uscar.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DOMAIN: \n",
    "Automobile\n",
    "### CONTEXT: \n",
    "The data concerns city-cycle fuel consumption in miles per gallon, to be predicted in terms of 3 multivalued discrete and 5 continuous attributes <br />\n",
    "### DATA DESCRIPTION: \n",
    "The data concerns city-cycle fuel consumption in miles per gallon <br />\n",
    "###  Attribute Information:\n",
    "1. mpg: continuous\n",
    "2. cylinders(cyl): multi-valued discrete\n",
    "3. displacement(disp): continuous\n",
    "4. horsepower(hp): continuous\n",
    "5. weight(wt): continuous\n",
    "6. acceleration(acc): continuous\n",
    "7. model year(yr): multi-valued discrete\n",
    "8. origin: multi-valued discrete\n",
    "9. car name: string (unique for each instance) <br/>\n",
    "\n",
    "### PROJECT OBJECTIVE: \n",
    "Goal is to cluster the data and treat them as individual datasets to train Regression models to predict ‘mpg’"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Loading the required packages\n",
    "import numpy as np   \n",
    "from sklearn.linear_model import LinearRegression\n",
    "from scipy import stats \n",
    "from scipy.stats import zscore\n",
    "from scipy.cluster.hierarchy import dendrogram, linkage\n",
    "from scipy.cluster.hierarchy import fcluster\n",
    "from sklearn.cluster import KMeans \n",
    "from sklearn.metrics import silhouette_samples, silhouette_score\n",
    "import pandas as pd    \n",
    "import matplotlib.pyplot as plt \n",
    "import seaborn as sns\n",
    "%matplotlib inline \n",
    "sns.set(color_codes=True)\n",
    "%matplotlib inline\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "      <th>yr</th>\n",
       "      <th>origin</th>\n",
       "      <th>car_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>18.0</td>\n",
       "      <td>8</td>\n",
       "      <td>307.0</td>\n",
       "      <td>130</td>\n",
       "      <td>3504</td>\n",
       "      <td>12.0</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "      <td>chevrolet chevelle malibu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15.0</td>\n",
       "      <td>8</td>\n",
       "      <td>350.0</td>\n",
       "      <td>165</td>\n",
       "      <td>3693</td>\n",
       "      <td>11.5</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "      <td>buick skylark 320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>18.0</td>\n",
       "      <td>8</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150</td>\n",
       "      <td>3436</td>\n",
       "      <td>11.0</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "      <td>plymouth satellite</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16.0</td>\n",
       "      <td>8</td>\n",
       "      <td>304.0</td>\n",
       "      <td>150</td>\n",
       "      <td>3433</td>\n",
       "      <td>12.0</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "      <td>amc rebel sst</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17.0</td>\n",
       "      <td>8</td>\n",
       "      <td>302.0</td>\n",
       "      <td>140</td>\n",
       "      <td>3449</td>\n",
       "      <td>10.5</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "      <td>ford torino</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    mpg  cyl   disp   hp    wt   acc  yr  origin                   car_name\n",
       "0  18.0    8  307.0  130  3504  12.0  70       1  chevrolet chevelle malibu\n",
       "1  15.0    8  350.0  165  3693  11.5  70       1          buick skylark 320\n",
       "2  18.0    8  318.0  150  3436  11.0  70       1         plymouth satellite\n",
       "3  16.0    8  304.0  150  3433  12.0  70       1              amc rebel sst\n",
       "4  17.0    8  302.0  140  3449  10.5  70       1                ford torino"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Loading the json file and concatinating it with car names\n",
    "ca=pd.read_json (r'./car.json')\n",
    "ca1=pd.read_csv('./Car name.csv')\n",
    "car=pd.concat([ca,ca1],axis=1)\n",
    "car.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The dataset contains 398 rows and 9 columns\n"
     ]
    }
   ],
   "source": [
    "row, column = car.shape\n",
    "print('The dataset contains', row, 'rows and', column, 'columns')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# save this data as to csv,xlsx and json\n",
    "car.to_csv('mpg.csv', index=False)\n",
    "car.to_excel('mpg.xlsx', index = False)\n",
    "car.to_json('mpg.json', orient = 'split', compression = 'infer', index = 'true')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "      <th>yr</th>\n",
       "      <th>origin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>18.0</td>\n",
       "      <td>8</td>\n",
       "      <td>307.0</td>\n",
       "      <td>130</td>\n",
       "      <td>3504</td>\n",
       "      <td>12.0</td>\n",
       "      <td>70</td>\n",
       "      <td>america</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15.0</td>\n",
       "      <td>8</td>\n",
       "      <td>350.0</td>\n",
       "      <td>165</td>\n",
       "      <td>3693</td>\n",
       "      <td>11.5</td>\n",
       "      <td>70</td>\n",
       "      <td>america</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>18.0</td>\n",
       "      <td>8</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150</td>\n",
       "      <td>3436</td>\n",
       "      <td>11.0</td>\n",
       "      <td>70</td>\n",
       "      <td>america</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16.0</td>\n",
       "      <td>8</td>\n",
       "      <td>304.0</td>\n",
       "      <td>150</td>\n",
       "      <td>3433</td>\n",
       "      <td>12.0</td>\n",
       "      <td>70</td>\n",
       "      <td>america</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17.0</td>\n",
       "      <td>8</td>\n",
       "      <td>302.0</td>\n",
       "      <td>140</td>\n",
       "      <td>3449</td>\n",
       "      <td>10.5</td>\n",
       "      <td>70</td>\n",
       "      <td>america</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    mpg  cyl   disp   hp    wt   acc  yr   origin\n",
       "0  18.0    8  307.0  130  3504  12.0  70  america\n",
       "1  15.0    8  350.0  165  3693  11.5  70  america\n",
       "2  18.0    8  318.0  150  3436  11.0  70  america\n",
       "3  16.0    8  304.0  150  3433  12.0  70  america\n",
       "4  17.0    8  302.0  140  3449  10.5  70  america"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dropping/ignoring car_name \n",
    "car = car.drop('car_name', axis=1)\n",
    "# Also replacing the categorical var with actual values\n",
    "car['origin'] = car['origin'].replace({1: 'america', 2: 'europe', 3: 'asia'})\n",
    "car.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The data type of each attribute: \n",
      "\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 398 entries, 0 to 397\n",
      "Data columns (total 8 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   mpg     398 non-null    float64\n",
      " 1   cyl     398 non-null    int64  \n",
      " 2   disp    398 non-null    float64\n",
      " 3   hp      398 non-null    object \n",
      " 4   wt      398 non-null    int64  \n",
      " 5   acc     398 non-null    float64\n",
      " 6   yr      398 non-null    int64  \n",
      " 7   origin  398 non-null    object \n",
      "dtypes: float64(3), int64(3), object(2)\n",
      "memory usage: 25.0+ KB\n"
     ]
    }
   ],
   "source": [
    "print('The data type of each attribute: \\n')\n",
    "car.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mpg</th>\n",
       "      <td>398.0</td>\n",
       "      <td>23.514573</td>\n",
       "      <td>7.815984</td>\n",
       "      <td>9.0</td>\n",
       "      <td>17.500</td>\n",
       "      <td>23.0</td>\n",
       "      <td>29.000</td>\n",
       "      <td>46.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cyl</th>\n",
       "      <td>398.0</td>\n",
       "      <td>5.454774</td>\n",
       "      <td>1.701004</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.000</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.000</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>disp</th>\n",
       "      <td>398.0</td>\n",
       "      <td>193.425879</td>\n",
       "      <td>104.269838</td>\n",
       "      <td>68.0</td>\n",
       "      <td>104.250</td>\n",
       "      <td>148.5</td>\n",
       "      <td>262.000</td>\n",
       "      <td>455.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wt</th>\n",
       "      <td>398.0</td>\n",
       "      <td>2970.424623</td>\n",
       "      <td>846.841774</td>\n",
       "      <td>1613.0</td>\n",
       "      <td>2223.750</td>\n",
       "      <td>2803.5</td>\n",
       "      <td>3608.000</td>\n",
       "      <td>5140.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>acc</th>\n",
       "      <td>398.0</td>\n",
       "      <td>15.568090</td>\n",
       "      <td>2.757689</td>\n",
       "      <td>8.0</td>\n",
       "      <td>13.825</td>\n",
       "      <td>15.5</td>\n",
       "      <td>17.175</td>\n",
       "      <td>24.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yr</th>\n",
       "      <td>398.0</td>\n",
       "      <td>76.010050</td>\n",
       "      <td>3.697627</td>\n",
       "      <td>70.0</td>\n",
       "      <td>73.000</td>\n",
       "      <td>76.0</td>\n",
       "      <td>79.000</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      count         mean         std     min       25%     50%       75%  \\\n",
       "mpg   398.0    23.514573    7.815984     9.0    17.500    23.0    29.000   \n",
       "cyl   398.0     5.454774    1.701004     3.0     4.000     4.0     8.000   \n",
       "disp  398.0   193.425879  104.269838    68.0   104.250   148.5   262.000   \n",
       "wt    398.0  2970.424623  846.841774  1613.0  2223.750  2803.5  3608.000   \n",
       "acc   398.0    15.568090    2.757689     8.0    13.825    15.5    17.175   \n",
       "yr    398.0    76.010050    3.697627    70.0    73.000    76.0    79.000   \n",
       "\n",
       "         max  \n",
       "mpg     46.6  \n",
       "cyl      8.0  \n",
       "disp   455.0  \n",
       "wt    5140.0  \n",
       "acc     24.8  \n",
       "yr      82.0  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#5-point summary\n",
    "car.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "      <th>yr</th>\n",
       "      <th>origin</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>25.0</td>\n",
       "      <td>4</td>\n",
       "      <td>98.0</td>\n",
       "      <td>?</td>\n",
       "      <td>2046</td>\n",
       "      <td>19.0</td>\n",
       "      <td>71</td>\n",
       "      <td>america</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>200.0</td>\n",
       "      <td>?</td>\n",
       "      <td>2875</td>\n",
       "      <td>17.0</td>\n",
       "      <td>74</td>\n",
       "      <td>america</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330</th>\n",
       "      <td>40.9</td>\n",
       "      <td>4</td>\n",
       "      <td>85.0</td>\n",
       "      <td>?</td>\n",
       "      <td>1835</td>\n",
       "      <td>17.3</td>\n",
       "      <td>80</td>\n",
       "      <td>europe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>336</th>\n",
