SofieYuningrumSafitri_205150409111017(Proyek_Akhir).ipynb

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  "metadata": {
    "colab": {
      "name": "SofieYuningrumSafitri_205150409111017(Proyek Akhir).ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/nanangyudi/2020pds_d/blob/main/SofieYuningrumSafitri_205150409111017(Proyek_Akhir).ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JmW1u-9auqIX"
      },
      "source": [
        "> **Deskripsi Tujuan Bisnis**\n",
        "\n",
        "Pengolahan data ini bertujuan untuk memprediksi perfomance karyawan\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xI2rU_CZwd8d"
      },
      "source": [
        "> **Analisa Pendekatan**\n",
        "\n",
        "Dalam analisis ini peneliti menggunakan metode EDA (Exploratory Data Analysis). EDA merupakan metode eksplorasi data dengan menggunakan teknik aritmatika sederhana dan teknik grafis dalam meringkas data pengamatan.\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4kUNgCUQwwPc"
      },
      "source": [
        "\n",
        "\n",
        "> **Pengumpulan Data**\n",
        "\n",
        "Dalam tahap pengumpulan data disini menggunakan dataset yang diambil dari https://www.kaggle.com/rhuebner/human-resources-data-set yang berjudul Human Resources Data Set, dengan ukuran file sebesar 75.06 KB\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gzPzZ8jwxQZ2"
      },
      "source": [
        "> **Pemahaman Terhadap Data Yang Telah Dikumpulkan**\n",
        "\n",
        "Dataset yang berjudul Human Resources Data Set ini berisikan data karyawan pada sebuah perusahaan. Data ini terdiri dari Employee Name, Employee ID, Married ID, Marital Status, Gender ID, EmpStatus ID, Department ID, PerfScore, From Diversity JobFair ID, Salary, TermD, Position ID, Position, State, ZIP, DOB, Sex, Marital Description, CitizenDesc, HispanicLatino, RaceDesc, DateofHire, TermReason, EmploymentStatus, Department, ManagerName, ManagerID, RecruitmentSource, PerformanceScore, EngagementSurvey, EmpSatisfaction, SpecialProjectsCount, LastPerformanceReview_Date, DaysLateLast30, Absences"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qm-jh-dMymki"
      },
      "source": [
        "\n",
        "\n",
        "> **Eksplorasi Data**\n",
        "\n",
        "Library yang digunakan dalam explorasi data adalah pandas, Matpolib, dan Seaborn"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jQfe4o7IzGvA"
      },
      "source": [
        "\n",
        "\n",
        "### **Eksplorasi Data**\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rfmhTFx6TqcR"
      },
      "source": [
        "**Import library yang akan digunakan menjalankan project ini**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "H_eF9RZZMqG8"
      },
      "source": [
        "import pandas as pd \n",
        "pd.set_option('display.max_columns', None)\n",
        "import numpy as np \n",
        "import re"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Xf7b2L5EUDkK"
      },
      "source": [
        "**Membaca data dari github dan simpan pada variable bernama data**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PXZSG2qeMXR0",
        "outputId": "908fed7c-0d89-4b92-a2ca-d367558e04e4"
      },
      "source": [
        "url = 'https://raw.githubusercontent.com/sofiesafitri/data/main/HRDataset_v14.csv'\n",
        "data = pd.read_csv(url, error_bad_lines=False)\n",
        "print(\"read dataset in dataframe!\")\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "read dataset in dataframe!\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "o2faQSkvUPjc"
      },
      "source": [
        "**Menampilkan data dari file**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 668
        },
        "id": "ZZzGGaX9QB1s",
        "outputId": "e9917d24-978b-4edb-cf24-f330cf9525bf"
      },
      "source": [
        "data.head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Employee_Name</th>\n",
              "      <th>EmpID</th>\n",
              "      <th>MarriedID</th>\n",
              "      <th>MaritalStatusID</th>\n",
              "      <th>GenderID</th>\n",
              "      <th>EmpStatusID</th>\n",
              "      <th>DeptID</th>\n",
              "      <th>PerfScoreID</th>\n",
              "      <th>FromDiversityJobFairID</th>\n",
              "      <th>Salary</th>\n",
              "      <th>Termd</th>\n",
              "      <th>PositionID</th>\n",
              "      <th>Position</th>\n",
              "      <th>State</th>\n",
              "      <th>Zip</th>\n",
              "      <th>DOB</th>\n",
              "      <th>Sex</th>\n",
              "      <th>MaritalDesc</th>\n",
              "      <th>CitizenDesc</th>\n",
              "      <th>HispanicLatino</th>\n",
              "      <th>RaceDesc</th>\n",
              "      <th>DateofHire</th>\n",
              "      <th>DateofTermination</th>\n",
              "      <th>TermReason</th>\n",
              "      <th>EmploymentStatus</th>\n",
              "      <th>Department</th>\n",
              "      <th>ManagerName</th>\n",
              "      <th>ManagerID</th>\n",
              "      <th>RecruitmentSource</th>\n",
              "      <th>PerformanceScore</th>\n",
              "      <th>EngagementSurvey</th>\n",
              "      <th>EmpSatisfaction</th>\n",
              "      <th>SpecialProjectsCount</th>\n",
              "      <th>LastPerformanceReview_Date</th>\n",
              "      <th>DaysLateLast30</th>\n",
              "      <th>Absences</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Adinolfi, Wilson  K</td>\n",
              "      <td>10026</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>62506</td>\n",
              "      <td>0</td>\n",
              "      <td>19</td>\n",
              "      <td>Production Technician I</td>\n",
              "      <td>MA</td>\n",
              "      <td>1960</td>\n",
              "      <td>07/10/83</td>\n",
              "      <td>M</td>\n",
              "      <td>Single</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>White</td>\n",
              "      <td>7/5/2011</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N/A-StillEmployed</td>\n",
              "      <td>Active</td>\n",
              "      <td>Production</td>\n",
              "      <td>Michael Albert</td>\n",
              "      <td>22.0</td>\n",
              "      <td>LinkedIn</td>\n",
              "      <td>Exceeds</td>\n",
              "      <td>4.60</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>1/17/2019</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Ait Sidi, Karthikeyan</td>\n",
              "      <td>10084</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>104437</td>\n",
              "      <td>1</td>\n",
              "      <td>27</td>\n",
              "      <td>Sr. DBA</td>\n",
              "      <td>MA</td>\n",
              "      <td>2148</td>\n",
              "      <td>05/05/75</td>\n",
              "      <td>M</td>\n",
              "      <td>Married</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>White</td>\n",
              "      <td>3/30/2015</td>\n",
              "      <td>6/16/2016</td>\n",
              "      <td>career change</td>\n",
              "      <td>Voluntarily Terminated</td>\n",
              "      <td>IT/IS</td>\n",
              "      <td>Simon Roup</td>\n",
              "      <td>4.0</td>\n",
              "      <td>Indeed</td>\n",
              "      <td>Fully Meets</td>\n",
              "      <td>4.96</td>\n",
              "      <td>3</td>\n",
              "      <td>6</td>\n",
              "      <td>2/24/2016</td>\n",
              "      <td>0</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Akinkuolie, Sarah</td>\n",
              "      <td>10196</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>64955</td>\n",
              "      <td>1</td>\n",
              "      <td>20</td>\n",
              "      <td>Production Technician II</td>\n",
              "      <td>MA</td>\n",
              "      <td>1810</td>\n",
              "      <td>09/19/88</td>\n",
              "      <td>F</td>\n",
              "      <td>Married</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>White</td>\n",
              "      <td>7/5/2011</td>\n",
              "      <td>9/24/2012</td>\n",
              "      <td>hours</td>\n",
              "      <td>Voluntarily Terminated</td>\n",
              "      <td>Production</td>\n",
              "      <td>Kissy Sullivan</td>\n",
              "      <td>20.0</td>\n",
              "      <td>LinkedIn</td>\n",
              "      <td>Fully Meets</td>\n",
              "      <td>3.02</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>5/15/2012</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Alagbe,Trina</td>\n",
              "      <td>10088</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>64991</td>\n",
              "      <td>0</td>\n",
              "      <td>19</td>\n",
              "      <td>Production Technician I</td>\n",
              "      <td>MA</td>\n",
              "      <td>1886</td>\n",
              "      <td>09/27/88</td>\n",
              "      <td>F</td>\n",
              "      <td>Married</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>White</td>\n",
              "      <td>1/7/2008</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N/A-StillEmployed</td>\n",
              "      <td>Active</td>\n",
              "      <td>Production</td>\n",
              "      <td>Elijiah Gray</td>\n",
              "      <td>16.0</td>\n",
              "      <td>Indeed</td>\n",
              "      <td>Fully Meets</td>\n",
              "      <td>4.84</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>1/3/2019</td>\n",
