feature_prepare.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm import tqdm \n",
    "from xml.etree import ElementTree as ET\n",
    "from datetime import datetime\n",
    "import re\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from collections import Counter\n",
    "from sklearn.model_selection import StratifiedShuffleSplit, train_test_split"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from graphviz import Digraph\n",
    "from IPython.display import display\n",
    "import random\n",
    "def create_hierarchy_graph(dot, egdes, feature_name, created_nodes):\n",
    "    # 定义不同层级的颜色\n",
    "    level_colors = {\n",
    "        1: 'lightblue',\n",
    "        2: 'lightgreen',\n",
    "        3: 'yellow',\n",
    "        4: 'orange',\n",
    "        5: 'red',\n",
    "        6: 'peachpuff',\n",
    "        7: 'pink',\n",
    "        8: 'grey',\n",
    "        9: 'cyan',  # 可以根据实际层级数量调整或添加更多颜色\n",
    "        10: 'hotpink',\n",
    "        11: 'ivory',\n",
    "        12: 'blue',\n",
    "        13: 'lawngreen',\n",
    "        14: 'lavender',\n",
    "        15: 'khaki',\n",
    "        16: 'olivedrab1',\n",
    "        17: 'paleturquoise',\n",
    "        18: 'papayawhip',\n",
    "        19: 'purple',\n",
    "    }\n",
    "    nodes = feature_name.split('/')\n",
    "    node_paths = []  # 用于存储每个节点的唯一路径标识符\n",
    "    node_count = {}  # 用于计数并生成唯一ID\n",
    "\n",
    "    for i in range(len(nodes)):\n",
    "        if i == 0:\n",
    "            node_paths.append(nodes[i])\n",
    "            dot.node(nodes[i], label=nodes[i], shape='rect')\n",
    "        else:\n",
    "            unique_id = f\"{'/'.join(nodes[:i])}/{nodes[i]}\"\n",
    "            # unique_id = f\"{nodes[i-1]}/{nodes[i]}\"\n",
    "            if len(nodes[:i]) > 1:\n",
    "                color = all_color\n",
    "                # print(color)\n",
    "            elif len(nodes[:i]) == 1:\n",
    "                if unique_id in created_nodes.keys():\n",
    "                    color = created_nodes[unique_id]['color']\n",
    "                    all_color = color\n",
    "                else:\n",
    "                    # color = level_colors.get(i + 1, 'white')\n",
    "                    if 'condition' in nodes[i]:\n",
    "                        color = 'teal'\n",
    "                        created_nodes[unique_id] = {'color': color}\n",
    "                        all_color = color\n",
    "                    elif 'disposition_first' in nodes[i]:\n",
    "                        color = 'tomato'\n",
    "                        created_nodes[unique_id] = {'color': color}\n",
    "                        all_color = color\n",
    "                    elif 'enrollment' in nodes[i]:\n",
    "                        color = 'gold'\n",
    "                        created_nodes[unique_id] = {'color': color}\n",
    "                        all_color = color\n",
    "                    elif 'expanded_access' in nodes[i]:\n",
    "                        color = 'lightskyblue'\n",
    "                        created_nodes[unique_id] = {'color': color}\n",
    "                        all_color = color\n",
    "                    elif 'intervention' in nodes[i]:\n",
    "                        color = 'lightcoral'\n",
    "                        created_nodes[unique_id] = {'color': color}\n",
    "                        all_color = color\n",
    "                    else:\n",
    "                        color = level_colors.get((len(created_nodes) + 1) % len(level_colors), 'white')\n",
    "                        created_nodes[unique_id] = {'color': color}\n",
    "                        all_color = color\n",
    "\n",
    "            node_paths.append(unique_id)\n",
    "            dot.node(unique_id, label=nodes[i], shape='rect', style='filled', fillcolor=color)\n",
    "            edge = (node_paths[i-1], node_paths[i])\n",
    "            if edge not in edges:\n",
    "                edges.append(edge)\n",
    "                dot.edge(*edge)\n",
    "\n",
    "            \n",
    "\n",
    "    \n",
    "edges = []\n",
    "dot = Digraph(comment='Hierarchy Graph')\n",
    "feature_name = 'clinical_results/participant_flow/period_list/period/milestone_list/milestone/participants_list/participants'\n",
    "create_hierarchy_graph(dot, edges, feature_name, created_nodes={})\n",
    "display(dot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_info = pd.read_csv('feature-select.csv')\n",
    "dot = Digraph(comment='Feature Hierarchy')\n",
    "dot.attr(rankdir='LR')\n",
    "edges = []\n",
    "created_nodes = {}\n",
    "feature_names = sorted(feature_info['feature_name'].to_list())\n",
    "for name in feature_names:\n",
    "    name = 'Clinical Trial/' + name \n",
    "    print(name, len(created_nodes))\n",
    "    if 'textblock' in name:\n",
    "        name = name.replace('\\textblock', '')\n",
    "    create_hierarchy_graph(dot, edges, name, created_nodes)\n",
    "    \n",
    "dot.render('feature_hierarchy_color', format='pdf', cleanup=True)\n",
    "display(dot)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## feature-select"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "feature-select.csv是手动选feature的文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>备注</th>\n",
       "      <th>Number</th>\n",
       "      <th>Percent</th>\n",
       "      <th>Sample1</th>\n",
       "      <th>Sample2</th>\n",
       "      <th>Sample3</th>\n",
       "      <th>Sample4</th>\n",
       "      <th>trial failure reason prediction**</th>\n",
       "      <th>trial eligibility criteria design**</th>\n",
       "      <th>trial duration prediction</th>\n",
       "      <th>trial approval prediction</th>\n",
       "      <th>trial failure reason prediction</th>\n",
       "      <th>trial recruitment prediction</th>\n",
       "      <th>trial eligibility criteria design</th>\n",
       "      <th>drug dose prediction (?)</th>\n",
       "      <th>drug repurposing</th>\n",
       "      <th>Adverse Event Prediction（可能包括不良事件的类型，受伤和死亡人数）</th>\n",
       "      <th>Patient Amount Time-Series Forecasting（就是病人的数量会有变化的，一开始可能纳入一些人，后来可能就跑路或者死亡了）</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>feature_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th>id_info/org_study_id</th>\n",
       "      <td>NaN</td>\n",
       "      <td>483179</td>\n",
       "      <td>0.999876</td>\n",
       "      <td>NCRR-M01RR01070-0506</td>\n",
       "      <td>NCRR-M01RR00400-0587</td>\n",
       "      <td>2002LS032</td>\n",
       "      <td>NCRR-M01RR03186-9943</td>\n",
       "      <td>N</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
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       "    <tr>\n",
       "      <th>id_info/secondary_id</th>\n",
       "      <td>NaN</td>\n",
       "      <td>97797</td>\n",
       "      <td>0.202378</td>\n",
       "      <td>M01RR001070</td>\n",
       "      <td>M01RR000400</td>\n",
       "      <td>MT1999-06</td>\n",
       "      <td>M01RR003186</td>\n",
       "      <td>N</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id_info/nct_id</th>\n",
       "      <td>索引ID</td>\n",
       "      <td>483239</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NCT00000102</td>\n",
       "      <td>NCT00000104</td>\n",
       "      <td>NCT00000105</td>\n",
       "      <td>NCT00000106</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
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       "      <td>Y</td>\n",
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       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>brief_title</th>\n",
       "      <td>NaN</td>\n",
       "      <td>483239</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Congenital Adrenal Hyperplasia: Calcium Channe...</td>\n",
       "      <td>Does Lead Burden Alter Neuropsychological Deve...</td>\n",
       "      <td>Vaccination With Tetanus and KLH to Assess Imm...</td>\n",
       "      <td>41.8 Degree Centigrade Whole Body Hyperthermia...</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sponsors/lead_sponsor/agency</th>\n",
       "      <td>NaN</td>\n",
       "      <td>483239</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>National Center for Research Resources (NCRR)</td>\n",
       "      <td>National Center for Research Resources (NCRR)</td>\n",
       "      <td>Masonic Cancer Center, University of Minnesota</td>\n",
       "      <td>National Center for Research Resources (NCRR)</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
       "      <td>？</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>clinical_results/baseline/measure_list/measure/analyzed_list/analyzed/units</th>\n",
       "      <td>NaN</td>\n",
       "      <td>107</td>\n",
       "      <td>0.000221</td>\n",
       "      <td>['Participants', 'community', 'Participants', ...</td>\n",
       "      <td>['Participants', 'limbs', 'Participants', 'lim...</td>\n",
       "      <td>['Participants', 'warts', 'Participants', 'war...</td>\n",
       "      <td>['Participants', 'ICUs', 'Participants', 'ICUs...</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>clinical_results/baseline/measure_list/measure/analyzed_list/analyzed/scope</th>\n",
       "      <td>NaN</td>\n",
       "      <td>107</td>\n",
       "      <td>0.000221</td>\n",
       "      <td>['Measure', 'Measure', 'Measure', 'Measure', '...</td>\n",
       "      <td>['Measure', 'Measure', 'Measure', 'Measure', '...</td>\n",
       "      <td>['Measure', 'Measure', 'Measure', 'Measure', '...</td>\n",
       "      <td>['Measure', 'Measure', 'Measure', 'Measure', '...</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>clinical_results/baseline/measure_list/measure/analyzed_list/analyzed/count_list/count{group_id}</th>\n",
       "      <td>NaN</td>\n",
       "      <td>107</td>\n",
       "      <td>0.000221</td>\n",
       "      <td>['B1', 'B2', 'B3', 'B4', 'B5', 'B1', 'B2', 'B3...</td>\n",
       "      <td>['B1', 'B1', 'B1', 'B1', 'B1', 'B1', 'B1', 'B1']</td>\n",
       "      <td>['B1', 'B2', 'B3', 'B1', 'B2', 'B3', 'B1', 'B2...</td>\n",
       "      <td>['B1', 'B2', 'B3', 'B1', 'B2', 'B3', 'B1', 'B2...</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>clinical_results/baseline/measure_list/measure/analyzed_list/analyzed/count_list/count{value}</th>\n",
       "      <td>NaN</td>\n",
       "      <td>107</td>\n",
       "      <td>0.000221</td>\n",
       "      <td>['NA', 'NA', 'NA', 'NA', 'NA', '40', '40', '24...</td>\n",
       "      <td>['326', '396', '326', '396', '326', '396', '32...</td>\n",
       "      <td>['3', '2', '5', '5', '5', '10', '3', '2', '5',...</td>\n",
       "      <td>['270', '270', '540', '9', '9', '18', '270', '...</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oversight_info/is_ppsd</th>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "      <td>0.000025</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>266 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                      备注  Number   Percent  \\\n",
       "feature_name                                                                 \n",
       "id_info/org_study_id                                 NaN  483179  0.999876   \n",
       "id_info/secondary_id                                 NaN   97797  0.202378   \n",
       "id_info/nct_id                                      索引ID  483239  1.000000   \n",
       "brief_title                                          NaN  483239  1.000000   \n",
       "sponsors/lead_sponsor/agency                         NaN  483239  1.000000   \n",
       "...                                                  ...     ...       ...   \n",
       "clinical_results/baseline/measure_list/measure/...   NaN     107  0.000221   \n",
       "clinical_results/baseline/measure_list/measure/...   NaN     107  0.000221   \n",
       "clinical_results/baseline/measure_list/measure/...   NaN     107  0.000221   \n",
       "clinical_results/baseline/measure_list/measure/...   NaN     107  0.000221   \n",
       "oversight_info/is_ppsd                               NaN      12  0.000025   \n",
       "\n",
       "                                                                                              Sample1  \\\n",
       "feature_name                                                                                            \n",
       "id_info/org_study_id                                                             NCRR-M01RR01070-0506   \n",
       "id_info/secondary_id                                                                      M01RR001070   \n",
       "id_info/nct_id                                                                            NCT00000102   \n",
       "brief_title                                         Congenital Adrenal Hyperplasia: Calcium Channe...   \n",
       "sponsors/lead_sponsor/agency                            National Center for Research Resources (NCRR)   \n",
       "...                                                                                               ...   \n",
       "clinical_results/baseline/measure_list/measure/...  ['Participants', 'community', 'Participants', ...   \n",
       "clinical_results/baseline/measure_list/measure/...  ['Measure', 'Measure', 'Measure', 'Measure', '...   \n",
       "clinical_results/baseline/measure_list/measure/...  ['B1', 'B2', 'B3', 'B4', 'B5', 'B1', 'B2', 'B3...   \n",
       "clinical_results/baseline/measure_list/measure/...  ['NA', 'NA', 'NA', 'NA', 'NA', '40', '40', '24...   \n",
       "oversight_info/is_ppsd                                                                            Yes   \n",
       "\n",
       "                                                                                              Sample2  \\\n",
       "feature_name                                                                                            \n",
       "id_info/org_study_id                                                             NCRR-M01RR00400-0587   \n",
       "id_info/secondary_id                                                                      M01RR000400   \n",
       "id_info/nct_id                                                                            NCT00000104   \n",
       "brief_title                                         Does Lead Burden Alter Neuropsychological Deve...   \n",
       "sponsors/lead_sponsor/agency                            National Center for Research Resources (NCRR)   \n",
       "...                                                                                               ...   \n",
       "clinical_results/baseline/measure_list/measure/...  ['Participants', 'limbs', 'Participants', 'lim...   \n",
       "clinical_results/baseline/measure_list/measure/...  ['Measure', 'Measure', 'Measure', 'Measure', '...   \n",
       "clinical_results/baseline/measure_list/measure/...   ['B1', 'B1', 'B1', 'B1', 'B1', 'B1', 'B1', 'B1']   \n",
       "clinical_results/baseline/measure_list/measure/...  ['326', '396', '326', '396', '326', '396', '32...   \n",
       "oversight_info/is_ppsd                                                                            Yes   \n",
       "\n",
       "                                                                                              Sample3  \\\n",
       "feature_name                                                                                            \n",
       "id_info/org_study_id                                                                        2002LS032   \n",
       "id_info/secondary_id                                                                        MT1999-06   \n",
       "id_info/nct_id                                                                            NCT00000105   \n",
       "brief_title                                         Vaccination With Tetanus and KLH to Assess Imm...   \n",
       "sponsors/lead_sponsor/agency                           Masonic Cancer Center, University of Minnesota   \n",
       "...                                                                                               ...   \n",
       "clinical_results/baseline/measure_list/measure/...  ['Participants', 'warts', 'Participants', 'war...   \n",
       "clinical_results/baseline/measure_list/measure/...  ['Measure', 'Measure', 'Measure', 'Measure', '...   \n",
       "clinical_results/baseline/measure_list/measure/...  ['B1', 'B2', 'B3', 'B1', 'B2', 'B3', 'B1', 'B2...   \n",
       "clinical_results/baseline/measure_list/measure/...  ['3', '2', '5', '5', '5', '10', '3', '2', '5',...   \n",
       "oversight_info/is_ppsd                                                                            Yes   \n",
       "\n",
       "                                                                                              Sample4  \\\n",
       "feature_name                                                                                            \n",
       "id_info/org_study_id                                                             NCRR-M01RR03186-9943   \n",
       "id_info/secondary_id                                                                      M01RR003186   \n",
       "id_info/nct_id                                                                            NCT00000106   \n",
       "brief_title                                         41.8 Degree Centigrade Whole Body Hyperthermia...   \n",
       "sponsors/lead_sponsor/agency                            National Center for Research Resources (NCRR)   \n",
       "...                                                                                               ...   \n",
       "clinical_results/baseline/measure_list/measure/...  ['Participants', 'ICUs', 'Participants', 'ICUs...   \n",
       "clinical_results/baseline/measure_list/measure/...  ['Measure', 'Measure', 'Measure', 'Measure', '...   \n",
       "clinical_results/baseline/measure_list/measure/...  ['B1', 'B2', 'B3', 'B1', 'B2', 'B3', 'B1', 'B2...   \n",
       "clinical_results/baseline/measure_list/measure/...  ['270', '270', '540', '9', '9', '18', '270', '...   \n",
       "oversight_info/is_ppsd                                                                            Yes   \n",
       "\n",
       "                                                   trial failure reason prediction**  \\\n",
       "feature_name                                                                           \n",
       "id_info/org_study_id                                                               N   \n",
       "id_info/secondary_id                                                               N   \n",
       "id_info/nct_id                                                                     N   \n",
       "brief_title                                                                        Y   \n",
       "sponsors/lead_sponsor/agency                                                       N   \n",
       "...                                                                              ...   \n",
       "clinical_results/baseline/measure_list/measure/...                                 N   \n",
       "clinical_results/baseline/measure_list/measure/...                                 N   \n",
       "clinical_results/baseline/measure_list/measure/...                                 N   \n",
       "clinical_results/baseline/measure_list/measure/...                                 N   \n",
       "oversight_info/is_ppsd                                                             N   \n",
       "\n",
       "                                                   trial eligibility criteria design**  \\\n",
       "feature_name                                                                             \n",
       "id_info/org_study_id                                                                 ？   \n",
       "id_info/secondary_id                                                                 ？   \n",
       "id_info/nct_id                                                                       Y   \n",
       "brief_title                                                                          Y   \n",
       "sponsors/lead_sponsor/agency                                                         N   \n",
       "...                                                                                ...   \n",
       "clinical_results/baseline/measure_list/measure/...                                   N   \n",
       "clinical_results/baseline/measure_list/measure/...                                   N   \n",
       "clinical_results/baseline/measure_list/measure/...                                   N   \n",
       "clinical_results/baseline/measure_list/measure/...                                   N   \n",
       "oversight_info/is_ppsd                                                               N   \n",
       "\n",
       "                                                   trial duration prediction  \\\n",
       "feature_name                                                                   \n",
       "id_info/org_study_id                                                       ？   \n",
       "id_info/secondary_id                                                       ？   \n",
       "id_info/nct_id                                                             Y   \n",
       "brief_title                                                                Y   \n",
       "sponsors/lead_sponsor/agency                                               ？   \n",
       "...                                                                      ...   \n",
       "clinical_results/baseline/measure_list/measure/...                         N   \n",
       "clinical_results/baseline/measure_list/measure/...                         N   \n",
       "clinical_results/baseline/measure_list/measure/...                         N   \n",
       "clinical_results/baseline/measure_list/measure/...                         N   \n",
       "oversight_info/is_ppsd                                                     N   \n",
       "\n",
       "                                                   trial approval prediction  \\\n",
       "feature_name                                                                   \n",
       "id_info/org_study_id                                                       ？   \n",
       "id_info/secondary_id                                                       ？   \n",
       "id_info/nct_id                                                             Y   \n",
       "brief_title                                                                Y   \n",
       "sponsors/lead_sponsor/agency                                               ？   \n",
       "...                                                                      ...   \n",
       "clinical_results/baseline/measure_list/measure/...                         N   \n",
       "clinical_results/baseline/measure_list/measure/...                         N   \n",
       "clinical_results/baseline/measure_list/measure/...                         N   \n",
       "clinical_results/baseline/measure_list/measure/...                         N   \n",
       "oversight_info/is_ppsd                                                     N   \n",
       "\n",
       "                                                   trial failure reason prediction  \\\n",
       "feature_name                                                                         \n",
       "id_info/org_study_id                                                             ？   \n",
       "id_info/secondary_id                                                             ？   \n",
       "id_info/nct_id                                                                   Y   \n",
       "brief_title                                                                      Y   \n",
       "sponsors/lead_sponsor/agency                                                     ？   \n",
       "...                                                                            ...   \n",
       "clinical_results/baseline/measure_list/measure/...                               N   \n",
       "clinical_results/baseline/measure_list/measure/...                               N   \n",
       "clinical_results/baseline/measure_list/measure/...                               N   \n",
       "clinical_results/baseline/measure_list/measure/...                               N   \n",
       "oversight_info/is_ppsd                                                           N   \n",
       "\n",
       "                                                   trial recruitment prediction  \\\n",
       "feature_name                                                                      \n",
       "id_info/org_study_id                                                          ？   \n",
       "id_info/secondary_id                                                          ？   \n",
       "id_info/nct_id                                                                Y   \n",
       "brief_title                                                                   Y   \n",
       "sponsors/lead_sponsor/agency                                                  ？   \n",
       "...                                                                         ...   \n",
       "clinical_results/baseline/measure_list/measure/...                            N   \n",
       "clinical_results/baseline/measure_list/measure/...                            N   \n",
       "clinical_results/baseline/measure_list/measure/...                            N   \n",
       "clinical_results/baseline/measure_list/measure/...                            N   \n",
       "oversight_info/is_ppsd                                                        N   \n",
       "\n",
       "                                                   trial eligibility criteria design  \\\n",
       "feature_name                                                                           \n",
       "id_info/org_study_id                                                               ？   \n",
       "id_info/secondary_id                                                               ？   \n",
       "id_info/nct_id                                                                     Y   \n",
       "brief_title                                                                        Y   \n",
       "sponsors/lead_sponsor/agency                                                       ？   \n",
       "...                                                                              ...   \n",
       "clinical_results/baseline/measure_list/measure/...                                 N   \n",
       "clinical_results/baseline/measure_list/measure/...                                 N   \n",
       "clinical_results/baseline/measure_list/measure/...                                 N   \n",
       "clinical_results/baseline/measure_list/measure/...                                 N   \n",
       "oversight_info/is_ppsd                                                             N   \n",
       "\n",
       "                                                   drug dose prediction (?)  \\\n",
       "feature_name                                                                  \n",
       "id_info/org_study_id                                                      ？   \n",
       "id_info/secondary_id                                                      ？   \n",
       "id_info/nct_id                                                            Y   \n",
       "brief_title                                                               N   \n",
       "sponsors/lead_sponsor/agency                                              ？   \n",
       "...                                                                     ...   \n",
       "clinical_results/baseline/measure_list/measure/...                        N   \n",
       "clinical_results/baseline/measure_list/measure/...                        N   \n",
       "clinical_results/baseline/measure_list/measure/...                        N   \n",
       "clinical_results/baseline/measure_list/measure/...                        N   \n",
       "oversight_info/is_ppsd                                                    N   \n",
       "\n",
       "                                                   drug repurposing  \\\n",
       "feature_name                                                          \n",
       "id_info/org_study_id                                              ？   \n",
       "id_info/secondary_id                                              ？   \n",
       "id_info/nct_id                                                    Y   \n",
       "brief_title                                                       N   \n",
       "sponsors/lead_sponsor/agency                                      ？   \n",
       "...                                                             ...   \n",
