Countries_of_the_World_EDA_Assignment_1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Abstract\n",
    "\n",
    "The purpose of research is to analyze and understand the data set provided to us. We are provided with the countries of the world data set to analyze the factors affecting a country's GDP per capita in order to make a predictive model of countries GDP using exploratory data analysis. This data set helps me to understand the data frames and introduced us more with the libraries such as panda, numpy, seaborn and few more and helped us to preprocess the data, visualization of the different kinds of graphs as heatmaps, distplot, pairplot, boxplot etcetra. The methods used as df.describe, np.array, sns.barplot etcetra helped me to understand more about the plots. I found five errors in my code and all were related to Nan values or zero division error. I learned about the imputer class and its methods as imputer.fit, imputer.transform which helped in dealing with the missing values. So this assignment helped me in learning the fundamentals of the machine learning which will further help me to understand more complex models by analyzing and visualizing them.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Data\n",
    "\n",
    "GDP ($ per capita) (Target - the dependent variable)\n",
    "\n",
    "\n",
    "Possible independent variables (predictors)\n",
    "\n",
    "Country                                    \n",
    "Region                                     \n",
    "Population                                  \n",
    "Area (sq. mi.)                              \n",
    "Pop. Density (per sq. mi.)                \n",
    "Coastline (coast/area ratio)              \n",
    "Net migration                             \n",
    "Infant mortality (per 1000 births)        \n",
    "Literacy (%)                              \n",
    "Phones (per 1000)                         \n",
    "Arable (%)                                \n",
    "Crops (%)                                 \n",
    "Other (%)                                 \n",
    "Climate                                   \n",
    "Birthrate                                 \n",
    "Deathrate                                 \n",
    "Agriculture                               \n",
    "Industry                                  \n",
    "Service  \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### Acknowledgements\n",
    "\n",
    "Source: All these data sets are made up of data from the US government. Data from the World Factbook is public domain. The website says \"The World Factbook is in the public domain and may be used freely by anyone at anytime without seeking permission.\" \n",
    "[https://www.cia.gov/library/publications/the-world-factbook/docs/faqs.html](https://www.cia.gov/library/publications/the-world-factbook/docs/faqs.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# importing libraries\n",
    "%matplotlib inline \n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from scipy import stats\n",
    "import seaborn as sns\n",
    "import re\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.impute import SimpleImputer\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.metrics import mean_squared_error"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above I am importing the SimpleImputer class additionally in order to deal with the missing values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# importing the dataset\n",
    "df=pd.read_csv(\"countries of the world.csv\", decimal = ',')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "df stands for Data Frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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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>Country</th>\n",
       "      <th>Region</th>\n",
       "      <th>Population</th>\n",
       "      <th>Area (sq. mi.)</th>\n",
       "      <th>Pop. Density (per sq. mi.)</th>\n",
       "      <th>Coastline (coast/area ratio)</th>\n",
       "      <th>Net migration</th>\n",
       "      <th>Infant mortality (per 1000 births)</th>\n",
       "      <th>GDP ($ per capita)</th>\n",
       "      <th>Literacy (%)</th>\n",
       "      <th>Phones (per 1000)</th>\n",
       "      <th>Arable (%)</th>\n",
       "      <th>Crops (%)</th>\n",
       "      <th>Other (%)</th>\n",
       "      <th>Climate</th>\n",
       "      <th>Birthrate</th>\n",
       "      <th>Deathrate</th>\n",
       "      <th>Agriculture</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Service</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>ASIA (EX. NEAR EAST)</td>\n",
       "      <td>31056997</td>\n",
       "      <td>647500</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>23.06</td>\n",
       "      <td>163.07</td>\n",
       "      <td>700.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>12.13</td>\n",
       "      <td>0.22</td>\n",
       "      <td>87.65</td>\n",
       "      <td>1.0</td>\n",
       "      <td>46.60</td>\n",
       "      <td>20.34</td>\n",
       "      <td>0.380</td>\n",
       "      <td>0.240</td>\n",
       "      <td>0.380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>EASTERN EUROPE</td>\n",
       "      <td>3581655</td>\n",
       "      <td>28748</td>\n",
       "      <td>124.6</td>\n",
       "      <td>1.26</td>\n",
       "      <td>-4.93</td>\n",
       "      <td>21.52</td>\n",
       "      <td>4500.0</td>\n",
       "      <td>86.5</td>\n",
       "      <td>71.2</td>\n",
       "      <td>21.09</td>\n",
       "      <td>4.42</td>\n",
       "      <td>74.49</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15.11</td>\n",
       "      <td>5.22</td>\n",
       "      <td>0.232</td>\n",
       "      <td>0.188</td>\n",
       "      <td>0.579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>NORTHERN AFRICA</td>\n",
       "      <td>32930091</td>\n",
       "      <td>2381740</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0.04</td>\n",
       "      <td>-0.39</td>\n",
       "      <td>31.00</td>\n",
       "      <td>6000.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>78.1</td>\n",
       "      <td>3.22</td>\n",
       "      <td>0.25</td>\n",
       "      <td>96.53</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.14</td>\n",
       "      <td>4.61</td>\n",
       "      <td>0.101</td>\n",
       "      <td>0.600</td>\n",
       "      <td>0.298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>American Samoa</td>\n",
       "      <td>OCEANIA</td>\n",
       "      <td>57794</td>\n",
       "      <td>199</td>\n",
       "      <td>290.4</td>\n",
       "      <td>58.29</td>\n",
       "      <td>-20.71</td>\n",
       "      <td>9.27</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>259.5</td>\n",
       "      <td>10.00</td>\n",
       "      <td>15.00</td>\n",
       "      <td>75.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>22.46</td>\n",
       "      <td>3.27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>WESTERN EUROPE</td>\n",
       "      <td>71201</td>\n",
       "      <td>468</td>\n",
       "      <td>152.1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6.60</td>\n",
       "      <td>4.05</td>\n",
       "      <td>19000.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>497.2</td>\n",
       "      <td>2.22</td>\n",
       "      <td>0.00</td>\n",
       "      <td>97.78</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.71</td>\n",
       "      <td>6.25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Country                               Region  Population  \\\n",
       "0     Afghanistan         ASIA (EX. NEAR EAST)             31056997   \n",
       "1         Albania   EASTERN EUROPE                          3581655   \n",
       "2         Algeria   NORTHERN AFRICA                        32930091   \n",
       "3  American Samoa   OCEANIA                                   57794   \n",
       "4         Andorra   WESTERN EUROPE                            71201   \n",
       "\n",
       "   Area (sq. mi.)  Pop. Density (per sq. mi.)  Coastline (coast/area ratio)  \\\n",
       "0          647500                        48.0                          0.00   \n",
       "1           28748                       124.6                          1.26   \n",
       "2         2381740                        13.8                          0.04   \n",
       "3             199                       290.4                         58.29   \n",
       "4             468                       152.1                          0.00   \n",
       "\n",
       "   Net migration  Infant mortality (per 1000 births)  GDP ($ per capita)  \\\n",
       "0          23.06                              163.07               700.0   \n",
       "1          -4.93                               21.52              4500.0   \n",
       "2          -0.39                               31.00              6000.0   \n",
       "3         -20.71                                9.27              8000.0   \n",
       "4           6.60                                4.05             19000.0   \n",
       "\n",
       "   Literacy (%)  Phones (per 1000)  Arable (%)  Crops (%)  Other (%)  Climate  \\\n",
       "0          36.0                3.2       12.13       0.22      87.65      1.0   \n",
       "1          86.5               71.2       21.09       4.42      74.49      3.0   \n",
       "2          70.0               78.1        3.22       0.25      96.53      1.0   \n",
       "3          97.0              259.5       10.00      15.00      75.00      2.0   \n",
       "4         100.0              497.2        2.22       0.00      97.78      3.0   \n",
       "\n",
       "   Birthrate  Deathrate  Agriculture  Industry  Service  \n",
       "0      46.60      20.34        0.380     0.240    0.380  \n",
       "1      15.11       5.22        0.232     0.188    0.579  \n",
       "2      17.14       4.61        0.101     0.600    0.298  \n",
       "3      22.46       3.27          NaN       NaN      NaN  \n",
       "4       8.71       6.25          NaN       NaN      NaN  "
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "df.head() by default will return us the first five values of the csv file as per the input provided by us."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "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>Population</th>\n",
       "      <th>Area (sq. mi.)</th>\n",
       "      <th>Pop. Density (per sq. mi.)</th>\n",
       "      <th>Coastline (coast/area ratio)</th>\n",
       "      <th>Net migration</th>\n",
       "      <th>Infant mortality (per 1000 births)</th>\n",
       "      <th>GDP ($ per capita)</th>\n",
       "      <th>Literacy (%)</th>\n",
       "      <th>Phones (per 1000)</th>\n",
       "      <th>Arable (%)</th>\n",
       "      <th>Crops (%)</th>\n",
       "      <th>Other (%)</th>\n",
       "      <th>Climate</th>\n",
       "      <th>Birthrate</th>\n",
       "      <th>Deathrate</th>\n",
       "      <th>Agriculture</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Service</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.270000e+02</td>\n",
       "      <td>2.270000e+02</td>\n",
       "      <td>227.000000</td>\n",
       "      <td>227.000000</td>\n",
       "      <td>224.000000</td>\n",
       "      <td>224.000000</td>\n",
       "      <td>226.000000</td>\n",
       "      <td>209.000000</td>\n",
       "      <td>223.000000</td>\n",
       "      <td>225.000000</td>\n",
       "      <td>225.000000</td>\n",
       "      <td>225.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>224.000000</td>\n",
       "      <td>223.000000</td>\n",
       "      <td>212.000000</td>\n",
       "      <td>211.000000</td>\n",
