Sleep_Health.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/saleteyara/equipe7-2024.1/blob/branch_notebook/Sleep_Health.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": {
        "id": "37iPuWaWQdQp"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Sleep Health and Lifestyle Dataset**\n",
        "\n"
      ],
      "metadata": {
        "id": "zirflq0ceMqj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "id": "aK31PU9_OlDz",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a2b93b74-0c8e-4844-c8bb-2cb24f999e92"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv(\"/content/Sleep_health_and_lifestyle_dataset.csv\")"
      ],
      "metadata": {
        "id": "6D1ZNmAfRskL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 319
        },
        "outputId": "20cb7c27-44b9-4c4d-dfbb-9f0f43546e74"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "FileNotFoundError",
          "evalue": "[Errno 2] No such file or directory: '/content/Sleep_health_and_lifestyle_dataset.csv'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-6-612cb8aa56f1>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"/content/Sleep_health_and_lifestyle_dataset.csv\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/parsers/readers.py\u001b[0m in \u001b[0;36mread_csv\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend)\u001b[0m\n\u001b[1;32m    910\u001b[0m     \u001b[0mkwds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkwds_defaults\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    911\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 912\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    913\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    914\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/parsers/readers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m    575\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    576\u001b[0m     \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 577\u001b[0;31m     \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    578\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    579\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/parsers/readers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m   1405\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1406\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhandles\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mIOHandles\u001b[0m \u001b[0;34m|\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1407\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1408\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1409\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/parsers/readers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[0;34m(self, f, engine)\u001b[0m\n\u001b[1;32m   1659\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0;34m\"b\"\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmode\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1660\u001b[0m                     \u001b[0mmode\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;34m\"b\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1661\u001b[0;31m             self.handles = get_handle(\n\u001b[0m\u001b[1;32m   1662\u001b[0m                 \u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1663\u001b[0m                 \u001b[0mmode\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/common.py\u001b[0m in \u001b[0;36mget_handle\u001b[0;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[1;32m    857\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mioargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mencoding\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;34m\"b\"\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mioargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    858\u001b[0m             \u001b[0;31m# Encoding\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 859\u001b[0;31m             handle = open(\n\u001b[0m\u001b[1;32m    860\u001b[0m                 \u001b[0mhandle\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    861\u001b[0m                 \u001b[0mioargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/content/Sleep_health_and_lifestyle_dataset.csv'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 148
        },
        "id": "ixIW3uDsS-3o",
        "outputId": "0ddd2d30-d54b-4399-b845-f271d13b1b4e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "NameError",
          "evalue": "name 'df' is not defined",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-8-c42a15b2c7cf>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m: name 'df' is not defined"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 148
        },
        "id": "nip17PC7OUf7",
        "outputId": "ebcda124-c91f-4294-f09d-0ee7ca15f143"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "NameError",
          "evalue": "name 'df' is not defined",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-1-633337079cd0>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m: name 'df' is not defined"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"Gender\"]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ce6N6kk0VXfn",
        "outputId": "296bf6f8-d8a8-40c5-be25-0420a53b3eb5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0        Male\n",
              "1        Male\n",
              "2        Male\n",
              "3        Male\n",
              "4        Male\n",
              "        ...  \n",
              "369    Female\n",
              "370    Female\n",
              "371    Female\n",
              "372    Female\n",
              "373    Female\n",
              "Name: Gender, Length: 374, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"Gender_encoded\"]=df[\"Gender\"].replace({\"Male\":0, \"Female\": 1})\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        },
        "id": "ndr48ftyV0Ll",
        "outputId": "4fc0805c-c5e8-4ae6-8e64-e7ab9bd61dbb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Person ID  Gender  Age            Occupation  Sleep Duration  \\\n",
              "0            1    Male   27     Software Engineer             6.1   \n",
              "1            2    Male   28                Doctor             6.2   \n",
              "2            3    Male   28                Doctor             6.2   \n",
              "3            4    Male   28  Sales Representative             5.9   \n",
              "4            5    Male   28  Sales Representative             5.9   \n",
              "..         ...     ...  ...                   ...             ...   \n",
