datasci_6_anova.ipynb

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      "cell_type": "markdown",
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        "<a href=\"https://colab.research.google.com/github/Helzheng123/datasci_6_anova/blob/main/datasci_6_anova.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "cell_type": "code",
      "execution_count": 43,
      "metadata": {
        "colab": {
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        },
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        "outputId": "dca82aaf-a892-498f-eecf-6a51d62fa96a"
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      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: ucimlrepo in /usr/local/lib/python3.10/dist-packages (0.0.3)\n"
          ]
        }
      ],
      "source": [
        "!pip install ucimlrepo"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from ucimlrepo import fetch_ucirepo\n",
        "import pandas as pd\n",
        "import scipy.stats as stats\n",
        "import statsmodels.api as sm\n",
        "import re\n",
        "import matplotlib.pyplot as plt\n",
        "from statsmodels.formula.api import ols\n",
        "from statsmodels.stats.multicomp import pairwise_tukeyhsd"
      ],
      "metadata": {
        "id": "TjxhC6RVX90N"
      },
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#1. Data Preparation:"
      ],
      "metadata": {
        "id": "8INoy_RLtCfI"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### **Research Question**:  How do the race of the patient (race) and their A1C test results (A1Cresult) jointly influence the duration of their hospital stay (time_in_hospital)?\n",
        "\n",
        "**VARIABLES OF INTEREST**:\n",
        "- Factor 1 (IV1): (Race - race): Caucasian, Asian, African American, Hispanic, Other\n",
        "- Factor 2 (IV2): (A1C test result - a1c): >8%, 7%, Normal, None (not measure)\n",
        "- Dependent Variable: Duration hospital stay (time_in_hospital)"
      ],
      "metadata": {
        "id": "0b11hyUFar8-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# fetch dataset\n",
        "diabetes_130_us_hospitals_for_years_1999_2008 = fetch_ucirepo(id=296)\n",
        "\n",
        "# data (as pandas dataframes)\n",
        "X = diabetes_130_us_hospitals_for_years_1999_2008.data.features\n",
        "y = diabetes_130_us_hospitals_for_years_1999_2008.data.targets"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ivpQZGr9X3rr",
        "outputId": "93532a18-f0ad-407e-f498-a723bd1bea73"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/ucimlrepo/fetch.py:97: DtypeWarning: Columns (10) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(data_url)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataframe1 = pd.DataFrame(X)\n",
        "dataframe1"
      ],
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      },
      "execution_count": 46,
      "outputs": [
        {
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              "                   race  gender      age weight  admission_type_id  \\\n",
              "0             Caucasian  Female   [0-10)    NaN                  6   \n",
              "1             Caucasian  Female  [10-20)    NaN                  1   \n",
              "2       AfricanAmerican  Female  [20-30)    NaN                  1   \n",
              "3             Caucasian    Male  [30-40)    NaN                  1   \n",
              "4             Caucasian    Male  [40-50)    NaN                  1   \n",
              "...                 ...     ...      ...    ...                ...   \n",
              "101761  AfricanAmerican    Male  [70-80)    NaN                  1   \n",
              "101762  AfricanAmerican  Female  [80-90)    NaN                  1   \n",
              "101763        Caucasian    Male  [70-80)    NaN                  1   \n",
              "101764        Caucasian  Female  [80-90)    NaN                  2   \n",
              "101765        Caucasian    Male  [70-80)    NaN                  1   \n",
              "\n",
              "        discharge_disposition_id  admission_source_id  time_in_hospital  \\\n",
              "0                             25                    1                 1   \n",
              "1                              1                    7                 3   \n",
              "2                              1                    7                 2   \n",
              "3                              1                    7                 2   \n",
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              "...                          ...                  ...               ...   \n",
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              "101763                         1                    7                 1   \n",
              "101764                         3                    7                10   \n",
              "101765                         1                    7                 6   \n",
              "\n",
              "       payer_code         medical_specialty  ...  examide  citoglipton  \\\n",
              "0             NaN  Pediatrics-Endocrinology  ...       No           No   \n",
              "1             NaN                       NaN  ...       No           No   \n",
              "2             NaN                       NaN  ...       No           No   \n",
              "3             NaN                       NaN  ...       No           No   \n",
              "4             NaN                       NaN  ...       No           No   \n",
              "...           ...                       ...  ...      ...          ...   \n",
              "101761         MC                       NaN  ...       No           No   \n",
              "101762         MC                       NaN  ...       No           No   \n",
              "101763         MC                       NaN  ...       No           No   \n",
              "101764         MC           Surgery-General  ...       No           No   \n",
              "101765        NaN                       NaN  ...       No           No   \n",
              "\n",
              "        insulin  glyburide-metformin  glipizide-metformin  \\\n",
              "0            No                   No                   No   \n",
              "1            Up                   No                   No   \n",
              "2            No                   No                   No   \n",
              "3            Up                   No                   No   \n",
              "4        Steady                   No                   No   \n",
              "...         ...                  ...                  ...   \n",
              "101761     Down                   No                   No   \n",
              "101762   Steady                   No                   No   \n",
              "101763     Down                   No                   No   \n",
              "101764       Up                   No                   No   \n",
              "101765       No                   No                   No   \n",
              "\n",
              "        glimepiride-pioglitazone metformin-rosiglitazone  \\\n",
              "0                             No                      No   \n",
              "1                             No                      No   \n",
              "2                             No                      No   \n",
              "3                             No                      No   \n",
              "4                             No                      No   \n",
              "...                          ...                     ...   \n",
              "101761                        No                      No   \n",
              "101762                        No                      No   \n",
              "101763                        No                      No   \n",
              "101764                        No                      No   \n",
              "101765                        No                      No   \n",
              "\n",
              "       metformin-pioglitazone change  diabetesMed  \n",
              "0                          No     No           No  \n",
              "1                          No     Ch          Yes  \n",
              "2                          No     No          Yes  \n",
              "3                          No     Ch          Yes  \n",
              "4                          No     Ch          Yes  \n",
              "...                       ...    ...          ...  \n",
              "101761                     No     Ch          Yes  \n",
              "101762                     No     No          Yes  \n",
              "101763                     No     Ch          Yes  \n",
              "101764                     No     Ch          Yes  \n",
              "101765                     No     No           No  \n",
              "\n",
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              "      <th></th>\n",