       "      <td>212.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.874028e+07</td>\n",
       "      <td>5.982270e+05</td>\n",
       "      <td>379.047137</td>\n",
       "      <td>21.165330</td>\n",
       "      <td>0.038125</td>\n",
       "      <td>35.506964</td>\n",
       "      <td>9689.823009</td>\n",
       "      <td>82.838278</td>\n",
       "      <td>236.061435</td>\n",
       "      <td>13.797111</td>\n",
       "      <td>4.564222</td>\n",
       "      <td>81.638311</td>\n",
       "      <td>2.139024</td>\n",
       "      <td>22.114732</td>\n",
       "      <td>9.241345</td>\n",
       "      <td>0.150844</td>\n",
       "      <td>0.282711</td>\n",
       "      <td>0.565283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.178913e+08</td>\n",
       "      <td>1.790282e+06</td>\n",
       "      <td>1660.185825</td>\n",
       "      <td>72.286863</td>\n",
       "      <td>4.889269</td>\n",
       "      <td>35.389899</td>\n",
       "      <td>10049.138513</td>\n",
       "      <td>19.722173</td>\n",
       "      <td>227.991829</td>\n",
       "      <td>13.040402</td>\n",
       "      <td>8.361470</td>\n",
       "      <td>16.140835</td>\n",
       "      <td>0.699397</td>\n",
       "      <td>11.176716</td>\n",
       "      <td>4.990026</td>\n",
       "      <td>0.146798</td>\n",
       "      <td>0.138272</td>\n",
       "      <td>0.165841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>7.026000e+03</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-20.990000</td>\n",
       "      <td>2.290000</td>\n",
       "      <td>500.000000</td>\n",
       "      <td>17.600000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>33.330000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.290000</td>\n",
       "      <td>2.290000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.062000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4.376240e+05</td>\n",
       "      <td>4.647500e+03</td>\n",
       "      <td>29.150000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>-0.927500</td>\n",
       "      <td>8.150000</td>\n",
       "      <td>1900.000000</td>\n",
       "      <td>70.600000</td>\n",
       "      <td>37.800000</td>\n",
       "      <td>3.220000</td>\n",
       "      <td>0.190000</td>\n",
       "      <td>71.650000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>12.672500</td>\n",
       "      <td>5.910000</td>\n",
       "      <td>0.037750</td>\n",
       "      <td>0.193000</td>\n",
       "      <td>0.429250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>4.786994e+06</td>\n",
       "      <td>8.660000e+04</td>\n",
       "      <td>78.800000</td>\n",
       "      <td>0.730000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>5550.000000</td>\n",
       "      <td>92.500000</td>\n",
       "      <td>176.200000</td>\n",
       "      <td>10.420000</td>\n",
       "      <td>1.030000</td>\n",
       "      <td>85.700000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>18.790000</td>\n",
       "      <td>7.840000</td>\n",
       "      <td>0.099000</td>\n",
       "      <td>0.272000</td>\n",
       "      <td>0.571000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.749777e+07</td>\n",
       "      <td>4.418110e+05</td>\n",
       "      <td>190.150000</td>\n",
       "      <td>10.345000</td>\n",
       "      <td>0.997500</td>\n",
       "      <td>55.705000</td>\n",
       "      <td>15700.000000</td>\n",
       "      <td>98.000000</td>\n",
       "      <td>389.650000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>4.440000</td>\n",
       "      <td>95.440000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>29.820000</td>\n",
       "      <td>10.605000</td>\n",
       "      <td>0.221000</td>\n",
       "      <td>0.341000</td>\n",
       "      <td>0.678500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.313974e+09</td>\n",
       "      <td>1.707520e+07</td>\n",
       "      <td>16271.500000</td>\n",
       "      <td>870.660000</td>\n",
       "      <td>23.060000</td>\n",
       "      <td>191.190000</td>\n",
       "      <td>55100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1035.600000</td>\n",
       "      <td>62.110000</td>\n",
       "      <td>50.680000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>50.730000</td>\n",
       "      <td>29.740000</td>\n",
       "      <td>0.769000</td>\n",
       "      <td>0.906000</td>\n",
       "      <td>0.954000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Population  Area (sq. mi.)  Pop. Density (per sq. mi.)  \\\n",
       "count  2.270000e+02    2.270000e+02                  227.000000   \n",
       "mean   2.874028e+07    5.982270e+05                  379.047137   \n",
       "std    1.178913e+08    1.790282e+06                 1660.185825   \n",
       "min    7.026000e+03    2.000000e+00                    0.000000   \n",
       "25%    4.376240e+05    4.647500e+03                   29.150000   \n",
       "50%    4.786994e+06    8.660000e+04                   78.800000   \n",
       "75%    1.749777e+07    4.418110e+05                  190.150000   \n",
       "max    1.313974e+09    1.707520e+07                16271.500000   \n",
       "\n",
       "       Coastline (coast/area ratio)  Net migration  \\\n",
       "count                    227.000000     224.000000   \n",
       "mean                      21.165330       0.038125   \n",
       "std                       72.286863       4.889269   \n",
       "min                        0.000000     -20.990000   \n",
       "25%                        0.100000      -0.927500   \n",
       "50%                        0.730000       0.000000   \n",
       "75%                       10.345000       0.997500   \n",
       "max                      870.660000      23.060000   \n",
       "\n",
       "       Infant mortality (per 1000 births)  GDP ($ per capita)  Literacy (%)  \\\n",
       "count                          224.000000          226.000000    209.000000   \n",
       "mean                            35.506964         9689.823009     82.838278   \n",
       "std                             35.389899        10049.138513     19.722173   \n",
       "min                              2.290000          500.000000     17.600000   \n",
       "25%                              8.150000         1900.000000     70.600000   \n",
       "50%                             21.000000         5550.000000     92.500000   \n",
       "75%                             55.705000        15700.000000     98.000000   \n",
       "max                            191.190000        55100.000000    100.000000   \n",
       "\n",
       "       Phones (per 1000)  Arable (%)   Crops (%)   Other (%)     Climate  \\\n",
       "count         223.000000  225.000000  225.000000  225.000000  205.000000   \n",
       "mean          236.061435   13.797111    4.564222   81.638311    2.139024   \n",
       "std           227.991829   13.040402    8.361470   16.140835    0.699397   \n",
       "min             0.200000    0.000000    0.000000   33.330000    1.000000   \n",
       "25%            37.800000    3.220000    0.190000   71.650000    2.000000   \n",
       "50%           176.200000   10.420000    1.030000   85.700000    2.000000   \n",
       "75%           389.650000   20.000000    4.440000   95.440000    3.000000   \n",
       "max          1035.600000   62.110000   50.680000  100.000000    4.000000   \n",
       "\n",
       "        Birthrate   Deathrate  Agriculture    Industry     Service  \n",
       "count  224.000000  223.000000   212.000000  211.000000  212.000000  \n",
       "mean    22.114732    9.241345     0.150844    0.282711    0.565283  \n",
       "std     11.176716    4.990026     0.146798    0.138272    0.165841  \n",
       "min      7.290000    2.290000     0.000000    0.020000    0.062000  \n",
       "25%     12.672500    5.910000     0.037750    0.193000    0.429250  \n",
       "50%     18.790000    7.840000     0.099000    0.272000    0.571000  \n",
       "75%     29.820000   10.605000     0.221000    0.341000    0.678500  \n",
       "max     50.730000   29.740000     0.769000    0.906000    0.954000  "
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "df.describe() results in 3 kind of data : Numeric Data(Default) , Object Data and Categorical Data.\n",
    "\n",
    "df.describe() by default will include the numeric data(count,min,max,mean,std,lower percentile(default = 25%),\n",
    "50 percentile and upper percentile(default = 75%)) which is displayed in our Output above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "imputer = SimpleImputer(missing_values=np.nan, strategy=\"median\")\n",
    "imputer = imputer.fit(df.iloc[:,2:])\n",
    "df.iloc[:,2:] = imputer.transform(df.iloc[:,2:])\n",
    "\n",
    "#df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I am inserting the above code in the assignment in order to replace all the Nan values with the median. As we know that while plotting a graph null values are not getting plotted and I was facing errors in 4 inputs. So,to remove those errors i am inporting an imputer class which deals with the missing values.\n",
    "\n",
    "imputer.fit - will find the median for each column.\n",
    "\n",
    "df.iloc[:,2:] - will do the slicing.\n",
    "\n",
    "imputer.transform - will replace the missing values with the median.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sort countries by GDP per capita"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "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>GDP ($ per capita)</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>55100.0</td>\n",
       "      <td>Luxembourg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>37800.0</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>37800.0</td>\n",
       "      <td>Norway</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>36000.0</td>\n",
       "      <td>Bermuda</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>35000.0</td>\n",
       "      <td>Cayman Islands</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>34600.0</td>\n",
       "      <td>San Marino</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>32700.0</td>\n",
       "      <td>Switzerland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>31100.0</td>\n",
       "      <td>Denmark</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>30900.0</td>\n",
       "      <td>Iceland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>Austria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>29800.0</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>29600.0</td>\n",
       "      <td>Ireland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>29100.0</td>\n",
       "      <td>Belgium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>29000.0</td>\n",
       "      <td>Australia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>28800.0</td>\n",
       "      <td>Hong Kong</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>28600.0</td>\n",
       "      <td>Netherlands</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>28200.0</td>\n",
       "      <td>Japan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>28000.0</td>\n",
       "      <td>Aruba</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>27700.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>27600.0</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     GDP ($ per capita)          Country\n",
       "121             55100.0      Luxembourg \n",
       "214             37800.0   United States \n",
       "154             37800.0          Norway \n",
       "22              36000.0         Bermuda \n",
       "38              35000.0  Cayman Islands \n",
       "177             34600.0      San Marino \n",
       "196             32700.0     Switzerland \n",
       "54              31100.0         Denmark \n",