       "clinical_results/baseline/measure_list/measure/...                N   \n",
       "clinical_results/baseline/measure_list/measure/...                N   \n",
       "clinical_results/baseline/measure_list/measure/...                N   \n",
       "clinical_results/baseline/measure_list/measure/...                N   \n",
       "oversight_info/is_ppsd                                            N   \n",
       "\n",
       "                                                   Adverse Event Prediction（可能包括不良事件的类型，受伤和死亡人数）  \\\n",
       "feature_name                                                                                       \n",
       "id_info/org_study_id                                                                           ？   \n",
       "id_info/secondary_id                                                                           ？   \n",
       "id_info/nct_id                                                                                 Y   \n",
       "brief_title                                                                                    N   \n",
       "sponsors/lead_sponsor/agency                                                                   ？   \n",
       "...                                                                                          ...   \n",
       "clinical_results/baseline/measure_list/measure/...                                             N   \n",
       "clinical_results/baseline/measure_list/measure/...                                             N   \n",
       "clinical_results/baseline/measure_list/measure/...                                             N   \n",
       "clinical_results/baseline/measure_list/measure/...                                             N   \n",
       "oversight_info/is_ppsd                                                                         N   \n",
       "\n",
       "                                                   Patient Amount Time-Series Forecasting（就是病人的数量会有变化的，一开始可能纳入一些人，后来可能就跑路或者死亡了）  \n",
       "feature_name                                                                                                                     \n",
       "id_info/org_study_id                                                                                ？                            \n",
       "id_info/secondary_id                                                                                ？                            \n",
       "id_info/nct_id                                                                                      Y                            \n",
       "brief_title                                                                                         N                            \n",
       "sponsors/lead_sponsor/agency                                                                        ？                            \n",
       "...                                                                                               ...                            \n",
       "clinical_results/baseline/measure_list/measure/...                                                  N                            \n",
       "clinical_results/baseline/measure_list/measure/...                                                  N                            \n",
       "clinical_results/baseline/measure_list/measure/...                                                  N                            \n",
       "clinical_results/baseline/measure_list/measure/...                                                  N                            \n",
       "oversight_info/is_ppsd                                                                              N                            \n",
       "\n",
       "[266 rows x 18 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_info = pd.read_csv('feature-select.csv').set_index('feature_name')\n",
    "feature_info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取全部48万条所有数据\n",
    "All_data = []\n",
    "for i in range(10):\n",
    "    All_data.append(pd.read_csv(f'../../preprocess_data/All_data_part{i}.csv', index_col=0, low_memory=False))\n",
    "    # print(len(All_data[i].columns))\n",
    "    \n",
    "All_Ori = pd.concat(All_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 以adverse-event的为基础，处理特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['phase',\n",
       " 'study_type',\n",
       " 'has_expanded_access',\n",
       " 'study_design_info/intervention_model',\n",
       " 'study_design_info/primary_purpose',\n",
       " 'eligibility/gender',\n",
       " 'eligibility/healthy_volunteers',\n",
       " 'oversight_info/has_dmc',\n",
       " 'study_design_info/allocation',\n",
       " 'patient_data/sharing_ipd',\n",
       " 'oversight_info/is_fda_regulated_drug',\n",
       " 'oversight_info/is_fda_regulated_device',\n",
       " 'eligibility/minimum_age',\n",
       " 'eligibility/maximum_age',\n",
       " 'number_of_arms',\n",
       " 'id_info/nct_id',\n",
       " 'brief_title',\n",
       " 'brief_summary/textblock',\n",
       " 'study_design_info/masking',\n",
       " 'condition',\n",
       " 'intervention/intervention_type',\n",
       " 'intervention/intervention_name',\n",
       " 'eligibility/criteria/textblock',\n",
       " 'location/facility/address/city',\n",
       " 'condition_browse/mesh_term',\n",
       " 'intervention_browse/mesh_term',\n",
       " 'icdcode',\n",
       " 'keyword',\n",
       " 'enrollment',\n",
       " 'arm_group/arm_group_type']"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mortality_rate_MI_handmake.csv是第一次手动筛选的特征 适用四个task, 选择出选中的特征\n",
    "handmake = pd.read_csv('adverse-event-rate-prediction/mortality_rate_MI_handmake.csv',index_col=0)\n",
    "handmake = handmake[handmake['____/__'] == 'Y']\n",
    "selected_feature = list(handmake.index)\n",
    "selected_feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "40\n"
     ]
    }
   ],
   "source": [
    "# 经过检查后添加的一部分特征\n",
    "selected_feature.extend(['eligibility/sampling_method', 'patient_data/ipd_info_type', 'sponsors/lead_sponsor/agency_class', 'completion_date{type}', 'start_date{type}', 'enrollment{type}',\n",
    "                         'responsible_party/responsible_party_type', 'study_design_info/observational_model', 'study_design_info/time_perspective', 'biospec_retention', \n",
    "                        #  'clinical_results/baseline/measure_list/measure/dispersion', 'clinical_results/baseline/measure_list/measure/param', \n",
    "                        #  'clinical_results/reported_events/serious_events/category_list/category/event_list/event/assessment',\n",
    "                        #  'clinical_results/outcome_list/outcome/analysis_list/analysis/dispersion_type',\n",
    "                        #  'clinical_results/outcome_list/outcome/analysis_list/analysis/non_inferiority_type'\n",
    "                         ])\n",
    "print(len(selected_feature))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 一些明确的特征类型 文本、类别、连续\n",
    "text_feature = ['brief_title', 'brief_summary', 'detailed_description', 'eligibility/criteria/textblock','eligibility/study_pop/textblock', 'intervention/description',\n",
    "'keyword', 'study_design_info/intervention_model_description', 'study_design_info/masking_description']\n",
    "# condition -> condition_browse/mesh_term -> embedding \n",
    "# intervention/intervention_name -> intervention_browse/mesh_term -> embedding \n",
    "category_feature = ['eligibility/gender', 'eligibility/healthy_volunteers', 'eligibility/sampling_method', 'has_expanded_access', 'oversight_info/has_dmc',\n",
    "'oversight_info/is_fda_regulated_device', 'oversight_info/is_fda_regulated_drug', 'patient_data/sharing_ipd', 'phase', 'responsible_party/responsible_party_type',\n",
    "'sponsors/lead_sponsor/agency_class', 'study_design_info/allocation', 'study_design_info/intervention_model', 'study_design_info/masking_num',\n",
    "'study_design_info/observational_model', 'study_design_info/primary_purpose', 'study_design_info/time_perspective', 'study_type'] # \"MaskingType-*\"(0/1) + ipd_info_type-*(0/1)\n",
    "continue_feature = ['eligibility/minimum_age', 'eligibility/maximum_age', 'enrollment', 'number_of_arms'] # \"*arm number\", \"intervention number\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "All = All_Ori[selected_feature]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "        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>status</th>\n",
       "      <th>why_stop</th>\n",
       "      <th>label</th>\n",
       "      <th>phase</th>\n",
       "      <th>diseases</th>\n",
       "      <th>icdcodes</th>\n",
       "      <th>drugs</th>\n",
       "      <th>smiless</th>\n",
       "      <th>criteria</th>\n",
       "      <th>complete_year</th>\n",
       "      <th>start_year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nctid</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>NCT00000102</th>\n",
       "      <td>completed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1</td>\n",
       "      <td>phase 1/phase 2</td>\n",
       "      <td>['congenital adrenal hyperplasia']</td>\n",
       "      <td>[\"['N25.0', 'Q61.4', 'N23', 'N26.9', 'P96.0', ...</td>\n",
       "      <td>['nifedipine']</td>\n",
       "      <td>['COC(=O)C1=C(C)NC(C)=C(C1C1=CC=CC=C1[N+]([O-]...</td>\n",
       "      <td>\\n        Inclusion Criteria:\\r\\n\\r\\n         ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000110</th>\n",
       "      <td>completed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['obesity']</td>\n",
       "      <td>[\"['E66.8', 'E66.9', 'E66.1', 'O99.214', 'O99....</td>\n",
       "      <td>['dietary fat']</td>\n",
       "      <td>[]</td>\n",
       "      <td>\\n        Inclusion Criteria:\\r\\n\\r\\n         ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000114</th>\n",
       "      <td>completed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1</td>\n",
       "      <td>phase 3</td>\n",
       "      <td>['retinitis pigmentosa']</td>\n",
       "      <td>[]</td>\n",
       "      <td>['vitamin e', 'vitamin a']</td>\n",
       "      <td>['CC(C)CCC[C@@H](C)CCC[C@@H](C)CCC[C@]1(C)CCC2...</td>\n",
       "      <td>\\n        Men and nonpregnant women between ag...</td>\n",
       "      <td>1987.0</td>\n",
       "      <td>1984.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000115</th>\n",
       "      <td>completed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1</td>\n",
       "      <td>phase 2</td>\n",
       "      <td>['macular edema, cystoid']</td>\n",
       "      <td>[]</td>\n",
       "      <td>['acetazolamide']</td>\n",
       "      <td>['CC(=O)NC1=NN=C(S1)S(N)(=O)=O']</td>\n",
       "      <td>\\n        Males and females 8 years of age or ...</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>1990.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000117</th>\n",
       "      <td>completed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1</td>\n",
       "      <td>phase 3</td>\n",
       "      <td>['optic neuritis']</td>\n",
       "      <td>[\"['H46.8', 'H46.9']\"]</td>\n",
       "      <td>['immunoglobulin']</td>\n",
       "      <td>[]</td>\n",
       "      <td>\\n        To be eligible, patients must have a...</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>1995.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06263959</th>\n",
       "      <td>recruiting</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1</td>\n",
       "      <td>phase 2</td>\n",
       "      <td>['chronic hepatitis b']</td>\n",
       "      <td>[\"['B18.0', 'B18.1', 'B18.2', 'B18.8', 'B18.9']\"]</td>\n",
       "      <td>['gst-hg131', 'placebo to match gst-hg131']</td>\n",
       "      <td>[]</td>\n",
       "      <td>\\n        Inclusion Criteria:\\r\\n\\r\\n         ...</td>\n",
       "      <td>2024.0</td>\n",
       "      <td>2023.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06263998</th>\n",
       "      <td>not yet recruiting</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1</td>\n",
       "      <td>phase 1</td>\n",
       "      <td>['xerophthalmia']</td>\n",
       "      <td>[]</td>\n",
       "      <td>['ncp112', 'ncp112 placebo']</td>\n",
       "      <td>[]</td>\n",
       "      <td>\\n        Inclusion Criteria:\\r\\n\\r\\n         ...</td>\n",
       "      <td>2025.0</td>\n",
       "      <td>2024.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264141</th>\n",
       "      <td>recruiting</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1</td>\n",
       "      <td>phase 2</td>\n",
       "      <td>['recurrent acute rhinosinusitis']</td>\n",
       "      <td>[]</td>\n",
       "      <td>['nitric oxide releasing solution']</td>\n",
       "      <td>[]</td>\n",
       "      <td>\\n        Inclusion Criteria:\\r\\n\\r\\n         ...</td>\n",
       "      <td>2024.0</td>\n",
       "      <td>2024.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264180</th>\n",
       "      <td>not yet recruiting</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1</td>\n",
       "      <td>phase 3</td>\n",
       "      <td>['advanced melanoma']</td>\n",
       "      <td>[\"['K74.02', 'G47.22', 'H35.3133', 'H35.3134',...</td>\n",
       "      <td>['single-agent chemotherapy']</td>\n",
       "      <td>[]</td>\n",
       "      <td>\\n        Key Inclusion Criteria:\\r\\n\\r\\n     ...</td>\n",
       "      <td>2029.0</td>\n",
       "      <td>2024.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264310</th>\n",
       "      <td>not yet recruiting</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1</td>\n",
       "      <td>phase 2</td>\n",
       "      <td>['heart failure', 'worsening heart failure (wh...</td>\n",
       "      <td>[\"['I50.814', 'I09.81', 'I50.82', 'I50.89', 'I...</td>\n",
       "      <td>['placebo', 'r2r01']</td>\n",
       "      <td>[]</td>\n",
       "      <td>\\n        Inclusion Criteria:\\r\\n\\r\\n         ...</td>\n",
       "      <td>2025.0</td>\n",
       "      <td>2024.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>171992 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         status why_stop  label            phase  \\\n",
       "nctid                                                              \n",
       "NCT00000102           completed      NaN     -1  phase 1/phase 2   \n",
       "NCT00000110           completed      NaN     -1              NaN   \n",
       "NCT00000114           completed      NaN     -1          phase 3   \n",
       "NCT00000115           completed      NaN     -1          phase 2   \n",
       "NCT00000117           completed      NaN     -1          phase 3   \n",
       "...                         ...      ...    ...              ...   \n",
       "NCT06263959          recruiting      NaN     -1          phase 2   \n",
       "NCT06263998  not yet recruiting      NaN     -1          phase 1   \n",
       "NCT06264141          recruiting      NaN     -1          phase 2   \n",
       "NCT06264180  not yet recruiting      NaN     -1          phase 3   \n",
       "NCT06264310  not yet recruiting      NaN     -1          phase 2   \n",
       "\n",
       "                                                      diseases  \\\n",
       "nctid                                                            \n",
       "NCT00000102                 ['congenital adrenal hyperplasia']   \n",
       "NCT00000110                                        ['obesity']   \n",
       "NCT00000114                           ['retinitis pigmentosa']   \n",
       "NCT00000115                         ['macular edema, cystoid']   \n",
       "NCT00000117                                 ['optic neuritis']   \n",
       "...                                                        ...   \n",
       "NCT06263959                            ['chronic hepatitis b']   \n",
       "NCT06263998                                  ['xerophthalmia']   \n",
       "NCT06264141                 ['recurrent acute rhinosinusitis']   \n",
       "NCT06264180                              ['advanced melanoma']   \n",
       "NCT06264310  ['heart failure', 'worsening heart failure (wh...   \n",
       "\n",
       "                                                      icdcodes  \\\n",
       "nctid                                                            \n",
       "NCT00000102  [\"['N25.0', 'Q61.4', 'N23', 'N26.9', 'P96.0', ...   \n",
       "NCT00000110  [\"['E66.8', 'E66.9', 'E66.1', 'O99.214', 'O99....   \n",
       "NCT00000114                                                 []   \n",
       "NCT00000115                                                 []   \n",
       "NCT00000117                             [\"['H46.8', 'H46.9']\"]   \n",
       "...                                                        ...   \n",
       "NCT06263959  [\"['B18.0', 'B18.1', 'B18.2', 'B18.8', 'B18.9']\"]   \n",
       "NCT06263998                                                 []   \n",
       "NCT06264141                                                 []   \n",
       "NCT06264180  [\"['K74.02', 'G47.22', 'H35.3133', 'H35.3134',...   \n",
       "NCT06264310  [\"['I50.814', 'I09.81', 'I50.82', 'I50.89', 'I...   \n",
       "\n",
       "                                                   drugs  \\\n",
       "nctid                                                      \n",
       "NCT00000102                               ['nifedipine']   \n",
       "NCT00000110                              ['dietary fat']   \n",
       "NCT00000114                   ['vitamin e', 'vitamin a']   \n",
       "NCT00000115                            ['acetazolamide']   \n",
       "NCT00000117                           ['immunoglobulin']   \n",
       "...                                                  ...   \n",
       "NCT06263959  ['gst-hg131', 'placebo to match gst-hg131']   \n",
       "NCT06263998                 ['ncp112', 'ncp112 placebo']   \n",
       "NCT06264141          ['nitric oxide releasing solution']   \n",
       "NCT06264180                ['single-agent chemotherapy']   \n",
       "NCT06264310                         ['placebo', 'r2r01']   \n",
       "\n",
       "                                                       smiless  \\\n",
       "nctid                                                            \n",
       "NCT00000102  ['COC(=O)C1=C(C)NC(C)=C(C1C1=CC=CC=C1[N+]([O-]...   \n",
       "NCT00000110                                                 []   \n",
       "NCT00000114  ['CC(C)CCC[C@@H](C)CCC[C@@H](C)CCC[C@]1(C)CCC2...   \n",
       "NCT00000115                   ['CC(=O)NC1=NN=C(S1)S(N)(=O)=O']   \n",
       "NCT00000117                                                 []   \n",
       "...                                                        ...   \n",
       "NCT06263959                                                 []   \n",
       "NCT06263998                                                 []   \n",
       "NCT06264141                                                 []   \n",
       "NCT06264180                                                 []   \n",
       "NCT06264310                                                 []   \n",
       "\n",
       "                                                      criteria  complete_year  \\\n",
       "nctid                                                                           \n",
       "NCT00000102  \\n        Inclusion Criteria:\\r\\n\\r\\n         ...            NaN   \n",
       "NCT00000110  \\n        Inclusion Criteria:\\r\\n\\r\\n         ...            NaN   \n",
       "NCT00000114  \\n        Men and nonpregnant women between ag...         1987.0   \n",
       "NCT00000115  \\n        Males and females 8 years of age or ...         1994.0   \n",
       "NCT00000117  \\n        To be eligible, patients must have a...         1997.0   \n",
       "...                                                        ...            ...   \n",
       "NCT06263959  \\n        Inclusion Criteria:\\r\\n\\r\\n         ...         2024.0   \n",
       "NCT06263998  \\n        Inclusion Criteria:\\r\\n\\r\\n         ...         2025.0   \n",
       "NCT06264141  \\n        Inclusion Criteria:\\r\\n\\r\\n         ...         2024.0   \n",
       "NCT06264180  \\n        Key Inclusion Criteria:\\r\\n\\r\\n     ...         2029.0   \n",
       "NCT06264310  \\n        Inclusion Criteria:\\r\\n\\r\\n         ...         2025.0   \n",
       "\n",
       "             start_year  \n",
       "nctid                    \n",
       "NCT00000102         NaN  \n",
       "NCT00000110         NaN  \n",
       "NCT00000114      1984.0  \n",
       "NCT00000115      1990.0  \n",
       "NCT00000117      1995.0  \n",
       "...                 ...  \n",
       "NCT06263959      2023.0  \n",
       "NCT06263998      2024.0  \n",
       "NCT06264141      2024.0  \n",
       "NCT06264180      2024.0  \n",
       "NCT06264310      2024.0  \n",
       "\n",
       "[171992 rows x 11 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# raw_data 是参考HINT提取出的数据，包含icdcode和smiless\n",
    "raw_data = pd.read_csv('raw_data.csv', index_col=0)\n",
    "raw_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## patient_data/ipd_info_type 处理成多个multi-hot特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "patient_data/ipd_info_type\n",
       "['Study Protocol', 'Statistical Analysis Plan (SAP)', 'Informed Consent Form (ICF)', 'Clinical Study Report (CSR)']                     2985\n",
       "['Study Protocol', 'Statistical Analysis Plan (SAP)']                                                                                   2898\n",
       "Study Protocol                                                                                                                          2799\n",
       "['Study Protocol', 'Statistical Analysis Plan (SAP)', 'Informed Consent Form (ICF)']                                                    2709\n",
       "['Study Protocol', 'Statistical Analysis Plan (SAP)', 'Informed Consent Form (ICF)', 'Clinical Study Report (CSR)', 'Analytic Code']    2374\n",
       "['Study Protocol', 'Statistical Analysis Plan (SAP)', 'Clinical Study Report (CSR)']                                                    2089\n",
       "['Study Protocol', 'Informed Consent Form (ICF)']                                                                                       1083\n",
       "['Study Protocol', 'Clinical Study Report (CSR)']                                                                                        561\n",
       "Clinical Study Report (CSR)                                                                                                              530\n",
       "['Study Protocol', 'Statistical Analysis Plan (SAP)', 'Analytic Code']                                                                   513\n",
       "['Study Protocol', 'Statistical Analysis Plan (SAP)', 'Informed Consent Form (ICF)', 'Analytic Code']                                    503\n",
       "['Study Protocol', 'Informed Consent Form (ICF)', 'Clinical Study Report (CSR)']                                                         445\n",
       "['Study Protocol', 'Statistical Analysis Plan (SAP)', 'Clinical Study Report (CSR)', 'Analytic Code']                                    312\n",
       "Statistical Analysis Plan (SAP)                                                                                                          209\n",
       "Analytic Code                                                                                                                            180\n",
       "['Study Protocol', 'Analytic Code']                                                                                                      161\n",
       "Informed Consent Form (ICF)                                                                                                              150\n",
       "['Study Protocol', 'Informed Consent Form (ICF)', 'Analytic Code']                                                                       119\n",
       "['Statistical Analysis Plan (SAP)', 'Informed Consent Form (ICF)']                                                                        81\n",
       "['Statistical Analysis Plan (SAP)', 'Clinical Study Report (CSR)']                                                                        76\n",
       "['Study Protocol', 'Informed Consent Form (ICF)', 'Clinical Study Report (CSR)', 'Analytic Code']                                         73\n",
       "['Statistical Analysis Plan (SAP)', 'Analytic Code']                                                                                      66\n",
       "['Study Protocol', 'Clinical Study Report (CSR)', 'Analytic Code']                                                                        52\n",
       "['Statistical Analysis Plan (SAP)', 'Informed Consent Form (ICF)', 'Clinical Study Report (CSR)']                                         40\n",
       "['Clinical Study Report (CSR)', 'Analytic Code']                                                                                          29\n",
       "['Informed Consent Form (ICF)', 'Clinical Study Report (CSR)']                                                                            28\n",
       "['Statistical Analysis Plan (SAP)', 'Clinical Study Report (CSR)', 'Analytic Code']                                                       13\n",
       "['Informed Consent Form (ICF)', 'Analytic Code']                                                                                          12\n",
       "['Statistical Analysis Plan (SAP)', 'Informed Consent Form (ICF)', 'Analytic Code']                                                       11\n",
       "['Statistical Analysis Plan (SAP)', 'Informed Consent Form (ICF)', 'Clinical Study Report (CSR)', 'Analytic Code']                         7\n",
       "['Informed Consent Form (ICF)', 'Clinical Study Report (CSR)', 'Analytic Code']                                                            2\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "All['patient_data/ipd_info_type'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Study Protocol', 'Informed Consent Form (ICF)', 'Clinical Study Report (CSR)', 'Analytic Code']\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'ipd_info_type-Study Protocol': 1,\n",
       " 'ipd_info_type-Informed Consent Form (ICF)': 1,\n",
       " 'ipd_info_type-Clinical Study Report (CSR)': 1,\n",
       " 'ipd_info_type-Analytic Code': 1}"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "value = All['patient_data/ipd_info_type']['NCT00805532']\n",
    "\n",
    "def ipd_info_type_2Mulitlabel(value):\n",
    "    if type(value) == list:\n",
    "        counts = dict(Counter(value))\n",
    "    elif type(value) == str and value[0] != '[':\n",
    "        counts = {'ipd_info_type-' + value:1}\n",
    "    elif type(value) == str and value[0] == '[':\n",
    "        value = eval(value)\n",
    "        counts = dict(Counter(value))\n",
    "        # for key, value in counts.items():\n",
    "        counts = {'ipd_info_type-' + key: value for key, value in counts.items()}\n",
    "    else: \n",
    "        counts = {}\n",
    "        \n",
    "    return counts\n",
    "\n",
    "print(All['patient_data/ipd_info_type']['NCT00805532'])\n",
    "ipd_info_type_2Mulitlabel(value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ipd_info_type-Statistical Analysis Plan (SAP)\n",
      "1.0    14886\n",
      "0.0     6224\n",
      "Name: count, dtype: int64\n",
      "ipd_info_type-Informed Consent Form (ICF)\n",
      "1.0    10622\n",
      "0.0    10488\n",
      "Name: count, dtype: int64\n",
      "ipd_info_type-Study Protocol\n",
      "1.0    19676\n",
      "0.0     1434\n",
      "Name: count, dtype: int64\n",
      "ipd_info_type-Clinical Study Report (CSR)\n",
      "0.0    11494\n",
      "1.0     9616\n",
      "Name: count, dtype: int64\n",
      "ipd_info_type-Analytic Code\n",
      "0.0    16683\n",
      "1.0     4427\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "ipd_info_types = pd.DataFrame(All['patient_data/ipd_info_type'].apply(ipd_info_type_2Mulitlabel).tolist(), index=All.index)\n",
    "ipd_info_types[All['patient_data/ipd_info_type'].notna()] = ipd_info_types[All['patient_data/ipd_info_type'].notna()].fillna(0).astype(int)\n",
    "All = pd.merge(All, ipd_info_types, left_index=True, right_index=True)\n",
    "for feature in All.columns:\n",
    "    if 'ipd_info_type-' in feature:\n",
    "        print(All[feature].value_counts())\n",
    "# 卸磨杀驴\n",
    "All = All.drop('patient_data/ipd_info_type', axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 将study_design_info/masking处理成Multi-hot和 masking num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "study_design_info/masking\n",
       "None (Open Label)                                                          204096\n",
       "Quadruple (Participant, Care Provider, Investigator, Outcomes Assessor)     33975\n",
