StatisticalLearning_Project2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q1 Import the necessary libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy.stats import zscore, ttest_ind, mannwhitneyu, chisquare, levene, f_oneway\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q2 Read the data as a data frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "insurance_df = pd.read_csv ('C:/Users/kulkarni1/Documents/AIMLWorkspace/Databases/insurance.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q3.a Shape of the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of the data:  (1338, 7)\n"
     ]
    }
   ],
   "source": [
    "print ('Shape of the data: ', insurance_df.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q3.b Data type of each attribute"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Datatypes of the columns\n",
      " age           int64\n",
      "sex          object\n",
      "bmi         float64\n",
      "children      int64\n",
      "smoker       object\n",
      "region       object\n",
      "charges     float64\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "print ('Datatypes of the columns\\n', insurance_df.dtypes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q3.c Checking the presence of missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Check if any values are NULL:  False\n"
     ]
    }
   ],
   "source": [
    "# Pandas recognize Empty and \"NA\" as missing values. This is checked by isnull() function\n",
    "print ('Check if any values are NULL: ', insurance_df.isnull().values.any())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q3.d 5 point summary of numerical attributes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>age</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>charges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1338.000000</td>\n",
       "      <td>1338.000000</td>\n",
       "      <td>1338.000000</td>\n",
       "      <td>1338.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>39.207025</td>\n",
       "      <td>30.663397</td>\n",
       "      <td>1.094918</td>\n",
       "      <td>13270.422265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>14.049960</td>\n",
       "      <td>6.098187</td>\n",
       "      <td>1.205493</td>\n",
       "      <td>12110.011237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>15.960000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1121.873900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>27.000000</td>\n",
       "      <td>26.296250</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4740.287150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>39.000000</td>\n",
       "      <td>30.400000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>9382.033000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>51.000000</td>\n",
       "      <td>34.693750</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>16639.912515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>64.000000</td>\n",
       "      <td>53.130000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>63770.428010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               age          bmi     children       charges\n",
       "count  1338.000000  1338.000000  1338.000000   1338.000000\n",
       "mean     39.207025    30.663397     1.094918  13270.422265\n",
       "std      14.049960     6.098187     1.205493  12110.011237\n",
       "min      18.000000    15.960000     0.000000   1121.873900\n",
       "25%      27.000000    26.296250     0.000000   4740.287150\n",
       "50%      39.000000    30.400000     1.000000   9382.033000\n",
       "75%      51.000000    34.693750     2.000000  16639.912515\n",
       "max      64.000000    53.130000     5.000000  63770.428010"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "insurance_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q3.e Distribution of ‘bmi’, ‘age’ and ‘charges’ columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20746690f28>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Bngt8C/jDzHxt4UY6PBHRAf40Mz8winVon/MD7eoS4AuZeWdEvJMRem0ARMQ6mhPsbwOeA26lfZ2wSOtQPtwlaRSVn5aRpFFkuEtSQYa7JBVkuEtSQYa7JBVkuEtSQYa7JBX0f0TmDZM0jQ3SAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#from pandas.plotting import scatter_matrix\n",
    "#scatter_matrix(iris_df, alpha=0.2, figsize=(10, 10))\n",
    "#plt.show()\n",
    "\n",
    "insurance_df['age'].hist()\n",
    "#sns.countplot(x='age', data=insurance_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x207469543c8>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "insurance_df['bmi'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20746a6d2b0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "insurance_df['charges'].hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q3.f Measure of skewness of ‘bmi’, ‘age’ and ‘charges’ columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "age         0.055673\n",
       "bmi         0.284047\n",
       "children    0.938380\n",
       "charges     1.515880\n",
       "dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "insurance_df.skew()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Applying Bulmer's rule to interpret the skewnees:\n",
    "- The skewness for age and bmi are within -0.5  and 0.5. The distribution is approximately symmetric\n",
    "- The skewnees for children is 0.94, which is close to 1. The distribution is moderately skewed.\n",
    "- The skewness for charges is 1.51, which is more than 1. The distribution is highlyt skewed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#cols = insurance_df.select_dtypes (include=[np.number])\n",
    "#cols = cols.apply (zscore)\n",
    "\n",
    "insurance_z = insurance_df[['age', 'bmi', 'charges']].copy()\n",
    "insurance_z['age_z'] = zscore(insurance_df['age'])\n",
    "insurance_z['bmi_z'] = zscore(insurance_df['bmi'])\n",
    "insurance_z['charges_z'] = zscore(insurance_df['charges'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q3. g Checking the presence of outliers in ‘bmi’, ‘age’ and ‘charges' columns\n",
    "Outliers are checked from the BoxPlot and the Zscore (>1.5 of IQR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>smoker</th>\n",
       "      <th>region</th>\n",
       "      <th>charges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>33.770</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1725.55230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>62</td>\n",
       "      <td>female</td>\n",
       "      <td>26.290</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>27808.72510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>34.100</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1137.01100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>63</td>\n",
       "      <td>female</td>\n",
       "      <td>23.085</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>14451.83515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>26.315</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2198.18985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>63</td>\n",
       "      <td>male</td>\n",
       "      <td>28.310</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>13770.09790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>62</td>\n",
       "      <td>female</td>\n",
       "      <td>32.965</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>15612.19335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>38.665</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>3393.35635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>35.625</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2211.13075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>31.680</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>34303.16720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>64</td>\n",
       "      <td>male</td>\n",
       "      <td>24.700</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>30166.61817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>61</td>\n",
       "      <td>female</td>\n",
       "      <td>39.100</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>14235.07200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>64</td>\n",
       "      <td>female</td>\n",
       "      <td>31.300</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>47291.05500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>30.115</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>21344.84670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>61</td>\n",
       "      <td>female</td>\n",
       "      <td>29.920</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>30942.19180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>63</td>\n",
       "      <td>male</td>\n",
       "      <td>35.090</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>47055.53210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>23.750</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>1705.62450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>61</td>\n",
       "      <td>female</td>\n",
       "      <td>22.040</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>13616.35860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>25.175</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>northeast</td>\n",