              "      <th>race</th>\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-3fc34776-3e40-463e-a9d6-4a9bbf1e1ae4 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-3fc34776-3e40-463e-a9d6-4a9bbf1e1ae4');\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-3ea05825-7d25-475b-a8b5-c6c4a55e15ff\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-3ea05825-7d25-475b-a8b5-c6c4a55e15ff')\"\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-3ea05825-7d25-475b-a8b5-c6c4a55e15ff button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataframe2 = pd.DataFrame(y)\n",
        "dataframe2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "xDRwxEfdY6-G",
        "outputId": "63e7e091-4963-4f84-f3a2-be0983745529"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       readmitted\n",
              "0              NO\n",
              "1             >30\n",
              "2              NO\n",
              "3              NO\n",
              "4              NO\n",
              "...           ...\n",
              "101761        >30\n",
              "101762         NO\n",
              "101763         NO\n",
              "101764         NO\n",
              "101765         NO\n",
              "\n",
              "[101766 rows x 1 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-46a22c75-cab6-45e3-a543-db30a5f92934\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>readmitted</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>NO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>&gt;30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>NO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>NO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>NO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101761</th>\n",
              "      <td>&gt;30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101762</th>\n",
              "      <td>NO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101763</th>\n",
              "      <td>NO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101764</th>\n",
              "      <td>NO</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101765</th>\n",
              "      <td>NO</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>101766 rows × 1 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-46a22c75-cab6-45e3-a543-db30a5f92934')\"\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 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .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-46a22c75-cab6-45e3-a543-db30a5f92934 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-46a22c75-cab6-45e3-a543-db30a5f92934');\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-743e2e3c-2aa9-4851-801b-117578c38619\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-743e2e3c-2aa9-4851-801b-117578c38619')\"\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-743e2e3c-2aa9-4851-801b-117578c38619 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Checking Column names\n",
        "dataframe1.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "St8K1iF6c_p-",
        "outputId": "a8e12dcd-cce8-4613-b2c2-6144ed66ccda"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['race', 'gender', 'age', 'weight', 'admission_type_id',\n",
              "       'discharge_disposition_id', 'admission_source_id', 'time_in_hospital',\n",
              "       'payer_code', 'medical_specialty', 'num_lab_procedures',\n",
              "       'num_procedures', 'num_medications', 'number_outpatient',\n",
              "       'number_emergency', 'number_inpatient', 'diag_1', 'diag_2', 'diag_3',\n",
              "       'number_diagnoses', 'max_glu_serum', 'A1Cresult', 'metformin',\n",
              "       'repaglinide', 'nateglinide', 'chlorpropamide', 'glimepiride',\n",
              "       'acetohexamide', 'glipizide', 'glyburide', 'tolbutamide',\n",
              "       'pioglitazone', 'rosiglitazone', 'acarbose', 'miglitol', 'troglitazone',\n",
              "       'tolazamide', 'examide', 'citoglipton', 'insulin',\n",
              "       'glyburide-metformin', 'glipizide-metformin',\n",
              "       'glimepiride-pioglitazone', 'metformin-rosiglitazone',\n",
              "       'metformin-pioglitazone', 'change', 'diabetesMed'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Cleaning columns for dataset\n",
        "\n",
        "def clean_column(df):\n",
        "  def clean_name(name):\n",
        "        cleaned_name = re.sub(r'[^a-zA-Z0-9]', '', name)\n",
        "        return cleaned_name.lower()\n",
        "\n",
        "  dataframe1.columns = [clean_name(col) for col in dataframe1.columns]\n",
        "  return df\n",
        "\n",
        "clean_df = clean_column(dataframe1)\n",
        "clean_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        },
        "id": "yq0SCxjIdWVc",
        "outputId": "ccaf03d9-27d1-41c6-875e-ed4abd8055bf"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   race  gender      age weight  admissiontypeid  \\\n",
              "0             Caucasian  Female   [0-10)    NaN                6   \n",
              "1             Caucasian  Female  [10-20)    NaN                1   \n",
              "2       AfricanAmerican  Female  [20-30)    NaN                1   \n",
              "3             Caucasian    Male  [30-40)    NaN                1   \n",
              "4             Caucasian    Male  [40-50)    NaN                1   \n",
              "...                 ...     ...      ...    ...              ...   \n",
              "101761  AfricanAmerican    Male  [70-80)    NaN                1   \n",
              "101762  AfricanAmerican  Female  [80-90)    NaN                1   \n",
              "101763        Caucasian    Male  [70-80)    NaN                1   \n",
              "101764        Caucasian  Female  [80-90)    NaN                2   \n",
              "101765        Caucasian    Male  [70-80)    NaN                1   \n",
              "\n",
              "        dischargedispositionid  admissionsourceid  timeinhospital payercode  \\\n",
              "0                           25                  1               1       NaN   \n",
              "1                            1                  7               3       NaN   \n",
              "2                            1                  7               2       NaN   \n",
              "3                            1                  7               2       NaN   \n",
              "4                            1                  7               1       NaN   \n",
              "...                        ...                ...             ...       ...   \n",
              "101761                       3                  7               3        MC   \n",
              "101762                       4                  5               5        MC   \n",
              "101763                       1                  7               1        MC   \n",
              "101764                       3                  7              10        MC   \n",
              "101765                       1                  7               6       NaN   \n",
              "\n",
              "                medicalspecialty  ...  examide  citoglipton  insulin  \\\n",
              "0       Pediatrics-Endocrinology  ...       No           No       No   \n",
              "1                            NaN  ...       No           No       Up   \n",
              "2                            NaN  ...       No           No       No   \n",
              "3                            NaN  ...       No           No       Up   \n",
              "4                            NaN  ...       No           No   Steady   \n",
              "...                          ...  ...      ...          ...      ...   \n",
              "101761                       NaN  ...       No           No     Down   \n",
              "101762                       NaN  ...       No           No   Steady   \n",
              "101763                       NaN  ...       No           No     Down   \n",
              "101764           Surgery-General  ...       No           No       Up   \n",
              "101765                       NaN  ...       No           No       No   \n",
              "\n",
              "        glyburidemetformin  glipizidemetformin  glimepiridepioglitazone  \\\n",
              "0                       No                  No                       No   \n",
              "1                       No                  No                       No   \n",
              "2                       No                  No                       No   \n",
              "3                       No                  No                       No   \n",
              "4                       No                  No                       No   \n",
              "...                    ...                 ...                      ...   \n",
              "101761                  No                  No                       No   \n",
              "101762                  No                  No                       No   \n",
              "101763                  No                  No                       No   \n",
              "101764                  No                  No                       No   \n",
              "101765                  No                  No                       No   \n",
              "\n",
              "       metforminrosiglitazone metforminpioglitazone change  diabetesmed  \n",
