HR Analytics.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for basic operations\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# for data visualization\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# for data analysis\n",
    "import dabl\n",
    "\n",
    "# for interactivity\n",
    "import ipywidgets as widgets\n",
    "from ipywidgets import interact\n",
    "from ipywidgets import interact_manual"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# reading teh dataset\n",
    "data = pd.read_csv('employee.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1470, 35)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# shape of the data\n",
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Age', 'Attrition', 'BusinessTravel', 'DailyRate', 'Department',\n",
       "       'DistanceFromHome', 'Education', 'EducationField', 'EmployeeCount',\n",
       "       'EmployeeNumber', 'EnvironmentSatisfaction', 'Gender', 'HourlyRate',\n",
       "       'JobInvolvement', 'JobLevel', 'JobRole', 'JobSatisfaction',\n",
       "       'MaritalStatus', 'MonthlyIncome', 'MonthlyRate', 'NumCompaniesWorked',\n",
       "       'Over18', 'OverTime', 'PercentSalaryHike', 'PerformanceRating',\n",
       "       'RelationshipSatisfaction', 'StandardHours', 'StockOptionLevel',\n",
       "       'TotalWorkingYears', 'TrainingTimesLastYear', 'WorkLifeBalance',\n",
       "       'YearsAtCompany', 'YearsInCurrentRole', 'YearsSinceLastPromotion',\n",
       "       'YearsWithCurrManager'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# column\n",
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>Attrition</th>\n",
       "      <th>BusinessTravel</th>\n",
       "      <th>DailyRate</th>\n",
       "      <th>Department</th>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <th>Education</th>\n",
       "      <th>EducationField</th>\n",
       "      <th>EmployeeCount</th>\n",
       "      <th>EmployeeNumber</th>\n",
       "      <th>EnvironmentSatisfaction</th>\n",
       "      <th>Gender</th>\n",
       "      <th>HourlyRate</th>\n",
       "      <th>JobInvolvement</th>\n",
       "      <th>JobLevel</th>\n",
       "      <th>JobRole</th>\n",
       "      <th>JobSatisfaction</th>\n",
       "      <th>MaritalStatus</th>\n",
       "      <th>MonthlyIncome</th>\n",
       "      <th>MonthlyRate</th>\n",
       "      <th>NumCompaniesWorked</th>\n",
       "      <th>Over18</th>\n",
       "      <th>OverTime</th>\n",
       "      <th>PercentSalaryHike</th>\n",
       "      <th>PerformanceRating</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <th>StandardHours</th>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>41</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1102</td>\n",
       "      <td>Sales</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Female</td>\n",
       "      <td>94</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>Sales Executive</td>\n",
       "      <td>4</td>\n",
       "      <td>Single</td>\n",
       "      <td>5993</td>\n",
       "      <td>19479</td>\n",
       "      <td>8</td>\n",
       "      <td>Y</td>\n",
       "      <td>Yes</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>49</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Frequently</td>\n",
       "      <td>279</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Male</td>\n",
       "      <td>61</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Research Scientist</td>\n",
       "      <td>2</td>\n",
       "      <td>Married</td>\n",
       "      <td>5130</td>\n",
       "      <td>24907</td>\n",
       "      <td>1</td>\n",
       "      <td>Y</td>\n",
       "      <td>No</td>\n",
       "      <td>23</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1373</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Other</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>Male</td>\n",
       "      <td>92</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>Laboratory Technician</td>\n",
       "      <td>3</td>\n",
       "      <td>Single</td>\n",
       "      <td>2090</td>\n",
       "      <td>2396</td>\n",
       "      <td>6</td>\n",
       "      <td>Y</td>\n",
       "      <td>Yes</td>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>33</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Frequently</td>\n",
       "      <td>1392</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>Female</td>\n",
       "      <td>56</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Research Scientist</td>\n",
       "      <td>3</td>\n",
       "      <td>Married</td>\n",
       "      <td>2909</td>\n",
       "      <td>23159</td>\n",
       "      <td>1</td>\n",
       "      <td>Y</td>\n",
       "      <td>Yes</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>27</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>591</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>Male</td>\n",
       "      <td>40</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Laboratory Technician</td>\n",
       "      <td>2</td>\n",
       "      <td>Married</td>\n",
       "      <td>3468</td>\n",
       "      <td>16632</td>\n",
       "      <td>9</td>\n",
       "      <td>Y</td>\n",
       "      <td>No</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Age Attrition     BusinessTravel  DailyRate              Department  \\\n",
       "0   41       Yes      Travel_Rarely       1102                   Sales   \n",
       "1   49        No  Travel_Frequently        279  Research & Development   \n",
       "2   37       Yes      Travel_Rarely       1373  Research & Development   \n",
       "3   33        No  Travel_Frequently       1392  Research & Development   \n",
       "4   27        No      Travel_Rarely        591  Research & Development   \n",
       "\n",
       "   DistanceFromHome  Education EducationField  EmployeeCount  EmployeeNumber  \\\n",
       "0                 1          2  Life Sciences              1               1   \n",
       "1                 8          1  Life Sciences              1               2   \n",
       "2                 2          2          Other              1               4   \n",
       "3                 3          4  Life Sciences              1               5   \n",
       "4                 2          1        Medical              1               7   \n",
       "\n",
       "   EnvironmentSatisfaction  Gender  HourlyRate  JobInvolvement  JobLevel  \\\n",
       "0                        2  Female          94               3         2   \n",
       "1                        3    Male          61               2         2   \n",
       "2                        4    Male          92               2         1   \n",
       "3                        4  Female          56               3         1   \n",
       "4                        1    Male          40               3         1   \n",
       "\n",
       "                 JobRole  JobSatisfaction MaritalStatus  MonthlyIncome  \\\n",
       "0        Sales Executive                4        Single           5993   \n",
       "1     Research Scientist                2       Married           5130   \n",
       "2  Laboratory Technician                3        Single           2090   \n",
       "3     Research Scientist                3       Married           2909   \n",
       "4  Laboratory Technician                2       Married           3468   \n",
       "\n",
       "   MonthlyRate  NumCompaniesWorked Over18 OverTime  PercentSalaryHike  \\\n",
       "0        19479                   8      Y      Yes                 11   \n",
       "1        24907                   1      Y       No                 23   \n",
       "2         2396                   6      Y      Yes                 15   \n",
       "3        23159                   1      Y      Yes                 11   \n",
       "4        16632                   9      Y       No                 12   \n",
       "\n",
       "   PerformanceRating  RelationshipSatisfaction  StandardHours  \\\n",
       "0                  3                         1             80   \n",
       "1                  4                         4             80   \n",
       "2                  3                         2             80   \n",
       "3                  3                         3             80   \n",
       "4                  3                         4             80   \n",
       "\n",
       "   StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  \\\n",
       "0                 0                  8                      0   \n",
       "1                 1                 10                      3   \n",
       "2                 0                  7                      3   \n",
       "3                 0                  8                      3   \n",
       "4                 1                  6                      3   \n",
       "\n",
       "   WorkLifeBalance  YearsAtCompany  YearsInCurrentRole  \\\n",
       "0                1               6                   4   \n",
       "1                3              10                   7   \n",
       "2                3               0                   0   \n",
       "3                3               8                   7   \n",
       "4                3               2                   2   \n",
       "\n",
       "   YearsSinceLastPromotion  YearsWithCurrManager  \n",
       "0                        0                     5  \n",
       "1                        1                     7  \n",
       "2                        0                     0  \n",
       "3                        3                     0  \n",
       "4                        2                     2  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# head of teh data\n",
    "pd.set_option('max_columns', 100)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Attrition</th>\n",
       "      <th>BusinessTravel</th>\n",
       "      <th>DailyRate</th>\n",
       "      <th>Department</th>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <th>Education</th>\n",
       "      <th>EducationField</th>\n",
       "      <th>EmployeeCount</th>\n",
       "      <th>EmployeeNumber</th>\n",
       "      <th>...</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <th>StandardHours</th>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1465</th>\n",
       "      <td>36</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Frequently</td>\n",
       "      <td>884</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
       "      <td>2061</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1466</th>\n",
       "      <td>39</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>613</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
       "      <td>2062</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1467</th>\n",
       "      <td>27</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>155</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>2064</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1468</th>\n",
       "      <td>49</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Frequently</td>\n",
       "      <td>1023</td>\n",
       "      <td>Sales</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
       "      <td>2065</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1469</th>\n",
       "      <td>34</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>628</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
       "      <td>2068</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Age Attrition     BusinessTravel  DailyRate              Department  \\\n",
       "1465   36        No  Travel_Frequently        884  Research & Development   \n",
       "1466   39        No      Travel_Rarely        613  Research & Development   \n",
       "1467   27        No      Travel_Rarely        155  Research & Development   \n",
       "1468   49        No  Travel_Frequently       1023                   Sales   \n",
       "1469   34        No      Travel_Rarely        628  Research & Development   \n",
       "\n",
       "      DistanceFromHome  Education EducationField  EmployeeCount  \\\n",
       "1465                23          2        Medical              1   \n",
       "1466                 6          1        Medical              1   \n",
       "1467                 4          3  Life Sciences              1   \n",
       "1468                 2          3        Medical              1   \n",
       "1469                 8          3        Medical              1   \n",
       "\n",
       "      EmployeeNumber  ...  RelationshipSatisfaction StandardHours  \\\n",
       "1465            2061  ...                         3            80   \n",
       "1466            2062  ...                         1            80   \n",
       "1467            2064  ...                         2            80   \n",
       "1468            2065  ...                         4            80   \n",
       "1469            2068  ...                         1            80   \n",
       "\n",
       "      StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  \\\n",
       "1465                 1                 17                      3   \n",
       "1466                 1                  9                      5   \n",
       "1467                 1                  6                      0   \n",
       "1468                 0                 17                      3   \n",
       "1469                 0                  6                      3   \n",
       "\n",
       "     WorkLifeBalance  YearsAtCompany YearsInCurrentRole  \\\n",
       "1465               3               5                  2   \n",
       "1466               3               7                  7   \n",
       "1467               3               6                  2   \n",
       "1468               2               9                  6   \n",
       "1469               4               4                  3   \n",
       "\n",
       "      YearsSinceLastPromotion  YearsWithCurrManager  \n",
       "1465                        0                     3  \n",
       "1466                        1                     7  \n",
       "1467                        0                     3  \n",
       "1468                        0                     8  \n",
       "1469                        1                     2  \n",
       "\n",
       "[5 rows x 35 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# tail of teh data\n",
    "data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
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    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Attrition</th>\n",
       "      <th>BusinessTravel</th>\n",
       "      <th>DailyRate</th>\n",
       "      <th>Department</th>\n",
       "      <th>DistanceFromHome</th>\n",
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       "      <th>EducationField</th>\n",
       "      <th>EmployeeCount</th>\n",
       "      <th>EmployeeNumber</th>\n",
       "      <th>...</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
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       "      <th>YearsWithCurrManager</th>\n",
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       "      <th>973</th>\n",
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       "      <td>No</td>\n",
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       "      <td>817</td>\n",
       "      <td>Research &amp; Development</td>\n",
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       "      <td>No</td>\n",
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       "      <td>116</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>2014</td>\n",
       "      <td>...</td>\n",
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       "      <th>266</th>\n",
       "      <td>31</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1463</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>23</td>\n",
       "      <td>3</td>\n",
       "      <td>Medical</td>\n",
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       "      <td>...</td>\n",
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       "      <td>Yes</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1219</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Technical Degree</td>\n",
       "      <td>1</td>\n",
       "      <td>1106</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
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       "      <td>1</td>\n",
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       "      <td>3</td>\n",
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       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
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       "</table>\n",
       "<p>5 rows × 35 columns</p>\n",
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      "text/plain": [
       "      Age Attrition     BusinessTravel  DailyRate              Department  \\\n",
       "973    35        No      Travel_Rarely        817  Research & Development   \n",
       "1429   39        No      Travel_Rarely        116  Research & Development   \n",
       "1398   33        No  Travel_Frequently       1303  Research & Development   \n",
       "266    31        No      Travel_Rarely       1463  Research & Development   \n",
       "796    25       Yes      Travel_Rarely       1219  Research & Development   \n",
       "\n",
       "      DistanceFromHome  Education    EducationField  EmployeeCount  \\\n",
       "973                  1          3           Medical              1   \n",
       "1429                24          1     Life Sciences              1   \n",
       "1398                 7          2     Life Sciences              1   \n",
       "266                 23          3           Medical              1   \n",
       "796                  4          1  Technical Degree              1   \n",
       "\n",
       "      EmployeeNumber  ...  RelationshipSatisfaction StandardHours  \\\n",
       "973             1369  ...                         2            80   \n",
       "1429            2014  ...                         1            80   \n",
       "1398            1970  ...                         3            80   \n",
