Employee_EDA.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Kitsunnneee/EDA-Practice/blob/main/Employee_EDA.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "37W4c3aZrSV0",
        "outputId": "d1f1081b-cc3f-4c73-c089-7d9e6a24bf34"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "M-GgXicPrqKt",
        "outputId": "07822837-8cd1-4cbf-df6b-9a5135b7815d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Archive:  /content/drive/MyDrive/ML Practice/playground-series-s3e3.zip\n",
            "  inflating: sample_submission.csv   \n",
            "  inflating: test.csv                \n",
            "  inflating: train.csv               \n"
          ]
        }
      ],
      "source": [
        "!unzip '/content/drive/MyDrive/ML Practice/playground-series-s3e3.zip'"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lGr-GOe_r7K0",
        "outputId": "86461c8a-979a-47df-c498-111cc8d2ae73"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.8/dist-packages (1.3.5)\n",
            "Requirement already satisfied: numpy>=1.17.3 in /usr/local/lib/python3.8/dist-packages (from pandas) (1.21.6)\n",
            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas) (2022.7)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas) (2.8.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.8/dist-packages (from python-dateutil>=2.7.3->pandas) (1.15.0)\n"
          ]
        }
      ],
      "source": [
        "!pip install pandas"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ahfHQwlpsHju"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "data = pd.read_csv('/content/train.csv')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 352
        },
        "id": "FgSA7_PVsTCi",
        "outputId": "717c9e54-6aff-42c1-e204-989f97e76ebd"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "   id  Age     BusinessTravel  DailyRate              Department  \\\n",
              "0   0   36  Travel_Frequently        599  Research & Development   \n",
              "1   1   35      Travel_Rarely        921                   Sales   \n",
              "2   2   32      Travel_Rarely        718                   Sales   \n",
              "3   3   38      Travel_Rarely       1488  Research & Development   \n",
              "4   4   50      Travel_Rarely       1017  Research & Development   \n",
              "\n",
              "   DistanceFromHome  Education EducationField  EmployeeCount  \\\n",
              "0                24          3        Medical              1   \n",
              "1                 8          3          Other              1   \n",
              "2                26          3      Marketing              1   \n",
              "3                 2          3        Medical              1   \n",
              "4                 5          4        Medical              1   \n",
              "\n",
              "   EnvironmentSatisfaction  ... StandardHours  StockOptionLevel  \\\n",
              "0                        4  ...            80                 1   \n",
              "1                        1  ...            80                 1   \n",
              "2                        3  ...            80                 2   \n",
              "3                        3  ...            80                 0   \n",
              "4                        2  ...            80                 0   \n",
              "\n",
              "   TotalWorkingYears  TrainingTimesLastYear WorkLifeBalance  YearsAtCompany  \\\n",
              "0                 10                      2               3              10   \n",
              "1                  4                      3               3               4   \n",
              "2                  4                      3               3               3   \n",
              "3                 15                      1               1               6   \n",
              "4                 31                      0               3              31   \n",
              "\n",
              "  YearsInCurrentRole  YearsSinceLastPromotion  YearsWithCurrManager  Attrition  \n",
              "0                  0                        7                     8          0  \n",
              "1                  2                        0                     3          0  \n",
              "2                  2                        1                     2          0  \n",
              "3                  0                        0                     2          0  \n",
              "4                 14                        4                    10          1  \n",
              "\n",
              "[5 rows x 35 columns]"
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              "<p>5 rows × 35 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0273e28b-76ff-44d0-b57e-65ae5f85cbe0')\"\n",
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              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ],
      "source": [
        "data.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UpDi0d10sY4A",
        "outputId": "e223280d-2b17-40bf-9cd1-09ff3964a996"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1677, 35)"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ],
      "source": [
        "data.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KKdThyWWsudd",
        "outputId": "1b2178b0-0e9f-4404-9791-9b058eeae6d0"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: fastai in /usr/local/lib/python3.8/dist-packages (2.7.10)\n",
            "Requirement already satisfied: torch<1.14,>=1.7 in /usr/local/lib/python3.8/dist-packages (from fastai) (1.13.1+cu116)\n",
            "Requirement already satisfied: spacy<4 in /usr/local/lib/python3.8/dist-packages (from fastai) (3.4.4)\n",
            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.8/dist-packages (from fastai) (3.2.2)\n",
            "Requirement already satisfied: pip in /usr/local/lib/python3.8/dist-packages (from fastai) (22.0.4)\n",
            "Requirement already satisfied: fastdownload<2,>=0.0.5 in /usr/local/lib/python3.8/dist-packages (from fastai) (0.0.7)\n",
            "Requirement already satisfied: fastprogress>=0.2.4 in /usr/local/lib/python3.8/dist-packages (from fastai) (1.0.3)\n",
            "Requirement already satisfied: torchvision>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from fastai) (0.14.1+cu116)\n",
            "Requirement already satisfied: pyyaml in /usr/local/lib/python3.8/dist-packages (from fastai) (6.0)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.8/dist-packages (from fastai) (2.25.1)\n",
            "Requirement already satisfied: pillow>6.0.0 in /usr/local/lib/python3.8/dist-packages (from fastai) (7.1.2)\n",
            "Requirement already satisfied: fastcore<1.6,>=1.4.5 in /usr/local/lib/python3.8/dist-packages (from fastai) (1.5.27)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from fastai) (21.3)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from fastai) (1.7.3)\n",
            "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.8/dist-packages (from fastai) (1.0.2)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.8/dist-packages (from fastai) (1.3.5)\n",
            "Requirement already satisfied: pydantic!=1.8,!=1.8.1,<1.11.0,>=1.7.4 in /usr/local/lib/python3.8/dist-packages (from spacy<4->fastai) (1.10.4)\n",
            "Requirement already satisfied: wasabi<1.1.0,>=0.9.1 in /usr/local/lib/python3.8/dist-packages (from spacy<4->fastai) (0.10.1)\n",
            "Requirement already satisfied: spacy-legacy<3.1.0,>=3.0.10 in /usr/local/lib/python3.8/dist-packages (from spacy<4->fastai) (3.0.11)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.8/dist-packages (from spacy<4->fastai) (57.4.0)\n",
            "Requirement already satisfied: typer<0.8.0,>=0.3.0 in /usr/local/lib/python3.8/dist-packages (from spacy<4->fastai) (0.7.0)\n",
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            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas->fastai) (2022.7)\n",
            "Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.8/dist-packages (from scikit-learn->fastai) (1.2.0)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.8/dist-packages (from scikit-learn->fastai) (3.1.0)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.8/dist-packages (from python-dateutil>=2.1->matplotlib->fastai) (1.15.0)\n",
            "Requirement already satisfied: confection<1.0.0,>=0.0.1 in /usr/local/lib/python3.8/dist-packages (from thinc<8.2.0,>=8.1.0->spacy<4->fastai) (0.0.3)\n",
            "Requirement already satisfied: blis<0.8.0,>=0.7.8 in /usr/local/lib/python3.8/dist-packages (from thinc<8.2.0,>=8.1.0->spacy<4->fastai) (0.7.9)\n",
            "Requirement already satisfied: click<9.0.0,>=7.1.1 in /usr/local/lib/python3.8/dist-packages (from typer<0.8.0,>=0.3.0->spacy<4->fastai) (7.1.2)\n",
            "Requirement already satisfied: MarkupSafe>=0.23 in /usr/local/lib/python3.8/dist-packages (from jinja2->spacy<4->fastai) (2.0.1)\n"
          ]
        }
      ],
      "source": [
        "!pip install fastai"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Q6Kpzmo_sycm",
        "outputId": "20026ca0-e704-4981-e084-2048823553dc"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 1677 entries, 0 to 1676\n",
            "Data columns (total 35 columns):\n",
            " #   Column                    Non-Null Count  Dtype \n",
            "---  ------                    --------------  ----- \n",
            " 0   id                        1677 non-null   int64 \n",
            " 1   Age                       1677 non-null   int64 \n",
            " 2   BusinessTravel            1677 non-null   object\n",
            " 3   DailyRate                 1677 non-null   int64 \n",
            " 4   Department                1677 non-null   object\n",
            " 5   DistanceFromHome          1677 non-null   int64 \n",
            " 6   Education                 1677 non-null   int64 \n",
            " 7   EducationField            1677 non-null   object\n",
            " 8   EmployeeCount             1677 non-null   int64 \n",
            " 9   EnvironmentSatisfaction   1677 non-null   int64 \n",
            " 10  Gender                    1677 non-null   object\n",
            " 11  HourlyRate                1677 non-null   int64 \n",
            " 12  JobInvolvement            1677 non-null   int64 \n",
            " 13  JobLevel                  1677 non-null   int64 \n",
            " 14  JobRole                   1677 non-null   object\n",
            " 15  JobSatisfaction           1677 non-null   int64 \n",
            " 16  MaritalStatus             1677 non-null   object\n",
            " 17  MonthlyIncome             1677 non-null   int64 \n",
            " 18  MonthlyRate               1677 non-null   int64 \n",
            " 19  NumCompaniesWorked        1677 non-null   int64 \n",
            " 20  Over18                    1677 non-null   object\n",
            " 21  OverTime                  1677 non-null   object\n",
            " 22  PercentSalaryHike         1677 non-null   int64 \n",
            " 23  PerformanceRating         1677 non-null   int64 \n",
            " 24  RelationshipSatisfaction  1677 non-null   int64 \n",
            " 25  StandardHours             1677 non-null   int64 \n",
            " 26  StockOptionLevel          1677 non-null   int64 \n",
            " 27  TotalWorkingYears         1677 non-null   int64 \n",
            " 28  TrainingTimesLastYear     1677 non-null   int64 \n",
            " 29  WorkLifeBalance           1677 non-null   int64 \n",
            " 30  YearsAtCompany            1677 non-null   int64 \n",
            " 31  YearsInCurrentRole        1677 non-null   int64 \n",
            " 32  YearsSinceLastPromotion   1677 non-null   int64 \n",
            " 33  YearsWithCurrManager      1677 non-null   int64 \n",
            " 34  Attrition                 1677 non-null   int64 \n",
            "dtypes: int64(27), object(8)\n",
            "memory usage: 458.7+ KB\n"
          ]
        }
      ],
      "source": [
        "data.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "id": "XHNEtDrqtDbv",
        "outputId": "30eb8cb1-d4d8-49e5-8b20-5c4b4e178cdb"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                id          Age    DailyRate  DistanceFromHome    Education  \\\n",
              "count  1677.000000  1677.000000  1677.000000       1677.000000  1677.000000   \n",
              "mean    838.000000    36.036971   892.749553          8.683959     2.937984   \n",
              "std     484.252517     8.507112   374.496259          7.826143     1.039078   \n",
              "min       0.000000    18.000000   107.000000          1.000000     1.000000   \n",
              "25%     419.000000    30.000000   589.000000          2.000000     2.000000   \n",
              "50%     838.000000    35.000000   890.000000          7.000000     3.000000   \n",
              "75%    1257.000000    41.000000  1223.000000         12.000000     4.000000   \n",
              "max    1676.000000    60.000000  3921.000000         29.000000    15.000000   \n",
              "\n",
              "       EmployeeCount  EnvironmentSatisfaction   HourlyRate  JobInvolvement  \\\n",
              "count         1677.0              1677.000000  1677.000000     1677.000000   \n",
              "mean             1.0                 2.757901    67.798450        2.782349   \n",
              "std              0.0                 1.086835    19.435928        0.650664   \n",
              "min              1.0                 1.000000    30.000000        1.000000   \n",
              "25%              1.0                 2.000000    51.000000        2.000000   \n",
              "50%              1.0                 3.000000    69.000000        3.000000   \n",
              "75%              1.0                 4.000000    84.000000        3.000000   \n",
              "max              1.0                 4.000000   100.000000        4.000000   \n",
              "\n",
              "          JobLevel  ...  StandardHours  StockOptionLevel  TotalWorkingYears  \\\n",
              "count  1677.000000  ...         1677.0       1677.000000        1677.000000   \n",
              "mean      1.998807  ...           80.0          0.721527          10.709600   \n",
              "std       1.083065  ...            0.0          0.771259           7.255135   \n",
              "min       1.000000  ...           80.0          0.000000           0.000000   \n",
              "25%       1.000000  ...           80.0          0.000000           6.000000   \n",
              "50%       2.000000  ...           80.0          1.000000           9.000000   \n",
              "75%       2.000000  ...           80.0          1.000000          14.000000   \n",
              "max       7.000000  ...           80.0          3.000000          41.000000   \n",
              "\n",
              "       TrainingTimesLastYear  WorkLifeBalance  YearsAtCompany  \\\n",
              "count            1677.000000      1677.000000     1677.000000   \n",
              "mean                2.732856         2.769827        6.806798   \n",
              "std                 1.145271         0.647721        5.883282   \n",
              "min                 0.000000         1.000000        0.000000   \n",
              "25%                 2.000000         2.000000        3.000000   \n",
              "50%                 3.000000         3.000000        5.000000   \n",
              "75%                 3.000000         3.000000        9.000000   \n",
              "max                 6.000000         4.000000       41.000000   \n",
              "\n",
              "       YearsInCurrentRole  YearsSinceLastPromotion  YearsWithCurrManager  \\\n",
              "count         1677.000000              1677.000000           1677.000000   \n",
              "mean             4.144305                 1.978533              4.186643   \n",
              "std              3.583398                 3.045716              3.576189   \n",
              "min              0.000000                 0.000000              0.000000   \n",
              "25%              2.000000                 0.000000              2.000000   \n",
              "50%              3.000000                 1.000000              3.000000   \n",
              "75%              7.000000                 2.000000              7.000000   \n",
              "max             18.000000                15.000000             17.000000   \n",
              "\n",
              "         Attrition  \n",
              "count  1677.000000  \n",
              "mean      0.119261  \n",
              "std       0.324192  \n",
              "min       0.000000  \n",
              "25%       0.000000  \n",
              "50%       0.000000  \n",
              "75%       0.000000  \n",
              "max       1.000000  \n",
              "\n",
              "[8 rows x 27 columns]"
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              "      <th>id</th>\n",
              "      <th>Age</th>\n",
              "      <th>DailyRate</th>\n",
              "      <th>DistanceFromHome</th>\n",
              "      <th>Education</th>\n",
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              "      <th>JobInvolvement</th>\n",
              "      <th>JobLevel</th>\n",
              "      <th>...</th>\n",
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              "      <th>YearsSinceLastPromotion</th>\n",
              "      <th>YearsWithCurrManager</th>\n",
              "      <th>Attrition</th>\n",
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              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1677.000000</td>\n",
              "      <td>1677.000000</td>\n",
              "      <td>1677.000000</td>\n",
              "      <td>1677.000000</td>\n",
              "      <td>1677.000000</td>\n",
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              "      <td>1677.000000</td>\n",
              "      <td>1677.000000</td>\n",
              "      <td>1677.000000</td>\n",
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              "      <td>1677.000000</td>\n",
              "      <td>1677.000000</td>\n",
              "      <td>1677.000000</td>\n",
              "      <td>1677.000000</td>\n",
              "      <td>1677.000000</td>\n",
              "      <td>1677.000000</td>\n",
              "      <td>1677.000000</td>\n",
              "      <td>1677.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>838.000000</td>\n",
              "      <td>36.036971</td>\n",
              "      <td>892.749553</td>\n",
              "      <td>8.683959</td>\n",
              "      <td>2.937984</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.757901</td>\n",
              "      <td>67.798450</td>\n",
              "      <td>2.782349</td>\n",
              "      <td>1.998807</td>\n",
              "      <td>...</td>\n",
              "      <td>80.0</td>\n",
              "      <td>0.721527</td>\n",
              "      <td>10.709600</td>\n",
              "      <td>2.732856</td>\n",
              "      <td>2.769827</td>\n",
              "      <td>6.806798</td>\n",
              "      <td>4.144305</td>\n",
              "      <td>1.978533</td>\n",
              "      <td>4.186643</td>\n",
              "      <td>0.119261</td>\n",
              "    </tr>\n",
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              "      <th>std</th>\n",
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              "      <td>8.507112</td>\n",
              "      <td>374.496259</td>\n",
              "      <td>7.826143</td>\n",
              "      <td>1.039078</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.086835</td>\n",
              "      <td>19.435928</td>\n",
              "      <td>0.650664</td>\n",
              "      <td>1.083065</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.771259</td>\n",
              "      <td>7.255135</td>\n",
              "      <td>1.145271</td>\n",
              "      <td>0.647721</td>\n",
              "      <td>5.883282</td>\n",
              "      <td>3.583398</td>\n",
              "      <td>3.045716</td>\n",
              "      <td>3.576189</td>\n",
              "      <td>0.324192</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
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              "      <td>18.000000</td>\n",
              "      <td>107.000000</td>\n",
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              "      <td>1.000000</td>\n",
              "      <td>1.0</td>\n",
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              "      <td>30.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
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              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>419.000000</td>\n",
              "      <td>30.000000</td>\n",
              "      <td>589.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>51.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>80.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>6.000000</td>\n",
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              "      <td>2.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>2.000000</td>\n",
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              "      <td>2.000000</td>\n",
              "      <td>0.000000</td>\n",
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              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>838.000000</td>\n",
              "      <td>35.000000</td>\n",
              "      <td>890.000000</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>69.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>80.0</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>3.000000</td>\n",
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              "      <td>0.000000</td>\n",
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              "    <tr>\n",
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              "      <td>41.000000</td>\n",
              "      <td>1223.000000</td>\n",
              "      <td>12.000000</td>\n",
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              "      <td>4.000000</td>\n",
              "      <td>84.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>2.000000</td>\n",
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              "      <td>1.000000</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>2.000000</td>\n",
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              "      <td>60.000000</td>\n",
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              "      <td>15.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>7.000000</td>\n",
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              "      <td>80.0</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>41.000000</td>\n",
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              "      <td>4.000000</td>\n",
              "      <td>41.000000</td>\n",
              "      <td>18.000000</td>\n",
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              "      <td>17.000000</td>\n",
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              "<p>8 rows × 27 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5a66aa2d-17e7-4943-8110-f81bef85ac9c')\"\n",
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              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-5a66aa2d-17e7-4943-8110-f81bef85ac9c button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5a66aa2d-17e7-4943-8110-f81bef85ac9c');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ],
      "source": [
        "data.describe()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Jbr3liwjtezC",
        "outputId": "ee2659e5-0b59-4518-bc82-3342974f573c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The number of numerical data is 27\n"
          ]
        }
      ],
      "source": [