       "      <td>23.6</td>\n",
       "      <td>4</td>\n",
       "      <td>140.0</td>\n",
       "      <td>?</td>\n",
       "      <td>2905</td>\n",
       "      <td>14.3</td>\n",
       "      <td>80</td>\n",
       "      <td>america</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>354</th>\n",
       "      <td>34.5</td>\n",
       "      <td>4</td>\n",
       "      <td>100.0</td>\n",
       "      <td>?</td>\n",
       "      <td>2320</td>\n",
       "      <td>15.8</td>\n",
       "      <td>81</td>\n",
       "      <td>europe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>23.0</td>\n",
       "      <td>4</td>\n",
       "      <td>151.0</td>\n",
       "      <td>?</td>\n",
       "      <td>3035</td>\n",
       "      <td>20.5</td>\n",
       "      <td>82</td>\n",
       "      <td>america</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      mpg  cyl   disp hp    wt   acc  yr   origin\n",
       "32   25.0    4   98.0  ?  2046  19.0  71  america\n",
       "126  21.0    6  200.0  ?  2875  17.0  74  america\n",
       "330  40.9    4   85.0  ?  1835  17.3  80   europe\n",
       "336  23.6    4  140.0  ?  2905  14.3  80  america\n",
       "354  34.5    4  100.0  ?  2320  15.8  81   europe\n",
       "374  23.0    4  151.0  ?  3035  20.5  82  america"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# isdigit()? on 'horsepower' \n",
    "hpIsDigit = pd.DataFrame(car.hp.str.isdigit()) \n",
    "\n",
    "#print isDigit = False!\n",
    "car[hpIsDigit['hp'] == False]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "      <th>yr</th>\n",
       "      <th>origin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>25.0</td>\n",
       "      <td>4</td>\n",
       "      <td>98.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2046</td>\n",
       "      <td>19.0</td>\n",
       "      <td>71</td>\n",
       "      <td>america</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>21.0</td>\n",
       "      <td>6</td>\n",
       "      <td>200.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2875</td>\n",
       "      <td>17.0</td>\n",
       "      <td>74</td>\n",
       "      <td>america</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330</th>\n",
       "      <td>40.9</td>\n",
       "      <td>4</td>\n",
       "      <td>85.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1835</td>\n",
       "      <td>17.3</td>\n",
       "      <td>80</td>\n",
       "      <td>europe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>336</th>\n",
       "      <td>23.6</td>\n",
       "      <td>4</td>\n",
       "      <td>140.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2905</td>\n",
       "      <td>14.3</td>\n",
       "      <td>80</td>\n",
       "      <td>america</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>354</th>\n",
       "      <td>34.5</td>\n",
       "      <td>4</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2320</td>\n",
       "      <td>15.8</td>\n",
       "      <td>81</td>\n",
       "      <td>europe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>23.0</td>\n",
       "      <td>4</td>\n",
       "      <td>151.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3035</td>\n",
       "      <td>20.5</td>\n",
       "      <td>82</td>\n",
       "      <td>america</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      mpg  cyl   disp  hp    wt   acc  yr   origin\n",
       "32   25.0    4   98.0 NaN  2046  19.0  71  america\n",
       "126  21.0    6  200.0 NaN  2875  17.0  74  america\n",
       "330  40.9    4   85.0 NaN  1835  17.3  80   europe\n",
       "336  23.6    4  140.0 NaN  2905  14.3  80  america\n",
       "354  34.5    4  100.0 NaN  2320  15.8  81   europe\n",
       "374  23.0    4  151.0 NaN  3035  20.5  82  america"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Replace missing values with NaN\n",
    "car = car.replace('?', np.nan)\n",
    "car[hpIsDigit['hp'] == False] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "mpg       23.0\n",
       "cyl        4.0\n",
       "disp     148.5\n",
       "hp        93.5\n",
       "wt      2803.5\n",
       "acc       15.5\n",
       "yr        76.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#replace the missing values with median value. \n",
    "car.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#replace hp with median\n",
    "car['hp'].fillna((car['hp'].median()), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The data set has no missing values \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "mpg       0\n",
       "cyl       0\n",
       "disp      0\n",
       "hp        0\n",
       "wt        0\n",
       "acc       0\n",
       "yr        0\n",
       "origin    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print('The data set has no missing values \\n')\n",
    "car.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mpg</th>\n",
       "      <th>cyl</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "      <th>yr</th>\n",
       "      <th>origin</th>\n",
       "      <th>mpg_level</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>18.0</td>\n",
       "      <td>8</td>\n",
       "      <td>307.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>3504</td>\n",
       "      <td>12.0</td>\n",
       "      <td>70</td>\n",
       "      <td>america</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15.0</td>\n",
       "      <td>8</td>\n",
       "      <td>350.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>3693</td>\n",
       "      <td>11.5</td>\n",
       "      <td>70</td>\n",
       "      <td>america</td>\n",
       "      <td>low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>18.0</td>\n",
       "      <td>8</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3436</td>\n",
       "      <td>11.0</td>\n",
       "      <td>70</td>\n",
       "      <td>america</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16.0</td>\n",
       "      <td>8</td>\n",
       "      <td>304.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3433</td>\n",
       "      <td>12.0</td>\n",
       "      <td>70</td>\n",
       "      <td>america</td>\n",
       "      <td>low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17.0</td>\n",
       "      <td>8</td>\n",
       "      <td>302.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>3449</td>\n",
       "      <td>10.5</td>\n",
       "      <td>70</td>\n",
       "      <td>america</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    mpg  cyl   disp     hp    wt   acc  yr   origin mpg_level\n",
       "0  18.0    8  307.0  130.0  3504  12.0  70  america    medium\n",
       "1  15.0    8  350.0  165.0  3693  11.5  70  america       low\n",
       "2  18.0    8  318.0  150.0  3436  11.0  70  america    medium\n",
       "3  16.0    8  304.0  150.0  3433  12.0  70  america       low\n",
       "4  17.0    8  302.0  140.0  3449  10.5  70  america    medium"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#creating mpg_level attribute using the 25% and 75% of mpg values( <  17 as low, > 17 and <29 as medium, > 29 as high  )\n",
    "car['mpg_level'] = car['mpg'].apply(lambda x: 'low' if x<17 else 'high' if x>29 else 'medium')\n",
    "car.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cyl</th>\n",
       "      <th>yr</th>\n",
       "      <th>origin</th>\n",
       "      <th>mpg_level</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>america</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>america</td>\n",
       "      <td>low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>america</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>america</td>\n",
       "      <td>low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>america</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cyl  yr   origin mpg_level\n",
       "0    8  70  america    medium\n",
       "1    8  70  america       low\n",
       "2    8  70  america    medium\n",
       "3    8  70  america       low\n",
       "4    8  70  america    medium"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#categorical variable\n",
    "car_cat = car.iloc[:,[1,6,7,8]]\n",
    "car_cat.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mpg</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>18.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>3504</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>3693</td>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>18.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3436</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16.0</td>\n",
       "      <td>304.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3433</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17.0</td>\n",
       "      <td>302.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>3449</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    mpg   disp     hp    wt   acc\n",
       "0  18.0  307.0  130.0  3504  12.0\n",
       "1  15.0  350.0  165.0  3693  11.5\n",
       "2  18.0  318.0  150.0  3436  11.0\n",
       "3  16.0  304.0  150.0  3433  12.0\n",
       "4  17.0  302.0  140.0  3449  10.5"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#numeric variables\n",
    "car_num=car.drop(['cyl','yr','origin','mpg_level'],axis=1)\n",
    "car_num.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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NwEeB54BrgaOAhxiF89aqnBY3FtRlKpskqd4y87qI2Au4l+Ko+fzM/GpELAbmA5OB64CrKowpSVJX6tj3oGfmz4BDBm5HxHnAhyguMLPe560NTIsbjgXoyJy2JUndYaRpcZ2SmacBpw1qWwjsVkUeSZLGio4V6BGxKzArM+eXTT3AKuBpYKuGRdfpvDVJkiSp06ZtOonJEzpzAbnlq1ay9NcrhskxmckTJnQoxyqW/nr5MDmmMHlCx0oMlq9azdJfvzBMlo2YPGFch3K8yNJf/7Yj29LY1rm/nqIgPycibgSWAccAl2XmUxGxPCL2yczbgA8C13cwlyRJkrROJk+YyNuv+VRHtnXdO/+BpQxdoE+eMIH/Nf+ijuRY8K6jWcrQBfrkCeP586uu7kgOgO+8+xCGmwc6ecI43jX/hx3JMf9dew2bQ2pFx74HPTMfAD4P3EYxrf2+zLyyvPtw4OyIeAyYCpzbqVySJEmSJNVB24+gZ+aODT9fAFwwxDL3A3u1O4skSZIkSXXVsSPokiRJkiRpeBbokiRJkiTVQCcvEidJkiRJG5RNNt2YiRM6c1x05ao+nvv180Pet9mmGzO+QzkAVq/q49khsmy+yUaMm9iZq+sDvLjyRX71XPdcYd8CXZIkSZLaZOKEXs66+hcd2dbfHrLlsPeNn9DLzVcs7kgOgP0/MHPI9nETx7HojEUdy7HVyVutfaEacYq7JEmSJEk1YIEuSZIkSVINWKBLkiRJklQDFuiSJEmSJNWAF4mTJEmSJG1wNt9kCuMmdqYkfnHlan713AtrXc4CXZIkSZK0wRk3cTz/79xbO7Ktl39836aWc4q7JEmSJEk1YIEuSZIkSVINWKBLkiRJklQDFuiSJEmSJNWABbokSZIkSTVggS5JkiRJUg34NWuSJKklEfFZ4D3lzQWZeXJEXArsCzxfts/JzKsrCShJUpeyQJckSU2LiAOAA4HXAf3AdyPiEGAP4C2ZuajKfJIkdbO2FugRMR24HTg4M5+MiGOAj1N06HcDx2bmynIk/iPAs+WqF2Xm+e3MJkmS1ski4MTMXAkQEY8C25f/5kbENsDVFEfQ+6qLKUlS92lbgR4RewMXAbPK27OAk4A3AEuBecDHgLMpRt3fl5l3tCuPJElaf5n58MDPEfEKiqnubwb2Bz4KPAdcCxxF8TmgaTNmTB21nK2aOXNaZdtuZI6XqksOqE8Wc6ypLlnMsaa6ZOmmHO08gn40RQF+eXl7BfDRzPwNQEQ8SDHaDkWB/qmI2AG4BfhEZi5vYzZJkrQeImIXYAFwUmYmcEjDfecBH6LFAn3JkmX09fVX8kFq8eKla7TVJQd0Pos51lSXLOZYU12ymGNNvrcOnaO3t2fYQem2XcU9M2dn5g8abj+Vmf8OEBEzgeOBb0XEVOBeiqPrrwc2BU5tVy5JkrR+ImIfYCHwycy8LCJ2jYh3NSzSA6yqJp0kSd2r4xeJK89Nux64JDNvLpvf3nD/mcBc4NOtPG6V0+LGgrpM+5Ak1VtEbAdcA7w3M28sm3uAcyLiRmAZcAxwWTUJJUnqXh0t0CPilcD3gHMz88yybXvggMycWy62TqPuA9PihmMBOrLhpn1IkuplpGlxHfIJYDJwVkQMtH0Z+DxwGzABmJ+ZV1YTT5Kk7tWxAj0ipgE3AJ/OzMsb7noBOCMibgKepDhv3e9NlSSphjLzBOCEYe6+oJNZJEkaazp5BH028HLgxIg4sWz7dmZ+JiKOBb4DTARuBc7sYC5JkiRJkirX9gI9M3csfzy7/DfUMvOB+e3OIkmSJElSXbXtKu6SJEmSJKl5FuiSJEmSJNVAUwV6+dVog9tePfpxJElSp9i/S5JULyOegx4Rm5c/XhcR+1N8BRoUX6HyTeCV7YsmSZLawf5dkqR6WttF4q4E/rT8eUlD+2rgqrYkkiRJ7Wb/LklSDY1YoGfm2wAiYm5mfqQzkSRJUjvZv0uSVE9Nfc1aZn4kInYANuf30+DIzHvaFUySJLWX/bskSfXSVIEeEXOAk4D/AfrL5n5gpzblkiRJbWb/LklSvTRVoAMfAnbOzGfaGUaSJHWU/bskSTXS7Peg/9zOW5KkMcf+XZKkGmn2CPrCiDgD+BbwwkCj56hJktTV7N8lSaqRZgv0I8v/D21o8xw1SZK625Hl//bvkiTVQLNXcf+DdgeRJEmdZf8uSVK9NHsV978dqj0zzxrdOJIkqVPs3yVJqpdmp7jv2vDzRGA/YOHox5EkSR1k/y5JUo00O8X9w423I2Jr4JK2JJIkSR1h/y5JUr00+zVrL1F+JcuOoxtFkiRVyf5dkqRqrcs56D3AHsD/tCWRJEnqiHXt3yPis8B7ypsLMvPkiDgAOAuYAnwtM08Z7bySJI1163IOej/wX8BJox9HkiR1UMv9e1mIHwi8rlznuxHxfuALFOew/xxYEBEHZeb1bUktSdIY1dI56BGxAzAhM3/azHoRMR24HTg4M58cbnQ9InYHLgamA7cAx2Xm6hafiyq22SYTGT9xUtUxamv1yhU8+9zKqmNI0u+sY/++CDgxM1eW6z4KzAIez8wnyrYrKL5b3QJdkqQWNDvFfWfgW8DWQG9E/JKi6H50hHX2Bi6i6LSJiCnAXIYeXb8CmJ2Zd0bEJcDRwIXr/rRUhfETJ/HjM2ZXHaO23nDyxYAFuqT6WJf+PTMfblj/FRRT3c+jKNwHLAK2bTXPjBlTW11l1MycOa2ybTcyx0vVJQfUJ4s51lSXLOZYU12ydFOOZqe4fwk4IzMvA4iIDwPnA38ywjpHAx8DLi9v78UQo+sR8QgwJTPvLJebB8zBAl2SpHZbl/6dctldgAUUU+JXUw7Il3qAvlbDLFmyjL6+/ko+SC1evHSNtrrkgM5nMcea6pLFHGuqSxZzrMn31qFz9Pb2DDso3WyB/vKBzhsgMy8ddGGZNWTmbICIGGjamqFH14drb0mVo+5jQV1GlcY6X2dJNdNy/w4QEfsA84G/zsyvRsR+wFYNi2wJPDPqaSVJGuOaLdDHR8TmmfkrgIjYguLCMK3oHbTOwOj6cO0tGRh1H46F0ciGG1Vqha/x2o3G6yxpwzbSqPs6aLl/j4jtgGuA92bmjWXzXcVdsTPwBHAYxWltkiSpBc0W6OcBd0bE1yg67vcBZ7e4racZenR9uHZJktRe69K/fwKYDJzVMEvuy8CRFEfVJwPXAVe1Ia8kSWNaswX6dcCJwETgD4FtgKtb3NaQo+uZ+VRELI+IfTLzNuCDeNVXSZI6oeX+PTNPAE4Y5u7dRjWdJEkbmN4ml5sHnJ+Z/wf4APBpWpy6lpnL+f3o+iPAY/x+dP1w4OyIeAyYCpzbymNLkqR1Mo/17N8lSdLoafYI+haZeS78rtA+JyKOaGbFzNyx4eeFDDG6npn3U1zlXZIkdc469++SJGn0NXsEfXxEbD1wIyJeTnExN0mS1L3s3yVJqpFmj6CfBdwXEd+luIjMARTfeypJkrqX/bskSTXS1BH0zJxL0WnfC9wNvC0zv9LOYJIkqb3s3yVJqpdmj6CTmQ8AD7QxiyRJ6jD7d0mS6qPZc9AlSZIkSVIbWaBLkiRJklQDFuiSJEmSJNWABbokSZIkSTVggS5JkiRJUg1YoEuSJEmSVAMW6JIkSZIk1YAFuiRJkiRJNTC+6gCSmjd9k0lMmjix6hi1tWLlSn7z3IqqY0iSJEnrxAJd6iKTJk7kyEtPqDpGbc378D8DFuiSJEnqTk5xlyRJkiSpBizQJUmSJEmqAQt0SZIkSZJqwHPQJUlSyyJiOnA7cHBmPhkRlwL7As+Xi8zJzKsrCyhJUheyQJckSS2JiL2Bi4BZDc17AG/JzEXVpJIkqft1vECPiNnA8Q1NfwBcDmyMI++SJHWDo4GPUfTfRMRGwPbA3IjYBriaoh/vqy6iJEndp+MFemZeDFwMEBG7ANcApwE34ci7JEm1l5mzASJioGlL4Ebgo8BzwLXAURRH2SVJUpOqnuJ+IfAp4Lc48i5JUlfKzJ8BhwzcjojzgA/RYoE+Y8bUUU7WvJkzp1W27UbmeKm65ID6ZDHHmuqSxRxrqkuWbspRWYEeEQcAUzLzGxGxE+s58l5lpz4W1GWnHet8ndvP11jqvIjYFZiVmfPLph5gVauPs2TJMvr6+iv5O168eOkabXXJAZ3PYo411SWLOdZUlyzmWJPvrUPn6O3tGbZ+rfII+rHAWTA6I+8Dnfpw/NA+suF22lb4Gq/d+r7OvsZrNxr7slRnI3XqFeoBzomIG4FlwDHAZdVGkiSp+1TyPegRMRHYD/h2eXvXiHhXwyLrNPIuSZI6LzMfAD4P3AY8AtyXmVdWm0qSpO5T1RH01wI/ycyBK7Y78i5JUpfJzB0bfr4AuKC6NJIkdb9KjqADOwFPD9xw5F2SJEmStKGr5Ah6Zn4d+PqgNkfeJUmSJEkbrKqOoEuSJEmSpAYW6JIkSZIk1YAFuiRJkiRJNWCBLkmSJElSDVigS5IkSZJUAxbokiRJkiTVgAW6JEmSJEk1YIEuSZIkSVINWKBLkiRJklQDFuiSJEmSJNWABbokSZIkSTVggS5JkiRJUg1YoEuSJEmSVAMW6JIkSZIk1YAFuiRJkiRJNWCBLkmSJElSDVigS5IkSZJUAxbokiRJkiTVwPiqA0iSpO4TEdOB24GDM/PJiDgAOAuYAnwtM0+pNKAkSV2okgI9Im4CXgasKpuOBaZhxy5JUu1FxN7ARcCs8vYUYC6wH/BzYEFEHJSZ11eXUpKk7tPxKe4R0UPRoe+Wmbtn5u7AAxQd+zuAVwF7RsRBnc4mSZKacjTwMeCZ8vZewOOZ+URmrgauAA6tKpwkSd2qiiPoUf5/Q0TMoBiBf5CyYweIiIGO3ZF3SZJqJjNnA0QMdOlsDSxqWGQRsG2rjztjxtT1zrauZs6cVtm2G5njpeqSA+qTxRxrqksWc6ypLlm6KUcVBfpmwELgr4AJwM3AF1jPjr3KTn0sqMtOO9b5Orefr7FUiV6gv+F2D9DX6oMsWbKMvr7+Sv6OFy9eukZbXXJA57OYY011yWKONdUliznW5Hvr0Dl6e3uGrV87XqBn5h3AHQO3I+IS4HTg1obFWu7YBzr14fihfWTD7bSt8DVeu/V9nX2N12409mWpzkbq1Cv0NLBVw+0t+f30d0mS1KSOF+gRsS8wKTMXlk09wJPYsUuS1K3uAiIidgaeAA6juLaMJElqQRXfg74p8MWImBwR04AjgE9RduwRMY6iY/f8c0mSukBmLgeOBOYDjwCPAVdVmUmSpG5UxRT3a8uvZ7kXGAecn5l3RMSRFB37ZOA67NglSaq1zNyx4eeFwG7VpZEkqftV8j3omXkqcOqgNjt2SZIkSdIGq4op7pIkSZIkaRALdEmSJEmSasACXZIkSZKkGrBAlyRJkiSpBizQJUmSJEmqAQt0SZIkSZJqwAJdkiRJkqQasECXJEmSJKkGLNAlSZIkSaoBC3RJkiRJkmrAAl2SJEmSpBqwQJckSZIkqQYs0CVJkiRJqgELdEmSJEmSasACXZIkSZKkGrBAlyRJkiSpBizQJUmSJEmqAQt0SZIkSZJqYHzVASRJ0tgQETcBLwNWlU3HZuZdFUaSJKmrVFKgR8RngfeUNxdk5skRcSmwL/B82T4nM6+uIp8kSWpNRPQAs4AdMnN11XkkSepGHS/QI+IA4EDgdUA/8N2IOATYA3hLZi7qdCZJkrTeovz/hoiYAVyUmV+qMpAkSd2miiPoi4ATM3MlQEQ8Cmxf/psbEdsAV1McQe+rIJ8kSWrdZsBC4K+ACcDNEZGZ+e/NPsCMGVPblW2tZs6cVtm2G5njpeqSA+qTxRxrqksWc6ypLlm6KUfHC/TMfHjg54h4BcVU9zcD+wMfBZ4DrgWOAi5q9nGr7NTHgrrstGOdr3P7+RpL1cjMO4A7Bm5HxCXA24GmC/QlS5bR19dfyd/x4sVL12irSw7ofBZzrKkuWcyxprpkMceafG8dOkdvb8+w9WtlF4mLiF2ABcBJmZnAIQ33nQd8iBYK9IFOfTh+aB/ZcDttK3yN1259X2df47UbjX1ZqrOROvUqRcS+wKTMXFg29fD7i8VJkqQmVHWRuH2A+cBfZ+ZXI2JXYFZmzi8XsVOXJKm7bAqcHhFvopjifgRwXKWJJEnqMlVcJG474BrgvZl5Y9ncA5wTETcCy4BjgMs6nU2SJK2bzLw2IvYG7gXGAeeX094lSVKTqjiC/glgMnBWxMAFX/ky8HngNopR9/mZeWUF2SRJ0jrKzFOBU6vOIUlSt6riInEnACcMc/cFncwiSZIkSVJd9FYdQJIkSZIkWaBLkiRJklQLFuiSJEmSJNWABbokSZIkSTVggS5JkiRJUg1YoEuSJEmSVAMW6JIkSZIk1YAFuiRJkiRJNWCBLkmSJElSDVigS5IkSZJUAxbokiRJkiTVgAW6JEmSJEk1YIEuSZIkSVINWKBLkiRJklQDFuiSJEmSJNWABbokSZIkSTVggS5JkiRJUg2MrzqAJNXNptMmMmHypKpj1NKq5Sv49dKVVceQJEkak2pVoEfEYcApwATgnMw8v+JIkjZAEyZP4roPfbjqGLX09n+9FEahQN9k+hQmTqpVF1QbK1es5rnfvFB1jHVmXy5J0rqrzaejiNgG+BzwBmAFcHtE3JSZj1SbTJI02iZOGs8/fPqqqmPU0qc+9+6qI6wz+3JJktZPnc5BPwC4MTN/lZnPA1cB3fspRZKkDY99uSRJ66E2R9CBrYFFDbcXAXs1sd44gN7enrUuuMVmG69TsA1BM69fMyZOnzEqjzNWjcbrvMXUzUchydg1WvvylC3cl4czWq/xJptuNCqPMxaN9Bo33DeuI2FaM2p9ee+0zvbZw73m46Z19r1gpN/95Kkvq0WOqRu/vBY5Nt2oczlg5Cwv22jTmuSYWpMcnX1/HynLzI0m1iLH9I0695Y94vvIxp09Pjvse+v0znZhI/ar0zp33aGBHCP15T39/f0dCzSSiPg0MDkzTy1vHw28ITOPW8uq+wI/aHc+SZJq5s3ArVWHaGRfLklSS9boy+t0BP1pioADtgSeaWK9H5XrLQJebEMuSZLqZBywFUX/Vzf25ZIkrd2wfXmdjqBvQzF6sBfwPHA7cExm/rDSYJIkqSn25ZIkrZ/aXCQuM/8b+DRwE3Af8BU7dEmSuod9uSRJ66c2R9AlSZIkSdqQ1eYIuiRJkiRJGzILdEmSJEmSasACXZIkSZKkGrBAlyRJkiSpBizQJUmSJEmqgfFVB9hQRcQ/AVtk5pFVZxlrIuIDwN+VN6/PzE9UmWcsiog/Bz4LbAzckJknVBxpTIqI04F3A/3AJZl5VsWRxpyIuAl4GbCqbDo2M++qMJKaEBGzgeMbmv4AuBx4uGzvARYAJ2dmW7+uZoQs3wa+CIwD7gFmZ+bKCnL8G3A2MA14ADiinTnKLGv0wxFxDPBxivezuyn+1qp4PTYG9gWeL9vnZObV7crRkGfIzyYRMQH4LvB/M/PmKnJExAHAWcAU4GuZeUqbMwz3u7kbOBl4EbgRODEzV1eU5Rqqf02WAL9paNsGuCszD+5wjssp3js69vc7UpbMPL6Tfzcj5SjvPx54d2buP1rb9GvWKhARbwW+CiywQB9dEbER8DQwC/g1cBvw6cz8fpW5xpKI2An4AbA38P8oOtF/yMzrKw02xkTEfsDngP2BCcAjwJ9lZlaZayyJiB6K94sd2v0hUO0TEbtQfJg+DPgKsDuwHLiFovi6oYIsbwTuBQ7MzEcj4irgu5l5cYdzvBW4C3hbZj4QEVcCt2TmhW3c9lD98CXAScAbgKXAPOC+zDy7XTkGZWr8vdxE8XtZ1Iltl9sf8rMJ8HNgLvB64KAOFBpD5fh74HxgvzLPAuCcTvXpDb+bDwDzgT0zc1FEXAD8tJMD0w1Z/oTitan6NXljZv6ybNuyzPRnmfl4h3McTjHQV8nf76AsbwRm0MG/m+FyZOYvI+LVwA0U++r+o7Udp7h3WERsTvGh+x+qzjJGjaPYrzemKGomAC9UmmjsOYRiNPnpzFwFvJfiA6BGUWb+B/DHZeH4MooZT8+PvJZaFOX/N0TE/eUouLrPhcCnMvNHwKsz83lgU2ATiiKkiiy/pOiPpkfEOGAyne2LLgQ+BewJ3JGZD5TtfwW0+2jxUP1wAh/NzN+UMxoeBLZvc45GA6/Hb8vtzo2IByJiTkR04rPwcJ9NjqKYZdGpPnSoHL8BHs/MJ8r+5grg0A7lgd//bran2FcHBk6uBd7ZwRyNWXaiBq/JQHFe+iLw5U4V5405KA7GVPn3+7ss5WvS6b+bIXNExCTgX4DPjPZGLNA7718oRk2frTrIWJSZS4FTgccoRomfBG6vMtMYtDMwLiK+HRH3AR/F/bktMnNVRMyhOHq+EPjviiONNZtRvK6HUBxpPC4i/rTaSGpFOTV3SmZ+A373N3M08DNgEXBfVVko3htvBp4BtgCuqiDHzsCyiPhq+X49hzYPWgzTD9+Smf9e5ptJMV30W+3MMWDQ67ElxayvjwB/BLyZ4sN+Ww332SQzT87Ma9q9/bXk2Jrib2XAImDbTuQZ9Lu5H/ijiNiuHNR6N8XvqyMGZanLazLQ9gqK2XTndiLD4ByZ+VRVf7+DswB0+u9muBzA5ymO5P9stLdlgd5B5TkMP8/MhVVnGasi4rUUHe8OFG+wLwKegz66xgMHUHyoeSPFVPcjKk00hmXmZ4GZwHbA0RXHGVMy847M/FBmPleOyl8CvL3qXGrJsRTnif5OZl5EMQXyF8BpVWQpp6P+I/AaYCvgzsE5O5GD4v36bRTnHL+B4sjpJ9u58ZH64YjYhmJQ7JIOTkv93euRmT/LzEMyc1Fm/hY4jw78zdfls8kwOWZRnFc8oAfo61Ckxt/NTyj2zW9TnEb3ANDWc5yHy0JRH1X+mjQ4BrggM1d0KMOQOSr6+x0yS0Ua3+P/FNg+My9tx4Ys0DvrvcCB5Sj26cBfRETHzt/YQLwNWJiZ/1O+kc2jGHXU6PkF8P3MXJyZL1BMl9yr4kxjTkS8MiJ2Byg/SH4TeG2locaYiNi3vCbIgB5+f7E41VxETKQ4R/Tb5e3tImIfgHJa6lfp0N/M4CwUR2Yfysz/zMw+4CI60BcNkeMXwJ3lVN0Xga/T/vfrIfvhiHglxYy2yzLz/7Y5AzDkPrJrRLyrYZFO/c3X5bPJcDm2alhmS4pZH201xO9mMvDDzHxdZr6JYsbYf7Y7x1BZKGYXVP6aNHgnxftZRwyVo4q/3+GyVGGIHO8HdilruouBPSLia6O1Pa/i3kGZ+bupkxFxJLB/Zv5NdYnGpPuBMyJiY4pzzf4c+FG1kcaca4HLImJTiouFHERxwQyNrp2AORGxL8VI/jsoplJp9GwKnB4Rb6I4F/MI4LhKE6kVrwV+Up5zDsU55/9WDmw9RzFF9taKsjwEnBkRL8/M/0fx99uJvmhwjhso3ke2y8yfAwcDP25zhqH64cfKLJ/OzMvbvP1Gg1+PHuCciLgRWEZxZPKyDuSoy2eToXLcBRweETsDT1BcbLETfc3g383GwMLyIlwrKK6X8OUO5Bgqy11A1OA1ISK2oJhW/UQHtj9kjoiYRjV/v2tkqdBLcmTmRwbuiIj9gdMy872jtTGPoGtMyeJqvVdSfAB5gOJD9z9WGmqMyeIrqM6g+OD7CPAU0JYpPhuyzLyO4sqx91Lsz7dnZsdG0DcEmXktL32N52bmHdWmUgt2ojjSBUBmPkRxTuDtFIXIb4EzK8ryKMW5vjdFxAPAHnRmSvPgHD+nmJb5nYh4DNic4jVqm2H64V8CLwdOjIj7yn+ntzNHafDr8QDF87+Nov+6LzOvbHeIunw2GSbHacCRFFdQf4RiMKUT10sY/LtZQnGNhDspBrhuzMyvdCDHUFmWU4PXZIS2TueYTTV/v0NlqUpHc/g1a5IkSZIk1YBH0CVJkiRJqgELdEmSJEmSasACXZIkSZKkGrBAlyRJkiSpBizQJUmSJEmqAQt0SZIkSZJqwAJdkiRJkqQasECXJEmSJKkGLNAlSZIkSaoBC3RJkiRJkmrAAl2SJEmSpBqwQJckSZIkqQbGVx1A2lBExI7AfwIPlk29wDLgnMz8ernM6cBPM/NfR3iczwD3Z+a3hrjvd+tHRD8wMzN/2ULGPYGjMvO4iNgD+GRmvrvZ9ddFRIwDvgm8Cjg3M7+0jo9zH7B/Zv56hGUuBr6amd9fl21IksYO++Vhtzkq/fJoioibgS9l5lWj/LjzgIcy859G83Gl9WGBLnXWC5m5+8CNiNgBWBgRL2bm/Mz8TBOP8SfAI0Pd0eT6I9kF2LZ8rLuBtn4IKG0DvA3YODNfXNcHaXxdR1hm9ro+viRpTLJfXtOo9MuS1o0FulShzHyqHHk/CZjfOJIbEXOAQ4CVwBLgSOAvgT2AL0bEi8A7gM2BPwSuBV7OS0eCP1eOvvcCp2TmtRFxJPDuzDwYYOA28L+B04FNIuJS4DKK0erXRMQmwPnA7kA/cD3wqcxcHRHLgX8EDgS2As7IzAsHP9eIeDPwRWCj8jmdAtwGfBeYAPw4It6Vmf/ZsM5I210BfAvYDTgc+BEwE3i23M5fAM8BdwGvzsz9B0bggbuBhcB1wN7AZsDJmXn1Wn5lkqQxzH55rf3yPOC3wK7lc/t2+Vr8ObAlMDszbyyXe6HM9zLgBuDjmbkqIt4OfAF4EbgPOADYNzOfXOsvqMjwpnL9jcvHmFO+jrcDZ2bm/HK5LwBk5v+JiKOAj5av+xLg+Mx8rJntSZ3mOehS9e6n6Oh+JyK2A/4a2DMz96Do2PbOzPMpisuTGorJjTJzl8z8P0M89s8y8/XAB4DLImLmcCEy8+fAZ4AfZOaHB919LkWHtivFB5HdgE+U900CfpmZb6L4QHF2REwe9HxmAFcBJ2Tma4EjgCuALYC3Ux7BaPwQ0MR2JwLfycwojyoMmA28AXgN8EaKD0lD2Qn4XmbuBXwSOGeY5SRJGxb75eH7ZYDXU8waeAtwIrCs3NY/U/SnA/YG/hR4dfnv2HK7lwMfKGcu3ERxxL4pEbEZcCnwwfJ1fAdwYURsD1wEfLhcbhzFa3xxROxXPr83Z+brgDMAB+RVWxboUvX6KUajG/03xQeEeyLin4D7MvOaYda/dYTH/jJAZj5EMf3ujeuY8SCKUfv+zFxRPu5BDfcPnHd3D8UHg40Hrb83xTl4d5V5HqYYpd9/Pbf7gyHWeTvwr5m5PDNXAv8yzGOvojiCPpB787VkkSRtGOyXR/adzFyVmb8Anqc44g7F+fyNfem8zFxW5vtXimnzbwEeycz7y+1eBvymiW0OeCPFrIBrymvPXEfx+3ot8DXgjRGxZbmtn2Tm48D/AnYGbi/XOQPYLCLs91VLFuhS9fbk9xeoASAz+4D9KKbPLaEY/T5jmPWXjfDYjeeO9VIUpf1AT0P7xCYy9pbrNd6e0HD7hTL3wDKNjw8wbtD6Qz3Gumx3qOe+etD2hzt/bmX5OsOar4kkacNlvzyyFYNurxpmudWDHvtF1uyjAfpo3jjg0fLo/u7lUfg/opgR91vgG8BhFEfSL25Y5/KG5V9PMevg2Ra2K3WMBbpUoYiYBZwKnDmofTfgIYpO6PPA2RQfGKDo3JrpQKH4IEFEvJ5i9PguYDHwmoiYHBETeOkFZ4Z77O8Bx0dET0RMAo4B/r3JDAB3AK+MiL3KPLtQjKLfvJb11mW7C4APRMSkiBhP8RoM/hAiSdIa7JfX2i+34r1lXzyZYor5dyiO0s+KiNeW230XsCnN99N3Aq+IiLeU6+8OPM7vp8lfVG5rH2B+2fY94P0RsVV5+ziK69BItWSBLnXWlIi4r/x3DzAP+LvMXNC4UDn16+vA3RFxN/AR4G/Lu78NfD4ijmhieztFxL0Uo8jvy8xfUZw39x/AY8AtFOfODbizXOebgx7n4xQXeXmw/JfA55p8zpRfKXMocF5EPAh8BfhwZv5kLauuy3bnUXzguRe4neLCN4OnKkqSBPbLrfbLrfgtxaloD5b/X1o+3/cD/1q+3m+jGIRoqp/OzMXAuyguync/xfnsHxy4wFxm/pjiSP1Vmbm8bLuB4qJy/x4RD1AcYf/LhtkFUq309Pe7b0oaOyLiQOBlmXlFefufgeXDXKxHkiSNsuG+XzwiplNcLf60zPxtOZNgAbC1BbNU8GvWJI01DwMnRcTJFOed3U/xVTWSJKlCmfmbiFgJ/CgiVlGcv/4eYP+IOHuY1W7KzL/pWEipYh5BlyRJkiSpBjwHXZIkSZKkGhgLU9wnUVxFcxHDf52SJEljxTiK7wH+EWt+3VG3si+XJG1Ihu3Lx0KBvifFlSElSdqQvBm4teoQo8S+XJK0IVqjLx8LBfoigGeffZ6+Ps+nlySNbb29PWy22cZQ9n9jhH25JGmDMVJfPhYK9BcB+vr67dQlSRuSsTQV3L5ckrQhWqMv9yJxkiRJkiTVgAW6JEmSJEk1YIEuSZIkSVINWKBLkiRJklQDbb1IXER8FnhPeXNBZp4cEZcC+wLPl+1zMvPqiNgduBiYDtwCHJeZq9uZT5IkSZKkumhbgR4RBwAHAq8D+oHvRsQhwB7AWzJz8CXlrwBmZ+adEXEJcDRwYbvySZIkSZJUJ+08gr4IODEzVwJExKPA9uW/uRGxDXA1MAfYDpiSmXeW684r2y3QJUmSJEkbhLYV6Jn58MDPEfEKiqnubwb2Bz4KPAdcCxwFPMRLv6R9EbBtK9ubMWPq+gWWJEmSJKlCbT0HHSAidgEWACdlZgKHNNx3HvAh4BGKafADeoC+VrazZMky+vr6177gINOmT2bypAktr6f6W75iFUt/s7zqGJI0qnp7exyUHsS+fGyyH5e0IWr3ReL2AeYDf52ZX42IXYFZmTm/XKQHWAU8DWzVsOqWwDPtzDZg8qQJHHbyv3ViU+qwr5xxOEuxY5eksc6+fGyyH5e0IWrb16xFxHbANcBhmfnVsrkHOCciNouICcAxwNWZ+RSwvCzoAT4IXN+ubJIkSZIk1U07j6B/ApgMnBURA21fBj4P3AZMAOZn5pXlfYcDF0XEdOAe4Nw2ZpMkSZIkqVbaeZG4E4AThrn7giGWvx/Yq115JEmSJEmqs7ZNcZckSZIkSc2zQJckSZIkqQba/jVrkiSpO0XEZ4H3lDcXZObJEXEAcBYwBfhaZp5SLrs7cDEwHbgFOC4zV3c+tSRJ3csj6JIkaQ1lIX4g8Dpgd+ANEfF+YC7wDuBVwJ4RcVC5yhXA8Zk5i+JbW47ueGhJkrqcBbokSRrKIuDEzFyZmauAR4FZwOOZ+UR5dPwK4NCI2AGYkpl3luvOAw6tIrQkSd3MKe6SJGkNmfnwwM8R8QqKqe7nURTuAxYB2wJbD9Pekhkzpq5TVo1dM2dOqzqCJHWUBbokSRpWROwCLABOAlZTHEUf0AP0UczI6x+ivSVLliyjr69/7QsOYhE3di1evLTqCJI06np7e4YdlHaKuyRJGlJE7AMsBD6ZmZcBTwNbNSyyJfDMCO2SJKkFFuiSJGkNEbEdcA1wWGZ+tWy+q7grdo6IccBhwPWZ+RSwvCzoAT4IXN/pzJIkdTunuEuSpKF8ApgMnBURA21fBo4E5pf3XQdcVd53OHBRREwH7gHO7WRYSZLGAgt0SZK0hsw8AThhmLt3G2L5+4G92hpKkqQxzinukiRJkiTVgAW6JEmSJEk1YIEuSZIkSVINWKBLkiRJklQDFuiSJEmSJNWABbokSZIkSTVggS5JkiRJUg1YoEuSJEmSVAMW6JIkSZIk1YAFuiRJkiRJNWCBLkmSJElSDVigS5IkSZJUAxbokiRJkiTVgAW6JEmSJEk1YIEuSZIkSVINWKBLkiRJklQDFuiSJEmSJNWABbokSZIkSTUwvuoAkiSpviJiOnA7cDDwauAfGu7eBrgrMw+OiM8CHwGeLe+7KDPP72hYSZK6nAW6JEkaUkTsDVwEzALIzOuA68r7tgRuA/6mXHwP4H2ZeUcFUSVJGhOc4i5JkoZzNPAx4Jkh7vsi8OXMfLy8vQfwqYh4ICK+FBGTOxVSkqSxwiPokiRpSJk5GyAiXtIeEa8A9gcG7p8K3AucBPwUmAecCny6le3NmDF1PRNrrJk5c1rVESSpoyzQJUlSq44BLsjMFQCZuQx4+8CdEXEmMJcWC/QlS5bR19ffchiLuLFr8eKlVUeQpFHX29sz7KC0U9wlSVKr3gl8deBGRGwfER9puL8HWNXpUJIkdTuPoEuSpKZFxBbAlMx8oqH5BeCMiLgJeJLivPWrK4gnSVJX8wi6JElqxU7A040NmbkYOBb4DpAUR9DP7Hw0SZK6W1uPoJffifqe8uaCzDw5Ig4AzgKmAF/LzFPKZXcHLgamA7cAx2Xm6nbmkyRJa5eZOzb8/EPgj4ZYZj4wv4OxJEkac9p2BL0sxA8EXgfsDrwhIt5PcdGYdwCvAvaMiIPKVa4Ajs/MWRQj70e3K5skSZIkSXXTzinui4ATM3NlZq4CHgVmAY9n5hPl0fErgEMjYgeK89nuLNedBxzaxmySJEmSJNVK26a4Z+bDAz+X35f6HuA8isJ9wCJgW2DrYdqb5nenaih+9Y4kSZKkbtH2q7hHxC7AAuAkYDXFUfQBPUAfxZH8/iHam+Z3p2oofn+qpLFmpO9OlSRJ3a2tV3GPiH2AhcAnM/Myiqu+btWwyJbAMyO0S5IkSZK0QWjnReK2A64BDsvMr5bNdxV3xc4RMQ44DLg+M58ClpcFPcAHgevblU2SJEmSpLpp5xT3TwCTgbMiYqDty8CRFF/DMhm4DriqvO9w4KKImA7cA5zbxmySJEmSJNVKOy8SdwJwwjB37zbE8vcDe7UrjyRJkiRJddbWc9AlSZIkSVJzLNAlSZIkSaoBC3RJkiRJkmrAAl2SJEmSpBqwQJckSZIkqQYs0CVJkiRJqgELdEmSJEmSasACXZIkSZKkGrBAlyRJkiSpBizQJUmSJEmqgfFVB5AkSfUVEdOB24GDM/PJiLgU2Bd4vlxkTmZeHRG7AxcD04FbgOMyc3UVmSVJ6lYW6JIkaUgRsTdwETCroXkP4C2ZuWjQ4lcAszPzzoi4BDgauLAzSSVJGhss0CVJ0nCOBj4GXA4QERsB2wNzI2Ib4GpgDrAdMCUz7yzXm1e2W6BLktQCC3RJkjSkzJwNEBEDTVsCNwIfBZ4DrgWOAh4CGo+oLwK2bXV7M2ZMXY+0GotmzpxWdQRJ6igLdEmS1JTM/BlwyMDtiDgP+BDwCNDfsGgP0Nfq4y9Zsoy+vv61LziIRdzYtXjx0qojSNKo6+3tGXZQ2qu4S5KkpkTErhHxroamHmAV8DSwVUP7lsAzncwmSdJYYIEuSZKa1QOcExGbRcQE4Bjg6sx8ClgeEfuUy30QuL6qkJIkdSsLdEmS1JTMfAD4PHAbxbT2+zLzyvLuw4GzI+IxYCpwbjUpJUnqXp6DLkmSRpSZOzb8fAFwwRDL3A/s1cFYkiSNOR5BlyRJkiSpBizQJUmSJEmqAQt0SZIkSZJqwAJdkiRJkqQasECXJEmSJKkGLNAlSZIkSaoBC3RJkiRJkmrAAl2SJEmSpBqwQJckSZIkqQYs0CVJkiRJqgELdEmSJEmSasACXZIkSZKkGrBAlyRJkiSpBizQJUmSJEmqAQt0SZIkSZJqwAJdkiRJkqQasECXJEmSJKkGxrfzwSNiOnA7cHBmPhkRlwL7As+Xi8zJzKsjYnfgYmA6cAtwXGaubmc2SZIkSZLqpG0FekTsDVwEzGpo3gN4S2YuGrT4FcDszLwzIi4BjgYubFc2SZLUnCEG248BPg70A3cDx2bmyoj4LPAR4Nly1Ysy8/xKQkuS1KXaeQT9aOBjwOUAEbERsD0wNyK2Aa4G5gDbAVMy885yvXlluwW6JEkVGjzYHhGzgJOANwBLKfrsjwFnUwzCvy8z76gkrCRJY0DbCvTMnA0QEQNNWwI3Ah8FngOuBY4CHgIaj6gvArZtVy5JktS0lwy2AyuAj2bmbwAi4kGKwXcoCvRPRcQOFKerfSIzl3c4ryRJXa2t56A3ysyfAYcM3I6I84APAY9QTJMb0AP0tfr4M2ZMXd+IGoNmzpxWdQRJ6lqDB9sz8yngqbJtJnA8cGRETAXupTi6/lOKI+unAp/ueGhJkrpYxwr0iNgVmJWZ88umHmAV8DSwVcOiWwLPtPr4S5Yso6+vf+0LDmIBN7YtXry06giSNKp6e3sqH5QuT1W7HrgkM28um9/ecP+ZwFxaLNCrfl6qHz+nSdrQdKxApyjIz4mIG4FlwDHAZZn5VEQsj4h9MvM24IMUnb4kSaqZiHgl8D3g3Mw8s2zbHjggM+eWiw0MwrfEwXYN5kC7pLFopMH2jn0PemY+AHweuI1iWvt9mXlleffhwNkR8RgwFTi3U7kkSVJzImIacANwykBxXnoBOCMi/iAieijOW7+6ioySJHWzth9Bz8wdG36+ALhgiGXuB/ZqdxZJkrReZgMvB06MiBPLtm9n5mci4ljgO8BE4FbgzGEeQ5IkDaOpAj0itsnM/x7U9urMfKQ9sSRJ0mhZ3368YbD97PLfUMvMB+YPdZ8kSWrOiAV6RGxe/nhdROxPcU4ZwATgm8Ar2xdNkiStD/txSZK6y9qOoF8J/Gn585KG9tXAVW1JJEmSRov9uCRJXWTEAj0z3wYQEXMz8yOdiSRJkkaD/bgkSd2lqXPQM/MjEbEDsDm/nx5HZt7TrmCSJGl02I9LktQdmr1I3BzgJOB/gIEvKO0HdmpTLkmSNErsxyVJ6g7Nfs3ah4CdM/OZdoaRJEltYT8uSVIX6G1yuZ/bqUuS1LXsxyVJ6gLNHkFfGBFnAN8CXhho9Nw1SZK6gv24JEldoNkC/cjy/0Mb2jx3TZKk7nBk+b/9uCRJNdbsVdz/oN1BJElSe9iPS5LUHZq9ivvfDtWemWeNbhxJkjTa7MclSeoOzU5x37Xh54nAfsDC0Y8jSZLawH5ckqQu0OwU9w833o6IrYFL2pJIkiSNKvtxSZK6Q7Nfs/YS5Ve17Di6USRJUifYj0uSVE/rcg56D7AH8D9tSSRJkkaV/bgkSd1hXc5B7wf+Czhp9ONIkqQ2sB+XJKkLtHQOekTsAEzIzJ+2NZUkSRo19uOSJHWHZqe47wx8C9ga6I2IXwIHZ+aj7QwnSZLWn/24JEndodmLxH0JOCMzN8vMTYC/B85vXyxJkjSK7MclSeoCzRboL8/MywZuZOalwMz2RJIkSaNsnfvxiJgeEQ9FxI7l7QMi4oGIeDwi/r5hud0j4u6I+ElEXBwRzV7nRpIklZot0MdHxOYDNyJiC4qLzEiSpPpbp348IvYGbgVmlbenAHOBdwCvAvaMiIPKxa8Ajs/MWRRXij96VJ+BJEkbgGZHt88D7oyIr1F06O8Dzm5bKkmSNJrWtR8/GvgYcHl5ey/g8cx8AiAirgAOjYhHgCmZeWe53DxgDnDhqD0DSZI2AM0W6NcBJwITgT8EtgGublcoSZI0qtapH8/M2QARMdC0NbCoYZFFwLYjtLdkxoypra6iMW7mzGlVR5Ckjmq2QJ8HnJ+Z50bEZOA4iilub29XMEmSNGrmMTr9eC8vnRrfA/SN0N6SJUuW0dfX+hl0FnFj1+LFS6uOIEmjrre3Z9hB6WbPQd8iM88FyMzlmXkOsNXoxJMkSW02Wv3404PW2xJ4ZoR2SZLUgmaPoI+PiK0z8xmAiHg5xei4JEmqv9Hqx+8qVo+dgSeAw4C5mflURCyPiH0y8zbgg8D1oxVe6qTNNpnI+ImTqo6hNli9cgXPPrey6hjSiJot0M8C7ouI71JMYTsAOKltqSRJ0mgalX48M5dHxJHAfGAyxbntV5V3Hw5cFBHTgXuAc0cht9Rx4ydO4sdnzK46htrgDSdfDFigq96aKtAzc25E3A28FVgNfDEzH2prMkmSNCrWtx/PzB0bfl4I7DbEMvdTXOVdkiSto2aPoJOZDwAPtDGLJElqE/txSZLqr9mLxEmSJEmSpDZq+gi6JEmSJKk10zeZxKSJE6uOoTZYsXIlv3luxag+pgW6JEmSJLXJpIkTOfLSE6qOoTaY9+F/Bka3QHeKuyRJkiRJNWCBLkmSJElSDVigS5IkSZJUAxbokiRJkiTVQFsvEhcR04HbgYMz88mIOAA4C5gCfC0zTymX2x24GJgO3AIcl5mr25lNkiRJkqQ6adsR9IjYG7gVmFXengLMBd4BvArYMyIOKhe/Ajg+M2cBPcDR7colSZIkSVIdtXOK+9HAx4Bnytt7AY9n5hPl0fErgEMjYgdgSmbeWS43Dzi0jbkkSZIkSaqdtk1xz8zZABEx0LQ1sKhhkUXAtiO0t2TGjKnrlFNj28yZ06qOIEmSJElNaes56IP0Av0Nt3uAvhHaW7JkyTL6+vrXvuAgFnBj2+LFS6uOIEmjqre3x0FpSZLGqE5exf1pYKuG21tSTH8frl2SJEmSpA1GJwv0u4CIiJ0jYhxwGHB9Zj4FLI+IfcrlPghc38FckiRJkiRVrmMFemYuB44E5gOPAI8BV5V3Hw6cHRGPAVOBczuVS5IkSZKkOmj7OeiZuWPDzwuB3YZY5n6Kq7xLkiRJkrRB6uQUd0mSJEmSNIxOXsVdkiR1uYiYDRzf0PQHwOXAxsC+wPNl+5zMvLrD8SRJ6moW6JIkqWmZeTFwMUBE7AJcA5wG3AS8JTMXVRZOkqQuZ4EuSZLW1YXAp4DfAtsDcyNiG+BqiiPofVWGkySp21igS5KklkXEAcCUzPxGROwE3Ah8FHgOuBY4CriolcecMWPqqOdUd5s5c1rVETTGuE9ptI32PmWBLkmS1sWxwFkAmfkz4JCBOyLiPOBDtFigL1myjL6+/paD+IF77Fq8eGnHt+n+NLa5T2m0rcs+1dvbM+ygtFdxlyRJLYmIicB+wLfL27tGxLsaFukBVlWRTZKkbuYRdEmS1KrXAj/JzIErtvcA50TEjcAy4BjgsqrCSZLUrTyCLkmSWrUT8PTAjcx8APg8cBvwCHBfZl5ZUTZJkrqWR9AlSVJLMvPrwNcHtV0AXFBNIkmSxgaPoEuSJEmSVAMW6JIkSZIk1YAFuiRJkiRJNeA56NIo22yTiYyfOKnqGBplq1eu4NnnVlYdQ5IkSWOYBbo0ysZPnMSPz5hddQyNsjecfDFggS5JkqT2cYq7JEmSJEk1YIEuSZIkSVINWKBLkiRJklQDFuiSJEmSJNWABbokSZIkSTVggS5JkiRJUg1YoEuSJEmSVAN+D7ok1dj0TSYxaeLEqmOoDVasXMlvnltRdQxJklQjFuiSVGOTJk7kyEtPqDqG2mDeh/8ZsECXJEm/5xR3SZIkSZJqwAJdkiRJkqQasECXJEmSJKkGLNAlSZIkSaoBLxInSZJaEhE3AS8DVpVNxwLTgLOAKcDXMvOUiuJJktS1LNAlSVLTIqIHmAXskJmry7YpQAL7AT8HFkTEQZl5fXVJJUnqPhbokiSpFVH+f0NEzAAuAh4EHs/MJwAi4grgUMACXZKkFligS5KkVmwGLAT+CpgA3Ax8AVjUsMwiYNtWH3jGjKmjEE9jycyZ06qOoDHGfUqjbbT3KQt0SZLUtMy8A7hj4HZEXAKcDtzasFgP0NfqYy9Zsoy+vv6WM/mBe+xavHhpx7fp/jS2uU9ptK3LPtXb2zPsoLRXcZckSU2LiH0j4q0NTT3Ak8BWDW1bAs90MpckSWOBR9AlSVIrNgVOj4g3UUxxPwI4Dvh6ROwMPAEcBsytLKEkSV3KI+iSJKlpmXktsAC4F/gxMLec9n4kMB94BHgMuKqqjJIkdSuPoEuSpJZk5qnAqYPaFgK7VZNIkqSxoZICPSJuAl4GrCqbjgWmAWcBU4CvZeYpVWSTJEmSJKkKHS/QI6IHmAXskJmry7YpQAL7AT8HFkTEQZnp96dKkiRJkjYIVRxBj/L/GyJiBnAR8CDweGY+ARARVwCHAhbokiRJkqQNQhUF+mbAQuCvKK7+ejPwBWBRwzKLgG1bedDhvkdOGza/d1Kjyf1Jo819SpIkNep4gV5e6fWOgdsRcQlwOnBrw2I9QF8rj7tkyTL6+vpbzuOHo7Ft8eKlHd+m+9TY5f6k0bYu+1Rvb4+D0pIkjVEd/5q1iNg3It7a0NQDPAls1dC2JfBMJ3NJkiRJklSlKqa4bwqcHhFvopjifgRwHPD1iNgZeAI4DJhbQTZJkiRJkirR8SPomXktsAC4F/gxMLec9n4kMB94BHgMuKrT2SRJkiRJqkol34OemacCpw5qWwjsVkUeSZIkSZKq1vEj6JIkSZIkaU0W6JIkSZIk1YAFuiRJkiRJNWCBLkmSJElSDVigS5IkSZJUAxbokiRJkiTVgAW6JEmSJEk1YIEuSZIkSVINWKBLkiRJklQD46sOIEmSuktEfBZ4T3lzQWaeHBGXAvsCz5ftczLz6koCSpLUpSzQJUlS0yLiAOBA4HVAP/DdiDgE2AN4S2YuqjKfJEndzAJdkiS1YhFwYmauBIiIR4Hty39zI2Ib4GqKI+h91cWUJKn7WKBLkqSmZebDAz9HxCsoprq/Gdgf+CjwHHAtcBRwUSuPPWPG1FHLqbFh5sxpVUfQGOM+pdE22vuUBbokSWpZROwCLABOyswEDmm47zzgQ7RYoC9Zsoy+vv6Ws/iBe+xavHhpx7fp/jS2uU9ptK3LPtXb2zPsoLRXcZckSS2JiH2AhcAnM/OyiNg1It7VsEgPsKqadJIkdS+PoEuSpKZFxHbANcB7M/PGsrkHOCcibgSWAccAl1WTUJKk7mWBLkmSWvEJYDJwVkQMtH0Z+DxwGzABmJ+ZV1YTT5Kk7mWBLkmSmpaZJwAnDHP3BZ3MIknSWOM56JIkSZIk1YAFuiRJkiRJNWCBLkmSJElSDVigS5IkSZJUAxbokiRJkiTVgAW6JEmSJEk1YIEuSZIkSVINWKBLkiRJklQDFuiSJEmSJNWABbokSZIkSTVggS5JkiRJUg1YoEuSJEmSVAMW6JIkSZIk1YAFuiRJkiRJNWCBLkmSJElSDVigS5IkSZJUAxbokiRJkiTVgAW6JEmSJEk1ML7qAI0i4jDgFGACcE5mnl9xJEmS1AL7ckmS1l1tjqBHxDbA54B9gd2BYyLi1ZWGkiRJTbMvlyRp/dTpCPoBwI2Z+SuAiLgKeDdw+lrWGwfQ29uzzhveYrON13ld1dv67BfrY+L0GZVsV+1V1f60xdTNK9mu2m9d9qmGdcaNapjRYV+uUWU/rtFmX67RNtp9eU9/f/96RhodEfF3wMaZeUp5ezawV2Yes5ZV9wV+0O58kiTVzJuBW6sO0ci+XJKklqzRl9fpCHov0Dha0AP0NbHejyie2CLgxTbkkiSpTsYBW1H0f3VjXy5J0toN25fXqUB/mqJzHrAl8EwT662gZkcQJElqs/+sOsAw7MslSWrOkH15nQr07wOnRcRM4HngXcDapsRJkqT6sC+XJGk91OYq7pn538CngZuA+4CvZOYPKw0lSZKaZl8uSdL6qc1F4iRJkiRJ2pDV5gi6JEmSJEkbMgt0SZIkSZJqwAJdkiRJkqQasECXJEmSJKkGLNAlSZIkSaoBC3QREfdVnUHdKyIujog9qs4hSWNdROwfETeXP/veqxE17i8NbVtHxHVrWe+0iDitndnU3YbatzR6xlcdQNXLzN2rzqDulZmzq84gSRsa33u1LjLzGeDtVeeQNDwL9JqLiPHAhcBrgJcDDwB/B1wJPAbsAtwD3A4cCWwGHJKZj0bEnsDZwEbAL4FjM/OJcsTrV+W67wXuzcyeiNgcuAR4JbAC+NvMvDEijgc+CGwMrATen5nZgaevigyz3x0BfAXYslxsTmZ+u9yfTgNuHWKd92fmCx0Nr0pFxCeB9wDjgO9R7BM3ZeaO5f2nAWTmaRGxGLgb2ArYEzgJ+ADwInADcDKwHfBtfv9+9xTwgcz8VUT8GXA6MAF4Ajg6M5d05IlKLYiI/YFPU/Shf0CxTy8D3gn0UBRMr2OI/TkiDqToy5dT/B0MPObNFO+9AKdl5v5l+zzg5vLfNazls8JoP1fVzszyiPkfAknxPvu9zNwxIrYF/o1if3gQ2C8zty3X2ysibge2AS7NzNM6H111FxGzgP8P2Bx4Hvg40AdckJl7R8TGwLPAmzPzroj4F+D7mfmNykJ3Aae419+bgJWZ+UZgZ2BTio78tcAXgN2AfYAdy2WuBI6JiInAxcBhmfl64EzgoobHfSAzIzPva2j7v8BPM/NVFAX55yJiOsUHiP0z8zXAtcDxbXquqo+h9rt3Ak9m5huAo4A3N7GOo/QbkLJgfgNFsf06ig92h4+wyhbAF8pZPAcAfwHsUa67M3BcudyuFJ39LsCjwGkRMRP4R+Btmfk6isGAL4z2c5JG0d4U+/QeFP3o4szcg2Iw8ziG2J8jYhJwGfDu8r231QHPET8rrP9TUhfYHvgY8CqKAfYDGu77Z+Brmfla4CqK9+wBLwf+mOI9/aSImNaZuOoyVwDnlvvQ31DsRw8BW0fEJhSfFZ8F9iuX/xOK9zeNwCPoNZeZt0TEkoj4GMWR7VcAU4FfZOa9ABHxNLCwXOUpitH5WRSjpd+OiIGHm97w0HcNsbn9gMPK7T4IvLF8/MOA95WjZH8G3Ddaz0/1NMx+tyPwzojYBlhAMaCztnWmdja5KnYARRHy4/L2FNY+EDzwXvRW4MrM/C1ARMylmLWxAPhJZt5cLncZxUyOGyg+eN5UvseNo5gZJNXVQ5n5c4CI+CUv7bf/nKH3512BZxqOdF/GoPfetVjbZwWNffdn5hMAEfEoxcDogD+lmFFBZl4dEb9uuO/6zFwBrCj3182BpR1JrG4xFdgpM78JkJl3RsSvgAD+HdifYmDwHGC/iLgW+K/M/E01cbuHBXrNRcRfUEx5+2fgUoo31qcopsk1Wj3o9jjgZwPnl0fEOIrR0AFDjcKvAvobtv3KcrkbgS8B1wO/oDi6pTFshP3ulRSDNH8OnBgRr17LOj2dTa6KjQPOycyzACJiU2AT4JaGZSZQvNcA0HAKxOBCvoff91GN72+95e1xwK2Z+RfltibjgJDqbaR+e7j9eQde+j46uK+Hot9uXGZCk9vUhqHxd95P0ZcPeJHhB1EHr2d/rsGG2ncG+u4FFIP2e1B8bjwGOJhiJq7Wwinu9XcA8PXMvBT4NcV0o3FNrPcYsHlEDExD/gjFUaeR3AK8H35XnH+X4g/rp5l5NvAj4JAmt6/uNtR+twnFeeffAD4KvIyXzspY131VY8eNwAcjYmp5HYNrKE6N2DwiZpbTdf9shHXfHxFTynU/DNxU3hcRsXv584cpBgvvAt5YzuwBOBX4p1F+PlKnDLc/PwC8PCJ2K9vfP8S6vwR2iojJ5bVkBp9+JA3n+5QzJyPiIIpT06Rm/Qb4WUT8JUBE/BHFaRQPURxBfxvwYmY+RzH79gQs0JtigV5/F1F8aH0Q+AZwG0XhM6JyWtKhwJkRMXCBr6PWstpngVdExP0UFw35IMV5Ir0R8QjFBWYew2lxG4Kh9rsdKAqlB4EfACdl5q/Xso77ygYkM78DzKcoNh6i6JDPBc6gGOD7PvDDYda9lqLjvht4GPgv4Lzy7l8BcyLiYYqBob/PzF9QDDx+vdznXg+c2JYnJrXfkPtzZq6iKMovj4h7KC76+hKZ+TDF0aqHKd57f9Cx1Op2JwDvioh7KS4a/Otq46gLfQD4ePm+9SXgLzNzZTmN/ecUFxCGYhB+WWY+XlHOrtLT39+/9qUkSapAROwI3DxwFXhJ0uiIiI9TXFH7kYh4PXBReTFCSRXyHHRJkiRpw/M4cGVE9FF8jd/RFeeRhEfQJUmSJEmqBc9BlyRJkiSpBizQJUmSJEmqAQt0SZIkSZJqwAJdkiRJkqQasECXJEmSJKkG/n/f1m+GwOUsmQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1008x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plotting categorical variables\n",
    "fig = plt.figure(1, (14, 8))\n",
    "\n",
    "for i,car in enumerate(car_cat.columns):\n",
    "    ax = plt.subplot(2,2,i+1)\n",
    "    sns.countplot(car_cat[car], order=car_cat[car].value_counts().index)\n",
    "    ax.set_xlabel(None)\n",
    "    ax.set_title(f'Distribution of {car}')\n",
    "    plt.tight_layout()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "American 4 cylinder cars produced in 1973 with medium mpg level seem to dominate the dateset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plot histograms\n",
    "car_num.hist(bins = 20, figsize = (10, 8), color = 'blue')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1224x936 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plot density\n",