              "0                          No                    No     No           No  \n",
              "1                          No                    No     Ch          Yes  \n",
              "2                          No                    No     No          Yes  \n",
              "3                          No                    No     Ch          Yes  \n",
              "4                          No                    No     Ch          Yes  \n",
              "...                       ...                   ...    ...          ...  \n",
              "101761                     No                    No     Ch          Yes  \n",
              "101762                     No                    No     No          Yes  \n",
              "101763                     No                    No     Ch          Yes  \n",
              "101764                     No                    No     Ch          Yes  \n",
              "101765                     No                    No     No           No  \n",
              "\n",
              "[101766 rows x 47 columns]"
            ],
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              "      <th></th>\n",
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              "      <th>metforminrosiglitazone</th>\n",
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              "      <td>NaN</td>\n",
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              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
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              "      <td>Yes</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <th>101761</th>\n",
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              "      <td>7</td>\n",
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              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101762</th>\n",
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              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
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              "    <tr>\n",
              "      <th>101763</th>\n",
              "      <td>Caucasian</td>\n",
              "      <td>Male</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Down</td>\n",
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              "      <td>No</td>\n",
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              "      <td>Ch</td>\n",
              "      <td>Yes</td>\n",
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              "    <tr>\n",
              "      <th>101764</th>\n",
              "      <td>Caucasian</td>\n",
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              "      <td>Yes</td>\n",
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              "    <tr>\n",
              "      <th>101765</th>\n",
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              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>101766 rows × 47 columns</p>\n",
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              "                                                    [key], {});\n",
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              "\n",
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              "            'suggestCharts', [key], {});\n",
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              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = clean_df.rename(columns = {'a1cresult' : 'A1C_result', 'timeinhospital' : 'time_in_hospital'})\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        },
        "id": "EE_D0efJe5LW",
        "outputId": "e03fedae-ce7e-4a47-c794-25e86a2ee2b6"
      },
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   race  gender      age weight  admissiontypeid  \\\n",
              "0             Caucasian  Female   [0-10)    NaN                6   \n",
              "1             Caucasian  Female  [10-20)    NaN                1   \n",
              "2       AfricanAmerican  Female  [20-30)    NaN                1   \n",
              "3             Caucasian    Male  [30-40)    NaN                1   \n",
              "4             Caucasian    Male  [40-50)    NaN                1   \n",
              "...                 ...     ...      ...    ...              ...   \n",
              "101761  AfricanAmerican    Male  [70-80)    NaN                1   \n",
              "101762  AfricanAmerican  Female  [80-90)    NaN                1   \n",
              "101763        Caucasian    Male  [70-80)    NaN                1   \n",
              "101764        Caucasian  Female  [80-90)    NaN                2   \n",
              "101765        Caucasian    Male  [70-80)    NaN                1   \n",
              "\n",
              "        dischargedispositionid  admissionsourceid  time_in_hospital payercode  \\\n",
              "0                           25                  1                 1       NaN   \n",
              "1                            1                  7                 3       NaN   \n",
              "2                            1                  7                 2       NaN   \n",
              "3                            1                  7                 2       NaN   \n",
              "4                            1                  7                 1       NaN   \n",
              "...                        ...                ...               ...       ...   \n",
              "101761                       3                  7                 3        MC   \n",
              "101762                       4                  5                 5        MC   \n",
              "101763                       1                  7                 1        MC   \n",
              "101764                       3                  7                10        MC   \n",
              "101765                       1                  7                 6       NaN   \n",
              "\n",
              "                medicalspecialty  ...  examide  citoglipton  insulin  \\\n",
              "0       Pediatrics-Endocrinology  ...       No           No       No   \n",
              "1                            NaN  ...       No           No       Up   \n",
              "2                            NaN  ...       No           No       No   \n",
              "3                            NaN  ...       No           No       Up   \n",
              "4                            NaN  ...       No           No   Steady   \n",
              "...                          ...  ...      ...          ...      ...   \n",
              "101761                       NaN  ...       No           No     Down   \n",
              "101762                       NaN  ...       No           No   Steady   \n",
              "101763                       NaN  ...       No           No     Down   \n",
              "101764           Surgery-General  ...       No           No       Up   \n",
              "101765                       NaN  ...       No           No       No   \n",
              "\n",
              "        glyburidemetformin  glipizidemetformin  glimepiridepioglitazone  \\\n",
              "0                       No                  No                       No   \n",
              "1                       No                  No                       No   \n",
              "2                       No                  No                       No   \n",
              "3                       No                  No                       No   \n",
              "4                       No                  No                       No   \n",
              "...                    ...                 ...                      ...   \n",
              "101761                  No                  No                       No   \n",
              "101762                  No                  No                       No   \n",
              "101763                  No                  No                       No   \n",
              "101764                  No                  No                       No   \n",
              "101765                  No                  No                       No   \n",
              "\n",
              "       metforminrosiglitazone metforminpioglitazone change  diabetesmed  \n",
              "0                          No                    No     No           No  \n",
              "1                          No                    No     Ch          Yes  \n",
              "2                          No                    No     No          Yes  \n",
              "3                          No                    No     Ch          Yes  \n",
              "4                          No                    No     Ch          Yes  \n",
              "...                       ...                   ...    ...          ...  \n",
              "101761                     No                    No     Ch          Yes  \n",
              "101762                     No                    No     No          Yes  \n",
              "101763                     No                    No     Ch          Yes  \n",
              "101764                     No                    No     Ch          Yes  \n",
