ML_lab.ipynb

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  "metadata": {
    "colab": {
      "name": "ML lab.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyNkUO2SGm4AEII260sIGDla",
      "include_colab_link": true
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      "name": "python3",
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      "name": "python"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/theYogeshArora/Python-Workshop/blob/main/ML_lab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Read the data from\n",
        "https://archive.ics.uci.edu/ml/datasets/Cervical+cancer+%28Risk+Factors%29"
      ],
      "metadata": {
        "id": "eLhT5GDet1lF"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "4F2hmz2abpeh"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "\n",
        "# Read the online file by the URL provides above, and assign it to variable \"df\"\n",
        "other_path = \"https://archive.ics.uci.edu/ml/machine-learning-databases/00383/risk_factors_cervical_cancer.csv\"\n",
        "df = pd.read_csv(other_path, header=None)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Check the bottom 10 rows of data."
      ],
      "metadata": {
        "id": "jfMdk6bft_Af"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "print(\"The first 5 rows of the dataframe\") \n",
        "df.tail(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 381
        },
        "id": "Es9PrSDzb8ds",
        "outputId": "072b2603-11d6-478e-b952-222a69ce18b4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The first 5 rows of the dataframe\n"
          ]
        },
        {
          "output_type": "execute_result",
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              "      \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",
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              "      display: none;\n",
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              "      width: 32px;\n",
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              "\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",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\n",
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              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "\n",
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              "          document.querySelector('#df-02ce563c-038a-4c5f-bb58-b1abfe821345 button.colab-df-convert');\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-02ce563c-038a-4c5f-bb58-b1abfe821345');\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",
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              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
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              "          element.appendChild(docLink);\n",
              "        }\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
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            "text/plain": [
              "     0    1     2    3    4     5     6    7     8   ... 27 28 29 30 31 32 33 34 35\n",
              "849  31  3.0  18.0  1.0  0.0   0.0   0.0  1.0   0.5  ...  ?  0  0  0  0  0  0  0  0\n",
              "850  32  3.0  18.0  1.0  1.0  11.0  0.16  1.0   6.0  ...  ?  1  0  1  0  0  0  0  0\n",
              "851  19  1.0  14.0  0.0  0.0   0.0   0.0  0.0   0.0  ...  ?  0  0  0  0  0  0  0  0\n",
              "852  23  2.0  15.0  2.0  0.0   0.0   0.0  0.0   0.0  ...  ?  0  0  0  0  0  0  0  0\n",
              "853  43  3.0  17.0  3.0  0.0   0.0   0.0  1.0   5.0  ...  ?  0  0  0  0  0  0  0  0\n",
              "854  34  3.0  18.0  0.0  0.0   0.0   0.0  0.0   0.0  ...  ?  0  0  0  0  0  0  0  0\n",
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              "856  25  2.0  17.0  0.0  0.0   0.0   0.0  1.0  0.08  ...  ?  0  0  0  0  0  0  1  0\n",
              "857  33  2.0  24.0  2.0  0.0   0.0   0.0  1.0  0.08  ...  ?  0  0  0  0  0  0  0  0\n",
              "858  29  2.0  20.0  1.0  0.0   0.0   0.0  1.0   0.5  ...  ?  0  0  0  0  0  0  0  0\n",
              "\n",
              "[10 rows x 36 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Find the name of the columns of the data."
      ],
      "metadata": {
        "id": "y5bukKKUuCWn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(df.columns)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pUo9aBRQcfiJ",
        "outputId": "418dc65c-93f8-4919-8198-7d8b933eabca"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Int64Index([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n",
            "            17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,\n",
            "            34, 35],\n",
            "           dtype='int64')\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Check the type of Data"
      ],
      "metadata": {
        "id": "IbSiHUQluKax"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(df.dtypes)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HamRMjZ3csbm",
        "outputId": "cf07505c-d342-43b9-8a4a-f257648f109e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0     object\n",
            "1     object\n",
            "2     object\n",
            "3     object\n",
            "4     object\n",
            "5     object\n",
            "6     object\n",
            "7     object\n",
            "8     object\n",
            "9     object\n",
            "10    object\n",
            "11    object\n",
            "12    object\n",
            "13    object\n",
            "14    object\n",
            "15    object\n",
            "16    object\n",
            "17    object\n",
            "18    object\n",
            "19    object\n",
            "20    object\n",
            "21    object\n",
            "22    object\n",
            "23    object\n",
            "24    object\n",
            "25    object\n",
            "26    object\n",
            "27    object\n",
            "28    object\n",
            "29    object\n",
            "30    object\n",
            "31    object\n",
            "32    object\n",
            "33    object\n",
            "34    object\n",
            "35    object\n",
            "dtype: object\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Give the statistics of of the columns"
      ],
      "metadata": {
        "id": "GL_LNearuMqa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe(include = \"all\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "TzMRbQdJdHu_",
        "outputId": "bc9b18ab-cc99-44b8-ae32-e9e92231c50c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-455df2c4-479d-4384-8617-2c90b02b3ab9')\"\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",
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              "      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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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-455df2c4-479d-4384-8617-2c90b02b3ab9 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-455df2c4-479d-4384-8617-2c90b02b3ab9');\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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              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "         0    1     2    3    4    5    6   ...   29   30   31   32   33   34   35\n",
              "count   859  859   859  859  859  859  859  ...  859  859  859  859  859  859  859\n",