        "numerical = [feature for feature in data.columns if data[feature].dtypes!='O']\n",
        "\n",
        "print(f\"The number of numerical data is {len(numerical)}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "id": "kB7JDm8vupyk",
        "outputId": "6feb796e-dd4f-4a33-e0b7-5aeaef0afd58"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   id  Age  DailyRate  DistanceFromHome  Education  EmployeeCount  \\\n",
              "0   0   36        599                24          3              1   \n",
              "1   1   35        921                 8          3              1   \n",
              "2   2   32        718                26          3              1   \n",
              "3   3   38       1488                 2          3              1   \n",
              "4   4   50       1017                 5          4              1   \n",
              "\n",
              "   EnvironmentSatisfaction  HourlyRate  JobInvolvement  JobLevel  ...  \\\n",
              "0                        4          42               3         1  ...   \n",
              "1                        1          46               3         1  ...   \n",
              "2                        3          80               3         2  ...   \n",
              "3                        3          40               3         2  ...   \n",
              "4                        2          37               3         5  ...   \n",
              "\n",
              "   StandardHours  StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  \\\n",
              "0             80                 1                 10                      2   \n",
              "1             80                 1                  4                      3   \n",
              "2             80                 2                  4                      3   \n",
              "3             80                 0                 15                      1   \n",
              "4             80                 0                 31                      0   \n",
              "\n",
              "   WorkLifeBalance  YearsAtCompany  YearsInCurrentRole  \\\n",
              "0                3              10                   0   \n",
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              "2                3               3                   2   \n",
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              "4                3              31                  14   \n",
              "\n",
              "   YearsSinceLastPromotion  YearsWithCurrManager  Attrition  \n",
              "0                        7                     8          0  \n",
              "1                        0                     3          0  \n",
              "2                        1                     2          0  \n",
              "3                        0                     2          0  \n",
              "4                        4                    10          1  \n",
              "\n",
              "[5 rows x 27 columns]"
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              "<p>5 rows × 27 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d094aa54-0395-446c-9add-2d52c4853ed6')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "  </svg>\n",
              "      </button>\n",
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              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
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              "      border-radius: 50%;\n",
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              "      display: none;\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-d094aa54-0395-446c-9add-2d52c4853ed6 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-d094aa54-0395-446c-9add-2d52c4853ed6');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ],
      "source": [
        "data[numerical].head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1Mr9M7bJu2oo",
        "outputId": "66a5ab5c-7c89-4a58-fd6e-9a5ad4759c0d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.8/dist-packages (3.2.2)\n",
            "Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.8/dist-packages (from matplotlib) (2.8.2)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.8/dist-packages (from matplotlib) (0.11.0)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.8/dist-packages (from matplotlib) (1.4.4)\n",
            "Requirement already satisfied: numpy>=1.11 in /usr/local/lib/python3.8/dist-packages (from matplotlib) (1.21.6)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.8/dist-packages (from matplotlib) (3.0.9)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.8/dist-packages (from python-dateutil>=2.1->matplotlib) (1.15.0)\n"
          ]
        }
      ],
      "source": [
        "!pip install matplotlib"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "tYg6uGyQxnZ-"
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "dL0ZzYnwxw5_"
      },
      "outputs": [],
      "source": [
        "   cat_var = [num for num in numerical if data[num].nunique() < 20]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "STFthNI_zKCh",
        "outputId": "7e60c629-e2e8-48fc-ebed-a8444c1f4bb2"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Education',\n",
              " 'EmployeeCount',\n",
              " 'EnvironmentSatisfaction',\n",
              " 'JobInvolvement',\n",
              " 'JobLevel',\n",
              " 'JobSatisfaction',\n",
              " 'NumCompaniesWorked',\n",
              " 'PercentSalaryHike',\n",
              " 'PerformanceRating',\n",
              " 'RelationshipSatisfaction',\n",
              " 'StandardHours',\n",
              " 'StockOptionLevel',\n",
              " 'TrainingTimesLastYear',\n",
              " 'WorkLifeBalance',\n",
              " 'YearsInCurrentRole',\n",
              " 'YearsSinceLastPromotion',\n",
              " 'YearsWithCurrManager',\n",
              " 'Attrition']"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ],
      "source": [
        "cat_var"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 270
        },
        "id": "djliDqms1jAD",
        "outputId": "74618d92-2a04-41fd-8aca-38239fe28e19"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Education  EmployeeCount  EnvironmentSatisfaction  JobInvolvement  \\\n",
              "0          3              1                        4               3   \n",
              "1          3              1                        1               3   \n",
              "2          3              1                        3               3   \n",
              "3          3              1                        3               3   \n",
              "4          4              1                        2               3   \n",
              "\n",
              "   JobLevel  JobSatisfaction  NumCompaniesWorked  PercentSalaryHike  \\\n",
              "0         1                4                   1                 13   \n",
              "1         1                1                   1                 17   \n",
              "2         2                4                   0                 17   \n",
              "3         2                1                   3                 14   \n",
              "4         5                1                   1                 13   \n",
              "\n",
              "   PerformanceRating  RelationshipSatisfaction  StandardHours  \\\n",
              "0                  3                         2             80   \n",
              "1                  3                         4             80   \n",
              "2                  3                         4             80   \n",
              "3                  3                         3             80   \n",
              "4                  3                         3             80   \n",
              "\n",
              "   StockOptionLevel  TrainingTimesLastYear  WorkLifeBalance  \\\n",
              "0                 1                      2                3   \n",
              "1                 1                      3                3   \n",
              "2                 2                      3                3   \n",
              "3                 0                      1                1   \n",
              "4                 0                      0                3   \n",
              "\n",
              "   YearsInCurrentRole  YearsSinceLastPromotion  YearsWithCurrManager  \\\n",
              "0                   0                        7                     8   \n",
              "1                   2                        0                     3   \n",
              "2                   2                        1                     2   \n",
              "3                   0                        0                     2   \n",
              "4                  14                        4                    10   \n",
              "\n",
              "   Attrition  \n",
              "0          0  \n",
              "1          0  \n",
              "2          0  \n",
              "3          0  \n",
              "4          1  "
            ],
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              "      <th>JobSatisfaction</th>\n",
              "      <th>NumCompaniesWorked</th>\n",
              "      <th>PercentSalaryHike</th>\n",
              "      <th>PerformanceRating</th>\n",
              "      <th>RelationshipSatisfaction</th>\n",
              "      <th>StandardHours</th>\n",
              "      <th>StockOptionLevel</th>\n",
              "      <th>TrainingTimesLastYear</th>\n",
              "      <th>WorkLifeBalance</th>\n",
              "      <th>YearsInCurrentRole</th>\n",
              "      <th>YearsSinceLastPromotion</th>\n",
              "      <th>YearsWithCurrManager</th>\n",
              "      <th>Attrition</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>13</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>8</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>17</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>17</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>80</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>14</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>80</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>13</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>80</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>14</td>\n",
              "      <td>4</td>\n",
              "      <td>10</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d9eb6896-6823-4907-8190-6e5e92b52a0c')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-d9eb6896-6823-4907-8190-6e5e92b52a0c button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-d9eb6896-6823-4907-8190-6e5e92b52a0c');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ],
      "source": [
        "data[cat_var].head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "50G9CFa42JxS",
        "outputId": "ffd0dd8f-7591-44fb-a46b-3366fc980124"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: seaborn in /usr/local/lib/python3.8/dist-packages (0.11.2)\n",
            "Requirement already satisfied: numpy>=1.15 in /usr/local/lib/python3.8/dist-packages (from seaborn) (1.21.6)\n",
            "Requirement already satisfied: matplotlib>=2.2 in /usr/local/lib/python3.8/dist-packages (from seaborn) (3.2.2)\n",
            "Requirement already satisfied: scipy>=1.0 in /usr/local/lib/python3.8/dist-packages (from seaborn) (1.7.3)\n",
            "Requirement already satisfied: pandas>=0.23 in /usr/local/lib/python3.8/dist-packages (from seaborn) (1.3.5)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.8/dist-packages (from matplotlib>=2.2->seaborn) (1.4.4)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.8/dist-packages (from matplotlib>=2.2->seaborn) (3.0.9)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.8/dist-packages (from matplotlib>=2.2->seaborn) (0.11.0)\n",
            "Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.8/dist-packages (from matplotlib>=2.2->seaborn) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas>=0.23->seaborn) (2022.7)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.8/dist-packages (from python-dateutil>=2.1->matplotlib>=2.2->seaborn) (1.15.0)\n"
          ]
        }
      ],
      "source": [
        "!pip install seaborn"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "urXhvWcc7Lm4",
        "outputId": "4dfef9d3-56bb-41d8-aa30-d41729eb5805"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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1lKp6B/A+4N1d+wvd61YBz6qqNx04UFX9K4OtOi7q5v77gbEkJzHYZ/8VVXUGgzB4/VAdd1XV04BLgbf09GeVFmQQqHWbGXwfA93j5iXmDru6qh44jPc5HfhWFzgwOAN4ztD4x7vHm4C1h3Fc6WFbPukCpElJ8ljgbOCMJAUsAwoYZd+lHx7hcu7rHh/Af5caM88I1LKXAR+uqlOqam1VrQa+BawBTh6a94N57aUsNnc3sDbJaV371cDnH1rZ0pFlEKhlm4F/mNf3MeDngfVJvpLkFQwWkX+ja//aIY55JXBRkpuTPPFAZ1X9GHgtcHWSrwH/y2DtQZo4PzUkSY3zjECSGmcQSFLjDAJJapxBIEmNMwgkqXEGgSQ1ziCQpMb9H8L5pmhnLHPOAAAAAElFTkSuQmCC\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "import seaborn as sns\n",
        "for cat in cat_var:\n",
        "  sns.barplot(x=cat,y='Attrition',data = data[cat_var])\n",
        "  plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "BgBB9HXXQ8sM"
      },
      "outputs": [],
      "source": [
        "cont_var = [num for num in numerical if num not in cat_var+['id']]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qxUJM-E3U4SK",
        "outputId": "121a46f6-49ef-414b-dbe3-f4da080c95e5"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Age',\n",
              " 'DailyRate',\n",
              " 'DistanceFromHome',\n",
              " 'HourlyRate',\n",
              " 'MonthlyIncome',\n",
              " 'MonthlyRate',\n",
              " 'TotalWorkingYears',\n",
              " 'YearsAtCompany']"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ],
      "source": [
        "cont_var"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "RAw6M4CzU52K",
        "outputId": "73d19e2f-3916-49cf-cdb0-63c4ccc891f1"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      Age  DailyRate  DistanceFromHome  HourlyRate  MonthlyIncome  \\\n",
              "0      36        599                24          42           2596   \n",
              "1      35        921                 8          46           2899   \n",
              "2      32        718                26          80           4627   \n",
              "3      38       1488                 2          40           5347   \n",
              "4      50       1017                 5          37          19033   \n",
              "...   ...        ...               ...         ...            ...   \n",
              "1672   30        945                 1          73           8722   \n",
              "1673   32       1303                 2          48           3544   \n",
              "1674   29       1184                24          36           2804   \n",
              "1675   36        441                 9          48           5406   \n",
              "1676   36       1141                20          35           2593   \n",
              "\n",
              "      MonthlyRate  TotalWorkingYears  YearsAtCompany  \n",
              "0            5099                 10              10  \n",
              "1           10778                  4               4  \n",
              "2           16495                  4               3  \n",
              "3           13384                 15               6  \n",
              "4           19805                 31              31  \n",
              "...           ...                ...             ...  \n",
              "1672        14255                 10              10  \n",
              "1673        15972                 10               4  \n",
              "1674        15322                  1               1  \n",
              "1675         4051                 10              10  \n",
              "1676        17381                 10               8  \n",
              "\n",
              "[1677 rows x 8 columns]"
            ],
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              "\n",
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              "      <th></th>\n",
              "      <th>Age</th>\n",
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              "      <td>2596</td>\n",
              "      <td>5099</td>\n",
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              "      <td>10</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>35</td>\n",
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              "      <td>13384</td>\n",
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              "      <td>6</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>50</td>\n",
              "      <td>1017</td>\n",
              "      <td>5</td>\n",
              "      <td>37</td>\n",
              "      <td>19033</td>\n",
              "      <td>19805</td>\n",
              "      <td>31</td>\n",
              "      <td>31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1672</th>\n",
              "      <td>30</td>\n",
              "      <td>945</td>\n",
              "      <td>1</td>\n",
              "      <td>73</td>\n",
              "      <td>8722</td>\n",
              "      <td>14255</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1673</th>\n",
              "      <td>32</td>\n",
              "      <td>1303</td>\n",
              "      <td>2</td>\n",
              "      <td>48</td>\n",
              "      <td>3544</td>\n",
              "      <td>15972</td>\n",
              "      <td>10</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1674</th>\n",
              "      <td>29</td>\n",
              "      <td>1184</td>\n",
              "      <td>24</td>\n",
              "      <td>36</td>\n",
              "      <td>2804</td>\n",
              "      <td>15322</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1675</th>\n",
              "      <td>36</td>\n",
              "      <td>441</td>\n",
              "      <td>9</td>\n",
              "      <td>48</td>\n",
              "      <td>5406</td>\n",
              "      <td>4051</td>\n",
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              "      <td>10</td>\n",
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              "      <th>1676</th>\n",
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              "      <td>1141</td>\n",
              "      <td>20</td>\n",
              "      <td>35</td>\n",
              "      <td>2593</td>\n",
              "      <td>17381</td>\n",
              "      <td>10</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1677 rows × 8 columns</p>\n",
              "</div>\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a174ad5b-f704-4a32-b2a6-69d8b77068b3 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a174ad5b-f704-4a32-b2a6-69d8b77068b3');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ],
      "source": [
        "data[cont_var]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "ZOsSRSslU_Mm",
        "outputId": "0f34c2ca-2010-4c4b-dc8f-c5d8c5d9be7c"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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TwApEkkOSrE/ylSRfTvI7rX2/JFcnubXd79vak+SCJJuS3JzkyEFlkyRNb5BnENuBs6vqcOD5wGuSHA6sBq6pqsOAa9o8wEuAw9ptFXDhALNJkqYxsAJRVXdW1Zfa9P30vkPiIOAkYG1bbS1wcps+Cbikeq4FFic5cFD5JElTW5AxiCRLgecAXwCWVNWdbdG/AEva9EHAt/oedntrkyQNQapqsDtIFgGfBt5eVR9Pcm9VLe5bfk9V7ZvkSuDcqvpca78GOKeqrpuwvVX0uqBYsmTJUevWrevc77Zt21i0aNGkuTZuuW+Oz2xuluwBWx8aaoQpjXK+2WRbdtA+gw3TYbrfvWEz39zsCPlWrFhxfVUtn25bU31h0Jwl2Q34GPBXVfXx1rw1yYFVdWfrQrqrtW8BDul7+MGt7RGqag2wBmD58uU1NjbWue8NGzYw2TKAM1ZfNavnMt/OXrad8zYO9PDPySjnm022zaeNDTZMh+l+94bNfHOzM+Ub5LuYAlwEfLWq/rRv0RXAyja9Eri8r/3X27uZng/c19cVJUlaYIP8F/GFwOnAxiQ3trb/BpwLXJrkLOCbwCvbsk8CxwObgAeBMweYTZI0jYEViDaWMNlXlP6775Oo3mDIawaVR5I0O36SWpLUyQIhSepkgZAkdbJASJI6WSAkSZ0sEJKkThYISVInC4QkqZMFQpLUyQIhSepkgZAkdbJASJI6WSAkSZ0sEJKkThYISVInC4QkqZMFQpLUyQIhSepkgZAkdbJASJI6WSAkSZ0sEJKkThYISVInC4QkqZMFQpLUyQIhSepkgZAkdbJASJI6WSAkSZ0GViCSXJzkriS39LXtl+TqJLe2+31be5JckGRTkpuTHDmoXJKkmRnkGcQHgeMmtK0Grqmqw4Br2jzAS4DD2m0VcOEAc0mSZmBgBaKqPgPcPaH5JGBtm14LnNzXfkn1XAssTnLgoLJJkqaXqhrcxpOlwJVV9ew2f29VLW7TAe6pqsVJrgTOrarPtWXXAOdU1XUd21xF7yyDJUuWHLVu3brOfW/bto1FixZNmm3jlvvm8MzmbskesPWhoUaY0ijnm022ZQftM9gwHab73Rs2883NjpBvxYoV11fV8um2teu8pZqlqqoks65OVbUGWAOwfPnyGhsb61xvw4YNTLYM4IzVV8121/Pq7GXbOW/j0A7/tEY532yybT5tbLBhOkz3uzds5pubnSnfQr+Laet411G7v6u1bwEO6Vvv4NYmSRqShS4QVwAr2/RK4PK+9l9v72Z6PnBfVd25wNkkSX0G1oeQ5MPAGLB/ktuBtwDnApcmOQv4JvDKtvongeOBTcCDwJmDyiVJmpmBFYiqOnWSRcd2rFvAawaVRZI0e36SWpLUyQIhSepkgZAkdbJASJI6WSAkSZ0sEJKkThYISVInC4QkqZMFQpLUyQIhSepkgZAkdbJASJI6WSAkSZ0sEJKkThYISVInC4QkqZMFQpLUyQIhSepkgZAkdbJASJI6WSAkSZ0sEJKkThYISVInC4QkqZMFQpLUyQIhSepkgZAkdbJASJI6WSAkSZ1GqkAkOS7J15JsSrJ62HkkaWc2MgUiyS7Au4GXAIcDpyY5fLipJGnnteuwA/R5HrCpqm4DSLIOOAn4ylBTSdIklq6+amj73nzuCQPfR6pq4DuZiSQvB46rqt9s86cDR1fVayestwpY1WafAXxtkk3uD3x7QHHng/kevVHOBuabK/PNzUzyPbmqDphuQ6N0BjEjVbUGWDPdekmuq6rlCxDpUTHfozfK2cB8c2W+uZnPfCMzBgFsAQ7pmz+4tUmShmCUCsQ/AocleUqSxwOnAFcMOZMk7bRGpoupqrYneS3wf4BdgIur6stz2OS03VBDZr5Hb5SzgfnmynxzM2/5RmaQWpI0Wkapi0mSNEIsEJKkTjtcgRiVy3Uk2ZxkY5Ibk1zX2vZLcnWSW9v9vq09SS5omW9OcuQA8lyc5K4kt/S1zTpPkpVt/VuTrBxwvj9MsqUdwxuTHN+37E0t39eS/HJf+0B+/kkOSbI+yVeSfDnJ77T2oR/DKbKNxPFL8oQkX0xyU8v31tb+lCRfaPv6SHtzCkl2b/Ob2vKl0+UeUL4PJvlG3/E7orUv+OujbXuXJDckubLND/74VdUOc6M3uP114FDg8cBNwOFDyrIZ2H9C2x8Dq9v0auAdbfp44G+AAM8HvjCAPC8CjgRuebR5gP2A29r9vm163wHm+0PgjR3rHt5+trsDT2k/810G+fMHDgSObNN7Af/ccgz9GE6RbSSOXzsGi9r0bsAX2jG5FDiltb8HeFWbfjXwnjZ9CvCRqXIPMN8HgZd3rL/gr4+2/TcAHwKubPMDP3472hnEjy7XUVX/BoxfrmNUnASsbdNrgZP72i+pnmuBxUkOnM8dV9VngLvnmOeXgaur6u6quge4GjhugPkmcxKwrqq+X1XfADbR+9kP7OdfVXdW1Zfa9P3AV4GDGIFjOEW2ySzo8WvHYFub3a3dCjgGuKy1Tzx248f0MuDYJJki96DyTWbBXx9JDgZOAN7f5sMCHL8drUAcBHyrb/52pn6hDFIBf5fk+vQuDwKwpKrubNP/Aixp08PKPds8w8j52nYaf/F4982w87VT9ufQ+09zpI7hhGwwIsevdY/cCNxF7w/n14F7q2p7x75+lKMtvw944kLmq6rx4/f2dvzOT7L7xHwTcgzyZ/tO4PeAH7b5J7IAx29HKxCj5Oeq6kh6V6d9TZIX9S+s3jnfyLzHeNTyNBcCTwWOAO4EzhtuHEiyCPgY8Lqq+m7/smEfw45sI3P8qurhqjqC3hUSngc8c1hZukzMl+TZwJvo5XwuvW6jc4aRLcmJwF1Vdf1C73tHKxAjc7mOqtrS7u8CPkHvRbF1vOuo3d/VVh9W7tnmWdCcVbW1vXB/CLyPH58ODyVfkt3o/QH+q6r6eGseiWPYlW3Ujl/LdC+wHngBva6Z8Q/r9u/rRzna8n2A7yxwvuNa111V1feBDzC84/dC4GVJNtPr9jsG+DMW4vjN1wDKKNzofTL8NnoDMOODbM8aQo49gb36pv+BXl/kn/DIAc0/btMn8MhBry8OKNdSHjkIPKs89P6L+ga9Abh92/R+A8x3YN/06+n1nwI8i0cOtt1Gb4B1YD//diwuAd45oX3ox3CKbCNx/IADgMVteg/gs8CJwEd55CDrq9v0a3jkIOulU+UeYL4D+47vO4Fzh/n6aPsY48eD1AM/fvP6B2gUbvTeYfDP9Po43zykDIe2H8RNwJfHc9DrB7wGuBX4v+O/PO0X7d0t80Zg+QAyfZheN8MP6PU9nvVo8gC/QW9waxNw5oDz/UXb/830rsvV/wfvzS3f14CXDPrnD/wcve6jm4Eb2+34UTiGU2QbieMH/DRwQ8txC/AHfa+TL7bj8FFg99b+hDa/qS0/dLrcA8r3qXb8bgH+kh+/02nBXx992x/jxwVi4MfPS21IkjrtaGMQkqR5YoGQJHWyQEiSOlkgJEmdLBCSpE4WCO20kjzcrtL55XYlz7OTTPmaSPKTSS5r02PjV9acYv3+K6p+JcmpM8j1uiQ/MbtnI80/C4R2Zg9V1RFV9Szgl+hdFuUtUz2gqu6oqpfPcj/nV+8yDicB722fep7K6wALhIbOAiHxo0uirKJ3cbskWZrks0m+1G4/C72L4aXvOyta2+Pa9f8P6JvfND7ft49bgQfpfcqWJBcmuW7CdxD8NvCTwPok61vbi5N8vuX4aLvmkjRwFgipqarxS048id41lX6pehdc/FXggike90N6n7Q9rTX9InBTVf1r/3rti2VubcUIep9UXk7vk7y/kOSnq+oC4A5gRVWtSLI/8PvAL7Ys19H7XgBp4HadfhVpp7Qb8K72LWIPA0+fZv2LgcvpXbPnN+hd3G3c65Oc2bbx0r72V7ZLwe9K70t/Dqd3uYd+z2/tf9+7pD+PBz7/aJ6QNFsWCKlJcii9YnAXvbGIrcDP0DvT/t5Uj62qbyXZmuQYelf9PK1v8flV9T+TvAy4KMlT6RWENwLPrap7knyQ3jV0/l0set9PMO3gtjTf7GKSgDZe8B7gXdW7QNk+wJ2t++h0el1P03k/va6mj1bVwxMXVtUV9LqIVgJ7Aw8A9yVZQm+AfNz99L46FOBa4IVJntZy7plkurMZaV5YILQz22P8ba70rsT6d8Bb27I/B1YmuYnel8Y8MIPtXQEs4pHdSxO9jd4YwkZ6VxD9J3rfM/z3feusAf42yfo2jnEG8OEkN9PrXhqpL9vRjsuruUrzJMlyet1JPz/sLNJ8cAxCmgdJVgOv4pFjD9JjmmcQkqROjkFIkjpZICRJnSwQkqROFghJUicLhCSp0/8HvMUniAxk6PgAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "for feature in cont_var:\n",
        "  dataset = data.copy()\n",
        "  data[feature].hist()\n",
        "  plt.xlabel(feature)\n",
        "  plt.ylabel('Attrition')\n",
        "  plt.title(feature)\n",
        "  plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "COaNL70lV_wU",
        "outputId": "f0e9e1d5-ac8d-4021-d16a-4433b570af62"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.8/dist-packages (1.21.6)\n"