              "101765                     No                    No     No           No  \n",
              "\n",
              "[101766 rows x 47 columns]"
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              "<p>101766 rows × 47 columns</p>\n",
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              "          + ' 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-8a61b332-45f9-4e83-a297-b75957d0ba97\">\n",
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              "            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",
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              "    background-color: var(--disabled-bg-color);\n",
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              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
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              "\n",
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              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    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-8a61b332-45f9-4e83-a297-b75957d0ba97 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "subset = df[['race', 'A1C_result', 'time_in_hospital']]\n",
        "subset"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "AoygeVOVeaEd",
        "outputId": "ef2f8d00-83f2-42db-f92f-9c53961e175d"
      },
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   race A1C_result  time_in_hospital\n",
              "0             Caucasian       None                 1\n",
              "1             Caucasian       None                 3\n",
              "2       AfricanAmerican       None                 2\n",
              "3             Caucasian       None                 2\n",
              "4             Caucasian       None                 1\n",
              "...                 ...        ...               ...\n",
              "101761  AfricanAmerican         >8                 3\n",
              "101762  AfricanAmerican       None                 5\n",
              "101763        Caucasian       None                 1\n",
              "101764        Caucasian       None                10\n",
              "101765        Caucasian       None                 6\n",
              "\n",
              "[101766 rows x 3 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-28b2dda3-f425-4b45-8e47-75f779a2fbec\" class=\"colab-df-container\">\n",
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              "      <th>race</th>\n",
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              "    <tr>\n",
              "      <th>101762</th>\n",
              "      <td>AfricanAmerican</td>\n",
              "      <td>None</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101763</th>\n",
              "      <td>Caucasian</td>\n",
              "      <td>None</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101764</th>\n",
              "      <td>Caucasian</td>\n",
              "      <td>None</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101765</th>\n",
              "      <td>Caucasian</td>\n",
              "      <td>None</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>101766 rows × 3 columns</p>\n",
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              "\n",
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              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-28b2dda3-f425-4b45-8e47-75f779a2fbec 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-28b2dda3-f425-4b45-8e47-75f779a2fbec');\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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              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "  </button>\n",
              "\n",
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              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
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              "  [theme=dark] .colab-df-quickchart {\n",
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              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
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              "    height: 32px;\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "\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",
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              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
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              "      border-left-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "    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-a85005a8-8c3a-4141-9211-120b8cb09a81 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "missing_values = subset.isnull().sum()\n",
        "missing_values"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jbCJiH5Gfopt",
        "outputId": "05637e90-37c5-4020-a3d8-aafbc2ea3700"
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "race                2273\n",
              "A1C_result             0\n",
              "time_in_hospital       0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Drop values\n",
        "\n",
        "new_df = subset.dropna()\n",
        "new_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "xKtSqoBYf8fj",
        "outputId": "55369240-e5d8-4993-c748-78e6f19f2303"
      },
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   race A1C_result  time_in_hospital\n",
              "0             Caucasian       None                 1\n",
              "1             Caucasian       None                 3\n",
              "2       AfricanAmerican       None                 2\n",
              "3             Caucasian       None                 2\n",
              "4             Caucasian       None                 1\n",
              "...                 ...        ...               ...\n",
              "101761  AfricanAmerican         >8                 3\n",
              "101762  AfricanAmerican       None                 5\n",
              "101763        Caucasian       None                 1\n",
              "101764        Caucasian       None                10\n",
              "101765        Caucasian       None                 6\n",
              "\n",
              "[99493 rows x 3 columns]"
            ],
            "text/html": [
              "\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>race</th>\n",
              "      <th>A1C_result</th>\n",
              "      <th>time_in_hospital</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Caucasian</td>\n",
              "      <td>None</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Caucasian</td>\n",
              "      <td>None</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>AfricanAmerican</td>\n",
              "      <td>None</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Caucasian</td>\n",
              "      <td>None</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Caucasian</td>\n",
              "      <td>None</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101761</th>\n",
              "      <td>AfricanAmerican</td>\n",
              "      <td>&gt;8</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101762</th>\n",
              "      <td>AfricanAmerican</td>\n",
              "      <td>None</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101763</th>\n",
              "      <td>Caucasian</td>\n",
              "      <td>None</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101764</th>\n",
              "      <td>Caucasian</td>\n",
              "      <td>None</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101765</th>\n",
              "      <td>Caucasian</td>\n",
              "      <td>None</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>99493 rows × 3 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-29869307-6e41-4400-80a6-4e3112268b2d')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "      display:flex;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      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-29869307-6e41-4400-80a6-4e3112268b2d 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-29869307-6e41-4400-80a6-4e3112268b2d');\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-48f2c316-2a8c-40f2-85a8-a564abfd9c12\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-48f2c316-2a8c-40f2-85a8-a564abfd9c12')\"\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",
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              "    30% {\n",
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              "      border-top-color: var(--fill-color);\n",
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              "    }\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-48f2c316-2a8c-40f2-85a8-a564abfd9c12 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 2. Assumption Checks:"
      ],
      "metadata": {
        "id": "1QGJBPJ7tLIX"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Normality test using the Shapiro-Wilk Test**\n",
        "\n",
        "- **Null Hypothesis (H0)**: The data follows a normal distribution.\n",
        "\n",
        "- **Alternative Hypothesis (H1)**: The data does not follow a normal distribution."
