06  4.389476e+06  4.926667e+06   \n",
       "Indonesia     9.125241e+05  8.908148e+05  8.608542e+05  9.318774e+05   \n",
       "Germany       3.752514e+06  3.898727e+06  3.381389e+06  3.495163e+06   \n",
       "Canada        1.842018e+06  1.801480e+06  1.552900e+06  1.526706e+06   \n",
       "Australia     1.576184e+06  1.467484e+06  1.351520e+06  1.210028e+06   \n",
       "Mexico        1.274443e+06  1.314564e+06  1.170565e+06  1.077828e+06   \n",
       "Italy         2.130491e+06  2.151733e+06  1.832273e+06  1.869202e+06   \n",
       "India         1.856722e+06  2.039127e+06  2.103588e+06  2.290432e+06   \n",
       "France        2.811078e+06  2.852166e+06  2.438208e+06  2.471286e+06   \n",
       "Brazil        2.472806e+06  2.455994e+06  1.802214e+06  1.796275e+06   \n",
       "Argentina     5.520251e+05  5.263197e+05  5.947493e+05  5.575314e+05   \n",
       "\n",
       "                      2017          2018  \n",
       "Country Name                              \n",
       "Turkey        8.515492e+05  7.665091e+05  \n",
       "South Africa  3.488716e+05  3.662982e+05  \n",
       "Japan         4.859951e+06  4.970916e+06  \n",
       "Indonesia     1.015423e+06  1.042173e+06  \n",
       "Germany       3.693204e+06  3.996759e+06  \n",
       "Canada        1.646867e+06  1.709327e+06  \n",
       "Australia     1.330803e+06  1.432195e+06  \n",
       "Mexico        1.158071e+06  1.223809e+06  \n",
       "Italy         1.946570e+06  2.073902e+06  \n",
       "India         2.652551e+06  2.726323e+06  \n",
       "France        2.586285e+06  2.777535e+06  \n",
       "Brazil        2.053595e+06  1.868626e+06  \n",
       "Argentina     6.426959e+05  5.184751e+05  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#GDP for 10 countries in millions\n",
    "GDP_10Countries_Millions = GDP_G20_Millions.loc[['Turkey','South Africa','Japan','Indonesia',  \n",
    "                         'Germany','Canada','Australia','Mexico',\n",
    "                        'Italy','India','France','Brazil','Argentina',],:]\n",
    "GDP_10Countries_Millions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country Name</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>Turkey</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>38621.275478</td>\n",
       "      <td>41484.236168</td>\n",
       "      <td>40834.761059</td>\n",
       "      <td>36901.364039</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>15532.788738</td>\n",
       "      <td>21476.519211</td>\n",
       "      <td>24830.016465</td>\n",
       "      <td>25252.585427</td>\n",
       "      <td>22048.236882</td>\n",
       "      <td>21201.639090</td>\n",
       "      <td>18913.096953</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>207455.070886</td>\n",
       "      <td>224290.391709</td>\n",
       "      <td>229038.756794</td>\n",
       "      <td>188976.621837</td>\n",
       "      <td>174158.463384</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>19020.899472</td>\n",
       "      <td>21235.362053</td>\n",
       "      <td>28480.713916</td>\n",
       "      <td>31276.233613</td>\n",
       "      <td>30652.050762</td>\n",
       "      <td>29290.078234</td>\n",
       "      <td>30849.572368</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>166815.050492</td>\n",
       "      <td>167905.092106</td>\n",
       "      <td>180662.617960</td>\n",
       "      <td>174835.712588</td>\n",
       "      <td>185185.415633</td>\n",
       "      <td>192251.272249</td>\n",
       "      <td>162760.132566</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>66537.119181</td>\n",
       "      <td>86646.119556</td>\n",
       "      <td>94367.150902</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>47255.623061</td>\n",
       "      <td>63715.785738</td>\n",
       "      <td>70993.530384</td>\n",
       "      <td>75415.872486</td>\n",
       "      <td>82560.700001</td>\n",
       "      <td>75922.910956</td>\n",
       "      <td>71924.520559</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>46693.812764</td>\n",
       "      <td>54574.296002</td>\n",
       "      <td>60271.667362</td>\n",
       "      <td>61292.823127</td>\n",
       "      <td>59848.484480</td>\n",
       "      <td>69163.679844</td>\n",
