DS_L2_17_Apr_Assignment_2_DS.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "DS_L2_17_Apr_Assignment_2_DS.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyOo+3RkQjePr3z9uSQ9FNdU",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Sanyam8055/100-Days-of-ML/blob/master/DS_L2_17_Apr_Assignment_2_DS.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L5hIbBssr2cv",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "f55ecefc-562d-499e-f3d2-177217a65d86"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
            "  import pandas.util.testing as tm\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HmfkLxOksMnA",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "file_url=\"https://raw.githubusercontent.com/shala2020/shala2020.github.io/master/Lecture_Materials/Assignments/DataScience/L2/train.csv\"\n",
        "df= pd.read_csv(file_url)\n",
        "file_url1=\"https://raw.githubusercontent.com/shala2020/shala2020.github.io/master/Lecture_Materials/Assignments/DataScience/L2/moviesData.csv\"\n",
        "movie = pd.read_csv(file_url1)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9FzU9a5_s38k",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 549
        },
        "outputId": "33c23a28-424a-4614-bc78-44f3b79bd2c8"
      },
      "source": [
        "df.head(10)"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>OverTime</th>\n",
              "      <th>PercentSalaryHike</th>\n",
              "      <th>PerformanceRating</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>ID</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>41</td>\n",
              "      <td>1</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>Yes</td>\n",
              "      <td>11</td>\n",
              "      <td>3</td>\n",
              "      <td>1</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",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>49</td>\n",
              "      <td>0</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>No</td>\n",
              "      <td>23</td>\n",
              "      <td>4</td>\n",
              "      <td>4</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",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>37</td>\n",
              "      <td>1</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>Yes</td>\n",
              "      <td>15</td>\n",
              "      <td>3</td>\n",
              "      <td>2</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",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>33</td>\n",
              "      <td>0</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>Yes</td>\n",
              "      <td>11</td>\n",
              "      <td>3</td>\n",
              "      <td>3</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",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>27</td>\n",
              "      <td>0</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>No</td>\n",
              "      <td>12</td>\n",
              "      <td>3</td>\n",
              "      <td>4</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",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>32</td>\n",
              "      <td>0</td>\n",
              "      <td>Travel_Frequently</td>\n",
              "      <td>1005</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>8</td>\n",
              "      <td>4</td>\n",
              "      <td>Male</td>\n",
              "      <td>79</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>Laboratory Technician</td>\n",
              "      <td>4</td>\n",
              "      <td>Single</td>\n",
              "      <td>3068</td>\n",
              "      <td>11864</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>13</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>3</td>\n",
              "      <td>6</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>59</td>\n",
              "      <td>0</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>1324</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>Medical</td>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "      <td>3</td>\n",
              "      <td>Female</td>\n",
              "      <td>81</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>Laboratory Technician</td>\n",
              "      <td>1</td>\n",
              "      <td>Married</td>\n",
              "      <td>2670</td>\n",
              "      <td>9964</td>\n",