       "266              367  ...                         2            80   \n",
       "796             1106  ...                         2            80   \n",
       "\n",
       "      StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  \\\n",
       "973                  1                 10                      0   \n",
       "1429                 0                 18                      2   \n",
       "1398                 3                  9                      2   \n",
       "266                  1                 10                      2   \n",
       "796                  1                  7                      3   \n",
       "\n",
       "     WorkLifeBalance  YearsAtCompany YearsInCurrentRole  \\\n",
       "973                3               9                  7   \n",
       "1429               3               7                  7   \n",
       "1398               3               9                  7   \n",
       "266                3               9                  0   \n",
       "796                4               7                  7   \n",
       "\n",
       "      YearsSinceLastPromotion  YearsWithCurrManager  \n",
       "973                         0                     0  \n",
       "1429                        1                     7  \n",
       "1398                        2                     8  \n",
       "266                         7                     8  \n",
       "796                         5                     6  \n",
       "\n",
       "[5 rows x 35 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sample\n",
    "data.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1470 entries, 0 to 1469\n",
      "Data columns (total 35 columns):\n",
      "Age                         1470 non-null int64\n",
      "Attrition                   1470 non-null object\n",
      "BusinessTravel              1470 non-null object\n",
      "DailyRate                   1470 non-null int64\n",
      "Department                  1470 non-null object\n",
      "DistanceFromHome            1470 non-null int64\n",
      "Education                   1470 non-null int64\n",
      "EducationField              1470 non-null object\n",
      "EmployeeCount               1470 non-null int64\n",
      "EmployeeNumber              1470 non-null int64\n",
      "EnvironmentSatisfaction     1470 non-null int64\n",
      "Gender                      1470 non-null object\n",
      "HourlyRate                  1470 non-null int64\n",
      "JobInvolvement              1470 non-null int64\n",
      "JobLevel                    1470 non-null int64\n",
      "JobRole                     1470 non-null object\n",
      "JobSatisfaction             1470 non-null int64\n",
      "MaritalStatus               1470 non-null object\n",
      "MonthlyIncome               1470 non-null int64\n",
      "MonthlyRate                 1470 non-null int64\n",
      "NumCompaniesWorked          1470 non-null int64\n",
      "Over18                      1470 non-null object\n",
      "OverTime                    1470 non-null object\n",
      "PercentSalaryHike           1470 non-null int64\n",
      "PerformanceRating           1470 non-null int64\n",
      "RelationshipSatisfaction    1470 non-null int64\n",
      "StandardHours               1470 non-null int64\n",
      "StockOptionLevel            1470 non-null int64\n",
      "TotalWorkingYears           1470 non-null int64\n",
      "TrainingTimesLastYear       1470 non-null int64\n",
      "WorkLifeBalance             1470 non-null int64\n",
      "YearsAtCompany              1470 non-null int64\n",
      "YearsInCurrentRole          1470 non-null int64\n",
      "YearsSinceLastPromotion     1470 non-null int64\n",
      "YearsWithCurrManager        1470 non-null int64\n",
      "dtypes: int64(26), object(9)\n",
      "memory usage: 402.1+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Inferential Statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "            background-color:  #faed2d;\n",
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       "            background-color:  #faec2a;\n",
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       "            background-color:  #fc7f00;\n",
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       "            background-color:  #e4ff7a;\n",
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       "            background-color:  #e4ff7a;\n",
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       "            background-color:  #ffd00b;\n",
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       "            background-color:  #e4ff7a;\n",
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       "            background-color:  #fc7f00;\n",
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       "            background-color:  #e4ff7a;\n",
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       "            background-color:  #ffda11;\n",
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       "            background-color:  #ffd00b;\n",
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       "            background-color:  #ecf85d;\n",
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       "            background-color:  #f0f550;\n",
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       "            background-color:  #e4ff7a;\n",
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       "            background-color:  #f1f44d;\n",
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       "            background-color:  #ffbd00;\n",
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       "            background-color:  #fc7f00;\n",
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       "            background-color:  #ffbe01;\n",
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       "            background-color:  #ffaa00;\n",
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       "            background-color:  #ffb500;\n",
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       "            background-color:  #ffa600;\n",
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       "            background-color:  #ffe81a;\n",
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       "            background-color:  #ffaa00;\n",
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       "            background-color:  #faec2c;\n",
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       "            background-color:  #ffbf01;\n",
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       "            background-color:  #fceb26;\n",
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       "            background-color:  #ffbf01;\n",
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       "            background-color:  #ffa300;\n",
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       "            background-color:  #ffaa00;\n",
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       "            background-color:  #fc7f00;\n",
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       "            background-color:  #ffda11;\n",
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       "            background-color:  #ffe81a;\n",
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       "            background-color:  #f6f03b;\n",
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       "            background-color:  #ebf960;\n",
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       "            background-color:  #ff9f00;\n",
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       "            background-color:  #fc7f00;\n",
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       "            background-color:  #ffa000;\n",
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       "            background-color:  #fc7f00;\n",
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       "            background-color:  #fe9a00;\n",
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       "            background-color:  #ffa600;\n",
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       "            background-color:  #ffbd00;\n",
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       "            background-color:  #fc7f00;\n",
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       "            background-color:  #ffd00c;\n",
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       "            background-color:  #ffa100;\n",
       "            color:  #000000;\n",
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       "            background-color:  #ffc706;\n",
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       "            background-color:  #ffa900;\n",
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       "            background-color:  #ffa300;\n",
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       "            background-color:  #fc7f00;\n",
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       "            background-color:  #fc7f00;\n",
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       "            background-color:  #ffda11;\n",
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       "            background-color:  #ffd20d;\n",
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       "            background-color:  #ffbd00;\n",
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       "            background-color:  #ffa600;\n",
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       "            background-color:  #fcea24;\n",
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       "            background-color:  #ffd00c;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col24 {\n",
       "            background-color:  #faed2d;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col25 {\n",
       "            background-color:  #ffcc09;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col0 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col1 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col2 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col3 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col4 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col5 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col6 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col7 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col8 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col9 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col10 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col11 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col12 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col13 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col14 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col15 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col16 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col17 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col18 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col19 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col20 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col21 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col22 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col23 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col24 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }    #T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col25 {\n",
       "            background-color:  #fc7f00;\n",
       "            color:  #000000;\n",
       "        }</style><table id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Age</th>        <th class=\"col_heading level0 col1\" >DailyRate</th>        <th class=\"col_heading level0 col2\" >DistanceFromHome</th>        <th class=\"col_heading level0 col3\" >Education</th>        <th class=\"col_heading level0 col4\" >EmployeeCount</th>        <th class=\"col_heading level0 col5\" >EmployeeNumber</th>        <th class=\"col_heading level0 col6\" >EnvironmentSatisfaction</th>        <th class=\"col_heading level0 col7\" >HourlyRate</th>        <th class=\"col_heading level0 col8\" >JobInvolvement</th>        <th class=\"col_heading level0 col9\" >JobLevel</th>        <th class=\"col_heading level0 col10\" >JobSatisfaction</th>        <th class=\"col_heading level0 col11\" >MonthlyIncome</th>        <th class=\"col_heading level0 col12\" >MonthlyRate</th>        <th class=\"col_heading level0 col13\" >NumCompaniesWorked</th>        <th class=\"col_heading level0 col14\" >PercentSalaryHike</th>        <th class=\"col_heading level0 col15\" >PerformanceRating</th>        <th class=\"col_heading level0 col16\" >RelationshipSatisfaction</th>        <th class=\"col_heading level0 col17\" >StandardHours</th>        <th class=\"col_heading level0 col18\" >StockOptionLevel</th>        <th class=\"col_heading level0 col19\" >TotalWorkingYears</th>        <th class=\"col_heading level0 col20\" >TrainingTimesLastYear</th>        <th class=\"col_heading level0 col21\" >WorkLifeBalance</th>        <th class=\"col_heading level0 col22\" >YearsAtCompany</th>        <th class=\"col_heading level0 col23\" >YearsInCurrentRole</th>        <th class=\"col_heading level0 col24\" >YearsSinceLastPromotion</th>        <th class=\"col_heading level0 col25\" >YearsWithCurrManager</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2level0_row0\" class=\"row_heading level0 row0\" >mean</th>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col0\" class=\"data row0 col0\" >36.9238</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col1\" class=\"data row0 col1\" >802.486</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col2\" class=\"data row0 col2\" >9.19252</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col3\" class=\"data row0 col3\" >2.91293</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col4\" class=\"data row0 col4\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col5\" class=\"data row0 col5\" >1024.87</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col6\" class=\"data row0 col6\" >2.72177</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col7\" class=\"data row0 col7\" >65.8912</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col8\" class=\"data row0 col8\" >2.72993</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col9\" class=\"data row0 col9\" >2.06395</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col10\" class=\"data row0 col10\" >2.72857</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col11\" class=\"data row0 col11\" >6502.93</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col12\" class=\"data row0 col12\" >14313.1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col13\" class=\"data row0 col13\" >2.6932</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col14\" class=\"data row0 col14\" >15.2095</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col15\" class=\"data row0 col15\" >3.15374</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col16\" class=\"data row0 col16\" >2.71224</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col17\" class=\"data row0 col17\" >80</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col18\" class=\"data row0 col18\" >0.793878</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col19\" class=\"data row0 col19\" >11.2796</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col20\" class=\"data row0 col20\" >2.79932</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col21\" class=\"data row0 col21\" >2.76122</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col22\" class=\"data row0 col22\" >7.00816</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col23\" class=\"data row0 col23\" >4.22925</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col24\" class=\"data row0 col24\" >2.18776</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row0_col25\" class=\"data row0 col25\" >4.12313</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2level0_row1\" class=\"row_heading level0 row1\" >std</th>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col0\" class=\"data row1 col0\" >9.13537</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col1\" class=\"data row1 col1\" >403.509</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col2\" class=\"data row1 col2\" >8.10686</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col3\" class=\"data row1 col3\" >1.02416</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col4\" class=\"data row1 col4\" >0</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col5\" class=\"data row1 col5\" >602.024</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col6\" class=\"data row1 col6\" >1.09308</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col7\" class=\"data row1 col7\" >20.3294</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col8\" class=\"data row1 col8\" >0.711561</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col9\" class=\"data row1 col9\" >1.10694</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col10\" class=\"data row1 col10\" >1.10285</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col11\" class=\"data row1 col11\" >4707.96</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col12\" class=\"data row1 col12\" >7117.79</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col13\" class=\"data row1 col13\" >2.49801</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col14\" class=\"data row1 col14\" >3.65994</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col15\" class=\"data row1 col15\" >0.360824</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col16\" class=\"data row1 col16\" >1.08121</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col17\" class=\"data row1 col17\" >0</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col18\" class=\"data row1 col18\" >0.852077</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col19\" class=\"data row1 col19\" >7.78078</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col20\" class=\"data row1 col20\" >1.28927</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col21\" class=\"data row1 col21\" >0.706476</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col22\" class=\"data row1 