hospital_risk_admission/Risk Admission Lab v1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1f9a47ca-25c3-4cec-972e-79d613492c5f",
   "metadata": {},
   "source": [
    "# Getting Started with the Data Science Service\n",
    "\n",
    "Data Science service uses [conda](https://anaconda.org/) environments to manage python dependencies.\n",
    "\n",
    "[![Notebook Examples](https://img.shields.io/badge/docs-notebook--examples-blue)](https://github.com/oracle-samples/oci-data-science-ai-samples/tree/master/notebook_examples)\n",
    "[![Conda Environments](https://img.shields.io/badge/docs-conda--environments-blue)](https://docs.oracle.com/en-us/iaas/data-science/using/conda_understand_environments.htm)\n",
    "[![Source Code](https://img.shields.io/badge/source-accelerated--datascience-blue)](https://github.com/oracle/accelerated-data-science)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c54869f-16ad-4916-9fba-0b90367d5864",
   "metadata": {},
   "source": [
    "## Upgrade Accelerated Data Science SDK - `oracle-ads`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25b1b37f-40ed-4f6d-886c-c2ce7ac62548",
   "metadata": {},
   "source": [
    "The Oracle Accelerated Data Science (ADS) SDK is maintained by the Oracle Cloud Infrastructure Data Science service team. It speeds up common data science activities by providing tools that automate and/or simplify common data science tasks, along with providing a data scientist friendly pythonic interface to Oracle Cloud Infrastructure (OCI) services, most notably OCI Data Science, Data Flow, Object Storage, and the Autonomous Database. ADS gives you an interface to manage the lifecycle of machine learning models, from data acquisition to model evaluation, interpretation, and model deployment."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "877c4eb5-85a2-4aa1-a6af-44b9162fa33e",
   "metadata": {},
   "source": [
    "Before you begin with a conda environment, upgrade `oracle-ads` library - [![PyPI](https://img.shields.io/pypi/v/oracle-ads.svg)](https://pypi.org/project/oracle-ads/)  [![Python](https://img.shields.io/pypi/pyversions/oracle-ads.svg?style=plastic)](https://pypi.org/project/oracle-ads/)\n",
    "\n",
    "\n",
    "You can check your version of `oracle-ads` by running - "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "222fb07b-2814-49c2-b8fa-39dc26fba643",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.13.5\n"
     ]
    }
   ],
   "source": [
    "import ads\n",
    "\n",
    "print(ads.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f2433a51-bbcf-4bfc-b32a-b3c91a9a7c3f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Uncomment this code and set the correct proxy links if have to setup proxy for internet\n",
    "# import os\n",
    "# os.environ['http_proxy']=\"http://myproxy\"\n",
    "# os.environ['https_proxy']=\"http://myproxy\"\n",
    "\n",
    "# Use os.environ['no_proxy'] to route trafic directly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "77b1c768-746c-4c2d-853f-cb3871d8c1a6",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: geopandas in ./conda/automlx251_p311_cpu_x86_64_v2/lib/python3.11/site-packages (1.1.1)\n",
      "Requirement already satisfied: numpy>=1.24 in ./conda/automlx251_p311_cpu_x86_64_v2/lib/python3.11/site-packages (from geopandas) (1.26.4)\n",
      "Requirement already satisfied: pyogrio>=0.7.2 in ./conda/automlx251_p311_cpu_x86_64_v2/lib/python3.11/site-packages (from geopandas) (0.11.1)\n",
      "Requirement already satisfied: packaging in ./conda/automlx251_p311_cpu_x86_64_v2/lib/python3.11/site-packages (from geopandas) (24.2)\n",
      "Requirement already satisfied: pandas>=2.0.0 in ./conda/automlx251_p311_cpu_x86_64_v2/lib/python3.11/site-packages (from geopandas) (2.2.2)\n",
      "Requirement already satisfied: pyproj>=3.5.0 in ./conda/automlx251_p311_cpu_x86_64_v2/lib/python3.11/site-packages (from geopandas) (3.7.2)\n",
      "Requirement already satisfied: shapely>=2.0.0 in ./conda/automlx251_p311_cpu_x86_64_v2/lib/python3.11/site-packages (from geopandas) (2.1.1)\n",
      "Requirement already satisfied: python-dateutil>=2.8.2 in ./conda/automlx251_p311_cpu_x86_64_v2/lib/python3.11/site-packages (from pandas>=2.0.0->geopandas) (2.9.0.post0)\n",
      "Requirement already satisfied: pytz>=2020.1 in ./conda/automlx251_p311_cpu_x86_64_v2/lib/python3.11/site-packages (from pandas>=2.0.0->geopandas) (2025.2)\n",
      "Requirement already satisfied: tzdata>=2022.7 in ./conda/automlx251_p311_cpu_x86_64_v2/lib/python3.11/site-packages (from pandas>=2.0.0->geopandas) (2025.2)\n",
      "Requirement already satisfied: certifi in ./conda/automlx251_p311_cpu_x86_64_v2/lib/python3.11/site-packages (from pyogrio>=0.7.2->geopandas) (2025.1.31)\n",
      "Requirement already satisfied: six>=1.5 in ./conda/automlx251_p311_cpu_x86_64_v2/lib/python3.11/site-packages (from python-dateutil>=2.8.2->pandas>=2.0.0->geopandas) (1.17.0)\n"
     ]
    }
   ],
   "source": [
    "# To upgrade run -\n",
    "#! pip install oracle-ads --upgrade\n",
    "! pip install geopandas\n",
    "#!pip install --upgrade oci\n",
    "#!pip install --upgrade ads"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "884f70fb-aff9-4d15-be8a-6b429c8bc291",
   "metadata": {},
   "source": [
    "## Authentication\n",
    "To interact with oci services you need to authenticate with one of the following mechanism - "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e5ba81e-e557-4035-bcc1-4492ca4eb2ca",
   "metadata": {},
   "source": [
    "### 1. Resource Principal\n",
    "\n",
    "Resource Principal works by authorizing the notebook instance that you are using to read/manage OCI service resource such as Object Storage, Data Science Jobs, Data Science Models, Data Science Model Deployment, etc. Check these references - \n",
    "    \n",
    "- Refer how to setup policy for managing Data science service resource [here](https://docs.oracle.com/en-us/iaas/data-science/using/policies.htm)\n",
    "- Refer how to setup policy for managing Object Storage service resource [here](https://docs.oracle.com/en-us/iaas/Content/Identity/policiescommon/commonpolicies.htm#write-objects-to-buckets)\n",
    "    \n",
    "    \n",
    "Other useful resources - \n",
    "\n",
    "- https://docs.oracle.com/en-us/iaas/Content/Identity/Concepts/commonpolicies.htm\n",
    "- https://docs.oracle.com/en-us/iaas/Content/Identity/Concepts/policygetstarted.htm#Getting_Started_with_Policies\n",
    "\n",
    "Once the policies are setup, configure `oracle-ads` to use resource principal as follows - \n",
    "\n",
    "\n",
    "```python\n",
    "ads.set_auth('resource_principal')\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50d09ed1-9ae3-4bf5-a44e-70e3336df119",
   "metadata": {},
   "source": [
    "### 2. API Key\n",
    "\n",
    "To setup API Key refer - \n",
    "\n",
    "- https://docs.oracle.com/en-us/iaas/Content/API/Concepts/apisigningkey.htm\n",
    "- https://docs.oracle.com/en-us/iaas/Content/API/Concepts/sdkconfig.htm\n",
    "\n",
    "\n",
    "Once you have setup the config and the keys, you can setup ads to use API Keys - \n",
    "\n",
    "```python\n",
    "\n",
    "ads.set_auth('api_key')\n",
    "\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c287178a-2edb-465d-ab43-6da3673676cf",
   "metadata": {},
   "source": [
    "## Working with Data on Object Storage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "da1fa0ca-724c-4d66-8cb8-6dfd9f59de75",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import ads\n",
    "import pandas as pd\n",
    "\n",
    "ads.set_auth(\"resource_principal\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0c6100de-4e45-4dcc-b752-050240d908a2",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "bucket_name = \"risk_admission_bucket\"\n",
    "namespace = \"idi1o0a010nx\"\n",
    "\n",
    "\n",
    "file_name = \"dataset_ed_admission.csv\"\n",
    "df = pd.read_csv(\n",
    "    f\"oci://{bucket_name}@{namespace}/{file_name}\",\n",
    "    storage_options=ads.common.auth.default_signer(),\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "beeabd72-63a0-4d30-a3b4-99a542ecf3ee",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       "<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>stay_id</th>\n",
       "      <th>intime</th>\n",
       "      <th>outtime</th>\n",
       "      <th>gender</th>\n",
       "      <th>race</th>\n",
       "      <th>arrival_transport</th>\n",
       "      <th>disposition</th>\n",
       "      <th>admitted_from_ed</th>\n",
       "      <th>temperature</th>\n",
       "      <th>heartrate</th>\n",
       "      <th>resprate</th>\n",
       "      <th>o2sat</th>\n",
       "      <th>sbp</th>\n",
       "      <th>dbp</th>\n",
       "      <th>n_diagnosis</th>\n",
       "      <th>split</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10014729</td>\n",
       "      <td>23300884.0</td>\n",
       "      <td>37887480</td>\n",
       "      <td>2125-03-19 12:36:00</td>\n",
       "      <td>2125-03-19 16:59:47</td>\n",
       "      <td>F</td>\n",
       "      <td>WHITE - OTHER EUROPEAN</td>\n",
       "      <td>WALK IN</td>\n",
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       "      <td>1</td>\n",
       "      <td>99.1</td>\n",
       "      <td>90.0</td>\n",
       "      <td>26.0</td>\n",
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       "      <td>86.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>4.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>34176810</td>\n",
       "      <td>2154-02-05 17:09:00</td>\n",
       "      <td>2154-02-05 22:54:00</td>\n",
       "      <td>F</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>97.7</td>\n",
       "      <td>74.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>133.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>val</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10018328</td>\n",
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       "      <td>2154-08-03 15:31:00</td>\n",
       "      <td>2154-08-03 22:29:00</td>\n",
       "      <td>F</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>HOME</td>\n",
       "      <td>0</td>\n",
       "      <td>96.2</td>\n",
       "      <td>74.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>val</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10020640</td>\n",
       "      <td>27984218.0</td>\n",
       "      <td>38797992</td>\n",
       "      <td>2153-02-12 21:59:00</td>\n",
       "      <td>2153-02-13 01:38:00</td>\n",
       "      <td>F</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>99.2</td>\n",
       "      <td>130.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>val</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10015272</td>\n",
       "      <td>27993466.0</td>\n",
       "      <td>33473053</td>\n",
       "      <td>2137-06-12 16:54:00</td>\n",
       "      <td>2137-06-12 18:37:22</td>\n",
       "      <td>F</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>97.5</td>\n",
       "      <td>118.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>train</td>\n",
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       "   subject_id     hadm_id   stay_id               intime              outtime  \\\n",
       "0    10014729  23300884.0  37887480  2125-03-19 12:36:00  2125-03-19 16:59:47   \n",
       "1    10018328  26706939.0  34176810  2154-02-05 17:09:00  2154-02-05 22:54:00   \n",
       "2    10018328         NaN  32103106  2154-08-03 15:31:00  2154-08-03 22:29:00   \n",
       "3    10020640  27984218.0  38797992  2153-02-12 21:59:00  2153-02-13 01:38:00   \n",
       "4    10015272  27993466.0  33473053  2137-06-12 16:54:00  2137-06-12 18:37:22   \n",
       "\n",
       "  gender                    race arrival_transport disposition  \\\n",
       "0      F  WHITE - OTHER EUROPEAN           WALK IN    ADMITTED   \n",
       "1      F                   WHITE         AMBULANCE    ADMITTED   \n",
       "2      F                   WHITE         AMBULANCE        HOME   \n",
       "3      F                   WHITE         AMBULANCE    ADMITTED   \n",
       "4      F                   WHITE         AMBULANCE    ADMITTED   \n",
       "\n",
       "   admitted_from_ed  temperature  heartrate  resprate  o2sat    sbp   dbp  \\\n",
       "0                 1         99.1       90.0      26.0    NaN   86.0  61.0   \n",
       "1                 1         97.7       74.0      20.0   96.0  133.0  65.0   \n",
       "2                 0         96.2       74.0      18.0  100.0  142.0  75.0   \n",
       "3                 1         99.2      130.0      32.0   94.0  106.0  74.0   \n",
       "4                 1         97.5      118.0      18.0   96.0  100.0  56.0   \n",
       "\n",
       "   n_diagnosis  split  \n",
       "0          4.0  train  \n",
       "1          1.0    val  \n",
       "2          1.0    val  \n",
       "3          5.0    val  \n",
       "4          1.0  train  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "736c5691-f9dd-442e-9021-f3e4c9083030",
   "metadata": {},
   "source": [
    "### Working with other sources\n",
    "\n",
    "Learn how to work with other sources [here](https://accelerated-data-science.readthedocs.io/en/latest/user_guide/loading_data/connect.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d8973b9-4b4e-4b68-beb7-ac97836000da",
   "metadata": {
    "tags": []
   },
   "source": [
    "## References\n",
    "\n",
    "* [Oracle Accelerated Data Science SDK Guide](https://accelerated-data-science.readthedocs.io/en/latest/)\n",
    "* [Oracle Accelerated Data Science Source Code](https://github.com/oracle/accelerated-data-science)\n",
    "* [Notebook Examples](https://github.com/oracle-samples/oci-data-science-ai-samples/tree/master/notebook_examples)\n",
    "* [Conda environments](https://docs.oracle.com/en-us/iaas/data-science/using/conda_understand_environments.htm)\n",
    "* [Publish Conda Environments](https://docs.oracle.com/en-us/iaas/data-science/using/conda_publishs_object.htm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "76e77774-a4ee-4ab0-a22e-399e6a6a1a75",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ZIP baixado e validado: Wallet_ORADB23ai.zip\n"
     ]
    }
   ],
   "source": [
    "## Download Wallet\n",
    "\n",
    "import os, io, zipfile, requests\n",
    "from urllib.parse import urlparse, parse_qs, urlencode, urlunparse\n",
    "\n",
    "def normalize_dropbox_url(u: str) -> str:\n",
    "    \"\"\"\n",
    "    - Se for www.dropbox.com, força dl=1 (download direto)\n",
    "    - Também funciona para links de pasta (/scl/fo/...) e de arquivo (/s/...)\n",
    "    - Alternativa: trocar host para dl.dropboxusercontent.com\n",
    "    \"\"\"\n",
    "    p = urlparse(u)\n",
    "    q = parse_qs(p.query)\n",
    "    q[\"dl\"] = [\"1\"]  # força download\n",
    "    new_query = urlencode({k: v[0] for k, v in q.items()})\n",
    "    return urlunparse((p.scheme, p.netloc, p.path, p.params, new_query, p.fragment))\n",
    "\n",
    "def download_dropbox_zip(url, out_path, chunk=1<<20):\n",
    "    url = normalize_dropbox_url(url)\n",
    "    with requests.get(url, stream=True, allow_redirects=True, timeout=120) as r:\n",
    "        r.raise_for_status()\n",
    "        # cheque simples de conteúdo\n",
    "        ctype = r.headers.get(\"content-type\",\"\").lower()\n",
    "        # Dropbox às vezes serve \"application/zip\" ou \"application/binary\"\n",
    "        if \"text/html\" in ctype:\n",
    "            raise RuntimeError(\"O Dropbox devolveu HTML (provável link sem dl=1 ou sem permissão).\")\n",
    "        with open(out_path, \"wb\") as f:\n",
    "            for part in r.iter_content(chunk_size=chunk):\n",
    "                if part:\n",
    "                    f.write(part)\n",
    "    # valida o ZIP\n",
    "    if not zipfile.is_zipfile(out_path):\n",
    "        raise RuntimeError(f\"Arquivo salvo não é um ZIP válido: {out_path}\")\n",
    "    # teste de integridade\n",
    "    with zipfile.ZipFile(out_path) as z:\n",
    "        bad = z.testzip()\n",
    "        if bad:\n",
    "            raise RuntimeError(f\"ZIP corrompido. Primeiro arquivo com problema: {bad}\")\n",
    "    return out_path\n",
    "\n",
    "# ---- use aqui o SEU link de compartilhamento (de pasta ou arquivo) ----\n",
    "url = \"https://<link para baixar o Wallet se houver>\"\n",
    "zip_path = \"Wallet_ORADB23ai.zip\"\n",
    "\n",
    "download_dropbox_zip(url, zip_path)\n",
    "print(\"ZIP baixado e validado:\", zip_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "00edebb4-f42d-414e-a6f9-f3d5ce7250b5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     SUBJECT_ID     HADM_ID   STAY_ID              INTIME             OUTTIME  \\\n",
      "0      10014729  23300884.0  37887480 2125-03-19 12:36:00 2125-03-19 16:59:47   \n",
      "1      10015272  27993466.0  33473053 2137-06-12 16:54:00 2137-06-12 18:37:22   \n",
      "2      10016810  20973395.0  35758326 2185-06-15 23:08:00 2185-06-16 02:16:00   \n",
      "3      10016810         NaN  31824062 2185-07-08 11:55:00 2185-07-08 11:59:00   \n",
      "4      10006580         NaN  32259573 2137-09-29 21:06:00 2137-09-29 22:54:00   \n",
      "..          ...         ...       ...                 ...                 ...   \n",
      "198    10017492  27417763.0  38213541 2116-06-26 14:29:00 2116-06-26 18:26:30   \n",
      "199    10038999  29026789.0  34205403 2132-05-17 19:56:00 2132-05-18 01:36:00   \n",
      "200    10038999  27189241.0  30272878 2131-05-22 20:33:00 2131-05-22 21:50:33   \n",
      "201    10009049  22995465.0  31628990 2174-05-26 04:20:00 2174-05-26 09:18:00   \n",
      "202    10004457  28723315.0  32405286 2141-08-12 12:08:00 2141-08-12 17:20:00   \n",
      "\n",
      "    GENDER                          RACE ARRIVAL_TRANSPORT DISPOSITION  \\\n",
      "0        F        WHITE - OTHER EUROPEAN           WALK IN    ADMITTED   \n",
      "1        F                         WHITE         AMBULANCE    ADMITTED   \n",
      "2        F                       UNKNOWN           UNKNOWN    ADMITTED   \n",
      "3        F                       UNKNOWN           UNKNOWN       OTHER   \n",
      "4        F  HISPANIC/LATINO - SALVADORAN           WALK IN        HOME   \n",
      "..     ...                           ...               ...         ...   \n",
      "198      M    PATIENT DECLINED TO ANSWER         AMBULANCE    ADMITTED   \n",
      "199      M                         WHITE         AMBULANCE    ADMITTED   \n",
      "200      M                         WHITE           UNKNOWN    ADMITTED   \n",
      "201      M                         WHITE         AMBULANCE    ADMITTED   \n",
      "202      M                         WHITE           WALK IN    ADMITTED   \n",
      "\n",
      "     ADMITTED_FROM_ED  TEMPERATURE  HEARTRATE  RESPRATE  O2SAT    SBP   DBP  \\\n",
      "0                   1         99.1       90.0      26.0    NaN   86.0  61.0   \n",
      "1                   1         97.5      118.0      18.0   96.0  100.0  56.0   \n",
      "2                   1         98.8       72.0      18.0   90.0   98.0  48.0   \n",
      "3                   0          NaN        NaN       NaN    NaN    NaN   NaN   \n",
      "4                   0         98.1       89.0      18.0   96.0  131.0  90.0   \n",
      "..                ...          ...        ...       ...    ...    ...   ...   \n",
      "198                 1          NaN        NaN       NaN    NaN    NaN   NaN   \n",
      "199                 1         97.6      116.0      14.0   99.0  140.0  78.0   \n",
      "200                 1          NaN        NaN       NaN    NaN    NaN   NaN   \n",
      "201                 1         99.0       87.0      18.0   96.0  126.0  68.0   \n",
      "202                 1         97.6      103.0      16.0   98.0  138.0  72.0   \n",
      "\n",
      "     N_DIAGNOSIS  SPLIT  \n",
      "0              4  train  \n",
      "1              1  train  \n",
      "2              1  train  \n",
      "3              1  train  \n",
      "4              1  train  \n",
      "..           ...    ...  \n",
      "198            2  train  \n",
      "199            2  train  \n",
      "200            1  train  \n",
      "201            1  train  \n",
      "202            4  train  \n",
      "\n",
      "[203 rows x 18 columns]\n"
     ]
    }
   ],
   "source": [
    "## Working with Autonomous Database\n",
    "\n",
    "# If you are using Wallet file, provide the zip file path for `wallet_location`\n",
    "connection_parameters = {\n",
    "    \"user_name\": \"admin\",\n",
    "    \"password\": \"********\",\n",
    "    \"service_name\": \"oradb23ai_high\",\n",
    "    \"wallet_location\": \"Wallet.zip\",\n",
    "}\n",
    "import pandas as pd\n",
    "import ads\n",
    "\n",
    "# read of a SQL query into a dataframe with a bind variable. Use bind variables\n",
    "# rather than string substitution to avoid the SQL injection attack vector.\n",
    "df = pd.DataFrame.ads.read_sql(\n",
    "    \"\"\"\n",
    "    select * from ADMIN.DATASET_ED_ADMISSION\n",
    "    WHERE\n",
    "        SPLIT <= :split\n",
    "    \"\"\",\n",
    "    bind_variables={\n",
    "        \"split\" : \"train\"\n",
    "    }\n",
    "    ,\n",
    "    connection_parameters=connection_parameters,\n",
    ")\n",
    "\n",
    "print(df)\n",
    "\n",
    "train = df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "0883b6c8-dc59-4b71-9668-1df4e2a1defc",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "oracle-ads version: 2.13.5\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3be2b1c9ca444a82b8608b32ece1322a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "loop1:   0%|          | 0/4 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✖ Não consegui construir o objeto Dataset do ADS.\n",
      "Último erro capturado: No module named 'ads.dataset.dataframe_dataset'\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<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>STAY_ID</th>\n",
       "      <th>INTIME</th>\n",
       "      <th>OUTTIME</th>\n",
       "      <th>GENDER</th>\n",
       "      <th>RACE</th>\n",
       "      <th>ARRIVAL_TRANSPORT</th>\n",
       "      <th>DISPOSITION</th>\n",
       "      <th>ADMITTED_FROM_ED</th>\n",
       "      <th>TEMPERATURE</th>\n",
       "      <th>HEARTRATE</th>\n",
       "      <th>RESPRATE</th>\n",
       "      <th>O2SAT</th>\n",
       "      <th>SBP</th>\n",
       "      <th>DBP</th>\n",
       "      <th>N_DIAGNOSIS</th>\n",
       "      <th>SPLIT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10014729</td>\n",
       "      <td>23300884.0</td>\n",
       "      <td>37887480</td>\n",
       "      <td>2125-03-19 12:36:00</td>\n",
       "      <td>2125-03-19 16:59:47</td>\n",
       "      <td>F</td>\n",
       "      <td>WHITE - OTHER EUROPEAN</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>99.1</td>\n",
       "      <td>90.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>86.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>4</td>\n",
       "      <td>train</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10015272</td>\n",
       "      <td>27993466.0</td>\n",
       "      <td>33473053</td>\n",
       "      <td>2137-06-12 16:54:00</td>\n",
       "      <td>2137-06-12 18:37:22</td>\n",
       "      <td>F</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>97.5</td>\n",
       "      <td>118.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>1</td>\n",
       "      <td>train</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10016810</td>\n",
       "      <td>20973395.0</td>\n",
       "      <td>35758326</td>\n",
       "      <td>2185-06-15 23:08:00</td>\n",
       "      <td>2185-06-16 02:16:00</td>\n",
       "      <td>F</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.8</td>\n",
       "      <td>72.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>1</td>\n",
       "      <td>train</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10016810</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31824062</td>\n",
       "      <td>2185-07-08 11:55:00</td>\n",
       "      <td>2185-07-08 11:59:00</td>\n",
       "      <td>F</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>OTHER</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>train</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10006580</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32259573</td>\n",
       "      <td>2137-09-29 21:06:00</td>\n",
       "      <td>2137-09-29 22:54:00</td>\n",
       "      <td>F</td>\n",
       "      <td>HISPANIC/LATINO - SALVADORAN</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>HOME</td>\n",
       "      <td>0</td>\n",
       "      <td>98.1</td>\n",
       "      <td>89.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1</td>\n",
       "      <td>train</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SUBJECT_ID     HADM_ID   STAY_ID              INTIME             OUTTIME  \\\n",
       "0    10014729  23300884.0  37887480 2125-03-19 12:36:00 2125-03-19 16:59:47   \n",
       "1    10015272  27993466.0  33473053 2137-06-12 16:54:00 2137-06-12 18:37:22   \n",
       "2    10016810  20973395.0  35758326 2185-06-15 23:08:00 2185-06-16 02:16:00   \n",
       "3    10016810         NaN  31824062 2185-07-08 11:55:00 2185-07-08 11:59:00   \n",
       "4    10006580         NaN  32259573 2137-09-29 21:06:00 2137-09-29 22:54:00   \n",
       "\n",
       "  GENDER                          RACE ARRIVAL_TRANSPORT DISPOSITION  \\\n",
       "0      F        WHITE - OTHER EUROPEAN           WALK IN    ADMITTED   \n",
       "1      F                         WHITE         AMBULANCE    ADMITTED   \n",
       "2      F                       UNKNOWN           UNKNOWN    ADMITTED   \n",
       "3      F                       UNKNOWN           UNKNOWN       OTHER   \n",
       "4      F  HISPANIC/LATINO - SALVADORAN           WALK IN        HOME   \n",
       "\n",
       "   ADMITTED_FROM_ED  TEMPERATURE  HEARTRATE  RESPRATE  O2SAT    SBP   DBP  \\\n",
       "0                 1         99.1       90.0      26.0    NaN   86.0  61.0   \n",
       "1                 1         97.5      118.0      18.0   96.0  100.0  56.0   \n",
       "2                 1         98.8       72.0      18.0   90.0   98.0  48.0   \n",
       "3                 0          NaN        NaN       NaN    NaN    NaN   NaN   \n",
       "4                 0         98.1       89.0      18.0   96.0  131.0  90.0   \n",
       "\n",
       "   N_DIAGNOSIS  SPLIT  \n",
       "0            4  train  \n",
       "1            1  train  \n",
       "2            1  train  \n",
       "3            1  train  \n",
       "4            1  train  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 203 entries, 0 to 202\n",
      "Data columns (total 18 columns):\n",
      " #   Column             Non-Null Count  Dtype         \n",
      "---  ------             --------------  -----         \n",
      " 0   SUBJECT_ID         203 non-null    int64         \n",
      " 1   HADM_ID            158 non-null    float64       \n",
      " 2   STAY_ID            203 non-null    int64         \n",
      " 3   INTIME             203 non-null    datetime64[ns]\n",
      " 4   OUTTIME            203 non-null    datetime64[ns]\n",
      " 5   GENDER             203 non-null    category      \n",
      " 6   RACE               203 non-null    category      \n",
