Subina_chapter_1_mimic.ipynb

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    "kernelspec": {
      "name": "python3",
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    "language_info": {
      "name": "python"
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  "cells": [
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uQrZUS5tP2CY",
        "outputId": "3cc89327-1355-4825-de01-e3ddffb03f75"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'handson-ml-mimic-iv'...\n",
            "remote: Enumerating objects: 83, done.\u001b[K\n",
            "remote: Counting objects: 100% (83/83), done.\u001b[K\n",
            "remote: Compressing objects: 100% (68/68), done.\u001b[K\n",
            "remote: Total 83 (delta 29), reused 40 (delta 13), pack-reused 0\u001b[K\n",
            "Receiving objects: 100% (83/83), 3.86 MiB | 13.88 MiB/s, done.\n",
            "Resolving deltas: 100% (29/29), done.\n"
          ]
        }
      ],
      "source": [
        "\n",
        "!git clone https://github.com/iupui-soic/handson-ml-mimic-iv.git"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "print(os.getcwd())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YB30emMDP5cC",
        "outputId": "93d7ce2f-c6dc-4ed0-d370-8c413eb261c9"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/handson-ml-mimic-iv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "os.chdir('/content/handson-ml-mimic-iv')"
      ],
      "metadata": {
        "id": "BhQE2lG9aQE4"
      },
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ILK3VmfmP5r-",
        "outputId": "ce63a0d6-b6c9-4a38-c250-0bb201cdc916"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import dask.dataframe as dd\n",
        "import pandas as pd"
      ],
      "metadata": {
        "id": "YTU9qz_CP54Q"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from mimic.mimic import MIMIC, MIMICManipulations"
      ],
      "metadata": {
        "id": "z5ZrrmUcRWNG"
      },
      "execution_count": 35,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mimic_instance = MIMIC('/content/drive/MyDrive/mimiv-iv')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LfaBwb_IRnuj",
        "outputId": "a1155f8e-04e5-47f4-db90-63589da3f42e"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "MIMIC dataset found at path : /content/drive/MyDrive/mimiv-iv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mimic_manipulation_instance = MIMICManipulations('/content/drive/MyDrive/mimiv-iv')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xY_nVhLuTJWt",
        "outputId": "ca9a5b5e-55b2-4c40-ef57-8be5a45885c2"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "MIMIC dataset found at path : /content/drive/MyDrive/mimiv-iv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!ls '/content/drive/My Drive/mimiv-iv'"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xiPwxSWmTKUx",
        "outputId": "e594b302-cb8c-42b5-d81e-da9c818473de"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "admissions.parquet\t d_icd_procedures.parquet  labevents.parquet\t   provider.parquet\n",
            "caregiver.parquet\t d_items.parquet\t   omr.parquet\t\t   services.parquet\n",
            "chartevents.parquet\t d_labitems.parquet\t   outputevents.parquet    transfers.parquet\n",
            "d_hcpcs.parquet\t\t drgcodes.parquet\t   patients.parquet\n",
            "diagnoses_icd.parquet\t emar.parquet\t\t   poe_detail.parquet\n",
            "d_icd_diagnoses.parquet  icustays.parquet\t   procedures_icd.parquet\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_admissions = pd.read_parquet('/content/drive/My Drive/mimiv-iv/admissions.parquet')"
      ],
      "metadata": {
        "id": "AB5b8uu8TKgu"
      },
      "execution_count": 39,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_admissions.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 400
        },
        "id": "Yv2lL4f0duYb",
        "outputId": "a1cd5d3c-4123-47b9-f112-e87ab6452497"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   subject_id   hadm_id           admittime           dischtime deathtime  \\\n",
              "0    10000032  22595853 2180-05-06 22:23:00 2180-05-07 17:15:00       NaT   \n",
              "1    10000032  22841357 2180-06-26 18:27:00 2180-06-27 18:49:00       NaT   \n",
              "2    10000032  25742920 2180-08-05 23:44:00 2180-08-07 17:50:00       NaT   \n",
              "3    10000032  29079034 2180-07-23 12:35:00 2180-07-25 17:55:00       NaT   \n",
              "4    10000068  25022803 2160-03-03 23:16:00 2160-03-04 06:26:00       NaT   \n",
              "\n",
              "   admission_type admit_provider_id      admission_location  \\\n",
              "0          URGENT            P874LG  TRANSFER FROM HOSPITAL   \n",
              "1        EW EMER.            P09Q6Y          EMERGENCY ROOM   \n",
              "2        EW EMER.            P60CC5          EMERGENCY ROOM   \n",
              "3        EW EMER.            P30KEH          EMERGENCY ROOM   \n",
              "4  EU OBSERVATION            P51VDL          EMERGENCY ROOM   \n",
              "\n",
              "  discharge_location insurance language marital_status   race  \\\n",
              "0               HOME     Other  ENGLISH        WIDOWED  WHITE   \n",
              "1               HOME  Medicaid  ENGLISH        WIDOWED  WHITE   \n",
              "2            HOSPICE  Medicaid  ENGLISH        WIDOWED  WHITE   \n",
              "3               HOME  Medicaid  ENGLISH        WIDOWED  WHITE   \n",
              "4               None     Other  ENGLISH         SINGLE  WHITE   \n",
              "\n",
              "            edregtime           edouttime  hospital_expire_flag  \n",
              "0 2180-05-06 19:17:00 2180-05-06 23:30:00                     0  \n",
              "1 2180-06-26 15:54:00 2180-06-26 21:31:00                     0  \n",
              "2 2180-08-05 20:58:00 2180-08-06 01:44:00                     0  \n",
              "3 2180-07-23 05:54:00 2180-07-23 14:00:00                     0  \n",
              "4 2160-03-03 21:55:00 2160-03-04 06:26:00                     0  "
            ],
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              "      <th>subject_id</th>\n",
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              "      <th>language</th>\n",
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              "      <th>0</th>\n",
              "      <td>10000032</td>\n",
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              "      <td>2180-05-06 22:23:00</td>\n",
              "      <td>2180-05-07 17:15:00</td>\n",
              "      <td>NaT</td>\n",
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              "      <td>2180-05-06 19:17:00</td>\n",
              "      <td>2180-05-06 23:30:00</td>\n",
              "      <td>0</td>\n",
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              "      <th>1</th>\n",
              "      <td>10000032</td>\n",
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              "      <td>2180-06-26 18:27:00</td>\n",