       "      <td>61331.265035</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>99125.639915</td>\n",
       "      <td>92490.822517</td>\n",
       "      <td>94331.150651</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>88728.998130</td>\n",
       "      <td>87688.493713</td>\n",
       "      <td>74763.335912</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>44433.089145</td>\n",
       "      <td>57364.187545</td>\n",
       "      <td>70000.012687</td>\n",
       "      <td>70683.894202</td>\n",
       "      <td>71384.838385</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>154585.014837</td>\n",
       "      <td>150430.812834</td>\n",
       "      <td>157901.087060</td>\n",
       "      <td>146440.776347</td>\n",
       "      <td>154617.145931</td>\n",
       "      <td>157213.088025</td>\n",
       "      <td>133229.531150</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>91078.459386</td>\n",
       "      <td>124774.741551</td>\n",
       "      <td>150102.210967</td>\n",
       "      <td>144339.262076</td>\n",
       "      <td>144383.459762</td>\n",
       "      <td>146094.314874</td>\n",
       "      <td>112477.280394</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>18417.095850</td>\n",
       "      <td>21264.868070</td>\n",
       "      <td>28048.977624</td>\n",
       "      <td>29187.289635</td>\n",
       "      <td>30011.453977</td>\n",
       "      <td>28218.313515</td>\n",
       "      <td>34353.372950</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       2009           2010           2011           2012  \\\n",
       "Country Name                                                               \n",
       "Turkey             0.000000       0.000000       0.000000   38621.275478   \n",
       "South Africa   15532.788738   21476.519211   24830.016465   25252.585427   \n",
       "Japan              0.000000  207455.070886  224290.391709  229038.756794   \n",
       "Indonesia      19020.899472   21235.362053   28480.713916   31276.233613   \n",
       "Germany       166815.050492  167905.092106  180662.617960  174835.712588   \n",
       "Canada         66537.119181   86646.119556   94367.150902       0.000000   \n",
       "Australia      47255.623061   63715.785738   70993.530384   75415.872486   \n",
       "Mexico         46693.812764   54574.296002   60271.667362   61292.823127   \n",
       "Italy          99125.639915   92490.822517   94331.150651       0.000000   \n",
       "India          44433.089145   57364.187545   70000.012687   70683.894202   \n",
       "France        154585.014837  150430.812834  157901.087060  146440.776347   \n",
       "Brazil         91078.459386  124774.741551  150102.210967  144339.262076   \n",
       "Argentina      18417.095850   21264.868070   28048.977624   29187.289635   \n",
       "\n",
       "                       2013           2014           2015  2016  2017  2018  \n",
       "Country Name                                                                 \n",
       "Turkey         41484.236168   40834.761059   36901.364039   NaN   NaN   NaN  \n",
       "South Africa   22048.236882   21201.639090   18913.096953   NaN   NaN   NaN  \n",
       "Japan         188976.621837  174158.463384       0.000000   NaN   NaN   NaN  \n",
       "Indonesia      30652.050762   29290.078234   30849.572368   NaN   NaN   NaN  \n",
       "Germany       185185.415633  192251.272249  162760.132566   NaN   NaN   NaN  \n",
       "Canada             0.000000       0.000000       0.000000   NaN   NaN   NaN  \n",
       "Australia      82560.700001   75922.910956   71924.520559   NaN   NaN   NaN  \n",
       "Mexico         59848.484480   69163.679844   61331.265035   NaN   NaN   NaN  \n",
       "Italy          88728.998130   87688.493713   74763.335912   NaN   NaN   NaN  \n",
       "India          71384.838385       0.000000       0.000000   NaN   NaN   NaN  \n",
       "France        154617.145931  157213.088025  133229.531150   NaN   NaN   NaN  \n",
       "Brazil        144383.459762  146094.314874  112477.280394   NaN   NaN   NaN  \n",
       "Argentina      30011.453977   28218.313515   34353.372950   NaN   NaN   NaN  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Education Expenditure Data of 10 countries in millions\n",