              "      <td>0</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Anderson, Carol</td>\n",
              "      <td>10069</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>50825</td>\n",
              "      <td>1</td>\n",
              "      <td>19</td>\n",
              "      <td>Production Technician I</td>\n",
              "      <td>MA</td>\n",
              "      <td>2169</td>\n",
              "      <td>09/08/89</td>\n",
              "      <td>F</td>\n",
              "      <td>Divorced</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>White</td>\n",
              "      <td>7/11/2011</td>\n",
              "      <td>9/6/2016</td>\n",
              "      <td>return to school</td>\n",
              "      <td>Voluntarily Terminated</td>\n",
              "      <td>Production</td>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "      <td>Google Search</td>\n",
              "      <td>Fully Meets</td>\n",
              "      <td>5.00</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>2/1/2016</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Anderson, Linda</td>\n",
              "      <td>10002</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>57568</td>\n",
              "      <td>0</td>\n",
              "      <td>19</td>\n",
              "      <td>Production Technician I</td>\n",
              "      <td>MA</td>\n",
              "      <td>1844</td>\n",
              "      <td>05/22/77</td>\n",
              "      <td>F</td>\n",
              "      <td>Single</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>White</td>\n",
              "      <td>1/9/2012</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N/A-StillEmployed</td>\n",
              "      <td>Active</td>\n",
              "      <td>Production</td>\n",
              "      <td>Amy Dunn</td>\n",
              "      <td>11.0</td>\n",
              "      <td>LinkedIn</td>\n",
              "      <td>Exceeds</td>\n",
              "      <td>5.00</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>1/7/2019</td>\n",
              "      <td>0</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Andreola, Colby</td>\n",
              "      <td>10194</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>95660</td>\n",
              "      <td>0</td>\n",
              "      <td>24</td>\n",
              "      <td>Software Engineer</td>\n",
              "      <td>MA</td>\n",
              "      <td>2110</td>\n",
              "      <td>05/24/79</td>\n",
              "      <td>F</td>\n",
              "      <td>Single</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>White</td>\n",
              "      <td>11/10/2014</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N/A-StillEmployed</td>\n",
              "      <td>Active</td>\n",
              "      <td>Software Engineering</td>\n",
              "      <td>Alex Sweetwater</td>\n",
              "      <td>10.0</td>\n",
              "      <td>LinkedIn</td>\n",
              "      <td>Fully Meets</td>\n",
              "      <td>3.04</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>1/2/2019</td>\n",
              "      <td>0</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Athwal, Sam</td>\n",
              "      <td>10062</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>59365</td>\n",
              "      <td>0</td>\n",
              "      <td>19</td>\n",
              "      <td>Production Technician I</td>\n",
              "      <td>MA</td>\n",
              "      <td>2199</td>\n",
              "      <td>02/18/83</td>\n",
              "      <td>M</td>\n",
              "      <td>Widowed</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>White</td>\n",
              "      <td>9/30/2013</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N/A-StillEmployed</td>\n",
              "      <td>Active</td>\n",
              "      <td>Production</td>\n",
              "      <td>Ketsia Liebig</td>\n",
              "      <td>19.0</td>\n",
              "      <td>Employee Referral</td>\n",
              "      <td>Fully Meets</td>\n",
              "      <td>5.00</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>2/25/2019</td>\n",
              "      <td>0</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Bachiochi, Linda</td>\n",
              "      <td>10114</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>47837</td>\n",
              "      <td>0</td>\n",
              "      <td>19</td>\n",
              "      <td>Production Technician I</td>\n",
              "      <td>MA</td>\n",
              "      <td>1902</td>\n",
              "      <td>02/11/70</td>\n",
              "      <td>F</td>\n",
              "      <td>Single</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>Black or African American</td>\n",
              "      <td>7/6/2009</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N/A-StillEmployed</td>\n",
              "      <td>Active</td>\n",
              "      <td>Production</td>\n",
              "      <td>Brannon Miller</td>\n",
              "      <td>12.0</td>\n",
              "      <td>Diversity Job Fair</td>\n",
              "      <td>Fully Meets</td>\n",
              "      <td>4.46</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>1/25/2019</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Bacong, Alejandro</td>\n",
              "      <td>10250</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>50178</td>\n",
              "      <td>0</td>\n",
              "      <td>14</td>\n",
              "      <td>IT Support</td>\n",
              "      <td>MA</td>\n",
              "      <td>1886</td>\n",
              "      <td>01/07/88</td>\n",
              "      <td>M</td>\n",
              "      <td>Divorced</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>White</td>\n",
              "      <td>1/5/2015</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N/A-StillEmployed</td>\n",
              "      <td>Active</td>\n",
              "      <td>IT/IS</td>\n",
              "      <td>Peter Monroe</td>\n",
              "      <td>7.0</td>\n",
              "      <td>Indeed</td>\n",
              "      <td>Fully Meets</td>\n",
              "      <td>5.00</td>\n",
              "      <td>5</td>\n",
              "      <td>6</td>\n",
              "      <td>2/18/2019</td>\n",
              "      <td>0</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              Employee_Name  EmpID  MarriedID  MaritalStatusID  GenderID  \\\n",
              "0       Adinolfi, Wilson  K  10026          0                0         1   \n",
              "1  Ait Sidi, Karthikeyan     10084          1                1         1   \n",
              "2         Akinkuolie, Sarah  10196          1                1         0   \n",
              "3              Alagbe,Trina  10088          1                1         0   \n",
              "4          Anderson, Carol   10069          0                2         0   \n",
              "5         Anderson, Linda    10002          0                0         0   \n",
              "6           Andreola, Colby  10194          0                0         0   \n",
              "7               Athwal, Sam  10062          0                4         1   \n",
              "8          Bachiochi, Linda  10114          0                0         0   \n",
              "9        Bacong, Alejandro   10250          0                2         1   \n",
              "\n",
              "   EmpStatusID  DeptID  PerfScoreID  FromDiversityJobFairID  Salary  Termd  \\\n",
              "0            1       5            4                       0   62506      0   \n",
              "1            5       3            3                       0  104437      1   \n",
              "2            5       5            3                       0   64955      1   \n",
              "3            1       5            3                       0   64991      0   \n",
              "4            5       5            3                       0   50825      1   \n",
              "5            1       5            4                       0   57568      0   \n",
              "6            1       4            3                       0   95660      0   \n",
              "7            1       5            3                       0   59365      0   \n",
              "8            3       5            3                       1   47837      0   \n",
              "9            1       3            3                       0   50178      0   \n",
              "\n",
              "   PositionID                  Position State   Zip       DOB Sex MaritalDesc  \\\n",
              "0          19   Production Technician I    MA  1960  07/10/83  M       Single   \n",
              "1          27                   Sr. DBA    MA  2148  05/05/75  M      Married   \n",
              "2          20  Production Technician II    MA  1810  09/19/88   F     Married   \n",
              "3          19   Production Technician I    MA  1886  09/27/88   F     Married   \n",
              "4          19   Production Technician I    MA  2169  09/08/89   F    Divorced   \n",
              "5          19   Production Technician I    MA  1844  05/22/77   F      Single   \n",
              "6          24         Software Engineer    MA  2110  05/24/79   F      Single   \n",
              "7          19   Production Technician I    MA  2199  02/18/83  M      Widowed   \n",
              "8          19   Production Technician I    MA  1902  02/11/70   F      Single   \n",
              "9          14                IT Support    MA  1886  01/07/88  M     Divorced   \n",
              "\n",
              "  CitizenDesc HispanicLatino                   RaceDesc  DateofHire  \\\n",
              "0  US Citizen             No                      White    7/5/2011   \n",