      " 7   ARRIVAL_TRANSPORT  203 non-null    category      \n",
      " 8   DISPOSITION        203 non-null    category      \n",
      " 9   ADMITTED_FROM_ED   203 non-null    int64         \n",
      " 10  TEMPERATURE        179 non-null    float64       \n",
      " 11  HEARTRATE          181 non-null    float64       \n",
      " 12  RESPRATE           182 non-null    float64       \n",
      " 13  O2SAT              181 non-null    float64       \n",
      " 14  SBP                182 non-null    float64       \n",
      " 15  DBP                182 non-null    float64       \n",
      " 16  N_DIAGNOSIS        203 non-null    int64         \n",
      " 17  SPLIT              203 non-null    category      \n",
      "dtypes: category(5), datetime64[ns](2), float64(7), int64(4)\n",
      "memory usage: 22.9 KB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "## Visualize Data\n",
    "\n",
    "TARGET_COL = \"admitted_from_ed\"  # ajuste se houver alvo; se não houver, pode deixar None\n",
    "\n",
    "import pandas as pd, numpy as np, ads, sys\n",
    "\n",
    "print(\"oracle-ads version:\", getattr(ads, \"__version__\", \"unknown\"))\n",
    "\n",
    "# --- 0) Higieniza tipos para evitar falhas no type_discovery ---\n",
    "df_clean = df.copy()\n",
    "# datas (heurística por nome de coluna)\n",
    "for c in df_clean.columns:\n",
    "    cl = c.lower()\n",
    "    if any(k in cl for k in [\"time\", \"date\", \"_at\", \"dt\"]):\n",
    "        try:\n",
    "            df_clean[c] = pd.to_datetime(df_clean[c], errors=\"coerce\")\n",
    "        except Exception:\n",
    "            pass\n",
    "# categorias leves\n",
    "for c in df_clean.select_dtypes(include=[\"object\"]).columns:\n",
    "    if 1 < df_clean[c].nunique(dropna=True) <= 1000:\n",
    "        df_clean[c] = df_clean[c].astype(\"category\")\n",
    "\n",
    "DATASET_NAME = \"ED Admission\"\n",
    "DATASET_DESC = \"Dataset PS para modelagem\"\n",
    "\n",
    "ds = None\n",
    "last_err = None\n",
    "\n",
    "# --- 1) Tentativa principal: DatasetFactory ---\n",
    "try:\n",
    "    from ads.dataset.factory import DatasetFactory\n",
    "    try:\n",
    "        ds = DatasetFactory.from_dataframe(\n",
    "            df_clean,\n",
    "            target=TARGET_COL,\n",
    "            dataset_name=DATASET_NAME,\n",
    "            dataset_description=DATASET_DESC,\n",
    "            type_discovery=False  # evita o erro de typed discovery\n",
    "        )\n",
    "        print(\"✔ Usando DatasetFactory (type_discovery=False)\")\n",
    "    except TypeError:\n",
    "        ds = DatasetFactory.from_dataframe(\n",
    "            df_clean,\n",
    "            target=TARGET_COL,\n",
    "            dataset_name=DATASET_NAME,\n",
    "            dataset_description=DATASET_DESC\n",
    "        )\n",
    "        print(\"✔ Usando DatasetFactory (sem type_discovery)\")\n",
    "except Exception as e:\n",
    "    last_err = e\n",
    "\n",
    "# --- 2) Fallback: construtor direto ADSDataset ---\n",
    "if ds is None:\n",
    "    try:\n",
    "        from ads.dataset.dataset import ADSDataset\n",
    "        try:\n",
    "            ds = ADSDataset(\n",
    "                df_clean,\n",
    "                target=TARGET_COL,\n",
    "                name=DATASET_NAME,\n",
    "                description=DATASET_DESC,\n",
    "                type_discovery=False\n",
    "            )\n",
    "            print(\"✔ Usando ADSDataset(...) (type_discovery=False)\")\n",
    "        except TypeError:\n",
    "            ds = ADSDataset(\n",
    "                df_clean,\n",
    "                target=TARGET_COL,\n",
    "                name=DATASET_NAME,\n",
    "                description=DATASET_DESC\n",
    "            )\n",
    "            print(\"✔ Usando ADSDataset(...) (sem type_discovery)\")\n",
    "    except Exception as e2:\n",
    "        last_err = e2\n",
    "\n",
    "# --- 3) Fallback: construtor direto Dataset (nome antigo) ---\n",
    "if ds is None:\n",
    "    try:\n",
    "        from ads.dataset.dataset import Dataset\n",
    "        try:\n",
    "            ds = Dataset(\n",
    "                df_clean,\n",
    "                target=TARGET_COL,\n",
    "                name=DATASET_NAME,\n",
    "                description=DATASET_DESC,\n",
    "                type_discovery=False\n",
    "            )\n",
    "            print(\"✔ Usando Dataset(...) (type_discovery=False)\")\n",
    "        except TypeError:\n",
    "            ds = Dataset(\n",
    "                df_clean,\n",
    "                target=TARGET_COL,\n",
    "                name=DATASET_NAME,\n",
    "                description=DATASET_DESC\n",
    "            )\n",
    "            print(\"✔ Usando Dataset(...) (sem type_discovery)\")\n",
    "    except Exception as e3:\n",
    "        last_err = e3\n",
    "\n",
    "# --- 4) Fallback (mais raro): DataFrameDataset ---\n",
    "if ds is None:\n",
    "    try:\n",
    "        from ads.dataset.dataframe_dataset import DataFrameDataset\n",
    "        ds = DataFrameDataset(\n",
    "            df_clean,\n",
    "            target=TARGET_COL,\n",
    "            name=DATASET_NAME,\n",
    "            description=DATASET_DESC\n",
    "        )\n",
    "        print(\"✔ Usando DataFrameDataset(...)\")\n",
    "    except Exception as e4:\n",
    "        last_err = e4\n",
    "\n",
    "# --- Finalização: roles + visualização ---\n",
    "if ds is not None:\n",
    "    # if \"stay_id\" in df_clean.columns:\n",
    "    #     ds.set_role(\"stay_id\", \"id\")\n",
    "    # for col in [\"intime\",\"outtime\",\"first_vitals_time\",\"first_pyxis_time\"]:\n",
    "    #     if col in df_clean.columns:\n",
    "    #         ds.set_role(col, \"timestamp\")\n",
    "    \n",
    "    from bokeh.io import reset_output, output_notebook\n",
    "    reset_output()\n",
    "    ds.show_in_notebook()\n",
    "else:\n",
    "    # Último recurso: visão rápida do DF caso nenhuma classe esteja disponível\n",
    "    print(\"✖ Não consegui construir o objeto Dataset do ADS.\")\n",
    "    print(\"Último erro capturado:\", last_err)\n",
    "    from IPython.display import display\n",
    "    display(df_clean.head())\n",
    "    print(df_clean.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e22281c3-cecb-42ed-b13d-31800fee5c19",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "treino sklearn: 1.3.2\n",
      "3.11.11 | packaged by conda-forge | (main, Mar  3 2025, 20:43:55) [GCC 13.3.0]\n",
      "treino ads: 2.13.5\n"
     ]
    }
   ],
   "source": [
    "## Verifica a versão do sklearn e se está executando via o package correto\n",
    "\n",
    "import sklearn, sys\n",
    "print(\"treino sklearn:\", sklearn.__version__)\n",
    "print(sys.version)\n",
    "\n",
    "import ads\n",
    "print(\"treino ads:\", ads.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f4bbab17-211b-455c-8056-42fc705a2bc8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0      0.333     0.143     0.200         7\n",
      "           1      0.867     0.951     0.907        41\n",
      "\n",
      "    accuracy                          0.833        48\n",
      "   macro avg      0.600     0.547     0.553        48\n",
      "weighted avg      0.789     0.833     0.804        48\n",
      "\n",
      "Kappa: 0.12328767123287676\n",
      "Matriz de confusão:\n",
      " [[ 1  6]\n",
      " [ 2 39]]\n"
     ]
    }
   ],
   "source": [
    "## Train with scikit-learning (Produção)\n",
    "\n",
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.preprocessing import OneHotEncoder, StandardScaler\n",
    "from sklearn.impute import SimpleImputer\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import classification_report, confusion_matrix, cohen_kappa_score\n",
    "\n",
    "# ----------------------------------\n",
    "# 1) Normaliza nomes de colunas\n",
    "# ----------------------------------\n",
    "def normalize_cols(df: pd.DataFrame) -> pd.DataFrame:\n",
    "    cols = (\n",
    "        df.columns.astype(str)\n",
    "          .str.strip()\n",
    "          .str.replace(r\"\\s+\", \"_\", regex=True)\n",
    "          .str.replace(r\"[^\\w]+\", \"_\", regex=True)\n",
    "          .str.replace(r\"_+\", \"_\", regex=True)\n",
    "          .str.strip(\"_\")\n",
    "          .str.lower()\n",
    "    )\n",
    "    df2 = df.copy()\n",
    "    df2.columns = cols\n",
    "    return df2\n",
    "\n",
    "dfn = normalize_cols(df)\n",
    "\n",
    "# ----------------------------------\n",
    "# 2) Define target (já 0/1)\n",
    "# ----------------------------------\n",
    "TARGET_COL = \"admitted_from_ed\"\n",
    "if TARGET_COL not in dfn.columns:\n",
    "    raise KeyError(f\"Coluna {TARGET_COL} não encontrada no DataFrame!\")\n",
    "\n",
    "dfn[TARGET_COL] = dfn[TARGET_COL].astype(int)\n",
    "\n",
    "# ----------------------------------\n",
    "# 3) Features\n",
    "# ----------------------------------\n",
    "# gera features extras a partir das datas\n",
    "for c in [\"intime\", \"outtime\"]:\n",
    "    if c in dfn.columns:\n",
    "        dfn[c] = pd.to_datetime(dfn[c], errors=\"coerce\")\n",
    "\n",
    "if {\"intime\",\"outtime\"} <= set(dfn.columns):\n",
    "    dfn[\"los_minutes\"] = (dfn[\"outtime\"] - dfn[\"intime\"]).dt.total_seconds()/60\n",
    "    dfn[\"arrival_hour\"] = dfn[\"intime\"].dt.hour\n",
    "    dfn[\"arrival_weekday\"] = dfn[\"intime\"].dt.day_name()\n",
    "\n",
    "candidate_features = [\n",
    "    \"gender\",\"race\",\"arrival_transport\",\n",
    "    \"temperature\",\"heartrate\",\"resprate\",\"o2sat\",\"sbp\",\"dbp\",\n",
    "    \"n_diagnosis\",\"los_minutes\",\"arrival_hour\",\"arrival_weekday\"\n",
    "]\n",
    "features = [c for c in candidate_features if c in dfn.columns]\n",
    "\n",
    "X = dfn[features].copy()\n",
    "y = dfn[TARGET_COL]\n",
    "\n",
    "# ----------------------------------\n",
    "# 4) Split train/test\n",
    "# ----------------------------------\n",
    "if \"split\" in dfn.columns:\n",
    "    train_mask = dfn[\"split\"].astype(str).str.lower().eq(\"train\")\n",
    "    val_mask   = dfn[\"split\"].astype(str).str.lower().isin([\"val\",\"test\"])\n",
    "    X_train, y_train = X[train_mask], y[train_mask]\n",
    "    X_test, y_test   = X[val_mask], y[val_mask]\n",
    "else:\n",
    "    X_train, X_test, y_train, y_test = train_test_split(\n",
    "        X, y, test_size=0.2, random_state=42, stratify=y\n",
    "    )\n",
    "\n",
    "# ----------------------------------\n",
    "# 5) Pipeline com RandomForest\n",
    "# ----------------------------------\n",
    "cat_cols = X_train.select_dtypes(include=[\"object\",\"category\"]).columns.tolist()\n",
    "num_cols = [c for c in features if c not in cat_cols]\n",
    "\n",
    "pre = ColumnTransformer(\n",
    "    transformers=[\n",
    "        (\"cat\", Pipeline(steps=[\n",
    "            (\"imputer\", SimpleImputer(strategy=\"most_frequent\")),\n",
    "            (\"onehot\",  OneHotEncoder(handle_unknown=\"ignore\"))\n",
    "        ]), cat_cols),\n",
    "        (\"num\", Pipeline(steps=[\n",
    "            (\"imputer\", SimpleImputer(strategy=\"median\")),\n",
    "            (\"scaler\",  StandardScaler())\n",
    "        ]), num_cols),\n",
    "    ]\n",
    ")\n",
    "\n",
    "clf = Pipeline(steps=[\n",
    "    (\"preprocess\", pre),\n",
    "    (\"model\", RandomForestClassifier(\n",
    "        class_weight=\"balanced\",\n",
    "        n_estimators=300,\n",
    "        random_state=42\n",
    "    ))\n",
    "])\n",
    "\n",
    "# ----------------------------------\n",
    "# 6) Treino e avaliação\n",
    "# ----------------------------------\n",
    "clf.fit(X_train, y_train)\n",
    "y_pred = clf.predict(X_test)\n",
    "\n",
    "print(classification_report(y_test, y_pred, digits=3))\n",
    "print(\"Kappa:\", cohen_kappa_score(y_test, y_pred))\n",
    "print(\"Matriz de confusão:\\n\", confusion_matrix(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "431bc153-e815-48e4-ba86-b0cadd1d9340",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "backup local OK\n"
     ]
    }
   ],
   "source": [
    "## Salvar o modelo scikit-learning\n",
    "\n",
    "import joblib, os\n",
    "os.makedirs(\"artifacts\", exist_ok=True)\n",
    "joblib.dump(clf, \"artifacts/model.pkl\")          # seu Pipeline scikit-learn\n",
    "joblib.dump(list(X_train.columns), \"artifacts/feature_order.pkl\")  # ordem das colunas\n",
    "print(\"backup local OK\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "9bb5133c-4ba5-41f5-b829-e7ca61c0f4a5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:ads.common:In the future model input will be serialized by `cloudpickle` by default. Currently, model input are serialized into a dictionary containing serialized input data and original data type information.Set `model_input_serializer=\"cloudpickle\"` to use cloudpickle model input serializer.\n",
      "WARNING:py.warnings:/home/datascience/conda/automlx251_p311_cpu_x86_64_v2/lib/python3.11/site-packages/ads/model/runtime/env_info.py:92: UserWarning: slug will be deprecated. Provide conda pack path instead.             ?, ?it/s]\n",
      "  warnings.warn(\"slug will be deprecated. Provide conda pack path instead.\")\n",
      "\n",
      "Start loading model.joblib from model directory /home/datascience/oci_model_artifact ...\n",
      "Model is successfully loaded.\n",
      "['input_schema.json', 'score.py', '.model-ignore', 'runtime.yaml', 'test_json_output.json', 'model.joblib']\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "loop1:   0%|          | 0/4 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:ads.model.datascience_model:the JSON object must be str, bytes or bytearray, not Schema\n",
      "Model ID: ocid1.datasciencemodel.oc1.sa-saopaulo-1.amaaaaaafioir7iaq5rnhagfiztsbom7bzqvyenwrcsta3g67qvfllf5erna\n",
      "Model Deployment OCID: ocid1.datasciencemodeldeployment.oc1.sa-saopaulo-1.amaaaaaafioir7iafffqtvgm2mj24zw7vnnyamcxzhwqelkdpg5n5qw4jgkq\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Creating model deployment:   0%|          | [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Deployment OCID: ocid1.datasciencemodeldeployment.oc1.sa-saopaulo-1.amaaaaaafioir7iafffqtvgm2mj24zw7vnnyamcxzhwqelkdpg5n5qw4jgkq\n",
      "Deployment endpoint: https://modeldeployment.sa-saopaulo-1.oci.customer-oci.com/ocid1.datasciencemodeldeployment.oc1.sa-saopaulo-1.amaaaaaafioir7iafffqtvgm2mj24zw7vnnyamcxzhwqelkdpg5n5qw4jgkq\n",
      "Local predict: {'code': 'NotAuthorizedOrNotFound', 'message': 'Authorization failed or requested resource not found.'}\n"
     ]
    }
   ],
   "source": [
    "## Registrar no Model Catalog\n",
    "\n",
    "import ads\n",
    "ads.set_auth(\n",
    "    auth=\"api_key\",\n",
    "    oci_config_location=\"/home/datascience/.oci/config\",\n",
    "    profile=\"DEFAULT\"\n",
    ")\n",
    "\n",
    "import os, joblib\n",
    "from ads.model.framework.sklearn_model import SklearnModel\n",
    "\n",
    "compartment_id = \"ocid1.compartment.oc1..aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa\"\n",
    "#conda_slug     = \"oci://service-conda-packs@id19sfcrra6z/service_pack/cpu/Oracle_AutoMLx_v25.1_for_CPU_on_Python_3.11/2.0/automlx251_p311_cpu_x86_64_v2\"   # igual ao exemplo oficial\n",
    "conda_slug = \"automlx251_p311_cpu_x86_64_v2\"\n",
    "project_id = \"ocid1.datascienceproject.oc1.sa-saopaulo-1.aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa\"\n",
    "\n",
    "# (opcional) salvar artefatos locais\n",
    "# os.makedirs(\"artifacts\", exist_ok=True)\n",
    "# joblib.dump(clf, \"artifacts/model.pkl\")\n",
    "\n",
    "artifact_dir = \"oci_model_artifact\"  # diretório de trabalho local do pacote\n",
    "sk = SklearnModel(estimator=clf, artifact_dir=artifact_dir, X_sample=X_train.head(5))\n",
    "\n",
    "sk.prepare(\n",
    "    training_conda_env=conda_slug,\n",
    "    inference_conda_env=conda_slug,      # OU: inference_conda_env_path=\"oci://<bucket@ns>/.../conda_pack.tar.gz\"\n",
    "    X_sample=X_train.head(5),  # …mas **garanta aqui** no prepare também\n",
    "    force_overwrite=True,\n",
    "    model_input_serializer=\"cloudpickle\"  # remove o warning futuro\n",
    ")\n",
    "\n",
    "# **REGISTRA** no Model Catalog\n",
    "sk.save(\n",
    "    display_name=\"ED-Admission RF\",\n",
    "    description=\"RandomForest admitted_from_ed (0/1)\",\n",
    "    compartment_id=compartment_id,\n",
    ")\n",
    "\n",
    "model_id = getattr(sk, \"model_id\", None) or getattr(getattr(sk, \"dsc_model\", None), \"id\", None)\n",
    "print(\"Model ID:\", model_id)\n",
    "\n",
    "# 🔹 DEPLOY do modelo (cria endpoint REST ativo)\n",
    "deployment = sk.deploy(\n",
    "    display_name=\"ED-Admission Deployment\",\n",
    "    compartment_id=compartment_id,\n",
    "    project_id=project_id,\n",
    "    deployment_instance_shape=\"VM.Standard.E3.Flex\",\n",
    "    instance_count=1\n",
    ")\n",
    "\n",
    "print(\"Deployment OCID:\", deployment.id)\n",
    "print(\"Deployment endpoint:\", deployment.url)\n",
    "\n",
    "# 🔹 Teste de predição local\n",
    "print(\"Local predict:\", sk.predict(X_train.head(3)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a48e5d32-95b3-4eb1-9d16-c4da5de0c0ca",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[{\"gender\":\"F\",\"race\":\"WHITE - OTHER EUROPEAN\",\"arrival_transport\":\"WALK IN\",\"temperature\":99.1,\"heartrate\":90.0,\"resprate\":26.0,\"o2sat\":null,\"sbp\":86.0,\"dbp\":61.0,\"n_diagnosis\":4,\"los_minutes\":263.7833333333,\"arrival_hour\":12,\"arrival_weekday\":\"Monday\"},{\"gender\":\"F\",\"race\":\"WHITE\",\"arrival_transport\":\"AMBULANCE\",\"temperature\":97.5,\"heartrate\":118.0,\"resprate\":18.0,\"o2sat\":96.0,\"sbp\":100.0,\"dbp\":56.0,\"n_diagnosis\":1,\"los_minutes\":103.3666666667,\"arrival_hour\":16,\"arrival_weekday\":\"Wednesday\"},{\"gender\":\"F\",\"race\":\"UNKNOWN\",\"arrival_transport\":\"UNKNOWN\",\"temperature\":98.8,\"heartrate\":72.0,\"resprate\":18.0,\"o2sat\":90.0,\"sbp\":98.0,\"dbp\":48.0,\"n_diagnosis\":1,\"los_minutes\":188.0,\"arrival_hour\":23,\"arrival_weekday\":\"Wednesday\"},{\"gender\":\"F\",\"race\":\"UNKNOWN\",\"arrival_transport\":\"UNKNOWN\",\"temperature\":null,\"heartrate\":null,\"resprate\":null,\"o2sat\":null,\"sbp\":null,\"dbp\":null,\"n_diagnosis\":1,\"los_minutes\":4.0,\"arrival_hour\":11,\"arrival_weekday\":\"Friday\"},{\"gender\":\"F\",\"race\":\"HISPANIC\\/LATINO - SALVADORAN\",\"arrival_transport\":\"WALK IN\",\"temperature\":98.1,\"heartrate\":89.0,\"resprate\":18.0,\"o2sat\":96.0,\"sbp\":131.0,\"dbp\":90.0,\"n_diagnosis\":1,\"los_minutes\":108.0,\"arrival_hour\":21,\"arrival_weekday\":\"Sunday\"}]\n",
      "Start loading model.joblib from model directory /home/datascience/oci_model_artifact ...\n",
      "Model is successfully loaded.\n",
      "WARNING:py.warnings:/home/datascience/oci_model_artifact/score.py:100: FutureWarning: Passing literal json to 'read_json' is deprecated and will be removed in a future version. To read from a literal string, wrap it in a 'StringIO' object.\n",
      "  return pd.read_json(json_data, dtype=fetch_data_type_from_schema(input_schema_path))\n",
      "\n",
      "{'prediction': [1, 1, 1, 0, 0]}\n"
     ]
    }
   ],
   "source": [
    "## Validate\n",
    "\n",
    "MODEL_FILE = os.path.join(artifact_dir, \"model.joblib\")\n",
    "\n",
    "def load_model(model_path=MODEL_FILE):\n",
    "    if not os.path.exists(model_path):\n",
    "        raise FileNotFoundError(f\"Modelo não encontrado em: {model_path}\")\n",
    "    return joblib.load(model_path)\n",
    "\n",
    "def predict(data, model=None) -> dict:\n",
    "    # carrega sob demanda (não avalia nada no momento do import)\n",
    "    if model is None:\n",
    "        model = load_model()\n",
    "\n",
    "    if isinstance(data, str):\n",
    "        X = pd.read_json(io.StringIO(data))\n",
    "    elif isinstance(data, dict):\n",
    "        X = pd.DataFrame.from_dict(data)\n",
    "    else:\n",
    "        # já é DataFrame/array?\n",
    "        X = pd.DataFrame(data)\n",
    "\n",
    "    preds = model.predict(X).tolist()\n",
    "    return {\"prediction\": preds}\n",
    "\n",
    "payload = X_train.iloc[:5].to_json(orient=\"records\")\n",
    "\n",
    "print(payload)\n",
    "\n",
    "import sys\n",
    "sys.path.insert(0, artifact_dir)\n",
    "\n",
    "from score import load_model, predict  # do pacote gerado\n",
    "\n",
    "_ = load_model()                       # carrega o model.joblib\n",
    "preds = predict(payload, _)            # chama a função predict do score.py\n",
    "print(preds)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "bd8752e5-fb11-4660-a5af-bae676b4ecb1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Deployment OCID: ocid1.datasciencemodeldeployment.oc1.sa-saopaulo-1.amaaaaaafioir7iafffqtvgm2mj24zw7vnnyamcxzhwqelkdpg5n5qw4jgkq\n",
      "Deployment endpoint: https://modeldeployment.sa-saopaulo-1.oci.customer-oci.com/ocid1.datasciencemodeldeployment.oc1.sa-saopaulo-1.amaaaaaafioir7iafffqtvgm2mj24zw7vnnyamcxzhwqelkdpg5n5qw4jgkq\n",
      "     SUBJECT_ID     HADM_ID   STAY_ID              INTIME             OUTTIME  \\\n",
      "0      10014729  23300884.0  37887480 2125-03-19 12:36:00 2125-03-19 16:59:47   \n",
      "1      10015272  27993466.0  33473053 2137-06-12 16:54:00 2137-06-12 18:37:22   \n",
      "2      10016810  20973395.0  35758326 2185-06-15 23:08:00 2185-06-16 02:16:00   \n",
      "3      10016810         NaN  31824062 2185-07-08 11:55:00 2185-07-08 11:59:00   \n",
      "4      10006580         NaN  32259573 2137-09-29 21:06:00 2137-09-29 22:54:00   \n",
      "..          ...         ...       ...                 ...                 ...   \n",
      "198    10017492  27417763.0  38213541 2116-06-26 14:29:00 2116-06-26 18:26:30   \n",
      "199    10038999  29026789.0  34205403 2132-05-17 19:56:00 2132-05-18 01:36:00   \n",
      "200    10038999  27189241.0  30272878 2131-05-22 20:33:00 2131-05-22 21:50:33   \n",
      "201    10009049  22995465.0  31628990 2174-05-26 04:20:00 2174-05-26 09:18:00   \n",
      "202    10004457  28723315.0  32405286 2141-08-12 12:08:00 2141-08-12 17:20:00   \n",
      "\n",
      "    GENDER                          RACE ARRIVAL_TRANSPORT DISPOSITION  \\\n",
      "0        F        WHITE - OTHER EUROPEAN           WALK IN    ADMITTED   \n",
      "1        F                         WHITE         AMBULANCE    ADMITTED   \n",
      "2        F                       UNKNOWN           UNKNOWN    ADMITTED   \n",
      "3        F                       UNKNOWN           UNKNOWN       OTHER   \n",
      "4        F  HISPANIC/LATINO - SALVADORAN           WALK IN        HOME   \n",
      "..     ...                           ...               ...         ...   \n",
      "198      M    PATIENT DECLINED TO ANSWER         AMBULANCE    ADMITTED   \n",
      "199      M                         WHITE         AMBULANCE    ADMITTED   \n",
      "200      M                         WHITE           UNKNOWN    ADMITTED   \n",
      "201      M                         WHITE         AMBULANCE    ADMITTED   \n",
      "202      M                         WHITE           WALK IN    ADMITTED   \n",
      "\n",
      "     ADMITTED_FROM_ED  TEMPERATURE  HEARTRATE  RESPRATE  O2SAT    SBP   DBP  \\\n",
      "0                   1         99.1       90.0      26.0    NaN   86.0  61.0   \n",
      "1                   1         97.5      118.0      18.0   96.0  100.0  56.0   \n",
      "2                   1         98.8       72.0      18.0   90.0   98.0  48.0   \n",
      "3                   0          NaN        NaN       NaN    NaN    NaN   NaN   \n",
      "4                   0         98.1       89.0      18.0   96.0  131.0  90.0   \n",
      "..                ...          ...        ...       ...    ...    ...   ...   \n",
      "198                 1          NaN        NaN       NaN    NaN    NaN   NaN   \n",
      "199                 1         97.6      116.0      14.0   99.0  140.0  78.0   \n",
      "200                 1          NaN        NaN       NaN    NaN    NaN   NaN   \n",
      "201                 1         99.0       87.0      18.0   96.0  126.0  68.0   \n",
      "202                 1         97.6      103.0      16.0   98.0  138.0  72.0   \n",
      "\n",
      "     N_DIAGNOSIS  SPLIT  \n",
      "0              4  train  \n",
      "1              1  train  \n",
      "2              1  train  \n",
      "3              1  train  \n",
      "4              1  train  \n",
      "..           ...    ...  \n",
      "198            2  train  \n",
      "199            2  train  \n",
      "200            1  train  \n",
      "201            1  train  \n",
      "202            4  train  \n",
      "\n",
      "[203 rows x 18 columns]\n",
      "WARNING:py.warnings:/home/datascience/conda/automlx251_p311_cpu_x86_64_v2/lib/python3.11/site-packages/ads/model/deployment/model_deployment.py:302: UserWarning: Parameter `properties` was deprecated in 2.8.2 from ModelDeployment constructor and will be removed in 3.0.0. Please use `spec` or the builder pattern to initialize model deployment instance. Check: https://accelerated-data-science.readthedocs.io/en/latest/user_guide/model_registration/quick_start.html\n",
      "  warnings.warn(\n",
      "\n",
      "Status: State.ACTIVE\n",
      "Endpoint: https://modeldeployment.sa-saopaulo-1.oci.customer-oci.com/ocid1.datasciencemodeldeployment.oc1.sa-saopaulo-1.amaaaaaafioir7iafffqtvgm2mj24zw7vnnyamcxzhwqelkdpg5n5qw4jgkq\n",
      "https://modeldeployment.sa-saopaulo-1.oci.customer-oci.com/ocid1.datasciencemodeldeployment.oc1.sa-saopaulo-1.amaaaaaafioir7iafffqtvgm2mj24zw7vnnyamcxzhwqelkdpg5n5qw4jgkq/predict\n",
      "200 {\"prediction\":[1,1]}\n"
     ]
    }
   ],
   "source": [
    "## Consumindo o Endpoint - Código Simples\n",
    "\n",
    "import requests\n",
    "import oci\n",
    "import pandas as pd\n",
    "from ads.model.deployment import ModelDeployment\n",
    "import os\n",
    "from oci.signer import Signer\n",
    "import ads\n",
    "\n",
    "# Profile do OCI-CLI\n",
    "PROFILE = \"DEFAULT\"\n",
    "\n",
    "# Em caso de estar no notebook integrado ao processo de deployment do modelo - habilitar\n",
    "print(\"Deployment OCID:\", deployment.id)\n",
    "print(\"Deployment endpoint:\", deployment.url)\n",
    "DEPLOYMENT_ID = deployment.id\n",
    "\n",
    "# Caso contrário, se estiver em código avulso - habilitar\n",
    "#DEPLOYMENT_ID = \"ocid1.datasciencemodeldeployment.oc1.sa-saopaulo.aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa\"\n",
    "\n",
    "ads.set_auth(\n",
    "    auth=\"api_key\",\n",
    "    oci_config_location=\"/home/datascience/.oci/config\",\n",
    "    profile=PROFILE\n",
    ")\n",
    "\n",
    "# Recupera metadados do deployment\n",
    "md = ModelDeployment.from_id(DEPLOYMENT_ID)\n",
    "print(\"Status:\", md.status)\n",
    "print(\"Endpoint:\", md.url)\n",
    "\n",
    "# Endpoint correto (não adicionar /predict manualmente se já vier com ele)\n",
    "#endpoint = \"https://modeldeployment.sa-saopaulo-1.oci.customer-oci.com/ocid1.datasciencemodeldeployment.oc1.sa-saopaulo-1.aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa/predict\"\n",
    "endpoint = md.url + \"/predict\"\n",
    "\n",
    "print(endpoint)\n",
    "\n",
    "# -----------------------------\n",
    "# 1) Autenticação\n",
