{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "___\n",
    "\n",
    "<a href='http://www.pieriandata.com'><img src='../Pierian_Data_Logo.png'/></a>\n",
    "___\n",
    "<center><em>Copyright by Pierian Data Inc.</em></center>\n",
    "<center><em>For more information, visit us at <a href='http://www.pieriandata.com'>www.pieriandata.com</a></em></center>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CIA Country Analysis and Clustering\n",
    "\n",
    "\n",
    "Source: All these data sets are made up of data from the US government. \n",
    "https://www.cia.gov/library/publications/the-world-factbook/docs/faqs.html\n",
    "\n",
    "## Goal: \n",
    "\n",
    "### Gain insights into similarity between countries and regions of the world by experimenting with different cluster amounts. What do these clusters represent? *Note: There is no 100% right answer, make sure to watch the video for thoughts.*\n",
    "\n",
    "----\n",
    "\n",
    "## Imports and Data\n",
    "\n",
    "**TASK: Run the following cells to import libraries and read in data.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 701,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 702,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('../DATA/CIA_Country_Facts.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploratory Data Analysis\n",
    "\n",
    "**TASK: Explore the rows and columns of the data as well as the data types of the columns.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 703,
   "metadata": {},
   "outputs": [],
   "source": [
    "# CODE HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 704,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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": 704,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 705,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 227 entries, 0 to 226\n",
      "Data columns (total 20 columns):\n",
      " #   Column                              Non-Null Count  Dtype  \n",
      "---  ------                              --------------  -----  \n",
      " 0   Country                             227 non-null    object \n",
      " 1   Region                              227 non-null    object \n",
      " 2   Population                          227 non-null    int64  \n",
      " 3   Area (sq. mi.)                      227 non-null    int64  \n",
      " 4   Pop. Density (per sq. mi.)          227 non-null    float64\n",
      " 5   Coastline (coast/area ratio)        227 non-null    float64\n",
      " 6   Net migration                       224 non-null    float64\n",
      " 7   Infant mortality (per 1000 births)  224 non-null    float64\n",
      " 8   GDP ($ per capita)                  226 non-null    float64\n",
      " 9   Literacy (%)                        209 non-null    float64\n",
      " 10  Phones (per 1000)                   223 non-null    float64\n",
      " 11  Arable (%)                          225 non-null    float64\n",
      " 12  Crops (%)                           225 non-null    float64\n",
      " 13  Other (%)                           225 non-null    float64\n",
      " 14  Climate                             205 non-null    float64\n",
      " 15  Birthrate                           224 non-null    float64\n",
      " 16  Deathrate                           223 non-null    float64\n",
      " 17  Agriculture                         212 non-null    float64\n",
      " 18  Industry                            211 non-null    float64\n",
      " 19  Service                             212 non-null    float64\n",
      "dtypes: float64(16), int64(2), object(2)\n",
      "memory usage: 35.6+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 706,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Population</th>\n",
       "      <td>227.0</td>\n",
       "      <td>2.874028e+07</td>\n",
       "      <td>1.178913e+08</td>\n",
       "      <td>7026.000</td>\n",
       "      <td>437624.00000</td>\n",
       "      <td>4786994.000</td>\n",
       "      <td>1.749777e+07</td>\n",
       "      <td>1.313974e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Area (sq. mi.)</th>\n",
       "      <td>227.0</td>\n",
       "      <td>5.982270e+05</td>\n",
       "      <td>1.790282e+06</td>\n",
       "      <td>2.000</td>\n",
       "      <td>4647.50000</td>\n",
       "      <td>86600.000</td>\n",
       "      <td>4.418110e+05</td>\n",
       "      <td>1.707520e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pop. Density (per sq. mi.)</th>\n",
       "      <td>227.0</td>\n",
       "      <td>3.790471e+02</td>\n",
       "      <td>1.660186e+03</td>\n",
       "      <td>0.000</td>\n",
       "      <td>29.15000</td>\n",
       "      <td>78.800</td>\n",
       "      <td>1.901500e+02</td>\n",
       "      <td>1.627150e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Coastline (coast/area ratio)</th>\n",
       "      <td>227.0</td>\n",
       "      <td>2.116533e+01</td>\n",
       "      <td>7.228686e+01</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.10000</td>\n",
       "      <td>0.730</td>\n",
       "      <td>1.034500e+01</td>\n",
       "      <td>8.706600e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Net migration</th>\n",
       "      <td>224.0</td>\n",
       "      <td>3.812500e-02</td>\n",
       "      <td>4.889269e+00</td>\n",
       "      <td>-20.990</td>\n",
       "      <td>-0.92750</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9.975000e-01</td>\n",
       "      <td>2.306000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Infant mortality (per 1000 births)</th>\n",
       "      <td>224.0</td>\n",
       "      <td>3.550696e+01</td>\n",
       "      <td>3.538990e+01</td>\n",
       "      <td>2.290</td>\n",
       "      <td>8.15000</td>\n",
       "      <td>21.000</td>\n",
       "      <td>5.570500e+01</td>\n",
       "      <td>1.911900e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDP ($ per capita)</th>\n",
       "      <td>226.0</td>\n",
       "      <td>9.689823e+03</td>\n",
       "      <td>1.004914e+04</td>\n",
       "      <td>500.000</td>\n",
       "      <td>1900.00000</td>\n",
       "      <td>5550.000</td>\n",
       "      <td>1.570000e+04</td>\n",
       "      <td>5.510000e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Literacy (%)</th>\n",
       "      <td>209.0</td>\n",
       "      <td>8.283828e+01</td>\n",
       "      <td>1.972217e+01</td>\n",
       "      <td>17.600</td>\n",
       "      <td>70.60000</td>\n",
       "      <td>92.500</td>\n",
       "      <td>9.800000e+01</td>\n",
       "      <td>1.000000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Phones (per 1000)</th>\n",
       "      <td>223.0</td>\n",
       "      <td>2.360614e+02</td>\n",
       "      <td>2.279918e+02</td>\n",
       "      <td>0.200</td>\n",
       "      <td>37.80000</td>\n",
       "      <td>176.200</td>\n",
       "      <td>3.896500e+02</td>\n",
       "      <td>1.035600e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arable (%)</th>\n",
       "      <td>225.0</td>\n",
       "      <td>1.379711e+01</td>\n",
       "      <td>1.304040e+01</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3.22000</td>\n",
       "      <td>10.420</td>\n",
       "      <td>2.000000e+01</td>\n",
       "      <td>6.211000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Crops (%)</th>\n",
       "      <td>225.0</td>\n",
       "      <td>4.564222e+00</td>\n",
       "      <td>8.361470e+00</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.19000</td>\n",
       "      <td>1.030</td>\n",
       "      <td>4.440000e+00</td>\n",
       "      <td>5.068000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other (%)</th>\n",
       "      <td>225.0</td>\n",
       "      <td>8.163831e+01</td>\n",
       "      <td>1.614083e+01</td>\n",
       "      <td>33.330</td>\n",
       "      <td>71.65000</td>\n",
       "      <td>85.700</td>\n",
       "      <td>9.544000e+01</td>\n",
       "      <td>1.000000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Climate</th>\n",
       "      <td>205.0</td>\n",
       "      <td>2.139024e+00</td>\n",
       "      <td>6.993968e-01</td>\n",
       "      <td>1.000</td>\n",
       "      <td>2.00000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>3.000000e+00</td>\n",
       "      <td>4.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Birthrate</th>\n",
       "      <td>224.0</td>\n",
       "      <td>2.211473e+01</td>\n",
       "      <td>1.117672e+01</td>\n",
       "      <td>7.290</td>\n",
       "      <td>12.67250</td>\n",
       "      <td>18.790</td>\n",
       "      <td>2.982000e+01</td>\n",
       "      <td>5.073000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Deathrate</th>\n",
       "      <td>223.0</td>\n",
       "      <td>9.241345e+00</td>\n",
       "      <td>4.990026e+00</td>\n",
       "      <td>2.290</td>\n",
       "      <td>5.91000</td>\n",
       "      <td>7.840</td>\n",
       "      <td>1.060500e+01</td>\n",
       "      <td>2.974000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agriculture</th>\n",
       "      <td>212.0</td>\n",
       "      <td>1.508443e-01</td>\n",
       "      <td>1.467980e-01</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.03775</td>\n",
       "      <td>0.099</td>\n",
       "      <td>2.210000e-01</td>\n",
       "      <td>7.690000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Industry</th>\n",
       "      <td>211.0</td>\n",
       "      <td>2.827109e-01</td>\n",
       "      <td>1.382722e-01</td>\n",
       "      <td>0.020</td>\n",
       "      <td>0.19300</td>\n",
       "      <td>0.272</td>\n",
       "      <td>3.410000e-01</td>\n",
       "      <td>9.060000e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Service</th>\n",
       "      <td>212.0</td>\n",
       "      <td>5.652830e-01</td>\n",
       "      <td>1.658410e-01</td>\n",
       "      <td>0.062</td>\n",
       "      <td>0.42925</td>\n",
       "      <td>0.571</td>\n",
       "      <td>6.785000e-01</td>\n",
       "      <td>9.540000e-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    count          mean           std  \\\n",
       "Population                          227.0  2.874028e+07  1.178913e+08   \n",
       "Area (sq. mi.)                      227.0  5.982270e+05  1.790282e+06   \n",
       "Pop. Density (per sq. mi.)          227.0  3.790471e+02  1.660186e+03   \n",
       "Coastline (coast/area ratio)        227.0  2.116533e+01  7.228686e+01   \n",
       "Net migration                       224.0  3.812500e-02  4.889269e+00   \n",
       "Infant mortality (per 1000 births)  224.0  3.550696e+01  3.538990e+01   \n",
       "GDP ($ per capita)                  226.0  9.689823e+03  1.004914e+04   \n",
       "Literacy (%)                        209.0  8.283828e+01  1.972217e+01   \n",
       "Phones (per 1000)                   223.0  2.360614e+02  2.279918e+02   \n",
       "Arable (%)                          225.0  1.379711e+01  1.304040e+01   \n",