       "      <td>15518.18025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>36.850</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>36149.48350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>63</td>\n",
       "      <td>male</td>\n",
       "      <td>41.470</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>13405.39030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>15.960</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>1694.79640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>63</td>\n",
       "      <td>female</td>\n",
       "      <td>37.700</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>48824.45000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>38.280</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1631.82120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>61</td>\n",
       "      <td>male</td>\n",
       "      <td>31.570</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>12557.60530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>34.430</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1137.46970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>64</td>\n",
       "      <td>female</td>\n",
       "      <td>39.330</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>14901.51670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>63</td>\n",
       "      <td>female</td>\n",
       "      <td>31.800</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>13880.94900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>26.730</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1615.76670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>63</td>\n",
       "      <td>female</td>\n",
       "      <td>27.740</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>northeast</td>\n",
       "      <td>29523.16560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1079</th>\n",
       "      <td>63</td>\n",
       "      <td>male</td>\n",
       "      <td>33.660</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>15161.53440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1080</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>21.780</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>11884.04858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1084</th>\n",
       "      <td>62</td>\n",
       "      <td>female</td>\n",
       "      <td>30.495</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>15019.76005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1095</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>31.350</td>\n",
       "      <td>4</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>4561.18850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1125</th>\n",
       "      <td>63</td>\n",
       "      <td>female</td>\n",
       "      <td>25.080</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>14254.60820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1150</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>30.305</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2203.73595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1163</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>28.215</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2200.83085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1170</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>27.360</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "      <td>northeast</td>\n",
       "      <td>17178.68240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1187</th>\n",
       "      <td>62</td>\n",
       "      <td>female</td>\n",
       "      <td>32.680</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>13844.79720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1204</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>27.280</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>18223.45120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1212</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>21.470</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>1702.45530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1215</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>39.140</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>12890.05765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1236</th>\n",
       "      <td>63</td>\n",
       "      <td>female</td>\n",
       "      <td>21.660</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>14449.85440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1241</th>\n",
       "      <td>64</td>\n",
       "      <td>male</td>\n",
       "      <td>36.960</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>49577.66240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1244</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>33.330</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1135.94070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1248</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>39.820</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1633.96180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1265</th>\n",
       "      <td>64</td>\n",
       "      <td>male</td>\n",
       "      <td>23.760</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>26926.51440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1282</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>21.660</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>northeast</td>\n",
       "      <td>14283.45940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1283</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>30.030</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1720.35370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1284</th>\n",
       "      <td>61</td>\n",
       "      <td>male</td>\n",
       "      <td>36.300</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>47403.88000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>26.125</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>1708.92575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1301</th>\n",
       "      <td>62</td>\n",
       "      <td>male</td>\n",
       "      <td>30.875</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "      <td>northwest</td>\n",
       "      <td>46718.16325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1315</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>28.310</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>11272.33139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1317</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>53.130</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1163.46270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1321</th>\n",
       "      <td>62</td>\n",
       "      <td>male</td>\n",
       "      <td>26.695</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>northeast</td>\n",
       "      <td>28101.33305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1322</th>\n",
       "      <td>62</td>\n",
       "      <td>male</td>\n",
       "      <td>38.830</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>12981.34570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1325</th>\n",
       "      <td>61</td>\n",
       "      <td>male</td>\n",
       "      <td>33.535</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>13143.33665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1334</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>31.920</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>2205.98080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1335</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>36.850</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1629.83350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1337</th>\n",
       "      <td>61</td>\n",
       "      <td>female</td>\n",
       "      <td>29.070</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>northwest</td>\n",
       "      <td>29141.36030</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>160 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      age     sex     bmi  children smoker     region      charges\n",
       "1      18    male  33.770         1     no  southeast   1725.55230\n",
       "11     62  female  26.290         0    yes  southeast  27808.72510\n",
       "22     18    male  34.100         0     no  southeast   1137.01100\n",
       "26     63  female  23.085         0     no  northeast  14451.83515\n",
       "31     18  female  26.315         0     no  northeast   2198.18985\n",
       "33     63    male  28.310         0     no  northwest  13770.09790\n",
       "36     62  female  32.965         3     no  northwest  15612.19335\n",
       "46     18  female  38.665         2     no  northeast   3393.35635\n",
       "50     18  female  35.625         0     no  northeast   2211.13075\n",
       "57     18    male  31.680         2    yes  southeast  34303.16720\n",
       "62     64    male  24.700         1     no  northwest  30166.61817\n",
       "66     61  female  39.100         2     no  southwest  14235.07200\n",