              "      <td>2180-06-27 18:49:00</td>\n",
              "      <td>NaT</td>\n",
              "      <td>EW EMER.</td>\n",
              "      <td>P09Q6Y</td>\n",
              "      <td>EMERGENCY ROOM</td>\n",
              "      <td>HOME</td>\n",
              "      <td>Medicaid</td>\n",
              "      <td>ENGLISH</td>\n",
              "      <td>WIDOWED</td>\n",
              "      <td>WHITE</td>\n",
              "      <td>2180-06-26 15:54:00</td>\n",
              "      <td>2180-06-26 21:31:00</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>10000032</td>\n",
              "      <td>25742920</td>\n",
              "      <td>2180-08-05 23:44:00</td>\n",
              "      <td>2180-08-07 17:50:00</td>\n",
              "      <td>NaT</td>\n",
              "      <td>EW EMER.</td>\n",
              "      <td>P60CC5</td>\n",
              "      <td>EMERGENCY ROOM</td>\n",
              "      <td>HOSPICE</td>\n",
              "      <td>Medicaid</td>\n",
              "      <td>ENGLISH</td>\n",
              "      <td>WIDOWED</td>\n",
              "      <td>WHITE</td>\n",
              "      <td>2180-08-05 20:58:00</td>\n",
              "      <td>2180-08-06 01:44:00</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>10000032</td>\n",
              "      <td>29079034</td>\n",
              "      <td>2180-07-23 12:35:00</td>\n",
              "      <td>2180-07-25 17:55:00</td>\n",
              "      <td>NaT</td>\n",
              "      <td>EW EMER.</td>\n",
              "      <td>P30KEH</td>\n",
              "      <td>EMERGENCY ROOM</td>\n",
              "      <td>HOME</td>\n",
              "      <td>Medicaid</td>\n",
              "      <td>ENGLISH</td>\n",
              "      <td>WIDOWED</td>\n",
              "      <td>WHITE</td>\n",
              "      <td>2180-07-23 05:54:00</td>\n",
              "      <td>2180-07-23 14:00:00</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>10000068</td>\n",
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              "      <td>2160-03-03 23:16:00</td>\n",
              "      <td>2160-03-04 06:26:00</td>\n",
              "      <td>NaT</td>\n",
              "      <td>EU OBSERVATION</td>\n",
              "      <td>P51VDL</td>\n",
              "      <td>EMERGENCY ROOM</td>\n",
              "      <td>None</td>\n",
              "      <td>Other</td>\n",
              "      <td>ENGLISH</td>\n",
              "      <td>SINGLE</td>\n",
              "      <td>WHITE</td>\n",
              "      <td>2160-03-03 21:55:00</td>\n",
              "      <td>2160-03-04 06:26:00</td>\n",
              "      <td>0</td>\n",
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              "      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-d00fc9cb-75a7-4bcc-9546-8c2029b1aa8e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_admissions"
            }
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_admissions.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LmRc4i5gduj5",
        "outputId": "d63c9f57-bd10-4e27-cfad-958e002fe1ee"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(431231, 16)"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_admissions.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "quJB8TewlJll",
        "outputId": "0ce34fae-5a62-4332-fcfa-c2d4385b1196"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 431231 entries, 0 to 431230\n",
            "Data columns (total 16 columns):\n",
            " #   Column                Non-Null Count   Dtype         \n",
            "---  ------                --------------   -----         \n",
            " 0   subject_id            431231 non-null  int32         \n",
            " 1   hadm_id               431231 non-null  int32         \n",
            " 2   admittime             431231 non-null  datetime64[us]\n",
            " 3   dischtime             431231 non-null  datetime64[us]\n",
            " 4   deathtime             8598 non-null    datetime64[us]\n",
            " 5   admission_type        431231 non-null  object        \n",
            " 6   admit_provider_id     431227 non-null  object        \n",
            " 7   admission_location    431231 non-null  object        \n",
            " 8   discharge_location    312076 non-null  object        \n",
            " 9   insurance             431231 non-null  object        \n",
            " 10  language              431231 non-null  object        \n",
            " 11  marital_status        421998 non-null  object        \n",
            " 12  race                  431231 non-null  object        \n",
            " 13  edregtime             299282 non-null  datetime64[us]\n",
            " 14  edouttime             299282 non-null  datetime64[us]\n",
            " 15  hospital_expire_flag  431231 non-null  int16         \n",
            "dtypes: datetime64[us](5), int16(1), int32(2), object(8)\n",
            "memory usage: 46.9+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_admissions.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "jLyIwrvtlJ5V",
        "outputId": "a67f4649-9e79-4dcc-b386-0bcbfdc2cfa0"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         subject_id       hadm_id                   admittime  \\\n",
              "count  4.312310e+05  4.312310e+05                      431231   \n",
              "mean   1.500766e+07  2.500314e+07  2155-02-27 21:07:41.694079   \n",
              "min    1.000003e+07  2.000002e+07         2105-10-04 17:26:00   \n",
              "25%    1.251557e+07  2.250155e+07         2135-02-22 13:35:00   \n",
              "50%    1.501288e+07  2.500669e+07         2155-01-20 15:22:00   \n",
              "75%    1.749622e+07  2.750470e+07         2175-04-05 03:02:00   \n",
              "max    1.999999e+07  2.999993e+07         2212-04-06 12:13:00   \n",
              "std    2.877498e+06  2.888180e+06                         NaN   \n",
              "\n",
              "                        dischtime                   deathtime  \\\n",
              "count                      431231                        8598   \n",
              "mean   2155-03-04 08:43:37.370134  2153-05-28 01:26:50.181438   \n",
              "min           2105-10-12 11:11:00         2110-01-25 09:40:00   \n",
              "25%           2135-02-27 14:04:00         2133-06-22 01:37:00   \n",
              "50%           2155-01-24 16:54:00         2153-02-22 19:09:00   \n",
              "75%           2175-04-08 22:41:00         2173-06-30 06:52:30   \n",
              "max           2212-04-12 14:06:00         2211-01-17 12:34:00   \n",
              "std                           NaN                         NaN   \n",
              "\n",
              "                        edregtime                   edouttime  \\\n",
              "count                      299282                      299282   \n",
              "mean   2155-07-30 01:42:37.077940  2155-07-30 11:54:38.147501   \n",
              "min           2106-02-06 15:47:00         2106-02-07 09:31:00   \n",