       "Double (Participant, Investigator)                                          24732\n",
       "Single (Outcomes Assessor)                                                  23295\n",
       "Single (Participant)                                                        20871\n",
       "Triple (Participant, Investigator, Outcomes Assessor)                       10395\n",
       "Triple (Participant, Care Provider, Investigator)                           10328\n",
       "Double (Participant, Outcomes Assessor)                                     10319\n",
       "Double                                                                       6116\n",
       "Single (Investigator)                                                        6083\n",
       "Double (Investigator, Outcomes Assessor)                                     4810\n",
       "Double (Participant, Care Provider)                                          3461\n",
       "Triple (Participant, Care Provider, Outcomes Assessor)                       3001\n",
       "Single                                                                       1269\n",
       "Single (Care Provider)                                                       1132\n",
       "Triple (Care Provider, Investigator, Outcomes Assessor)                       874\n",
       "Double (Care Provider, Outcomes Assessor)                                     780\n",
       "Double (Care Provider, Investigator)                                          434\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "All['study_design_info/masking'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_masking_num(x):\n",
    "    if pd.isnull(x):\n",
    "        return None\n",
    "    if 'Double' in x:\n",
    "        return 2\n",
    "    elif 'Single' in x:\n",
    "        return 1\n",
    "    elif 'Triple' in x:\n",
    "        return 3\n",
    "    elif 'Quadruple' in x:\n",
    "        return 4\n",
    "    else:\n",
    "        return 0\n",
    "\n",
    "All['study_design_info/masking_num'] = All['study_design_info/masking'].apply(get_masking_num)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "study_design_info/masking_num\n",
       "0.0    204096\n",
       "1.0     52650\n",
       "2.0     50652\n",
       "4.0     33975\n",
       "3.0     24598\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "All['study_design_info/masking_num'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_masking_multihot(x):\n",
    "    # Indent the code block properly\n",
    "    if pd.isnull(x):\n",
    "        return [None, None, None, None]\n",
    "    vector = [0, 0, 0, 0]\n",
    "    if 'Participant' in x:\n",
    "        vector[0] = 1\n",
    "    if 'Care Provider' in x:\n",
    "        vector[1] = 1\n",
    "    if 'Investigator' in x:\n",
    "        vector[2] = 1\n",
    "    if 'Outcomes Assessor' in x:\n",
    "        vector[3] = 1\n",
    "    if get_masking_num(x) != 0 and sum(vector) == 0:\n",
    "        return [None, None, None, None]\n",
    "    assert sum(vector) == get_masking_num(x)\n",
    "    return vector\n",
    "\n",
    "# masking_multihot = pd.DataFrame(All['study_design_info/masking'].apply(get_masking_multihot).tolist(), index=All.index, columns = ['MaskingType-Participant', 'MaskingType-Care Provider', 'MaskingType-Investigator', 'MaskingType-Outcomes Assessor'])\n",
    "# All = pd.merge(All, masking_multihot, right_index=True, left_index=True)\n",
    "# print(len(All.columns))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "49\n",
      "MaskingType-Participant\n",
      "0.0    248889\n",
      "1.0    117082\n",
      "Name: count, dtype: int64\n",
      "MaskingType-Care Provider\n",
      "0.0    311986\n",
      "1.0     53985\n",
      "Name: count, dtype: int64\n",
      "MaskingType-Investigator\n",
      "0.0    274340\n",
      "1.0     91631\n",
      "Name: count, dtype: int64\n",
      "MaskingType-Outcomes Assessor\n",
      "0.0    278522\n",
      "1.0     87449\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "masking_types = pd.DataFrame(All['study_design_info/masking'].apply(get_masking_multihot).tolist(), index=All.index, columns = ['MaskingType-Participant', 'MaskingType-Care Provider', 'MaskingType-Investigator', 'MaskingType-Outcomes Assessor'])\n",
    "masking_types[All['study_design_info/masking'].notna()] = masking_types[All['study_design_info/masking'].notna()].fillna(0).astype(int)\n",
    "All = pd.merge(All, masking_types, left_index=True, right_index=True)\n",
    "print(len(All.columns))\n",
    "for feature in All.columns:\n",
    "    if 'MaskingType-' in feature:\n",
    "        print(All[feature].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 卸磨杀驴\n",
    "All = All.drop('study_design_info/masking', axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 将arm_group/arm_group_type处理成\n",
    "\n",
    "Placebo Comparator Arm Number\t\n",
    "\n",
    "Experimental Arm Number\t\n",
    "\n",
    "No Intervention Arm Number\t\n",
    "\n",
    "Active Comparator Arm Number\t\n",
    "\n",
    "Other Arm Number\t\n",
    "\n",
    "Sham Comparator Arm Number\n",
    "\n",
    "6个数值特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NCT00000102                                                  NaN\n",
      "NCT00000104                                                  NaN\n",
      "NCT00000105                                                  NaN\n",
      "NCT00000106                                                  NaN\n",
      "NCT00000107                                                  NaN\n",
      "                                     ...                        \n",
      "NCT06264297                ['Active Comparator', 'Experimental']\n",
      "NCT06264310    ['Placebo Comparator', 'Experimental', 'Experi...\n",
      "NCT06264323                                                  NaN\n",
      "NCT06264336                ['Experimental', 'Active Comparator']\n",
      "NCT06264349    ['Experimental', 'Experimental', 'No Intervent...\n",
      "Name: arm_group/arm_group_type, Length: 483239, dtype: object\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'Placebo Comparator Arm Number': 1, 'Experimental Arm Number': 6}"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "value = All['arm_group/arm_group_type']['NCT00001259']\n",
    "\n",
    "def arm_group_type_2Mulitlabel(value):\n",
    "    if type(value) == list:\n",
    "        counts = dict(Counter(value))\n",
    "    elif type(value) == str and value[0] != '[':\n",
    "        counts = {value+' Arm Number':1}\n",
    "    elif type(value) == str and value[0] == '[':\n",
    "        value = eval(value)\n",
    "        counts = dict(Counter(value))\n",
    "        # for key, value in counts.items():\n",
    "        counts = {key+' Arm Number':value for key, value in counts.items()}\n",
    "    else: \n",
    "        counts = {}\n",
    "        \n",
    "    return counts\n",
    "\n",
    "print(All['arm_group/arm_group_type'])\n",
    "arm_group_type_2Mulitlabel(value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "54\n",
      "Experimental Arm Number\n",
      "1.0     210793\n",
      "0.0      64243\n",
      "2.0      42772\n",
      "3.0      15014\n",
      "4.0       7145\n",
      "5.0       2325\n",
      "6.0       2127\n",
      "7.0        738\n",
      "8.0        696\n",
      "9.0        375\n",
      "10.0       280\n",
      "12.0       176\n",
      "11.0       136\n",
      "16.0        72\n",
      "14.0        70\n",
      "15.0        69\n",
      "13.0        69\n",
      "17.0        29\n",
      "18.0        26\n",
      "32.0        19\n",
      "20.0        16\n",
      "24.0        11\n",
      "19.0         9\n",
      "22.0         8\n",
      "23.0         6\n",
      "21.0         4\n",
      "25.0         4\n",
      "26.0         3\n",
      "28.0         2\n",
      "30.0         2\n",
      "43.0         1\n",
      "44.0         1\n",
      "40.0         1\n",
      "38.0         1\n",
      "37.0         1\n",
      "27.0         1\n",
      "29.0         1\n",
      "34.0         1\n",
      "33.0         1\n",
      "Name: count, dtype: int64\n",
      "Active Comparator Arm Number\n",
      "0.0     224795\n",
      "1.0      91488\n",
      "2.0      23921\n",
      "3.0       4832\n",
      "4.0       1439\n",
      "5.0        285\n",
      "6.0        257\n",
      "7.0         70\n",
      "8.0         62\n",
      "9.0         30\n",
      "12.0        17\n",
      "10.0        15\n",
      "11.0         9\n",
      "16.0         8\n",
      "14.0         7\n",
      "15.0         6\n",
      "13.0         3\n",
      "22.0         2\n",
      "19.0         1\n",
      "26.0         1\n",
      "Name: count, dtype: int64\n",
      "Placebo Comparator Arm Number\n",
      "0.0     283919\n",
      "1.0      59977\n",
      "2.0       2486\n",
      "3.0        463\n",
      "4.0        200\n",
      "5.0         77\n",
      "6.0         48\n",
      "7.0         26\n",
      "8.0         24\n",
      "9.0         12\n",
      "10.0         7\n",
      "11.0         3\n",
      "14.0         3\n",
      "27.0         1\n",
      "20.0         1\n",
      "17.0         1\n",
      "Name: count, dtype: int64\n",
      "No Intervention Arm Number\n",
      "0.0     304443\n",
      "1.0      41493\n",
      "2.0       1105\n",
      "3.0        138\n",
      "4.0         42\n",
      "5.0         13\n",
      "6.0          9\n",
      "7.0          2\n",
      "8.0          1\n",
      "10.0         1\n",
      "12.0         1\n",
      "Name: count, dtype: int64\n",
      "Other Arm Number\n",
      "0.0     321528\n",
      "1.0      19111\n",
      "2.0       4894\n",
      "3.0        959\n",
      "4.0        460\n",
      "5.0        116\n",
      "6.0        105\n",
      "7.0         26\n",
      "8.0         22\n",
      "9.0          8\n",
      "10.0         7\n",
      "11.0         2\n",
      "16.0         2\n",
      "18.0         2\n",
      "14.0         1\n",
      "17.0         1\n",
      "15.0         1\n",
      "21.0         1\n",
      "24.0         1\n",
      "12.0         1\n",
      "Name: count, dtype: int64\n",
      "Sham Comparator Arm Number\n",
      "0.0    338200\n",
      "1.0      8702\n",
      "2.0       292\n",
      "3.0        37\n",
      "4.0        13\n",
      "6.0         4\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "arm_group_types = pd.DataFrame(All['arm_group/arm_group_type'].apply(arm_group_type_2Mulitlabel).tolist(), index=All.index)\n",
    "arm_group_types[All['arm_group/arm_group_type'].notna()] = arm_group_types[All['arm_group/arm_group_type'].notna()].fillna(0).astype(int)\n",
    "All = pd.merge(All, arm_group_types, left_index=True, right_index=True)\n",
    "print(len(All.columns))\n",
    "for feature in All.columns:\n",
    "    if 'Arm Number' in feature:\n",
    "        print(All[feature].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# All = pd.merge(All, pd.DataFrame(All['arm_group/arm_group_type'].apply(arm_group_type_2Mulitlabel).tolist(), index=All.index), left_index=True, right_index=True)\n",
    "# print(len(All.columns))\n",
    "# # 卸磨杀驴\n",
    "All = All.drop('arm_group/arm_group_type', axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 将intervention/intervention_type处理成多个整数特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "intervention/intervention_type\n",
       "Drug                                                                      61032\n",
       "['Drug', 'Drug']                                                          57942\n",
       "Other                                                                     42591\n",
       "Device                                                                    32324\n",
       "Behavioral                                                                23488\n",
       "                                                                          ...  \n",
       "['Procedure', 'Procedure', 'Procedure', 'Procedure', 'Drug', 'Device']        1\n",
       "['Drug', 'Drug', 'Drug', 'Drug', 'Drug', 'Behavioral']                        1\n",
       "['Procedure', 'Biological', 'Drug', 'Procedure']                              1\n",
       "['Device', 'Behavioral', 'Other', 'Device']                                   1\n",
       "['Device', 'Diagnostic Test', 'Device', 'Device']                             1\n",
       "Name: count, Length: 6889, dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "All['intervention/intervention_type'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "def intervention_type_2Mulitlabel(value):\n",
    "    if type(value) == list:\n",
    "        counts = dict(Counter(value))\n",
    "    elif type(value) == str and value[0] != '[':\n",
    "        counts = {value+' intervention Number':1}\n",
    "    elif type(value) == str and value[0] == '[':\n",
    "        value = eval(value)\n",
    "        counts = dict(Counter(value))\n",
    "        # for key, value in counts.items():\n",
    "        counts = {key+' intervention Number':value for key, value in counts.items()}\n",
    "    else: \n",
    "        counts = {}\n",
    "        \n",
    "    return counts\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "64\n",
      "Drug intervention Number\n",
      "0.0     253958\n",
      "1.0      80229\n",
      "2.0      65485\n",
      "3.0      19016\n",
      "4.0       8954\n",
      "5.0       3244\n",
      "6.0       1892\n",
      "7.0        854\n",
      "8.0        546\n",
      "9.0        277\n",
      "10.0       231\n",
      "11.0       121\n",
      "12.0       113\n",
      "13.0        62\n",
      "15.0        38\n",
      "14.0        38\n",
      "16.0        21\n",
      "18.0        18\n",
      "17.0        15\n",
      "20.0        11\n",
      "21.0         8\n",
      "19.0         7\n",
      "30.0         3\n",
      "29.0         2\n",
      "38.0         2\n",
      "27.0         2\n",
      "34.0         2\n",
      "37.0         1\n",
      "24.0         1\n",
      "26.0         1\n",
      "47.0         1\n",
      "23.0         1\n",
      "57.0         1\n",
      "40.0         1\n",
      "97.0         1\n",
      "60.0         1\n",
      "25.0         1\n",
      "35.0         1\n",
      "22.0         1\n",
      "Name: count, dtype: int64\n",
      "Procedure intervention Number\n",
      "0.0     387581\n",
      "1.0      29873\n",
      "2.0      14038\n",
      "3.0       2340\n",
      "4.0        790\n",
      "5.0        234\n",
      "6.0        151\n",
      "7.0         68\n",
      "8.0         32\n",
      "10.0        20\n",
      "9.0         18\n",
      "11.0         4\n",
      "15.0         3\n",
      "13.0         2\n",
      "14.0         2\n",
      "17.0         2\n",
      "20.0         1\n",
      "12.0         1\n",
      "16.0         1\n",
      "Name: count, dtype: int64\n",
      "Biological intervention Number\n",
      "0.0     409378\n",
      "1.0      16824\n",
      "2.0       5898\n",
      "3.0       1677\n",
      "4.0        725\n",
      "5.0        295\n",
      "6.0        152\n",
      "7.0         71\n",
      "8.0         55\n",
      "9.0         28\n",
      "10.0        21\n",
      "11.0        11\n",
      "12.0         9\n",
      "13.0         6\n",
      "15.0         4\n",
      "17.0         2\n",
      "14.0         1\n",
      "18.0         1\n",
      "25.0         1\n",
      "16.0         1\n",
      "24.0         1\n",
      "Name: count, dtype: int64\n",
      "Device intervention Number\n",
      "0.0     375355\n",
      "1.0      42180\n",
      "2.0      14866\n",
      "3.0       1922\n",
      "4.0        575\n",
      "5.0        146\n",
      "6.0         58\n",
      "7.0         24\n",
      "8.0         18\n",
      "9.0          9\n",
      "10.0         4\n",
      "11.0         1\n",
      "48.0         1\n",
      "16.0         1\n",
      "15.0         1\n",
      "Name: count, dtype: int64\n",
      "Behavioral intervention Number\n",
      "0.0     386700\n",
      "1.0      29498\n",
      "2.0      14622\n",
      "3.0       2914\n",
      "4.0        916\n",
      "5.0        255\n",
      "6.0        127\n",
      "8.0         41\n",
      "7.0         36\n",
      "9.0         19\n",
      "10.0         9\n",
      "11.0         5\n",
      "16.0         5\n",
      "12.0         4\n",
      "14.0         3\n",
      "13.0         3\n",
      "32.0         2\n",
      "15.0         1\n",
      "17.0         1\n",
      "Name: count, dtype: int64\n",
      "Other intervention Number\n",
      "0.0     341025\n",
      "1.0      65099\n",
      "2.0      21632\n",
      "3.0       4654\n",
      "4.0       1626\n",
      "5.0        503\n",
      "6.0        315\n",
      "7.0        110\n",
      "8.0         80\n",
      "9.0         35\n",
      "10.0        22\n",
      "12.0        17\n",
      "11.0        16\n",
      "16.0         7\n",
      "14.0         5\n",
      "13.0         4\n",
      "15.0         4\n",
      "23.0         2\n",
      "18.0         2\n",
      "24.0         1\n",
      "20.0         1\n",
      "19.0         1\n",
      "Name: count, dtype: int64\n",
      "Dietary Supplement intervention Number\n",
      "0.0     420817\n",
      "1.0       7045\n",
      "2.0       5573\n",
      "3.0       1096\n",
      "4.0        447\n",
      "5.0         76\n",
      "6.0         60\n",
      "7.0         15\n",
      "8.0         12\n",
      "9.0          7\n",
      "12.0         4\n",
      "10.0         3\n",
      "13.0         2\n",
      "17.0         2\n",
      "11.0         1\n",
      "18.0         1\n",
      "Name: count, dtype: int64\n",
      "Genetic intervention Number\n",
      "0.0    432720\n",
      "1.0      1858\n",
      "2.0       299\n",
      "3.0       145\n",
      "4.0        70\n",
      "5.0        41\n",
      "6.0        18\n",
      "7.0         9\n",
      "8.0         1\n",
      "Name: count, dtype: int64\n",
      "Radiation intervention Number\n",
      "0.0     426124\n",
      "1.0       7513\n",
      "2.0       1282\n",
      "3.0        168\n",
      "4.0         45\n",
      "5.0         12\n",
      "6.0          8\n",
      "7.0          4\n",
      "9.0          2\n",
      "8.0          2\n",
      "10.0         1\n",
      "Name: count, dtype: int64\n",
      "Diagnostic Test intervention Number\n",
      "0.0     421081\n",
      "1.0      11228\n",
      "2.0       1698\n",
      "3.0        580\n",
      "4.0        239\n",
      "5.0        137\n",
      "6.0         69\n",
      "7.0         34\n",
      "8.0         29\n",
      "9.0         22\n",
      "12.0        11\n",
      "11.0         7\n",
      "10.0         6\n",
      "14.0         5\n",
      "15.0         4\n",
      "13.0         4\n",
      "18.0         3\n",
      "19.0         2\n",
      "28.0         1\n",
      "16.0         1\n",
      "Name: count, dtype: int64\n",
      "Combination Product intervention Number\n",
      "0.0     432874\n",
      "1.0       1730\n",
      "2.0        413\n",
      "3.0         90\n",
      "4.0         33\n",
      "5.0          8\n",
      "6.0          7\n",
      "7.0          4\n",
      "10.0         1\n",
      "8.0          1\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "intervention_types = pd.DataFrame(All['intervention/intervention_type'].apply(intervention_type_2Mulitlabel).tolist(), index=All.index)\n",
    "intervention_types[All['intervention/intervention_type'].notna()] = intervention_types[All['intervention/intervention_type'].notna()].fillna(0).astype(int)\n",
    "All = pd.merge(All, intervention_types, left_index=True, right_index=True)\n",
    "print(len(All.columns))\n",
    "for feature in All.columns:\n",
    "    if 'intervention Number' in feature:\n",
    "        print(All[feature].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['phase', 'study_type', 'has_expanded_access',\n",
      "       'study_design_info/intervention_model',\n",
      "       'study_design_info/primary_purpose', 'eligibility/gender',\n",
      "       'eligibility/healthy_volunteers', 'oversight_info/has_dmc',\n",
      "       'study_design_info/allocation', 'patient_data/sharing_ipd',\n",
      "       'oversight_info/is_fda_regulated_drug',\n",
      "       'oversight_info/is_fda_regulated_device', 'eligibility/minimum_age',\n",
      "       'eligibility/maximum_age', 'number_of_arms', 'id_info/nct_id',\n",
      "       'brief_title', 'brief_summary/textblock', 'condition',\n",
      "       'intervention/intervention_name', 'eligibility/criteria/textblock',\n",
      "       'location/facility/address/city', 'condition_browse/mesh_term',\n",
      "       'intervention_browse/mesh_term', 'icdcode', 'keyword', 'enrollment',\n",
      "       'eligibility/sampling_method', 'sponsors/lead_sponsor/agency_class',\n",
      "       'completion_date{type}', 'start_date{type}', 'enrollment{type}',\n",
      "       'responsible_party/responsible_party_type',\n",
      "       'study_design_info/observational_model',\n",
      "       'study_design_info/time_perspective', 'biospec_retention',\n",
      "       'ipd_info_type-Statistical Analysis Plan (SAP)',\n",
      "       'ipd_info_type-Informed Consent Form (ICF)',\n",
      "       'ipd_info_type-Study Protocol',\n",
      "       'ipd_info_type-Clinical Study Report (CSR)',\n",
      "       'ipd_info_type-Analytic Code', 'study_design_info/masking_num',\n",
      "       'MaskingType-Participant', 'MaskingType-Care Provider',\n",
      "       'MaskingType-Investigator', 'MaskingType-Outcomes Assessor',\n",
      "       'Experimental Arm Number', 'Active Comparator Arm Number',\n",
      "       'Placebo Comparator Arm Number', 'No Intervention Arm Number',\n",
      "       'Other Arm Number', 'Sham Comparator Arm Number',\n",
      "       'Drug intervention Number', 'Procedure intervention Number',\n",
      "       'Biological intervention Number', 'Device intervention Number',\n",
      "       'Behavioral intervention Number', 'Other intervention Number',\n",
      "       'Dietary Supplement intervention Number', 'Genetic intervention Number',\n",
      "       'Radiation intervention Number', 'Diagnostic Test intervention Number',\n",
      "       'Combination Product intervention Number'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "# 卸磨杀驴\n",
    "All = All.drop('intervention/intervention_type', axis=1)\n",
    "print(All.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(483239, 63)\n"
     ]
    }
   ],
   "source": [
    "print(All.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "All.to_csv('All_data_prepared.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "duration 里enrollment两个全扔  四个全扔 enrollment type GDP+人口+老龄化程度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### city 转成GDP　population　aging　percent （没有使用这部分特征）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "\n",
    "def remove_non_numeric(s):\n",
    "    pattern = r'[^0-9.]'\n",
    "    return re.sub(pattern, '', s)\n",
    "\n",
    "def refine(x):\n",
    "    # print(x)\n",
    "    gdp, people, age = x.split(',')\n",
    "    gdp = remove_non_numeric(gdp)\n",
    "    people = remove_non_numeric(people)\n",
    "    age = remove_non_numeric(age)\n",
    "    if len(gdp) == 0:\n",
    "        gdp = '0'\n",
    "    if len(people) == 0:\n",
    "        people = '0'\n",
    "    if len(age) == 0:\n",
    "        age = '0'\n",
    "    return gdp, people, age\n",
    "\n",
    "def map2value(x):\n",
    "    x = re.sub(r\"\\s+\", \" \", x)\n",
    "    if len(x.split(' ')) == 2:\n",
    "        if len(x.split(' ')[-1].split(',')) == 3:\n",
    "            return refine(x.split(' ')[-1])\n",
    "        elif len(x.split(' ')[-1].split(',')) > 3:\n",
    "            return refine(','.join(x.split(' ')[-1].split(',')[-3:]))\n",
    "        elif len(x.split(' ')[-1].split(',')) < 3:\n",
    "            return map2value(''.join(x.split(' ')))\n",
    "    elif len(x.split(' ')) == 1:\n",
    "        if len(x.split(',')) == 3 :\n",
    "            return refine(x)\n",
    "        elif len(x.split(',')) > 3:\n",
    "            return refine(','.join(x.split(',')[-3:]))\n",
    "        else:\n",
    "            return refine(','.join(['0', x]))\n",
    "    elif len(x.split(' ')) == 3:\n",
    "        lis = x.split(' ')\n",
    "        lis = list(filter(lambda a: a != '', lis))\n",
    "        x = ' '.join(lis)\n",
    "        if len(x.split(',')) == 3 :\n",
    "            # print(x.split(' '),''.join(x.split(' ')[-3:]))\n",
    "            return map2value(''.join(x.split(' ')[-3:]))\n",
    "    elif len(x.split(' ')) == 4:\n",
    "        lis = x.split(' ')\n",
    "        lis = list(filter(lambda a: a != '', lis))\n",
    "        x = ' '.join(lis[1:])\n",
    "        if len(x.split(',')) == 3 :\n",
    "            # print(x.split(' '),''.join(x.split(' ')[-3:]))\n",
    "            return map2value(''.join(x.split(' ')))\n",
    "    elif len(x.split(' ')) > 4:\n",
    "        lis = x.split(' ')\n",
    "        lis = list(filter(lambda a: a != '', lis))\n",
    "        x = ' '.join(lis[1:])\n",
    "        if len(x.split(',')) == 3 :\n",
    "            # print(x.split(' '),''.join(x.split(' ')[-3:]))\n",
    "            return map2value(''.join(x.split(' ')))\n",
    "    else:\n",
    "        print(len(x.split(' ')), x)\n",
    "        \n",
    "\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "city_labels = pd.read_csv('city_labels_afternaafternaaaaaa.csv', index_col=0)\n",
    "GDP = []\n",
    "Population = []\n",
    "Aging = []\n",
    "def transfer2city(x):\n",
    "    if pd.isnull(x):\n",
    "        GDP.append(None)\n",
    "        Population.append(None)\n",
    "        Aging.append(None)\n",
    "\n",
    "    elif type(x) == str and x[0]!='[':\n",
    "        x = x.title()\n",
    "        result = city_labels.loc[x, 'label'].strip().replace('  ', ' ')\n",
    "        gdp, people, age = map2value(result)\n",
    "        GDP.append(eval(gdp))\n",
    "        Population.append(eval(people))\n",
    "        Aging.append(eval(age))\n",
    "        \n",
    "    elif type(x) == str and x[0]=='[' and x[-1] ==']':\n",
    "        try:\n",
    "            city_lis = eval(x)\n",
    "            gdps, peoples, ages = [], [], []\n",
    "            for x in city_lis:\n",
    "                x = x.title()\n",
    "                result = city_labels.loc[x, 'label'].strip().replace('  ', ' ')\n",
    "                gdp, people, age = map2value(result)\n",
    "                gdps.append(eval(gdp))\n",
    "                peoples.append(eval(people))\n",
    "                ages.append(eval(age))\n",
    "\n",
    "            GDP.append(sum(gdps)/len(gdps))\n",
    "            Population.append(sum(peoples)/len(peoples))\n",
    "            Aging.append(sum(ages)/len(ages))\n",
    "        except:\n",
    "            try:\n",
    "                result = city_labels.loc[x, 'label'].strip().replace('  ', ' ')\n",
    "                # print(result)\n",
    "                gdp, people, age = map2value(result)\n",
    "                # print(gdp, people, age)\n",
    "                GDP.append(eval(gdp))\n",
    "                Population.append(eval(people))\n",
    "                Aging.append(eval(age))\n",
    "            except:\n",
    "                GDP.append(None)\n",
    "                Population.append(None)\n",
    "                Aging.append(None)\n",
    "            \n",
    "    elif type(x) == list:\n",
    "        city_lis = x\n",
    "        gdps, peoples, ages = [], [], []\n",
    "        for x in city_lis:\n",
    "            x = x.title()\n",
    "            result = city_labels.loc[x, 'label'].strip().replace('  ', ' ')\n",
    "            gdp, people, age = map2value(result)\n",
    "            gdps.append(eval(gdp))\n",
    "            peoples.append(eval(people))\n",
    "            ages.append(eval(age))\n",
    "\n",
    "        GDP.append(sum(gdps)/len(gdps))\n",
    "        Population.append(sum(peoples)/len(peoples))\n",
    "        Aging.append(sum(ages)/len(ages))               \n",
    "    else:\n",
    "        try:\n",
    "            result = city_labels.loc[x, 'label']\n",
    "            gdp, people, age = map2value(result)\n",
    "            GDP.append(eval(gdp))\n",
    "            Population.append(eval(people))\n",
    "            Aging.append(eval(age))\n",
    "        except:\n",
    "            GDP.append(None)\n",
    "            Population.append(None)\n",
    "            Aging.append(None)\n",
    "\n",
    "for c in All['location/facility/address/city']:\n",
    "    transfer2city(c)\n",
    "\n",
    "All['location/facility/address/city-GDP'] = GDP\n",
    "All['location/facility/address/city-Population'] = Population\n",