    "plt.figure(figsize=(17, 13))\n",
    "col = 1\n",
    "for i in car_num.columns:\n",
    "    plt.subplot(3, 3, col)\n",
    "    sns.distplot(car_num[i], color = 'b')\n",
    "    col += 1 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Displacement and Horsepower seem to be skewed to the right"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#joining the categorical and numerical variables\n",
    "car=pd.concat([car_cat,car_num],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 398 entries, 0 to 397\n",
      "Data columns (total 9 columns):\n",
      " #   Column     Non-Null Count  Dtype  \n",
      "---  ------     --------------  -----  \n",
      " 0   cyl        398 non-null    int64  \n",
      " 1   yr         398 non-null    int64  \n",
      " 2   origin     398 non-null    object \n",
      " 3   mpg_level  398 non-null    object \n",
      " 4   mpg        398 non-null    float64\n",
      " 5   disp       398 non-null    float64\n",
      " 6   hp         398 non-null    float64\n",
      " 7   wt         398 non-null    int64  \n",
      " 8   acc        398 non-null    float64\n",
      "dtypes: float64(4), int64(3), object(2)\n",
      "memory usage: 28.1+ KB\n"
     ]
    }
   ],
   "source": [
    "#checking for attribute type\n",
    "car.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#create dummy varibale for mpg_level and origin and creating a seperate datset for k-means and heirarchical clustering\n",
    "car = pd.get_dummies(car, columns=['origin'])\n",
    "car = pd.get_dummies(car, columns=['mpg_level'])\n",
    "car.head()\n",
    "carH=car.copy()\n",
    "carK=car.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1260x1260 with 56 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#pair plot for the numeric attributes\n",
    "car_attr = car.iloc[:, 0:7]\n",
    "sns.pairplot(car_attr, diag_kind='kde');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There appears to be a linear relationship between the variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "#dropping the created dummy variable\n",
    "car2=car.drop(['origin_america','origin_asia','origin_europe','mpg_level_high','mpg_level_low','mpg_level_medium'],axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x1440 with 7 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#checking of outliers\n",
    "plt.figure(figsize=(25, 20))\n",
    "col = 1\n",
    "for i in car2.columns:\n",
    "    plt.subplot(3, 3, col)\n",
    "    sns.boxplot(car2[i],color='blue')\n",
    "    col += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "#replacing outliers with IQR (Q1 and Q3 +-1.5*IQR)\n",
    "IQR1 = stats.iqr(car2['hp'], interpolation = 'midpoint')\n",
    "IQR2 = stats.iqr(car2['acc'], interpolation = 'midpoint')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Horsepower after imputing outliers\n",
    "Q3 = car2['hp'].quantile(0.75)\n",
    "car2['hp'] = np.where(car2[\"hp\"] >(Q3+1.5*IQR1), 198.5,car2['hp'])\n",
    "sns.boxplot(car2['hp']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#accelaration after imputing outliers\n",
    "Q1 = car2['acc'].quantile(0.25)\n",
    "Q31=car2['acc'].quantile(0.75)\n",
    "car2['acc'] = np.where(car2[\"acc\"] >(Q31+1.5*IQR2),22.10 ,car2['acc'])\n",
    "car2['acc'] = np.where(car2[\"acc\"] <(Q1-1.5*IQR2),(Q1-1.5*IQR2),car2['acc'])\n",
    "sns.boxplot(car2['acc']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#checking for correlation\n",
    "plt.figure(figsize=(10,8))\n",
    "corr=car2.corr()\n",
    "sns.heatmap(corr,annot=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Except Year, most of the variable are correlated with each other"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Heirarchical Clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>cyl</th>\n",
       "      <th>yr</th>\n",
       "      <th>mpg</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>18.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>3504</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>15.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>3693</td>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>18.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3436</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>16.0</td>\n",
       "      <td>304.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3433</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>17.0</td>\n",
       "      <td>302.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>3449</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cyl  yr   mpg   disp     hp    wt   acc\n",
       "0    8  70  18.0  307.0  130.0  3504  12.0\n",
       "1    8  70  15.0  350.0  165.0  3693  11.5\n",
       "2    8  70  18.0  318.0  150.0  3436  11.0\n",
       "3    8  70  16.0  304.0  150.0  3433  12.0\n",
       "4    8  70  17.0  302.0  140.0  3449  10.5"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#separating numeric variables\n",
    "cc = car.iloc[:,0:7] \n",
    "cc.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\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>cyl</th>\n",
       "      <th>yr</th>\n",
       "      <th>mpg</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-0.706439</td>\n",
       "      <td>1.090604</td>\n",
       "      <td>0.673118</td>\n",
       "      <td>0.630870</td>\n",
       "      <td>-1.295498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-1.090751</td>\n",
       "      <td>1.503514</td>\n",
       "      <td>1.589958</td>\n",
       "      <td>0.854333</td>\n",
       "      <td>-1.477038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-0.706439</td>\n",
       "      <td>1.196232</td>\n",
       "      <td>1.197027</td>\n",
       "      <td>0.550470</td>\n",
       "      <td>-1.658577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-0.962647</td>\n",
       "      <td>1.061796</td>\n",
       "      <td>1.197027</td>\n",
       "      <td>0.546923</td>\n",
       "      <td>-1.295498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-0.834543</td>\n",
       "      <td>1.042591</td>\n",
       "      <td>0.935072</td>\n",
       "      <td>0.565841</td>\n",
       "      <td>-1.840117</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        cyl        yr       mpg      disp        hp        wt       acc\n",
       "0  1.498191 -1.627426 -0.706439  1.090604  0.673118  0.630870 -1.295498\n",
       "1  1.498191 -1.627426 -1.090751  1.503514  1.589958  0.854333 -1.477038\n",
       "2  1.498191 -1.627426 -0.706439  1.196232  1.197027  0.550470 -1.658577\n",
       "3  1.498191 -1.627426 -0.962647  1.061796  1.197027  0.546923 -1.295498\n",
       "4  1.498191 -1.627426 -0.834543  1.042591  0.935072  0.565841 -1.840117"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#scaling the variable\n",
    "cc_z = cc.apply(zscore)\n",
    "cc_z.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "#calculating pairwise distance using average linkage method\n",
    "link_method = linkage(cc_z.iloc[:,0:7], method = 'average')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plotting the H-cluster\n",
    "plt.figure(figsize=(25, 10))\n",
    "dendrogram(link_method)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Appers to be to much of a visual clutter, we'll go ahead and cut down the dendrogram to give us 2 clusters/groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWwAAAD7CAYAAABOi672AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAAAMqElEQVR4nO3df7CldV3A8fe9d++ViV10uV10VURS+Sg5hRHBCFYEGZUzDROGNZUOg2ihWZmODU6sTNYwEeY05aJCNI6MmcNQuTlhqzASRqiLY5SfMQaChZ263bDZxWJ/3Nsf57l67o+95+HuefbsZ/f9+oe95znPPZ+9fPc9333Ojx1bWFhAknT0Gx/1AJKkdgy2JBVhsCWpCIMtSUUYbEkqYkOH3/tZwDnAbuBgh48jSceSCWALcD/wdP+BLoN9DvCFDr+/JB3LXgPc039Dq2BHxOeBU4D9zU1vycz7Bpy2G+DJJ59ift7Xeg/D9PRG5ub2jnoMaQXX5vCMj4+xefOJ0DS038BgR8QYcAZwWmYeeAaPexBgfn7BYA+RP0sdrVybQ7fiUnKbJx2j+e+dEfHViHjbcGeSJLXR5pLIZmAH8HZgErgrIjIzP9vmAaanNx7GeFpuZmbTqEeQVuXa7N7AYGfmF4EvLn4dETcDPwW0Cvbc3F7/qjQkMzObmJ3dM+oxpBVcm8MzPj52yI3uwEsiEXFBRFzUd9MY33nyUZJ0hLS5JPIc4LqIeDW9SyJvBN7a5VCSpJUG7rAz89PAdmAn8GXgluYyiSTpCBrr8POwXww87DXs4bjrgcf5yjf+i/37fNOojj4Xn3saZ790etRjHBP6rmGfDjyy5NgoBtIzd9+D/8HDj//PqMeQVnj0P/dy985dox7juNDlW9M1ZKe/4Nn85uu/f9RjSEtc//GvjHqE44Y7bEkqwmBLUhEGW5KKMNiSVITBlqQiDLYkFWGwJakIgy1JRRhsSSrCYEtSEQZbkoow2JJUhMGWpCIMtiQVYbAlqQiDLUlFGGxJKsJgS1IRBluSijDYklSEwZakIgy2JBVhsCWpCIMtSUUYbEkqwmBLUhEGW5KKMNiSVITBlqQiDLYkFWGwJamI1sGOiBsi4tYOZ5EkraFVsCPiIuCNHc8iSVrDwGBHxMnA+4Hf634cSdKhtNlh3wRcAzzZ8SySpDVsWOtgRFwJPJaZOyLiTet5gOnpjes5TctMTk0AMDOzacSTSEu5No+cNYMNXA5siYgHgJOBjRHxgcz8jbYPMDe3l/n5hcMYUQD79x1kcmqC2dk9ox5FWsK1OVzj42OH3OiuGezM/PHFXzc77B99JrGWJA2Pr8OWpCIGXRL5tsy8Fbi1s0kkSWtyhy1JRRhsSSrCYEtSEQZbkoow2JJUhMGWpCIMtiQVYbAlqQiDLUlFGGxJKsJgS1IRBluSijDYklSEwZakIgy2JBVhsCWpCIMtSUUYbEkqwmBLUhEGW5KKMNiSVITBlqQiDLYkFWGwJakIgy1JRRhsSSrCYEtSEQZbkoow2JJUhMGWpCIMtiQVYbAlqQiDLUlFGGxJKmJDmztFxHXAZcACcHNm3tjpVJKkFQbusCPiR4AfA74P+EHg7RERXQ8mSVpqYLAz827gwsw8AJxCb1f+VNeDSZKWanUNOzP3R8T7gH8BdgCPdzqVJGmFVtewATLz2oi4Hvgb4M3Ah9ucNz29cZ2jqd/k1AQAMzObRjyJtJRr88gZGOyIeDlwQmY+kJnfiojb6V3PbmVubi/z8wuHM6OA/fsOMjk1wezsnlGPIi3h2hyu8fGxQ2502+ywvwd4X0RcQO9VIj8D3DK88SRJbbR50vFvge3ATuDLwL2Z+YmuB5MkLdXqGnZmbgW2djqJJGlNvtNRkoow2JJUhMGWpCIMtiQVYbAlqQiDLUlFGGxJKsJgS1IRBluSijDYklSEwZakIgy2JBVhsCWpCIMtSUUYbEkqwmBLUhEGW5KKMNiSVITBlqQiDLYkFWGwJakIgy1JRRhsSSrCYEtSEQZbkoow2JJUhMGWpCIMtiQVYbAlqQiDLUlFGGxJKsJgS1IRBluSijDYklTEhjZ3iohrgZ9rvtyeme/ubiRJ0moG7rAj4mLgtcCrgLOAsyPi0o7nkiQt02aHvRt4Z2buA4iIfwVe1OlUkqQVBgY7Mx9c/HVEvIzepZHz2z7A9PTG9U2mJSanJgCYmdk04kmkpVybR06ra9gAEfG9wHbgXZn5jbbnzc3tZX5+YT2zqc/+fQeZnJpgdnbPqEeRlnBtDtf4+NghN7qtXiUSEecDO4D3ZOafD3E2SVJLA3fYEXEqcAdweWZ+rvOJJEmranNJ5LeAE4AbI2Lxtm2Zua2zqSRJK7R50vEdwDuOwCySpDX4TkdJKsJgS1IRBluSijDYklSEwZakIgy2JBVhsCWpCIMtSUUYbEkqwmBLUhEGW5KKMNiSVITBlqQiDLYkFWGwJakIgy1JRRhsSSrCYEtSEQZbkoow2JJUhMGWpCIMtiQVYbAlqQiDLUlFGGxJKsJgS1IRBluSijDYklSEwZakIgy2JBVhsCWpCIMtSUUYbEkqYkObO0XEScC9wOsy85FOJ5IkrWrgDjsizgXuAc7ofhxJ0qG0uSTyZuBq4ImOZ5EkrWHgJZHMvBIgIrqfRpJ0SK2uYR+O6emNXT/EcWFyagKAmZlNI55EWsq1eeR0Huy5ub3Mzy90/TDHvP37DjI5NcHs7J5RjyIt4docrvHxsUNudH1ZnyQVYbAlqYjWl0Qy88UdziFJGsAdtiQVYbAlqQiDLUlFGGxJKsJgS1IRBluSijDYklSEwZakIgy2JBVhsCWpCIMtSUUYbEkqwmBLUhEGW5KKMNiSVITBlqQiDLYkFWGwJakIgy1JRRhsSSrCYEtSEQZbkoow2JJUhMGWpCIMtiQVYbAlqQiDLUlFGGxJKsJgS1IRBluSijDYklSEwZakIgy2JBVhsCWpiA1t7hQRvwC8F5gE/igz/6TTqSRJKwzcYUfEC4D3AxcAZwFXRcSZHc8lSVqmzQ77YuBzmfnfABHxKeAy4LoB500AjI+PHdaA6tl80rPYMDnhz1NHHdfmcPX9HCeWH2sT7OcDu/u+3g38UIvztgBs3nxii7tqkGuuOG/UI0ircm12ZgvwUP8NbYI9Diz0fT0GzLc4737gNfQCf7DlgJJ0vJugF+v7lx9oE+xd9MK76HnAEy3Oexq4p810kqQlHlrtxjbB/ntga0TMAE8BPwtcNcTBJEktDHyVSGY+DlwDfB54ALgtM/+p47kkScuMLSwsDL6XJGnkfKejJBVhsCWpCIMtSUUYbEkqotWHP6kbEXE9sCMz74yIMeBW4GuZeUNzfAL4Q+ASev+vbsjMbc2xlwE3A98N7AV+OTO/HhGnAh8ELsvMNm9wkla1uD6BU4B30XsD3beAX8vML0XEycCH6H3G0FPAn2XmHzfnngl8GNjYnPeezPw71+fhcYc9IhFxHvCKJtavoPcH47Jld3sLcAbwSuAc4NcjYvFjAT4ObMvMM4FrgU9FxFhmPkbv5Ze/egR+GzpGLa5P4N+BPwAuycyzgN8Fbm/u9gF6m4UzgfOAn4yI1zXH/hS4pTnnCuCTEbHB9Xl4DPbobKW3AwG4Gvgo8JfL7nMpvV3Lgcx8EvgE8IvNJyi+vPmazPwMvZ3Mq5rzPgr8dkRMdfo70LFsK731+TRwZWYufp7Ql4DnNWvrbOBjmXkwM/cB2/nOpmMC2Nz8ehPwf33f2/W5TgZ7BCLiOfTe7n8nQGa+LTNvW+WupwKP9X29C3hhc/sTy/5KuXiMzHwCmAPOH/rwOub1r8/MfCQztze3jwE3An/dBPo+4JciYjIiNtJ7F/SW5ttcTS/Ku+i9W/pXMvMAuD4Ph8EejZcCu5tFv5bVPnjr4Cq39x9b9DAQhzmnjk8r1mdEnAh8sjl2ZXPzO+mtw53AHcBngX0RcQLwF8CbMvOFwA8DNzXXrxe5PtfBYI/GAu1+9o/S+3jbRc+nt5N+FNjS7HiWH1u0Hz8lUeuzZH1GxIuAe+mtpwsz85vNoZOAd2fmKzPzYnqbhn+j95zLd2XmpwEy8x+BB4Fz+x7D9bkOBns0HgKe2+xE1vJXwBURsaH5a+obgDsycxe9PxiXA0TET9D7yNuv9Z17OvD1YQ+u48K312dEbALuAm7PzDdk5v/23e+tNP+QSUQ8l97O+zZ6a/PZEfHq5thL6D0xubPvXNfnOviyvhHIzG9GxBeAC4HPrHHXDwEvAb4KTAE3ZebdzbGfBz4SEe+l94TO6xevaTd/eE4B/qGj34KOYcvW51nAacClEXFp390uAn4f+FhE/DO93fXvZOb9AM19P9hsSg4AV2XmQ80x1+c6+eFPI9LsPq7JzJ/u4HtvBWb9x5K1Xq7Po5OXREYkM+8FMiIuGeb3bZ7Y+QFg2zC/r44vrs+jkztsSSrCHbYkFWGwJakIgy1JRRhsSSrCYEtSEQZbkor4f+Eu0ZSMg+OwAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# dendrogram function to arrive at dendrogram\n",