              "25%           2135-07-26 21:51:45         2135-07-27 20:26:30   \n",
              "50%           2155-07-03 18:46:30         2155-07-04 04:20:00   \n",
              "75%           2175-09-11 14:26:45         2175-09-11 20:59:30   \n",
              "max           2212-04-05 23:23:00         2212-04-06 14:20:00   \n",
              "std                           NaN                         NaN   \n",
              "\n",
              "       hospital_expire_flag  \n",
              "count         431231.000000  \n",
              "mean               0.019964  \n",
              "min                0.000000  \n",
              "25%                0.000000  \n",
              "50%                0.000000  \n",
              "75%                0.000000  \n",
              "max                1.000000  \n",
              "std                0.139876  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a09755a9-4cf6-4004-b9c6-36adc47985e1\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>subject_id</th>\n",
              "      <th>hadm_id</th>\n",
              "      <th>admittime</th>\n",
              "      <th>dischtime</th>\n",
              "      <th>deathtime</th>\n",
              "      <th>edregtime</th>\n",
              "      <th>edouttime</th>\n",
              "      <th>hospital_expire_flag</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>4.312310e+05</td>\n",
              "      <td>4.312310e+05</td>\n",
              "      <td>431231</td>\n",
              "      <td>431231</td>\n",
              "      <td>8598</td>\n",
              "      <td>299282</td>\n",
              "      <td>299282</td>\n",
              "      <td>431231.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>1.500766e+07</td>\n",
              "      <td>2.500314e+07</td>\n",
              "      <td>2155-02-27 21:07:41.694079</td>\n",
              "      <td>2155-03-04 08:43:37.370134</td>\n",
              "      <td>2153-05-28 01:26:50.181438</td>\n",
              "      <td>2155-07-30 01:42:37.077940</td>\n",
              "      <td>2155-07-30 11:54:38.147501</td>\n",
              "      <td>0.019964</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000003e+07</td>\n",
              "      <td>2.000002e+07</td>\n",
              "      <td>2105-10-04 17:26:00</td>\n",
              "      <td>2105-10-12 11:11:00</td>\n",
              "      <td>2110-01-25 09:40:00</td>\n",
              "      <td>2106-02-06 15:47:00</td>\n",
              "      <td>2106-02-07 09:31:00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>1.251557e+07</td>\n",
              "      <td>2.250155e+07</td>\n",
              "      <td>2135-02-22 13:35:00</td>\n",
              "      <td>2135-02-27 14:04:00</td>\n",
              "      <td>2133-06-22 01:37:00</td>\n",
              "      <td>2135-07-26 21:51:45</td>\n",
              "      <td>2135-07-27 20:26:30</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>1.501288e+07</td>\n",
              "      <td>2.500669e+07</td>\n",
              "      <td>2155-01-20 15:22:00</td>\n",
              "      <td>2155-01-24 16:54:00</td>\n",
              "      <td>2153-02-22 19:09:00</td>\n",
              "      <td>2155-07-03 18:46:30</td>\n",
              "      <td>2155-07-04 04:20:00</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>1.749622e+07</td>\n",
              "      <td>2.750470e+07</td>\n",
              "      <td>2175-04-05 03:02:00</td>\n",
              "      <td>2175-04-08 22:41:00</td>\n",
              "      <td>2173-06-30 06:52:30</td>\n",
              "      <td>2175-09-11 14:26:45</td>\n",
              "      <td>2175-09-11 20:59:30</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.999999e+07</td>\n",
              "      <td>2.999993e+07</td>\n",
              "      <td>2212-04-06 12:13:00</td>\n",
              "      <td>2212-04-12 14:06:00</td>\n",
              "      <td>2211-01-17 12:34:00</td>\n",
              "      <td>2212-04-05 23:23:00</td>\n",
              "      <td>2212-04-06 14:20:00</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>2.877498e+06</td>\n",
              "      <td>2.888180e+06</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.139876</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a09755a9-4cf6-4004-b9c6-36adc47985e1')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\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-a09755a9-4cf6-4004-b9c6-36adc47985e1 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-a09755a9-4cf6-4004-b9c6-36adc47985e1');\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-a98d2b78-2d1a-41c0-b293-d228d9fd72c3\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-a98d2b78-2d1a-41c0-b293-d228d9fd72c3')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
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              "    </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-a98d2b78-2d1a-41c0-b293-d228d9fd72c3 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df_admissions\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"subject_id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 6894824.276515122,\n        \"min\": 431231.0,\n        \"max\": 19999987.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          15007664.969607936,\n          17496223.5,\n          431231.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"hadm_id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 11230533.526033193,\n        \"min\": 431231.0,\n        \"max\": 29999928.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          25003138.264725868,\n          27504698.0,\n          431231.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"admittime\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"1970-01-01 00:00:00.000431231\",\n        \"max\": \"2212-04-06 12:13:00\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"431231\",\n          \"2155-02-27 21:07:41.694079\",\n          \"2175-04-05 03:02:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"dischtime\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"1970-01-01 00:00:00.000431231\",\n        \"max\": \"2212-04-12 14:06:00\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"431231\",\n          \"2155-03-04 08:43:37.370134\",\n          \"2175-04-08 22:41:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"deathtime\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"1970-01-01 00:00:00.000008598\",\n        \"max\": \"2211-01-17 12:34:00\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"8598\",\n          \"2153-05-28 01:26:50.181438\",\n          \"2173-06-30 06:52:30\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"edregtime\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"1970-01-01 00:00:00.000299282\",\n        \"max\": \"2212-04-05 23:23:00\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"299282\",\n          \"2155-07-30 01:42:37.077940\",\n          \"2175-09-11 14:26:45\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"edouttime\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"1970-01-01 00:00:00.000299282\",\n        \"max\": \"2212-04-06 14:20:00\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"299282\",\n          \"2155-07-30 11:54:38.147501\",\n          \"2175-09-11 20:59:30\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"hospital_expire_flag\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 152463.1235985651,\n        \"min\": 0.0,\n        \"max\": 431231.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.019963778114282137,\n          0.13987591303876895,\n          0.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_admissions.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QfFms7P3lKD2",
