Problem_3.ipynb

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        "**Problem 3**\n",
        "\n",
        "A drug is generally administered to a patient in certain patterns or in regular intervals of time.\n",
        "\n",
        "   **For example Chemotherapy which is drug treatment in case of Cancer is generally given to patients in an interval 3-4 weeks, i.e.**\n",
        "   **Every 3-4 weeks patients are administered with the drug.**\n",
        "\n",
        "Similarly to Chemotherapy, “Target Drug” is also administered/prescribed in certain patterns, we want to analyse in what patterns “Target Drug“ is administered/prescribed to patients, there might be multiple patterns in which “Target Drug” is administered/prescribed, come up with an analysis which to extract the dominant patterns in the data using clustering or other unsupervised techniques.\n",
        "\n",
        "Visualise the prescription patterns with time on X-axis (month) and prescriptions on Y-axis for each of the patterns you are able to extract(Below is an example of a prescription pattern, where a prescription is made at least once in the first two months followed by one prescription for every two months)."
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      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.cluster import KMeans\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn.decomposition import PCA\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "\n",
        "from yellowbrick.cluster import KElbowVisualizer, SilhouetteVisualizer\n",
        "from sklearn.metrics import silhouette_score\n",
        "\n",
        "%matplotlib inline\n",
        "sns.set_context('notebook')\n",
        "plt.style.use('fivethirtyeight') #https://matplotlib.org/stable/gallery/style_sheets/style_sheets_reference.html\n",
        "from warnings import filterwarnings\n",
        "filterwarnings('ignore')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pdf = pd.read_parquet('/content/test.parquet')"
      ],
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        "id": "0vF7AZraNh9y"
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      "execution_count": 2,
      "outputs": []
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              "                                  Patient-Uid       Date        Incident\n",
              "0        a0f9e8a9-1c7c-11ec-8d25-16262ee38c7f 2016-12-08  SYMPTOM_TYPE_0\n",
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              "4        a0f9e8a9-1c7c-11ec-8d25-16262ee38c7f 2017-11-04  SYMPTOM_TYPE_0\n",
              "...                                       ...        ...             ...\n",
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              "1372857  a10272c9-1c7c-11ec-b3ce-16262ee38c7f 2017-02-04     DRUG_TYPE_2\n",
              "1372858  a10272c9-1c7c-11ec-b3ce-16262ee38c7f 2017-09-25     DRUG_TYPE_8\n",
              "1372859  a10272c9-1c7c-11ec-b3ce-16262ee38c7f 2017-05-19     DRUG_TYPE_7\n",
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              "Patient-Uid    0\n",
              "Date           0\n",
              "Incident       0\n",
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 1053424 entries, 0 to 1372859\n",
            "Data columns (total 3 columns):\n",
            " #   Column       Non-Null Count    Dtype         \n",
            "---  ------       --------------    -----         \n",
            " 0   Patient-Uid  1053424 non-null  object        \n",
            " 1   Date         1053424 non-null  datetime64[ns]\n",
            " 2   Incident     1053424 non-null  object        \n",
            "dtypes: datetime64[ns](1), object(2)\n",
            "memory usage: 32.1+ MB\n"
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        "df['Date'] = pd.to_datetime(df['Date'], errors='coerce')\n"
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              "                                  Patient-Uid       Date        Incident\n",
              "0        a0f9e8a9-1c7c-11ec-8d25-16262ee38c7f 2016-12-08  SYMPTOM_TYPE_0\n",
              "1        a0f9e8a9-1c7c-11ec-8d25-16262ee38c7f 2018-10-17     DRUG_TYPE_0\n",
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              "3        a0f9e8a9-1c7c-11ec-8d25-16262ee38c7f 2018-12-05     DRUG_TYPE_1\n",
              "4        a0f9e8a9-1c7c-11ec-8d25-16262ee38c7f 2017-11-04  SYMPTOM_TYPE_0\n",
              "...                                       ...        ...             ...\n",
              "1372854  a10272c9-1c7c-11ec-b3ce-16262ee38c7f 2017-05-11    DRUG_TYPE_13\n",
              "1372856  a10272c9-1c7c-11ec-b3ce-16262ee38c7f 2018-08-22     DRUG_TYPE_2\n",
              "1372857  a10272c9-1c7c-11ec-b3ce-16262ee38c7f 2017-02-04     DRUG_TYPE_2\n",
              "1372858  a10272c9-1c7c-11ec-b3ce-16262ee38c7f 2017-09-25     DRUG_TYPE_8\n",
              "1372859  a10272c9-1c7c-11ec-b3ce-16262ee38c7f 2017-05-19     DRUG_TYPE_7\n",
              "\n",
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              "      <td>a10272c9-1c7c-11ec-b3ce-16262ee38c7f</td>\n",