col22\" >6.12653</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col23\" class=\"data row1 col23\" >3.62314</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col24\" class=\"data row1 col24\" >3.22243</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row1_col25\" class=\"data row1 col25\" >3.56814</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2level0_row2\" class=\"row_heading level0 row2\" >min</th>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col0\" class=\"data row2 col0\" >18</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col1\" class=\"data row2 col1\" >102</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col2\" class=\"data row2 col2\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col3\" class=\"data row2 col3\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col4\" class=\"data row2 col4\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col5\" class=\"data row2 col5\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col6\" class=\"data row2 col6\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col7\" class=\"data row2 col7\" >30</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col8\" class=\"data row2 col8\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col9\" class=\"data row2 col9\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col10\" class=\"data row2 col10\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col11\" class=\"data row2 col11\" >1009</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col12\" class=\"data row2 col12\" >2094</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col13\" class=\"data row2 col13\" >0</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col14\" class=\"data row2 col14\" >11</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col15\" class=\"data row2 col15\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col16\" class=\"data row2 col16\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col17\" class=\"data row2 col17\" >80</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col18\" class=\"data row2 col18\" >0</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col19\" class=\"data row2 col19\" >0</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col20\" class=\"data row2 col20\" >0</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col21\" class=\"data row2 col21\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col22\" class=\"data row2 col22\" >0</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col23\" class=\"data row2 col23\" >0</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col24\" class=\"data row2 col24\" >0</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row2_col25\" class=\"data row2 col25\" >0</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2level0_row3\" class=\"row_heading level0 row3\" >25%</th>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col0\" class=\"data row3 col0\" >30</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col1\" class=\"data row3 col1\" >465</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col2\" class=\"data row3 col2\" >2</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col3\" class=\"data row3 col3\" >2</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col4\" class=\"data row3 col4\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col5\" class=\"data row3 col5\" >491.25</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col6\" class=\"data row3 col6\" >2</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col7\" class=\"data row3 col7\" >48</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col8\" class=\"data row3 col8\" >2</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col9\" class=\"data row3 col9\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col10\" class=\"data row3 col10\" >2</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col11\" class=\"data row3 col11\" >2911</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col12\" class=\"data row3 col12\" >8047</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col13\" class=\"data row3 col13\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col14\" class=\"data row3 col14\" >12</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col15\" class=\"data row3 col15\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col16\" class=\"data row3 col16\" >2</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col17\" class=\"data row3 col17\" >80</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col18\" class=\"data row3 col18\" >0</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col19\" class=\"data row3 col19\" >6</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col20\" class=\"data row3 col20\" >2</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col21\" class=\"data row3 col21\" >2</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col22\" class=\"data row3 col22\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col23\" class=\"data row3 col23\" >2</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col24\" class=\"data row3 col24\" >0</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row3_col25\" class=\"data row3 col25\" >2</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2level0_row4\" class=\"row_heading level0 row4\" >50%</th>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col0\" class=\"data row4 col0\" >36</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col1\" class=\"data row4 col1\" >802</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col2\" class=\"data row4 col2\" >7</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col3\" class=\"data row4 col3\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col4\" class=\"data row4 col4\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col5\" class=\"data row4 col5\" >1020.5</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col6\" class=\"data row4 col6\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col7\" class=\"data row4 col7\" >66</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col8\" class=\"data row4 col8\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col9\" class=\"data row4 col9\" >2</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col10\" class=\"data row4 col10\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col11\" class=\"data row4 col11\" >4919</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col12\" class=\"data row4 col12\" >14235.5</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col13\" class=\"data row4 col13\" >2</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col14\" class=\"data row4 col14\" >14</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col15\" class=\"data row4 col15\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col16\" class=\"data row4 col16\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col17\" class=\"data row4 col17\" >80</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col18\" class=\"data row4 col18\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col19\" class=\"data row4 col19\" >10</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col20\" class=\"data row4 col20\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col21\" class=\"data row4 col21\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col22\" class=\"data row4 col22\" >5</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col23\" class=\"data row4 col23\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col24\" class=\"data row4 col24\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row4_col25\" class=\"data row4 col25\" >3</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2level0_row5\" class=\"row_heading level0 row5\" >75%</th>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col0\" class=\"data row5 col0\" >43</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col1\" class=\"data row5 col1\" >1157</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col2\" class=\"data row5 col2\" >14</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col3\" class=\"data row5 col3\" >4</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col4\" class=\"data row5 col4\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col5\" class=\"data row5 col5\" >1555.75</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col6\" class=\"data row5 col6\" >4</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col7\" class=\"data row5 col7\" >83.75</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col8\" class=\"data row5 col8\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col9\" class=\"data row5 col9\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col10\" class=\"data row5 col10\" >4</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col11\" class=\"data row5 col11\" >8379</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col12\" class=\"data row5 col12\" >20461.5</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col13\" class=\"data row5 col13\" >4</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col14\" class=\"data row5 col14\" >18</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col15\" class=\"data row5 col15\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col16\" class=\"data row5 col16\" >4</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col17\" class=\"data row5 col17\" >80</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col18\" class=\"data row5 col18\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col19\" class=\"data row5 col19\" >15</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col20\" class=\"data row5 col20\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col21\" class=\"data row5 col21\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col22\" class=\"data row5 col22\" >9</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col23\" class=\"data row5 col23\" >7</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col24\" class=\"data row5 col24\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row5_col25\" class=\"data row5 col25\" >7</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2level0_row6\" class=\"row_heading level0 row6\" >max</th>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col0\" class=\"data row6 col0\" >60</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col1\" class=\"data row6 col1\" >1499</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col2\" class=\"data row6 col2\" >29</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col3\" class=\"data row6 col3\" >5</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col4\" class=\"data row6 col4\" >1</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col5\" class=\"data row6 col5\" >2068</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col6\" class=\"data row6 col6\" >4</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col7\" class=\"data row6 col7\" >100</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col8\" class=\"data row6 col8\" >4</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col9\" class=\"data row6 col9\" >5</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col10\" class=\"data row6 col10\" >4</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col11\" class=\"data row6 col11\" >19999</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col12\" class=\"data row6 col12\" >26999</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col13\" class=\"data row6 col13\" >9</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col14\" class=\"data row6 col14\" >25</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col15\" class=\"data row6 col15\" >4</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col16\" class=\"data row6 col16\" >4</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col17\" class=\"data row6 col17\" >80</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col18\" class=\"data row6 col18\" >3</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col19\" class=\"data row6 col19\" >40</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col20\" class=\"data row6 col20\" >6</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col21\" class=\"data row6 col21\" >4</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col22\" class=\"data row6 col22\" >40</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col23\" class=\"data row6 col23\" >18</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col24\" class=\"data row6 col24\" >15</td>\n",
       "                        <td id=\"T_85ada7e2_7d7a_11ea_a8cc_507b9d42aeb2row6_col25\" class=\"data row6 col25\" >17</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1beef852208>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# basic descriptive stats\n",
    "data.describe().iloc[1:,:].style.background_gradient(cmap = 'Wistia')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# correlation\n",
    "plt.rcParams['figure.figsize'] = (15, 10)\n",
    "plt.style.use('fivethirtyeight')\n",
    "pd.set_option('max_columns', 100)\n",
    "sns.heatmap(data.corr(), cmap = 'Reds')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>DailyRate</th>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <th>Education</th>\n",
       "      <th>EmployeeCount</th>\n",
       "      <th>EmployeeNumber</th>\n",
       "      <th>EnvironmentSatisfaction</th>\n",
       "      <th>HourlyRate</th>\n",
       "      <th>JobInvolvement</th>\n",
       "      <th>JobLevel</th>\n",
       "      <th>...</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <th>StandardHours</th>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <td>83.455049</td>\n",
       "      <td>39.298434</td>\n",
       "      <td>-0.124873</td>\n",
       "      <td>1.946390</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-55.797199</td>\n",
       "      <td>0.101319</td>\n",
       "      <td>4.510422</td>\n",
       "      <td>0.193841</td>\n",
       "      <td>5.153276</td>\n",
       "      <td>...</td>\n",
       "      <td>0.528776</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.291977</td>\n",
       "      <td>48.361684</td>\n",
       "      <td>-0.231093</td>\n",
       "      <td>-0.138695</td>\n",
       "      <td>17.423359</td>\n",
       "      <td>7.046750</td>\n",
       "      <td>6.373743</td>\n",
       "      <td>6.587332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DailyRate</th>\n",
       "      <td>39.298434</td>\n",
       "      <td>162819.593737</td>\n",
       "      <td>-16.308004</td>\n",
       "      <td>-6.945424</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-12386.713294</td>\n",
       "      <td>8.095750</td>\n",
       "      <td>191.800350</td>\n",
       "      <td>13.246309</td>\n",
       "      <td>1.324944</td>\n",
       "      <td>...</td>\n",
       "      <td>3.423048</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.489565</td>\n",
       "      <td>45.570709</td>\n",
       "      <td>1.275892</td>\n",
       "      <td>-10.789322</td>\n",
       "      <td>-84.187085</td>\n",
       "      <td>14.520296</td>\n",
       "      <td>-43.206982</td>\n",
       "      <td>-37.957055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <td>-0.124873</td>\n",
       "      <td>-16.308004</td>\n",
       "      <td>65.721251</td>\n",
       "      <td>0.174705</td>\n",
       "      <td>0.0</td>\n",
       "      <td>160.649502</td>\n",
       "      <td>-0.142451</td>\n",
       "      <td>5.130567</td>\n",
       "      <td>0.050667</td>\n",
       "      <td>0.047586</td>\n",
       "      <td>...</td>\n",
       "      <td>0.057478</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.309961</td>\n",
       "      <td>0.291951</td>\n",
       "      <td>-0.386118</td>\n",
       "      <td>-0.152094</td>\n",
       "      <td>0.472219</td>\n",
       "      <td>0.553521</td>\n",
       "      <td>0.261991</td>\n",
       "      <td>0.416715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Education</th>\n",
       "      <td>1.946390</td>\n",
       "      <td>-6.945424</td>\n",
       "      <td>0.174705</td>\n",
       "      <td>1.048914</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.939251</td>\n",
       "      <td>-0.030370</td>\n",
       "      <td>0.349263</td>\n",
       "      <td>0.030927</td>\n",
       "      <td>0.115170</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.010097</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.016076</td>\n",
       "      <td>1.181612</td>\n",
       "      <td>-0.033143</td>\n",
       "      <td>0.007105</td>\n",
       "      <td>0.433659</td>\n",
       "      <td>0.223515</td>\n",
       "      <td>0.179056</td>\n",
       "      <td>0.252390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EmployeeCount</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EmployeeNumber</th>\n",
       "      <td>-55.797199</td>\n",
       "      <td>-12386.713294</td>\n",
       "      <td>160.649502</td>\n",
       "      <td>25.939251</td>\n",
       "      <td>0.0</td>\n",
       "      <td>362433.299749</td>\n",
       "      <td>11.595582</td>\n",
       "      <td>430.551701</td>\n",
       "      <td>-2.950629</td>\n",
       "      <td>-12.341279</td>\n",
       "      <td>...</td>\n",
       "      <td>-45.473775</td>\n",
       "      <td>0.0</td>\n",
       "      <td>31.920482</td>\n",
       "      <td>-67.289749</td>\n",
       "      <td>18.320126</td>\n",
       "      <td>4.384426</td>\n",
       "      <td>-41.458396</td>\n",
       "      <td>-18.357800</td>\n",
       "      <td>-17.496817</td>\n",
       "      <td>-19.755358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EnvironmentSatisfaction</th>\n",
       "      <td>0.101319</td>\n",
       "      <td>8.095750</td>\n",
       "      <td>-0.142451</td>\n",
       "      <td>-0.030370</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.595582</td>\n",
       "      <td>1.194829</td>\n",
       "      <td>-1.107908</td>\n",
       "      <td>-0.006438</td>\n",
       "      <td>0.001466</td>\n",
       "      <td>...</td>\n",
       "      <td>0.009059</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.003197</td>\n",
       "      <td>-0.022905</td>\n",
       "      <td>-0.027283</td>\n",
       "      <td>0.021335</td>\n",
       "      <td>0.009761</td>\n",
       "      <td>0.071317</td>\n",
       "      <td>0.057040</td>\n",
       "      <td>-0.019496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HourlyRate</th>\n",