       "93              30900.0         Iceland \n",
       "12              30000.0         Austria \n",
       "36              29800.0          Canada \n",
       "98              29600.0         Ireland \n",
       "19              29100.0         Belgium \n",
       "11              29000.0       Australia \n",
       "91              28800.0       Hong Kong \n",
       "146             28600.0     Netherlands \n",
       "103             28200.0           Japan \n",
       "10              28000.0           Aruba \n",
       "213             27700.0  United Kingdom \n",
       "76              27600.0         Germany "
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_gdp_countries = df.sort_values('GDP ($ per capita)',ascending=False)\n",
    "# Look at top 20\n",
    "top_gdp_countries[['GDP ($ per capita)','Country']].head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "df.sort_values default will sort the values by,axis =0,ascending=True,inplace=False,kind='quicksort', na_position='last').\n",
    "\n",
    "As mentioned above \"df.sort_values('GDP,ascending=False)\"it will sort and display the results but not in ascending order And\n",
    "top_gdp_countries[['GDP ($ per capita)','Country']].head(20) will result in top 20 sorted rows.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(16,6))\n",
    "sns.barplot(x='Country', y='GDP ($ per capita)', data=top_gdp_countries.head(33), palette='Set2')\n",
    "ax.set_xlabel(ax.get_xlabel(), labelpad=15)\n",
    "ax.set_ylabel(ax.get_ylabel(), labelpad=30)\n",
    "ax.xaxis.label.set_fontsize(16)\n",
    "ax.yaxis.label.set_fontsize(16)\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The gist of the above bar graph is: \n",
    "\n",
    "labelpad - It is the distance between the label and its attributes.\n",
    "\n",
    "It is plotting the first 30 sorted GDP countries having \"Country\" on x-axis having (labelpad=15 and font size= 16)\n",
    "and \"GDP\" on y-axis having (labelpad=30 and font size= 16 and attributes(10000-50000) as per the first 30 GDP countries) with color palette as Set 2.\n",
    "\n",
    "plt.xticks(rotation=90) is plottong the names of the countries in the rotation of 90 degree.\n",
    "\n",
    "plt.show() will display the graph.\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(16,6))\n",
    "sns.barplot(x='Country', y='GDP ($ per capita)', data=top_gdp_countries.tail(33), palette='Set1')\n",
    "ax.set_xlabel(ax.get_xlabel(), labelpad=15)\n",
    "ax.set_ylabel(ax.get_ylabel(), labelpad=30)\n",
    "ax.xaxis.label.set_fontsize(16)\n",
    "ax.yaxis.label.set_fontsize(16)\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The gist of the above bar graph is:\n",
    "\n",
    "labelpad - It is the distance between the label and its attributes.\n",
    "\n",
    "It is plotting the last(tail) 33 sorted GDP countries having \"Country\" on x-axis having (labelpad=15 and font size= 16) and \"GDP\" on y-axis having (labelpad=30 and font size= 16 and attributes(0-1200) as per the last 33 GDP countries) with color palette as Set 1.\n",
    "plt.xticks(rotation=90) is plottong the names of the countries in the rotation of 90 degree.\n",
    "\n",
    "plt.xticks(rotation=90) is plottong the names of the countries in the rotation of 90 degree.\n",
    "\n",
    "plt.show() will display the graph."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "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>total_missing</th>\n",
       "      <th>percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [total_missing, percent]\n",
       "Index: []"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total = df.isnull().sum()[df.isnull().sum() != 0].sort_values(ascending = False)\n",
    "percent = pd.Series(round(total/len(df)*100,2))\n",
    "pd.concat([total, percent], axis=1, keys=['total_missing', 'percent'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above output is based on the total and percent calculated with the above provided code.\n",
    "\n",
    "total = calculated by checking the number of nulls if exists and then the sum of all the non zero values excluding \n",
    "the nulls and then sorting them in the descending order.\n",
    "\n",
    "percent = calculated by the total divided by the number of rows * 100 which is then rounded to 2 decimels place. \n",
    "\n",
    "By concatinating total as total-missing and percent as percent with axis = 1 (displaying the result in column order).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking for null values\n",
    "df.isnull().values.any() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Country                               0\n",
       "Region                                0\n",
       "Population                            0\n",
       "Area (sq. mi.)                        0\n",
       "Pop. Density (per sq. mi.)            0\n",
       "Coastline (coast/area ratio)          0\n",
       "Net migration                         0\n",
       "Infant mortality (per 1000 births)    0\n",
       "GDP ($ per capita)                    0\n",
       "Literacy (%)                          0\n",
       "Phones (per 1000)                     0\n",
       "Arable (%)                            0\n",
       "Crops (%)                             0\n",
       "Other (%)                             0\n",
       "Climate                               0\n",
       "Birthrate                             0\n",
       "Deathrate                             0\n",
       "Agriculture                           0\n",
       "Industry                              0\n",
       "Service                               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above output is displaying the number of null values of all the fields."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above is calculating the sum of all the total of nulls calculated in the above output."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Regions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "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>GDP ($ per capita)</th>\n",
       "      <th>Literacy (%)</th>\n",
       "      <th>Agriculture</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Region</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ASIA (EX. NEAR EAST)</th>\n",
       "      <td>3450.0</td>\n",
       "      <td>90.60</td>\n",
       "      <td>0.1610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BALTICS</th>\n",
       "      <td>11400.0</td>\n",
       "      <td>99.80</td>\n",
       "      <td>0.0400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C.W. OF IND. STATES</th>\n",
       "      <td>3450.0</td>\n",
       "      <td>99.05</td>\n",
       "      <td>0.1980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EASTERN EUROPE</th>\n",
       "      <td>9100.0</td>\n",
       "      <td>98.45</td>\n",
       "      <td>0.0815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LATIN AMER. &amp; CARIB</th>\n",
       "      <td>6300.0</td>\n",
       "      <td>94.00</td>\n",
       "      <td>0.0700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEAR EAST</th>\n",
       "      <td>9250.0</td>\n",
       "      <td>85.00</td>\n",
       "      <td>0.0350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NORTHERN AFRICA</th>\n",
       "      <td>5775.0</td>\n",
       "      <td>72.10</td>\n",
       "      <td>0.1165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NORTHERN AMERICA</th>\n",
       "      <td>29800.0</td>\n",
       "      <td>97.00</td>\n",
       "      <td>0.0220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OCEANIA</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>93.70</td>\n",
       "      <td>0.0990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUB-SAHARAN AFRICA</th>\n",
       "      <td>1300.0</td>\n",
       "      <td>63.20</td>\n",
       "      <td>0.2690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WESTERN EUROPE</th>\n",
       "      <td>27200.0</td>\n",
       "      <td>98.80</td>\n",
       "      <td>0.0290</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     GDP ($ per capita)  Literacy (%)  \\\n",
       "Region                                                                  \n",
       "ASIA (EX. NEAR EAST)                             3450.0         90.60   \n",
       "BALTICS                                         11400.0         99.80   \n",
       "C.W. OF IND. STATES                              3450.0         99.05   \n",
       "EASTERN EUROPE                                   9100.0         98.45   \n",
       "LATIN AMER. & CARIB                              6300.0         94.00   \n",
       "NEAR EAST                                        9250.0         85.00   \n",
       "NORTHERN AFRICA                                  5775.0         72.10   \n",
       "NORTHERN AMERICA                                29800.0         97.00   \n",
       "OCEANIA                                          5000.0         93.70   \n",
       "SUB-SAHARAN AFRICA                               1300.0         63.20   \n",
       "WESTERN EUROPE                                  27200.0         98.80   \n",
       "\n",
       "                                     Agriculture  \n",
       "Region                                            \n",
       "ASIA (EX. NEAR EAST)                      0.1610  \n",
       "BALTICS                                   0.0400  \n",
       "C.W. OF IND. STATES                       0.1980  \n",
       "EASTERN EUROPE                            0.0815  \n",
       "LATIN AMER. & CARIB                       0.0700  \n",
       "NEAR EAST                                 0.0350  \n",
       "NORTHERN AFRICA                           0.1165  \n",
       "NORTHERN AMERICA                          0.0220  \n",
       "OCEANIA                                   0.0990  \n",
       "SUB-SAHARAN AFRICA                        0.2690  \n",
       "WESTERN EUROPE                            0.0290  "
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('Region')[['GDP ($ per capita)', 'Literacy (%)', 'Agriculture']].median()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the above output we are calculating the median of the GDP,Literacy and Agriculture as per the same type of regions as we have grouped the region."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(sum(map(ord, \"distributions\")))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "np.random.seed - It is random number generator.\n",
    "\n",
    "ord - gives us the byte represenation of a character.\n",
    "\n",
    "map - applies a function to every item of an interable\n",
    "\n",
    "sum - sums up the elements of an iterable.\n",
    " \n",
    "So, the above function will generate the random numbers by providing us the sum of all the iterable items with a byte  of a character."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Region</th>\n",
       "      <th>Population</th>\n",
       "      <th>Area (sq. mi.)</th>\n",
       "      <th>Pop. Density (per sq. mi.)</th>\n",
       "      <th>Coastline (coast/area ratio)</th>\n",
       "      <th>Net migration</th>\n",
       "      <th>Infant mortality (per 1000 births)</th>\n",
       "      <th>GDP ($ per capita)</th>\n",
       "      <th>Literacy (%)</th>\n",
       "      <th>Phones (per 1000)</th>\n",
       "      <th>Arable (%)</th>\n",
       "      <th>Crops (%)</th>\n",
       "      <th>Other (%)</th>\n",
       "      <th>Climate</th>\n",
       "      <th>Birthrate</th>\n",
       "      <th>Deathrate</th>\n",
       "      <th>Agriculture</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Service</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>ASIA (EX. NEAR EAST)</td>\n",
       "      <td>31056997.0</td>\n",