       "94     64  female  31.300         2    yes  southwest  47291.05500\n",
       "102    18  female  30.115         0     no  northeast  21344.84670\n",
       "103    61  female  29.920         3    yes  southeast  30942.19180\n",
       "109    63    male  35.090         0    yes  southeast  47055.53210\n",
       "121    18    male  23.750         0     no  northeast   1705.62450\n",
       "131    61  female  22.040         0     no  northeast  13616.35860\n",
       "157    18    male  25.175         0    yes  northeast  15518.18025\n",
       "161    18  female  36.850         0    yes  southeast  36149.48350\n",
       "170    63    male  41.470         0     no  southeast  13405.39030\n",
       "172    18    male  15.960         0     no  northeast   1694.79640\n",
       "175    63  female  37.700         0    yes  southwest  48824.45000\n",
       "181    18  female  38.280         0     no  southeast   1631.82120\n",
       "190    61    male  31.570         0     no  southeast  12557.60530\n",
       "194    18    male  34.430         0     no  southeast   1137.46970\n",
       "199    64  female  39.330         0     no  northeast  14901.51670\n",
       "208    63  female  31.800         0     no  southwest  13880.94900\n",
       "236    18  female  26.730         0     no  southeast   1615.76670\n",
       "244    63  female  27.740         0    yes  northeast  29523.16560\n",
       "...   ...     ...     ...       ...    ...        ...          ...\n",
       "1079   63    male  33.660         3     no  southeast  15161.53440\n",
       "1080   18    male  21.780         2     no  southeast  11884.04858\n",
       "1084   62  female  30.495         2     no  northwest  15019.76005\n",
       "1095   18  female  31.350         4     no  northeast   4561.18850\n",
       "1125   63  female  25.080         0     no  northwest  14254.60820\n",
       "1150   18  female  30.305         0     no  northeast   2203.73595\n",
       "1163   18  female  28.215         0     no  northeast   2200.83085\n",
       "1170   18    male  27.360         1    yes  northeast  17178.68240\n",
       "1187   62  female  32.680         0     no  northwest  13844.79720\n",
       "1204   18  female  27.280         3    yes  southeast  18223.45120\n",
       "1212   18    male  21.470         0     no  northeast   1702.45530\n",
       "1215   18    male  39.140         0     no  northeast  12890.05765\n",
       "1236   63  female  21.660         0     no  northeast  14449.85440\n",
       "1241   64    male  36.960         2    yes  southeast  49577.66240\n",
       "1244   18    male  33.330         0     no  southeast   1135.94070\n",
       "1248   18  female  39.820         0     no  southeast   1633.96180\n",
       "1265   64    male  23.760         0    yes  southeast  26926.51440\n",
       "1282   18  female  21.660         0    yes  northeast  14283.45940\n",
       "1283   18    male  30.030         1     no  southeast   1720.35370\n",
       "1284   61    male  36.300         1    yes  southwest  47403.88000\n",
       "1296   18    male  26.125         0     no  northeast   1708.92575\n",
       "1301   62    male  30.875         3    yes  northwest  46718.16325\n",
       "1315   18    male  28.310         1     no  northeast  11272.33139\n",
       "1317   18    male  53.130         0     no  southeast   1163.46270\n",
       "1321   62    male  26.695         0    yes  northeast  28101.33305\n",
       "1322   62    male  38.830         0     no  southeast  12981.34570\n",
       "1325   61    male  33.535         0     no  northeast  13143.33665\n",
       "1334   18  female  31.920         0     no  northeast   2205.98080\n",
       "1335   18  female  36.850         0     no  southeast   1629.83350\n",
       "1337   61  female  29.070         0    yes  northwest  29141.36030\n",
       "\n",
       "[160 rows x 7 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Checking the presence of outliers for age\n",
    "sns.boxplot (x=insurance_z['age'])\n",
    "insurance_df[abs(insurance_z['age_z']) > 1.5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>smoker</th>\n",
       "      <th>region</th>\n",
       "      <th>charges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>56</td>\n",
       "      <td>female</td>\n",
       "      <td>39.820</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>11090.71780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>27</td>\n",
       "      <td>male</td>\n",
       "      <td>42.130</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>39611.75770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>56</td>\n",
       "      <td>male</td>\n",
       "      <td>40.300</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>10602.38500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>23</td>\n",
       "      <td>male</td>\n",
       "      <td>17.385</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>2775.19215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>19</td>\n",
       "      <td>male</td>\n",
       "      <td>20.425</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>1625.43375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>26</td>\n",
       "      <td>male</td>\n",
       "      <td>20.800</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>2302.30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>60</td>\n",
       "      <td>male</td>\n",
       "      <td>39.900</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>48173.36100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>48</td>\n",
       "      <td>female</td>\n",
       "      <td>41.230</td>\n",
       "      <td>4</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>11033.66170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>56</td>\n",
       "      <td>male</td>\n",
       "      <td>19.950</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>northeast</td>\n",
       "      <td>22412.64850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>38</td>\n",
       "      <td>male</td>\n",
       "      <td>19.300</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southwest</td>\n",
       "      <td>15820.69900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>58</td>\n",
       "      <td>male</td>\n",
       "      <td>49.060</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>11381.32540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>32</td>\n",
       "      <td>female</td>\n",
       "      <td>17.765</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>northwest</td>\n",
       "      <td>32734.18630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>27</td>\n",
       "      <td>male</td>\n",
       "      <td>18.905</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>4827.90495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>63</td>\n",
       "      <td>male</td>\n",
       "      <td>41.470</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>13405.39030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>15.960</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>1694.79640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>22</td>\n",
       "      <td>male</td>\n",
       "      <td>19.950</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>4005.42250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>36</td>\n",
       "      <td>male</td>\n",
       "      <td>41.895</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "      <td>northeast</td>\n",
       "      <td>43753.33705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>51</td>\n",
       "      <td>female</td>\n",
       "      <td>18.050</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>9644.25250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>40</td>\n",
       "      <td>male</td>\n",
       "      <td>41.230</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>6610.10970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>58</td>\n",
       "      <td>female</td>\n",
       "      <td>41.910</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>24227.33724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>19</td>\n",
       "      <td>female</td>\n",
       "      <td>17.800</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>1727.78500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>19</td>\n",
       "      <td>male</td>\n",
       "      <td>20.900</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>1832.09400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>17.290</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>northeast</td>\n",
       "      <td>12829.45510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>38</td>\n",
       "      <td>female</td>\n",
       "      <td>40.150</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>5400.98050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>265</th>\n",
       "      <td>46</td>\n",
       "      <td>male</td>\n",
       "      <td>42.350</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>46151.12450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>266</th>\n",
       "      <td>40</td>\n",
       "      <td>male</td>\n",
       "      <td>19.800</td>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>17179.52200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>276</th>\n",