       "      <td>4.510422</td>\n",
       "      <td>191.800350</td>\n",
       "      <td>5.130567</td>\n",
       "      <td>0.349263</td>\n",
       "      <td>0.0</td>\n",
       "      <td>430.551701</td>\n",
       "      <td>-1.107908</td>\n",
       "      <td>413.285626</td>\n",
       "      <td>0.620006</td>\n",
       "      <td>-0.626800</td>\n",
       "      <td>...</td>\n",
       "      <td>0.029244</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.870674</td>\n",
       "      <td>-0.369139</td>\n",
       "      <td>-0.224036</td>\n",
       "      <td>-0.066170</td>\n",
       "      <td>-2.438866</td>\n",
       "      <td>-1.775575</td>\n",
       "      <td>-1.750142</td>\n",
       "      <td>-1.459700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JobInvolvement</th>\n",
       "      <td>0.193841</td>\n",
       "      <td>13.246309</td>\n",
       "      <td>0.050667</td>\n",
       "      <td>0.030927</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-2.950629</td>\n",
       "      <td>-0.006438</td>\n",
       "      <td>0.620006</td>\n",
       "      <td>0.506319</td>\n",
       "      <td>-0.009948</td>\n",
       "      <td>...</td>\n",
       "      <td>0.026386</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.013049</td>\n",
       "      <td>-0.030634</td>\n",
       "      <td>-0.014071</td>\n",
       "      <td>-0.007348</td>\n",
       "      <td>-0.093097</td>\n",
       "      <td>0.022473</td>\n",
       "      <td>-0.055454</td>\n",
       "      <td>0.065951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JobLevel</th>\n",
       "      <td>5.153276</td>\n",
       "      <td>1.324944</td>\n",
       "      <td>0.047586</td>\n",
       "      <td>0.115170</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-12.341279</td>\n",
       "      <td>0.001466</td>\n",
       "      <td>-0.626800</td>\n",
       "      <td>-0.009948</td>\n",
       "      <td>1.225316</td>\n",
       "      <td>...</td>\n",
       "      <td>0.025901</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.013190</td>\n",
       "      <td>6.737044</td>\n",
       "      <td>-0.025961</td>\n",
       "      <td>0.029574</td>\n",
       "      <td>3.626435</td>\n",
       "      <td>1.561913</td>\n",
       "      <td>1.262322</td>\n",
       "      <td>1.482250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JobSatisfaction</th>\n",
       "      <td>-0.049285</td>\n",
       "      <td>13.604357</td>\n",
       "      <td>-0.032802</td>\n",
       "      <td>-0.012759</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-30.705067</td>\n",
       "      <td>-0.008179</td>\n",
       "      <td>-1.599339</td>\n",
       "      <td>-0.016853</td>\n",
       "      <td>-0.002373</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.014850</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.010046</td>\n",
       "      <td>-0.173208</td>\n",
       "      <td>-0.008217</td>\n",
       "      <td>-0.015161</td>\n",
       "      <td>-0.025693</td>\n",
       "      <td>-0.009209</td>\n",
       "      <td>-0.064728</td>\n",
       "      <td>-0.108830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MonthlyIncome</th>\n",
       "      <td>21412.198982</td>\n",
       "      <td>14641.125975</td>\n",
       "      <td>-649.386355</td>\n",
       "      <td>457.874204</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-42028.530023</td>\n",
       "      <td>-32.210416</td>\n",
       "      <td>-1511.673923</td>\n",
       "      <td>-51.159481</td>\n",
       "      <td>4952.416922</td>\n",
       "      <td>...</td>\n",
       "      <td>131.703156</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.693112</td>\n",
       "      <td>28312.303770</td>\n",
       "      <td>-131.935513</td>\n",
       "      <td>102.053699</td>\n",
       "      <td>14833.730990</td>\n",
       "      <td>6205.846259</td>\n",
       "      <td>5233.677307</td>\n",
       "      <td>5780.054075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MonthlyRate</th>\n",
       "      <td>1823.988823</td>\n",
       "      <td>-92428.502266</td>\n",
       "      <td>1585.264627</td>\n",
       "      <td>-190.148240</td>\n",
       "      <td>0.0</td>\n",
       "      <td>54198.679015</td>\n",
       "      <td>292.537298</td>\n",
       "      <td>-2213.447553</td>\n",
       "      <td>-82.667086</td>\n",
       "      <td>311.714963</td>\n",
       "      <td>...</td>\n",
       "      <td>-31.439933</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-208.164513</td>\n",
       "      <td>1464.435332</td>\n",
       "      <td>13.461200</td>\n",
       "      <td>40.043086</td>\n",
       "      <td>-1031.535222</td>\n",
       "      <td>-330.479133</td>\n",
       "      <td>35.937006</td>\n",
       "      <td>-933.244190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NumCompaniesWorked</th>\n",
       "      <td>6.837739</td>\n",
       "      <td>38.457493</td>\n",
       "      <td>-0.592359</td>\n",
       "      <td>0.323165</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.881380</td>\n",
       "      <td>0.034389</td>\n",
       "      <td>1.125195</td>\n",
       "      <td>0.026684</td>\n",
       "      <td>0.394036</td>\n",
       "      <td>...</td>\n",
       "      <td>0.142425</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.064016</td>\n",
       "      <td>4.618854</td>\n",
       "      <td>-0.212734</td>\n",
       "      <td>-0.014764</td>\n",
       "      <td>-1.812334</td>\n",
       "      <td>-0.821380</td>\n",
       "      <td>-0.296339</td>\n",
       "      <td>-0.983301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PercentSalaryHike</th>\n",
       "      <td>0.121489</td>\n",
       "      <td>33.529204</td>\n",
       "      <td>1.193809</td>\n",
       "      <td>-0.041648</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-28.520432</td>\n",
       "      <td>-0.126824</td>\n",
       "      <td>-0.674252</td>\n",
       "      <td>-0.044805</td>\n",
       "      <td>-0.140705</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.160226</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.023476</td>\n",
       "      <td>-0.586872</td>\n",
       "      <td>-0.024636</td>\n",
       "      <td>-0.008480</td>\n",
       "      <td>-0.807021</td>\n",
       "      <td>-0.020156</td>\n",
       "      <td>-0.261286</td>\n",
       "      <td>-0.156517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PerformanceRating</th>\n",
       "      <td>0.006276</td>\n",
       "      <td>0.068910</td>\n",
       "      <td>0.079300</td>\n",
       "      <td>-0.009068</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-4.422436</td>\n",
       "      <td>-0.011654</td>\n",
       "      <td>-0.015930</td>\n",
       "      <td>-0.007464</td>\n",
       "      <td>-0.008476</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.012231</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001078</td>\n",
       "      <td>0.018933</td>\n",
       "      <td>-0.007247</td>\n",
       "      <td>0.000656</td>\n",
       "      <td>0.007594</td>\n",
       "      <td>0.045738</td>\n",
       "      <td>0.020808</td>\n",
       "      <td>0.029389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <td>0.528776</td>\n",
       "      <td>3.423048</td>\n",
       "      <td>0.057478</td>\n",
       "      <td>-0.010097</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-45.473775</td>\n",
       "      <td>0.009059</td>\n",
       "      <td>0.029244</td>\n",
       "      <td>0.026386</td>\n",
       "      <td>0.025901</td>\n",
       "      <td>...</td>\n",
       "      <td>1.169013</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.042335</td>\n",
       "      <td>0.202360</td>\n",
       "      <td>0.003480</td>\n",
       "      <td>0.014975</td>\n",
       "      <td>0.128287</td>\n",
       "      <td>-0.059242</td>\n",
       "      <td>0.116692</td>\n",
       "      <td>-0.003347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StandardHours</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <td>0.291977</td>\n",
       "      <td>14.489565</td>\n",
       "      <td>0.309961</td>\n",
       "      <td>0.016076</td>\n",
       "      <td>0.0</td>\n",
       "      <td>31.920482</td>\n",
       "      <td>0.003197</td>\n",
       "      <td>0.870674</td>\n",
       "      <td>0.013049</td>\n",
       "      <td>0.013190</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.042335</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.726035</td>\n",
       "      <td>0.067200</td>\n",
       "      <td>0.012385</td>\n",
       "      <td>0.002485</td>\n",
       "      <td>0.078607</td>\n",
       "      <td>0.156884</td>\n",
       "      <td>0.039408</td>\n",
       "      <td>0.075091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <td>48.361684</td>\n",
       "      <td>45.570709</td>\n",
       "      <td>0.291951</td>\n",
       "      <td>1.181612</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-67.289749</td>\n",
       "      <td>-0.022905</td>\n",
       "      <td>-0.369139</td>\n",
       "      <td>-0.030634</td>\n",
       "      <td>6.737044</td>\n",
       "      <td>...</td>\n",
       "      <td>0.202360</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.067200</td>\n",
       "      <td>60.540563</td>\n",
       "      <td>-0.357740</td>\n",
       "      <td>0.005539</td>\n",
       "      <td>29.942577</td>\n",
       "      <td>12.978065</td>\n",
       "      <td>10.151009</td>\n",
       "      <td>12.748396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <td>-0.231093</td>\n",
       "      <td>1.275892</td>\n",
       "      <td>-0.386118</td>\n",
       "      <td>-0.033143</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.320126</td>\n",
       "      <td>-0.027283</td>\n",
       "      <td>-0.224036</td>\n",
       "      <td>-0.014071</td>\n",
       "      <td>-0.025961</td>\n",
       "      <td>...</td>\n",
       "      <td>0.003480</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.012385</td>\n",
       "      <td>-0.357740</td>\n",
       "      <td>1.662219</td>\n",
       "      <td>0.025569</td>\n",
       "      <td>0.028188</td>\n",
       "      <td>-0.026801</td>\n",
       "      <td>-0.008586</td>\n",
       "      <td>-0.018841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <td>-0.138695</td>\n",
       "      <td>-10.789322</td>\n",
       "      <td>-0.152094</td>\n",
       "      <td>0.007105</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.384426</td>\n",
       "      <td>0.021335</td>\n",
       "      <td>-0.066170</td>\n",
       "      <td>-0.007348</td>\n",
       "      <td>0.029574</td>\n",
       "      <td>...</td>\n",
       "      <td>0.014975</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.002485</td>\n",
       "      <td>0.005539</td>\n",
       "      <td>0.025569</td>\n",
       "      <td>0.499108</td>\n",
       "      <td>0.052325</td>\n",
       "      <td>0.127616</td>\n",
       "      <td>0.020355</td>\n",
       "      <td>0.006956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <td>17.423359</td>\n",
       "      <td>-84.187085</td>\n",
       "      <td>0.472219</td>\n",
       "      <td>0.433659</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-41.458396</td>\n",
       "      <td>0.009761</td>\n",
       "      <td>-2.438866</td>\n",
       "      <td>-0.093097</td>\n",
       "      <td>3.626435</td>\n",
       "      <td>...</td>\n",
       "      <td>0.128287</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.078607</td>\n",
       "      <td>29.942577</td>\n",
       "      <td>0.028188</td>\n",
       "      <td>0.052325</td>\n",
       "      <td>37.534310</td>\n",
       "      <td>16.842239</td>\n",
       "      <td>12.208813</td>\n",
       "      <td>16.815196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <td>7.046750</td>\n",
       "      <td>14.520296</td>\n",
       "      <td>0.553521</td>\n",
       "      <td>0.223515</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-18.357800</td>\n",
       "      <td>0.071317</td>\n",
       "      <td>-1.775575</td>\n",
       "      <td>0.022473</td>\n",
       "      <td>1.561913</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.059242</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.156884</td>\n",
       "      <td>12.978065</td>\n",
       "      <td>-0.026801</td>\n",
       "      <td>0.127616</td>\n",
       "      <td>16.842239</td>\n",
       "      <td>13.127122</td>\n",
       "      <td>6.398725</td>\n",
       "      <td>9.235198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <td>6.373743</td>\n",
       "      <td>-43.206982</td>\n",
       "      <td>0.261991</td>\n",
       "      <td>0.179056</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-17.496817</td>\n",
       "      <td>0.057040</td>\n",
       "      <td>-1.750142</td>\n",
       "      <td>-0.055454</td>\n",
       "      <td>1.262322</td>\n",
       "      <td>...</td>\n",
       "      <td>0.116692</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.039408</td>\n",
       "      <td>10.151009</td>\n",
       "      <td>-0.008586</td>\n",
       "      <td>0.020355</td>\n",
       "      <td>12.208813</td>\n",
       "      <td>6.398725</td>\n",
       "      <td>10.384057</td>\n",
       "      <td>5.866587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "      <td>6.587332</td>\n",
       "      <td>-37.957055</td>\n",
       "      <td>0.416715</td>\n",
       "      <td>0.252390</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-19.755358</td>\n",
       "      <td>-0.019496</td>\n",
       "      <td>-1.459700</td>\n",
       "      <td>0.065951</td>\n",
       "      <td>1.482250</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.003347</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.075091</td>\n",
       "      <td>12.748396</td>\n",
       "      <td>-0.018841</td>\n",
       "      <td>0.006956</td>\n",
       "      <td>16.815196</td>\n",
       "      <td>9.235198</td>\n",
       "      <td>5.866587</td>\n",
       "      <td>12.731595</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>26 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   Age      DailyRate  DistanceFromHome  \\\n",
       "Age                          83.455049      39.298434         -0.124873   \n",
       "DailyRate                    39.298434  162819.593737        -16.308004   \n",
       "DistanceFromHome             -0.124873     -16.308004         65.721251   \n",
       "Education                     1.946390      -6.945424          0.174705   \n",
       "EmployeeCount                 0.000000       0.000000          0.000000   \n",
       "EmployeeNumber              -55.797199  -12386.713294        160.649502   \n",
       "EnvironmentSatisfaction       0.101319       8.095750         -0.142451   \n",
       "HourlyRate                    4.510422     191.800350          5.130567   \n",
       "JobInvolvement                0.193841      13.246309          0.050667   \n",
       "JobLevel                      5.153276       1.324944          0.047586   \n",
       "JobSatisfaction              -0.049285      13.604357         -0.032802   \n",
       "MonthlyIncome             21412.198982   14641.125975       -649.386355   \n",
       "MonthlyRate                1823.988823  -92428.502266       1585.264627   \n",
       "NumCompaniesWorked            6.837739      38.457493         -0.592359   \n",
       "PercentSalaryHike             0.121489      33.529204          1.193809   \n",
       "PerformanceRating             0.006276       0.068910          0.079300   \n",
       "RelationshipSatisfaction      0.528776       3.423048          0.057478   \n",
       "StandardHours                 0.000000       0.000000          0.000000   \n",
       "StockOptionLevel              0.291977      14.489565          0.309961   \n",
       "TotalWorkingYears            48.361684      45.570709          0.291951   \n",
       "TrainingTimesLastYear        -0.231093       1.275892         -0.386118   \n",
       "WorkLifeBalance              -0.138695     -10.789322         -0.152094   \n",
       "YearsAtCompany               17.423359     -84.187085          0.472219   \n",
       "YearsInCurrentRole            7.046750      14.520296          0.553521   \n",
       "YearsSinceLastPromotion       6.373743     -43.206982          0.261991   \n",
       "YearsWithCurrManager          6.587332     -37.957055          0.416715   \n",
       "\n",
       "                           Education  EmployeeCount  EmployeeNumber  \\\n",
       "Age                         1.946390            0.0      -55.797199   \n",
       "DailyRate                  -6.945424            0.0   -12386.713294   \n",
       "DistanceFromHome            0.174705            0.0      160.649502   \n",
       "Education                   1.048914            0.0       25.939251   \n",
       "EmployeeCount               0.000000            0.0        0.000000   \n",
       "EmployeeNumber             25.939251            0.0   362433.299749   \n",
       "EnvironmentSatisfaction    -0.030370            0.0       11.595582   \n",
       "HourlyRate                  0.349263            0.0      430.551701   \n",
       "JobInvolvement              0.030927            0.0       -2.950629   \n",
       "JobLevel                    0.115170            0.0      -12.341279   \n",
       "JobSatisfaction            -0.012759            0.0      -30.705067   \n",
       "MonthlyIncome             457.874204            0.0   -42028.530023   \n",
       "MonthlyRate              -190.148240            0.0    54198.679015   \n",
       "NumCompaniesWorked          0.323165            0.0       -1.881380   \n",
       "PercentSalaryHike          -0.041648            0.0      -28.520432   \n",
       "PerformanceRating          -0.009068            0.0       -4.422436   \n",
       "RelationshipSatisfaction   -0.010097            0.0      -45.473775   \n",
       "StandardHours               0.000000            0.0        0.000000   \n",
       "StockOptionLevel            0.016076            0.0       31.920482   \n",