          ]
        }
      ],
      "source": [
        "!pip install numpy\n",
        "import numpy as np"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "c2lwPlCWnGji",
        "outputId": "f8daeafc-e345-4550-b129-6d1a853a74e0"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAEWCAYAAABrDZDcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAY6ElEQVR4nO3dfZRcdX3H8feHzWMlIcUsUZNAEAMURaVseWhsi2BsDDaxiJpYKvZQONViH7C0cOKBgnKQ5tSjrVgF60NRoKAtrhKNORJsyzFpNkWwREJXiCRByAoIKA8h8ds/5m4YZmfu3NnMndnd3+d1zp7M/d3f3Pn+Zu7cT+beO3cUEZiZWboO6HYBZmbWXQ4CM7PEOQjMzBLnIDAzS5yDwMwscQ4CM7PEOQjMzBLnIDArSNLtkh6XNLXbtZi1k4PArABJC4DfAgJY1tVizNrMQWBWzHuADcAXgLOHGyW9VNLXJT0paZOkj0j6r6r5R0taJ+kxSVslvbPzpZvlm9TtAszGifcAHwM2AhskzYmIR4CrgV8ALwMWAGuBHwNIegmwDrgEeAtwLLBO0v9GxJaOj8CsAX8iMGtC0huAw4CbImIz8CPg3ZJ6gLcDl0bE09nG/YtVd30rsC0iPh8ReyLiTuCrwDs6PASzXA4Cs+bOBr4dET/Npq/P2nqpfKreXtW3+vZhwImSfjb8B/wBlU8PZmOGdw2Z5ZA0HXgn0CPp4ax5KjALmAPsAeYB92Xz5lfdfTvw3YhY3KFyzUZFvgy1WWOSVlI5DvB6YHfVrJuATVRCYC/wx8ChwLeBByPiDZJmAP8LfAi4Mbvf64GfR8QPOzMCs+a8a8gs39nA5yPiwYh4ePgP+CSV3TznAwcBDwPXATcAzwFExFPAm4EVwENZn6uofKIwGzP8icCsjSRdBbwsIs5u2tlsjPAnArP9kH1P4LWqOAE4B/j3btdl1gofLDbbPzOo7A56BfAI8PfA17pakVmLvGvIzCxx3jVkZpa4cbdraPbs2bFgwYJul2FmNq5s3rz5pxHRW2/euAuCBQsWMDAw0O0yzMzGFUk/bjTPu4bMzBLnIDAzS5yDwMwscQ4CM7PEOQjMzBJX2llDkj5H5Yc5dkXEa+rMF/AJYCnwNPDeiPifMmpZ/LHb+b9dv9g3vfCQl7DuglOa3u+1l36LJ5/bu2965tQe7r5sSe59brlzJ6vXbuWhnz3DK2ZN58LfPYq3HTe3Yf8/uPZ73PGjx/ZNLzriYL587sltGUsrfYuOtWi9R69aw7N7X/iy4rQece8VS0f0O/yiW6n+SqOABz56+ov6LLjo1hH329ZinyLPRbNlNBvTiVes45GnXrhA6ZwZU9i4anHTec2eg1ddfCt7qjpMEgxeeXpuvXmvZ6PnotX2dq3r9dp3PfVc4ccECtfxoVt+wA0bt7M3gh6JlSdWrhpe3XbSK3+VbY8+03R59Wq5eeDBpu+PVp+3Tijtm8WSfhv4OfAvDYJgKfABKkFwIvCJiDix2XL7+vqildNHa1fiYc3CoPaNNCwvDG65cycX/9sPeOb5F+43fXIPV55xbN0XuvYNMKzRxrWVsbTSt+hYi9Zbu8EcVrvhrN0ADqveENbb2A3bVrBPkeei2TKajal2Qz9szowpAA3n7Xpqd+5zUBsCRcyc2tPw9Zxz0LS6z8UkUfdxGrXPmTGFJ5/du9/reqNa66n3mJMPEAier3ptGtXxoVt+wJc2PFjosarVW16993oj1e+PVrcR7SRpc0T01ZtX2q6hiPgPYOQr/4LlVEIiImIDMEvSy9tdR72VPq99WKOVM2+lXb1264gV45nn97J67da6/eu9MfLaWxlLK32LjrVovfU2mPXaG23f2v1fk9GuA9Wajanehn64PW9es+eg1RCA/Nez0ZgbPU6j9kee2t2Wdb1oCDR6zOd/GS8Kgbw6bti4fURbEfWWV++93kj12FvdRnRKN48RzOXFP+u3I2sbQdJ5kgYkDQwNDXWkuNF46GfPtNRuNtGMlXW9Xh1792PvR+3yRjvOsbqNGBcHiyPimojoi4i+3t6635AeE14xa3pL7WYTzVhZ1+vV0SO1bXmjHedY3UZ0Mwh28uLfd52XtbXVwkNe0lL7sJlTe1pqB7jwd49i+uQXz58+uWffAa1ai444uKX2VsbSSt+iYy1a77Se+m+42vZGb8vRv13rG+06UK3ZmIaPBdSaM2NK7rxmz8GkUTwZea9nozE3epxG7XNmTGnLup73firymJMPEJNrXptGdQwfGG5VveXVe683Uj32VrcRndLNIOgH3pP9oMdJwBMR8ZN2P8i6C04ZsfIXOWvo7suWjFhJm5019Lbj5nLlGccyd9Z0BMydNT33INCXzz15xBsk76yhVsbSSt+iYy1a771XLB2x4ax31tADHz19xIaw9oyZ2rOD6rU361PkuWi2jGZj2rhq8YgN/vCZQXnzmj0Hg1eePmJjPEn59ea9no2ei8ErT2+pfeOqxW1Z1+++bEnd9qKPufodr2P1ma8rVMdH3nYsZ5106L5PBj0SZ5106Ii2RUcc3HR59d7rH3/X65u+P1rdRnRKmWcN3QCcAsym8oMdlwKTASLi09npo58EllA5ffSPIqLp6UCtnjVkZmb5Zw2V9j2CiFjZZH4Af1rW45uZWTHj4mCxmZmVx0FgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeJKDQJJSyRtlTQo6aI68w+VtF7SnZLulrS0zHrMzGyk0oJAUg9wNfAW4BhgpaRjarp9CLgpIo4DVgCfKqseMzOrr8xPBCcAgxFxf0TsBm4Eltf0CWBmdvsg4KES6zEzszrKDIK5wPaq6R1ZW7W/Bc6StANYA3yg3oIknSdpQNLA0NBQGbWamSWr2weLVwJfiIh5wFLgOkkjaoqIayKiLyL6ent7O16kmdlEVmYQ7ATmV03Py9qqnQPcBBAR3wOmAbNLrMnMzGqUGQSbgIWSDpc0hcrB4P6aPg8CpwFI+jUqQeB9P2ZmHVRaEETEHuB8YC3wQypnB90j6XJJy7JuHwTOlXQXcAPw3oiIsmoyM7ORJpW58IhYQ+UgcHXbJVW3twCLyqzBzMzydftgsZmZdZmDwMwscQ4CM7PEOQjMzBLnIDAzS5yDwMwscQ4CM7PEOQjMzBLnIDAzS5yDwMwscQ4CM7PEOQjMzBLnIDAzS5yDwMwscQ4CM7PEOQjMzBLnIDAzS5yDwMwscQ4CM7PEOQjMzBLnIDAzS5yDwMwscQ4CM7PEOQjMzBLnIDAzS5yDwMwscQ4CM7PEOQjMzBLnIDAzS5yDwMwscaUGgaQlkrZKGpR0UYM+75S0RdI9kq4vsx4zMxtpUlkLltQDXA0sBnYAmyT1R8SWqj4LgYuBRRHxuKRDyqrHzMzqK/MTwQnAYETcHxG7gRuB5TV9zgWujojHASJiV4n1mJlZHWUGwVxge9X0jqyt2pHAkZLukLRB0pJ6C5J0nqQBSQNDQ0MllWtmlqZuHyyeBCwETgFWAtdKmlXbKSKuiYi+iOjr7e3tcIlmZhNbmUGwE5hfNT0va6u2A+iPiOcj4gHgPirBYGZmHdL0YLGkI4ELgcOq+0fEqU3uuglYKOlwKgGwAnh3TZ9bqHwS+Lyk2VR2Fd1fuHozM9tvRc4auhn4NHAtsLfogiNij6TzgbVAD/C5iLhH0uXAQET0Z/PeLGlLtuwLI+LRVgdhZmajp4jI7yBtjojjO1RPU319fTEwMNDtMszMxpVsW95Xb16RYwRfl/R+SS+XdPDwX5trNDOzLimya+js7N8Lq9oCeGX7yzEzs05rGgQRcXgnCjEzs+4octbQZOB9wG9nTbcDn4mI50usy8zMOqTIrqF/AiYDn8qm/zBr++OyijIzs84pEgS/ERGvq5q+TdJdZRVkZmadVeSsob2SjhiekPRKWvg+gZmZjW1FPhFcCKyXdD8gKt8w/qNSqzIzs44pctbQd7LfDTgqa9oaEc+VW5aZmXVKwyCQdGpE3CbpjJpZr5JERPxbybWZmVkH5H0i+B3gNuD36swLwEFgZjYBNAyCiLg0u3l5donofbIripqZ2QRQ5Kyhr9Zp+0q7CzEzs+7IO0ZwNPBq4KCa4wQzgWllF2ZmZp2Rd4zgKOCtwCxefJzgKSo/Om9mZhNA3jGCrwFfk3RyRHyvgzWZmVkH5e0a+uuI+Dvg3ZJW1s6PiD8rtTIzM+uIvF1DP8z+9c+BmZlNYHm7hr4uqQc4NiL+qoM1mZlZB+WePhoRe4FFHarFzMy6oMhF574vqR+4GfjFcKMvMWFmNjEUCYJpwKPAqVVtvsSEmdkEUSQIPhsRd1Q3SPLuIjOzCaLIJSb+sWCbmZmNQ3nfIzgZ+E2gV9IFVbNmAj1lF2ZmZp2Rt2toCnBg1mdGVfuTwJllFmVmZp2T9z2C7wLflfRM9g3jfSS9A/i/soszM7PyFTlGsKJO28XtLsTMzLoj7xjBW4ClwFxJ/1A1awbwfNmFmZlZZ+QdI3gI2Awsy/4ddhjwdJlFmZlZ5zTcNRQRd0XEF4BXAXcDrwEuA97ICxekMzOzca5hEEg6UtKlwA+ofG/gQUAR8caI+GSRhUtaImmrpEFJF+X0e7ukkNTX6gDMzGz/5O0auhf4T+CtETEIIOkviy44u3Lp1cBiYAewSVJ/RGyp6TcD+HNgY4u1m5lZG+SdNXQG8BNgvaRrJZ0GqIVlnwAMRsT9EbEbuBFYXqffh4GrgGdbWLaZmbVJ3jGCWyJiBXA0sB74C+AQSf8k6c0Flj0X2F41vSNr20fSrwPzI+LWvAVJOk/SgKSBoaGhAg9tZmZFNf0eQUT8IiKuj4jfA+YBdwJ/s78PLOkA4GPABwvUcE1E9EVEX29v7/4+tJmZVSnyhbJ9IuLxbKN8WoHuO4H5VdPzsrZhM6iciXS7pG3ASUC/DxibmXVWS0HQok3AQkmHS5pC5RvK/cMzI+KJiJgdEQsiYgGwAVgWEf6NZDOzDiotCCJiD3A+sJbK9w5uioh7JF0uaVlZj2tmZq0p8sM0oxYRa4A1NW2XNOh7Spm1mJlZfWXuGjIzs3HAQWBmljgHgZlZ4hwEZmaJcxCYmSXOQWBmljgHgZlZ4hwEZmaJcxCYmSXOQWBmljgHgZlZ4hwEZmaJcxCYmSXOQWBmljgHgZlZ4hwEZmaJcxCYmSXOQWBmljgHgZlZ4hwEZmaJcxCYmSXOQWBmljgHgZlZ4hwEZmaJcxCYmSXOQWBmljgHgZlZ4hwEZmaJcxCYmSXOQWBmlrhSg0DSEklbJQ1KuqjO/AskbZF0t6TvSDqszHrMzGyk0oJAUg9wNfAW4BhgpaRjarrdCfRFxGuBrwB/V1Y9ZmZWX5mfCE4ABiPi/ojYDdwILK/uEBHrI+LpbHIDMK/EeszMrI4yg2AusL1qekfW1sg5wDfrzZB0nqQBSQNDQ0NtLNHMzMbEwWJJZwF9wOp68yPimojoi4i+3t7ezhZnZjbBTSpx2TuB+VXT87K2F5H0JmAV8DsR8VyJ9ZiZWR1lfiLYBCyUdLikKcAKoL+6g6TjgM8AyyJiV4m1mJlZA6UFQUTsAc4H1gI/BG6KiHskXS5pWdZtNXAgcLOk70vqb7A4MzMrSZm7hoiINcCamrZLqm6/qczHNzOz5sbEwWIzM+seB4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiZtU5sIlLQE+AfQAn42Ij9bMnwr8C3A88CjwrojY1u46XnXxreyJF6YnCQavPL3p/Y5etYZn975wx2k94t4rlube58Qr1vHIU7v3Tc+ZMYWNqxY37L/goltHtG37aOPaWulfRt9u9GtHn04sI2/+aOflzW/3442l9npa6VvG/WvNnNrDk8/tbTjdyKIjDuaOHz3W0mPV3mfREQfz5XNPbmkZeRQRzXuNZsFSD3AfsBjYAWwCVkbElqo+7wdeGxF/ImkF8PsR8a685fb19cXAwEDhOmpDYFizMKgNgWF5YVAbAsMahUHeSll0o9mofxl9u9GvHX06sYx2bmDKXq5NDK2GgaTNEdFXb16Zu4ZOAAYj4v6I2A3cCCyv6bMc+GJ2+yvAaZLUziLqhUBe+7B6IZDXDtQNgbx2M7PRavVTRZ4yg2AusL1qekfWVrdPROwBngBeWrsgSedJGpA0MDQ0VFK5ZmZpGhcHiyPimojoi4i+3t7ebpdjZjahlBkEO4H5VdPzsra6fSRNAg6ictC4bSY12NHUqH3YtJ76HRq1Q+VYQCvtZmajteiIg9u2rDKDYBOwUNLhkqYAK4D+mj79wNnZ7TOB26LNR68Hrzx9xEa/yFlD916xdMRGv9lZQxtXLR6x0c87a6jRGTztaC+jbzf6taNPJ5aRN3+084o8brsfb6y072/fMu5fa+bUntzpRkazAa+9z7g5awhA0lLg41ROH/1cRFwh6XJgICL6JU0DrgOOAx4DVkTE/XnLbPWsITMzyz9rqNTvEUTEGmBNTdslVbefBd5RZg1mZpZvXBwsNjOz8jgIzMwS5yAwM0ucg8DMLHGlnjVUBklDwI+7XUdBs4GfdruINpkoY5ko44CJM5aJMg4Y22M5LCLqfiN33AXBeCJpoNHpWuPNRBnLRBkHTJyxTJRxwPgdi3cNmZklzkFgZpY4B0G5rul2AW00UcYyUcYBE2csE2UcME7H4mMEZmaJ8ycCM7PEOQjMzBLnINhPkqZJ+m9Jd0m6R9JldfpMlfSvkgYlbZS0oPOV5is4jgskbZF0t6TvSDqsG7U2U2QsVX3fLikkjblT/oqOQ9I7s9flHknXd7rOIgquX4dKWi/pzmwda3zN9y6T1JPV+Y0688b8+32EiPDffvwBAg7Mbk8GNgIn1fR5P/Dp7PYK4F+7Xfcox/FG4Fey2+8bi+MoOpZs3gzgP4ANQF+36x7la7IQuBP41Wz6kG7XvR9juQZ4X3b7GGBbt+vOGc8FwPXAN+rMG/Pv99o/fyLYT1Hx82xycvZXewR+OfDF7PZXgNMkNfmNtM4qMo6IWB8RT2eTG6j86tyYU/A1AfgwcBXwbKdqa0XBcZwLXB0Rj2f32dXBEgsrOJYAZma3DwIe6lB5LZE0Dzgd+GyDLmP+/V7LQdAG2cfE7wO7gHURsbGmy1xgO0BE7AGeAF7a2SqbKzCOaucA3+xMZa1rNhZJvw7Mj4hbu1JgQQVekyOBIyXdIWmDpCWdr7KYAmP5W+AsSTuo/I7JBzpcYlEfB/4a+GWD+ePi/V7NQdAGEbE3Il5P5X/IJ0h6TbdrGo2i45B0FtAHrO5kfa3IG4ukA4CPAR/sVn1FFXhNJlHZPXQKsBK4VtKszlZZTIGxrAS+EBHzgKXAddlrNWZIeiuwKyI2d7uWdhpTT/J4FxE/A9YDtf8r2wnMB5A0icrH3kc7W11xOeNA0puAVcCyiHiu07W1qsFYZgCvAW6XtA04CegfiweMh+W8JjuA/oh4PiIeAO6jEgxjVs5YzgFuyvp8D5hG5SJuY8kiYFm23twInCrpSzV9xtX7HRwE+01S7/D/wCRNBxYD99Z06wfOzm6fCdwW2ZGksaLIOCQdB3yGSgiMyX3R0HwsEfFERMyOiAURsYDK8Y5lETGmfgy74Lp1C5VPA0iaTWVXUe7vfndDwbE8CJyW9fk1KkEw1Mk6m4mIiyNiXrberKDyXj6rptuYf7/XKvU3ixPxcuCLknqoBOtNEfENSZcDAxHRD/wzlY+5g8BjVFagsabIOFYDBwI3Z8e+HoyIZV2ruLEiYxkPioxjLfBmSVuAvcCFETEW//dZZCwfpLJr6y+pHDh+71jfgA4bh+/3F/ElJszMEuddQ2ZmiXMQmJklzkFgZpY4B4GZWeIcBGZmiXMQmLVA0tuyq5Ue3e1azNrFQWDWmpXAf2X/mk0IDgKzgiQdCLyByqUQVmRtB0j6lKR7Ja2TtEbSmdm84yV9V9JmSWslvbyL5Zs15CAwK2458K2IuA94VNLxwBnAAirXz/9D4GQASZOBfwTOjIjjgc8BV3SjaLNmfIkJs+JWAp/Ibt+YTU8Cbo6IXwIPS1qfzT+KyoXt1mWX4+gBftLZcs2KcRCYFSDpYOBU4FhJQWXDHsC/N7oLcE9EnNyhEs1GzbuGzIo5E7guIg7Lrlo6H3iAykXF3p4dK5hDdiVQYCvQK2nfriJJr+5G4WbNOAjMilnJyP/9fxV4GZXfBNgCfAn4H+CJiNhNJTyuknQX8H3gNztXrllxvvqo2X6SdGBE/FzSS4H/BhZFxMPdrsusKB8jMNt/38h+dGUK8GGHgI03/kRgZpY4HyMwM0ucg8DMLHEOAjOzxDkIzMwS5yAwM0vc/wMnr5FpWhXgvwAAAABJRU5ErkJggg==\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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BrgIeCbwGeDL3PWBPkrSLmTEYkjw0yauBq2k+t/A1IFX15Kp66yAzT3JckuuTbE5y2iz9fiVJJZmY7wpIkhbXbKeSrgM+DTy9qjYDJPn9QWfcPpn1LOBYYAuwKcnGqrq2r98q4PeAy+ZZuyRpCGa7K+mXgW8AlyR5e5JjgMxj3kcAm6vqhqq6BzgfOGGafn8K/AXw/XnMW5I0JLNdY/hgVZ0IPAy4BHgxsH+Sv0ryiwPM+0Dgpp7hLW3bdkkeCxxcVR+dbUZJTkkymWRy69atAyxakrRQc36Ooaq+W1XvrapnAAcBXwD+cGcXnGQ34A3ASweo4ZyqmqiqiTVr1uzsoiVJsxjkA27bVdW32530MQN0vxk4uGf4oLZtyiqaO50+keRG4ChgoxegJWm05hUM87QJWJfksCR70nyCeuPUyKq6vapWV9XaqloLXAocX1V+x7QkjdDQgqGq7gVOBS6i+dzDBVV1TZIzkhw/rOVKknbOIF/Us2BVdSFwYV/bq2bou36YtUiSBjPMU0mSpGXIYJAkdRgMkqQOg0GS1GEwSJI6DAZJUofBIEnqMBgkSR0GgySpw2CQJHUYDJKkDoNBktRhMEiSOgwGSVKHwSBJ6jAYJEkdBoMkqcNgkCR1GAySpA6DQZLUYTBIkjoMBklSh8EgSeowGCRJHQaDJKnDYJAkdRgMkqQOg0GS1GEwSJI6DAZJUsdQgyHJcUmuT7I5yWnTjH9JkmuTXJXkX5McOsx6JElzG1owJFkBnAU8FXg4cFKSh/d1+wIwUVWPAt4P/OWw6pEkDWaYRwxHAJur6oaqugc4Hziht0NVXVJV32sHLwUOGmI9kqQBDDMYDgRu6hne0rbN5DeBj003IskpSSaTTG7dunURS5Qk9RuLi89JngtMAK+fbnxVnVNVE1U1sWbNmqUtTpLuZ3Yf4rxvBg7uGT6obetI8hTgdOBJVXX3EOuRJA1gmEcMm4B1SQ5LsidwIrCxt0OSxwB/DRxfVbcMsRZJ0oCGFgxVdS9wKnAR8EXggqq6JskZSY5vu70e2Bt4X5IrkmycYXaSpCUyzFNJVNWFwIV9ba/qef+UYS5fkjR/Y3HxWZI0PgwGSVKHwSBJ6jAYJEkdBoMkqcNgkCR1GAySpA6DQZLUYTBIkjoMBklSh8EgSeowGCRJHQaDJKnDYJAkdRgMkqQOg0GS1GEwSJI6DAZJUofBIEnqMBgkSR0GgySpw2CQJHUYDJKkDoNBktRhMEiSOgwGSVKHwSBJ6jAYJEkdBoMkqcNgkCR1GAySpI7dhznzJMcBbwJWAO+oqjP7xj8AeBfwOOBW4NlVdeNi17H2tI/u0HbjmU9b7MWMpXFc96WqabGXs7PzW+j0851uPv0H6bsYfWYbv5Bx82mfznz6jqth/h6nqoYz42QF8CXgWGALsAk4qaqu7enzO8CjquqFSU4E/ntVPXu2+U5MTNTk5OTAdcz2nz/qHeSwjeO6L1VNi72cnZ3fQqef73Tz6T9I38Xos9x3wONsPj/LSS6vqolB+g7zVNIRwOaquqGq7gHOB07o63MC8Lft+/cDxyTJEGuSJM1hmMFwIHBTz/CWtm3aPlV1L3A78GP9M0pySpLJJJNbt24dUrmSJFgmF5+r6pyqmqiqiTVr1oy6HEnapQ0zGG4GDu4ZPqhtm7ZPkt2BfWkuQkuSRmSYwbAJWJfksCR7AicCG/v6bASe175/FvDxWuSr4TNdnNnVLzzDeK77UtW02MvZ2fktdPr5Tjef9kH6Lkaf2cYvdNx82ne277halnclASTZALyR5nbVd1bV65KcAUxW1cYkK4F3A48B/gs4sapumG2e870rSZI0v7uShvo5hqq6ELiwr+1VPe+/D/zqMGuQJM3Psrj4LElaOgaDJKnDYJAkdRgMkqSOod6VNAxJtgJfXeDkq4H/XMRylsJyrBmWZ93WvDSseen01n1oVQ30CeFlFww7I8nkoLdrjYvlWDMsz7qteWlY89JZaN2eSpIkdRgMkqSO+1swnDPqAhZgOdYMy7Nua14a1rx0FlT3/eoagyRpbve3IwZJ0hwMBklSxy4ZDEmOS3J9ks1JTptm/AOS/H07/rIka5e+yh1qmqvmk5NsTXJF+/qtUdTZV9M7k9yS5N9nGJ8kb27X6aokj13qGqepaa6a1ye5vWc7v2q6fkspycFJLklybZJrkvzeNH3GalsPWPNYbeskK5N8LsmVbc2vmabPWO07Bqx5/vuOqtqlXjSP+P4ycDiwJ3Al8PC+Pr8DnN2+PxH4+2VQ88nAW0e9fftq+nngscC/zzB+A/AxIMBRwGXLoOb1wEdGXWdfTQcAj23frwK+NM3Px1ht6wFrHqtt3W67vdv3ewCXAUf19Rm3fccgNc9737ErHjEcAWyuqhuq6h7gfOCEvj4nAH/bvn8/cEySLGGN/QapeexU1adovkdjJicA76rGpcB+SQ5YmuqmN0DNY6eqvlFVn2/f3wl8kR2/P32stvWANY+Vdtt9px3co331350zVvuOAWuet10xGA4EbuoZ3sKOP5Db+1TVvcDtwI8tSXXTG6RmgF9pTxO8P8nB04wfN4Ou17h5Qnto/rEkjxh1Mb3aUxePofnLsNfYbutZaoYx29ZJViS5ArgFuLiqZtzOY7LvGKRmmOe+Y1cMhl3Vh4G1VfUo4GLu+6tFi+vzNM+UeTTwFuCDI65nuyR7Ax8AXlxVd4y6nkHMUfPYbeuq2lZVP0PzHfVHJHnkqGuaywA1z3vfsSsGw81AbyIe1LZN2yfJ7sC+wK1LUt305qy5qm6tqrvbwXcAj1ui2nbGIP8XY6Wq7pg6NK/mGwj3SLJ6xGWRZA+aHex7quofpukydtt6rprHdVsDVNVtwCXAcX2jxm3fsd1MNS9k37ErBsMmYF2Sw5LsSXOBaGNfn43A89r3zwI+Xu1VmhGZs+a+88XH05yzHXcbgd9o75g5Cri9qr4x6qJmk+THp84ZJzmC5ndkpL/4bT3/F/hiVb1hhm5jta0HqXnctnWSNUn2a9//CHAscF1ft7HadwxS80L2HUP9zudRqKp7k5wKXERzt887q+qaJGcAk1W1keYH9t1JNtNciDxxdBUPXPPvJjkeuJem5pNHVnAryXk0d5asTrIFeDXNxS+q6mya7/veAGwGvgc8fzSV3meAmp8F/HaSe4G7gBNH/EcDwNHArwNXt+eSAV4BHAJju60HqXnctvUBwN8mWUETUhdU1UfGed/BYDXPe9/hIzEkSR274qkkSdJOMBgkSR0GgySpw2CQJHUYDJKkDoNBYyXJtvYJkNe0j0p4aZLd2nETSd48y7RrkzxnCWtdm+SunqdWXtF+DmUxl3Fukmf1tX1npv7SYtjlPsegZe+u9uP9JNkfeC+wD/DqqpoEJmeZdi3wnHaapfLlqXr7Jdm9fZ6OtKx4xKCxVVW3AKcAp7af6F2f5CMASZ7U81f6F5KsAs4Efq5t+/32L/pPJ/l8+/rZdtr1ST7RPlDsuiTv6fkE7uOT/Ft7tPK5JKvah5S9Psmm9kFk/3Ommtt5fzrJRuDaNM/L/5skV7d1Prntd3KSDya5OMmNSU5N8pK2z6VJHjjX9mm3yeuT/Hs7/2f31PDJJB9KckOSM5P8Wrs+Vyd5cNtvTZIPtOu1KcnRO/Ufpl3HYj0X3JevxXgB35mm7TbgQfQ8v5/mwWBHt+/3pjn63T6+bf9RYGX7fh3NJ0Fp+91O8zyh3YDPAk+k+S6MG4DHt/32aed7CvDKtu0BNEcth9EcodwFXNG+zmrn/V3gsLb/S2k+yQ7wMOBrwEqaT59upvmugjVtPS9s+/0fmofOAZwLfKVnGVdMbSPgV2geirai3T5fo/kk7Pp2mx3Q1nsz8Jp2mt8D3ti+fy/wxPb9ITSPrxj5z4Cv0b88laTl6jPAG5K8B/iHqtqSHR+Lvwfw1iQ/A2wDHtoz7nNVtQWgfWTDWpqd8zeqahM0D3lrx/8i8Kiec/370gTNl+g7lZRkfTvvr7RNT6R5cihVdV2Sr/bUcUk131VwZ5LbacIO4GrgUT21vqyq3t+zjKlrDE8EzquqbcC3knwSeDxwB7Cp2mclJfky8M89835y+/4pwMN7tts+Sfau+57vr/spg0FjLcnhNDv1W4CfmmqvqjOTfJTm+UCfSfJL00z++8C3gEfTHBl8v2fc3T3vtzH770KAF1XVRX21rZ2h/3dnmVev3hp+2DP8wznqWax570bzbV+920XyGoPGV5I1wNk0X0tYfeMeXFVXV9Vf0Dyd9mHAnTSnZqbsS3ME8EOaB7qtmGOR1wMHJHl8u4xVaR6tfBHNw972aNsfmmSvAVfj08CvTU1Hc8rm+gGnHWTez26vgayh+drSz81j+n8GXjQ10B5ZSR4xaOz8SHtqZw+ap0G+G5jusc0vbi/k/hC4hub7jn8IbEtyJc25+bcBH0jyG8A/Mcdf8lV1T3sB9y1pHmF8F83plnfQnGr6fHuReivwzAHX523AXyW5ul2fk6vq7mlOey3EPwJPoPmO8AJeXlXfTPKwAaf/XeCsJFfR7As+BbxwMQrT8ubTVSVJHZ5KkiR1GAySpA6DQZLUYTBIkjoMBklSh8EgSeowGCRJHf8ffozHetVUnNcAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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knVqxaDrQVXZhZmbWGo12DXUD2+R9plW0Pwd8qMyizMysdRp9juDnwM8lvZx/wngzSR8GHiy7ODMzK1+RYwSLarSdOdqFmJlZezQ6RvB+4AhglqR/qFg0DdhQdmFmZtYajY4RPAbcASzM/x+wC/BSmUWZmVnr1N01FBF3R8RlwJuAe4C9gbOBd/P6BenMzGycqxsEknaX9CXgV2SfG/gdoIh4d0RcWGRwSQskPSBpjaQzGvT7oKSQ1NvsBMzMbMs02jV0P3ArcFRErAGQ9FdFB86vXHoRcDiwFlglaWlErK7qNw34LLCyydrNzGwUNDpr6FjgcWC5pEslHQaoibEPANZExEMRsR64Bji6Rr+/Af4eeKWJsc3MbJQ0OkZwfUQsAvYElgN/CcyU9E1J7y0w9izg0YrHa/O2zSS9DZgTET9pNJCkkyX1Serr7+8v8K3NzKyoYT9HEBEvRsT3IuIDwGzgTuCvt/QbS5oAfA04rUANl0REb0T09vT0bOm3NjOzCkU+ULZZRDydr5QPK9B9HTCn4vHsvG3ANLIzkW6R9AhwELDUB4zNzFqrqSBo0ipgnqRdJXWTfUJ56cDCiHg2InaIiLkRMRdYASyMCN8j2cyshUoLgojYCHwGWEb2uYNrI+JeSedIWljW9zUzs+YUuTHNiEXEjcCNVW1frNN3fpm1mJlZbWXuGjIzs3HAQWBmljgHgZlZ4hwEZmaJcxCYmSXOQWBmljgHgZlZ4hwEZmaJcxCYmSXOQWBmljgHgZlZ4hwEZmaJcxCYmSXOQWBmljgHgZlZ4hwEZmaJcxCYmSXOQWBmljgHgZlZ4hwEZmaJcxCYmSXOQWBmljgHgZlZ4hwEZmaJcxCYmSXOQWBmljgHgZlZ4hwEZmaJcxCYmSXOQWBmlrhSg0DSAkkPSFoj6Yway0+VtFrSPZJ+JmmXMusxM7OhSgsCSV3ARcD7gb2AxZL2qup2J9AbEfsCPwC+WlY9ZmZWW5lbBAcAayLioYhYD1wDHF3ZISKWR8RL+cMVwOwS6zEzsxrKDIJZwKMVj9fmbfWcCPy01gJJJ0vqk9TX398/iiWamdmYOFgsaQnQC5xfa3lEXBIRvRHR29PT09rizMw63MQSx14HzKl4PDtvG0TSe4CzgHdFxKsl1mNmZjWUuUWwCpgnaVdJ3cAiYGllB0n7Ad8GFkbEkyXWYmZmdZQWBBGxEfgMsAy4D7g2Iu6VdI6khXm384FtgOsk3SVpaZ3hzMysJGXuGiIibgRurGr7YsXX7ynz+5uZ2fDGxMFiMzNrHweBmVniHARmZolzEJiZJc5BYGaWOAeBmVniHARmZolzEJiZJc5BYGaWOAeBmVniHARmZolzEJiZJc5BYGaWOAeBmVniHARmZolzEJiZJc5BYGaWOAeBmVniHARmZolzEJiZJc5BYGaWOAeBmVniHARmZolzEJiZJc5BYGaWOAeBmVniHARmZolzEJiZJc5BYGaWOAeBmVniHARmZombWObgkhYAXwe6gO9ExHlVyycDVwD7A08Bx0fEI6Ndx9wzfjKk7ZHzjhz0+MBzb+KJ59dvfrzjtG5WnnV4oTF2PeMnREW7gIcrxt/3S//Gc69u2vx4+uQu7jl7wbDjjnTZ4V+7hQeffHFz+7yZW3PTqfMbPm8stdfyyHlH1nwdKx83MlGwMeo/bmRKl3hlU9R9bNYO1euwLaGIcn6hJXUBvwYOB9YCq4DFEbG6os+ngH0j4i8kLQL+a0Qc32jc3t7e6OvrK1xHoxXNwAtZHQIDBsKg0RgCar2CA2FQvfIa0MxKrBnzZm49KASGazez8auZMJB0R0T01lpW5q6hA4A1EfFQRKwHrgGOrupzNHB5/vUPgMMkqcSaaqoVAo3aK9WL0YH2eiv7MkIAqLuydwiYWT1lBsEs4NGKx2vztpp9ImIj8CywffVAkk6W1Cepr7+/v6RyzczSNC4OFkfEJRHRGxG9PT097S7HzKyjlBkE64A5FY9n5201+0iaCGxLdtC4pXac1t1Ue6V6+7EG2qdP7qq5vF77lpo3c+um2s3MygyCVcA8SbtK6gYWAUur+iwF/jT/+kPAzTHKR6/rHUypbF951uFDVvqVZw01GuPh844cEgaVZw3dc/aCISv9gbOGGo070mU3nTp/yEp/4KyhIq/FWGiv17fW61jURDV+3MiULjV8bNYO4+KsIQBJRwAXkJ0++t2IOFfSOUBfRCyVNAW4EtgP+AOwKCIeajRms2cNmZlZ47OGSv0cQUTcCNxY1fbFiq9fAT5cZg1mZtbYuDhYbGZm5XEQmJklzkFgZpY4B4GZWeJKPWuoDJL6gd+O8Ok7AL8fxXLaqVPm0inzgM6ZS6fMAzpnLqMxj10iouYncsddEGwJSX31Tp8abzplLp0yD+icuXTKPKBz5lL2PLxryMwscQ4CM7PEpRYEl7S7gFHUKXPplHlA58ylU+YBnTOXUueR1DECMzMbKrUtAjMzq+IgMDNLXMcFgaQpkv5D0t2S7pV0doO+H5QUksbc6WVF5yHpOEmr8z7fa3WdRRSZi6SdJS2XdKeke/Ir145JkrryOm+osWyypO9LWiNppaS5ra+wuGHmcmr+u3WPpJ9J2qUdNRbRaB4Vfcbs+73ScHMp4z1f6tVH2+RV4NCIeEHSJODfJf00IlZUdpI0DfgssLIdRRYw7DwkzQPOBA6JiKclzWxXscMo8jP5AnBtRHxT0l5kV62d24Zai/gscB8wvcayE4GnI+JNkhYBfw8c38rimtRoLncCvRHxkqRPAl9l7M6l0TzGw/u9Ut25lPWe77gtgsi8kD+clP+rdUT8b8jepK+0qrZmFJzHScBFEfF0/pwnW1hiYQXnErz+i78t8FiLymuKpNnAkcB36nQ5Grg8//oHwGGSxuSdbIabS0Qsj4iX8ocryO4yOOYU+JnAGH+/Dygwl1Le8x0XBLB50+ou4EngpohYWbX8bcCciPhJWwosaLh5ALsDu0u6TdIKSQtaX2UxBebyZWCJpLVkWwOntLjEoi4APg+8Vmf5LOBRgIjYCDwLbN+a0po23FwqnQj8tNxyRqzhPMbL+z033M+klPd8RwZBRGyKiLeS/QVzgKS9B5ZJmgB8DTitXfUV1WgeuYnAPGA+sBi4VNKM1lZZTIG5LAYui4jZwBHAlfnPasyQdBTwZETc0e5atlQzc5G0BOgFzi+9sCYNN4/x9H4v+DMp5T0/pt5ooy0ingGWA5WpOQ3YG7hF0iPAQcDSsXwAqc48ANYCSyNiQ0Q8DPya7JdkzGowlxOBa/M+twNTyC60NZYcAizMf2+uAQ6V9M9VfdYBcwAkTSTbzfVUK4ssqMhckPQe4CxgYUS82toSCxluHuPp/V7kZ1LOez4iOuof0APMyL+eCtwKHNWg/y1kB8TaXnuz8yBbmV6ef70D2S6J7dtd+wjn8lPghPzrN5MdI1C7a28wp/nADTXaPw18K/96EdkB8LbXO8K57Af8BpjX7hq3ZB5Vfcbk+72Jn0kp7/lO3CJ4A7Bc0j3AKrL90TdIOkfSwjbX1owi81gGPCVpNdlf2adHxFj867PIXE4DTpJ0N3A1WSiMi4+9V83jH4HtJa0BTgXOaF9lzauay/nANsB1ku6StLSNpTVlHL7f62rFe96XmDAzS1wnbhGYmVkTHARmZolzEJiZJc5BYGaWOAeBmVniHATW8SS9UPX4BEkXljV+jeXzJT2bn4J5v6T/WWDMY/KL75mVzkFgNkL5J4eLujWyS2zsBxwl6ZBh+h8DOAisJRwEljRJcyXdXHHN/Z3z9sskfaii3wv5//Ml3Zp/uGp11VhXSDqm4vFVko6u7BMRLwN3kV2cDkknSVql7F4NP5S0laR3AAuB8/OtiN3yf/8m6Y78++9Z0ktiCXIQWAqm5ivUu/IroJ5TsewbZB/Z3xe4CviHAuO9DfhsROxe1f6PwAkAkrYF3gEMuuKlpD8iuzbML/KmH0XE2yPiLWTXoD8xIn4JLCX71OhbI+I3ZDcvPyUi9gc+B1xccO5mw+rEG9OYVXs53y0DZMcIyK6mCXAwcGz+9ZVkN18Zzn9EdsGvQSLi55IultQDfBD4YURszG9H8F/yy2fMAy6IiP/Mn7a3pL8FZpBdzmFZ9biStiELlesqbm0wuUCdZoU4CMxq20i+xZxfyri7YtmLDZ53BbCE7IJzn6hovzUijpK0K7BC0rURcRdwGXBMRNydB9T8GmNOAJ6pDDOz0eRdQ5a6X5KttAE+SnZlVIBHgP3zrxeS3VWtiMuAvwSIiNXVC/MtifOAv86bpgGPK7uF50cruj6fLyMingMelvRhAGXeUrAes2E5CCx1pwCfyK+M+jGy+8UCXAq8K9+dczCNtwI2i4gnyPb1/1ODbt8C3qnsxvb/g+w+urcB91f0uQY4XdlNzHcjC4kT83ruJbslptmo8NVHzUaRpK2AXwFvi4hn212PWRHeIjAbJfndvO4DvuEQsPHEWwRmZonzFoGZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeL+P8x0fFVanVzvAAAAAElFTkSuQmCC\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/pandas/core/arraylike.py:364: RuntimeWarning: divide by zero encountered in log\n",
            "  result = getattr(ufunc, method)(*inputs, **kwargs)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "for feature in cont_var:\n",
        "  dataset = data.copy()\n",
        "  if 0 in dataset.nunique():\n",
        "    pass\n",
        "  else:\n",
        "    dataset[feature]=np.log(dataset[feature])\n",
        "    plt.scatter(dataset[feature],dataset['Attrition'])\n",
        "    plt.xlabel(feature)\n",
        "    plt.ylabel('Attrition')\n",
        "    plt.title(feature)\n",
        "    plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "yW85bTFrnPs8",
        "outputId": "86008710-dbb2-442f-b581-cb07578e400b"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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hZmbDpuWuoYh4oH9KRdPS/GPAk622lXSppMck3bGF9b2S1kpamqazBvUKzMxsSHLddE7S3wDXAP8/Fe1E+wfVXAYc2qbOLRGxb5rOzROLmZl1Vt67j36S7KyhpwEi4tfAq1ptkJ5V0HLUYGZmwy/vlcUbImKjlJ1NKmkMnTmj6K2SlgEPA5+JiJXNKkmaDkwH6OrqolardaBrq5oyPjd9fX2l9OO/AeukvIlggaQzgfGS3gX8LXD9EPu+Hdg1IvokHUa2q2las4oRMQuYBdDT0xO9vb1D7NoqZ94cyvjc1Gq14vsp6bVYdeTdNTQTeBxYAXwcmAt8figdR8TTEdGX5ucCYyVNGkqbZmY2cHlHBOOBSyPin+H3t6YeDzw72I4lvRp4NCJC0v5kSWnNYNszM7PByZsI/h04BOhLy+OBG4G3bWkDSVcBvcAkSauBs0mPt4yIi4GjgE9I2gSsB46JCF/JbGZWsryJYFz/bhyAtF//Za02iIhj26y/ALggZ/9mZlaQvMcInpH0pv4FSW8m+xVvZmYjXN4RwanAv0p6mOw+Q68Gji4sKjMzK02uRBARiyTtDfyfVHRPRDxfXFhmZlaWvCMCgP2A7rTNmyQREd8vJCozMytNrkQg6QpgD2ApsDkVB+BEYGY2wuUdEfQAr/PpnWZmLz15zxq6g+wAsZmZvcTkHRFMAu6UtBDY0F8YEYcXEpWZmZUmbyL4YpFBmJnZ8Ml7+uiCogMxM7PhkfcJZW+RtEhSn6SNkjZLerro4MzMrHh5DxZfABwL/JrshnMfAy4sKigzMytP3kRARKwCRkfE5oj4Hu2fR2xmZiNA3oPFz0raBlgq6avAIwwgiZiZ2dYr75f58anuDOAZYGfgL4oKyszMypM3ERwZEc+lx0ueExGnAe8vMjAzMytH3kRwQpOyEzsYh5mZDZOWxwgkHQt8GNhN0uy6VdsDTxYZmJmZlaPdweJfkh0YngT8U135OmB5UUGZmVl5WiaCiHgAeEDSIcD6iHhB0l7A3sCKMgI0M7Ni5T1GcDMwTtJU4Eays4gua7WBpEslPSbpji2sl6RvSVolaXn9M5HNzKw8eROBIuJZslNGL4qIDwGvb7PNZbS+6Oy9wLQ0TQe+kzMWMzProNyJQNJbgeOAOalsdKsNIuJmWh9QPgL4fmRuBSZKmpIzHjMz65C8VxafCpwBXBcRKyXtDswfYt9TgQfrllenskcaK0qaTjZqoKuri1qtNsSurYrK+Nz09fWV0o//BqyTBnIb6gV1y/cBpxQVVJP+ZwGzAHp6eqK3t7esru2lYt4cyvjc1Gq14vsp6bVYdbS7juAbEXGqpOvJHlb/R4b4hLKHyG5V0W+nVGZmZiVqNyK4Iv37jwX0PRuYIelq4ABgbUS8aLeQmZkVq911BEvSvwskTU7zj+dpWNJVQC8wSdJq4GxgbGrjYmAucBiwCngW+OjgXoKZmQ1F22MEkr5IdtfRUdmiNgHfjohzW20XEce2WR/AJ/OHamZmRWh5+qik04ADgf0iYseIeAXZbpwDJX26jADNzKxY7a4jOB44NiJ+01+Qzhj6K+AjRQZmZmblaJcIxkbEE42F6TjB2GJCMjOzMrVLBBsHuc7MzEaIdgeL95H0dJNyAeMKiMfMzErW7vTRlvcTMjOzkS/vTefMzOwlyonAzKzinAjMzCrOicDMrOKcCMzMKs6JwMys4vI+ocxsxOueOad9pU6YV2w/O4z3Rf3WWU4EVgn3n/e+UvrpnjmntL7MOsW7hszMKs6JwMys4pwIzMwqzonAzKzinAjMzCrOicDMrOIKTQSSDpV0j6RVkmY2WX+ipMclLU3Tx4qMx8zMXqyw6wgkjQYuBN4FrAYWSZodEXc2VP1hRMwoKg4zM2utyBHB/sCqiLgvIjYCVwNHFNifmZkNQpGJYCrwYN3y6lTW6IOSlku6RtLOBcZjZmZNDPctJq4HroqIDZI+DlwOHNxYSdJ0YDpAV1cXtVqt1CDNBsKfTxtpikwEDwH1v/B3SmW/FxFr6hYvAb7arKGImAXMAujp6Yne3t6OBmrWMfPm4M+njTRF7hpaBEyTtJukbYBjgNn1FSRNqVs8HLirwHjMzKyJwkYEEbFJ0gzgZ8Bo4NKIWCnpXGBxRMwGTpF0OLAJeBI4sah4zMysuUKPEUTEXGBuQ9lZdfNnAGcUGYOZmbXmK4vNzCrOicDMrOKcCMzMKs6JwMys4pwIzMwqzonAzKzinAjMzCrOicDMrOKcCMzMKs6JwMys4pwIzMwqzonAzKzinAjMzCrOicDMrOKcCMzMKs6JwMys4pwIzMwqzonAzKzinAjMzCrOicDMrOKcCMzMKq7QRCDpUEn3SFolaWaT9dtK+mFaf5uk7iLjMTOzFyssEUgaDVwIvBd4HXCspNc1VPtr4HcRsSfwdeArRcVjZmbNFTki2B9YFRH3RcRG4GrgiIY6RwCXp/lrgHdKUoExmZlZgzEFtj0VeLBueTVwwJbqRMQmSWuBVwJP1FeSNB2YDtDV1UWtVisoZLM/OOiggwa1nQY4rp0/f/6g+jHrlCITQcdExCxgFkBPT0/09vYOb0BWCREx4G1qtRr+fNpIU+SuoYeAneuWd0plTetIGgPsAKwpMCYzM2tQZCJYBEyTtJukbYBjgNkNdWYDJ6T5o4D/iMH8DDMzs0ErbNdQ2uc/A/gZMBq4NCJWSjoXWBwRs4HvAldIWgU8SZYszMysRIUeI4iIucDchrKz6uafAz5UZAxmZtaaryw2M6s4JwIzs4pzIjAzqzgnAjOzitNIO1tT0uPAA8Mdh9kWTKLhynizrcSuETG52YoRlwjMtmaSFkdEz3DHYTYQ3jVkZlZxTgRmZhXnRGDWWbOGOwCzgfIxAjOzivOIwMys4pwIzMwqzonAtiqSNktaKmmlpGWSTpc0Kq3rkfStFtt2S/pwibF2S1qf4u2ftulwH5dJOqqhrK+TfZiNiCeUWaWsj4h9ASS9CvgXYHvg7IhYDCxusW038OG0TVnu7Y+3kaQxEbGpxFjMBsUjAttqRcRjZM+qnqFMr6QbACT9ed2v8P+WNAE4D/izVPbp9Iv9Fkm3p+ltadteSTVJ10i6W9KVkpTW7Sfpl2k0slDSBEmjJX1N0iJJyyV9fEsxp7ZvkTQbuFPSOEnfk7QixXlQqneipJ9IuknS/ZJmSDot1blV0o7t3p/0nnxN0h2p/aPrYlgg6d8k3SfpPEnHpdezQtIeqd5kSdem17VI0oFD+g+zkSsiPHnaaiagr0nZU0AX0AvckMquBw5M89uRjW5/vz6VvwwYl+ankT0QiVRvLdnjU0cB/wW8HdgGuA/YL9XbPrU7Hfh8KtuWbFSyG9kIZD2wNE0XprafAXZL9U8neygTwN7A/wDjgBOBVcAEYHKK56RU7+vAqWn+MuA3dX0s7X+PgA8CN5E9+KkrtT0lxfBUmt+W7JGw56RtPgV8I83/C/D2NL8LcNdw//97Gp7Ju4ZspPpP4HxJVwI/jojV6Ud9vbHABZL2BTYDe9WtWxgRqwEkLSX7Ul8LPBIRiwAi4um0/t3AG+r21e9Allh+RcOuIUm9qe3fpKK3A99O7d0t6YG6OOZHxDpgnaS1ZMkNYAXwhrpY/y4irqnro/8YwduBqyJiM/CopAXAfsDTwKKIeCTVvxe4sa7tg9L8IcDr6t637SVtFxE+BlExTgS2VZO0O9mX+GPAa/vLI+I8SXOAw4D/lPSeJpt/GngU2Ifsl/9zdes21M1vpvXfgoCTI+JnDbF1b6H+My3aqlcfwwt1yy+0iadTbY8C3hLZkwKtwnyMwLZakiYDFwMXREQ0rNsjIlZExFeARWS7XdaR7WrptwPZL/wXgOPJdqG0cg8wRdJ+qY8JksaQPXf7E5LGpvK9JL0858u4BTiufzuyXTD35Nw2T9tHp2MYk4F3AAsHsP2NwMn9C2nkZBXkEYFtbcanXTVjgU3AFcD5Teqdmg68vgCsBH6a5jdLWka2b/0i4FpJHwHm0eaXekRsTAdcvy1pPNn+/0OAS8h2Hd2eDio/DhyZ8/VcBHxH0or0ek6MiA1NdmMNxnXAW4FlQACfjYjfSto75/anABdKWk72XXAzcFInArORxbeYMDOrOO8aMjOrOCcCM7OKcyIwM6s4JwIzs4pzIjAzqzgnAjOzinMiMDOruP8F4p9qtKrkIrMAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/pandas/core/arraylike.py:364: RuntimeWarning: divide by zero encountered in log\n",
            "  result = getattr(ufunc, method)(*inputs, **kwargs)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/pandas/core/arraylike.py:364: RuntimeWarning: divide by zero encountered in log\n",
            "  result = getattr(ufunc, method)(*inputs, **kwargs)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "for feature in cont_var:\n",
        "  dataset = data.copy()\n",
        "  if 0 in dataset.nunique():\n",
        "    pass\n",
        "  else:\n",
        "    dataset[feature]=np.log(dataset[feature])\n",
        "    dataset.boxplot(column=feature)\n",
        "    plt.ylabel(feature)\n",
        "    plt.title(feature)\n",
        "    plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NSpPOq8nnZgR",
        "outputId": "0428d783-10c9-477c-afb6-cf8982a73b2e"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['BusinessTravel',\n",
              " 'Department',\n",
              " 'EducationField',\n",
              " 'Gender',\n",
              " 'JobRole',\n",
              " 'MaritalStatus',\n",
              " 'Over18',\n",