              "1  US Citizen             No                      White   3/30/2015   \n",
              "2  US Citizen             No                      White    7/5/2011   \n",
              "3  US Citizen             No                      White    1/7/2008   \n",
              "4  US Citizen             No                      White   7/11/2011   \n",
              "5  US Citizen             No                      White    1/9/2012   \n",
              "6  US Citizen             No                      White  11/10/2014   \n",
              "7  US Citizen             No                      White   9/30/2013   \n",
              "8  US Citizen             No  Black or African American    7/6/2009   \n",
              "9  US Citizen             No                      White    1/5/2015   \n",
              "\n",
              "  DateofTermination         TermReason        EmploymentStatus  \\\n",
              "0               NaN  N/A-StillEmployed                  Active   \n",
              "1         6/16/2016      career change  Voluntarily Terminated   \n",
              "2         9/24/2012              hours  Voluntarily Terminated   \n",
              "3               NaN  N/A-StillEmployed                  Active   \n",
              "4          9/6/2016   return to school  Voluntarily Terminated   \n",
              "5               NaN  N/A-StillEmployed                  Active   \n",
              "6               NaN  N/A-StillEmployed                  Active   \n",
              "7               NaN  N/A-StillEmployed                  Active   \n",
              "8               NaN  N/A-StillEmployed                  Active   \n",
              "9               NaN  N/A-StillEmployed                  Active   \n",
              "\n",
              "             Department      ManagerName  ManagerID   RecruitmentSource  \\\n",
              "0     Production          Michael Albert       22.0            LinkedIn   \n",
              "1                 IT/IS       Simon Roup        4.0              Indeed   \n",
              "2     Production          Kissy Sullivan       20.0            LinkedIn   \n",
              "3     Production            Elijiah Gray       16.0              Indeed   \n",
              "4     Production          Webster Butler       39.0       Google Search   \n",
              "5     Production                Amy Dunn       11.0            LinkedIn   \n",
              "6  Software Engineering  Alex Sweetwater       10.0            LinkedIn   \n",
              "7     Production           Ketsia Liebig       19.0   Employee Referral   \n",
              "8     Production          Brannon Miller       12.0  Diversity Job Fair   \n",
              "9                 IT/IS     Peter Monroe        7.0              Indeed   \n",
              "\n",
              "  PerformanceScore  EngagementSurvey  EmpSatisfaction  SpecialProjectsCount  \\\n",
              "0          Exceeds              4.60                5                     0   \n",
              "1      Fully Meets              4.96                3                     6   \n",
              "2      Fully Meets              3.02                3                     0   \n",
              "3      Fully Meets              4.84                5                     0   \n",
              "4      Fully Meets              5.00                4                     0   \n",
              "5          Exceeds              5.00                5                     0   \n",
              "6      Fully Meets              3.04                3                     4   \n",
              "7      Fully Meets              5.00                4                     0   \n",
              "8      Fully Meets              4.46                3                     0   \n",
              "9      Fully Meets              5.00                5                     6   \n",
              "\n",
              "  LastPerformanceReview_Date  DaysLateLast30  Absences  \n",
              "0                  1/17/2019               0         1  \n",
              "1                  2/24/2016               0        17  \n",
              "2                  5/15/2012               0         3  \n",
              "3                   1/3/2019               0        15  \n",
              "4                   2/1/2016               0         2  \n",
              "5                   1/7/2019               0        15  \n",
              "6                   1/2/2019               0        19  \n",
              "7                  2/25/2019               0        19  \n",
              "8                  1/25/2019               0         4  \n",
              "9                  2/18/2019               0        16  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7cp3GHJzOs56"
      },
      "source": [
        "**Mendeskipsikan data dari file. Terdiri dari count,mean,std,min,25%,50%,75%, dan max**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "BKTnSKm7OlpG",
        "outputId": "5887ab75-b7ad-4ad1-84f9-fe7da029fce8"
      },
      "source": [
        "data.describe()"
      ],
      "execution_count": null,
      "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>EmpID</th>\n",
              "      <th>MarriedID</th>\n",
              "      <th>MaritalStatusID</th>\n",
              "      <th>GenderID</th>\n",
              "      <th>EmpStatusID</th>\n",
              "      <th>DeptID</th>\n",
              "      <th>PerfScoreID</th>\n",
              "      <th>FromDiversityJobFairID</th>\n",
              "      <th>Salary</th>\n",
              "      <th>Termd</th>\n",
              "      <th>PositionID</th>\n",
              "      <th>Zip</th>\n",
              "      <th>ManagerID</th>\n",
              "      <th>EngagementSurvey</th>\n",
              "      <th>EmpSatisfaction</th>\n",
              "      <th>SpecialProjectsCount</th>\n",
              "      <th>DaysLateLast30</th>\n",
              "      <th>Absences</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>311.000000</td>\n",
              "      <td>311.000000</td>\n",
              "      <td>311.000000</td>\n",
              "      <td>311.000000</td>\n",
              "      <td>311.000000</td>\n",
              "      <td>311.000000</td>\n",
              "      <td>311.000000</td>\n",
              "      <td>311.000000</td>\n",
              "      <td>311.000000</td>\n",
              "      <td>311.000000</td>\n",
              "      <td>311.000000</td>\n",
              "      <td>311.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>311.000000</td>\n",
              "      <td>311.000000</td>\n",
              "      <td>311.000000</td>\n",
              "      <td>311.000000</td>\n",
              "      <td>311.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>10156.000000</td>\n",
              "      <td>0.398714</td>\n",
              "      <td>0.810289</td>\n",
              "      <td>0.434084</td>\n",
              "      <td>2.392283</td>\n",
              "      <td>4.610932</td>\n",
              "      <td>2.977492</td>\n",
              "      <td>0.093248</td>\n",
              "      <td>69020.684887</td>\n",
              "      <td>0.334405</td>\n",
              "      <td>16.845659</td>\n",
              "      <td>6555.482315</td>\n",
              "      <td>14.570957</td>\n",
              "      <td>4.110000</td>\n",
              "      <td>3.890675</td>\n",
              "      <td>1.218650</td>\n",
              "      <td>0.414791</td>\n",
              "      <td>10.237942</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>89.922189</td>\n",
              "      <td>0.490423</td>\n",
              "      <td>0.943239</td>\n",
              "      <td>0.496435</td>\n",
              "      <td>1.794383</td>\n",
              "      <td>1.083487</td>\n",
              "      <td>0.587072</td>\n",
              "      <td>0.291248</td>\n",
              "      <td>25156.636930</td>\n",
              "      <td>0.472542</td>\n",
              "      <td>6.223419</td>\n",
              "      <td>16908.396884</td>\n",
              "      <td>8.078306</td>\n",
              "      <td>0.789938</td>\n",
              "      <td>0.909241</td>\n",
              "      <td>2.349421</td>\n",
              "      <td>1.294519</td>\n",
              "      <td>5.852596</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>10001.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>45046.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1013.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.120000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>10078.500000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>55501.500000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>1901.500000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>3.690000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>10156.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>62810.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>19.000000</td>\n",
              "      <td>2132.000000</td>\n",
              "      <td>15.000000</td>\n",
              "      <td>4.280000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>10.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>10233.500000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>72036.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>2355.000000</td>\n",
              "      <td>19.000000</td>\n",
              "      <td>4.700000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>15.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>10311.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>250000.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>30.000000</td>\n",
              "      <td>98052.000000</td>\n",