    "All['location/facility/address/city-Aging'] = Aging\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "All.to_csv('All_data_prepared-GDP.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 以下两个是GPT处理前的操作 （跳过）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "city_dict = {}\n",
    "def singcity(x):\n",
    "    if type(x) == str and x[0]!='[':\n",
    "        x = x.title()\n",
    "        if x in city_dict.keys():\n",
    "            city_dict[x] += 1\n",
    "        else:\n",
    "            city_dict[x] = 1\n",
    "        return x\n",
    "    elif type(x) == str and x[0]=='[' and x[-1] ==']':\n",
    "        try:\n",
    "            city_lis = eval(x)\n",
    "        except:\n",
    "            return x\n",
    "        for x in city_lis:\n",
    "            x = x.title()\n",
    "            if x in city_dict.keys():\n",
    "                city_dict[x] += 1\n",
    "            else:\n",
    "                city_dict[x] = 1\n",
    "        return city_lis\n",
    "    elif type(x) == list:\n",
    "        city_lis = x\n",
    "        for x in city_lis:\n",
    "            x = x.title()\n",
    "            if x in city_dict.keys():\n",
    "                city_dict[x] += 1\n",
    "            else:\n",
    "                city_dict[x] = 1\n",
    "        return city_lis               \n",
    "    else:\n",
    "        return x\n",
    "temp = All['location/facility/address/city'].apply(singcity)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for k,v in city_dict.items():\n",
    "    print(k, v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.DataFrame(city_dict.values(), index=city_dict.keys()).to_csv('city.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 完成All_data上smiless和icdcode的处理\n",
    "\n",
    "按照HINT的方式提取icdcode和smiless (此处与上面不重合)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>phase</th>\n",
       "      <th>study_type</th>\n",
       "      <th>has_expanded_access</th>\n",
       "      <th>study_design_info/intervention_model</th>\n",
       "      <th>study_design_info/primary_purpose</th>\n",
       "      <th>eligibility/gender</th>\n",
       "      <th>eligibility/healthy_volunteers</th>\n",
       "      <th>oversight_info/has_dmc</th>\n",
       "      <th>study_design_info/allocation</th>\n",
       "      <th>patient_data/sharing_ipd</th>\n",
       "      <th>...</th>\n",
       "      <th>Behavioral intervention Number</th>\n",
       "      <th>Other intervention Number</th>\n",
       "      <th>Dietary Supplement intervention Number</th>\n",
       "      <th>Genetic intervention Number</th>\n",
       "      <th>Radiation intervention Number</th>\n",
       "      <th>Diagnostic Test intervention Number</th>\n",
       "      <th>Combination Product intervention Number</th>\n",
       "      <th>location/facility/address/city-GDP</th>\n",
       "      <th>location/facility/address/city-Population</th>\n",
       "      <th>location/facility/address/city-Aging</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NCT00000102</th>\n",
       "      <td>Phase 1/Phase 2</td>\n",
       "      <td>Interventional</td>\n",
       "      <td>No</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>All</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>270.00</td>\n",
       "      <td>9.000</td>\n",
       "      <td>16.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000104</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Observational</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Female</td>\n",
       "      <td>Accepts Healthy Volunteers</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>190.00</td>\n",
       "      <td>4.100</td>\n",
       "      <td>23.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000105</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Observational</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All</td>\n",
       "      <td>Accepts Healthy Volunteers</td>\n",
       "      <td>Yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>190.00</td>\n",
       "      <td>4.100</td>\n",
       "      <td>23.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000106</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "      <td>No</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>All</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>58.10</td>\n",
       "      <td>1.300</td>\n",
       "      <td>23.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000107</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Observational</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All</td>\n",
       "      <td>Accepts Healthy Volunteers</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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>76.30</td>\n",
       "      <td>0.200</td>\n",
       "      <td>20.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264297</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "      <td>No</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>All</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Undecided</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1922.40</td>\n",
       "      <td>24.900</td>\n",
       "      <td>18.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264310</th>\n",
       "      <td>Phase 2</td>\n",
       "      <td>Interventional</td>\n",
       "      <td>No</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>All</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.88</td>\n",
       "      <td>0.408</td>\n",
       "      <td>19.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264323</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Observational</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All</td>\n",
       "      <td>Accepts Healthy Volunteers</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "      <td>...</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>0.00</td>\n",
       "      <td>131.800</td>\n",
       "      <td>29.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264336</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "      <td>No</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>All</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Undecided</td>\n",
       "      <td>...</td>\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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>609.40</td>\n",
       "      <td>8.800</td>\n",
       "      <td>16.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264349</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "      <td>No</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>Prevention</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Non-Randomized</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\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>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>483239 rows × 66 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       phase      study_type has_expanded_access  \\\n",
       "NCT00000102  Phase 1/Phase 2  Interventional                  No   \n",
       "NCT00000104              NaN   Observational                  No   \n",
       "NCT00000105              NaN   Observational                  No   \n",
       "NCT00000106              NaN  Interventional                  No   \n",
       "NCT00000107              NaN   Observational                  No   \n",
       "...                      ...             ...                 ...   \n",
       "NCT06264297              NaN  Interventional                  No   \n",
       "NCT06264310          Phase 2  Interventional                  No   \n",
       "NCT06264323              NaN   Observational                  No   \n",
       "NCT06264336              NaN  Interventional                  No   \n",
       "NCT06264349              NaN  Interventional                  No   \n",
       "\n",
       "            study_design_info/intervention_model  \\\n",
       "NCT00000102                  Parallel Assignment   \n",
       "NCT00000104                                  NaN   \n",
       "NCT00000105                                  NaN   \n",
       "NCT00000106                  Parallel Assignment   \n",
       "NCT00000107                                  NaN   \n",
       "...                                          ...   \n",
       "NCT06264297                  Parallel Assignment   \n",
       "NCT06264310                  Parallel Assignment   \n",
       "NCT06264323                                  NaN   \n",
       "NCT06264336                  Parallel Assignment   \n",
       "NCT06264349                  Parallel Assignment   \n",
       "\n",
       "            study_design_info/primary_purpose eligibility/gender  \\\n",
       "NCT00000102                         Treatment                All   \n",
       "NCT00000104                               NaN             Female   \n",
       "NCT00000105                               NaN                All   \n",
       "NCT00000106                         Treatment                All   \n",
       "NCT00000107                               NaN                All   \n",
       "...                                       ...                ...   \n",
       "NCT06264297                         Treatment                All   \n",
       "NCT06264310                         Treatment                All   \n",
       "NCT06264323                               NaN                All   \n",
       "NCT06264336                         Treatment                All   \n",
       "NCT06264349                        Prevention             Female   \n",
       "\n",
       "            eligibility/healthy_volunteers oversight_info/has_dmc  \\\n",
       "NCT00000102                             No                    NaN   \n",
       "NCT00000104     Accepts Healthy Volunteers                    NaN   \n",
       "NCT00000105     Accepts Healthy Volunteers                    Yes   \n",
       "NCT00000106                             No                    NaN   \n",
       "NCT00000107     Accepts Healthy Volunteers                    NaN   \n",
       "...                                    ...                    ...   \n",
       "NCT06264297                             No                     No   \n",
       "NCT06264310                             No                    Yes   \n",
       "NCT06264323     Accepts Healthy Volunteers                     No   \n",
       "NCT06264336                             No                     No   \n",
       "NCT06264349                             No                     No   \n",
       "\n",
       "            study_design_info/allocation patient_data/sharing_ipd  ...  \\\n",
       "NCT00000102                          NaN                      NaN  ...   \n",
       "NCT00000104                          NaN                      NaN  ...   \n",
       "NCT00000105                          NaN                      NaN  ...   \n",
       "NCT00000106                   Randomized                      NaN  ...   \n",
       "NCT00000107                          NaN                      NaN  ...   \n",
       "...                                  ...                      ...  ...   \n",
       "NCT06264297                   Randomized                Undecided  ...   \n",
       "NCT06264310                   Randomized                       No  ...   \n",
       "NCT06264323                          NaN                       No  ...   \n",
       "NCT06264336                   Randomized                Undecided  ...   \n",
       "NCT06264349               Non-Randomized                       No  ...   \n",
       "\n",
       "            Behavioral intervention Number Other intervention Number  \\\n",
       "NCT00000102                            0.0                       0.0   \n",
       "NCT00000104                            0.0                       0.0   \n",
       "NCT00000105                            0.0                       0.0   \n",
       "NCT00000106                            0.0                       0.0   \n",
       "NCT00000107                            NaN                       NaN   \n",
       "...                                    ...                       ...   \n",
       "NCT06264297                            0.0                       0.0   \n",
       "NCT06264310                            0.0                       0.0   \n",
       "NCT06264323                            NaN                       NaN   \n",
       "NCT06264336                            1.0                       0.0   \n",
       "NCT06264349                            0.0                       1.0   \n",
       "\n",
       "            Dietary Supplement intervention Number  \\\n",
       "NCT00000102                                    0.0   \n",
       "NCT00000104                                    0.0   \n",
       "NCT00000105                                    0.0   \n",
       "NCT00000106                                    0.0   \n",
       "NCT00000107                                    NaN   \n",
       "...                                            ...   \n",
       "NCT06264297                                    0.0   \n",
       "NCT06264310                                    0.0   \n",
       "NCT06264323                                    NaN   \n",
       "NCT06264336                                    0.0   \n",
       "NCT06264349                                    0.0   \n",
       "\n",
       "            Genetic intervention Number  Radiation intervention Number  \\\n",
       "NCT00000102                         0.0                            0.0   \n",
       "NCT00000104                         0.0                            0.0   \n",
       "NCT00000105                         0.0                            0.0   \n",
       "NCT00000106                         0.0                            0.0   \n",
       "NCT00000107                         NaN                            NaN   \n",
       "...                                 ...                            ...   \n",
       "NCT06264297                         0.0                            0.0   \n",
       "NCT06264310                         0.0                            0.0   \n",
       "NCT06264323                         NaN                            NaN   \n",
       "NCT06264336                         0.0                            0.0   \n",
       "NCT06264349                         0.0                            0.0   \n",
       "\n",
       "            Diagnostic Test intervention Number  \\\n",
       "NCT00000102                                 0.0   \n",
       "NCT00000104                                 0.0   \n",
       "NCT00000105                                 0.0   \n",
       "NCT00000106                                 0.0   \n",
       "NCT00000107                                 NaN   \n",
       "...                                         ...   \n",
       "NCT06264297                                 0.0   \n",
       "NCT06264310                                 0.0   \n",
       "NCT06264323                                 NaN   \n",
       "NCT06264336                                 0.0   \n",
       "NCT06264349                                 0.0   \n",
       "\n",
       "            Combination Product intervention Number  \\\n",
       "NCT00000102                                     0.0   \n",
       "NCT00000104                                     0.0   \n",
       "NCT00000105                                     0.0   \n",
       "NCT00000106                                     0.0   \n",
       "NCT00000107                                     NaN   \n",
       "...                                             ...   \n",
       "NCT06264297                                     0.0   \n",
       "NCT06264310                                     0.0   \n",
       "NCT06264323                                     NaN   \n",
       "NCT06264336                                     0.0   \n",
       "NCT06264349                                     0.0   \n",
       "\n",
       "            location/facility/address/city-GDP  \\\n",
       "NCT00000102                             270.00   \n",
       "NCT00000104                             190.00   \n",
       "NCT00000105                             190.00   \n",
       "NCT00000106                              58.10   \n",
       "NCT00000107                              76.30   \n",
       "...                                        ...   \n",
       "NCT06264297                            1922.40   \n",
       "NCT06264310                              15.88   \n",
       "NCT06264323                               0.00   \n",
       "NCT06264336                             609.40   \n",
       "NCT06264349                                NaN   \n",
       "\n",
       "            location/facility/address/city-Population  \\\n",
       "NCT00000102                                     9.000   \n",
       "NCT00000104                                     4.100   \n",
       "NCT00000105                                     4.100   \n",
       "NCT00000106                                     1.300   \n",
       "NCT00000107                                     0.200   \n",
       "...                                               ...   \n",
       "NCT06264297                                    24.900   \n",
       "NCT06264310                                     0.408   \n",
       "NCT06264323                                   131.800   \n",
       "NCT06264336                                     8.800   \n",
       "NCT06264349                                       NaN   \n",
       "\n",
       "            location/facility/address/city-Aging  \n",
       "NCT00000102                                16.20  \n",
       "NCT00000104                                23.70  \n",
       "NCT00000105                                23.70  \n",
       "NCT00000106                                23.00  \n",
       "NCT00000107                                20.10  \n",
       "...                                          ...  \n",
       "NCT06264297                                18.70  \n",
       "NCT06264310                                19.12  \n",
       "NCT06264323                                29.60  \n",
       "NCT06264336                                16.40  \n",
       "NCT06264349                                  NaN  \n",
       "\n",
       "[483239 rows x 66 columns]"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "All = pd.read_csv('All_data_prepared-GDP.csv', index_col=0)\n",
    "All"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['phase', 'study_type', 'has_expanded_access',\n",
       "       'study_design_info/intervention_model',\n",
       "       'study_design_info/primary_purpose', 'eligibility/gender',\n",
       "       'eligibility/healthy_volunteers', 'oversight_info/has_dmc',\n",
       "       'study_design_info/allocation', 'patient_data/sharing_ipd',\n",
       "       'oversight_info/is_fda_regulated_drug',\n",
       "       'oversight_info/is_fda_regulated_device', 'eligibility/minimum_age',\n",
       "       'eligibility/maximum_age', 'number_of_arms', 'id_info/nct_id',\n",
       "       'brief_title', 'brief_summary/textblock', 'condition',\n",
       "       'intervention/intervention_name', 'eligibility/criteria/textblock',\n",
       "       'location/facility/address/city', 'condition_browse/mesh_term',\n",
       "       'intervention_browse/mesh_term', 'icdcode', 'keyword', 'enrollment',\n",
       "       'eligibility/sampling_method', 'sponsors/lead_sponsor/agency_class',\n",
       "       'completion_date{type}', 'start_date{type}', 'enrollment{type}',\n",
       "       'responsible_party/responsible_party_type',\n",
       "       'study_design_info/observational_model',\n",
       "       'study_design_info/time_perspective', 'biospec_retention',\n",
       "       'ipd_info_type-Statistical Analysis Plan (SAP)',\n",
       "       'ipd_info_type-Informed Consent Form (ICF)',\n",
       "       'ipd_info_type-Study Protocol',\n",
       "       'ipd_info_type-Clinical Study Report (CSR)',\n",
       "       'ipd_info_type-Analytic Code', 'study_design_info/masking_num',\n",
       "       'MaskingType-Participant', 'MaskingType-Care Provider',\n",
       "       'MaskingType-Investigator', 'MaskingType-Outcomes Assessor',\n",
       "       'Experimental Arm Number', 'Active Comparator Arm Number',\n",
       "       'Placebo Comparator Arm Number', 'No Intervention Arm Number',\n",
       "       'Other Arm Number', 'Sham Comparator Arm Number',\n",
       "       'Drug intervention Number', 'Procedure intervention Number',\n",
       "       'Biological intervention Number', 'Device intervention Number',\n",
       "       'Behavioral intervention Number', 'Other intervention Number',\n",
       "       'Dietary Supplement intervention Number', 'Genetic intervention Number',\n",
       "       'Radiation intervention Number', 'Diagnostic Test intervention Number',\n",
       "       'Combination Product intervention Number',\n",
       "       'location/facility/address/city-GDP',\n",
       "       'location/facility/address/city-Population',\n",
       "       'location/facility/address/city-Aging'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "All.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv\n",
    "def load_disease2icd():\n",
    "\tdisease2icd = dict()\n",
    "\twith open('data/diseases.csv', 'r') as csvfile:\n",
    "\t\trows = list(csv.reader(csvfile, delimiter = ','))[1:]\n",
    "\tfor row in rows:\n",
    "\t\tdisease = row[0]\n",
    "\t\ticd = row[1]\n",
    "\t\tdisease2icd[disease] = icd \n",
    "\treturn disease2icd \n",
    "\n",
    "disease2icd = load_disease2icd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_drug2smiles_pkl():\n",
    "\tpkl_file = \"data/drug2smiles.pkl\"\n",
    "\tdrug2smiles = pickle.load(open(pkl_file, 'rb'))\n",
    "\treturn drug2smiles \n",
    "    \n",
    "def drug_hit_smiles(drug, drug2smiles):\n",
    "\t\"\"\"\n",
    "\t\theuristics\n",
    "\t\"\"\"\n",
    "\tif drug in drug2smiles:\n",
    "\t\t# print(\"drug hit: \", drug, \"?\")\n",
    "\t\treturn drug2smiles[drug]\n",
    "\tfor word in drug.split():\n",
    "\t\tif len(word)>=7 and word in drug2smiles:\n",
    "\t\t\t# print(\"drug hit: \", drug, '&', word)\n",
    "\t\t\treturn drug2smiles[word]\n",
    "\t# max_length = 0\n",
    "\t# for drug0 in drug2smiles:\n",
    "\t# \tlength = dynamic_programming(drug, drug0)\n",
    "\t# \tif length > max_length:\n",
    "\t# \t\tbest_drug = drug0 \n",
    "\t# \t\tmax_length = length \n",
    "\t# if max_length > 9: \n",
    "\t# \tprint(\"DP drug hit: \", drug, '&', best_drug)\n",
    "\t# \treturn drug2smiles[best_drug]\n",
    "\treturn None \n",
    "drug2smiles = load_drug2smiles_pkl()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:1: SyntaxWarning: 'list' object is not callable; perhaps you missed a comma?\n"
     ]
    }
   ],
   "source": [
    "icdcode_all = []\n",
    "smiless_all = []\n",
    "icd_hit = 0\n",
    "smiles_hit = 0\n",
    "while True:\n",
    "    conditions = All['condition']\n",
    "    if isinstance(conditions, float):\n",
    "        icdcode_all.append(None)\n",
    "    else:\n",
    "        for diseases in conditions:\n",
    "            icdcode_lst = []\n",
    "            if isinstance(diseases, float):\n",
    "                icdcode_all.append(None)\n",
    "                continue\n",
    "            elif isinstance(diseases, str) and diseases[0] != '[':\n",
    "                icdcode = disease2icd[diseases.lower()] if diseases.lower() in disease2icd else None\n",
    "                if icdcode is not None:\n",
    "                    icdcode_lst.append(icdcode)\n",
    "            elif isinstance(diseases, str) and diseases[0] == '[':\n",
    "                try:\n",
    "                    diseases = eval(diseases)\n",
    "                    for disease in diseases:\n",
    "                        icdcode = disease2icd[disease.lower()] if disease.lower() in disease2icd else None\n",
    "                        if icdcode is not None:\n",
    "                            icdcode_lst.append(icdcode)\n",
    "                except:\n",
    "                    diseases = diseases.lower()\n",
    "                    icdcode = disease2icd[diseases] if diseases in disease2icd else None\n",
    "                    if icdcode is not None:\n",
    "                        icdcode_lst.append(icdcode)\n",
    "            elif isinstance(diseases, list):\n",
    "                for disease in diseases:\n",
    "                    icdcode = disease2icd[disease.lower()] if disease.lower() in disease2icd else None\n",
    "                    if icdcode is not None:\n",
    "                        icdcode_lst.append(icdcode)\n",
    "\n",
    "            if len(icdcode_lst) > 0:\n",
    "                # print('icdcode hit: ', diseases, icdcode_lst)\n",
    "                icd_hit += 1\n",
    "                icdcode_all.append(icdcode_lst)\n",
    "            else:\n",
    "                icdcode_all.append(None)\n",
    "            \n",
    "    intervention_name = All['intervention/intervention_name']\n",
    "    if isinstance(intervention_name, float):\n",
    "        smiless_all.append(None)\n",
    "    else:\n",
    "        for drugs in intervention_name:\n",
    "            smiles_lst = []\n",
    "            if isinstance(drugs, float):\n",
    "                smiless_all.append(None)\n",
    "                continue\n",
    "            elif isinstance(drugs, str) and drugs[0] != '[':\n",
    "                smiles = drug_hit_smiles(drugs.lower(), drug2smiles)\n",
    "                if smiles is not None:\n",
    "                    smiles_lst.append(smiles)\n",
    "            elif isinstance(drugs, str) and drugs[0] == '[':\n",
    "                try:\n",
    "                    drugs = eval(drugs)\n",
    "                    for drug in drugs:\n",
    "                        smiles = drug_hit_smiles(drug.lower(), drug2smiles)\n",
    "                        if smiles is not None:\n",
    "                            smiles_lst.append(smiles)\n",
    "                except:\n",
    "                    smiles = drug_hit_smiles(drugs.lower(), drug2smiles)\n",
    "                    if smiles is not None:\n",
    "                        smiles_lst.append(smiles)\n",
    "            elif isinstance(drugs, list):\n",
    "                for drug in drugs:\n",
    "                    smiles = drug_hit_smiles(drug.lower(), drug2smiles)\n",
    "                    if smiles is not None:\n",
    "                        smiles_lst.append(smiles)\n",
    "\n",
    "            if len(smiles_lst) > 0:\n",
    "                # print('drug hit', drugs, smiles_lst)\n",
    "                smiles_hit += 1\n",
    "                smiless_all.append(smiles_lst)\n",
    "            else: \n",
    "                smiless_all.append(None)\n",
    "    break\n",
    "\n",
    "All['icdcode'] = icdcode_all\n",
    "All['smiless'] = smiless_all"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "检查重新提取出来的和按照HINT的筛选方式提取出来的差别，HINT根据intervention_type筛掉了一部分trial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [],
   "source": [
    "raw = pd.read_csv('raw_data.csv', index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['NCT00000116', 'NCT00000145', 'NCT00000263', 'NCT00000264',\n",
       "       'NCT00000281', 'NCT00000292', 'NCT00000322', 'NCT00000325',\n",
       "       'NCT00000495', 'NCT00000498',\n",
       "       ...\n",
       "       'NCT06258668', 'NCT06259149', 'NCT06259175', 'NCT06259669',\n",
       "       'NCT06259760', 'NCT06259916', 'NCT06261905', 'NCT06262685',\n",
       "       'NCT06262711', 'NCT06263270'],\n",
       "      dtype='object', length=14113)"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 筛选 raw 中非空和非 '[]' 的数据\n",
    "filtered_raw = raw[(raw['smiless'].notna()) & (raw['smiless'] != '[]') & (raw['smiless'] != '')].index\n",
    "\n",
    "# 筛选 All 中非空的数据\n",
    "filtered_All = All[All['smiless'].notna()].index\n",
    "\n",
    "# 找到不在 All['smiless'] 中的 filtered_raw 的索引\n",
    "difference_indices = filtered_All.difference(filtered_raw)\n",
    "\n",
    "difference_indices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NCT00000116    ['Vitamin A', 'Docosahexaenoic acid', 'Control...\n",
       "NCT00000145    ['Antioxidants', 'Zinc', 'Antioxidants and zinc']\n",
       "NCT00000263    ['30% Nitrous oxide', '0.25 g/Kg ethanol', '0....\n",
       "NCT00000264    ['30% Nitrous oxide', '0.35 g/Kg ethanol', '0....\n",
       "NCT00000281                                           Amantadine\n",
       "                                     ...                        \n",
       "NCT06259916                              ['Alcohol', 'Cannabis']\n",
       "NCT06261905    ['[11C]-PHNO', 'Calcitriol', 'Placebo Control'...\n",
       "NCT06262685    ['Preemptive pharmacogenetic atorvastatin dose...\n",