       "TotalWorkingYears           1.181612            0.0      -67.289749   \n",
       "TrainingTimesLastYear      -0.033143            0.0       18.320126   \n",
       "WorkLifeBalance             0.007105            0.0        4.384426   \n",
       "YearsAtCompany              0.433659            0.0      -41.458396   \n",
       "YearsInCurrentRole          0.223515            0.0      -18.357800   \n",
       "YearsSinceLastPromotion     0.179056            0.0      -17.496817   \n",
       "YearsWithCurrManager        0.252390            0.0      -19.755358   \n",
       "\n",
       "                          EnvironmentSatisfaction   HourlyRate  \\\n",
       "Age                                      0.101319     4.510422   \n",
       "DailyRate                                8.095750   191.800350   \n",
       "DistanceFromHome                        -0.142451     5.130567   \n",
       "Education                               -0.030370     0.349263   \n",
       "EmployeeCount                            0.000000     0.000000   \n",
       "EmployeeNumber                          11.595582   430.551701   \n",
       "EnvironmentSatisfaction                  1.194829    -1.107908   \n",
       "HourlyRate                              -1.107908   413.285626   \n",
       "JobInvolvement                          -0.006438     0.620006   \n",
       "JobLevel                                 0.001466    -0.626800   \n",
       "JobSatisfaction                         -0.008179    -1.599339   \n",
       "MonthlyIncome                          -32.210416 -1511.673923   \n",
       "MonthlyRate                            292.537298 -2213.447553   \n",
       "NumCompaniesWorked                       0.034389     1.125195   \n",
       "PercentSalaryHike                       -0.126824    -0.674252   \n",
       "PerformanceRating                       -0.011654    -0.015930   \n",
       "RelationshipSatisfaction                 0.009059     0.029244   \n",
       "StandardHours                            0.000000     0.000000   \n",
       "StockOptionLevel                         0.003197     0.870674   \n",
       "TotalWorkingYears                       -0.022905    -0.369139   \n",
       "TrainingTimesLastYear                   -0.027283    -0.224036   \n",
       "WorkLifeBalance                          0.021335    -0.066170   \n",
       "YearsAtCompany                           0.009761    -2.438866   \n",
       "YearsInCurrentRole                       0.071317    -1.775575   \n",
       "YearsSinceLastPromotion                  0.057040    -1.750142   \n",
       "YearsWithCurrManager                    -0.019496    -1.459700   \n",
       "\n",
       "                          JobInvolvement     JobLevel  ...  \\\n",
       "Age                             0.193841     5.153276  ...   \n",
       "DailyRate                      13.246309     1.324944  ...   \n",
       "DistanceFromHome                0.050667     0.047586  ...   \n",
       "Education                       0.030927     0.115170  ...   \n",
       "EmployeeCount                   0.000000     0.000000  ...   \n",
       "EmployeeNumber                 -2.950629   -12.341279  ...   \n",
       "EnvironmentSatisfaction        -0.006438     0.001466  ...   \n",
       "HourlyRate                      0.620006    -0.626800  ...   \n",
       "JobInvolvement                  0.506319    -0.009948  ...   \n",
       "JobLevel                       -0.009948     1.225316  ...   \n",
       "JobSatisfaction                -0.016853    -0.002373  ...   \n",
       "MonthlyIncome                 -51.159481  4952.416922  ...   \n",
       "MonthlyRate                   -82.667086   311.714963  ...   \n",
       "NumCompaniesWorked              0.026684     0.394036  ...   \n",
       "PercentSalaryHike              -0.044805    -0.140705  ...   \n",
       "PerformanceRating              -0.007464    -0.008476  ...   \n",
       "RelationshipSatisfaction        0.026386     0.025901  ...   \n",
       "StandardHours                   0.000000     0.000000  ...   \n",
       "StockOptionLevel                0.013049     0.013190  ...   \n",
       "TotalWorkingYears              -0.030634     6.737044  ...   \n",
       "TrainingTimesLastYear          -0.014071    -0.025961  ...   \n",
       "WorkLifeBalance                -0.007348     0.029574  ...   \n",
       "YearsAtCompany                 -0.093097     3.626435  ...   \n",
       "YearsInCurrentRole              0.022473     1.561913  ...   \n",
       "YearsSinceLastPromotion        -0.055454     1.262322  ...   \n",
       "YearsWithCurrManager            0.065951     1.482250  ...   \n",
       "\n",
       "                          RelationshipSatisfaction  StandardHours  \\\n",
       "Age                                       0.528776            0.0   \n",
       "DailyRate                                 3.423048            0.0   \n",
       "DistanceFromHome                          0.057478            0.0   \n",
       "Education                                -0.010097            0.0   \n",
       "EmployeeCount                             0.000000            0.0   \n",
       "EmployeeNumber                          -45.473775            0.0   \n",
       "EnvironmentSatisfaction                   0.009059            0.0   \n",
       "HourlyRate                                0.029244            0.0   \n",
       "JobInvolvement                            0.026386            0.0   \n",
       "JobLevel                                  0.025901            0.0   \n",
       "JobSatisfaction                          -0.014850            0.0   \n",
       "MonthlyIncome                           131.703156            0.0   \n",
       "MonthlyRate                             -31.439933            0.0   \n",
       "NumCompaniesWorked                        0.142425            0.0   \n",
       "PercentSalaryHike                        -0.160226            0.0   \n",
       "PerformanceRating                        -0.012231            0.0   \n",
       "RelationshipSatisfaction                  1.169013            0.0   \n",
       "StandardHours                             0.000000            0.0   \n",
       "StockOptionLevel                         -0.042335            0.0   \n",
       "TotalWorkingYears                         0.202360            0.0   \n",
       "TrainingTimesLastYear                     0.003480            0.0   \n",
       "WorkLifeBalance                           0.014975            0.0   \n",
       "YearsAtCompany                            0.128287            0.0   \n",
       "YearsInCurrentRole                       -0.059242            0.0   \n",
       "YearsSinceLastPromotion                   0.116692            0.0   \n",
       "YearsWithCurrManager                     -0.003347            0.0   \n",
       "\n",
       "                          StockOptionLevel  TotalWorkingYears  \\\n",
       "Age                               0.291977          48.361684   \n",
       "DailyRate                        14.489565          45.570709   \n",
       "DistanceFromHome                  0.309961           0.291951   \n",
       "Education                         0.016076           1.181612   \n",
       "EmployeeCount                     0.000000           0.000000   \n",
       "EmployeeNumber                   31.920482         -67.289749   \n",
       "EnvironmentSatisfaction           0.003197          -0.022905   \n",
       "HourlyRate                        0.870674          -0.369139   \n",
       "JobInvolvement                    0.013049          -0.030634   \n",
       "JobLevel                          0.013190           6.737044   \n",
       "JobSatisfaction                   0.010046          -0.173208   \n",
       "MonthlyIncome                    21.693112       28312.303770   \n",
       "MonthlyRate                    -208.164513        1464.435332   \n",
       "NumCompaniesWorked                0.064016           4.618854   \n",
       "PercentSalaryHike                 0.023476          -0.586872   \n",
       "PerformanceRating                 0.001078           0.018933   \n",
       "RelationshipSatisfaction         -0.042335           0.202360   \n",
       "StandardHours                     0.000000           0.000000   \n",
       "StockOptionLevel                  0.726035           0.067200   \n",
       "TotalWorkingYears                 0.067200          60.540563   \n",
       "TrainingTimesLastYear             0.012385          -0.357740   \n",
       "WorkLifeBalance                   0.002485           0.005539   \n",
       "YearsAtCompany                    0.078607          29.942577   \n",
       "YearsInCurrentRole                0.156884          12.978065   \n",
       "YearsSinceLastPromotion           0.039408          10.151009   \n",
       "YearsWithCurrManager              0.075091          12.748396   \n",
       "\n",
       "                          TrainingTimesLastYear  WorkLifeBalance  \\\n",
       "Age                                   -0.231093        -0.138695   \n",
       "DailyRate                              1.275892       -10.789322   \n",
       "DistanceFromHome                      -0.386118        -0.152094   \n",
       "Education                             -0.033143         0.007105   \n",
       "EmployeeCount                          0.000000         0.000000   \n",
       "EmployeeNumber                        18.320126         4.384426   \n",
       "EnvironmentSatisfaction               -0.027283         0.021335   \n",
       "HourlyRate                            -0.224036        -0.066170   \n",
       "JobInvolvement                        -0.014071        -0.007348   \n",
       "JobLevel                              -0.025961         0.029574   \n",
       "JobSatisfaction                       -0.008217        -0.015161   \n",
       "MonthlyIncome                       -131.935513       102.053699   \n",
       "MonthlyRate                           13.461200        40.043086   \n",
       "NumCompaniesWorked                    -0.212734        -0.014764   \n",
       "PercentSalaryHike                     -0.024636        -0.008480   \n",
       "PerformanceRating                     -0.007247         0.000656   \n",
       "RelationshipSatisfaction               0.003480         0.014975   \n",
       "StandardHours                          0.000000         0.000000   \n",
       "StockOptionLevel                       0.012385         0.002485   \n",
       "TotalWorkingYears                     -0.357740         0.005539   \n",
       "TrainingTimesLastYear                  1.662219         0.025569   \n",
       "WorkLifeBalance                        0.025569         0.499108   \n",
       "YearsAtCompany                         0.028188         0.052325   \n",
       "YearsInCurrentRole                    -0.026801         0.127616   \n",
       "YearsSinceLastPromotion               -0.008586         0.020355   \n",
       "YearsWithCurrManager                  -0.018841         0.006956   \n",
       "\n",
       "                          YearsAtCompany  YearsInCurrentRole  \\\n",
       "Age                            17.423359            7.046750   \n",
       "DailyRate                     -84.187085           14.520296   \n",
       "DistanceFromHome                0.472219            0.553521   \n",
       "Education                       0.433659            0.223515   \n",
       "EmployeeCount                   0.000000            0.000000   \n",
       "EmployeeNumber                -41.458396          -18.357800   \n",
       "EnvironmentSatisfaction         0.009761            0.071317   \n",
       "HourlyRate                     -2.438866           -1.775575   \n",
       "JobInvolvement                 -0.093097            0.022473   \n",
       "JobLevel                        3.626435            1.561913   \n",
       "JobSatisfaction                -0.025693           -0.009209   \n",
       "MonthlyIncome               14833.730990         6205.846259   \n",
       "MonthlyRate                 -1031.535222         -330.479133   \n",
       "NumCompaniesWorked             -1.812334           -0.821380   \n",
       "PercentSalaryHike              -0.807021           -0.020156   \n",
       "PerformanceRating               0.007594            0.045738   \n",
       "RelationshipSatisfaction        0.128287           -0.059242   \n",
       "StandardHours                   0.000000            0.000000   \n",
       "StockOptionLevel                0.078607            0.156884   \n",
       "TotalWorkingYears              29.942577           12.978065   \n",
       "TrainingTimesLastYear           0.028188           -0.026801   \n",
       "WorkLifeBalance                 0.052325            0.127616   \n",
       "YearsAtCompany                 37.534310           16.842239   \n",
       "YearsInCurrentRole             16.842239           13.127122   \n",
       "YearsSinceLastPromotion        12.208813            6.398725   \n",
       "YearsWithCurrManager           16.815196            9.235198   \n",
       "\n",
       "                          YearsSinceLastPromotion  YearsWithCurrManager  \n",
       "Age                                      6.373743              6.587332  \n",
       "DailyRate                              -43.206982            -37.957055  \n",
       "DistanceFromHome                         0.261991              0.416715  \n",
       "Education                                0.179056              0.252390  \n",
       "EmployeeCount                            0.000000              0.000000  \n",
       "EmployeeNumber                         -17.496817            -19.755358  \n",
       "EnvironmentSatisfaction                  0.057040             -0.019496  \n",
       "HourlyRate                              -1.750142             -1.459700  \n",
       "JobInvolvement                          -0.055454              0.065951  \n",
       "JobLevel                                 1.262322              1.482250  \n",
       "JobSatisfaction                         -0.064728             -0.108830  \n",
       "MonthlyIncome                         5233.677307           5780.054075  \n",
       "MonthlyRate                             35.937006           -933.244190  \n",
       "NumCompaniesWorked                      -0.296339             -0.983301  \n",
       "PercentSalaryHike                       -0.261286             -0.156517  \n",
       "PerformanceRating                        0.020808              0.029389  \n",
       "RelationshipSatisfaction                 0.116692             -0.003347  \n",
       "StandardHours                            0.000000              0.000000  \n",
       "StockOptionLevel                         0.039408              0.075091  \n",
       "TotalWorkingYears                       10.151009             12.748396  \n",
       "TrainingTimesLastYear                   -0.008586             -0.018841  \n",
       "WorkLifeBalance                          0.020355              0.006956  \n",
       "YearsAtCompany                          12.208813             16.815196  \n",
       "YearsInCurrentRole                       6.398725              9.235198  \n",
       "YearsSinceLastPromotion                 10.384057              5.866587  \n",
       "YearsWithCurrManager                     5.866587             12.731595  \n",
       "\n",
       "[26 rows x 26 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# covariance\n",
    "data.cov()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\roshan\\appdata\\local\\programs\\python\\python36\\lib\\site-packages\\dabl\\preprocessing.py:286: UserWarning: Suspiciously looks like an index: ['EmployeeNumber'], but unsure, so keeping it for now\n",
      "  \" so keeping it for now\".format(warn_for), UserWarning)\n",
      "c:\\users\\roshan\\appdata\\local\\programs\\python\\python36\\lib\\site-packages\\dabl\\preprocessing.py:318: UserWarning: Discarding near-constant features: ['EmployeeCount', 'Over18', 'StandardHours']\n",
      "  near_constant.index[near_constant].tolist()))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target looks like classification\n",