       "      <td>19</td>\n",
       "      <td>male</td>\n",
       "      <td>20.615</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>2803.69785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>281</th>\n",
       "      <td>54</td>\n",
       "      <td>male</td>\n",
       "      <td>40.565</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "      <td>northeast</td>\n",
       "      <td>48549.17835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>286</th>\n",
       "      <td>46</td>\n",
       "      <td>female</td>\n",
       "      <td>48.070</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>9432.92530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>292</th>\n",
       "      <td>25</td>\n",
       "      <td>male</td>\n",
       "      <td>45.540</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>42112.23560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1129</th>\n",
       "      <td>19</td>\n",
       "      <td>female</td>\n",
       "      <td>18.600</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>1728.89700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1131</th>\n",
       "      <td>27</td>\n",
       "      <td>male</td>\n",
       "      <td>45.900</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>3693.42800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1132</th>\n",
       "      <td>57</td>\n",
       "      <td>male</td>\n",
       "      <td>40.280</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>20709.02034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1133</th>\n",
       "      <td>52</td>\n",
       "      <td>female</td>\n",
       "      <td>18.335</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>9991.03765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1148</th>\n",
       "      <td>55</td>\n",
       "      <td>male</td>\n",
       "      <td>21.500</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>10791.96000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1156</th>\n",
       "      <td>19</td>\n",
       "      <td>male</td>\n",
       "      <td>44.880</td>\n",
       "      <td>0</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>39722.74620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1159</th>\n",
       "      <td>32</td>\n",
       "      <td>female</td>\n",
       "      <td>41.100</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>3989.84100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1161</th>\n",
       "      <td>34</td>\n",
       "      <td>male</td>\n",
       "      <td>42.130</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>5124.18870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1166</th>\n",
       "      <td>57</td>\n",
       "      <td>male</td>\n",
       "      <td>40.370</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>10982.50130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1172</th>\n",
       "      <td>56</td>\n",
       "      <td>female</td>\n",
       "      <td>41.910</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>11093.62290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1180</th>\n",
       "      <td>42</td>\n",
       "      <td>female</td>\n",
       "      <td>41.325</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>7650.77375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1201</th>\n",
       "      <td>46</td>\n",
       "      <td>male</td>\n",
       "      <td>40.375</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>8733.22925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1205</th>\n",
       "      <td>35</td>\n",
       "      <td>male</td>\n",
       "      <td>17.860</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>5116.50040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1212</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>21.470</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>1702.45530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1225</th>\n",
       "      <td>33</td>\n",
       "      <td>female</td>\n",
       "      <td>39.820</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>4795.65680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1226</th>\n",
       "      <td>38</td>\n",
       "      <td>male</td>\n",
       "      <td>16.815</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>6640.54485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1239</th>\n",
       "      <td>25</td>\n",
       "      <td>female</td>\n",
       "      <td>42.130</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>3238.43570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1240</th>\n",
       "      <td>52</td>\n",
       "      <td>male</td>\n",
       "      <td>41.800</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>47269.85400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1242</th>\n",
       "      <td>22</td>\n",
       "      <td>female</td>\n",
       "      <td>21.280</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>northwest</td>\n",
       "      <td>4296.27120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1248</th>\n",
       "      <td>18</td>\n",
       "      <td>female</td>\n",
       "      <td>39.820</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1633.96180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1251</th>\n",
       "      <td>19</td>\n",
       "      <td>male</td>\n",
       "      <td>19.800</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>1241.56500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1260</th>\n",
       "      <td>32</td>\n",
       "      <td>female</td>\n",
       "      <td>20.520</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>4544.23480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1286</th>\n",
       "      <td>28</td>\n",
       "      <td>female</td>\n",
       "      <td>17.290</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>3732.62510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1290</th>\n",
       "      <td>38</td>\n",
       "      <td>female</td>\n",
       "      <td>19.950</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>northeast</td>\n",
       "      <td>7133.90250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1302</th>\n",
       "      <td>25</td>\n",
       "      <td>female</td>\n",
       "      <td>20.800</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>3208.78700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1312</th>\n",
       "      <td>34</td>\n",
       "      <td>male</td>\n",
       "      <td>42.900</td>\n",
       "      <td>1</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>4536.25900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1316</th>\n",
       "      <td>19</td>\n",
       "      <td>female</td>\n",
       "      <td>20.600</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>1731.67700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1317</th>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>53.130</td>\n",
       "      <td>0</td>\n",
       "      <td>no</td>\n",
       "      <td>southeast</td>\n",
       "      <td>1163.46270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1323</th>\n",
       "      <td>42</td>\n",
       "      <td>female</td>\n",
       "      <td>40.370</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>southeast</td>\n",
       "      <td>43896.37630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1332</th>\n",
       "      <td>52</td>\n",
       "      <td>female</td>\n",
       "      <td>44.700</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>southwest</td>\n",
       "      <td>11411.68500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>174 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      age     sex     bmi  children smoker     region      charges\n",
       "13     56  female  39.820         0     no  southeast  11090.71780\n",
       "14     27    male  42.130         0    yes  southeast  39611.75770\n",
       "18     56    male  40.300         0     no  southwest  10602.38500\n",
       "28     23    male  17.385         1     no  northwest   2775.19215\n",
       "35     19    male  20.425         0     no  northwest   1625.43375\n",
       "37     26    male  20.800         0     no  southwest   2302.30000\n",
       "39     60    male  39.900         0    yes  southwest  48173.36100\n",
       "83     48  female  41.230         4     no  northwest  11033.66170\n",
       "98     56    male  19.950         0    yes  northeast  22412.64850\n",
       "99     38    male  19.300         0    yes  southwest  15820.69900\n",
       "116    58    male  49.060         0     no  southeast  11381.32540\n",
       "128    32  female  17.765         2    yes  northwest  32734.18630\n",
       "169    27    male  18.905         3     no  northeast   4827.90495\n",
       "170    63    male  41.470         0     no  southeast  13405.39030\n",
       "172    18    male  15.960         0     no  northeast   1694.79640\n",
       "182    22    male  19.950         3     no  northeast   4005.42250\n",
       "185    36    male  41.895         3    yes  northeast  43753.33705\n",
