Employee_Attrition.ipynb

{
 "cells": [
  {
   "cell_type": "code",
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   "metadata": {
    "id": "X0kBcmjfwblk"
   },
   "outputs": [],
   "source": [
    "#Import libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 299
    },
    "id": "0hiAEFybxeZ9",
    "outputId": "9587bb05-fad9-47f3-a8be-eb9c4f990ff3"
   },
   "outputs": [
    {
     "data": {
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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>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>...</td>\n",
       "      <td>1</td>\n",
       "      <td>80</td>\n",
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       "    </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>...</td>\n",
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       "      <td>80</td>\n",
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       "    </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",
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       "      <td>...</td>\n",
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       "      <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>...</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>...</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",
       "<p>5 rows × 35 columns</p>\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",
       "   ...  RelationshipSatisfaction StandardHours  StockOptionLevel  \\\n",
       "0  ...                         1            80                 0   \n",
       "1  ...                         4            80                 1   \n",
       "2  ...                         2            80                 0   \n",
       "3  ...                         3            80                 0   \n",
       "4  ...                         4            80                 1   \n",
       "\n",
       "   TotalWorkingYears  TrainingTimesLastYear WorkLifeBalance  YearsAtCompany  \\\n",
       "0                  8                      0               1               6   \n",
       "1                 10                      3               3              10   \n",
       "2                  7                      3               3               0   \n",
       "3                  8                      3               3               8   \n",
       "4                  6                      3               3               2   \n",
       "\n",
       "  YearsInCurrentRole  YearsSinceLastPromotion  YearsWithCurrManager  \n",
       "0                  4                        0                     5  \n",
       "1                  7                        1                     7  \n",
       "2                  0                        0                     0  \n",
       "3                  7                        3                     0  \n",
       "4                  2                        2                     2  \n",
       "\n",
       "[5 rows x 35 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('HR-Employee-Attrition.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "bYvIRySBxwUL",
    "outputId": "6dbc876b-f82f-445b-a48a-8695ce881b00"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1470, 35)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Ya4z7kJJyTur",
    "outputId": "d0d9dab0-2f60-492e-b5aa-60ada7142847"
   },
   "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": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "4W5CJmjnyuwq",
    "outputId": "38c20a59-d0d9-420f-f9e3-05376fdc8f8d"
   },
   "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",
      " #   Column                    Non-Null Count  Dtype \n",
      "---  ------                    --------------  ----- \n",
      " 0   Age                       1470 non-null   int64 \n",
      " 1   Attrition                 1470 non-null   object\n",
      " 2   BusinessTravel            1470 non-null   object\n",
      " 3   DailyRate                 1470 non-null   int64 \n",
      " 4   Department                1470 non-null   object\n",
      " 5   DistanceFromHome          1470 non-null   int64 \n",
      " 6   Education                 1470 non-null   int64 \n",
      " 7   EducationField            1470 non-null   object\n",
      " 8   EmployeeCount             1470 non-null   int64 \n",
      " 9   EmployeeNumber            1470 non-null   int64 \n",
      " 10  EnvironmentSatisfaction   1470 non-null   int64 \n",
      " 11  Gender                    1470 non-null   object\n",
      " 12  HourlyRate                1470 non-null   int64 \n",
      " 13  JobInvolvement            1470 non-null   int64 \n",
      " 14  JobLevel                  1470 non-null   int64 \n",
      " 15  JobRole                   1470 non-null   object\n",
      " 16  JobSatisfaction           1470 non-null   int64 \n",
      " 17  MaritalStatus             1470 non-null   object\n",
      " 18  MonthlyIncome             1470 non-null   int64 \n",
      " 19  MonthlyRate               1470 non-null   int64 \n",
      " 20  NumCompaniesWorked        1470 non-null   int64 \n",
      " 21  Over18                    1470 non-null   object\n",
      " 22  OverTime                  1470 non-null   object\n",
      " 23  PercentSalaryHike         1470 non-null   int64 \n",
      " 24  PerformanceRating         1470 non-null   int64 \n",
      " 25  RelationshipSatisfaction  1470 non-null   int64 \n",