    "# -----------------------------\n",
    "config = oci.config.from_file(\"~/.oci/config\", PROFILE)\n",
    "auth = Signer(\n",
    "    tenancy=config[\"tenancy\"],\n",
    "    user=config[\"user\"],\n",
    "    fingerprint=config[\"fingerprint\"],\n",
    "    private_key_file_location=config[\"key_file\"],\n",
    "    pass_phrase=None,  # deixe None se a chave não tem senha\n",
    ")\n",
    "\n",
    "# -----------------------------\n",
    "# 2) Payload\n",
    "# -----------------------------\n",
    "# 1) Colunas na ORDEM do schema\n",
    "columns = [\n",
    "    \"gender\",\"race\",\"arrival_transport\",\n",
    "    \"temperature\",\"heartrate\",\"resprate\",\"o2sat\",\"sbp\",\"dbp\",\n",
    "    \"n_diagnosis\",\"los_minutes\",\"arrival_hour\",\"arrival_weekday\"\n",
    "]\n",
    "\n",
    "# 2) Monte as linhas como dict e force a ordem virando DataFrame -> JSON records\n",
    "rows_df = pd.DataFrame([\n",
    "    {\n",
    "        \"gender\":\"F\",\"race\":\"Caucasian\",\"arrival_transport\":\"Ambulance\",\n",
    "        \"temperature\":98.6,\"heartrate\":88,\"resprate\":20,\"o2sat\":95,\n",
    "        \"sbp\":110,\"dbp\":70,\"n_diagnosis\":2,\"los_minutes\":120.0,\n",
    "        \"arrival_hour\":14,\"arrival_weekday\":\"Monday\"\n",
    "    },\n",
    "    {\n",
    "        \"gender\":\"M\",\"race\":\"WHITE\",\"arrival_transport\":\"WALK IN\",\n",
    "        \"temperature\":99.1,\"heartrate\":72,\"resprate\":18,\"o2sat\":96,\n",
    "        \"sbp\":131,\"dbp\":90,\"n_diagnosis\":1,\"los_minutes\":60.0,\n",
    "        \"arrival_hour\":23,\"arrival_weekday\":\"Friday\"\n",
    "    }\n",
    "])[columns]  # garante ordem\n",
    "\n",
    "# 3) PAYLOAD: string JSON em orient=\"records\"\n",
    "payload = {\"data\": rows_df.to_json(orient=\"records\")}\n",
    "\n",
    "# -----------------------------\n",
    "# 3) Chamada REST\n",
    "# -----------------------------\n",
    "resp = requests.post(md.url + \"/predict\", json=payload, auth=auth)\n",
    "print(resp.status_code, resp.text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0e6cf40e-14cc-4256-a550-402887a60543",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---- DataFrame carregado do banco ----\n",
      "WARNING:py.warnings:/home/datascience/conda/automlx251_p311_cpu_x86_64_v2/lib/python3.11/site-packages/ads/model/deployment/model_deployment.py:302: UserWarning: Parameter `properties` was deprecated in 2.8.2 from ModelDeployment constructor and will be removed in 3.0.0. Please use `spec` or the builder pattern to initialize model deployment instance. Check: https://accelerated-data-science.readthedocs.io/en/latest/user_guide/model_registration/quick_start.html\n",
      "  warnings.warn(\n",
      "\n",
      "Status: State.ACTIVE\n",
      "Endpoint: https://modeldeployment.sa-saopaulo-1.oci.customer-oci.com/ocid1.datasciencemodeldeployment.oc1.sa-saopaulo-1.amaaaaaafioir7iafffqtvgm2mj24zw7vnnyamcxzhwqelkdpg5n5qw4jgkq/predict\n",
      "---- Resultado (todas as colunas + prediction) ----\n"
     ]
    },
    {
     "data": {
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       "<style scoped>\n",
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       "<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>stay_id</th>\n",
       "      <th>intime</th>\n",
       "      <th>outtime</th>\n",
       "      <th>gender</th>\n",
       "      <th>race</th>\n",
       "      <th>arrival_transport</th>\n",
       "      <th>disposition</th>\n",
       "      <th>admitted_from_ed</th>\n",
       "      <th>temperature</th>\n",
       "      <th>heartrate</th>\n",
       "      <th>resprate</th>\n",
       "      <th>o2sat</th>\n",
       "      <th>sbp</th>\n",
       "      <th>dbp</th>\n",
       "      <th>n_diagnosis</th>\n",
       "      <th>split</th>\n",
       "      <th>los_minutes</th>\n",
       "      <th>arrival_hour</th>\n",
       "      <th>arrival_weekday</th>\n",
       "      <th>prediction</th>\n",
       "      <th>prediction_class</th>\n",
       "      <th>match</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10001217</td>\n",
       "      <td>24597018.0</td>\n",
       "      <td>39866888</td>\n",
       "      <td>2157-11-18 17:38:00</td>\n",
       "      <td>2157-11-19 01:24:00</td>\n",
       "      <td>F</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>99.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>2</td>\n",
       "      <td>test</td>\n",
       "      <td>466.000000</td>\n",
       "      <td>17</td>\n",
       "      <td>Friday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10001217</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39300221</td>\n",
       "      <td>2157-11-29 19:28:00</td>\n",
       "      <td>2157-11-29 21:22:00</td>\n",
       "      <td>F</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>HOME</td>\n",
       "      <td>0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>19</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10014078</td>\n",
       "      <td>25809882.0</td>\n",
       "      <td>38676365</td>\n",
       "      <td>2166-08-21 21:39:00</td>\n",
       "      <td>2166-08-22 00:36:00</td>\n",
       "      <td>F</td>\n",
       "      <td>UNABLE TO OBTAIN</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>177.000000</td>\n",
       "      <td>21</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10037928</td>\n",
       "      <td>23721604.0</td>\n",
       "      <td>32259566</td>\n",
       "      <td>2179-03-27 14:15:00</td>\n",
       "      <td>2179-03-27 19:48:00</td>\n",
       "      <td>F</td>\n",
       "      <td>HISPANIC/LATINO - CUBAN</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>99.8</td>\n",
       "      <td>97.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>333.000000</td>\n",
       "      <td>14</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10037928</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32891808</td>\n",
       "      <td>2178-01-24 21:23:00</td>\n",
       "      <td>2178-01-24 23:59:00</td>\n",
       "      <td>F</td>\n",
       "      <td>HISPANIC/LATINO - CUBAN</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>HOME</td>\n",
       "      <td>0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>4</td>\n",
       "      <td>test</td>\n",
       "      <td>156.000000</td>\n",
       "      <td>21</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10037928</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34992024</td>\n",
       "      <td>2183-11-28 17:19:00</td>\n",
       "      <td>2183-11-28 23:57:00</td>\n",
       "      <td>F</td>\n",
       "      <td>HISPANIC/LATINO - CUBAN</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>HOME</td>\n",
       "      <td>0</td>\n",
       "      <td>36.5</td>\n",
       "      <td>95.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>6</td>\n",
       "      <td>test</td>\n",
       "      <td>398.000000</td>\n",
       "      <td>17</td>\n",
       "      <td>Friday</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10037928</td>\n",
       "      <td>29802992.0</td>\n",
       "      <td>37953392</td>\n",
       "      <td>2179-07-24 18:21:00</td>\n",
       "      <td>2179-07-25 01:17:00</td>\n",
       "      <td>F</td>\n",
       "      <td>HISPANIC/LATINO - CUBAN</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.3</td>\n",
       "      <td>76.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>144.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>6</td>\n",
       "      <td>test</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>18</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10037928</td>\n",
       "      <td>22228639.0</td>\n",
       "      <td>35156583</td>\n",
       "      <td>2183-08-03 19:27:00</td>\n",
       "      <td>2183-08-04 16:07:00</td>\n",
       "      <td>F</td>\n",
       "      <td>HISPANIC/LATINO - CUBAN</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>HOME</td>\n",
       "      <td>1</td>\n",
       "      <td>97.8</td>\n",
       "      <td>75.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>3</td>\n",
       "      <td>test</td>\n",
       "      <td>1240.000000</td>\n",
       "      <td>19</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10037928</td>\n",
       "      <td>22490490.0</td>\n",
       "      <td>38207210</td>\n",
       "      <td>2177-07-14 14:52:00</td>\n",
       "      <td>2177-07-14 20:38:00</td>\n",
       "      <td>F</td>\n",
       "      <td>HISPANIC/LATINO - CUBAN</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.2</td>\n",
       "      <td>72.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>2</td>\n",
       "      <td>test</td>\n",
       "      <td>346.000000</td>\n",
       "      <td>14</td>\n",
       "      <td>Monday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10037928</td>\n",
       "      <td>24885579.0</td>\n",
       "      <td>37483564</td>\n",
       "      <td>2182-04-28 17:25:00</td>\n",
       "      <td>2182-04-29 07:49:00</td>\n",
       "      <td>F</td>\n",
       "      <td>HISPANIC/LATINO - CUBAN</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.2</td>\n",
       "      <td>105.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>864.000000</td>\n",
       "      <td>17</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10037928</td>\n",
       "      <td>24656677.0</td>\n",
       "      <td>32443787</td>\n",
       "      <td>2178-12-21 03:17:00</td>\n",
       "      <td>2178-12-21 05:30:41</td>\n",
       "      <td>F</td>\n",
       "      <td>HISPANIC/LATINO - CUBAN</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.1</td>\n",
       "      <td>130.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>179.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>133.683333</td>\n",
       "      <td>3</td>\n",
       "      <td>Monday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>10037928</td>\n",
       "      <td>22326517.0</td>\n",
       "      <td>39740242</td>\n",
       "      <td>2177-12-21 16:49:00</td>\n",
       "      <td>2177-12-21 22:26:00</td>\n",
       "      <td>F</td>\n",
       "      <td>HISPANIC/LATINO - CUBAN</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.7</td>\n",
       "      <td>108.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>151.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>3</td>\n",
       "      <td>test</td>\n",
       "      <td>337.000000</td>\n",
       "      <td>16</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>10037928</td>\n",
       "      <td>24225421.0</td>\n",
       "      <td>34478228</td>\n",
       "      <td>2178-09-28 20:29:00</td>\n",
       "      <td>2178-09-29 00:43:00</td>\n",
       "      <td>F</td>\n",
       "      <td>HISPANIC/LATINO - CUBAN</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>97.6</td>\n",
       "      <td>96.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>3</td>\n",
       "      <td>test</td>\n",
       "      <td>254.000000</td>\n",
       "      <td>20</td>\n",
       "      <td>Monday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>10037928</td>\n",
       "      <td>20192635.0</td>\n",
       "      <td>37036523</td>\n",
       "      <td>2177-09-04 06:29:00</td>\n",
       "      <td>2177-09-04 12:06:40</td>\n",
       "      <td>F</td>\n",
       "      <td>HISPANIC/LATINO - CUBAN</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>test</td>\n",
       "      <td>337.666667</td>\n",
       "      <td>6</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>10019003</td>\n",
       "      <td>27525946.0</td>\n",
       "      <td>38260469</td>\n",
       "      <td>2153-04-12 13:03:00</td>\n",
       "      <td>2153-04-12 21:40:00</td>\n",
       "      <td>F</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>99.1</td>\n",
       "      <td>96.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>517.000000</td>\n",
       "      <td>13</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>10019003</td>\n",
       "      <td>29279905.0</td>\n",
       "      <td>31254712</td>\n",
       "      <td>2153-03-27 21:28:00</td>\n",
       "      <td>2153-03-28 02:21:00</td>\n",
       "      <td>F</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.4</td>\n",
       "      <td>96.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>4</td>\n",
       "      <td>test</td>\n",
       "      <td>293.000000</td>\n",
       "      <td>21</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10019003</td>\n",
       "      <td>26529390.0</td>\n",
       "      <td>38020791</td>\n",
       "      <td>2155-05-17 21:03:00</td>\n",
       "      <td>2155-05-18 00:03:15</td>\n",
       "      <td>F</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.1</td>\n",
       "      <td>97.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>180.250000</td>\n",
       "      <td>21</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>10019003</td>\n",
       "      <td>26703331.0</td>\n",
       "      <td>35568186</td>\n",
       "      <td>2155-06-10 20:37:00</td>\n",
       "      <td>2155-06-10 23:10:36</td>\n",
       "      <td>F</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>97.8</td>\n",
       "      <td>92.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>3</td>\n",
       "      <td>test</td>\n",
       "      <td>153.600000</td>\n",
       "      <td>20</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>10019003</td>\n",
       "      <td>21457723.0</td>\n",
       "      <td>36686656</td>\n",
       "      <td>2155-07-10 12:46:00</td>\n",
       "      <td>2155-07-10 17:48:57</td>\n",
       "      <td>F</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.6</td>\n",
       "      <td>98.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>105.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>2</td>\n",
       "      <td>test</td>\n",
       "      <td>302.950000</td>\n",
       "      <td>12</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>10003400</td>\n",
       "      <td>22390287.0</td>\n",
       "      <td>34922474</td>\n",
       "      <td>2137-02-07 13:06:00</td>\n",
       "      <td>2137-02-07 21:44:00</td>\n",
       "      <td>F</td>\n",
       "      <td>BLACK/AFRICAN AMERICAN</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.8</td>\n",
       "      <td>124.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>3</td>\n",
       "      <td>test</td>\n",
       "      <td>518.000000</td>\n",
       "      <td>13</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>10003400</td>\n",
       "      <td>26467376.0</td>\n",
       "      <td>33678912</td>\n",
       "      <td>2136-12-09 13:16:00</td>\n",
       "      <td>2136-12-09 14:45:10</td>\n",
       "      <td>F</td>\n",
       "      <td>BLACK/AFRICAN AMERICAN</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.3</td>\n",
       "      <td>157.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>2</td>\n",
       "      <td>test</td>\n",
       "      <td>89.166667</td>\n",
       "      <td>13</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>10003400</td>\n",
       "      <td>27296885.0</td>\n",
       "      <td>36976997</td>\n",
       "      <td>2136-12-31 13:41:00</td>\n",
       "      <td>2137-01-01 00:35:00</td>\n",
       "      <td>F</td>\n",
       "      <td>BLACK/AFRICAN AMERICAN</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>97.7</td>\n",
       "      <td>91.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>2</td>\n",
       "      <td>test</td>\n",
       "      <td>654.000000</td>\n",
       "      <td>13</td>\n",
       "      <td>Monday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>10003400</td>\n",
       "      <td>26090619.0</td>\n",
       "      <td>33347721</td>\n",
       "      <td>2134-06-05 21:42:00</td>\n",
       "      <td>2134-06-06 03:44:00</td>\n",
       "      <td>F</td>\n",
       "      <td>BLACK/AFRICAN AMERICAN</td>\n",
       "      <td>OTHER</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>97.3</td>\n",
       "      <td>43.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>4</td>\n",
       "      <td>test</td>\n",
       "      <td>362.000000</td>\n",
       "      <td>21</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>10003400</td>\n",
       "      <td>29483621.0</td>\n",
       "      <td>34948767</td>\n",
       "      <td>2136-11-04 16:08:00</td>\n",
       "      <td>2136-11-04 22:12:00</td>\n",
       "      <td>F</td>\n",
       "      <td>BLACK/AFRICAN AMERICAN</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>99.9</td>\n",
       "      <td>86.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>2</td>\n",
       "      <td>test</td>\n",
       "      <td>364.000000</td>\n",
       "      <td>16</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>10002930</td>\n",
       "      <td>28697806.0</td>\n",
       "      <td>32272346</td>\n",
       "      <td>2200-06-04 16:38:00</td>\n",
       "      <td>2200-06-05 10:26:00</td>\n",
       "      <td>F</td>\n",
       "      <td>BLACK/AFRICAN AMERICAN</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>HOME</td>\n",
       "      <td>1</td>\n",
       "      <td>97.3</td>\n",
       "      <td>89.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>3</td>\n",
       "      <td>test</td>\n",
       "      <td>1068.000000</td>\n",
       "      <td>16</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>10002930</td>\n",
       "      <td>25696644.0</td>\n",
       "      <td>31579293</td>\n",
       "      <td>2196-04-14 05:55:00</td>\n",
       "      <td>2196-04-14 13:40:00</td>\n",
       "      <td>F</td>\n",
       "      <td>BLACK/AFRICAN AMERICAN</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>95.6</td>\n",
       "      <td>89.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>3</td>\n",
       "      <td>test</td>\n",
       "      <td>465.000000</td>\n",
       "      <td>5</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>10002930</td>\n",
       "      <td>20282368.0</td>\n",
       "      <td>39266792</td>\n",
       "      <td>2201-03-23 12:04:00</td>\n",
       "      <td>2201-03-26 14:24:00</td>\n",
       "      <td>F</td>\n",
       "      <td>BLACK/AFRICAN AMERICAN</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>TRANSFER</td>\n",
       "      <td>1</td>\n",
       "      <td>98.1</td>\n",
       "      <td>76.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>181.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>3</td>\n",
       "      <td>test</td>\n",
       "      <td>4460.000000</td>\n",
       "      <td>12</td>\n",
       "      <td>Monday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>10002930</td>\n",
       "      <td>25922998.0</td>\n",
       "      <td>30193781</td>\n",
       "      <td>2198-04-17 11:42:00</td>\n",
       "      <td>2198-04-17 21:24:00</td>\n",
       "      <td>F</td>\n",
       "      <td>BLACK/AFRICAN AMERICAN</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.2</td>\n",
       "      <td>88.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>3</td>\n",
       "      <td>test</td>\n",
       "      <td>582.000000</td>\n",
       "      <td>11</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>10002930</td>\n",
       "      <td>28477649.0</td>\n",
       "      <td>38615683</td>\n",
       "      <td>2197-04-07 03:20:00</td>\n",
       "      <td>2197-04-07 06:56:40</td>\n",
       "      <td>F</td>\n",
       "      <td>BLACK/AFRICAN AMERICAN</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>97.5</td>\n",
       "      <td>108.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>154.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>216.666667</td>\n",
       "      <td>3</td>\n",
       "      <td>Friday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>10002930</td>\n",
       "      <td>25282382.0</td>\n",
       "      <td>35540249</td>\n",
       "      <td>2197-04-16 22:57:00</td>\n",
       "      <td>2197-04-17 09:48:00</td>\n",
       "      <td>F</td>\n",
       "      <td>BLACK/AFRICAN AMERICAN</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>HOME</td>\n",
       "      <td>1</td>\n",
       "      <td>98.5</td>\n",
       "      <td>110.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>3</td>\n",
       "      <td>test</td>\n",
       "      <td>651.000000</td>\n",
       "      <td>22</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>10002930</td>\n",
       "      <td>23720373.0</td>\n",
       "      <td>35114287</td>\n",
       "      <td>2199-02-17 14:32:00</td>\n",
       "      <td>2199-02-19 13:38:00</td>\n",
       "      <td>F</td>\n",
       "      <td>BLACK/AFRICAN AMERICAN</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>TRANSFER</td>\n",
       "      <td>1</td>\n",
       "      <td>98.9</td>\n",
       "      <td>102.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>4</td>\n",
       "      <td>test</td>\n",
       "      <td>2826.000000</td>\n",
       "      <td>14</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>10002930</td>\n",
       "      <td>20846853.0</td>\n",
       "      <td>39910144</td>\n",
       "      <td>2201-02-12 15:11:00</td>\n",
       "      <td>2201-02-13 11:11:00</td>\n",
       "      <td>F</td>\n",
       "      <td>BLACK/AFRICAN AMERICAN</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>HOME</td>\n",
       "      <td>1</td>\n",
       "      <td>97.7</td>\n",
       "      <td>103.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>3</td>\n",
       "      <td>test</td>\n",
       "      <td>1200.000000</td>\n",
       "      <td>15</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>10021938</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38449411</td>\n",
       "      <td>2181-09-02 19:21:00</td>\n",
       "      <td>2181-09-03 01:49:00</td>\n",
       "      <td>M</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>HOME</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>388.000000</td>\n",
       "      <td>19</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>10021938</td>\n",
       "      <td>23112364.0</td>\n",
       "      <td>38890884</td>\n",
       "      <td>2181-10-12 20:17:00</td>\n",
       "      <td>2181-10-13 02:52:00</td>\n",
       "      <td>M</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>99.8</td>\n",
       "      <td>110.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>395.000000</td>\n",
       "      <td>20</td>\n",
       "      <td>Friday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>10021938</td>\n",
       "      <td>27154822.0</td>\n",
       "      <td>32204198</td>\n",
       "      <td>2181-10-25 09:23:00</td>\n",
       "      <td>2181-10-25 11:35:00</td>\n",
       "      <td>M</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.4</td>\n",
       "      <td>89.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>217.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>132.000000</td>\n",
       "      <td>9</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>10005866</td>\n",
       "      <td>27167814.0</td>\n",
       "      <td>30804580</td>\n",
       "      <td>2148-03-10 04:46:00</td>\n",
       "      <td>2148-03-10 16:18:48</td>\n",
       "      <td>M</td>\n",
       "      <td>PORTUGUESE</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>97.4</td>\n",
       "      <td>66.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>692.800000</td>\n",
       "      <td>4</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>10005866</td>\n",
       "      <td>26134779.0</td>\n",
       "      <td>31806264</td>\n",
       "      <td>2149-09-12 15:31:00</td>\n",
       "      <td>2149-09-13 09:02:00</td>\n",
       "      <td>M</td>\n",
       "      <td>PORTUGUESE</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.2</td>\n",
       "      <td>84.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>175.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>1051.000000</td>\n",
       "      <td>15</td>\n",
       "      <td>Friday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>10005866</td>\n",
       "      <td>22589518.0</td>\n",
       "      <td>32537287</td>\n",
       "      <td>2149-02-11 08:52:00</td>\n",
       "      <td>2149-02-11 23:09:00</td>\n",
       "      <td>M</td>\n",
       "      <td>PORTUGUESE</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>157.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>857.000000</td>\n",
       "      <td>8</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>10005866</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31023359</td>\n",
       "      <td>2149-09-28 01:53:00</td>\n",
       "      <td>2149-09-28 16:26:00</td>\n",
       "      <td>M</td>\n",
       "      <td>PORTUGUESE</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>HOME</td>\n",
       "      <td>0</td>\n",
       "      <td>97.2</td>\n",
       "      <td>88.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>163.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>4</td>\n",
       "      <td>test</td>\n",
       "      <td>873.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>10005866</td>\n",
       "      <td>21636229.0</td>\n",
       "      <td>30225689</td>\n",
       "      <td>2149-09-20 05:50:00</td>\n",
       "      <td>2149-09-20 15:53:00</td>\n",
       "      <td>M</td>\n",
       "      <td>PORTUGUESE</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>97.6</td>\n",
       "      <td>72.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>163.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>603.000000</td>\n",
       "      <td>5</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>10005866</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32281632</td>\n",
       "      <td>2148-06-13 08:36:00</td>\n",
       "      <td>2148-06-13 17:30:00</td>\n",
       "      <td>M</td>\n",
       "      <td>PORTUGUESE</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>TRANSFER</td>\n",
       "      <td>0</td>\n",
       "      <td>97.9</td>\n",
       "      <td>63.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>149.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>534.000000</td>\n",
       "      <td>8</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>10005866</td>\n",
       "      <td>23514107.0</td>\n",
       "      <td>35681380</td>\n",
       "      <td>2149-06-20 10:20:00</td>\n",
       "      <td>2149-06-20 20:59:00</td>\n",
       "      <td>M</td>\n",
       "      <td>PORTUGUESE</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>639.000000</td>\n",
       "      <td>10</td>\n",
       "      <td>Friday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>10005866</td>\n",
       "      <td>26158160.0</td>\n",
       "      <td>34558830</td>\n",
       "      <td>2146-06-05 22:26:00</td>\n",
       "      <td>2146-06-06 01:45:00</td>\n",
       "      <td>M</td>\n",
       "      <td>PORTUGUESE</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>22</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>10005866</td>\n",
       "      <td>20364112.0</td>\n",
       "      <td>31121963</td>\n",
       "      <td>2149-10-01 02:07:00</td>\n",
       "      <td>2149-10-01 18:56:59</td>\n",
       "      <td>M</td>\n",
       "      <td>PORTUGUESE</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.8</td>\n",
       "      <td>106.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>163.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2</td>\n",