       "NCT06262711                             ['Vitamin C', 'Placebo']\n",
       "NCT06263270    ['CYT-108, a recombinant protease inhibitor', ...\n",
       "Name: intervention/intervention_name, Length: 14113, dtype: object"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "All['intervention/intervention_name'].loc[difference_indices]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "117805 343642\n"
     ]
    }
   ],
   "source": [
    "print(smiles_hit, icd_hit)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [],
   "source": [
    "All.to_csv('All_data_prepared-GDP-smile-icd.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "All = pd.read_csv('All_data_prepared-GDP-smile-icd.csv', index_col=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 删除和 target 对应的条数里面太少(全为nan)的和所有值都一样的部分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10 (31306, 76)\n",
      "eligibility/study_pop/textblock In the columns!\n",
      "study_design_info/allocation In the columns!\n",
      "study_design_info/intervention_model In the columns!\n",
      "study_design_info/intervention_model_description In the columns!\n",
      "study_design_info/primary_purpose In the columns!\n",
      "study_design_info/time_perspective In the columns!\n",
      "study_design_info/observational_model In the columns!\n",
      "study_design_info/masking In the columns!\n",
      "(31306, 78)\n",
      "start_date{type} is unique!\n",
      "eligibility/gender_based is unique!\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Active Comparator Arm Number</th>\n",
       "      <th>Behavioral intervention Number</th>\n",
       "      <th>Biological intervention Number</th>\n",
       "      <th>Combination Product intervention Number</th>\n",
       "      <th>Device intervention Number</th>\n",
       "      <th>Diagnostic Test intervention Number</th>\n",
       "      <th>Dietary Supplement intervention Number</th>\n",
       "      <th>Drug intervention Number</th>\n",
       "      <th>Experimental Arm Number</th>\n",
       "      <th>Genetic intervention Number</th>\n",
       "      <th>...</th>\n",
       "      <th>study_design_info/allocation</th>\n",
       "      <th>study_design_info/intervention_model</th>\n",
       "      <th>study_design_info/intervention_model_description</th>\n",
       "      <th>study_design_info/masking</th>\n",
       "      <th>study_design_info/masking_description</th>\n",
       "      <th>study_design_info/masking_num</th>\n",
       "      <th>study_design_info/observational_model</th>\n",
       "      <th>study_design_info/primary_purpose</th>\n",
       "      <th>study_design_info/time_perspective</th>\n",
       "      <th>study_type</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ntcid</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>NCT00001259</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Non-Randomized</td>\n",
       "      <td>Crossover Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Triple (Participant, Investigator, Outcomes As...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00001277</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Non-Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Diagnostic</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00001305</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single Group Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00001322</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Non-Randomized</td>\n",
       "      <td>Crossover Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Basic Science</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00001849</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single Group Assignment</td>\n",
       "      <td>Comparison of results in patients receiving si...</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Diagnostic</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06002347</th>\n",
       "      <td>0.0</td>\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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single Group Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Prevention</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06033079</th>\n",
       "      <td>0.0</td>\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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>We will conduct a randomized controlled trial ...</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Health Services Research</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06076681</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Double (Participant, Investigator)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06076694</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06097676</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Crossover Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Quadruple (Participant, Care Provider, Investi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>31306 rows × 72 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Active Comparator Arm Number  Behavioral intervention Number  \\\n",
       "ntcid                                                                       \n",
       "NCT00001259                           0.0                             0.0   \n",
       "NCT00001277                           0.0                             0.0   \n",
       "NCT00001305                           0.0                             0.0   \n",
       "NCT00001322                           0.0                             0.0   \n",
       "NCT00001849                           0.0                             0.0   \n",
       "...                                   ...                             ...   \n",
       "NCT06002347                           0.0                             1.0   \n",
       "NCT06033079                           0.0                             1.0   \n",
       "NCT06076681                           0.0                             0.0   \n",
       "NCT06076694                           1.0                             0.0   \n",
       "NCT06097676                           1.0                             0.0   \n",
       "\n",
       "             Biological intervention Number  \\\n",
       "ntcid                                         \n",
       "NCT00001259                             0.0   \n",
       "NCT00001277                             0.0   \n",
       "NCT00001305                             0.0   \n",
       "NCT00001322                             0.0   \n",
       "NCT00001849                             0.0   \n",
       "...                                     ...   \n",
       "NCT06002347                             0.0   \n",
       "NCT06033079                             0.0   \n",
       "NCT06076681                             0.0   \n",
       "NCT06076694                             0.0   \n",
       "NCT06097676                             0.0   \n",
       "\n",
       "             Combination Product intervention Number  \\\n",
       "ntcid                                                  \n",
       "NCT00001259                                      0.0   \n",
       "NCT00001277                                      0.0   \n",
       "NCT00001305                                      0.0   \n",
       "NCT00001322                                      0.0   \n",
       "NCT00001849                                      0.0   \n",
       "...                                              ...   \n",
       "NCT06002347                                      0.0   \n",
       "NCT06033079                                      0.0   \n",
       "NCT06076681                                      0.0   \n",
       "NCT06076694                                      0.0   \n",
       "NCT06097676                                      0.0   \n",
       "\n",
       "             Device intervention Number  Diagnostic Test intervention Number  \\\n",
       "ntcid                                                                          \n",
       "NCT00001259                         0.0                                  0.0   \n",
       "NCT00001277                         0.0                                  0.0   \n",
       "NCT00001305                         0.0                                  0.0   \n",
       "NCT00001322                         0.0                                  0.0   \n",
       "NCT00001849                         2.0                                  0.0   \n",
       "...                                 ...                                  ...   \n",
       "NCT06002347                         0.0                                  0.0   \n",
       "NCT06033079                         0.0                                  0.0   \n",
       "NCT06076681                         0.0                                  0.0   \n",
       "NCT06076694                         0.0                                  0.0   \n",
       "NCT06097676                         0.0                                  0.0   \n",
       "\n",
       "             Dietary Supplement intervention Number  Drug intervention Number  \\\n",
       "ntcid                                                                           \n",
       "NCT00001259                                     0.0                       6.0   \n",
       "NCT00001277                                     0.0                       2.0   \n",
       "NCT00001305                                     0.0                       1.0   \n",
       "NCT00001322                                     0.0                       5.0   \n",
       "NCT00001849                                     0.0                       3.0   \n",
       "...                                             ...                       ...   \n",
       "NCT06002347                                     0.0                       0.0   \n",
       "NCT06033079                                     0.0                       0.0   \n",
       "NCT06076681                                     0.0                       3.0   \n",
       "NCT06076694                                     0.0                       3.0   \n",
       "NCT06097676                                     0.0                       5.0   \n",
       "\n",
       "             Experimental Arm Number  Genetic intervention Number  ...  \\\n",
       "ntcid                                                              ...   \n",
       "NCT00001259                      6.0                          0.0  ...   \n",
       "NCT00001277                      1.0                          0.0  ...   \n",
       "NCT00001305                      1.0                          0.0  ...   \n",
       "NCT00001322                      3.0                          0.0  ...   \n",
       "NCT00001849                      1.0                          0.0  ...   \n",
       "...                              ...                          ...  ...   \n",
       "NCT06002347                      1.0                          0.0  ...   \n",
       "NCT06033079                      1.0                          0.0  ...   \n",
       "NCT06076681                      4.0                          0.0  ...   \n",
       "NCT06076694                      4.0                          0.0  ...   \n",
       "NCT06097676                      3.0                          0.0  ...   \n",
       "\n",
       "             study_design_info/allocation  \\\n",
       "ntcid                                       \n",
       "NCT00001259                Non-Randomized   \n",
       "NCT00001277                Non-Randomized   \n",
       "NCT00001305                           NaN   \n",
       "NCT00001322                Non-Randomized   \n",
       "NCT00001849                           NaN   \n",
       "...                                   ...   \n",
       "NCT06002347                           NaN   \n",
       "NCT06033079                    Randomized   \n",
       "NCT06076681                    Randomized   \n",
       "NCT06076694                    Randomized   \n",
       "NCT06097676                    Randomized   \n",
       "\n",
       "             study_design_info/intervention_model  \\\n",
       "ntcid                                               \n",
       "NCT00001259                  Crossover Assignment   \n",
       "NCT00001277                   Parallel Assignment   \n",
       "NCT00001305               Single Group Assignment   \n",
       "NCT00001322                  Crossover Assignment   \n",
       "NCT00001849               Single Group Assignment   \n",
       "...                                           ...   \n",
       "NCT06002347               Single Group Assignment   \n",
       "NCT06033079                   Parallel Assignment   \n",
       "NCT06076681                   Parallel Assignment   \n",
       "NCT06076694                   Parallel Assignment   \n",
       "NCT06097676                  Crossover Assignment   \n",
       "\n",
       "              study_design_info/intervention_model_description  \\\n",
       "ntcid                                                            \n",
       "NCT00001259                                                NaN   \n",
       "NCT00001277                                                NaN   \n",
       "NCT00001305                                                NaN   \n",
       "NCT00001322                                                NaN   \n",
       "NCT00001849  Comparison of results in patients receiving si...   \n",
       "...                                                        ...   \n",
       "NCT06002347                                                NaN   \n",
       "NCT06033079  We will conduct a randomized controlled trial ...   \n",
       "NCT06076681                                                NaN   \n",
       "NCT06076694                                                NaN   \n",
       "NCT06097676                                                NaN   \n",
       "\n",
       "                                     study_design_info/masking  \\\n",
       "ntcid                                                            \n",
       "NCT00001259  Triple (Participant, Investigator, Outcomes As...   \n",
       "NCT00001277                                  None (Open Label)   \n",
       "NCT00001305                                  None (Open Label)   \n",
       "NCT00001322                                                NaN   \n",
       "NCT00001849                                  None (Open Label)   \n",
       "...                                                        ...   \n",
       "NCT06002347                                  None (Open Label)   \n",
       "NCT06033079                                  None (Open Label)   \n",
       "NCT06076681                 Double (Participant, Investigator)   \n",
       "NCT06076694                                  None (Open Label)   \n",
       "NCT06097676  Quadruple (Participant, Care Provider, Investi...   \n",
       "\n",
       "             study_design_info/masking_description  \\\n",
       "ntcid                                                \n",
       "NCT00001259                                    NaN   \n",
       "NCT00001277                                    NaN   \n",
       "NCT00001305                                    NaN   \n",
       "NCT00001322                                    NaN   \n",
       "NCT00001849                                    NaN   \n",
       "...                                            ...   \n",
       "NCT06002347                                    NaN   \n",
       "NCT06033079                                    NaN   \n",
       "NCT06076681                                    NaN   \n",
       "NCT06076694                                    NaN   \n",
       "NCT06097676                                    NaN   \n",
       "\n",
       "             study_design_info/masking_num  \\\n",
       "ntcid                                        \n",
       "NCT00001259                            3.0   \n",
       "NCT00001277                            0.0   \n",
       "NCT00001305                            0.0   \n",
       "NCT00001322                            NaN   \n",
       "NCT00001849                            0.0   \n",
       "...                                    ...   \n",
       "NCT06002347                            0.0   \n",
       "NCT06033079                            0.0   \n",
       "NCT06076681                            2.0   \n",
       "NCT06076694                            0.0   \n",
       "NCT06097676                            4.0   \n",
       "\n",
       "             study_design_info/observational_model  \\\n",
       "ntcid                                                \n",
       "NCT00001259                                    NaN   \n",
       "NCT00001277                                    NaN   \n",
       "NCT00001305                                    NaN   \n",
       "NCT00001322                                    NaN   \n",
       "NCT00001849                                    NaN   \n",
       "...                                            ...   \n",
       "NCT06002347                                    NaN   \n",
       "NCT06033079                                    NaN   \n",
       "NCT06076681                                    NaN   \n",
       "NCT06076694                                    NaN   \n",
       "NCT06097676                                    NaN   \n",
       "\n",
       "             study_design_info/primary_purpose  \\\n",
       "ntcid                                            \n",
       "NCT00001259                          Treatment   \n",
       "NCT00001277                         Diagnostic   \n",
       "NCT00001305                          Treatment   \n",
       "NCT00001322                      Basic Science   \n",
       "NCT00001849                         Diagnostic   \n",
       "...                                        ...   \n",
       "NCT06002347                         Prevention   \n",
       "NCT06033079           Health Services Research   \n",
       "NCT06076681                          Treatment   \n",
       "NCT06076694                          Treatment   \n",
       "NCT06097676                              Other   \n",
       "\n",
       "             study_design_info/time_perspective      study_type  \n",
       "ntcid                                                            \n",
       "NCT00001259                                 NaN  Interventional  \n",
       "NCT00001277                                 NaN  Interventional  \n",
       "NCT00001305                                 NaN  Interventional  \n",
       "NCT00001322                                 NaN  Interventional  \n",
       "NCT00001849                                 NaN  Interventional  \n",
       "...                                         ...             ...  \n",
       "NCT06002347                                 NaN  Interventional  \n",
       "NCT06033079                                 NaN  Interventional  \n",
       "NCT06076681                                 NaN  Interventional  \n",
       "NCT06076694                                 NaN  Interventional  \n",
       "NCT06097676                                 NaN  Interventional  \n",
       "\n",
       "[31306 rows x 72 columns]"
      ]
     },
     "execution_count": 189,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "task_name = 'adverse-event-rate-prediction'\n",
    "target = pd.read_csv(f'{task_name}/output.csv', index_col=0)\n",
    "part = All.loc[target.index]\n",
    "add_feature = ['eligibility/study_pop/textblock', 'intervention/description', 'study_design_info/allocation', 'study_design_info/intervention_model', \n",
    "'study_design_info/intervention_model_description', 'study_design_info/primary_purpose', 'study_design_info/time_perspective', 'study_design_info/observational_model', \n",
    "'study_design_info/masking', 'study_design_info/masking_description'] # 仔细筛选后加的\n",
    "print(len(add_feature), part.shape)\n",
    "for c in add_feature:\n",
    "    if c in part.columns:\n",
    "        print(c, 'In the columns!')\n",
    "    else:\n",
    "        part[c] = All_Ori[c].loc[target.index]\n",
    "print(part.shape)\n",
    "drop_feature = ['enrollment{type}', 'id_info/nct_id', 'biospec_retention','completion_date{type}']\n",
    "for c in part.columns:\n",
    "    if c =='icdcode' or c == 'smiless' :\n",
    "        continue\n",
    "    if part[c].isnull().sum() == len(part):\n",
    "        print(f'{c} is all null!')\n",
    "        drop_feature.append(c)\n",
    "    if part[c].nunique(dropna=True) == 1:  # 除去缺失值后的所有值一样 即方差为0\n",
    "        print(f'{c} is unique!')\n",
    "        drop_feature.append(c)\n",
    "\n",
    "part = part.drop(drop_feature, axis=1)\n",
    "sorted_columns = sorted(part.columns)\n",
    "part = part.reindex(columns=sorted_columns)\n",
    "part"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 划分训练测试 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import StratifiedShuffleSplit, train_test_split\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(25044, 72) (25044, 2) (6262, 72) (6262, 2)\n",
      "(25044, 72) (25044, 2) (6262, 72) (6262, 2)\n"
     ]
    }
   ],
   "source": [
    "tasks = ['serious_adverse_rate', 'mortality_rate']\n",
    "for task in tasks:\n",
    "    part[task] = target[task]\n",
    "    train_index, test_index = train_test_split(part, test_size=0.2, random_state=42)\n",
    "    train_x = train_index.drop(task, axis=1)\n",
    "    train_y = pd.DataFrame(train_index[task])\n",
    "    test_x = test_index.drop(task, axis=1)\n",
    "    test_y = pd.DataFrame(test_index[task])\n",
    "    train_y['Y/N'] = train_index[task].apply(lambda x: 1 if x > 0 else 0) # 二分类\n",
    "    test_y['Y/N'] = test_index[task].apply(lambda x: 1 if x > 0 else 0)\n",
    "    print(train_x.shape, train_y.shape, test_x.shape, test_y.shape)\n",
    "    train_x.to_csv(f'{task_name}/{task}_train_x.csv') # (25044, 68)\n",
    "    train_y.to_csv(f'{task_name}/{task}_train_y.csv')\n",
    "    test_x.to_csv(f'{task_name}/{task}_test_x.csv')\n",
    "    test_y.to_csv(f'{task_name}/{task}_test_y.csv')\n",
    "    test_x.iloc[:10].to_csv(f'preview-set/{task}_input.csv')\n",
    "    test_y.iloc[:10].to_csv(f'preview-set/{task}_output.csv')\n",
    "    part = part.drop(task, axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4978"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_x['icdcode'].isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## trial-duration-prediction\n",
    "\n",
    "删nan太多的特征 全一样的特征 --> 划分训练测试\n",
    "\n",
    "选的时候删除了长度target超过十年的部分，最终target采用time_day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "11 (462610, 67)\n",
      "study_design_info/allocation In the columns!\n",
      "study_design_info/intervention_model In the columns!\n",
      "study_design_info/primary_purpose In the columns!\n",
      "study_design_info/time_perspective In the columns!\n",
      "study_design_info/observational_model In the columns!\n",
      "(462610, 73)\n",
      "(462610, 73)\n",
      "(277869, 73)\n",
      "(143769, 59)\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Active Comparator Arm Number</th>\n",
       "      <th>Behavioral intervention Number</th>\n",
       "      <th>Biological intervention Number</th>\n",
       "      <th>Combination Product intervention Number</th>\n",
       "      <th>Device intervention Number</th>\n",
       "      <th>Diagnostic Test intervention Number</th>\n",
       "      <th>Dietary Supplement intervention Number</th>\n",
       "      <th>Drug intervention Number</th>\n",
       "      <th>Experimental Arm Number</th>\n",
       "      <th>Genetic intervention Number</th>\n",
       "      <th>...</th>\n",
       "      <th>study_design_info/allocation</th>\n",
       "      <th>study_design_info/intervention_model</th>\n",
       "      <th>study_design_info/intervention_model_description</th>\n",
       "      <th>study_design_info/masking</th>\n",
       "      <th>study_design_info/masking_description</th>\n",
       "      <th>study_design_info/masking_num</th>\n",
       "      <th>study_design_info/observational_model</th>\n",
       "      <th>study_design_info/primary_purpose</th>\n",
       "      <th>study_design_info/time_perspective</th>\n",
       "      <th>study_type</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ntcid</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>NCT00000116</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Quadruple (Participant, Care Provider, Investi...</td>\n",
       "      <td>In this trial neither the participants, nor th...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000125</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Prevention</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000242</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</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>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000271</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000317</th>\n",
       "      <td>0.0</td>\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>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Crossover Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Double (Participant, Investigator)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264193</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single Group Assignment</td>\n",
       "      <td>The hypoxic group included rowers participatin...</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Diagnostic</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264206</th>\n",
       "      <td>0.0</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Non-Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264271</th>\n",
       "      <td>NaN</td>\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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</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>Case-Control</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrospective</td>\n",
       "      <td>Observational</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264284</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</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>Case-Only</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrospective</td>\n",
       "      <td>Observational</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264323</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>...</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>Cohort</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Prospective</td>\n",
       "      <td>Observational</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>143769 rows × 59 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Active Comparator Arm Number  Behavioral intervention Number  \\\n",
       "ntcid                                                                       \n",
       "NCT00000116                           0.0                             0.0   \n",
       "NCT00000125                           0.0                             0.0   \n",
       "NCT00000242                           NaN                             0.0   \n",
       "NCT00000271                           0.0                             0.0   \n",
       "NCT00000317                           0.0                             1.0   \n",
       "...                                   ...                             ...   \n",
       "NCT06264193                           0.0                             0.0   \n",
       "NCT06264206                           0.0                             0.0   \n",
       "NCT06264271                           NaN                             1.0   \n",
       "NCT06264284                           NaN                             0.0   \n",
       "NCT06264323                           NaN                             NaN   \n",
       "\n",
       "             Biological intervention Number  \\\n",
       "ntcid                                         \n",
       "NCT00000116                             0.0   \n",
       "NCT00000125                             0.0   \n",
       "NCT00000242                             0.0   \n",
       "NCT00000271                             0.0   \n",
       "NCT00000317                             0.0   \n",
       "...                                     ...   \n",
       "NCT06264193                             0.0   \n",
       "NCT06264206                             0.0   \n",
       "NCT06264271                             0.0   \n",
       "NCT06264284                             0.0   \n",
       "NCT06264323                             NaN   \n",
       "\n",
       "             Combination Product intervention Number  \\\n",
       "ntcid                                                  \n",