    "\n",
    "EducationExpenditureData_Millions_10Countries = (EducationPercentData_10Countries * GDP_10Countries_Millions)/100\n",
    "EducationExpenditureData_Millions_10Countries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
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       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>451.405969</td>\n",
       "      <td>515.838476</td>\n",
       "      <td>673.333632</td>\n",
       "      <td>693.338494</td>\n",
       "      <td>705.489114</td>\n",
       "      <td>656.522077</td>\n",
       "      <td>791.228497</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>2178.511738</td>\n",
       "      <td>2891.998400</td>\n",
       "      <td>3177.862763</td>\n",
       "      <td>3316.080263</td>\n",
       "      <td>3566.968510</td>\n",
       "      <td>3230.193379</td>\n",
       "      <td>3015.604039</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>467.318268</td>\n",
       "      <td>634.030016</td>\n",
       "      <td>755.471906</td>\n",
       "      <td>719.677676</td>\n",
       "      <td>713.326593</td>\n",
       "      <td>715.401173</td>\n",
       "      <td>546.106667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>1978.588956</td>\n",
       "      <td>2548.020038</td>\n",
       "      <td>2747.801748</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>China</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>2388.998249</td>\n",
       "      <td>2313.341227</td>\n",
       "      <td>2416.504152</td>\n",
       "      <td>2230.296176</td>\n",
       "      <td>2342.731594</td>\n",
       "      <td>2370.662735</td>\n",
       "      <td>2000.642694</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>2036.756431</td>\n",
       "      <td>2053.208553</td>\n",
       "      <td>2250.546948</td>\n",
       "      <td>2173.875331</td>\n",
       "      <td>2296.286520</td>\n",
       "      <td>2373.985395</td>\n",
       "      <td>1992.494615</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>36.592425</td>\n",
       "      <td>46.600396</td>\n",
       "      <td>56.124110</td>\n",
       "      <td>55.962161</td>\n",
       "      <td>55.832120</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>79.472138</td>\n",
       "      <td>87.559793</td>\n",
       "      <td>115.913078</td>\n",
       "      <td>125.666295</td>\n",
       "      <td>121.619551</td>\n",
       "      <td>114.804022</td>\n",
       "      <td>119.496901</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>1677.384342</td>\n",
       "      <td>1560.304534</td>\n",
       "      <td>1588.616133</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1473.072928</td>\n",
       "      <td>1442.502620</td>\n",
       "      <td>1231.065691</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1619.856882</td>\n",
       "      <td>1754.557835</td>\n",
       "      <td>1794.566727</td>\n",
       "      <td>1482.809226</td>\n",
       "      <td>1368.352740</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>404.257137</td>\n",
       "      <td>465.178901</td>\n",
       "      <td>506.101761</td>\n",
       "      <td>507.272051</td>\n",
       "      <td>488.415646</td>\n",
       "      <td>556.776598</td>\n",
       "      <td>487.177716</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saudi Arabia</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>304.738855</td>\n",
       "      <td>416.335359</td>\n",
       "      <td>475.092729</td>\n",
       "      <td>476.479941</td>\n",
       "      <td>410.067039</td>\n",
       "      <td>388.738648</td>\n",
       "      <td>342.063265</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>517.920670</td>\n",
       "      <td>547.376910</td>\n",
       "      <td>530.110712</td>\n",
       "      <td>471.453559</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     2009         2010         2011         2012         2013  \\\n",
       "Country Name                                                                    \n",
       "Argentina      451.405969   515.838476   673.333632   693.338494   705.489114   \n",
       "Australia     2178.511738  2891.998400  3177.862763  3316.080263  3566.968510   \n",