              "369        370  Female   59                 Nurse             8.1   \n",
              "370        371  Female   59                 Nurse             8.0   \n",
              "371        372  Female   59                 Nurse             8.1   \n",
              "372        373  Female   59                 Nurse             8.1   \n",
              "373        374  Female   59                 Nurse             8.1   \n",
              "\n",
              "     Quality of Sleep  Physical Activity Level  Stress Level BMI Category  \\\n",
              "0                   6                       42             6   Overweight   \n",
              "1                   6                       60             8       Normal   \n",
              "2                   6                       60             8       Normal   \n",
              "3                   4                       30             8        Obese   \n",
              "4                   4                       30             8        Obese   \n",
              "..                ...                      ...           ...          ...   \n",
              "369                 9                       75             3   Overweight   \n",
              "370                 9                       75             3   Overweight   \n",
              "371                 9                       75             3   Overweight   \n",
              "372                 9                       75             3   Overweight   \n",
              "373                 9                       75             3   Overweight   \n",
              "\n",
              "    Blood Pressure  Heart Rate  Daily Steps Sleep Disorder  Gender_encoded  \n",
              "0           126/83          77         4200            NaN               0  \n",
              "1           125/80          75        10000            NaN               0  \n",
              "2           125/80          75        10000            NaN               0  \n",
              "3           140/90          85         3000    Sleep Apnea               0  \n",
              "4           140/90          85         3000    Sleep Apnea               0  \n",
              "..             ...         ...          ...            ...             ...  \n",
              "369         140/95          68         7000    Sleep Apnea               1  \n",
              "370         140/95          68         7000    Sleep Apnea               1  \n",
              "371         140/95          68         7000    Sleep Apnea               1  \n",
              "372         140/95          68         7000    Sleep Apnea               1  \n",
              "373         140/95          68         7000    Sleep Apnea               1  \n",
              "\n",
              "[374 rows x 14 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-188d6f27-fd0a-414f-af16-69cbfd1349a4\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Person ID</th>\n",
              "      <th>Gender</th>\n",
              "      <th>Age</th>\n",
              "      <th>Occupation</th>\n",
              "      <th>Sleep Duration</th>\n",
              "      <th>Quality of Sleep</th>\n",
              "      <th>Physical Activity Level</th>\n",
              "      <th>Stress Level</th>\n",
              "      <th>BMI Category</th>\n",
              "      <th>Blood Pressure</th>\n",
              "      <th>Heart Rate</th>\n",
              "      <th>Daily Steps</th>\n",
              "      <th>Sleep Disorder</th>\n",
              "      <th>Gender_encoded</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Male</td>\n",
              "      <td>27</td>\n",
              "      <td>Software Engineer</td>\n",
              "      <td>6.1</td>\n",
              "      <td>6</td>\n",
              "      <td>42</td>\n",
              "      <td>6</td>\n",
              "      <td>Overweight</td>\n",
              "      <td>126/83</td>\n",
              "      <td>77</td>\n",
              "      <td>4200</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>Male</td>\n",
              "      <td>28</td>\n",
              "      <td>Doctor</td>\n",
              "      <td>6.2</td>\n",
              "      <td>6</td>\n",
              "      <td>60</td>\n",
              "      <td>8</td>\n",
              "      <td>Normal</td>\n",
              "      <td>125/80</td>\n",
              "      <td>75</td>\n",
              "      <td>10000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Male</td>\n",
              "      <td>28</td>\n",
              "      <td>Doctor</td>\n",
              "      <td>6.2</td>\n",
              "      <td>6</td>\n",
              "      <td>60</td>\n",
              "      <td>8</td>\n",
              "      <td>Normal</td>\n",
              "      <td>125/80</td>\n",
              "      <td>75</td>\n",
              "      <td>10000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Male</td>\n",
              "      <td>28</td>\n",
              "      <td>Sales Representative</td>\n",
              "      <td>5.9</td>\n",
              "      <td>4</td>\n",
              "      <td>30</td>\n",
              "      <td>8</td>\n",
              "      <td>Obese</td>\n",
              "      <td>140/90</td>\n",
              "      <td>85</td>\n",
              "      <td>3000</td>\n",
              "      <td>Sleep Apnea</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Male</td>\n",
              "      <td>28</td>\n",
              "      <td>Sales Representative</td>\n",
              "      <td>5.9</td>\n",
              "      <td>4</td>\n",
              "      <td>30</td>\n",
              "      <td>8</td>\n",
              "      <td>Obese</td>\n",
              "      <td>140/90</td>\n",
              "      <td>85</td>\n",
              "      <td>3000</td>\n",
              "      <td>Sleep Apnea</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>369</th>\n",
              "      <td>370</td>\n",
              "      <td>Female</td>\n",
              "      <td>59</td>\n",
              "      <td>Nurse</td>\n",
              "      <td>8.1</td>\n",
              "      <td>9</td>\n",
              "      <td>75</td>\n",
              "      <td>3</td>\n",
              "      <td>Overweight</td>\n",
              "      <td>140/95</td>\n",
              "      <td>68</td>\n",
              "      <td>7000</td>\n",
              "      <td>Sleep Apnea</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>370</th>\n",
              "      <td>371</td>\n",
              "      <td>Female</td>\n",