      ],
      "metadata": {
        "id": "xnB6VFyfwOxz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Normality test\n",
        "# p value is less than 0.05, therefore, with the shapiro test, we reject the null hypothesis.\n",
        "\n",
        "stats.shapiro(new_df['time_in_hospital'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rfXSpOffkC5y",
        "outputId": "c2b74c5f-8e84-42dd-a58e-0f5ac6249921"
      },
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/scipy/stats/_morestats.py:1882: UserWarning: p-value may not be accurate for N > 5000.\n",
            "  warnings.warn(\"p-value may not be accurate for N > 5000.\")\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ShapiroResult(statistic=0.8867098093032837, pvalue=0.0)"
            ]
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# graph visualization\n",
        "# histogram is right skewed\n",
        "\n",
        "plt.hist(new_df['time_in_hospital'], bins=20, edgecolor='k', alpha=0.7)\n",
        "plt.title('Histogram of Time in Hospital')\n",
        "plt.xlabel('Time In Hospital')\n",
        "plt.ylabel('Number')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "FF-UJVfflGjk",
        "outputId": "44e7a0f0-1634-4df4-cce8-586bb56b7e11"
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# for categorical data\n",
        "# all p values are close to or less than 0, all less than 0.05\n",
        "\n",
        "groups = new_df.groupby(['race', 'A1C_result'])\n",
        "\n",
        "for (race_status, A1C_result_status), group_df in groups:\n",
        "    _, p_value = stats.shapiro(group_df['time_in_hospital'])\n",
        "\n",
        "    print(f\"Group ({race_status}, {A1C_result_status}):\")\n",
        "    print(f\"P-value from Shapiro-Wilk Test: {p_value}\\n\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MkF4FTwwmBNb",
        "outputId": "7bd38b45-1911-4f4b-9bd1-9bf39fb26adc"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Group (AfricanAmerican, >7):\n",
            "P-value from Shapiro-Wilk Test: 1.8906119489850806e-16\n",
            "\n",
            "Group (AfricanAmerican, >8):\n",
            "P-value from Shapiro-Wilk Test: 6.7359146155303186e-34\n",
            "\n",
            "Group (AfricanAmerican, None):\n",
            "P-value from Shapiro-Wilk Test: 0.0\n",
            "\n",
            "Group (AfricanAmerican, Norm):\n",
            "P-value from Shapiro-Wilk Test: 2.9696700824519264e-25\n",
            "\n",
            "Group (Asian, >7):\n",
            "P-value from Shapiro-Wilk Test: 0.0023467366117984056\n",
            "\n",
            "Group (Asian, >8):\n",
            "P-value from Shapiro-Wilk Test: 2.233798113593366e-05\n",
            "\n",
            "Group (Asian, None):\n",
            "P-value from Shapiro-Wilk Test: 2.6558121925662052e-21\n",
            "\n",
            "Group (Asian, Norm):\n",
            "P-value from Shapiro-Wilk Test: 0.0007482930086553097\n",
            "\n",
            "Group (Caucasian, >7):\n",
            "P-value from Shapiro-Wilk Test: 1.7925673399754353e-38\n",
            "\n",
            "Group (Caucasian, >8):\n",
            "P-value from Shapiro-Wilk Test: 0.0\n",
            "\n",
            "Group (Caucasian, None):\n",
            "P-value from Shapiro-Wilk Test: 0.0\n",
            "\n",
            "Group (Caucasian, Norm):\n",
            "P-value from Shapiro-Wilk Test: 1.930148504761003e-41\n",
            "\n",
            "Group (Hispanic, >7):\n",
            "P-value from Shapiro-Wilk Test: 2.1721559733123286e-06\n",
            "\n",
            "Group (Hispanic, >8):\n",
            "P-value from Shapiro-Wilk Test: 1.0855431137324345e-12\n",
            "\n",
            "Group (Hispanic, None):\n",
            "P-value from Shapiro-Wilk Test: 1.793864359413239e-35\n",
            "\n",
            "Group (Hispanic, Norm):\n",
            "P-value from Shapiro-Wilk Test: 4.4957931777389604e-07\n",
            "\n",
            "Group (Other, >7):\n",
            "P-value from Shapiro-Wilk Test: 1.5921328667900525e-05\n",
            "\n",
            "Group (Other, >8):\n",
            "P-value from Shapiro-Wilk Test: 1.617614514559662e-10\n",
            "\n",
            "Group (Other, None):\n",
            "P-value from Shapiro-Wilk Test: 2.446808042197051e-30\n",
            "\n",
            "Group (Other, Norm):\n",
            "P-value from Shapiro-Wilk Test: 0.00019315516692586243\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/scipy/stats/_morestats.py:1882: UserWarning: p-value may not be accurate for N > 5000.\n",
            "  warnings.warn(\"p-value may not be accurate for N > 5000.\")\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "####**Insights**: The p-value for the shapiro test is 0.0 which is less than 0.05, resulting in the **rejection** of the null hypothesis. The data does not have a normal distribution. It is also shown in the histogram where the data is skewed right."
      ],
      "metadata": {
        "id": "C0VzcsZgnxqT"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Homogeneity of Variance (Homoscedasticity) Levene/Bartlett test**:\n",
        "\n",
        "- **Null Hypothesis (H0)**: The variances are equal across groups (homogeneity of variance exists).\n",
        "\n",
        "- **Alternative Hypothesis (H1)**: The variances are not equal across all groups (homogeneity of variance is violated)."