       "Brazil         467.318268   634.030016   755.471906   719.677676   713.326593   \n",
       "Canada        1978.588956  2548.020038  2747.801748     0.000000     0.000000   \n",
       "China                 NaN          NaN          NaN          NaN          NaN   \n",
       "France        2388.998249  2313.341227  2416.504152  2230.296176  2342.731594   \n",
       "Germany       2036.756431  2053.208553  2250.546948  2173.875331  2296.286520   \n",
       "India           36.592425    46.600396    56.124110    55.962161    55.832120   \n",
       "Indonesia       79.472138    87.559793   115.913078   125.666295   121.619551   \n",
       "Italy         1677.384342  1560.304534  1588.616133     0.000000  1473.072928   \n",
       "Japan            0.000000  1619.856882  1754.557835  1794.566727  1482.809226   \n",
       "Mexico         404.257137   465.178901   506.101761   507.272051   488.415646   \n",
       "Saudi Arabia          NaN          NaN          NaN          NaN          NaN   \n",
       "South Africa   304.738855   416.335359   475.092729   476.479941   410.067039   \n",
       "Turkey           0.000000     0.000000     0.000000   517.920670   547.376910   \n",
       "\n",
       "                     2014         2015  2016  2017  2018  \n",
       "Country Name                                              \n",
       "Argentina      656.522077   791.228497   NaN   NaN   NaN  \n",
       "Australia     3230.193379  3015.604039   NaN   NaN   NaN  \n",
       "Brazil         715.401173   546.106667   NaN   NaN   NaN  \n",
       "Canada           0.000000     0.000000   NaN   NaN   NaN  \n",
       "China                 NaN          NaN   NaN   NaN   NaN  \n",
       "France        2370.662735  2000.642694   NaN   NaN   NaN  \n",
       "Germany       2373.985395  1992.494615   NaN   NaN   NaN  \n",
       "India            0.000000     0.000000   NaN   NaN   NaN  \n",
       "Indonesia      114.804022   119.496901   NaN   NaN   NaN  \n",
       "Italy         1442.502620  1231.065691   NaN   NaN   NaN  \n",
       "Japan         1368.352740     0.000000   NaN   NaN   NaN  \n",
       "Mexico         556.776598   487.177716   NaN   NaN   NaN  \n",
       "Saudi Arabia          NaN          NaN   NaN   NaN   NaN  \n",
       "South Africa   388.738648   342.063265   NaN   NaN   NaN  \n",
       "Turkey         530.110712   471.453559   NaN   NaN   NaN  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Education Per Person expenditure for countries in million dollars(US dollars)\n",
    "Education_Per_Person_G20 = EducationExpenditureData_Millions_G20/PopulationData_Millions\n",
    "Education_Per_Person_G20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country Name</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>Turkey</th>\n",
       "      <td>71.339185</td>\n",
       "      <td>72.326914</td>\n",
       "      <td>73.409455</td>\n",
       "      <td>74.569867</td>\n",
       "      <td>75.787333</td>\n",
       "      <td>77.030628</td>\n",
       "      <td>78.271472</td>\n",
       "      <td>79.512426</td>\n",
       "      <td>80.745020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>50.970818</td>\n",
       "      <td>51.584663</td>\n",
       "      <td>52.263516</td>\n",
       "      <td>52.998213</td>\n",
       "      <td>53.767396</td>\n",
       "      <td>54.539571</td>\n",
       "      <td>55.291225</td>\n",
       "      <td>56.015473</td>\n",
       "      <td>56.717156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>128.047000</td>\n",
       "      <td>128.070000</td>\n",
       "      <td>127.833000</td>\n",
       "      <td>127.629000</td>\n",
       "      <td>127.445000</td>\n",
       "      <td>127.276000</td>\n",
       "      <td>127.141000</td>\n",
       "      <td>126.994511</td>\n",
       "      <td>126.785797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>239.340478</td>\n",
       "      <td>242.524123</td>\n",
       "      <td>245.707511</td>\n",
       "      <td>248.883232</td>\n",
       "      <td>252.032263</td>\n",
       "      <td>255.131116</td>\n",
       "      <td>258.162113</td>\n",
       "      <td>261.115456</td>\n",
       "      <td>263.991379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>81.902307</td>\n",
