tutorials/data/tutorial03_datasources.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Tutorial 03: Data sources\n",
    "\n",
    "This tutorial shows TemporAI `DataSource`s."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Skip the below cell if you are not on Google Colab / already have TemporAI installed:*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install temporai\n",
    "\n",
    "# Or from the repo, for the latest version:\n",
    "# %pip install git+https://github.com/vanderschaarlab/temporai.git"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## `DataSource` class\n",
    "\n",
    "A TemporAI `DataSource` implements a `load()` method which returns a TemporAI dataset.\n",
    "\n",
    "`DataSource`s are useful to load in some custom datasets, having done the necessary preprocessing,\n",
    "perhaps user-configured.\n",
    "\n",
    "Data sources, like methods, are TemporAI *plugins*, and can be loaded with the `plugin_loader`, but `plugin_type=\"datasource\"` needs to be specified.\n",
    "\n",
    "Below is an example of `SineDataSource`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tempor import plugin_loader\n",
    "\n",
    "# Get the DataSource class:\n",
    "SineDataSource = plugin_loader.get_class(\"prediction.one_off.sine\", plugin_type=\"datasource\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The constructor of the `Dataloader` can take various keyword arguments - this is where the user may customize the data\n",
    "preprocessing etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tempor.datasources.prediction.one_off.plugin_sine.SineDataSource at 0x7ff8f84f6070>"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Initialize.\n",
    "\n",
    "sine_datasource = SineDataSource(\n",
    "    no=80,  # Here, number of samples.\n",
    "    seq_len=5,  # Here, time series sequence length.\n",
    "    # ...\n",
    ")\n",
    "\n",
    "sine_datasource"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'tempor.data.dataset.OneOffPredictionDataset'>\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "OneOffPredictionDataset(\n",
       "    time_series=TimeSeriesSamples([80, *, 5]),\n",
       "    static=StaticSamples([80, 4]),\n",
       "    predictive=OneOffPredictionTaskData(targets=StaticSamples([80, 1]))\n",
       ")"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load the Dataset:\n",
    "data = sine_datasource.load()\n",
    "\n",
    "print(type(data))\n",
    "\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<p><span style=\"font-family: monospace;\">TimeSeriesSamples</span> with data:</p><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></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sample_idx</th>\n",
       "      <th>time_idx</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
       "      <th>0</th>\n",
       "      <td>-0.151203</td>\n",
       "      <td>0.206110</td>\n",
       "      <td>0.783078</td>\n",
       "      <td>0.768667</td>\n",
       "      <td>0.957344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.679518</td>\n",
       "      <td>0.785370</td>\n",
       "      <td>0.913243</td>\n",
       "      <td>0.999923</td>\n",
       "      <td>0.973799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.997174</td>\n",
       "      <td>0.999603</td>\n",
       "      <td>0.985913</td>\n",
       "      <td>0.784278</td>\n",
       "      <td>0.730349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.561921</td>\n",
       "      <td>0.749235</td>\n",
       "      <td>0.996514</td>\n",
       "      <td>0.218111</td>\n",
       "      <td>0.291970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.297606</td>\n",
       "      <td>0.150635</td>\n",
       "      <td>0.944377</td>\n",
       "      <td>-0.445537</td>\n",
       "      <td>-0.224335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">79</th>\n",
       "      <th>0</th>\n",
       "      <td>0.999730</td>\n",
       "      <td>0.101680</td>\n",
       "      <td>-0.976039</td>\n",
       "      <td>-0.999547</td>\n",
       "      <td>-0.715265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.803590</td>\n",
       "      <td>0.577241</td>\n",
       "      <td>-0.696389</td>\n",
       "      <td>-0.897416</td>\n",
       "      <td>-0.312411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.269220</td>\n",
       "      <td>0.903914</td>\n",
       "      <td>-0.188132</td>\n",
       "      <td>-0.586595</td>\n",
       "      <td>0.160840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.378464</td>\n",
       "      <td>0.997443</td>\n",
       "      <td>0.381883</td>\n",
       "      <td>-0.139366</td>\n",
       "      <td>0.597849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.866853</td>\n",
       "      <td>0.833703</td>\n",
       "      <td>0.826536</td>\n",
       "      <td>0.340273</td>\n",
       "      <td>0.900138</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>400 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "TimeSeriesSamples with data:\n",
       "                            0         1         2         3         4\n",
       "sample_idx time_idx                                                  \n",
       "0          0        -0.151203  0.206110  0.783078  0.768667  0.957344\n",
       "           1         0.679518  0.785370  0.913243  0.999923  0.973799\n",
       "           2         0.997174  0.999603  0.985913  0.784278  0.730349\n",
       "           3         0.561921  0.749235  0.996514  0.218111  0.291970\n",
       "           4        -0.297606  0.150635  0.944377 -0.445537 -0.224335\n",
       "...                       ...       ...       ...       ...       ...\n",
       "79         0         0.999730  0.101680 -0.976039 -0.999547 -0.715265\n",
       "           1         0.803590  0.577241 -0.696389 -0.897416 -0.312411\n",
       "           2         0.269220  0.903914 -0.188132 -0.586595  0.160840\n",
       "           3        -0.378464  0.997443  0.381883 -0.139366  0.597849\n",
       "           4        -0.866853  0.833703  0.826536  0.340273  0.900138\n",
       "\n",
       "[400 rows x 5 columns]"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.time_series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<p><span style=\"font-family: monospace;\">StaticSamples</span> with data:</p><div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sample_idx</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.374540</td>\n",
       "      <td>0.950714</td>\n",
       "      <td>0.731994</td>\n",
       "      <td>0.598658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.156019</td>\n",
       "      <td>0.155995</td>\n",
       "      <td>0.058084</td>\n",
       "      <td>0.866176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.601115</td>\n",
       "      <td>0.708073</td>\n",
       "      <td>0.020584</td>\n",
       "      <td>0.969910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.832443</td>\n",
       "      <td>0.212339</td>\n",
       "      <td>0.181825</td>\n",
       "      <td>0.183405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.304242</td>\n",
       "      <td>0.524756</td>\n",
       "      <td>0.431945</td>\n",
       "      <td>0.291229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>0.051682</td>\n",
       "      <td>0.531355</td>\n",
       "      <td>0.540635</td>\n",
       "      <td>0.637430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>0.726091</td>\n",
       "      <td>0.975852</td>\n",
       "      <td>0.516300</td>\n",
       "      <td>0.322956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>0.795186</td>\n",
       "      <td>0.270832</td>\n",
       "      <td>0.438971</td>\n",
       "      <td>0.078456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>0.025351</td>\n",
       "      <td>0.962648</td>\n",
       "      <td>0.835980</td>\n",
       "      <td>0.695974</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>0.408953</td>\n",
       "      <td>0.173294</td>\n",
       "      <td>0.156437</td>\n",
       "      <td>0.250243</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>80 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "StaticSamples with data:\n",
       "                   0         1         2         3\n",
       "sample_idx                                        \n",
       "0           0.374540  0.950714  0.731994  0.598658\n",
       "1           0.156019  0.155995  0.058084  0.866176\n",
       "2           0.601115  0.708073  0.020584  0.969910\n",
       "3           0.832443  0.212339  0.181825  0.183405\n",
       "4           0.304242  0.524756  0.431945  0.291229\n",
       "...              ...       ...       ...       ...\n",
       "75          0.051682  0.531355  0.540635  0.637430\n",
       "76          0.726091  0.975852  0.516300  0.322956\n",
       "77          0.795186  0.270832  0.438971  0.078456\n",
       "78          0.025351  0.962648  0.835980  0.695974\n",
       "79          0.408953  0.173294  0.156437  0.250243\n",
       "\n",
       "[80 rows x 4 columns]"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.static"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<p><span style=\"font-family: monospace;\">StaticSamples</span> with data:</p><div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sample_idx</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>80 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "StaticSamples with data:\n",
       "            0\n",
       "sample_idx   \n",
       "0           1\n",
       "1           1\n",
       "2           1\n",
       "3           0\n",
       "4           1\n",
       "...        ..\n",