              "      <td>39.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>20.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              EmpID   MarriedID  MaritalStatusID    GenderID  EmpStatusID  \\\n",
              "count    311.000000  311.000000       311.000000  311.000000   311.000000   \n",
              "mean   10156.000000    0.398714         0.810289    0.434084     2.392283   \n",
              "std       89.922189    0.490423         0.943239    0.496435     1.794383   \n",
              "min    10001.000000    0.000000         0.000000    0.000000     1.000000   \n",
              "25%    10078.500000    0.000000         0.000000    0.000000     1.000000   \n",
              "50%    10156.000000    0.000000         1.000000    0.000000     1.000000   \n",
              "75%    10233.500000    1.000000         1.000000    1.000000     5.000000   \n",
              "max    10311.000000    1.000000         4.000000    1.000000     5.000000   \n",
              "\n",
              "           DeptID  PerfScoreID  FromDiversityJobFairID         Salary  \\\n",
              "count  311.000000   311.000000              311.000000     311.000000   \n",
              "mean     4.610932     2.977492                0.093248   69020.684887   \n",
              "std      1.083487     0.587072                0.291248   25156.636930   \n",
              "min      1.000000     1.000000                0.000000   45046.000000   \n",
              "25%      5.000000     3.000000                0.000000   55501.500000   \n",
              "50%      5.000000     3.000000                0.000000   62810.000000   \n",
              "75%      5.000000     3.000000                0.000000   72036.000000   \n",
              "max      6.000000     4.000000                1.000000  250000.000000   \n",
              "\n",
              "            Termd  PositionID           Zip   ManagerID  EngagementSurvey  \\\n",
              "count  311.000000  311.000000    311.000000  303.000000        311.000000   \n",
              "mean     0.334405   16.845659   6555.482315   14.570957          4.110000   \n",
              "std      0.472542    6.223419  16908.396884    8.078306          0.789938   \n",
              "min      0.000000    1.000000   1013.000000    1.000000          1.120000   \n",
              "25%      0.000000   18.000000   1901.500000   10.000000          3.690000   \n",
              "50%      0.000000   19.000000   2132.000000   15.000000          4.280000   \n",
              "75%      1.000000   20.000000   2355.000000   19.000000          4.700000   \n",
              "max      1.000000   30.000000  98052.000000   39.000000          5.000000   \n",
              "\n",
              "       EmpSatisfaction  SpecialProjectsCount  DaysLateLast30    Absences  \n",
              "count       311.000000            311.000000      311.000000  311.000000  \n",
              "mean          3.890675              1.218650        0.414791   10.237942  \n",
              "std           0.909241              2.349421        1.294519    5.852596  \n",
              "min           1.000000              0.000000        0.000000    1.000000  \n",
              "25%           3.000000              0.000000        0.000000    5.000000  \n",
              "50%           4.000000              0.000000        0.000000   10.000000  \n",
              "75%           5.000000              0.000000        0.000000   15.000000  \n",
              "max           5.000000              8.000000        6.000000   20.000000  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "80cu6zpWUU2R"
      },
      "source": [
        "**Menampilkan dimensi data**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-V7W3Q1XQV6e",
        "outputId": "4e68d049-a5cf-46e4-c8c0-111b33955d14"
      },
      "source": [
        "dimensi = data.shape\n",
        "print(f'Dimensi data sejumlah {dimensi[0]} data, dan terdiri dari {dimensi[1]} kolom')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Dimensi data sejumlah 311 data, dan terdiri dari 36 kolom\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hbloeI11Rogv"
      },
      "source": [
        "**Menampilkan jumlah karyawan dalam grafik berdasarkan jenis kelamin**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 284
        },
        "id": "-INl1BFWPsoH",
        "outputId": "c0018e0f-7143-431e-b7fa-3a4f1eec5310"
      },
      "source": [
        "data['Sex'].value_counts() \r\n",
        "data['Sex'].value_counts().plot(kind='bar')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fe756a322e8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        },
        {
          "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": "markdown",
      "metadata": {
        "id": "yfkMDRwQR3IB"
      },
      "source": [
        "Pada grafik ditampilkan jumlah perempuan(Female) lebih banyak daripada jumlah laki-laki (Male)\r\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "p1ffM8XwV2V_"
      },
      "source": [
        "**Menampilkan grafik pendapatan karyawan**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "GGf-0C1BTpmi",
        "outputId": "bd44b689-91d4-482f-87c0-08d0f3ac1ae4"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "fig=plt.figure()\n",
        "ax = fig.add_subplot(1,1,1)\n",
        "\n",
        "#Variable\n",
        "ax.hist(data['Salary'],bins = 10)\n",
        "#Labels and Title\n",
        "plt.title('Grafik Salary')\n",
        "plt.xlabel('Salary')\n",
        "plt.ylabel('Jumlah')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEWCAYAAAB8LwAVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAY8ElEQVR4nO3de7SddX3n8ffHIHgBBCSlGS4NsFLXAEsjPSLWS7Faq+ASnXEYaAfQOhNvzOjSrg7IGkWnzqD10npDYkXAQQSLVFrxQqmXUSsaNIaAIomGBUwgAeQi0CjwnT/2L7I5PCfZCdmXk/N+rbXXefbv+T37+e5fds7nPJf9PKkqJEma7jHjLkCSNJkMCElSJwNCktTJgJAkdTIgJEmdDAhJUicDQppBklckuSHJL5M8PcnVSY5o805L8n9GUMPZSf5y2OuRuhgQ2i4kOTbJFUnuSbKuTb8hSR7Fy74POKmqdq6qH1bVwVX19a2obZ8kFyW5NcmdSVYmedWjqEsaCQNCs16StwJ/A/wV8NvAXsDrgGcDO86wzLwBXvp3gKu3QYmfBm5or/dk4Hjglm3wujNKj/+/9aj4AdKsluRJwLuAN1TV31XV3dXzw6r606ra0PqdneSMJJcmuQd4fpKjkvwwyV1tV9Jpre9OSX4JzAN+lGR1a1+T5IUdNTw2yfltK6ErkJ4BnF1V91TV/a22L/Ut/7kkN7eti28mOXiG97p7kn9Msj7JL9r0Pn3zv57k3Um+DdwLvDXJldNe4y1JvrAlY6y5y4DQbPcsYCdgkF96fwK8G9gF+BZwD3ACsBtwFPD6JC+vqg1VtXNb5mlVdeBML5jk8cDfAxuAY6rqVx3dvgt8tO0G269j/peARcBvAT8AzpthdY8BPkVvS2Q/4D7gI9P6HA8sae/xQ8D+Sf7ttPnnzvR+pH4GhGa7PYFbq+r+jQ1JvpPkjiT3JXleX98vVNW3q+rBqvrXqvp6VV3Vnq8Azgf+YAvWvSvwZWA18OqqemCGfv8B+L/A/wB+nmR5kmdsnFlVZ7Utnw3AacDT2pbRw1TVbVV1UVXdW1V30wu76fWeXVVXty2VDcAFwH9q43IwsBD4xy14j5rDDAjNdrcBeybZYWNDVf1+Ve3W5vV/xm/oXzDJM5N8re2yuZPecYs9t2DdhwNPBU6vTVz1sqp+UVUnV9XB9I6PLAf+vh0nmJfk9CSrk9wFrGmLPaKOJE9IcmaS61vfbwK7TTuecsO0xc4B/qQdrD8euHDjbjdpcwwIzXb/Qm/3ztED9J3+S/wzwCXAvlX1JODjwJac9fRV4H8DlyfZa5AFqupWemdH/RtgD3q7vY4GXgg8id5f+MxQx1uBpwDPrKpdged19H3Ye6yq7wK/Ap7b1vXpQeqUwIDQLFdVdwDvBD6W5JVJdknymCSLgSduZvFdgNur6l+THEbvF+iWrv+99ILm8iSdWx9J3pPkkCQ7JNkFeD2wqqpuazVsoLe18wTgf22m3vuAO5LsAbxjwDLPpXes4tdV9a0Bl5EMCM1+7Zf0W4C/oHf66C3AmcB/B76ziUXfALwryd3A24ELt3L9/5Pegep/ar+4p3sCcDFwB/AzegeZX9bmnQtcD9wEXEPvgPZM/hp4PHBr6/flAUv8NHAIMPQv9mn7Em8YJG3f2plW64BDq+q6cdej2cMtCGn793rg+4aDttQOm+8iabZKsobeQeyXj7kUzULuYpIkdXIXkySp06zexbTnnnvWwoULx12GJM0qV1555a1VNX9z/WZ1QCxcuJBly5aNuwxJmlWSXD9IP3cxSZI6GRCSpE5DC4gk+7YLoV3TbtX4pta+R5LLklzXfu7e2pPkQ0lWJVmR5NBh1SZJ2rxhbkHcD7y1qg6id9XLNyY5CDgZuLyqFgGXt+cAL6F3TfxF9K5nf8YQa5MkbcbQAqKq1lbVD9r03cCPgb3pXbnynNbtHB76As/RwLntbmDfpXcZ4wXDqk+StGkjOQaRZCHwdOAKYK+qWttm3Uzv+vjQC4/+a9nf2NokSWMw9IBIsjNwEfDmqrqrf167ycoWfZU7yZIky5IsW79+/TasVJLUb6gBkeSx9MLhvKr6fGu+ZeOuo/ZzXWu/Cdi3b/F9WtvDVNXSqpqqqqn58zf7PQ9J0lYa5llMAT4J/LiqPtA36xLgxDZ9Ig/dbP4S4IR2NtPhwJ19u6IkSSM2zG9SP5vePXCvSrK8tb0NOB24MMlr6N0o5Zg271LgSGAVcC/w6iHWBsDCk7847FV0WnP6UWNZryRtiaEFRLu14Uz3931BR/8C3jiseiRJW8ZvUkuSOhkQkqROBoQkqZMBIUnqZEBIkjoZEJKkTgaEJKmTASFJ6mRASJI6GRCSpE4GhCSpkwEhSepkQEiSOhkQkqROBoQkqZMBIUnqZEBIkjoZEJKkTkMLiCRnJVmXZGVf2wVJlrfHmo33qk6yMMl9ffM+Pqy6JEmDGdo9qYGzgY8A525sqKr/uHE6yfuBO/v6r66qxUOsR5K0BYYWEFX1zSQLu+YlCXAM8IfDWr8k6dEZ1zGI5wK3VNV1fW37J/lhkm8kee5MCyZZkmRZkmXr168ffqWSNEeNKyCOA87ve74W2K+qng68BfhMkl27FqyqpVU1VVVT8+fPH0GpkjQ3jTwgkuwA/Dvggo1tVbWhqm5r01cCq4HfHXVtkqSHjGML4oXAT6rqxo0NSeYnmdemDwAWAT8bQ22SpGaYp7meD/wL8JQkNyZ5TZt1LA/fvQTwPGBFO+3174DXVdXtw6pNkrR5wzyL6bgZ2l/V0XYRcNGwapEkbTm/SS1J6mRASJI6GRCSpE4GhCSpkwEhSepkQEiSOhkQkqROBoQkqZMBIUnqZEBIkjoZEJKkTgaEJKmTASFJ6mRASJI6GRCSpE4GhCSpkwEhSeo0zFuOnpVkXZKVfW2nJbkpyfL2OLJv3ilJViW5NskfD6suSdJghrkFcTbw4o72D1bV4va4FCDJQfTuVX1wW+ZjSeYNsTZJ0mYMLSCq6pvA7QN2Pxr4bFVtqKqfA6uAw4ZVmyRp88ZxDOKkJCvaLqjdW9vewA19fW5sbY+QZEmSZUmWrV+/fti1StKcNeqAOAM4EFgMrAXev6UvUFVLq2qqqqbmz5+/reuTJDUjDYiquqWqHqiqB4FP8NBupJuAffu67tPaJEljMtKASLKg7+krgI1nOF0CHJtkpyT7A4uA742yNknSw+0wrBdOcj5wBLBnkhuBdwBHJFkMFLAGeC1AVV2d5ELgGuB+4I1V9cCwapMkbd7QAqKqjuto/uQm+r8bePew6pEkbRm/SS1J6mRASJI6GRCSpE4GhCSpkwEhSepkQEiSOhkQkqROBoQkqZMBIUnqZEBIkjoZEJKkTgaEJKmTASFJ6mRASJI6GRCSpE4GhCSpkwEhSeo0tIBIclaSdUlW9rX9VZKfJFmR5OIku7X2hUnuS7K8PT4+rLokSYMZ5hbE2cCLp7VdBhxSVU8Ffgqc0jdvdVUtbo/XDbEuSdIAhhYQVfVN4PZpbV+tqvvb0+8C+wxr/ZKkR2ecxyD+DPhS3/P9k/wwyTeSPHemhZIsSbIsybL169cPv0pJmqPGEhBJTgXuB85rTWuB/arq6cBbgM8k2bVr2apaWlVTVTU1f/780RQsSXPQyAMiyauAlwJ/WlUFUFUbquq2Nn0lsBr43VHXJkl6yEgDIsmLgb8AXlZV9/a1z08yr00fACwCfjbK2iRJD7fDsF44yfnAEcCeSW4E3kHvrKWdgMuSAHy3nbH0POBdSX4NPAi8rqpu73xhSdJIDC0gquq4juZPztD3IuCiYdUiSdpyfpNaktTJgJAkdRpoF1OS3wcW9vevqnOHVJMkaQJsNiCSfBo4EFgOPNCaCzAgJGk7NsgWxBRw0MbvLEiS5oZBjkGsBH572IVIkibLjFsQSf6B3q6kXYBrknwP2LBxflW9bPjlSZLGZVO7mN43siokSRNnxoCoqm+MshBJ0mTZ7DGIJIcn+X6SXyb5VZIHktw1iuIkSeMzyEHqjwDHAdcBjwf+M/DRYRYlSRq/gb5JXVWrgHlV9UBVfYpH3kpUkrSdGeR7EPcm2RFYnuS99G7u4yU6JGk7N8gv+uOBecBJwD3AvsC/H2ZRkqTx2+wWRFVd3ybvA9453HIkSZNiU1+Uu4reF+U6VdVTh1KRJGkibGoL4qUjq0KSNHE29UW56/ufJ9l1U/0lSduXQb4o99okNwMrgCvbY9kgL57krCTrkqzsa9sjyWVJrms/d2/tSfKhJKuSrEhy6Na9JUnStjDIWUx/DhxSVQurav/2OGDA1z+bR35n4mTg8qpaBFzengO8BFjUHkuAMwZchyRpCAYJiNXAvVvz4lX1TeD2ac1HA+e