       "Crops (%)                           225.0  4.564222e+00  8.361470e+00   \n",
       "Other (%)                           225.0  8.163831e+01  1.614083e+01   \n",
       "Climate                             205.0  2.139024e+00  6.993968e-01   \n",
       "Birthrate                           224.0  2.211473e+01  1.117672e+01   \n",
       "Deathrate                           223.0  9.241345e+00  4.990026e+00   \n",
       "Agriculture                         212.0  1.508443e-01  1.467980e-01   \n",
       "Industry                            211.0  2.827109e-01  1.382722e-01   \n",
       "Service                             212.0  5.652830e-01  1.658410e-01   \n",
       "\n",
       "                                         min           25%          50%  \\\n",
       "Population                          7026.000  437624.00000  4786994.000   \n",
       "Area (sq. mi.)                         2.000    4647.50000    86600.000   \n",
       "Pop. Density (per sq. mi.)             0.000      29.15000       78.800   \n",
       "Coastline (coast/area ratio)           0.000       0.10000        0.730   \n",
       "Net migration                        -20.990      -0.92750        0.000   \n",
       "Infant mortality (per 1000 births)     2.290       8.15000       21.000   \n",
       "GDP ($ per capita)                   500.000    1900.00000     5550.000   \n",
       "Literacy (%)                          17.600      70.60000       92.500   \n",
       "Phones (per 1000)                      0.200      37.80000      176.200   \n",
       "Arable (%)                             0.000       3.22000       10.420   \n",
       "Crops (%)                              0.000       0.19000        1.030   \n",
       "Other (%)                             33.330      71.65000       85.700   \n",
       "Climate                                1.000       2.00000        2.000   \n",
       "Birthrate                              7.290      12.67250       18.790   \n",
       "Deathrate                              2.290       5.91000        7.840   \n",
       "Agriculture                            0.000       0.03775        0.099   \n",
       "Industry                               0.020       0.19300        0.272   \n",
       "Service                                0.062       0.42925        0.571   \n",
       "\n",
       "                                             75%           max  \n",
       "Population                          1.749777e+07  1.313974e+09  \n",
       "Area (sq. mi.)                      4.418110e+05  1.707520e+07  \n",
       "Pop. Density (per sq. mi.)          1.901500e+02  1.627150e+04  \n",
       "Coastline (coast/area ratio)        1.034500e+01  8.706600e+02  \n",
       "Net migration                       9.975000e-01  2.306000e+01  \n",
       "Infant mortality (per 1000 births)  5.570500e+01  1.911900e+02  \n",
       "GDP ($ per capita)                  1.570000e+04  5.510000e+04  \n",
       "Literacy (%)                        9.800000e+01  1.000000e+02  \n",
       "Phones (per 1000)                   3.896500e+02  1.035600e+03  \n",
       "Arable (%)                          2.000000e+01  6.211000e+01  \n",
       "Crops (%)                           4.440000e+00  5.068000e+01  \n",
       "Other (%)                           9.544000e+01  1.000000e+02  \n",
       "Climate                             3.000000e+00  4.000000e+00  \n",
       "Birthrate                           2.982000e+01  5.073000e+01  \n",
       "Deathrate                           1.060500e+01  2.974000e+01  \n",
       "Agriculture                         2.210000e-01  7.690000e-01  \n",
       "Industry                            3.410000e-01  9.060000e-01  \n",
       "Service                             6.785000e-01  9.540000e-01  "
      ]
     },
     "execution_count": 706,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().transpose()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis\n",
    "\n",
    "Let's create some visualizations. Please feel free to expand on these with your own analysis and charts!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: Create a histogram of the Population column.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 707,
   "metadata": {},
   "outputs": [],
   "source": [
    "# CODE HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 708,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Population', ylabel='Count'>"
      ]
     },
     "execution_count": 708,
     "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.histplot(data=df,x='Population')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: You should notice the histogram is skewed due to a few large countries, reset the X axis to only show countries with less than 0.5 billion people**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 709,
   "metadata": {},
   "outputs": [],
   "source": [
    "#CODE HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 710,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Population', ylabel='Count'>"
      ]
     },
     "execution_count": 710,
     "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.histplot(data=df[df['Population']<500000000],x='Population')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: Now let's explore GDP and Regions. Create a bar chart showing the mean GDP per Capita per region (recall the black bar represents std).**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 711,
   "metadata": {},
   "outputs": [],
   "source": [
    "# CODE HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 712,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2000x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6),dpi=200)\n",
    "sns.barplot(data=df,y='GDP ($ per capita)',x='Region',estimator=np.mean)\n",
    "plt.xticks(rotation=90);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: Create a scatterplot showing the relationship between Phones per 1000 people and the GDP per Capita. Color these points by Region.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 713,
   "metadata": {},
   "outputs": [],
   "source": [
    "#CODE HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 714,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x194e5896160>"
      ]
     },
     "execution_count": 714,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2000x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6),dpi=200)\n",
    "sns.scatterplot(data=df,x='GDP ($ per capita)',y='Phones (per 1000)',hue='Region')\n",
    "plt.legend(loc=(1.05,0.5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: Create a scatterplot showing the relationship between GDP per Capita and Literacy (color the points by Region). What conclusions do you draw from this plot?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 715,
   "metadata": {},
   "outputs": [],
   "source": [
    "#CODE HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 716,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='GDP ($ per capita)', ylabel='Literacy (%)'>"
      ]
     },
     "execution_count": 716,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6),dpi=200)\n",
    "sns.scatterplot(data=df,x='GDP ($ per capita)',y='Literacy (%)',hue='Region')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: Create a Heatmap of the Correlation between columns in the DataFrame.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 717,
   "metadata": {},
   "outputs": [],
   "source": [
    "#CODE HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 718,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 718,
     "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": [
    "sns.heatmap(df.corr())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: Seaborn can auto perform hierarchal clustering through the clustermap() function. Create a clustermap of the correlations between each column with this function.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 719,
   "metadata": {},
   "outputs": [],
   "source": [
    "# CODE HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 720,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.matrix.ClusterGrid at 0x194e3dc53d0>"
      ]
     },
     "execution_count": 720,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.clustermap(df.corr())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Preparation and Model Discovery\n",
    "\n",
    "Let's now prepare our data for Kmeans Clustering!\n",
    "\n",
    "### Missing Data\n",
    "\n",
    "**TASK: Report the number of missing elements per column.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 721,
   "metadata": {},
   "outputs": [],
   "source": [
    "#CODE HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 722,
   "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                          3\n",
       "Infant mortality (per 1000 births)     3\n",
       "GDP ($ per capita)                     1\n",
       "Literacy (%)                          18\n",
       "Phones (per 1000)                      4\n",
       "Arable (%)                             2\n",
       "Crops (%)                              2\n",
       "Other (%)                              2\n",
       "Climate                               22\n",
       "Birthrate                              3\n",
       "Deathrate                              4\n",
       "Agriculture                           15\n",
       "Industry                              16\n",
       "Service                               15\n",
       "dtype: int64"
      ]
     },
     "execution_count": 722,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: What countries have NaN for Agriculture? What is the main aspect of these countries?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 723,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3            American Samoa\n",
       "4                   Andorra\n",
       "78                Gibraltar\n",
       "80                Greenland\n",
       "83                     Guam\n",
       "134                 Mayotte\n",
       "140              Montserrat\n",
       "144                   Nauru\n",
       "153      N. Mariana Islands\n",
       "171            Saint Helena\n",
       "174    St Pierre & Miquelon\n",
       "177              San Marino\n",
       "208       Turks & Caicos Is\n",
       "221       Wallis and Futuna\n",
       "223          Western Sahara\n",
       "Name: Country, dtype: object"
      ]
     },
     "execution_count": 723,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Agriculture'].isnull()]['Country']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: You should have noticed most of these countries are tiny islands, with the exception of Greenland and Western Sahara. Go ahead and fill any of these countries missing NaN values with 0, since they are so small or essentially non-existant. There should be 15 countries in total you do this for. For a hint on how to do this, recall you can do the following:**\n",
    "\n",
    "    df[df['feature'].isnull()]\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 724,
   "metadata": {},
   "outputs": [],