       "      <td>81.776930</td>\n",
       "      <td>80.274983</td>\n",
       "      <td>80.425823</td>\n",
       "      <td>80.645605</td>\n",
       "      <td>80.982500</td>\n",
       "      <td>81.686611</td>\n",
       "      <td>82.348669</td>\n",
       "      <td>82.695000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>33.628571</td>\n",
       "      <td>34.005274</td>\n",
       "      <td>34.342780</td>\n",
       "      <td>34.750545</td>\n",
       "      <td>35.152370</td>\n",
       "      <td>35.535348</td>\n",
       "      <td>35.832513</td>\n",
       "      <td>36.264604</td>\n",
       "      <td>36.708083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>21.691700</td>\n",
       "      <td>22.031750</td>\n",
       "      <td>22.340024</td>\n",
       "      <td>22.742475</td>\n",
       "      <td>23.145901</td>\n",
       "      <td>23.504138</td>\n",
       "      <td>23.850784</td>\n",
       "      <td>24.210809</td>\n",
       "      <td>24.598933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>115.505228</td>\n",
       "      <td>117.318941</td>\n",
       "      <td>119.090017</td>\n",
       "      <td>120.828307</td>\n",
       "      <td>122.535969</td>\n",
       "      <td>124.221600</td>\n",
       "      <td>125.890949</td>\n",
       "      <td>127.540423</td>\n",
       "      <td>129.163276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>59.095365</td>\n",
       "      <td>59.277417</td>\n",
       "      <td>59.379449</td>\n",
       "      <td>59.539717</td>\n",
       "      <td>60.233948</td>\n",
       "      <td>60.789140</td>\n",
       "      <td>60.730582</td>\n",
       "      <td>60.627498</td>\n",
       "      <td>60.551416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>1214.270132</td>\n",
       "      <td>1230.980691</td>\n",
       "      <td>1247.236029</td>\n",
       "      <td>1263.065852</td>\n",
       "      <td>1278.562207</td>\n",
       "      <td>1293.859294</td>\n",
       "      <td>1309.053980</td>\n",
       "      <td>1324.171354</td>\n",
       "      <td>1339.180127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>64.707044</td>\n",
       "      <td>65.027507</td>\n",
       "      <td>65.342775</td>\n",
       "      <td>65.659789</td>\n",
       "      <td>65.998660</td>\n",
       "      <td>66.316092</td>\n",
       "      <td>66.593366</td>\n",
       "      <td>66.859768</td>\n",
       "      <td>67.118648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>194.895996</td>\n",
       "      <td>196.796269</td>\n",
       "      <td>198.686688</td>\n",
       "      <td>200.560983</td>\n",
       "      <td>202.408632</td>\n",
       "      <td>204.213133</td>\n",
       "      <td>205.962108</td>\n",
       "      <td>207.652865</td>\n",
       "      <td>209.288278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>40.799407</td>\n",
       "      <td>41.223889</td>\n",
       "      <td>41.656879</td>\n",
       "      <td>42.096739</td>\n",
       "      <td>42.539925</td>\n",
       "      <td>42.981515</td>\n",
       "      <td>43.417765</td>\n",
       "      <td>43.847430</td>\n",
       "      <td>44.271041</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                     2009         2010         2011         2012         2013  \\\n",
       "Country Name                                                                    \n",
       "Turkey          71.339185    72.326914    73.409455    74.569867    75.787333   \n",
       "South Africa    50.970818    51.584663    52.263516    52.998213    53.767396   \n",
       "Japan          128.047000   128.070000   127.833000   127.629000   127.445000   \n",
       "Indonesia      239.340478   242.524123   245.707511   248.883232   252.032263   \n",
       "Germany         81.902307    81.776930    80.274983    80.425823    80.645605   \n",
       "Canada          33.628571    34.005274    34.342780    34.750545    35.152370   \n",
       "Australia       21.691700    22.031750    22.340024    22.742475    23.145901   \n",
       "Mexico         115.505228   117.318941   119.090017   120.828307   122.535969   \n",
       "Italy           59.095365    59.277417    59.379449    59.539717    60.233948   \n",