       "NCT00000116                                      0.0   \n",
       "NCT00000125                                      0.0   \n",
       "NCT00000242                                      0.0   \n",
       "NCT00000271                                      0.0   \n",
       "NCT00000317                                      0.0   \n",
       "...                                              ...   \n",
       "NCT06264193                                      0.0   \n",
       "NCT06264206                                      0.0   \n",
       "NCT06264271                                      0.0   \n",
       "NCT06264284                                      0.0   \n",
       "NCT06264323                                      NaN   \n",
       "\n",
       "             Device intervention Number  Diagnostic Test intervention Number  \\\n",
       "ntcid                                                                          \n",
       "NCT00000116                         0.0                                  0.0   \n",
       "NCT00000125                         0.0                                  0.0   \n",
       "NCT00000242                         0.0                                  0.0   \n",
       "NCT00000271                         0.0                                  0.0   \n",
       "NCT00000317                         0.0                                  0.0   \n",
       "...                                 ...                                  ...   \n",
       "NCT06264193                         0.0                                  0.0   \n",
       "NCT06264206                         0.0                                  1.0   \n",
       "NCT06264271                         0.0                                  0.0   \n",
       "NCT06264284                         0.0                                  0.0   \n",
       "NCT06264323                         NaN                                  NaN   \n",
       "\n",
       "             Dietary Supplement intervention Number  Drug intervention Number  \\\n",
       "ntcid                                                                           \n",
       "NCT00000116                                     3.0                       0.0   \n",
       "NCT00000125                                     0.0                       1.0   \n",
       "NCT00000242                                     0.0                       1.0   \n",
       "NCT00000271                                     0.0                       2.0   \n",
       "NCT00000317                                     0.0                       2.0   \n",
       "...                                             ...                       ...   \n",
       "NCT06264193                                     0.0                       0.0   \n",
       "NCT06264206                                     0.0                       0.0   \n",
       "NCT06264271                                     0.0                       0.0   \n",
       "NCT06264284                                     0.0                       0.0   \n",
       "NCT06264323                                     NaN                       NaN   \n",
       "\n",
       "             Experimental Arm Number  Genetic intervention Number  ...  \\\n",
       "ntcid                                                              ...   \n",
       "NCT00000116                      1.0                          0.0  ...   \n",
       "NCT00000125                      0.0                          0.0  ...   \n",
       "NCT00000242                      NaN                          0.0  ...   \n",
       "NCT00000271                      1.0                          0.0  ...   \n",
       "NCT00000317                      1.0                          0.0  ...   \n",
       "...                              ...                          ...  ...   \n",
       "NCT06264193                      1.0                          0.0  ...   \n",
       "NCT06264206                      1.0                          0.0  ...   \n",
       "NCT06264271                      NaN                          0.0  ...   \n",
       "NCT06264284                      NaN                          0.0  ...   \n",
       "NCT06264323                      NaN                          NaN  ...   \n",
       "\n",
       "             study_design_info/allocation  \\\n",
       "ntcid                                       \n",
       "NCT00000116                    Randomized   \n",
       "NCT00000125                    Randomized   \n",
       "NCT00000242                           NaN   \n",
       "NCT00000271                    Randomized   \n",
       "NCT00000317                    Randomized   \n",
       "...                                   ...   \n",
       "NCT06264193                           NaN   \n",
       "NCT06264206                Non-Randomized   \n",
       "NCT06264271                           NaN   \n",
       "NCT06264284                           NaN   \n",
       "NCT06264323                           NaN   \n",
       "\n",
       "             study_design_info/intervention_model  \\\n",
       "ntcid                                               \n",
       "NCT00000116                   Parallel Assignment   \n",
       "NCT00000125                   Parallel Assignment   \n",
       "NCT00000242                                   NaN   \n",
       "NCT00000271                   Parallel Assignment   \n",
       "NCT00000317                  Crossover Assignment   \n",
       "...                                           ...   \n",
       "NCT06264193               Single Group Assignment   \n",
       "NCT06264206                   Parallel Assignment   \n",
       "NCT06264271                                   NaN   \n",
       "NCT06264284                                   NaN   \n",
       "NCT06264323                                   NaN   \n",
       "\n",
       "              study_design_info/intervention_model_description  \\\n",
       "ntcid                                                            \n",
       "NCT00000116                                                NaN   \n",
       "NCT00000125                                                NaN   \n",
       "NCT00000242                                                NaN   \n",
       "NCT00000271                                                NaN   \n",
       "NCT00000317                                                NaN   \n",
       "...                                                        ...   \n",
       "NCT06264193  The hypoxic group included rowers participatin...   \n",
       "NCT06264206                                                NaN   \n",
       "NCT06264271                                                NaN   \n",
       "NCT06264284                                                NaN   \n",
       "NCT06264323                                                NaN   \n",
       "\n",
       "                                     study_design_info/masking  \\\n",
       "ntcid                                                            \n",
       "NCT00000116  Quadruple (Participant, Care Provider, Investi...   \n",
       "NCT00000125                                  None (Open Label)   \n",
       "NCT00000242                                                NaN   \n",
       "NCT00000271                                  None (Open Label)   \n",
       "NCT00000317                 Double (Participant, Investigator)   \n",
       "...                                                        ...   \n",
       "NCT06264193                                  None (Open Label)   \n",
       "NCT06264206                                  None (Open Label)   \n",
       "NCT06264271                                                NaN   \n",
       "NCT06264284                                                NaN   \n",
       "NCT06264323                                                NaN   \n",
       "\n",
       "                         study_design_info/masking_description  \\\n",
       "ntcid                                                            \n",
       "NCT00000116  In this trial neither the participants, nor th...   \n",
       "NCT00000125                                                NaN   \n",
       "NCT00000242                                                NaN   \n",
       "NCT00000271                                                NaN   \n",
       "NCT00000317                                                NaN   \n",
       "...                                                        ...   \n",
       "NCT06264193                                                NaN   \n",
       "NCT06264206                                                NaN   \n",
       "NCT06264271                                                NaN   \n",
       "NCT06264284                                                NaN   \n",
       "NCT06264323                                                NaN   \n",
       "\n",
       "             study_design_info/masking_num  \\\n",
       "ntcid                                        \n",
       "NCT00000116                            4.0   \n",
       "NCT00000125                            0.0   \n",
       "NCT00000242                            NaN   \n",
       "NCT00000271                            0.0   \n",
       "NCT00000317                            2.0   \n",
       "...                                    ...   \n",
       "NCT06264193                            0.0   \n",
       "NCT06264206                            0.0   \n",
       "NCT06264271                            NaN   \n",
       "NCT06264284                            NaN   \n",
       "NCT06264323                            NaN   \n",
       "\n",
       "             study_design_info/observational_model  \\\n",
       "ntcid                                                \n",
       "NCT00000116                                    NaN   \n",
       "NCT00000125                                    NaN   \n",
       "NCT00000242                                    NaN   \n",
       "NCT00000271                                    NaN   \n",
       "NCT00000317                                    NaN   \n",
       "...                                            ...   \n",
       "NCT06264193                                    NaN   \n",
       "NCT06264206                                    NaN   \n",
       "NCT06264271                           Case-Control   \n",
       "NCT06264284                              Case-Only   \n",
       "NCT06264323                                 Cohort   \n",
       "\n",
       "             study_design_info/primary_purpose  \\\n",
       "ntcid                                            \n",
       "NCT00000116                          Treatment   \n",
       "NCT00000125                         Prevention   \n",
       "NCT00000242                          Treatment   \n",
       "NCT00000271                          Treatment   \n",
       "NCT00000317                          Treatment   \n",
       "...                                        ...   \n",
       "NCT06264193                         Diagnostic   \n",
       "NCT06264206                          Treatment   \n",
       "NCT06264271                                NaN   \n",
       "NCT06264284                                NaN   \n",
       "NCT06264323                                NaN   \n",
       "\n",
       "             study_design_info/time_perspective      study_type  \n",
       "ntcid                                                            \n",
       "NCT00000116                                 NaN  Interventional  \n",
       "NCT00000125                                 NaN  Interventional  \n",
       "NCT00000242                                 NaN  Interventional  \n",
       "NCT00000271                                 NaN  Interventional  \n",
       "NCT00000317                                 NaN  Interventional  \n",
       "...                                         ...             ...  \n",
       "NCT06264193                                 NaN  Interventional  \n",
       "NCT06264206                                 NaN  Interventional  \n",
       "NCT06264271                       Retrospective   Observational  \n",
       "NCT06264284                       Retrospective   Observational  \n",
       "NCT06264323                         Prospective   Observational  \n",
       "\n",
       "[143769 rows x 59 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "task_name = 'trial-duration-prediction'\n",
    "target = pd.read_csv(f'{task_name}/output.csv', index_col=0)\n",
    "part = All.loc[target.index]\n",
    "add_feature = ['eligibility/study_pop/textblock', 'intervention/description', 'study_design_info/allocation', 'study_design_info/intervention_model', \n",
    "'study_design_info/intervention_model_description', 'study_design_info/primary_purpose', 'study_design_info/time_perspective', 'study_design_info/observational_model', \n",
    "'study_design_info/masking', 'study_design_info/masking_description',]\n",
    "print(len(add_feature), part.shape)\n",
    "for c in add_feature:\n",
    "    if c =='icdcode' or c == 'smiless' :\n",
    "        continue\n",
    "    if c in part.columns:\n",
    "        print(c, 'In the columns!')\n",
    "    else:\n",
    "        part[c] = All_Ori[c].loc[target.index]\n",
    "print(part.shape)\n",
    "drop_feature = ['enrollment{type}', 'enrollment', 'id_info/nct_id', 'completion_date{type}', 'start_date{type}', 'patient_data/ipd_info_type', 'patient_data/sharing_ipd',\n",
    "'oversight_info/is_fda_regulated_drug',  'oversight_info/has_dmc', 'oversight_info/is_fda_regulated_device',]  # duration 里不使用enrollment\n",
    "if 'patient_data/ipd_info_type' in drop_feature:\n",
    "    drop_feature.extend([f for f in part.columns if 'ipd_info_type-' in f])\n",
    "    drop_feature.remove('patient_data/ipd_info_type')\n",
    "for c in part.columns:\n",
    "    if part[c].isnull().sum() == len(part):\n",
    "        print(f'{c} is all null!')\n",
    "        drop_feature.append(c)\n",
    "    # if part[c].nunique(dropna=True) == 1:  # 除去缺失值后的所有值一样 即方差为0\n",
    "    #     print(f'{c} is unique!')\n",
    "    #     drop_feature.append(c)\n",
    "print(part.shape)\n",
    "part = part[part['completion_date{type}']=='Actual']\n",
    "print(part.shape)\n",
    "part = part[part['start_date{type}']=='Actual']\n",
    "part = part.drop(drop_feature, axis=1)\n",
    "sorted_columns = sorted(part.columns)\n",
    "print(part.shape)\n",
    "part = part.reindex(columns=sorted_columns)\n",
    "part"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "part.drop('overall_status', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(115015, 58) (115015,) (28754, 58) (28754,)\n"
     ]
    }
   ],
   "source": [
    "tasks = ['year']\n",
    "target['year'] = target['time_day'].apply(lambda x: x/365)\n",
    "target = target[target['year'] < 10] # 10年内完成的\n",
    "for task in tasks:\n",
    "    part[task] = target[task]\n",
    "    part_10 = part[part[task].notna() & part[task] < 10]\n",
    "    train_index, test_index = train_test_split(part_10, test_size=0.2, random_state=42)\n",
    "    train_x = train_index.drop(task, axis=1)\n",
    "    train_y = train_index[task]\n",
    "    test_x = test_index.drop(task, axis=1)\n",
    "    test_y = test_index[task]\n",
    "    print(train_x.shape, train_y.shape, test_x.shape, test_y.shape)\n",
    "    train_x.to_csv(f'{task_name}/train_x_10.csv')\n",
    "    train_y.to_csv(f'{task_name}/train_y_10.csv')\n",
    "    test_x.to_csv(f'{task_name}/test_x_10.csv')\n",
    "    test_y.to_csv(f'{task_name}/test_y_10.csv')\n",
    "    # test_x.iloc[:10].to_csv(f'preview-set/{task_name}_input.csv')\n",
    "    # test_y.iloc[:10].to_csv(f'preview-set/{task_name}_output.csv')\n",
    "    part = part.drop(task, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    28424.000000\n",
       "mean         1.910582\n",
       "std          1.753774\n",
       "min          0.002740\n",
       "25%          0.605479\n",
       "50%          1.372603\n",
       "75%          2.695890\n",
       "max          9.991781\n",
       "Name: year, dtype: float64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_y.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count                452147\n",
       "unique                 8690\n",
       "top       December 31, 2023\n",
       "freq                   3429\n",
       "Name: completion_date, dtype: object"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target['completion_date'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "sub = pd.to_datetime('2022-01-01')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "target['completion_date'] = target['completion_date'].apply(lambda x: pd.to_datetime(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(304402, 5) (147745, 5)\n",
      "(108659, 60) (33281, 60)\n",
      "(108659, 58) (108659, 5) (33281, 58) (33281, 5)\n"
     ]
    }
   ],
   "source": [
    "tarin_target_part = target[target['completion_date'] < sub]\n",
    "test_target_part = target[target['completion_date'] >= sub]\n",
    "print(tarin_target_part.shape, test_target_part.shape)\n",
    "part['completion_date'] = target['completion_date']\n",
    "part['year'] = target['year']\n",
    "train_index = part[part['completion_date'] < sub]\n",
    "test_index = part[part['completion_date'] >= sub]\n",
    "print(train_index.shape, test_index.shape)\n",
    "train_x = train_index.drop('year', axis=1)\n",
    "train_x = train_x.drop('completion_date', axis=1)\n",
    "train_y = target.loc[train_index.index]\n",
    "test_x = test_index.drop('year', axis=1)\n",
    "test_x = test_x.drop('completion_date', axis=1)\n",
    "test_y = target.loc[test_index.index]\n",
    "print(train_x.shape, train_y.shape, test_x.shape, test_y.shape)\n",
    "train_x.to_csv(f'{task_name}/train_x_2022.csv')\n",
    "train_y.to_csv(f'{task_name}/train_y_2022.csv')\n",
    "test_x.to_csv(f'{task_name}/test_x_2022.csv')\n",
    "test_y.to_csv(f'{task_name}/test_y_2022.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    108659.000000\n",
       "mean          1.908080\n",
       "std           1.760976\n",
       "min           0.002740\n",
       "25%           0.602740\n",
       "50%           1.375342\n",
       "75%           2.668493\n",
       "max           9.994521\n",
       "Name: year, dtype: float64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_y.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## patient-dropout-prediction\n",
    "\n",
    "删nan太多的特征 全一样的特征 --> 划分训练测试"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10 (62058, 67)\n",
      "study_design_info/allocation In the columns!\n",
      "study_design_info/intervention_model In the columns!\n",
      "study_design_info/primary_purpose In the columns!\n",
      "study_design_info/time_perspective In the columns!\n",
      "study_design_info/observational_model In the columns!\n",
      "(62058, 72)\n",
      "start_date{type} is unique!\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        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>Active Comparator Arm Number</th>\n",
       "      <th>Behavioral intervention Number</th>\n",
       "      <th>Biological intervention Number</th>\n",
       "      <th>Combination Product intervention Number</th>\n",
       "      <th>Device intervention Number</th>\n",
       "      <th>Diagnostic Test intervention Number</th>\n",
       "      <th>Dietary Supplement intervention Number</th>\n",
       "      <th>Drug intervention Number</th>\n",
       "      <th>Experimental Arm Number</th>\n",
       "      <th>Genetic intervention Number</th>\n",
       "      <th>...</th>\n",
       "      <th>study_design_info/allocation</th>\n",
       "      <th>study_design_info/intervention_model</th>\n",
       "      <th>study_design_info/intervention_model_description</th>\n",
       "      <th>study_design_info/masking</th>\n",
       "      <th>study_design_info/masking_description</th>\n",
       "      <th>study_design_info/masking_num</th>\n",
       "      <th>study_design_info/observational_model</th>\n",
       "      <th>study_design_info/primary_purpose</th>\n",
       "      <th>study_design_info/time_perspective</th>\n",
       "      <th>study_type</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ntcid</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>NCT00000125</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Prevention</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000134</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Factorial Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Double (Participant, Investigator)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000135</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Double (Participant, Care Provider)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000136</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single (Outcomes Assessor)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000142</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06002347</th>\n",
       "      <td>0.0</td>\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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single Group Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Prevention</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06033079</th>\n",
       "      <td>0.0</td>\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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>We will conduct a randomized controlled trial ...</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Health Services Research</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06076681</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Double (Participant, Investigator)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06076694</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06097676</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Crossover Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Quadruple (Participant, Care Provider, Investi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>62058 rows × 67 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Active Comparator Arm Number  Behavioral intervention Number  \\\n",
       "ntcid                                                                       \n",
       "NCT00000125                           0.0                             0.0   \n",
       "NCT00000134                           2.0                             0.0   \n",
       "NCT00000135                           0.0                             0.0   \n",
       "NCT00000136                           0.0                             0.0   \n",
       "NCT00000142                           0.0                             0.0   \n",
       "...                                   ...                             ...   \n",
       "NCT06002347                           0.0                             1.0   \n",
       "NCT06033079                           0.0                             1.0   \n",
       "NCT06076681                           0.0                             0.0   \n",
       "NCT06076694                           1.0                             0.0   \n",
       "NCT06097676                           1.0                             0.0   \n",
       "\n",
       "             Biological intervention Number  \\\n",
       "ntcid                                         \n",
       "NCT00000125                             0.0   \n",
       "NCT00000134                             0.0   \n",
       "NCT00000135                             0.0   \n",
       "NCT00000136                             0.0   \n",
       "NCT00000142                             0.0   \n",
       "...                                     ...   \n",
       "NCT06002347                             0.0   \n",
       "NCT06033079                             0.0   \n",
       "NCT06076681                             0.0   \n",
       "NCT06076694                             0.0   \n",
       "NCT06097676                             0.0   \n",
       "\n",
       "             Combination Product intervention Number  \\\n",
       "ntcid                                                  \n",
       "NCT00000125                                      0.0   \n",
       "NCT00000134                                      0.0   \n",
       "NCT00000135                                      0.0   \n",
       "NCT00000136                                      0.0   \n",
       "NCT00000142                                      0.0   \n",
       "...                                              ...   \n",
       "NCT06002347                                      0.0   \n",
       "NCT06033079                                      0.0   \n",
       "NCT06076681                                      0.0   \n",
       "NCT06076694                                      0.0   \n",
       "NCT06097676                                      0.0   \n",
       "\n",
       "             Device intervention Number  Diagnostic Test intervention Number  \\\n",
       "ntcid                                                                          \n",
       "NCT00000125                         0.0                                  0.0   \n",
       "NCT00000134                         0.0                                  0.0   \n",
       "NCT00000135                         0.0                                  0.0   \n",
       "NCT00000136                         0.0                                  0.0   \n",
       "NCT00000142                         0.0                                  0.0   \n",
       "...                                 ...                                  ...   \n",
       "NCT06002347                         0.0                                  0.0   \n",
       "NCT06033079                         0.0                                  0.0   \n",
       "NCT06076681                         0.0                                  0.0   \n",
       "NCT06076694                         0.0                                  0.0   \n",
       "NCT06097676                         0.0                                  0.0   \n",
       "\n",
       "             Dietary Supplement intervention Number  Drug intervention Number  \\\n",
       "ntcid                                                                           \n",
       "NCT00000125                                     0.0                       1.0   \n",
       "NCT00000134                                     0.0                       2.0   \n",
       "NCT00000135                                     0.0                       1.0   \n",
       "NCT00000136                                     0.0                       2.0   \n",
       "NCT00000142                                     0.0                       1.0   \n",
       "...                                             ...                       ...   \n",
       "NCT06002347                                     0.0                       0.0   \n",
       "NCT06033079                                     0.0                       0.0   \n",
       "NCT06076681                                     0.0                       3.0   \n",
       "NCT06076694                                     0.0                       3.0   \n",
       "NCT06097676                                     0.0                       5.0   \n",
       "\n",
       "             Experimental Arm Number  Genetic intervention Number  ...  \\\n",
       "ntcid                                                              ...   \n",
       "NCT00000125                      0.0                          0.0  ...   \n",
       "NCT00000134                      1.0                          0.0  ...   \n",
       "NCT00000135                      1.0                          0.0  ...   \n",
       "NCT00000136                      2.0                          0.0  ...   \n",
       "NCT00000142                      3.0                          0.0  ...   \n",
       "...                              ...                          ...  ...   \n",
       "NCT06002347                      1.0                          0.0  ...   \n",
       "NCT06033079                      1.0                          0.0  ...   \n",
       "NCT06076681                      4.0                          0.0  ...   \n",
       "NCT06076694                      4.0                          0.0  ...   \n",
       "NCT06097676                      3.0                          0.0  ...   \n",
       "\n",
       "             study_design_info/allocation  \\\n",
       "ntcid                                       \n",
       "NCT00000125                    Randomized   \n",
       "NCT00000134                    Randomized   \n",
       "NCT00000135                    Randomized   \n",
       "NCT00000136                    Randomized   \n",
       "NCT00000142                    Randomized   \n",