   "source": [
    "# REMOVAL OF TINY ISLANDS\n",
    "df[df['Agriculture'].isnull()] = df[df['Agriculture'].isnull()].fillna(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: Now check to see what is still missing by counting number of missing elements again per feature:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 725,
   "metadata": {},
   "outputs": [],
   "source": [
    "#CODE HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 726,
   "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                          1\n",
       "Infant mortality (per 1000 births)     1\n",
       "GDP ($ per capita)                     0\n",
       "Literacy (%)                          13\n",
       "Phones (per 1000)                      2\n",
       "Arable (%)                             1\n",
       "Crops (%)                              1\n",
       "Other (%)                              1\n",
       "Climate                               18\n",
       "Birthrate                              1\n",
       "Deathrate                              2\n",
       "Agriculture                            0\n",
       "Industry                               1\n",
       "Service                                1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 726,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: Notice climate is missing for a few countries, but not the Region! Let's use this to our advantage. Fill in the missing Climate values based on the mean climate value for its region.**\n",
    "\n",
    "Hints on how to do this: https://stackoverflow.com/questions/19966018/pandas-filling-missing-values-by-mean-in-each-group\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 727,
   "metadata": {},
   "outputs": [],
   "source": [
    "# CODE HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 728,
   "metadata": {},
   "outputs": [],
   "source": [
    "# https://stackoverflow.com/questions/19966018/pandas-filling-missing-values-by-mean-in-each-group\n",
    "df['Climate'] = df['Climate'].fillna(df.groupby('Region')['Climate'].transform('mean'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: Check again on many elements are missing:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 729,
   "metadata": {},
   "outputs": [],
   "source": [
    "#CODE HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 730,
   "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                          1\n",
       "Infant mortality (per 1000 births)     1\n",
       "GDP ($ per capita)                     0\n",
       "Literacy (%)                          13\n",
       "Phones (per 1000)                      2\n",
       "Arable (%)                             1\n",
       "Crops (%)                              1\n",
       "Other (%)                              1\n",
       "Climate                                0\n",
       "Birthrate                              1\n",
       "Deathrate                              2\n",
       "Agriculture                            0\n",
       "Industry                               1\n",
       "Service                                1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 730,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: It looks like Literacy percentage is missing. Use the same tactic as we did with Climate missing values and fill in any missing Literacy % values with the mean Literacy % of the Region.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 731,
   "metadata": {},
   "outputs": [],
   "source": [
    "#CODE HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 732,
   "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>25</th>\n",
       "      <td>Bosnia &amp; Herzegovina</td>\n",
       "      <td>EASTERN EUROPE</td>\n",
       "      <td>4498976</td>\n",
       "      <td>51129</td>\n",
       "      <td>88.0</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.31</td>\n",
       "      <td>21.05</td>\n",
       "      <td>6100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>215.4</td>\n",
       "      <td>13.60</td>\n",
       "      <td>2.96</td>\n",
       "      <td>83.44</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>8.77</td>\n",
       "      <td>8.27</td>\n",
       "      <td>0.142</td>\n",
       "      <td>0.308</td>\n",
       "      <td>0.550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>Faroe Islands</td>\n",
       "      <td>WESTERN EUROPE</td>\n",
       "      <td>47246</td>\n",
       "      <td>1399</td>\n",
       "      <td>33.8</td>\n",
       "      <td>79.84</td>\n",
       "      <td>1.41</td>\n",
       "      <td>6.24</td>\n",
       "      <td>22000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>503.8</td>\n",
       "      <td>2.14</td>\n",
       "      <td>0.00</td>\n",
       "      <td>97.86</td>\n",
       "      <td>2.826087</td>\n",
       "      <td>14.05</td>\n",
       "      <td>8.70</td>\n",
       "      <td>0.270</td>\n",
       "      <td>0.110</td>\n",
       "      <td>0.620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>Gaza Strip</td>\n",
       "      <td>NEAR EAST</td>\n",
       "      <td>1428757</td>\n",
       "      <td>360</td>\n",
       "      <td>3968.8</td>\n",
       "      <td>11.11</td>\n",
       "      <td>1.60</td>\n",
       "      <td>22.93</td>\n",
       "      <td>600.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>244.3</td>\n",
       "      <td>28.95</td>\n",
       "      <td>21.05</td>\n",
       "      <td>50.00</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>39.45</td>\n",
       "      <td>3.80</td>\n",
       "      <td>0.030</td>\n",
       "      <td>0.283</td>\n",
       "      <td>0.687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>Guernsey</td>\n",
       "      <td>WESTERN EUROPE</td>\n",
       "      <td>65409</td>\n",
       "      <td>78</td>\n",
       "      <td>838.6</td>\n",
       "      <td>64.10</td>\n",
       "      <td>3.84</td>\n",
       "      <td>4.71</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>842.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>8.81</td>\n",
       "      <td>10.01</td>\n",
       "      <td>0.030</td>\n",
       "      <td>0.100</td>\n",
       "      <td>0.870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>Isle of Man</td>\n",
       "      <td>WESTERN EUROPE</td>\n",
       "      <td>75441</td>\n",
       "      <td>572</td>\n",
       "      <td>131.9</td>\n",
       "      <td>27.97</td>\n",
       "      <td>5.36</td>\n",
       "      <td>5.93</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>676.0</td>\n",
       "      <td>9.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>91.00</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>11.05</td>\n",
       "      <td>11.19</td>\n",
       "      <td>0.010</td>\n",
       "      <td>0.130</td>\n",
       "      <td>0.860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>Jersey</td>\n",
       "      <td>WESTERN EUROPE</td>\n",
       "      <td>91084</td>\n",
       "      <td>116</td>\n",
       "      <td>785.2</td>\n",
       "      <td>60.34</td>\n",
       "      <td>2.76</td>\n",
       "      <td>5.24</td>\n",
       "      <td>24800.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>811.3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>9.30</td>\n",
       "      <td>9.28</td>\n",
       "      <td>0.050</td>\n",
       "      <td>0.020</td>\n",
       "      <td>0.930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>Kiribati</td>\n",
       "      <td>OCEANIA</td>\n",
       "      <td>105432</td>\n",
       "      <td>811</td>\n",
       "      <td>130.0</td>\n",
       "      <td>140.94</td>\n",
       "      <td>0.00</td>\n",
       "      <td>48.52</td>\n",
       "      <td>800.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.7</td>\n",
       "      <td>2.74</td>\n",
       "      <td>50.68</td>\n",
       "      <td>46.58</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>30.65</td>\n",
       "      <td>8.26</td>\n",
       "      <td>0.089</td>\n",
       "      <td>0.242</td>\n",
       "      <td>0.668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>Macedonia</td>\n",
       "      <td>EASTERN EUROPE</td>\n",
       "      <td>2050554</td>\n",
       "      <td>25333</td>\n",
       "      <td>80.9</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-1.45</td>\n",
       "      <td>10.09</td>\n",
       "      <td>6700.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>260.0</td>\n",
       "      <td>22.26</td>\n",
       "      <td>1.81</td>\n",
       "      <td>75.93</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>12.02</td>\n",
       "      <td>8.77</td>\n",
       "      <td>0.118</td>\n",
       "      <td>0.319</td>\n",
       "      <td>0.563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>Slovakia</td>\n",
       "      <td>EASTERN EUROPE</td>\n",
       "      <td>5439448</td>\n",
       "      <td>48845</td>\n",
       "      <td>111.4</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.30</td>\n",
       "      <td>7.41</td>\n",
       "      <td>13300.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>220.1</td>\n",
       "      <td>30.16</td>\n",
       "      <td>2.62</td>\n",
       "      <td>67.22</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>10.65</td>\n",
       "      <td>9.45</td>\n",
       "      <td>0.035</td>\n",
       "      <td>0.294</td>\n",
       "      <td>0.672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>Solomon Islands</td>\n",
       "      <td>OCEANIA</td>\n",
       "      <td>552438</td>\n",
       "      <td>28450</td>\n",
       "      <td>19.4</td>\n",
       "      <td>18.67</td>\n",
       "      <td>0.00</td>\n",
       "      <td>21.29</td>\n",
       "      <td>1700.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.4</td>\n",
       "      <td>0.64</td>\n",
       "      <td>2.00</td>\n",
       "      <td>97.36</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>30.01</td>\n",
       "      <td>3.92</td>\n",
       "      <td>0.420</td>\n",
       "      <td>0.110</td>\n",
       "      <td>0.470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>Tuvalu</td>\n",
       "      <td>OCEANIA</td>\n",
       "      <td>11810</td>\n",
       "      <td>26</td>\n",
       "      <td>454.2</td>\n",
       "      <td>92.31</td>\n",
       "      <td>0.00</td>\n",
       "      <td>20.03</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>59.3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>22.18</td>\n",
       "      <td>7.11</td>\n",
       "      <td>0.166</td>\n",
       "      <td>0.272</td>\n",
       "      <td>0.562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>Virgin Islands</td>\n",
       "      <td>LATIN AMER. &amp; CARIB</td>\n",
       "      <td>108605</td>\n",
       "      <td>1910</td>\n",
       "      <td>56.9</td>\n",
       "      <td>9.84</td>\n",
       "      <td>-8.94</td>\n",
       "      <td>8.03</td>\n",
       "      <td>17200.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>652.8</td>\n",