06XOAl/e1n1s93wV2S7Jga9YrSXr0BjmmcArwnSRX8PDLff+3rVznXlW1tk3fDOzVpvcGbujrd2NrW9vXRpIl9LYw2G+//bayBEnS5gwSEGcC/wxcBTy4LVdeVZVki+5UV1VLgaUAU1NT3uVOkoZkkIB4bFW9ZRuu85YkC6pqbduFtK6130TvW9ob7dPaJEljMMgxiC8lWZJkQTsDaY8kezyKdV4CnNimTwS+0Nd+Qjub6XDgzr5dUZKkERtkC+K49vOUvrYCNnsmU5LzgSOAPZPcCLwDOB24MMlrgOuBY1r3S4EjgVX0Doq/eoDaJElDMsi1mPbf2hevquNmmPWCjr4FvHFr1yVJ2rY2GxBJTuhqr6pzt305kqRJMcgupmf0TT+O3l//PwAMCEnajg2yi+m/9j9Pshvw2aFVJEmaCFtzZ7h7gK0+LiFJmh0GOQbxDzx0X4h5wEHAhcMsSpI0foMcg3gfDwXE/cD1VeUX2CRpO7epO8rdTS8YMm1WJdlA7yJ+p1bV5UOsT5I0Jpu6YdAuM81LMg84BDiv/ZQkbWe25iA1VfVAVf0I+PA2rkeSNCG2KiA2qqozt1UhkqTJ8qgCQpK0/TIgJEmdDAhJUicDQpLUyYCQJHUyICRJnQwISVKnQa7FtE0leQpwQV/TAcDbgd2A/wKsb+1vq6pLR1yeJKkZeUBU1bXAYvjNJTtuAi6mdw/qD1bV+0ZdkyTpkca9i+kFwOqqun7MdUiSphl3QBwLnN/3/KQkK5KclWT3rgWSLEmyLMmy9evXd3WRJG0DYwuIJDsCLwM+15rOAA6kt/tpLfD+ruWqamlVTVXV1Pz580dSqyTNRePcgngJ8IOqugWgqm5pV4l9EPgEcNgYa5OkOW+cAXEcfbuXkizom/cKYOXIK5Ik/cbIz2ICSPJE4I+A1/Y1vzfJYnp3sVszbZ4kacTGEhBVdQ/w5Gltx4+jFklSt3GfxSRJmlAGhCSpkwEhSepkQEiSOo3lIPVct/DkL45lvWtOP2os65U0O7kFIUnqZEBIkjoZEJKkTgaEJKmTASFJ6mRASJI6GRCSpE4GhCSpkwEhSepkQEiSOhkQkqROBoQkqdPYLtaXZA1wN/AAcH9VTSXZA7gAWEjvtqPHVNUvxlWjJM1l496CeH5VLa6qqfb8ZODyqloEXN6eS5LGYNwBMd3RwDlt+hzg5WOsRZLmtHEGRAFfTXJlkiWtba+qWtumbwb2mr5QkiVJliVZtn79+lHVKklzzjhvGPScqropyW8BlyX5Sf/MqqokNX2hqloKLAWYmpp6xHxJ0rYxti2Iqrqp/VwHXAwcBtySZAFA+7luXPVJ0lw3loBI8sQku2ycBl4ErAQuAU5s3U4EvjCO+iRJ49vFtBdwcZKNNXymqr6c5PvAhUleA1wPHDOm+iRpzhtLQFTVz4CndbTfBrxg9BVJkqabtNNcJUkTwoCQJHUyICRJnQwISVInA0KS1MmAkCR1MiAkSZ0MCElSJwNCktTJgJAkdTIgJEmdDAhJUicDQpLUaZx3lNOILTz5i2Nb95rTjxrbuiVtHbcgJEmdDAhJUicDQpLUaeQBkWTfJF9Lck2Sq5O8qbWfluSmJMvb48hR1yZJesg4DlLfD7y1qn6QZBfgyiSXtXkfrKr3jaEmSdI0Iw+IqloLrG3Tdyf5MbD3qOuQJG3aWI9BJFkIPB24ojWdlGRFkrOS7D62wiRJ4wuIJDsDFwFvrqq7gDOAA4HF9LYw3j/DckuSLEuybP369SOrV5LmmrEERJLH0guH86rq8wBVdUtVPVBVDwKfAA7rWraqllbVVFVNzZ8/f3RFS9IcM46zmAJ8EvhxVX2gr31BX7dXACtHXZsk6SHjOIvp2cDxwFVJlre2twHHJVkMFLAGeO0YapMkNeM4i+lbQDpmXTrqWiRJM/Ob1JKkTgaEJKmTASFJ6mRASJI6GRCSpE4GhCSpkwEhSepkQEiSOhkQkqROBoQkqZMBIUnqZEBIkjoZEJKkTuO43LfmoIUnf3Es611z+lFjWa+0PXALQpLUyYCQJHUyICRJnQwISVKniTtIneTFwN8A84C/rarTx1yStFXGdWB+nDwpYPsyUQGRZB7wUeCPgBuB7ye5pKquGW9lmq3m4i9paVuZqIAADgNWVdXPAJJ8FjgaMCAkzWgu/iEwiq21SQuIvYEb+p7fCDyzv0OSJcCS9vSXSa4dUi17ArcO6bW3J47TYObEOOU92+Rl5sRYPVp5z6Map98ZpNOkBcRmVdVSYOmw15NkWVVNDXs9s53jNBjHaXCO1WBGMU6TdhbTTcC+fc/3aW2SpBGbtID4PrAoyf5JdgSOBS4Zc02SNCdN1C6mqro/yUnAV+id5npWVV09pnKGvhtrO+E4DcZxGpxjNZjh72qvqmGvQ5I0C03aLiZJ0oQwICRJnbb7gEiyJslVSZYnWdba9khyWZLr2s/dW3uSfCjJqiQrkhza9zontv7XJTmxr/332uuvastm9O9yyyU5K8m6JCv72oY+LjOtY5LNMFanJbmpfa6WJzmyb94p7X1fm+SP+9pf3NpWJTm5r33/JFe09gvaCRok2ak9X9XmLxzNO946SfZN8rUk1yS5OsmbWrufqz6bGKfJ+0xV1Xb9ANYAe05rey9wcps+GXhPmz4S+BIQ4HDgita+B/Cz9nP3Nr17m/e91jdt2ZeM+z0POC7PAw4FVo5yXGZaxyQ/Zhir04A/7+h7EPAjYCdgf2A1vRMu5rXpA4AdW5+D2jIXAse26Y8Dr2/TbwA+3qaPBS4Y91hsZpwWAIe26V2An7bx8HM12DhN3Gdq7IM1gn+MNTwyIK4FFvT9Y13bps8EjpveDzgOOLOv/czWtgD4SV/7w/pN+gNYyMN/6Q19XGZax6Q/OsZqpv/MpwCn9D3/CvCs9vjK9H7tF92twA6t/Tf9Ni7bpndo/TLusdiCMfsCveuq+bkabJwm7jO13e9iAgr4apIr07tMB8BeVbW2Td8M7NWmuy71sfdm2m/saJ+tRjEuM61jNjqp7Ro5q2+XxpaO1ZOBO6rq/mntD3utNv/O1n/itV0XTweuwM/VjKaNE0zYZ2ouBMRzqupQ4CXAG5M8r39m9aLUc32nGcW4zPKxPwM4EFgMrAXeP95yJkeSnYGLgDdX1V398/xcPaRjnCbuM7XdB0RV3dR+rgMupnfF2FuSLABoP9e17jNd6mNT7ft0tM9WoxiXmdYxq1TVLVX1QFU9CHyC3ucKtnysbgN2S7LDtPaHvVab/6TWf2IleSy9X3rnVdXnW7Ofq2m6xmkSP1PbdUAkeWKSXTZOAy8CVtK7fMfGMyNOpLcPkNZ+Qju74nDgzrbZ+hXgRUl2b5t9L6K3T28tcFeSw9vZFCf0vdZsNIpxmWkds8rGX0bNK+h9rqD3/o5tZ4vsDyyid2C18zIy7a/drwGvbMtPH/eNY/VK4J9b/4nU/q0/Cfy4qj7QN8vPVZ+ZxmkiP1PjPkAz5IM/B9A7sv8j4Grg1Nb+ZOBy4Drgn4A9Wnvo3bBoNXAVMNX3Wn8GrGqPV/e1T7V/yNXAR5glBxGB8+ltxv6a3j7K14xiXGZaxyQ/ZhirT7exWNH+0y3o639qe9/X0ndWG72zdn7a5p067XP6vTaGnwN2au2Pa89XtfkHjHssNjNOz6G3a2cFsLw9jvRzNfA4TdxnykttSJI6bde7mCRJW8+AkCR1MiAkSZ0MCElSJwNCktTJgJA2I8mp7aqbK9pVNp+5ib5nJ3nlTPOl2WSibjkqTZokzwJeSu/qmxuS7Envypnb6vV3qIeumSNNFLcgpE1bANxaVRsAqurWqvp/Sd6e5PtJViZZuvG+BP1m6pPk60n+Or37k5ya5Oft0gsk2bX/uTROBoS0aV8F9k3y0yQfS/IHrf0jVfWMqjoEeDy9rYzpNtVnx6qaqqp3Al8HjmrtxwKfr6pfD+XdSFvAgJA2oap+CfwesARYD1yQ5FXA89sdua4C/hA4uGPxTfW5oG/6b4FXt+lXA5/atu9C2joeg5A2o6oeoPdX/tfbL/vXAk+ld+2gG5KcRu8aN7+R5HHAxzbR556+1/92koVJjgDmVdVKpAngFoS0CUmekmRRX9NiehdMA7i1XdO/66ylxw3Qp9+5wGdw60ETxC0IadN2Bj6cZDfgfnpXwVwC3EHvqqI307vs8sNU1R1JPrGpPtOcB/wlvSvHShPBq7lKE6B9d+Loqjp+3LVIG7kFIY1Zkg/TuyXukeOuRernFoQkqZMHqSVJnQwISVInA0KS1MmAkCR1MiAkSZ3+P5oWhmedoVg/AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BfTFPpp6Y-mZ"
      },
      "source": [
        "Pada grafik diatas diperoleh data berupa gaji karyawan kebanyakan sejumlah $50000 US Dollar"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Cc3nY5f_mkyf"
      },
      "source": [
        "**Tabel Pengelompokkan posisi pekerjaan dengan bagaimana cara direkrut**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Aps-Ebgplq3I",
        "outputId": "56aacd21-ba32-4300-9801-c8b2cad5fb25"
      },
      "source": [
        "dt= data.groupby(['Position','RecruitmentSource'])\n",
        "dt.size()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Position                  RecruitmentSource \n",
              "Accountant I              Diversity Job Fair    1\n",
              "                          Indeed                1\n",
              "                          Website               1\n",
              "Administrative Assistant  Diversity Job Fair    1\n",
              "                          Indeed                1\n",
              "                                               ..\n",
              "Sr. Accountant            Other                 1\n",
              "Sr. DBA                   Indeed                1\n",
              "                          LinkedIn              1\n",
              "Sr. Network Engineer      Employee Referral     3\n",
              "                          LinkedIn              2\n",
              "Length: 80, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6-E5R6womA1K"
      },
      "source": [
        "Tabel diatas ditunjukkan posisi pekerjaan dan darimana dia direkrut."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zFV6rTShWBrP"
      },
      "source": [
        "**Keragaman gender lintas departemen**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 551
        },
        "id": "Fx2LP_RdVzPx",
        "outputId": "4240396f-3bac-4d9b-a0b1-6feac36e10a3"
      },
      "source": [
        "import seaborn as sns\r\n",
        "plt.figure(figsize=(16,9))\r\n",
        "ax=sns.countplot(x=data['Department'],hue=data['Sex'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x648 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5M4TFP7dWKyH"
      },
      "source": [
        "Pada grafik ditampilkan penyebaran gender pada semua departemen.\r\n",
        "Kesimpulan yang dapat ditarik yaitu:\r\n",
        "Tidak ada laki-laki di kantor eksekutif dan tidak ada perempuan di departemen software engineering.\r\n",
        "Keragaman gender tidak dipertahankan di departemen produksi dan rekayasa perangkat lunak. (Jumlah perempuan hampir dua kali lipat jumlah laki-laki)\r\n",
        "\r\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ec-X9g1vny-D"
      },
      "source": [
        "**Corellation Mapping**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 364
        },
        "id": "WS35lqkfn8_a",
        "outputId": "20652671-6558-4007-9487-93b90141001d"
      },
      "source": [
        "\n",
        "dt = pd.DataFrame(data,columns=['Salary','SpecialProjectsCount','EmpSatisfaction','EngagementSurvey','DaysLateLast30','Absences'])\n",
        "\n",
        "corrMatrix = dt.corr()\n",
        "sns.heatmap(corrMatrix, annot=True)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2WZdHw4q5H-f"
      },
      "source": [
        "*0.00 - 0,199 = sangat rendah*\n",
        "\n",
        "*0,20 - 0,3999 = rendah*\n",
        "\n",
        "*0,40 - 0,5999 = sedang*\n",
        "\n",
        "*0,60 - 0,799 = kuat*\n",
        "\n",
        "*0,80 - 1,000 = sangat kuat*"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Mk7seypi0gpO"
      },
      "source": [
        "Dilihat dari Corelation Mapping diatas dapat disimpulkan bahwa yang mempunyai:\n",
        "\n",
        "Korelasi positif yaitu kolom \"SpecialProjectsCount\" dan \"Salary\".\n",
        "\n",
        "Korelasi negatif yaitu kolom \"EngagementSurvey\" dan \"DaysLateLast30\"\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7ZZ24vKfatHB"
      },
      "source": [
        "**Melihat keterkaitan antara citizen dengan gaji karyawan**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "7IP_xxMjZpKh",
        "outputId": "5b81ff8a-a8d3-4ad7-da1b-d7cf4ec9b9ee"
      },
      "source": [
        "#Plots in matplotlib reside within a figureobject, use plt.figure to create new figure\n",
        "fig=plt.figure()\n",
        "\n",
        "#Create one or more subplots usingadd_subplot, because you can'tcreate blank figure\n",
        "ax = fig.add_subplot(1,1,1)\n",
        "\n",
        "#Variable\n",
        "ax.scatter(data['CitizenDesc'],data['Salary'])\n",
        "\n",
        "#Labels and Tit\n",
        "plt.title('Citizen dan Salary')\n",
        "plt.xlabel('Citizen')\n",
        "plt.ylabel('Salary')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "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": "markdown",
      "metadata": {
        "id": "ubH8jf1CbGUA"
      },
      "source": [
        "Berdasarkan Scatterplot diatas menunjukkan bahwa karyawan dengan kewarganegaraan US(United States) Memiliki gaji yang cenderung tinggi."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LIkNV5hFpYLV"
      },
      "source": [
        "**Menampilkan Top 10 Karyawan dengan Gaji Tertinggi**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 379
        },
        "id": "vxxj-KgvoauI",
        "outputId": "9f5a01dd-f198-4be5-e470-259fc612e5c7"
      },
      "source": [