       "India         1214.270132  1230.980691  1247.236029  1263.065852  1278.562207   \n",
       "France          64.707044    65.027507    65.342775    65.659789    65.998660   \n",
       "Brazil         194.895996   196.796269   198.686688   200.560983   202.408632   \n",
       "Argentina       40.799407    41.223889    41.656879    42.096739    42.539925   \n",
       "\n",
       "                     2014         2015         2016         2017  \n",
       "Country Name                                                      \n",
       "Turkey          77.030628    78.271472    79.512426    80.745020  \n",
       "South Africa    54.539571    55.291225    56.015473    56.717156  \n",
       "Japan          127.276000   127.141000   126.994511   126.785797  \n",
       "Indonesia      255.131116   258.162113   261.115456   263.991379  \n",
       "Germany         80.982500    81.686611    82.348669    82.695000  \n",
       "Canada          35.535348    35.832513    36.264604    36.708083  \n",
       "Australia       23.504138    23.850784    24.210809    24.598933  \n",
       "Mexico         124.221600   125.890949   127.540423   129.163276  \n",
       "Italy           60.789140    60.730582    60.627498    60.551416  \n",
       "India         1293.859294  1309.053980  1324.171354  1339.180127  \n",
       "France          66.316092    66.593366    66.859768    67.118648  \n",
       "Brazil         204.213133   205.962108   207.652865   209.288278  \n",
       "Argentina       42.981515    43.417765    43.847430    44.271041  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Population data of 10 Countries in Million dollars\n",
    "PopulationData_Millions_10Countries = PopulationData_Millions.loc[['Turkey','South Africa','Japan','Indonesia',  \n",
    "                         'Germany','Canada','Australia','Mexico',\n",
    "                        'Italy','India','France','Brazil','Argentina',],:]\n",
    "PopulationData_Millions_10Countries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country Name</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>Turkey</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>517.920670</td>\n",
       "      <td>547.376910</td>\n",
       "      <td>530.110712</td>\n",
       "      <td>471.453559</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>304.738855</td>\n",
       "      <td>416.335359</td>\n",
       "      <td>475.092729</td>\n",
       "      <td>476.479941</td>\n",
       "      <td>410.067039</td>\n",
       "      <td>388.738648</td>\n",
       "      <td>342.063265</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Japan</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1619.856882</td>\n",
       "      <td>1754.557835</td>\n",
       "      <td>1794.566727</td>\n",
       "      <td>1482.809226</td>\n",
       "      <td>1368.352740</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indonesia</th>\n",
       "      <td>79.472138</td>\n",
       "      <td>87.559793</td>\n",
       "      <td>115.913078</td>\n",
       "      <td>125.666295</td>\n",
       "      <td>121.619551</td>\n",
       "      <td>114.804022</td>\n",
       "      <td>119.496901</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>2036.756431</td>\n",
       "      <td>2053.208553</td>\n",
       "      <td>2250.546948</td>\n",
       "      <td>2173.875331</td>\n",
       "      <td>2296.286520</td>\n",
       "      <td>2373.985395</td>\n",
       "      <td>1992.494615</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>1978.588956</td>\n",
       "      <td>2548.020038</td>\n",
       "      <td>2747.801748</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>2178.511738</td>\n",
       "      <td>2891.998400</td>\n",
       "      <td>3177.862763</td>\n",
       "      <td>3316.080263</td>\n",
       "      <td>3566.968510</td>\n",
       "      <td>3230.193379</td>\n",
       "      <td>3015.604039</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>404.257137</td>\n",
       "      <td>465.178901</td>\n",
       "      <td>506.101761</td>\n",
       "      <td>507.272051</td>\n",
       "      <td>488.415646</td>\n",
       "      <td>556.776598</td>\n",
       "      <td>487.177716</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>1677.384342</td>\n",