       "      <td>647500.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>23.06</td>\n",
       "      <td>163.07</td>\n",
       "      <td>700.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>12.13</td>\n",
       "      <td>0.22</td>\n",
       "      <td>87.65</td>\n",
       "      <td>1.0</td>\n",
       "      <td>46.60</td>\n",
       "      <td>20.34</td>\n",
       "      <td>0.380</td>\n",
       "      <td>0.240</td>\n",
       "      <td>0.380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>EASTERN EUROPE</td>\n",
       "      <td>3581655.0</td>\n",
       "      <td>28748.0</td>\n",
       "      <td>124.6</td>\n",
       "      <td>1.26</td>\n",
       "      <td>-4.93</td>\n",
       "      <td>21.52</td>\n",
       "      <td>4500.0</td>\n",
       "      <td>86.5</td>\n",
       "      <td>71.2</td>\n",
       "      <td>21.09</td>\n",
       "      <td>4.42</td>\n",
       "      <td>74.49</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15.11</td>\n",
       "      <td>5.22</td>\n",
       "      <td>0.232</td>\n",
       "      <td>0.188</td>\n",
       "      <td>0.579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>NORTHERN AFRICA</td>\n",
       "      <td>32930091.0</td>\n",
       "      <td>2381740.0</td>\n",
       "      <td>13.8</td>\n",
       "      <td>0.04</td>\n",
       "      <td>-0.39</td>\n",
       "      <td>31.00</td>\n",
       "      <td>6000.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>78.1</td>\n",
       "      <td>3.22</td>\n",
       "      <td>0.25</td>\n",
       "      <td>96.53</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.14</td>\n",
       "      <td>4.61</td>\n",
       "      <td>0.101</td>\n",
       "      <td>0.600</td>\n",
       "      <td>0.298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>American Samoa</td>\n",
       "      <td>OCEANIA</td>\n",
       "      <td>57794.0</td>\n",
       "      <td>199.0</td>\n",
       "      <td>290.4</td>\n",
       "      <td>58.29</td>\n",
       "      <td>-20.71</td>\n",
       "      <td>9.27</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>259.5</td>\n",
       "      <td>10.00</td>\n",
       "      <td>15.00</td>\n",
       "      <td>75.00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>22.46</td>\n",
       "      <td>3.27</td>\n",
       "      <td>0.099</td>\n",
       "      <td>0.272</td>\n",
       "      <td>0.571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>WESTERN EUROPE</td>\n",
       "      <td>71201.0</td>\n",
       "      <td>468.0</td>\n",
       "      <td>152.1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6.60</td>\n",
       "      <td>4.05</td>\n",
       "      <td>19000.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>497.2</td>\n",
       "      <td>2.22</td>\n",
       "      <td>0.00</td>\n",
       "      <td>97.78</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.71</td>\n",
       "      <td>6.25</td>\n",
       "      <td>0.099</td>\n",
       "      <td>0.272</td>\n",
       "      <td>0.571</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Country                               Region  Population  \\\n",
       "0     Afghanistan         ASIA (EX. NEAR EAST)           31056997.0   \n",
       "1         Albania   EASTERN EUROPE                        3581655.0   \n",
       "2         Algeria   NORTHERN AFRICA                      32930091.0   \n",
       "3  American Samoa   OCEANIA                                 57794.0   \n",
       "4         Andorra   WESTERN EUROPE                          71201.0   \n",
       "\n",
       "   Area (sq. mi.)  Pop. Density (per sq. mi.)  Coastline (coast/area ratio)  \\\n",
       "0        647500.0                        48.0                          0.00   \n",
       "1         28748.0                       124.6                          1.26   \n",
       "2       2381740.0                        13.8                          0.04   \n",
       "3           199.0                       290.4                         58.29   \n",
       "4           468.0                       152.1                          0.00   \n",
       "\n",
       "   Net migration  Infant mortality (per 1000 births)  GDP ($ per capita)  \\\n",
       "0          23.06                              163.07               700.0   \n",
       "1          -4.93                               21.52              4500.0   \n",
       "2          -0.39                               31.00              6000.0   \n",
       "3         -20.71                                9.27              8000.0   \n",
       "4           6.60                                4.05             19000.0   \n",
       "\n",
       "   Literacy (%)  Phones (per 1000)  Arable (%)  Crops (%)  Other (%)  Climate  \\\n",
       "0          36.0                3.2       12.13       0.22      87.65      1.0   \n",
       "1          86.5               71.2       21.09       4.42      74.49      3.0   \n",
       "2          70.0               78.1        3.22       0.25      96.53      1.0   \n",
       "3          97.0              259.5       10.00      15.00      75.00      2.0   \n",
       "4         100.0              497.2        2.22       0.00      97.78      3.0   \n",
       "\n",
       "   Birthrate  Deathrate  Agriculture  Industry  Service  \n",
       "0      46.60      20.34        0.380     0.240    0.380  \n",
       "1      15.11       5.22        0.232     0.188    0.579  \n",
       "2      17.14       4.61        0.101     0.600    0.298  \n",
       "3      22.46       3.27        0.099     0.272    0.571  \n",
       "4       8.71       6.25        0.099     0.272    0.571  "
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above is providing us the first 5 records."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1fed66a0>"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(np.array(df['Literacy (%)']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "sns.boxplot - It will draw a box plot to show distributions with respect to the Literacy.\n",
    "\n",
    "np.array - It will return an array as per the data frame Literacy.\n",
    "\n",
    "The above boxplot is created by taking the array of the DataFrame Literacy (%).The Literacy percentage is displayed between its Minimum (33) and Maximum (100) having Median (93). \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a246b0a90>"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(df['GDP ($ per capita)'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "sns.boxplot - It will draw a box plot to show distributions with respect to the GDP ($ per capita).\n",
    "\n",
    "The above boxplot is created by taking the array of the DataFrame GDP. The GDP ($ per capita) is displayed between its Minimum (0) and Maximum (37000) having Median (8000)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "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>Population</th>\n",
       "      <th>Area (sq. mi.)</th>\n",
       "      <th>Pop. Density (per sq. mi.)</th>\n",
       "      <th>Coastline (coast/area ratio)</th>\n",
       "      <th>Net migration</th>\n",
       "      <th>Infant mortality (per 1000 births)</th>\n",
       "      <th>GDP ($ per capita)</th>\n",
       "      <th>Literacy (%)</th>\n",
       "      <th>Phones (per 1000)</th>\n",
       "      <th>Arable (%)</th>\n",
       "      <th>Crops (%)</th>\n",
       "      <th>Other (%)</th>\n",
       "      <th>Climate</th>\n",
       "      <th>Birthrate</th>\n",
       "      <th>Deathrate</th>\n",
       "      <th>Agriculture</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Service</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Population</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.469985</td>\n",
       "      <td>-0.028190</td>\n",
       "      <td>-0.068199</td>\n",
       "      <td>0.000036</td>\n",
       "      <td>0.024298</td>\n",
       "      <td>-0.038864</td>\n",
       "      <td>-0.052456</td>\n",
       "      <td>-0.029663</td>\n",
       "      <td>0.188704</td>\n",
       "      <td>-0.059782</td>\n",
       "      <td>-0.121084</td>\n",
       "      <td>-0.024411</td>\n",
       "      <td>-0.044189</td>\n",
       "      <td>-0.027215</td>\n",
       "      <td>0.006249</td>\n",
       "      <td>0.100471</td>\n",
       "      <td>-0.081254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Area (sq. mi.)</th>\n",
       "      <td>0.469985</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.066917</td>\n",
       "      <td>-0.095627</td>\n",
       "      <td>0.047472</td>\n",
       "      <td>-0.005594</td>\n",
       "      <td>0.072491</td>\n",
       "      <td>0.025232</td>\n",
       "      <td>0.054703</td>\n",
       "      <td>-0.078881</td>\n",
       "      <td>-0.142477</td>\n",
       "      <td>0.138118</td>\n",
       "      <td>-0.091789</td>\n",
       "      <td>-0.065285</td>\n",
       "      <td>0.041447</td>\n",
       "      <td>-0.044291</td>\n",
       "      <td>0.122299</td>\n",
       "      <td>-0.054677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pop. Density (per sq. mi.)</th>\n",
       "      <td>-0.028190</td>\n",
       "      <td>-0.066917</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.241690</td>\n",
       "      <td>0.178011</td>\n",
       "      <td>-0.142953</td>\n",
       "      <td>0.196093</td>\n",
       "      <td>0.101518</td>\n",
       "      <td>0.280802</td>\n",
       "      <td>-0.081404</td>\n",
       "      <td>-0.032330</td>\n",
       "      <td>0.082237</td>\n",
       "      <td>-0.001699</td>\n",
       "      <td>-0.158282</td>\n",
       "      <td>-0.069021</td>\n",
       "      <td>-0.106589</td>\n",
       "      <td>-0.109147</td>\n",
       "      <td>0.189446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Coastline (coast/area ratio)</th>\n",
       "      <td>-0.068199</td>\n",
       "      <td>-0.095627</td>\n",
       "      <td>0.241690</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.134051</td>\n",
       "      <td>-0.137171</td>\n",
       "      <td>0.049614</td>\n",
       "      <td>0.127766</td>\n",
       "      <td>0.152497</td>\n",
       "      <td>-0.121735</td>\n",
       "      <td>0.339312</td>\n",
       "      <td>-0.078279</td>\n",
       "      <td>-0.033284</td>\n",
       "      <td>-0.075378</td>\n",
       "      <td>-0.161813</td>\n",
       "      <td>-0.043559</td>\n",
       "      <td>-0.189342</td>\n",
       "      <td>0.183868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Net migration</th>\n",
       "      <td>0.000036</td>\n",
       "      <td>0.047472</td>\n",
       "      <td>0.178011</td>\n",
       "      <td>-0.134051</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.024945</td>\n",
       "      <td>0.381877</td>\n",
       "      <td>-0.005668</td>\n",
       "      <td>0.239220</td>\n",
       "      <td>-0.060119</td>\n",
       "      <td>-0.344059</td>\n",
       "      <td>0.225192</td>\n",
       "      <td>-0.020845</td>\n",
       "      <td>-0.066087</td>\n",
       "      <td>0.033964</td>\n",
       "      <td>-0.108935</td>\n",
       "      <td>-0.025006</td>\n",
       "      <td>0.114301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Infant mortality (per 1000 births)</th>\n",
       "      <td>0.024298</td>\n",
       "      <td>-0.005594</td>\n",
       "      <td>-0.142953</td>\n",
       "      <td>-0.137171</td>\n",
       "      <td>-0.024945</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.596424</td>\n",
       "      <td>-0.756088</td>\n",
       "      <td>-0.666106</td>\n",
       "      <td>-0.110154</td>\n",
       "      <td>-0.066185</td>\n",
       "      <td>0.123398</td>\n",
       "      <td>-0.333355</td>\n",
       "      <td>0.845636</td>\n",
       "      <td>0.656874</td>\n",