       "75          1\n",
       "76          0\n",
       "77          1\n",
       "78          1\n",
       "79          1\n",
       "\n",
       "[80 rows x 1 columns]"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.predictive.targets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternatively you can initialize the datasource *instance* directly in one step, to the same effect, as below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tempor.datasources.prediction.one_off.plugin_sine.SineDataSource at 0x7ff8f8552d90>"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sine_datasource = plugin_loader.get(\"prediction.one_off.sine\", \"datasource\", no=80, seq_len=5)\n",
    "\n",
    "sine_datasource"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Provided `DataSource`s\n",
    "\n",
    "TemporAI comes with a number of data sources.\n",
    "\n",
    "To list them all by category:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">{</span>\n",
       "    <span style=\"color: #008000; text-decoration-color: #008000\">'prediction'</span>: <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'one_off'</span>: <span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'sine'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'google_stocks'</span><span style=\"font-weight: bold\">]</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'temporal'</span>: <span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'uci_diabetes'</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'dummy_prediction'</span><span style=\"font-weight: bold\">]}</span>,\n",
       "    <span style=\"color: #008000; text-decoration-color: #008000\">'time_to_event'</span>: <span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'pbc'</span><span style=\"font-weight: bold\">]</span>,\n",
       "    <span style=\"color: #008000; text-decoration-color: #008000\">'treatments'</span>: <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'one_off'</span>: <span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'pkpd'</span><span style=\"font-weight: bold\">]</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'temporal'</span>: <span style=\"font-weight: bold\">[</span><span style=\"color: #008000; text-decoration-color: #008000\">'dummy_treatments'</span><span style=\"font-weight: bold\">]}</span>\n",
       "<span style=\"font-weight: bold\">}</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m{\u001b[0m\n",
       "    \u001b[32m'prediction'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'one_off'\u001b[0m: \u001b[1m[\u001b[0m\u001b[32m'sine'\u001b[0m, \u001b[32m'google_stocks'\u001b[0m\u001b[1m]\u001b[0m, \u001b[32m'temporal'\u001b[0m: \u001b[1m[\u001b[0m\u001b[32m'uci_diabetes'\u001b[0m, \u001b[32m'dummy_prediction'\u001b[0m\u001b[1m]\u001b[0m\u001b[1m}\u001b[0m,\n",
       "    \u001b[32m'time_to_event'\u001b[0m: \u001b[1m[\u001b[0m\u001b[32m'pbc'\u001b[0m\u001b[1m]\u001b[0m,\n",
       "    \u001b[32m'treatments'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'one_off'\u001b[0m: \u001b[1m[\u001b[0m\u001b[32m'pkpd'\u001b[0m\u001b[1m]\u001b[0m, \u001b[32m'temporal'\u001b[0m: \u001b[1m[\u001b[0m\u001b[32m'dummy_treatments'\u001b[0m\u001b[1m]\u001b[0m\u001b[1m}\u001b[0m\n",
       "\u001b[1m}\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from rich.pretty import pprint\n",
    "\n",
    "pprint(\n",
    "    plugin_loader.list(plugin_type=\"datasource\"),\n",
    "    indent_guides=False,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Below you can see more information about each available data source and examples of the TemporAI `DataSet` it loads."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\n",
      "SineDataSource loads the following dataset:\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OneOffPredictionDataset(\n",
      "    time_series=TimeSeriesSamples([100, *, 5]),\n",
      "    static=StaticSamples([100, 4]),\n",
      "    predictive=OneOffPredictionTaskData(targets=StaticSamples([100, 1]))\n",
      ")\n",
      "This contains:\n",
      "\n",
      "time_series:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<p><span style=\"font-family: monospace;\">TimeSeriesSamples</span> with data:</p><div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        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></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sample_idx</th>\n",
       "      <th>time_idx</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
       "      <th>0</th>\n",
       "      <td>-0.019015</td>\n",
       "      <td>-0.048177</td>\n",
       "      <td>-0.108546</td>\n",
       "      <td>0.441865</td>\n",
       "      <td>0.024508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.300030</td>\n",
       "      <td>0.364550</td>\n",
       "      <td>0.576590</td>\n",
       "      <td>0.890053</td>\n",
       "      <td>0.534722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.587904</td>\n",
       "      <td>0.713509</td>\n",
       "      <td>0.972993</td>\n",
       "      <td>0.986179</td>\n",
       "      <td>0.892946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.814697</td>\n",
       "      <td>0.937661</td>\n",
       "      <td>0.882158</td>\n",
       "      <td>0.692221</td>\n",
       "      <td>0.997357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.956846</td>\n",
       "      <td>0.997797</td>\n",
       "      <td>0.349572</td>\n",
       "      <td>0.124454</td>\n",
       "      <td>0.818278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">99</th>\n",
       "      <th>5</th>\n",
       "      <td>0.967121</td>\n",
       "      <td>0.126890</td>\n",
       "      <td>0.926979</td>\n",
       "      <td>0.982022</td>\n",
       "      <td>0.963113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.706533</td>\n",
       "      <td>0.413329</td>\n",
       "      <td>0.569034</td>\n",
       "      <td>0.656214</td>\n",
       "      <td>0.989224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.252748</td>\n",
       "      <td>0.663121</td>\n",
       "      <td>0.024381</td>\n",
       "      <td>0.050668</td>\n",
       "      <td>0.999771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-0.270150</td>\n",
       "      <td>0.854119</td>\n",
       "      <td>-0.528273</td>\n",
       "      <td>-0.576478</td>\n",
       "      <td>0.994586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>-0.719177</td>\n",
       "      <td>0.969389</td>\n",
       "      <td>-0.907592</td>\n",
       "      <td>-0.957876</td>\n",
       "      <td>0.973752</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "TimeSeriesSamples with data:\n",
       "                            0         1         2         3         4\n",
       "sample_idx time_idx                                                  \n",
       "0          0        -0.019015 -0.048177 -0.108546  0.441865  0.024508\n",
       "           1         0.300030  0.364550  0.576590  0.890053  0.534722\n",
       "           2         0.587904  0.713509  0.972993  0.986179  0.892946\n",
       "           3         0.814697  0.937661  0.882158  0.692221  0.997357\n",
       "           4         0.956846  0.997797  0.349572  0.124454  0.818278\n",
       "...                       ...       ...       ...       ...       ...\n",
       "99         5         0.967121  0.126890  0.926979  0.982022  0.963113\n",
       "           6         0.706533  0.413329  0.569034  0.656214  0.989224\n",
       "           7         0.252748  0.663121  0.024381  0.050668  0.999771\n",
       "           8        -0.270150  0.854119 -0.528273 -0.576478  0.994586\n",
       "           9        -0.719177  0.969389 -0.907592 -0.957876  0.973752\n",
       "\n",
       "[1000 rows x 5 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "static:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<p><span style=\"font-family: monospace;\">StaticSamples</span> with data:</p><div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
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       "    <tr>\n",
       "      <th>sample_idx</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.374540</td>\n",
       "      <td>0.950714</td>\n",
       "      <td>0.731994</td>\n",
       "      <td>0.598658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.156019</td>\n",
       "      <td>0.155995</td>\n",
       "      <td>0.058084</td>\n",
       "      <td>0.866176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.601115</td>\n",
       "      <td>0.708073</td>\n",
       "      <td>0.020584</td>\n",
       "      <td>0.969910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.832443</td>\n",
       "      <td>0.212339</td>\n",
       "      <td>0.181825</td>\n",
       "      <td>0.183405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.304242</td>\n",
       "      <td>0.524756</td>\n",
       "      <td>0.431945</td>\n",
       "      <td>0.291229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>0.118165</td>\n",
       "      <td>0.696737</td>\n",
       "      <td>0.628943</td>\n",
       "      <td>0.877472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>0.735071</td>\n",
       "      <td>0.803481</td>\n",
       "      <td>0.282035</td>\n",
       "      <td>0.177440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>0.750615</td>\n",
       "      <td>0.806835</td>\n",
       "      <td>0.990505</td>\n",
       "      <td>0.412618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>0.372018</td>\n",
       "      <td>0.776413</td>\n",
       "      <td>0.340804</td>\n",
       "      <td>0.930757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>0.858413</td>\n",