    "dendrogram(\n",
    "    link_method,\n",
    "    truncate_mode='lastp',  \n",
    "    p=2,  \n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1,\n",
       "       1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 1, 1, 2, 2, 2, 2, 1, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2,\n",
       "       2, 1, 2, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1,\n",
       "       1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2], dtype=int32)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#vieweing the clusters formed\n",
    "clusters = fcluster(link_method, 2, criterion='maxclust')\n",
    "clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cyl</th>\n",
       "      <th>yr</th>\n",
       "      <th>mpg</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "      <th>clusters_H</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-0.706439</td>\n",
       "      <td>1.090604</td>\n",
       "      <td>0.673118</td>\n",
       "      <td>0.630870</td>\n",
       "      <td>-1.295498</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-1.090751</td>\n",
       "      <td>1.503514</td>\n",
       "      <td>1.589958</td>\n",
       "      <td>0.854333</td>\n",
       "      <td>-1.477038</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-0.706439</td>\n",
       "      <td>1.196232</td>\n",
       "      <td>1.197027</td>\n",
       "      <td>0.550470</td>\n",
       "      <td>-1.658577</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-0.962647</td>\n",
       "      <td>1.061796</td>\n",
       "      <td>1.197027</td>\n",
       "      <td>0.546923</td>\n",
       "      <td>-1.295498</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-0.834543</td>\n",
       "      <td>1.042591</td>\n",
       "      <td>0.935072</td>\n",
       "      <td>0.565841</td>\n",
       "      <td>-1.840117</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        cyl        yr       mpg      disp        hp        wt       acc  \\\n",
       "0  1.498191 -1.627426 -0.706439  1.090604  0.673118  0.630870 -1.295498   \n",
       "1  1.498191 -1.627426 -1.090751  1.503514  1.589958  0.854333 -1.477038   \n",
       "2  1.498191 -1.627426 -0.706439  1.196232  1.197027  0.550470 -1.658577   \n",
       "3  1.498191 -1.627426 -0.962647  1.061796  1.197027  0.546923 -1.295498   \n",
       "4  1.498191 -1.627426 -0.834543  1.042591  0.935072  0.565841 -1.840117   \n",
       "\n",
       "   clusters_H  \n",
       "0           1  \n",
       "1           1  \n",
       "2           1  \n",
       "3           1  \n",
       "4           1  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#attaching the clusters formed to the scales data\n",
    "cc_z['clusters_H'] = clusters\n",
    "cc_z.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    100\n",
       "2    298\n",
       "Name: clusters_H, dtype: int64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#vieweing the distribution of clusters\n",
    "cc_z.clusters_H.value_counts().sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        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>cyl</th>\n",
       "      <th>yr</th>\n",
       "      <th>mpg</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "      <th>clusters_H</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>18.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>3504</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>15.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>3693</td>\n",
       "      <td>11.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>18.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3436</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>16.0</td>\n",
       "      <td>304.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3433</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>17.0</td>\n",
       "      <td>302.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>3449</td>\n",
       "      <td>10.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cyl  yr   mpg   disp     hp    wt   acc  clusters_H\n",
       "0    8  70  18.0  307.0  130.0  3504  12.0           1\n",
       "1    8  70  15.0  350.0  165.0  3693  11.5           1\n",
       "2    8  70  18.0  318.0  150.0  3436  11.0           1\n",
       "3    8  70  16.0  304.0  150.0  3433  12.0           1\n",
       "4    8  70  17.0  302.0  140.0  3449  10.5           1"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#attaching the clusters formed to the original data\n",
    "cc['clusters_H']=clusters\n",
    "carH['clusters_H']=clusters\n",
    "cc.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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>cyl</th>\n",
       "      <th>yr</th>\n",
       "      <th>mpg</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "      <th>clusters_H</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>18.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>3504</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>15.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>3693</td>\n",
       "      <td>11.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>18.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3436</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>16.0</td>\n",
       "      <td>304.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3433</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>17.0</td>\n",
       "      <td>302.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>3449</td>\n",
       "      <td>10.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cyl  yr   mpg   disp     hp    wt   acc  clusters_H\n",
       "0    8  70  18.0  307.0  130.0  3504  12.0           1\n",
       "1    8  70  15.0  350.0  165.0  3693  11.5           1\n",
       "2    8  70  18.0  318.0  150.0  3436  11.0           1\n",
       "3    8  70  16.0  304.0  150.0  3433  12.0           1\n",
       "4    8  70  17.0  302.0  140.0  3449  10.5           1"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#create a new data set named Hclus\n",
    "Hclus=cc\n",
    "Hclus.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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>cyl</th>\n",
       "      <th>yr</th>\n",
       "      <th>mpg</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "      <th>Freq</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>clusters_H</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7.980000</td>\n",
       "      <td>73.740000</td>\n",
       "      <td>14.684000</td>\n",
       "      <td>345.470000</td>\n",
       "      <td>160.400000</td>\n",
       "      <td>4121.560000</td>\n",
       "      <td>12.702000</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.607383</td>\n",
       "      <td>76.771812</td>\n",
       "      <td>26.477852</td>\n",
       "      <td>142.404362</td>\n",
       "      <td>85.479866</td>\n",
       "      <td>2584.137584</td>\n",
       "      <td>16.529866</td>\n",
       "      <td>298</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 cyl         yr        mpg        disp          hp  \\\n",
       "clusters_H                                                           \n",
       "1           7.980000  73.740000  14.684000  345.470000  160.400000   \n",
       "2           4.607383  76.771812  26.477852  142.404362   85.479866   \n",
       "\n",
       "                     wt        acc  Freq  \n",
       "clusters_H                                \n",
       "1           4121.560000  12.702000   100  \n",
       "2           2584.137584  16.529866   298  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#aggregating the numerical variable with the clusters formed with the mean\n",
    "aggdata=cc.iloc[:,0:8].groupby('clusters_H').mean()\n",
    "aggdata['Freq']=cc.clusters_H.value_counts().sort_index()\n",
    "aggdata"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Clearly shows two disting group with a difference in average between the clusters and variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plotting the clusters formed\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.scatterplot(x=\"mpg\", y=\"hp\", hue=\"clusters_H\",\n",
    "              data=cc_z, \n",
    "                    palette=['green','brown']);\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## K-Means Clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>cyl</th>\n",
       "      <th>yr</th>\n",
       "      <th>mpg</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-0.706439</td>\n",
       "      <td>1.090604</td>\n",
       "      <td>0.673118</td>\n",
       "      <td>0.630870</td>\n",
       "      <td>-1.295498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-1.090751</td>\n",
       "      <td>1.503514</td>\n",
       "      <td>1.589958</td>\n",
       "      <td>0.854333</td>\n",
       "      <td>-1.477038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-0.706439</td>\n",
       "      <td>1.196232</td>\n",
       "      <td>1.197027</td>\n",
       "      <td>0.550470</td>\n",
       "      <td>-1.658577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-0.962647</td>\n",
       "      <td>1.061796</td>\n",
       "      <td>1.197027</td>\n",
       "      <td>0.546923</td>\n",
       "      <td>-1.295498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-0.834543</td>\n",
       "      <td>1.042591</td>\n",
       "      <td>0.935072</td>\n",
       "      <td>0.565841</td>\n",
       "      <td>-1.840117</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        cyl        yr       mpg      disp        hp        wt       acc\n",
       "0  1.498191 -1.627426 -0.706439  1.090604  0.673118  0.630870 -1.295498\n",
       "1  1.498191 -1.627426 -1.090751  1.503514  1.589958  0.854333 -1.477038\n",
       "2  1.498191 -1.627426 -0.706439  1.196232  1.197027  0.550470 -1.658577\n",
       "3  1.498191 -1.627426 -0.962647  1.061796  1.197027  0.546923 -1.295498\n",
       "4  1.498191 -1.627426 -0.834543  1.042591  0.935072  0.565841 -1.840117"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#seperating the numeric values\n",
    "cc = car.iloc[:,0:7] \n",
    "cc_z1 = cc.apply(zscore)\n",
    "cc_z1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2785.9999999999995, 1294.8418950727323, 946.019790855379, 738.3923281527318]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#calculatint the within sum of squares\n",
    "wss =[] \n",
    "for i in range(1,5):\n",
    "    KM = KMeans(n_clusters=i)\n",
    "    KM.fit(cc_z1)\n",
    "    wss.append(KM.inertia_)\n",
    "wss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plotting the WSS against the number of cluster to come up with optimal number of clusters using Elbow-method\n",