       "      <td>0.707926</td>\n",
       "      <td>0.009511</td>\n",
       "      <td>-0.619634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP ($ per capita)</th>\n",
       "      <td>-0.038864</td>\n",
       "      <td>0.072491</td>\n",
       "      <td>0.196093</td>\n",
       "      <td>0.049614</td>\n",
       "      <td>0.381877</td>\n",
       "      <td>-0.596424</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.495909</td>\n",
       "      <td>0.830903</td>\n",
       "      <td>0.021194</td>\n",
       "      <td>-0.217685</td>\n",
       "      <td>0.095431</td>\n",
       "      <td>0.295621</td>\n",
       "      <td>-0.645865</td>\n",
       "      <td>-0.198155</td>\n",
       "      <td>-0.572473</td>\n",
       "      <td>-0.029482</td>\n",
       "      <td>0.532418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Literacy (%)</th>\n",
       "      <td>-0.052456</td>\n",
       "      <td>0.025232</td>\n",
       "      <td>0.101518</td>\n",
       "      <td>0.127766</td>\n",
       "      <td>-0.005668</td>\n",
       "      <td>-0.756088</td>\n",
       "      <td>0.495909</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.565414</td>\n",
       "      <td>0.085631</td>\n",
       "      <td>0.044724</td>\n",
       "      <td>-0.093081</td>\n",
       "      <td>0.359711</td>\n",
       "      <td>-0.754837</td>\n",
       "      <td>-0.394168</td>\n",
       "      <td>-0.597133</td>\n",
       "      <td>0.040135</td>\n",
       "      <td>0.481603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Phones (per 1000)</th>\n",
       "      <td>-0.029663</td>\n",
       "      <td>0.054703</td>\n",
       "      <td>0.280802</td>\n",
       "      <td>0.152497</td>\n",
       "      <td>0.239220</td>\n",
       "      <td>-0.666106</td>\n",
       "      <td>0.830903</td>\n",
       "      <td>0.565414</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.059448</td>\n",
       "      <td>-0.150963</td>\n",
       "      <td>0.028768</td>\n",
       "      <td>0.345543</td>\n",
       "      <td>-0.719766</td>\n",
       "      <td>-0.257397</td>\n",
       "      <td>-0.581195</td>\n",
       "      <td>-0.143477</td>\n",
       "      <td>0.626184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arable (%)</th>\n",
       "      <td>0.188704</td>\n",
       "      <td>-0.078881</td>\n",
       "      <td>-0.081404</td>\n",
       "      <td>-0.121735</td>\n",
       "      <td>-0.060119</td>\n",
       "      <td>-0.110154</td>\n",
       "      <td>0.021194</td>\n",
       "      <td>0.085631</td>\n",
       "      <td>0.059448</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.095226</td>\n",
       "      <td>-0.856845</td>\n",
       "      <td>0.346590</td>\n",
       "      <td>-0.183561</td>\n",
       "      <td>0.053051</td>\n",
       "      <td>-0.021570</td>\n",
       "      <td>-0.057425</td>\n",
       "      <td>0.085316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Crops (%)</th>\n",
       "      <td>-0.059782</td>\n",
       "      <td>-0.142477</td>\n",
       "      <td>-0.032330</td>\n",
       "      <td>0.339312</td>\n",
       "      <td>-0.344059</td>\n",
       "      <td>-0.066185</td>\n",
       "      <td>-0.217685</td>\n",
       "      <td>0.044724</td>\n",
       "      <td>-0.150963</td>\n",
       "      <td>0.095226</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.594559</td>\n",
       "      <td>0.007573</td>\n",
       "      <td>0.114433</td>\n",
       "      <td>-0.204403</td>\n",
       "      <td>0.053917</td>\n",
       "      <td>-0.110649</td>\n",
       "      <td>0.048249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other (%)</th>\n",
       "      <td>-0.121084</td>\n",
       "      <td>0.138118</td>\n",
       "      <td>0.082237</td>\n",
       "      <td>-0.078279</td>\n",
       "      <td>0.225192</td>\n",
       "      <td>0.123398</td>\n",
       "      <td>0.095431</td>\n",
       "      <td>-0.093081</td>\n",
       "      <td>0.028768</td>\n",
       "      <td>-0.856845</td>\n",
       "      <td>-0.594559</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.284773</td>\n",
       "      <td>0.088560</td>\n",
       "      <td>0.063237</td>\n",
       "      <td>-0.009575</td>\n",
       "      <td>0.104848</td>\n",
       "      <td>-0.095457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Climate</th>\n",
       "      <td>-0.024411</td>\n",
       "      <td>-0.091789</td>\n",
       "      <td>-0.001699</td>\n",
       "      <td>-0.033284</td>\n",
       "      <td>-0.020845</td>\n",
       "      <td>-0.333355</td>\n",
       "      <td>0.295621</td>\n",
       "      <td>0.359711</td>\n",
       "      <td>0.345543</td>\n",
       "      <td>0.346590</td>\n",
       "      <td>0.007573</td>\n",
       "      <td>-0.284773</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.413845</td>\n",
       "      <td>0.009837</td>\n",
       "      <td>-0.190383</td>\n",
       "      <td>-0.089623</td>\n",
       "      <td>0.259324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Birthrate</th>\n",
       "      <td>-0.044189</td>\n",
       "      <td>-0.065285</td>\n",
       "      <td>-0.158282</td>\n",
       "      <td>-0.075378</td>\n",
       "      <td>-0.066087</td>\n",
       "      <td>0.845636</td>\n",
       "      <td>-0.645865</td>\n",
       "      <td>-0.754837</td>\n",
       "      <td>-0.719766</td>\n",
       "      <td>-0.183561</td>\n",
       "      <td>0.114433</td>\n",
       "      <td>0.088560</td>\n",
       "      <td>-0.413845</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.396017</td>\n",
       "      <td>0.669846</td>\n",
       "      <td>-0.053082</td>\n",
       "      <td>-0.542931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Deathrate</th>\n",
       "      <td>-0.027215</td>\n",
       "      <td>0.041447</td>\n",
       "      <td>-0.069021</td>\n",
       "      <td>-0.161813</td>\n",
       "      <td>0.033964</td>\n",
       "      <td>0.656874</td>\n",
       "      <td>-0.198155</td>\n",
       "      <td>-0.394168</td>\n",
       "      <td>-0.257397</td>\n",
       "      <td>0.053051</td>\n",
       "      <td>-0.204403</td>\n",
       "      <td>0.063237</td>\n",
       "      <td>0.009837</td>\n",
       "      <td>0.396017</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.387979</td>\n",
       "      <td>0.031261</td>\n",
       "      <td>-0.352791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agriculture</th>\n",
       "      <td>0.006249</td>\n",
       "      <td>-0.044291</td>\n",
       "      <td>-0.106589</td>\n",
       "      <td>-0.043559</td>\n",
       "      <td>-0.108935</td>\n",
       "      <td>0.707926</td>\n",
       "      <td>-0.572473</td>\n",
       "      <td>-0.597133</td>\n",
       "      <td>-0.581195</td>\n",
       "      <td>-0.021570</td>\n",
       "      <td>0.053917</td>\n",
       "      <td>-0.009575</td>\n",
       "      <td>-0.190383</td>\n",
       "      <td>0.669846</td>\n",
       "      <td>0.387979</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.319742</td>\n",
       "      <td>-0.612064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Industry</th>\n",
       "      <td>0.100471</td>\n",
       "      <td>0.122299</td>\n",
       "      <td>-0.109147</td>\n",
       "      <td>-0.189342</td>\n",
       "      <td>-0.025006</td>\n",
       "      <td>0.009511</td>\n",
       "      <td>-0.029482</td>\n",
       "      <td>0.040135</td>\n",
       "      <td>-0.143477</td>\n",
       "      <td>-0.057425</td>\n",
       "      <td>-0.110649</td>\n",
       "      <td>0.104848</td>\n",
       "      <td>-0.089623</td>\n",
       "      <td>-0.053082</td>\n",
       "      <td>0.031261</td>\n",
       "      <td>-0.319742</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.542978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Service</th>\n",
       "      <td>-0.081254</td>\n",
       "      <td>-0.054677</td>\n",
       "      <td>0.189446</td>\n",
       "      <td>0.183868</td>\n",
       "      <td>0.114301</td>\n",
       "      <td>-0.619634</td>\n",
       "      <td>0.532418</td>\n",
       "      <td>0.481603</td>\n",
       "      <td>0.626184</td>\n",
       "      <td>0.085316</td>\n",
       "      <td>0.048249</td>\n",
       "      <td>-0.095457</td>\n",
       "      <td>0.259324</td>\n",
       "      <td>-0.542931</td>\n",
       "      <td>-0.352791</td>\n",
       "      <td>-0.612064</td>\n",
       "      <td>-0.542978</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    Population  Area (sq. mi.)  \\\n",
       "Population                            1.000000        0.469985   \n",
       "Area (sq. mi.)                        0.469985        1.000000   \n",
       "Pop. Density (per sq. mi.)           -0.028190       -0.066917   \n",
       "Coastline (coast/area ratio)         -0.068199       -0.095627   \n",
       "Net migration                         0.000036        0.047472   \n",
       "Infant mortality (per 1000 births)    0.024298       -0.005594   \n",
       "GDP ($ per capita)                   -0.038864        0.072491   \n",
       "Literacy (%)                         -0.052456        0.025232   \n",
       "Phones (per 1000)                    -0.029663        0.054703   \n",
       "Arable (%)                            0.188704       -0.078881   \n",
       "Crops (%)                            -0.059782       -0.142477   \n",
       "Other (%)                            -0.121084        0.138118   \n",
       "Climate                              -0.024411       -0.091789   \n",
       "Birthrate                            -0.044189       -0.065285   \n",
       "Deathrate                            -0.027215        0.041447   \n",
       "Agriculture                           0.006249       -0.044291   \n",
       "Industry                              0.100471        0.122299   \n",
       "Service                              -0.081254       -0.054677   \n",
       "\n",
       "                                    Pop. Density (per sq. mi.)  \\\n",
       "Population                                           -0.028190   \n",
       "Area (sq. mi.)                                       -0.066917   \n",
       "Pop. Density (per sq. mi.)                            1.000000   \n",
       "Coastline (coast/area ratio)                          0.241690   \n",
       "Net migration                                         0.178011   \n",
       "Infant mortality (per 1000 births)                   -0.142953   \n",
       "GDP ($ per capita)                                    0.196093   \n",
       "Literacy (%)                                          0.101518   \n",
       "Phones (per 1000)                                     0.280802   \n",
       "Arable (%)                                           -0.081404   \n",
       "Crops (%)                                            -0.032330   \n",
       "Other (%)                                             0.082237   \n",
       "Climate                                              -0.001699   \n",
       "Birthrate                                            -0.158282   \n",
       "Deathrate                                            -0.069021   \n",
       "Agriculture                                          -0.106589   \n",
       "Industry                                             -0.109147   \n",
       "Service                                               0.189446   \n",
       "\n",
       "                                    Coastline (coast/area ratio)  \\\n",
       "Population                                             -0.068199   \n",
       "Area (sq. mi.)                                         -0.095627   \n",
       "Pop. Density (per sq. mi.)                              0.241690   \n",