       "      <td>0.428994</td>\n",
       "      <td>0.750871</td>\n",
       "      <td>0.754543</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "StaticSamples with data:\n",
       "                   0         1         2         3\n",
       "sample_idx                                        \n",
       "0           0.374540  0.950714  0.731994  0.598658\n",
       "1           0.156019  0.155995  0.058084  0.866176\n",
       "2           0.601115  0.708073  0.020584  0.969910\n",
       "3           0.832443  0.212339  0.181825  0.183405\n",
       "4           0.304242  0.524756  0.431945  0.291229\n",
       "...              ...       ...       ...       ...\n",
       "95          0.118165  0.696737  0.628943  0.877472\n",
       "96          0.735071  0.803481  0.282035  0.177440\n",
       "97          0.750615  0.806835  0.990505  0.412618\n",
       "98          0.372018  0.776413  0.340804  0.930757\n",
       "99          0.858413  0.428994  0.750871  0.754543\n",
       "\n",
       "[100 rows x 4 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predictive.targets:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<p><span style=\"font-family: monospace;\">StaticSamples</span> with data:</p><div>\n",
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       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>95</th>\n",
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       "      <th>96</th>\n",
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       "</table>\n",
       "<p>100 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "StaticSamples with data:\n",
       "            0\n",
       "sample_idx   \n",
       "0           0\n",
       "1           1\n",
       "2           0\n",
       "3           0\n",
       "4           1\n",
       "...        ..\n",
       "95          1\n",
       "96          1\n",
       "97          1\n",
       "98          0\n",
       "99          0\n",
       "\n",
       "[100 rows x 1 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\n",
      "GoogleStocksDataSource loads the following dataset:\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OneOffPredictionDataset(\n",
      "    time_series=TimeSeriesSamples([50, *, 5]),\n",
      "    predictive=OneOffPredictionTaskData(targets=StaticSamples([50, 1]))\n",
      ")\n",
      "This contains:\n",
      "\n",
      "time_series:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<p><span style=\"font-family: monospace;\">TimeSeriesSamples</span> with data:</p><div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sample_idx</th>\n",
       "      <th>time_idx</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
       "      <th>0.875000</th>\n",
       "      <td>0.661264</td>\n",
       "      <td>0.652789</td>\n",
       "      <td>0.677836</td>\n",
       "      <td>0.696887</td>\n",
       "      <td>0.185147</td>\n",
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       "    <tr>\n",
       "      <th>0.886364</th>\n",
       "      <td>0.667446</td>\n",
       "      <td>0.716935</td>\n",
       "      <td>0.731552</td>\n",
       "      <td>0.748318</td>\n",
       "      <td>0.150912</td>\n",
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       "    <tr>\n",
       "      <th>0.897727</th>\n",
       "      <td>0.751374</td>\n",
       "      <td>0.784055</td>\n",
       "      <td>0.800261</td>\n",
       "      <td>0.791407</td>\n",
       "      <td>0.140203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.909091</th>\n",
       "      <td>0.785577</td>\n",
       "      <td>0.838572</td>\n",
       "      <td>0.831813</td>\n",
       "      <td>0.832628</td>\n",
       "      <td>0.244291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.920455</th>\n",
       "      <td>0.885578</td>\n",
       "      <td>0.879778</td>\n",
       "      <td>0.900782</td>\n",
       "      <td>0.889539</td>\n",
       "      <td>0.413625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">9</th>\n",
       "      <th>0.806818</th>\n",
       "      <td>0.642857</td>\n",
       "      <td>0.647974</td>\n",
       "      <td>0.649153</td>\n",
       "      <td>0.639975</td>\n",
       "      <td>0.625178</td>\n",
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       "    <tr>\n",
       "      <th>0.818182</th>\n",
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       "      <td>0.757221</td>\n",
       "      <td>0.741200</td>\n",
       "      <td>0.789788</td>\n",
       "      <td>0.333141</td>\n",
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       "    <tr>\n",
       "      <th>0.829545</th>\n",
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       "      <td>0.732512</td>\n",
       "      <td>0.772230</td>\n",
       "      <td>0.732379</td>\n",
       "      <td>0.120629</td>\n",
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       "    <tr>\n",
       "      <th>0.840909</th>\n",
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       "      <td>0.721525</td>\n",
       "      <td>0.713076</td>\n",
       "      <td>0.101900</td>\n",
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       "    <tr>\n",
       "      <th>0.875000</th>\n",
       "      <td>0.661264</td>\n",
       "      <td>0.652789</td>\n",
       "      <td>0.677836</td>\n",
       "      <td>0.696887</td>\n",
       "      <td>0.185147</td>\n",
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       "</table>\n",
       "<p>500 rows × 5 columns</p>\n",
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       "TimeSeriesSamples with data:\n",
       "                         Open      High       Low     Close    Volume\n",
       "sample_idx time_idx                                                  \n",
       "0          0.875000  0.661264  0.652789  0.677836  0.696887  0.185147\n",
       "           0.886364  0.667446  0.716935  0.731552  0.748318  0.150912\n",
       "           0.897727  0.751374  0.784055  0.800261  0.791407  0.140203\n",
       "           0.909091  0.785577  0.838572  0.831813  0.832628  0.244291\n",
       "           0.920455  0.885578  0.879778  0.900782  0.889539  0.413625\n",
       "...                       ...       ...       ...       ...       ...\n",
       "9          0.806818  0.642857  0.647974  0.649153  0.639975  0.625178\n",
       "           0.818182  0.687362  0.757221  0.741200  0.789788  0.333141\n",
       "           0.829545  0.756044  0.732512  0.772230  0.732379  0.120629\n",
       "           0.840909  0.710852  0.687907  0.721525  0.713076  0.101900\n",
       "           0.875000  0.661264  0.652789  0.677836  0.696887  0.185147\n",
       "\n",
       "[500 rows x 5 columns]"
      ]
     },
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    },
    {
     "name": "stdout",
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     "text": [
      "predictive.targets:\n"
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       "    <tr>\n",
       "      <th>36</th>\n",
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       "      <th>41</th>\n",
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    {
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     "text": [
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\n",
      "UCIDiabetesDataSource loads the following dataset:\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TemporalPredictionDataset(\n",
      "    time_series=TimeSeriesSamples([70, *, 18]),\n",
      "    predictive=TemporalPredictionTaskData(\n",
      "        targets=TimeSeriesSamples([70, *, 1])\n",
      "    )\n",
      ")\n",
      "This contains:\n",
      "\n",
      "time_series:\n"
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       "      <th>147</th>\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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>259.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\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>NaN</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>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\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>NaN</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>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\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>NaN</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>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18199 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "TimeSeriesSamples with data:\n",
       "                     post-lunch_blood_glucose_measurement  \\\n",
       "sample_idx time_idx                                         \n",
       "0          0                                          NaN   \n",
       "           1                                          NaN   \n",
       "           2                                          NaN   \n",
       "           3                                          NaN   \n",
       "           4                                          NaN   \n",
       "...                                                   ...   \n",
       "69         146                                        NaN   \n",
       "           147                                        NaN   \n",
       "           148                                        NaN   \n",
       "           149                                        NaN   \n",
       "           150                                        NaN   \n",
       "\n",
       "                     more-than-usual_meal_ingestion  \\\n",
       "sample_idx time_idx                                   \n",
       "0          0                                    NaN   \n",
       "           1                                    NaN   \n",