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              "      <td>a10272c9-1c7c-11ec-b3ce-16262ee38c7f</td>\n",
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          },
          "metadata": {},
          "execution_count": 10
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Split the 'Date' column into separate year, month, and day columns\n",
        "df['Year'] = df['Date'].dt.year\n",
        "df['Month'] = df['Date'].dt.month\n",
        "df['Day'] = df['Date'].dt.day\n",
        "\n",
        "# Drop the original 'Date' column if not needed\n",
        "df.drop(columns='Date', inplace=True)\n",
        "\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "m6_2ALLypU5R",
        "outputId": "60c8fe13-5235-4e1f-a3be-655d6e6ee6d9"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                  Patient-Uid        Incident  Year  Month  \\\n",
              "0        a0f9e8a9-1c7c-11ec-8d25-16262ee38c7f  SYMPTOM_TYPE_0  2016     12   \n",
              "1        a0f9e8a9-1c7c-11ec-8d25-16262ee38c7f     DRUG_TYPE_0  2018     10   \n",
              "2        a0f9e8a9-1c7c-11ec-8d25-16262ee38c7f     DRUG_TYPE_2  2017     12   \n",
              "3        a0f9e8a9-1c7c-11ec-8d25-16262ee38c7f     DRUG_TYPE_1  2018     12   \n",
              "4        a0f9e8a9-1c7c-11ec-8d25-16262ee38c7f  SYMPTOM_TYPE_0  2017     11   \n",
              "...                                       ...             ...   ...    ...   \n",
              "1372854  a10272c9-1c7c-11ec-b3ce-16262ee38c7f    DRUG_TYPE_13  2017      5   \n",
              "1372856  a10272c9-1c7c-11ec-b3ce-16262ee38c7f     DRUG_TYPE_2  2018      8   \n",
              "1372857  a10272c9-1c7c-11ec-b3ce-16262ee38c7f     DRUG_TYPE_2  2017      2   \n",
              "1372858  a10272c9-1c7c-11ec-b3ce-16262ee38c7f     DRUG_TYPE_8  2017      9   \n",
              "1372859  a10272c9-1c7c-11ec-b3ce-16262ee38c7f     DRUG_TYPE_7  2017      5   \n",
              "\n",
              "         Day  \n",
              "0          8  \n",
              "1         17  \n",
              "2          1  \n",
              "3          5  \n",
              "4          4  \n",
              "...      ...  \n",
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              "1372857    4  \n",
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              "\n",
              "[1053424 rows x 5 columns]"
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              "      <td>a10272c9-1c7c-11ec-b3ce-16262ee38c7f</td>\n",
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              "      <th>1372858</th>\n",
              "      <td>a10272c9-1c7c-11ec-b3ce-16262ee38c7f</td>\n",
              "      <td>DRUG_TYPE_8</td>\n",
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              "      <td>9</td>\n",
              "      <td>25</td>\n",
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              "    <tr>\n",
              "      <th>1372859</th>\n",
              "      <td>a10272c9-1c7c-11ec-b3ce-16262ee38c7f</td>\n",
              "      <td>DRUG_TYPE_7</td>\n",
              "      <td>2017</td>\n",
              "      <td>5</td>\n",
              "      <td>19</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df1 = pd.concat([df, pd.get_dummies(df['Incident'])], axis=1)\n"
      ],
      "metadata": {
        "id": "FpbzjpmSpUqK"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df1.head()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 516
        },
        "id": "3Z58freppUSO",
        "outputId": "5f6906be-9d5f-4fd3-ce63-bea251f13000"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                            Patient-Uid        Incident  Year  Month  Day  \\\n",
              "0  a0f9e8a9-1c7c-11ec-8d25-16262ee38c7f  SYMPTOM_TYPE_0  2016     12    8   \n",
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              "3  a0f9e8a9-1c7c-11ec-8d25-16262ee38c7f     DRUG_TYPE_1  2018     12    5   \n",
              "4  a0f9e8a9-1c7c-11ec-8d25-16262ee38c7f  SYMPTOM_TYPE_0  2017     11    4   \n",
              "\n",
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              "    [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-cdfaedc2-fff0-4c4c-a7ef-f666b9001ad3 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-cdfaedc2-fff0-4c4c-a7ef-f666b9001ad3');\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-5b268066-41d2-40aa-94e3-aa57322067a5\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-5b268066-41d2-40aa-94e3-aa57322067a5')\"\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-5b268066-41d2-40aa-94e3-aa57322067a5 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": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dfs = df1.drop(['Patient-Uid', 'Incident'], axis=1)\n",
        "dfs.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 256
        },
        "id": "gKvrLQZtpA9p",
        "outputId": "d4f56020-f569-42e8-8fbc-0fe7920be0af"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Year  Month  Day  DRUG_TYPE_0  DRUG_TYPE_1  DRUG_TYPE_10  DRUG_TYPE_11  \\\n",
              "0  2016     12    8            0            0             0             0   \n",