       "...                                   ...   \n",
       "NCT06002347                           NaN   \n",
       "NCT06033079                    Randomized   \n",
       "NCT06076681                    Randomized   \n",
       "NCT06076694                    Randomized   \n",
       "NCT06097676                    Randomized   \n",
       "\n",
       "             study_design_info/intervention_model  \\\n",
       "ntcid                                               \n",
       "NCT00000125                   Parallel Assignment   \n",
       "NCT00000134                  Factorial Assignment   \n",
       "NCT00000135                   Parallel Assignment   \n",
       "NCT00000136                   Parallel Assignment   \n",
       "NCT00000142                   Parallel Assignment   \n",
       "...                                           ...   \n",
       "NCT06002347               Single Group Assignment   \n",
       "NCT06033079                   Parallel Assignment   \n",
       "NCT06076681                   Parallel Assignment   \n",
       "NCT06076694                   Parallel Assignment   \n",
       "NCT06097676                  Crossover Assignment   \n",
       "\n",
       "              study_design_info/intervention_model_description  \\\n",
       "ntcid                                                            \n",
       "NCT00000125                                                NaN   \n",
       "NCT00000134                                                NaN   \n",
       "NCT00000135                                                NaN   \n",
       "NCT00000136                                                NaN   \n",
       "NCT00000142                                                NaN   \n",
       "...                                                        ...   \n",
       "NCT06002347                                                NaN   \n",
       "NCT06033079  We will conduct a randomized controlled trial ...   \n",
       "NCT06076681                                                NaN   \n",
       "NCT06076694                                                NaN   \n",
       "NCT06097676                                                NaN   \n",
       "\n",
       "                                     study_design_info/masking  \\\n",
       "ntcid                                                            \n",
       "NCT00000125                                  None (Open Label)   \n",
       "NCT00000134                 Double (Participant, Investigator)   \n",
       "NCT00000135                Double (Participant, Care Provider)   \n",
       "NCT00000136                         Single (Outcomes Assessor)   \n",
       "NCT00000142                                  None (Open Label)   \n",
       "...                                                        ...   \n",
       "NCT06002347                                  None (Open Label)   \n",
       "NCT06033079                                  None (Open Label)   \n",
       "NCT06076681                 Double (Participant, Investigator)   \n",
       "NCT06076694                                  None (Open Label)   \n",
       "NCT06097676  Quadruple (Participant, Care Provider, Investi...   \n",
       "\n",
       "             study_design_info/masking_description  \\\n",
       "ntcid                                                \n",
       "NCT00000125                                    NaN   \n",
       "NCT00000134                                    NaN   \n",
       "NCT00000135                                    NaN   \n",
       "NCT00000136                                    NaN   \n",
       "NCT00000142                                    NaN   \n",
       "...                                            ...   \n",
       "NCT06002347                                    NaN   \n",
       "NCT06033079                                    NaN   \n",
       "NCT06076681                                    NaN   \n",
       "NCT06076694                                    NaN   \n",
       "NCT06097676                                    NaN   \n",
       "\n",
       "             study_design_info/masking_num  \\\n",
       "ntcid                                        \n",
       "NCT00000125                            0.0   \n",
       "NCT00000134                            2.0   \n",
       "NCT00000135                            2.0   \n",
       "NCT00000136                            1.0   \n",
       "NCT00000142                            0.0   \n",
       "...                                    ...   \n",
       "NCT06002347                            0.0   \n",
       "NCT06033079                            0.0   \n",
       "NCT06076681                            2.0   \n",
       "NCT06076694                            0.0   \n",
       "NCT06097676                            4.0   \n",
       "\n",
       "             study_design_info/observational_model  \\\n",
       "ntcid                                                \n",
       "NCT00000125                                    NaN   \n",
       "NCT00000134                                    NaN   \n",
       "NCT00000135                                    NaN   \n",
       "NCT00000136                                    NaN   \n",
       "NCT00000142                                    NaN   \n",
       "...                                            ...   \n",
       "NCT06002347                                    NaN   \n",
       "NCT06033079                                    NaN   \n",
       "NCT06076681                                    NaN   \n",
       "NCT06076694                                    NaN   \n",
       "NCT06097676                                    NaN   \n",
       "\n",
       "             study_design_info/primary_purpose  \\\n",
       "ntcid                                            \n",
       "NCT00000125                         Prevention   \n",
       "NCT00000134                          Treatment   \n",
       "NCT00000135                          Treatment   \n",
       "NCT00000136                          Treatment   \n",
       "NCT00000142                          Treatment   \n",
       "...                                        ...   \n",
       "NCT06002347                         Prevention   \n",
       "NCT06033079           Health Services Research   \n",
       "NCT06076681                          Treatment   \n",
       "NCT06076694                          Treatment   \n",
       "NCT06097676                              Other   \n",
       "\n",
       "             study_design_info/time_perspective      study_type  \n",
       "ntcid                                                            \n",
       "NCT00000125                                 NaN  Interventional  \n",
       "NCT00000134                                 NaN  Interventional  \n",
       "NCT00000135                                 NaN  Interventional  \n",
       "NCT00000136                                 NaN  Interventional  \n",
       "NCT00000142                                 NaN  Interventional  \n",
       "...                                         ...             ...  \n",
       "NCT06002347                                 NaN  Interventional  \n",
       "NCT06033079                                 NaN  Interventional  \n",
       "NCT06076681                                 NaN  Interventional  \n",
       "NCT06076694                                 NaN  Interventional  \n",
       "NCT06097676                                 NaN  Interventional  \n",
       "\n",
       "[62058 rows x 67 columns]"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "task_name = 'patient-dropout-prediction'\n",
    "target = pd.read_csv(f'{task_name}/output.csv', index_col=0)\n",
    "part = All.loc[target.index]\n",
    "add_feature = ['eligibility/study_pop/textblock', 'intervention/description', 'study_design_info/allocation', 'study_design_info/intervention_model', \n",
    "'study_design_info/intervention_model_description', 'study_design_info/primary_purpose', 'study_design_info/time_perspective', 'study_design_info/observational_model', \n",
    "'study_design_info/masking', 'study_design_info/masking_description']\n",
    "print(len(add_feature), part.shape)\n",
    "for c in add_feature:\n",
    "    if c in part.columns:\n",
    "        print(c, 'In the columns!')\n",
    "    else:\n",
    "        part[c] = All_Ori[c].loc[target.index]\n",
    "print(part.shape)\n",
    "drop_feature = ['enrollment{type}', 'id_info/nct_id', 'biospec_retention','completion_date{type}']\n",
    "for c in part.columns:\n",
    "    if c =='icdcode' or c == 'smiless' :\n",
    "        continue\n",
    "    if part[c].isnull().sum() == len(part):\n",
    "        print(f'{c} is all null!')\n",
    "        drop_feature.append(c)\n",
    "    if part[c].nunique(dropna=True) == 1:  # 除去缺失值后的所有值一样 即方差为0\n",
    "        print(f'{c} is unique!')\n",
    "        drop_feature.append(c)\n",
    "\n",
    "part = part.drop(drop_feature, axis=1)\n",
    "sorted_columns = sorted(part.columns)\n",
    "part = part.reindex(columns=sorted_columns)\n",
    "part"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(49646, 67) (49646, 2) (12412, 67) (12412, 2)\n"
     ]
    }
   ],
   "source": [
    "tasks = ['droupout_rate']\n",
    "for task in tasks:\n",
    "    part[task] = target[task]\n",
    "    train_index, test_index = train_test_split(part, test_size=0.2, random_state=42)\n",
    "    train_x = train_index.drop(task, axis=1)\n",
    "    train_y = pd.DataFrame(train_index[task])\n",
    "    test_x = test_index.drop(task, axis=1)\n",
    "    test_y = pd.DataFrame(test_index[task])\n",
    "    train_y['Y/N'] = train_index[task].apply(lambda x: 1 if x > 0 else 0)\n",
    "    test_y['Y/N'] = test_index[task].apply(lambda x: 1 if x > 0 else 0)\n",
    "    print(train_x.shape, train_y.shape, test_x.shape, test_y.shape)\n",
    "    train_x.to_csv(f'{task_name}/train_x.csv')\n",
    "    train_y.to_csv(f'{task_name}/train_y.csv')\n",
    "    test_x.to_csv(f'{task_name}/test_x.csv')\n",
    "    test_y.to_csv(f'{task_name}/test_y.csv')\n",
    "    # test_x.iloc[:10].to_csv(f'preview-set/{task_name}_input.csv')\n",
    "    # test_y.iloc[:10].to_csv(f'preview-set/{task_name}_output.csv')\n",
    "    part = part.drop(task, axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## trial-approval-prediction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "删nan太多的特征 全一样的特征 --> 划分训练测试  分类任务 分层采样"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NCT01227460\n",
      "NCT03003741\n",
      "NCT01636921\n",
      "NCT01565421\n",
      "NCT03036280\n",
      "NCT01225848\n",
      "NCT02157870\n",
      "NCT01890980\n",
      "NCT00103090\n",
      "NCT03290664\n",
      "1 (43202, 67)\n",
      "(43202, 68)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Active Comparator Arm Number</th>\n",
       "      <th>Behavioral intervention Number</th>\n",
       "      <th>Biological intervention Number</th>\n",
       "      <th>Combination Product intervention Number</th>\n",
       "      <th>Device intervention Number</th>\n",
       "      <th>Diagnostic Test intervention Number</th>\n",
       "      <th>Dietary Supplement intervention Number</th>\n",
       "      <th>Drug intervention Number</th>\n",
       "      <th>Experimental Arm Number</th>\n",
       "      <th>Genetic intervention Number</th>\n",
       "      <th>...</th>\n",
       "      <th>responsible_party/responsible_party_type</th>\n",
       "      <th>smiless</th>\n",
       "      <th>sponsors/lead_sponsor/agency_class</th>\n",
       "      <th>study_design_info/allocation</th>\n",
       "      <th>study_design_info/intervention_model</th>\n",
       "      <th>study_design_info/masking_num</th>\n",
       "      <th>study_design_info/observational_model</th>\n",
       "      <th>study_design_info/primary_purpose</th>\n",
       "      <th>study_design_info/time_perspective</th>\n",
       "      <th>study_type</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nctid</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>NCT00618644</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</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>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single Group Assignment</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT01266603</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\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>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Sponsor</td>\n",
       "      <td>None</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single Group Assignment</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT02773381</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Sponsor</td>\n",
       "      <td>[CC[C@H](C)[C@H](NC(=O)[C@H](CC1=CC=CC=C1)NC(=...</td>\n",
       "      <td>Industry</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Crossover Assignment</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT01248130</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Principal Investigator</td>\n",
       "      <td>None</td>\n",
       "      <td>Other</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT01515007</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Sponsor</td>\n",
       "      <td>[OC(=O)C1=CN(C2CC2)C2=CC(N3CCNCC3)=C(F)C=C2C1=O]</td>\n",
       "      <td>Industry</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT01198366</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Sponsor</td>\n",
       "      <td>None</td>\n",
       "      <td>Other</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Prevention</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT01169987</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>...</td>\n",
       "      <td>Sponsor</td>\n",
       "      <td>None</td>\n",
       "      <td>Industry</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Cohort</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Prospective</td>\n",
       "      <td>Observational</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT01978236</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Sponsor</td>\n",
       "      <td>[CC(C)(C)C1=NC(=C(S1)C1=NC(N)=NC=C1)C1=C(F)C(N...</td>\n",
       "      <td>Industry</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Single Group Assignment</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT02158754</th>\n",
       "      <td>NaN</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Sponsor</td>\n",
       "      <td>None</td>\n",
       "      <td>Industry</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Case-Control</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrospective</td>\n",
       "      <td>Observational</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT02078310</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Sponsor</td>\n",
       "      <td>None</td>\n",
       "      <td>Industry</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Basic Science</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>43202 rows × 64 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Active Comparator Arm Number  Behavioral intervention Number  \\\n",
       "nctid                                                                       \n",
       "NCT00618644                           0.0                             0.0   \n",
       "NCT01266603                           0.0                             0.0   \n",
       "NCT02773381                           0.0                             0.0   \n",
       "NCT01248130                           1.0                             0.0   \n",
       "NCT01515007                           0.0                             0.0   \n",
       "...                                   ...                             ...   \n",
       "NCT01198366                           0.0                             0.0   \n",
       "NCT01169987                           NaN                             NaN   \n",
       "NCT01978236                           0.0                             0.0   \n",
       "NCT02158754                           NaN                             0.0   \n",
       "NCT02078310                           0.0                             0.0   \n",
       "\n",
       "             Biological intervention Number  \\\n",
       "nctid                                         \n",
       "NCT00618644                             0.0   \n",
       "NCT01266603                             1.0   \n",
       "NCT02773381                             0.0   \n",
       "NCT01248130                             0.0   \n",
       "NCT01515007                             0.0   \n",
       "...                                     ...   \n",
       "NCT01198366                             4.0   \n",
       "NCT01169987                             NaN   \n",
       "NCT01978236                             0.0   \n",
       "NCT02158754                             0.0   \n",
       "NCT02078310                             0.0   \n",
       "\n",
       "             Combination Product intervention Number  \\\n",
       "nctid                                                  \n",
       "NCT00618644                                      0.0   \n",
       "NCT01266603                                      0.0   \n",
       "NCT02773381                                      0.0   \n",
       "NCT01248130                                      0.0   \n",
       "NCT01515007                                      0.0   \n",
       "...                                              ...   \n",
       "NCT01198366                                      0.0   \n",
       "NCT01169987                                      NaN   \n",
       "NCT01978236                                      0.0   \n",
       "NCT02158754                                      0.0   \n",
       "NCT02078310                                      0.0   \n",
       "\n",
       "             Device intervention Number  Diagnostic Test intervention Number  \\\n",
       "nctid                                                                          \n",
       "NCT00618644                         0.0                                  0.0   \n",
       "NCT01266603                         0.0                                  0.0   \n",
       "NCT02773381                         0.0                                  0.0   \n",
       "NCT01248130                         0.0                                  0.0   \n",
       "NCT01515007                         0.0                                  0.0   \n",
       "...                                 ...                                  ...   \n",
       "NCT01198366                         0.0                                  0.0   \n",
       "NCT01169987                         NaN                                  NaN   \n",
       "NCT01978236                         0.0                                  0.0   \n",
       "NCT02158754                         0.0                                  1.0   \n",
       "NCT02078310                         0.0                                  0.0   \n",
       "\n",
       "             Dietary Supplement intervention Number  Drug intervention Number  \\\n",
       "nctid                                                                           \n",
       "NCT00618644                                     0.0                       1.0   \n",
       "NCT01266603                                     0.0                       1.0   \n",
       "NCT02773381                                     0.0                       2.0   \n",
       "NCT01248130                                     0.0                       1.0   \n",
       "NCT01515007                                     0.0                       2.0   \n",
       "...                                             ...                       ...   \n",
       "NCT01198366                                     0.0                       0.0   \n",
       "NCT01169987                                     NaN                       NaN   \n",
       "NCT01978236                                     0.0                       2.0   \n",
       "NCT02158754                                     0.0                       0.0   \n",
       "NCT02078310                                     0.0                       4.0   \n",
       "\n",
       "             Experimental Arm Number  Genetic intervention Number  ...  \\\n",
       "nctid                                                              ...   \n",
       "NCT00618644                      1.0                          0.0  ...   \n",
       "NCT01266603                      1.0                          0.0  ...   \n",
       "NCT02773381                      1.0                          0.0  ...   \n",
       "NCT01248130                      0.0                          0.0  ...   \n",
       "NCT01515007                      1.0                          0.0  ...   \n",
       "...                              ...                          ...  ...   \n",
       "NCT01198366                      4.0                          0.0  ...   \n",
       "NCT01169987                      NaN                          NaN  ...   \n",
       "NCT01978236                      2.0                          0.0  ...   \n",
       "NCT02158754                      NaN                          0.0  ...   \n",
       "NCT02078310                      2.0                          0.0  ...   \n",
       "\n",
       "             responsible_party/responsible_party_type  \\\n",
       "nctid                                                   \n",
       "NCT00618644                                       NaN   \n",
       "NCT01266603                                   Sponsor   \n",
       "NCT02773381                                   Sponsor   \n",
       "NCT01248130                    Principal Investigator   \n",
       "NCT01515007                                   Sponsor   \n",
       "...                                               ...   \n",
       "NCT01198366                                   Sponsor   \n",
       "NCT01169987                                   Sponsor   \n",
       "NCT01978236                                   Sponsor   \n",
       "NCT02158754                                   Sponsor   \n",
       "NCT02078310                                   Sponsor   \n",
       "\n",
       "                                                       smiless  \\\n",
       "nctid                                                            \n",
       "NCT00618644                                               None   \n",
       "NCT01266603                                               None   \n",
       "NCT02773381  [CC[C@H](C)[C@H](NC(=O)[C@H](CC1=CC=CC=C1)NC(=...   \n",
       "NCT01248130                                               None   \n",
       "NCT01515007   [OC(=O)C1=CN(C2CC2)C2=CC(N3CCNCC3)=C(F)C=C2C1=O]   \n",
       "...                                                        ...   \n",
       "NCT01198366                                               None   \n",
       "NCT01169987                                               None   \n",
       "NCT01978236  [CC(C)(C)C1=NC(=C(S1)C1=NC(N)=NC=C1)C1=C(F)C(N...   \n",
       "NCT02158754                                               None   \n",
       "NCT02078310                                               None   \n",
       "\n",
       "             sponsors/lead_sponsor/agency_class  study_design_info/allocation  \\\n",
       "nctid                                                                           \n",
       "NCT00618644                               Other                           NaN   \n",
       "NCT01266603                               Other                           NaN   \n",
       "NCT02773381                            Industry                    Randomized   \n",
       "NCT01248130                               Other                    Randomized   \n",
       "NCT01515007                            Industry                    Randomized   \n",
       "...                                         ...                           ...   \n",
       "NCT01198366                               Other                    Randomized   \n",
       "NCT01169987                            Industry                           NaN   \n",
       "NCT01978236                            Industry                    Randomized   \n",
       "NCT02158754                            Industry                           NaN   \n",
       "NCT02078310                            Industry                    Randomized   \n",
       "\n",
       "             study_design_info/intervention_model  \\\n",
       "nctid                                               \n",
       "NCT00618644               Single Group Assignment   \n",
       "NCT01266603               Single Group Assignment   \n",
       "NCT02773381                  Crossover Assignment   \n",
       "NCT01248130                   Parallel Assignment   \n",
       "NCT01515007                   Parallel Assignment   \n",
       "...                                           ...   \n",
       "NCT01198366                   Parallel Assignment   \n",
       "NCT01169987                                   NaN   \n",
       "NCT01978236               Single Group Assignment   \n",
       "NCT02158754                                   NaN   \n",
       "NCT02078310                   Parallel Assignment   \n",
       "\n",
       "             study_design_info/masking_num  \\\n",
       "nctid                                        \n",
       "NCT00618644                            2.0   \n",
       "NCT01266603                            0.0   \n",
       "NCT02773381                            2.0   \n",
       "NCT01248130                            3.0   \n",
       "NCT01515007                            4.0   \n",
       "...                                    ...   \n",
       "NCT01198366                            4.0   \n",
       "NCT01169987                            NaN   \n",
       "NCT01978236                            0.0   \n",
       "NCT02158754                            NaN   \n",
       "NCT02078310                            4.0   \n",
       "\n",
       "             study_design_info/observational_model  \\\n",
       "nctid                                                \n",
       "NCT00618644                                    NaN   \n",
       "NCT01266603                                    NaN   \n",
       "NCT02773381                                    NaN   \n",
       "NCT01248130                                    NaN   \n",
       "NCT01515007                                    NaN   \n",
       "...                                            ...   \n",
       "NCT01198366                                    NaN   \n",
       "NCT01169987                                 Cohort   \n",
       "NCT01978236                                    NaN   \n",
       "NCT02158754                           Case-Control   \n",
       "NCT02078310                                    NaN   \n",
       "\n",
       "             study_design_info/primary_purpose  \\\n",
       "nctid                                            \n",
       "NCT00618644                          Treatment   \n",
       "NCT01266603                          Treatment   \n",
       "NCT02773381                          Treatment   \n",
       "NCT01248130                          Treatment   \n",
       "NCT01515007                          Treatment   \n",
       "...                                        ...   \n",
       "NCT01198366                         Prevention   \n",
       "NCT01169987                                NaN   \n",
       "NCT01978236                          Treatment   \n",
       "NCT02158754                                NaN   \n",
       "NCT02078310                      Basic Science   \n",
       "\n",
       "             study_design_info/time_perspective      study_type  \n",
       "nctid                                                            \n",
       "NCT00618644                                 NaN  Interventional  \n",
       "NCT01266603                                 NaN  Interventional  \n",
       "NCT02773381                                 NaN  Interventional  \n",
       "NCT01248130                                 NaN  Interventional  \n",
       "NCT01515007                                 NaN  Interventional  \n",
       "...                                         ...             ...  \n",
       "NCT01198366                                 NaN  Interventional  \n",
       "NCT01169987                         Prospective   Observational  \n",
       "NCT01978236                                 NaN  Interventional  \n",
       "NCT02158754                       Retrospective   Observational  \n",
       "NCT02078310                                 NaN  Interventional  \n",
       "\n",