              "      <td>59</td>\n",
              "      <td>Nurse</td>\n",
              "      <td>8.0</td>\n",
              "      <td>9</td>\n",
              "      <td>75</td>\n",
              "      <td>3</td>\n",
              "      <td>Overweight</td>\n",
              "      <td>140/95</td>\n",
              "      <td>68</td>\n",
              "      <td>7000</td>\n",
              "      <td>Sleep Apnea</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>371</th>\n",
              "      <td>372</td>\n",
              "      <td>Female</td>\n",
              "      <td>59</td>\n",
              "      <td>Nurse</td>\n",
              "      <td>8.1</td>\n",
              "      <td>9</td>\n",
              "      <td>75</td>\n",
              "      <td>3</td>\n",
              "      <td>Overweight</td>\n",
              "      <td>140/95</td>\n",
              "      <td>68</td>\n",
              "      <td>7000</td>\n",
              "      <td>Sleep Apnea</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>372</th>\n",
              "      <td>373</td>\n",
              "      <td>Female</td>\n",
              "      <td>59</td>\n",
              "      <td>Nurse</td>\n",
              "      <td>8.1</td>\n",
              "      <td>9</td>\n",
              "      <td>75</td>\n",
              "      <td>3</td>\n",
              "      <td>Overweight</td>\n",
              "      <td>140/95</td>\n",
              "      <td>68</td>\n",
              "      <td>7000</td>\n",
              "      <td>Sleep Apnea</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>373</th>\n",
              "      <td>374</td>\n",
              "      <td>Female</td>\n",
              "      <td>59</td>\n",
              "      <td>Nurse</td>\n",
              "      <td>8.1</td>\n",
              "      <td>9</td>\n",
              "      <td>75</td>\n",
              "      <td>3</td>\n",
              "      <td>Overweight</td>\n",
              "      <td>140/95</td>\n",
              "      <td>68</td>\n",
              "      <td>7000</td>\n",
              "      <td>Sleep Apnea</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>374 rows × 14 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      margin-bottom: 4px;\n",
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              "      buttonEl.style.display =\n",
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              "        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",
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              "\n",
              "  .colab-df-quickchart {\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
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              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
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              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "    20% {\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
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              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_3574ab14-8448-4cb4-baed-847d37308a30\">\n",
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              "        width: 32px;\n",
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              "\n",
              "      .colab-df-generate:hover {\n",
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              "      [theme=dark] .colab-df-generate:hover {\n",
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              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\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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              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
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              "\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 374,\n  \"fields\": [\n    {\n      \"column\": \"Person ID\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 108,\n        \"min\": 1,\n        \"max\": 374,\n        \"num_unique_values\": 374,\n        \"samples\": [\n          330,\n          34,\n          16\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Gender\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Female\",\n          \"Male\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 8,\n        \"min\": 27,\n        \"max\": 59,\n        \"num_unique_values\": 31,\n        \"samples\": [\n          56,\n          42\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Occupation\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 11,\n        \"samples\": [\n          \"Engineer\",\n          \"Software Engineer\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sleep Duration\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.7956567308898189,\n        \"min\": 5.8,\n        \"max\": 8.5,\n        \"num_unique_values\": 27,\n        \"samples\": [\n          7.7,\n          5.8\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Quality of Sleep\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 4,\n        \"max\": 9,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          6,\n          4\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Physical Activity Level\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 20,\n        \"min\": 30,\n        \"max\": 90,\n        \"num_unique_values\": 16,\n        \"samples\": [\n          42,\n          60\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Stress Level\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 3,\n        \"max\": 8,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          6,\n          8\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"BMI Category\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"Normal\",\n          \"Normal Weight\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Blood Pressure\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 25,\n        \"samples\": [\n          \"128/85\",\n          \"119/77\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Heart Rate\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 4,\n        \"min\": 65,\n        \"max\": 86,\n        \"num_unique_values\": 19,\n        \"samples\": [\n          77,\n          80\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Daily Steps\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1617,\n        \"min\": 3000,\n        \"max\": 10000,\n        \"num_unique_values\": 20,\n        \"samples\": [\n          4200,\n          6200\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sleep Disorder\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Insomnia\",\n          \"Sleep Apnea\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Gender_encoded\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Psjqmci5bhgb",