              "1  2018     10   17            1            0             0             0   \n",
              "2  2017     12    1            0            0             0             0   \n",
              "3  2018     12    5            0            1             0             0   \n",
              "4  2017     11    4            0            0             0             0   \n",
              "\n",
              "   DRUG_TYPE_12  DRUG_TYPE_13  DRUG_TYPE_14  ...  SYMPTOM_TYPE_6  \\\n",
              "0             0             0             0  ...               0   \n",
              "1             0             0             0  ...               0   \n",
              "2             0             0             0  ...               0   \n",
              "3             0             0             0  ...               0   \n",
              "4             0             0             0  ...               0   \n",
              "\n",
              "   SYMPTOM_TYPE_7  SYMPTOM_TYPE_8  SYMPTOM_TYPE_9  TEST_TYPE_0  TEST_TYPE_1  \\\n",
              "0               0               0               0            0            0   \n",
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              "3               0               0               0            0            0   \n",
              "4               0               0               0            0            0   \n",
              "\n",
              "   TEST_TYPE_2  TEST_TYPE_3  TEST_TYPE_4  TEST_TYPE_5  \n",
              "0            0            0            0            0  \n",
              "1            0            0            0            0  \n",
              "2            0            0            0            0  \n",
              "3            0            0            0            0  \n",
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              "\n",
              "[5 rows x 58 columns]"
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              "</table>\n",
              "<p>5 rows × 58 columns</p>\n",
              "</div>\n",
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              "\n",
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              "\n",
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              "\n",
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              "\n",
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              "\n",
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              "      fill: #D2E3FC;\n",
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              "\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",
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              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-6621fec2-5e62-4a8a-bb53-d5bd420f791e 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-6621fec2-5e62-4a8a-bb53-d5bd420f791e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "\n",
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              "      --disabled-bg-color: #DDD;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "\n",
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              "    cursor: pointer;\n",
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              "    padding: 0;\n",
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              "  }\n",
              "\n",
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              "    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-7991cfc6-110f-4d42-8fcf-8db1dda88232 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": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df1.columns\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dCLhPWKQp4OJ",
        "outputId": "08308d62-0eb6-4a35-c10f-0efb65272223"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Patient-Uid', 'Incident', 'Year', 'Month', 'Day', 'DRUG_TYPE_0',\n",
              "       'DRUG_TYPE_1', 'DRUG_TYPE_10', 'DRUG_TYPE_11', 'DRUG_TYPE_12',\n",
              "       'DRUG_TYPE_13', 'DRUG_TYPE_14', 'DRUG_TYPE_15', 'DRUG_TYPE_16',\n",
              "       'DRUG_TYPE_17', 'DRUG_TYPE_2', 'DRUG_TYPE_3', 'DRUG_TYPE_4',\n",
              "       'DRUG_TYPE_5', 'DRUG_TYPE_6', 'DRUG_TYPE_7', 'DRUG_TYPE_8',\n",
              "       'DRUG_TYPE_9', 'PRIMARY_DIAGNOSIS', 'SYMPTOM_TYPE_0', 'SYMPTOM_TYPE_1',\n",
              "       'SYMPTOM_TYPE_10', 'SYMPTOM_TYPE_11', 'SYMPTOM_TYPE_12',\n",
              "       'SYMPTOM_TYPE_13', 'SYMPTOM_TYPE_14', 'SYMPTOM_TYPE_15',\n",
              "       'SYMPTOM_TYPE_16', 'SYMPTOM_TYPE_17', 'SYMPTOM_TYPE_18',\n",
              "       'SYMPTOM_TYPE_19', 'SYMPTOM_TYPE_2', 'SYMPTOM_TYPE_20',\n",
              "       'SYMPTOM_TYPE_21', 'SYMPTOM_TYPE_22', 'SYMPTOM_TYPE_23',\n",
              "       'SYMPTOM_TYPE_24', 'SYMPTOM_TYPE_25', 'SYMPTOM_TYPE_26',\n",
              "       'SYMPTOM_TYPE_27', 'SYMPTOM_TYPE_28', 'SYMPTOM_TYPE_29',\n",
              "       'SYMPTOM_TYPE_3', 'SYMPTOM_TYPE_4', 'SYMPTOM_TYPE_5', 'SYMPTOM_TYPE_6',\n",
              "       'SYMPTOM_TYPE_7', 'SYMPTOM_TYPE_8', 'SYMPTOM_TYPE_9', 'TEST_TYPE_0',\n",
              "       'TEST_TYPE_1', 'TEST_TYPE_2', 'TEST_TYPE_3', 'TEST_TYPE_4',\n",