      ],
      "metadata": {
        "id": "XDy7wihVo9jo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "new_df['race'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "whXNcanFxPmY",
        "outputId": "21f2fcdc-5d5d-4735-c871-2606f3d2a2eb"
      },
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Caucasian          76099\n",
              "AfricanAmerican    19210\n",
              "Hispanic            2037\n",
              "Other               1506\n",
              "Asian                641\n",
              "Name: race, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Levene's Test\n",
        "\n",
        "stats.levene(\n",
        "    new_df['time_in_hospital'][new_df['race'] == 'AfricanAmerican'][new_df['A1C_result'] == '>7'],\n",
        "    new_df['time_in_hospital'][new_df['race'] == 'AfricanAmerican'][new_df['A1C_result'] == '>8'],\n",
        "    new_df['time_in_hospital'][new_df['race'] == 'AfricanAmerican'][new_df['A1C_result'] == 'None'],\n",
        "    new_df['time_in_hospital'][new_df['race'] == 'AfricanAmerican'][new_df['A1C_result'] == 'Norm'],\n",
        "    new_df['time_in_hospital'][new_df['race'] == 'Caucasian'][new_df['A1C_result'] == '>7'],\n",
        "    new_df['time_in_hospital'][new_df['race'] == 'Caucasian'][new_df['A1C_result'] == '>8'],\n",
        "    new_df['time_in_hospital'][new_df['race'] == 'Caucasian'][new_df['A1C_result'] == 'None'],\n",
        "    new_df['time_in_hospital'][new_df['race'] == 'Caucasian'][new_df['A1C_result'] == 'Norm'],\n",
        "     new_df['time_in_hospital'][new_df['race'] == 'Hispanic'][new_df['A1C_result'] == '>7'],\n",
        "    new_df['time_in_hospital'][new_df['race'] == 'Hispanic'][new_df['A1C_result'] == '>8'],\n",
        "    new_df['time_in_hospital'][new_df['race'] == 'Hispanic'][new_df['A1C_result'] == 'None'],\n",
        "    new_df['time_in_hospital'][new_df['race'] == 'Hispanic'][new_df['A1C_result'] == 'Norm'],\n",
        "     new_df['time_in_hospital'][new_df['race'] == 'Asian'][new_df['A1C_result'] == '>7'],\n",
        "    new_df['time_in_hospital'][new_df['race'] == 'Asian'][new_df['A1C_result'] == '>8'],\n",
        "    new_df['time_in_hospital'][new_df['race'] == 'Asian'][new_df['A1C_result'] == 'None'],\n",
        "    new_df['time_in_hospital'][new_df['race'] == 'Asian'][new_df['A1C_result'] == 'Norm'],\n",
        "     new_df['time_in_hospital'][new_df['race'] == 'Other'][new_df['A1C_result'] == '>7'],\n",
        "    new_df['time_in_hospital'][new_df['race'] == 'Other'][new_df['A1C_result'] == '>8'],\n",
        "    new_df['time_in_hospital'][new_df['race'] == 'Other'][new_df['A1C_result'] == 'None'],\n",
        "    new_df['time_in_hospital'][new_df['race'] == 'Other'][new_df['A1C_result'] == 'Norm'],\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gk_GUhywwkLC",
        "outputId": "c78cfa48-4f1d-4d59-ede3-a45caa3023af"
      },
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LeveneResult(statistic=7.4501020039258, pvalue=9.580811219790571e-21)"
            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "####**Insights**: The p-value of this test is 9.58e-21, which is smaller than 0.05. In this case, we will **reject** the null hypothesis because homogeneity of variance is violated and are not equal across all groups."
      ],
      "metadata": {
        "id": "j0SY3TxJ0f9G"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 3. Conduct the ANOVA:"
      ],
      "metadata": {
        "id": "gAjlXYwatQT5"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Two Way ANOVA Test**:\n",
        "\n",
        "Main Effect:\n",
        "- The difference in time in hospital between different race, disregarding A1C result.\n",
        "- The difference in time in hospital between different A1C result, disregarding race.\n",
        "\n",
        "Interaction Effect:\n",
        "- Investigating the effect of race and A1C result on time in hospital."
      ],
      "metadata": {
        "id": "5HZWOY1sBPkX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Perform Two Way ANOVA\n",
        "model = ols('time_in_hospital ~ C(race) * C(A1C_result)', data=new_df).fit()\n",
        "\n",
        "anova_table = sm.stats.anova_lm(model, typ=2)\n",
        "print(anova_table)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O06kHaSHBO1A",
        "outputId": "bacfa35f-7d77-495d-b403-7687ce6eb6e0"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                              sum_sq       df           F        PR(>F)\n",
            "C(race)                   641.735130      4.0   18.075566  7.501203e-15\n",
            "C(A1C_result)            3895.231358      3.0  146.287793  1.363867e-94\n",
            "C(race):C(A1C_result)     276.823623     12.0    2.599070  1.845652e-03\n",
            "Residual               882895.150091  99473.0         NaN           NaN\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "####**Insights**:\n",
        "\n",
        "Race Effect (Main Effect of Race):\n",
        "- F-value: 18.08\n",
        "- P-value: 7.50e-15\n",
        "- The p-value is below the significance level of 0.05, indicating that there is a **statistically significant difference** in time in hospital when compared to different race, regardless of the A1C result.\n",