        "data[[\"Employee_Name\",\"Salary\"]].nlargest(10,\"Salary\").plot.bar(x=\"Employee_Name\",y=\"Salary\",width=0.4,)#'vertical', 'horizontal',color=color\n",
        "plt.title(\"Top 10 Employees With High Salary\",fontsize=20)\n",
        "plt.xlabel(\"Employee Name\",fontsize=15)\n",
        "plt.ylabel(\"Salary\",fontsize=15)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "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": "markdown",
      "metadata": {
        "id": "rqj8WSZbpvaO"
      },
      "source": [
        "Grafik diatas menunjukan 10 karyawan dengan gaji tertinggi"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HP_n7Pa4zV_d"
      },
      "source": [
        "\n",
        "\n",
        "### **Pemodelan Data**\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NFp8cMJnZN4R"
      },
      "source": [
        "Pada tahap ini dibuat model regresi linier sederhana untuk memprediksi kinerja karyawan"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qdBTQEZPYsnD"
      },
      "source": [
        "from sklearn.model_selection import train_test_split"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tc7C3ez3ZZQC",
        "outputId": "0a55e07d-23ca-4d0a-8dbe-6a277f3bc1e5"
      },
      "source": [
        "data[['EmpSatisfaction','Salary','SpecialProjectsCount','ManagerID']].isna().sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "EmpSatisfaction         0\n",
              "Salary                  0\n",
              "SpecialProjectsCount    0\n",
              "ManagerID               8\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CSDIzgl9bzXO"
      },
      "source": [
        "Terdapat 8 nilai yang hilang di kolom ManagerID"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 589
        },
        "id": "DNfigKUtb7Nv",
        "outputId": "20df886d-99f6-41e1-d292-6467c9e6b87d"
      },
      "source": [
        "data[data['ManagerID'].isna()]\r\n",
        "\r\n",
        "#the manager Webster Butler tidak memiliki ID yang ditetapkan kepadanya dala 8 instansi"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Employee_Name</th>\n",
              "      <th>EmpID</th>\n",
              "      <th>MarriedID</th>\n",
              "      <th>MaritalStatusID</th>\n",
              "      <th>GenderID</th>\n",
              "      <th>EmpStatusID</th>\n",
              "      <th>DeptID</th>\n",
              "      <th>PerfScoreID</th>\n",
              "      <th>FromDiversityJobFairID</th>\n",
              "      <th>Salary</th>\n",
              "      <th>Termd</th>\n",
              "      <th>PositionID</th>\n",
              "      <th>Position</th>\n",
              "      <th>State</th>\n",
              "      <th>Zip</th>\n",
              "      <th>DOB</th>\n",
              "      <th>Sex</th>\n",
              "      <th>MaritalDesc</th>\n",
              "      <th>CitizenDesc</th>\n",
              "      <th>HispanicLatino</th>\n",
              "      <th>RaceDesc</th>\n",
              "      <th>DateofHire</th>\n",
              "      <th>DateofTermination</th>\n",
              "      <th>TermReason</th>\n",
              "      <th>EmploymentStatus</th>\n",
              "      <th>Department</th>\n",
              "      <th>ManagerName</th>\n",
              "      <th>ManagerID</th>\n",
              "      <th>RecruitmentSource</th>\n",
              "      <th>PerformanceScore</th>\n",
              "      <th>EngagementSurvey</th>\n",
              "      <th>EmpSatisfaction</th>\n",
              "      <th>SpecialProjectsCount</th>\n",
              "      <th>LastPerformanceReview_Date</th>\n",
              "      <th>DaysLateLast30</th>\n",
              "      <th>Absences</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Becker, Scott</td>\n",
              "      <td>10277</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>53250</td>\n",
              "      <td>0</td>\n",
              "      <td>19</td>\n",
              "      <td>Production Technician I</td>\n",
              "      <td>MA</td>\n",
              "      <td>2452</td>\n",
              "      <td>04/06/79</td>\n",
              "      <td>M</td>\n",
              "      <td>Single</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>Asian</td>\n",
              "      <td>7/8/2013</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N/A-StillEmployed</td>\n",
              "      <td>Active</td>\n",
              "      <td>Production</td>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>NaN</td>\n",
              "      <td>LinkedIn</td>\n",
              "      <td>Fully Meets</td>\n",
              "      <td>4.20</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>1/11/2019</td>\n",
              "      <td>0</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>Buccheri, Joseph</td>\n",
              "      <td>10184</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>65288</td>\n",
              "      <td>0</td>\n",
              "      <td>20</td>\n",
              "      <td>Production Technician II</td>\n",
              "      <td>MA</td>\n",
              "      <td>1013</td>\n",
              "      <td>07/28/83</td>\n",
              "      <td>M</td>\n",
              "      <td>Single</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>White</td>\n",
              "      <td>9/29/2014</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N/A-StillEmployed</td>\n",
              "      <td>Active</td>\n",
              "      <td>Production</td>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Google Search</td>\n",
              "      <td>Fully Meets</td>\n",
              "      <td>3.19</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>2/1/2019</td>\n",
              "      <td>0</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>Chang, Donovan  E</td>\n",
              "      <td>10154</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>60380</td>\n",
              "      <td>0</td>\n",
              "      <td>19</td>\n",
              "      <td>Production Technician I</td>\n",
              "      <td>MA</td>\n",
              "      <td>1845</td>\n",
              "      <td>08/24/83</td>\n",
              "      <td>M</td>\n",
              "      <td>Single</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>White</td>\n",
              "      <td>7/8/2013</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N/A-StillEmployed</td>\n",
              "      <td>Active</td>\n",
              "      <td>Production</td>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>NaN</td>\n",
              "      <td>LinkedIn</td>\n",
              "      <td>Fully Meets</td>\n",
              "      <td>3.80</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>1/14/2019</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>88</th>\n",
              "      <td>Fancett, Nicole</td>\n",
              "      <td>10136</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>65902</td>\n",
              "      <td>0</td>\n",
              "      <td>20</td>\n",
              "      <td>Production Technician II</td>\n",
              "      <td>MA</td>\n",
              "      <td>2324</td>\n",
              "      <td>09/27/87</td>\n",
              "      <td>F</td>\n",
              "      <td>Single</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>Black or African American</td>\n",
              "      <td>2/17/2014</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N/A-StillEmployed</td>\n",
              "      <td>Active</td>\n",
              "      <td>Production</td>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>NaN</td>\n",
              "      <td>LinkedIn</td>\n",
              "      <td>Fully Meets</td>\n",
              "      <td>4.00</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>1/7/2019</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>135</th>\n",
              "      <td>Hutter, Rosalie</td>\n",
              "      <td>10214</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>64995</td>\n",
              "      <td>0</td>\n",
              "      <td>20</td>\n",
              "      <td>Production Technician II</td>\n",
              "      <td>MA</td>\n",
              "      <td>2351</td>\n",
              "      <td>05/07/92</td>\n",
              "      <td>F</td>\n",
              "      <td>Separated</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>White</td>\n",
              "      <td>6/5/2015</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N/A-StillEmployed</td>\n",
              "      <td>Active</td>\n",
              "      <td>Production</td>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Indeed</td>\n",
              "      <td>Fully Meets</td>\n",
              "      <td>4.50</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>2/14/2019</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>177</th>\n",
              "      <td>Manchester, Robyn</td>\n",
              "      <td>10077</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>62385</td>\n",
              "      <td>0</td>\n",
              "      <td>20</td>\n",
              "      <td>Production Technician II</td>\n",
              "      <td>MA</td>\n",
              "      <td>2324</td>\n",
              "      <td>08/25/76</td>\n",
              "      <td>F</td>\n",
              "      <td>Married</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>White</td>\n",
              "      <td>5/11/2016</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N/A-StillEmployed</td>\n",
              "      <td>Active</td>\n",
              "      <td>Production</td>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>NaN</td>\n",
              "      <td>LinkedIn</td>\n",
              "      <td>Fully Meets</td>\n",
              "      <td>5.00</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>1/21/2019</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>232</th>\n",