              "unique   45   14    23   13    4   32   64  ...    3    3    3    3    3    3    3\n",
              "top      23  2.0  15.0  1.0  0.0  0.0  0.0  ...    0    0    0    0    0    0    0\n",
              "freq     54  272   163  270  722  722  722  ...  849  840  834  823  784  814  803\n",
              "\n",
              "[4 rows x 36 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Identify missing values (Convert \"?\" to NaN)"
      ],
      "metadata": {
        "id": "2rG5cGt2uPb6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "\n",
        "# replace \"?\" to NaN\n",
        "df.replace(\"?\", np.nan, inplace = True)\n",
        "df.head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 322
        },
        "id": "6ByMnjMVdMG6",
        "outputId": "6e5f8a5d-f430-42ad-f4fb-188c92eecb2a"
      },
      "execution_count": null,
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        {
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            "text/plain": [
              "    0                          1   ...        34      35\n",
              "0  Age  Number of sexual partners  ...  Citology  Biopsy\n",
              "1   18                        4.0  ...         0       0\n",
              "2   15                        1.0  ...         0       0\n",
              "3   34                        1.0  ...         0       0\n",
              "4   52                        5.0  ...         0       0\n",
              "\n",
              "[5 rows x 36 columns]"
            ]
          },
          "metadata": {},
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    },
    {
      "cell_type": "markdown",
      "source": [
        "Count missing values in each column"
      ],
      "metadata": {
        "id": "DYxIx3NluTeY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "missing_data = df.isnull()\n",
        "missing_data.head(5)\n",
        "for column in missing_data.columns.values.tolist():\n",
        "    print(column)\n",
        "    print (missing_data[column].value_counts())\n",
        "    print(\"\")  "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
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      "cell_type": "markdown",
      "source": [
        "Drop Columns:\n",
        "a.(int) STDs: Time since first diagnosisb.(int)\n",
        "b. STDs: Time since last diagnosis"
      ],
      "metadata": {
        "id": "gG4gYZ6OuXkV"
      }
    },
    {
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      "source": [
        "df.drop(27, axis = 1, inplace=True)\n",
        "df.drop(26, axis = 1, inplace=True)\n",
        "df.head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 322
        },
        "id": "2nw5zXWRufbc",
        "outputId": "27cb4168-78e3-4d2a-c8f9-0d65451c105d"
      },
      "execution_count": null,
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              "      <th></th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "      <th>5</th>\n",
              "      <th>6</th>\n",
              "      <th>7</th>\n",
              "      <th>8</th>\n",
              "      <th>9</th>\n",
              "      <th>10</th>\n",
              "      <th>11</th>\n",
              "      <th>12</th>\n",
              "      <th>13</th>\n",
              "      <th>14</th>\n",
              "      <th>15</th>\n",
              "      <th>16</th>\n",
              "      <th>17</th>\n",
              "      <th>18</th>\n",
              "      <th>19</th>\n",
              "      <th>20</th>\n",
              "      <th>21</th>\n",
              "      <th>22</th>\n",
              "      <th>23</th>\n",
              "      <th>24</th>\n",
              "      <th>25</th>\n",
              "      <th>28</th>\n",
              "      <th>29</th>\n",
              "      <th>30</th>\n",
              "      <th>31</th>\n",
              "      <th>32</th>\n",
              "      <th>33</th>\n",
              "      <th>34</th>\n",
              "      <th>35</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Age</td>\n",
              "      <td>Number of sexual partners</td>\n",
              "      <td>First sexual intercourse</td>\n",
              "      <td>Num of pregnancies</td>\n",
              "      <td>Smokes</td>\n",
              "      <td>Smokes (years)</td>\n",
              "      <td>Smokes (packs/year)</td>\n",
              "      <td>Hormonal Contraceptives</td>\n",
              "      <td>Hormonal Contraceptives (years)</td>\n",
              "      <td>IUD</td>\n",
              "      <td>IUD (years)</td>\n",
              "      <td>STDs</td>\n",
              "      <td>STDs (number)</td>\n",
              "      <td>STDs:condylomatosis</td>\n",
              "      <td>STDs:cervical condylomatosis</td>\n",
              "      <td>STDs:vaginal condylomatosis</td>\n",
              "      <td>STDs:vulvo-perineal condylomatosis</td>\n",
              "      <td>STDs:syphilis</td>\n",
              "      <td>STDs:pelvic inflammatory disease</td>\n",
              "      <td>STDs:genital herpes</td>\n",
              "      <td>STDs:molluscum contagiosum</td>\n",
              "      <td>STDs:AIDS</td>\n",
              "      <td>STDs:HIV</td>\n",
              "      <td>STDs:Hepatitis B</td>\n",
              "      <td>STDs:HPV</td>\n",
              "      <td>STDs: Number of diagnosis</td>\n",
              "      <td>Dx:Cancer</td>\n",
              "      <td>Dx:CIN</td>\n",
              "      <td>Dx:HPV</td>\n",
              "      <td>Dx</td>\n",
              "      <td>Hinselmann</td>\n",
              "      <td>Schiller</td>\n",
              "      <td>Citology</td>\n",
              "      <td>Biopsy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>18</td>\n",
              "      <td>4.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>15</td>\n",
              "      <td>1.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>34</td>\n",
              "      <td>1.0</td>\n",
              "      <td>?</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>52</td>\n",
              "      <td>5.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>37.0</td>\n",
              "      <td>37.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b49fbdce-ed62-40ec-9d78-a809d5fc94a0')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\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",
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              "          document.querySelector('#df-b49fbdce-ed62-40ec-9d78-a809d5fc94a0 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-b49fbdce-ed62-40ec-9d78-a809d5fc94a0');\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",
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              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          element.appendChild(docLink);\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "    0                          1   ...        34      35\n",
              "0  Age  Number of sexual partners  ...  Citology  Biopsy\n",
              "1   18                        4.0  ...         0       0\n",
              "2   15                        1.0  ...         0       0\n",
              "3   34                        1.0  ...         0       0\n",
              "4   52                        5.0  ...         0       0\n",
              "\n",
              "[5 rows x 34 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    }
  ]
}