    "plt.plot(range(1,5), wss);\n",
    "plt.title('Elbow Method');\n",
    "plt.xlabel(\"Number of Clusters\")\n",
    "plt.ylabel(\"WSS\");\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "#using 2 centroids for clustering\n",
    "k_means = KMeans(n_clusters = 2)\n",
    "k_means.fit(cc_z1)\n",
    "labels = k_means.labels_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.48235946103916116"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculating silhouette_score\n",
    "silhouette_score(cc_z1,labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "#calculating silhouette score for different centroids\n",
    "kmeans_kwargs = {\n",
    "   \"init\": \"random\",\n",
    "   \"n_init\": 10,\n",
    "   \"max_iter\": 300,\n",
    "   \"random_state\": 42,\n",
    "}\n",
    "\n",
    "\n",
    "silhouette_coefficients = []\n",
    "\n",
    " # Notice you start at 2 clusters for silhouette coefficient\n",
    "for k in range(2, 7):\n",
    "    kmeans = KMeans(n_clusters=k, **kmeans_kwargs)\n",
    "    kmeans.fit(cc_z1)\n",
    "    score = silhouette_score(cc_z1,kmeans.labels_)\n",
    "    silhouette_coefficients.append(score)\n",
    "    \n",
    "\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plotting silhouette score for different centroids\n",
    "plt.plot(range(2, 7), silhouette_coefficients)\n",
    "plt.xticks(range(2, 7))\n",
    "plt.xlabel(\"Number of Clusters\")\n",
    "plt.ylabel(\"Silhouette Coefficient\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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>cyl</th>\n",
       "      <th>yr</th>\n",
       "      <th>mpg</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "      <th>cluster_K</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>18.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>3504</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>15.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>3693</td>\n",
       "      <td>11.5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>18.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3436</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>16.0</td>\n",
       "      <td>304.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3433</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>17.0</td>\n",
       "      <td>302.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>3449</td>\n",
       "      <td>10.5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cyl  yr   mpg   disp     hp    wt   acc  cluster_K\n",
       "0    8  70  18.0  307.0  130.0  3504  12.0          0\n",
       "1    8  70  15.0  350.0  165.0  3693  11.5          0\n",
       "2    8  70  18.0  318.0  150.0  3436  11.0          0\n",
       "3    8  70  16.0  304.0  150.0  3433  12.0          0\n",
       "4    8  70  17.0  302.0  140.0  3449  10.5          0"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#attaching the labels to the datasets\n",
    "cc[\"cluster_K\"] = labels\n",
    "carK['cluster_K']=labels\n",
    "Kclus=cc\n",
    "Kclus.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    105\n",
       "1    293\n",
       "Name: cluster_K, dtype: int64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#vieweing the distribution of clusters\n",
    "cc.cluster_K.value_counts().sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cyl</th>\n",
       "      <th>yr</th>\n",
       "      <th>mpg</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "      <th>cluster_K</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-0.706439</td>\n",
       "      <td>1.090604</td>\n",
       "      <td>0.673118</td>\n",
       "      <td>0.630870</td>\n",
       "      <td>-1.295498</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-1.090751</td>\n",
       "      <td>1.503514</td>\n",
       "      <td>1.589958</td>\n",
       "      <td>0.854333</td>\n",
       "      <td>-1.477038</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-0.706439</td>\n",
       "      <td>1.196232</td>\n",
       "      <td>1.197027</td>\n",
       "      <td>0.550470</td>\n",
       "      <td>-1.658577</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-0.962647</td>\n",
       "      <td>1.061796</td>\n",
       "      <td>1.197027</td>\n",
       "      <td>0.546923</td>\n",
       "      <td>-1.295498</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.498191</td>\n",
       "      <td>-1.627426</td>\n",
       "      <td>-0.834543</td>\n",
       "      <td>1.042591</td>\n",
       "      <td>0.935072</td>\n",
       "      <td>0.565841</td>\n",
       "      <td>-1.840117</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        cyl        yr       mpg      disp        hp        wt       acc  \\\n",
       "0  1.498191 -1.627426 -0.706439  1.090604  0.673118  0.630870 -1.295498   \n",
       "1  1.498191 -1.627426 -1.090751  1.503514  1.589958  0.854333 -1.477038   \n",
       "2  1.498191 -1.627426 -0.706439  1.196232  1.197027  0.550470 -1.658577   \n",
       "3  1.498191 -1.627426 -0.962647  1.061796  1.197027  0.546923 -1.295498   \n",
       "4  1.498191 -1.627426 -0.834543  1.042591  0.935072  0.565841 -1.840117   \n",
       "\n",
       "   cluster_K  \n",
       "0          0  \n",
       "1          0  \n",
       "2          0  \n",
       "3          0  \n",
       "4          0  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#attaching the clsuters to the scaled data\n",
    "cc_z1[\"cluster_K\"] = labels\n",
    "cc_z1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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>cyl</th>\n",
       "      <th>yr</th>\n",
       "      <th>mpg</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "      <th>Freq</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cluster_K</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7.923810</td>\n",
       "      <td>73.742857</td>\n",
       "      <td>14.851429</td>\n",
       "      <td>341.809524</td>\n",
       "      <td>158.000000</td>\n",
       "      <td>4093.771429</td>\n",
       "      <td>12.867619</td>\n",
       "      <td>105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.569966</td>\n",
       "      <td>76.822526</td>\n",
       "      <td>26.619113</td>\n",
       "      <td>140.250853</td>\n",
       "      <td>85.061433</td>\n",
       "      <td>2567.860068</td>\n",
       "      <td>16.535836</td>\n",
       "      <td>293</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                cyl         yr        mpg        disp          hp  \\\n",
       "cluster_K                                                           \n",
       "0          7.923810  73.742857  14.851429  341.809524  158.000000   \n",
       "1          4.569966  76.822526  26.619113  140.250853   85.061433   \n",
       "\n",
       "                    wt        acc  Freq  \n",
       "cluster_K                                \n",
       "0          4093.771429  12.867619   105  \n",
       "1          2567.860068  16.535836   293  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#aggregating the numerical variable with the clusters formed with the mean\n",
    "aggdata=cc.iloc[:,0:8].groupby('cluster_K').mean()\n",
    "aggdata['Freq']=cc.cluster_K.value_counts().sort_index()\n",
    "aggdata"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Clearly shows two disting group with a difference in average between the clusters and variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plotting the clusters\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.scatterplot(x=\"mpg\", y=\"hp\", hue=\"cluster_K\",\n",
    "              data=cc_z1, \n",
    "                    palette=['green','brown']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    100\n",
       "2    298\n",
       "Name: clusters_H, dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "carH.clusters_H.value_counts().sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    105\n",
       "1    293\n",
       "Name: cluster_K, dtype: int64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "carK.cluster_K.value_counts().sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(398, 14)"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "carH.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(398, 14)"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "carK.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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>cyl</th>\n",
       "      <th>yr</th>\n",
       "      <th>mpg</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "      <th>origin_america</th>\n",
       "      <th>origin_asia</th>\n",
       "      <th>origin_europe</th>\n",
       "      <th>mpg_level_high</th>\n",
       "      <th>mpg_level_low</th>\n",
       "      <th>mpg_level_medium</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>18.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>3504</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>15.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>3693</td>\n",
       "      <td>11.5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>18.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3436</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>16.0</td>\n",
       "      <td>304.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3433</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>17.0</td>\n",
       "      <td>302.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>3449</td>\n",
       "      <td>10.5</td>\n",
       "      <td>1</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",
       "</div>"
      ],
      "text/plain": [
       "   cyl  yr   mpg   disp     hp    wt   acc  origin_america  origin_asia  \\\n",
       "0    8  70  18.0  307.0  130.0  3504  12.0               1            0   \n",
       "1    8  70  15.0  350.0  165.0  3693  11.5               1            0   \n",
       "2    8  70  18.0  318.0  150.0  3436  11.0               1            0   \n",
       "3    8  70  16.0  304.0  150.0  3433  12.0               1            0   \n",
       "4    8  70  17.0  302.0  140.0  3449  10.5               1            0   \n",
       "\n",
       "   origin_europe  mpg_level_high  mpg_level_low  mpg_level_medium  \n",
       "0              0               0              0                 1  \n",
       "1              0               0              1                 0  \n",
       "2              0               0              0                 1  \n",
       "3              0               0              1                 0  \n",
       "4              0               0              0                 1  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Linear regression on the original dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = car.drop(['mpg','origin_europe','mpg_level_low'], axis=1)\n",
    "# the dependent variable\n",
    "y = car[['mpg']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split X and y into training and test set in 70:30 ratio\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.30, random_state=15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regression_model = LinearRegression()\n",
    "regression_model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The coefficient for cyl is -0.5134441386218929\n",
      "The coefficient for yr is 0.44346504291168326\n",