              "       'TEST_TYPE_5'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# plt.boxplot(data=df1, x='Patient-Uid')\n"
      ],
      "metadata": {
        "id": "FciWr46_p4K6"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ss = StandardScaler()\n",
        "\n",
        "x_std = ss.fit_transform(df1.drop(['Patient-Uid', 'Incident'], axis=1))\n",
        "x_std"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5wwMhy4Bp4F9",
        "outputId": "7cfb833e-748a-4290-f990-a069b39c1d4f"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[-0.86314311,  1.62966652, -0.87639932, ..., -0.05077642,\n",
              "        -0.01892112, -0.00616221],\n",
              "       [ 0.6070774 ,  1.04241525,  0.15272343, ..., -0.05077642,\n",
              "        -0.01892112, -0.00616221],\n",
              "       [-0.12803286,  1.62966652, -1.67682812, ..., -0.05077642,\n",
              "        -0.01892112, -0.00616221],\n",
              "       ...,\n",
              "       [-0.12803286, -1.3065898 , -1.3337872 , ..., -0.05077642,\n",
              "        -0.01892112, -0.00616221],\n",
              "       [-0.12803286,  0.74878962,  1.06749921, ..., -0.05077642,\n",
              "        -0.01892112, -0.00616221],\n",
              "       [-0.12803286, -0.4257129 ,  0.38141738, ..., -0.05077642,\n",
              "        -0.01892112, -0.00616221]])"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "km = KMeans(n_clusters=2)\n",
        "km.fit(x_std)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 75
        },
        "id": "evL1Aswup4B7",
        "outputId": "7b320d2e-231e-4d7a-82af-3dad749729bc"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "KMeans(n_clusters=2)"
            ],
            "text/html": [
              "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KMeans(n_clusters=2)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">KMeans</label><div class=\"sk-toggleable__content\"><pre>KMeans(n_clusters=2)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.**\n",
        "**On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org**"
      ],
      "metadata": {
        "id": "UTqZuVFMqQgI"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "centeroids = km.cluster_centers_\n",
        "centeroids"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V9z9fSr5p3-q",
        "outputId": "a9eac3e5-e847-4f96-a7fe-a2b9a6f01b0e"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[-3.55270339e-03, -2.31168968e-04, -4.24358654e-04,\n",
              "         4.40677165e-02,  6.27752222e-02, -6.35857673e-02,\n",
              "         1.81579856e-02,  7.44175764e-03,  8.92863821e-03,\n",
              "         9.87722586e-03,  5.18627880e-03,  2.88076433e-03,\n",
              "        -2.75578314e-03,  4.40023005e-02,  2.87722661e-02,\n",
              "         6.00517841e-03,  1.99945761e-02,  6.69987595e-02,\n",
              "         4.39911256e-02,  3.39191461e-02,  2.25176844e-02,\n",
              "        -3.71900602e-01,  1.85461624e-02,  7.61423208e-03,\n",
              "         5.91127147e-03,  3.89787819e-03,  4.27893816e-03,\n",
              "         3.22399329e-03,  6.97670728e-03,  5.96910749e-03,\n",
              "         5.55700262e-03,  3.73881279e-03,  1.79140225e-03,\n",
              "         1.17030978e-03,  7.37405130e-03,  7.26816589e-04,\n",
              "         1.46708880e-03,  1.49352780e-03,  6.40990155e-04,\n",
              "         9.48693187e-04,  2.79748781e-04,  6.09702675e-04,\n",
              "         3.95625272e-04,  4.42322921e-04,  5.76671379e-03,\n",
              "         4.35386233e-03,  5.07541427e-03,  1.03079304e-02,\n",
              "         1.51062300e-02,  1.25133386e-02,  7.25439977e-03,\n",
              "         5.75308312e-03,  1.46937124e-02,  2.63270579e-02,\n",
              "         7.03562959e-03,  7.28955511e-03,  2.71635036e-03,\n",
              "         8.84658438e-04],\n",
              "       [ 2.47468521e-02,  1.61023976e-03,  2.95592953e-03,\n",
              "        -3.06959840e-01, -4.37269586e-01,  4.42915551e-01,\n",
              "        -1.26481987e-01, -5.18366031e-02, -6.21936776e-02,\n",
              "        -6.88011975e-02, -3.61257500e-02, -2.00663666e-02,\n",
              "         1.91957927e-02, -3.06504176e-01, -2.00417241e-01,\n",
              "        -4.18299097e-02, -1.39275015e-01, -4.66689225e-01,\n",
              "        -3.06426335e-01, -2.36268554e-01, -1.56850079e-01,\n",
              "         2.59052563e+00, -1.29185887e-01, -5.30379980e-02,\n",
              "        -4.11757878e-02, -2.71512154e-02, -2.98055419e-02,\n",
              "        -2.24571759e-02, -4.85972299e-02, -4.15786526e-02,\n",
              "        -3.87080786e-02, -2.60432231e-02, -1.24782628e-02,\n",
              "        -8.15195635e-03, -5.13649852e-02, -5.06274255e-03,\n",
              "        -1.02192121e-02, -1.04033766e-02, -4.46490653e-03,\n",
              "        -6.60825501e-03, -1.94862924e-03, -4.24696921e-03,\n",
              "        -2.75578314e-03, -3.08106214e-03, -4.01688510e-02,\n",
              "        -3.03274367e-02, -3.53535076e-02, -7.18013304e-02,\n",