              "      <td>4</td>\n",
              "      <td>Yes</td>\n",
              "      <td>20</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>12</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>30</td>\n",
              "      <td>0</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>1358</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>11</td>\n",
              "      <td>4</td>\n",
              "      <td>Male</td>\n",
              "      <td>67</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>Laboratory Technician</td>\n",
              "      <td>3</td>\n",
              "      <td>Divorced</td>\n",
              "      <td>2693</td>\n",
              "      <td>13335</td>\n",
              "      <td>1</td>\n",
              "      <td>No</td>\n",
              "      <td>22</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>38</td>\n",
              "      <td>0</td>\n",
              "      <td>Travel_Frequently</td>\n",
              "      <td>216</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>23</td>\n",
              "      <td>3</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>12</td>\n",
              "      <td>4</td>\n",
              "      <td>Male</td>\n",
              "      <td>44</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>Manufacturing Director</td>\n",
              "      <td>3</td>\n",
              "      <td>Single</td>\n",
              "      <td>9526</td>\n",
              "      <td>8787</td>\n",
              "      <td>0</td>\n",
              "      <td>No</td>\n",
              "      <td>21</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>9</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>36</td>\n",
              "      <td>0</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>1299</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>27</td>\n",
              "      <td>3</td>\n",
              "      <td>Medical</td>\n",
              "      <td>1</td>\n",
              "      <td>13</td>\n",
              "      <td>3</td>\n",
              "      <td>Male</td>\n",
              "      <td>94</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>Healthcare Representative</td>\n",
              "      <td>3</td>\n",
              "      <td>Married</td>\n",
              "      <td>5237</td>\n",
              "      <td>16577</td>\n",
              "      <td>6</td>\n",
              "      <td>No</td>\n",
              "      <td>13</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>17</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Age  Attrition  ... YearsWithCurrManager  ID\n",
              "0   41          1  ...                    5   0\n",
              "1   49          0  ...                    7   1\n",
              "2   37          1  ...                    0   2\n",
              "3   33          0  ...                    0   3\n",
              "4   27          0  ...                    2   4\n",
              "5   32          0  ...                    6   5\n",
              "6   59          0  ...                    0   6\n",
              "7   30          0  ...                    0   7\n",
              "8   38          0  ...                    8   8\n",
              "9   36          0  ...                    7   9\n",
              "\n",
              "[10 rows x 34 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g1y4I127v0WY",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        },
        "outputId": "b11a54c6-6854-45b1-bc9f-50168ac19345"
      },
      "source": [
        "df.MonthlyRate.head(5)"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    19479\n",
              "1    24907\n",
              "2     2396\n",
              "3    23159\n",
              "4    16632\n",
              "Name: MonthlyRate, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7dtcsLOowSNO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        },
        "outputId": "722b4b2a-def7-4693-9b19-9eacb315e435"
      },
      "source": [
        "print(df.MonthlyRate.mean())\n",
        "print(df.MonthlyRate.max())\n",
        "print(df.MonthlyRate.min())"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "14243.53112840467\n",
            "26999\n",
            "2094\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tePXOxAYxSoe",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "outputId": "5d047a04-f031-4288-ea38-2fce0a8a2536"