        "\n",
        "A1C Result Effect (Main Effect of A1C Result):\n",
        "- F-value: 146.29\n",
        "- P-value: 1.36e-94\n",
        "- The p-value is below the significance level of 0.05, indicating that there is a **statistically significant difference** in time in hospital when compared to different A1C result level, regardless of race.\n",
        "\n",
        "Interaction Effect (Race:A1C Result):\n",
        "- F-value: 2.60\n",
        "- P-value: 1.85e-03\n",
        "- The p-value is below the significance level of 0.05, indicating that there was a **significant interaction** between race and A1C result. This shows that the effect of race on time in hospital does vary depending on the A1C result (and vice versa).\n"
      ],
      "metadata": {
        "id": "IqMPf1PGD0lw"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Kruskal-Wallis H Test For Non-Parametric ANOVA**:"
      ],
      "metadata": {
        "id": "UfuN3QqvAfwL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Putting data into each group\n",
        "\n",
        "group1 = new_df['time_in_hospital'][new_df['race'] == 'AfricanAmerican'][new_df['A1C_result'] == '>7']\n",
        "group2 = new_df['time_in_hospital'][new_df['race'] == 'AfricanAmerican'][new_df['A1C_result'] == '>8']\n",
        "group3 = new_df['time_in_hospital'][new_df['race'] == 'AfricanAmerican'][new_df['A1C_result'] == 'None']\n",
        "group4 = new_df['time_in_hospital'][new_df['race'] == 'AfricanAmerican'][new_df['A1C_result'] == 'Norm']\n",
        "group5 = new_df['time_in_hospital'][new_df['race'] == 'Caucasian'][new_df['A1C_result'] == '>7']\n",
        "group6 = new_df['time_in_hospital'][new_df['race'] == 'Caucasian'][new_df['A1C_result'] == '>8']\n",
        "group7 = new_df['time_in_hospital'][new_df['race'] == 'Caucasian'][new_df['A1C_result'] == 'None']\n",
        "group8 = new_df['time_in_hospital'][new_df['race'] == 'Caucasian'][new_df['A1C_result'] == 'Norm']\n",
        "group9 = new_df['time_in_hospital'][new_df['race'] == 'Hispanic'][new_df['A1C_result'] == '>7']\n",
        "group10 = new_df['time_in_hospital'][new_df['race'] == 'Hispanic'][new_df['A1C_result'] == '>8']\n",
        "group11 = new_df['time_in_hospital'][new_df['race'] == 'Hispanic'][new_df['A1C_result'] == 'None']\n",
        "group12 = new_df['time_in_hospital'][new_df['race'] == 'Hispanic'][new_df['A1C_result'] == 'Norm']\n",
        "group13 = new_df['time_in_hospital'][new_df['race'] == 'Asian'][new_df['A1C_result'] == '>7']\n",
        "group14 = new_df['time_in_hospital'][new_df['race'] == 'Asian'][new_df['A1C_result'] == '>8']\n",
        "group15 = new_df['time_in_hospital'][new_df['race'] == 'Asian'][new_df['A1C_result'] == 'None']\n",
        "group16 = new_df['time_in_hospital'][new_df['race'] == 'Asian'][new_df['A1C_result'] == 'Norm']\n",
        "group17 = new_df['time_in_hospital'][new_df['race'] == 'Other'][new_df['A1C_result'] == '>7']\n",
        "group18 = new_df['time_in_hospital'][new_df['race'] == 'Other'][new_df['A1C_result'] == '>8']\n",
        "group19 = new_df['time_in_hospital'][new_df['race'] == 'Other'][new_df['A1C_result'] == 'None']\n",
        "group20 = new_df['time_in_hospital'][new_df['race'] == 'Other'][new_df['A1C_result'] == 'Norm']"
      ],
      "metadata": {
        "id": "2ensl3W59Btg"
      },
      "execution_count": 60,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Performing Kruskal-Wallis H Test\n",
        "\n",
        "h_stat, p_val = stats.kruskal(group1, group2, group3, group4, group5, group6, group7, group8, group9, group10, group11, group12, group13, group14, group15, group16, group17, group18, group19, group20)\n",
        "print(f\"H-statistic: {h_stat}\")\n",
        "print(f\"P-value: {p_val}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gH-lLfx9Asos",
        "outputId": "f584f6ca-7ff3-4cfb-badb-6de94d56a72a"
      },
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "H-statistic: 586.9162836240483\n",
            "P-value: 2.904007184732194e-112\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### **Insights**: Since our data doesn't follow a normal distribution and the variances across the groups are not equal, we will conduct a Kruskal-Wallis H Test since it *does not assume equal variances*. A parametric one-way ANOVA test *assumes normality and equal variances*, therefore, it is necessary to conduct a Kruskal-Wallis H test in this condition.\n",
        "\n",
        "- The H-statistic is 586.92, illustrating a greater variability between the groups.\n",
        "- The p-value is 2.90e-112 which shows that there are significant differences between the groups. Because it is such a small p-value, it shows that this is unlikely due to random chance."
      ],
      "metadata": {
        "id": "7SJV9nJKCvo7"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 4. **Post-Hoc Test**:\n"
      ],
      "metadata": {
        "id": "KO0s9XcxC2yB"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**Hypotheses**:\n",
        "**Null Hypothesis (H0)**: There is no statistical differences in mean between two groups.\n",
        "\n",
        "**Alternative Hypothesis (H1)**: There is a statistical difference in mean between two groups."