       "      <td>test</td>\n",
       "      <td>1009.983333</td>\n",
       "      <td>2</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>10026406</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39571461</td>\n",
       "      <td>2129-11-25 19:02:00</td>\n",
       "      <td>2129-11-26 00:46:00</td>\n",
       "      <td>M</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>HOME</td>\n",
       "      <td>0</td>\n",
       "      <td>98.7</td>\n",
       "      <td>118.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>344.000000</td>\n",
       "      <td>19</td>\n",
       "      <td>Friday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>10026406</td>\n",
       "      <td>25260176.0</td>\n",
       "      <td>37202404</td>\n",
       "      <td>2129-01-02 23:41:00</td>\n",
       "      <td>2129-01-03 18:33:00</td>\n",
       "      <td>M</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>ADMITTED</td>\n",
       "      <td>1</td>\n",
       "      <td>98.0</td>\n",
       "      <td>105.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>153.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>4</td>\n",
       "      <td>test</td>\n",
       "      <td>1132.000000</td>\n",
       "      <td>23</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>10026406</td>\n",
       "      <td>25166559.0</td>\n",
       "      <td>38237602</td>\n",
       "      <td>2133-03-01 16:42:00</td>\n",
       "      <td>2133-03-04 17:05:00</td>\n",
       "      <td>M</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>WALK IN</td>\n",
       "      <td>HOME</td>\n",
       "      <td>1</td>\n",
       "      <td>97.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>133.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>4</td>\n",
       "      <td>test</td>\n",
       "      <td>4343.000000</td>\n",
       "      <td>16</td>\n",
       "      <td>Sunday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>10025463</td>\n",
       "      <td>24470193.0</td>\n",
       "      <td>35470228</td>\n",
       "      <td>2137-10-08 18:16:00</td>\n",
       "      <td>2137-10-08 21:20:50</td>\n",
       "      <td>M</td>\n",
       "      <td>WHITE</td>\n",
       "      <td>AMBULANCE</td>\n",
       "      <td>OTHER</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>184.833333</td>\n",
       "      <td>18</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    subject_id     hadm_id   stay_id              intime             outtime  \\\n",
       "0     10001217  24597018.0  39866888 2157-11-18 17:38:00 2157-11-19 01:24:00   \n",
       "1     10001217         NaN  39300221 2157-11-29 19:28:00 2157-11-29 21:22:00   \n",
       "2     10014078  25809882.0  38676365 2166-08-21 21:39:00 2166-08-22 00:36:00   \n",
       "3     10037928  23721604.0  32259566 2179-03-27 14:15:00 2179-03-27 19:48:00   \n",
       "4     10037928         NaN  32891808 2178-01-24 21:23:00 2178-01-24 23:59:00   \n",
       "5     10037928         NaN  34992024 2183-11-28 17:19:00 2183-11-28 23:57:00   \n",
       "6     10037928  29802992.0  37953392 2179-07-24 18:21:00 2179-07-25 01:17:00   \n",
       "7     10037928  22228639.0  35156583 2183-08-03 19:27:00 2183-08-04 16:07:00   \n",
       "8     10037928  22490490.0  38207210 2177-07-14 14:52:00 2177-07-14 20:38:00   \n",
       "9     10037928  24885579.0  37483564 2182-04-28 17:25:00 2182-04-29 07:49:00   \n",
       "10    10037928  24656677.0  32443787 2178-12-21 03:17:00 2178-12-21 05:30:41   \n",
       "11    10037928  22326517.0  39740242 2177-12-21 16:49:00 2177-12-21 22:26:00   \n",
       "12    10037928  24225421.0  34478228 2178-09-28 20:29:00 2178-09-29 00:43:00   \n",
       "13    10037928  20192635.0  37036523 2177-09-04 06:29:00 2177-09-04 12:06:40   \n",
       "14    10019003  27525946.0  38260469 2153-04-12 13:03:00 2153-04-12 21:40:00   \n",
       "15    10019003  29279905.0  31254712 2153-03-27 21:28:00 2153-03-28 02:21:00   \n",
       "16    10019003  26529390.0  38020791 2155-05-17 21:03:00 2155-05-18 00:03:15   \n",
       "17    10019003  26703331.0  35568186 2155-06-10 20:37:00 2155-06-10 23:10:36   \n",
       "18    10019003  21457723.0  36686656 2155-07-10 12:46:00 2155-07-10 17:48:57   \n",
       "19    10003400  22390287.0  34922474 2137-02-07 13:06:00 2137-02-07 21:44:00   \n",
       "20    10003400  26467376.0  33678912 2136-12-09 13:16:00 2136-12-09 14:45:10   \n",
       "21    10003400  27296885.0  36976997 2136-12-31 13:41:00 2137-01-01 00:35:00   \n",
       "22    10003400  26090619.0  33347721 2134-06-05 21:42:00 2134-06-06 03:44:00   \n",
       "23    10003400  29483621.0  34948767 2136-11-04 16:08:00 2136-11-04 22:12:00   \n",
       "24    10002930  28697806.0  32272346 2200-06-04 16:38:00 2200-06-05 10:26:00   \n",
       "25    10002930  25696644.0  31579293 2196-04-14 05:55:00 2196-04-14 13:40:00   \n",
       "26    10002930  20282368.0  39266792 2201-03-23 12:04:00 2201-03-26 14:24:00   \n",
       "27    10002930  25922998.0  30193781 2198-04-17 11:42:00 2198-04-17 21:24:00   \n",
       "28    10002930  28477649.0  38615683 2197-04-07 03:20:00 2197-04-07 06:56:40   \n",
       "29    10002930  25282382.0  35540249 2197-04-16 22:57:00 2197-04-17 09:48:00   \n",
       "30    10002930  23720373.0  35114287 2199-02-17 14:32:00 2199-02-19 13:38:00   \n",
       "31    10002930  20846853.0  39910144 2201-02-12 15:11:00 2201-02-13 11:11:00   \n",
       "32    10021938         NaN  38449411 2181-09-02 19:21:00 2181-09-03 01:49:00   \n",
       "33    10021938  23112364.0  38890884 2181-10-12 20:17:00 2181-10-13 02:52:00   \n",
       "34    10021938  27154822.0  32204198 2181-10-25 09:23:00 2181-10-25 11:35:00   \n",
       "35    10005866  27167814.0  30804580 2148-03-10 04:46:00 2148-03-10 16:18:48   \n",
       "36    10005866  26134779.0  31806264 2149-09-12 15:31:00 2149-09-13 09:02:00   \n",
       "37    10005866  22589518.0  32537287 2149-02-11 08:52:00 2149-02-11 23:09:00   \n",
       "38    10005866         NaN  31023359 2149-09-28 01:53:00 2149-09-28 16:26:00   \n",
       "39    10005866  21636229.0  30225689 2149-09-20 05:50:00 2149-09-20 15:53:00   \n",
       "40    10005866         NaN  32281632 2148-06-13 08:36:00 2148-06-13 17:30:00   \n",
       "41    10005866  23514107.0  35681380 2149-06-20 10:20:00 2149-06-20 20:59:00   \n",
       "42    10005866  26158160.0  34558830 2146-06-05 22:26:00 2146-06-06 01:45:00   \n",
       "43    10005866  20364112.0  31121963 2149-10-01 02:07:00 2149-10-01 18:56:59   \n",
       "44    10026406         NaN  39571461 2129-11-25 19:02:00 2129-11-26 00:46:00   \n",
       "45    10026406  25260176.0  37202404 2129-01-02 23:41:00 2129-01-03 18:33:00   \n",
       "46    10026406  25166559.0  38237602 2133-03-01 16:42:00 2133-03-04 17:05:00   \n",
       "47    10025463  24470193.0  35470228 2137-10-08 18:16:00 2137-10-08 21:20:50   \n",
       "\n",
       "   gender                     race arrival_transport disposition  \\\n",
       "0       F                    WHITE           WALK IN    ADMITTED   \n",
       "1       F                    WHITE           WALK IN        HOME   \n",
       "2       F         UNABLE TO OBTAIN         AMBULANCE    ADMITTED   \n",
       "3       F  HISPANIC/LATINO - CUBAN         AMBULANCE    ADMITTED   \n",
       "4       F  HISPANIC/LATINO - CUBAN           WALK IN        HOME   \n",
       "5       F  HISPANIC/LATINO - CUBAN         AMBULANCE        HOME   \n",
       "6       F  HISPANIC/LATINO - CUBAN         AMBULANCE    ADMITTED   \n",
       "7       F  HISPANIC/LATINO - CUBAN         AMBULANCE        HOME   \n",
       "8       F  HISPANIC/LATINO - CUBAN         AMBULANCE    ADMITTED   \n",
       "9       F  HISPANIC/LATINO - CUBAN           WALK IN    ADMITTED   \n",
       "10      F  HISPANIC/LATINO - CUBAN         AMBULANCE    ADMITTED   \n",
       "11      F  HISPANIC/LATINO - CUBAN           WALK IN    ADMITTED   \n",
       "12      F  HISPANIC/LATINO - CUBAN           WALK IN    ADMITTED   \n",
       "13      F  HISPANIC/LATINO - CUBAN         AMBULANCE    ADMITTED   \n",
       "14      F                    WHITE           WALK IN    ADMITTED   \n",
       "15      F                    WHITE         AMBULANCE    ADMITTED   \n",
       "16      F                    WHITE           WALK IN    ADMITTED   \n",
       "17      F                    WHITE         AMBULANCE    ADMITTED   \n",
       "18      F                    WHITE         AMBULANCE    ADMITTED   \n",
       "19      F   BLACK/AFRICAN AMERICAN         AMBULANCE    ADMITTED   \n",
       "20      F   BLACK/AFRICAN AMERICAN         AMBULANCE    ADMITTED   \n",
       "21      F   BLACK/AFRICAN AMERICAN         AMBULANCE    ADMITTED   \n",
       "22      F   BLACK/AFRICAN AMERICAN             OTHER    ADMITTED   \n",
       "23      F   BLACK/AFRICAN AMERICAN           WALK IN    ADMITTED   \n",
       "24      F   BLACK/AFRICAN AMERICAN         AMBULANCE        HOME   \n",
       "25      F   BLACK/AFRICAN AMERICAN           UNKNOWN    ADMITTED   \n",
       "26      F   BLACK/AFRICAN AMERICAN         AMBULANCE    TRANSFER   \n",
       "27      F   BLACK/AFRICAN AMERICAN           WALK IN    ADMITTED   \n",
       "28      F   BLACK/AFRICAN AMERICAN         AMBULANCE    ADMITTED   \n",
       "29      F   BLACK/AFRICAN AMERICAN           WALK IN        HOME   \n",
       "30      F   BLACK/AFRICAN AMERICAN         AMBULANCE    TRANSFER   \n",
       "31      F   BLACK/AFRICAN AMERICAN         AMBULANCE        HOME   \n",
       "32      M                    WHITE         AMBULANCE        HOME   \n",
       "33      M                    WHITE         AMBULANCE    ADMITTED   \n",
       "34      M                    WHITE         AMBULANCE    ADMITTED   \n",
       "35      M               PORTUGUESE         AMBULANCE    ADMITTED   \n",
       "36      M               PORTUGUESE           WALK IN    ADMITTED   \n",
       "37      M               PORTUGUESE           WALK IN    ADMITTED   \n",
       "38      M               PORTUGUESE           WALK IN        HOME   \n",
       "39      M               PORTUGUESE           WALK IN    ADMITTED   \n",
       "40      M               PORTUGUESE         AMBULANCE    TRANSFER   \n",
       "41      M               PORTUGUESE           WALK IN    ADMITTED   \n",
       "42      M               PORTUGUESE         AMBULANCE    ADMITTED   \n",
       "43      M               PORTUGUESE         AMBULANCE    ADMITTED   \n",
       "44      M                    WHITE           WALK IN        HOME   \n",
       "45      M                    WHITE         AMBULANCE    ADMITTED   \n",
       "46      M                    WHITE           WALK IN        HOME   \n",
       "47      M                    WHITE         AMBULANCE       OTHER   \n",
       "\n",
       "    admitted_from_ed  temperature  heartrate  resprate  o2sat    sbp    dbp  \\\n",
       "0                  1         99.0       81.0      16.0   97.0  160.0  102.0   \n",
       "1                  0         98.0       75.0      20.0   98.0  132.0   95.0   \n",
       "2                  1          NaN        NaN       NaN    NaN    NaN    NaN   \n",
       "3                  1         99.8       97.0      32.0   88.0  176.0   86.0   \n",
       "4                  0         97.0       81.0      18.0   99.0  161.0   55.0   \n",
       "5                  0         36.5       95.0      18.0   98.0  150.0   56.0   \n",
       "6                  1         98.3       76.0      16.0   98.0  144.0   56.0   \n",
       "7                  1         97.8       75.0      16.0   95.0  159.0   60.0   \n",
       "8                  1         98.2       72.0      16.0   96.0  126.0   43.0   \n",
       "9                  1         98.2      105.0      24.0   96.0  177.0   69.0   \n",
       "10                 1         98.1      130.0      15.0   95.0  179.0   69.0   \n",
       "11                 1         98.7      108.0      22.0   98.0  151.0   55.0   \n",
       "12                 1         97.6       96.0      16.0   94.0  121.0   65.0   \n",
       "13                 1          NaN        NaN       NaN    NaN    NaN    NaN   \n",
       "14                 1         99.1       96.0      17.0   96.0  114.0   66.0   \n",
       "15                 1         98.4       96.0      15.0   97.0   98.0   56.0   \n",
       "16                 1         98.1       97.0      16.0   93.0  117.0   60.0   \n",
       "17                 1         97.8       92.0      26.0   95.0  116.0   57.0   \n",
       "18                 1         98.6       98.0      16.0   97.0  105.0   43.0   \n",
       "19                 1         98.8      124.0      16.0   98.0  136.0   82.0   \n",
       "20                 1         98.3      157.0      18.0  100.0  115.0   81.0   \n",
       "21                 1         97.7       91.0      16.0  100.0  111.0   68.0   \n",
       "22                 1         97.3       43.0      16.0   99.0  140.0  100.0   \n",
       "23                 1         99.9       86.0      18.0  100.0  142.0   92.0   \n",
       "24                 1         97.3       89.0      16.0  100.0  106.0   61.0   \n",
       "25                 1         95.6       89.0      16.0  100.0  106.0   65.0   \n",
       "26                 1         98.1       76.0      18.0  100.0  181.0   94.0   \n",
       "27                 1         98.2       88.0      16.0  100.0  150.0   98.0   \n",
       "28                 1         97.5      108.0      16.0  100.0  154.0   92.0   \n",
       "29                 1         98.5      110.0      18.0  100.0  123.0   67.0   \n",
       "30                 1         98.9      102.0      20.0  100.0  180.0   85.0   \n",
       "31                 1         97.7      103.0      18.0   97.0  137.0   87.0   \n",
       "32                 0          NaN        NaN       NaN    NaN    NaN    NaN   \n",
       "33                 1         99.8      110.0      18.0   93.0  178.0   85.0   \n",
       "34                 1         98.4       89.0      18.0   97.0  217.0  116.0   \n",
       "35                 1         97.4       66.0      18.0   99.0  111.0   68.0   \n",
       "36                 1         98.2       84.0      18.0  100.0  175.0   80.0   \n",
       "37                 1         98.0       82.0      22.0  100.0  157.0   82.0   \n",
       "38                 0         97.2       88.0      18.0  100.0  163.0   89.0   \n",
       "39                 1         97.6       72.0      16.0  100.0  163.0   81.0   \n",
       "40                 0         97.9       63.0      18.0   99.0  149.0   72.0   \n",
       "41                 1         98.0       76.0      18.0   99.0  147.0   92.0   \n",
       "42                 1          NaN        NaN       NaN    NaN    NaN    NaN   \n",
       "43                 1         98.8      106.0      20.0  100.0  163.0  103.0   \n",
       "44                 0         98.7      118.0      22.0   99.0  131.0   89.0   \n",
       "45                 1         98.0      105.0      20.0   98.0  153.0   77.0   \n",
       "46                 1         97.0       98.0      20.0   99.0  133.0  110.0   \n",
       "47                 1          NaN        NaN       NaN    NaN    NaN    NaN   \n",
       "\n",
       "    n_diagnosis split  los_minutes  arrival_hour arrival_weekday  prediction  \\\n",
       "0             2  test   466.000000            17          Friday           1   \n",
       "1             1  test   114.000000            19         Tuesday           1   \n",
       "2             1  test   177.000000            21        Thursday           1   \n",
       "3             1  test   333.000000            14        Saturday           1   \n",
       "4             4  test   156.000000            21        Saturday           1   \n",
       "5             6  test   398.000000            17          Friday           0   \n",
       "6             6  test   416.000000            18        Saturday           1   \n",
       "7             3  test  1240.000000            19          Sunday           1   \n",
       "8             2  test   346.000000            14          Monday           1   \n",
       "9             1  test   864.000000            17          Sunday           1   \n",
       "10            1  test   133.683333             3          Monday           1   \n",
       "11            3  test   337.000000            16          Sunday           1   \n",
       "12            3  test   254.000000            20          Monday           1   \n",
       "13            3  test   337.666667             6        Thursday           1   \n",
       "14            1  test   517.000000            13        Thursday           1   \n",
       "15            4  test   293.000000            21         Tuesday           1   \n",
       "16            1  test   180.250000            21        Saturday           1   \n",
       "17            3  test   153.600000            20         Tuesday           1   \n",
       "18            2  test   302.950000            12        Thursday           1   \n",
       "19            3  test   518.000000            13        Thursday           1   \n",
       "20            2  test    89.166667            13          Sunday           1   \n",
       "21            2  test   654.000000            13          Monday           1   \n",
       "22            4  test   362.000000            21        Saturday           1   \n",
       "23            2  test   364.000000            16          Sunday           0   \n",
       "24            3  test  1068.000000            16       Wednesday           1   \n",
       "25            3  test   465.000000             5        Thursday           1   \n",
       "26            3  test  4460.000000            12          Monday           1   \n",
       "27            3  test   582.000000            11         Tuesday           0   \n",
       "28            1  test   216.666667             3          Friday           1   \n",
       "29            3  test   651.000000            22          Sunday           1   \n",
       "30            4  test  2826.000000            14          Sunday           1   \n",
       "31            3  test  1200.000000            15        Thursday           1   \n",
       "32            1  test   388.000000            19          Sunday           1   \n",
       "33            1  test   395.000000            20          Friday           1   \n",
       "34            1  test   132.000000             9        Thursday           1   \n",
       "35            1  test   692.800000             4          Sunday           1   \n",
       "36            1  test  1051.000000            15          Friday           1   \n",
       "37            1  test   857.000000             8         Tuesday           1   \n",
       "38            4  test   873.000000             1          Sunday           1   \n",
       "39            1  test   603.000000             5        Saturday           1   \n",
       "40            1  test   534.000000             8        Thursday           1   \n",
       "41            1  test   639.000000            10          Friday           1   \n",
       "42            1  test   199.000000            22          Sunday           1   \n",
       "43            2  test  1009.983333             2       Wednesday           1   \n",
       "44            1  test   344.000000            19          Friday           1   \n",
       "45            4  test  1132.000000            23          Sunday           1   \n",
       "46            4  test  4343.000000            16          Sunday           1   \n",
       "47            1  test   184.833333            18         Tuesday           1   \n",
       "\n",
       "    prediction_class  match  \n",
       "0                  1   True  \n",
       "1                  1  False  \n",
       "2                  1   True  \n",
       "3                  1   True  \n",
       "4                  1  False  \n",
       "5                  0   True  \n",
       "6                  1   True  \n",
       "7                  1   True  \n",
       "8                  1   True  \n",
       "9                  1   True  \n",
       "10                 1   True  \n",
       "11                 1   True  \n",
       "12                 1   True  \n",
       "13                 1   True  \n",
       "14                 1   True  \n",
       "15                 1   True  \n",
       "16                 1   True  \n",
       "17                 1   True  \n",
       "18                 1   True  \n",
       "19                 1   True  \n",
       "20                 1   True  \n",
       "21                 1   True  \n",
       "22                 1   True  \n",
       "23                 0  False  \n",
       "24                 1   True  \n",
       "25                 1   True  \n",
       "26                 1   True  \n",
       "27                 0  False  \n",
       "28                 1   True  \n",
       "29                 1   True  \n",
       "30                 1   True  \n",
       "31                 1   True  \n",
       "32                 1  False  \n",
       "33                 1   True  \n",
       "34                 1   True  \n",
       "35                 1   True  \n",
       "36                 1   True  \n",
       "37                 1   True  \n",
       "38                 1  False  \n",
       "39                 1   True  \n",
       "40                 1  False  \n",
       "41                 1   True  \n",
       "42                 1   True  \n",
       "43                 1   True  \n",
       "44                 1  False  \n",
       "45                 1   True  \n",
       "46                 1   True  \n",
       "47                 1   True  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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       "<table id=\"T_6feb9\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_6feb9_level0_col0\" class=\"col_heading level0 col0\" >subject_id</th>\n",
       "      <th id=\"T_6feb9_level0_col1\" class=\"col_heading level0 col1\" >hadm_id</th>\n",
       "      <th id=\"T_6feb9_level0_col2\" class=\"col_heading level0 col2\" >stay_id</th>\n",
       "      <th id=\"T_6feb9_level0_col3\" class=\"col_heading level0 col3\" >intime</th>\n",
       "      <th id=\"T_6feb9_level0_col4\" class=\"col_heading level0 col4\" >outtime</th>\n",
       "      <th id=\"T_6feb9_level0_col5\" class=\"col_heading level0 col5\" >gender</th>\n",
       "      <th id=\"T_6feb9_level0_col6\" class=\"col_heading level0 col6\" >race</th>\n",
       "      <th id=\"T_6feb9_level0_col7\" class=\"col_heading level0 col7\" >arrival_transport</th>\n",
       "      <th id=\"T_6feb9_level0_col8\" class=\"col_heading level0 col8\" >disposition</th>\n",
       "      <th id=\"T_6feb9_level0_col9\" class=\"col_heading level0 col9\" >admitted_from_ed</th>\n",
       "      <th id=\"T_6feb9_level0_col10\" class=\"col_heading level0 col10\" >temperature</th>\n",
       "      <th id=\"T_6feb9_level0_col11\" class=\"col_heading level0 col11\" >heartrate</th>\n",
       "      <th id=\"T_6feb9_level0_col12\" class=\"col_heading level0 col12\" >resprate</th>\n",
       "      <th id=\"T_6feb9_level0_col13\" class=\"col_heading level0 col13\" >o2sat</th>\n",
       "      <th id=\"T_6feb9_level0_col14\" class=\"col_heading level0 col14\" >sbp</th>\n",
       "      <th id=\"T_6feb9_level0_col15\" class=\"col_heading level0 col15\" >dbp</th>\n",
       "      <th id=\"T_6feb9_level0_col16\" class=\"col_heading level0 col16\" >n_diagnosis</th>\n",
       "      <th id=\"T_6feb9_level0_col17\" class=\"col_heading level0 col17\" >split</th>\n",
       "      <th id=\"T_6feb9_level0_col18\" class=\"col_heading level0 col18\" >los_minutes</th>\n",
       "      <th id=\"T_6feb9_level0_col19\" class=\"col_heading level0 col19\" >arrival_hour</th>\n",
       "      <th id=\"T_6feb9_level0_col20\" class=\"col_heading level0 col20\" >arrival_weekday</th>\n",
       "      <th id=\"T_6feb9_level0_col21\" class=\"col_heading level0 col21\" >prediction</th>\n",
       "      <th id=\"T_6feb9_level0_col22\" class=\"col_heading level0 col22\" >prediction_class</th>\n",
       "      <th id=\"T_6feb9_level0_col23\" class=\"col_heading level0 col23\" >match</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_6feb9_row0_col0\" class=\"data row0 col0\" >10001217</td>\n",
       "      <td id=\"T_6feb9_row0_col1\" class=\"data row0 col1\" >24597018.000000</td>\n",
       "      <td id=\"T_6feb9_row0_col2\" class=\"data row0 col2\" >39866888</td>\n",
       "      <td id=\"T_6feb9_row0_col3\" class=\"data row0 col3\" >2157-11-18 17:38:00</td>\n",
       "      <td id=\"T_6feb9_row0_col4\" class=\"data row0 col4\" >2157-11-19 01:24:00</td>\n",
       "      <td id=\"T_6feb9_row0_col5\" class=\"data row0 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row0_col6\" class=\"data row0 col6\" >WHITE</td>\n",
       "      <td id=\"T_6feb9_row0_col7\" class=\"data row0 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row0_col8\" class=\"data row0 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row0_col9\" class=\"data row0 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row0_col10\" class=\"data row0 col10\" >99.000000</td>\n",
       "      <td id=\"T_6feb9_row0_col11\" class=\"data row0 col11\" >81.000000</td>\n",
       "      <td id=\"T_6feb9_row0_col12\" class=\"data row0 col12\" >16.000000</td>\n",
       "      <td id=\"T_6feb9_row0_col13\" class=\"data row0 col13\" >97.000000</td>\n",
       "      <td id=\"T_6feb9_row0_col14\" class=\"data row0 col14\" >160.000000</td>\n",
       "      <td id=\"T_6feb9_row0_col15\" class=\"data row0 col15\" >102.000000</td>\n",
       "      <td id=\"T_6feb9_row0_col16\" class=\"data row0 col16\" >2</td>\n",
       "      <td id=\"T_6feb9_row0_col17\" class=\"data row0 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row0_col18\" class=\"data row0 col18\" >466.000000</td>\n",
       "      <td id=\"T_6feb9_row0_col19\" class=\"data row0 col19\" >17</td>\n",
       "      <td id=\"T_6feb9_row0_col20\" class=\"data row0 col20\" >Friday</td>\n",
       "      <td id=\"T_6feb9_row0_col21\" class=\"data row0 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row0_col22\" class=\"data row0 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row0_col23\" class=\"data row0 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_6feb9_row1_col0\" class=\"data row1 col0\" >10001217</td>\n",
       "      <td id=\"T_6feb9_row1_col1\" class=\"data row1 col1\" >nan</td>\n",
       "      <td id=\"T_6feb9_row1_col2\" class=\"data row1 col2\" >39300221</td>\n",
       "      <td id=\"T_6feb9_row1_col3\" class=\"data row1 col3\" >2157-11-29 19:28:00</td>\n",
       "      <td id=\"T_6feb9_row1_col4\" class=\"data row1 col4\" >2157-11-29 21:22:00</td>\n",
       "      <td id=\"T_6feb9_row1_col5\" class=\"data row1 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row1_col6\" class=\"data row1 col6\" >WHITE</td>\n",
       "      <td id=\"T_6feb9_row1_col7\" class=\"data row1 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row1_col8\" class=\"data row1 col8\" >HOME</td>\n",
       "      <td id=\"T_6feb9_row1_col9\" class=\"data row1 col9\" >0</td>\n",
       "      <td id=\"T_6feb9_row1_col10\" class=\"data row1 col10\" >98.000000</td>\n",
       "      <td id=\"T_6feb9_row1_col11\" class=\"data row1 col11\" >75.000000</td>\n",