      "Linear Discriminant Analysis training set score: 0.502\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x432 with 15 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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AeJgWLVqoZ8+emjZtmsNym812xUuFlOVlVggHAHigqVOnaseOHfriiy/syxo1aqQvv/xShYWF9mU7duxQxYoVVadOnTKbjXAAgAeqW7euHn74YS1evNi+LD4+Xr/88oueeeYZHThwQOvXr1diYqJGjBihqlWrltlsvBwXwA2hPL6T+9lnn9Wbb75p/3utWrX07rvvaurUqWrXrp0CAwPVv39/TZ06tUznIhwA4AFeeeWVYsuCg4OVlZXlsOyee+5xOHzlDhyqAgAYIRwAACOEAwBghHAAAIwQDgCAEcIBADBCOAAARggHAMAI4QAAGOGd4wBuCKafLni9vO3TCX+LPQ4AcLORI0eqbdu2unDhgsPyLVu2qEaNGtq1a5ebJisZexwAruhafkv35t+0XWX27Nm65557lJKSoueee06SdPr0aY0dO1bjx49X69at3TyhI/Y4AMDNLBaLFi5cqPnz52v37t2SpClTpshisSghIUGStH//fvXv318RERGqV6+eRowYoRMnTtjv49tvv1WPHj0UGRmpiIgItW3bVtu2bXPJvIQDADxA+/bt9cgjj2jUqFFatWqV3n33XS1ZskQVK1bU0aNH1b17dzVr1kwbN27Uhx9+qNzcXA0dOlQ2m03S5c/qCA8P1xdffKGtW7fq2WefVeXKlV0yK4eqAMBDJCYmatOmTYqLi9P06dPVuHFjSVJqaqqaN2/u8Lkbr7zyiqKjo7Vv3z7deeedysrK0oQJE9SgQQNJlz8IylXY4wAAD1GlShU9/vjjqlSpksaNG2dfvnfvXqWnpys8PNz+p1mzZpKkn3/+WZI0ZswYjRkzRr169dKLL76oH374wWVzEg4A8CB+fn7y9fWVr+//np4LCwvVtWtXpaenO/zZs2ePOnfuLEn661//qp07dyo2NlY7d+5UTEyM3njjDZfMyKEqAPBwd9xxhz7++GNFRUXJ3//KT9v16tVTvXr1NGbMGI0fP16vv/66HnzwQafPwx4HAHi4kSNHKicnR/Hx8dq9e7d+/vlnbdq0SY8//rjOnTun/Px8TZw4Udu2bdOhQ4f05ZdfateuXWrUqJFL5mGPA8ANoTy/vyQ8PFzr169XYmKi+vbtq/PnzysiIkIdO3ZUhQoV5OPjo5MnT2rUqFE6ceKEbrnlFnXt2lVJSUkumYdwAIAHGTJkiIYMGVJsef369bVy5coSv8bf31+vvfaaq0ez41AVAMAI4QAAGCEcAAAjhAMAYIRwAACMEA4AXqfown+4suv5HhEOAF6lWrVqslqtxOMqbDabrFarqlWrdk1fz/s4AHgVf39/3XzzzTp9+rS7R9Hp06cVEBDg7jFKdPPNN1/18iVXQzgAeB1/f38FBga6ewydOHFCkZGR7h7D6ThUBQAwQjgAAEYIBwDACOEAABghHAAAI4QDAGCEcAAAjBAOAIARwgEAMEI4AABGCAcAwAjhAAAYIRwAACOEAwBghHAAAIwQDgCAET7ICShnbhre3mj9/OWbXTLH1ZjOqL++6pI54BrscQAAjBAOAIARwgEAMEI4AABGODkO4IZUHl5k4KnY4wAAGCEcAAAjhAMAYIRwAACMcHIccAJOtOJGwh4HAMAI4QAAGCEcAAAjnOMAbhCch4GzsMcBADBCOAAARggHAMAI4QAAGCEcAAAjhAMAYIRwAACMEA4AgBHCAQAwQjgAAEYIBwDACOEAABghHAAAI4QDAGCEy6oDKNdMLxcvccn468UeBwDACOEAABghHAAAI4QDAGCEk+OAm5ie1G0uTup6ApOfm7f+zNjjAAAYIRwAACOEAwBghHAAAIwQDgCAEcIBADBCOAAARggHAMAI4QAAGCEcAAAjhAMAYIRwAACMEA4AgBHCAQAwQjgAAEYIBwDACOEAABghHAAAI4QDAGCEcAAAjBAOAIARwgEAMEI4AABGCAcAwAjhAAAYIRwAACOEAwBghHAAAIwQDgCAEX93DwB4kpuGtzdaP3/5ZpfMAXgy9jgAAEYIBwDACOEAABghHAAAI4QDAGCEcAAAjBAOAIARwgEAMEI4AABGCAcAwAjhAAAYIRwAACOEAwBghHAAAIxwWXV4PNNLneuvr5p/jbhEOlBa7HEAAIwQDgCAEcIBADBCOAAARjg5jjLD53njRnWtL9bw1P8z7HEAAIwQDgCAEcIBADBCOAAARggHAMAI4QAAGCEcAAAjhAMAYIRwAACM8M5xL3Etlx6/lq/j3dwA2OMAABghHAAAI4QDAGCEcAAAjJTbk+Oc1AUA92CPAwBghHAAAIwQDgCAEcIBADDiY7Vabc64o++//17169c3/rrk5GSlpKQ4YwQAgKRJkyZp8uTJLrt/t4fD07Fd5Y+3bpu3bpfkvdvmrdvFoSoAgBHCAQAwQjgAAEYIBwDACOEAABghHAAAI4QDAGCEcAAAjBAOAIARwgEAMEI4AABGCAcAwAjhAAAYIRwAACP+7h4AQNmwLD1itL41LtxFk6C8Y48DAGCEcAAAjBAOAIARwgEAMEI4AABGCAcAwAjhAAAYIRwAACOEAwBghHAAAIwQDgCAEcIBADBCOAAARggHAMAI4QAAGCEcAAAjhAMAYIRwAACMEA4AgBHCAQAwQjgAAEYIBwDACOEAABghHAAAI4QDAGCEcAAAjBAOAIARwgEAMOLv7gEAb2BZesRofWtcuIsmcS7T7ZLKz7bh2hEOoJzx1kih/OBQFQDACOEAABghHAAAI5zjANzE/MRzVVnru2QUwAh7HAAAI4QDAGCEcAAAjBAOAIARwgEAMEI4AABGCAcAwAjhAAAYIRwAACOEAwBghHAAAIwQDgCAEcIBADBCOAAARggHAMAI4QAAGCEcAAAjfAIgAKcz/XTDL9u6aBC4BHscAAAjhAMAYIRwAACMEA4AgBHCAQAwQjgAAEYIBwDACO/jAH7D9P0H1rhwF00CeC72OAAARtjjgFcy3XOQ2HsASos9DgCAEcIBADBCOAAARggHAMAI4QAAGCEcAAAjhAMAYIRwAACMEA4AgBHCAQAwQjgAAEa4VhUAj8HVicsHwgGPZ/pk8mVbFw0CQBKHqgAAhggHAMAI4QAAGCEcAAAjhAMAYIRwAACMEA4AgBHCAQAwQjgAAEYIBwDACOEAABghHAAAI1zkEGWGK58C3oE9DgCAEcIBADBCOAAARggHAMAI4QAAGCEcAAAjhAMAYIRwAACMEA4AgBHCAQAwQjgAAEYIBwDACOEAABghHAAAI4QDAGCEcAAAjBAOAIARwgEAMEI4AABGCAcAwAjhAAAYIRwAACOEAwBghHAAAIwQDgCAEcIBADBCOAAARggHAMCIv7sHQPljWXrE+GusceEumASAOxAOAOUav8iUPQ5VAQCMEA4AgBHCAQAwwjmOG5zp8WGODQNgjwMAYIRwAACMEA4AgBHCAQAwQjgAAEYIBwDACOEAABghHAAAI4QDAGCEcAAAjBAOAIARwgEAMEI4AABGuDougBsSV4a+doTDS5j+J/iyrYsGAeD1OFQFADBCOAAARggHAMAI4QAAGCEcAAAjvKrKw5i+OkriZYIAyhZ7HAAAI4QDAGCEcAAAjHCOw4W4pAEAb8QeBwDACHscAGDA7EhCVVnru2wUt2GPAwBghHAAAIwQDgCAEc5xAICLedsVIcptOHipKwC4h9vDUR4CUB5mBICy4vZwAABK5qm/tPpYrVZbmTwSAMAr8KoqAIARwgEAMEI4AABGCAcAwAjhAAAYIRwAACMuC4fNZlO/fv1ksVi0atUqVz1MmRk/frzuvPNOhYWFKTo6WoMHD9aBAwfcPdZ1O3XqlCZOnKiWLVsqLCxMjRs31tNPP62TJ0+6e7TrtmzZMt1///2KioqSxWJRZmamu0e6ZqmpqWrWrJlCQ0N13333afv27e4e6bplZGRo0KBBuu2222SxWJSWlubukZxi7ty56tChgyIjIxUdHa2BAwdq//797h7LqVwWjpdffll+fn6uuvsy17x5cy1atEi7du3S+++/L5vNpt69e+vixYvuHu26HDt2TMeOHVNiYqK2b9+uJUuWaPv27YqPj3f3aNft7Nmz6tixoxISEtw9ynX54IMPlJCQoGeeeUZbt25Vq1atNGDAAB0+fNjdo12XM2fO6Pbbb9esWbNUpUoVd4/jNNu2bVN8fLzWr1+v1atXy9/fX71799apU6fcPZrTuOQNgF9//bWGDh2qzZs3q379+lq+fLl69erl7Idxq++++05t27bVl19+qfr1veuTWjZs2KCBAwcqMzNTAQEB7h7nun399dfq0KGD9u3bp9q1a7t7HGOdOnVS48aNtWDBAvuyFi1aqFevXpo2bZobJ3Oe8PBwzZ49W0OGDHH3KE6Xn5+vqKgopaWlqVu3bu4exymcvseRl5en+Ph4zZs3T8HBwc6+e49w5swZpaWlKSIiQlFRUe4ex+ny8vJUqVIlVa1a1d2j3PAuXLigvXv3qmPHjg7LO3bsqF27drlpKpjIz89XYWGhLBaLu0dxGqeH4+mnn1anTp3UpUsXZ9+126Wmpio8PFzh4eH6/PPPtXr1alWqVMndYzmV1WrV888/r2HDhsnfn0uZuVtOTo4uXbpU7Jew4OBgnThxwk1TwURCQoKaNm2qVq1auXsUpylVOGbOnCmLxXLVP+np6Xrrrbf03XffKSkpydVzO0Vpt6vIgAEDtHXrVq1bt07R0dEaPny4zp4968YtuDLTbZMu70kNHjxYNWvW1IwZM9w0+dVdy3Z5Ax8fH4e/22y2YsvgeaZMmaKdO3fq9ddf96pzvqX6lXL06NF64IEHrrpORESE3njjDf3nP/9ReLjjFRrj4uLUqlUrffrpp9c+qQuUdruKBAYGKjAwUNHR0WrZsqVuvfVWrV69WoMGDXL1qMZMty0/P18DBgyQJL399tuqXLmyS+e7VqbbVd4FBQXJz8+v2N5Fdna21x4K9haTJ0/WBx98oDVr1ujWW2919zhOVapwBAUFKSgo6A/Xe+655/T44487LGvTpo2SkpLUvXv3a5vQhUq7XSWx2Wyy2Wy6cOGCk6dyDpNty8vL04ABA2Sz2fTee+/ppptucvF01+56fmblUcWKFXXnnXdq06ZN6t27t335pk2b1LNnTzdOhquZNGmSPvjgA61du1YNGjRw9zhO59SD2LVq1VKtWrWKLY+IiCjXxT148KBWr16t9u3bKygoSEePHtW8efNUsWJFxcbGunu865KXl6e+ffsqLy9PaWlpOnv2rP3wW/Xq1VWxYkU3T3jtjh8/ruPHj+uHH36QJB04cEC5ubmKjIxU9erV3Txd6Y0dO1aPPfaY7rrrLrVu3Vr/+Mc/9MsvvyguLs7do12X/Px8HTx4UJJUWFiorKwsffPNN6pevboiIyPdPN21mzBhgt5++22tXLlSFotFx48flyRVq1bNo38pM+Hyz+OwWCzl/uW4WVlZevLJJ7V3717l5uYqJCREbdq00cSJE8v9bxPp6enq0aNHibetWbNG7dq1K+OJnCc5OVkpKSnFli9cuLDcvewzNTVV8+fP1/Hjx3XbbbfphRde0D333OPusa7Llf7tDR48WK+88oobJnKOK716atKkSZo8eXIZT+MafJATAMAI16oCABghHAAAI4QDAGCEcAAAjBAOAIARwgEAMEI4UG7t3btX3bp1U0REhNdeowrwRFz+FOXSpUuXFBcXp8LCQs2YMUPVqlVTw4YNnf44f//731WtWrVy94ZBwJV4AyDKpczMTN1xxx164YUXNGbMGJc9TsuWLRUSEqJ169a57DGA8oZDVSiXsrOzJV2+YnF55KmX4wdKg3Cg3Bk9erQ6deok6fIFAC0Wi5o2bSpJ+uWXX/TEE0+oUaNGCgkJUYsWLTR//nzZbI471i+99JJiY2NVt25dhYaGqk2bNlqxYoXDOk2bNtX333+vjIwM+2d9FD1OWlqaLBaLMjMzHb4mMzNTFotFaWlpDvOGhobq0KFDevDBBxUVFWW/hL0k/fjjj3rkkUcUHR1tvw7aypUrnfcNA5yMcxwod+Li4lS7dm3NmjVLDz/8sGJiYlStWjX9+uuv6ty5swoKCjR8+HCFhYVpx44dmjZtmo4dO6ZZs2bZ72PRolfUdfQAAAQCSURBVEXq3LmzevfuLR8fH61du1bjx49XYWGhHn74YUmXL5I4YcIEBQQE6JlnnpF0+Qqn16KwsFB9+/ZVixYtlJiYaP9QnwMHDig2NlZBQUEaO3asAgMDtWHDBo0bN06nT5926WE44FoRDpQ7rVq1ko+Pj2bNmqWWLVtq4MCBkqQnnnhC58+fV0ZGhkJCQiRdjkxYWJhefvlljR49WrVr15Yk7d692+Ez1UeNGqXevXtrwYIF9nDcf//9SkxMVHBwsP0xrtXFixfVpUsXvfDCCw7LExISFBoaqk2bNtnniY+PV1xcnJKTkzV8+PBrjhXgKhyqglew2WxatWqVYmNj5efnp5ycHPufTp06qbCwUBkZGfb1i56kL168qFOnTiknJ0f33nuvDh48qNzcXJfM+Oijjzr83Wq1avPmzerdu7fOnTvnMHPnzp2Vl5enr7/+2iWzANeDPQ54hezsbFmtVq1cufKK5weKTqhL0rp16zRnzhx9++23unTpksN6p0+fdvpJd19fX0VFRTks+/HHH2Wz2ZSSklLi54b8fmbAUxAOeIXCwkJJUv/+/TV06NAS16lbt64kaefOnRo6dKj+9Kc/ad68eQoLC1PFihW1YcMGLVq0yH5fV+Pj43PVOX6vQoUK8vf3L3HdMWPGqEuXLiV+3e233/6HswBljXDAK9SoUUMBAQEqKChQ+/btr7ruRx99pMqVK+vDDz9U5cqV7ctLeuf5lQJR9Clvvz+sdejQoVLPXPRxyv7+/n84M+BJOMcBr+Dn56eePXtq7dq12rt3b7Hbc3NzdfHiRfu6Pj4+DnsHRYe5fq9q1aqyWq3Flhftvfw+Nq+++mqpZw4ODta9996rZcuWKSsrq9jtHKaCp2KPA15j+vTpysjIUNeuXfXQQw/p9ttvV15envbv3681a9Zoz549Cg0NVdeuXbVw4UL16dNHAwcO1KlTp7R8+XKFhITo+PHjDvfZvHlzLVu2TLNmzVK9evVUrVo1devWTY0aNVJMTIxmzpypU6dOKSQkRJ988olOnTplNPPcuXMVGxure+65R8OHD1d0dLRycnK0b98+bdy4UYcPH3bmtwhwCsIBr1GjRg198cUXmjNnjtatW6dly5YpMDBQ9erVU0JCgqpXry5JateunV555RXNmzdPkydPVq1atTRy5EhZLBaNGzfO4T4TEhJ07NgxLVq0SKdPn1ZkZKS6desmSVqyZImefvppLVy4UFWqVFHfvn0VHx+vmJiYUs9cr149bd68WbNnz9a7776r7OxsBQUFqWHDhkpKSnLeNwdwIq5VBQAwwjkOAIARwgEAMEI4AABGCAcAwAjhAAAYIRwAACOEAwBghHAAAIwQDgCAkf8HkmsjGqTCaH8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# using dabl to analyze the target col relations\n",
    "dabl.plot(data, target_col = 'Attrition')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Interactive Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4c4eca0af2ee472f912542cb2be2df29",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column1', options=('DailyRate', 'DistanceFromHome', 'Education', '…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact\n",
    "def check(column1 = list(data.select_dtypes('number').columns[1:]),\n",
    "          column2 = list(data.select_dtypes('number').columns[2:])):\n",
    "    print(\"Correlation :\", data[column1].corr(data[column2]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "61fe8df2f2574b468c4fc233fe055045",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column1', options=('DailyRate', 'DistanceFromHome', 'Education', '…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact\n",
    "def check(column1 = list(data.select_dtypes('number').columns[1:]),\n",
    "          column2 = list(data.select_dtypes('number').columns[2:])):\n",
    "    print(\"Covariance :\", data[column1].cov(data[column2]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0b60550c021547f7ab1ad07e18c43acd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column1', options=('DailyRate', 'DistanceFromHome', 'Education', '…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact\n",
    "def check(column1 = list(data.select_dtypes('number').columns[1:])):\n",
    "    print(\"Maximum Value :\", data[column1].max())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1bafc92a171f449d88c676e807df8476",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column1', options=('DailyRate', 'DistanceFromHome', 'Education', '…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact\n",
    "def check(column1 = list(data.select_dtypes('number').columns[1:])):\n",
    "    print(\"Minimum Value :\", data[column1].min())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "267584760694429fa5e89712c8e7e627",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column1', options=('DailyRate', 'DistanceFromHome', 'Education', '…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact\n",
    "def check(column1 = list(data.select_dtypes('number').columns[1:])):\n",
    "    print(\"Average Value :\", data[column1].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bac3a6779090423382bada7c1148e272",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column1', options=('DailyRate', 'DistanceFromHome', 'Education', '…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact\n",
    "def check(column1 = list(data.select_dtypes('number').columns[1:])):\n",
    "    print(\"Standard Devaiation :\", data[column1].std())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ae83d61cbf6b480ca80a8ae53cb942b2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column1', options=('DailyRate', 'DistanceFromHome', 'Education', '…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact\n",
    "def check(column1 = list(data.select_dtypes('number').columns[1:])):\n",
    "    print(\"Maximum Value :\", data[column1].max())\n",
    "    print(\"Minimum Value :\", data[column1].min())\n",
    "    print(\"Average Value :\", data[column1].mean())\n",
    "    print(\"Standard Deviation :\", data[column1].std())\n",
    "    print(\"Variance :\", data[column1].var())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c7ff44f05328489c9607025d098e2df6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column1', options=('MonthlyRate',), value='MonthlyRate'), IntSlide…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact\n",
    "def check(column1 = ['MonthlyRate'],\n",
    "          values = 26000):\n",
    "    x = data[data[column1] > values][['EmployeeNumber','MonthlyRate','DailyRate']]\n",
    "    x = x.sort_values(by = 'MonthlyRate', ascending = False)\n",
    "    return x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['bmh',\n",
       " 'classic',\n",
       " 'dark_background',\n",
       " 'fast',\n",
       " 'fivethirtyeight',\n",
       " 'ggplot',\n",
       " 'grayscale',\n",
       " 'seaborn-bright',\n",
       " 'seaborn-colorblind',\n",
       " 'seaborn-dark-palette',\n",
       " 'seaborn-dark',\n",
       " 'seaborn-darkgrid',\n",
       " 'seaborn-deep',\n",
       " 'seaborn-muted',\n",
       " 'seaborn-notebook',\n",
       " 'seaborn-paper',\n",
       " 'seaborn-pastel',\n",
       " 'seaborn-poster',\n",
       " 'seaborn-talk',\n",
       " 'seaborn-ticks',\n",
       " 'seaborn-white',\n",
       " 'seaborn-whitegrid',\n",
       " 'seaborn',\n",
       " 'Solarize_Light2',\n",
       " 'tableau-colorblind10',\n",
       " '_classic_test']"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.style.available"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams['figure.figsize'] = (15, 5)\n",
    "plt.style.use('fivethirtyeight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3ac9d3f2fbb24b82830000946869f651",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column1', options=('DailyRate', 'DistanceFromHome', 'Education', '…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact_manual\n",
    "def check(column1 = list(data.select_dtypes('number').columns[1:]),\n",
    "          column2 = list(data.select_dtypes('number').columns[2:])):\n",
    "    sns.scatterplot(data[column1], data[column2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9bb58d7d73c84882a2f77c47e207da2d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column1', options=('BusinessTravel', 'Department', 'EducationField…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact_manual\n",
    "def check(column1 = list(data.select_dtypes('object').columns[1:]),\n",
    "          column2 = list(data.select_dtypes('number').columns[2:])):\n",
    "    sns.barplot(data[column1], data[column2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c4b4880ed716440286c8e52a3fd64a33",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column1', options=('BusinessTravel', 'Department', 'EducationField…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact_manual\n",
    "def check(column1 = list(data.select_dtypes('object').columns[1:]),\n",
    "          column2 = list(data.select_dtypes('number').columns[2:])):\n",
    "    sns.violinplot(data[column1], data[column2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "34ec44061ccc475da50aeec17f65d9f6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column1', options=('BusinessTravel', 'Department', 'EducationField…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact_manual\n",
    "def check(column1 = list(data.select_dtypes('object').columns[1:]),\n",
    "          column2 = list(data.select_dtypes('number').columns[2:])):\n",
    "    sns.boxplot(data[column1], data[column2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b937ade1779a4c28b386a0ab23ce02ac",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column1', options=('BusinessTravel', 'Department', 'EducationField…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact_manual\n",
    "def check(column1 = list(data.select_dtypes('object').columns[1:]),\n",
    "          column2 = list(data.select_dtypes('number').columns[2:])):\n",
    "    sns.boxenplot(data[column1], data[column2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4866583f5c6c4599b686842acf9cc1b7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column1', options=('BusinessTravel', 'Department', 'EducationField…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact_manual\n",
    "def check(column1 = list(data.select_dtypes('object').columns[1:]),\n",
    "          column2 = list(data.select_dtypes('object').columns[2:])):\n",
    "    x = pd.crosstab(data[column1], data[column2])\n",
    "    x.plot(kind = 'bar', stacked = False)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ca23363737b44e4692efaa3bcda3313d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column1', options=('DailyRate', 'DistanceFromHome', 'Education', '…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact_manual\n",
    "def check(column1 = list(data.select_dtypes('number').columns[1:]),\n",
    "          column2 = list(data.select_dtypes('number').columns[2:]),\n",
    "          color = list(data.select_dtypes('object').columns[3:])):\n",
    "    sns.scatterplot(data[column1], data[column2], hue = data[color])\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "71139a4f8d074d01abd47234841508b5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column1', options=('DailyRate', 'DistanceFromHome', 'Education', '…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact_manual\n",
    "def check(column1 = list(data.select_dtypes('number').columns[1:]),\n",
    "          column2 = list(data.select_dtypes('number').columns[2:]),\n",
    "          color = list(data.select_dtypes('object').columns[3:]),\n",
    "          size = list(data.select_dtypes('number').columns[4:])):\n",
    "    sns.scatterplot(data[column1],\n",
    "                    data[column2],\n",
    "                    hue = data[color],\n",
    "                    size = data[size])\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Aggregations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Age', 'Attrition', 'BusinessTravel', 'DailyRate', 'Department',\n",
       "       'DistanceFromHome', 'Education', 'EducationField', 'EmployeeCount',\n",
       "       'EmployeeNumber', 'EnvironmentSatisfaction', 'Gender', 'HourlyRate',\n",
       "       'JobInvolvement', 'JobLevel', 'JobRole', 'JobSatisfaction',\n",
       "       'MaritalStatus', 'MonthlyIncome', 'MonthlyRate', 'NumCompaniesWorked',\n",
       "       'Over18', 'OverTime', 'PercentSalaryHike', 'PerformanceRating',\n",
       "       'RelationshipSatisfaction', 'StandardHours', 'StockOptionLevel',\n",
       "       'TotalWorkingYears', 'TrainingTimesLastYear', 'WorkLifeBalance',\n",
       "       'YearsAtCompany', 'YearsInCurrentRole', 'YearsSinceLastPromotion',\n",
       "       'YearsWithCurrManager'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ID OF EMPLYEE FROM EACH DEPT. HAVING LEAST SALARY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>EmployeeNumber</th>\n",
       "      <th>MonthlyRate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Department</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Human Resources</th>\n",
       "      <td>103</td>\n",
       "      <td>2097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Research &amp; Development</th>\n",
       "      <td>2</td>\n",
       "      <td>2094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sales</th>\n",
       "      <td>1</td>\n",
       "      <td>2137</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        EmployeeNumber  MonthlyRate\n",
       "Department                                         \n",
       "Human Resources                    103         2097\n",
       "Research & Development               2         2094\n",
       "Sales                                1         2137"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[['EmployeeNumber',\n",
    "      'Department',\n",
    "      'MonthlyRate']].groupby(['Department']).agg('min')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ALL OF THE EMPLOYEE WHO OFTEN DO BUSINESS TRAVEL AND BELONG TO Sales DEPT WITH MONTHLY SALARY MORE THAN 5000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Travel_Rarely        1043\n",
       "Travel_Frequently     277\n",
       "Non-Travel            150\n",
       "Name: BusinessTravel, dtype: int64"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['BusinessTravel'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Research & Development    961\n",
       "Sales                     446\n",
       "Human Resources            63\n",
       "Name: Department, dtype: int64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Department'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "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>EmployeeNumber</th>\n",
       "      <th>Department</th>\n",
       "      <th>MonthlyRate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1438</th>\n",
       "      <td>2023</td>\n",
       "      <td>Sales</td>\n",
       "      <td>26956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1319</th>\n",
       "      <td>1853</td>\n",
       "      <td>Sales</td>\n",
       "      <td>26075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>347</th>\n",
       "      <td>467</td>\n",
       "      <td>Sales</td>\n",