      "The coefficient for disp is 0.010688858394647005\n",
      "The coefficient for hp is 0.010315514536313984\n",
      "The coefficient for wt is -0.004538788568737149\n",
      "The coefficient for acc is 0.19183425608862584\n",
      "The coefficient for origin_america is -1.7306209513689026\n",
      "The coefficient for origin_asia is -0.8976724344009384\n",
      "The coefficient for mpg_level_high is 8.55237466381703\n",
      "The coefficient for mpg_level_medium is 1.5941218694850463\n"
     ]
    }
   ],
   "source": [
    "for idx, col_name in enumerate(X_train.columns):\n",
    "    print(\"The coefficient for {} is {}\".format(col_name, regression_model.coef_[0][idx]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The intercept for our model is -1.6635717568650676\n"
     ]
    }
   ],
   "source": [
    "intercept = regression_model.intercept_[0]\n",
    "print(\"The intercept for our model is {}\".format(intercept))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8967703023839787"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regression_model.score(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9037421476349177"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "O=regression_model.score(X_test, y_test)\n",
    "O"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Linear regression on data with K means cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "#renaming the cluster labels to light and heavy vehicles and creating dummy variables of it\n",
    "carK['cluster_K']=carK['cluster_K'].astype('category')\n",
    "carK['cluster_K'] = carK['cluster_K'].replace({1: 'heavy', 0: 'light'})\n",
    "carK = pd.get_dummies(carK, columns=['cluster_K'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "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>cyl</th>\n",
       "      <th>yr</th>\n",
       "      <th>mpg</th>\n",
       "      <th>disp</th>\n",
       "      <th>hp</th>\n",
       "      <th>wt</th>\n",
       "      <th>acc</th>\n",
       "      <th>origin_america</th>\n",
       "      <th>origin_asia</th>\n",
       "      <th>origin_europe</th>\n",
       "      <th>mpg_level_high</th>\n",
       "      <th>mpg_level_low</th>\n",
       "      <th>mpg_level_medium</th>\n",
       "      <th>cluster_K_heavy</th>\n",
       "      <th>cluster_K_light</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>18.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>3504</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1</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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>15.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>3693</td>\n",
       "      <td>11.5</td>\n",
       "      <td>1</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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>18.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3436</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1</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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>16.0</td>\n",
       "      <td>304.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3433</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1</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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>17.0</td>\n",
       "      <td>302.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>3449</td>\n",
       "      <td>10.5</td>\n",
       "      <td>1</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>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cyl  yr   mpg   disp     hp    wt   acc  origin_america  origin_asia  \\\n",
       "0    8  70  18.0  307.0  130.0  3504  12.0               1            0   \n",
       "1    8  70  15.0  350.0  165.0  3693  11.5               1            0   \n",
       "2    8  70  18.0  318.0  150.0  3436  11.0               1            0   \n",
       "3    8  70  16.0  304.0  150.0  3433  12.0               1            0   \n",
       "4    8  70  17.0  302.0  140.0  3449  10.5               1            0   \n",
       "\n",
       "   origin_europe  mpg_level_high  mpg_level_low  mpg_level_medium  \\\n",
       "0              0               0              0                 1   \n",
       "1              0               0              1                 0   \n",
       "2              0               0              0                 1   \n",
       "3              0               0              1                 0   \n",
       "4              0               0              0                 1   \n",
       "\n",
       "   cluster_K_heavy  cluster_K_light  \n",
       "0                0                1  \n",
       "1                0                1  \n",
       "2                0                1  \n",
       "3                0                1  \n",
       "4                0                1  "
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "carK.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = carK.drop(['mpg','origin_europe','mpg_level_low','cluster_K_light'], axis=1)\n",
    "# the dependent variable\n",
    "y = carK[['mpg']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split X and y into training and test set in 70:30 ratio\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.30, random_state=12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regression_model = LinearRegression()\n",
    "regression_model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The coefficient for cyl is -1.1945995644777496\n",
      "The coefficient for yr is 0.43186510415059687\n",
      "The coefficient for disp is 0.017477496279109942\n",
      "The coefficient for hp is -0.01013804583590585\n",
      "The coefficient for wt is -0.004068430169386417\n",
      "The coefficient for acc is 0.1856482874625026\n",
      "The coefficient for origin_america is -1.691831549430407\n",
      "The coefficient for origin_asia is -0.7407779192303018\n",
      "The coefficient for mpg_level_high is 9.283120939156879\n",
      "The coefficient for mpg_level_medium is 2.2500017142312516\n",
      "The coefficient for cluster_K_heavy is -2.5115140143384758\n"
     ]
    }
   ],
   "source": [
    "for idx, col_name in enumerate(X_train.columns):\n",
    "    print(\"The coefficient for {} is {}\".format(col_name, regression_model.coef_[0][idx]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The intercept for our model is 3.71566082105576\n"
     ]
    }
   ],
   "source": [
    "intercept = regression_model.intercept_[0]\n",
    "print(\"The intercept for our model is {}\".format(intercept))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8942370456543635"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regression_model.score(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9117893808052381"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "K=regression_model.score(X_test, y_test)\n",
    "K"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Linear regression on data with H-clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "#renaming the cluster labels to light and heavy vehicles and creating summy variable of it\n",
    "carH['clusters_H']=carH['clusters_H'].astype('category')\n",
    "carH['clusters_H'] = carH['clusters_H'].replace({1: 'heavy', 2: 'light'})\n",
    "carH = pd.get_dummies(carH, columns=['clusters_H'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = carH.drop(['mpg','origin_europe','mpg_level_low','clusters_H_light'], axis=1)\n",
    "# the dependent variable\n",
    "y = carH[['mpg']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split X and y into training and test set in 70:30 ratio\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.30, random_state=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regression_model = LinearRegression()\n",
    "regression_model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The coefficient for cyl is -1.0104832432575337\n",
      "The coefficient for yr is 0.4475417357550159\n",
      "The coefficient for disp is 0.01511520052461449\n",
      "The coefficient for hp is -0.013301584387234262\n",
      "The coefficient for wt is -0.0042641797806725655\n",
      "The coefficient for acc is 0.11805139164484654\n",
      "The coefficient for origin_america is -2.1174569315391114\n",
      "The coefficient for origin_asia is -1.3974915348558097\n",
      "The coefficient for mpg_level_high is 8.565948239298276\n",
      "The coefficient for mpg_level_medium is 1.6577250698582757\n",
      "The coefficient for clusters_H_heavy is 2.03897446880741\n"
     ]
    }
   ],
   "source": [
    "for idx, col_name in enumerate(X_train.columns):\n",
    "    print(\"The coefficient for {} is {}\".format(col_name, regression_model.coef_[0][idx]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The intercept for our model is 2.5727293182326036\n"
     ]
    }
   ],
   "source": [
    "intercept = regression_model.intercept_[0]\n",
    "print(\"The intercept for our model is {}\".format(intercept))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8988409890950728"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regression_model.score(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9010238373846718"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "H=regression_model.score(X_test, y_test)\n",
    "H"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "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>Model</th>\n",
       "      <th>r^2 on Test</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Linear Regression on Original Data set</td>\n",
       "      <td>90.374215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Linear Regression with K means clusters</td>\n",
       "      <td>91.178938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Linear Regression with Heirarchical clusters</td>\n",
       "      <td>90.102384</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Model  r^2 on Test\n",
       "0        Linear Regression on Original Data set    90.374215\n",
       "1       Linear Regression with K means clusters    91.178938\n",
       "2  Linear Regression with Heirarchical clusters    90.102384"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "modellists = []\n",
    "modellists.append(['Linear Regression on Original Data set', O*100])\n",
    "modellists.append(['Linear Regression with K means clusters', K*100])\n",
    "modellists.append(['Linear Regression with Heirarchical clusters', H*100])\n",
    "mdl_df = pd.DataFrame(modellists, columns = ['Model','r^2 on Test'])\n",
    "mdl_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Summary\n",
    "K-means appears to explain the highest variation in the datset, but with a difference of only 1% when compared with other models, to get more clarity a larger dataset may be used, since this is a dataset of used cars it doesn't give us how many previous owners has the cars seen which might be helful variable,the gender of the previous owners, the reason/purpose that the cars were being used is also an important factor which the dataset doen't capture. With the above mentioned features it may be possible to get a higher accuracy or explainability of the models and its variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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