       "      <td id=\"T_6feb9_row1_col12\" class=\"data row1 col12\" >20.000000</td>\n",
       "      <td id=\"T_6feb9_row1_col13\" class=\"data row1 col13\" >98.000000</td>\n",
       "      <td id=\"T_6feb9_row1_col14\" class=\"data row1 col14\" >132.000000</td>\n",
       "      <td id=\"T_6feb9_row1_col15\" class=\"data row1 col15\" >95.000000</td>\n",
       "      <td id=\"T_6feb9_row1_col16\" class=\"data row1 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row1_col17\" class=\"data row1 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row1_col18\" class=\"data row1 col18\" >114.000000</td>\n",
       "      <td id=\"T_6feb9_row1_col19\" class=\"data row1 col19\" >19</td>\n",
       "      <td id=\"T_6feb9_row1_col20\" class=\"data row1 col20\" >Tuesday</td>\n",
       "      <td id=\"T_6feb9_row1_col21\" class=\"data row1 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row1_col22\" class=\"data row1 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row1_col23\" class=\"data row1 col23\" >False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "      <td id=\"T_6feb9_row2_col0\" class=\"data row2 col0\" >10014078</td>\n",
       "      <td id=\"T_6feb9_row2_col1\" class=\"data row2 col1\" >25809882.000000</td>\n",
       "      <td id=\"T_6feb9_row2_col2\" class=\"data row2 col2\" >38676365</td>\n",
       "      <td id=\"T_6feb9_row2_col3\" class=\"data row2 col3\" >2166-08-21 21:39:00</td>\n",
       "      <td id=\"T_6feb9_row2_col4\" class=\"data row2 col4\" >2166-08-22 00:36:00</td>\n",
       "      <td id=\"T_6feb9_row2_col5\" class=\"data row2 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row2_col6\" class=\"data row2 col6\" >UNABLE TO OBTAIN</td>\n",
       "      <td id=\"T_6feb9_row2_col7\" class=\"data row2 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row2_col8\" class=\"data row2 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row2_col9\" class=\"data row2 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row2_col10\" class=\"data row2 col10\" >nan</td>\n",
       "      <td id=\"T_6feb9_row2_col11\" class=\"data row2 col11\" >nan</td>\n",
       "      <td id=\"T_6feb9_row2_col12\" class=\"data row2 col12\" >nan</td>\n",
       "      <td id=\"T_6feb9_row2_col13\" class=\"data row2 col13\" >nan</td>\n",
       "      <td id=\"T_6feb9_row2_col14\" class=\"data row2 col14\" >nan</td>\n",
       "      <td id=\"T_6feb9_row2_col15\" class=\"data row2 col15\" >nan</td>\n",
       "      <td id=\"T_6feb9_row2_col16\" class=\"data row2 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row2_col17\" class=\"data row2 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row2_col18\" class=\"data row2 col18\" >177.000000</td>\n",
       "      <td id=\"T_6feb9_row2_col19\" class=\"data row2 col19\" >21</td>\n",
       "      <td id=\"T_6feb9_row2_col20\" class=\"data row2 col20\" >Thursday</td>\n",
       "      <td id=\"T_6feb9_row2_col21\" class=\"data row2 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row2_col22\" class=\"data row2 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row2_col23\" class=\"data row2 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "      <td id=\"T_6feb9_row3_col0\" class=\"data row3 col0\" >10037928</td>\n",
       "      <td id=\"T_6feb9_row3_col1\" class=\"data row3 col1\" >23721604.000000</td>\n",
       "      <td id=\"T_6feb9_row3_col2\" class=\"data row3 col2\" >32259566</td>\n",
       "      <td id=\"T_6feb9_row3_col3\" class=\"data row3 col3\" >2179-03-27 14:15:00</td>\n",
       "      <td id=\"T_6feb9_row3_col4\" class=\"data row3 col4\" >2179-03-27 19:48:00</td>\n",
       "      <td id=\"T_6feb9_row3_col5\" class=\"data row3 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row3_col6\" class=\"data row3 col6\" >HISPANIC/LATINO - CUBAN</td>\n",
       "      <td id=\"T_6feb9_row3_col7\" class=\"data row3 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row3_col8\" class=\"data row3 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row3_col9\" class=\"data row3 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row3_col10\" class=\"data row3 col10\" >99.800000</td>\n",
       "      <td id=\"T_6feb9_row3_col11\" class=\"data row3 col11\" >97.000000</td>\n",
       "      <td id=\"T_6feb9_row3_col12\" class=\"data row3 col12\" >32.000000</td>\n",
       "      <td id=\"T_6feb9_row3_col13\" class=\"data row3 col13\" >88.000000</td>\n",
       "      <td id=\"T_6feb9_row3_col14\" class=\"data row3 col14\" >176.000000</td>\n",
       "      <td id=\"T_6feb9_row3_col15\" class=\"data row3 col15\" >86.000000</td>\n",
       "      <td id=\"T_6feb9_row3_col16\" class=\"data row3 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row3_col17\" class=\"data row3 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row3_col18\" class=\"data row3 col18\" >333.000000</td>\n",
       "      <td id=\"T_6feb9_row3_col19\" class=\"data row3 col19\" >14</td>\n",
       "      <td id=\"T_6feb9_row3_col20\" class=\"data row3 col20\" >Saturday</td>\n",
       "      <td id=\"T_6feb9_row3_col21\" class=\"data row3 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row3_col22\" class=\"data row3 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row3_col23\" class=\"data row3 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "      <td id=\"T_6feb9_row4_col0\" class=\"data row4 col0\" >10037928</td>\n",
       "      <td id=\"T_6feb9_row4_col1\" class=\"data row4 col1\" >nan</td>\n",
       "      <td id=\"T_6feb9_row4_col2\" class=\"data row4 col2\" >32891808</td>\n",
       "      <td id=\"T_6feb9_row4_col3\" class=\"data row4 col3\" >2178-01-24 21:23:00</td>\n",
       "      <td id=\"T_6feb9_row4_col4\" class=\"data row4 col4\" >2178-01-24 23:59:00</td>\n",
       "      <td id=\"T_6feb9_row4_col5\" class=\"data row4 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row4_col6\" class=\"data row4 col6\" >HISPANIC/LATINO - CUBAN</td>\n",
       "      <td id=\"T_6feb9_row4_col7\" class=\"data row4 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row4_col8\" class=\"data row4 col8\" >HOME</td>\n",
       "      <td id=\"T_6feb9_row4_col9\" class=\"data row4 col9\" >0</td>\n",
       "      <td id=\"T_6feb9_row4_col10\" class=\"data row4 col10\" >97.000000</td>\n",
       "      <td id=\"T_6feb9_row4_col11\" class=\"data row4 col11\" >81.000000</td>\n",
       "      <td id=\"T_6feb9_row4_col12\" class=\"data row4 col12\" >18.000000</td>\n",
       "      <td id=\"T_6feb9_row4_col13\" class=\"data row4 col13\" >99.000000</td>\n",
       "      <td id=\"T_6feb9_row4_col14\" class=\"data row4 col14\" >161.000000</td>\n",
       "      <td id=\"T_6feb9_row4_col15\" class=\"data row4 col15\" >55.000000</td>\n",
       "      <td id=\"T_6feb9_row4_col16\" class=\"data row4 col16\" >4</td>\n",
       "      <td id=\"T_6feb9_row4_col17\" class=\"data row4 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row4_col18\" class=\"data row4 col18\" >156.000000</td>\n",
       "      <td id=\"T_6feb9_row4_col19\" class=\"data row4 col19\" >21</td>\n",
       "      <td id=\"T_6feb9_row4_col20\" class=\"data row4 col20\" >Saturday</td>\n",
       "      <td id=\"T_6feb9_row4_col21\" class=\"data row4 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row4_col22\" class=\"data row4 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row4_col23\" class=\"data row4 col23\" >False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "      <td id=\"T_6feb9_row5_col0\" class=\"data row5 col0\" >10037928</td>\n",
       "      <td id=\"T_6feb9_row5_col1\" class=\"data row5 col1\" >nan</td>\n",
       "      <td id=\"T_6feb9_row5_col2\" class=\"data row5 col2\" >34992024</td>\n",
       "      <td id=\"T_6feb9_row5_col3\" class=\"data row5 col3\" >2183-11-28 17:19:00</td>\n",
       "      <td id=\"T_6feb9_row5_col4\" class=\"data row5 col4\" >2183-11-28 23:57:00</td>\n",
       "      <td id=\"T_6feb9_row5_col5\" class=\"data row5 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row5_col6\" class=\"data row5 col6\" >HISPANIC/LATINO - CUBAN</td>\n",
       "      <td id=\"T_6feb9_row5_col7\" class=\"data row5 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row5_col8\" class=\"data row5 col8\" >HOME</td>\n",
       "      <td id=\"T_6feb9_row5_col9\" class=\"data row5 col9\" >0</td>\n",
       "      <td id=\"T_6feb9_row5_col10\" class=\"data row5 col10\" >36.500000</td>\n",
       "      <td id=\"T_6feb9_row5_col11\" class=\"data row5 col11\" >95.000000</td>\n",
       "      <td id=\"T_6feb9_row5_col12\" class=\"data row5 col12\" >18.000000</td>\n",
       "      <td id=\"T_6feb9_row5_col13\" class=\"data row5 col13\" >98.000000</td>\n",
       "      <td id=\"T_6feb9_row5_col14\" class=\"data row5 col14\" >150.000000</td>\n",
       "      <td id=\"T_6feb9_row5_col15\" class=\"data row5 col15\" >56.000000</td>\n",
       "      <td id=\"T_6feb9_row5_col16\" class=\"data row5 col16\" >6</td>\n",
       "      <td id=\"T_6feb9_row5_col17\" class=\"data row5 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row5_col18\" class=\"data row5 col18\" >398.000000</td>\n",
       "      <td id=\"T_6feb9_row5_col19\" class=\"data row5 col19\" >17</td>\n",
       "      <td id=\"T_6feb9_row5_col20\" class=\"data row5 col20\" >Friday</td>\n",
       "      <td id=\"T_6feb9_row5_col21\" class=\"data row5 col21\" >0</td>\n",
       "      <td id=\"T_6feb9_row5_col22\" class=\"data row5 col22\" >0</td>\n",
       "      <td id=\"T_6feb9_row5_col23\" class=\"data row5 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "      <td id=\"T_6feb9_row6_col0\" class=\"data row6 col0\" >10037928</td>\n",
       "      <td id=\"T_6feb9_row6_col1\" class=\"data row6 col1\" >29802992.000000</td>\n",
       "      <td id=\"T_6feb9_row6_col2\" class=\"data row6 col2\" >37953392</td>\n",
       "      <td id=\"T_6feb9_row6_col3\" class=\"data row6 col3\" >2179-07-24 18:21:00</td>\n",
       "      <td id=\"T_6feb9_row6_col4\" class=\"data row6 col4\" >2179-07-25 01:17:00</td>\n",
       "      <td id=\"T_6feb9_row6_col5\" class=\"data row6 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row6_col6\" class=\"data row6 col6\" >HISPANIC/LATINO - CUBAN</td>\n",
       "      <td id=\"T_6feb9_row6_col7\" class=\"data row6 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row6_col8\" class=\"data row6 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row6_col9\" class=\"data row6 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row6_col10\" class=\"data row6 col10\" >98.300000</td>\n",
       "      <td id=\"T_6feb9_row6_col11\" class=\"data row6 col11\" >76.000000</td>\n",
       "      <td id=\"T_6feb9_row6_col12\" class=\"data row6 col12\" >16.000000</td>\n",
       "      <td id=\"T_6feb9_row6_col13\" class=\"data row6 col13\" >98.000000</td>\n",
       "      <td id=\"T_6feb9_row6_col14\" class=\"data row6 col14\" >144.000000</td>\n",
       "      <td id=\"T_6feb9_row6_col15\" class=\"data row6 col15\" >56.000000</td>\n",
       "      <td id=\"T_6feb9_row6_col16\" class=\"data row6 col16\" >6</td>\n",
       "      <td id=\"T_6feb9_row6_col17\" class=\"data row6 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row6_col18\" class=\"data row6 col18\" >416.000000</td>\n",
       "      <td id=\"T_6feb9_row6_col19\" class=\"data row6 col19\" >18</td>\n",
       "      <td id=\"T_6feb9_row6_col20\" class=\"data row6 col20\" >Saturday</td>\n",
       "      <td id=\"T_6feb9_row6_col21\" class=\"data row6 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row6_col22\" class=\"data row6 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row6_col23\" class=\"data row6 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "      <td id=\"T_6feb9_row7_col0\" class=\"data row7 col0\" >10037928</td>\n",
       "      <td id=\"T_6feb9_row7_col1\" class=\"data row7 col1\" >22228639.000000</td>\n",
       "      <td id=\"T_6feb9_row7_col2\" class=\"data row7 col2\" >35156583</td>\n",
       "      <td id=\"T_6feb9_row7_col3\" class=\"data row7 col3\" >2183-08-03 19:27:00</td>\n",
       "      <td id=\"T_6feb9_row7_col4\" class=\"data row7 col4\" >2183-08-04 16:07:00</td>\n",
       "      <td id=\"T_6feb9_row7_col5\" class=\"data row7 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row7_col6\" class=\"data row7 col6\" >HISPANIC/LATINO - CUBAN</td>\n",
       "      <td id=\"T_6feb9_row7_col7\" class=\"data row7 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row7_col8\" class=\"data row7 col8\" >HOME</td>\n",
       "      <td id=\"T_6feb9_row7_col9\" class=\"data row7 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row7_col10\" class=\"data row7 col10\" >97.800000</td>\n",
       "      <td id=\"T_6feb9_row7_col11\" class=\"data row7 col11\" >75.000000</td>\n",
       "      <td id=\"T_6feb9_row7_col12\" class=\"data row7 col12\" >16.000000</td>\n",
       "      <td id=\"T_6feb9_row7_col13\" class=\"data row7 col13\" >95.000000</td>\n",
       "      <td id=\"T_6feb9_row7_col14\" class=\"data row7 col14\" >159.000000</td>\n",
       "      <td id=\"T_6feb9_row7_col15\" class=\"data row7 col15\" >60.000000</td>\n",
       "      <td id=\"T_6feb9_row7_col16\" class=\"data row7 col16\" >3</td>\n",
       "      <td id=\"T_6feb9_row7_col17\" class=\"data row7 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row7_col18\" class=\"data row7 col18\" >1240.000000</td>\n",
       "      <td id=\"T_6feb9_row7_col19\" class=\"data row7 col19\" >19</td>\n",
       "      <td id=\"T_6feb9_row7_col20\" class=\"data row7 col20\" >Sunday</td>\n",
       "      <td id=\"T_6feb9_row7_col21\" class=\"data row7 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row7_col22\" class=\"data row7 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row7_col23\" class=\"data row7 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "      <td id=\"T_6feb9_row8_col0\" class=\"data row8 col0\" >10037928</td>\n",
       "      <td id=\"T_6feb9_row8_col1\" class=\"data row8 col1\" >22490490.000000</td>\n",
       "      <td id=\"T_6feb9_row8_col2\" class=\"data row8 col2\" >38207210</td>\n",
       "      <td id=\"T_6feb9_row8_col3\" class=\"data row8 col3\" >2177-07-14 14:52:00</td>\n",
       "      <td id=\"T_6feb9_row8_col4\" class=\"data row8 col4\" >2177-07-14 20:38:00</td>\n",
       "      <td id=\"T_6feb9_row8_col5\" class=\"data row8 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row8_col6\" class=\"data row8 col6\" >HISPANIC/LATINO - CUBAN</td>\n",
       "      <td id=\"T_6feb9_row8_col7\" class=\"data row8 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row8_col8\" class=\"data row8 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row8_col9\" class=\"data row8 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row8_col10\" class=\"data row8 col10\" >98.200000</td>\n",
       "      <td id=\"T_6feb9_row8_col11\" class=\"data row8 col11\" >72.000000</td>\n",
       "      <td id=\"T_6feb9_row8_col12\" class=\"data row8 col12\" >16.000000</td>\n",
       "      <td id=\"T_6feb9_row8_col13\" class=\"data row8 col13\" >96.000000</td>\n",
       "      <td id=\"T_6feb9_row8_col14\" class=\"data row8 col14\" >126.000000</td>\n",
       "      <td id=\"T_6feb9_row8_col15\" class=\"data row8 col15\" >43.000000</td>\n",
       "      <td id=\"T_6feb9_row8_col16\" class=\"data row8 col16\" >2</td>\n",
       "      <td id=\"T_6feb9_row8_col17\" class=\"data row8 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row8_col18\" class=\"data row8 col18\" >346.000000</td>\n",
       "      <td id=\"T_6feb9_row8_col19\" class=\"data row8 col19\" >14</td>\n",
       "      <td id=\"T_6feb9_row8_col20\" class=\"data row8 col20\" >Monday</td>\n",
       "      <td id=\"T_6feb9_row8_col21\" class=\"data row8 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row8_col22\" class=\"data row8 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row8_col23\" class=\"data row8 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
       "      <td id=\"T_6feb9_row9_col0\" class=\"data row9 col0\" >10037928</td>\n",
       "      <td id=\"T_6feb9_row9_col1\" class=\"data row9 col1\" >24885579.000000</td>\n",
       "      <td id=\"T_6feb9_row9_col2\" class=\"data row9 col2\" >37483564</td>\n",
       "      <td id=\"T_6feb9_row9_col3\" class=\"data row9 col3\" >2182-04-28 17:25:00</td>\n",
       "      <td id=\"T_6feb9_row9_col4\" class=\"data row9 col4\" >2182-04-29 07:49:00</td>\n",
       "      <td id=\"T_6feb9_row9_col5\" class=\"data row9 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row9_col6\" class=\"data row9 col6\" >HISPANIC/LATINO - CUBAN</td>\n",
       "      <td id=\"T_6feb9_row9_col7\" class=\"data row9 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row9_col8\" class=\"data row9 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row9_col9\" class=\"data row9 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row9_col10\" class=\"data row9 col10\" >98.200000</td>\n",
       "      <td id=\"T_6feb9_row9_col11\" class=\"data row9 col11\" >105.000000</td>\n",
       "      <td id=\"T_6feb9_row9_col12\" class=\"data row9 col12\" >24.000000</td>\n",
       "      <td id=\"T_6feb9_row9_col13\" class=\"data row9 col13\" >96.000000</td>\n",
       "      <td id=\"T_6feb9_row9_col14\" class=\"data row9 col14\" >177.000000</td>\n",
       "      <td id=\"T_6feb9_row9_col15\" class=\"data row9 col15\" >69.000000</td>\n",
       "      <td id=\"T_6feb9_row9_col16\" class=\"data row9 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row9_col17\" class=\"data row9 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row9_col18\" class=\"data row9 col18\" >864.000000</td>\n",
       "      <td id=\"T_6feb9_row9_col19\" class=\"data row9 col19\" >17</td>\n",
       "      <td id=\"T_6feb9_row9_col20\" class=\"data row9 col20\" >Sunday</td>\n",
       "      <td id=\"T_6feb9_row9_col21\" class=\"data row9 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row9_col22\" class=\"data row9 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row9_col23\" class=\"data row9 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
       "      <td id=\"T_6feb9_row10_col0\" class=\"data row10 col0\" >10037928</td>\n",
       "      <td id=\"T_6feb9_row10_col1\" class=\"data row10 col1\" >24656677.000000</td>\n",
       "      <td id=\"T_6feb9_row10_col2\" class=\"data row10 col2\" >32443787</td>\n",
       "      <td id=\"T_6feb9_row10_col3\" class=\"data row10 col3\" >2178-12-21 03:17:00</td>\n",
       "      <td id=\"T_6feb9_row10_col4\" class=\"data row10 col4\" >2178-12-21 05:30:41</td>\n",
       "      <td id=\"T_6feb9_row10_col5\" class=\"data row10 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row10_col6\" class=\"data row10 col6\" >HISPANIC/LATINO - CUBAN</td>\n",
       "      <td id=\"T_6feb9_row10_col7\" class=\"data row10 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row10_col8\" class=\"data row10 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row10_col9\" class=\"data row10 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row10_col10\" class=\"data row10 col10\" >98.100000</td>\n",
       "      <td id=\"T_6feb9_row10_col11\" class=\"data row10 col11\" >130.000000</td>\n",
       "      <td id=\"T_6feb9_row10_col12\" class=\"data row10 col12\" >15.000000</td>\n",
       "      <td id=\"T_6feb9_row10_col13\" class=\"data row10 col13\" >95.000000</td>\n",
       "      <td id=\"T_6feb9_row10_col14\" class=\"data row10 col14\" >179.000000</td>\n",
       "      <td id=\"T_6feb9_row10_col15\" class=\"data row10 col15\" >69.000000</td>\n",
       "      <td id=\"T_6feb9_row10_col16\" class=\"data row10 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row10_col17\" class=\"data row10 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row10_col18\" class=\"data row10 col18\" >133.683333</td>\n",
       "      <td id=\"T_6feb9_row10_col19\" class=\"data row10 col19\" >3</td>\n",
       "      <td id=\"T_6feb9_row10_col20\" class=\"data row10 col20\" >Monday</td>\n",
       "      <td id=\"T_6feb9_row10_col21\" class=\"data row10 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row10_col22\" class=\"data row10 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row10_col23\" class=\"data row10 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
       "      <td id=\"T_6feb9_row11_col0\" class=\"data row11 col0\" >10037928</td>\n",
       "      <td id=\"T_6feb9_row11_col1\" class=\"data row11 col1\" >22326517.000000</td>\n",
       "      <td id=\"T_6feb9_row11_col2\" class=\"data row11 col2\" >39740242</td>\n",
       "      <td id=\"T_6feb9_row11_col3\" class=\"data row11 col3\" >2177-12-21 16:49:00</td>\n",
       "      <td id=\"T_6feb9_row11_col4\" class=\"data row11 col4\" >2177-12-21 22:26:00</td>\n",
       "      <td id=\"T_6feb9_row11_col5\" class=\"data row11 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row11_col6\" class=\"data row11 col6\" >HISPANIC/LATINO - CUBAN</td>\n",
       "      <td id=\"T_6feb9_row11_col7\" class=\"data row11 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row11_col8\" class=\"data row11 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row11_col9\" class=\"data row11 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row11_col10\" class=\"data row11 col10\" >98.700000</td>\n",
       "      <td id=\"T_6feb9_row11_col11\" class=\"data row11 col11\" >108.000000</td>\n",
       "      <td id=\"T_6feb9_row11_col12\" class=\"data row11 col12\" >22.000000</td>\n",
       "      <td id=\"T_6feb9_row11_col13\" class=\"data row11 col13\" >98.000000</td>\n",
       "      <td id=\"T_6feb9_row11_col14\" class=\"data row11 col14\" >151.000000</td>\n",
       "      <td id=\"T_6feb9_row11_col15\" class=\"data row11 col15\" >55.000000</td>\n",
       "      <td id=\"T_6feb9_row11_col16\" class=\"data row11 col16\" >3</td>\n",
       "      <td id=\"T_6feb9_row11_col17\" class=\"data row11 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row11_col18\" class=\"data row11 col18\" >337.000000</td>\n",
       "      <td id=\"T_6feb9_row11_col19\" class=\"data row11 col19\" >16</td>\n",
       "      <td id=\"T_6feb9_row11_col20\" class=\"data row11 col20\" >Sunday</td>\n",
       "      <td id=\"T_6feb9_row11_col21\" class=\"data row11 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row11_col22\" class=\"data row11 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row11_col23\" class=\"data row11 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
       "      <td id=\"T_6feb9_row12_col0\" class=\"data row12 col0\" >10037928</td>\n",
       "      <td id=\"T_6feb9_row12_col1\" class=\"data row12 col1\" >24225421.000000</td>\n",
       "      <td id=\"T_6feb9_row12_col2\" class=\"data row12 col2\" >34478228</td>\n",
       "      <td id=\"T_6feb9_row12_col3\" class=\"data row12 col3\" >2178-09-28 20:29:00</td>\n",
       "      <td id=\"T_6feb9_row12_col4\" class=\"data row12 col4\" >2178-09-29 00:43:00</td>\n",
       "      <td id=\"T_6feb9_row12_col5\" class=\"data row12 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row12_col6\" class=\"data row12 col6\" >HISPANIC/LATINO - CUBAN</td>\n",
       "      <td id=\"T_6feb9_row12_col7\" class=\"data row12 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row12_col8\" class=\"data row12 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row12_col9\" class=\"data row12 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row12_col10\" class=\"data row12 col10\" >97.600000</td>\n",
       "      <td id=\"T_6feb9_row12_col11\" class=\"data row12 col11\" >96.000000</td>\n",
       "      <td id=\"T_6feb9_row12_col12\" class=\"data row12 col12\" >16.000000</td>\n",
       "      <td id=\"T_6feb9_row12_col13\" class=\"data row12 col13\" >94.000000</td>\n",
       "      <td id=\"T_6feb9_row12_col14\" class=\"data row12 col14\" >121.000000</td>\n",
       "      <td id=\"T_6feb9_row12_col15\" class=\"data row12 col15\" >65.000000</td>\n",
       "      <td id=\"T_6feb9_row12_col16\" class=\"data row12 col16\" >3</td>\n",
       "      <td id=\"T_6feb9_row12_col17\" class=\"data row12 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row12_col18\" class=\"data row12 col18\" >254.000000</td>\n",
       "      <td id=\"T_6feb9_row12_col19\" class=\"data row12 col19\" >20</td>\n",
       "      <td id=\"T_6feb9_row12_col20\" class=\"data row12 col20\" >Monday</td>\n",
       "      <td id=\"T_6feb9_row12_col21\" class=\"data row12 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row12_col22\" class=\"data row12 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row12_col23\" class=\"data row12 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
       "      <td id=\"T_6feb9_row13_col0\" class=\"data row13 col0\" >10037928</td>\n",
       "      <td id=\"T_6feb9_row13_col1\" class=\"data row13 col1\" >20192635.000000</td>\n",
       "      <td id=\"T_6feb9_row13_col2\" class=\"data row13 col2\" >37036523</td>\n",
       "      <td id=\"T_6feb9_row13_col3\" class=\"data row13 col3\" >2177-09-04 06:29:00</td>\n",
       "      <td id=\"T_6feb9_row13_col4\" class=\"data row13 col4\" >2177-09-04 12:06:40</td>\n",
       "      <td id=\"T_6feb9_row13_col5\" class=\"data row13 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row13_col6\" class=\"data row13 col6\" >HISPANIC/LATINO - CUBAN</td>\n",
       "      <td id=\"T_6feb9_row13_col7\" class=\"data row13 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row13_col8\" class=\"data row13 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row13_col9\" class=\"data row13 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row13_col10\" class=\"data row13 col10\" >nan</td>\n",
       "      <td id=\"T_6feb9_row13_col11\" class=\"data row13 col11\" >nan</td>\n",
       "      <td id=\"T_6feb9_row13_col12\" class=\"data row13 col12\" >nan</td>\n",
       "      <td id=\"T_6feb9_row13_col13\" class=\"data row13 col13\" >nan</td>\n",
       "      <td id=\"T_6feb9_row13_col14\" class=\"data row13 col14\" >nan</td>\n",
       "      <td id=\"T_6feb9_row13_col15\" class=\"data row13 col15\" >nan</td>\n",
       "      <td id=\"T_6feb9_row13_col16\" class=\"data row13 col16\" >3</td>\n",
       "      <td id=\"T_6feb9_row13_col17\" class=\"data row13 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row13_col18\" class=\"data row13 col18\" >337.666667</td>\n",
       "      <td id=\"T_6feb9_row13_col19\" class=\"data row13 col19\" >6</td>\n",
       "      <td id=\"T_6feb9_row13_col20\" class=\"data row13 col20\" >Thursday</td>\n",
       "      <td id=\"T_6feb9_row13_col21\" class=\"data row13 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row13_col22\" class=\"data row13 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row13_col23\" class=\"data row13 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
       "      <td id=\"T_6feb9_row14_col0\" class=\"data row14 col0\" >10019003</td>\n",
       "      <td id=\"T_6feb9_row14_col1\" class=\"data row14 col1\" >27525946.000000</td>\n",
       "      <td id=\"T_6feb9_row14_col2\" class=\"data row14 col2\" >38260469</td>\n",
       "      <td id=\"T_6feb9_row14_col3\" class=\"data row14 col3\" >2153-04-12 13:03:00</td>\n",
       "      <td id=\"T_6feb9_row14_col4\" class=\"data row14 col4\" >2153-04-12 21:40:00</td>\n",
       "      <td id=\"T_6feb9_row14_col5\" class=\"data row14 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row14_col6\" class=\"data row14 col6\" >WHITE</td>\n",