      " 26  StandardHours             1470 non-null   int64 \n",
      " 27  StockOptionLevel          1470 non-null   int64 \n",
      " 28  TotalWorkingYears         1470 non-null   int64 \n",
      " 29  TrainingTimesLastYear     1470 non-null   int64 \n",
      " 30  WorkLifeBalance           1470 non-null   int64 \n",
      " 31  YearsAtCompany            1470 non-null   int64 \n",
      " 32  YearsInCurrentRole        1470 non-null   int64 \n",
      " 33  YearsSinceLastPromotion   1470 non-null   int64 \n",
      " 34  YearsWithCurrManager      1470 non-null   int64 \n",
      "dtypes: int64(26), object(9)\n",
      "memory usage: 402.1+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 304
    },
    "id": "3Y0XQOdQy9TG",
    "outputId": "86b9d2ec-247f-4716-c8d1-352dbbade7e5"
   },
   "outputs": [
    {
     "data": {
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       "  <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>count</th>\n",
       "      <td>1470.000000</td>\n",
       "      <td>1470.000000</td>\n",
       "      <td>1470.000000</td>\n",
       "      <td>1470.000000</td>\n",
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       "      <td>1470.000000</td>\n",
       "      <td>1470.000000</td>\n",
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       "      <td>1470.000000</td>\n",
       "      <td>1470.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>36.923810</td>\n",
       "      <td>802.485714</td>\n",
       "      <td>9.192517</td>\n",
       "      <td>2.912925</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1024.865306</td>\n",
       "      <td>2.721769</td>\n",
       "      <td>65.891156</td>\n",
       "      <td>2.729932</td>\n",
       "      <td>2.063946</td>\n",
       "      <td>...</td>\n",
       "      <td>2.712245</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.793878</td>\n",
       "      <td>11.279592</td>\n",
       "      <td>2.799320</td>\n",
       "      <td>2.761224</td>\n",
       "      <td>7.008163</td>\n",
       "      <td>4.229252</td>\n",
       "      <td>2.187755</td>\n",
       "      <td>4.123129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>9.135373</td>\n",
       "      <td>403.509100</td>\n",
       "      <td>8.106864</td>\n",
       "      <td>1.024165</td>\n",
       "      <td>0.0</td>\n",
       "      <td>602.024335</td>\n",
       "      <td>1.093082</td>\n",
       "      <td>20.329428</td>\n",
       "      <td>0.711561</td>\n",
       "      <td>1.106940</td>\n",
       "      <td>...</td>\n",
       "      <td>1.081209</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.852077</td>\n",
       "      <td>7.780782</td>\n",
       "      <td>1.289271</td>\n",
       "      <td>0.706476</td>\n",
       "      <td>6.126525</td>\n",
       "      <td>3.623137</td>\n",
       "      <td>3.222430</td>\n",
       "      <td>3.568136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>102.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</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>25%</th>\n",
       "      <td>30.000000</td>\n",
       "      <td>465.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>491.250000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
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       "    <tr>\n",
       "      <th>50%</th>\n",
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       "      <td>802.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1020.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>80.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>43.000000</td>\n",
       "      <td>1157.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1555.750000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>83.750000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>80.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>7.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>60.000000</td>\n",
       "      <td>1499.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2068.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>80.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>17.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Age    DailyRate  DistanceFromHome    Education  EmployeeCount  \\\n",
       "count  1470.000000  1470.000000       1470.000000  1470.000000         1470.0   \n",
       "mean     36.923810   802.485714          9.192517     2.912925            1.0   \n",
       "std       9.135373   403.509100          8.106864     1.024165            0.0   \n",
       "min      18.000000   102.000000          1.000000     1.000000            1.0   \n",
       "25%      30.000000   465.000000          2.000000     2.000000            1.0   \n",
       "50%      36.000000   802.000000          7.000000     3.000000            1.0   \n",
       "75%      43.000000  1157.000000         14.000000     4.000000            1.0   \n",
       "max      60.000000  1499.000000         29.000000     5.000000            1.0   \n",
       "\n",
       "       EmployeeNumber  EnvironmentSatisfaction   HourlyRate  JobInvolvement  \\\n",
       "count     1470.000000              1470.000000  1470.000000     1470.000000   \n",
       "mean      1024.865306                 2.721769    65.891156        2.729932   \n",
       "std        602.024335                 1.093082    20.329428        0.711561   \n",
       "min          1.000000                 1.000000    30.000000        1.000000   \n",