              " 'OverTime']"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ],
      "source": [
        "cat_feat = [feature for feature in data.columns if data[feature].dtypes == 'O']\n",
        "cat_feat"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "VcO8Ujn_oeJG",
        "outputId": "ab758b83-849c-4966-8450-4c1a250b563d"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         BusinessTravel              Department   EducationField  Gender  \\\n",
              "0     Travel_Frequently  Research & Development          Medical    Male   \n",
              "1         Travel_Rarely                   Sales            Other    Male   \n",
              "2         Travel_Rarely                   Sales        Marketing    Male   \n",
              "3         Travel_Rarely  Research & Development          Medical  Female   \n",
              "4         Travel_Rarely  Research & Development          Medical  Female   \n",
              "...                 ...                     ...              ...     ...   \n",
              "1672      Travel_Rarely                   Sales    Life Sciences  Female   \n",
              "1673      Travel_Rarely  Research & Development    Life Sciences    Male   \n",
              "1674  Travel_Frequently         Human Resources  Human Resources    Male   \n",
              "1675      Travel_Rarely                   Sales        Marketing    Male   \n",
              "1676      Travel_Rarely  Research & Development    Life Sciences  Female   \n",
              "\n",
              "                        JobRole MaritalStatus Over18 OverTime  \n",
              "0         Laboratory Technician       Married      Y      Yes  \n",
              "1          Sales Representative       Married      Y       No  \n",
              "2               Sales Executive      Divorced      Y       No  \n",
              "3     Healthcare Representative       Married      Y       No  \n",
              "4                       Manager        Single      Y      Yes  \n",
              "...                         ...           ...    ...      ...  \n",
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              "1675            Sales Executive      Divorced      Y       No  \n",
              "1676      Laboratory Technician        Single      Y       No  \n",
              "\n",
              "[1677 rows x 8 columns]"
            ],
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              "                                                     [key], {});\n",
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            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ],
      "source": [
        "data[cat_feat]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IkV2P4mooiNc",
        "outputId": "73538877-46bc-4bd2-e265-3e12c4c66406"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "BusinessTravel has 3 number of features\n",
            "Department has 3 number of features\n",
            "EducationField has 6 number of features\n",
            "Gender has 2 number of features\n",
            "JobRole has 9 number of features\n",
            "MaritalStatus has 3 number of features\n",
            "Over18 has 1 number of features\n",
            "OverTime has 2 number of features\n"
          ]
        }
      ],
      "source": [
        "for cat in cat_feat:\n",
        "  print(f\"{cat} has {len(data[cat].unique())} number of features\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "2woGtLhupC-D",
        "outputId": "592eefd3-9c00-4103-f60a-97ccec0ec8cd"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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Z0w7uPrSPlrXa+sXtatz9EuCSvl6umU1095F9vdw3QzE1RjE1bm2MSzE1Zm2MqbdKnshtB7arvN42p3U7j5kNBDYFXigYk4iINEHJZDMB2NnMRpjZIOAY4Jq6ea4BPpvPjwJu1fc1IiKtp9hpNHdfamYnATcCbcBP3X2KmZ0JTHT3a4D/An5hZjOAeURCWpP6/NRcH1BMjVFMjVsb41JMjVkbY+qVYhcIiIiI1OjiexERKU7JRkREimso2ZjZ/EYXaGZnmNkpvQ+px2V/p5tpp5nZFDN7xMwmmdneq1jG5fkboOq0+/OzT5vZnHw+aWW3zzGzA8zs5ZznUTO7JH8ztDrbMtLMzlvFttxtZpt189n51W0xsxPM7IIG1/sNM3tL3eslub4ZZvZXMzs4p/+iVlZmdn13sfRWluH7K6+/ZGbHV16fUKmLR83sH/tq3ZV1eP79Ml8PzHUuMrNxb2K5b2inOX1otrWHzOwD9fOZ2T09LHMPMzt8Je8ty3KabGbX1tdTX9WdmQ03s4UZ/zQze8DMTqi8f0T1tlRmNt/MxpvZyHzdbTs1swFmdl7G/xcz+7OZ/b8e4lhhPau5DZuZWaeZLTaz183sVTOba2Y79DD/P/RmXb2Mb3l59TDPatXDm4ilb7fd3Vf5B8xvZL6c9wzglEbnr/vswNWJA9gHuBdYP18PAbauvG/AgLrPXA4ctZLlnwBc0ECcBwDj8vkGwOPAE73Z5ka3pbtyqG1Lo3HnZ2YCQyqvvwE8V193Od9vVlZWb2I7BzbSTqrbBGxB/LBtu75af60cgWXAw1mPh2Vdvlyr316uo9v+QlwAc9mq5usu5p7quLoc4GfAafn8De3/TZbdcGBy5fWOwCTgc92tJ8t3PPFD7ZX2L+BY4g4iA/L1+4Cpva3XBrZhWa0fZHndClzayDb3UTkasaPf1s1744GRva2HviijN7PtPa2j0QW8oVMAHwHuBx4C/gRsmdPPAH5BDJyPAV+sFPDZwGTgL8DROf0A4E7iMui/5rT/AR4EpgAn5rTvZyOZBPwqp/038Eou8xuVApqe8y0Ensv11S6GuJuuRLEXcHuu60bg68AFwNcy9leJq+TuBN6Rn9kyX79CDFLvB64FZgOXZiN+Kcvlqpz3LGBRLutx4AHg08A4ImFcRgxwi4BH87MPAq8THe90ouN2AkuBzozlZ8AS4MWcvjDLYl4l9nm57Mcqy1gA3JfLuCuX8dd8vz23ZWn+zQbuAxz4LvBD4B5gVq7vRaKztmW5L8t1dABvoStp/SRjmwV8MLd1ca7z02TyAd6R5XNC1sXwrL/7gOOzvp7MbZoMXEx22lzWuUS7uQUYWunAPwImAt+kq95rsV5HJO0Hcptez3IYletYkvO+Bnw5Y3sy51ua792f6/pzltVC4JFc7tPAUzl9GTCHaAeduczFub5lxC2cbgKeyW18hWjDc/Lv+fzsc8DVle2enGV1WtbJz7NOx2dZ3wt8CJhG9NfXiTZyVy5j71z2a/nYntM3yrL8M9E2n6rrZzfltu4AXEn8Tu7hrLMlGf+EnLYoY7sT+H2WzZY5r+c8X8n1L6OrPzxZqYPpwEVE35lKtOVFuT0TiCtcf0q0u1eIdv8E8LWMe2yuazHRvk7L+a4HDs0yX1pZ159y+YsyhvlE/9yUGM+epau9HJ3l9WAu5y9ZnxcQbXt6fn5u1tevc9tey/q8JevrnKzrhVmHR2bs7yTa6NRc586V8fgg4KF8fgJdO2qXE33v/lzuTsANGWP9uPb7rIPauDY2Y5iU29rwGN7XyeatdA3gXwB+WEk2tT3FIcTgsjXwceBmYlDakuiAW2WgC4ARlWVvno8b5IZtUR8HMWBMITr0Y8Sg+nmiE3QCh1Q6y6vAR/P188DJwHrEoFkbkI4G7siG8QwxgO4MbEZ0xFtzvitynnG5LTtkwS/NbbkD+C1wHPAtojH9kGj8PyMa7/FE568lmxlEB5pENLyrgP0zjjuBzYkGtg3RQD3XuSCfzyEa/XPEYPJTojONIjrIfcAhxBHCTOBjwG9ze/4p55mUn3meaJAzs+ynEzdUfZnotP+VdXdP1t8i4L3AefmZgcRe2+PEAD+TSDbjMp7xRKc6j+iAe2dZn0HXUdWkfO+CLMOzc9q9dCX3T+V2XgQcn59z4NP5/HS6Otx44KJ8vrzeiY6/iEiov8tymJHruQHYJOvueODg/NyrxK2TXsn5dyISydLcvs0zjrZc78lEm5mVZf0C0T7G5fr/HfhMzvsaMbg8l9s7O5c/C/gicBvw3dyOf83pI+hKNjsSibOT2Em5hWjDM4n6vyfjfIxoS1fStTPXDlycz88mBpkRWZ+b5PQ9s7yMrn52cM57WC73JzlvrZ3OJ9rUq7nts4g6f5ZINlcA/5zLmpT1MJ9IMttkvNcRY8d3iEuBXwB+SfS3pcCPs562J/rCPVk+D+S8w/JxPVY8snlbLvvlrNNZxCC8H7Av0Q5mEAP7zTltM2JM+VJu483EODUpy3Bb4PCs3yH5+Vqy6cztHp3l9UDW8Qii3WxOtIP7ifHj8Hz9V2BD4Hxix2w4MfZtUBkPNwMWriTZjKNrh+wWMknxxnGttsPeRiTT4ax4BNXwGN7d35v5nc22wBVmthUwiBhUa/7g7guBhWZ2G9EJ9wN+4+7LgOfM7HZikHoFeMDdq5//mpn9fT7fjugw9XcW2I/otP8CfCAfzwXOJDr/xmZ2P7F3PQD4uJk9ms+fJu6x9i7gZjODKEDLZU8h9hT+RDTETmD9fO8gYqC7mtjb25k4whpMNMLdiEH7/cRe3GCiA32caHS/yb/ziURSW/e5wLeJzvIB4KMZz3zgQKIjPU10YIjBZ2xOX0pU/jJiEN0xt/OSnPY2ovGeRCT+f6Pr+7o983EAMXje5O6PZ5lMIQatkbktbwPek8toIwY/MsZDgY2Jo7o2YpDagy5XZTm2EY38nRnbcZWyrbky5zkgy7SNGJRPzve2JAa5JUTnfT4/10l0GojB6HeVZdamL693YpAg494zt3E9YpB4iehwn8/3a21jGZG0nwHIspqa8+4F/G3O9xDRER/KcngrcVS0ETGIHZBl9PVKeQ3IdT1D1Ou4jPWO3NbtgOPze7RhGevOuR07EXv2M4j2P5log1cR9fXDnO9JYsC5nOh7O+T3OZsBB5rZJKLNtuWyZwP/bmYfzBjXy/In1/NgPj+YOEpemq8XE4lpItHeriX60tbE0Wit7A8ikvmpRDL+LNEe1s+yfIFoXzcSCWIUkYi2I5LiAOI03mLiyG19om4d+APRvgYSbaQW94CM4xmizTixV34BMa7dRtQzRDt4jRh4f0H0qV/m9n6ISKL3EvU/jRjTjieO3v9EJMzad6RPEe3oCuLsyf3EjvXysS/73SbEWEDWwXNEe7iXOBK7Flgvx9jlH2XlrnL3ZWa2Edkmcj2w4rh2PECO0S+b2VvrlrM6Y/gbvJmr0c4nsufuwP8lGmiN181b/7regtoTMzuAqMh93P09RGcdvJLP4e7L3H080SGvIga914g93qMyvl8ThfI5Yu8LonKmuPse+bc78IN87xNEI/st0blGuvuudau+M+N7J/DJXJ4RDf0cYi9xN+LIYFF+Zhnd/5C2s/J8nrsPI85jLyYSzaXEkc2BxGlAiIEfYhC6kGiQtc98BLjB3fcg9ogeJjrGKKKDfRoYbGYjcpkvuvu7s2yq8dU6fXWwNeKo6g5iMD/V3aflewOBfd19AyIZziQGHyPquFaPLxGH9udm2deX7RVEfd2Y2/1+4B+JPbyzgB+4+wbuvom77+LuZ3RTprBiu6u1seX1TuyRLyQG4i2JnaaxWWb7EYPkQOA/iAT+DLH3+ixRl4tzmctyXVsRe7BkeV4HvJ1IXg8RR1tzcz0b5ONjRAL/ZS7vEKL9PkoktaPpSpQAX83YLwDOcvfaaax2Ys/biDobALyU8z5D1PPBwCJ3/xJxSnQT4rTVW+uW/UnidMhNRFsZSiTSw4n6rNXjAiJJ1+p/ZeW/hKjz7wMLch1X0zX+GDDI3f9ItIuZGVtNLYF10tU+30Wc9lkKHAH8OZd7DpEAIPpdrc9V+15nlskIom90Znm8QOxwfIs4yjmc2Nl6hkhaNxFHJfcSfeI24IxswyOIdrF/xn53xvMcXclmQd1jTz5O7JA86+7bu/s0d/91buvrxE7CQZX5e6qH2vqWt4nKX33f661VbtObSTab0nWvs8/WvXekmQ02sy2IAptA7MUfbWZtZjaUyPwPrGS5L7r7a2b2DqKya5aY2Xr5vLa83c1sQ+DviUbTTtfAODez+T653E/RdQQ2HRhqZvsA5HK3zvc2y/cfyM9tZGbvyfduIc7D1v5nzzziMH4IcbpqX2KQIOOq7cFBHK1ADCBTKtMfIRr7lsCTeWXJHkRH2oOopwXEkdRW+Zm3EZ2gtte2QW7ns0RD3cjMBgD/O8vkOWJwW0BXfW1CDHBuZlsSe8e1geRVIjmNBX5F14B0IzFwfJhIytPMbHPgj0QHnJ9leWIua2atPDKuZUQdjCCOPq1StkAcLRB1ORK4wt0nEt9B7EgM1keZ2dZm9k4z27xyJdEA4tQMRF3fxRutUO/pLmIg/FFux1PETsYWxN74XsSpiY2yDFdmMFG+nWa2P3GqZFe69ox3Jer4QKLeOonTdbXTKrVlbJXltivRT24m6uN54MtZvjOB/bONDcjyfJ04HTkk1/mkmX2iEt+uAGa2k7vfT9TlAqKNvwR8J5d9DDAol70p8Ly7LyH64nqV5a1H7KCdnzHuR9eAXi2nBUSd75nrt4x1L6I/jQXWy/60EV1nI+7L9T9F9JlNc7m75HLnEmcCvldZ1zB69ipd48NC4hTewNzm54l+2UYcFR1KnCZ/KzA3k/TjxI7A48RRyzE5pu1NJJq5xBmIXc3skPz8vt3EcTNx9L6/xS29Ns9+BJHMvlqb0cxq5bYjcSr78tyOd+f04XTVw0q5+ytU2kRd37uFOPImt2fTXEf1f1Q0OoavNIBGvrPpJA6na38nEwPuE8Rh9NnA+Mp3Nj9n9S4QGFdZ1/pEh59GXCgwHjgg3zsrp9cuEDiH6FSvEwPv74gGPZnYK32cOBL4b+KQdiyVq9GIgfwOYu9mSs53ETH4PJqF/Syxd326d32Rdhdx6DiJGOB3IfbehhOHo7OIwf2R3NaRxOBwHjG4T2DFCwSOIw6NXyP2xhYSnX8xMQj+B3lhQE7zLLfLc72zcv4F+Tg/lzE143+B6Ehzct4X6Dq/+0Au79XcpsXEwHBDLnsy0flqcW1AnAZZkvG8TJziGkgM5J2V6b8lTgm+nHXxg6zPEVnutS/jL6Pu6jS6vsgdnq+3Jjry3VmWC4m2+CDwvtp3ekSbmEx8D1S9QGBkZdm1el+Wf18kBs67iDa9gGhn+2R5LWPFiwROIL8vzOWNI/aIv0HXQNCZZXZrxlm7oGIxccrmV0TbWJzLrJ2uHUcc1dUS7vPEALw50W6eIwazKcSOzrSMbRrR/oZnPX4my/mGXMf0Stn8Ltf9LDGgG5FIns8Y52Y8mxKJ696cv3YqdApxuu414IRKuV6VMU0i2v7CWtlnLFOzDKcSffm+XFY7XRdVtOf2jc1Y5xB9sRbbK0QfvY6uiygeJep+KnHa7hS6LjipXTgxma62tISuCwRq5XUTMZjOp+sCgTnEkdYsui6YmUucBh9MtPs5RBueT7SLWnnNydjmZx3UYplJXg1KnCp7iq4LBG7O8tqX6GNTM85xlfmnVMrxEaLeH6irhxNY8Tuboyrv1drEw7xxXPtD1vMk4swSxFmhyaz6AoFVXr25ztyuxuJ3E+e6+y1NWv9MYsBb2/5fRssws/nuvlGz4+iOmW3k7vNzr/5C4DF3P7fZcdXU4svn3wa2cvevNzksaSEtfweB/GHSX4k9+aYkGhHgi/nl+xTiiOHiJsdT78OWPwwljkb/rdkBSWtZZ45sRESkeVr+yEZERJpPyUZERIpTshERkeKUbESS9XB3c4u7VHd7J2gzm5l3K37EzG5f2R2EK/MXuzO6yNpKyUakbxyYdw0YT/xAV0QqlGxEKvJX1Wdb1/9WObry9iZmdp2ZTTezn+QdGurdS/yyvC6w/osAAAFlSURBVPZ/R27NI55bzGz7bta3k5ndYGYPmtmdedcMkZajZCOyoo8Rdxh4D3EvsbPzZrMQt+/5KnGz1Z1y3nqHEne+gLh9yM/yiOdXxB0k6l1C3JNsL+JX5hf10XaIrFXezF2fRVrRqu5s+wSAmf0m5706P3db3ttqPlD7L5P70JWQfgGMqa5oFXfhFWkpSjYijevpbuYHEvel+xXx7y5ObmB51Tszi7Q0nUYTWVFPd7YdlXfoHUDchXiFu0q7+1LiZpzH51HOPcTdhCFuvHpn3fw93YVXpKUo2YgAZjaQuEvz74m76T5M3LF5tLt35GwTiDsFTyPujP37+uW4+7PEXYG/Qny/8zkze4S4C3N3N7b8NPB5M6vdefzIPtwskbWG7o0mAuQRxaXuPqrZsYi0Ih3ZyDrPzL5EHI3o9zEihejIRkREitORjYiIFKdkIyIixSnZiIhIcUo2IiJSnJKNiIgU9/8BhrIVNX+tgIUAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "for cat in cat_feat:\n",
        "  sns.barplot(x=cat,y='Attrition',data = data)\n",
        "  plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ih1SV8SRpWg0",
        "outputId": "2d30c3b4-47f8-4c66-f3a1-6f80d2ce13f6"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.8/dist-packages (1.0.2)\n",
            "Requirement already satisfied: numpy>=1.14.6 in /usr/local/lib/python3.8/dist-packages (from scikit-learn) (1.21.6)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.8/dist-packages (from scikit-learn) (3.1.0)\n",
            "Requirement already satisfied: scipy>=1.1.0 in /usr/local/lib/python3.8/dist-packages (from scikit-learn) (1.7.3)\n",
            "Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.8/dist-packages (from scikit-learn) (1.2.0)\n"
          ]
        }
      ],
      "source": [
        "!pip install scikit-learn"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WFuSU--BqBhh",
        "outputId": "8e352cd6-b878-4c36-f48f-6cb99331c0b8"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((1341, 35), (336, 35))"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ],
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "X_train,X_test,Y_train,Y_test = train_test_split(data,data['Attrition'],test_size = 0.2,random_state=0)\n",
        "X_train.shape,X_test.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "5jsJtaGPq2wL",
        "outputId": "ce5dfc49-b826-4c14-d8f0-bfd4b5a3353c"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           Age  DailyRate  DistanceFromHome  HourlyRate  MonthlyIncome  \\\n",
              "0     3.610918   6.396930          3.218876    3.761200       7.862112   \n",
              "1     3.583519   6.826545          2.197225    3.850148       7.972466   \n",
              "2     3.496508   6.577861          3.295837    4.394449       8.439880   \n",
              "3     3.663562   7.305860          1.098612    3.713572       8.584478   \n",
              "4     3.931826   6.925595          1.791759    3.637586       9.853982   \n",
              "...        ...        ...               ...         ...            ...   \n",
              "1672  3.433987   6.852243          0.693147    4.304065       9.073718   \n",
              "1673  3.496508   7.173192          1.098612    3.891820       8.173293   \n",
              "1674  3.401197   7.077498          3.218876    3.610918       7.939159   \n",
              "1675  3.610918   6.091310          2.302585    3.891820       8.595450   \n",
              "1676  3.610918   7.040536          3.044522    3.583519       7.860956   \n",
              "\n",
              "      MonthlyRate  TotalWorkingYears  YearsAtCompany  \n",
              "0        8.536996           2.397895        2.397895  \n",
              "1        9.285355           1.609438        1.609438  \n",
              "2        9.710873           1.609438        1.386294  \n",
              "3        9.501890           2.772589        1.945910  \n",
              "4        9.893740           3.465736        3.465736  \n",
              "...           ...                ...             ...  \n",
              "1672     9.564933           2.397895        2.397895  \n",
              "1673     9.678655           2.397895        1.609438  \n",
              "1674     9.637110           0.693147        0.693147  \n",
              "1675     8.306966           2.397895        2.397895  \n",
              "1676     9.763190           2.397895        2.197225  \n",
              "\n",
              "[1677 rows x 8 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-8920b0d0-490a-4dc3-8d55-4618ad922af7\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Age</th>\n",
              "      <th>DailyRate</th>\n",
              "      <th>DistanceFromHome</th>\n",
              "      <th>HourlyRate</th>\n",
              "      <th>MonthlyIncome</th>\n",
              "      <th>MonthlyRate</th>\n",
              "      <th>TotalWorkingYears</th>\n",
              "      <th>YearsAtCompany</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3.610918</td>\n",
              "      <td>6.396930</td>\n",
              "      <td>3.218876</td>\n",
              "      <td>3.761200</td>\n",
              "      <td>7.862112</td>\n",
              "      <td>8.536996</td>\n",
              "      <td>2.397895</td>\n",
              "      <td>2.397895</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3.583519</td>\n",
              "      <td>6.826545</td>\n",
              "      <td>2.197225</td>\n",
              "      <td>3.850148</td>\n",
              "      <td>7.972466</td>\n",
              "      <td>9.285355</td>\n",
              "      <td>1.609438</td>\n",
              "      <td>1.609438</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3.496508</td>\n",
              "      <td>6.577861</td>\n",
              "      <td>3.295837</td>\n",
              "      <td>4.394449</td>\n",
              "      <td>8.439880</td>\n",
              "      <td>9.710873</td>\n",
              "      <td>1.609438</td>\n",
              "      <td>1.386294</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3.663562</td>\n",
              "      <td>7.305860</td>\n",
              "      <td>1.098612</td>\n",
              "      <td>3.713572</td>\n",
              "      <td>8.584478</td>\n",
              "      <td>9.501890</td>\n",
              "      <td>2.772589</td>\n",
              "      <td>1.945910</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3.931826</td>\n",
              "      <td>6.925595</td>\n",
              "      <td>1.791759</td>\n",
              "      <td>3.637586</td>\n",
              "      <td>9.853982</td>\n",
              "      <td>9.893740</td>\n",
              "      <td>3.465736</td>\n",
              "      <td>3.465736</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1672</th>\n",
              "      <td>3.433987</td>\n",
              "      <td>6.852243</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>4.304065</td>\n",
              "      <td>9.073718</td>\n",
              "      <td>9.564933</td>\n",
              "      <td>2.397895</td>\n",
              "      <td>2.397895</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1673</th>\n",
              "      <td>3.496508</td>\n",
              "      <td>7.173192</td>\n",
              "      <td>1.098612</td>\n",
              "      <td>3.891820</td>\n",
              "      <td>8.173293</td>\n",
              "      <td>9.678655</td>\n",
              "      <td>2.397895</td>\n",
              "      <td>1.609438</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1674</th>\n",
              "      <td>3.401197</td>\n",
              "      <td>7.077498</td>\n",
              "      <td>3.218876</td>\n",
              "      <td>3.610918</td>\n",
              "      <td>7.939159</td>\n",
              "      <td>9.637110</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>0.693147</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1675</th>\n",
              "      <td>3.610918</td>\n",
              "      <td>6.091310</td>\n",
              "      <td>2.302585</td>\n",
              "      <td>3.891820</td>\n",
              "      <td>8.595450</td>\n",
              "      <td>8.306966</td>\n",
              "      <td>2.397895</td>\n",
              "      <td>2.397895</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1676</th>\n",
              "      <td>3.610918</td>\n",
              "      <td>7.040536</td>\n",
              "      <td>3.044522</td>\n",
              "      <td>3.583519</td>\n",
              "      <td>7.860956</td>\n",
              "      <td>9.763190</td>\n",
              "      <td>2.397895</td>\n",
              "      <td>2.197225</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1677 rows × 8 columns</p>\n",
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          },
          "metadata": {},
          "execution_count": 33
        }
      ],
      "source": [
        "for cont in cont_var:\n",
        "    data[cont] = np.log(data[cont]+1)\n",
        "\n",
        "data[cont_var]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "0wJ4FkCZrB3U"
      },
      "outputs": [],
      "source": [
        "for cat in cat_feat:\n",
        "  temp = data.groupby(cat)['Attrition'].count()/len(data)\n",
        "  temp_df = temp[temp>0.01].index\n",
        "  data[cat] = np.where(data[cat].isin(temp_df),data[cat],'Rare_var')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "YqJIi0ICrN-U",
        "outputId": "7f730d24-a832-4cb9-92cb-c089dcecb8fb"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    id       Age     BusinessTravel  DailyRate              Department  \\\n",
              "0    0  3.610918  Travel_Frequently   6.396930  Research & Development   \n",
              "1    1  3.583519      Travel_Rarely   6.826545                   Sales   \n",
              "2    2  3.496508      Travel_Rarely   6.577861                   Sales   \n",
              "3    3  3.663562      Travel_Rarely   7.305860  Research & Development   \n",
              "4    4  3.931826      Travel_Rarely   6.925595  Research & Development   \n",
              "5    5  3.332205      Travel_Rarely   6.340359  Research & Development   \n",
              "6    6  3.555348      Travel_Rarely   6.851185  Research & Development   \n",
              "7    7  3.713572      Travel_Rarely   6.917706  Research & Development   \n",
              "8    8  3.951244  Travel_Frequently   7.168580                   Sales   \n",
              "9    9  3.258097      Travel_Rarely   6.693324  Research & Development   \n",
              "10  10  3.583519      Travel_Rarely   6.786717  Research & Development   \n",
              "11  11  3.401197      Travel_Rarely   6.543912  Research & Development   \n",
              "12  12  3.663562      Travel_Rarely   4.934474  Research & Development   \n",
              "13  13  3.891820      Travel_Rarely   7.160846  Research & Development   \n",
              "14  14  3.295837      Travel_Rarely   6.785588  Research & Development   \n",
              "15  15  3.688879  Travel_Frequently   6.463029  Research & Development   \n",
              "16  16  3.526361      Travel_Rarely   6.796824  Research & Development   \n",
              "17  17  3.970292      Travel_Rarely   6.410175  Research & Development   \n",
              "18  18  3.761200      Travel_Rarely   7.310550  Research & Development   \n",
              "19  19  3.258097         Non-Travel   6.996681  Research & Development   \n",
              "\n",
              "    DistanceFromHome  Education    EducationField  EmployeeCount  \\\n",
              "0           3.218876          3           Medical              1   \n",
              "1           2.197225          3             Other              1   \n",
              "2           3.295837          3         Marketing              1   \n",
              "3           1.098612          3           Medical              1   \n",
              "4           1.791759          4           Medical              1   \n",
              "5           1.098612          3             Other              1   \n",
              "6           2.397895          4           Medical              1   \n",
              "7           1.098612          3     Life Sciences              1   \n",
              "8           1.945910          3     Life Sciences              1   \n",
              "9           2.302585          1           Medical              1   \n",
              "10          2.197225          3  Technical Degree              1   \n",
              "11          3.367296          3     Life Sciences              1   \n",
              "12          1.098612          2     Life Sciences              1   \n",
              "13          1.098612          2     Life Sciences              1   \n",
              "14          0.693147          2     Life Sciences              1   \n",
              "15          3.258097          4           Medical              1   \n",
              "16          2.484907          2     Life Sciences              1   \n",
              "17          1.098612          4  Technical Degree              1   \n",
              "18          2.302585          4     Life Sciences              1   \n",
              "19          0.693147          1           Medical              1   \n",
              "\n",
              "    EnvironmentSatisfaction  ... StandardHours  StockOptionLevel  \\\n",
              "0                         4  ...            80                 1   \n",
              "1                         1  ...            80                 1   \n",
              "2                         3  ...            80                 2   \n",
              "3                         3  ...            80                 0   \n",
              "4                         2  ...            80                 0   \n",
              "5                         3  ...            80                 0   \n",
              "6                         2  ...            80                 0   \n",
              "7                         4  ...            80                 1   \n",
              "8                         4  ...            80                 1   \n",
              "9                         3  ...            80                 1   \n",
              "10                        2  ...            80                 1   \n",
              "11                        3  ...            80                 0   \n",
              "12                        4  ...            80                 0   \n",
              "13                        2  ...            80                 1   \n",
              "14                        4  ...            80                 0   \n",