       "      <td>11.76</td>\n",
       "      <td>2.94</td>\n",
       "      <td>85.30</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>13.96</td>\n",
       "      <td>6.43</td>\n",
       "      <td>0.010</td>\n",
       "      <td>0.190</td>\n",
       "      <td>0.800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>West Bank</td>\n",
       "      <td>NEAR EAST</td>\n",
       "      <td>2460492</td>\n",
       "      <td>5860</td>\n",
       "      <td>419.9</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.98</td>\n",
       "      <td>19.62</td>\n",
       "      <td>800.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>145.2</td>\n",
       "      <td>16.90</td>\n",
       "      <td>18.97</td>\n",
       "      <td>64.13</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>31.67</td>\n",
       "      <td>3.92</td>\n",
       "      <td>0.090</td>\n",
       "      <td>0.280</td>\n",
       "      <td>0.630</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Country                               Region  Population  \\\n",
       "25   Bosnia & Herzegovina  EASTERN EUROPE                          4498976   \n",
       "66          Faroe Islands  WESTERN EUROPE                            47246   \n",
       "74             Gaza Strip  NEAR EAST                               1428757   \n",
       "85               Guernsey  WESTERN EUROPE                            65409   \n",
       "99            Isle of Man  WESTERN EUROPE                            75441   \n",
       "104                Jersey  WESTERN EUROPE                            91084   \n",
       "108              Kiribati  OCEANIA                                  105432   \n",
       "123             Macedonia  EASTERN EUROPE                          2050554   \n",
       "185              Slovakia  EASTERN EUROPE                          5439448   \n",
       "187       Solomon Islands  OCEANIA                                  552438   \n",
       "209                Tuvalu  OCEANIA                                   11810   \n",
       "220        Virgin Islands              LATIN AMER. & CARIB          108605   \n",
       "222             West Bank  NEAR EAST                               2460492   \n",
       "\n",
       "     Area (sq. mi.)  Pop. Density (per sq. mi.)  Coastline (coast/area ratio)  \\\n",
       "25            51129                        88.0                          0.04   \n",
       "66             1399                        33.8                         79.84   \n",
       "74              360                      3968.8                         11.11   \n",
       "85               78                       838.6                         64.10   \n",
       "99              572                       131.9                         27.97   \n",
       "104             116                       785.2                         60.34   \n",
       "108             811                       130.0                        140.94   \n",
       "123           25333                        80.9                          0.00   \n",
       "185           48845                       111.4                          0.00   \n",
       "187           28450                        19.4                         18.67   \n",
       "209              26                       454.2                         92.31   \n",
       "220            1910                        56.9                          9.84   \n",
       "222            5860                       419.9                          0.00   \n",
       "\n",
       "     Net migration  Infant mortality (per 1000 births)  GDP ($ per capita)  \\\n",
       "25            0.31                               21.05              6100.0   \n",
       "66            1.41                                6.24             22000.0   \n",
       "74            1.60                               22.93               600.0   \n",
       "85            3.84                                4.71             20000.0   \n",
       "99            5.36                                5.93             21000.0   \n",
       "104           2.76                                5.24             24800.0   \n",
       "108           0.00                               48.52               800.0   \n",
       "123          -1.45                               10.09              6700.0   \n",
       "185           0.30                                7.41             13300.0   \n",
       "187           0.00                               21.29              1700.0   \n",
       "209           0.00                               20.03              1100.0   \n",
       "220          -8.94                                8.03             17200.0   \n",
       "222           2.98                               19.62               800.0   \n",
       "\n",
       "     Literacy (%)  Phones (per 1000)  Arable (%)  Crops (%)  Other (%)  \\\n",
       "25            NaN              215.4       13.60       2.96      83.44   \n",
       "66            NaN              503.8        2.14       0.00      97.86   \n",
       "74            NaN              244.3       28.95      21.05      50.00   \n",
       "85            NaN              842.4         NaN        NaN        NaN   \n",
       "99            NaN              676.0        9.00       0.00      91.00   \n",
       "104           NaN              811.3        0.00       0.00     100.00   \n",
       "108           NaN               42.7        2.74      50.68      46.58   \n",
       "123           NaN              260.0       22.26       1.81      75.93   \n",
       "185           NaN              220.1       30.16       2.62      67.22   \n",
       "187           NaN               13.4        0.64       2.00      97.36   \n",
       "209           NaN               59.3        0.00       0.00     100.00   \n",
       "220           NaN              652.8       11.76       2.94      85.30   \n",
       "222           NaN              145.2       16.90      18.97      64.13   \n",
       "\n",
       "      Climate  Birthrate  Deathrate  Agriculture  Industry  Service  \n",
       "25   4.000000       8.77       8.27        0.142     0.308    0.550  \n",
       "66   2.826087      14.05       8.70        0.270     0.110    0.620  \n",
       "74   3.000000      39.45       3.80        0.030     0.283    0.687  \n",
       "85   3.000000       8.81      10.01        0.030     0.100    0.870  \n",
       "99   3.000000      11.05      11.19        0.010     0.130    0.860  \n",
       "104  3.000000       9.30       9.28        0.050     0.020    0.930  \n",
       "108  2.000000      30.65       8.26        0.089     0.242    0.668  \n",
       "123  3.000000      12.02       8.77        0.118     0.319    0.563  \n",
       "185  3.000000      10.65       9.45        0.035     0.294    0.672  \n",
       "187  2.000000      30.01       3.92        0.420     0.110    0.470  \n",
       "209  2.000000      22.18       7.11        0.166     0.272    0.562  \n",
       "220  2.000000      13.96       6.43        0.010     0.190    0.800  \n",
       "222  3.000000      31.67       3.92        0.090     0.280    0.630  "
      ]
     },
     "execution_count": 732,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Literacy (%)'].isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 733,
   "metadata": {},
   "outputs": [],
   "source": [
    "# https://stackoverflow.com/questions/19966018/pandas-filling-missing-values-by-mean-in-each-group\n",
    "df['Literacy (%)'] = df['Literacy (%)'].fillna(df.groupby('Region')['Literacy (%)'].transform('mean'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: Check again on the remaining missing values:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 734,
   "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                         1\n",
       "Infant mortality (per 1000 births)    1\n",
       "GDP ($ per capita)                    0\n",
       "Literacy (%)                          0\n",
       "Phones (per 1000)                     2\n",
       "Arable (%)                            1\n",
       "Crops (%)                             1\n",
       "Other (%)                             1\n",
       "Climate                               0\n",
       "Birthrate                             1\n",
       "Deathrate                             2\n",
       "Agriculture                           0\n",
       "Industry                              1\n",
       "Service                               1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 734,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: Optional: We are now missing values for only a few countries. Go ahead and drop these countries OR feel free to fill in these last few remaining values with any preferred methodology. For simplicity, we will drop these.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 735,
   "metadata": {},
   "outputs": [],
   "source": [
    "# CODE HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 736,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.dropna()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Feature Preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: It is now time to prepare the data for clustering. The Country column is still a unique identifier string, so it won't be useful for clustering, since its unique for each point. Go ahead and drop this Country column.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 737,
   "metadata": {},
   "outputs": [],
   "source": [
    "#CODE HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 738,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df.drop(\"Country\",axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: Now let's create the X array of features, the Region column is still categorical strings, use Pandas to create dummy variables from this column to create a finalzed X matrix of continuous features along with the dummy variables for the Regions.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 739,
   "metadata": {},
   "outputs": [],
   "source": [
    "#COde here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 740,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = pd.get_dummies(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 741,
   "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>...</th>\n",
       "      <th>Region_BALTICS</th>\n",
       "      <th>Region_C.W. OF IND. STATES</th>\n",
       "      <th>Region_EASTERN EUROPE</th>\n",
       "      <th>Region_LATIN AMER. &amp; CARIB</th>\n",
       "      <th>Region_NEAR EAST</th>\n",
       "      <th>Region_NORTHERN AFRICA</th>\n",
       "      <th>Region_NORTHERN AMERICA</th>\n",
       "      <th>Region_OCEANIA</th>\n",
       "      <th>Region_SUB-SAHARAN AFRICA</th>\n",