       "25%        491.250000                 2.000000    48.000000        2.000000   \n",
       "50%       1020.500000                 3.000000    66.000000        3.000000   \n",
       "75%       1555.750000                 4.000000    83.750000        3.000000   \n",
       "max       2068.000000                 4.000000   100.000000        4.000000   \n",
       "\n",
       "          JobLevel  ...  RelationshipSatisfaction  StandardHours  \\\n",
       "count  1470.000000  ...               1470.000000         1470.0   \n",
       "mean      2.063946  ...                  2.712245           80.0   \n",
       "std       1.106940  ...                  1.081209            0.0   \n",
       "min       1.000000  ...                  1.000000           80.0   \n",
       "25%       1.000000  ...                  2.000000           80.0   \n",
       "50%       2.000000  ...                  3.000000           80.0   \n",
       "75%       3.000000  ...                  4.000000           80.0   \n",
       "max       5.000000  ...                  4.000000           80.0   \n",
       "\n",
       "       StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  \\\n",
       "count       1470.000000        1470.000000            1470.000000   \n",
       "mean           0.793878          11.279592               2.799320   \n",
       "std            0.852077           7.780782               1.289271   \n",
       "min            0.000000           0.000000               0.000000   \n",
       "25%            0.000000           6.000000               2.000000   \n",
       "50%            1.000000          10.000000               3.000000   \n",
       "75%            1.000000          15.000000               3.000000   \n",
       "max            3.000000          40.000000               6.000000   \n",
       "\n",
       "       WorkLifeBalance  YearsAtCompany  YearsInCurrentRole  \\\n",
       "count      1470.000000     1470.000000         1470.000000   \n",
       "mean          2.761224        7.008163            4.229252   \n",
       "std           0.706476        6.126525            3.623137   \n",
       "min           1.000000        0.000000            0.000000   \n",
       "25%           2.000000        3.000000            2.000000   \n",
       "50%           3.000000        5.000000            3.000000   \n",
       "75%           3.000000        9.000000            7.000000   \n",
       "max           4.000000       40.000000           18.000000   \n",
       "\n",
       "       YearsSinceLastPromotion  YearsWithCurrManager  \n",
       "count              1470.000000           1470.000000  \n",
       "mean                  2.187755              4.123129  \n",
       "std                   3.222430              3.568136  \n",
       "min                   0.000000              0.000000  \n",
       "25%                   0.000000              2.000000  \n",
       "50%                   1.000000              3.000000  \n",
       "75%                   3.000000              7.000000  \n",
       "max                  15.000000             17.000000  \n",
       "\n",
       "[8 rows x 26 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "gMvGHrcEzEio",
    "outputId": "2fbab979-6b2f-48ff-e2c0-0b6e75b6321a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No     1233\n",
       "Yes     237\n",
       "Name: Attrition, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Count of number of employees that stayed and left the company\n",
    "df['Attrition'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 350
    },
    "id": "EZnZ1xFKzf-r",
    "outputId": "3d60ff57-f517-4e93-cca0-32c54fdb0cd3"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\preet\\anaconda3\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Attrition', ylabel='count'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(df['Attrition'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "OMAsfWKEzqJk",
    "outputId": "d16db424-f46c-457f-ee78-3db1f9b2f527"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8077858880778589"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This is the percentage if we just guessed 'No' for attrition\n",
    "(1233 - 237) / 1233"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hG5u4J0E0FtJ"
   },
   "source": [
    "So I want to create a model that gives me more than 80% accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 351
    },
    "id": "_hcqaWdN0Bwi",
    "outputId": "9a1d02bd-7f9d-4589-9a97-8b3b87f1e2bc"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Age', ylabel='count'>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (12,5))\n",
    "sns.countplot(x = 'Age', hue = 'Attrition', data = df, palette = 'colorblind')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "CykxsgCi0eX7",
    "outputId": "0e1a6048-b4c8-422f-d4af-67f6401613aa"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Attrition:['Yes' 'No']\n",
      "No     1233\n",
      "Yes     237\n",
      "Name: Attrition, dtype: int64\n",
      "----------------------------------------\n",
      "BusinessTravel:['Travel_Rarely' 'Travel_Frequently' 'Non-Travel']\n",
      "Travel_Rarely        1043\n",
      "Travel_Frequently     277\n",
      "Non-Travel            150\n",
      "Name: BusinessTravel, dtype: int64\n",
      "----------------------------------------\n",