       "      <td id=\"T_6feb9_row14_col7\" class=\"data row14 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row14_col8\" class=\"data row14 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row14_col9\" class=\"data row14 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row14_col10\" class=\"data row14 col10\" >99.100000</td>\n",
       "      <td id=\"T_6feb9_row14_col11\" class=\"data row14 col11\" >96.000000</td>\n",
       "      <td id=\"T_6feb9_row14_col12\" class=\"data row14 col12\" >17.000000</td>\n",
       "      <td id=\"T_6feb9_row14_col13\" class=\"data row14 col13\" >96.000000</td>\n",
       "      <td id=\"T_6feb9_row14_col14\" class=\"data row14 col14\" >114.000000</td>\n",
       "      <td id=\"T_6feb9_row14_col15\" class=\"data row14 col15\" >66.000000</td>\n",
       "      <td id=\"T_6feb9_row14_col16\" class=\"data row14 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row14_col17\" class=\"data row14 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row14_col18\" class=\"data row14 col18\" >517.000000</td>\n",
       "      <td id=\"T_6feb9_row14_col19\" class=\"data row14 col19\" >13</td>\n",
       "      <td id=\"T_6feb9_row14_col20\" class=\"data row14 col20\" >Thursday</td>\n",
       "      <td id=\"T_6feb9_row14_col21\" class=\"data row14 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row14_col22\" class=\"data row14 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row14_col23\" class=\"data row14 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
       "      <td id=\"T_6feb9_row15_col0\" class=\"data row15 col0\" >10019003</td>\n",
       "      <td id=\"T_6feb9_row15_col1\" class=\"data row15 col1\" >29279905.000000</td>\n",
       "      <td id=\"T_6feb9_row15_col2\" class=\"data row15 col2\" >31254712</td>\n",
       "      <td id=\"T_6feb9_row15_col3\" class=\"data row15 col3\" >2153-03-27 21:28:00</td>\n",
       "      <td id=\"T_6feb9_row15_col4\" class=\"data row15 col4\" >2153-03-28 02:21:00</td>\n",
       "      <td id=\"T_6feb9_row15_col5\" class=\"data row15 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row15_col6\" class=\"data row15 col6\" >WHITE</td>\n",
       "      <td id=\"T_6feb9_row15_col7\" class=\"data row15 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row15_col8\" class=\"data row15 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row15_col9\" class=\"data row15 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row15_col10\" class=\"data row15 col10\" >98.400000</td>\n",
       "      <td id=\"T_6feb9_row15_col11\" class=\"data row15 col11\" >96.000000</td>\n",
       "      <td id=\"T_6feb9_row15_col12\" class=\"data row15 col12\" >15.000000</td>\n",
       "      <td id=\"T_6feb9_row15_col13\" class=\"data row15 col13\" >97.000000</td>\n",
       "      <td id=\"T_6feb9_row15_col14\" class=\"data row15 col14\" >98.000000</td>\n",
       "      <td id=\"T_6feb9_row15_col15\" class=\"data row15 col15\" >56.000000</td>\n",
       "      <td id=\"T_6feb9_row15_col16\" class=\"data row15 col16\" >4</td>\n",
       "      <td id=\"T_6feb9_row15_col17\" class=\"data row15 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row15_col18\" class=\"data row15 col18\" >293.000000</td>\n",
       "      <td id=\"T_6feb9_row15_col19\" class=\"data row15 col19\" >21</td>\n",
       "      <td id=\"T_6feb9_row15_col20\" class=\"data row15 col20\" >Tuesday</td>\n",
       "      <td id=\"T_6feb9_row15_col21\" class=\"data row15 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row15_col22\" class=\"data row15 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row15_col23\" class=\"data row15 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
       "      <td id=\"T_6feb9_row16_col0\" class=\"data row16 col0\" >10019003</td>\n",
       "      <td id=\"T_6feb9_row16_col1\" class=\"data row16 col1\" >26529390.000000</td>\n",
       "      <td id=\"T_6feb9_row16_col2\" class=\"data row16 col2\" >38020791</td>\n",
       "      <td id=\"T_6feb9_row16_col3\" class=\"data row16 col3\" >2155-05-17 21:03:00</td>\n",
       "      <td id=\"T_6feb9_row16_col4\" class=\"data row16 col4\" >2155-05-18 00:03:15</td>\n",
       "      <td id=\"T_6feb9_row16_col5\" class=\"data row16 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row16_col6\" class=\"data row16 col6\" >WHITE</td>\n",
       "      <td id=\"T_6feb9_row16_col7\" class=\"data row16 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row16_col8\" class=\"data row16 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row16_col9\" class=\"data row16 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row16_col10\" class=\"data row16 col10\" >98.100000</td>\n",
       "      <td id=\"T_6feb9_row16_col11\" class=\"data row16 col11\" >97.000000</td>\n",
       "      <td id=\"T_6feb9_row16_col12\" class=\"data row16 col12\" >16.000000</td>\n",
       "      <td id=\"T_6feb9_row16_col13\" class=\"data row16 col13\" >93.000000</td>\n",
       "      <td id=\"T_6feb9_row16_col14\" class=\"data row16 col14\" >117.000000</td>\n",
       "      <td id=\"T_6feb9_row16_col15\" class=\"data row16 col15\" >60.000000</td>\n",
       "      <td id=\"T_6feb9_row16_col16\" class=\"data row16 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row16_col17\" class=\"data row16 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row16_col18\" class=\"data row16 col18\" >180.250000</td>\n",
       "      <td id=\"T_6feb9_row16_col19\" class=\"data row16 col19\" >21</td>\n",
       "      <td id=\"T_6feb9_row16_col20\" class=\"data row16 col20\" >Saturday</td>\n",
       "      <td id=\"T_6feb9_row16_col21\" class=\"data row16 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row16_col22\" class=\"data row16 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row16_col23\" class=\"data row16 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
       "      <td id=\"T_6feb9_row17_col0\" class=\"data row17 col0\" >10019003</td>\n",
       "      <td id=\"T_6feb9_row17_col1\" class=\"data row17 col1\" >26703331.000000</td>\n",
       "      <td id=\"T_6feb9_row17_col2\" class=\"data row17 col2\" >35568186</td>\n",
       "      <td id=\"T_6feb9_row17_col3\" class=\"data row17 col3\" >2155-06-10 20:37:00</td>\n",
       "      <td id=\"T_6feb9_row17_col4\" class=\"data row17 col4\" >2155-06-10 23:10:36</td>\n",
       "      <td id=\"T_6feb9_row17_col5\" class=\"data row17 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row17_col6\" class=\"data row17 col6\" >WHITE</td>\n",
       "      <td id=\"T_6feb9_row17_col7\" class=\"data row17 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row17_col8\" class=\"data row17 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row17_col9\" class=\"data row17 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row17_col10\" class=\"data row17 col10\" >97.800000</td>\n",
       "      <td id=\"T_6feb9_row17_col11\" class=\"data row17 col11\" >92.000000</td>\n",
       "      <td id=\"T_6feb9_row17_col12\" class=\"data row17 col12\" >26.000000</td>\n",
       "      <td id=\"T_6feb9_row17_col13\" class=\"data row17 col13\" >95.000000</td>\n",
       "      <td id=\"T_6feb9_row17_col14\" class=\"data row17 col14\" >116.000000</td>\n",
       "      <td id=\"T_6feb9_row17_col15\" class=\"data row17 col15\" >57.000000</td>\n",
       "      <td id=\"T_6feb9_row17_col16\" class=\"data row17 col16\" >3</td>\n",
       "      <td id=\"T_6feb9_row17_col17\" class=\"data row17 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row17_col18\" class=\"data row17 col18\" >153.600000</td>\n",
       "      <td id=\"T_6feb9_row17_col19\" class=\"data row17 col19\" >20</td>\n",
       "      <td id=\"T_6feb9_row17_col20\" class=\"data row17 col20\" >Tuesday</td>\n",
       "      <td id=\"T_6feb9_row17_col21\" class=\"data row17 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row17_col22\" class=\"data row17 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row17_col23\" class=\"data row17 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
       "      <td id=\"T_6feb9_row18_col0\" class=\"data row18 col0\" >10019003</td>\n",
       "      <td id=\"T_6feb9_row18_col1\" class=\"data row18 col1\" >21457723.000000</td>\n",
       "      <td id=\"T_6feb9_row18_col2\" class=\"data row18 col2\" >36686656</td>\n",
       "      <td id=\"T_6feb9_row18_col3\" class=\"data row18 col3\" >2155-07-10 12:46:00</td>\n",
       "      <td id=\"T_6feb9_row18_col4\" class=\"data row18 col4\" >2155-07-10 17:48:57</td>\n",
       "      <td id=\"T_6feb9_row18_col5\" class=\"data row18 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row18_col6\" class=\"data row18 col6\" >WHITE</td>\n",
       "      <td id=\"T_6feb9_row18_col7\" class=\"data row18 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row18_col8\" class=\"data row18 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row18_col9\" class=\"data row18 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row18_col10\" class=\"data row18 col10\" >98.600000</td>\n",
       "      <td id=\"T_6feb9_row18_col11\" class=\"data row18 col11\" >98.000000</td>\n",
       "      <td id=\"T_6feb9_row18_col12\" class=\"data row18 col12\" >16.000000</td>\n",
       "      <td id=\"T_6feb9_row18_col13\" class=\"data row18 col13\" >97.000000</td>\n",
       "      <td id=\"T_6feb9_row18_col14\" class=\"data row18 col14\" >105.000000</td>\n",
       "      <td id=\"T_6feb9_row18_col15\" class=\"data row18 col15\" >43.000000</td>\n",
       "      <td id=\"T_6feb9_row18_col16\" class=\"data row18 col16\" >2</td>\n",
       "      <td id=\"T_6feb9_row18_col17\" class=\"data row18 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row18_col18\" class=\"data row18 col18\" >302.950000</td>\n",
       "      <td id=\"T_6feb9_row18_col19\" class=\"data row18 col19\" >12</td>\n",
       "      <td id=\"T_6feb9_row18_col20\" class=\"data row18 col20\" >Thursday</td>\n",
       "      <td id=\"T_6feb9_row18_col21\" class=\"data row18 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row18_col22\" class=\"data row18 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row18_col23\" class=\"data row18 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
       "      <td id=\"T_6feb9_row19_col0\" class=\"data row19 col0\" >10003400</td>\n",
       "      <td id=\"T_6feb9_row19_col1\" class=\"data row19 col1\" >22390287.000000</td>\n",
       "      <td id=\"T_6feb9_row19_col2\" class=\"data row19 col2\" >34922474</td>\n",
       "      <td id=\"T_6feb9_row19_col3\" class=\"data row19 col3\" >2137-02-07 13:06:00</td>\n",
       "      <td id=\"T_6feb9_row19_col4\" class=\"data row19 col4\" >2137-02-07 21:44:00</td>\n",
       "      <td id=\"T_6feb9_row19_col5\" class=\"data row19 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row19_col6\" class=\"data row19 col6\" >BLACK/AFRICAN AMERICAN</td>\n",
       "      <td id=\"T_6feb9_row19_col7\" class=\"data row19 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row19_col8\" class=\"data row19 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row19_col9\" class=\"data row19 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row19_col10\" class=\"data row19 col10\" >98.800000</td>\n",
       "      <td id=\"T_6feb9_row19_col11\" class=\"data row19 col11\" >124.000000</td>\n",
       "      <td id=\"T_6feb9_row19_col12\" class=\"data row19 col12\" >16.000000</td>\n",
       "      <td id=\"T_6feb9_row19_col13\" class=\"data row19 col13\" >98.000000</td>\n",
       "      <td id=\"T_6feb9_row19_col14\" class=\"data row19 col14\" >136.000000</td>\n",
       "      <td id=\"T_6feb9_row19_col15\" class=\"data row19 col15\" >82.000000</td>\n",
       "      <td id=\"T_6feb9_row19_col16\" class=\"data row19 col16\" >3</td>\n",
       "      <td id=\"T_6feb9_row19_col17\" class=\"data row19 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row19_col18\" class=\"data row19 col18\" >518.000000</td>\n",
       "      <td id=\"T_6feb9_row19_col19\" class=\"data row19 col19\" >13</td>\n",
       "      <td id=\"T_6feb9_row19_col20\" class=\"data row19 col20\" >Thursday</td>\n",
       "      <td id=\"T_6feb9_row19_col21\" class=\"data row19 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row19_col22\" class=\"data row19 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row19_col23\" class=\"data row19 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
       "      <td id=\"T_6feb9_row20_col0\" class=\"data row20 col0\" >10003400</td>\n",
       "      <td id=\"T_6feb9_row20_col1\" class=\"data row20 col1\" >26467376.000000</td>\n",
       "      <td id=\"T_6feb9_row20_col2\" class=\"data row20 col2\" >33678912</td>\n",
       "      <td id=\"T_6feb9_row20_col3\" class=\"data row20 col3\" >2136-12-09 13:16:00</td>\n",
       "      <td id=\"T_6feb9_row20_col4\" class=\"data row20 col4\" >2136-12-09 14:45:10</td>\n",
       "      <td id=\"T_6feb9_row20_col5\" class=\"data row20 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row20_col6\" class=\"data row20 col6\" >BLACK/AFRICAN AMERICAN</td>\n",
       "      <td id=\"T_6feb9_row20_col7\" class=\"data row20 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row20_col8\" class=\"data row20 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row20_col9\" class=\"data row20 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row20_col10\" class=\"data row20 col10\" >98.300000</td>\n",
       "      <td id=\"T_6feb9_row20_col11\" class=\"data row20 col11\" >157.000000</td>\n",
       "      <td id=\"T_6feb9_row20_col12\" class=\"data row20 col12\" >18.000000</td>\n",
       "      <td id=\"T_6feb9_row20_col13\" class=\"data row20 col13\" >100.000000</td>\n",
       "      <td id=\"T_6feb9_row20_col14\" class=\"data row20 col14\" >115.000000</td>\n",
       "      <td id=\"T_6feb9_row20_col15\" class=\"data row20 col15\" >81.000000</td>\n",
       "      <td id=\"T_6feb9_row20_col16\" class=\"data row20 col16\" >2</td>\n",
       "      <td id=\"T_6feb9_row20_col17\" class=\"data row20 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row20_col18\" class=\"data row20 col18\" >89.166667</td>\n",
       "      <td id=\"T_6feb9_row20_col19\" class=\"data row20 col19\" >13</td>\n",
       "      <td id=\"T_6feb9_row20_col20\" class=\"data row20 col20\" >Sunday</td>\n",
       "      <td id=\"T_6feb9_row20_col21\" class=\"data row20 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row20_col22\" class=\"data row20 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row20_col23\" class=\"data row20 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
       "      <td id=\"T_6feb9_row21_col0\" class=\"data row21 col0\" >10003400</td>\n",
       "      <td id=\"T_6feb9_row21_col1\" class=\"data row21 col1\" >27296885.000000</td>\n",
       "      <td id=\"T_6feb9_row21_col2\" class=\"data row21 col2\" >36976997</td>\n",
       "      <td id=\"T_6feb9_row21_col3\" class=\"data row21 col3\" >2136-12-31 13:41:00</td>\n",
       "      <td id=\"T_6feb9_row21_col4\" class=\"data row21 col4\" >2137-01-01 00:35:00</td>\n",
       "      <td id=\"T_6feb9_row21_col5\" class=\"data row21 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row21_col6\" class=\"data row21 col6\" >BLACK/AFRICAN AMERICAN</td>\n",
       "      <td id=\"T_6feb9_row21_col7\" class=\"data row21 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row21_col8\" class=\"data row21 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row21_col9\" class=\"data row21 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row21_col10\" class=\"data row21 col10\" >97.700000</td>\n",
       "      <td id=\"T_6feb9_row21_col11\" class=\"data row21 col11\" >91.000000</td>\n",
       "      <td id=\"T_6feb9_row21_col12\" class=\"data row21 col12\" >16.000000</td>\n",
       "      <td id=\"T_6feb9_row21_col13\" class=\"data row21 col13\" >100.000000</td>\n",
       "      <td id=\"T_6feb9_row21_col14\" class=\"data row21 col14\" >111.000000</td>\n",
       "      <td id=\"T_6feb9_row21_col15\" class=\"data row21 col15\" >68.000000</td>\n",
       "      <td id=\"T_6feb9_row21_col16\" class=\"data row21 col16\" >2</td>\n",
       "      <td id=\"T_6feb9_row21_col17\" class=\"data row21 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row21_col18\" class=\"data row21 col18\" >654.000000</td>\n",
       "      <td id=\"T_6feb9_row21_col19\" class=\"data row21 col19\" >13</td>\n",
       "      <td id=\"T_6feb9_row21_col20\" class=\"data row21 col20\" >Monday</td>\n",
       "      <td id=\"T_6feb9_row21_col21\" class=\"data row21 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row21_col22\" class=\"data row21 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row21_col23\" class=\"data row21 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
       "      <td id=\"T_6feb9_row22_col0\" class=\"data row22 col0\" >10003400</td>\n",
       "      <td id=\"T_6feb9_row22_col1\" class=\"data row22 col1\" >26090619.000000</td>\n",
       "      <td id=\"T_6feb9_row22_col2\" class=\"data row22 col2\" >33347721</td>\n",
       "      <td id=\"T_6feb9_row22_col3\" class=\"data row22 col3\" >2134-06-05 21:42:00</td>\n",
       "      <td id=\"T_6feb9_row22_col4\" class=\"data row22 col4\" >2134-06-06 03:44:00</td>\n",
       "      <td id=\"T_6feb9_row22_col5\" class=\"data row22 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row22_col6\" class=\"data row22 col6\" >BLACK/AFRICAN AMERICAN</td>\n",
       "      <td id=\"T_6feb9_row22_col7\" class=\"data row22 col7\" >OTHER</td>\n",
       "      <td id=\"T_6feb9_row22_col8\" class=\"data row22 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row22_col9\" class=\"data row22 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row22_col10\" class=\"data row22 col10\" >97.300000</td>\n",
       "      <td id=\"T_6feb9_row22_col11\" class=\"data row22 col11\" >43.000000</td>\n",
       "      <td id=\"T_6feb9_row22_col12\" class=\"data row22 col12\" >16.000000</td>\n",
       "      <td id=\"T_6feb9_row22_col13\" class=\"data row22 col13\" >99.000000</td>\n",
       "      <td id=\"T_6feb9_row22_col14\" class=\"data row22 col14\" >140.000000</td>\n",
       "      <td id=\"T_6feb9_row22_col15\" class=\"data row22 col15\" >100.000000</td>\n",
       "      <td id=\"T_6feb9_row22_col16\" class=\"data row22 col16\" >4</td>\n",
       "      <td id=\"T_6feb9_row22_col17\" class=\"data row22 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row22_col18\" class=\"data row22 col18\" >362.000000</td>\n",
       "      <td id=\"T_6feb9_row22_col19\" class=\"data row22 col19\" >21</td>\n",
       "      <td id=\"T_6feb9_row22_col20\" class=\"data row22 col20\" >Saturday</td>\n",
       "      <td id=\"T_6feb9_row22_col21\" class=\"data row22 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row22_col22\" class=\"data row22 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row22_col23\" class=\"data row22 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
       "      <td id=\"T_6feb9_row23_col0\" class=\"data row23 col0\" >10003400</td>\n",
       "      <td id=\"T_6feb9_row23_col1\" class=\"data row23 col1\" >29483621.000000</td>\n",
       "      <td id=\"T_6feb9_row23_col2\" class=\"data row23 col2\" >34948767</td>\n",
       "      <td id=\"T_6feb9_row23_col3\" class=\"data row23 col3\" >2136-11-04 16:08:00</td>\n",
       "      <td id=\"T_6feb9_row23_col4\" class=\"data row23 col4\" >2136-11-04 22:12:00</td>\n",
       "      <td id=\"T_6feb9_row23_col5\" class=\"data row23 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row23_col6\" class=\"data row23 col6\" >BLACK/AFRICAN AMERICAN</td>\n",
       "      <td id=\"T_6feb9_row23_col7\" class=\"data row23 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row23_col8\" class=\"data row23 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row23_col9\" class=\"data row23 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row23_col10\" class=\"data row23 col10\" >99.900000</td>\n",
       "      <td id=\"T_6feb9_row23_col11\" class=\"data row23 col11\" >86.000000</td>\n",
       "      <td id=\"T_6feb9_row23_col12\" class=\"data row23 col12\" >18.000000</td>\n",
       "      <td id=\"T_6feb9_row23_col13\" class=\"data row23 col13\" >100.000000</td>\n",
       "      <td id=\"T_6feb9_row23_col14\" class=\"data row23 col14\" >142.000000</td>\n",
       "      <td id=\"T_6feb9_row23_col15\" class=\"data row23 col15\" >92.000000</td>\n",
       "      <td id=\"T_6feb9_row23_col16\" class=\"data row23 col16\" >2</td>\n",
       "      <td id=\"T_6feb9_row23_col17\" class=\"data row23 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row23_col18\" class=\"data row23 col18\" >364.000000</td>\n",
       "      <td id=\"T_6feb9_row23_col19\" class=\"data row23 col19\" >16</td>\n",
       "      <td id=\"T_6feb9_row23_col20\" class=\"data row23 col20\" >Sunday</td>\n",
       "      <td id=\"T_6feb9_row23_col21\" class=\"data row23 col21\" >0</td>\n",
       "      <td id=\"T_6feb9_row23_col22\" class=\"data row23 col22\" >0</td>\n",
       "      <td id=\"T_6feb9_row23_col23\" class=\"data row23 col23\" >False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
       "      <td id=\"T_6feb9_row24_col0\" class=\"data row24 col0\" >10002930</td>\n",
       "      <td id=\"T_6feb9_row24_col1\" class=\"data row24 col1\" >28697806.000000</td>\n",
       "      <td id=\"T_6feb9_row24_col2\" class=\"data row24 col2\" >32272346</td>\n",
       "      <td id=\"T_6feb9_row24_col3\" class=\"data row24 col3\" >2200-06-04 16:38:00</td>\n",
       "      <td id=\"T_6feb9_row24_col4\" class=\"data row24 col4\" >2200-06-05 10:26:00</td>\n",
       "      <td id=\"T_6feb9_row24_col5\" class=\"data row24 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row24_col6\" class=\"data row24 col6\" >BLACK/AFRICAN AMERICAN</td>\n",
       "      <td id=\"T_6feb9_row24_col7\" class=\"data row24 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row24_col8\" class=\"data row24 col8\" >HOME</td>\n",
       "      <td id=\"T_6feb9_row24_col9\" class=\"data row24 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row24_col10\" class=\"data row24 col10\" >97.300000</td>\n",
       "      <td id=\"T_6feb9_row24_col11\" class=\"data row24 col11\" >89.000000</td>\n",
       "      <td id=\"T_6feb9_row24_col12\" class=\"data row24 col12\" >16.000000</td>\n",
       "      <td id=\"T_6feb9_row24_col13\" class=\"data row24 col13\" >100.000000</td>\n",
       "      <td id=\"T_6feb9_row24_col14\" class=\"data row24 col14\" >106.000000</td>\n",
       "      <td id=\"T_6feb9_row24_col15\" class=\"data row24 col15\" >61.000000</td>\n",
       "      <td id=\"T_6feb9_row24_col16\" class=\"data row24 col16\" >3</td>\n",
       "      <td id=\"T_6feb9_row24_col17\" class=\"data row24 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row24_col18\" class=\"data row24 col18\" >1068.000000</td>\n",
       "      <td id=\"T_6feb9_row24_col19\" class=\"data row24 col19\" >16</td>\n",
       "      <td id=\"T_6feb9_row24_col20\" class=\"data row24 col20\" >Wednesday</td>\n",
       "      <td id=\"T_6feb9_row24_col21\" class=\"data row24 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row24_col22\" class=\"data row24 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row24_col23\" class=\"data row24 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
       "      <td id=\"T_6feb9_row25_col0\" class=\"data row25 col0\" >10002930</td>\n",
       "      <td id=\"T_6feb9_row25_col1\" class=\"data row25 col1\" >25696644.000000</td>\n",
       "      <td id=\"T_6feb9_row25_col2\" class=\"data row25 col2\" >31579293</td>\n",
       "      <td id=\"T_6feb9_row25_col3\" class=\"data row25 col3\" >2196-04-14 05:55:00</td>\n",
       "      <td id=\"T_6feb9_row25_col4\" class=\"data row25 col4\" >2196-04-14 13:40:00</td>\n",
       "      <td id=\"T_6feb9_row25_col5\" class=\"data row25 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row25_col6\" class=\"data row25 col6\" >BLACK/AFRICAN AMERICAN</td>\n",
       "      <td id=\"T_6feb9_row25_col7\" class=\"data row25 col7\" >UNKNOWN</td>\n",
       "      <td id=\"T_6feb9_row25_col8\" class=\"data row25 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row25_col9\" class=\"data row25 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row25_col10\" class=\"data row25 col10\" >95.600000</td>\n",
       "      <td id=\"T_6feb9_row25_col11\" class=\"data row25 col11\" >89.000000</td>\n",
       "      <td id=\"T_6feb9_row25_col12\" class=\"data row25 col12\" >16.000000</td>\n",
       "      <td id=\"T_6feb9_row25_col13\" class=\"data row25 col13\" >100.000000</td>\n",
       "      <td id=\"T_6feb9_row25_col14\" class=\"data row25 col14\" >106.000000</td>\n",
       "      <td id=\"T_6feb9_row25_col15\" class=\"data row25 col15\" >65.000000</td>\n",
       "      <td id=\"T_6feb9_row25_col16\" class=\"data row25 col16\" >3</td>\n",
       "      <td id=\"T_6feb9_row25_col17\" class=\"data row25 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row25_col18\" class=\"data row25 col18\" >465.000000</td>\n",
       "      <td id=\"T_6feb9_row25_col19\" class=\"data row25 col19\" >5</td>\n",
       "      <td id=\"T_6feb9_row25_col20\" class=\"data row25 col20\" >Thursday</td>\n",
       "      <td id=\"T_6feb9_row25_col21\" class=\"data row25 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row25_col22\" class=\"data row25 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row25_col23\" class=\"data row25 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
       "      <td id=\"T_6feb9_row26_col0\" class=\"data row26 col0\" >10002930</td>\n",
       "      <td id=\"T_6feb9_row26_col1\" class=\"data row26 col1\" >20282368.000000</td>\n",
       "      <td id=\"T_6feb9_row26_col2\" class=\"data row26 col2\" >39266792</td>\n",
       "      <td id=\"T_6feb9_row26_col3\" class=\"data row26 col3\" >2201-03-23 12:04:00</td>\n",
       "      <td id=\"T_6feb9_row26_col4\" class=\"data row26 col4\" >2201-03-26 14:24:00</td>\n",
       "      <td id=\"T_6feb9_row26_col5\" class=\"data row26 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row26_col6\" class=\"data row26 col6\" >BLACK/AFRICAN AMERICAN</td>\n",
       "      <td id=\"T_6feb9_row26_col7\" class=\"data row26 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row26_col8\" class=\"data row26 col8\" >TRANSFER</td>\n",
       "      <td id=\"T_6feb9_row26_col9\" class=\"data row26 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row26_col10\" class=\"data row26 col10\" >98.100000</td>\n",
       "      <td id=\"T_6feb9_row26_col11\" class=\"data row26 col11\" >76.000000</td>\n",
       "      <td id=\"T_6feb9_row26_col12\" class=\"data row26 col12\" >18.000000</td>\n",
       "      <td id=\"T_6feb9_row26_col13\" class=\"data row26 col13\" >100.000000</td>\n",
       "      <td id=\"T_6feb9_row26_col14\" class=\"data row26 col14\" >181.000000</td>\n",
       "      <td id=\"T_6feb9_row26_col15\" class=\"data row26 col15\" >94.000000</td>\n",
       "      <td id=\"T_6feb9_row26_col16\" class=\"data row26 col16\" >3</td>\n",
       "      <td id=\"T_6feb9_row26_col17\" class=\"data row26 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row26_col18\" class=\"data row26 col18\" >4460.000000</td>\n",
       "      <td id=\"T_6feb9_row26_col19\" class=\"data row26 col19\" >12</td>\n",
       "      <td id=\"T_6feb9_row26_col20\" class=\"data row26 col20\" >Monday</td>\n",
       "      <td id=\"T_6feb9_row26_col21\" class=\"data row26 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row26_col22\" class=\"data row26 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row26_col23\" class=\"data row26 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