      },
      "source": [
        "  df.head()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>OverTime</th>\n",
              "      <th>PercentSalaryHike</th>\n",
              "      <th>PerformanceRating</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>ID</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>41</td>\n",
              "      <td>1</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>Yes</td>\n",
              "      <td>11</td>\n",
              "      <td>3</td>\n",
              "      <td>1</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",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>49</td>\n",
              "      <td>0</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>No</td>\n",
              "      <td>23</td>\n",
              "      <td>4</td>\n",
              "      <td>4</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",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>37</td>\n",
              "      <td>1</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>Yes</td>\n",
              "      <td>15</td>\n",
              "      <td>3</td>\n",
              "      <td>2</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",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>33</td>\n",
              "      <td>0</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>Yes</td>\n",
              "      <td>11</td>\n",
              "      <td>3</td>\n",
              "      <td>3</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",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>27</td>\n",
              "      <td>0</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>No</td>\n",
              "      <td>12</td>\n",
              "      <td>3</td>\n",
              "      <td>4</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",
              "      <td>4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Age  Attrition  ... YearsWithCurrManager  ID\n",
              "0   41          1  ...                    5   0\n",
              "1   49          0  ...                    7   1\n",
              "2   37          1  ...                    0   2\n",
              "3   33          0  ...                    0   3\n",
              "4   27          0  ...                    2   4\n",
              "\n",
              "[5 rows x 34 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-QYKRrcdysvB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "248dd0f4-632e-4a15-ed13-8ec0b23aa58c"
      },
      "source": [
        "df.isna()\n",
        "df.dropna()\n",
        "df.shape"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1028, 35)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BVkasnSH247N",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df[\"MonthRateNew\"]=(df[\"MonthlyRate\"]-df[\"MonthlyRate\"].mean())/df[\"MonthlyRate\"].std()\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pJjB3pYt2_KP",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "outputId": "d03083d3-195b-4779-ee40-37cc05c5bbc2"
      },
      "source": [
        "\n",
        "df.head()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>OverTime</th>\n",
              "      <th>PercentSalaryHike</th>\n",
              "      <th>PerformanceRating</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>ID</th>\n",
              "      <th>MonthRateNew</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>41</td>\n",
              "      <td>1</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>Yes</td>\n",
              "      <td>11</td>\n",
              "      <td>3</td>\n",
              "      <td>1</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",
              "      <td>0</td>\n",
              "      <td>0.742749</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>49</td>\n",
              "      <td>0</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>No</td>\n",
              "      <td>23</td>\n",
              "      <td>4</td>\n",
              "      <td>4</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",
              "      <td>1</td>\n",
              "      <td>1.512813</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>37</td>\n",
              "      <td>1</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>Yes</td>\n",
              "      <td>15</td>\n",
              "      <td>3</td>\n",