       "198    51  female  18.050         0     no  northwest   9644.25250\n",
       "209    40    male  41.230         1     no  northeast   6610.10970\n",
       "227    58  female  41.910         0     no  southeast  24227.33724\n",
       "232    19  female  17.800         0     no  southwest   1727.78500\n",
       "248    19    male  20.900         1     no  southwest   1832.09400\n",
       "250    18    male  17.290         2    yes  northeast  12829.45510\n",
       "257    38  female  40.150         0     no  southeast   5400.98050\n",
       "265    46    male  42.350         3    yes  southeast  46151.12450\n",
       "266    40    male  19.800         1    yes  southeast  17179.52200\n",
       "276    19    male  20.615         2     no  northwest   2803.69785\n",
       "281    54    male  40.565         3    yes  northeast  48549.17835\n",
       "286    46  female  48.070         2     no  northeast   9432.92530\n",
       "292    25    male  45.540         2    yes  southeast  42112.23560\n",
       "...   ...     ...     ...       ...    ...        ...          ...\n",
       "1129   19  female  18.600         0     no  southwest   1728.89700\n",
       "1131   27    male  45.900         2     no  southwest   3693.42800\n",
       "1132   57    male  40.280         0     no  northeast  20709.02034\n",
       "1133   52  female  18.335         0     no  northwest   9991.03765\n",
       "1148   55    male  21.500         1     no  southwest  10791.96000\n",
       "1156   19    male  44.880         0    yes  southeast  39722.74620\n",
       "1159   32  female  41.100         0     no  southwest   3989.84100\n",
       "1161   34    male  42.130         2     no  southeast   5124.18870\n",
       "1166   57    male  40.370         0     no  southeast  10982.50130\n",
       "1172   56  female  41.910         0     no  southeast  11093.62290\n",
       "1180   42  female  41.325         1     no  northeast   7650.77375\n",
       "1201   46    male  40.375         2     no  northwest   8733.22925\n",
       "1205   35    male  17.860         1     no  northwest   5116.50040\n",
       "1212   18    male  21.470         0     no  northeast   1702.45530\n",
       "1225   33  female  39.820         1     no  southeast   4795.65680\n",
       "1226   38    male  16.815         2     no  northeast   6640.54485\n",
       "1239   25  female  42.130         1     no  southeast   3238.43570\n",
       "1240   52    male  41.800         2    yes  southeast  47269.85400\n",
       "1242   22  female  21.280         3     no  northwest   4296.27120\n",
       "1248   18  female  39.820         0     no  southeast   1633.96180\n",
       "1251   19    male  19.800         0     no  southwest   1241.56500\n",
       "1260   32  female  20.520         0     no  northeast   4544.23480\n",
       "1286   28  female  17.290         0     no  northeast   3732.62510\n",
       "1290   38  female  19.950         2     no  northeast   7133.90250\n",
       "1302   25  female  20.800         1     no  southwest   3208.78700\n",
       "1312   34    male  42.900         1     no  southwest   4536.25900\n",
       "1316   19  female  20.600         0     no  southwest   1731.67700\n",
       "1317   18    male  53.130         0     no  southeast   1163.46270\n",
       "1323   42  female  40.370         2    yes  southeast  43896.37630\n",
       "1332   52  female  44.700         3     no  southwest  11411.68500\n",
       "\n",
       "[174 rows x 7 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Checking the presence of outliers for bmi\n",
    "sns.boxplot (x=insurance_z['bmi'], whis=1.5)\n",
    "insurance_df[abs(insurance_z['bmi_z']) > 1.5]"
   ]
  },
  {
   "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",
       "    }\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>age</th>\n",
       "      <th>bmi</th>\n",
       "      <th>charges</th>\n",
       "      <th>age_z</th>\n",
       "      <th>bmi_z</th>\n",
       "      <th>charges_z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>27</td>\n",
       "      <td>42.130</td>\n",
       "      <td>39611.75770</td>\n",
       "      <td>-0.869155</td>\n",
       "      <td>1.881033</td>\n",
       "      <td>2.175983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>30</td>\n",
       "      <td>35.300</td>\n",
       "      <td>36837.46700</td>\n",
       "      <td>-0.655551</td>\n",
       "      <td>0.760609</td>\n",
       "      <td>1.946807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>34</td>\n",
       "      <td>31.920</td>\n",
       "      <td>37701.87680</td>\n",
       "      <td>-0.370746</td>\n",
       "      <td>0.206139</td>\n",
       "      <td>2.018214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>31</td>\n",
       "      <td>36.300</td>\n",
       "      <td>38711.00000</td>\n",
       "      <td>-0.584350</td>\n",
       "      <td>0.924654</td>\n",
       "      <td>2.101574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>22</td>\n",
       "      <td>35.600</td>\n",
       "      <td>35585.57600</td>\n",
       "      <td>-1.225161</td>\n",
       "      <td>0.809822</td>\n",
       "      <td>1.843392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>28</td>\n",
       "      <td>36.400</td>\n",
       "      <td>51194.55914</td>\n",
       "      <td>-0.797954</td>\n",
       "      <td>0.941058</td>\n",
       "      <td>3.132806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>35</td>\n",
       "      <td>36.670</td>\n",
       "      <td>39774.27630</td>\n",
       "      <td>-0.299545</td>\n",
       "      <td>0.985350</td>\n",
       "      <td>2.189409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>60</td>\n",
       "      <td>39.900</td>\n",
       "      <td>48173.36100</td>\n",
       "      <td>1.480485</td>\n",
       "      <td>1.515214</td>\n",
       "      <td>2.883233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>36</td>\n",
       "      <td>35.200</td>\n",
       "      <td>38709.17600</td>\n",
       "      <td>-0.228344</td>\n",
       "      <td>0.744205</td>\n",
       "      <td>2.101424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>36</td>\n",
       "      <td>34.430</td>\n",
       "      <td>37742.57570</td>\n",
       "      <td>-0.228344</td>\n",
       "      <td>0.617890</td>\n",
       "      <td>2.021576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>58</td>\n",
       "      <td>36.955</td>\n",
       "      <td>47496.49445</td>\n",
       "      <td>1.338082</td>\n",
       "      <td>1.032103</td>\n",
       "      <td>2.827319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>18</td>\n",
       "      <td>31.680</td>\n",
       "      <td>34303.16720</td>\n",
       "      <td>-1.509965</td>\n",
       "      <td>0.166768</td>\n",
       "      <td>1.737456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>22</td>\n",
       "      <td>37.620</td>\n",
       "      <td>37165.16380</td>\n",
       "      <td>-1.225161</td>\n",
       "      <td>1.141192</td>\n",
       "      <td>1.973877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>37</td>\n",
       "      <td>34.800</td>\n",
       "      <td>39836.51900</td>\n",
       "      <td>-0.157143</td>\n",
       "      <td>0.678587</td>\n",
       "      <td>2.194550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>57</td>\n",
       "      <td>31.160</td>\n",
       "      <td>43578.93940</td>\n",
       "      <td>1.266881</td>\n",
       "      <td>0.081465</td>\n",
       "      <td>2.503701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>64</td>\n",
       "      <td>31.300</td>\n",
       "      <td>47291.05500</td>\n",
       "      <td>1.765289</td>\n",
       "      <td>0.104431</td>\n",
       "      <td>2.810349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>63</td>\n",
       "      <td>35.090</td>\n",
       "      <td>47055.53210</td>\n",
       "      <td>1.694088</td>\n",
       "      <td>0.726160</td>\n",
       "      <td>2.790893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>44</td>\n",
       "      <td>31.350</td>\n",
       "      <td>39556.49450</td>\n",
       "      <td>0.341265</td>\n",
       "      <td>0.112633</td>\n",
       "      <td>2.171418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>32</td>\n",
       "      <td>17.765</td>\n",
       "      <td>32734.18630</td>\n",
       "      <td>-0.513149</td>\n",
       "      <td>-2.115911</td>\n",
       "      <td>1.607847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>46</td>\n",
       "      <td>30.495</td>\n",
       "      <td>40720.55105</td>\n",
       "      <td>0.483668</td>\n",
       "      <td>-0.027625</td>\n",
       "      <td>2.267578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>30</td>\n",
       "      <td>35.530</td>\n",
       "      <td>36950.25670</td>\n",
       "      <td>-0.655551</td>\n",
       "      <td>0.798339</td>\n",
       "      <td>1.956124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>18</td>\n",
       "      <td>36.850</td>\n",
       "      <td>36149.48350</td>\n",
       "      <td>-1.509965</td>\n",
       "      <td>1.014878</td>\n",
       "      <td>1.889975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>63</td>\n",