       "           2                                    NaN   \n",
       "           3                                    NaN   \n",
       "           4                                    NaN   \n",
       "...                                             ...   \n",
       "69         146                                  NaN   \n",
       "           147                                  NaN   \n",
       "           148                                  NaN   \n",
       "           149                                  NaN   \n",
       "           150                                  NaN   \n",
       "\n",
       "                     unspecified_special_event  typical_exercise_activity  \\\n",
       "sample_idx time_idx                                                         \n",
       "0          0                               NaN                        NaN   \n",
       "           1                               NaN                        NaN   \n",
       "           2                               NaN                        NaN   \n",
       "           3                               NaN                        NaN   \n",
       "           4                               NaN                        NaN   \n",
       "...                                        ...                        ...   \n",
       "69         146                             NaN                        NaN   \n",
       "           147                             NaN                        NaN   \n",
       "           148                             NaN                        NaN   \n",
       "           149                             NaN                        NaN   \n",
       "           150                             NaN                        NaN   \n",
       "\n",
       "                     less-than-usual_exercise_activity  \\\n",
       "sample_idx time_idx                                      \n",
       "0          0                                       NaN   \n",
       "           1                                       NaN   \n",
       "           2                                       NaN   \n",
       "           3                                       NaN   \n",
       "           4                                       NaN   \n",
       "...                                                ...   \n",
       "69         146                                     NaN   \n",
       "           147                                     NaN   \n",
       "           148                                     NaN   \n",
       "           149                                     NaN   \n",
       "           150                                     NaN   \n",
       "\n",
       "                     post-supper_blood_glucose_measurement  \\\n",
       "sample_idx time_idx                                          \n",
       "0          0                                           NaN   \n",
       "           1                                           NaN   \n",
       "           2                                           NaN   \n",
       "           3                                           NaN   \n",
       "           4                                           NaN   \n",
       "...                                                    ...   \n",
       "69         146                                         NaN   \n",
       "           147                                         NaN   \n",
       "           148                                         NaN   \n",
       "           149                                         NaN   \n",
       "           150                                         NaN   \n",
       "\n",
       "                     more-than-usual_exercise_activity  \\\n",
       "sample_idx time_idx                                      \n",
       "0          0                                       NaN   \n",
       "           1                                       NaN   \n",
       "           2                                       NaN   \n",
       "           3                                       NaN   \n",
       "           4                                       NaN   \n",
       "...                                                ...   \n",
       "69         146                                     NaN   \n",
       "           147                                     NaN   \n",
       "           148                                     NaN   \n",
       "           149                                     NaN   \n",
       "           150                                     NaN   \n",
       "\n",
       "                     unspecified_blood_glucose_measurement  \\\n",
       "sample_idx time_idx                                          \n",
       "0          0                                           NaN   \n",
       "           1                                           NaN   \n",
       "           2                                         123.0   \n",
       "           3                                           NaN   \n",
       "           4                                           NaN   \n",
       "...                                                    ...   \n",
       "69         146                                       145.0   \n",
       "           147                                         NaN   \n",
       "           148                                         NaN   \n",
       "           149                                         NaN   \n",
       "           150                                         NaN   \n",
       "\n",
       "                     pre-snack_blood_glucose_measurement  \\\n",
       "sample_idx time_idx                                        \n",
       "0          0                                         NaN   \n",
       "           1                                         NaN   \n",
       "           2                                         NaN   \n",
       "           3                                         NaN   \n",
       "           4                                         NaN   \n",
       "...                                                  ...   \n",
       "69         146                                       NaN   \n",
       "           147                                       NaN   \n",
       "           148                                       NaN   \n",
       "           149                                       NaN   \n",
       "           150                                       NaN   \n",
       "\n",
       "                     ultralente_insulin_dose  less-than-usual_meal_ingestion  \\\n",
       "sample_idx time_idx                                                            \n",
       "0          0                             NaN                             NaN   \n",
       "           1                             NaN                             NaN   \n",
       "           2                             NaN                             NaN   \n",
       "           3                             NaN                             NaN   \n",
       "           4                             NaN                             NaN   \n",
       "...                                      ...                             ...   \n",
       "69         146                           NaN                             NaN   \n",
       "           147                           NaN                             NaN   \n",
       "           148                           NaN                             NaN   \n",
       "           149                           NaN                             NaN   \n",
       "           150                           NaN                             NaN   \n",
       "\n",
       "                     pre-supper_blood_glucose_measurement  \\\n",
       "sample_idx time_idx                                         \n",
       "0          0                                          NaN   \n",
       "           1                                        119.0   \n",
       "           2                                          NaN   \n",
       "           3                                          NaN   \n",
       "           4                                          NaN   \n",
       "...                                                   ...   \n",
       "69         146                                        NaN   \n",
       "           147                                        NaN   \n",
       "           148                                        NaN   \n",
       "           149                                        NaN   \n",
       "           150                                        NaN   \n",
       "\n",
       "                     regular_insulin_dose  \\\n",
       "sample_idx time_idx                         \n",
       "0          0                          9.0   \n",
       "           1                          7.0   \n",
       "           2                          NaN   \n",
       "           3                         10.0   \n",
       "           4                          2.0   \n",
       "...                                   ...   \n",
       "69         146                        NaN   \n",
       "           147                        1.0   \n",
       "           148                        NaN   \n",
       "           149                        NaN   \n",
       "           150                        NaN   \n",
       "\n",
       "                     pre-breakfast_blood_glucose_measurement  \\\n",
       "sample_idx time_idx                                            \n",
       "0          0                                           100.0   \n",
       "           1                                             NaN   \n",