              "        -1.05224557e-01, -8.71634093e-02, -5.05315357e-02,\n",
              "        -4.00739047e-02, -1.02351108e-01, -1.83384802e-01,\n",
              "        -4.90076614e-02, -5.07764152e-02, -1.89211181e-02,\n",
              "        -6.16221202e-03]])"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "km.labels_\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UrCVflQtp38E",
        "outputId": "39515d75-92c6-4e95-c8af-ce140a067199"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 0, 0, ..., 0, 0, 0], dtype=int32)"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "km.inertia_\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fUHt2nvOp3uI",
        "outputId": "1cf680b3-1d23-4c04-c5fd-9a78c46e0111"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "59906307.60214362"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "inertias = []\n",
        "lists_k = list(range(1, 11))\n",
        "\n",
        "for k in lists_k:\n",
        "  km1 = KMeans(n_clusters = k)\n",
        "  km1.fit(x_std)\n",
        "  cluster_labels = km1.predict(x_std)\n",
        "  inertias.append(km1.inertia_)"
      ],
      "metadata": {
        "id": "OarY4l9xqjBA"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sns.set_style('darkgrid')\n",
        "plt.figure(figsize=(4,4))\n",
        "sns.lineplot(x=lists_k, y=inertias, marker='o')\n",
        "plt.xlabel('No of Cluster')\n",
        "plt.ylabel('Inertia')\n",
        "#plt.show"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "OgJq_hiKqi92",
        "outputId": "e67abdd7-0904-4be1-9a95-c14ebc3e9406"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Inertia')"
            ]
          },
          "metadata": {},
          "execution_count": 23
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 400x400 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "visualizer1 = KElbowVisualizer(km1, k=(1,10),size=(1080, 500))\n",
        "\n",
        "visualizer1.fit(x_std)        # Fit the data to the visualizer\n",
        "visualizer1.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 478
        },
        "id": "1Se_hJFoqi69",
        "outputId": "38ec6023-366b-446d-9939-387250b94292"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: title={'center': 'Distortion Score Elbow for KMeans Clustering'}, xlabel='k', ylabel='distortion score'>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Another methods**"
      ],
      "metadata": {
        "id": "j5sPeTO3q52r"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Filter data for patients who have taken the \"Target Drug\" at least once\n",
        "target_drug_data = df1[df1['Incident'] == 'TARGET DRUG']"
      ],
      "metadata": {
        "id": "jjKV3zYwqi3z"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# # Create a feature matrix with patient prescriptions in each month\n",
        "# target_drug_data['Month'] = target_drug_data['Date'].dt.to_period('M')\n",
        "feature_matrix = df1.pivot_table(index='Patient-Uid', columns='Month', values='Incident', aggfunc='size', fill_value=0)\n"
      ],
      "metadata": {
        "id": "5MJdXqWQqi1R"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Apply K-means clustering to identify prescription patterns\n",
        "n_clusters = range(2, 10)  # Try different number of clusters\n",
        "cluster_scores = []\n",
        "\n",
        "for n in n_clusters:\n",
        "    kmeans = KMeans(n_clusters=n, random_state=42)\n",
        "    cluster_labels = kmeans.fit_predict(feature_matrix)\n",
        "    cluster_score = silhouette_score(feature_matrix, cluster_labels)\n",
        "    cluster_scores.append(cluster_score)\n",
        "\n",
        "print(cluster_scores)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kPYVywx1qiwP",
        "outputId": "ddae3418-75e5-444b-cf00-0600e0fc77a1"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0.4857878325749402, 0.3459329368523544, 0.23332531651953894, 0.17631373848462334, 0.15071569422563375, 0.1040675292203424, 0.09716463384615635, 0.08925711432903226]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Determine the optimal number of clusters using the elbow method\n",
        "plt.plot(n_clusters, cluster_scores, marker='o')\n",
        "plt.xlabel('Number of Clusters')\n",
        "plt.ylabel('Silhouette Score')\n",
        "plt.title('Silhouette Score vs. Number of Clusters')\n",
        "plt.grid(True)\n",
        "plt.xticks(n_clusters)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 566
        },
        "id": "YWT3mYNtqitc",
        "outputId": "97c0b1a1-a2a0-40fe-bbc8-ee19a0e29a5e"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x550 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pca = PCA(n_components=2)\n",
        "\n",
        "df3 = pd.DataFrame(pca.fit_transform(feature_matrix), columns=['PCA1', 'PCA2'])\n",
        "df3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "ofyyEEy9qihH",
        "outputId": "3d50c89c-362a-4ab1-ba9e-be6fc89fdaff"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            PCA1      PCA2\n",
              "0     -12.608195 -6.701797\n",
              "1      10.771202  2.337343\n",