       "      <td>37.700</td>\n",
       "      <td>48824.45000</td>\n",
       "      <td>1.694088</td>\n",
       "      <td>1.154316</td>\n",
       "      <td>2.937018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>36</td>\n",
       "      <td>41.895</td>\n",
       "      <td>43753.33705</td>\n",
       "      <td>-0.228344</td>\n",
       "      <td>1.842482</td>\n",
       "      <td>2.518108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>27</td>\n",
       "      <td>36.080</td>\n",
       "      <td>37133.89820</td>\n",
       "      <td>-0.869155</td>\n",
       "      <td>0.888564</td>\n",
       "      <td>1.971294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>19</td>\n",
       "      <td>34.800</td>\n",
       "      <td>34779.61500</td>\n",
       "      <td>-1.438764</td>\n",
       "      <td>0.678587</td>\n",
       "      <td>1.776814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>23</td>\n",
       "      <td>36.670</td>\n",
       "      <td>38511.62830</td>\n",
       "      <td>-1.153959</td>\n",
       "      <td>0.985350</td>\n",
       "      <td>2.085105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>55</td>\n",
       "      <td>26.800</td>\n",
       "      <td>35160.13457</td>\n",
       "      <td>1.124479</td>\n",
       "      <td>-0.633769</td>\n",
       "      <td>1.808247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>251</th>\n",
       "      <td>63</td>\n",
       "      <td>32.200</td>\n",
       "      <td>47305.30500</td>\n",
       "      <td>1.694088</td>\n",
       "      <td>0.252071</td>\n",
       "      <td>2.811526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>252</th>\n",
       "      <td>54</td>\n",
       "      <td>34.210</td>\n",
       "      <td>44260.74990</td>\n",
       "      <td>1.053277</td>\n",
       "      <td>0.581801</td>\n",
       "      <td>2.560024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1096</th>\n",
       "      <td>51</td>\n",
       "      <td>34.960</td>\n",
       "      <td>44641.19740</td>\n",
       "      <td>0.839674</td>\n",
       "      <td>0.704834</td>\n",
       "      <td>2.591451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1111</th>\n",
       "      <td>38</td>\n",
       "      <td>38.390</td>\n",
       "      <td>41949.24410</td>\n",
       "      <td>-0.085942</td>\n",
       "      <td>1.267507</td>\n",
       "      <td>2.369077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1117</th>\n",
       "      <td>25</td>\n",
       "      <td>33.330</td>\n",
       "      <td>36124.57370</td>\n",
       "      <td>-1.011557</td>\n",
       "      <td>0.437442</td>\n",
       "      <td>1.887917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1118</th>\n",
       "      <td>33</td>\n",
       "      <td>35.750</td>\n",
       "      <td>38282.74950</td>\n",
       "      <td>-0.441948</td>\n",
       "      <td>0.834429</td>\n",
       "      <td>2.066198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1120</th>\n",
       "      <td>23</td>\n",
       "      <td>31.400</td>\n",
       "      <td>34166.27300</td>\n",
       "      <td>-1.153959</td>\n",
       "      <td>0.120836</td>\n",
       "      <td>1.726147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1122</th>\n",
       "      <td>53</td>\n",
       "      <td>36.860</td>\n",
       "      <td>46661.44240</td>\n",
       "      <td>0.982076</td>\n",
       "      <td>1.016519</td>\n",
       "      <td>2.758338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1124</th>\n",
       "      <td>23</td>\n",
       "      <td>42.750</td>\n",
       "      <td>40904.19950</td>\n",
       "      <td>-1.153959</td>\n",
       "      <td>1.982741</td>\n",
       "      <td>2.282748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1139</th>\n",
       "      <td>19</td>\n",
       "      <td>32.490</td>\n",
       "      <td>36898.73308</td>\n",
       "      <td>-1.438764</td>\n",
       "      <td>0.299644</td>\n",
       "      <td>1.951868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1146</th>\n",
       "      <td>60</td>\n",
       "      <td>32.800</td>\n",
       "      <td>52590.82939</td>\n",
       "      <td>1.480485</td>\n",
       "      <td>0.350498</td>\n",
       "      <td>3.248148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1152</th>\n",
       "      <td>43</td>\n",
       "      <td>32.560</td>\n",
       "      <td>40941.28540</td>\n",
       "      <td>0.270064</td>\n",
       "      <td>0.311127</td>\n",
       "      <td>2.285812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1156</th>\n",
       "      <td>19</td>\n",
       "      <td>44.880</td>\n",
       "      <td>39722.74620</td>\n",
       "      <td>-1.438764</td>\n",
       "      <td>2.332155</td>\n",
       "      <td>2.185152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1186</th>\n",
       "      <td>20</td>\n",
       "      <td>35.625</td>\n",
       "      <td>37465.34375</td>\n",
       "      <td>-1.367563</td>\n",
       "      <td>0.813924</td>\n",
       "      <td>1.998674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1196</th>\n",
       "      <td>19</td>\n",
       "      <td>30.020</td>\n",
       "      <td>33307.55080</td>\n",
       "      <td>-1.438764</td>\n",
       "      <td>-0.105546</td>\n",
       "      <td>1.655211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1206</th>\n",
       "      <td>59</td>\n",
       "      <td>34.800</td>\n",
       "      <td>36910.60803</td>\n",
       "      <td>1.409283</td>\n",
       "      <td>0.678587</td>\n",
       "      <td>1.952849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1207</th>\n",
       "      <td>36</td>\n",
       "      <td>33.400</td>\n",
       "      <td>38415.47400</td>\n",
       "      <td>-0.228344</td>\n",
       "      <td>0.448925</td>\n",
       "      <td>2.077162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1218</th>\n",
       "      <td>46</td>\n",
       "      <td>34.600</td>\n",
       "      <td>41661.60200</td>\n",
       "      <td>0.483668</td>\n",
       "      <td>0.645778</td>\n",
       "      <td>2.345315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1230</th>\n",
       "      <td>52</td>\n",
       "      <td>34.485</td>\n",
       "      <td>60021.39897</td>\n",
       "      <td>0.910875</td>\n",
       "      <td>0.626913</td>\n",
       "      <td>3.861966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1240</th>\n",
       "      <td>52</td>\n",
       "      <td>41.800</td>\n",
       "      <td>47269.85400</td>\n",
       "      <td>0.910875</td>\n",
       "      <td>1.826898</td>\n",
       "      <td>2.808597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1241</th>\n",
       "      <td>64</td>\n",
       "      <td>36.960</td>\n",
       "      <td>49577.66240</td>\n",
       "      <td>1.765289</td>\n",
       "      <td>1.032923</td>\n",
       "      <td>2.999239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1249</th>\n",
       "      <td>32</td>\n",
       "      <td>33.630</td>\n",
       "      <td>37607.52770</td>\n",
       "      <td>-0.513149</td>\n",
       "      <td>0.486655</td>\n",
       "      <td>2.010420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1267</th>\n",
       "      <td>24</td>\n",
       "      <td>31.065</td>\n",
       "      <td>34254.05335</td>\n",
       "      <td>-1.082758</td>\n",
       "      <td>0.065881</td>\n",
       "      <td>1.733399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1284</th>\n",
       "      <td>61</td>\n",
       "      <td>36.300</td>\n",
       "      <td>47403.88000</td>\n",
       "      <td>1.551686</td>\n",
       "      <td>0.924654</td>\n",
       "      <td>2.819669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1288</th>\n",
       "      <td>20</td>\n",
       "      <td>39.400</td>\n",
       "      <td>38344.56600</td>\n",
       "      <td>-1.367563</td>\n",
       "      <td>1.433192</td>\n",
       "      <td>2.071304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1291</th>\n",
       "      <td>19</td>\n",
       "      <td>34.900</td>\n",
       "      <td>34828.65400</td>\n",
       "      <td>-1.438764</td>\n",
       "      <td>0.694991</td>\n",
       "      <td>1.780865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1300</th>\n",
       "      <td>45</td>\n",
       "      <td>30.360</td>\n",
       "      <td>62592.87309</td>\n",
       "      <td>0.412467</td>\n",
       "      <td>-0.049771</td>\n",
       "      <td>4.074389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1301</th>\n",
       "      <td>62</td>\n",
       "      <td>30.875</td>\n",
       "      <td>46718.16325</td>\n",
       "      <td>1.622887</td>\n",
       "      <td>0.034712</td>\n",
       "      <td>2.763024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1303</th>\n",
       "      <td>43</td>\n",
       "      <td>27.800</td>\n",
       "      <td>37829.72420</td>\n",
       "      <td>0.270064</td>\n",
       "      <td>-0.469724</td>\n",
       "      <td>2.028775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1308</th>\n",
       "      <td>25</td>\n",
       "      <td>30.200</td>\n",