        "outputId": "c416bbce-0424-4977-f0a1-82b44fd4a568"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "subject_id                   0\n",
              "hadm_id                      0\n",
              "admittime                    0\n",
              "dischtime                    0\n",
              "deathtime               422633\n",
              "admission_type               0\n",
              "admit_provider_id            4\n",
              "admission_location           0\n",
              "discharge_location      119155\n",
              "insurance                    0\n",
              "language                     0\n",
              "marital_status            9233\n",
              "race                         0\n",
              "edregtime               131949\n",
              "edouttime               131949\n",
              "hospital_expire_flag         0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_admissions.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "49SEwKdTlZ_f",
        "outputId": "e386583c-11fb-4b31-9c82-f681d98a03d1"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['subject_id', 'hadm_id', 'admittime', 'dischtime', 'deathtime',\n",
              "       'admission_type', 'admit_provider_id', 'admission_location',\n",
              "       'discharge_location', 'insurance', 'language', 'marital_status', 'race',\n",
              "       'edregtime', 'edouttime', 'hospital_expire_flag'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_admissions.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RBtt3sdtlaH8",
        "outputId": "e0a9b7fd-8008-4775-8051-52e887904a13"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "subject_id                       int32\n",
              "hadm_id                          int32\n",
              "admittime               datetime64[us]\n",
              "dischtime               datetime64[us]\n",
              "deathtime               datetime64[us]\n",
              "admission_type                  object\n",
              "admit_provider_id               object\n",
              "admission_location              object\n",
              "discharge_location              object\n",
              "insurance                       object\n",
              "language                        object\n",
              "marital_status                  object\n",
              "race                            object\n",
              "edregtime               datetime64[us]\n",
              "edouttime               datetime64[us]\n",
              "hospital_expire_flag             int16\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_admissions[['subject_id', 'hadm_id', 'admittime', 'dischtime', 'admission_type', 'admission_location', 'discharge_location', 'insurance', 'language',\n",
        "                    'marital_status', 'hospital_expire_flag']].head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 400
        },
        "id": "jTIebgBzlhNe",
        "outputId": "debbd37e-46cc-4161-adbb-f69e020d852f"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   subject_id   hadm_id           admittime           dischtime  \\\n",
              "0    10000032  22595853 2180-05-06 22:23:00 2180-05-07 17:15:00   \n",
              "1    10000032  22841357 2180-06-26 18:27:00 2180-06-27 18:49:00   \n",
              "2    10000032  25742920 2180-08-05 23:44:00 2180-08-07 17:50:00   \n",
              "3    10000032  29079034 2180-07-23 12:35:00 2180-07-25 17:55:00   \n",
              "4    10000068  25022803 2160-03-03 23:16:00 2160-03-04 06:26:00   \n",
              "\n",
              "   admission_type      admission_location discharge_location insurance  \\\n",
              "0          URGENT  TRANSFER FROM HOSPITAL               HOME     Other   \n",
              "1        EW EMER.          EMERGENCY ROOM               HOME  Medicaid   \n",
              "2        EW EMER.          EMERGENCY ROOM            HOSPICE  Medicaid   \n",
              "3        EW EMER.          EMERGENCY ROOM               HOME  Medicaid   \n",
              "4  EU OBSERVATION          EMERGENCY ROOM               None     Other   \n",
              "\n",
              "  language marital_status  hospital_expire_flag  \n",
              "0  ENGLISH        WIDOWED                     0  \n",
              "1  ENGLISH        WIDOWED                     0  \n",
              "2  ENGLISH        WIDOWED                     0  \n",
              "3  ENGLISH        WIDOWED                     0  \n",
              "4  ENGLISH         SINGLE                     0  "
            ],
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"                    'marital_status', 'hospital_expire_flag']]\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"subject_id\",\n      \"properties\": {\n        \"dtype\": \"int32\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          10000068,\n          10000032\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"hadm_id\",\n      \"properties\": {\n        \"dtype\": \"int32\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          22841357,\n          25022803\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"admittime\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2160-03-03 23:16:00\",\n        \"max\": \"2180-08-05 23:44:00\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"2180-06-26 18:27:00\",\n          \"2160-03-03 23:16:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"dischtime\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2160-03-04 06:26:00\",\n        \"max\": \"2180-08-07 17:50:00\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"2180-06-27 18:49:00\",\n          \"2160-03-04 06:26:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"admission_type\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"URGENT\",\n          \"EW EMER.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"admission_location\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"EMERGENCY ROOM\",\n          \"TRANSFER FROM HOSPITAL\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"discharge_location\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"HOSPICE\",\n          \"HOME\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"insurance\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Medicaid\",\n          \"Other\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"language\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"ENGLISH\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"marital_status\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"SINGLE\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"hospital_expire_flag\",\n      \"properties\": {\n        \"dtype\": \"int16\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_patients = pd.read_parquet('/content/drive/MyDrive/mimiv-iv/patients.parquet')"