              "2      -0.264476 -0.787946\n",
              "3       5.945629  7.260891\n",
              "4      -7.130944 -1.366883\n",
              "...          ...       ...\n",
              "11477  -4.603623 -0.848861\n",
              "11478 -18.002715  4.905965\n",
              "11479  -1.157607  1.466852\n",
              "11480 -16.193975 -6.016350\n",
              "11481  23.978818 -0.559068\n",
              "\n",
              "[11482 rows x 2 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5a01580b-fcf8-4d78-9f3f-df5ad76c30ae\" 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",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>PCA1</th>\n",
              "      <th>PCA2</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-12.608195</td>\n",
              "      <td>-6.701797</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.771202</td>\n",
              "      <td>2.337343</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-0.264476</td>\n",
              "      <td>-0.787946</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>5.945629</td>\n",
              "      <td>7.260891</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-7.130944</td>\n",
              "      <td>-1.366883</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11477</th>\n",
              "      <td>-4.603623</td>\n",
              "      <td>-0.848861</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11478</th>\n",
              "      <td>-18.002715</td>\n",
              "      <td>4.905965</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11479</th>\n",
              "      <td>-1.157607</td>\n",
              "      <td>1.466852</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11480</th>\n",
              "      <td>-16.193975</td>\n",
              "      <td>-6.016350</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11481</th>\n",
              "      <td>23.978818</td>\n",
              "      <td>-0.559068</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>11482 rows × 2 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-5a01580b-fcf8-4d78-9f3f-df5ad76c30ae')\"\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",
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              "  </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",
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              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\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-5a01580b-fcf8-4d78-9f3f-df5ad76c30ae 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-5a01580b-fcf8-4d78-9f3f-df5ad76c30ae');\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-53577109-95de-4db1-813b-ed85996111ce\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-53577109-95de-4db1-813b-ed85996111ce')\"\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-53577109-95de-4db1-813b-ed85996111ce 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": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df3.columns\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8jyzfo5VtcqE",
        "outputId": "89ccecfa-e682-49c3-d8ca-f4fdabb62d72"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['PCA1', 'PCA2'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a1 = km1.cluster_centers_\n"
      ],
      "metadata": {
        "id": "HxYEsPhutcmC"
      },
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "reduce_centers = pca.fit_transform(a1)\n",
        "reduce_centers"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2nGYvKU0tci0",
        "outputId": "74e73c67-1202-4a83-9682-f55b2f3e06db"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[-1.49979546, -1.56120302],\n",
              "       [-1.48939865, -1.53289663],\n",
              "       [-3.52429238,  9.86416644],\n",
              "       [-1.57228905, -1.73299479],\n",
              "       [-1.49838829, -1.61513489],\n",
              "       [-1.52723485, -1.61131253],\n",
              "       [-1.45701304, -1.4710383 ],\n",
              "       [14.10015077,  1.27114683],\n",
              "       [-1.53173904, -1.6107331 ]])"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df3['Cluster Labels'] = cluster_labels\n",
        "df3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "He3xVkyltcWV",
        "outputId": "ea5e4903-9ad2-4b60-bdac-bee775e96273"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            PCA1      PCA2  Cluster Labels\n",
              "0     -12.608195 -6.701797               3\n",
              "1      10.771202  2.337343               4\n",
              "2      -0.264476 -0.787946               6\n",
              "3       5.945629  7.260891               4\n",
              "4      -7.130944 -1.366883               6\n",
              "...          ...       ...             ...\n",
              "11477  -4.603623 -0.848861               6\n",
              "11478 -18.002715  4.905965               3\n",
              "11479  -1.157607  1.466852               6\n",
              "11480 -16.193975 -6.016350               3\n",
              "11481  23.978818 -0.559068               1\n",
              "\n",