       "      <td>25751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>866</th>\n",
       "      <td>1212</td>\n",
       "      <td>Sales</td>\n",
       "      <td>25440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>91</td>\n",
       "      <td>Sales</td>\n",
       "      <td>24668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1223</th>\n",
       "      <td>1716</td>\n",
       "      <td>Sales</td>\n",
       "      <td>24164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576</th>\n",
       "      <td>800</td>\n",
       "      <td>Sales</td>\n",
       "      <td>24008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>533</th>\n",
       "      <td>729</td>\n",
       "      <td>Sales</td>\n",
       "      <td>23772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>548</th>\n",
       "      <td>754</td>\n",
       "      <td>Sales</td>\n",
       "      <td>23683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>760</th>\n",
       "      <td>1050</td>\n",
       "      <td>Sales</td>\n",
       "      <td>23537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528</th>\n",
       "      <td>723</td>\n",
       "      <td>Sales</td>\n",
       "      <td>23452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>981</th>\n",
       "      <td>1380</td>\n",
       "      <td>Sales</td>\n",
       "      <td>23288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>299</td>\n",
       "      <td>Sales</td>\n",
       "      <td>22967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>154</td>\n",
       "      <td>Sales</td>\n",
       "      <td>22952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>195</td>\n",
       "      <td>Sales</td>\n",
       "      <td>22812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>818</th>\n",
       "      <td>1135</td>\n",
       "      <td>Sales</td>\n",
       "      <td>21981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1144</th>\n",
       "      <td>1613</td>\n",
       "      <td>Sales</td>\n",
       "      <td>21602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>648</th>\n",
       "      <td>900</td>\n",
       "      <td>Sales</td>\n",
       "      <td>21222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1395</th>\n",
       "      <td>1967</td>\n",
       "      <td>Sales</td>\n",
       "      <td>21075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>235</td>\n",
       "      <td>Sales</td>\n",
       "      <td>20989</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      EmployeeNumber Department  MonthlyRate\n",
       "1438            2023      Sales        26956\n",
       "1319            1853      Sales        26075\n",
       "347              467      Sales        25751\n",
       "866             1212      Sales        25440\n",
       "70                91      Sales        24668\n",
       "1223            1716      Sales        24164\n",
       "576              800      Sales        24008\n",
       "533              729      Sales        23772\n",
       "548              754      Sales        23683\n",
       "760             1050      Sales        23537\n",
       "528              723      Sales        23452\n",
       "981             1380      Sales        23288\n",
       "216              299      Sales        22967\n",
       "117              154      Sales        22952\n",
       "144              195      Sales        22812\n",
       "818             1135      Sales        21981\n",
       "1144            1613      Sales        21602\n",
       "648              900      Sales        21222\n",
       "1395            1967      Sales        21075\n",
       "171              235      Sales        20989"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = data[(data['BusinessTravel'] == 'Travel_Frequently') & \n",
    "    (data['Department'] == 'Sales') &\n",
    "    (data['MonthlyRate'] > 5000)][['EmployeeNumber',\n",
    "                                  'Department',\n",
    "                                  'MonthlyRate']].sort_values(by = 'MonthlyRate',\n",
    "                                                              ascending = False)\n",
    "x.head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ALL THE EMPLOYEE WHO HAVE 10 YRS OF EXPERIENCE BUT STILL GET LESS THAN AVERAGE SALARY IN THE ORGANIZATION"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "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>EmployeeNumber</th>\n",
       "      <th>MonthlyRate</th>\n",
       "      <th>Department</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1452</th>\n",
       "      <td>2044</td>\n",
       "      <td>14255</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1277</th>\n",
       "      <td>1789</td>\n",
       "      <td>14218</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>119</td>\n",
       "      <td>14115</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1333</th>\n",
       "      <td>1869</td>\n",
       "      <td>14011</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>184</td>\n",
       "      <td>13982</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>988</th>\n",
       "      <td>1392</td>\n",
       "      <td>13953</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>728</th>\n",
       "      <td>1013</td>\n",
       "      <td>13943</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>241</td>\n",
       "      <td>13939</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>701</th>\n",
       "      <td>981</td>\n",
       "      <td>13938</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511</th>\n",
       "      <td>699</td>\n",
       "      <td>13934</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>978</th>\n",
       "      <td>1375</td>\n",
       "      <td>13888</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>148</td>\n",
       "      <td>13871</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>699</th>\n",
       "      <td>976</td>\n",
       "      <td>13829</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>837</th>\n",
       "      <td>1166</td>\n",
       "      <td>13782</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>1243</td>\n",
       "      <td>13755</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1377</th>\n",
       "      <td>1941</td>\n",
       "      <td>13738</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1103</th>\n",
       "      <td>1557</td>\n",
       "      <td>13693</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1210</th>\n",
       "      <td>1698</td>\n",
       "      <td>13637</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1344</th>\n",
       "      <td>1885</td>\n",
       "      <td>13588</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1331</th>\n",
       "      <td>1867</td>\n",
       "      <td>13583</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      EmployeeNumber  MonthlyRate              Department\n",
       "1452            2044        14255                   Sales\n",
       "1277            1789        14218  Research & Development\n",
       "90               119        14115  Research & Development\n",
       "1333            1869        14011                   Sales\n",
       "139              184        13982         Human Resources\n",
       "988             1392        13953  Research & Development\n",
       "728             1013        13943  Research & Development\n",
       "175              241        13939  Research & Development\n",
       "701              981        13938                   Sales\n",
       "511              699        13934  Research & Development\n",
       "978             1375        13888  Research & Development\n",
       "112              148        13871         Human Resources\n",
       "699              976        13829  Research & Development\n",
       "837             1166        13782  Research & Development\n",
       "888             1243        13755                   Sales\n",
       "1377            1941        13738  Research & Development\n",
       "1103            1557        13693                   Sales\n",
       "1210            1698        13637  Research & Development\n",
       "1344            1885        13588  Research & Development\n",
       "1331            1867        13583  Research & Development"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# find the avg salary\n",
    "avg_sal = data['MonthlyRate'].mean()\n",
    "\n",
    "data[(data['TotalWorkingYears'] > 10) &\n",
    "    (data['MonthlyRate'] < avg_sal)][['EmployeeNumber',\n",
    "                                      'MonthlyRate',\n",
    "                                     'Department']].sort_values(by = 'MonthlyRate',\n",
    "                                                                ascending = False).head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ALL THE EMPLOYEES WHO ARE WORKING IN THE SAME DEPT FOR MORE THAN 5 YEARS AND STILL GET LESS PAY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>EmployeeNumber</th>\n",
       "      <th>MonthlyRate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>36</td>\n",
       "      <td>2094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>459</th>\n",
       "      <td>616</td>\n",
       "      <td>2112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473</th>\n",
       "      <td>638</td>\n",
       "      <td>2125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1370</th>\n",
       "      <td>1934</td>\n",
       "      <td>2125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>244</td>\n",
       "      <td>2137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>968</th>\n",
       "      <td>1362</td>\n",
       "      <td>2261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>927</th>\n",
       "      <td>1294</td>\n",
       "      <td>2323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>789</th>\n",
       "      <td>1098</td>\n",
       "      <td>2326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>881</th>\n",
       "      <td>1235</td>\n",
       "      <td>2338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>81</td>\n",
       "      <td>2354</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      EmployeeNumber  MonthlyRate\n",
       "28                36         2094\n",
       "459              616         2112\n",
       "473              638         2125\n",
       "1370            1934         2125\n",
       "178              244         2137\n",
       "968             1362         2261\n",
       "927             1294         2323\n",
       "789             1098         2326\n",
       "881             1235         2338\n",
       "63                81         2354"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[(data['YearsInCurrentRole'] > 5)][['EmployeeNumber',\n",
    "                                        'MonthlyRate']].sort_values(by = 'MonthlyRate').head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Age                         0\n",
       "Attrition                   0\n",
       "BusinessTravel              0\n",
       "DailyRate                   0\n",
       "Department                  0\n",
       "DistanceFromHome            0\n",
       "Education                   0\n",
       "EducationField              0\n",
       "EmployeeCount               0\n",
       "EmployeeNumber              0\n",
       "EnvironmentSatisfaction     0\n",
       "Gender                      0\n",
       "HourlyRate                  0\n",
       "JobInvolvement              0\n",
       "JobLevel                    0\n",
       "JobRole                     0\n",
       "JobSatisfaction             0\n",
       "MaritalStatus               0\n",
       "MonthlyIncome               0\n",
       "MonthlyRate                 0\n",
       "NumCompaniesWorked          0\n",
       "Over18                      0\n",
       "OverTime                    0\n",
       "PercentSalaryHike           0\n",
       "PerformanceRating           0\n",
       "RelationshipSatisfaction    0\n",
       "StandardHours               0\n",
       "StockOptionLevel            0\n",
       "TotalWorkingYears           0\n",
       "TrainingTimesLastYear       0\n",
       "WorkLifeBalance             0\n",
       "YearsAtCompany              0\n",
       "YearsInCurrentRole          0\n",
       "YearsSinceLastPromotion     0\n",
       "YearsWithCurrManager        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# lets check the missing values\n",
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Attrition', 'BusinessTravel', 'Department', 'EducationField', 'Gender',\n",
       "       'JobRole', 'MaritalStatus', 'Over18', 'OverTime'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# lets check the column which are categorical in nature or are strings\n",
    "data.select_dtypes('object').columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0da850a975c1490a917d1b6e9d033c5e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='column', options=('Attrition', 'BusinessTravel', 'Department', 'Ed…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "@interact\n",
    "def check(column = list(data.select_dtypes('object').columns)):\n",
    "    return data[column].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Label Encoding\n",
    "\n",
    "\n",
    "data['BusinessTravel'].replace(('Travel_Rarely',\n",
    "                                'Travel_Frequently',\n",
    "                                'Non-Travel'),\n",
    "                               (0, 1, 2), inplace = True)\n",
    "data['Department'].replace(('Research & Development',\n",
    "                            'Sales',\n",
    "                            'Human Resources'),\n",
    "                           (0, 1, 2), inplace = True)\n",
    "data['EducationField'].replace(('Life Sciences',\n",
    "                                'Medical',\n",
    "                                'Marketing',\n",
    "                                'Technical Degree',\n",
    "                                'Other',\n",
    "                                'Human Resources'),\n",
    "                               (0, 1, 2, 3, 4 ,5), inplace = True)\n",
    "data['Gender'].replace(('Male',\n",
    "                        'Female'),\n",
    "                       (0, 1), inplace = True)\n",
    "data['JobRole'].replace(('Sales Executive',\n",
    "                         'Research Scientist',\n",
    "                         'Laboratory Technician',\n",
    "                        'Manufacturing Director',\n",
    "                         'Healthcare Representative',\n",
    "                         'Manager',\n",
    "                         'Sales Representative',\n",
    "                        'Research Director',\n",
    "                         'Human Resources'),\n",
    "                        (0, 1, 2, 3, 4, 5, 6, 7, 8), inplace = True)\n",
    "data['MaritalStatus'].replace(('Married',\n",
    "                               'Single',\n",
    "                               'Divorced'),\n",
    "                              (0, 1, 2), inplace = True)\n",
    "data['OverTime'].replace(('No',\n",
    "                          'Yes'),\n",
    "                         (0, 1), inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1465</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1466</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1467</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1468</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1469</th>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1470 rows × 0 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: []\n",
       "Index: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...]\n",
       "\n",
       "[1470 rows x 0 columns]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# lets drop some useless columns\n",
    "data = data.drop(['EmployeeNumber','Over18'], axis = 1)\n",
    "\n",
    "# lets check the number of column still having string values\n",
    "data.select_dtypes('object')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Attrition</th>\n",
       "      <th>BusinessTravel</th>\n",
       "      <th>DailyRate</th>\n",
       "      <th>Department</th>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <th>Education</th>\n",
       "      <th>EducationField</th>\n",
       "      <th>EmployeeCount</th>\n",
       "      <th>EnvironmentSatisfaction</th>\n",
       "      <th>Gender</th>\n",
       "      <th>HourlyRate</th>\n",
       "      <th>JobInvolvement</th>\n",
       "      <th>JobLevel</th>\n",
       "      <th>JobRole</th>\n",
       "      <th>JobSatisfaction</th>\n",
       "      <th>MaritalStatus</th>\n",
       "      <th>MonthlyIncome</th>\n",
       "      <th>MonthlyRate</th>\n",
       "      <th>NumCompaniesWorked</th>\n",
       "      <th>OverTime</th>\n",
       "      <th>PercentSalaryHike</th>\n",
       "      <th>PerformanceRating</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <th>StandardHours</th>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1102</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>94</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>5993</td>\n",
       "      <td>19479</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>49</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>279</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>61</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5130</td>\n",
       "      <td>24907</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1373</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>92</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2090</td>\n",
       "      <td>2396</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1392</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>56</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2909</td>\n",
       "      <td>23159</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>591</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3468</td>\n",
       "      <td>16632</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Age  Attrition  BusinessTravel  DailyRate  Department  DistanceFromHome  \\\n",
       "0   41          1               0       1102           1                 1   \n",