       "      <td id=\"T_6feb9_row27_col0\" class=\"data row27 col0\" >10002930</td>\n",
       "      <td id=\"T_6feb9_row27_col1\" class=\"data row27 col1\" >25922998.000000</td>\n",
       "      <td id=\"T_6feb9_row27_col2\" class=\"data row27 col2\" >30193781</td>\n",
       "      <td id=\"T_6feb9_row27_col3\" class=\"data row27 col3\" >2198-04-17 11:42:00</td>\n",
       "      <td id=\"T_6feb9_row27_col4\" class=\"data row27 col4\" >2198-04-17 21:24:00</td>\n",
       "      <td id=\"T_6feb9_row27_col5\" class=\"data row27 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row27_col6\" class=\"data row27 col6\" >BLACK/AFRICAN AMERICAN</td>\n",
       "      <td id=\"T_6feb9_row27_col7\" class=\"data row27 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row27_col8\" class=\"data row27 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row27_col9\" class=\"data row27 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row27_col10\" class=\"data row27 col10\" >98.200000</td>\n",
       "      <td id=\"T_6feb9_row27_col11\" class=\"data row27 col11\" >88.000000</td>\n",
       "      <td id=\"T_6feb9_row27_col12\" class=\"data row27 col12\" >16.000000</td>\n",
       "      <td id=\"T_6feb9_row27_col13\" class=\"data row27 col13\" >100.000000</td>\n",
       "      <td id=\"T_6feb9_row27_col14\" class=\"data row27 col14\" >150.000000</td>\n",
       "      <td id=\"T_6feb9_row27_col15\" class=\"data row27 col15\" >98.000000</td>\n",
       "      <td id=\"T_6feb9_row27_col16\" class=\"data row27 col16\" >3</td>\n",
       "      <td id=\"T_6feb9_row27_col17\" class=\"data row27 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row27_col18\" class=\"data row27 col18\" >582.000000</td>\n",
       "      <td id=\"T_6feb9_row27_col19\" class=\"data row27 col19\" >11</td>\n",
       "      <td id=\"T_6feb9_row27_col20\" class=\"data row27 col20\" >Tuesday</td>\n",
       "      <td id=\"T_6feb9_row27_col21\" class=\"data row27 col21\" >0</td>\n",
       "      <td id=\"T_6feb9_row27_col22\" class=\"data row27 col22\" >0</td>\n",
       "      <td id=\"T_6feb9_row27_col23\" class=\"data row27 col23\" >False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
       "      <td id=\"T_6feb9_row28_col0\" class=\"data row28 col0\" >10002930</td>\n",
       "      <td id=\"T_6feb9_row28_col1\" class=\"data row28 col1\" >28477649.000000</td>\n",
       "      <td id=\"T_6feb9_row28_col2\" class=\"data row28 col2\" >38615683</td>\n",
       "      <td id=\"T_6feb9_row28_col3\" class=\"data row28 col3\" >2197-04-07 03:20:00</td>\n",
       "      <td id=\"T_6feb9_row28_col4\" class=\"data row28 col4\" >2197-04-07 06:56:40</td>\n",
       "      <td id=\"T_6feb9_row28_col5\" class=\"data row28 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row28_col6\" class=\"data row28 col6\" >BLACK/AFRICAN AMERICAN</td>\n",
       "      <td id=\"T_6feb9_row28_col7\" class=\"data row28 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row28_col8\" class=\"data row28 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row28_col9\" class=\"data row28 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row28_col10\" class=\"data row28 col10\" >97.500000</td>\n",
       "      <td id=\"T_6feb9_row28_col11\" class=\"data row28 col11\" >108.000000</td>\n",
       "      <td id=\"T_6feb9_row28_col12\" class=\"data row28 col12\" >16.000000</td>\n",
       "      <td id=\"T_6feb9_row28_col13\" class=\"data row28 col13\" >100.000000</td>\n",
       "      <td id=\"T_6feb9_row28_col14\" class=\"data row28 col14\" >154.000000</td>\n",
       "      <td id=\"T_6feb9_row28_col15\" class=\"data row28 col15\" >92.000000</td>\n",
       "      <td id=\"T_6feb9_row28_col16\" class=\"data row28 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row28_col17\" class=\"data row28 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row28_col18\" class=\"data row28 col18\" >216.666667</td>\n",
       "      <td id=\"T_6feb9_row28_col19\" class=\"data row28 col19\" >3</td>\n",
       "      <td id=\"T_6feb9_row28_col20\" class=\"data row28 col20\" >Friday</td>\n",
       "      <td id=\"T_6feb9_row28_col21\" class=\"data row28 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row28_col22\" class=\"data row28 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row28_col23\" class=\"data row28 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
       "      <td id=\"T_6feb9_row29_col0\" class=\"data row29 col0\" >10002930</td>\n",
       "      <td id=\"T_6feb9_row29_col1\" class=\"data row29 col1\" >25282382.000000</td>\n",
       "      <td id=\"T_6feb9_row29_col2\" class=\"data row29 col2\" >35540249</td>\n",
       "      <td id=\"T_6feb9_row29_col3\" class=\"data row29 col3\" >2197-04-16 22:57:00</td>\n",
       "      <td id=\"T_6feb9_row29_col4\" class=\"data row29 col4\" >2197-04-17 09:48:00</td>\n",
       "      <td id=\"T_6feb9_row29_col5\" class=\"data row29 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row29_col6\" class=\"data row29 col6\" >BLACK/AFRICAN AMERICAN</td>\n",
       "      <td id=\"T_6feb9_row29_col7\" class=\"data row29 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row29_col8\" class=\"data row29 col8\" >HOME</td>\n",
       "      <td id=\"T_6feb9_row29_col9\" class=\"data row29 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row29_col10\" class=\"data row29 col10\" >98.500000</td>\n",
       "      <td id=\"T_6feb9_row29_col11\" class=\"data row29 col11\" >110.000000</td>\n",
       "      <td id=\"T_6feb9_row29_col12\" class=\"data row29 col12\" >18.000000</td>\n",
       "      <td id=\"T_6feb9_row29_col13\" class=\"data row29 col13\" >100.000000</td>\n",
       "      <td id=\"T_6feb9_row29_col14\" class=\"data row29 col14\" >123.000000</td>\n",
       "      <td id=\"T_6feb9_row29_col15\" class=\"data row29 col15\" >67.000000</td>\n",
       "      <td id=\"T_6feb9_row29_col16\" class=\"data row29 col16\" >3</td>\n",
       "      <td id=\"T_6feb9_row29_col17\" class=\"data row29 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row29_col18\" class=\"data row29 col18\" >651.000000</td>\n",
       "      <td id=\"T_6feb9_row29_col19\" class=\"data row29 col19\" >22</td>\n",
       "      <td id=\"T_6feb9_row29_col20\" class=\"data row29 col20\" >Sunday</td>\n",
       "      <td id=\"T_6feb9_row29_col21\" class=\"data row29 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row29_col22\" class=\"data row29 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row29_col23\" class=\"data row29 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
       "      <td id=\"T_6feb9_row30_col0\" class=\"data row30 col0\" >10002930</td>\n",
       "      <td id=\"T_6feb9_row30_col1\" class=\"data row30 col1\" >23720373.000000</td>\n",
       "      <td id=\"T_6feb9_row30_col2\" class=\"data row30 col2\" >35114287</td>\n",
       "      <td id=\"T_6feb9_row30_col3\" class=\"data row30 col3\" >2199-02-17 14:32:00</td>\n",
       "      <td id=\"T_6feb9_row30_col4\" class=\"data row30 col4\" >2199-02-19 13:38:00</td>\n",
       "      <td id=\"T_6feb9_row30_col5\" class=\"data row30 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row30_col6\" class=\"data row30 col6\" >BLACK/AFRICAN AMERICAN</td>\n",
       "      <td id=\"T_6feb9_row30_col7\" class=\"data row30 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row30_col8\" class=\"data row30 col8\" >TRANSFER</td>\n",
       "      <td id=\"T_6feb9_row30_col9\" class=\"data row30 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row30_col10\" class=\"data row30 col10\" >98.900000</td>\n",
       "      <td id=\"T_6feb9_row30_col11\" class=\"data row30 col11\" >102.000000</td>\n",
       "      <td id=\"T_6feb9_row30_col12\" class=\"data row30 col12\" >20.000000</td>\n",
       "      <td id=\"T_6feb9_row30_col13\" class=\"data row30 col13\" >100.000000</td>\n",
       "      <td id=\"T_6feb9_row30_col14\" class=\"data row30 col14\" >180.000000</td>\n",
       "      <td id=\"T_6feb9_row30_col15\" class=\"data row30 col15\" >85.000000</td>\n",
       "      <td id=\"T_6feb9_row30_col16\" class=\"data row30 col16\" >4</td>\n",
       "      <td id=\"T_6feb9_row30_col17\" class=\"data row30 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row30_col18\" class=\"data row30 col18\" >2826.000000</td>\n",
       "      <td id=\"T_6feb9_row30_col19\" class=\"data row30 col19\" >14</td>\n",
       "      <td id=\"T_6feb9_row30_col20\" class=\"data row30 col20\" >Sunday</td>\n",
       "      <td id=\"T_6feb9_row30_col21\" class=\"data row30 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row30_col22\" class=\"data row30 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row30_col23\" class=\"data row30 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
       "      <td id=\"T_6feb9_row31_col0\" class=\"data row31 col0\" >10002930</td>\n",
       "      <td id=\"T_6feb9_row31_col1\" class=\"data row31 col1\" >20846853.000000</td>\n",
       "      <td id=\"T_6feb9_row31_col2\" class=\"data row31 col2\" >39910144</td>\n",
       "      <td id=\"T_6feb9_row31_col3\" class=\"data row31 col3\" >2201-02-12 15:11:00</td>\n",
       "      <td id=\"T_6feb9_row31_col4\" class=\"data row31 col4\" >2201-02-13 11:11:00</td>\n",
       "      <td id=\"T_6feb9_row31_col5\" class=\"data row31 col5\" >F</td>\n",
       "      <td id=\"T_6feb9_row31_col6\" class=\"data row31 col6\" >BLACK/AFRICAN AMERICAN</td>\n",
       "      <td id=\"T_6feb9_row31_col7\" class=\"data row31 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row31_col8\" class=\"data row31 col8\" >HOME</td>\n",
       "      <td id=\"T_6feb9_row31_col9\" class=\"data row31 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row31_col10\" class=\"data row31 col10\" >97.700000</td>\n",
       "      <td id=\"T_6feb9_row31_col11\" class=\"data row31 col11\" >103.000000</td>\n",
       "      <td id=\"T_6feb9_row31_col12\" class=\"data row31 col12\" >18.000000</td>\n",
       "      <td id=\"T_6feb9_row31_col13\" class=\"data row31 col13\" >97.000000</td>\n",
       "      <td id=\"T_6feb9_row31_col14\" class=\"data row31 col14\" >137.000000</td>\n",
       "      <td id=\"T_6feb9_row31_col15\" class=\"data row31 col15\" >87.000000</td>\n",
       "      <td id=\"T_6feb9_row31_col16\" class=\"data row31 col16\" >3</td>\n",
       "      <td id=\"T_6feb9_row31_col17\" class=\"data row31 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row31_col18\" class=\"data row31 col18\" >1200.000000</td>\n",
       "      <td id=\"T_6feb9_row31_col19\" class=\"data row31 col19\" >15</td>\n",
       "      <td id=\"T_6feb9_row31_col20\" class=\"data row31 col20\" >Thursday</td>\n",
       "      <td id=\"T_6feb9_row31_col21\" class=\"data row31 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row31_col22\" class=\"data row31 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row31_col23\" class=\"data row31 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
       "      <td id=\"T_6feb9_row32_col0\" class=\"data row32 col0\" >10021938</td>\n",
       "      <td id=\"T_6feb9_row32_col1\" class=\"data row32 col1\" >nan</td>\n",
       "      <td id=\"T_6feb9_row32_col2\" class=\"data row32 col2\" >38449411</td>\n",
       "      <td id=\"T_6feb9_row32_col3\" class=\"data row32 col3\" >2181-09-02 19:21:00</td>\n",
       "      <td id=\"T_6feb9_row32_col4\" class=\"data row32 col4\" >2181-09-03 01:49:00</td>\n",
       "      <td id=\"T_6feb9_row32_col5\" class=\"data row32 col5\" >M</td>\n",
       "      <td id=\"T_6feb9_row32_col6\" class=\"data row32 col6\" >WHITE</td>\n",
       "      <td id=\"T_6feb9_row32_col7\" class=\"data row32 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row32_col8\" class=\"data row32 col8\" >HOME</td>\n",
       "      <td id=\"T_6feb9_row32_col9\" class=\"data row32 col9\" >0</td>\n",
       "      <td id=\"T_6feb9_row32_col10\" class=\"data row32 col10\" >nan</td>\n",
       "      <td id=\"T_6feb9_row32_col11\" class=\"data row32 col11\" >nan</td>\n",
       "      <td id=\"T_6feb9_row32_col12\" class=\"data row32 col12\" >nan</td>\n",
       "      <td id=\"T_6feb9_row32_col13\" class=\"data row32 col13\" >nan</td>\n",
       "      <td id=\"T_6feb9_row32_col14\" class=\"data row32 col14\" >nan</td>\n",
       "      <td id=\"T_6feb9_row32_col15\" class=\"data row32 col15\" >nan</td>\n",
       "      <td id=\"T_6feb9_row32_col16\" class=\"data row32 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row32_col17\" class=\"data row32 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row32_col18\" class=\"data row32 col18\" >388.000000</td>\n",
       "      <td id=\"T_6feb9_row32_col19\" class=\"data row32 col19\" >19</td>\n",
       "      <td id=\"T_6feb9_row32_col20\" class=\"data row32 col20\" >Sunday</td>\n",
       "      <td id=\"T_6feb9_row32_col21\" class=\"data row32 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row32_col22\" class=\"data row32 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row32_col23\" class=\"data row32 col23\" >False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
       "      <td id=\"T_6feb9_row33_col0\" class=\"data row33 col0\" >10021938</td>\n",
       "      <td id=\"T_6feb9_row33_col1\" class=\"data row33 col1\" >23112364.000000</td>\n",
       "      <td id=\"T_6feb9_row33_col2\" class=\"data row33 col2\" >38890884</td>\n",
       "      <td id=\"T_6feb9_row33_col3\" class=\"data row33 col3\" >2181-10-12 20:17:00</td>\n",
       "      <td id=\"T_6feb9_row33_col4\" class=\"data row33 col4\" >2181-10-13 02:52:00</td>\n",
       "      <td id=\"T_6feb9_row33_col5\" class=\"data row33 col5\" >M</td>\n",
       "      <td id=\"T_6feb9_row33_col6\" class=\"data row33 col6\" >WHITE</td>\n",
       "      <td id=\"T_6feb9_row33_col7\" class=\"data row33 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row33_col8\" class=\"data row33 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row33_col9\" class=\"data row33 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row33_col10\" class=\"data row33 col10\" >99.800000</td>\n",
       "      <td id=\"T_6feb9_row33_col11\" class=\"data row33 col11\" >110.000000</td>\n",
       "      <td id=\"T_6feb9_row33_col12\" class=\"data row33 col12\" >18.000000</td>\n",
       "      <td id=\"T_6feb9_row33_col13\" class=\"data row33 col13\" >93.000000</td>\n",
       "      <td id=\"T_6feb9_row33_col14\" class=\"data row33 col14\" >178.000000</td>\n",
       "      <td id=\"T_6feb9_row33_col15\" class=\"data row33 col15\" >85.000000</td>\n",
       "      <td id=\"T_6feb9_row33_col16\" class=\"data row33 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row33_col17\" class=\"data row33 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row33_col18\" class=\"data row33 col18\" >395.000000</td>\n",
       "      <td id=\"T_6feb9_row33_col19\" class=\"data row33 col19\" >20</td>\n",
       "      <td id=\"T_6feb9_row33_col20\" class=\"data row33 col20\" >Friday</td>\n",
       "      <td id=\"T_6feb9_row33_col21\" class=\"data row33 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row33_col22\" class=\"data row33 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row33_col23\" class=\"data row33 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
       "      <td id=\"T_6feb9_row34_col0\" class=\"data row34 col0\" >10021938</td>\n",
       "      <td id=\"T_6feb9_row34_col1\" class=\"data row34 col1\" >27154822.000000</td>\n",
       "      <td id=\"T_6feb9_row34_col2\" class=\"data row34 col2\" >32204198</td>\n",
       "      <td id=\"T_6feb9_row34_col3\" class=\"data row34 col3\" >2181-10-25 09:23:00</td>\n",
       "      <td id=\"T_6feb9_row34_col4\" class=\"data row34 col4\" >2181-10-25 11:35:00</td>\n",
       "      <td id=\"T_6feb9_row34_col5\" class=\"data row34 col5\" >M</td>\n",
       "      <td id=\"T_6feb9_row34_col6\" class=\"data row34 col6\" >WHITE</td>\n",
       "      <td id=\"T_6feb9_row34_col7\" class=\"data row34 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row34_col8\" class=\"data row34 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row34_col9\" class=\"data row34 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row34_col10\" class=\"data row34 col10\" >98.400000</td>\n",
       "      <td id=\"T_6feb9_row34_col11\" class=\"data row34 col11\" >89.000000</td>\n",
       "      <td id=\"T_6feb9_row34_col12\" class=\"data row34 col12\" >18.000000</td>\n",
       "      <td id=\"T_6feb9_row34_col13\" class=\"data row34 col13\" >97.000000</td>\n",
       "      <td id=\"T_6feb9_row34_col14\" class=\"data row34 col14\" >217.000000</td>\n",
       "      <td id=\"T_6feb9_row34_col15\" class=\"data row34 col15\" >116.000000</td>\n",
       "      <td id=\"T_6feb9_row34_col16\" class=\"data row34 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row34_col17\" class=\"data row34 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row34_col18\" class=\"data row34 col18\" >132.000000</td>\n",
       "      <td id=\"T_6feb9_row34_col19\" class=\"data row34 col19\" >9</td>\n",
       "      <td id=\"T_6feb9_row34_col20\" class=\"data row34 col20\" >Thursday</td>\n",
       "      <td id=\"T_6feb9_row34_col21\" class=\"data row34 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row34_col22\" class=\"data row34 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row34_col23\" class=\"data row34 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
       "      <td id=\"T_6feb9_row35_col0\" class=\"data row35 col0\" >10005866</td>\n",
       "      <td id=\"T_6feb9_row35_col1\" class=\"data row35 col1\" >27167814.000000</td>\n",
       "      <td id=\"T_6feb9_row35_col2\" class=\"data row35 col2\" >30804580</td>\n",
       "      <td id=\"T_6feb9_row35_col3\" class=\"data row35 col3\" >2148-03-10 04:46:00</td>\n",
       "      <td id=\"T_6feb9_row35_col4\" class=\"data row35 col4\" >2148-03-10 16:18:48</td>\n",
       "      <td id=\"T_6feb9_row35_col5\" class=\"data row35 col5\" >M</td>\n",
       "      <td id=\"T_6feb9_row35_col6\" class=\"data row35 col6\" >PORTUGUESE</td>\n",
       "      <td id=\"T_6feb9_row35_col7\" class=\"data row35 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row35_col8\" class=\"data row35 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row35_col9\" class=\"data row35 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row35_col10\" class=\"data row35 col10\" >97.400000</td>\n",
       "      <td id=\"T_6feb9_row35_col11\" class=\"data row35 col11\" >66.000000</td>\n",
       "      <td id=\"T_6feb9_row35_col12\" class=\"data row35 col12\" >18.000000</td>\n",
       "      <td id=\"T_6feb9_row35_col13\" class=\"data row35 col13\" >99.000000</td>\n",
       "      <td id=\"T_6feb9_row35_col14\" class=\"data row35 col14\" >111.000000</td>\n",
       "      <td id=\"T_6feb9_row35_col15\" class=\"data row35 col15\" >68.000000</td>\n",
       "      <td id=\"T_6feb9_row35_col16\" class=\"data row35 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row35_col17\" class=\"data row35 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row35_col18\" class=\"data row35 col18\" >692.800000</td>\n",
       "      <td id=\"T_6feb9_row35_col19\" class=\"data row35 col19\" >4</td>\n",
       "      <td id=\"T_6feb9_row35_col20\" class=\"data row35 col20\" >Sunday</td>\n",
       "      <td id=\"T_6feb9_row35_col21\" class=\"data row35 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row35_col22\" class=\"data row35 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row35_col23\" class=\"data row35 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
       "      <td id=\"T_6feb9_row36_col0\" class=\"data row36 col0\" >10005866</td>\n",
       "      <td id=\"T_6feb9_row36_col1\" class=\"data row36 col1\" >26134779.000000</td>\n",
       "      <td id=\"T_6feb9_row36_col2\" class=\"data row36 col2\" >31806264</td>\n",
       "      <td id=\"T_6feb9_row36_col3\" class=\"data row36 col3\" >2149-09-12 15:31:00</td>\n",
       "      <td id=\"T_6feb9_row36_col4\" class=\"data row36 col4\" >2149-09-13 09:02:00</td>\n",
       "      <td id=\"T_6feb9_row36_col5\" class=\"data row36 col5\" >M</td>\n",
       "      <td id=\"T_6feb9_row36_col6\" class=\"data row36 col6\" >PORTUGUESE</td>\n",
       "      <td id=\"T_6feb9_row36_col7\" class=\"data row36 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row36_col8\" class=\"data row36 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row36_col9\" class=\"data row36 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row36_col10\" class=\"data row36 col10\" >98.200000</td>\n",
       "      <td id=\"T_6feb9_row36_col11\" class=\"data row36 col11\" >84.000000</td>\n",
       "      <td id=\"T_6feb9_row36_col12\" class=\"data row36 col12\" >18.000000</td>\n",
       "      <td id=\"T_6feb9_row36_col13\" class=\"data row36 col13\" >100.000000</td>\n",
       "      <td id=\"T_6feb9_row36_col14\" class=\"data row36 col14\" >175.000000</td>\n",
       "      <td id=\"T_6feb9_row36_col15\" class=\"data row36 col15\" >80.000000</td>\n",
       "      <td id=\"T_6feb9_row36_col16\" class=\"data row36 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row36_col17\" class=\"data row36 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row36_col18\" class=\"data row36 col18\" >1051.000000</td>\n",
       "      <td id=\"T_6feb9_row36_col19\" class=\"data row36 col19\" >15</td>\n",
       "      <td id=\"T_6feb9_row36_col20\" class=\"data row36 col20\" >Friday</td>\n",
       "      <td id=\"T_6feb9_row36_col21\" class=\"data row36 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row36_col22\" class=\"data row36 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row36_col23\" class=\"data row36 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
       "      <td id=\"T_6feb9_row37_col0\" class=\"data row37 col0\" >10005866</td>\n",
       "      <td id=\"T_6feb9_row37_col1\" class=\"data row37 col1\" >22589518.000000</td>\n",
       "      <td id=\"T_6feb9_row37_col2\" class=\"data row37 col2\" >32537287</td>\n",
       "      <td id=\"T_6feb9_row37_col3\" class=\"data row37 col3\" >2149-02-11 08:52:00</td>\n",
       "      <td id=\"T_6feb9_row37_col4\" class=\"data row37 col4\" >2149-02-11 23:09:00</td>\n",
       "      <td id=\"T_6feb9_row37_col5\" class=\"data row37 col5\" >M</td>\n",
       "      <td id=\"T_6feb9_row37_col6\" class=\"data row37 col6\" >PORTUGUESE</td>\n",
       "      <td id=\"T_6feb9_row37_col7\" class=\"data row37 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row37_col8\" class=\"data row37 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row37_col9\" class=\"data row37 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row37_col10\" class=\"data row37 col10\" >98.000000</td>\n",
       "      <td id=\"T_6feb9_row37_col11\" class=\"data row37 col11\" >82.000000</td>\n",
       "      <td id=\"T_6feb9_row37_col12\" class=\"data row37 col12\" >22.000000</td>\n",
       "      <td id=\"T_6feb9_row37_col13\" class=\"data row37 col13\" >100.000000</td>\n",
       "      <td id=\"T_6feb9_row37_col14\" class=\"data row37 col14\" >157.000000</td>\n",
       "      <td id=\"T_6feb9_row37_col15\" class=\"data row37 col15\" >82.000000</td>\n",
       "      <td id=\"T_6feb9_row37_col16\" class=\"data row37 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row37_col17\" class=\"data row37 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row37_col18\" class=\"data row37 col18\" >857.000000</td>\n",
       "      <td id=\"T_6feb9_row37_col19\" class=\"data row37 col19\" >8</td>\n",
       "      <td id=\"T_6feb9_row37_col20\" class=\"data row37 col20\" >Tuesday</td>\n",
       "      <td id=\"T_6feb9_row37_col21\" class=\"data row37 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row37_col22\" class=\"data row37 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row37_col23\" class=\"data row37 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
       "      <td id=\"T_6feb9_row38_col0\" class=\"data row38 col0\" >10005866</td>\n",
       "      <td id=\"T_6feb9_row38_col1\" class=\"data row38 col1\" >nan</td>\n",
       "      <td id=\"T_6feb9_row38_col2\" class=\"data row38 col2\" >31023359</td>\n",
       "      <td id=\"T_6feb9_row38_col3\" class=\"data row38 col3\" >2149-09-28 01:53:00</td>\n",
       "      <td id=\"T_6feb9_row38_col4\" class=\"data row38 col4\" >2149-09-28 16:26:00</td>\n",
       "      <td id=\"T_6feb9_row38_col5\" class=\"data row38 col5\" >M</td>\n",
       "      <td id=\"T_6feb9_row38_col6\" class=\"data row38 col6\" >PORTUGUESE</td>\n",
       "      <td id=\"T_6feb9_row38_col7\" class=\"data row38 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row38_col8\" class=\"data row38 col8\" >HOME</td>\n",
       "      <td id=\"T_6feb9_row38_col9\" class=\"data row38 col9\" >0</td>\n",
       "      <td id=\"T_6feb9_row38_col10\" class=\"data row38 col10\" >97.200000</td>\n",
       "      <td id=\"T_6feb9_row38_col11\" class=\"data row38 col11\" >88.000000</td>\n",
       "      <td id=\"T_6feb9_row38_col12\" class=\"data row38 col12\" >18.000000</td>\n",
       "      <td id=\"T_6feb9_row38_col13\" class=\"data row38 col13\" >100.000000</td>\n",
       "      <td id=\"T_6feb9_row38_col14\" class=\"data row38 col14\" >163.000000</td>\n",
       "      <td id=\"T_6feb9_row38_col15\" class=\"data row38 col15\" >89.000000</td>\n",
       "      <td id=\"T_6feb9_row38_col16\" class=\"data row38 col16\" >4</td>\n",
       "      <td id=\"T_6feb9_row38_col17\" class=\"data row38 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row38_col18\" class=\"data row38 col18\" >873.000000</td>\n",
       "      <td id=\"T_6feb9_row38_col19\" class=\"data row38 col19\" >1</td>\n",
       "      <td id=\"T_6feb9_row38_col20\" class=\"data row38 col20\" >Sunday</td>\n",
       "      <td id=\"T_6feb9_row38_col21\" class=\"data row38 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row38_col22\" class=\"data row38 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row38_col23\" class=\"data row38 col23\" >False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
       "      <td id=\"T_6feb9_row39_col0\" class=\"data row39 col0\" >10005866</td>\n",
       "      <td id=\"T_6feb9_row39_col1\" class=\"data row39 col1\" >21636229.000000</td>\n",
       "      <td id=\"T_6feb9_row39_col2\" class=\"data row39 col2\" >30225689</td>\n",
       "      <td id=\"T_6feb9_row39_col3\" class=\"data row39 col3\" >2149-09-20 05:50:00</td>\n",
       "      <td id=\"T_6feb9_row39_col4\" class=\"data row39 col4\" >2149-09-20 15:53:00</td>\n",
       "      <td id=\"T_6feb9_row39_col5\" class=\"data row39 col5\" >M</td>\n",
       "      <td id=\"T_6feb9_row39_col6\" class=\"data row39 col6\" >PORTUGUESE</td>\n",
       "      <td id=\"T_6feb9_row39_col7\" class=\"data row39 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row39_col8\" class=\"data row39 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row39_col9\" class=\"data row39 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row39_col10\" class=\"data row39 col10\" >97.600000</td>\n",
       "      <td id=\"T_6feb9_row39_col11\" class=\"data row39 col11\" >72.000000</td>\n",
       "      <td id=\"T_6feb9_row39_col12\" class=\"data row39 col12\" >16.000000</td>\n",
       "      <td id=\"T_6feb9_row39_col13\" class=\"data row39 col13\" >100.000000</td>\n",
       "      <td id=\"T_6feb9_row39_col14\" class=\"data row39 col14\" >163.000000</td>\n",
       "      <td id=\"T_6feb9_row39_col15\" class=\"data row39 col15\" >81.000000</td>\n",