       "      <td>1560.304534</td>\n",
       "      <td>1588.616133</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1473.072928</td>\n",
       "      <td>1442.502620</td>\n",
       "      <td>1231.065691</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>India</th>\n",
       "      <td>36.592425</td>\n",
       "      <td>46.600396</td>\n",
       "      <td>56.124110</td>\n",
       "      <td>55.962161</td>\n",
       "      <td>55.832120</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>2388.998249</td>\n",
       "      <td>2313.341227</td>\n",
       "      <td>2416.504152</td>\n",
       "      <td>2230.296176</td>\n",
       "      <td>2342.731594</td>\n",
       "      <td>2370.662735</td>\n",
       "      <td>2000.642694</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brazil</th>\n",
       "      <td>467.318268</td>\n",
       "      <td>634.030016</td>\n",
       "      <td>755.471906</td>\n",
       "      <td>719.677676</td>\n",
       "      <td>713.326593</td>\n",
       "      <td>715.401173</td>\n",
       "      <td>546.106667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>451.405969</td>\n",
       "      <td>515.838476</td>\n",
       "      <td>673.333632</td>\n",
       "      <td>693.338494</td>\n",
       "      <td>705.489114</td>\n",
       "      <td>656.522077</td>\n",
       "      <td>791.228497</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     2009         2010         2011         2012         2013  \\\n",
       "Country Name                                                                    \n",
       "Turkey           0.000000     0.000000     0.000000   517.920670   547.376910   \n",
       "South Africa   304.738855   416.335359   475.092729   476.479941   410.067039   \n",
       "Japan            0.000000  1619.856882  1754.557835  1794.566727  1482.809226   \n",
       "Indonesia       79.472138    87.559793   115.913078   125.666295   121.619551   \n",
       "Germany       2036.756431  2053.208553  2250.546948  2173.875331  2296.286520   \n",
       "Canada        1978.588956  2548.020038  2747.801748     0.000000     0.000000   \n",
       "Australia     2178.511738  2891.998400  3177.862763  3316.080263  3566.968510   \n",
       "Mexico         404.257137   465.178901   506.101761   507.272051   488.415646   \n",
       "Italy         1677.384342  1560.304534  1588.616133     0.000000  1473.072928   \n",
       "India           36.592425    46.600396    56.124110    55.962161    55.832120   \n",
       "France        2388.998249  2313.341227  2416.504152  2230.296176  2342.731594   \n",
       "Brazil         467.318268   634.030016   755.471906   719.677676   713.326593   \n",
       "Argentina      451.405969   515.838476   673.333632   693.338494   705.489114   \n",
       "\n",
       "                     2014         2015  2016  2017  2018  \n",
       "Country Name                                              \n",
       "Turkey         530.110712   471.453559   NaN   NaN   NaN  \n",
       "South Africa   388.738648   342.063265   NaN   NaN   NaN  \n",
       "Japan         1368.352740     0.000000   NaN   NaN   NaN  \n",
       "Indonesia      114.804022   119.496901   NaN   NaN   NaN  \n",
       "Germany       2373.985395  1992.494615   NaN   NaN   NaN  \n",
       "Canada           0.000000     0.000000   NaN   NaN   NaN  \n",
       "Australia     3230.193379  3015.604039   NaN   NaN   NaN  \n",
       "Mexico         556.776598   487.177716   NaN   NaN   NaN  \n",
       "Italy         1442.502620  1231.065691   NaN   NaN   NaN  \n",
       "India            0.000000     0.000000   NaN   NaN   NaN  \n",
       "France        2370.662735  2000.642694   NaN   NaN   NaN  \n",
       "Brazil         715.401173   546.106667   NaN   NaN   NaN  \n",
       "Argentina      656.522077   791.228497   NaN   NaN   NaN  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Education Data Per Person for 10 Countries in US dollars\n",
    "EducationData_Per_Person_10Countries = EducationExpenditureData_Millions_10Countries/PopulationData_Millions_10Countries\n",
    "EducationData_Per_Person_10Countries\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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