       "Coastline (coast/area ratio)                            1.000000   \n",
       "Net migration                                          -0.134051   \n",
       "Infant mortality (per 1000 births)                     -0.137171   \n",
       "GDP ($ per capita)                                      0.049614   \n",
       "Literacy (%)                                            0.127766   \n",
       "Phones (per 1000)                                       0.152497   \n",
       "Arable (%)                                             -0.121735   \n",
       "Crops (%)                                               0.339312   \n",
       "Other (%)                                              -0.078279   \n",
       "Climate                                                -0.033284   \n",
       "Birthrate                                              -0.075378   \n",
       "Deathrate                                              -0.161813   \n",
       "Agriculture                                            -0.043559   \n",
       "Industry                                               -0.189342   \n",
       "Service                                                 0.183868   \n",
       "\n",
       "                                    Net migration  \\\n",
       "Population                               0.000036   \n",
       "Area (sq. mi.)                           0.047472   \n",
       "Pop. Density (per sq. mi.)               0.178011   \n",
       "Coastline (coast/area ratio)            -0.134051   \n",
       "Net migration                            1.000000   \n",
       "Infant mortality (per 1000 births)      -0.024945   \n",
       "GDP ($ per capita)                       0.381877   \n",
       "Literacy (%)                            -0.005668   \n",
       "Phones (per 1000)                        0.239220   \n",
       "Arable (%)                              -0.060119   \n",
       "Crops (%)                               -0.344059   \n",
       "Other (%)                                0.225192   \n",
       "Climate                                 -0.020845   \n",
       "Birthrate                               -0.066087   \n",
       "Deathrate                                0.033964   \n",
       "Agriculture                             -0.108935   \n",
       "Industry                                -0.025006   \n",
       "Service                                  0.114301   \n",
       "\n",
       "                                    Infant mortality (per 1000 births)  \\\n",
       "Population                                                    0.024298   \n",
       "Area (sq. mi.)                                               -0.005594   \n",
       "Pop. Density (per sq. mi.)                                   -0.142953   \n",
       "Coastline (coast/area ratio)                                 -0.137171   \n",
       "Net migration                                                -0.024945   \n",
       "Infant mortality (per 1000 births)                            1.000000   \n",
       "GDP ($ per capita)                                           -0.596424   \n",
       "Literacy (%)                                                 -0.756088   \n",
       "Phones (per 1000)                                            -0.666106   \n",
       "Arable (%)                                                   -0.110154   \n",
       "Crops (%)                                                    -0.066185   \n",
       "Other (%)                                                     0.123398   \n",
       "Climate                                                      -0.333355   \n",
       "Birthrate                                                     0.845636   \n",
       "Deathrate                                                     0.656874   \n",
       "Agriculture                                                   0.707926   \n",
       "Industry                                                      0.009511   \n",
       "Service                                                      -0.619634   \n",
       "\n",
       "                                    GDP ($ per capita)  Literacy (%)  \\\n",
       "Population                                   -0.038864     -0.052456   \n",
       "Area (sq. mi.)                                0.072491      0.025232   \n",
       "Pop. Density (per sq. mi.)                    0.196093      0.101518   \n",
       "Coastline (coast/area ratio)                  0.049614      0.127766   \n",
       "Net migration                                 0.381877     -0.005668   \n",
       "Infant mortality (per 1000 births)           -0.596424     -0.756088   \n",
       "GDP ($ per capita)                            1.000000      0.495909   \n",
       "Literacy (%)                                  0.495909      1.000000   \n",
       "Phones (per 1000)                             0.830903      0.565414   \n",
       "Arable (%)                                    0.021194      0.085631   \n",
       "Crops (%)                                    -0.217685      0.044724   \n",
       "Other (%)                                     0.095431     -0.093081   \n",
       "Climate                                       0.295621      0.359711   \n",
       "Birthrate                                    -0.645865     -0.754837   \n",
       "Deathrate                                    -0.198155     -0.394168   \n",
       "Agriculture                                  -0.572473     -0.597133   \n",
       "Industry                                     -0.029482      0.040135   \n",
       "Service                                       0.532418      0.481603   \n",
       "\n",
       "                                    Phones (per 1000)  Arable (%)  Crops (%)  \\\n",
       "Population                                  -0.029663    0.188704  -0.059782   \n",
       "Area (sq. mi.)                               0.054703   -0.078881  -0.142477   \n",
       "Pop. Density (per sq. mi.)                   0.280802   -0.081404  -0.032330   \n",
       "Coastline (coast/area ratio)                 0.152497   -0.121735   0.339312   \n",
       "Net migration                                0.239220   -0.060119  -0.344059   \n",
       "Infant mortality (per 1000 births)          -0.666106   -0.110154  -0.066185   \n",
       "GDP ($ per capita)                           0.830903    0.021194  -0.217685   \n",
       "Literacy (%)                                 0.565414    0.085631   0.044724   \n",
       "Phones (per 1000)                            1.000000    0.059448  -0.150963   \n",
       "Arable (%)                                   0.059448    1.000000   0.095226   \n",
       "Crops (%)                                   -0.150963    0.095226   1.000000   \n",
       "Other (%)                                    0.028768   -0.856845  -0.594559   \n",
       "Climate                                      0.345543    0.346590   0.007573   \n",
       "Birthrate                                   -0.719766   -0.183561   0.114433   \n",
       "Deathrate                                   -0.257397    0.053051  -0.204403   \n",
       "Agriculture                                 -0.581195   -0.021570   0.053917   \n",
       "Industry                                    -0.143477   -0.057425  -0.110649   \n",
       "Service                                      0.626184    0.085316   0.048249   \n",
       "\n",
       "                                    Other (%)   Climate  Birthrate  Deathrate  \\\n",
       "Population                          -0.121084 -0.024411  -0.044189  -0.027215   \n",
       "Area (sq. mi.)                       0.138118 -0.091789  -0.065285   0.041447   \n",
       "Pop. Density (per sq. mi.)           0.082237 -0.001699  -0.158282  -0.069021   \n",
       "Coastline (coast/area ratio)        -0.078279 -0.033284  -0.075378  -0.161813   \n",
       "Net migration                        0.225192 -0.020845  -0.066087   0.033964   \n",
       "Infant mortality (per 1000 births)   0.123398 -0.333355   0.845636   0.656874   \n",
       "GDP ($ per capita)                   0.095431  0.295621  -0.645865  -0.198155   \n",
       "Literacy (%)                        -0.093081  0.359711  -0.754837  -0.394168   \n",
       "Phones (per 1000)                    0.028768  0.345543  -0.719766  -0.257397   \n",
       "Arable (%)                          -0.856845  0.346590  -0.183561   0.053051   \n",
       "Crops (%)                           -0.594559  0.007573   0.114433  -0.204403   \n",
       "Other (%)                            1.000000 -0.284773   0.088560   0.063237   \n",
       "Climate                             -0.284773  1.000000  -0.413845   0.009837   \n",
       "Birthrate                            0.088560 -0.413845   1.000000   0.396017   \n",
       "Deathrate                            0.063237  0.009837   0.396017   1.000000   \n",
       "Agriculture                         -0.009575 -0.190383   0.669846   0.387979   \n",
       "Industry                             0.104848 -0.089623  -0.053082   0.031261   \n",
       "Service                             -0.095457  0.259324  -0.542931  -0.352791   \n",
       "\n",
       "                                    Agriculture  Industry   Service  \n",
       "Population                             0.006249  0.100471 -0.081254  \n",
       "Area (sq. mi.)                        -0.044291  0.122299 -0.054677  \n",
       "Pop. Density (per sq. mi.)            -0.106589 -0.109147  0.189446  \n",
       "Coastline (coast/area ratio)          -0.043559 -0.189342  0.183868  \n",
       "Net migration                         -0.108935 -0.025006  0.114301  \n",
       "Infant mortality (per 1000 births)     0.707926  0.009511 -0.619634  \n",
       "GDP ($ per capita)                    -0.572473 -0.029482  0.532418  \n",
       "Literacy (%)                          -0.597133  0.040135  0.481603  \n",
       "Phones (per 1000)                     -0.581195 -0.143477  0.626184  \n",
       "Arable (%)                            -0.021570 -0.057425  0.085316  \n",
       "Crops (%)                              0.053917 -0.110649  0.048249  \n",
       "Other (%)                             -0.009575  0.104848 -0.095457  \n",
       "Climate                               -0.190383 -0.089623  0.259324  \n",
       "Birthrate                              0.669846 -0.053082 -0.542931  \n",
       "Deathrate                              0.387979  0.031261 -0.352791  \n",
       "Agriculture                            1.000000 -0.319742 -0.612064  \n",
       "Industry                              -0.319742  1.000000 -0.542978  \n",
       "Service                               -0.612064 -0.542978  1.000000  "
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "df.corr() = It computes the pairwise correlation of columns, excluding NA/null values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,10))\n",
    "sns.heatmap(data=df.iloc[:,2:].corr(),annot=True,fmt='.2f',cmap='coolwarm')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "iloc - gets rows or columns at particular positions in the index so that it only takes integers.\n",
    "\n",
    "annot - give us the values of the data if it is true.\n",
    "\n",
    "cmap - map the data vales to the color map.\n",
    "\n",
    "fmt - give us the string formatting code.\n",
    "\n",
    "The above heatmap is plotted as per the correlation of the columns by displaying the data values corresponding to the columns as annot is True and formatting it to 2 decimal place as fmt is .2f provided the cmap as coolwarm."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "'literacy','phones_per_1000','infant_mortality_per_1000_births','birthrate','deathrate' have higest absolute value correlation with 'gdp_$_per_capita'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "# choose attributes which shows relation\n",