       "           2                                             NaN   \n",
       "           3                                           216.0   \n",
       "           4                                             NaN   \n",
       "...                                                      ...   \n",
       "69         146                                           NaN   \n",
       "           147                                         259.0   \n",
       "           148                                           NaN   \n",
       "           149                                           NaN   \n",
       "           150                                           NaN   \n",
       "\n",
       "                     nph_insulin_dose  \\\n",
       "sample_idx time_idx                     \n",
       "0          0                     13.0   \n",
       "           1                      NaN   \n",
       "           2                      NaN   \n",
       "           3                     13.0   \n",
       "           4                      NaN   \n",
       "...                               ...   \n",
       "69         146                    NaN   \n",
       "           147                    7.0   \n",
       "           148                    7.0   \n",
       "           149                    7.0   \n",
       "           150                    7.0   \n",
       "\n",
       "                     post-breakfast_blood_glucose_measurement  \\\n",
       "sample_idx time_idx                                             \n",
       "0          0                                              NaN   \n",
       "           1                                              NaN   \n",
       "           2                                              NaN   \n",
       "           3                                              NaN   \n",
       "           4                                              NaN   \n",
       "...                                                       ...   \n",
       "69         146                                            NaN   \n",
       "           147                                            NaN   \n",
       "           148                                            NaN   \n",
       "           149                                            NaN   \n",
       "           150                                            NaN   \n",
       "\n",
       "                     pre-lunch_blood_glucose_measurement  \\\n",
       "sample_idx time_idx                                        \n",
       "0          0                                         NaN   \n",
       "           1                                         NaN   \n",
       "           2                                         NaN   \n",
       "           3                                         NaN   \n",
       "           4                                         NaN   \n",
       "...                                                  ...   \n",
       "69         146                                       NaN   \n",
       "           147                                       NaN   \n",
       "           148                                       NaN   \n",
       "           149                                       NaN   \n",
       "           150                                       NaN   \n",
       "\n",
       "                     typical_meal_ingestion  \n",
       "sample_idx time_idx                          \n",
       "0          0                            NaN  \n",
       "           1                            NaN  \n",
       "           2                            NaN  \n",
       "           3                            NaN  \n",
       "           4                            NaN  \n",
       "...                                     ...  \n",
       "69         146                          NaN  \n",
       "           147                          NaN  \n",
       "           148                          NaN  \n",
       "           149                          NaN  \n",
       "           150                          NaN  \n",
       "\n",
       "[18199 rows x 18 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predictive.targets:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<p><span style=\"font-family: monospace;\">TimeSeriesSamples</span> with data:</p><div>\n",
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       "      <th></th>\n",
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       "      <th>hypoglycemic_symptoms</th>\n",
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       "      <th rowspan=\"5\" valign=\"top\">69</th>\n",
       "      <th>146</th>\n",
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       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>NaN</td>\n",
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       "      <th>148</th>\n",
       "      <td>NaN</td>\n",
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       "      <th>149</th>\n",
       "      <td>NaN</td>\n",
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       "      <th>150</th>\n",
       "      <td>NaN</td>\n",
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      ],
      "text/plain": [
       "TimeSeriesSamples with data:\n",
       "                     hypoglycemic_symptoms\n",
       "sample_idx time_idx                       \n",
       "0          0                           NaN\n",
       "           1                           NaN\n",
       "           2                           NaN\n",
       "           3                           NaN\n",
       "           4                           NaN\n",
       "...                                    ...\n",
       "69         146                         NaN\n",
       "           147                         NaN\n",
       "           148                         NaN\n",
       "           149                         NaN\n",
       "           150                         NaN\n",
       "\n",
       "[18199 rows x 1 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\n",
      "DummyTemporalPredictionDataSource loads the following dataset:\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TemporalPredictionDataset(\n",
      "    time_series=TimeSeriesSamples([100, *, 5]),\n",
      "    static=StaticSamples([100, 3]),\n",
      "    predictive=TemporalPredictionTaskData(\n",
      "        targets=TimeSeriesSamples([100, *, 2])\n",
      "    )\n",
      ")\n",
      "This contains:\n",
      "\n",
      "time_series:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<p><span style=\"font-family: monospace;\">TimeSeriesSamples</span> with data:</p><div>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sample_idx</th>\n",
       "      <th>time_idx</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.893763</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.047522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.257931</td>\n",
       "      <td>2.172271</td>\n",
       "      <td>2.226089</td>\n",
       "      <td>2.360713</td>\n",
       "      <td>1.981578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.247657</td>\n",
       "      <td>0.853397</td>\n",
       "      <td>2.525946</td>\n",
       "      <td>3.213647</td>\n",
       "      <td>2.897191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.396456</td>\n",
       "      <td>5.386071</td>\n",
       "      <td>3.721545</td>\n",
       "      <td>2.503248</td>\n",
       "      <td>3.517212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.387812</td>\n",
       "      <td>3.365264</td>\n",
       "      <td>5.612532</td>\n",
       "      <td>5.573375</td>\n",
       "      <td>4.767746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">99</th>\n",
       "      <th>12</th>\n",
       "      <td>12.654769</td>\n",
       "      <td>14.810888</td>\n",
       "      <td>12.914859</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.818675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13.418815</td>\n",
       "      <td>12.135655</td>\n",
       "      <td>12.481295</td>\n",
       "      <td>13.336797</td>\n",
       "      <td>13.696168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>13.785503</td>\n",
       "      <td>14.431228</td>\n",
       "      <td>15.193174</td>\n",
       "      <td>17.551818</td>\n",
       "      <td>14.464249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15.344934</td>\n",
       "      <td>15.916966</td>\n",
       "      <td>14.368132</td>\n",
       "      <td>15.965113</td>\n",
       "      <td>15.419334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16.033907</td>\n",
       "      <td>15.162631</td>\n",
       "      <td>17.338485</td>\n",
       "      <td>17.007235</td>\n",
       "      <td>17.034645</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1547 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "TimeSeriesSamples with data:\n",
       "                             0          1          2          3          4\n",
       "sample_idx time_idx                                                       \n",
       "0          0               NaN   0.893763        NaN        NaN   1.047522\n",
       "           1          1.257931   2.172271   2.226089   2.360713   1.981578\n",
       "           2          2.247657   0.853397   2.525946   3.213647   2.897191\n",
       "           3          3.396456   5.386071   3.721545   2.503248   3.517212\n",
       "           4          4.387812   3.365264   5.612532   5.573375   4.767746\n",
       "...                        ...        ...        ...        ...        ...\n",
       "99         12        12.654769  14.810888  12.914859        NaN  12.818675\n",