       "1   49          0               1        279           0                 8   \n",
       "2   37          1               0       1373           0                 2   \n",
       "3   33          0               1       1392           0                 3   \n",
       "4   27          0               0        591           0                 2   \n",
       "\n",
       "   Education  EducationField  EmployeeCount  EnvironmentSatisfaction  Gender  \\\n",
       "0          2               0              1                        2       1   \n",
       "1          1               0              1                        3       0   \n",
       "2          2               4              1                        4       0   \n",
       "3          4               0              1                        4       1   \n",
       "4          1               1              1                        1       0   \n",
       "\n",
       "   HourlyRate  JobInvolvement  JobLevel  JobRole  JobSatisfaction  \\\n",
       "0          94               3         2        0                4   \n",
       "1          61               2         2        1                2   \n",
       "2          92               2         1        2                3   \n",
       "3          56               3         1        1                3   \n",
       "4          40               3         1        2                2   \n",
       "\n",
       "   MaritalStatus  MonthlyIncome  MonthlyRate  NumCompaniesWorked  OverTime  \\\n",
       "0              1           5993        19479                   8         1   \n",
       "1              0           5130        24907                   1         0   \n",
       "2              1           2090         2396                   6         1   \n",
       "3              0           2909        23159                   1         1   \n",
       "4              0           3468        16632                   9         0   \n",
       "\n",
       "   PercentSalaryHike  PerformanceRating  RelationshipSatisfaction  \\\n",
       "0                 11                  3                         1   \n",
       "1                 23                  4                         4   \n",
       "2                 15                  3                         2   \n",
       "3                 11                  3                         3   \n",
       "4                 12                  3                         4   \n",
       "\n",
       "   StandardHours  StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  \\\n",
       "0             80                 0                  8                      0   \n",
       "1             80                 1                 10                      3   \n",
       "2             80                 0                  7                      3   \n",
       "3             80                 0                  8                      3   \n",
       "4             80                 1                  6                      3   \n",
       "\n",
       "   WorkLifeBalance  YearsAtCompany  YearsInCurrentRole  \\\n",
       "0                1               6                   4   \n",
       "1                3              10                   7   \n",
       "2                3               0                   0   \n",
       "3                3               8                   7   \n",
       "4                3               2                   2   \n",
       "\n",
       "   YearsSinceLastPromotion  YearsWithCurrManager  \n",
       "0                        0                     5  \n",
       "1                        1                     7  \n",
       "2                        0                     0  \n",
       "3                        3                     0  \n",
       "4                        2                     2  "
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# lets check the head of teh data\n",
    "pd.set_option('max_columns', 100)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of x : (1470, 32)\n",
      "Shape of y : (1470,)\n"
     ]
    }
   ],
   "source": [
    "# splittig the target variables\n",
    "y = data['Attrition']\n",
    "x = data.drop(['Attrition'], axis = 1)\n",
    "\n",
    "# lets check teh shape of the new var\n",
    "print(\"Shape of x :\", x.shape)\n",
    "print(\"Shape of y :\", y.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of x_train : (1176, 32)\n",
      "Shape of y_train  : (1176,)\n",
      "Shape of x_test : (294, 32)\n",
      "Shape of y_test : (294,)\n"
     ]
    }
   ],
   "source": [
    "# train test split\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "x_train, x_test, y_train, y_test  = train_test_split(x, y, test_size = 0.2, random_state = 0)\n",
    "\n",
    "# lets check the shape\n",
    "print(\"Shape of x_train :\", x_train.shape)\n",
    "print(\"Shape of y_train  :\", y_train.shape)\n",
    "print(\"Shape of x_test :\", x_test.shape)\n",
    "print(\"Shape of y_test :\", y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "# standardization\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "sc = StandardScaler()\n",
    "x_train = sc.fit_transform(x_train)\n",
    "x_test = sc.transform(x_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Modelling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### RANDOM FOREST CLASSIFIER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Accuracy : 1.0\n",
      "Testing Accuracy : 0.8537414965986394\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import classification_report\n",
    "\n",
    "model = RandomForestClassifier()\n",
    "model.fit(x_train, y_train)\n",
    "y_pred = model.predict(x_test)\n",
    "\n",
    "# accuracy\n",
    "print(\"Training Accuracy :\", model.score(x_train, y_train))\n",
    "print(\"Testing Accuracy :\", model.score(x_test, y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# lets print the confusion matrix\n",
    "\n",
    "cm = confusion_matrix(y_test, y_pred)\n",
    "plt.rcParams['figure.figsize'] = (6, 6)\n",
    "sns.heatmap(cm, \n",
    "            cmap = 'copper',\n",
    "            annot = True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.85      1.00      0.92       245\n",
      "           1       0.88      0.14      0.25        49\n",
      "\n",
      "    accuracy                           0.85       294\n",
      "   macro avg       0.86      0.57      0.58       294\n",
      "weighted avg       0.86      0.85      0.81       294\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# classification report\n",
    "\n",
    "cr = classification_report(y_test, y_pred)\n",
    "print(cr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### LOGISTIC REGRESSION"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Accuracy : 0.8877551020408163\n",
      "Testing Accuracy : 0.8605442176870748\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import classification_report\n",
    "\n",
    "model = LogisticRegression()\n",
    "model.fit(x_train, y_train)\n",
    "y_pred = model.predict(x_test)\n",
    "\n",
    "# accuracy\n",
    "print(\"Training Accuracy :\", model.score(x_train, y_train))\n",
    "print(\"Testing Accuracy :\", model.score(x_test, y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# lets print the confusion matrix\n",
    "\n",
    "cm = confusion_matrix(y_test, y_pred)\n",
    "plt.rcParams['figure.figsize'] = (6, 6)\n",
    "sns.heatmap(cm, \n",
    "            cmap = 'copper',\n",
    "            annot = True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.88      0.96      0.92       245\n",
      "           1       0.65      0.35      0.45        49\n",
      "\n",
      "    accuracy                           0.86       294\n",
      "   macro avg       0.77      0.66      0.69       294\n",
      "weighted avg       0.84      0.86      0.84       294\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# classification report\n",
    "\n",
    "cr = classification_report(y_test, y_pred)\n",
    "print(cr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DECISION TREE CLASSIFIER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Accuracy : 1.0\n",
      "Testing Accuracy : 0.7414965986394558\n"
     ]
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import classification_report\n",
    "\n",
    "model = DecisionTreeClassifier()\n",
    "model.fit(x_train, y_train)\n",
    "y_pred = model.predict(x_test)\n",
    "\n",
    "# accuracy\n",
    "print(\"Training Accuracy :\", model.score(x_train, y_train))\n",
    "print(\"Testing Accuracy :\", model.score(x_test, y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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+iyTZgwKquTLqiuJTp1R86pRb25nTpSoqLNTXGedvBX/5+TW689cP6MjXh3TsyNe6a/ZvdPp0qd57a5MvpnxFqKyVN9P+fJd0O+7o0aM1evRolZeXq6CgQJIUEhKiBg0aGJ2cr2382yFJ0h3L3Df+7x35C/16VJQk6URRmb7JK3GdC2zcUC/MG6RH//wPjfnvbWreuKGm3tRVU27697LTgKg2WnP/9Xrmnf164X+/lK2enzq2bqbR1/3XT57r8nv6afHLn2nqH87PdXCPq7RoUm/X+a2fHlfBqbPaknpcW1KPu703Y92Enzwu6o4XVj0t/0aN9NDiZWrWPEhf7P1Md08co9OlJRd/M34Sq1YcfoWFhcY/WvODT5keAlegqHF/9PUUYEEf76v+i7aeKls/2yvXaTTpaa9cx1t45AgAGHLF3lUFAPhpLJobPKsKAOAZggMADHF66b8L2blzpxISEhQREaGgoCBt2LDB7fyMGTMUFBTkdgwdOtStz9mzZzVv3jx16tRJbdu2VUJCgrKzsy/6uQgOADCk0umd40JKS0vVrVs3LV26VAEBF76lPjY2VhkZGa7jjTfecDufmJiozZs36/nnn9eWLVtUXFys8ePHu752UR32OADAEJOb43FxcYqLi5MkzZw584J9/P39q32yR1FRkdavX6+VK1dq0KDzTwJfs2aNoqKitH37dg0ZMqTasak4AMCidu/erbCwMPXq1UuzZ8/Wif94vMzevXtVXl6uwYMHu9ratWunLl26KDU1tcbrUnEAgCG+vKtq6NChGj58uEJDQ3X8+HEtXrxY8fHx2r59u/z9/ZWXlyebzaaQEPenfdvtduXl5VVz1fMIDgAwxJff4xgzZozr78jISEVHRysqKkrbtm1TfHx8te/7z4elVoelKgAwpNJLhze0adNGbdu2VWbm+W/Gt2rVShUVFa7HSP1Lfn6+7HZ7jdciOADgClBQUKCcnBzXZnl0dLQaNGjg9iN82dnZysjIUExMTI3XYqkKAAwxuVRVUlLiqh4qKyuVlZWl9PR0BQcHKzg4WEuXLlV8fLwcDoeOHz+uRx99VHa7XbfeeqskqXnz5po0aZIWLVoku92u4OBgPfTQQ4qMjFRsbGyNYxMcAGCIyS2OtLQ0DR8+3PU6KSlJSUlJmjBhgp588kkdOHBAr776qoqKiuRwODRgwAC9+OKLCgz892/6LFmyRDabTVOmTFFZWZkGDhyo1atXy2az1Tg2T8dFncXTcWGCN5+Oe+LZe7xyHftdq71yHW9hjwMA4BGWqgDAkOoeF1LXERwAYEh1Dyis61iqAgB4hIoDAAyx6g85ERwAYAg/HQsA8IhVN8fZ4wAAeISKAwAMsepdVQQHABhi0S0OggMATLHq5jh7HAAAj1BxAIAhFi04CA4AMKXSosnBUhUAwCNUHABgiDXrDYIDAIyx6l1VBAcAGGLR3GCPAwDgGSoOADDEqndVERwAYIg1Y4PgAABjrLo5zh4HAMAjVBwAYIhFCw6CAwBMYXMcAOARi+YGexwAAM9QcQCAIfx0LADAIyxVAQAgKg4AMIa7qgAAHrFobhAcAGCKVTfH2eMAAHiEigMADLHqUhUVBwAY4nQ6vXJcyM6dO5WQkKCIiAgFBQVpw4YNrnPl5eV6+OGH1b9/f7Vt21ZdunTR9OnT9c0337hdY9iwYQoKCnI7pk6detHPRXAAgCGVTu8cF1JaWqpu3bpp6dKlCggIcDt3+vRp/fOf/9TcuXO1Y8cObdy4UdnZ2Ro7dqzOnTvn1nfixInKyMhwHU899dRFPxdLVQBQB8XFxSkuLk6SNHPmTLdzzZs311tvveXW9tRTT6lv377KyMhQZGSkq71x48ZyOBwejU3FAQCGmFyq8lRxcbEkKSgoyK1906ZN6tSpk/r27auFCxe6+tWEigMADKkte+M//PCDFi5cqJtuuklXXXWVq33cuHFq3769WrdurS+//FKPPPKI9u3bV6Va+TGCAwAs7Ny5c7rrrrtUVFSkV155xe3cHXfc4fo7MjJSHTt21JAhQ7R3715FR0dXe02WqgDAEF8vVZ07d07Tpk3T/v379fbbb6tFixY19u/Ro4dsNpsyMzNr7EfFAQCGVHdH1OVQXl6uqVOn6uDBg3r33XcvaQN8//79qqiouGhfggMADPHWxvaFlJSUuCqDyspKZWVlKT09XcHBwWrTpo0mT56stLQ0vfLKK/Lz81Nubq4kqVmzZgoICNCRI0f0+uuvKy4uTi1atFBGRoYWLlyo7t27q2/fvjWOTXAAQB2Ulpam4cOHu14nJSUpKSlJEyZM0IIFC7RlyxZJUmxsrNv7Vq5cqYkTJ6pBgwbasWOHVq9erdLSUl111VWKi4vTggULZLPZahyb4AAAQ0w+cmTAgAEqLCys9nxN5ySpXbt2rnDxFMEBAIZY9em4BAcAGOLLzXGTuB0XAOARKg4AMMTkXVW+RHAAgCEWzQ2CAwBMsermOHscAACPUHEAgCFWvauK4AAAQ6y6Oc5SFQDAI1QcAGCIRQsOggMATLHqUhXBAQCGWDM22OMAAHiIigMADKlkqQoA4AmL5gbBAQCmWHVznD0OAIBHqDgAwBBr1hsEBwAYw+Y4AMAjFs2NyxMcnUf+z+UYBleYQ7lFvp4CcEWi4gAAQ6x6VxXBAQCGWDQ3uB0XAOAZKg4AMKTSojfkEhwAYIhVl6oIDgAwxKqb4+xxAAA8QsUBAIZYtOAgOADAFDbHAQAesWrFwR4HAMAjVBwAYAh3VQEAPOJ0eue4kJ07dyohIUEREREKCgrShg0bfjS2U0lJSeratatat26tYcOG6eDBg259zp49q3nz5qlTp05q27atEhISlJ2dfdHPRXAAQB1UWlqqbt26aenSpQoICKhyfsWKFVq5cqWWLVumDz/8UHa7XaNGjVJxcbGrT2JiojZv3qznn39eW7ZsUXFxscaPH6+KiooaxyY4AMAQp9PpleNC4uLitGjRIo0YMUL16tWrMu6qVat03333acSIEerWrZtWrVqlkpISvfnmm5KkoqIirV+/Xo8++qgGDRqk6OhorVmzRvv379f27dtr/FwEBwAYUumlw1PHjh1Tbm6uBg8e7GoLCAhQ//79lZqaKknau3evysvL3fq0a9dOXbp0cfWpDpvjAGCIrzbHc3NzJUl2u92t3W63KycnR5KUl5cnm82mkJCQKn3y8vJqvD4VBwBYlJ+fn9trp9NZpe3HLqUPwQEAhpi8q6omDodDkqpUDvn5+a4qpFWrVqqoqFBBQUG1fapDcACAISY3x2sSGhoqh8OhlJQUV1tZWZl2796tmJgYSVJ0dLQaNGjg1ic7O1sZGRmuPtVhjwMADKk0uMVRUlKizMzM8+NUViorK0vp6ekKDg5W+/btNWPGDD3xxBMKDw9XWFiYli9friZNmmjs2LGSpObNm2vSpElatGiR7Ha7goOD9dBDDykyMlKxsbE1jk1wAEAdlJaWpuHDh7teJyUlKSkpSRMmTNCqVas0Z84cnTlzRvPmzVNhYaF69eql5ORkBQYGut6zZMkS2Ww2TZkyRWVlZRo4cKBWr14tm81W49h+hYWFxrf9r+0SanoIXIEO5Rb5egqwoMLCQq9da83dN3rlOnev2eaV63gLFQcAGGLRR1URHABgCg85BABAVBwAYIzJu6p8ieAAAEOcFv3pWJaqAAAeoeIAAEMsujdOcACAKVa9q4rgAABDrLo5zh4HAMAjVBwAYAhLVQAAj1gzNggOADDGqhUHexwAAI9QcQCAIRYtOAgOADCl0qLJQXAAgCHWjA32OAAAHqLiAABDrHpXFcEBAIZYNDdYqgIAeIaKAwAM4a4qAIBHLJobBAcAmMJPxwIAICoOADCGpSoAgEfYHAcAeMSiucEeBwDAM1QcAGCIVe+qIjgAwBCWqgAAEBUHABjDXVUAAI9YNDcIDgAwxaq/x8EeBwDUMVFRUQoKCqpy3HbbbZKkGTNmVDk3dOhQr41PxQEAhpiqN1JSUlRRUeF6/d133yk2NlYjR450tcXGxmrNmjWu1w0bNvTa+AQHABhiaqmqZcuWbq/Xr1+vwMBAt+Dw9/eXw+EwMj5LVQBgSKXTO0dNnE6n1q9fr/Hjx6tx48au9t27dyssLEy9evXS7NmzdeLECa99LioOAKjDUlJSdOzYMU2aNMnVNnToUA0fPlyhoaE6fvy4Fi9erPj4eG3fvl3+/v4/e0yCAwAMuRx3Va1bt049e/ZU9+7dXW1jxoxx/R0ZGano6GhFRUVp27Ztio+P/9ljslQFAIY4nd45qnPixAlt2bJFkydPrnEebdq0Udu2bZWZmemVz0XFAQCGmH7I4YYNG+Tv76/Ro0fX2K+goEA5OTle2yyn4gCAOsjpdOrPf/6zRo8ercDAQFd7SUmJFi5cqE8++UTHjh3TRx99pISEBNntdt16661eGZuKAwAMudgdUT/HRx99pMzMTD333HNu7TabTQcOHNCrr76qoqIiORwODRgwQC+++KJbwPwcBAcAGGJyc3zgwIEqLCys0h4QEKDk5GRj40osVQEAPETFAQCGWPQZhwQHAJjCT8cCADxicnPcl9jjAAB4hIoDAAyx6g85ERwAYIhFc4PgAABTrFpxsMcBAPAIFQcAGFLp6wkYQnAAgCFWXaoiOADAEIvmBnscAADPEByX2cQp0/XOhzv1+aHj+vzQcb327vuKHRrn1qdjp6v1p+fX6x8Zx/TPzG/1l/d36Orwzj6aMeqKAQMG6O2331ZWVpacTmeVX4V79NFHdfDgQZWUlOjkyZP64IMP1K9fPx/N9srgdDq9ctQ2BMdl9t2332r54oc18obrNfrGQdrz8d+18sUN6hIRKUlq1yFUr27epqxvjun/jY3XrbH99D/LFqu0tNTHM0dt17RpU+3bt09z5szR6dOnq5zPyMjQrFmzFBUVpeuuu05HjhzR1q1b1apVKx/M9srg9NJR2/gVFhYan9e1XUJND1GnfXLwiJ5Y8oheW/+SnnjmOTmdTs2ddZevp1XrHcot8vUUaq3i4mLde++9WrduXbV9AgMDderUKd144416//33L+PsarcL/cbFTzV1aA+vXOeFD9K8ch1v8UrFkZWVpVmzZnnjUleUevXqadiI0WrcpInSPv1Efn5+GhR3k77+KkNrN76pPfu/1qatH+qWEaN8PVVYTIMGDXTXXXepqKhIe/fu9fV0LKvS6fTKUdt4JTi+//57vfLKK9641BWhc9duSjucpX3H8/TI40/p3qm366svDyikpV1NmwbqnjkPaOeOFE25bZTe/csmLV/5nGJvuNHX04YFDBs2TMXFxSorK9P999+vG264QXl5eb6elmU5nd45aptLuh33YqGQlZXllclcKY4cPqQRQwaoWfPmunFYvJatWKXbx9yqou+/lyT9besWvbhmpSTp4P4v9ItronX7lOna/tdtvpw2LCAlJUXR0dFq2bKl7rzzTr3++uvq16+fvvvuO19PzZJq48a2N1xScMycOVONGzeWn5/fBc9XVlr1+5FmlJeX6/jRI5Kkff/cq6jonrrjrpn67/kPqLy8XF9/leHW//ChrzRs5GhfTBUWc/r0aR0+fFiHDx9WamqqvvrqK02fPl2LFy/29dRQh1xScLRp00ZLly5VfHz8Bc+np6crNjbWm/O6ovjVq6eGDRuqvLxcX+z9XJ2uDnc7/1+dwvRt1jc+mh2srF69evL39/f1NCzLogXHpQXHNddco/T09GqDw8/Pz7IlmbfNfehhbf/gfeV8m60mTZpq+Oixiul/ne66/TZJ0tqVT+t/nn1R/0jdpd0f/119fzlAt4wcrVlTJvp45qjtmjRporCwMEnnA6FDhw665pprdPLkSRUWFurBBx/U5s2blZOTI7vdrlmzZqldu3Z6/fXXfTxz66qslTfT/nyXdDvurl27VFpaqhtuuOGC50tLS5WWlqbrrrvugue5Hffflq54RjG/HCC7vZWKi08p48B+rX3maX28/UNXn1Hjf6V7Zj+gNm2v0tEjmVrz9JN6761NPpx17cTtuO6uv/56bd++vUr7Sy+9pJkzZ2rDhg2KiYlRSEiICgoK9Omnn2rJkiX65JNPLv9ka1VrG3wAAAeiSURBVDFv3o77q+u7e+U6G3eke+U63sL3OFBnERwwgeC4OB5yCACGWHUJn+AAAEMsmhs8qwoA4BkqDgAwxKp3VREcAGCIVZeqCA4AMMSqm+PscQAAPELFAQCGWLTgIDgAwJTa+Fsa3kBwAIAh1owN9jgAoM5JSkpSUFCQ29G5c2fXeafTqaSkJHXt2lWtW7fWsGHDdPDgQa+NT8UBAIaYvKsqPDxc7777ruu1zWZz/b1ixQqtXLlSK1euVHh4uB5//HGNGjVKn376qQIDA3/22FQcAGCIyZ+OrV+/vhwOh+to2bLl/43p1KpVq3TfffdpxIgR6tatm1atWqWSkhK9+eabXvlcBAcAGOJ0Or1yXMjRo0cVERGh7t27a+rUqTp69Kgk6dixY8rNzdXgwYNdfQMCAtS/f3+lpqZ65XOxVAUAdUzv3r31zDPPKDw8XPn5+frDH/6guLg47dmzR7m5uZIku93u9h673a6cnByvjE9wAIAhlYa2OH78o3q9e/dWdHS0Nm7cqGuvvVbS+V9m/U9Op7NK20/FUhUAGOL00n8X07RpU3Xt2lWZmZlyOBySpLy8PLc++fn5VaqQn4rgAIA6rqysTIcOHZLD4VBoaKgcDodSUlLczu/evVsxMTFeGY+lKgAwxNTduAsXLtRNN92kdu3aufY4Tp8+rQkTJsjPz08zZszQE088ofDwcIWFhWn58uVq0qSJxo4d65XxCQ4AMMTU9zi+/fZbTZ8+XQUFBWrZsqV69+6tv/71r+rQoYMkac6cOTpz5ozmzZunwsJC9erVS8nJyV75Dock+RUWFhr/Vvy1XUJND4Er0KHcIl9PARZUWFjotWvF9ex88U6X4P3Pv/LKdbyFPQ4AgEdYqgIAQy7ljqi6iOAAAEMs+lR1ggMATOGnYwEAEBUHABhj6pEjvkZwAIAhVl2qIjgAwBBrxgZ7HAAAD1FxAIAhLFUBADxi1c1xlqoAAB6h4gAAQ1iqAgB4xJqxQXAAgDFWrTjY4wAAeISKAwAMsWjBQXAAgCmVFk0OggMADLFobrDHAQDwDBUHABjCT8cCADzCUhUAAKLiAABjuKsKAOARi+YGwQEAplh1c5w9DgCAR6g4AMAQlqoAAB5hcxwA4BGL5gZ7HAAAz1BxAIAhVv0hJ4IDAAyxZmwQHABgjFU3x9njAAB4hOAAAEOcTu8cP/bkk09q0KBBat++va6++mqNHz9eBw4ccOszY8YMBQUFuR1Dhw71yudiqQoADDG1Of7xxx9r2rRp6tmzp5xOp5YsWaKRI0cqNTVVwcHBrn6xsbFas2aN63XDhg29Mj7BAQB1THJystvrNWvWqEOHDtqzZ49uvvlmV7u/v78cDofXx2epCgAMMbVU9WMlJSWqrKxUUFCQW/vu3bsVFhamXr16afbs2Tpx4oRXPhcVBwAYcrmejrtgwQJFRUWpT58+rrahQ4dq+PDhCg0N1fHjx7V48WLFx8dr+/bt8vf3/1njERwAYEjlZciN3/72t9qzZ4+2bt0qm83mah8zZozr78jISEVHRysqKkrbtm1TfHz8zxqT4ACAOioxMVHJycnavHmzOnbsWGPfNm3aqG3btsrMzPzZ4xIcAGCIyUeOzJ8/X8nJyXr33XfVuXPni/YvKChQTk6OVzbLCQ4AMMRUbsydO1evvfaaXn75ZQUFBSk3N1eS1KRJEzVt2lQlJSVaunSp4uPj5XA4dPz4cT366KOy2+269dZbf/b4BAcAGGJqc3zt2rWSpBEjRri1z58/X4mJibLZbDpw4IBeffVVFRUVyeFwaMCAAXrxxRcVGBj4s8cnOACgjiksLKzxfEBAQJXvengTwQEAhlyOu6p8geAAAEP4PQ4AgEcsmhs8cgQA4BkqDgAwhKUqAIBHKn09AUNYqgIAeISKAwAMYakKAOARi+YGwQEApli14mCPAwDgESoOADDEqndVERwAYIhVl6oIDgAwxKK5Ib/CwkKLfjQAgAlsjgMAPEJwAAA8QnAAADxCcAAAPEJwAAA8QnDUEmvXrlX37t3lcDh0/fXXa9euXb6eEuq4nTt3KiEhQREREQoKCtKGDRt8PSVYBMFRCyQnJ2vBggX6zW9+o7///e/q06ePxo0bp2+++cbXU0MdVlpaqm7dumnp0qUKCAjw9XRgIXyPoxYYMmSIIiMj9fTTT7vaevbsqREjRujhhx/24cxgFVdddZUef/xxTZw40ddTgQVQcfjYDz/8oL1792rw4MFu7YMHD1ZqaqqPZgUA1SM4fKygoEAVFRWy2+1u7Xa7XXl5eT6aFQBUj+CoJfz8/NxeO53OKm0AUBsQHD4WEhIim81WpbrIz8+vUoUAQG1AcPhYw4YNFR0drZSUFLf2lJQUxcTE+GhWAFA9HqteC8yaNUt33323evXqpZiYGL3wwgv67rvvNGXKFF9PDXVYSUmJMjMzJUmVlZXKyspSenq6goOD1b59ex/PDnUZt+PWEmvXrtWKFSuUm5uriIgILVmyRL/85S99PS3UYR999JGGDx9epX3ChAlatWqVD2YEqyA4AAAeYY8DAOARggMA4BGCAwDgEYIDAOARggMA4BGCAwDgEYIDAOARggMA4JH/D1BkqlFVKQBrAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# lets print the confusion matrix\n",
    "\n",
    "cm = confusion_matrix(y_test, y_pred)\n",
    "plt.rcParams['figure.figsize'] = (6, 6)\n",
    "sns.heatmap(cm, \n",
    "            cmap = 'copper',\n",
    "            annot = True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.85      0.84      0.84       245\n",
      "           1       0.25      0.27      0.25        49\n",
      "\n",
      "    accuracy                           0.74       294\n",
      "   macro avg       0.55      0.55      0.55       294\n",
      "weighted avg       0.75      0.74      0.75       294\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# classification report\n",
    "\n",
    "cr = classification_report(y_test, y_pred)\n",
    "print(cr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}