    "x = df[['GDP ($ per capita)','Literacy (%)','Phones (per 1000)','Service','Infant mortality (per 1000 births)','Birthrate','Deathrate']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a24deb5f8>"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# show corr of the same\n",
    "sns.heatmap(x.corr(), annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above heatmap is plaotted as the correlation of the above mentioned columns and diplaying the data values in the map as the annot is True.Death Rate have the highest absolute value correlation with GDP($ per capita)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=3, ncols=3, figsize=(20,20))\n",
    "plt.subplots_adjust(hspace=0.4)\n",
    "\n",
    "corr_to_gdp = pd.Series() \n",
    "for col in df.columns.values[2:]:\n",
    "    if ((col!='GDP ($ per capita)')&(col!='Climate')):\n",
    "        corr_to_gdp[col] = df['GDP ($ per capita)'].corr(df[col])\n",
    "abs_corr_to_gdp = corr_to_gdp.abs().sort_values(ascending=False)\n",
    "corr_to_gdp = corr_to_gdp.loc[abs_corr_to_gdp.index]\n",
    "\n",
    "for i in range(3):\n",
    "    for j in range(3):\n",
    "        sns.regplot(x=corr_to_gdp.index.values[i*3+j], y='GDP ($ per capita)', data=df,\n",
    "                   ax=axes[i,j], fit_reg=False, marker='.')\n",
    "        title = 'correlation='+str(corr_to_gdp[i*3+j])\n",
    "        axes[i,j].set_title(title)\n",
    "axes[1,2].set_xlim(0,102)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is having 1 dependent variable(Y) - GDP($ per capita) and 9 independent variables(x)- Phones (per 1000), Birthrate, Infant mortaality(per 1000 births),Agriculture, Service,Literacy,Net migration,Crops,Deathrate.\n",
    "\n",
    "The above regplots are axes level function and the subplots are plotted as a fixed y axis - GDP($ per capita) and changing x-axis with the correalted columns sorted in ascending order. i.e. correaltion is done to gdp.It is plotting all the 9 subplots after 0.4 space within the subplots.It is calculating absolute correaltion to gdp and correaltion to gdp and is ploting the graphs with different colors..\n",
    "\n",
    "marker (.) states that the graphs are plotted with this mark."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GDP ($ per capita)</th>\n",
       "      <th>Phones (per 1000)</th>\n",
       "      <th>Service</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Region</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ASIA (EX. NEAR EAST)</th>\n",
       "      <td>3450.0</td>\n",
       "      <td>75.75</td>\n",
       "      <td>0.4950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BALTICS</th>\n",
       "      <td>11400.0</td>\n",
       "      <td>321.40</td>\n",
       "      <td>0.6660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C.W. OF IND. STATES</th>\n",
       "      <td>3450.0</td>\n",
       "      <td>155.35</td>\n",
       "      <td>0.4595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EASTERN EUROPE</th>\n",
       "      <td>9100.0</td>\n",
       "      <td>296.05</td>\n",
       "      <td>0.5910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LATIN AMER. &amp; CARIB</th>\n",
       "      <td>6300.0</td>\n",
       "      <td>220.40</td>\n",
       "      <td>0.6150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEAR EAST</th>\n",
       "      <td>9250.0</td>\n",
       "      <td>193.60</td>\n",
       "      <td>0.5840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NORTHERN AFRICA</th>\n",
       "      <td>5775.0</td>\n",
       "      <td>125.35</td>\n",
       "      <td>0.4255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NORTHERN AMERICA</th>\n",
       "      <td>29800.0</td>\n",
       "      <td>683.20</td>\n",
       "      <td>0.6840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OCEANIA</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>118.60</td>\n",
       "      <td>0.5710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUB-SAHARAN AFRICA</th>\n",
       "      <td>1300.0</td>\n",
       "      <td>9.70</td>\n",
       "      <td>0.4400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WESTERN EUROPE</th>\n",
       "      <td>27200.0</td>\n",
       "      <td>564.50</td>\n",
       "      <td>0.6915</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     GDP ($ per capita)  Phones (per 1000)  \\\n",
       "Region                                                                       \n",
       "ASIA (EX. NEAR EAST)                             3450.0              75.75   \n",
       "BALTICS                                         11400.0             321.40   \n",
       "C.W. OF IND. STATES                              3450.0             155.35   \n",
       "EASTERN EUROPE                                   9100.0             296.05   \n",
       "LATIN AMER. & CARIB                              6300.0             220.40   \n",
       "NEAR EAST                                        9250.0             193.60   \n",
       "NORTHERN AFRICA                                  5775.0             125.35   \n",
       "NORTHERN AMERICA                                29800.0             683.20   \n",
       "OCEANIA                                          5000.0             118.60   \n",
       "SUB-SAHARAN AFRICA                               1300.0               9.70   \n",
       "WESTERN EUROPE                                  27200.0             564.50   \n",
       "\n",
       "                                     Service  \n",
       "Region                                        \n",
       "ASIA (EX. NEAR EAST)                  0.4950  \n",
       "BALTICS                               0.6660  \n",
       "C.W. OF IND. STATES                   0.4595  \n",
       "EASTERN EUROPE                        0.5910  \n",
       "LATIN AMER. & CARIB                   0.6150  \n",
       "NEAR EAST                             0.5840  \n",
       "NORTHERN AFRICA                       0.4255  \n",
       "NORTHERN AMERICA                      0.6840  \n",
       "OCEANIA                               0.5710  \n",
       "SUB-SAHARAN AFRICA                    0.4400  \n",
       "WESTERN EUROPE                        0.6915  "
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('Region')[['GDP ($ per capita)', 'Phones (per 1000)', 'Service']].median()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " In the above output the medians of GDP,Phones and Service are calculated as per the region as regions are grouped."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "# choose attributes which shows relation\n",
    "x = df[['GDP ($ per capita)','Phones (per 1000)','Service']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.7/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n",
      "/anaconda3/lib/python3.7/site-packages/statsmodels/nonparametric/kde.py:488: RuntimeWarning: invalid value encountered in true_divide\n",
      "  binned = fast_linbin(X, a, b, gridsize) / (delta * nobs)\n",
      "/anaconda3/lib/python3.7/site-packages/statsmodels/nonparametric/kdetools.py:34: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  FAC1 = 2*(np.pi*bw/RANGE)**2\n",
      "/anaconda3/lib/python3.7/site-packages/numpy/core/fromnumeric.py:83: RuntimeWarning: invalid value encountered in reduce\n",
      "  return ufunc.reduce(obj, axis, dtype, out, **passkwargs)\n",
      "/anaconda3/lib/python3.7/site-packages/numpy/core/_methods.py:140: RuntimeWarning: Degrees of freedom <= 0 for slice\n",
      "  keepdims=keepdims)\n",
      "/anaconda3/lib/python3.7/site-packages/numpy/core/_methods.py:132: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  ret = ret.dtype.type(ret / rcount)\n",
      "/anaconda3/lib/python3.7/site-packages/statsmodels/nonparametric/bandwidths.py:20: RuntimeWarning: invalid value encountered in minimum\n",
      "  return np.minimum(np.std(X, axis=0, ddof=1), IQR)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1a1fff3e10>"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640.375x540 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(x, hue=\"GDP ($ per capita)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "hue = \"GDP($ per capita)\" means that the variables in data to map plot aspects to different colors.\n",
    "\n",
    "On the right side GDP($ per capita) are generated and printed with different set of colors and graphs will be scatterplotted as per the three attributes mentioned above with respect to hue as GPD.\n",
    "\n",
    "First graph is GDP plotted with GDP.\n",
    "\n",
    "Second graph is GDP plotted with Phones.\n",
    "\n",
    "Third graph is GDP plotted with Service.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GDP ($ per capita)</th>\n",
       "      <th>Phones (per 1000)</th>\n",
       "      <th>Service</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>GDP ($ per capita)</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.830903</td>\n",
       "      <td>0.532418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Phones (per 1000)</th>\n",
       "      <td>0.830903</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.626184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Service</th>\n",
       "      <td>0.532418</td>\n",
       "      <td>0.626184</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    GDP ($ per capita)  Phones (per 1000)   Service\n",
       "GDP ($ per capita)            1.000000           0.830903  0.532418\n",
       "Phones (per 1000)             0.830903           1.000000  0.626184\n",
       "Service                       0.532418           0.626184  1.000000"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above output is providing us with the correaltions of the columns for all the attributes of x(GDP,Phones,Servoce)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        700.0\n",
       "1       4500.0\n",
       "2       6000.0\n",
       "3       8000.0\n",
       "4      19000.0\n",
       "5       1900.0\n",
       "6       8600.0\n",
       "7      11000.0\n",
       "8      11200.0\n",
       "9       3500.0\n",
       "10     28000.0\n",
       "11     29000.0\n",
       "12     30000.0\n",
       "13      3400.0\n",
       "14     16700.0\n",
       "15     16900.0\n",
       "16      1900.0\n",
       "17     15700.0\n",
       "18      6100.0\n",
       "19     29100.0\n",
       "20      4900.0\n",
       "21      1100.0\n",
       "22     36000.0\n",
       "23      1300.0\n",
       "24      2400.0\n",
       "25      6100.0\n",
       "26      9000.0\n",
       "27      7600.0\n",
       "28     16000.0\n",
       "29     18600.0\n",
       "        ...   \n",
       "197     3300.0\n",
       "198    23400.0\n",
       "199     1000.0\n",
       "200      600.0\n",
       "201     7400.0\n",
       "202     1500.0\n",
       "203     2200.0\n",
       "204     9500.0\n",
       "205     6900.0\n",
       "206     6700.0\n",
       "207     5800.0\n",
       "208     9600.0\n",
       "209     1100.0\n",
       "210     1400.0\n",
       "211     5400.0\n",
       "212    23200.0\n",
       "213    27700.0\n",
       "214    37800.0\n",
       "215    12800.0\n",
       "216     1700.0\n",
       "217     2900.0\n",
       "218     4800.0\n",
       "219     2500.0\n",
       "220    17200.0\n",
       "221     3700.0\n",
       "222      800.0\n",
       "223     5550.0\n",
       "224      800.0\n",
       "225      800.0\n",
       "226     1900.0\n",