      "Department:['Sales' 'Research & Development' 'Human Resources']\n",
      "Research & Development    961\n",
      "Sales                     446\n",
      "Human Resources            63\n",
      "Name: Department, dtype: int64\n",
      "----------------------------------------\n",
      "EducationField:['Life Sciences' 'Other' 'Medical' 'Marketing' 'Technical Degree'\n",
      " 'Human Resources']\n",
      "Life Sciences       606\n",
      "Medical             464\n",
      "Marketing           159\n",
      "Technical Degree    132\n",
      "Other                82\n",
      "Human Resources      27\n",
      "Name: EducationField, dtype: int64\n",
      "----------------------------------------\n",
      "Gender:['Female' 'Male']\n",
      "Male      882\n",
      "Female    588\n",
      "Name: Gender, dtype: int64\n",
      "----------------------------------------\n",
      "JobRole:['Sales Executive' 'Research Scientist' 'Laboratory Technician'\n",
      " 'Manufacturing Director' 'Healthcare Representative' 'Manager'\n",
      " 'Sales Representative' 'Research Director' 'Human Resources']\n",
      "Sales Executive              326\n",
      "Research Scientist           292\n",
      "Laboratory Technician        259\n",
      "Manufacturing Director       145\n",
      "Healthcare Representative    131\n",
      "Manager                      102\n",
      "Sales Representative          83\n",
      "Research Director             80\n",
      "Human Resources               52\n",
      "Name: JobRole, dtype: int64\n",
      "----------------------------------------\n",
      "MaritalStatus:['Single' 'Married' 'Divorced']\n",
      "Married     673\n",
      "Single      470\n",
      "Divorced    327\n",
      "Name: MaritalStatus, dtype: int64\n",
      "----------------------------------------\n",
      "Over18:['Y']\n",
      "Y    1470\n",
      "Name: Over18, dtype: int64\n",
      "----------------------------------------\n",
      "OverTime:['Yes' 'No']\n",
      "No     1054\n",
      "Yes     416\n",
      "Name: OverTime, dtype: int64\n",
      "----------------------------------------\n"
     ]
    }
   ],
   "source": [
    "# Print all data type and their unique names\n",
    "for column in df.columns:\n",
    "  if df[column].dtype == object:\n",
    "    print(str(column) + \":\" + str(df[column].unique()))\n",
    "    print(df[column].value_counts())\n",
    "    print(\"----------------------------------------\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "iUKuH-h78tG3"
   },
   "source": [
    "Dropping all the columns that are not necessary and have only one unique value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "id": "EYD8W7Zh1qGW"
   },
   "outputs": [],
   "source": [
    "df.drop('Over18', axis = 1, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "id": "XA68632j2sjk"
   },
   "outputs": [],
   "source": [
    "df = df.drop(['EmployeeNumber','StandardHours', 'EmployeeCount'], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "id": "gw8lgYIr3Ps7"
   },
   "outputs": [],
   "source": [
    "cm = df.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 945
    },
    "id": "4cW4YJ5r3UZa",
    "outputId": "b45af172-cb35-4437-b431-cc8d15d03ced"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1008 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (14,14))\n",
    "sns.heatmap(cm, annot = True, fmt = '.0%')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "DjlbLOUR78L1"
   },
   "source": [
    "**From the heatmap, we can see the following characteristics:**\n",
    "\n",
    "\n",
    "*   Job level and Total Working Hours are correlated\n",
    "*   Monthly Income and Total Working Hours are correlated\n",
    "*   Job Level and Monthly Income are highly correlated\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "xElxlAzn3aaj",
    "outputId": "d9d2f2eb-2451-4c88-e756-c5088fe87545"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-16-bc9d5f493f8f>:5: DeprecationWarning: Converting `np.inexact` or `np.floating` to a dtype is deprecated. The current result is `float64` which is not strictly correct.\n",
      "  if df[column].dtype == np.number:\n"
     ]
    }
   ],
   "source": [
    "# Transform Categorical columns into numeric columns\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "for column in df.columns:\n",
    "  if df[column].dtype == np.number:\n",
    "    continue\n",
    "  else:\n",
    "    df[column] = LabelEncoder().fit_transform(df[column]) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "id": "LFxzbWKG404P"
   },
   "outputs": [],
   "source": [
    "df['Age_years'] = df['Age']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "id": "vyQ05vFv5CG_"
   },
   "outputs": [],
   "source": [
    "df = df.drop('Age', axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 215
    },
    "id": "_vlXivXC5Fnw",
    "outputId": "f437c309-ac60-4681-f579-021e14674b62"
   },
   "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>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>EnvironmentSatisfaction</th>\n",
       "      <th>Gender</th>\n",
       "      <th>HourlyRate</th>\n",
       "      <th>...</th>\n",
       "      <th>RelationshipSatisfaction</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",