              "15                        1  ...            80                 0   \n",
              "16                        3  ...            80                 1   \n",
              "17                        2  ...            80                 0   \n",
              "18                        4  ...            80                 0   \n",
              "19                        4  ...            80                 0   \n",
              "\n",
              "    TotalWorkingYears  TrainingTimesLastYear WorkLifeBalance  YearsAtCompany  \\\n",
              "0            2.397895                      2               3        2.397895   \n",
              "1            1.609438                      3               3        1.609438   \n",
              "2            1.609438                      3               3        1.386294   \n",
              "3            2.772589                      1               1        1.945910   \n",
              "4            3.465736                      0               3        3.465736   \n",
              "5            1.945910                      0               3        0.693147   \n",
              "6            0.693147                      2               3        0.693147   \n",
              "7            1.945910                      3               2        1.386294   \n",
              "8            2.944439                      3               3        2.833213   \n",
              "9            2.302585                      2               2        2.302585   \n",
              "10           2.397895                      2               3        2.397895   \n",
              "11           2.397895                      2               3        2.302585   \n",
              "12           1.609438                      2               2        1.098612   \n",
              "13           2.890372                      3               3        2.079442   \n",
              "14           1.945910                      2               3        1.791759   \n",
              "15           3.044522                      2               2        3.044522   \n",
              "16           1.609438                      2               3        1.098612   \n",
              "17           3.367296                      5               1        2.397895   \n",
              "18           3.091042                      1               1        3.044522   \n",
              "19           1.791759                      3               4        1.791759   \n",
              "\n",
              "   YearsInCurrentRole  YearsSinceLastPromotion  YearsWithCurrManager  \\\n",
              "0                   0                        7                     8   \n",
              "1                   2                        0                     3   \n",
              "2                   2                        1                     2   \n",
              "3                   0                        0                     2   \n",
              "4                  14                        4                    10   \n",
              "5                   0                        1                     0   \n",
              "6                   0                        0                     0   \n",
              "7                   2                        1                     2   \n",
              "8                  14                        4                     9   \n",
              "9                   7                        7                     8   \n",
              "10                  9                        1                     9   \n",
              "11                  0                        0                     7   \n",
              "12                  2                        2                     2   \n",
              "13                  7                        4                     7   \n",
              "14                  4                        1                     4   \n",
              "15                  9                        6                    10   \n",
              "16                  2                        2                     2   \n",
              "17                  2                        0                     8   \n",
              "18                  7                        0                     8   \n",
              "19                  3                        1                     4   \n",
              "\n",
              "    Attrition  \n",
              "0           0  \n",
              "1           0  \n",
              "2           0  \n",
              "3           0  \n",
              "4           1  \n",
              "5           0  \n",
              "6           0  \n",
              "7           0  \n",
              "8           0  \n",
              "9           0  \n",
              "10          0  \n",
              "11          0  \n",
              "12          0  \n",
              "13          0  \n",
              "14          0  \n",
              "15          0  \n",
              "16          0  \n",
              "17          0  \n",
              "18          0  \n",
              "19          0  \n",
              "\n",
              "[20 rows x 35 columns]"
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              "      <td>1</td>\n",
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              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>0</td>\n",
              "      <td>1.945910</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>6</td>\n",
              "      <td>3.555348</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.851185</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>2.397895</td>\n",
              "      <td>4</td>\n",
              "      <td>Medical</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>0</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>7</td>\n",
              "      <td>3.713572</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.917706</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>1.098612</td>\n",
              "      <td>3</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>1.945910</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>1.386294</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>8</td>\n",
              "      <td>3.951244</td>\n",
              "      <td>Travel_Frequently</td>\n",
              "      <td>7.168580</td>\n",
              "      <td>Sales</td>\n",
              "      <td>1.945910</td>\n",
              "      <td>3</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>2.944439</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>2.833213</td>\n",
              "      <td>14</td>\n",
              "      <td>4</td>\n",
              "      <td>9</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>9</td>\n",
              "      <td>3.258097</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.693324</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>2.302585</td>\n",
              "      <td>1</td>\n",
              "      <td>Medical</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>2.302585</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2.302585</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>8</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>10</td>\n",
              "      <td>3.583519</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.786717</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>2.197225</td>\n",
              "      <td>3</td>\n",
              "      <td>Technical Degree</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>2.397895</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>2.397895</td>\n",
              "      <td>9</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>11</td>\n",
              "      <td>3.401197</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.543912</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>3.367296</td>\n",
              "      <td>3</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>0</td>\n",
              "      <td>2.397895</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>2.302585</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>12</td>\n",
              "      <td>3.663562</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>4.934474</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>1.098612</td>\n",
              "      <td>2</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>0</td>\n",
              "      <td>1.609438</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1.098612</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>13</td>\n",
              "      <td>3.891820</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>7.160846</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>1.098612</td>\n",
              "      <td>2</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>2.890372</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>2.079442</td>\n",
              "      <td>7</td>\n",
              "      <td>4</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>14</td>\n",
              "      <td>3.295837</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.785588</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>2</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>0</td>\n",
              "      <td>1.945910</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>1.791759</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>15</td>\n",
              "      <td>3.688879</td>\n",
              "      <td>Travel_Frequently</td>\n",
              "      <td>6.463029</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>3.258097</td>\n",
              "      <td>4</td>\n",
              "      <td>Medical</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>0</td>\n",
              "      <td>3.044522</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>3.044522</td>\n",
              "      <td>9</td>\n",
              "      <td>6</td>\n",
              "      <td>10</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>16</td>\n",
              "      <td>3.526361</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.796824</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>2.484907</td>\n",
              "      <td>2</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>1.609438</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>1.098612</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>17</td>\n",
              "      <td>3.970292</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.410175</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>1.098612</td>\n",
              "      <td>4</td>\n",
              "      <td>Technical Degree</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>0</td>\n",
              "      <td>3.367296</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>2.397895</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>18</td>\n",
              "      <td>3.761200</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>7.310550</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>2.302585</td>\n",
              "      <td>4</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>0</td>\n",
              "      <td>3.091042</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>3.044522</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>19</td>\n",
              "      <td>3.258097</td>\n",
              "      <td>Non-Travel</td>\n",
              "      <td>6.996681</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>1</td>\n",
              "      <td>Medical</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>0</td>\n",
              "      <td>1.791759</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>1.791759</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>20 rows × 35 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-09c63915-1d46-42ad-b57f-75d572a77586')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-09c63915-1d46-42ad-b57f-75d572a77586 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-09c63915-1d46-42ad-b57f-75d572a77586');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ],
      "source": [
        "data.head(20)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "zOMyXZ4CtN9_"
      },
      "outputs": [],
      "source": [
        "for feature in cat_feat:\n",
        "    labels_ordered=data.groupby([feature])['Attrition'].mean().sort_values().index\n",
        "    labels_ordered={k:i for i,k in enumerate(labels_ordered,0)}\n",
        "    data[feature]=data[feature].map(labels_ordered)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "12lV5tT8uiJn",
        "outputId": "dbb26f3a-0d49-41a5-e674-a0ce4d1fad0c"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        id       Age  BusinessTravel  DailyRate  Department  DistanceFromHome  \\\n",
              "0        0  3.610918               2   6.396930           0          3.218876   \n",
              "1        1  3.583519               1   6.826545           1          2.197225   \n",
              "2        2  3.496508               1   6.577861           1          3.295837   \n",
              "3        3  3.663562               1   7.305860           0          1.098612   \n",
              "4        4  3.931826               1   6.925595           0          1.791759   \n",
              "...    ...       ...             ...        ...         ...               ...   \n",
              "1672  1672  3.433987               1   6.852243           1          0.693147   \n",
              "1673  1673  3.496508               1   7.173192           0          1.098612   \n",
              "1674  1674  3.401197               2   7.077498           2          3.218876   \n",
              "1675  1675  3.610918               1   6.091310           1          2.302585   \n",
              "1676  1676  3.610918               1   7.040536           0          3.044522   \n",
              "\n",
              "      Education  EducationField  EmployeeCount  EnvironmentSatisfaction  ...  \\\n",
              "0             3               2              1                        4  ...   \n",
              "1             3               0              1                        1  ...   \n",
              "2             3               4              1                        3  ...   \n",
              "3             3               2              1                        3  ...   \n",
              "4             4               2              1                        2  ...   \n",
              "...         ...             ...            ...                      ...  ...   \n",
              "1672          3               1              1                        4  ...   \n",
              "1673          3               1              1                        1  ...   \n",
              "1674          3               5              1                        2  ...   \n",
              "1675          2               4              1                        2  ...   \n",
              "1676          3               1              1                        3  ...   \n",
              "\n",
              "      StandardHours  StockOptionLevel  TotalWorkingYears  \\\n",
              "0                80                 1           2.397895   \n",
              "1                80                 1           1.609438   \n",
              "2                80                 2           1.609438   \n",
              "3                80                 0           2.772589   \n",
              "4                80                 0           3.465736   \n",
              "...             ...               ...                ...   \n",
              "1672             80                 0           2.397895   \n",
              "1673             80                 1           2.397895   \n",
              "1674             80                 0           0.693147   \n",
              "1675             80                 2           2.397895   \n",
              "1676             80                 0           2.397895   \n",
              "\n",
              "      TrainingTimesLastYear  WorkLifeBalance  YearsAtCompany  \\\n",
              "0                         2                3        2.397895   \n",
              "1                         3                3        1.609438   \n",
              "2                         3                3        1.386294   \n",
              "3                         1                1        1.945910   \n",
              "4                         0                3        3.465736   \n",
              "...                     ...              ...             ...   \n",
              "1672                      2                4        2.397895   \n",
              "1673                      3                4        1.609438   \n",
              "1674                      2                3        0.693147   \n",
              "1675                      3                2        2.397895   \n",
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              "      YearsInCurrentRole  YearsSinceLastPromotion  YearsWithCurrManager  \\\n",
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              "\n",
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            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ],
      "source": [
        "data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eNq7WeodulUq",
        "outputId": "3a375cc5-44a5-4bd4-df01-5ab3b094edfb"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "MinMaxScaler()"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ],
      "source": [
        "feature = [feat for feat in data.columns if feat not in ['id','Attrition']]\n",
        "\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "\n",
        "scaler = MinMaxScaler(copy=True,feature_range=(0,1))\n",
        "scaler.fit(data[feature])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "qvn342Bxwc_o"
      },
      "outputs": [],
      "source": [
        "new_train = pd.concat([data[['id','Attrition']].reset_index(drop=True),pd.DataFrame(scaler.transform(data[feature]),columns = feature)],axis=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "9DyI2Czhw83_"
      },
      "outputs": [],
      "source": [
        "new_train.to_csv('Xtrain.csv',index=False)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install scikit-learn\n",
        "from sklearn.linear_model import Lasso\n",
        "from sklearn.feature_selection import SelectFromModel\n",
        "\n",
        "dataset = pd.read_csv('Xtrain.csv')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lMpAzG9a7T5H",
        "outputId": "5e68cf4b-4b6a-4717-a497-9c5a8595dad2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.8/dist-packages (1.0.2)\n",
            "Requirement already satisfied: scipy>=1.1.0 in /usr/local/lib/python3.8/dist-packages (from scikit-learn) (1.7.3)\n",
            "Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.8/dist-packages (from scikit-learn) (1.2.0)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.8/dist-packages (from scikit-learn) (3.1.0)\n",
            "Requirement already satisfied: numpy>=1.14.6 in /usr/local/lib/python3.8/dist-packages (from scikit-learn) (1.21.6)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataset"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "pAvajCN-4c8w",
        "outputId": "b0a634f8-6ecb-4f8b-89f9-8bb2d335c114"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        id  Attrition       Age  BusinessTravel  DailyRate  Department  \\\n",
              "0        0          0  0.571381             1.0   0.477364         0.0   \n",
              "1        1          0  0.547892             0.5   0.596960         0.5   \n",
              "2        2          0  0.473296             0.5   0.527731         0.5   \n",
              "3        3          0  0.616513             0.5   0.730391         0.0   \n",
              "4        4          1  0.846500             0.5   0.624533         0.0   \n",
              "...    ...        ...       ...             ...        ...         ...   \n",
              "1672  1672          0  0.419696             0.5   0.604113         0.5   \n",
              "1673  1673          0  0.473296             0.5   0.693459         0.0   \n",
              "1674  1674          1  0.391585             1.0   0.666820         1.0   \n",
              "1675  1675          0  0.571381             0.5   0.392286         0.5   \n",
              "1676  1676          0  0.571381             0.5   0.656530         0.0   \n",
              "\n",
              "      DistanceFromHome  Education  EducationField  EmployeeCount  ...  \\\n",
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          "metadata": {},
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    {
      "cell_type": "code",
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        "ytrain = dataset[['Attrition']]"
      ],
      "metadata": {
        "id": "OFVt1Doz5Ij5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
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        "xtrain = dataset.drop(['id','Attrition'],axis=1)"
      ],
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        "id": "3kt0c2K15N4o"
      },
      "execution_count": null,
      "outputs": []
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        "xtrain"
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        "id": "7xBS2CbK5fVR",
        "outputId": "84211540-836f-4037-864e-5271c349a638"
      },
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      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           Age  BusinessTravel  DailyRate  Department  DistanceFromHome  \\\n",
              "0     0.571381             1.0   0.477364         0.0          0.932674   \n",
              "1     0.547892             0.5   0.596960         0.5          0.555410   \n",
              "2     0.473296             0.5   0.527731         0.5          0.961094   \n",
              "3     0.616513             0.5   0.730391         0.0          0.149726   \n",
              "4     0.846500             0.5   0.624533         0.0          0.405684   \n",
              "...        ...             ...        ...         ...               ...   \n",
              "1672  0.419696             0.5   0.604113         0.5          0.000000   \n",
              "1673  0.473296             0.5   0.693459         0.0          0.149726   \n",
              "1674  0.391585             1.0   0.666820         1.0          0.932674   \n",
              "1675  0.571381             0.5   0.392286         0.5          0.594316   \n",
              "1676  0.571381             0.5   0.656530         0.0          0.868291   \n",
              "\n",
              "      Education  EducationField  EmployeeCount  EnvironmentSatisfaction  \\\n",
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              "4      0.214286             0.4            0.0                 0.333333   \n",
              "...         ...             ...            ...                      ...   \n",
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              "1673   0.142857             0.2            0.0                 0.000000   \n",
              "1674   0.142857             1.0            0.0                 0.333333   \n",
              "1675   0.071429             0.8            0.0                 0.333333   \n",
              "1676   0.142857             0.2            0.0                 0.666667   \n",
              "\n",
              "      Gender  ...  RelationshipSatisfaction  StandardHours  StockOptionLevel  \\\n",
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              "1        1.0  ...                  1.000000            0.0          0.333333   \n",
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              "3        0.0  ...                  0.666667            0.0          0.000000   \n",
              "4        0.0  ...                  0.666667            0.0          0.000000   \n",
              "...      ...  ...                       ...            ...               ...   \n",