       "      <td>33900.65300</td>\n",
       "      <td>-1.011557</td>\n",
       "      <td>-0.076018</td>\n",
       "      <td>1.704205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1313</th>\n",
       "      <td>19</td>\n",
       "      <td>34.700</td>\n",
       "      <td>36397.57600</td>\n",
       "      <td>-1.438764</td>\n",
       "      <td>0.662182</td>\n",
       "      <td>1.910469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1323</th>\n",
       "      <td>42</td>\n",
       "      <td>40.370</td>\n",
       "      <td>43896.37630</td>\n",
       "      <td>0.198863</td>\n",
       "      <td>1.592315</td>\n",
       "      <td>2.529924</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>156 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      age     bmi      charges     age_z     bmi_z  charges_z\n",
       "14     27  42.130  39611.75770 -0.869155  1.881033   2.175983\n",
       "19     30  35.300  36837.46700 -0.655551  0.760609   1.946807\n",
       "23     34  31.920  37701.87680 -0.370746  0.206139   2.018214\n",
       "29     31  36.300  38711.00000 -0.584350  0.924654   2.101574\n",
       "30     22  35.600  35585.57600 -1.225161  0.809822   1.843392\n",
       "34     28  36.400  51194.55914 -0.797954  0.941058   3.132806\n",
       "38     35  36.670  39774.27630 -0.299545  0.985350   2.189409\n",
       "39     60  39.900  48173.36100  1.480485  1.515214   2.883233\n",
       "49     36  35.200  38709.17600 -0.228344  0.744205   2.101424\n",
       "53     36  34.430  37742.57570 -0.228344  0.617890   2.021576\n",
       "55     58  36.955  47496.49445  1.338082  1.032103   2.827319\n",
       "57     18  31.680  34303.16720 -1.509965  0.166768   1.737456\n",
       "82     22  37.620  37165.16380 -1.225161  1.141192   1.973877\n",
       "84     37  34.800  39836.51900 -0.157143  0.678587   2.194550\n",
       "86     57  31.160  43578.93940  1.266881  0.081465   2.503701\n",
       "94     64  31.300  47291.05500  1.765289  0.104431   2.810349\n",
       "109    63  35.090  47055.53210  1.694088  0.726160   2.790893\n",
       "123    44  31.350  39556.49450  0.341265  0.112633   2.171418\n",
       "128    32  17.765  32734.18630 -0.513149 -2.115911   1.607847\n",
       "146    46  30.495  40720.55105  0.483668 -0.027625   2.267578\n",
       "158    30  35.530  36950.25670 -0.655551  0.798339   1.956124\n",
       "161    18  36.850  36149.48350 -1.509965  1.014878   1.889975\n",
       "175    63  37.700  48824.45000  1.694088  1.154316   2.937018\n",
       "185    36  41.895  43753.33705 -0.228344  1.842482   2.518108\n",
       "203    27  36.080  37133.89820 -0.869155  0.888564   1.971294\n",
       "223    19  34.800  34779.61500 -1.438764  0.678587   1.776814\n",
       "240    23  36.670  38511.62830 -1.153959  0.985350   2.085105\n",
       "242    55  26.800  35160.13457  1.124479 -0.633769   1.808247\n",
       "251    63  32.200  47305.30500  1.694088  0.252071   2.811526\n",
       "252    54  34.210  44260.74990  1.053277  0.581801   2.560024\n",
       "...   ...     ...          ...       ...       ...        ...\n",
       "1096   51  34.960  44641.19740  0.839674  0.704834   2.591451\n",
       "1111   38  38.390  41949.24410 -0.085942  1.267507   2.369077\n",
       "1117   25  33.330  36124.57370 -1.011557  0.437442   1.887917\n",
       "1118   33  35.750  38282.74950 -0.441948  0.834429   2.066198\n",
       "1120   23  31.400  34166.27300 -1.153959  0.120836   1.726147\n",
       "1122   53  36.860  46661.44240  0.982076  1.016519   2.758338\n",
       "1124   23  42.750  40904.19950 -1.153959  1.982741   2.282748\n",
       "1139   19  32.490  36898.73308 -1.438764  0.299644   1.951868\n",
       "1146   60  32.800  52590.82939  1.480485  0.350498   3.248148\n",
       "1152   43  32.560  40941.28540  0.270064  0.311127   2.285812\n",
       "1156   19  44.880  39722.74620 -1.438764  2.332155   2.185152\n",
       "1186   20  35.625  37465.34375 -1.367563  0.813924   1.998674\n",
       "1196   19  30.020  33307.55080 -1.438764 -0.105546   1.655211\n",
       "1206   59  34.800  36910.60803  1.409283  0.678587   1.952849\n",
       "1207   36  33.400  38415.47400 -0.228344  0.448925   2.077162\n",
       "1218   46  34.600  41661.60200  0.483668  0.645778   2.345315\n",
       "1230   52  34.485  60021.39897  0.910875  0.626913   3.861966\n",
       "1240   52  41.800  47269.85400  0.910875  1.826898   2.808597\n",
       "1241   64  36.960  49577.66240  1.765289  1.032923   2.999239\n",
       "1249   32  33.630  37607.52770 -0.513149  0.486655   2.010420\n",
       "1267   24  31.065  34254.05335 -1.082758  0.065881   1.733399\n",
       "1284   61  36.300  47403.88000  1.551686  0.924654   2.819669\n",
       "1288   20  39.400  38344.56600 -1.367563  1.433192   2.071304\n",
       "1291   19  34.900  34828.65400 -1.438764  0.694991   1.780865\n",
       "1300   45  30.360  62592.87309  0.412467 -0.049771   4.074389\n",
       "1301   62  30.875  46718.16325  1.622887  0.034712   2.763024\n",
       "1303   43  27.800  37829.72420  0.270064 -0.469724   2.028775\n",
       "1308   25  30.200  33900.65300 -1.011557 -0.076018   1.704205\n",
       "1313   19  34.700  36397.57600 -1.438764  0.662182   1.910469\n",
       "1323   42  40.370  43896.37630  0.198863  1.592315   2.529924\n",
       "\n",
       "[156 rows x 6 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Checking the presence of outliers for charges\n",
    "sns.boxplot (x=insurance_z['charges'])\n",
    "insurance_z[abs(insurance_z['charges_z']) > 1.5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q3.h Distribution of categorical columns (include children)\n",
    "Distribution of Categorical columns is shown by CountPlot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20746c41cc0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set (style=\"darkgrid\")\n",
    "sns.countplot(x='sex', data=insurance_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20746c98550>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='smoker', data=insurance_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20746cd2048>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='region', data=insurance_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20746d44b70>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='children', data=insurance_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q3.i Pair plot that includes all the columns of the data frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x20746b9c0f0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot (insurance_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q4.a Do charges of people who smoke differ significantly from the people who don't ?\n",
    "\n",
    "First plotting the scatter plot for the charges for smokers and non-smokers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20746bc89b0>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot (x=insurance_df['age'], y=insurance_df['charges'], hue=insurance_df['smoker'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then, grouping the charges for smokers and non-smokers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>region</th>\n",
       "      <th>charges</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>smoker</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>no</th>\n",
       "      <td>1064</td>\n",
       "      <td>1064</td>\n",
       "      <td>1064</td>\n",
       "      <td>1064</td>\n",
       "      <td>1064</td>\n",
       "      <td>1064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yes</th>\n",
       "      <td>274</td>\n",
       "      <td>274</td>\n",
       "      <td>274</td>\n",
       "      <td>274</td>\n",
       "      <td>274</td>\n",
       "      <td>274</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         age   sex   bmi  children  region  charges\n",
       "smoker                                             \n",
       "no      1064  1064  1064      1064    1064     1064\n",
       "yes      274   274   274       274     274      274"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "insurance_df.groupby (['smoker']).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2074772a550>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Getting the Charges for Smokers and non-Smokers by a filter\n",
    "smoke_filter = insurance_df.apply (lambda row: (row['smoker'] == 'yes'), axis=1)\n",
    "charges_smoker = (insurance_df[smoke_filter])['charges']\n",
    "charges_no_smoker = (insurance_df[~smoke_filter])['charges']\n",
    "\n",
    "charges_smoker.hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20746a18240>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "charges_no_smoker.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Based on the histograms the smoker and non_smoker charges, don't seem to be normally distributed \n",
    "### ttest_ind may not be apprropriate and Mann-Whitneyu test is carried out to check different populations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Conducting Mann-Whitneyu test to check if the two non-parametric populations are significantly different\n",
    "\n",