      ],
      "metadata": {
        "id": "k2sP3SJwlhXe"
      },
      "execution_count": 50,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_patients = df_patients.drop(['dod'], axis=1)"
      ],
      "metadata": {
        "id": "AXIhyTELmo5l"
      },
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_patients.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tF27BoRHmpK-",
        "outputId": "4a156a64-943f-4dec-c953-9b5550ff989f"
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "subject_id           0\n",
              "gender               0\n",
              "anchor_age           0\n",
              "anchor_year          0\n",
              "anchor_year_group    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_transfer = pd.read_parquet('/content/drive/MyDrive/mimiv-iv/transfers.parquet')"
      ],
      "metadata": {
        "id": "08VaA7SlmpWo"
      },
      "execution_count": 53,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_transfer.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 380
        },
        "id": "fCuJXZcZlhiO",
        "outputId": "c41cc780-b444-4eb3-f69b-eda84b3797d2"
      },
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   subject_id     hadm_id  transfer_id  eventtype              careunit  \\\n",
              "0    10000032  22595853.0     33258284         ED  Emergency Department   \n",
              "1    10000032  22595853.0     35223874      admit            Transplant   \n",
              "2    10000032  22595853.0     36904543  discharge                  None   \n",
              "3    10000032  22841357.0     34100253  discharge                  None   \n",
              "4    10000032  22841357.0     34703856      admit            Transplant   \n",
              "\n",
              "               intime             outtime  \n",
              "0 2180-05-06 19:17:00 2180-05-06 23:30:00  \n",
              "1 2180-05-06 23:30:00 2180-05-07 17:21:27  \n",
              "2 2180-05-07 17:21:27                 NaT  \n",
              "3 2180-06-27 18:49:12                 NaT  \n",
              "4 2180-06-26 21:31:00 2180-06-27 18:49:12  "
            ],
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
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              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "\n",
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              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_transfer"
            }
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_transfer.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PlVaMuzbm7G2",
        "outputId": "974b94d8-ebc0-4147-e037-d7592585b16b"
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "subject_id          0\n",
              "hadm_id        330023\n",
              "transfer_id         0\n",
              "eventtype           0\n",
              "careunit       431231\n",
              "intime              0\n",
              "outtime        431228\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_transfer.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NsnrwUVsm7Md",
        "outputId": "88986a6c-381b-45ff-9a5d-4e24b1a619db"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1890972, 7)"
            ]
          },
          "metadata": {},
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_hcpcs = pd.read_parquet('/content/drive/MyDrive/mimiv-iv/d_hcpcs.parquet')"
      ],
      "metadata": {
        "id": "Cpjnx-3hm7Rh"
      },
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_hcpcs.head()"
      ],
      "metadata": {
        "colab": {
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            "application/vnd.google.colaboratory.intrinsic+json": {
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              "variable_name": "df_hcpcs",
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            }
          },
          "metadata": {},
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_d_icd_procedures = pd.read_parquet('/content/drive/MyDrive/mimiv-iv/d_icd_procedures.parquet')"
      ],
      "metadata": {
        "id": "u9oYiSngm7XQ"
      },
      "execution_count": 59,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_d_icd_procedures.head()"
      ],
      "metadata": {
        "colab": {
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          "height": 206
        },
        "id": "uleuKw6NnQ68",
        "outputId": "75739324-5ca3-48c1-ddc9-f73aa1efbe58"
      },
      "execution_count": 60,
      "outputs": [
        {
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            "text/plain": [
              "  icd_code  icd_version                                         long_title\n",
              "0     0001            9  Therapeutic ultrasound of vessels of head and ...\n",
              "1     0002            9                    Therapeutic ultrasound of heart\n",
              "2     0003            9  Therapeutic ultrasound of peripheral vascular ...\n",
              "3     0009            9                       Other therapeutic ultrasound\n",
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              "      border-right-color: var(--fill-color);\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "        console.error('Error during call to suggestCharts:', error);\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
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              "    (() => {\n",
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              "        document.querySelector('#df-959b20c0-844d-4353-8b6d-e73528d31875 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_d_icd_procedures",
              "summary": "{\n  \"name\": \"df_d_icd_procedures\",\n  \"rows\": 85257,\n  \"fields\": [\n    {\n      \"column\": \"icd_code\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 85251,\n        \"samples\": [\n          \"8413\",\n          \"3785\",\n          \"0QWJ37Z\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"icd_version\",\n      \"properties\": {\n        \"dtype\": \"int16\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          10,\n          9\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"long_title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 85256,\n        \"samples\": [\n          \"Drainage of Right Common Iliac Artery, Percutaneous Approach\",\n          \"Computerized Tomography (CT Scan) of Left Foot using High Osmolar Contrast\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_d_icd_diagnoses = pd.read_parquet('/content/drive/MyDrive/mimiv-iv/d_icd_diagnoses.parquet')"