              "      <td>2</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",
              "      <td>2</td>\n",
              "      <td>-1.680795</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>33</td>\n",
              "      <td>0</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>Yes</td>\n",
              "      <td>11</td>\n",
              "      <td>3</td>\n",
              "      <td>3</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",
              "      <td>3</td>\n",
              "      <td>1.264827</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>27</td>\n",
              "      <td>0</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>No</td>\n",
              "      <td>12</td>\n",
              "      <td>3</td>\n",
              "      <td>4</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",
              "      <td>4</td>\n",
              "      <td>0.338849</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Age  Attrition     BusinessTravel  ...  YearsWithCurrManager ID  MonthRateNew\n",
              "0   41          1      Travel_Rarely  ...                     5  0      0.742749\n",
              "1   49          0  Travel_Frequently  ...                     7  1      1.512813\n",
              "2   37          1      Travel_Rarely  ...                     0  2     -1.680795\n",
              "3   33          0  Travel_Frequently  ...                     0  3      1.264827\n",
              "4   27          0      Travel_Rarely  ...                     2  4      0.338849\n",
              "\n",
              "[5 rows x 35 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_eJGN2LK8kaY",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 456
        },
        "outputId": "45002168-2bc9-4d91-e03e-b06b50f84ca7"
      },
      "source": [
        "movie.isna()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Unnamed: 0</th>\n",
              "      <th>title</th>\n",
              "      <th>title_type</th>\n",
              "      <th>genre</th>\n",
              "      <th>runtime</th>\n",
              "      <th>mpaa_rating</th>\n",
              "      <th>studio</th>\n",
              "      <th>thtr_rel_year</th>\n",
              "      <th>thtr_rel_month</th>\n",
              "      <th>thtr_rel_day</th>\n",
              "      <th>dvd_rel_year</th>\n",
              "      <th>dvd_rel_month</th>\n",
              "      <th>dvd_rel_day</th>\n",
              "      <th>imdb_rating</th>\n",
              "      <th>imdb_num_votes</th>\n",
              "      <th>critics_rating</th>\n",
              "      <th>critics_score</th>\n",
              "      <th>audience_rating</th>\n",
              "      <th>audience_score</th>\n",
              "      <th>best_pic_nom</th>\n",
              "      <th>best_pic_win</th>\n",
              "      <th>best_actor_win</th>\n",
              "      <th>best_actress_win</th>\n",
              "      <th>best_dir_win</th>\n",
              "      <th>top200_box</th>\n",
              "      <th>director</th>\n",
              "      <th>actor1</th>\n",
              "      <th>actor2</th>\n",
              "      <th>actor3</th>\n",
              "      <th>actor4</th>\n",
              "      <th>actor5</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>595</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>596</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>597</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>598</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>599</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>600 rows × 31 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     Unnamed: 0  title  title_type  genre  ...  actor2  actor3  actor4  actor5\n",
              "0         False  False       False  False  ...   False   False   False   False\n",
              "1         False  False       False  False  ...   False   False   False   False\n",
              "2         False  False       False  False  ...   False   False   False   False\n",
              "3         False  False       False  False  ...   False   False   False   False\n",
              "4         False  False       False  False  ...   False   False   False   False\n",
              "..          ...    ...         ...    ...  ...     ...     ...     ...     ...\n",
              "595       False  False       False  False  ...   False   False   False   False\n",