       "      <th>Region_WESTERN EUROPE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\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>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\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>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\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>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\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>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\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>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Population  Area (sq. mi.)  Pop. Density (per sq. mi.)  \\\n",
       "0    31056997          647500                        48.0   \n",
       "1     3581655           28748                       124.6   \n",
       "2    32930091         2381740                        13.8   \n",
       "3       57794             199                       290.4   \n",
       "4       71201             468                       152.1   \n",
       "\n",
       "   Coastline (coast/area ratio)  Net migration  \\\n",
       "0                          0.00          23.06   \n",
       "1                          1.26          -4.93   \n",
       "2                          0.04          -0.39   \n",
       "3                         58.29         -20.71   \n",
       "4                          0.00           6.60   \n",
       "\n",
       "   Infant mortality (per 1000 births)  GDP ($ per capita)  Literacy (%)  \\\n",
       "0                              163.07               700.0          36.0   \n",
       "1                               21.52              4500.0          86.5   \n",
       "2                               31.00              6000.0          70.0   \n",
       "3                                9.27              8000.0          97.0   \n",
       "4                                4.05             19000.0         100.0   \n",
       "\n",
       "   Phones (per 1000)  Arable (%)  ...  \\\n",
       "0                3.2       12.13  ...   \n",
       "1               71.2       21.09  ...   \n",
       "2               78.1        3.22  ...   \n",
       "3              259.5       10.00  ...   \n",
       "4              497.2        2.22  ...   \n",
       "\n",
       "   Region_BALTICS                              Region_C.W. OF IND. STATES   \\\n",
       "0                                           0                            0   \n",
       "1                                           0                            0   \n",
       "2                                           0                            0   \n",
       "3                                           0                            0   \n",
       "4                                           0                            0   \n",
       "\n",
       "   Region_EASTERN EUROPE                       Region_LATIN AMER. & CARIB      \\\n",
       "0                                           0                               0   \n",
       "1                                           1                               0   \n",
       "2                                           0                               0   \n",
       "3                                           0                               0   \n",
       "4                                           0                               0   \n",
       "\n",
       "   Region_NEAR EAST                            \\\n",
       "0                                           0   \n",
       "1                                           0   \n",
       "2                                           0   \n",
       "3                                           0   \n",
       "4                                           0   \n",
       "\n",
       "   Region_NORTHERN AFRICA                      \\\n",
       "0                                           0   \n",
       "1                                           0   \n",
       "2                                           1   \n",
       "3                                           0   \n",
       "4                                           0   \n",
       "\n",
       "   Region_NORTHERN AMERICA                     \\\n",
       "0                                           0   \n",
       "1                                           0   \n",
       "2                                           0   \n",
       "3                                           0   \n",
       "4                                           0   \n",
       "\n",
       "   Region_OCEANIA                              \\\n",
       "0                                           0   \n",
       "1                                           0   \n",
       "2                                           0   \n",
       "3                                           1   \n",
       "4                                           0   \n",
       "\n",
       "   Region_SUB-SAHARAN AFRICA                   \\\n",
       "0                                           0   \n",
       "1                                           0   \n",
       "2                                           0   \n",
       "3                                           0   \n",
       "4                                           0   \n",
       "\n",
       "   Region_WESTERN EUROPE                       \n",
       "0                                           0  \n",
       "1                                           0  \n",
       "2                                           0  \n",
       "3                                           0  \n",
       "4                                           1  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 741,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scaling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: Due to some measurements being in terms of percentages and other metrics being total counts (population), we should scale this data first. Use Sklearn to scale the X feature matrics.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 742,
   "metadata": {},
   "outputs": [],
   "source": [
    "#CODE HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 743,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 744,
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler = StandardScaler()\n",
    "scaled_X = scaler.fit_transform(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 745,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.0133285 ,  0.01855412, -0.20308668, ..., -0.31544015,\n",
       "        -0.54772256, -0.36514837],\n",
       "       [-0.21730118, -0.32370888, -0.14378531, ..., -0.31544015,\n",
       "        -0.54772256, -0.36514837],\n",
       "       [ 0.02905136,  0.97784988, -0.22956327, ..., -0.31544015,\n",
       "        -0.54772256, -0.36514837],\n",
       "       ...,\n",
       "       [-0.06726127, -0.04756396, -0.20881553, ..., -0.31544015,\n",
       "        -0.54772256, -0.36514837],\n",
       "       [-0.15081724,  0.07669798, -0.22840201, ..., -0.31544015,\n",
       "         1.82574186, -0.36514837],\n",
       "       [-0.14464933, -0.12356132, -0.2160153 , ..., -0.31544015,\n",
       "         1.82574186, -0.36514837]])"
      ]
     },
     "execution_count": 745,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scaled_X"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating and Fitting Kmeans Model\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: Use a for loop to create and fit multiple KMeans models, testing from K=2-30 clusters. Keep track of the Sum of Squared Distances for each K value, then plot this out to create an \"elbow\" plot of K versus SSD. Optional: You may also want to create a bar plot showing the SSD difference from the previous cluster.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 746,
   "metadata": {},
   "outputs": [],
   "source": [
    "#CODE HERE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 747,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import KMeans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 748,
   "metadata": {},
   "outputs": [],
   "source": [
    "ssd = []\n",
    "\n",
    "for k in range(2,30):\n",
    "    \n",
    "    model = KMeans(n_clusters=k)\n",
    "    \n",
    "    \n",
    "    model.fit(scaled_X)\n",
    "    \n",
    "    #Sum of squared distances of samples to their closest cluster center.\n",
    "    ssd.append(model.inertia_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 749,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, ' Sum of Squared Distances')"
      ]
     },
     "execution_count": 749,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+kPA3h7sfm5SIJDIjj/kct184mGqHKXNX773SSnWqRCSuvqunLgx+xld/x8uGfD154UjUrh7Rj8nFJdz63HzKKmLDVPE6VYASh0gLl3B4yt1XBFdQnePuP3L3+cFtPHBu84UozW3i1MV7E0ZcWUUVE6cujigiEUkVYeY0zMxG1HjwxZCvkzSlOlUikkiD270C44C/mFmn4HEp8K2kRSSR65mfV2dF3ET1q0Sk5Wiwx+Dus9x9KDAUGOruw9x9dvJDk6jUVafKgO+dNSCagEQkZTSYNMzscDN7GHjK3bea2WAzG9cMsUlERg0v4Fejh1CQn4cBXdu15uT+Xbj0uF5RhyYiEQszPPVX4BHgtuDxx8Df2LfjnmSgRHWqyvZUkdf6wGq5ItIyhJnQ7ubuTwPVAO5eCWjJcAu0dutuzrv3LZ4uWhV1KCISkTBJY6eZdSVY6GdmJwNbkxqVpKRu7VvTp0tbbnt+PjOXbYo6HBGJQJik8QNgCnCkmb0DPAp8N6lRSUpqlZ3F7792HH26tOX6x2exfOPOqEMSkWZWb9Iws2zg9OD2ReA64Bh3r2tzJmkBOuXl8JerT8CAb036gK27KqIOSUSaUb1Jw92rgDHuXunuC9z9Q3fXb4kW7oiu7fjjN47nsA5tqKyujjocEWlGYa6eesfMfk/siqm94xFaq9GyndS/K09+52TMjKpqJ8vAzKIOS0SSLEzSGBb8vLNGmwNnNXk0klbMjJ3llYz6w9us317OtrJKVcQVyXANJg13P7M5ApH09I8P17J0w07i22+oIq5IZgvT08DMvgIcA+TG29z9zsSvkJbi19M+pvZ+TfGKuEoaIpknTBmRPwJXELvM1oDLgCOSHJekCVXEFWlZwqzT+KK7XwVscfefAacAn09uWJIuElW+VUVckcwUJmnE/2TcZWY9gQqgR/JCknRSV0XcvJxs/vPcz7NxR3lEUYlIsoRJGi+ZWT4wEZgNLAeeTGJMkkZqV8QtyM/jV6OHsHJzGRfc+y+tGhfJMObuDR8VP9isDZDr7ilde6qwsNCLioqiDqNFW7x2O2P+NJPcVln87bpT6N2lbdQhiUgDzGyWuxfWd0yYifCr4jdiE+KXBPdFEhr0uQ48Pu4kdu6pYsyfZmpiXCRDhBmeOqHG7TTgDuDiJMYkGWJwz448Pu4ktpZV8M2H36OiSiVHRNJdmMV9+1W0DeY3nkpWQJJZhvTqxKPfOpF128rJyQ7zN4qIpLJQi/tq2Qn0a+pAJHMN79N57/3XF6+nZMsuHnxjGatLy1R2RCTNNJg0zOxFgg2YiA1nDQaeTmZQkpm27NzD9Y8WsafK9/4PpbIjIuklTE/j1zXuVwIr3P2zJMUjGaxzu9a0z81h0849+7Wr7IhI+ggzp/FmcwQiLcPmWgkjTldXiaSHMJfcbjezbXXctpvZtnpel2tm75vZXDNbYGY/C9r7mdl7ZrbEzP5mZq2D9jbB4yXB831rvNetQftiMxvZBOctEVHZEZH0FuZylt8B44ECoBdwC/A7d+/g7h3reV05cJa7DyW2J8d5ZnYycDdwj7sPALYA44LjxxGrbzUAuCc4DjMbDFxJrMruecADwTa0koYSlR25eeSgiCISkcYIkzQudvcH3H27u29z9weBSxp6kcfsCB7mBLf45k3PBO2TgFHB/UuCxwTPn22xreAuAZ5y93J3/xRYApwYIm5JQXWVHfn+lwfw+cM7RB2aiIQQZiJ8p5l9ndjaDAfGUGPb1/oEPYJZwADgD8BSoNTdK4NDPiPWgyH4uQrA3SvNbCvQNWifWeNta76m5mddC1wL0KdPnzDhSURGDS/YO+ldXe2cd+9bPDpjJVNuHEHX9m0ijk5E6hOmp/E14HJgHbCe2H4aXwvz5u5e5e7DiA1rnQgcdXBhhvqsh9y90N0Lu3fvnqyPkSaWlWX85rJhbNxRzo1PFGvVuEiKazBpuPtyd7/E3bsFt1HuvrwxH+LupcDrxPbiyDezeA+nF1AS3C8BegMEz3cCNtVsr+M1kgGG9OrEr0YPYcayTfzylUVRhyMi9UiYNMzsO2Y2MLhvZvYXM9tqZvPM7LiG3tjMugclRzCzPOAcYBGx5PFvwWFjgReC+1OCxwTPT/dYCd4pwJXB1VX9gIHA+408T0lxo4/rxbhT+/HIO8v5x4K1UYcjIgnUN6dxE/DX4P4YYCjQHxgO3EuseGF9egCTgnmNLOBpd3/JzBYCT5nZL4Bi4OHg+IeBx8xsCbCZ2BVTuPsCM3saWEhsceEN7l7VqLOUtHDr+UfRo1Mupw/S8KJIqkq4n4aZzQnmIzCzJ4D33P3e4PFsd2+wtxEV7aeR/rbuqqCiuppumhgXaTaHup9GtZn1MLNc4GzgnzWe00osSZqqaueKh2bw74/PYk+lJsZFUkl9w1M/BYqAbGCKuy8AMLPTgWXNEJu0UNlZxg1nDuC7TxZzzSPvsXxTmSriiqSIhEkjmH84Aujg7ltqPFVEbAc/kaS5aGhPJheX8NpH6/e2qSKuSPTqveTW3StrJQzcfWeNld4iSbNo7YGlzeIVcUUkGtpKTVLWmtLddbarIq5IdOpbpzEi+KnLVyQS9VW+ve35+XxYsrUZoxERqL+ncV/wc0ZzBCJSW10VcVu3yuL4I/J5ZtZnXHj/21x4/7948+MNAEwuLmHEhOn0G/8yIyZMZ3KxCgeINLX6rp