       "      <th>Age_years</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>624</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>64</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>113</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>805</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>62</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>820</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>26</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>312</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Attrition  BusinessTravel  DailyRate  Department  DistanceFromHome  \\\n",
       "0          1               2        624           2                 0   \n",
       "1          0               1        113           1                 7   \n",
       "2          1               2        805           1                 1   \n",
       "3          0               1        820           1                 2   \n",
       "4          0               2        312           1                 1   \n",
       "\n",
       "   Education  EducationField  EnvironmentSatisfaction  Gender  HourlyRate  \\\n",
       "0          1               1                        1       0          64   \n",
       "1          0               1                        2       1          31   \n",
       "2          1               4                        3       1          62   \n",
       "3          3               1                        3       0          26   \n",
       "4          0               3                        0       1          10   \n",
       "\n",
       "   ...  RelationshipSatisfaction  StockOptionLevel  TotalWorkingYears  \\\n",
       "0  ...                         0                 0                  8   \n",
       "1  ...                         3                 1                 10   \n",
       "2  ...                         1                 0                  7   \n",
       "3  ...                         2                 0                  8   \n",
       "4  ...                         3                 1                  6   \n",
       "\n",
       "   TrainingTimesLastYear  WorkLifeBalance  YearsAtCompany  YearsInCurrentRole  \\\n",
       "0                      0                0               6                   4   \n",
       "1                      3                2              10                   7   \n",
       "2                      3                2               0                   0   \n",
       "3                      3                2               8                   7   \n",
       "4                      3                2               2                   2   \n",
       "\n",
       "   YearsSinceLastPromotion  YearsWithCurrManager  Age_years  \n",
       "0                        0                     5         23  \n",
       "1                        1                     7         31  \n",
       "2                        0                     0         19  \n",
       "3                        3                     0         15  \n",
       "4                        2                     2          9  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "id": "0rce2BgG5IAb"
   },
   "outputs": [],
   "source": [
    "X = df.drop('Attrition', axis = 1).values\n",
    "y = df['Attrition'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "id": "Fia0lBVN5fxg"
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_train,X_test,y_train,y_test = train_test_split(X,y, test_size = 0.25,random_state = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "boVLcwF459-s",
    "outputId": "eea10c92-f0ba-4868-c0bd-65b3f32b9e4a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestClassifier(criterion='entropy', n_estimators=10, random_state=0)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Model Building\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "model = RandomForestClassifier(n_estimators = 10, criterion = 'entropy', random_state = 0)\n",
    "model.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "id": "gGgK2bgD6SFl"
   },
   "outputs": [],
   "source": [
    "pred = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "id": "kRxLcm1N6Vmh"
   },
   "outputs": [],
   "source": [
    "from sklearn.metrics import confusion_matrix, classification_report, accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 450
    },
    "id": "K8yxGlLh6btU",
    "outputId": "96d997ed-7b16-4cab-f424-1ab247b66099"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.86      1.00      0.93       310\n",
      "           1       0.90      0.16      0.26        58\n",
      "\n",
      "    accuracy                           0.86       368\n",
      "   macro avg       0.88      0.58      0.59       368\n",
      "weighted avg       0.87      0.86      0.82       368\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cm = confusion_matrix(y_test,pred)\n",
    "sns.heatmap(cm, annot = True)\n",
    "print(\"\\n\")\n",
    "print(classification_report(y_test,pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "9emwZHRD7Ku0",
    "outputId": "416eb916-dbda-40fe-cd51-da0989e90628"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The model testing accuracy is 0.8641304347826086\n"
     ]
    }
   ],
   "source": [
    "print(\"The model testing accuracy is {}\".format(accuracy_score(y_test,pred)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "ZxqedxM17cek"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "Employee Attrition.ipynb",
   "provenance": []
  },
  "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}