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              "1673     1.0  ...                  1.000000            0.0          0.333333   \n",
              "1674     1.0  ...                  0.666667            0.0          0.000000   \n",
              "1675     1.0  ...                  0.666667            0.0          0.666667   \n",
              "1676     0.0  ...                  1.000000            0.0          0.000000   \n",
              "\n",
              "      TotalWorkingYears  TrainingTimesLastYear  WorkLifeBalance  \\\n",
              "0              0.641548               0.333333         0.666667   \n",
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              "...                 ...                    ...              ...   \n",
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              "1673           0.641548               0.500000         1.000000   \n",
              "1674           0.185449               0.333333         0.666667   \n",
              "1675           0.641548               0.500000         0.333333   \n",
              "1676           0.641548               0.500000         0.333333   \n",
              "\n",
              "      YearsAtCompany  YearsInCurrentRole  YearsSinceLastPromotion  \\\n",
              "0           0.641548            0.000000                 0.466667   \n",
              "1           0.430599            0.111111                 0.000000   \n",
              "2           0.370898            0.111111                 0.066667   \n",
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              "1675        0.641548            0.166667                 0.000000   \n",
              "1676        0.587859            0.111111                 0.466667   \n",
              "\n",
              "      YearsWithCurrManager  \n",
              "0                 0.470588  \n",
              "1                 0.176471  \n",
              "2                 0.117647  \n",
              "3                 0.117647  \n",
              "4                 0.588235  \n",
              "...                    ...  \n",
              "1672              0.470588  \n",
              "1673              0.176471  \n",
              "1674              0.000000  \n",
              "1675              0.470588  \n",
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              "          dataTable['output_type'] = 'display_data';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 49
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    {
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        "ytrain"
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      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "select_mod = SelectFromModel(Lasso(alpha=0.005,random_state=0))\n",
        "select_mod.fit(xtrain,ytrain)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WQSHTrnC5jxb",
        "outputId": "51f4eefe-4a8f-491b-a948-dbd02e794c3c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "SelectFromModel(estimator=Lasso(alpha=0.005, random_state=0))"
            ]
          },
          "metadata": {},
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "select_mod.get_support()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YRlQb6ix5_MN",
        "outputId": "c21f5205-1247-4824-fd2d-ecbe79dd1d21"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ True,  True, False, False, False, False, False, False,  True,\n",
              "       False, False,  True, False,  True,  True,  True, False, False,\n",
              "       False, False,  True, False, False,  True, False,  True, False,\n",
              "       False, False,  True, False, False, False])"
            ]
          },
          "metadata": {},
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "selected_feature = xtrain.columns[(select_mod.get_support())]\n",
        "\n",
        "print(f\"Total number of feature : {dataset.shape[1]}\")\n",
        "print(f\"Selected feature : {len(selected_feature)}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hobxuQQq6FV3",
        "outputId": "1e83a8d3-a9ff-434f-9dd8-65f42aac72e2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Total number of feature : 35\n",
            "Selected feature : 11\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "selected_feature"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RjHVSVPX61a8",
        "outputId": "d3627f2a-366f-45b7-dca6-599a7eb2f0fb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Age', 'BusinessTravel', 'EnvironmentSatisfaction', 'JobInvolvement',\n",
              "       'JobRole', 'JobSatisfaction', 'MaritalStatus', 'OverTime',\n",
              "       'RelationshipSatisfaction', 'StockOptionLevel', 'YearsAtCompany'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "final_x_train = dataset[selected_feature]"
      ],
      "metadata": {
        "id": "uCPIc2Gq7CZL"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "final_x_train"
      ],
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          "height": 488
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        "outputId": "5eb12f69-0a4f-4697-d196-674c73936697"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           Age  BusinessTravel  EnvironmentSatisfaction  JobInvolvement  \\\n",
              "0     0.571381             1.0                 1.000000        0.666667   \n",
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              "\n",
              "      JobRole  JobSatisfaction  MaritalStatus  OverTime  \\\n",
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              "\n",
              "      RelationshipSatisfaction  StockOptionLevel  YearsAtCompany  \n",
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              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.587859</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1677 rows × 11 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d42e157e-e8d8-436b-8657-9bb12f4558fa')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      \n",
              "  <style>\n",
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              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
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              "      border-radius: 50%;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-d42e157e-e8d8-436b-8657-9bb12f4558fa');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.ensemble import RandomForestClassifier\n",
        "\n",
        "model = RandomForestClassifier(max_depth = 11)"
      ],
      "metadata": {
        "id": "-hOGrYWR7Mmm"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.fit(final_x_train,ytrain)\n",
        "print(f\"Accuracy on training data{model.score(final_x_train,ytrain)}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dFr-uyL28J5c",
        "outputId": "2d573275-9e32-45c2-a269-74a17710a76c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-65-33940ce5cc93>:1: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "  model.fit(final_x_train,ytrain)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy on training data0.9994036970781157\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for cont in cont_var:\n",
        "    X_test[cont] = np.log(X_test[cont]+1)\n",
        "\n",
        "X_test"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 644
        },
        "id": "NgMwQXSS8fnP",
        "outputId": "483dd2b7-474b-4401-acd2-899a079fc1a6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        id       Age     BusinessTravel  DailyRate              Department  \\\n",
              "1142  1142  3.465736  Travel_Frequently   6.748760  Research & Development   \n",
              "1044  1044  3.761200  Travel_Frequently   7.019297  Research & Development   \n",
              "1000  1000  3.401197      Travel_Rarely   6.196444  Research & Development   \n",
              "1121  1121  3.433987      Travel_Rarely   7.300473  Research & Development   \n",
              "1212  1212  3.912023      Travel_Rarely   6.897705  Research & Development   \n",
              "...    ...       ...                ...        ...                     ...   \n",
              "948    948  3.583519      Travel_Rarely   6.714171  Research & Development   \n",
              "61      61  3.332205      Travel_Rarely   7.001246  Research & Development   \n",
              "674    674  3.713572  Travel_Frequently   6.792344  Research & Development   \n",
              "1439  1439  3.610918      Travel_Rarely   6.890609  Research & Development   \n",
              "319    319  3.637586      Travel_Rarely   6.957497                   Sales   \n",
              "\n",
              "      DistanceFromHome  Education    EducationField  EmployeeCount  \\\n",
              "1142          3.258097          2     Life Sciences              1   \n",
              "1044          3.218876          4     Life Sciences              1   \n",
              "1000          3.401197          3     Life Sciences              1   \n",
              "1121          3.332205          4             Other              1   \n",
              "1212          1.945910          3           Medical              1   \n",
              "...                ...        ...               ...            ...   \n",
              "948           3.367296          2  Technical Degree              1   \n",
              "61            2.833213          4     Life Sciences              1   \n",
              "674           1.791759          3     Life Sciences              1   \n",
              "1439          2.302585          3           Medical              1   \n",
              "319           1.098612          4         Marketing              1   \n",
              "\n",
              "      EnvironmentSatisfaction  ... StandardHours  StockOptionLevel  \\\n",
              "1142                        4  ...            80                 0   \n",
              "1044                        3  ...            80                 1   \n",
              "1000                        4  ...            80                 0   \n",
              "1121                        3  ...            80                 1   \n",
              "1212                        4  ...            80                 1   \n",
              "...                       ...  ...           ...               ...   \n",
              "948                         3  ...            80                 3   \n",
              "61                          4  ...            80                 1   \n",
              "674                         1  ...            80                 0   \n",
              "1439                        1  ...            80                 1   \n",
              "319                         4  ...            80                 1   \n",
              "\n",
              "      TotalWorkingYears  TrainingTimesLastYear WorkLifeBalance  \\\n",
              "1142           2.397895                      3               4   \n",
              "1044           1.945910                      3               3   \n",
              "1000           2.484907                      2               3   \n",
              "1121           1.609438                      4               3   \n",
              "1212           3.178054                      2               3   \n",
              "...                 ...                    ...             ...   \n",
              "948            1.945910                      4               1   \n",
              "61             1.945910                      1               2   \n",
              "674            1.945910                      3               2   \n",
              "1439           2.397895                      5               2   \n",
              "319            2.079442                      2               3   \n",
              "\n",
              "      YearsAtCompany YearsInCurrentRole  YearsSinceLastPromotion  \\\n",
              "1142        2.397895                  9                        4   \n",
              "1044        1.945910                  3                        0   \n",
              "1000        2.484907                 10                        1   \n",
              "1121        1.386294                  2                        1   \n",
              "1212        2.197225                  7                        7   \n",
              "...              ...                ...                      ...   \n",
              "948         1.791759                  4                        4   \n",
              "61          1.945910                  4                        1   \n",
              "674         1.609438                  3                        1   \n",
              "1439        2.397895                  8                        0   \n",
              "319         1.791759                  4                        0   \n",
              "\n",
              "      YearsWithCurrManager  Attrition  \n",
              "1142                     8          0  \n",
              "1044                     4          0  \n",
              "1000                     9          0  \n",
              "1121                     2          0  \n",
              "1212                     7          0  \n",
              "...                    ...        ...  \n",
              "948                      3          1  \n",
              "61                       3          0  \n",
              "674                      3          1  \n",
              "1439                     7          0  \n",
              "319                      3          0  \n",
              "\n",
              "[336 rows x 35 columns]"
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              "      <th>id</th>\n",
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              "      <th>1044</th>\n",
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              "      <td>7.019297</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>3.218876</td>\n",
              "      <td>4</td>\n",
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              "      <td>Travel_Rarely</td>\n",
              "      <td>6.196444</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>3.401197</td>\n",
              "      <td>3</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
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              "      <td>80</td>\n",
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              "      <td>2.484907</td>\n",
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              "      <td>2.484907</td>\n",
              "      <td>10</td>\n",
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              "      <th>1121</th>\n",
              "      <td>1121</td>\n",
              "      <td>3.433987</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>7.300473</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>3.332205</td>\n",
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              "      <th>1212</th>\n",
              "      <td>1212</td>\n",
              "      <td>3.912023</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.897705</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>1.945910</td>\n",
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              "      <td>6.714171</td>\n",
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              "      <td>3.367296</td>\n",
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              "      <th>61</th>\n",
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              "      <td>Travel_Rarely</td>\n",
              "      <td>7.001246</td>\n",
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              "      <td>80</td>\n",
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              "      <th>1439</th>\n",
              "      <td>1439</td>\n",
              "      <td>3.610918</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.890609</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>2.302585</td>\n",
              "      <td>3</td>\n",
              "      <td>Medical</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "      <td>8</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
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              "    <tr>\n",
              "      <th>319</th>\n",
              "      <td>319</td>\n",
              "      <td>3.637586</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.957497</td>\n",
              "      <td>Sales</td>\n",
              "      <td>1.098612</td>\n",
              "      <td>4</td>\n",
              "      <td>Marketing</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>2.079442</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>1.791759</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>336 rows × 35 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-df1c5f5f-14c2-4acb-9bee-67d86084c61a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-df1c5f5f-14c2-4acb-9bee-67d86084c61a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for cat in cat_feat:\n",
        "  temp = X_test.groupby(cat)['Attrition'].count()/len(data)\n",
        "  temp_df = temp[temp>0.01].index\n",
        "  X_test[cat] = np.where(X_test[cat].isin(temp_df),X_test[cat],'Rare_var')"
      ],
      "metadata": {
        "id": "XQ0XBAV99L84"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_test.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        },
        "id": "QFMGO3-m9zDh",
        "outputId": "edb03eef-feba-4591-83cf-b7cb6da66ab3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        id       Age     BusinessTravel  DailyRate              Department  \\\n",
              "1142  1142  3.465736  Travel_Frequently   6.748760  Research & Development   \n",
              "1044  1044  3.761200  Travel_Frequently   7.019297  Research & Development   \n",
              "1000  1000  3.401197      Travel_Rarely   6.196444  Research & Development   \n",
              "1121  1121  3.433987      Travel_Rarely   7.300473  Research & Development   \n",
              "1212  1212  3.912023      Travel_Rarely   6.897705  Research & Development   \n",
              "\n",
              "      DistanceFromHome  Education EducationField  EmployeeCount  \\\n",
              "1142          3.258097          2  Life Sciences              1   \n",
              "1044          3.218876          4  Life Sciences              1   \n",
              "1000          3.401197          3  Life Sciences              1   \n",
              "1121          3.332205          4          Other              1   \n",
              "1212          1.945910          3        Medical              1   \n",
              "\n",
              "      EnvironmentSatisfaction  ... StandardHours  StockOptionLevel  \\\n",
              "1142                        4  ...            80                 0   \n",
              "1044                        3  ...            80                 1   \n",
              "1000                        4  ...            80                 0   \n",
              "1121                        3  ...            80                 1   \n",
              "1212                        4  ...            80                 1   \n",
              "\n",
              "      TotalWorkingYears  TrainingTimesLastYear WorkLifeBalance  \\\n",
              "1142           2.397895                      3               4   \n",
              "1044           1.945910                      3               3   \n",
              "1000           2.484907                      2               3   \n",
              "1121           1.609438                      4               3   \n",
              "1212           3.178054                      2               3   \n",
              "\n",
              "      YearsAtCompany YearsInCurrentRole  YearsSinceLastPromotion  \\\n",
              "1142        2.397895                  9                        4   \n",
              "1044        1.945910                  3                        0   \n",
              "1000        2.484907                 10                        1   \n",
              "1121        1.386294                  2                        1   \n",
              "1212        2.197225                  7                        7   \n",
              "\n",
              "      YearsWithCurrManager  Attrition  \n",
              "1142                     8          0  \n",
              "1044                     4          0  \n",
              "1000                     9          0  \n",
              "1121                     2          0  \n",
              "1212                     7          0  \n",
              "\n",
              "[5 rows x 35 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-126f6c93-18db-486d-bc60-fffde95cb105\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
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              "      <th>YearsInCurrentRole</th>\n",
              "      <th>YearsSinceLastPromotion</th>\n",
              "      <th>YearsWithCurrManager</th>\n",
              "      <th>Attrition</th>\n",
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              "  </thead>\n",
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              "      <th>1142</th>\n",
              "      <td>1142</td>\n",
              "      <td>3.465736</td>\n",
              "      <td>Travel_Frequently</td>\n",
              "      <td>6.748760</td>\n",
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              "      <th>1044</th>\n",
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              "      <td>Travel_Frequently</td>\n",
              "      <td>7.019297</td>\n",
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              "      <td>3.218876</td>\n",
              "      <td>4</td>\n",
              "      <td>Life Sciences</td>\n",
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              "      <th>1000</th>\n",
              "      <td>1000</td>\n",
              "      <td>3.401197</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.196444</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>3.401197</td>\n",
              "      <td>3</td>\n",
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              "      <td>4</td>\n",
              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>0</td>\n",
              "      <td>2.484907</td>\n",
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              "      <td>3</td>\n",
              "      <td>2.484907</td>\n",
              "      <td>10</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>1121</th>\n",
              "      <td>1121</td>\n",
              "      <td>3.433987</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>7.300473</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>3.332205</td>\n",
              "      <td>4</td>\n",
              "      <td>Other</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
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              "      <td>80</td>\n",
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              "      <td>1.609438</td>\n",
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              "      <th>1212</th>\n",
              "      <td>1212</td>\n",
              "      <td>3.912023</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.897705</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>1.945910</td>\n",
              "      <td>3</td>\n",
              "      <td>Medical</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>...</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>3.178054</td>\n",
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              "      <td>2.197225</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
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              "  </tbody>\n",
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              "<p>5 rows × 35 columns</p>\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-126f6c93-18db-486d-bc60-fffde95cb105');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for feature in cat_feat:\n",