6qMLOHgAIzu6/2k+7+veSFJbJvsnvi1MUHXD21dVcFL8wt4cn3V1Fd7UwuLmH8s/PYHVyiq0lzkeSob3FfN+DLxPa1+Gnt59190gEvShFa3NdyxP//PfXu1ympY66jID+Pd8af1dxhiaSlMIv76rvkdiOxch+L3H1uk0cn0gRiW64knhzXpLlI0wpz9dQmM3vezNYHt2fNrFfSIxNphEST5t076DoOkaYUJmk8QqzSbM/g9mLQJpIy6po0zzK48awBEUUkkpnCJI3D3P2RYKFfpbv/FVAZUkkpdW0j+9vLh3HVKX2pqKpm7qrSqEMUyQhhtnvdaGbfAJ4MHo8htjmSSEqpuY1sTfdPX8KDbyzh3iuHc8GQHhFEJpI5wvQ0vkVsu9e1wBpiGyRdk8ygRJrSuFP7cWyvfG58YjZPf7Aq6nBE0lqDPQ13XwFc3AyxiCRFp7wcHht3Itc9NosfPTuPbbsr+PZp/aMOSyQtqfaUtAhtW7fiz2MLOf8Ln+OeaR+zbtturSAXOQhh5jREMkKbVtncP2Y4yzbuZMbSTdz63HzKKmI7B2sFuUg46mlIi9IqO4vPH96BiVMX700YcSq7LtKwBnsaZpYPXAX0rXm8ak9JOtMKcpGDE2Z46hVgJjAf0IbNkhF65ufVWauqvnLsIhIuaeS6+w+SHolIM7p55KD95jTirju9X0QRiaSHMEnjMTP7DvASUB5vdPfNSYtKJMlql10/vFMu5ww+nKtOiSUNd99bDFFE9gmTNPYAE4HbgHgddQd0obuktUQryN/6eAMPvLGE+8YM57AOuRFEJpK6wlw99UNggLv3dfd+wU0JQzLWjvJK5qwq5aL736Z45ZaowxFJKWF6GkuAXckORCRVXDCkB327tuO6x4u44n9mcuclx5Cbk13nDoIiLU2YpLETmGNmr7P/nIYuuZWMNbhnR1688VS++2Qx45+bT+vsLPZUaStZkTDDU5OBu4B3gVk1biIZLb9ta/56zYl0bpuzN2HEaSGgtFRhCham7F7gIsmWnWWU7qqo87mS0jI27Sina3vtDigtR5gV4Z+y76qpvTQZLi1FooWAAMf/4p/ce+UwLhlWwO6KKrLMeGX+Gs1/SMYKM6dRWON+LnAZ0CU54YiknroWAublZHH9GUeShXFcn84AvDRvDT9+bh6V1U518GeW5j8k04QZnqq9S9/vzGwW8NPkhCSSWmovBEzUexh4WHtaZWexp6ruQohKGpIJwgxPHVfjYRaxnodKqkuLkmghYE1De+dTtqeqzudWl5axp7Ka1q1UWFrSW5hf/r+pcb8SWE5s+1cRqSXR/MfhHXMZcfd0xpzYh2+f1o+OuTkRRCdy6MIMT53ZHIGIZIK65z+yue70/hQt38J9r33CpHeXc/3pR3L1F/sydcFaTZpLWjH3Ay6Mij1hdhEwL9gjHDP7KfBVYAVwk7t/2mxRNlJhYaEXFRVFHYa0UJOLSxImgg9LtvKbfyzm9cUb6NAmm4pqZ3fFvjUgeTnZ/Gr0ECUOiYSZzXL3wnqPqSdpzANOdvddZnYh8FtgDDAcuMzdRzZ1wE1FSUNSXdHyzXzrrx+wbXflAc8V5OfxzvizIohKWrowSaO+WTl393jNqdHAw+4+y93/DHRvqiBFWqLCvl3YXkfCAO0eKKmtvqRhZtbezLKAs4HXajzXYL1oM+ttZq+b2UIzW2BmNwXtXcxsmpl9EvzsHP8wM7vPzJaY2byaV22Z2djg+E/MbOzBnapIakm0S6ADox94h8VrtzdvQCIh1Jc0fgfMAYqARe5eBGBmw4E1Id67Evihuw8GTgZuMLPBwHjgNXcfSCwRjQ+OPx8YGNyuBR4MPq8LcDtwEnAicHs80Yiks5tHDiIvJ3u/ttycLEYN60lZRTXd2rcGYPbKLSxYvRWIzZeMmDCdfuNfZsSE6UwuLmn2uKVlS3j1lLv/xcymAocBc2s8tRa4pqE3dvc1BMnF3beb2SKgALgEOCM4bBLwBnBL0P6oxyZZZppZvpn1CI6dFt8p0MymAecBT4Y+S5EUFHbR4MRXFzNj2SZ6d85j7bbdVFTF5iG12lyiUO8lt+5eApTUagvTy9iPmfUlNoH+HnB4jfdYCxwe3C8AVtV42WdBW6L22p9xLbEeCn369GlsiCKRCLNo8MFvHMfzxSXc9fIiKqv3v3Alttr8IyUNaTZJX55qZu2BZ4Hvu/u2ms8FvYq6L99qJHd/yN0L3b2we3fN00vmyG/bmmtG9KOquu5/KiWlu/nOo0U8/PanLFy9jergOA1lSTIktRyImeUQSxj/6+7PBc3rzKyHu68Jhp/WB+0lQO8aL+8VtJWwbzgr3v5GMuMWSUWJVpu3bZ3N4rXbmbZwHQCd8nK44oRePDZj5d5FhhrKkqaStJ6GmRnwMLFJ9N/WeGoKEL8CaizwQo32q4KrqE4GtgbDWFOBc82sczABfm7QJtKi1DVxnpeTzS8vHcJbPzqTd8afxW8vH8q5gw/nhTmr91uVDto4SppGMnsaI4BvAvPNbE7Q9mNgAvC0mY0jtro8XsfqFeAC9u1Jfg2Au282s58DHwTH3RmfFBdpSRqaOC/Iz2P0cb0YfVwv+o1/uc73KCktw92J/U0n0ngJV4SnM60Il5ZuxITpCTeOunhoT+4bM7yZI5J0cKgrwkUkTSVaA3LFCb24aGhPAHbtqWTG0th2OZo0l7C0L4ZIBgqzBuTJ91fx85cWMvCwdqzcXEZ5ZaxwoibNpT5KGiIZqqE1IF8/Kbae6a6XF1L7al7tNiiJaHhKpIXKzclm3Kn9SDStWVJaxspNu+p+Ulos9TREWrhE6z8AvjTxdfp0acupA7tx2oBufHFAN17/aL02jmrBlDREWri6dxvM4vvnfJ7cVtn865MNvFBcwhPvreSywl68NHeNFg22YEoaIi1cQ5PmY7/Yl4qqauasKuW7TxbXuWjw1ufms2XXHkYP70Wntvvvf17fToaSfpQ0RKTBSfOc7CxO6NuFdVt31/l8WUUVP3txIRceG7uc95lZnzFz2SbcnZfmrdGVWRlESUNEQks0/1GQn8tz/28E3Tu0AWD99t28sXg9G3fsOeDYsooq7nplEUf16EC/bu1o02rfehL1SlKfVoSLSGiTi0vqmP/I5lejhxzwy93d6X/rK/WWsc7OMvp2bcvAwzqQl5PFqwvWhXpvSY4wK8LV0xCR0MJuHAVgZgl7Jod1aMNtXzmaT9bt4ON12/l43XZWl5axOxjGiiurqOLOlxZy2sBudG3fZr/n1CuJhnoaIpI0jemZ9Bv/cr29kutO78+t5x+Nu/PHN5dy32ufUFaxL8moV3LoVHtKRCI1angBvxo9hIL8PIxYJd5Ev9h75ufV+R7d2rdm/PlHcdqA2OZqyzbu5O5XF++XMECl35uLhqdEJKnCbGkLidaLZPOTrwze7/Xd2rWp6+UArC4tY9223azfVs7gnh3JztpXAl7DWU1DSUNEUkLY+ZJObXMoSDBX0jM/j+eLS5jwfx/RMbcVJ/fvyilHdmV3RdV+w1m69PfgaU5DRNJOfXMlIwZ0492lG3l3ySbeXbaRVZvrLpEC0DM/l3fHn13n+7fEXkmYOQ0lDRFJS2F/sa/avIvT/vv1hO8zpKATpxzZlR9fcDQAj89cwV0vL2yRk+y65FZEMlbYuZLeXdomHM5q1yab/LY5bNxRvrft9ikLqKpVK16l4vdR0hCRjJdokv2uUQf2HmonjLjVwf7qj89cwbDenTm6RwdaZWe1uKEsJQ0RyXiNWZRY3yT7pxt38l8vLACgbetsCvJz+XTjLiqDRNPQBHsmJBjNaYiI1NDQgsTVpWUUrdjCrOWbeeL9lVRUHfg7tE2rLC4v7E2vznkUdM7j1AHdeGPxhtALHaOiiXARkYMQtkdQ3yr2Tnk5bC2rAODFG0/l+sdn1dmD6dEplxm3HngFV2PiaCqaCBcROQhhJ9kTV/3N453xZ7FtdwUlW8ro160dqxPsjrhm6242bC+ne4c2fFiylfLKao7p2ZFXP1y7X88kVdaWKGmIiBykRBPsN48cBEDH3Bw69ohtSpUowXTKa7W3pPyDby7l5XlraJVlmHHA0FcqXMWl2lMiIgepMbW1bh45iLyc7P3a8nKy+dnFX9j7+PaLBvPQN4/n2i/1r3OuBGI9jn99soFtuyv2a59cXMKICdPpN/5lRkyYzuTikkM/wTpoTkNEpJk0Zo5ixITpdfZM4sxg4GHtufKEPnRp17pJJtk1pyEikkLCzpVA4qGvn150NL07t2P2yi0Ur9xCtTsTpy6uc+/2ZAxlKWmIiKSghtaWnDqw295j73p5UZ3vkWjy/VAoaYiIpKhDvYor0R4lh0IT4SIiaS7RJHv8Kq6mpJ6GiEiaa0yZlEOlpCEikgEaM8l+KDQ8JSIioSlpiIhIaEoaIiISmpKGiIiEpqQhIiKhZWTtKTPbAKyIOo5D1A3YGHUQSZbp56jzS3+Zfo61z+8Id+9e3wsyMmlkAjMraqhwWLrL9HPU+aW/TD/Hgzk/DU+JiEhoShoiIhKakkbqeijqAJpBpp+jzi/9Zfo5Nvr8NKchIiKhqachIiKhKWmIiEhoShopyMyWm9l8M5tjZhmx2bmZ/cXM1pvZhzXaupjZNDP7JPjZOcoYD0WC87vDzEqC73GOmV0QZYyHwsx6m9nrZrbQzBaY2U1Be0Z8h/WcXyZ9h7lm9r6ZzQ3O8WdBez8ze8/MlpjZ38ysdb3vozmN1GNmy4FCd8+YRUVm9iVgB/Cou38haPtvYLO7TzCz8UBnd78lyjgPVoLzuwPY4e6/jjK2pmBmPYAe7j7bzDoAs4BRwNVkwHdYz/ldTuZ8hwa0c/cdZpYDvA3cBPwAeM7dnzKzPwJz3f3BRO+jnoY0C3d/C9hcq/kSYFJwfxKxf6RpKcH5ZQx3X+Pus4P724FFQAEZ8h3Wc34Zw2N2BA9zgpsDZwHPBO0NfodKGqnJgX+Y2SwzuzbqYJLocHdfE9xfCxweZTBJcqOZzQuGr9Jy6KY2M+sLDAfeIwO/w1rnBxn0HZpZtpnNAdYD04ClQKm7VwaHfEYDyVJJIzWd6u7HAecDNwRDHxnNY+OkmTZW+iBwJDAMWAP8JtJomoCZtQeeBb7v7ttqPpcJ32Ed55dR36G7V7n7MKAXcCJwVGPfQ0kjBbl7SfBzPfA8sS83E60LxpLjY8rrI46nSbn7uuAfaTXwJ9L8ewzGwZ8F/tfdnwuaM+Y7rOv8Mu07jHP3UuB14BQg38ziW3/3Akrqe62SRooxs3bBRBxm1g44F/iw/lelrSnA2OD+WOCFCGNpcvFfpoFLSePvMZhEfRhY5O6/rfFURnyHic4vw77D7maWH9zPA84hNnfzOvBvwWENfoe6eirFmFl/Yr0LgFbAE+5+V4QhNQkzexI4g1gp5nXA7cBk4GmgD7FS9pe7e1pOJic4vzOIDWs4sBy4rsb4f1oxs1OBfwHzgeqg+cfExv3T/jus5/zGkDnf4bHEJrqziXUYnnb3O4PfOU8BXYBi4BvuXp7wfZQ0REQkLA1PiYhIaEoaIiISmpKGiIiEpqQhIiKhKWmIiEhoShoiIZnZjhr3LzCzj83siBptfc3sMzPLqvW6OWZ2UoL37FuzMq5IqlPSEGkkMzsbuA84391XxNvdfTmwEjitxrFHAR3c/b3a7yOSjpQ0RBohqAP2J+BCd19axyFPAlfWeHwl8FTQo/iXmc0Obl+s472vNrPf13j8kpmdEdw/18xmBK/9e1AjSaTZKWmIhNeG2Cr2Ue7+UYJjngZG1ajlcwWxRLIeOCcoRHkFsZ5KKGbWDfgJ8OXg9UXE9kAQaXatGj5ERAIVwLvAOGKb1xzA3dcFcxRnm9k6oNLdPzSzTsDvzWwYUAV8vhGfezIwGHgnViKJ1sCMgz4LkUOgpCESXjWxndxeM7Mfu/svExwXH6JaF9wH+I/g8VBiPfzddbyukv17/7nBTwOmufuYQwtf5NBpeEqkEdx9F/AV4OtmNi7BYc8BFxAbhnoqaOsErAlKbH+TWNG42pYDw8wsy8x6s68M90xghJkNgL2VkBvTUxFpMuppiDSSu282s/OAt8xsg7tPqfV8qZnNAD7n7suC5geAZ83sKuBVYGcdb/0O8CmwkFjJ6vj2oxvM7GrgSTNrExz7E+DjJj41kQapyq2IiISm4SkREQlNSUNEREJT0hARkdCUNEREJDQlDRERCU1JQ0REQlPSEBGR0P4/LFLm3SJy11gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(range(2,30),ssd,'o--')\n",
    "plt.xlabel(\"K Value\")\n",
    "plt.ylabel(\" Sum of Squared Distances\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 750,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 750,
     "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": [
    "pd.Series(ssd).diff().plot(kind='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model Interpretation\n",
    "\n",
    "\n",
    "**TASK: What K value do you think is a good choice? Are there multiple reasonable choices? What features are helping define these cluster choices. As this is unsupervised learning, there is no 100% correct answer here. Please feel free to jump to the solutions for a full discussion on this!.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 751,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Nothing to really code here, but choose a K value and see what features \n",
    "# are most correlated to belonging to a particular cluster!\n",
    "\n",
    "# Remember, there is no 100% correct answer here!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-----\n",
    "\n",
    "\n",
    "#### Example Interpretation: Choosing K=3\n",
    "\n",
    "**One could say that there is a significant drop off in SSD difference at K=3 (although we can see it continues to drop off past this). What would an analysis look like for K=3? Let's explore which features are important in the decision of 3 clusters!**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 753,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(n_clusters=3)"
      ]
     },
     "execution_count": 753,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = KMeans(n_clusters=3)\n",
    "model.fit(scaled_X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 754,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2, 0, 0, 0, 1, 2, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 2, 1, 1, 1, 0, 2,\n",
       "       1, 2, 0, 1, 2, 0, 1, 0, 1, 2, 2, 2, 2, 2, 1, 0, 1, 2, 2, 0, 0, 0,\n",
       "       2, 2, 2, 0, 2, 1, 0, 1, 1, 2, 0, 0, 0, 0, 0, 2, 2, 1, 2, 1, 0, 1,\n",
       "       1, 0, 0, 2, 2, 0, 0, 1, 2, 1, 1, 0, 0, 0, 0, 0, 2, 2, 0, 2, 0, 1,\n",
       "       1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 2, 0, 0, 1, 0, 0, 2,\n",
       "       1, 0, 2, 2, 0, 1, 1, 1, 1, 1, 2, 2, 0, 0, 2, 1, 0, 0, 2, 0, 2, 0,\n",
       "       0, 0, 0, 0, 0, 2, 2, 0, 2, 1, 0, 0, 1, 0, 2, 2, 0, 1, 0, 2, 0, 0,\n",
       "       0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 2, 0, 0, 0, 0, 0, 0, 1, 0, 0, 2,\n",
       "       0, 2, 1, 1, 1, 0, 2, 2, 1, 0, 2, 0, 2, 1, 1, 0, 1, 0, 2, 0, 2, 0,\n",
       "       0, 0, 0, 0, 0, 0, 2, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2,\n",
       "       2])"
      ]
     },
     "execution_count": 754,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.labels_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 756,
   "metadata": {},
   "outputs": [],
   "source": [
    "X['K=3 Clusters'] = model.labels_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 757,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Literacy (%)                                 -0.419453\n",
       "Region_LATIN AMER. & CARIB                   -0.377533\n",
       "Region_OCEANIA                               -0.248224\n",
       "Crops (%)                                    -0.245934\n",
       "Phones (per 1000)                            -0.198737\n",
       "Region_C.W. OF IND. STATES                   -0.193384\n",
       "Region_NEAR EAST                             -0.179732\n",
       "Coastline (coast/area ratio)                 -0.158318\n",
       "Region_NORTHERN AFRICA                       -0.151646\n",
       "Service                                      -0.117898\n",
       "Population                                   -0.062404\n",
       "GDP ($ per capita)                           -0.060568\n",
       "Industry                                     -0.048420\n",
       "Area (sq. mi.)                               -0.039735\n",
       "Region_NORTHERN AMERICA                      -0.027789\n",
       "Pop. Density (per sq. mi.)                    0.013816\n",
       "Other (%)                                     0.016429\n",
       "Climate                                       0.024573\n",
       "Region_ASIA (EX. NEAR EAST)                   0.028712\n",
       "Region_BALTICS                                0.035283\n",
       "Region_EASTERN EUROPE                         0.043691\n",
       "Arable (%)                                    0.084553\n",
       "Region_WESTERN EUROPE                         0.109824\n",
       "Net migration                                 0.208539\n",
       "Agriculture                                   0.440815\n",
       "Birthrate                                     0.494413\n",