      ],
      "metadata": {
        "id": "fi0YJKIgnU5G"
      },
      "execution_count": 61,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_d_icd_diagnoses.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "rtpYihQ1nU7s",
        "outputId": "83985d55-fe3f-446e-c60f-957d00491423"
      },
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  icd_code  icd_version                             long_title\n",
              "0     0010            9         Cholera due to vibrio cholerae\n",
              "1     0011            9  Cholera due to vibrio cholerae el tor\n",
              "2     0019            9                   Cholera, unspecified\n",
              "3     0020            9                          Typhoid fever\n",
              "4     0021            9                    Paratyphoid fever A"
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              "\n",
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              "      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",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "\n",
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              "type": "dataframe",
              "variable_name": "df_d_icd_diagnoses"
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          },
          "metadata": {},
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_drgcodes = pd.read_parquet('/content/drive/MyDrive/mimiv-iv/drgcodes.parquet')"
      ],
      "metadata": {
        "id": "_01ekNOXn0us"
      },
      "execution_count": 64,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_drgcodes.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 469
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        "id": "nUoDc5mMn05z",
        "outputId": "59c582e9-af10-4311-e787-f8ac5954bc6d"
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   subject_id   hadm_id drg_type drg_code  \\\n",
              "0    10000032  22595853      APR      283   \n",
              "1    10000032  22595853     HCFA      442   \n",
              "2    10000032  22841357      APR      279   \n",
              "3    10000032  22841357     HCFA      442   \n",
              "4    10000032  25742920      APR      283   \n",
              "\n",
              "                                         description  drg_severity  \\\n",
              "0                       OTHER DISORDERS OF THE LIVER           2.0   \n",
              "1  DISORDERS OF LIVER EXCEPT MALIG,CIRR,ALC HEPA ...           NaN   \n",
              "2   HEPATIC COMA & OTHER MAJOR ACUTE LIVER DISORDERS           3.0   \n",
              "3  DISORDERS OF LIVER EXCEPT MALIG,CIRR,ALC HEPA ...           NaN   \n",
              "4                       OTHER DISORDERS OF THE LIVER           3.0   \n",
              "\n",
              "   drg_mortality  \n",
              "0            2.0  \n",
              "1            NaN  \n",
              "2            2.0  \n",
              "3            NaN  \n",
              "4            2.0  "
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>10000032</td>\n",
              "      <td>22841357</td>\n",
              "      <td>APR</td>\n",
              "      <td>279</td>\n",
              "      <td>HEPATIC COMA &amp; OTHER MAJOR ACUTE LIVER DISORDERS</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>10000032</td>\n",
              "      <td>22841357</td>\n",
              "      <td>HCFA</td>\n",
              "      <td>442</td>\n",
              "      <td>DISORDERS OF LIVER EXCEPT MALIG,CIRR,ALC HEPA ...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>10000032</td>\n",
              "      <td>25742920</td>\n",
              "      <td>APR</td>\n",
              "      <td>283</td>\n",
              "      <td>OTHER DISORDERS OF THE LIVER</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
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              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-eb24dbce-22fd-4899-b12e-737502becc72 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-eb24dbce-22fd-4899-b12e-737502becc72');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
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              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "\n",
              "\n",
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              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    </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",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
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              "      --disabled-bg-color: #3B4455;\n",
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              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
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              "    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",
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              "      border-color: transparent;\n",
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              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "      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-258146a6-16dd-4a1b-a71d-3d2ed1c40ec9 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_drgcodes"
            }
          },
          "metadata": {},
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_emar = pd.read_parquet('/content/drive/MyDrive/mimiv-iv/emar.parquet')"
      ],
      "metadata": {
        "id": "l8j52hOvn0_i"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"EMAR Data:\")\n",
        "print(df_emar.head())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "09UUnUhGn1DC",
        "outputId": "1328b49e-e862-45f7-e846-0fa9d63577a6"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "EMAR Data:\n",
            "   subject_id     hadm_id      emar_id  emar_seq       poe_id  pharmacy_id  \\\n",
            "0    10000032  22595853.0  10000032-10        10  10000032-36   48770010.0   \n",
            "1    10000032  22595853.0  10000032-11        11  10000032-22   14779570.0   \n",
            "2    10000032  22595853.0  10000032-12        12  10000032-37   93463122.0   \n",
            "3    10000032  22595853.0  10000032-13        13  10000032-28   42497745.0   \n",
            "4    10000032  22595853.0  10000032-14        14  10000032-29   69131933.0   \n",
            "\n",
            "  enter_provider_id           charttime                         medication  \\\n",
            "0              None 2180-05-07 00:44:00                 Potassium Chloride   \n",
            "1              None 2180-05-07 00:44:00        Sodium Chloride 0.9%  Flush   \n",
            "2              None 2180-05-07 06:10:00            Ipratropium Bromide Neb   \n",
            "3              None 2180-05-07 05:00:00                  Albuterol Inhaler   \n",
            "4              None 2180-05-07 07:51:00  Emtricitabine-Tenofovir (Truvada)   \n",
            "\n",
            "      event_txt        scheduletime           storetime  \n",