      ],
      "metadata": {
        "id": "DYsawuQOIoge"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# changing to strings/int (just making sure)\n",
        "new_df['race'] = new_df['race'].astype(str)\n",
        "new_df['A1C_result'] = new_df['A1C_result'].astype(str)\n",
        "new_df['time_in_hospital'] = new_df['time_in_hospital'].astype(int)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U9DUXKWKEwt2",
        "outputId": "61ae96dc-aa2d-4856-9594-756c382bb3d3"
      },
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-62-fa18b4ce8928>:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  new_df['race'] = new_df['race'].astype(str)\n",
            "<ipython-input-62-fa18b4ce8928>:3: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  new_df['A1C_result'] = new_df['A1C_result'].astype(str)\n",
            "<ipython-input-62-fa18b4ce8928>:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  new_df['time_in_hospital'] = new_df['time_in_hospital'].astype(int)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# For Race\n",
        "posthoc_race = pairwise_tukeyhsd(endog=new_df['time_in_hospital'], groups=new_df['race'], alpha=0.05)\n",
        "print(\"Tukey HSD test for Race:\\n\", posthoc_race)\n",
        "\n",
        "# For A1C Result\n",
        "posthoc_a1c = pairwise_tukeyhsd(endog=new_df['time_in_hospital'], groups=new_df['A1C_result'], alpha=0.05)\n",
        "print(\"\\nTukey HSD test for A1C Result:\\n\", posthoc_a1c)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Tt__XQ1wC2U7",
        "outputId": "c20379f9-7c40-4b3e-e9aa-016ad988ec98"
      },
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Tukey HSD test for Race:\n",
            "       Multiple Comparison of Means - Tukey HSD, FWER=0.05       \n",
            "================================================================\n",
            "     group1       group2  meandiff p-adj   lower   upper  reject\n",
            "----------------------------------------------------------------\n",
            "AfricanAmerican     Asian  -0.5125 0.0002 -0.8396 -0.1855   True\n",
            "AfricanAmerican Caucasian  -0.1221    0.0 -0.1879 -0.0564   True\n",
            "AfricanAmerican  Hispanic   -0.448    0.0 -0.6378 -0.2582   True\n",
            "AfricanAmerican     Other  -0.2343 0.0278 -0.4523 -0.0163   True\n",
            "          Asian Caucasian   0.3904 0.0087  0.0673  0.7135   True\n",
            "          Asian  Hispanic   0.0646 0.9894 -0.3043  0.4335  False\n",
            "          Asian     Other   0.2783 0.2778 -0.1059  0.6624  False\n",
            "      Caucasian  Hispanic  -0.3258    0.0 -0.5087  -0.143   True\n",
            "      Caucasian     Other  -0.1121 0.5995 -0.3241  0.0998  False\n",
            "       Hispanic     Other   0.2137 0.2175 -0.0631  0.4905  False\n",
            "----------------------------------------------------------------\n",
            "\n",
            "Tukey HSD test for A1C Result:\n",
            " Multiple Comparison of Means - Tukey HSD, FWER=0.05 \n",
            "====================================================\n",
            "group1 group2 meandiff p-adj   lower   upper  reject\n",
            "----------------------------------------------------\n",
            "    >7     >8   -0.157 0.0397 -0.3089 -0.0051   True\n",
            "    >7   None   -0.588    0.0 -0.7162 -0.4598   True\n",
            "    >7   Norm   0.0238  0.983 -0.1425  0.1902  False\n",
            "    >8   None   -0.431    0.0 -0.5209 -0.3412   True\n",
            "    >8   Norm   0.1808 0.0046  0.0418  0.3198   True\n",
            "  None   Norm   0.6118    0.0  0.4993  0.7243   True\n",
            "----------------------------------------------------\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Insights**:\n",
        "\n",
        "##1. Tukey HSD test for Race:\n",
        "- **African American and Asian**: p-value is *less than 0.05*, therefore, we have evidence to reject the null hypothesis as the difference in race between African American and Asian is statistically significant.\n",
        "\n",
        "- **African American and Caucasian**: p-value is *less than 0.05*, therefore, we have evidence to reject the null hypothesis as the difference in race between African American and Caucasian is statistically significant.\n",
        "\n",
        "- **African American and Hispanic**: p-value is *less than 0.05*, therefore, we have evidence to reject the null hypothesis as the difference in race between African American and Hispanic is statistically significant.\n",
        "\n",
        "- **African American and Other**: p-value is *less than 0.05*, therefore, we have evidence to reject the null hypothesis as the difference in race between African American and Other is statistically significant.\n",
        "\n",
        "- **Asian and Caucasian**: p-value is *less than 0.05*, therefore, we have evidence to reject the null hypothesis as the difference in race between Asian and Caucasian is statistically significant.\n",
        "\n",
        "- **Asian and Hispanic**: p-value is *greater than 0.05*, therefore we do not have enough evidence to reject the null hypothesis as the difference in race between Asian and Hispanic is not statistically significant.\n",
        "\n",
        "- **Asian and Other**: p-value is *greater than 0.05*, therefore we do not have enough evidence to reject the null hypothesis as the difference in race between Asian and Other is not statistically significant.\n",
        "\n",
        "- **Caucasian and Hispanic**: p-value is *less than 0.05*, therefore, we have evidence to reject the null hypothesis as the difference in race between\n",
        "Caucasian and Hispanic is statistically significant.\n",
        "\n",
        "- **Caucasian and Other**: p-value is *greater than 0.05*, therefore we do not have enough evidence to reject the null hypothesis as the difference in race between Caucasian and Other is not statistically significant.\n",
        "\n",
        "- **Hispanic and Other**: p-value is *greater than 0.05*, therefore we do not have enough evidence to reject the null hypothesis as the difference in race between Hispanic and Other is not statistically significant.\n",
        "\n",
        "##2. Tukey HSD test for A1C Result:\n",
        "\n",
        "a.**>7 and >8**:  p-value is *less than 0.05*, therefore, we have evidence to reject the null hypothesis as the difference in A1C result between >7 and >8 is statistically significant.\n",
        "\n",
        "b.**>7 and None**:  p-value is *less than 0.05*, therefore, we have evidence to reject the null hypothesis as the difference in A1C result between >7 and None is statistically significant.\n",
        "\n",
        "c. **>7 and Norm**:  p-value is *greater than 0.05*, therefore we do not have enough evidence to reject the null hypothesis as the difference in A1C result  between >7 and Norm is not statistically significant.\n",
        "\n",
        "d. **>8 and None**: p-value is *less than 0.05*, therefore, we have evidence to reject the null hypothesis as the difference in A1C result between >8 and None is statistically significant.\n",
        "\n",
        "e. **>8 and Norm**: p-value is *less than 0.05*, therefore, we have evidence to reject the null hypothesis as the difference in A1C result between >8 and Norm is statistically significant.\n",
        "\n",
        "f. **None and Norm**: p-value is *less than 0.05*, therefore, we have evidence to reject the null hypothesis as the difference in A1C result between None and Norm is statistically significant."
      ],
      "metadata": {
        "id": "wayN-sitHyJs"
      }
    }
  ]
}