              "      <td>Rivera, Haley</td>\n",
              "      <td>10011</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>46738</td>\n",
              "      <td>0</td>\n",
              "      <td>19</td>\n",
              "      <td>Production Technician I</td>\n",
              "      <td>MA</td>\n",
              "      <td>2171</td>\n",
              "      <td>01/12/73</td>\n",
              "      <td>F</td>\n",
              "      <td>Married</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>Asian</td>\n",
              "      <td>11/28/2011</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N/A-StillEmployed</td>\n",
              "      <td>Active</td>\n",
              "      <td>Production</td>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Google Search</td>\n",
              "      <td>Exceeds</td>\n",
              "      <td>4.36</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>2/11/2019</td>\n",
              "      <td>0</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>251</th>\n",
              "      <td>Sewkumar, Nori</td>\n",
              "      <td>10071</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>50923</td>\n",
              "      <td>0</td>\n",
              "      <td>19</td>\n",
              "      <td>Production Technician I</td>\n",
              "      <td>MA</td>\n",
              "      <td>2191</td>\n",
              "      <td>03/10/75</td>\n",
              "      <td>F</td>\n",
              "      <td>Single</td>\n",
              "      <td>US Citizen</td>\n",
              "      <td>No</td>\n",
              "      <td>Asian</td>\n",
              "      <td>9/30/2013</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N/A-StillEmployed</td>\n",
              "      <td>Active</td>\n",
              "      <td>Production</td>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Google Search</td>\n",
              "      <td>Fully Meets</td>\n",
              "      <td>5.00</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>2/6/2019</td>\n",
              "      <td>0</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Employee_Name  EmpID  MarriedID  MaritalStatusID  GenderID  \\\n",
              "19        Becker, Scott  10277          0                0         1   \n",
              "30   Buccheri, Joseph    10184          0                0         1   \n",
              "44    Chang, Donovan  E  10154          0                0         1   \n",
              "88      Fancett, Nicole  10136          0                0         0   \n",
              "135     Hutter, Rosalie  10214          0                3         0   \n",
              "177   Manchester, Robyn  10077          1                1         0   \n",
              "232     Rivera, Haley    10011          1                1         0   \n",
              "251      Sewkumar, Nori  10071          0                0         0   \n",
              "\n",
              "     EmpStatusID  DeptID  PerfScoreID  FromDiversityJobFairID  Salary  Termd  \\\n",
              "19             3       5            3                       0   53250      0   \n",
              "30             1       5            3                       0   65288      0   \n",
              "44             1       5            3                       0   60380      0   \n",
              "88             1       5            3                       0   65902      0   \n",
              "135            2       5            3                       0   64995      0   \n",
              "177            2       5            3                       0   62385      0   \n",
              "232            1       5            4                       0   46738      0   \n",
              "251            3       5            3                       0   50923      0   \n",
              "\n",
              "     PositionID                  Position State   Zip       DOB Sex  \\\n",
              "19           19   Production Technician I    MA  2452  04/06/79  M    \n",
              "30           20  Production Technician II    MA  1013  07/28/83  M    \n",
              "44           19   Production Technician I    MA  1845  08/24/83  M    \n",
              "88           20  Production Technician II    MA  2324  09/27/87   F   \n",
              "135          20  Production Technician II    MA  2351  05/07/92   F   \n",
              "177          20  Production Technician II    MA  2324  08/25/76   F   \n",
              "232          19   Production Technician I    MA  2171  01/12/73   F   \n",
              "251          19   Production Technician I    MA  2191  03/10/75   F   \n",
              "\n",
              "    MaritalDesc CitizenDesc HispanicLatino                   RaceDesc  \\\n",
              "19       Single  US Citizen             No                      Asian   \n",
              "30       Single  US Citizen             No                      White   \n",
              "44       Single  US Citizen             No                      White   \n",
              "88       Single  US Citizen             No  Black or African American   \n",
              "135   Separated  US Citizen             No                      White   \n",
              "177     Married  US Citizen             No                      White   \n",
              "232     Married  US Citizen             No                      Asian   \n",
              "251      Single  US Citizen             No                      Asian   \n",
              "\n",
              "     DateofHire DateofTermination         TermReason EmploymentStatus  \\\n",
              "19     7/8/2013               NaN  N/A-StillEmployed           Active   \n",
              "30    9/29/2014               NaN  N/A-StillEmployed           Active   \n",
              "44     7/8/2013               NaN  N/A-StillEmployed           Active   \n",
              "88    2/17/2014               NaN  N/A-StillEmployed           Active   \n",
              "135    6/5/2015               NaN  N/A-StillEmployed           Active   \n",
              "177   5/11/2016               NaN  N/A-StillEmployed           Active   \n",
              "232  11/28/2011               NaN  N/A-StillEmployed           Active   \n",
              "251   9/30/2013               NaN  N/A-StillEmployed           Active   \n",
              "\n",
              "            Department     ManagerName  ManagerID RecruitmentSource  \\\n",
              "19   Production         Webster Butler        NaN          LinkedIn   \n",
              "30   Production         Webster Butler        NaN     Google Search   \n",
              "44   Production         Webster Butler        NaN          LinkedIn   \n",
              "88   Production         Webster Butler        NaN          LinkedIn   \n",
              "135  Production         Webster Butler        NaN            Indeed   \n",
              "177  Production         Webster Butler        NaN          LinkedIn   \n",
              "232  Production         Webster Butler        NaN     Google Search   \n",
              "251  Production         Webster Butler        NaN     Google Search   \n",
              "\n",
              "    PerformanceScore  EngagementSurvey  EmpSatisfaction  SpecialProjectsCount  \\\n",
              "19       Fully Meets              4.20                4                     0   \n",
              "30       Fully Meets              3.19                3                     0   \n",
              "44       Fully Meets              3.80                5                     0   \n",
              "88       Fully Meets              4.00                4                     0   \n",
              "135      Fully Meets              4.50                3                     0   \n",
              "177      Fully Meets              5.00                3                     0   \n",
              "232          Exceeds              4.36                5                     0   \n",
              "251      Fully Meets              5.00                5                     0   \n",
              "\n",
              "    LastPerformanceReview_Date  DaysLateLast30  Absences  \n",
              "19                   1/11/2019               0        13  \n",
              "30                    2/1/2019               0         9  \n",
              "44                   1/14/2019               0         4  \n",
              "88                    1/7/2019               0         7  \n",
              "135                  2/14/2019               0         6  \n",
              "177                  1/21/2019               0         4  \n",
              "232                  2/11/2019               0        16  \n",
              "251                   2/6/2019               0        14  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oxJyeQM_cTPo"
      },
      "source": [
        "Pada data diatas ditunjukkan terdapat 8 data karyawan yang pada kolom ID Manager tidak memiliki nilai"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 700
        },
        "id": "aQSEekoDco9p",
        "outputId": "80dbff49-e648-4fe4-f9d8-2c1514248e4f"
      },
      "source": [
        "data[data['ManagerName']=='Webster Butler'][['ManagerName','ManagerID']]"
      ],
      "execution_count": null,
      "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",
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              "\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ManagerName</th>\n",