       "Infant mortality (per 1000 births)            0.614130\n",
       "Region_SUB-SAHARAN AFRICA                     0.670927\n",
       "Deathrate                                     0.727801\n",
       "K=3 Clusters                                  1.000000\n",
       "Name: K=3 Clusters, dtype: float64"
      ]
     },
     "execution_count": 757,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.corr()['K=3 Clusters'].sort_values()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "------------\n",
    "-------------\n",
    "\n",
    "# BONUS CHALLGENGE:\n",
    "## Geographical Model Interpretation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The best way to interpret this model is through visualizing the clusters of countries on a map! **NOTE: THIS IS A BONUS SECTION.  YOU MAY WANT TO JUMP TO THE SOLUTIONS LECTURE FOR A FULL GUIDE, SINCE WE WILL COVER TOPICS NOT PREVIOUSLY DISCUSSED AND BE HAVING A NUANCED DISCUSSION ON PERFORMANCE!**\n",
    "\n",
    "----\n",
    "----\n",
    "\n",
    "**IF YOU GET STUCK, PLEASE CHECK OUT THE SOLUTIONS LECTURE. AS THIS IS OPTIONAL AND COVERS MANY TOPICS NOT SHOWN IN ANY PREVIOUS LECTURE**\n",
    "\n",
    "----\n",
    "----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: Create cluster labels for a chosen K value. Based on the solutions, we believe either K=3 or K=15 are reasonable choices. But feel free to choose differently and explore.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 765,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(n_clusters=15)"
      ]
     },
     "execution_count": 765,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = KMeans(n_clusters=15)\n",
    "    \n",
    "model.fit(scaled_X)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 766,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(n_clusters=3)"
      ]
     },
     "execution_count": 766,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = KMeans(n_clusters=3)\n",
    "    \n",
    "model.fit(scaled_X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TASK: Let's put you in the real world! Your boss just asked you to plot out these clusters on a country level choropleth map, can you figure out how to do this? We won't step by step guide you at all on this, just show you an example result. You'll need to do the following:**\n",
    "\n",
    "1. Figure out how to install plotly library: https://plotly.com/python/getting-started/\n",
    "\n",
    "2. Figure out how to create a geographical choropleth map using plotly: https://plotly.com/python/choropleth-maps/#using-builtin-country-and-state-geometries\n",
    "\n",
    "3. You will need ISO Codes for this. Either use the wikipedia page, or use our provided file for this: **\"../DATA/country_iso_codes.csv\"**\n",
    "\n",
    "4. Combine the cluster labels, ISO Codes, and Country Names to create a world map plot with plotly given what you learned in Step 1 and Step 2.\n",
    "\n",
    "\n",
    "**Note: This is meant to be a more realistic project, where you have a clear objective of what you need to create and accomplish and the necessary online documentation. It's up to you to piece everything together to figure it out! If you get stuck, no worries! Check out the solution lecture.**\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 767,
   "metadata": {},
   "outputs": [],
   "source": [
    "iso_codes = pd.read_csv(\"../DATA/country_iso_codes.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 768,
   "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>ISO Code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>AFG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Akrotiri and Dhekelia – See United Kingdom, The</td>\n",
       "      <td>Akrotiri and Dhekelia – See United Kingdom, The</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Åland Islands</td>\n",
       "      <td>ALA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Albania</td>\n",
       "      <td>ALB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>DZA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>296</th>\n",
       "      <td>Congo, Dem. Rep.</td>\n",
       "      <td>COD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>297</th>\n",
       "      <td>Congo, Repub. of the</td>\n",
       "      <td>COG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>298</th>\n",
       "      <td>Tanzania</td>\n",
       "      <td>TZA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>299</th>\n",
       "      <td>Central African Rep.</td>\n",
       "      <td>CAF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300</th>\n",
       "      <td>Cote d'Ivoire</td>\n",
       "      <td>CIV</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>301 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             Country  \\\n",
       "0                                        Afghanistan   \n",
       "1    Akrotiri and Dhekelia – See United Kingdom, The   \n",
       "2                                      Åland Islands   \n",
       "3                                            Albania   \n",
       "4                                            Algeria   \n",
       "..                                               ...   \n",
       "296                                 Congo, Dem. Rep.   \n",
       "297                             Congo, Repub. of the   \n",
       "298                                         Tanzania   \n",
       "299                             Central African Rep.   \n",
       "300                                    Cote d'Ivoire   \n",
       "\n",
       "                                            ISO Code  \n",
       "0                                                AFG  \n",
       "1    Akrotiri and Dhekelia – See United Kingdom, The  \n",
       "2                                                ALA  \n",
       "3                                                ALB  \n",
       "4                                                DZA  \n",
       "..                                               ...  \n",
       "296                                              COD  \n",
       "297                                              COG  \n",
       "298                                              TZA  \n",
       "299                                              CAF  \n",
       "300                                              CIV  \n",
       "\n",
       "[301 rows x 2 columns]"
      ]
     },
     "execution_count": 768,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iso_codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 769,
   "metadata": {},
   "outputs": [],
   "source": [
    "iso_mapping = iso_codes.set_index('Country')['ISO Code'].to_dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 770,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Afghanistan': 'AFG',\n",
       " 'Akrotiri and Dhekelia – See United Kingdom, The': 'Akrotiri and Dhekelia – See United Kingdom, The',\n",
       " 'Åland Islands': 'ALA',\n",
       " 'Albania': 'ALB',\n",
       " 'Algeria': 'DZA',\n",
       " 'American Samoa': 'ASM',\n",
       " 'Andorra': 'AND',\n",
       " 'Angola': 'AGO',\n",
       " 'Anguilla': 'AIA',\n",
       " 'Antarctica\\u200a[a]': 'ATA',\n",
       " 'Antigua and Barbuda': 'ATG',\n",
       " 'Argentina': 'ARG',\n",
       " 'Armenia': 'ARM',\n",
       " 'Aruba': 'ABW',\n",
       " 'Ashmore and Cartier Islands – See Australia.': 'Ashmore and Cartier Islands – See Australia.',\n",
       " 'Australia\\u200a[b]': 'AUS',\n",
       " 'Austria': 'AUT',\n",
       " 'Azerbaijan': 'AZE',\n",
       " 'Bahamas (the)': 'BHS',\n",
       " 'Bahrain': 'BHR',\n",
       " 'Bangladesh': 'BGD',\n",
       " 'Barbados': 'BRB',\n",
       " 'Belarus': 'BLR',\n",
       " 'Belgium': 'BEL',\n",
       " 'Belize': 'BLZ',\n",
       " 'Benin': 'BEN',\n",
       " 'Bermuda': 'BMU',\n",
       " 'Bhutan': 'BTN',\n",
       " 'Bolivia (Plurinational State of)': 'BOL',\n",
       " 'Bonaire\\xa0Sint Eustatius\\xa0Saba': 'BES',\n",
       " 'Bosnia and Herzegovina': 'BIH',\n",
       " 'Botswana': 'BWA',\n",
       " 'Bouvet Island': 'BVT',\n",
       " 'Brazil': 'BRA',\n",
       " 'British Indian Ocean Territory (the)': 'IOT',\n",
       " 'British Virgin Islands – See Virgin Islands (British).': 'British Virgin Islands – See Virgin Islands (British).',\n",
       " 'Brunei Darussalam\\u200a[e]': 'BRN',\n",
       " 'Bulgaria': 'BGR',\n",
       " 'Burkina Faso': 'BFA',\n",
       " 'Burma – See Myanmar.': 'Burma – See Myanmar.',\n",
       " 'Burundi': 'BDI',\n",
       " 'Cabo Verde\\u200a[f]': 'CPV',\n",
       " 'Cambodia': 'KHM',\n",
       " 'Cameroon': 'CMR',\n",
       " 'Canada': 'CAN',\n",
       " 'Cape Verde – See Cabo Verde.': 'Cape Verde – See Cabo Verde.',\n",
       " 'Caribbean Netherlands – See Bonaire, Sint Eustatius and Saba.': 'Caribbean Netherlands – See Bonaire, Sint Eustatius and Saba.',\n",
       " 'Cayman Islands (the)': 'CYM',\n",
       " 'Central African Republic (the)': 'CAF',\n",
       " 'Chad': 'TCD',\n",
       " 'Chile': 'CHL',\n",
       " 'China': 'CHN',\n",
       " 'China, The Republic of – See Taiwan (Province of China).': 'China, The Republic of – See Taiwan (Province of China).',\n",
       " 'Christmas Island': 'CXR',\n",
       " 'Clipperton Island – See France.': 'Clipperton Island – See France.',\n",
       " 'Cocos (Keeling) Islands (the)': 'CCK',\n",
       " 'Colombia': 'COL',\n",
       " 'Comoros (the)': 'COM',\n",
       " 'Congo (the Democratic Republic of the)': 'COD',\n",
       " 'Congo (the)\\u200a[g]': 'COG',\n",
       " 'Cook Islands (the)': 'COK',\n",
       " 'Coral Sea Islands – See Australia.': 'Coral Sea Islands – See Australia.',\n",
       " 'Costa Rica': 'CRI',\n",
       " \"Côte d'Ivoire\\u200a[h]\": 'CIV',\n",
       " 'Croatia': 'HRV',\n",
       " 'Cuba': 'CUB',\n",
       " 'Curaçao': 'CUW',\n",
       " 'Cyprus': 'CYP',\n",
       " 'Czechia\\u200a[i]': 'CZE',\n",
       " \"Democratic People's Republic of Korea – See Korea, The Democratic People's Republic of.\": \"Democratic People's Republic of Korea – See Korea, The Democratic People's Republic of.\",\n",
       " 'Democratic Republic of the Congo – See Congo, The Democratic Republic of the.': 'Democratic Republic of the Congo – See Congo, The Democratic Republic of the.',\n",
       " 'Denmark': 'DNK',\n",
       " 'Djibouti': 'DJI',\n",
       " 'Dominica': 'DMA',\n",
       " 'Dominican Republic (the)': 'DOM',\n",
       " 'East Timor – See Timor-Leste.': 'East Timor – See Timor-Leste.',\n",
       " 'Ecuador': 'ECU',\n",
       " 'Egypt': 'EGY',\n",
       " 'El Salvador': 'SLV',\n",
       " 'England – See United Kingdom, The.': 'England – See United Kingdom, The.',\n",
       " 'Equatorial Guinea': 'GNQ',\n",
       " 'Eritrea': 'ERI',\n",
       " 'Estonia': 'EST',\n",
       " 'Eswatini\\u200a[j]': 'SWZ',\n",
       " 'Ethiopia': 'ETH',\n",
       " 'Falkland Islands (the) [Malvinas]\\u200a[k]': 'FLK',\n",
       " 'Faroe Islands (the)': 'FRO',\n",
       " 'Fiji': 'FJI',\n",
       " 'Finland': 'FIN',\n",
       " 'France\\u200a[l]': 'FRA',\n",