        "    labels_ordered=X_test.groupby([feature])['Attrition'].mean().sort_values().index\n",
        "    labels_ordered={k:i for i,k in enumerate(labels_ordered,0)}\n",
        "    X_test[feature]=X_test[feature].map(labels_ordered)"
      ],
      "metadata": {
        "id": "3qabQyag91Z-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_test"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "GCR8P9gP-Bmi",
        "outputId": "d4c0f171-ddbb-4219-f7e9-d4b244085179"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        id       Age  BusinessTravel  DailyRate  Department  DistanceFromHome  \\\n",
              "1142  1142  3.465736               2   6.748760           1          3.258097   \n",
              "1044  1044  3.761200               2   7.019297           1          3.218876   \n",
              "1000  1000  3.401197               1   6.196444           1          3.401197   \n",
              "1121  1121  3.433987               1   7.300473           1          3.332205   \n",
              "1212  1212  3.912023               1   6.897705           1          1.945910   \n",
              "...    ...       ...             ...        ...         ...               ...   \n",
              "948    948  3.583519               1   6.714171           1          3.367296   \n",
              "61      61  3.332205               1   7.001246           1          2.833213   \n",
              "674    674  3.713572               2   6.792344           1          1.791759   \n",
              "1439  1439  3.610918               1   6.890609           1          2.302585   \n",
              "319    319  3.637586               1   6.957497           2          1.098612   \n",
              "\n",
              "      Education  EducationField  EmployeeCount  EnvironmentSatisfaction  ...  \\\n",
              "1142          2               1              1                        4  ...   \n",
              "1044          4               1              1                        3  ...   \n",
              "1000          3               1              1                        4  ...   \n",
              "1121          4               3              1                        3  ...   \n",
              "1212          3               2              1                        4  ...   \n",
              "...         ...             ...            ...                      ...  ...   \n",
              "948           2               4              1                        3  ...   \n",
              "61            4               1              1                        4  ...   \n",
              "674           3               1              1                        1  ...   \n",
              "1439          3               2              1                        1  ...   \n",
              "319           4               5              1                        4  ...   \n",
              "\n",
              "      StandardHours  StockOptionLevel  TotalWorkingYears  \\\n",
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              "1439             80                 1           2.397895   \n",
              "319              80                 1           2.079442   \n",
              "\n",
              "      TrainingTimesLastYear  WorkLifeBalance  YearsAtCompany  \\\n",
              "1142                      3                4        2.397895   \n",
              "1044                      3                3        1.945910   \n",
              "1000                      2                3        2.484907   \n",
              "1121                      4                3        1.386294   \n",
              "1212                      2                3        2.197225   \n",
              "...                     ...              ...             ...   \n",
              "948                       4                1        1.791759   \n",
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              "1439                      5                2        2.397895   \n",
              "319                       2                3        1.791759   \n",
              "\n",
              "      YearsInCurrentRole  YearsSinceLastPromotion  YearsWithCurrManager  \\\n",
              "1142                   9                        4                     8   \n",
              "1044                   3                        0                     4   \n",
              "1000                  10                        1                     9   \n",
              "1121                   2                        1                     2   \n",
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              "948                    4                        4                     3   \n",
              "61                     4                        1                     3   \n",
              "674                    3                        1                     3   \n",
              "1439                   8                        0                     7   \n",
              "319                    4                        0                     3   \n",
              "\n",
              "      Attrition  \n",
              "1142          0  \n",
              "1044          0  \n",
              "1000          0  \n",
              "1121          0  \n",
              "1212          0  \n",
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              "948           1  \n",
              "61            0  \n",
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              "<p>336 rows × 35 columns</p>\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 72
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "feature = [feat for feat in X_test.columns if feat not in ['id','Attrition']]\n",
        "\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "\n",
        "scaler = MinMaxScaler(copy=True,feature_range=(0,1))\n",
        "scaler.fit(X_test[feature])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g0QTYIaC-DkP",
        "outputId": "030117f3-2edf-44fd-9d7a-eea54ae073a5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "MinMaxScaler()"
            ]
          },
          "metadata": {},
          "execution_count": 73
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_test.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "id": "JAKgI8-6-Tc5",
        "outputId": "f28074c9-127d-4921-9ce3-52c0289a58ec"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        id       Age  BusinessTravel  DailyRate  Department  DistanceFromHome  \\\n",
              "1142  1142  3.465736               2   6.748760           1          3.258097   \n",
              "1044  1044  3.761200               2   7.019297           1          3.218876   \n",
              "1000  1000  3.401197               1   6.196444           1          3.401197   \n",
              "1121  1121  3.433987               1   7.300473           1          3.332205   \n",
              "1212  1212  3.912023               1   6.897705           1          1.945910   \n",
              "\n",
              "      Education  EducationField  EmployeeCount  EnvironmentSatisfaction  ...  \\\n",
              "1142          2               1              1                        4  ...   \n",
              "1044          4               1              1                        3  ...   \n",
              "1000          3               1              1                        4  ...   \n",
              "1121          4               3              1                        3  ...   \n",
              "1212          3               2              1                        4  ...   \n",
              "\n",
              "      StandardHours  StockOptionLevel  TotalWorkingYears  \\\n",
              "1142             80                 0           2.397895   \n",
              "1044             80                 1           1.945910   \n",
              "1000             80                 0           2.484907   \n",
              "1121             80                 1           1.609438   \n",
              "1212             80                 1           3.178054   \n",
              "\n",
              "      TrainingTimesLastYear  WorkLifeBalance  YearsAtCompany  \\\n",
              "1142                      3                4        2.397895   \n",
              "1044                      3                3        1.945910   \n",
              "1000                      2                3        2.484907   \n",
              "1121                      4                3        1.386294   \n",
              "1212                      2                3        2.197225   \n",
              "\n",
              "      YearsInCurrentRole  YearsSinceLastPromotion  YearsWithCurrManager  \\\n",
              "1142                   9                        4                     8   \n",
              "1044                   3                        0                     4   \n",
              "1000                  10                        1                     9   \n",
              "1121                   2                        1                     2   \n",
              "1212                   7                        7                     7   \n",
              "\n",
              "      Attrition  \n",
              "1142          0  \n",
              "1044          0  \n",
              "1000          0  \n",
              "1121          0  \n",
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              "       id  Attrition       Age  BusinessTravel  DailyRate  Department  \\\n",
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              "     RelationshipSatisfaction  StandardHours  StockOptionLevel  \\\n",
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              "      <td>0.333333</td>\n",
              "      <td>0.452681</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>0.389918</td>\n",
              "      <td>0.117647</td>\n",
              "      <td>0.066667</td>\n",
              "      <td>0.142857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1212</td>\n",
              "      <td>0</td>\n",
              "      <td>0.841446</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.839861</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.462607</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.4</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.893880</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>0.618005</td>\n",
              "      <td>0.411765</td>\n",
              "      <td>0.466667</td>\n",
              "      <td>0.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>331</th>\n",
              "      <td>948</td>\n",
              "      <td>1</td>\n",
              "      <td>0.555767</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.769127</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.987481</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.8</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.547319</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.503962</td>\n",
              "      <td>0.235294</td>\n",
              "      <td>0.266667</td>\n",
              "      <td>0.214286</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>332</th>\n",
              "      <td>61</td>\n",
              "      <td>0</td>\n",
              "      <td>0.337215</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.879766</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.790261</td>\n",
              "      <td>0.75</td>\n",
              "      <td>0.2</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.547319</td>\n",
              "      <td>0.166667</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.547319</td>\n",
              "      <td>0.235294</td>\n",
              "      <td>0.066667</td>\n",
              "      <td>0.214286</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>333</th>\n",
              "      <td>674</td>\n",
              "      <td>1</td>\n",
              "      <td>0.668866</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.799256</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.405684</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.2</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.547319</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.452681</td>\n",
              "      <td>0.176471</td>\n",
              "      <td>0.066667</td>\n",
              "      <td>0.214286</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>334</th>\n",
              "      <td>1439</td>\n",
              "      <td>0</td>\n",
              "      <td>0.579594</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.837127</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.594316</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.4</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.674447</td>\n",
              "      <td>0.833333</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.674447</td>\n",
              "      <td>0.470588</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>335</th>\n",
              "      <td>319</td>\n",
              "      <td>0</td>\n",
              "      <td>0.602786</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.862905</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.149726</td>\n",
              "      <td>0.75</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.584877</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.666667</td>\n",
              "      <td>0.503962</td>\n",
              "      <td>0.235294</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.214286</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>336 rows × 35 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-dbeeab0e-b10b-45f0-997e-36d93d01beeb')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "          const element = document.querySelector('#df-dbeeab0e-b10b-45f0-997e-36d93d01beeb');\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 76
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x_test=new_test[selected_feature]\n",
        "y_test=new_test['Attrition']"
      ],
      "metadata": {
        "id": "SSG56Pbk-k6B"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(f\"Accuracy on training data{model.score(x_test,y_test)}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IBmHe9pe-7uw",
        "outputId": "7ad801d5-accc-4b63-ce57-8cdf53e82b47"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy on training data0.9821428571428571\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "test = pd.read_csv('test.csv')"
      ],
      "metadata": {
        "id": "5b2eNmRC_EIP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "test"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 626
        },
        "id": "dh-HMS3L_K1w",
        "outputId": "8e8fcb13-e75f-4ae6-d196-4fe7a8f46d73"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        id  Age     BusinessTravel  DailyRate              Department  \\\n",
              "0     1677   19         Non-Travel        992  Research & Development   \n",
              "1     1678   45      Travel_Rarely       1136                   Sales   \n",
              "2     1679   37      Travel_Rarely        155  Research & Development   \n",
              "3     1680   32      Travel_Rarely        688  Research & Development   \n",
              "4     1681   29  Travel_Frequently        464  Research & Development   \n",
              "...    ...  ...                ...        ...                     ...   \n",
              "1114  2791   31      Travel_Rarely        755                   Sales   \n",
              "1115  2792   40      Travel_Rarely        654  Research & Development   \n",
              "1116  2793   42  Travel_Frequently        884  Research & Development   \n",
              "1117  2794   25  Travel_Frequently       1469                   Sales   \n",
              "1118  2795   42      Travel_Rarely       1234  Research & Development   \n",
              "\n",
              "      DistanceFromHome  Education    EducationField  EmployeeCount  \\\n",
              "0                    1          1           Medical              1   \n",
              "1                    4          4         Marketing              1   \n",
              "2                   13          3     Life Sciences              1   \n",
              "3                    1          4     Life Sciences              1   \n",
              "4                    9          1     Life Sciences              1   \n",
              "...                ...        ...               ...            ...   \n",
              "1114                 1          1     Life Sciences              1   \n",
              "1115                26          5           Medical              1   \n",
              "1116                 1          4           Medical              1   \n",
              "1117                 1          2  Technical Degree              1   \n",
              "1118                 2          4     Life Sciences              1   \n",
              "\n",
              "      EnvironmentSatisfaction  ... RelationshipSatisfaction  StandardHours  \\\n",
              "0                           4  ...                        4             80   \n",
              "1                           3  ...                        3             80   \n",
              "2                           4  ...                        2             80   \n",
              "3                           3  ...                        3             80   \n",
              "4                           3  ...                        1             80   \n",
              "...                       ...  ...                      ...            ...   \n",
              "1114                        3  ...                        3             80   \n",
              "1115                        3  ...                        4             80   \n",
              "1116                        2  ...                        1             80   \n",
              "1117                        3  ...                        4             80   \n",
              "1118                        3  ...                        3             80   \n",
              "\n",
              "      StockOptionLevel  TotalWorkingYears TrainingTimesLastYear  \\\n",
              "0                    0                  1                     2   \n",
              "1                    1                  7                     3   \n",
              "2                    2                 13                     2   \n",
              "3                    0                 14                     2   \n",
              "4                    0                  1                     5   \n",
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              "1114                 1                  1                     1   \n",
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              "1116                 1                 10                     2   \n",
              "1117                 1                  5                     2   \n",
              "1118                 1                 23                     2   \n",
              "\n",
              "      WorkLifeBalance YearsAtCompany  YearsInCurrentRole  \\\n",
              "0                   2              1                   0   \n",
              "1                   3              2                   2   \n",
              "2                   2              7                   7   \n",
              "3                   2             14                  10   \n",
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              "1114                3              1                   0   \n",
              "1115                3             20                  10   \n",
              "1116                2              5                   3   \n",
              "1117                3              4                   2   \n",
              "1118                3             12                   7   \n",
              "\n",
              "      YearsSinceLastPromotion  YearsWithCurrManager  \n",
              "0                           0                     0  \n",
              "1                           2                     2  \n",
              "2                           1                     7  \n",
              "3                          11                     8  \n",
              "4                           0                     0  \n",
              "...                       ...                   ...  \n",
              "1114                        0                     0  \n",
              "1115                        1                     8  \n",
              "1116                        0                     2  \n",
              "1117                        1                     3  \n",
              "1118                        4                     9  \n",
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              "      <td>4</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>3</td>\n",
              "      <td>80</td>\n",
              "      <td>0</td>\n",
              "      <td>14</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>14</td>\n",
              "      <td>10</td>\n",
              "      <td>11</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1681</td>\n",
              "      <td>29</td>\n",
              "      <td>Travel_Frequently</td>\n",
              "      <td>464</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>9</td>\n",
              "      <td>1</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>80</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1114</th>\n",
              "      <td>2791</td>\n",
              "      <td>31</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>755</td>\n",
              "      <td>Sales</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>3</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1115</th>\n",
              "      <td>2792</td>\n",
              "      <td>40</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>654</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>26</td>\n",
              "      <td>5</td>\n",
              "      <td>Medical</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>4</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>20</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>20</td>\n",
              "      <td>10</td>\n",
              "      <td>1</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1116</th>\n",
              "      <td>2793</td>\n",
              "      <td>42</td>\n",
              "      <td>Travel_Frequently</td>\n",
              "      <td>884</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>Medical</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1117</th>\n",
              "      <td>2794</td>\n",
              "      <td>25</td>\n",
              "      <td>Travel_Frequently</td>\n",
              "      <td>1469</td>\n",
              "      <td>Sales</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>Technical Degree</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>4</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1118</th>\n",
              "      <td>2795</td>\n",
              "      <td>42</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>1234</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>3</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>23</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>12</td>\n",
              "      <td>7</td>\n",
              "      <td>4</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1119 rows × 34 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d74ce43e-1097-44ac-aefa-8f367ef0d08a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "    .colab-df-container {\n",
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              "    .colab-df-convert {\n",