        "outputId": "81b90d39-3477-4598-86bb-1febec93d775"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 374 entries, 0 to 373\n",
            "Data columns (total 14 columns):\n",
            " #   Column                   Non-Null Count  Dtype  \n",
            "---  ------                   --------------  -----  \n",
            " 0   Person ID                374 non-null    int64  \n",
            " 1   Gender                   374 non-null    object \n",
            " 2   Age                      374 non-null    int64  \n",
            " 3   Occupation               374 non-null    object \n",
            " 4   Sleep Duration           374 non-null    float64\n",
            " 5   Quality of Sleep         374 non-null    int64  \n",
            " 6   Physical Activity Level  374 non-null    int64  \n",
            " 7   Stress Level             374 non-null    int64  \n",
            " 8   BMI Category             374 non-null    object \n",
            " 9   Blood Pressure           374 non-null    object \n",
            " 10  Heart Rate               374 non-null    int64  \n",
            " 11  Daily Steps              374 non-null    int64  \n",
            " 12  Sleep Disorder           155 non-null    object \n",
            " 13  Gender_encoded           374 non-null    int64  \n",
            "dtypes: float64(1), int64(8), object(5)\n",
            "memory usage: 41.0+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"Gender\"].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dI2ud89RdqV0",
        "outputId": "c89f4a21-ad03-4110-e27c-d3031c6eac06"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Male', 'Female'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"Occupation\"].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZczVT3afdsje",
        "outputId": "ada4e6b3-7894-46a4-dfd8-3f1c9066ea15"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Software Engineer', 'Doctor', 'Sales Representative', 'Teacher',\n",
              "       'Nurse', 'Engineer', 'Accountant', 'Scientist', 'Lawyer',\n",
              "       'Salesperson', 'Manager'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"BMI Category\"].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6ey1IUktduf9",
        "outputId": "1afa7403-2baa-4f9b-dbfb-d6ed1a7e032c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Overweight', 'Normal', 'Obese', 'Normal Weight'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"Blood Pressure\"].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "M5z12M8qdwWR",
        "outputId": "7f14dea3-ce05-458e-db5b-d64b5a747a32"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['126/83', '125/80', '140/90', '120/80', '132/87', '130/86',\n",
              "       '117/76', '118/76', '128/85', '131/86', '128/84', '115/75',\n",
              "       '135/88', '129/84', '130/85', '115/78', '119/77', '121/79',\n",
              "       '125/82', '135/90', '122/80', '142/92', '140/95', '139/91',\n",
              "       '118/75'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "df[\"Sleep Disorder\"].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dCHKTv0wa6U2",
        "outputId": "0f91f4a2-496a-48de-bb8f-97d8ee5c73cb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([nan, 'Sleep Apnea', 'Insomnia'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.nunique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qOwEJfl3fjCo",
        "outputId": "8bc93fce-80c0-420a-e466-4e1e7e31d1c4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Person ID                  374\n",
              "Gender                       2\n",
              "Age                         31\n",
              "Occupation                  11\n",
              "Sleep Duration              27\n",
              "Quality of Sleep             6\n",
              "Physical Activity Level     16\n",
              "Stress Level                 6\n",
              "BMI Category                 4\n",
              "Blood Pressure              25\n",
              "Heart Rate                  19\n",
              "Daily Steps                 20\n",
              "Sleep Disorder               2\n",
              "Gender_encoded               2\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df= df.drop(columns=[\"Gender\"])\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 597
        },
        "id": "VZXq7r7YWe_J",
        "outputId": "84dad880-1061-4f98-8f2d-7a65f00ca053"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Person ID  Age            Occupation  Sleep Duration  Quality of Sleep  \\\n",
              "0            1   27     Software Engineer             6.1                 6   \n",
              "1            2   28                Doctor             6.2                 6   \n",
              "2            3   28                Doctor             6.2                 6   \n",
              "3            4   28  Sales Representative             5.9                 4   \n",
              "4            5   28  Sales Representative             5.9                 4   \n",
              "..         ...  ...                   ...             ...               ...   \n",
              "369        370   59                 Nurse             8.1                 9   \n",
              "370        371   59                 Nurse             8.0                 9   \n",
              "371        372   59                 Nurse             8.1                 9   \n",
              "372        373   59                 Nurse             8.1                 9   \n",
              "373        374   59                 Nurse             8.1                 9   \n",
              "\n",
              "     Physical Activity Level  Stress Level BMI Category Blood Pressure  \\\n",
              "0                         42             6   Overweight         126/83   \n",
              "1                         60             8       Normal         125/80   \n",
              "2                         60             8       Normal         125/80   \n",
              "3                         30             8        Obese         140/90   \n",
              "4                         30             8        Obese         140/90   \n",
              "..                       ...           ...          ...            ...   \n",