       "      <td id=\"T_6feb9_row39_col16\" class=\"data row39 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row39_col17\" class=\"data row39 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row39_col18\" class=\"data row39 col18\" >603.000000</td>\n",
       "      <td id=\"T_6feb9_row39_col19\" class=\"data row39 col19\" >5</td>\n",
       "      <td id=\"T_6feb9_row39_col20\" class=\"data row39 col20\" >Saturday</td>\n",
       "      <td id=\"T_6feb9_row39_col21\" class=\"data row39 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row39_col22\" class=\"data row39 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row39_col23\" class=\"data row39 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
       "      <td id=\"T_6feb9_row40_col0\" class=\"data row40 col0\" >10005866</td>\n",
       "      <td id=\"T_6feb9_row40_col1\" class=\"data row40 col1\" >nan</td>\n",
       "      <td id=\"T_6feb9_row40_col2\" class=\"data row40 col2\" >32281632</td>\n",
       "      <td id=\"T_6feb9_row40_col3\" class=\"data row40 col3\" >2148-06-13 08:36:00</td>\n",
       "      <td id=\"T_6feb9_row40_col4\" class=\"data row40 col4\" >2148-06-13 17:30:00</td>\n",
       "      <td id=\"T_6feb9_row40_col5\" class=\"data row40 col5\" >M</td>\n",
       "      <td id=\"T_6feb9_row40_col6\" class=\"data row40 col6\" >PORTUGUESE</td>\n",
       "      <td id=\"T_6feb9_row40_col7\" class=\"data row40 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row40_col8\" class=\"data row40 col8\" >TRANSFER</td>\n",
       "      <td id=\"T_6feb9_row40_col9\" class=\"data row40 col9\" >0</td>\n",
       "      <td id=\"T_6feb9_row40_col10\" class=\"data row40 col10\" >97.900000</td>\n",
       "      <td id=\"T_6feb9_row40_col11\" class=\"data row40 col11\" >63.000000</td>\n",
       "      <td id=\"T_6feb9_row40_col12\" class=\"data row40 col12\" >18.000000</td>\n",
       "      <td id=\"T_6feb9_row40_col13\" class=\"data row40 col13\" >99.000000</td>\n",
       "      <td id=\"T_6feb9_row40_col14\" class=\"data row40 col14\" >149.000000</td>\n",
       "      <td id=\"T_6feb9_row40_col15\" class=\"data row40 col15\" >72.000000</td>\n",
       "      <td id=\"T_6feb9_row40_col16\" class=\"data row40 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row40_col17\" class=\"data row40 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row40_col18\" class=\"data row40 col18\" >534.000000</td>\n",
       "      <td id=\"T_6feb9_row40_col19\" class=\"data row40 col19\" >8</td>\n",
       "      <td id=\"T_6feb9_row40_col20\" class=\"data row40 col20\" >Thursday</td>\n",
       "      <td id=\"T_6feb9_row40_col21\" class=\"data row40 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row40_col22\" class=\"data row40 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row40_col23\" class=\"data row40 col23\" >False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
       "      <td id=\"T_6feb9_row41_col0\" class=\"data row41 col0\" >10005866</td>\n",
       "      <td id=\"T_6feb9_row41_col1\" class=\"data row41 col1\" >23514107.000000</td>\n",
       "      <td id=\"T_6feb9_row41_col2\" class=\"data row41 col2\" >35681380</td>\n",
       "      <td id=\"T_6feb9_row41_col3\" class=\"data row41 col3\" >2149-06-20 10:20:00</td>\n",
       "      <td id=\"T_6feb9_row41_col4\" class=\"data row41 col4\" >2149-06-20 20:59:00</td>\n",
       "      <td id=\"T_6feb9_row41_col5\" class=\"data row41 col5\" >M</td>\n",
       "      <td id=\"T_6feb9_row41_col6\" class=\"data row41 col6\" >PORTUGUESE</td>\n",
       "      <td id=\"T_6feb9_row41_col7\" class=\"data row41 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row41_col8\" class=\"data row41 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row41_col9\" class=\"data row41 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row41_col10\" class=\"data row41 col10\" >98.000000</td>\n",
       "      <td id=\"T_6feb9_row41_col11\" class=\"data row41 col11\" >76.000000</td>\n",
       "      <td id=\"T_6feb9_row41_col12\" class=\"data row41 col12\" >18.000000</td>\n",
       "      <td id=\"T_6feb9_row41_col13\" class=\"data row41 col13\" >99.000000</td>\n",
       "      <td id=\"T_6feb9_row41_col14\" class=\"data row41 col14\" >147.000000</td>\n",
       "      <td id=\"T_6feb9_row41_col15\" class=\"data row41 col15\" >92.000000</td>\n",
       "      <td id=\"T_6feb9_row41_col16\" class=\"data row41 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row41_col17\" class=\"data row41 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row41_col18\" class=\"data row41 col18\" >639.000000</td>\n",
       "      <td id=\"T_6feb9_row41_col19\" class=\"data row41 col19\" >10</td>\n",
       "      <td id=\"T_6feb9_row41_col20\" class=\"data row41 col20\" >Friday</td>\n",
       "      <td id=\"T_6feb9_row41_col21\" class=\"data row41 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row41_col22\" class=\"data row41 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row41_col23\" class=\"data row41 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row42\" class=\"row_heading level0 row42\" >42</th>\n",
       "      <td id=\"T_6feb9_row42_col0\" class=\"data row42 col0\" >10005866</td>\n",
       "      <td id=\"T_6feb9_row42_col1\" class=\"data row42 col1\" >26158160.000000</td>\n",
       "      <td id=\"T_6feb9_row42_col2\" class=\"data row42 col2\" >34558830</td>\n",
       "      <td id=\"T_6feb9_row42_col3\" class=\"data row42 col3\" >2146-06-05 22:26:00</td>\n",
       "      <td id=\"T_6feb9_row42_col4\" class=\"data row42 col4\" >2146-06-06 01:45:00</td>\n",
       "      <td id=\"T_6feb9_row42_col5\" class=\"data row42 col5\" >M</td>\n",
       "      <td id=\"T_6feb9_row42_col6\" class=\"data row42 col6\" >PORTUGUESE</td>\n",
       "      <td id=\"T_6feb9_row42_col7\" class=\"data row42 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row42_col8\" class=\"data row42 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row42_col9\" class=\"data row42 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row42_col10\" class=\"data row42 col10\" >nan</td>\n",
       "      <td id=\"T_6feb9_row42_col11\" class=\"data row42 col11\" >nan</td>\n",
       "      <td id=\"T_6feb9_row42_col12\" class=\"data row42 col12\" >nan</td>\n",
       "      <td id=\"T_6feb9_row42_col13\" class=\"data row42 col13\" >nan</td>\n",
       "      <td id=\"T_6feb9_row42_col14\" class=\"data row42 col14\" >nan</td>\n",
       "      <td id=\"T_6feb9_row42_col15\" class=\"data row42 col15\" >nan</td>\n",
       "      <td id=\"T_6feb9_row42_col16\" class=\"data row42 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row42_col17\" class=\"data row42 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row42_col18\" class=\"data row42 col18\" >199.000000</td>\n",
       "      <td id=\"T_6feb9_row42_col19\" class=\"data row42 col19\" >22</td>\n",
       "      <td id=\"T_6feb9_row42_col20\" class=\"data row42 col20\" >Sunday</td>\n",
       "      <td id=\"T_6feb9_row42_col21\" class=\"data row42 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row42_col22\" class=\"data row42 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row42_col23\" class=\"data row42 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row43\" class=\"row_heading level0 row43\" >43</th>\n",
       "      <td id=\"T_6feb9_row43_col0\" class=\"data row43 col0\" >10005866</td>\n",
       "      <td id=\"T_6feb9_row43_col1\" class=\"data row43 col1\" >20364112.000000</td>\n",
       "      <td id=\"T_6feb9_row43_col2\" class=\"data row43 col2\" >31121963</td>\n",
       "      <td id=\"T_6feb9_row43_col3\" class=\"data row43 col3\" >2149-10-01 02:07:00</td>\n",
       "      <td id=\"T_6feb9_row43_col4\" class=\"data row43 col4\" >2149-10-01 18:56:59</td>\n",
       "      <td id=\"T_6feb9_row43_col5\" class=\"data row43 col5\" >M</td>\n",
       "      <td id=\"T_6feb9_row43_col6\" class=\"data row43 col6\" >PORTUGUESE</td>\n",
       "      <td id=\"T_6feb9_row43_col7\" class=\"data row43 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row43_col8\" class=\"data row43 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row43_col9\" class=\"data row43 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row43_col10\" class=\"data row43 col10\" >98.800000</td>\n",
       "      <td id=\"T_6feb9_row43_col11\" class=\"data row43 col11\" >106.000000</td>\n",
       "      <td id=\"T_6feb9_row43_col12\" class=\"data row43 col12\" >20.000000</td>\n",
       "      <td id=\"T_6feb9_row43_col13\" class=\"data row43 col13\" >100.000000</td>\n",
       "      <td id=\"T_6feb9_row43_col14\" class=\"data row43 col14\" >163.000000</td>\n",
       "      <td id=\"T_6feb9_row43_col15\" class=\"data row43 col15\" >103.000000</td>\n",
       "      <td id=\"T_6feb9_row43_col16\" class=\"data row43 col16\" >2</td>\n",
       "      <td id=\"T_6feb9_row43_col17\" class=\"data row43 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row43_col18\" class=\"data row43 col18\" >1009.983333</td>\n",
       "      <td id=\"T_6feb9_row43_col19\" class=\"data row43 col19\" >2</td>\n",
       "      <td id=\"T_6feb9_row43_col20\" class=\"data row43 col20\" >Wednesday</td>\n",
       "      <td id=\"T_6feb9_row43_col21\" class=\"data row43 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row43_col22\" class=\"data row43 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row43_col23\" class=\"data row43 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row44\" class=\"row_heading level0 row44\" >44</th>\n",
       "      <td id=\"T_6feb9_row44_col0\" class=\"data row44 col0\" >10026406</td>\n",
       "      <td id=\"T_6feb9_row44_col1\" class=\"data row44 col1\" >nan</td>\n",
       "      <td id=\"T_6feb9_row44_col2\" class=\"data row44 col2\" >39571461</td>\n",
       "      <td id=\"T_6feb9_row44_col3\" class=\"data row44 col3\" >2129-11-25 19:02:00</td>\n",
       "      <td id=\"T_6feb9_row44_col4\" class=\"data row44 col4\" >2129-11-26 00:46:00</td>\n",
       "      <td id=\"T_6feb9_row44_col5\" class=\"data row44 col5\" >M</td>\n",
       "      <td id=\"T_6feb9_row44_col6\" class=\"data row44 col6\" >WHITE</td>\n",
       "      <td id=\"T_6feb9_row44_col7\" class=\"data row44 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row44_col8\" class=\"data row44 col8\" >HOME</td>\n",
       "      <td id=\"T_6feb9_row44_col9\" class=\"data row44 col9\" >0</td>\n",
       "      <td id=\"T_6feb9_row44_col10\" class=\"data row44 col10\" >98.700000</td>\n",
       "      <td id=\"T_6feb9_row44_col11\" class=\"data row44 col11\" >118.000000</td>\n",
       "      <td id=\"T_6feb9_row44_col12\" class=\"data row44 col12\" >22.000000</td>\n",
       "      <td id=\"T_6feb9_row44_col13\" class=\"data row44 col13\" >99.000000</td>\n",
       "      <td id=\"T_6feb9_row44_col14\" class=\"data row44 col14\" >131.000000</td>\n",
       "      <td id=\"T_6feb9_row44_col15\" class=\"data row44 col15\" >89.000000</td>\n",
       "      <td id=\"T_6feb9_row44_col16\" class=\"data row44 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row44_col17\" class=\"data row44 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row44_col18\" class=\"data row44 col18\" >344.000000</td>\n",
       "      <td id=\"T_6feb9_row44_col19\" class=\"data row44 col19\" >19</td>\n",
       "      <td id=\"T_6feb9_row44_col20\" class=\"data row44 col20\" >Friday</td>\n",
       "      <td id=\"T_6feb9_row44_col21\" class=\"data row44 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row44_col22\" class=\"data row44 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row44_col23\" class=\"data row44 col23\" >False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row45\" class=\"row_heading level0 row45\" >45</th>\n",
       "      <td id=\"T_6feb9_row45_col0\" class=\"data row45 col0\" >10026406</td>\n",
       "      <td id=\"T_6feb9_row45_col1\" class=\"data row45 col1\" >25260176.000000</td>\n",
       "      <td id=\"T_6feb9_row45_col2\" class=\"data row45 col2\" >37202404</td>\n",
       "      <td id=\"T_6feb9_row45_col3\" class=\"data row45 col3\" >2129-01-02 23:41:00</td>\n",
       "      <td id=\"T_6feb9_row45_col4\" class=\"data row45 col4\" >2129-01-03 18:33:00</td>\n",
       "      <td id=\"T_6feb9_row45_col5\" class=\"data row45 col5\" >M</td>\n",
       "      <td id=\"T_6feb9_row45_col6\" class=\"data row45 col6\" >WHITE</td>\n",
       "      <td id=\"T_6feb9_row45_col7\" class=\"data row45 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row45_col8\" class=\"data row45 col8\" >ADMITTED</td>\n",
       "      <td id=\"T_6feb9_row45_col9\" class=\"data row45 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row45_col10\" class=\"data row45 col10\" >98.000000</td>\n",
       "      <td id=\"T_6feb9_row45_col11\" class=\"data row45 col11\" >105.000000</td>\n",
       "      <td id=\"T_6feb9_row45_col12\" class=\"data row45 col12\" >20.000000</td>\n",
       "      <td id=\"T_6feb9_row45_col13\" class=\"data row45 col13\" >98.000000</td>\n",
       "      <td id=\"T_6feb9_row45_col14\" class=\"data row45 col14\" >153.000000</td>\n",
       "      <td id=\"T_6feb9_row45_col15\" class=\"data row45 col15\" >77.000000</td>\n",
       "      <td id=\"T_6feb9_row45_col16\" class=\"data row45 col16\" >4</td>\n",
       "      <td id=\"T_6feb9_row45_col17\" class=\"data row45 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row45_col18\" class=\"data row45 col18\" >1132.000000</td>\n",
       "      <td id=\"T_6feb9_row45_col19\" class=\"data row45 col19\" >23</td>\n",
       "      <td id=\"T_6feb9_row45_col20\" class=\"data row45 col20\" >Sunday</td>\n",
       "      <td id=\"T_6feb9_row45_col21\" class=\"data row45 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row45_col22\" class=\"data row45 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row45_col23\" class=\"data row45 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row46\" class=\"row_heading level0 row46\" >46</th>\n",
       "      <td id=\"T_6feb9_row46_col0\" class=\"data row46 col0\" >10026406</td>\n",
       "      <td id=\"T_6feb9_row46_col1\" class=\"data row46 col1\" >25166559.000000</td>\n",
       "      <td id=\"T_6feb9_row46_col2\" class=\"data row46 col2\" >38237602</td>\n",
       "      <td id=\"T_6feb9_row46_col3\" class=\"data row46 col3\" >2133-03-01 16:42:00</td>\n",
       "      <td id=\"T_6feb9_row46_col4\" class=\"data row46 col4\" >2133-03-04 17:05:00</td>\n",
       "      <td id=\"T_6feb9_row46_col5\" class=\"data row46 col5\" >M</td>\n",
       "      <td id=\"T_6feb9_row46_col6\" class=\"data row46 col6\" >WHITE</td>\n",
       "      <td id=\"T_6feb9_row46_col7\" class=\"data row46 col7\" >WALK IN</td>\n",
       "      <td id=\"T_6feb9_row46_col8\" class=\"data row46 col8\" >HOME</td>\n",
       "      <td id=\"T_6feb9_row46_col9\" class=\"data row46 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row46_col10\" class=\"data row46 col10\" >97.000000</td>\n",
       "      <td id=\"T_6feb9_row46_col11\" class=\"data row46 col11\" >98.000000</td>\n",
       "      <td id=\"T_6feb9_row46_col12\" class=\"data row46 col12\" >20.000000</td>\n",
       "      <td id=\"T_6feb9_row46_col13\" class=\"data row46 col13\" >99.000000</td>\n",
       "      <td id=\"T_6feb9_row46_col14\" class=\"data row46 col14\" >133.000000</td>\n",
       "      <td id=\"T_6feb9_row46_col15\" class=\"data row46 col15\" >110.000000</td>\n",
       "      <td id=\"T_6feb9_row46_col16\" class=\"data row46 col16\" >4</td>\n",
       "      <td id=\"T_6feb9_row46_col17\" class=\"data row46 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row46_col18\" class=\"data row46 col18\" >4343.000000</td>\n",
       "      <td id=\"T_6feb9_row46_col19\" class=\"data row46 col19\" >16</td>\n",
       "      <td id=\"T_6feb9_row46_col20\" class=\"data row46 col20\" >Sunday</td>\n",
       "      <td id=\"T_6feb9_row46_col21\" class=\"data row46 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row46_col22\" class=\"data row46 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row46_col23\" class=\"data row46 col23\" >True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6feb9_level0_row47\" class=\"row_heading level0 row47\" >47</th>\n",
       "      <td id=\"T_6feb9_row47_col0\" class=\"data row47 col0\" >10025463</td>\n",
       "      <td id=\"T_6feb9_row47_col1\" class=\"data row47 col1\" >24470193.000000</td>\n",
       "      <td id=\"T_6feb9_row47_col2\" class=\"data row47 col2\" >35470228</td>\n",
       "      <td id=\"T_6feb9_row47_col3\" class=\"data row47 col3\" >2137-10-08 18:16:00</td>\n",
       "      <td id=\"T_6feb9_row47_col4\" class=\"data row47 col4\" >2137-10-08 21:20:50</td>\n",
       "      <td id=\"T_6feb9_row47_col5\" class=\"data row47 col5\" >M</td>\n",
       "      <td id=\"T_6feb9_row47_col6\" class=\"data row47 col6\" >WHITE</td>\n",
       "      <td id=\"T_6feb9_row47_col7\" class=\"data row47 col7\" >AMBULANCE</td>\n",
       "      <td id=\"T_6feb9_row47_col8\" class=\"data row47 col8\" >OTHER</td>\n",
       "      <td id=\"T_6feb9_row47_col9\" class=\"data row47 col9\" >1</td>\n",
       "      <td id=\"T_6feb9_row47_col10\" class=\"data row47 col10\" >nan</td>\n",
       "      <td id=\"T_6feb9_row47_col11\" class=\"data row47 col11\" >nan</td>\n",
       "      <td id=\"T_6feb9_row47_col12\" class=\"data row47 col12\" >nan</td>\n",
       "      <td id=\"T_6feb9_row47_col13\" class=\"data row47 col13\" >nan</td>\n",
       "      <td id=\"T_6feb9_row47_col14\" class=\"data row47 col14\" >nan</td>\n",
       "      <td id=\"T_6feb9_row47_col15\" class=\"data row47 col15\" >nan</td>\n",
       "      <td id=\"T_6feb9_row47_col16\" class=\"data row47 col16\" >1</td>\n",
       "      <td id=\"T_6feb9_row47_col17\" class=\"data row47 col17\" >test</td>\n",
       "      <td id=\"T_6feb9_row47_col18\" class=\"data row47 col18\" >184.833333</td>\n",
       "      <td id=\"T_6feb9_row47_col19\" class=\"data row47 col19\" >18</td>\n",
       "      <td id=\"T_6feb9_row47_col20\" class=\"data row47 col20\" >Tuesday</td>\n",
       "      <td id=\"T_6feb9_row47_col21\" class=\"data row47 col21\" >1</td>\n",
       "      <td id=\"T_6feb9_row47_col22\" class=\"data row47 col22\" >1</td>\n",
       "      <td id=\"T_6feb9_row47_col23\" class=\"data row47 col23\" >True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f51b698f010>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Consumindo o Endpoint - Código mais sofisticado para visualização\n",
    "\n",
    "# === Consumo do endpoint com comparação TARGET vs PRED ===\n",
    "import os\n",
    "import io\n",
    "import json\n",
    "import requests\n",
    "import oci\n",
    "from oci.signer import Signer\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# -----------------------------\n",
    "# Parâmetros\n",
    "# -----------------------------\n",
    "PROFILE      = \"DEFAULT\"  # ou \"LATINOAMERICA-SaoPaulo\", etc\n",
    "TARGET_COL   = \"admitted_from_ed\"  # seu alvo 0/1\n",
    "#DEPLOYMENT_ID = deployment.id  # se você já tem o objeto deployment no notebook\n",
    "# Caso esteja fora do notebook de deploy, comente a linha acima e defina manualmente:\n",
    "DEPLOYMENT_ID = \"ocid1.datasciencemodeldeployment.oc1.sa-saopaulo-1.aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa\"\n",
    "\n",
    "# Colunas de entrada exigidas pelo modelo (na ORDEM do schema)\n",
    "FEATURE_COLS = [\n",
    "    \"gender\",\"race\",\"arrival_transport\",\n",
    "    \"temperature\",\"heartrate\",\"resprate\",\"o2sat\",\"sbp\",\"dbp\",\n",
    "    \"n_diagnosis\",\"los_minutes\",\"arrival_hour\",\"arrival_weekday\"\n",
    "]\n",
    "\n",
    "# Conexão ao ADB (wallet zip local ao notebook)\n",
    "connection_parameters = {\n",
    "    \"user_name\": \"admin\",\n",
    "    \"password\": \"********\",\n",
    "    \"service_name\": \"oradb23ai_high\",\n",
    "    \"wallet_location\": \"Wallet.zip\",\n",
    "}\n",
    "\n",
    "# -----------------------------\n",
    "# 0) Lê TODAS as linhas da tabela (com todas as colunas)\n",
    "# -----------------------------\n",
    "import ads, ads.dbmixin.db_pandas_accessor  # habilita pd.DataFrame.ads\n",
    "\n",
    "df = pd.DataFrame.ads.read_sql(\n",
    "    \"\"\"\n",
    "    SELECT *\n",
    "    FROM ADMIN.DATASET_ED_ADMISSION\n",
    "    WHERE SPLIT <= :split\n",
    "    \"\"\",\n",
    "    bind_variables={\"split\": \"test\"},\n",
    "    connection_parameters=connection_parameters,\n",
    ")\n",
    "\n",
    "# Mostrar todas as colunas/linhas (cuidado: pode ser grande!)\n",
    "pd.set_option(\"display.max_columns\", None)\n",
    "pd.set_option(\"display.max_rows\", None)\n",
    "print(\"---- DataFrame carregado do banco ----\")\n",
    "\n",
    "# -----------------------------\n",
    "# 1) Normaliza nomes e cria features derivadas se faltarem\n",
    "# -----------------------------\n",
    "def normalize_cols(_df: pd.DataFrame) -> pd.DataFrame:\n",
    "    cols = (\n",
    "        _df.columns.astype(str)\n",
    "          .str.strip()\n",
    "          .str.replace(r\"\\s+\", \"_\", regex=True)\n",
    "          .str.replace(r\"[^\\w]+\", \"_\", regex=True)\n",
    "          .str.replace(r\"_+\", \"_\", regex=True)\n",
    "          .str.strip(\"_\")\n",
    "          .str.lower()\n",
    "    )\n",
    "    out = _df.copy()\n",
    "    out.columns = cols\n",
    "    return out\n",
    "\n",
    "dfn = normalize_cols(df)\n",
    "\n",
    "# converte possiveis datas\n",
    "for c in [\"intime\",\"outtime\"]:\n",
    "    if c in dfn.columns:\n",
    "        dfn[c] = pd.to_datetime(dfn[c], errors=\"coerce\")\n",
    "\n",
    "# cria as 3 features se possível\n",
    "if {\"intime\",\"outtime\"} <= set(dfn.columns):\n",
    "    dfn[\"los_minutes\"] = (dfn[\"outtime\"] - dfn[\"intime\"]).dt.total_seconds()/60\n",
    "if \"intime\" in dfn.columns:\n",
    "    dfn[\"arrival_hour\"] = dfn[\"intime\"].dt.hour\n",
    "    dfn[\"arrival_weekday\"] = dfn[\"intime\"].dt.day_name()\n",
    "\n",
    "# garante tipos básicos coerentes (numerics onde faz sentido)\n",
    "for num_col in [\"temperature\",\"heartrate\",\"resprate\",\"o2sat\",\"sbp\",\"dbp\",\"n_diagnosis\",\"los_minutes\",\"arrival_hour\"]:\n",
    "    if num_col in dfn.columns:\n",
    "        dfn[num_col] = pd.to_numeric(dfn[num_col], errors=\"coerce\")\n",
    "\n",
    "# -----------------------------\n",
    "# 2) Autenticação OCI e URL do deployment\n",
    "# -----------------------------\n",
    "from ads.model.deployment import ModelDeployment\n",
    "ads.set_auth(auth=\"api_key\", oci_config_location=\"~/.oci/config\", profile=PROFILE)\n",
    "md = ModelDeployment.from_id(DEPLOYMENT_ID)\n",
    "endpoint = md.url.rstrip(\"/\") + \"/predict\"\n",
    "print(\"Status:\", md.status)\n",
    "print(\"Endpoint:\", endpoint)\n",
    "\n",
    "config = oci.config.from_file(\"~/.oci/config\", PROFILE)\n",
    "signer = Signer(\n",
    "    tenancy=config[\"tenancy\"],\n",
    "    user=config[\"user\"],\n",
    "    fingerprint=config[\"fingerprint\"],\n",
    "    private_key_file_location=config[\"key_file\"],\n",
    "    pass_phrase=config.get(\"pass_phrase\"),\n",
    ")\n",
    "\n",
    "# -----------------------------\n",
    "# 3) Monta payloads em lotes e chama a API\n",
    "# -----------------------------\n",
    "# Verifica se todas as features existem\n",
    "missing = [c for c in FEATURE_COLS if c not in dfn.columns]\n",
    "if missing:\n",
    "    raise ValueError(f\"As seguintes colunas exigidas pelo modelo estão ausentes em dfn: {missing}\")\n",
    "\n",
    "# DataFrame apenas de features, preservando índice para recombinar depois\n",
    "X_all = dfn[FEATURE_COLS].copy()\n",
    "\n",
    "# Função que prepara payload no formato esperado: {\"data\": \"<json records>\"}\n",
    "def make_payload(df_part: pd.DataFrame) -> dict:\n",
    "    # Atenção: o seu deploy espera string JSON em orient=\"records\" dentro de \"data\"\n",
    "    return {\"data\": df_part.to_json(orient=\"records\")}\n",
    "\n",
    "# bateladas para não enviar tudo de uma vez\n",
    "BATCH = 500\n",
    "preds = []\n",
    "\n",
    "for start in range(0, len(X_all), BATCH):\n",
    "    part = X_all.iloc[start:start+BATCH]\n",
    "    payload = make_payload(part)\n",
    "    resp = requests.post(endpoint, json=payload, auth=signer, timeout=120)\n",
    "    if resp.status_code != 200:\n",
    "        raise RuntimeError(f\"Falha no /predict (status {resp.status_code}): {resp.text}\")\n",
    "    out = resp.json()\n",
    "    # Aceita { \"prediction\": [...] } ou { \"data\": [...] }\n",
    "    if isinstance(out, dict) and \"prediction\" in out:\n",
    "        preds.extend(out[\"prediction\"])\n",
    "    elif isinstance(out, dict) and \"data\" in out:\n",
    "        preds.extend(out[\"data\"])\n",
    "    else:\n",
    "        raise RuntimeError(f\"Resposta de formato inesperado: {out}\")\n",
    "\n",
    "# -----------------------------\n",
    "# 4) Junta com o DataFrame original e destaca o TARGET vs pred\n",
    "# -----------------------------\n",
    "result = dfn.copy()\n",
    "result[\"prediction\"] = preds[:len(result)]  # segurança caso algo retorne a mais\n",
    "\n",
    "if TARGET_COL in result.columns:\n",
    "    # normaliza tipo do alvo\n",
    "    result[TARGET_COL] = pd.to_numeric(result[TARGET_COL], errors=\"coerce\").astype(\"Int64\")\n",
    "    # pred em inteiro se veio prob/classe float\n",
    "    try:\n",
    "        result[\"prediction\"] = pd.to_numeric(result[\"prediction\"], errors=\"coerce\")\n",
    "        # se vier probabilidade, binariza em 0/1 só para comparação visual:\n",
    "        if result[\"prediction\"].between(0,1).all():\n",
    "            result[\"prediction_class\"] = (result[\"prediction\"] >= 0.5).astype(\"Int64\")\n",
    "            result[\"match\"] = (result[\"prediction_class\"] == result[TARGET_COL])\n",
    "        else:\n",
    "            result[\"prediction_class\"] = result[\"prediction\"].astype(\"Int64\")\n",
    "            result[\"match\"] = (result[\"prediction_class\"] == result[TARGET_COL])\n",
    "    except Exception:\n",
    "        # se for string/categoria\n",
    "        result[\"prediction_class\"] = result[\"prediction\"]\n",
    "        result[\"match\"] = (result[\"prediction_class\"].astype(str) == result[TARGET_COL].astype(str))\n",
    "else:\n",
    "    result[\"match\"] = pd.NA  # sem target para comparar\n",
    "\n",
    "print(\"---- Resultado (todas as colunas + prediction) ----\")\n",
    "display(result)\n",
    "\n",
    "# Estilo: destaca acertos/erros\n",
    "def highlight_match(row):\n",
    "    if pd.isna(row.get(\"match\", pd.NA)):\n",
    "        return [\"\"] * len(row)\n",
    "    return [\n",
    "        \"background-color: #d1fae5\" if row[\"match\"] is True and col in (TARGET_COL, \"prediction\", \"prediction_class\")\n",
    "        else \"background-color: #fee2e2\" if row[\"match\"] is False and col in (TARGET_COL, \"prediction\", \"prediction_class\")\n",
    "        else \"\"\n",
    "        for col in row.index\n",
    "    ]\n",
    "\n",
    "try:\n",
    "    styled = result.style.apply(highlight_match, axis=1)\n",
    "    display(styled)\n",
    "except Exception:\n",
    "    # fallback: sem estilo\n",
    "    display(result)"
   ]
  },
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   "source": []
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