            "0  Administered 2180-05-07 00:44:00 2180-05-07 00:44:00  \n",
            "1       Flushed 2180-05-07 00:44:00 2180-05-07 00:44:00  \n",
            "2  Administered 2180-05-07 06:00:00 2180-05-07 06:10:00  \n",
            "3  Administered 2180-05-07 06:29:00 2180-05-07 06:29:00  \n",
            "4  Administered 2180-05-07 08:00:00 2180-05-07 07:56:00  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "# Reading various hospital datasets from Parquet files using Dask\n",
        "\n",
        "\n",
        "\n",
        "df_outputevents = pd.read_parquet('/content/drive/MyDrive/mimiv-iv/outputevents.parquet')"
      ],
      "metadata": {
        "id": "-8Xw2piCooDt"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_outputevents.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 400
        },
        "id": "pUhwJl-SooI1",
        "outputId": "946a5865-3fd6-4e06-cf93-b276c654d711"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   subject_id   hadm_id   stay_id  caregiver_id           charttime  \\\n",
              "0    10000032  29079034  39553978         88981 2180-07-23 15:00:00   \n",
              "1    10000980  26913865  39765666         36518 2189-06-27 09:08:00   \n",
              "2    10000980  26913865  39765666         36518 2189-06-27 09:08:00   \n",
              "3    10000980  26913865  39765666         36518 2189-06-27 11:00:00   \n",
              "4    10000980  26913865  39765666         36518 2189-06-27 13:00:00   \n",
              "\n",
              "            storetime  itemid  value valueuom  \n",
              "0 2180-07-23 16:00:00  226560  175.0       ml  \n",
              "1 2189-06-27 09:08:00  226559  450.0       ml  \n",
              "2 2189-06-27 09:08:00  226633  400.0       ml  \n",
              "3 2189-06-27 10:51:00  226559  600.0       ml  \n",
              "4 2189-06-27 12:55:00  226559  800.0       ml  "
            ],
            "text/html": [
              "\n",
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              "<style scoped>\n",
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              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
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              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-f05564b4-1c75-4181-a06c-c1b5355df1e2');\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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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "\n",
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              "    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",
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              "        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",
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              "        document.querySelector('#df-eb7bcde3-c379-4b1d-94bb-dfe679cc7bba button');\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "\n",
              "    </div>\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_outputevents"
            }
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Data Exploration\n"
      ],
      "metadata": {
        "id": "oW3a0z82qSjk"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import sys\n",
        "sys.path.append('/content/handson-ml-mimic-iv')"
      ],
      "metadata": {
        "id": "y0yBT-paooLj"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "from mimic.mimic import MIMIC, MIMICManipulations\n",
        "\n",
        "# Initialize MIMIC and MIMICManipulations instances\n",
        "mimic_instance = MIMIC('/content/drive/MyDrive/mimiv-iv')\n",
        "mimic_manipulation_instance = MIMICManipulations('/content/drive/MyDrive/mimiv-iv')\n",
        "\n",
        "# Reading and filtering data from Parquet files\n",
        "df_admission = mimic_manipulation_instance.filter_core_admission(pd.read_parquet('/content/drive/MyDrive/mimiv-iv/admissions.parquet'))\n",
        "print(len(df_admission))\n",
        "print(df_admission.head())\n",
        "\n",
        "df_patient = mimic_manipulation_instance.filter_core_patients(pd.read_parquet('/content/drive/MyDrive/mimiv-iv/patients.parquet'))\n",
        "print(len(df_patient))\n",
        "print(df_patient.head())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sZZe74MDooO1",
        "outputId": "fc879221-ff27-4e30-94ff-dca6a1834183"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "MIMIC dataset found at path : /content/drive/MyDrive/mimiv-iv\n",
            "MIMIC dataset found at path : /content/drive/MyDrive/mimiv-iv\n",
            "180677\n",
            "            admission_type admit_provider_id      admission_location  \\\n",
            "subject_id                                                             \n",
            "10000032            URGENT            P874LG  TRANSFER FROM HOSPITAL   \n",
            "10000068    EU OBSERVATION            P51VDL          EMERGENCY ROOM   \n",
            "10000084          EW EMER.            P6957U   WALK-IN/SELF REFERRAL   \n",
            "10000108    EU OBSERVATION            P38XXV          EMERGENCY ROOM   \n",
            "10000117    EU OBSERVATION            P2358X          EMERGENCY ROOM   \n",
            "\n",
            "           discharge_location insurance language marital_status   race  \\\n",
            "subject_id                                                               \n",
            "10000032                 HOME     Other  ENGLISH        WIDOWED  WHITE   \n",
            "10000068                 None     Other  ENGLISH         SINGLE  WHITE   \n",
            "10000084     HOME HEALTH CARE  Medicare  ENGLISH        MARRIED  WHITE   \n",
            "10000108                 None     Other  ENGLISH         SINGLE  WHITE   \n",
            "10000117                 None     Other  ENGLISH       DIVORCED  WHITE   \n",
            "\n",
            "            hospital_expire_flag  los_admission  \n",
            "subject_id                                       \n",
            "10000032                       0       0.786111  \n",
            "10000068                       0       0.298611  \n",
            "10000084                       0       4.538889  \n",
            "10000108                       0       0.407639  \n",
            "10000117                       0       0.532639  \n",
            "299712\n",
            "           gender  anchor_age\n",
            "subject_id                   \n",
            "10000032        F          52\n",
            "10000048        F          23\n",
            "10000068        F          19\n",
            "10000084        M          72\n",
            "10000102        F          27\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_drgcodes = mimic_manipulation_instance.filter_hosp_drgcodes(pd.read_parquet('/content/drive/MyDrive/mimiv-iv/drgcodes.parquet'))\n",
        "print(len(df_drgcodes))\n",
        "print(df_drgcodes.head())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KAa8Z3w1qhjY",
        "outputId": "9e6cafb4-1f34-4b47-d6c0-eae242db31b6"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "144432\n",