              "      <th>ManagerID</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>65</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>88</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>89</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>105</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>124</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>135</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>151</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>174</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>177</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>198</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>206</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>214</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>232</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>251</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>276</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>280</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>300</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        ManagerName  ManagerID\n",
              "4    Webster Butler       39.0\n",
              "19   Webster Butler        NaN\n",
              "30   Webster Butler        NaN\n",
              "44   Webster Butler        NaN\n",
              "65   Webster Butler       39.0\n",
              "88   Webster Butler        NaN\n",
              "89   Webster Butler       39.0\n",
              "105  Webster Butler       39.0\n",
              "124  Webster Butler       39.0\n",
              "135  Webster Butler        NaN\n",
              "151  Webster Butler       39.0\n",
              "174  Webster Butler       39.0\n",
              "177  Webster Butler        NaN\n",
              "198  Webster Butler       39.0\n",
              "206  Webster Butler       39.0\n",
              "214  Webster Butler       39.0\n",
              "232  Webster Butler        NaN\n",
              "251  Webster Butler        NaN\n",
              "276  Webster Butler       39.0\n",
              "280  Webster Butler       39.0\n",
              "300  Webster Butler       39.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pJ3clVdUdJ01"
      },
      "source": [
        "*    Sepertinya 8 baris tanpa ManagerID telah dibiarkan kosong secara tidak sengaja yang bermanager Webster Butler\r\n",
        "*    Webster Butler memiliki ID 39 yang telah ditetapkan"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c94hsAGCdj8Q"
      },
      "source": [
        "**Mengganti ID Manager karyawan yang memiliki manager Webster Butler yang masih tidak bernilai menjadi memiliki ID = 39**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 700
        },
        "id": "Q4IniKPxdbEX",
        "outputId": "3d61bfbb-be28-4bff-f2c1-d0a243e7fb8d"
      },
      "source": [
        "data['ManagerID'] = data['ManagerID'].replace(np.nan, 39.0)\r\n",
        "data[data['ManagerName']=='Webster Butler'][['ManagerName','ManagerID']]"
      ],
      "execution_count": null,
      "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>ManagerName</th>\n",
              "      <th>ManagerID</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>65</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>88</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>89</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>105</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>124</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>135</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>151</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>174</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>177</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>198</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>206</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>214</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>232</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>251</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>276</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>280</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>300</th>\n",
              "      <td>Webster Butler</td>\n",
              "      <td>39.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        ManagerName  ManagerID\n",
              "4    Webster Butler       39.0\n",
              "19   Webster Butler       39.0\n",
              "30   Webster Butler       39.0\n",
              "44   Webster Butler       39.0\n",
              "65   Webster Butler       39.0\n",
              "88   Webster Butler       39.0\n",
              "89   Webster Butler       39.0\n",
              "105  Webster Butler       39.0\n",
              "124  Webster Butler       39.0\n",
              "135  Webster Butler       39.0\n",
              "151  Webster Butler       39.0\n",
              "174  Webster Butler       39.0\n",
              "177  Webster Butler       39.0\n",
              "198  Webster Butler       39.0\n",
              "206  Webster Butler       39.0\n",
              "214  Webster Butler       39.0\n",
              "232  Webster Butler       39.0\n",
              "251  Webster Butler       39.0\n",
              "276  Webster Butler       39.0\n",
              "280  Webster Butler       39.0\n",
              "300  Webster Butler       39.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vHlQjI5ud9rD"
      },
      "source": [
        "Sekarang semua data telah memiliki ID Manager"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iB2bkhC3eXcx"
      },
      "source": [
        "X = data[['EmpSatisfaction','Salary','SpecialProjectsCount','ManagerID']]\r\n",
        "y = data['PerfScoreID']\r\n",
        "\r\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CTtvLva1efsj",
        "outputId": "645e7126-0e91-448c-add0-dcc82995f8bf"
      },
      "source": [
        "#fitting data yang telah dikoreksi\r\n",
        "lm.fit(X_train,y_train)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1TNfclOgeq7U"
      },
      "source": [
        "Sekarang semua data telah memiliki nilai"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rwB8uI6-env7"
      },
      "source": [
        "predictions = lm.predict(X_test)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xtqEjo78z9Fp"
      },
      "source": [
        "### **Evaluasi Model**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qc-cfVuGfLll"
      },
      "source": [
        "Pada tahap ini dilakukan evaluasi model dengan menghitung jumlah sisa kuadrat dan skor varians yang dijelaskan (R ^ 2)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9qLHgusGfAe4",
        "outputId": "a08488c4-ac7d-477c-fe44-f27f1dcb5a9d"
      },
      "source": [
        "from sklearn import metrics\r\n",
        "\r\n",
        "print('MAE:', metrics.mean_absolute_error(y_test, predictions))\r\n",
        "print('MSE:', metrics.mean_squared_error(y_test, predictions))\r\n",
        "print('RMSE:', np.sqrt(metrics.mean_squared_error(y_test, predictions)))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "MAE: 0.3092076768791097\n",
            "MSE: 0.2347468097647208\n",
            "RMSE: 0.4845067695757416\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Y1gzq7xgfUyE"
      },
      "source": [
        "**Residuals**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 333
        },
        "id": "AUxNrE8jfWtq",
        "outputId": "660b8422-3463-476a-ff2e-1825e69f6b24"
      },
      "source": [
        "sns.distplot((y_test-predictions),bins=50);"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "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": "markdown",
      "metadata": {
        "id": "p-0XDppDfd9Z"
      },
      "source": [
        "Pada diagram diatas ditampilkan data yang bersifat normal"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "id": "kGKxWIxWfoVb",
        "outputId": "796c80a7-5f14-4929-95d1-5c6c1154ccbd"
      },
      "source": [
        "coeffecients = pd.DataFrame(lm.coef_,X.columns)\r\n",
        "coeffecients.columns = ['Coeffecient']\r\n",
        "coeffecients"
      ],
      "execution_count": null,
      "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>Coeffecient</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>EmpSatisfaction</th>\n",
              "      <td>0.245674</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Salary</th>\n",
              "      <td>0.000002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SpecialProjectsCount</th>\n",
              "      <td>-0.010926</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ManagerID</th>\n",
              "      <td>-0.003805</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                      Coeffecient\n",
              "EmpSatisfaction          0.245674\n",
              "Salary                   0.000002\n",
              "SpecialProjectsCount    -0.010926\n",
              "ManagerID               -0.003805"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PoIv9n_sfyuH"
      },
      "source": [
        "* Peningkatan 1 unit dalam EmpSatisfaction dikaitkan dengan peningkatan perfomance score sebesar ~ 0,25 poin.\r\n",
        "* Peningkatan 1 unit dalam PayRate tidak dikaitkan dengan peningkatan perfomance score.\r\n",
        "* Peningkatan 1 unit di SpecialProjectsCount tidak terkait dengan peningkatan perfomance score.\r\n",
        "* ManagerID, seperti yang diduga, tidak mempengaruhi perfomance score. Karena tidak masuk akal bahwa ManagerID akan menyebabkan peningkatan skor kinerja"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VcFfAONOgWAT"
      },
      "source": [
        "> Kesimpulan :\r\n",
        "\r\n",
        "Kepuasan karyawan adalah faktor terpenting dalam memprediksi kinerja karyawan, dan keduanya berkorelasi positif, meskipun sedikit. Perusahaan mungkin tertarik untuk meningkatkan kinerja karyawan melalui peningkatan kepuasan menggunakan strategi yang diteliti, mungkin untuk meningkatkan kepuasan mereka yang mendapat skor 3,0 atau kurang pada survei Kepuasan Karyawan."
      ]
    }
  ]
}