    "Null Hypothesis: Charges for people who smoke are DO NOT differ significantly than from the people who don't smoke\n",
    "\n",
    "Alternative Hypothesis: Charges for people who smoke are differ significantly than from the people who don't smoke\n",
    "\n",
    "Level of significant error: 0.05"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MannwhitneyuResult(statistic=7403.0, pvalue=2.6351167222517853e-130)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Conducting two-sample ttest for independent population (assuming underlying normal distribution for charges)\n",
    "#t_statistic, p_value = ttest_ind (charges_no_smoker, charges_smoker)\n",
    "#print('p_value for two-sample t-test for independent population: ', p_value)\n",
    "\n",
    "# However, the underlying population for \"charges\" doesn't seem to be normally distributed\n",
    "# So, conducting Mann-Whitney test\n",
    "mannwhitneyu (charges_smoker, charges_no_smoker)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, p_value almost close to Zero in MannWhitney test\n",
    "\n",
    "So, the Null Hypothesis is Rejected and Alternative Hypothesis is Accepted\n",
    "\n",
    "### Charges for the people who smoke are differ significantly than from the people who don't smoke"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q4.b Does bmi of males differ significantly from that of females ?\n",
    "\n",
    "First plotting the scatter plot for the bmi for males and females"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20747802518>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot (x=insurance_df['age'], y=insurance_df['bmi'], hue=insurance_df['sex'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then, grouping the bmi for male and female"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>age</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>charges</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>39.503021</td>\n",
       "      <td>30.377749</td>\n",
       "      <td>1.074018</td>\n",
       "      <td>12569.578844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>38.917160</td>\n",
       "      <td>30.943129</td>\n",
       "      <td>1.115385</td>\n",
       "      <td>13956.751178</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              age        bmi  children       charges\n",
       "sex                                                 \n",
       "female  39.503021  30.377749  1.074018  12569.578844\n",
       "male    38.917160  30.943129  1.115385  13956.751178"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "insurance_df.groupby (['sex']).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Getting the bmi distribution for male and female by a filter\n",
    "gender_filter = insurance_df.apply (lambda row: (row['sex'] == 'male'), axis=1)\n",
    "bmi_male = insurance_df[gender_filter]['bmi']\n",
    "bmi_female = insurance_df[~gender_filter]['bmi']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x207478a7a58>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bmi_male.hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x207477a9898>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bmi_female.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### From the above histograms, bmi for male and female resembles normal distribution\n",
    "### Two-sample ttest_ind is appropriate to check different populations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Conducting Two-sample ttest_ind to check if two populations are significantly different\n",
    "\n",
    "Null Hypothesis: BMI for male DO NOT differ significantly than from female\n",
    "\n",
    "Alternative Hypothesis: BMI for male differ significantly than from female\n",
    "\n",
    "Level of significant error: 0.05"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "p_value for two-sample t-test for independent population:  0.08997637178984932\n"
     ]
    }
   ],
   "source": [
    "# Conducting two-sample t-test for independent population (assuming underlying normal distribution for bmi)\n",
    "t_statistic, p_value = ttest_ind (bmi_male, bmi_female)\n",
    "print('p_value for two-sample t-test for independent population: ', p_value)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, p_value 0.089 > 0.05 the level of significant error\n",
    "\n",
    "So, the Null Hypothesis is NOT Rejected and Alternative Hypothesis is Rejected\n",
    "\n",
    "### BMI for male DO NOT differ significantly than from female"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Q4.c Is the proportion of smokers significantly different in different genders?\n",
    "### This is Chi-squared test to compare the categorical responses between the two independent groups (Gender v/s Smoker)\n",
    "\n",
    "One sided Chi-squared test of independence of proportions:\n",
    "\n",
    "Null Hypothesis: No significant difference in the proportion of smokers in different genders\n",
    "\n",
    "Alternative Hypothesis: Significant difference in the proportion of smokers in different genders\n",
    "\n",
    "Level of Significant error: 0.05"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>smoker</th>\n",
       "      <th>no</th>\n",
       "      <th>yes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>547</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>517</td>\n",
       "      <td>159</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "smoker   no  yes\n",
       "sex             \n",
       "female  547  115\n",
       "male    517  159"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Creating Two-way Contingency table with sex and smoker columns\n",
    "two_way = pd.crosstab (insurance_df.sex, insurance_df.smoker)\n",
    "two_way"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Power_divergenceResult(statistic=7.065693430656935, pvalue=0.007857389588994759)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Computing the Chi-square test statics and p_value for smoker\n",
    "chisquare(two_way['yes'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, p_value 0.00786 < 0.05, level of significance error\n",
    "\n",
    "So, the Null Hypothesis is Rejected and Alternative Hypothesis is Accepted\n",
    "\n",
    "### Significant difference between the proportions of smokers in different genders"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Q4.d Is the distribution of bmi across women with no children, one child and two children, the same ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Input Means:  30.361522491349486 30.05265822784811 30.64978991596637\n",
      "Input Variances:  35.481105813507966 33.2754679338247 43.5638493256126\n"
     ]
    }
   ],
   "source": [
    "# Getting the distribution for zero, one and two children\n",
    "zero_child = insurance_df[(insurance_df['sex'] == 'female') & (insurance_df['children'] == 0)]['bmi']\n",
    "one_child = insurance_df[(insurance_df['sex'] == 'female') & (insurance_df['children'] == 1)]['bmi']\n",
    "two_child = insurance_df[(insurance_df['sex'] == 'female') & (insurance_df['children'] == 2)]['bmi']\n",
    "\n",
    "#f_oneway (zero_child, one_child, two_child)\n",
    "print ('Input Means: ', np.mean(zero_child), np.mean(one_child), np.mean(two_child))\n",
    "print ('Input Variances: ', np.var(zero_child), np.var(one_child), np.var(two_child))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before conducting ANOVA, first find out if all the population have equal variance by Levene Test\n",
    "\n",
    "For one-sided Levene Test:\n",
    "\n",
    "Null Hypothesis: All variances are equal\n",
    "\n",
    "Alternative Hypothesis: Atleast one of the variances not equal\n",
    "\n",
    "Level of significance of error: 5%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LeveneResult(statistic=0.9433311607108589, pvalue=0.3899432394522804)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "levene (zero_child, one_child, two_child)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, p_value 0.3899 > 0.05 level of significance error\n",
    "\n",
    "So, the Null Hypothesis is NOT Rejected\n",
    "\n",
    "### All Variances of the three groups are equal. It is OK to proceed with ANOVA test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For One-tailed ANOVA test:\n",
    "\n",
    "Null Hypothesis: No significant difference among means of three groups\n",
    "\n",
    "Alternative Hypothesis: Significance difference between the means of at least one pair of groups\n",
    "\n",
    "For one-tailed test, level of significance Error: 5%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F_onewayResult(statistic=0.3344720147757968, pvalue=0.7158579926754841)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f_oneway (zero_child, one_child, two_child)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, p_value 0.71585 > 0.05 level of significance error\n",
    "\n",
    "So, the Null Hypothesis is NOT Rejected\n",
    "\n",
    "### No significant difference among the means of three groups\n",
    "\n",
    "### Based on the Levene and ANOVA test results, it is concluded that the distribution of bmi across women with no, one and two children are same"
   ]
  }
 ],
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