       "           13        13.418815  12.135655  12.481295  13.336797  13.696168\n",
       "           14        13.785503  14.431228  15.193174  17.551818  14.464249\n",
       "           15        15.344934  15.916966  14.368132  15.965113  15.419334\n",
       "           16        16.033907  15.162631  17.338485  17.007235  17.034645\n",
       "\n",
       "[1547 rows x 5 columns]"
      ]
     },
     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "static:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<p><span style=\"font-family: monospace;\">StaticSamples</span> with data:</p><div>\n",
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       "    <tr>\n",
       "      <th>sample_idx</th>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.753423</td>\n",
       "      <td>3.239284</td>\n",
       "      <td>0.995587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.829240</td>\n",
       "      <td>3.175298</td>\n",
       "      <td>0.770566</td>\n",
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       "      <th>2</th>\n",
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       "      <th>3</th>\n",
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       "      <td>3.234011</td>\n",
       "      <td>1.594861</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.501552</td>\n",
       "      <td>3.211027</td>\n",
       "      <td>0.639503</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>0.680235</td>\n",
       "      <td>3.287749</td>\n",
       "      <td>0.705369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>0.788814</td>\n",
       "      <td>3.313229</td>\n",
       "      <td>1.318394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>0.589116</td>\n",
       "      <td>3.268607</td>\n",
       "      <td>1.646737</td>\n",
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       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>0.551060</td>\n",
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       "      <td>0.998024</td>\n",
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       "      <th>99</th>\n",
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       "      <td>1.047537</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 3 columns</p>\n",
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       "StaticSamples with data:\n",
       "                   0         1         2\n",
       "sample_idx                              \n",
       "0           0.753423  3.239284  0.995587\n",
       "1           0.829240  3.175298  0.770566\n",
       "2           0.674581  3.229741  1.302317\n",
       "3           0.584040  3.234011  1.594861\n",
       "4           0.501552  3.211027  0.639503\n",
       "...              ...       ...       ...\n",
       "95          0.680235  3.287749  0.705369\n",
       "96          0.788814  3.313229  1.318394\n",
       "97          0.589116  3.268607  1.646737\n",
       "98          0.551060  3.268599  0.998024\n",
       "99          0.716501  3.254501  1.047537\n",
       "\n",
       "[100 rows x 3 columns]"
      ]
     },
     "metadata": {},
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    },
    {
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     "text": [
      "predictive.targets:\n"
     ]
    },
    {
     "data": {
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       "<p><span style=\"font-family: monospace;\">TimeSeriesSamples</span> with data:</p><div>\n",
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       "      <td>4.981217</td>\n",
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       "      <th>4</th>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">99</th>\n",
       "      <th>12</th>\n",
       "      <td>10.736462</td>\n",
       "      <td>13.415872</td>\n",
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       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>11.617465</td>\n",
       "      <td>15.103293</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>12.858327</td>\n",
       "      <td>16.105966</td>\n",
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       "      <th>15</th>\n",
       "      <td>13.652358</td>\n",
       "      <td>16.148926</td>\n",
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       "      <th>16</th>\n",
       "      <td>14.442286</td>\n",
       "      <td>17.567963</td>\n",
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       "<p>1547 rows × 2 columns</p>\n",
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      ],
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       "TimeSeriesSamples with data:\n",
       "                             0          1\n",
       "sample_idx time_idx                      \n",
       "0          0         -1.433570   0.714861\n",
       "           1         -0.600733   2.744446\n",
       "           2          0.622874   1.816995\n",
       "           3          1.879785   4.981217\n",
       "           4          2.477957   5.932101\n",
       "...                        ...        ...\n",
       "99         12        10.736462  13.415872\n",
       "           13        11.617465  15.103293\n",
       "           14        12.858327  16.105966\n",
       "           15        13.652358  16.148926\n",
       "           16        14.442286  17.567963\n",
       "\n",
       "[1547 rows x 2 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\n",
      "PBCDataSource loads the following dataset:\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TimeToEventAnalysisDataset(\n",
      "    time_series=TimeSeriesSamples([312, *, 14]),\n",
      "    static=StaticSamples([312, 1]),\n",
      "    predictive=TimeToEventAnalysisTaskData(targets=EventSamples([312, 1]))\n",
      ")\n",
      "This contains:\n",
      "\n",
      "time_series:\n"
     ]
    },
    {
     "data": {
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       "<p><span style=\"font-family: monospace;\">TimeSeriesSamples</span> with data:</p><div>\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>drug</th>\n",
       "      <th>ascites</th>\n",
       "      <th>hepatomegaly</th>\n",
       "      <th>spiders</th>\n",
       "      <th>edema</th>\n",
       "      <th>histologic</th>\n",
       "      <th>serBilir</th>\n",
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       "      <th>alkaline</th>\n",
       "      <th>SGOT</th>\n",
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       "      <th>sample_idx</th>\n",
       "      <th>time_idx</th>\n",
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       "      <td>0.136768</td>\n",
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       "      <td>-0.469461</td>\n",
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       "      <td>0.285613</td>\n",
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       "      <td>-0.456022</td>\n",
       "      <td>0.813132</td>\n",
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       "      <th>5.319790</th>\n",
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       "      <td>2.0</td>\n",
       "      <td>0.172710</td>\n",
       "      <td>-0.658914</td>\n",
       "      <td>-1.431455</td>\n",
       "      <td>-0.605844</td>\n",
       "      <td>-0.442126</td>\n",
       "      <td>-1.395605</td>\n",
       "      <td>0.339677</td>\n",
       "      <td>1.292856</td>\n",
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       "    <tr>\n",
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       "      <td>1.0</td>\n",
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       "      <td>2.0</td>\n",
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       "      <td>-0.603657</td>\n",
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       "      <td>-0.046806</td>\n",
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       "      <td>1.292856</td>\n",
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       "    <tr>\n",
       "      <th>7.266455</th>\n",
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       "      <td>1.0</td>\n",
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       "      <td>2.0</td>\n",
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       "      <td>-0.443529</td>\n",
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       "      <td>3.319599</td>\n",
       "      <td>0.059878</td>\n",
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       "      <td>0.986129</td>\n",
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       "      <td>1.624769</td>\n",
       "      <td>-1.962482</td>\n",
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       "    <tr>\n",
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       "      <td>0.0</td>\n",
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       "      <td>2.0</td>\n",
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       "      <td>2.901224</td>\n",
       "      <td>-0.099197</td>\n",
       "      <td>0.916176</td>\n",
       "      <td>0.641817</td>\n",
       "      <td>-0.998892</td>\n",
       "      <td>1.354223</td>\n",
       "      <td>-1.962482</td>\n",
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       "    <tr>\n",
       "      <th>2.921367</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.694010</td>\n",
       "      <td>-0.066873</td>\n",
       "      <td>0.338261</td>\n",
       "      <td>0.327254</td>\n",
       "      <td>0.552551</td>\n",
       "      <td>-0.894494</td>\n",
       "      <td>0.474950</td>\n",
       "      <td>-1.962482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.425145</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.340271</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.377580</td>\n",