       "Name: GDP ($ per capita), Length: 227, dtype: float64"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['GDP ($ per capita)']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above output is displaying all the values of GDP ($ per capita)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "gdp_no_nan= df['GDP ($ per capita)'][~np.isnan(df['GDP ($ per capita)'])]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above will provide us with the value of gdp_no_man as data value of GDP multiplied by the negation of the boolean result of the GDP .\n",
    "\n",
    "np.isnan - will test element-wise for NaN and return result as a boolean array."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        700.0\n",
       "1       4500.0\n",
       "2       6000.0\n",
       "3       8000.0\n",
       "4      19000.0\n",
       "5       1900.0\n",
       "6       8600.0\n",
       "7      11000.0\n",
       "8      11200.0\n",
       "9       3500.0\n",
       "10     28000.0\n",
       "11     29000.0\n",
       "12     30000.0\n",
       "13      3400.0\n",
       "14     16700.0\n",
       "15     16900.0\n",
       "16      1900.0\n",
       "17     15700.0\n",
       "18      6100.0\n",
       "19     29100.0\n",
       "20      4900.0\n",
       "21      1100.0\n",
       "22     36000.0\n",
       "23      1300.0\n",
       "24      2400.0\n",
       "25      6100.0\n",
       "26      9000.0\n",
       "27      7600.0\n",
       "28     16000.0\n",
       "29     18600.0\n",
       "        ...   \n",
       "197     3300.0\n",
       "198    23400.0\n",
       "199     1000.0\n",
       "200      600.0\n",
       "201     7400.0\n",
       "202     1500.0\n",
       "203     2200.0\n",
       "204     9500.0\n",
       "205     6900.0\n",
       "206     6700.0\n",
       "207     5800.0\n",
       "208     9600.0\n",
       "209     1100.0\n",
       "210     1400.0\n",
       "211     5400.0\n",
       "212    23200.0\n",
       "213    27700.0\n",
       "214    37800.0\n",
       "215    12800.0\n",
       "216     1700.0\n",
       "217     2900.0\n",
       "218     4800.0\n",
       "219     2500.0\n",
       "220    17200.0\n",
       "221     3700.0\n",
       "222      800.0\n",
       "223     5550.0\n",
       "224      800.0\n",
       "225      800.0\n",
       "226     1900.0\n",
       "Name: GDP ($ per capita), Length: 227, dtype: float64"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdp_no_nan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above output is displaying all the values of gdp_no_man calculated above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a2247fd68>"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#checking distribution of literacy of the world\n",
    "sns.distplot(np.array(gdp_no_nan))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above dist plot is as per the array of gdp_no_man as the line plotted is having the lowest lowest value is -10000 and the highest is towards 6000.On the x-axis there is GDP ($ per capita) and on the y-axis is the Literacy. The graph is checking the distribution of literacy of the world.The highest peak in the graph is at x-axis = 0 and y-axis near to 0.000006."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a2892f128>"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#checking distribution of literacy of the world\n",
    "sns.distplot(np.array(df['Phones (per 1000)']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above dist plot is as per the array of Phones(per 1000) as the line plotted is having the lowest lowest value is -200 and the highest is 1200.On the x-axis there is GDP ($ per capita) and on the y-axis is the Literacy. The graph is checking the distribution of literacy of the world.The highest peak in the graph is at x-axis = 0 and y-axis near to 0.0021."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a28488908>"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(np.array(df['Service']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above dist plot is as per the array of Service as the line plotted is having the lowest value is 0.0 and the highest is 1.0.On the x-axis there is GDP ($ per capita) and on the y-axis is the Literacy. The graph is checking the distribution of literacy of the world.The highest peak in the graph is at x-axis near to 0.6 and y-axis near to 2.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a28cc4780>"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(np.array(df['GDP ($ per capita)']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "sns.boxplot - It will draw a box plot to show distributions with respect to the GDP ($ per capita).\n",
    "\n",
    "np.array - It will return an array as per the data frame GDP ($ per capita).\n",
    "\n",
    "The above boxplot is created by taking the array of the DataFrame GDP ($ per capita).The GDP is displayed between its Minimum (0) and Maximum (37000) having Median (5000)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a29239080>"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(np.array(df['Phones (per 1000)']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "sns.boxplot - It will draw a box plot to show distributions with respect to the Phones (per 1000).\n",
    "\n",
    "np.array - It will return an array as per the data frame Phones (per 1000).\n",
    "\n",
    "The above boxplot is created by taking the array of the DataFrame Phones (per 1000).The Phones is displayed between its Minimum (0) and Maximum (900) having Median (198)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a2849b240>"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
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     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(np.array(df['Service']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "sns.boxplot - It will draw a box plot to show distributions with respect to the Service.\n",
    "\n",
    "np.array - It will return an array as per the data frame Service.\n",
    "\n",
    "The above boxplot is created by taking the array of the DataFrame Service.The Service is displayed between its Minimum (0.05) and Maximum (0.98) having Median (0.6)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "\n",
    "I would like to summarize that I learned the fundamental concepts of machine learning from this assignment that are applicable in real life models. Those concepts helped me to visualize the data before applying any machine learning algorithm on it and helped me to understand the relation between the attributes in dataset. By visualizing different plots like barplot, distplot I get to know the different plotting libraries like Seaborn, Matplotlib, which helped us to understand our data in more subtle way. \n",
    "This assignment also helped me to understand the data preprocessing part which is equally important as implementing the algorithm part. In this part I learned about different methods which helped me in understanding more about the attributes of our data. And another important library I learned was impute in sklearn. Its SimpleImputer helped in dealing with the missing values in our dataset in some ways.                                                                \n",
    "#### Hypothesis:\n",
    "There are many predictors in dataset that could contribute in predicting GDP. But according me, Services, Literacy, population could be predictors for predicting the GDP per capita. My thought was that with the increase in Services and Literacy rate, there would be increase in GDP per capita as well. And with decrease in the population, GDP per capita might get increase. \n",
    "\n",
    "#### Findings: \n",
    "After visualizing the different plots for the data, I observed that the hypothesis I made was true. We can analyze through the Heat Map, subplot that the predictors such as Literacy, Services has good correlation (>0.5) with the GDP ($ per capita), which means with the increase in these 2 factors, there is significant chance of increasing the GDP. We can observe from subplot of Literacy rate with GDP that Countries with Literacy rate near to 100 percent has very high chance of more GDP per capita. While on the other hand, Population is having a negative correlation (-0.04) with the GDP that means GDP might get decrease with the increase in population.\n",
    "\n",
    "But I have also found that apart from above predictors, there are some other attributes which can affect the GDP. We can observe from subplot that as the number of Phones increases, there was increase in GDP per capita. And this trend can also be observed from the correlation value between Phone and GDP (>.80). And some negative trends can be seen with attributes like Infant Mortality Rate and Birth Rate. For countries having birth rate between 10 and 20 the GDP per capita is more. Similarly, countries with Infant Mortality Rate less than 25 per 1000 has high value of GDP per capita.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Contributions \n",
    "\n",
    "\n",
    "I completed my assignment independently and I encountered 5 errors in the code out of 35 inputs.The errors were in the distplot,boxplot,pairplot,heatmaps and i described all the functions with their uses and explained them.\n",
    "They all were facing the common issue. \n",
    "\n",
    "There were null values in the code and due to which the graphs were not getting plotted.So, there are two ways to deal with this code:                                        \n",
    "1: Remove all the null values if it is not making a significant change.                                               \n",
    "2: Replace all the null values with the mean,median of the appropriate column so it will plot the graph.\n",
    "\n",
    "Below is the code added in the assignment:\n",
    "\n",
    "imputer = SimpleImputer(missing_values=np.nan, strategy=\"median\")                                                     \n",
    "imputer = imputer.fit(df.iloc[:,2:])                                                           \n",
    "df.iloc[:,2:] = imputer.transform(df.iloc[:,2:])\n",
    "\n",
    "#df.head()\n",
    "\n",
    "\n",
    "So,I contributed\n",
    "\n",
    "By Own: 40%                                                                                                           \n",
    "By External source: 20%                                                                                               \n",
    "Provided  by the professor : 40%\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  Citations\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://pandas.pydata.org/pandas-docs/stable/reference/\n",
    "\n",
    "https://docs.scipy.org/doc/numpy-1.15.0/reference/generated/\n",
    "\n",
    "https://seaborn.pydata.org/api.html\n",
    "\n",
    "https://scikit-learn.org/stable/modules/classes.html#module-sklearn.preprocessing\n",
    "\n",
    "https://scikit-learn.org/stable/modules/impute.html"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  License\n",
    "\n",
    "Must have a license such as the MIT License [https://opensource.org/licenses/MIT]( https://opensource.org/licenses/MIT)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Copyright 2019 Newzy Sharma \n",
    "\n",
    "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated \n",
    "documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the \n",
    "rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit\n",
    "persons to whom the Software is furnished to do so, subject to the following conditions:\n",
    "\n",
    "The above copyright notice and this permission notice shall be included in all copies or substantial portions of the \n",
    "Software.\n",
    "\n",
    "THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE \n",
    "WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR \n",
    "COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR \n",
    "OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."
   ]
  }
 ],
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