              "596       False  False       False  False  ...   False   False   False   False\n",
              "597       False  False       False  False  ...   False   False   False   False\n",
              "598       False  False       False  False  ...   False   False   False   False\n",
              "599       False  False       False  False  ...   False   False   False   False\n",
              "\n",
              "[600 rows x 31 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6pput2Rm-kEt",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "79b59ae6-ebca-4dc7-a010-29188bdd6bc6"
      },
      "source": [
        "movie_new=movie.dropna()\n",
        "movie_new.shape\n"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(572, 31)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mQ_SQZQgSqJl",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "movie = movie.fillna(movie.mean())"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "os9h3lb5-qb4",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 886
        },
        "outputId": "c80adba0-19df-4f2b-ebe7-6518e1ef1f3f"
      },
      "source": [
        "df.hist(column=\"Age\", bins=30, color=\"Blue\",figsize=(10,10))\n",
        "df.plot.scatter(x='Age',y='Attrition')"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f72d4568e48>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9CJLFRz4Ars-",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        },
        "outputId": "cd6cb420-5f65-460f-f51f-49a9d2b83ea5"
      },
      "source": [
        "df.Attrition.value_counts()\n",
        "sns.countplot(x=\"Attrition\", data=df)\n",
        "plt.ylim(0,1000)\n",
        "plt.show()"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Mx45JOP-TRr1",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 374
        },
        "outputId": "4a2ac16b-9ee3-405e-c6b5-fb59c6946d4e"
      },
      "source": [
        "pd.crosstab(df.BusinessTravel, df.Attrition).plot(kind=\"bar\")\n",
        "plt.ylabel(\"Attrition\")"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Attrition')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Jc_X36pqTU0b",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 322
        },
        "outputId": "37985e33-fa48-4021-f091-9577d74a6da8"
      },
      "source": [
        "new_df = pd.crosstab(df.Gender, df.Attrition)\n",
        "new_df.plot(kind=\"bar\", stacked=True)\n",
        "plt.ylabel(\"Attrition\")"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Attrition')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jd6TPkKvTwKT",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 905
        },
        "outputId": "aae5d9ab-2677-420b-bcf6-50840f7cff5c"
      },
      "source": [
        "df.hist(column=\"TotalWorkingYears\", bins=30, color=\"blue\")\n",
        "plt.show()\n",
        "\n",
        "df.hist(column=\"YearsAtCompany\", figsize=(10,10), color=\"blue\")"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f72d42fc080>]],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gviFMEaMT26w",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "outputId": "bd3fe51f-4b05-4305-d38b-913e107ee1a8"
      },
      "source": [
        "sns.boxplot('Department', 'MonthlyIncome', data=df)"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f72d47e8e10>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZEAAAEGCAYAAACkQqisAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAgAElEQVR4nO3de5wcZZ3v8c83CfeAEDIbQyYxmARc4GCECLgKhoWE4MrFXZfLUQkuh4QVCBx1BdFdQNHFg+A64qIBcwBFEAUlYCQGJMAKgQzkCkgyQIDJhly5hUSQ5Ld/1NOkZ+ie6emZnp6e+b5fr35N1VO3X3XV9K+eujyliMDMzKwc/aodgJmZ1S4nETMzK5uTiJmZlc1JxMzMyuYkYmZmZRtQ7QC62+DBg2PkyJHVDsPMrKY89thj6yKirnV5n0siI0eOpLGxsdphmJnVFEnPFyr36SwzMyubk4iZmZXNScTMzMrmJGJmZmVzEjHrAdatW8e5557L+vXrqx2KWYdULIlIGi7pPklPSnpC0nmpfJCkOZKWp797pHJJapDUJGmxpIPy5jU5jb9c0uS88oMlLUnTNEhSpdbHrJKuuOIKFi1axBVXXFHtUMw6pJI1kbeBL0XEfsBhwNmS9gMuBO6NiDHAvakf4FhgTPpMAa6BLOkAFwOHAocAF+cSTxrnzLzpJlVwfXq8ZcuWceyxx9LU1FTtUKwD1q1bx8MPPwzAQw895NqI1ZSKJZGIWBURj6fu14GngGHACcANabQbgBNT9wnAjZGZB+wuaShwDDAnIjZExMvAHGBSGrZbRMyLrD37G/Pm1SdddtllvPHGG3zjG9+odijWAa1rH66NWC3plmsikkYCHwIeAYZExKo06CVgSOoeBryYN1lzKmurvLlAeaHlT5HUKKlx7dq1nVqXnmrZsmWsWLECgBUrVrg2UkNytZCchx56qEqRmHVcxZOIpIHAbcD5EfFa/rBUg6j4W7EiYnpEjIuIcXV173pqv1e47LLLWvS7NmJm3aGizZ5I2o4sgdwUEben4tWShkbEqnRKak0qXwkMz5u8PpWtBMa3Kp+byusLjN8n5WohxfrNDBoaGipSS29uzk6K1NfXtzNmx40ePZpp06Z1+Xy7SiXvzhLwE+CpiLgqb9BMIHeH1WTgjrzy09JdWocBr6bTXrOBiZL2SBfUJwKz07DXJB2WlnVa3rz6nOHDh7fZb2aVs3nzZjZv3lztMKqikjWRjwKfA5ZIWpjKLgIuB26VdAbwPHBSGjYL+ATQBGwCPg8QERskfROYn8b7RkRsSN1fAK4HdgJ+lz590qhRo3jxxW2XjkaPHl3FaMx6pkod0efm29DQUJH592QVSyIR8V9Asec2jiowfgBnF5nXDGBGgfJG4IBOhNlrPProoy36H3nkkSpFYmZ9iZ9Y7yUmTJhAv37Z5uzXrx8TJ06sckRm1hc4ifQSkydPbrPfzKwSnER6ka1bt7b4a2ZWaU4ivcSPf/zjNvvNzCrBSaSXuOeee1r0z5kzp0qRmFlf4iTSS2zZsqXNfuu5Wjc+7caorZY4iZhV2ahRo1r0jxkzpkqRmHWck0gv0b9//zb7redq3QzHsmXLqhSJWcc5ifQSRx99dIv+CRMmVCkSM+tLnER6ialTp7bZb2ZWCU4iZlU2aNCgFv177rlnlSIx6zgnkV7Cz4nUrg0bNrTo9+txrZY4ifQSfk7EzKrBScTMzMrmJNJL7LXXXm32W8/lhw2tljmJ9BLr1q1rs996rlwT/sX6zXoy7629ROv3hxxzzDFVisQ6yk3WWC2r5DvWZ0haI2lpXtkvJC1MnxW51+ZKGilpc96wH+VNc7CkJZKaJDWk96kjaZCkOZKWp797VGpdasFxxx3Xov/444+vUiRm1pdUsiZyPTApvyAiTo6IsRExFrgNuD1v8DO5YRFxVl75NcCZwJj0yc3zQuDeiBgD3Jv6+6w777yzRf/MmTOrFImZ9SUVSyIR8QCwodCwVJs4Cbi5rXlIGgrsFhHz0jvYbwROTINPAG5I3TfklfdJs2fPbtF/9913VykSM+tLqnVN5HBgdUQszyvbW9ICSfdLOjyVDQOa88ZpTmUAQyJiVep+CRhSbGGSpkhqlNS4du3aLlqFnmXAgAFt9lvP5cYzrZZVK4mcSstayCpgRER8CPgi8HNJu5U6s1RLiTaGT4+IcRExrq6urtyYe7SNGze22W89V7b7Fu8368m6PYlIGgD8PfCLXFlEvBkR61P3Y8AzwD7ASqA+b/L6VAawOp3uyp32WlP56HuukSNHttlvPZeTiNWyatREjgb+FBHvnKaSVCepf+p+P9kF9GfT6arXJB2WrqOcBtyRJpsJTE7dk/PK+6RzzjmnRf95551XpUiso5xErJZV8hbfm4GHgX0lNUs6Iw06hXdfUD8CWJxu+f0VcFZE5C7KfwG4Dmgiq6H8LpVfDkyQtJwsMV1eqXWpBa3bymp9od3MrBIqdvU1Ik4tUn56gbLbyG75LTR+I3BAgfL1wFGdi7L3KNQA40UXXVSlaMysr/AT672En3o2s2pwEjEzs7I5ifQSO++8c5v9ZmaV4CTSS3zwgx9s0T927NgqRWJmfYmTSC+xaNGiFv0LFy6sUiRm1pc4ifQShx9+eIv+I444okqRWEe52ROrZU4iZlXmAwCrZU4ivcQDDzzQov/++++vUiRm1pc4ifQSgwcPbrPfeq4HH3ywRX/rAwKznsxJpJdYuXJlm/3Wc23durXNfrOezEmkl+jXr1+b/dZzedtZLfPe2kscdVTLZsSOPvroKkViHdV6W02YMKFKkZh1nJNILzF16tR3jmD79evH1KlTqxyRlWrq1KlkbzrwtrPa4yTSSwwePPidI9iJEyey5557VjkiK9XgwYOZOHEi4G1ntccv4u5Fpk6dyksvveQj2RrkbWe1ykmkmzU0NNDU1FSReTc3Zy+LvPTSS7t83qNHj2batGldPt9aU6ntV8ltB95+VjlOIr3I5s2bqx2ClcnbzmpVxZKIpBnAJ4E1EXFAKrsEOBNYm0a7KCJmpWFfBc4AtgDTImJ2Kp8EfB/oD1wXEZen8r2BW4A9gceAz0XEW5Van65SyaPB3LwbGhoqtoy+rlLbz9vOalUlL6xfD0wqUP69iBibPrkEsh/Zu9f3T9P8p6T+kvoDPwSOBfYDTk3jAnwnzWs08DJZAjIzs25UsSQSEQ8AG0oc/QTgloh4MyKeA5qAQ9KnKSKeTbWMW4ATlN0P+bfAr9L0NwAndukKmJlZu6pxi+85khZLmiFpj1Q2DHgxb5zmVFasfE/glYh4u1V5QZKmSGqU1Lh27dpio5mZWQd1dxK5BhgFjAVWAVd2x0IjYnpEjIuIcXV1dd2xSDOzPqFb786KiNW5bknXAnel3pXA8LxR61MZRcrXA7tLGpBqI/njm5lZN+nWmoikoXm9nwKWpu6ZwCmSdkh3XY0BHgXmA2Mk7S1pe7KL7zMjIoD7gE+n6ScDd3THOpiZ2TaVvMX3ZmA8MFhSM3AxMF7SWCCAFcBUgIh4QtKtwJPA28DZEbElzeccYDbZLb4zIuKJtIgLgFskXQYsAH5SqXUxM7PCKpZEIuLUAsVFf+gj4lvAtwqUzwJmFSh/luzuLTMzqxI3wGhmZmVzEjEzs7I5iZiZWdmcRMzMrGxOImZmVjYnETMzK1tJSUTSPpLulbQ09R8o6euVDc3MzHq6Umsi1wJfBf4CEBGLyZ4eNzOzPqzUJLJzRDzaquztgmOamVmfUWoSWSdpFFlzJUj6NFkrvGZm1oeV2uzJ2cB04AOSVgLPAZ+tWFRmZlYTSkoiqZ2qoyXtAvSLiNcrG5aZmdWCkpKIpN2B04CRwIDs7bQQEdMqFpmZmfV4pZ7OmgXMA5YAWysXjpmZ1ZJSk8iOEfHFikZiZmY1p9S7s34q6UxJQyUNyn0qGpmZmfV4pdZE3gKuAL5Gus03/X1/JYIyM7PaUGpN5EvA6IgYGRF7p0+bCUTSDElrck2lpLIrJP1J0mJJv04X7JE0UtJmSQvT50d50xwsaYmkJkkNSlf1U21ojqTl6e8eHV99MzPrjFKTSBOwqYPzvh6Y1KpsDnBARBwILCNrSiXnmYgYmz5n5ZVfA5wJjEmf3DwvBO6NiDHAvanfzMy6Uamns94AFkq6D3gzV9jWLb4R8YCkka3Kfp/XOw/4dFsLlTQU2C0i5qX+G4ETgd8BJwDj06g3AHOBC0pZGTMz6xqlJpHfpE9X+ifgF3n9e0taALwGfD0iHgSGAc154zSnMoAhEZFreuUlYEixBUmaAkwBGDFiRNdEb2ZmJT+xfoOk7YF9UtHTEfGXchcq6WtkDTjelIpWASMiYr2kg4HfSNq/1PlFREiKNoZPJ2u2hXHjxhUdz8zMOqbUJ9bHk50yWgEIGC5pckQ80NEFSjod+CRwVEQEQES8STpNFhGPSXqGLGGtBOrzJq9PZQCrJQ2NiFXptNeajsZiZmadU+qF9SuBiRHx8Yg4AjgG+F5HFyZpEvAV4PiI2JRXXiepf+p+P9kF9GfT6arXJB2W7so6DbgjTTYTmJy6J+eVm5lZNyk1iWwXEU/neiJiGbBdWxNIuhl4GNhXUrOkM4CrgV2BOa1u5T0CWCxpIfAr4KyI2JCGfQG4juwOsWfILqoDXA5MkLQcODr1m5lZNyr1wnqjpOuAn6X+zwCNbU0QEacWKP5JkXFvA24rMqwROKBA+XrgqLZiMDOzyio1ifwz2TtFcrf0Pgj8Z0UiMjOzmlFqEhkAfD8irgJI1y92qFhUZmZWE0q9JnIvsFNe/07APV0fjpmZ1ZJSk8iOEbEx15O6d65MSGZmVitKTSJvSDoo15MeCNxcmZDMzKxWlHpN5Hzgl5L+m+xhw/cCJ1csKjMzqwmlNnsyX9IHgH1TUaeaPTEzs96h1JoIwIeBkWmagyQRETdWJCozM6sJpbad9VNgFLAQ2JKKA3ASMTPrw0qtiYwD9ss1mGhmZgal3521lOxiupmZ2TtKrYkMBp6U9Cgt32x4fEWiMjOzmlBqErmkkkGYmVltKvUW3/srHYiZmdWeNpOIpNfJ7sJS+vvOILK30u5WwdjMrA9qaGigqamp2mF0yPLlywGYNm1aO2P2HKNHj+6SeNtMIhGxa6eXYGbWAU1NTSx4YgHsXu1IOmBr9mfBygXVjaNUr3TdrEp9TuRK4CcR8WTXLdrMrIjdYev4rdWOotfqN7fUG3NLmFeJ4z0FXCvpEUlnSXpPKRNJmiFpjaSleWWDJM2RtDz93SOVS1KDpCZJi1s1+Dg5jb9c0uS88oMlLUnTNKT3sJuZWTcpKYlExHUR8VHgNLKmTxZL+rmkI9uZ9HpgUquyC4F7I2IM2XtKLkzlxwJj0mcKcA1kSQe4GDgUOAS4OJd40jhn5k3XellmZlZBJddp0tsMP5A+64BFwBcl3VJsmoh4ANjQqvgE4IbUfQNwYl75jZGZB+wuaShwDDAnIjZExMvAHGBSGrZbRMxLT9LfmDcvMzPrBqVeE/kecBxZzeHbEfFoGvQdSU93cJlDImJV6n4JGJK6hwEv5o3XnMraKm8uUF4o/ilktRtGjBjRwXDNzKyYUmsii4EPRsTUvASSc0i5C081iIq3xxUR0yNiXESMq6urq/TizMz6jPaeE8ld3F4E7Nv6unVEPB4Rr3ZwmaslDY2IVemU1JpUvhIYnjdefSpbCYxvVT43ldcXGN/MzLpJe6ezrmxjWAB/W8YyZwKTgcvT3zvyys9J11gOBV5NiWY28O28i+kTga9GxAZJr0k6DHiE7KL/D8qIx8zMytTew4bt3X3VJkk3k9UiBktqJrvL6nLgVklnAM8DJ6XRZwGfAJqATcDnUwwbJH0TmJ/G+0ZE5C7Wf4HsDrCdgN+lj5mZdZOS32wo6W/Y9mZDgHbfbBgRpxYZdFSBcQM4u8h8ZgAzCpQ3Age0FYOZmVWO32xoZmZl85sNzcysbH6zoZmZla29W3zvJDtttSt+s6GZmbXS3ums73ZLFGZmVpPau8X3fgBJ34mIC/KHSfoO0GvfeOgX43SPrnoxjplVR6kX1icAF7QqO7ZAWa/R1NTEgiVPsnXnQdUOpWR6K7vv4bFnXqpyJKXpt6l125xmVmvauybyz2QP9L1f0uK8QbsCD1UysJ5g686D+PN+n6x2GL3Wjk/eVe0QzKyT2quJ/JzsKfB/Z9t7PwBez3tq3MzM+qj2rom8CrwKnJreJzIkTTNQ0sCIeKEbYjQzsx6q1CfWzwEuAVbzzivpCeDAyoRlZma1oNQL6+cD+0bE+koGY2ZmtaXUJ9ZfJDutZWZm9o5SayLPAnMl/ZaWT6xfVZGozMysJpSaRF5In+3Tx6xHq7WHRWvxQVHww6JWYhKJiEsBJA1M/RsrGZRZZzU1NbFs6eOMGLil/ZF7gO3/kp1Z/vOK+e2M2XO8sLF/tUOwHqDUu7MOAH4KDEr964DTIuKJCsZm1ikjBm7h6+N8vFMplzUOrHYI1gOUemF9OvDFiHhfRLwP+BJwbTkLlLSvpIV5n9cknS/pEkkr88o/kTfNVyU1SXpa0jF55ZNSWZOkCwsv0czMKqXUayK7RMR9uZ6ImCtpl3IWGBFPA2MB0gOMK4Ffk71T/XsR0aLlYEn7AacA+wN7AfdI2icN/iFZu17NwHxJMyPiyXLiMjOzjiv57ixJ/0p2Sgvgs2R3bHXWUcAzEfG8pGLjnADcEhFvAs9JagIOScOaIuJZAEm3pHGdRMzMukmpp7P+CagDbk+fulTWWacAN+f1nyNpsaQZkvZIZcPInlPJaU5lxcrfRdIUSY2SGteuXdsFYZuZGZSYRCLi5YiYFhEHpc95EfFyZxYsaXvgeOCXqegaYBTZqa5VwJWdmX++iJgeEeMiYlxdXV1XzdbMrM9rryn4mW0N7+TrcY8FHo+I1Wleq/OWey2Qayd8JTA8b7r6VEYb5WZm1g3auybyEbJTRjcDjwBFL1yU4VTyTmVJGhoRq1Lvp4ClqXsm8HNJV5FdWB8DPJpiGSNpb7LkcQrwv7swPjMza0d7SeS9ZHc/nUr2A/1b4ObOPh+S7uyaAEzNK/5/ksaStQ68IjcsIp6QdCvZBfO3gbMjYkuazznAbKA/MMPPrZiZda/23ieyBbgbuFvSDmTJZK6kSyPi6nIXGhFvAHu2KvtcG+N/C/hWgfJZwKxy4zAzs85p9xbflDz+jiyBjAQayJ7rMDOzPq69C+s3AgeQHe1fGhFL2xrfzMz6lvZqIp8F3gDOA6blPRAoICJitwrGZmZmPVx710RKfRjRzMz6ICcJMzMrm5OImZmVzUnEzMzK5iRiZmZlcxIxM7Oylfo+kT6nubmZfpteZccn72p/ZCtLv03raW5+u9phmFknuCZiZmZlc02kiPr6ela/OYA/7/fJaofSa+345F3U17+32mGYWSe4JmJmZmVzEjEzs7I5iZiZWdmcRMzMrGxOImZmVraqJRFJKyQtkbRQUmMqGyRpjqTl6e8eqVySGiQ1SVos6aC8+UxO4y+XNLla62Nm1hdV+xbfIyNiXV7/hcC9EXG5pAtT/wXAscCY9DkUuAY4VNIg4GJgHNm72R+TNDMiXu7OlTCzrtPc3AyvQr+5PlFSMa9AczR3yax62lY6Abghdd8AnJhXfmNk5gG7SxoKHAPMiYgNKXHMASZ1d9BmZn1VNWsiAfxeUgA/jojpwJCIWJWGvwQMSd3DgBfzpm1OZcXKW5A0BZgCMGLEiK5cBzPrYvX19azVWraO31rtUHqtfnP7UT+svkvmVc0k8rGIWCnpr4A5kv6UPzAiIiWYTksJajrAuHHjumSeZmZWxdNZEbEy/V0D/Bo4BFidTlOR/q5Jo68EhudNXp/KipWbmVk3qEoSkbSLpF1z3cBEYCkwE8jdYTUZuCN1zwROS3dpHQa8mk57zQYmStoj3ck1MZWZmVk3qNbprCHAryXlYvh5RNwtaT5wq6QzgOeBk9L4s4BPAE3AJuDzABGxQdI3gflpvG9ExIbuWw0zs76tKkkkIp4FPligfD1wVIHyAM4uMq8ZwIyujtHMzNpX7edEerR+mzbU1Eup9OfXAIgdd6tyJKXpt2kDUJmm4Jubm3nj9f5c1jiwIvM3eP71/uzS3DXPGljtchIpYvTo0dUOocOWL38dgDGjauUdHe+tye/ZzLZxEili2rRp1Q6hw3IxNzQ0VDmS6quvr+fPb6/i6+M2VjuUXuuyxoHsWN81zxpY7eppT6ybmVkNcRIxM7OyOYmYmVnZnETMzKxsTiJmZlY2JxEzMyubk4iZmZXNScTMzMrmJGJmZmVzEjEzs7I5iZiZWdmcRMzMrGxOImZmVja34mtmPc8r0G9uDR3j5hqLrpXX17wCDOuaWXV7EpE0HLiR7BW5AUyPiO9LugQ4E1ibRr0oImalab4KnAFsAaZFxOxUPgn4PtAfuC4iLu/OdbGe7YWNtfNSqtWbsh/MITtvrXIkpXthY3/2qcB8a/EdM8uXLwdgzLAxVY6kRMO67nuuRk3kbeBLEfG4pF2BxyTNScO+FxHfzR9Z0n7AKcD+wF7APZJy++4PgQlAMzBf0syIeLJb1sJ6tFr7IXor/QjtOLJGfoSAfajM9+x3+dSWbk8iEbEKWJW6X5f0FG1XrE4AbomIN4HnJDUBh6RhTel97Ui6JY3rJGI190PUl3+ErLZV9aSjpJHAh4BHUtE5khZLmiFpj1Q2DHgxb7LmVFasvNBypkhqlNS4du3aQqOYmVkZqpZEJA0EbgPOj4jXgGuAUcBYsprKlV21rIiYHhHjImJcXV1dV83WzKzPq8rdWZK2I0sgN0XE7QARsTpv+LXAXal3JTA8b/L6VEYb5WZm1g26vSYiScBPgKci4qq88qF5o30KWJq6ZwKnSNpB0t7AGOBRYD4wRtLekrYnu/g+szvWwczMMtWoiXwU+BywRNLCVHYRcKqksWS3/a4ApgJExBOSbiW7YP42cHZEbAGQdA4wm+wW3xkR8UR3roiZ1ZaGhgaampq6fL65W3wrcUPH6NGje/SNItW4O+u/ABUYNKuNab4FfKtA+ay2pjMz6w477bRTtUOoGj+xbmZ9Rk8+oq9VNdSugJmZ9TROImZmVjYnETMzK5uTiJmZlc1JxMzMyuYkYmZmZXMSMTOzsvk5kW5WqSdmoW8/NWtm1eEk0ov05admu0stNpsBPgiwynES6Wb+R7ZCfABgtcpJxKwDfBBg1pIvrJuZWdmcRMzMrGxOImZmVjYnETMzK5uTiJmZlc1JxMzMyuYkYmZmZXMSMTOzsikiqh1Dt5K0Fni+2nFU0GBgXbWDsLJ429W23r793hcRda0L+1wS6e0kNUbEuGrHYR3nbVfb+ur28+ksMzMrm5OImZmVzUmk95le7QCsbN52ta1Pbj9fEzEzs7K5JmJmZmVzEjEzs7I5ifRwkr4m6QlJiyUtlHRoG+NeL+nT3RlfJUjaktZ1qaQ7Je1e7ZhyJM2V1O5tnJLGSHo0bbd72hhvpKTNkhZIeipNc3qXBp0tZ7yku7p6vp0haXdJX2hj+MZW/adLurrykbVP0gpJS9L2vV/S+6odU7U4ifRgkj4CfBI4KCIOBI4GXqxuVN1ic0SMjYgDgA3A2d25cGU6+79xIXBN2m5ntjPuMxHxoYj4a+AU4HxJn+/k8mvB7kDRJFIDjkzbdy7w9e5euKT+3b3MQpxEerahwLqIeBMgItZFxH9L+jdJ89OR+nRJaj2hpIPTEdJjkmZLGprKp0l6Mh1B3dLN61OOh4FhAJJGSbo7rdODkj6Qyv8xfReLJD2QyvpLuiJ9T4slTU3lAyXdK+nxdCR5QiofKelpSTcCS4Hhki5I4yySdHleTP+YagzLJB1eJO63gHqAiHiu1JWNiGeBLwLTUly7SJqRlrcgL955kvbPTZerIRUbP5+kQZJ+k76XeZIOTOWXSPqppIclLZd0Ziofn/alOyQ9K+lySZ9Jy1giaVQar07Sbek7ny/po3nznZFifFZS7h3DlwOjUq3zilK/ozTPFrXuXK2lA7EeJ+mR9B3dI2lIO7G2JX8fLfYdfDyt58K0zF2VuSLtu0sknZy3Du/UGiVdrVQ7VVYD+o6kx8n2w0lpX14k6d40TrF9Zv9UtjBt+zEd+c6Ligh/eugHGAgsBJYB/wl8PJUPyhvnp8Bxqft64NPAdsBDQF0qPxmYkbr/G9ghde9e7XUsst4b09/+wC+BSan/XmBM6j4U+EPqXgIMy18nYArw9dS9A9AI7A0MAHZL5YOBJkDASGArcFgadmz6DnfO/87JjjqvTN2fAO4psg5fBtYCn2xnXUcCS1uV7U5WGwP4NvDZvPJlwC7A/wUuTeVDgafbGX88cFcq/wFwcer+W2Bh6r4EWATslL6bF4G90rSvpOXsAKzMW/Z5wH+k7p8DH0vdI4Cn8ub7UJp2MLA+7aPvWvdW38MWsv0/93kBuDp/Xy+wz5Qa6x5suzv1/+Rt04KxFohtBTA4df8HMKWd7+BO4KN5/9cDgH8A5pDt50PS+g3N31Zp/KuB0/OW+5XUXZe20d6t9tFi+8APgM+k8u2Bnbri/3UA1mNFxEZJBwOHA0cCv5B0IfC6pK8AOwODgCfIdtKcfYEDgDnKKin9gVVp2GLgJkm/AX7TLSvScTtJWkh2dPcU2XoMBP4G+KW2Vbx2SH//CFwv6Vbg9lQ2ETgw72j1PcAYoBn4tqQjyJLGMLJ/YIDnI2Je6j4a+P8RsQkgIjbkxZdbxmNkP4QtSDooLf9DKfYNZEerzwCjIv0XtyG/ZjkROF7Sl1P/jmQ/TrcCvwcuBk4CftXO+Pk+RvYDRkT8QdKeknZLw+6IiM3AZkn3AYeQ/SjPj4hVaf2eScuGLIEfmbqPBvbL2z67pe0G8NvIatRvSlrDtu+8LZsjYuw7X0p2NF5KsyKlxFpP9v80lOwHNb+2WCjW5gLLuU/SIGAj8K+prNh38EfgKkk3AbdHRLOkjwE3R8QWYLWk+4EPA6+1s36/SH8PAx6IVNPN20eL7QMPA1+TVJ9iWN7OckriJNLDpR1sLjBX0hJgKnAgMC4iXpR0CdlOkk/AExHxkQKz/DvgCOA4sjXq0p0AAAX7SURBVB3qf0XE25WKv0ybI2KspJ2B2WTXRK4HXsn/UcmJiLOU3XDwd8BjKfEKODciZuePm36I6oCDI+Ivklaw7ft7o8T43kx/t1D4f+ho4KH0Q/EpYCbwI2BWCQkEsuTzVC5k4B8i4unWI0lar+xU1MnAWW2NnztdU4LW8eX638wr25rXv5Vt30E/sprcn1stu/X0xb63jng7LQ9l16+2zxtWSqw/AK6KiJmSxpPVQApN31asR5Il2JuAS8lOQxb8DoDLJf2WrPb6R0nHlLJuSev/7/b202L7zFOSHiH7P5klaWpE/KGdebXL10R6MEn7tjpvORbI7Rjr0hFOobuxngbqlF2YR9J26XxoP2B4RNwHXEB2dD6wwPQ9QqoFTAO+BGwCnpP0j/DOxe8Ppu5REfFIRPwb2Smk4WTJ558lbZfG2UfSLmTrvCYlkCOBYnfVzAE+nxIZ6YizVAuAEyS9JyL+BFwBXAn8rL0JJY0Evkv2I0daj3OVfoklfShv9F8AXwHeExGLSxg/50HgM2n4eLLrbrmj3xMk7ShpT7LTKvNLWN+c3wPn5q3LuxJ+K68Du3Zg/vlWAAen7uPJTo91xHvITnUBTC4zBtIB2PnAaWkfKfgdpH10SUR8h+w7/QDZdjhZ2fW7OrKDu0fJWhnfT9IOyu5MPKrI4ucBR0jaOy0jt48W3AckvR94NiIagDvIDkY7zTWRnm0g8IO0I71Ndv5+CtnRz1LgJQr8k0fEW+k0ToOk95Bt5/8gOzf6s1QmoCEiXumWNSlTRCyQtBg4leyH7xpJXyf70biF7Bz+FSnZiuy6ySKy03YjgcfTP9Na4ESyo8Y7U62uEfhTkeXenX4AGiW9BcwCLiox5jmSfgbMk7SJ7FTJ58lOuR0eEWtbTTJK0gKyI87XybbL9WnYN8m23eJ0EPAc2R17kJ3C+n4ahxLGz7kEmJG+1020/BFdDNxHdj3gm5HdyLFPKetNlvB/mOY7AHiAbTWkd4mI9ZL+KGkp8LuI+JcSlwNwLXCHpEXA3ZRei8y5hOzU6MvAH8iul5UlIlZJupmsxlzsOzg/HbRsJTv9/Duymy8+Qra/Btm1jpcA0qnZpWTbb0GR5a6VNAW4PW3rNcAEiu8DJwGfk/QXst+Ob5e7zvnc7ImZAdmdSWQXqL9b7Visdvh0lpmZlc01ETMzK5trImZmVjYnETMzK5uTiJmZlc1JxKwAbWtJ+All7RJ9SZ1vlLGU5Z4uaa/eshzr/ZxEzArLtSS8P9m998eSNTFSMcpaZT2drL2qSuuu5Vgv5yRi1o6IWEP2kOc56Un5Yi0Ej5f0gKTfKmsR+Ee52oukayQ1pprNpbl5q2WrrKeStQ11U6oF7ZSG/3vqb5R0kLJWmZ+RdFbefP4lL55LU9lIZe8ouTYt9/dpnp9uvZxu+zKt13ESMStBZE209wf+CjgDeDUiPkzWYN6ZuaYnyBosPBfYDxgF/H0q/1pEjCNrauLjSs2vJ+sj4qCI+BnZU/SfSbWgzWn4C6nNsAfZ1lLzYWTtNSFpIlnjkoeQNY1zsLIGJknlP0w1qlfI2lT6VZHlmHWYmz0x67hiLQS/BTyaEg6pKYyPkTVPclJqomIAWXPf+5E1MQLbWmUtZmb6uwQYGBGvk7Xk/GZqEmdi+uSaxxiY4nkBeC4iFqbygq0Om3WGk4hZCVLjdVvI2icq1kLweAq0gptqKV8GPhwRL0u6npYts7bX7lN+K7StW6gdkOL594j4cat4RvLuFml96sq6lE9nmbUjtbD6I7IXIgXFWwgGOETS3ulayMnAfwG7kSWKV5U1yX5sG4srp2Xb2cA/Kb27Q9IwSX/VzjSdaUHX7B2uiZgVlnsx1nZkLSj/FLgqDbuOwi0EQ9aq8tXAaLLWcH8dEVtTK71/InsT3R/bWO71wI8kbSZr4bVdEfF7SX8NPJxa/94IfJas5lHScnxdxMrltrPMukg6nfXliGjd9LpZr+XTWWZmVjbXRMzMrGyuiZiZWdmcRMzMrGxOImZmVjYnETMzK5uTiJmZle1/ANSn7SlfwVbqAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dhxpEQc5UANp",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 187
        },
        "outputId": "29b15ab6-0035-4c65-a16c-2bcf1ad837b4"
      },
      "source": [
        "number_of_roles = df.JobRole.value_counts()\n",
        "number_of_roles"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Sales Executive              223\n",
              "Research Scientist           209\n",
              "Laboratory Technician        183\n",
              "Manufacturing Director       105\n",
              "Healthcare Representative     85\n",
              "Manager                       79\n",
              "Research Director             59\n",
              "Sales Representative          57\n",
              "Human Resources               28\n",
              "Name: JobRole, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SXaa0tJDUDqL",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 248
        },
        "outputId": "a5fed51e-57f3-428f-ecd2-de10eff214c8"
      },
      "source": [
        "plt.pie(number_of_roles)\n",
        "plt.pie(number_of_roles, labels=number_of_roles)\n",
        "plt.pie(number_of_roles, labels=number_of_roles.index.tolist())\n",
        "plt.show()"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "STgx6PeoUN5w",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}