       "      <td>0.251620</td>\n",
       "      <td>0.016956</td>\n",
       "      <td>-0.466462</td>\n",
       "      <td>-0.066141</td>\n",
       "      <td>-1.962482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.989158</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.507832</td>\n",
       "      <td>2.017110</td>\n",
       "      <td>0.795603</td>\n",
       "      <td>0.622990</td>\n",
       "      <td>0.169983</td>\n",
       "      <td>-0.351624</td>\n",
       "      <td>-0.133778</td>\n",
       "      <td>-1.962482</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1945 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "TimeSeriesSamples with data:\n",
       "                     drug  ascites  hepatomegaly  spiders  edema  histologic  \\\n",
       "sample_idx time_idx                                                            \n",
       "1          0.569489   0.0      1.0           1.0      1.0    1.0         3.0   \n",
       "           1.095170   0.0      1.0           1.0      1.0    1.0         3.0   \n",
       "2          5.319790   0.0      1.0           1.0      1.0    1.0         2.0   \n",
       "           6.261636   0.0      1.0           1.0      1.0    1.0         2.0   \n",
       "           7.266455   0.0      1.0           1.0      1.0    1.0         2.0   \n",
       "...                   ...      ...           ...      ...    ...         ...   \n",
       "312        1.045888   1.0      0.0           0.0      1.0    2.0         2.0   \n",
       "           1.867265   1.0      0.0           0.0      1.0    2.0         1.0   \n",
       "           2.921367   1.0      0.0           0.0      0.0    0.0         1.0   \n",
       "           3.425145   1.0      0.0           0.0      0.0    0.0         1.0   \n",
       "           3.989158   1.0      0.0           0.0      1.0    0.0         1.0   \n",
       "\n",
       "                     serBilir   serChol   albumin  alkaline      SGOT  \\\n",
       "sample_idx time_idx                                                     \n",
       "1          0.569489  3.281890  0.000000 -0.894575  0.195532 -1.485263   \n",
       "           1.095170  2.015877 -0.469461 -1.570646  0.285613  0.195488   \n",
       "2          5.319790  0.172710 -0.658914 -1.431455 -0.605844 -0.442126   \n",
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       "...                       ...       ...       ...       ...       ...   \n",
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       "\n",
       "                     platelets  prothrombin       age  \n",
       "sample_idx time_idx                                    \n",
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       "\n",
       "[1945 rows x 14 columns]"
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     "text": [
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\n",
      "PKPDDataSource loads the following dataset:\n",
      "\n",
      "Generating simple PKPD dataset with random seed 100...\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "OneOffTreatmentEffectsDataset(\n",
      "    time_series=TimeSeriesSamples([40, *, 2]),\n",
      "    predictive=OneOffTreatmentEffectsTaskData(\n",
      "        targets=TimeSeriesSamples([40, *, 1]),\n",
      "        treatments=EventSamples([40, 1])\n",
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      ")\n",
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       "      <td>(7, True)</td>\n",
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       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>(7, True)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>(7, True)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>(7, True)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>(7, True)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>(7, True)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>(7, True)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>(7, True)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>(7, True)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>(7, True)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>(7, True)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>(7, True)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>(7, True)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>(7, True)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>(7, True)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>(7, True)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>(7, True)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "EventSamples with data:\n",
       "                     a\n",
       "sample_idx            \n",
       "0           (7, False)\n",
       "1           (7, False)\n",
       "2           (7, False)\n",
       "3           (7, False)\n",
       "4           (7, False)\n",
       "5           (7, False)\n",
       "6           (7, False)\n",
       "7           (7, False)\n",
       "8           (7, False)\n",
       "9           (7, False)\n",
       "10          (7, False)\n",
       "11          (7, False)\n",
       "12          (7, False)\n",
       "13          (7, False)\n",
       "14          (7, False)\n",
       "15          (7, False)\n",
       "16          (7, False)\n",
       "17          (7, False)\n",
       "18          (7, False)\n",
       "19          (7, False)\n",
       "20           (7, True)\n",
       "21           (7, True)\n",
       "22           (7, True)\n",
       "23           (7, True)\n",
       "24           (7, True)\n",
       "25           (7, True)\n",
       "26           (7, True)\n",
       "27           (7, True)\n",
       "28           (7, True)\n",
       "29           (7, True)\n",
       "30           (7, True)\n",
       "31           (7, True)\n",
       "32           (7, True)\n",
       "33           (7, True)\n",
       "34           (7, True)\n",
       "35           (7, True)\n",
       "36           (7, True)\n",
       "37           (7, True)\n",
       "38           (7, True)\n",
       "39           (7, True)"
      ]
     },
     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\n",
      "DummyTemporalTreatmentEffectsDataSource loads the following dataset:\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TemporalTreatmentEffectsDataset(\n",
      "    time_series=TimeSeriesSamples([100, *, 5]),\n",
      "    static=StaticSamples([100, 3]),\n",
      "    predictive=TemporalTreatmentEffectsTaskData(\n",
      "        targets=TimeSeriesSamples([100, *, 2]),\n",
      "        treatments=TimeSeriesSamples([100, *, 2])\n",
      "    )\n",
      ")\n",
      "This contains:\n",
      "\n",
      "time_series:\n"
     ]
    },
    {
     "data": {
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       "<p><span style=\"font-family: monospace;\">TimeSeriesSamples</span> with data:</p><div>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
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       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
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       "    <tr>\n",
       "      <th>sample_idx</th>\n",
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       "      <th></th>\n",
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       "      <td>NaN</td>\n",
       "      <td>0.893763</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.047522</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.257931</td>\n",
       "      <td>2.172271</td>\n",
       "      <td>2.226089</td>\n",
       "      <td>2.360713</td>\n",
       "      <td>1.981578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.247657</td>\n",
       "      <td>0.853397</td>\n",
       "      <td>2.525946</td>\n",
       "      <td>3.213647</td>\n",
       "      <td>2.897191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.396456</td>\n",
       "      <td>5.386071</td>\n",
       "      <td>3.721545</td>\n",
       "      <td>2.503248</td>\n",
       "      <td>3.517212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.387812</td>\n",
       "      <td>3.365264</td>\n",
       "      <td>5.612532</td>\n",
       "      <td>5.573375</td>\n",
       "      <td>4.767746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">99</th>\n",
       "      <th>12</th>\n",
       "      <td>12.654769</td>\n",
       "      <td>14.810888</td>\n",
       "      <td>12.914859</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.818675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13.418815</td>\n",
       "      <td>12.135655</td>\n",
       "      <td>12.481295</td>\n",
       "      <td>13.336797</td>\n",
       "      <td>13.696168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>13.785503</td>\n",
       "      <td>14.431228</td>\n",
       "      <td>15.193174</td>\n",
       "      <td>17.551818</td>\n",
       "      <td>14.464249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15.344934</td>\n",
       "      <td>15.916966</td>\n",
       "      <td>14.368132</td>\n",
       "      <td>15.965113</td>\n",
       "      <td>15.419334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16.033907</td>\n",
       "      <td>15.162631</td>\n",
       "      <td>17.338485</td>\n",
       "      <td>17.007235</td>\n",
       "      <td>17.034645</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1547 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "TimeSeriesSamples with data:\n",
       "                             0          1          2          3          4\n",
       "sample_idx time_idx                                                       \n",