              "[11482 rows x 3 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-d94973d3-5cb7-48be-821c-4c8cb6b92563\" class=\"colab-df-container\">\n",
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>PCA1</th>\n",
              "      <th>PCA2</th>\n",
              "      <th>Cluster Labels</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-12.608195</td>\n",
              "      <td>-6.701797</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>10.771202</td>\n",
              "      <td>2.337343</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-0.264476</td>\n",
              "      <td>-0.787946</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>5.945629</td>\n",
              "      <td>7.260891</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-7.130944</td>\n",
              "      <td>-1.366883</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>11477</th>\n",
              "      <td>-4.603623</td>\n",
              "      <td>-0.848861</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11478</th>\n",
              "      <td>-18.002715</td>\n",
              "      <td>4.905965</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11479</th>\n",
              "      <td>-1.157607</td>\n",
              "      <td>1.466852</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11480</th>\n",
              "      <td>-16.193975</td>\n",
              "      <td>-6.016350</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11481</th>\n",
              "      <td>23.978818</td>\n",
              "      <td>-0.559068</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>11482 rows × 3 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-d94973d3-5cb7-48be-821c-4c8cb6b92563')\"\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",
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              "  </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-d94973d3-5cb7-48be-821c-4c8cb6b92563 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-d94973d3-5cb7-48be-821c-4c8cb6b92563');\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-e296938e-bf8e-46e2-8499-df4372b14ea8\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e296938e-bf8e-46e2-8499-df4372b14ea8')\"\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-e296938e-bf8e-46e2-8499-df4372b14ea8 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": 33
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Visualize the Cluster Data**"
      ],
      "metadata": {
        "id": "-IkJcQw-tyq2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.set_style('darkgrid')\n",
        "plt.figure(figsize=(8,6))\n",
        "sns.scatterplot(data=df3, x='PCA1', y='PCA2', hue='Cluster Labels')\n",
        "#plt.scatter(reduce_centers[:,0],reduce_centers[:,1], marker='x',s=300)\n",
        "plt.xlabel('PCA1')\n",
        "plt.ylabel('PCA2')\n",
        "plt.title('Clustering using Scatter plot')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 606
        },
        "id": "RXWbleK-ttVM",
        "outputId": "afc037f6-1caf-4090-b1c0-356d020d7a31"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Instantiate the clustering model and visualizer\n",
        "model = KMeans()\n",
        "visualizer = KElbowVisualizer(model, k=(1,10),size=(1080, 500))\n",
        "\n",
        "visualizer.fit(df3.iloc[:,:3])        # Fit the data to the visualizer\n",
        "visualizer.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 476
        },
        "id": "ZEFx_KIMttRJ",
        "outputId": "cca6df92-094b-400b-d27a-fba94fe54bb3"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: title={'center': 'Distortion Score Elbow for KMeans Clustering'}, xlabel='k', ylabel='distortion score'>"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print('Silhoette Score: ', silhouette_score(df3, model.labels_, metric='euclidean'))\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qr9yG9uYttMf",
        "outputId": "584bfe7b-1447-42ec-ad24-1561a4f5dacc"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Silhoette Score:  0.3487265474567875\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "visual = SilhouetteVisualizer(model, size= (1080, 500))\n",
        "visual.fit(df3)\n",
        "visual.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 522
        },
        "id": "WGQv0NUbttJZ",
        "outputId": "f030feea-a801-4955-d8cb-b37f83719181"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: title={'center': 'Silhouette Plot of KMeans Clustering for 11482 Samples in 9 Centers'}, xlabel='silhouette coefficient values', ylabel='cluster label'>"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Create an empty list to store the individual series**"
      ],
      "metadata": {
        "id": "kS-N1POduYW9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.columns[2:]\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L2_V8Ls2ttF2",
        "outputId": "0b14ca21-2ed7-4865-b991-b965bdae616f"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Year', 'Month', 'Day'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df1.columns\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZXAWWtc0ttB4",