       " 'French Guiana': 'GUF',\n",
       " 'French Polynesia': 'PYF',\n",
       " 'French Southern Territories (the)\\u200a[m]': 'ATF',\n",
       " 'Gabon': 'GAB',\n",
       " 'Gambia (the)': 'GMB',\n",
       " 'Georgia': 'GEO',\n",
       " 'Germany': 'DEU',\n",
       " 'Ghana': 'GHA',\n",
       " 'Gibraltar': 'GIB',\n",
       " 'Great Britain – See United Kingdom, The.': 'Great Britain – See United Kingdom, The.',\n",
       " 'Greece': 'GRC',\n",
       " 'Greenland': 'GRL',\n",
       " 'Grenada': 'GRD',\n",
       " 'Guadeloupe': 'GLP',\n",
       " 'Guam': 'GUM',\n",
       " 'Guatemala': 'GTM',\n",
       " 'Guernsey': 'GGY',\n",
       " 'Guinea': 'GIN',\n",
       " 'Guinea-Bissau': 'GNB',\n",
       " 'Guyana': 'GUY',\n",
       " 'Haiti': 'HTI',\n",
       " 'Hawaiian Islands – See United States of America, The.': 'Hawaiian Islands – See United States of America, The.',\n",
       " 'Heard Island and McDonald Islands': 'HMD',\n",
       " 'Holy See (the)\\u200a[n]': 'VAT',\n",
       " 'Honduras': 'HND',\n",
       " 'Hong Kong': 'HKG',\n",
       " 'Hungary': 'HUN',\n",
       " 'Iceland': 'ISL',\n",
       " 'India': 'IND',\n",
       " 'Indonesia': 'IDN',\n",
       " 'Iran (Islamic Republic of)': 'IRN',\n",
       " 'Iraq': 'IRQ',\n",
       " 'Ireland': 'IRL',\n",
       " 'Isle of Man': 'IMN',\n",
       " 'Israel': 'ISR',\n",
       " 'Italy': 'ITA',\n",
       " \"Ivory Coast – See Côte d'Ivoire.\": \"Ivory Coast – See Côte d'Ivoire.\",\n",
       " 'Jamaica': 'JAM',\n",
       " 'Jan Mayen – See Svalbard and Jan Mayen.': 'Jan Mayen – See Svalbard and Jan Mayen.',\n",
       " 'Japan': 'JPN',\n",
       " 'Jersey': 'JEY',\n",
       " 'Jordan': 'JOR',\n",
       " 'Kazakhstan': 'KAZ',\n",
       " 'Kenya': 'KEN',\n",
       " 'Kiribati': 'KIR',\n",
       " \"Korea (the Democratic People's Republic of)\\u200a[o]\": 'PRK',\n",
       " 'Korea (the Republic of)\\u200a[p]': 'KOR',\n",
       " 'Kuwait': 'KWT',\n",
       " 'Kyrgyzstan': 'KGZ',\n",
       " \"Lao People's Democratic Republic (the)\\u200a[q]\": 'LAO',\n",
       " 'Latvia': 'LVA',\n",
       " 'Lebanon': 'LBN',\n",
       " 'Lesotho': 'LSO',\n",
       " 'Liberia': 'LBR',\n",
       " 'Libya': 'LBY',\n",
       " 'Liechtenstein': 'LIE',\n",
       " 'Lithuania': 'LTU',\n",
       " 'Luxembourg': 'LUX',\n",
       " 'Macao\\u200a[r]': 'MAC',\n",
       " 'North Macedonia\\u200a[s]': 'MKD',\n",
       " 'Madagascar': 'MDG',\n",
       " 'Malawi': 'MWI',\n",
       " 'Malaysia': 'MYS',\n",
       " 'Maldives': 'MDV',\n",
       " 'Mali': 'MLI',\n",
       " 'Malta': 'MLT',\n",
       " 'Marshall Islands (the)': 'MHL',\n",
       " 'Martinique': 'MTQ',\n",
       " 'Mauritania': 'MRT',\n",
       " 'Mauritius': 'MUS',\n",
       " 'Mayotte': 'MYT',\n",
       " 'Mexico': 'MEX',\n",
       " 'Micronesia (Federated States of)': 'FSM',\n",
       " 'Moldova (the Republic of)': 'MDA',\n",
       " 'Monaco': 'MCO',\n",
       " 'Mongolia': 'MNG',\n",
       " 'Montenegro': 'MNE',\n",
       " 'Montserrat': 'MSR',\n",
       " 'Morocco': 'MAR',\n",
       " 'Mozambique': 'MOZ',\n",
       " 'Myanmar\\u200a[t]': 'MMR',\n",
       " 'Namibia': 'NAM',\n",
       " 'Nauru': 'NRU',\n",
       " 'Nepal': 'NPL',\n",
       " 'Netherlands (the)': 'NLD',\n",
       " 'New Caledonia': 'NCL',\n",
       " 'New Zealand': 'NZL',\n",
       " 'Nicaragua': 'NIC',\n",
       " 'Niger (the)': 'NER',\n",
       " 'Nigeria': 'NGA',\n",
       " 'Niue': 'NIU',\n",
       " 'Norfolk Island': 'NFK',\n",
       " \"North Korea – See Korea, The Democratic People's Republic of.\": \"North Korea – See Korea, The Democratic People's Republic of.\",\n",
       " 'Northern Ireland – See United Kingdom, The.': 'Northern Ireland – See United Kingdom, The.',\n",
       " 'Northern Mariana Islands (the)': 'MNP',\n",
       " 'Norway': 'NOR',\n",
       " 'Oman': 'OMN',\n",
       " 'Pakistan': 'PAK',\n",
       " 'Palau': 'PLW',\n",
       " 'Palestine, State of': 'PSE',\n",
       " 'Panama': 'PAN',\n",
       " 'Papua New Guinea': 'PNG',\n",
       " 'Paraguay': 'PRY',\n",
       " \"People's Republic of China – See China.\": \"People's Republic of China – See China.\",\n",
       " 'Peru': 'PER',\n",
       " 'Philippines (the)': 'PHL',\n",
       " 'Pitcairn\\u200a[u]': 'PCN',\n",
       " 'Poland': 'POL',\n",
       " 'Portugal': 'PRT',\n",
       " 'Puerto Rico': 'PRI',\n",
       " 'Qatar': 'QAT',\n",
       " 'Republic of China – See Taiwan (Province of China).': 'Republic of China – See Taiwan (Province of China).',\n",
       " 'Republic of Korea – See Korea, The Republic of.': 'Republic of Korea – See Korea, The Republic of.',\n",
       " 'Republic of the Congo – See Congo, The.': 'Republic of the Congo – See Congo, The.',\n",
       " 'Réunion': 'REU',\n",
       " 'Romania': 'ROU',\n",
       " 'Russian Federation (the)\\u200a[v]': 'RUS',\n",
       " 'Rwanda': 'RWA',\n",
       " 'Saba – See Bonaire, Sint Eustatius and Saba.': 'Saba – See Bonaire, Sint Eustatius and Saba.',\n",
       " 'Sahrawi Arab Democratic Republic – See Western Sahara.': 'Sahrawi Arab Democratic Republic – See Western Sahara.',\n",
       " 'Saint Barthélemy': 'BLM',\n",
       " 'Saint Helena\\xa0Ascension Island\\xa0Tristan da Cunha': 'SHN',\n",
       " 'Saint Kitts and Nevis': 'KNA',\n",
       " 'Saint Lucia': 'LCA',\n",
       " 'Saint Martin (French part)': 'MAF',\n",
       " 'Saint Pierre and Miquelon': 'SPM',\n",
       " 'Saint Vincent and the Grenadines': 'VCT',\n",
       " 'Samoa': 'WSM',\n",
       " 'San Marino': 'SMR',\n",
       " 'Sao Tome and Principe': 'STP',\n",
       " 'Saudi Arabia': 'SAU',\n",
       " 'Scotland – See United Kingdom, The.': 'Scotland – See United Kingdom, The.',\n",
       " 'Senegal': 'SEN',\n",
       " 'Serbia': 'SRB',\n",
       " 'Seychelles': 'SYC',\n",
       " 'Sierra Leone': 'SLE',\n",
       " 'Singapore': 'SGP',\n",
       " 'Sint Eustatius – See Bonaire, Sint Eustatius and Saba.': 'Sint Eustatius – See Bonaire, Sint Eustatius and Saba.',\n",
       " 'Sint Maarten (Dutch part)': 'SXM',\n",
       " 'Slovakia': 'SVK',\n",
       " 'Slovenia': 'SVN',\n",
       " 'Solomon Islands': 'SLB',\n",
       " 'Somalia': 'SOM',\n",
       " 'South Africa': 'ZAF',\n",
       " 'South Georgia and the South Sandwich Islands': 'SGS',\n",
       " 'South Korea – See Korea, The Republic of.': 'South Korea – See Korea, The Republic of.',\n",
       " 'South Sudan': 'SSD',\n",
       " 'Spain': 'ESP',\n",
       " 'Sri Lanka': 'LKA',\n",
       " 'Sudan (the)': 'SDN',\n",
       " 'Suriname': 'SUR',\n",
       " 'Svalbard\\xa0Jan Mayen': 'SJM',\n",
       " 'Sweden': 'SWE',\n",
       " 'Switzerland': 'CHE',\n",
       " 'Syrian Arab Republic (the)\\u200a[x]': 'SYR',\n",
       " 'Taiwan (Province of China)\\u200a[y]': 'TWN',\n",
       " 'Tajikistan': 'TJK',\n",
       " 'Tanzania, the United Republic of': 'TZA',\n",
       " 'Thailand': 'THA',\n",
       " 'Timor-Leste\\u200a[aa]': 'TLS',\n",
       " 'Togo': 'TGO',\n",
       " 'Tokelau': 'TKL',\n",
       " 'Tonga': 'TON',\n",
       " 'Trinidad and Tobago': 'TTO',\n",
       " 'Tunisia': 'TUN',\n",
       " 'Turkey': 'TUR',\n",
       " 'Turkmenistan': 'TKM',\n",
       " 'Turks and Caicos Islands (the)': 'TCA',\n",
       " 'Tuvalu': 'TUV',\n",
       " 'Uganda': 'UGA',\n",
       " 'Ukraine': 'UKR',\n",
       " 'United Arab Emirates (the)': 'ARE',\n",
       " 'United Kingdom of Great Britain and Northern Ireland (the)': 'GBR',\n",
       " 'United States Minor Outlying Islands (the)\\u200a[ac]': 'UMI',\n",
       " 'United States of America (the)': 'USA',\n",
       " 'United States Virgin Islands – See Virgin Islands (U.S.).': 'United States Virgin Islands – See Virgin Islands (U.S.).',\n",
       " 'Uruguay': 'URY',\n",
       " 'Uzbekistan': 'UZB',\n",
       " 'Vanuatu': 'VUT',\n",
       " 'Vatican City – See Holy See, The.': 'Vatican City – See Holy See, The.',\n",
       " 'Venezuela (Bolivarian Republic of)': 'VEN',\n",
       " 'Viet Nam\\u200a[ae]': 'VNM',\n",
       " 'Virgin Islands (British)\\u200a[af]': 'VGB',\n",
       " 'Virgin Islands (U.S.)\\u200a[ag]': 'VIR',\n",
       " 'Wales – See United Kingdom, The.': 'Wales – See United Kingdom, The.',\n",
       " 'Wallis and Futuna': 'WLF',\n",
       " 'Western Sahara\\u200a[ah]': 'ESH',\n",
       " 'Yemen': 'YEM',\n",
       " 'Zambia': 'ZMB',\n",
       " 'Zimbabwe': 'ZWE',\n",
       " 'United States': 'USA',\n",
       " 'United Kingdom': 'GBR',\n",
       " 'Venezuela': 'VEN',\n",
       " 'Australia': 'AUS',\n",
       " 'Iran': 'IRN',\n",
       " 'France': 'FRA',\n",
       " 'Russia': 'RUS',\n",
       " 'Korea, North': 'PRK',\n",
       " 'Korea, South': 'KOR',\n",
       " 'Myanmar': 'MMR',\n",
       " 'Burma': 'MMR',\n",
       " 'Vietnam': 'VNM',\n",
       " 'Laos': 'LAO',\n",
       " 'Bolivia': 'BOL',\n",
       " 'Niger': 'NER',\n",
       " 'Sudan': 'SDN',\n",
       " 'Congo, Dem. Rep.': 'COD',\n",
       " 'Congo, Repub. of the': 'COG',\n",
       " 'Tanzania': 'TZA',\n",
       " 'Central African Rep.': 'CAF',\n",
       " \"Cote d'Ivoire\": 'CIV'}"
      ]
     },
     "execution_count": 770,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iso_mapping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 771,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['ISO Code'] = df['Country'].map(iso_mapping)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 772,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Cluster'] = model.labels_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 773,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "coloraxis": "coloraxis",
         "geo": "geo",
         "hovertemplate": "<b>%{hovertext}</b><br><br>ISO Code=%{location}<br>Cluster=%{z}<extra></extra>",
         "hovertext": [
          "Afghanistan",
          "Albania",
          "Algeria",
          "American Samoa",
          "Andorra",
          "Angola",
          "Anguilla",
          "Antigua & Barbuda",
          "Argentina",
          "Armenia",
          "Aruba",
          "Australia",
          "Austria",
          "Azerbaijan",
          "Bahamas, The",
          "Bahrain",
          "Bangladesh",
          "Barbados",
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       "                            \n",
       "var gd = document.getElementById('70b6627b-664e-42b4-b53a-763d5ceed447');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
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       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
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       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import plotly.express as px\n",
    "\n",
    "fig = px.choropleth(df, locations=\"ISO Code\",\n",
    "                    color=\"Cluster\", # lifeExp is a column of gapminder\n",
    "                    hover_name=\"Country\", # column to add to hover information\n",
    "                    color_continuous_scale='Turbo'\n",
    "                    )\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  }
 ],
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