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              "      border-radius: 50%;\n",
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              "      fill: #1967D2;\n",
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              "      padding: 0 0 0 0;\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 82
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for cont in cont_var:\n",
        "    test[cont] = np.log(test[cont]+1)\n",
        "\n",
        "test"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 626
        },
        "id": "kpZgl986EknA",
        "outputId": "a72a216a-61cc-404d-9033-116a8e2c018f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        id       Age     BusinessTravel  DailyRate              Department  \\\n",
              "0     1677  2.995732         Non-Travel   6.900731  Research & Development   \n",
              "1     1678  3.828641      Travel_Rarely   7.036148                   Sales   \n",
              "2     1679  3.637586      Travel_Rarely   5.049856  Research & Development   \n",
              "3     1680  3.496508      Travel_Rarely   6.535241  Research & Development   \n",
              "4     1681  3.401197  Travel_Frequently   6.142037  Research & Development   \n",
              "...    ...       ...                ...        ...                     ...   \n",
              "1114  2791  3.465736      Travel_Rarely   6.628041                   Sales   \n",
              "1115  2792  3.713572      Travel_Rarely   6.484635  Research & Development   \n",
              "1116  2793  3.761200  Travel_Frequently   6.785588  Research & Development   \n",
              "1117  2794  3.258097  Travel_Frequently   7.293018                   Sales   \n",
              "1118  2795  3.761200      Travel_Rarely   7.118826  Research & Development   \n",
              "\n",
              "      DistanceFromHome  Education    EducationField  EmployeeCount  \\\n",
              "0             0.693147          1           Medical              1   \n",
              "1             1.609438          4         Marketing              1   \n",
              "2             2.639057          3     Life Sciences              1   \n",
              "3             0.693147          4     Life Sciences              1   \n",
              "4             2.302585          1     Life Sciences              1   \n",
              "...                ...        ...               ...            ...   \n",
              "1114          0.693147          1     Life Sciences              1   \n",
              "1115          3.295837          5           Medical              1   \n",
              "1116          0.693147          4           Medical              1   \n",
              "1117          0.693147          2  Technical Degree              1   \n",
              "1118          1.098612          4     Life Sciences              1   \n",
              "\n",
              "      EnvironmentSatisfaction  ... RelationshipSatisfaction  StandardHours  \\\n",
              "0                           4  ...                        4             80   \n",
              "1                           3  ...                        3             80   \n",
              "2                           4  ...                        2             80   \n",
              "3                           3  ...                        3             80   \n",
              "4                           3  ...                        1             80   \n",
              "...                       ...  ...                      ...            ...   \n",
              "1114                        3  ...                        3             80   \n",
              "1115                        3  ...                        4             80   \n",
              "1116                        2  ...                        1             80   \n",
              "1117                        3  ...                        4             80   \n",
              "1118                        3  ...                        3             80   \n",
              "\n",
              "      StockOptionLevel  TotalWorkingYears TrainingTimesLastYear  \\\n",
              "0                    0           0.693147                     2   \n",
              "1                    1           2.079442                     3   \n",
              "2                    2           2.639057                     2   \n",
              "3                    0           2.708050                     2   \n",
              "4                    0           0.693147                     5   \n",
              "...                ...                ...                   ...   \n",
              "1114                 1           0.693147                     1   \n",
              "1115                 1           3.044522                     4   \n",
              "1116                 1           2.397895                     2   \n",
              "1117                 1           1.791759                     2   \n",
              "1118                 1           3.178054                     2   \n",
              "\n",
              "      WorkLifeBalance YearsAtCompany  YearsInCurrentRole  \\\n",
              "0                   2       0.693147                   0   \n",
              "1                   3       1.098612                   2   \n",
              "2                   2       2.079442                   7   \n",
              "3                   2       2.708050                  10   \n",
              "4                   3       0.693147                   0   \n",
              "...               ...            ...                 ...   \n",
              "1114                3       0.693147                   0   \n",
              "1115                3       3.044522                  10   \n",
              "1116                2       1.791759                   3   \n",
              "1117                3       1.609438                   2   \n",
              "1118                3       2.564949                   7   \n",
              "\n",
              "      YearsSinceLastPromotion  YearsWithCurrManager  \n",
              "0                           0                     0  \n",
              "1                           2                     2  \n",
              "2                           1                     7  \n",
              "3                          11                     8  \n",
              "4                           0                     0  \n",
              "...                       ...                   ...  \n",
              "1114                        0                     0  \n",
              "1115                        1                     8  \n",
              "1116                        0                     2  \n",
              "1117                        1                     3  \n",
              "1118                        4                     9  \n",
              "\n",
              "[1119 rows x 34 columns]"
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              "      <th>id</th>\n",
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              "      <td>Non-Travel</td>\n",
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              "      <td>0.693147</td>\n",
              "      <td>1</td>\n",
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              "      <td>1678</td>\n",
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              "      <td>7.036148</td>\n",
              "      <td>Sales</td>\n",
              "      <td>1.609438</td>\n",
              "      <td>4</td>\n",
              "      <td>Marketing</td>\n",
              "      <td>1</td>\n",
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              "      <td>1679</td>\n",
              "      <td>3.637586</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>5.049856</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>2.639057</td>\n",
              "      <td>3</td>\n",
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              "      <td>4</td>\n",
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              "      <th>4</th>\n",
              "      <td>1681</td>\n",
              "      <td>3.401197</td>\n",
              "      <td>Travel_Frequently</td>\n",
              "      <td>6.142037</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>2.302585</td>\n",
              "      <td>1</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>80</td>\n",
              "      <td>0</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1114</th>\n",
              "      <td>2791</td>\n",
              "      <td>3.465736</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.628041</td>\n",
              "      <td>Sales</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>1</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>3</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1115</th>\n",
              "      <td>2792</td>\n",
              "      <td>3.713572</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.484635</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>3.295837</td>\n",
              "      <td>5</td>\n",
              "      <td>Medical</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>4</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>3.044522</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>3.044522</td>\n",
              "      <td>10</td>\n",
              "      <td>1</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1116</th>\n",
              "      <td>2793</td>\n",
              "      <td>3.761200</td>\n",
              "      <td>Travel_Frequently</td>\n",
              "      <td>6.785588</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>4</td>\n",
              "      <td>Medical</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>2.397895</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1.791759</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1117</th>\n",
              "      <td>2794</td>\n",
              "      <td>3.258097</td>\n",
              "      <td>Travel_Frequently</td>\n",
              "      <td>7.293018</td>\n",
              "      <td>Sales</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>2</td>\n",
              "      <td>Technical Degree</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>4</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>1.791759</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>1.609438</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1118</th>\n",
              "      <td>2795</td>\n",
              "      <td>3.761200</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>7.118826</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>1.098612</td>\n",
              "      <td>4</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>3</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>3.178054</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>2.564949</td>\n",
              "      <td>7</td>\n",
              "      <td>4</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1119 rows × 34 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8b4132b2-fd20-41ec-b191-c0152ccf72b4')\"\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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            ]
          },
          "metadata": {},
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.preprocessing import OneHotEncoder"
      ],
      "metadata": {
        "id": "QQ93YYbJE1hB"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "one = OneHotEncoder()\n",
        "one.fit(test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bwka0mMpE9zN",
        "outputId": "b330154b-9080-47df-b6c7-be92c541f0a3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "OneHotEncoder()"
            ]
          },
          "metadata": {},
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UTHX2W5MFKMq",
        "outputId": "2c7b452e-14f7-4dcd-9a3c-cb49e2a6a2aa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "  (1118, 3365)\t1.0\n",
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            "  (1118, 3407)\t1.0\n",
            "  (1118, 3422)\t1.0\n",
            "  (1118, 3443)\t1.0\n"
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "test"
      ],
      "metadata": {
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          "base_uri": "https://localhost:8080/",
          "height": 626
        },
        "id": "R2MzNMQFFbry",
        "outputId": "6f4273e9-1eda-4e00-b199-83111373d642"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        id       Age     BusinessTravel  DailyRate              Department  \\\n",
              "0     1677  2.995732         Non-Travel   6.900731  Research & Development   \n",
              "1     1678  3.828641      Travel_Rarely   7.036148                   Sales   \n",
              "2     1679  3.637586      Travel_Rarely   5.049856  Research & Development   \n",
              "3     1680  3.496508      Travel_Rarely   6.535241  Research & Development   \n",
              "4     1681  3.401197  Travel_Frequently   6.142037  Research & Development   \n",
              "...    ...       ...                ...        ...                     ...   \n",
              "1114  2791  3.465736      Travel_Rarely   6.628041                   Sales   \n",
              "1115  2792  3.713572      Travel_Rarely   6.484635  Research & Development   \n",
              "1116  2793  3.761200  Travel_Frequently   6.785588  Research & Development   \n",
              "1117  2794  3.258097  Travel_Frequently   7.293018                   Sales   \n",
              "1118  2795  3.761200      Travel_Rarely   7.118826  Research & Development   \n",
              "\n",
              "      DistanceFromHome  Education    EducationField  EmployeeCount  \\\n",
              "0             0.693147          1           Medical              1   \n",
              "1             1.609438          4         Marketing              1   \n",
              "2             2.639057          3     Life Sciences              1   \n",
              "3             0.693147          4     Life Sciences              1   \n",
              "4             2.302585          1     Life Sciences              1   \n",
              "...                ...        ...               ...            ...   \n",
              "1114          0.693147          1     Life Sciences              1   \n",
              "1115          3.295837          5           Medical              1   \n",
              "1116          0.693147          4           Medical              1   \n",
              "1117          0.693147          2  Technical Degree              1   \n",
              "1118          1.098612          4     Life Sciences              1   \n",
              "\n",
              "      EnvironmentSatisfaction  ... RelationshipSatisfaction  StandardHours  \\\n",
              "0                           4  ...                        4             80   \n",
              "1                           3  ...                        3             80   \n",
              "2                           4  ...                        2             80   \n",
              "3                           3  ...                        3             80   \n",
              "4                           3  ...                        1             80   \n",
              "...                       ...  ...                      ...            ...   \n",
              "1114                        3  ...                        3             80   \n",
              "1115                        3  ...                        4             80   \n",
              "1116                        2  ...                        1             80   \n",
              "1117                        3  ...                        4             80   \n",
              "1118                        3  ...                        3             80   \n",
              "\n",
              "      StockOptionLevel  TotalWorkingYears TrainingTimesLastYear  \\\n",
              "0                    0           0.693147                     2   \n",
              "1                    1           2.079442                     3   \n",
              "2                    2           2.639057                     2   \n",
              "3                    0           2.708050                     2   \n",
              "4                    0           0.693147                     5   \n",
              "...                ...                ...                   ...   \n",
              "1114                 1           0.693147                     1   \n",
              "1115                 1           3.044522                     4   \n",
              "1116                 1           2.397895                     2   \n",
              "1117                 1           1.791759                     2   \n",
              "1118                 1           3.178054                     2   \n",
              "\n",
              "      WorkLifeBalance YearsAtCompany  YearsInCurrentRole  \\\n",
              "0                   2       0.693147                   0   \n",
              "1                   3       1.098612                   2   \n",
              "2                   2       2.079442                   7   \n",
              "3                   2       2.708050                  10   \n",
              "4                   3       0.693147                   0   \n",
              "...               ...            ...                 ...   \n",
              "1114                3       0.693147                   0   \n",
              "1115                3       3.044522                  10   \n",
              "1116                2       1.791759                   3   \n",
              "1117                3       1.609438                   2   \n",
              "1118                3       2.564949                   7   \n",
              "\n",
              "      YearsSinceLastPromotion  YearsWithCurrManager  \n",
              "0                           0                     0  \n",
              "1                           2                     2  \n",
              "2                           1                     7  \n",
              "3                          11                     8  \n",
              "4                           0                     0  \n",
              "...                       ...                   ...  \n",
              "1114                        0                     0  \n",
              "1115                        1                     8  \n",
              "1116                        0                     2  \n",
              "1117                        1                     3  \n",
              "1118                        4                     9  \n",
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              "      <td>Sales</td>\n",
              "      <td>1.609438</td>\n",
              "      <td>4</td>\n",
              "      <td>Marketing</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>3</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>2.079442</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>1.098612</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1679</td>\n",
              "      <td>3.637586</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>5.049856</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>2.639057</td>\n",
              "      <td>3</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>...</td>\n",
              "      <td>2</td>\n",
              "      <td>80</td>\n",
              "      <td>2</td>\n",
              "      <td>2.639057</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2.079442</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1680</td>\n",
              "      <td>3.496508</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.535241</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>4</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>3</td>\n",
              "      <td>80</td>\n",
              "      <td>0</td>\n",
              "      <td>2.708050</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2.708050</td>\n",
              "      <td>10</td>\n",
              "      <td>11</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1681</td>\n",
              "      <td>3.401197</td>\n",
              "      <td>Travel_Frequently</td>\n",
              "      <td>6.142037</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>2.302585</td>\n",
              "      <td>1</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>80</td>\n",
              "      <td>0</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1114</th>\n",
              "      <td>2791</td>\n",
              "      <td>3.465736</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.628041</td>\n",
              "      <td>Sales</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>1</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>3</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1115</th>\n",
              "      <td>2792</td>\n",
              "      <td>3.713572</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>6.484635</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>3.295837</td>\n",
              "      <td>5</td>\n",
              "      <td>Medical</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>4</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>3.044522</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>3.044522</td>\n",
              "      <td>10</td>\n",
              "      <td>1</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1116</th>\n",
              "      <td>2793</td>\n",
              "      <td>3.761200</td>\n",
              "      <td>Travel_Frequently</td>\n",
              "      <td>6.785588</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>4</td>\n",
              "      <td>Medical</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>2.397895</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1.791759</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1117</th>\n",
              "      <td>2794</td>\n",
              "      <td>3.258097</td>\n",
              "      <td>Travel_Frequently</td>\n",
              "      <td>7.293018</td>\n",
              "      <td>Sales</td>\n",
              "      <td>0.693147</td>\n",
              "      <td>2</td>\n",
              "      <td>Technical Degree</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>4</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>1.791759</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>1.609438</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1118</th>\n",
              "      <td>2795</td>\n",
              "      <td>3.761200</td>\n",
              "      <td>Travel_Rarely</td>\n",
              "      <td>7.118826</td>\n",
              "      <td>Research &amp; Development</td>\n",
              "      <td>1.098612</td>\n",
              "      <td>4</td>\n",
              "      <td>Life Sciences</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>3</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>3.178054</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>2.564949</td>\n",
              "      <td>7</td>\n",
              "      <td>4</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1119 rows × 34 columns</p>\n",
              "</div>\n",
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              "    .colab-df-convert {\n",
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              "                                                     [key], {});\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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          "metadata": {},
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      "metadata": {
        "id": "ZPCEiLPOG9t_"
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      "execution_count": null,
      "outputs": []
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