              "369                       75             3   Overweight         140/95   \n",
              "370                       75             3   Overweight         140/95   \n",
              "371                       75             3   Overweight         140/95   \n",
              "372                       75             3   Overweight         140/95   \n",
              "373                       75             3   Overweight         140/95   \n",
              "\n",
              "     Heart Rate  Daily Steps Sleep Disorder  Gender_encoded  \n",
              "0            77         4200            NaN               0  \n",
              "1            75        10000            NaN               0  \n",
              "2            75        10000            NaN               0  \n",
              "3            85         3000    Sleep Apnea               0  \n",
              "4            85         3000    Sleep Apnea               0  \n",
              "..          ...          ...            ...             ...  \n",
              "369          68         7000    Sleep Apnea               1  \n",
              "370          68         7000    Sleep Apnea               1  \n",
              "371          68         7000    Sleep Apnea               1  \n",
              "372          68         7000    Sleep Apnea               1  \n",
              "373          68         7000    Sleep Apnea               1  \n",
              "\n",
              "[374 rows x 13 columns]"
            ],
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              "      <th>Person ID</th>\n",
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              "      <td>370</td>\n",
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              "      <td>7000</td>\n",
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              "      <td>7000</td>\n",
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              "      <td>7000</td>\n",
              "      <td>Sleep Apnea</td>\n",
              "      <td>1</td>\n",
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              "  </tbody>\n",
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              "<p>374 rows × 13 columns</p>\n",
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              "      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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-78338e9f-9319-4c97-887b-970a51ceee8d 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-78338e9f-9319-4c97-887b-970a51ceee8d');\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",
              "\n",
              "\n",
              "<div id=\"df-15a5bec4-10e1-4702-a1f1-b41496a8bc5a\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-15a5bec4-10e1-4702-a1f1-b41496a8bc5a')\"\n",
              "            title=\"Suggest charts\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-15a5bec4-10e1-4702-a1f1-b41496a8bc5a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_1f0fb21a-cc82-49fe-ac55-ea3755e2b7f2\">\n",
              "    <style>\n",
              "      .colab-df-generate {\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-generate: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-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate: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",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\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=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_1f0fb21a-cc82-49fe-ac55-ea3755e2b7f2 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 374,\n  \"fields\": [\n    {\n      \"column\": \"Person ID\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 108,\n        \"min\": 1,\n        \"max\": 374,\n        \"num_unique_values\": 374,\n        \"samples\": [\n          330,\n          34,\n          16\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 8,\n        \"min\": 27,\n        \"max\": 59,\n        \"num_unique_values\": 31,\n        \"samples\": [\n          56,\n          42,\n          52\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Occupation\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 11,\n        \"samples\": [\n          \"Engineer\",\n          \"Software Engineer\",\n          \"Salesperson\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sleep Duration\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.7956567308898189,\n        \"min\": 5.8,\n        \"max\": 8.5,\n        \"num_unique_values\": 27,\n        \"samples\": [\n          7.7,\n          5.8,\n          7.9\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Quality of Sleep\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 4,\n        \"max\": 9,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          6,\n          4,\n          9\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Physical Activity Level\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 20,\n        \"min\": 30,\n        \"max\": 90,\n        \"num_unique_values\": 16,\n        \"samples\": [\n          42,\n          60,\n          35\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Stress Level\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 3,\n        \"max\": 8,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          6,\n          8,\n          5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"BMI Category\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"Normal\",\n          \"Normal Weight\",\n          \"Overweight\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Blood Pressure\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 25,\n        \"samples\": [\n          \"128/85\",\n          \"119/77\",\n          \"126/83\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Heart Rate\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 4,\n        \"min\": 65,\n        \"max\": 86,\n        \"num_unique_values\": 19,\n        \"samples\": [\n          77,\n          80,\n          81\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Daily Steps\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1617,\n        \"min\": 3000,\n        \"max\": 10000,\n        \"num_unique_values\": 20,\n        \"samples\": [\n          4200,\n          6200,\n          7500\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sleep Disorder\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Insomnia\",\n          \"Sleep Apnea\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Gender_encoded\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "yvF0raPCf8WG"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}