       "0          0               NaN   0.893763        NaN        NaN   1.047522\n",
       "           1          1.257931   2.172271   2.226089   2.360713   1.981578\n",
       "           2          2.247657   0.853397   2.525946   3.213647   2.897191\n",
       "           3          3.396456   5.386071   3.721545   2.503248   3.517212\n",
       "           4          4.387812   3.365264   5.612532   5.573375   4.767746\n",
       "...                        ...        ...        ...        ...        ...\n",
       "99         12        12.654769  14.810888  12.914859        NaN  12.818675\n",
       "           13        13.418815  12.135655  12.481295  13.336797  13.696168\n",
       "           14        13.785503  14.431228  15.193174  17.551818  14.464249\n",
       "           15        15.344934  15.916966  14.368132  15.965113  15.419334\n",
       "           16        16.033907  15.162631  17.338485  17.007235  17.034645\n",
       "\n",
       "[1547 rows x 5 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "static:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<p><span style=\"font-family: monospace;\">StaticSamples</span> with data:</p><div>\n",
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       "      <th>0</th>\n",
       "      <td>0.753423</td>\n",
       "      <td>3.239284</td>\n",
       "      <td>0.995587</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.829240</td>\n",
       "      <td>3.175298</td>\n",
       "      <td>0.770566</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.674581</td>\n",
       "      <td>3.229741</td>\n",
       "      <td>1.302317</td>\n",
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       "      <th>3</th>\n",
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       "      <td>3.234011</td>\n",
       "      <td>1.594861</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.501552</td>\n",
       "      <td>3.211027</td>\n",
       "      <td>0.639503</td>\n",
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       "      <th>95</th>\n",
       "      <td>0.680235</td>\n",
       "      <td>3.287749</td>\n",
       "      <td>0.705369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>0.788814</td>\n",
       "      <td>3.313229</td>\n",
       "      <td>1.318394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>0.589116</td>\n",
       "      <td>3.268607</td>\n",
       "      <td>1.646737</td>\n",
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       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>0.551060</td>\n",
       "      <td>3.268599</td>\n",
       "      <td>0.998024</td>\n",
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       "      <th>99</th>\n",
       "      <td>0.716501</td>\n",
       "      <td>3.254501</td>\n",
       "      <td>1.047537</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "StaticSamples with data:\n",
       "                   0         1         2\n",
       "sample_idx                              \n",
       "0           0.753423  3.239284  0.995587\n",
       "1           0.829240  3.175298  0.770566\n",
       "2           0.674581  3.229741  1.302317\n",
       "3           0.584040  3.234011  1.594861\n",
       "4           0.501552  3.211027  0.639503\n",
       "...              ...       ...       ...\n",
       "95          0.680235  3.287749  0.705369\n",
       "96          0.788814  3.313229  1.318394\n",
       "97          0.589116  3.268607  1.646737\n",
       "98          0.551060  3.268599  0.998024\n",
       "99          0.716501  3.254501  1.047537\n",
       "\n",
       "[100 rows x 3 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predictive.targets:\n"
     ]
    },
    {
     "data": {
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       "      <th>3</th>\n",
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       "      <td>4.981217</td>\n",
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       "      <th>...</th>\n",
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       "      <th rowspan=\"5\" valign=\"top\">99</th>\n",
       "      <th>12</th>\n",
       "      <td>10.736462</td>\n",
       "      <td>13.415872</td>\n",
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       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>11.617465</td>\n",
       "      <td>15.103293</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>12.858327</td>\n",
       "      <td>16.105966</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>13.652358</td>\n",
       "      <td>16.148926</td>\n",
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       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>14.442286</td>\n",
       "      <td>17.567963</td>\n",
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       "<p>1547 rows × 2 columns</p>\n",
       "</div>"
      ],
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       "TimeSeriesSamples with data:\n",
       "                             0          1\n",
       "sample_idx time_idx                      \n",
       "0          0         -1.433570   0.714861\n",
       "           1         -0.600733   2.744446\n",
       "           2          0.622874   1.816995\n",
       "           3          1.879785   4.981217\n",
       "           4          2.477957   5.932101\n",
       "...                        ...        ...\n",
       "99         12        10.736462  13.415872\n",
       "           13        11.617465  15.103293\n",
       "           14        12.858327  16.105966\n",
       "           15        13.652358  16.148926\n",
       "           16        14.442286  17.567963\n",
       "\n",
       "[1547 rows x 2 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predictive.treatments:\n"
     ]
    },
    {
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       "      <td>0.622874</td>\n",
       "      <td>1.816995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.879785</td>\n",
       "      <td>4.981217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.477957</td>\n",
       "      <td>5.932101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">99</th>\n",
       "      <th>12</th>\n",
       "      <td>10.736462</td>\n",
       "      <td>13.415872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>11.617465</td>\n",
       "      <td>15.103293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>12.858327</td>\n",
       "      <td>16.105966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>13.652358</td>\n",
       "      <td>16.148926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>14.442286</td>\n",
       "      <td>17.567963</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1547 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "TimeSeriesSamples with data:\n",
       "                             0          1\n",
       "sample_idx time_idx                      \n",
       "0          0         -1.433570   0.714861\n",
       "           1         -0.600733   2.744446\n",
       "           2          0.622874   1.816995\n",
       "           3          1.879785   4.981217\n",
       "           4          2.477957   5.932101\n",
       "...                        ...        ...\n",
       "99         12        10.736462  13.415872\n",
       "           13        11.617465  15.103293\n",
       "           14        12.858327  16.105966\n",
       "           15        13.652358  16.148926\n",
       "           16        14.442286  17.567963\n",
       "\n",
       "[1547 rows x 2 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Display information about each datasource's default loaded dataset.\n",
    "\n",
    "all_datasources = plugin_loader.list_full_names(plugin_type=\"datasource\")\n",
    "\n",
    "from IPython.display import display\n",
    "\n",
    "for datasource_name in all_datasources:\n",
    "    print(f\"\\n{'-' * 80}\\n\")\n",
    "\n",
    "    datasource_cls = plugin_loader.get_class(datasource_name, plugin_type=\"datasource\")\n",
    "\n",
    "    print(f\"{datasource_cls.__name__} loads the following dataset:\\n\")\n",
    "    data = datasource_cls().load()\n",
    "    print(data)\n",
    "\n",
    "    print(\"This contains:\", end=\"\\n\\n\")\n",
    "\n",
    "    print(\"time_series:\")\n",
    "    display(data.time_series)\n",
    "    if data.static is not None:\n",
    "        print(\"static:\")\n",
    "        display(data.static)\n",
    "    if data.predictive.targets is not None:\n",
    "        print(\"predictive.targets:\")\n",
    "        display(data.predictive.targets)\n",
    "    if data.predictive.treatments is not None:\n",
    "        print(\"predictive.treatments:\")\n",
    "        display(data.predictive.treatments)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 🎉 Congratulations!\n",
    "\n",
    "Congratulations on completing this notebook tutorial! If you enjoyed this and would like to join the movement towards *Machine learning and AI for Medicine*, you can do so in the following ways!\n",
    "\n",
    "\n",
    "\n",
    "### ⭐ Star [TemporAI](https://github.com/vanderschaarlab/temporai) on GitHub\n",
    "\n",
    "- The easiest way to help our community is by just starring the repos! This helps raise awareness of the tools we're building.\n",
    "\n",
    "\n",
    "\n",
    "### Check out other projects from [vanderschaarlab](https://github.com/vanderschaarlab)\n",
    "- 📝 [HyperImpute](https://github.com/vanderschaarlab/hyperimpute)\n",
    "- 📊 [AutoPrognosis](https://github.com/vanderschaarlab/autoprognosis)\n",
    "- 🤖 [SynthCity](https://github.com/vanderschaarlab/synthcity)\n",
    " "
   ]
  }
 ],
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