            "           drg_type drg_code\n",
            "subject_id                  \n",
            "10000032        APR      283\n",
            "10000084        APR      042\n",
            "10000117        APR      308\n",
            "10000560        APR      442\n",
            "10000719        APR      560\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "x67HPYU9qoM1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_merge = df_admission.merge(df_patient, left_index=True, right_index=True)\n",
        "print(len(df_merge))\n",
        "df_merge.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 362
        },
        "id": "tPf4eL7kqoUl",
        "outputId": "35239c89-1a24-49cd-f52c-5daf8f5899cd"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "180677\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            admission_type admit_provider_id      admission_location  \\\n",
              "subject_id                                                             \n",
              "10000032            URGENT            P874LG  TRANSFER FROM HOSPITAL   \n",
              "10000068    EU OBSERVATION            P51VDL          EMERGENCY ROOM   \n",
              "10000084          EW EMER.            P6957U   WALK-IN/SELF REFERRAL   \n",
              "10000108    EU OBSERVATION            P38XXV          EMERGENCY ROOM   \n",
              "10000117    EU OBSERVATION            P2358X          EMERGENCY ROOM   \n",
              "\n",
              "           discharge_location insurance language marital_status   race  \\\n",
              "subject_id                                                               \n",
              "10000032                 HOME     Other  ENGLISH        WIDOWED  WHITE   \n",
              "10000068                 None     Other  ENGLISH         SINGLE  WHITE   \n",
              "10000084     HOME HEALTH CARE  Medicare  ENGLISH        MARRIED  WHITE   \n",
              "10000108                 None     Other  ENGLISH         SINGLE  WHITE   \n",
              "10000117                 None     Other  ENGLISH       DIVORCED  WHITE   \n",
              "\n",
              "            hospital_expire_flag  los_admission gender  anchor_age  \n",
              "subject_id                                                          \n",
              "10000032                       0       0.786111      F          52  \n",
              "10000068                       0       0.298611      F          19  \n",
              "10000084                       0       4.538889      M          72  \n",
              "10000108                       0       0.407639      M          25  \n",
              "10000117                       0       0.532639      F          48  "
            ],
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
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              "        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-438440f9-405b-4061-9a0a-d75ae17147ac\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-438440f9-405b-4061-9a0a-d75ae17147ac')\"\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-438440f9-405b-4061-9a0a-d75ae17147ac button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_merge"
            }
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_admissions = pd.read_parquet('/content/drive/MyDrive/mimiv-iv/admissions.parquet')\n",
        "df_patients = pd.read_parquet('/content/drive/MyDrive/mimiv-iv/patients.parquet')"
      ],
      "metadata": {
        "id": "IaK0574Nqt0j"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_merge = pd.merge(df_admissions, df_patients, on='subject_id')\n",
        "print(f\"Merged Admissions and Patients: {len(df_merge)}\")\n",
        "print(df_merge.head())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "00j5B3PfrXTp",
        "outputId": "e2342b59-8a7f-4831-d886-b5ad2272a881"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Merged Admissions and Patients: 431231\n",
            "   subject_id   hadm_id           admittime           dischtime deathtime  \\\n",
            "0    10000032  22595853 2180-05-06 22:23:00 2180-05-07 17:15:00       NaT   \n",
            "1    10000032  22841357 2180-06-26 18:27:00 2180-06-27 18:49:00       NaT   \n",
            "2    10000032  25742920 2180-08-05 23:44:00 2180-08-07 17:50:00       NaT   \n",
            "3    10000032  29079034 2180-07-23 12:35:00 2180-07-25 17:55:00       NaT   \n",
            "4    10000068  25022803 2160-03-03 23:16:00 2160-03-04 06:26:00       NaT   \n",
            "\n",
            "   admission_type admit_provider_id      admission_location  \\\n",
            "0          URGENT            P874LG  TRANSFER FROM HOSPITAL   \n",
            "1        EW EMER.            P09Q6Y          EMERGENCY ROOM   \n",
            "2        EW EMER.            P60CC5          EMERGENCY ROOM   \n",
            "3        EW EMER.            P30KEH          EMERGENCY ROOM   \n",
            "4  EU OBSERVATION            P51VDL          EMERGENCY ROOM   \n",
            "\n",
            "  discharge_location insurance  ... marital_status   race           edregtime  \\\n",
            "0               HOME     Other  ...        WIDOWED  WHITE 2180-05-06 19:17:00   \n",
            "1               HOME  Medicaid  ...        WIDOWED  WHITE 2180-06-26 15:54:00   \n",
            "2            HOSPICE  Medicaid  ...        WIDOWED  WHITE 2180-08-05 20:58:00   \n",
            "3               HOME  Medicaid  ...        WIDOWED  WHITE 2180-07-23 05:54:00   \n",
            "4               None     Other  ...         SINGLE  WHITE 2160-03-03 21:55:00   \n",
            "\n",
            "            edouttime hospital_expire_flag  gender anchor_age  anchor_year  \\\n",
            "0 2180-05-06 23:30:00                    0       F         52         2180   \n",
            "1 2180-06-26 21:31:00                    0       F         52         2180   \n",
            "2 2180-08-06 01:44:00                    0       F         52         2180   \n",
            "3 2180-07-23 14:00:00                    0       F         52         2180   \n",
            "4 2160-03-04 06:26:00                    0       F         19         2160   \n",
            "\n",
            "   anchor_year_group         dod  \n",
            "0        2014 - 2016  2180-09-09  \n",
            "1        2014 - 2016  2180-09-09  \n",
            "2        2014 - 2016  2180-09-09  \n",
            "3        2014 - 2016  2180-09-09  \n",
            "4        2008 - 2010        None  \n",
            "\n",
            "[5 rows x 21 columns]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_merge.to_csv('/content/drive/MyDrive/ch_02_end_to_end_ml.csv')"
      ],
      "metadata": {
        "id": "tRGczcE2r4pM"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "LFUKJiDysMEe"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Chapter 2"
      ],
      "metadata": {
        "id": "BBLnEfpesGSq"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}