        "outputId": "4fd3220b-c78b-4b2a-dc02-72017a8de200"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Patient-Uid', 'Incident', 'Year', 'Month', 'Day', 'DRUG_TYPE_0',\n",
              "       'DRUG_TYPE_1', 'DRUG_TYPE_10', 'DRUG_TYPE_11', 'DRUG_TYPE_12',\n",
              "       'DRUG_TYPE_13', 'DRUG_TYPE_14', 'DRUG_TYPE_15', 'DRUG_TYPE_16',\n",
              "       'DRUG_TYPE_17', 'DRUG_TYPE_2', 'DRUG_TYPE_3', 'DRUG_TYPE_4',\n",
              "       'DRUG_TYPE_5', 'DRUG_TYPE_6', 'DRUG_TYPE_7', 'DRUG_TYPE_8',\n",
              "       'DRUG_TYPE_9', 'PRIMARY_DIAGNOSIS', 'SYMPTOM_TYPE_0', 'SYMPTOM_TYPE_1',\n",
              "       'SYMPTOM_TYPE_10', 'SYMPTOM_TYPE_11', 'SYMPTOM_TYPE_12',\n",
              "       'SYMPTOM_TYPE_13', 'SYMPTOM_TYPE_14', 'SYMPTOM_TYPE_15',\n",
              "       'SYMPTOM_TYPE_16', 'SYMPTOM_TYPE_17', 'SYMPTOM_TYPE_18',\n",
              "       'SYMPTOM_TYPE_19', 'SYMPTOM_TYPE_2', 'SYMPTOM_TYPE_20',\n",
              "       'SYMPTOM_TYPE_21', 'SYMPTOM_TYPE_22', 'SYMPTOM_TYPE_23',\n",
              "       'SYMPTOM_TYPE_24', 'SYMPTOM_TYPE_25', 'SYMPTOM_TYPE_26',\n",
              "       'SYMPTOM_TYPE_27', 'SYMPTOM_TYPE_28', 'SYMPTOM_TYPE_29',\n",
              "       'SYMPTOM_TYPE_3', 'SYMPTOM_TYPE_4', 'SYMPTOM_TYPE_5', 'SYMPTOM_TYPE_6',\n",
              "       'SYMPTOM_TYPE_7', 'SYMPTOM_TYPE_8', 'SYMPTOM_TYPE_9', 'TEST_TYPE_0',\n",
              "       'TEST_TYPE_1', 'TEST_TYPE_2', 'TEST_TYPE_3', 'TEST_TYPE_4',\n",
              "       'TEST_TYPE_5'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(df1.columns[2:])\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ww940rl3ts1c",
        "outputId": "60ec60f7-861e-4a28-9926-0cf989ce7667"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "58"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5cvHbpJGuudu",
        "outputId": "c8ea2220-b8b1-4d69-b1f5-9e68c1d27b87"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Patient-Uid', 'Incident', 'Year', 'Month', 'Day'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Patient-Uid  Incident  Year  Month Day**"
      ],
      "metadata": {
        "id": "WJ3CDMUvvwoA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Create a pivot table to count the number of incidents for each patient and month\n",
        "pivot_df = pd.pivot_table(df, index = 'Patient-Uid', columns='Month',aggfunc='size', fill_value=0)\n",
        "\n",
        "\n",
        "# Convert pivot table to numpy array\n",
        "X = pivot_df.to_numpy()\n",
        "# Normalize matrix by row\n",
        "norm = pivot_df.div(pivot_df.sum(axis=1), axis=0)\n",
        "\n",
        "\n",
        "# K-means clustering model generating\n",
        "kmeans = KMeans(n_clusters=4)\n",
        "cluster = kmeans.fit_predict(norm)"
      ],
      "metadata": {
        "id": "a8Y1C5mwv36E"
      },
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Create an empty list to store the individual series\n",
        "s = []\n",
        "\n",
        "# Iterate through the range of columns\n",
        "for i in range(0, len(pivot_df.columns) - 1):\n",
        "    # Calculate the average of two sequential columns\n",
        "    a = (pivot_df.iloc[:, i] + pivot_df.iloc[:, i+1]) / 2\n",
        "    s.append(a)\n",
        "\n",
        "# Combine the series into a single DataFrame\n",
        "combined_df = pd.concat(s, axis=1)"
      ],
      "metadata": {
        "id": "X0PmLg1uwQd_"
      },
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "combined_df\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "LiqqOVjYwYzq",
        "outputId": "33c5af3c-7f1e-4b95-db10-40ca7069e973"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                        0     1     2     3     4     5   \\\n",
              "Patient-Uid                                                                \n",
              "a0f9e8a9-1c7c-11ec-8d25-16262ee38c7f   1.0   0.5   1.0   3.0   4.0   2.5   \n",
              "a0f9e9f9-1c7c-11ec-b565-16262ee38c7f   9.5  11.0  11.0  11.0  14.5  14.5   \n",
              "a0f9ea43-1c7c-11ec-aa10-16262ee38c7f   2.5   6.0   9.0   5.0   5.5   8.5   \n",
              "a0f9ea7c-1c7c-11ec-af15-16262ee38c7f   8.5   7.0   8.5  10.0  16.0  15.0   \n",
              "a0f9eab1-1c7c-11ec-a732-16262ee38c7f   4.0   3.5   5.0   6.0   6.0   4.0   \n",
              "...                                    ...   ...   ...   ...   ...   ...   \n",
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            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Plot the violin plot\n",
        "plt.axhline(y=1, color='red', linestyle='-')\n",
        "plt.xlabel(\"months\")\n",
        "plt.ylabel(\"Average prescription\")\n",
        "sns.violinplot( data=combined_df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 552
        },
        "id": "G1CHSSzHwdam",
        "outputId": "ae3947b3-0fca-4220-d62d-f9101b54923f"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='months', ylabel='Average prescription'>"
            ]
          },
          "metadata": {},
          "execution_count": 46
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x550 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}