       "[43202 rows x 64 columns]"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "task_name = 'trial-approval-prediction'\n",
    "target = pd.read_csv(f'{task_name}/output.csv', index_col=0)\n",
    "drop_index = []\n",
    "for i in target.index:\n",
    "    if i not in All.index:\n",
    "        drop_index.append(i)\n",
    "        print(i)\n",
    "target = target.drop(drop_index)\n",
    "part = All.loc[target.index]\n",
    "add_feature = ['intervention/description', ]\n",
    "print(len(add_feature), part.shape)\n",
    "for c in add_feature:\n",
    "    if c in part.columns:\n",
    "        print(c, 'In the columns!')\n",
    "    else:\n",
    "        part[c] = All_Ori[c].loc[target.index]\n",
    "print(part.shape)\n",
    "drop_feature = ['enrollment{type}', 'id_info/nct_id', 'completion_date{type}', 'start_date{type}',]  # duration 里不使用enrollment\n",
    "for c in part.columns:\n",
    "    if c == 'icdcode' or c == 'smiless':\n",
    "        continue\n",
    "    if part[c].isnull().sum() == len(part):\n",
    "        print(f'{c} is all null!')\n",
    "        drop_feature.append(c)\n",
    "    if part[c].nunique(dropna=True) == 1:  # 除去缺失值后的所有值一样 即方差为0\n",
    "        print(f'{c} is unique!')\n",
    "        drop_feature.append(c)\n",
    "\n",
    "part = part.drop(drop_feature, axis=1)\n",
    "sorted_columns = sorted(part.columns)\n",
    "part = part.reindex(columns=sorted_columns)\n",
    "part"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(34561, 64) (34561, 1) (8641, 64) (8641, 1)\n"
     ]
    }
   ],
   "source": [
    "strati = StratifiedShuffleSplit(n_splits=1, test_size=0.2, random_state=42)\n",
    "target['outcome'] = target['approval']\n",
    "task = 'outcome'\n",
    "for train_index, test_index in strati.split(part, target[task]):\n",
    "    train_index = train_index.tolist()\n",
    "    test_index = test_index.tolist()\n",
    "    train_x = part.iloc[train_index]\n",
    "    train_y = target.iloc[train_index].drop('approval', axis=1)\n",
    "    test_x = part.iloc[test_index]\n",
    "    test_y = target.iloc[test_index].drop('approval', axis=1)\n",
    "    print(train_x.shape, train_y.shape, test_x.shape, test_y.shape)\n",
    "    train_x.to_csv(f'{task_name}/train_x.csv')\n",
    "    train_y.to_csv(f'{task_name}/train_y.csv')\n",
    "    test_x.to_csv(f'{task_name}/test_x.csv')\n",
    "    test_y.to_csv(f'{task_name}/test_y.csv')\n",
    "    # test_x.iloc[:10].to_csv(f'preview-set/{task_name}_input.csv')\n",
    "    # test_y.iloc[:10].to_csv(f'preview-set/{task_name}_output.csv')\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "outcome\n",
      "0          0.626863\n",
      "1          0.373137\n",
      "Name: count, dtype: float64\n",
      "outcome\n",
      "0          0.626895\n",
      "1          0.373105\n",
      "Name: count, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(train_y.value_counts()/len(train_y))\n",
    "print(test_y.value_counts()/len(test_y))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## trial-failure-reason-prediction\n",
    "\n",
    "删nan太多的特征 全一样的特征 --> 划分训练测试  分类任务 分层采样\n",
    "\n",
    "feature-select.csv是手工选特征的结果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['brief_title',\n",
       " 'brief_summary/textblock',\n",
       " 'detailed_description/textblock',\n",
       " 'overall_status',\n",
       " 'phase',\n",
       " 'study_type',\n",
       " 'study_design_info/intervention_model',\n",
       " 'study_design_info/primary_purpose',\n",
       " 'study_design_info/masking',\n",
       " 'condition',\n",
       " 'intervention/intervention_type',\n",
       " 'intervention/intervention_name',\n",
       " 'eligibility/criteria/textblock',\n",
       " 'eligibility/minimum_age',\n",
       " 'eligibility/maximum_age',\n",
       " 'eligibility/healthy_volunteers',\n",
       " 'condition_browse/mesh_term',\n",
       " 'intervention_browse/mesh_term',\n",
       " 'icdcode',\n",
       " 'study_design_info/observational_model',\n",
       " 'study_design_info/time_perspective',\n",
       " 'keyword',\n",
       " 'oversight_info/has_dmc',\n",
       " 'biospec_descr/textblock',\n",
       " 'eligibility/study_pop/textblock',\n",
       " 'eligibility/sampling_method',\n",
       " 'study_design_info/allocation',\n",
       " 'number_of_arms',\n",
       " 'oversight_info/is_fda_regulated_drug',\n",
       " 'oversight_info/is_fda_regulated_device',\n",
       " 'study_design_info/intervention_model_description',\n",
       " 'eligibility/gender_based',\n",
       " 'eligibility/gender_description',\n",
       " 'smiless']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_info = pd.read_csv('feature-select.csv').set_index('feature_name')\n",
    "features = feature_info[feature_info['trial failure reason prediction**'] == 'Y'].index\n",
    "features = features.tolist()\n",
    "features.append('smiless') # 加入smiless\n",
    "features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "增加前几个task没有的特征，除掉这个task不需要的特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "detailed_description/textblock not in prepared data!\n",
      "overall_status not in prepared data!\n",
      "study_design_info/masking not in prepared data!\n",
      "intervention/intervention_type not in prepared data!\n",
      "biospec_descr/textblock not in prepared data!\n",
      "eligibility/study_pop/textblock not in prepared data!\n",
      "study_design_info/intervention_model_description not in prepared data!\n",
      "eligibility/gender_based not in prepared data!\n",
      "eligibility/gender_description not in prepared data!\n",
      "has_expanded_access not in selected feature!\n",
      "eligibility/gender not in selected feature!\n",
      "patient_data/sharing_ipd not in selected feature!\n",
      "id_info/nct_id not in selected feature!\n",
      "location/facility/address/city not in selected feature!\n",
      "enrollment not in selected feature!\n",
      "sponsors/lead_sponsor/agency_class not in selected feature!\n",
      "completion_date{type} not in selected feature!\n",
      "start_date{type} not in selected feature!\n",
      "enrollment{type} not in selected feature!\n",
      "responsible_party/responsible_party_type not in selected feature!\n",
      "biospec_retention not in selected feature!\n",
      "ipd_info_type-Statistical Analysis Plan (SAP) not in selected feature!\n",
      "ipd_info_type-Informed Consent Form (ICF) not in selected feature!\n",
      "ipd_info_type-Study Protocol not in selected feature!\n",
      "ipd_info_type-Clinical Study Report (CSR) not in selected feature!\n",
      "ipd_info_type-Analytic Code not in selected feature!\n",
      "study_design_info/masking_num not in selected feature!\n",
      "MaskingType-Participant not in selected feature!\n",
      "MaskingType-Care Provider not in selected feature!\n",
      "MaskingType-Investigator not in selected feature!\n",
      "MaskingType-Outcomes Assessor not in selected feature!\n",
      "Experimental Arm Number not in selected feature!\n",
      "Active Comparator Arm Number not in selected feature!\n",
      "Placebo Comparator Arm Number not in selected feature!\n",
      "No Intervention Arm Number not in selected feature!\n",
      "Other Arm Number not in selected feature!\n",
      "Sham Comparator Arm Number not in selected feature!\n",
      "Drug intervention Number not in selected feature!\n",
      "Procedure intervention Number not in selected feature!\n",
      "Biological intervention Number not in selected feature!\n",
      "Device intervention Number not in selected feature!\n",
      "Behavioral intervention Number not in selected feature!\n",
      "Other intervention Number not in selected feature!\n",
      "Dietary Supplement intervention Number not in selected feature!\n",
      "Genetic intervention Number not in selected feature!\n",
      "Radiation intervention Number not in selected feature!\n",
      "Diagnostic Test intervention Number not in selected feature!\n",
      "Combination Product intervention Number not in selected feature!\n",
      "location/facility/address/city-GDP not in selected feature!\n",
      "location/facility/address/city-Population not in selected feature!\n",
      "location/facility/address/city-Aging not in selected feature!\n",
      "9 27\n"
     ]
    }
   ],
   "source": [
    "add_feature = []\n",
    "for feature in features:\n",
    "    if feature not in All.columns:\n",
    "        add_feature.append(feature)\n",
    "        print(feature, 'not in prepared data!')\n",
    "\n",
    "drop_feature = ['overall_status', 'id_info/nct_id', ]\n",
    "for feature in All.columns:\n",
    "    if feature not in features:\n",
    "        drop_feature.append(feature)\n",
    "        print(feature, 'not in selected feature!')\n",
    "\n",
    "if 'arm_group/arm_group_type' not in drop_feature:\n",
    "    for i in drop_feature:\n",
    "        if 'Arm Number' in i:\n",
    "            drop_feature.remove(i)\n",
    "if 'intervention/intervention_type' not in drop_feature:\n",
    "    for i in drop_feature:\n",
    "        if 'intervention Number' in i:\n",
    "            drop_feature.remove(i)\n",
    "if 'location/facility/address/city' not in drop_feature:\n",
    "    drop_feature.remove('city-GDP')\n",
    "    drop_feature.remove('city-Population')\n",
    "    drop_feature.remove('city-Aging')\n",
    "if 'study_design_info/masking' not in drop_feature:\n",
    "    drop_feature.remove('MaskingType-Participant')\n",
    "    drop_feature.remove('MaskingType-Care Provider')\n",
    "    drop_feature.remove('MaskingType-Investigator')\n",
    "    drop_feature.remove('MaskingType-Outcomes Assessor')\n",
    "    drop_feature.remove('study_design_info/masking_num')\n",
    "if 'patient_data/ipd_info_type' not in drop_feature:\n",
    "    for i in drop_feature:\n",
    "        if 'ipd_info_type-' in i:\n",
    "            drop_feature.remove(i)\n",
    "            \n",
    "print(len(add_feature), len(drop_feature))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [],
   "source": [
    "for feature in add_feature:\n",
    "    All[feature] = All_Ori[feature]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "删nan太多的特征 全一样的特征 --> 划分训练测试  分类任务 分层采样"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NCT03003741\n",
      "NCT01636921\n",
      "NCT01565421\n",
      "NCT01867619\n",
      "NCT01479309\n",
      "NCT03036280\n",
      "NCT01225848\n",
      "NCT02087839\n",
      "NCT02157870\n",
      "NCT00103090\n",
      "NCT03290664\n",
      "NCT02349347\n",
      "eligibility/gender_based is unique!\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Behavioral intervention Number</th>\n",
       "      <th>Biological intervention Number</th>\n",
       "      <th>Combination Product intervention Number</th>\n",
       "      <th>Dietary Supplement intervention Number</th>\n",
       "      <th>Drug intervention Number</th>\n",
       "      <th>Experimental Arm Number</th>\n",
       "      <th>MaskingType-Care Provider</th>\n",
       "      <th>MaskingType-Investigator</th>\n",
       "      <th>MaskingType-Outcomes Assessor</th>\n",
       "      <th>MaskingType-Participant</th>\n",
       "      <th>...</th>\n",
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       "      <th>study_design_info/allocation</th>\n",
       "      <th>study_design_info/intervention_model</th>\n",
       "      <th>study_design_info/intervention_model_description</th>\n",
       "      <th>study_design_info/masking</th>\n",
       "      <th>study_design_info/masking_num</th>\n",
       "      <th>study_design_info/observational_model</th>\n",
       "      <th>study_design_info/primary_purpose</th>\n",
       "      <th>study_design_info/time_perspective</th>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single Group Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Double (Participant, Investigator)</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT03943303</th>\n",
       "      <td>0.0</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>The study will be carried out on the beaches o...</td>\n",
       "      <td>Single (Outcomes Assessor)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Health Services Research</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT01266603</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\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>...</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single Group Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT01248130</th>\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>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Triple (Participant, Care Provider, Investigator)</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00240214</th>\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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>[[H][C@@]1(C[C@@H](C)[C@]2([H])CC(=O)[C@H](C)\\...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Cohort</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Prospective</td>\n",
       "      <td>Observational</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT02121600</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>Non-Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Diagnostic</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT02478164</th>\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>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>...</td>\n",
       "      <td>[CN1CCN(CC2=CC=C(NC(=O)C3=CC(C#CC4=CN=C5C=CC=N...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single Group Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT01978236</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>[CC(C)(C)C1=NC(=C(S1)C1=NC(N)=NC=C1)C1=C(F)C(N...</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Single Group Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT02158754</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Case-Control</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Retrospective</td>\n",
       "      <td>Observational</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT03538444</th>\n",
       "      <td>0.0</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>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>40 individuals (20 per group) will be randomly...</td>\n",
       "      <td>Quadruple (Participant, Care Provider, Investi...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>41369 rows × 49 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Behavioral intervention Number  Biological intervention Number  \\\n",
       "nctid                                                                         \n",
       "NCT00618644                             0.0                             0.0   \n",
       "NCT03943303                             0.0                             0.0   \n",
       "NCT01266603                             0.0                             1.0   \n",
       "NCT01248130                             0.0                             0.0   \n",
       "NCT00240214                             0.0                             0.0   \n",
       "...                                     ...                             ...   \n",
       "NCT02121600                             0.0                             0.0   \n",
       "NCT02478164                             0.0                             0.0   \n",
       "NCT01978236                             0.0                             0.0   \n",
       "NCT02158754                             0.0                             0.0   \n",
       "NCT03538444                             0.0                             0.0   \n",
       "\n",
       "             Combination Product intervention Number  \\\n",
       "nctid                                                  \n",
       "NCT00618644                                      0.0   \n",
       "NCT03943303                                      0.0   \n",
       "NCT01266603                                      0.0   \n",
       "NCT01248130                                      0.0   \n",
       "NCT00240214                                      0.0   \n",
       "...                                              ...   \n",
       "NCT02121600                                      0.0   \n",
       "NCT02478164                                      0.0   \n",
       "NCT01978236                                      0.0   \n",
       "NCT02158754                                      0.0   \n",
       "NCT03538444                                      0.0   \n",
       "\n",
       "             Dietary Supplement intervention Number  Drug intervention Number  \\\n",
       "nctid                                                                           \n",
       "NCT00618644                                     0.0                       1.0   \n",
       "NCT03943303                                     0.0                       0.0   \n",
       "NCT01266603                                     0.0                       1.0   \n",
       "NCT01248130                                     0.0                       1.0   \n",
       "NCT00240214                                     0.0                       1.0   \n",
       "...                                             ...                       ...   \n",
       "NCT02121600                                     0.0                       0.0   \n",
       "NCT02478164                                     0.0                       1.0   \n",
       "NCT01978236                                     0.0                       2.0   \n",
       "NCT02158754                                     0.0                       0.0   \n",
       "NCT03538444                                     0.0                       0.0   \n",
       "\n",
       "             Experimental Arm Number  MaskingType-Care Provider  \\\n",
       "nctid                                                             \n",
       "NCT00618644                      1.0                        0.0   \n",
       "NCT03943303                      1.0                        0.0   \n",
       "NCT01266603                      1.0                        0.0   \n",
       "NCT01248130                      0.0                        1.0   \n",
       "NCT00240214                      NaN                        NaN   \n",
       "...                              ...                        ...   \n",
       "NCT02121600                      0.0                        0.0   \n",
       "NCT02478164                      1.0                        0.0   \n",
       "NCT01978236                      2.0                        0.0   \n",
       "NCT02158754                      NaN                        NaN   \n",
       "NCT03538444                      1.0                        1.0   \n",
       "\n",
       "             MaskingType-Investigator  MaskingType-Outcomes Assessor  \\\n",
       "nctid                                                                  \n",
       "NCT00618644                       1.0                            0.0   \n",
       "NCT03943303                       0.0                            1.0   \n",
       "NCT01266603                       0.0                            0.0   \n",
       "NCT01248130                       1.0                            0.0   \n",
       "NCT00240214                       NaN                            NaN   \n",
       "...                               ...                            ...   \n",
       "NCT02121600                       0.0                            0.0   \n",
       "NCT02478164                       0.0                            0.0   \n",
       "NCT01978236                       0.0                            0.0   \n",
       "NCT02158754                       NaN                            NaN   \n",
       "NCT03538444                       1.0                            1.0   \n",
       "\n",
       "             MaskingType-Participant  ...  \\\n",
       "nctid                                 ...   \n",
       "NCT00618644                      1.0  ...   \n",
       "NCT03943303                      0.0  ...   \n",
       "NCT01266603                      0.0  ...   \n",
       "NCT01248130                      1.0  ...   \n",
       "NCT00240214                      NaN  ...   \n",
       "...                              ...  ...   \n",
       "NCT02121600                      0.0  ...   \n",
       "NCT02478164                      0.0  ...   \n",
       "NCT01978236                      0.0  ...   \n",
       "NCT02158754                      NaN  ...   \n",
       "NCT03538444                      1.0  ...   \n",
       "\n",
       "                                                       smiless  \\\n",
       "nctid                                                            \n",
       "NCT00618644                                               None   \n",
       "NCT03943303                                               None   \n",
       "NCT01266603                                               None   \n",
       "NCT01248130                                               None   \n",
       "NCT00240214  [[H][C@@]1(C[C@@H](C)[C@]2([H])CC(=O)[C@H](C)\\...   \n",
       "...                                                        ...   \n",
       "NCT02121600                                               None   \n",
       "NCT02478164  [CN1CCN(CC2=CC=C(NC(=O)C3=CC(C#CC4=CN=C5C=CC=N...   \n",
       "NCT01978236  [CC(C)(C)C1=NC(=C(S1)C1=NC(N)=NC=C1)C1=C(F)C(N...   \n",
       "NCT02158754                                               None   \n",
       "NCT03538444                                               None   \n",
       "\n",
       "             study_design_info/allocation  \\\n",
       "nctid                                       \n",
       "NCT00618644                           NaN   \n",
       "NCT03943303                    Randomized   \n",
       "NCT01266603                           NaN   \n",
       "NCT01248130                    Randomized   \n",
       "NCT00240214                           NaN   \n",
       "...                                   ...   \n",
       "NCT02121600                Non-Randomized   \n",
       "NCT02478164                           NaN   \n",
       "NCT01978236                    Randomized   \n",
       "NCT02158754                           NaN   \n",
       "NCT03538444                    Randomized   \n",
       "\n",
       "             study_design_info/intervention_model  \\\n",
       "nctid                                               \n",
       "NCT00618644               Single Group Assignment   \n",
       "NCT03943303                   Parallel Assignment   \n",
       "NCT01266603               Single Group Assignment   \n",
       "NCT01248130                   Parallel Assignment   \n",
       "NCT00240214                                   NaN   \n",
       "...                                           ...   \n",
       "NCT02121600                   Parallel Assignment   \n",
       "NCT02478164               Single Group Assignment   \n",
       "NCT01978236               Single Group Assignment   \n",
       "NCT02158754                                   NaN   \n",
       "NCT03538444                   Parallel Assignment   \n",
       "\n",
       "              study_design_info/intervention_model_description  \\\n",
       "nctid                                                            \n",
       "NCT00618644                                                NaN   \n",
       "NCT03943303  The study will be carried out on the beaches o...   \n",
       "NCT01266603                                                NaN   \n",
       "NCT01248130                                                NaN   \n",
       "NCT00240214                                                NaN   \n",
       "...                                                        ...   \n",
       "NCT02121600                                                NaN   \n",
       "NCT02478164                                                NaN   \n",
       "NCT01978236                                                NaN   \n",
       "NCT02158754                                                NaN   \n",
       "NCT03538444  40 individuals (20 per group) will be randomly...   \n",
       "\n",
       "                                     study_design_info/masking  \\\n",
       "nctid                                                            \n",
       "NCT00618644                 Double (Participant, Investigator)   \n",
       "NCT03943303                         Single (Outcomes Assessor)   \n",
       "NCT01266603                                  None (Open Label)   \n",
       "NCT01248130  Triple (Participant, Care Provider, Investigator)   \n",
       "NCT00240214                                                NaN   \n",
       "...                                                        ...   \n",
       "NCT02121600                                  None (Open Label)   \n",
       "NCT02478164                                  None (Open Label)   \n",
       "NCT01978236                                  None (Open Label)   \n",
       "NCT02158754                                                NaN   \n",
       "NCT03538444  Quadruple (Participant, Care Provider, Investi...   \n",
       "\n",
       "            study_design_info/masking_num  \\\n",
       "nctid                                       \n",
       "NCT00618644                           2.0   \n",
       "NCT03943303                           1.0   \n",
       "NCT01266603                           0.0   \n",
       "NCT01248130                           3.0   \n",
       "NCT00240214                           NaN   \n",
       "...                                   ...   \n",
       "NCT02121600                           0.0   \n",
       "NCT02478164                           0.0   \n",
       "NCT01978236                           0.0   \n",
       "NCT02158754                           NaN   \n",
       "NCT03538444                           4.0   \n",
       "\n",
       "            study_design_info/observational_model  \\\n",
       "nctid                                               \n",
       "NCT00618644                                   NaN   \n",
       "NCT03943303                                   NaN   \n",
       "NCT01266603                                   NaN   \n",
       "NCT01248130                                   NaN   \n",
       "NCT00240214                                Cohort   \n",
       "...                                           ...   \n",
       "NCT02121600                                   NaN   \n",
       "NCT02478164                                   NaN   \n",
       "NCT01978236                                   NaN   \n",
       "NCT02158754                          Case-Control   \n",
       "NCT03538444                                   NaN   \n",
       "\n",
       "            study_design_info/primary_purpose  \\\n",
       "nctid                                           \n",
       "NCT00618644                         Treatment   \n",
       "NCT03943303          Health Services Research   \n",
       "NCT01266603                         Treatment   \n",
       "NCT01248130                         Treatment   \n",
       "NCT00240214                               NaN   \n",
       "...                                       ...   \n",
       "NCT02121600                        Diagnostic   \n",
       "NCT02478164                         Treatment   \n",
       "NCT01978236                         Treatment   \n",
       "NCT02158754                               NaN   \n",
       "NCT03538444                         Treatment   \n",
       "\n",
       "            study_design_info/time_perspective      study_type  \n",
       "nctid                                                           \n",
       "NCT00618644                                NaN  Interventional  \n",
       "NCT03943303                                NaN  Interventional  \n",
       "NCT01266603                                NaN  Interventional  \n",
       "NCT01248130                                NaN  Interventional  \n",
       "NCT00240214                        Prospective   Observational  \n",
       "...                                        ...             ...  \n",
       "NCT02121600                                NaN  Interventional  \n",
       "NCT02478164                                NaN  Interventional  \n",
       "NCT01978236                                NaN  Interventional  \n",
       "NCT02158754                      Retrospective   Observational  \n",
       "NCT03538444                                NaN  Interventional  \n",
       "\n",
       "[41369 rows x 49 columns]"
      ]
     },
     "execution_count": 174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "task_name = 'trial-failure-reason-prediction'\n",
    "target = pd.read_csv(f'{task_name}/output.csv', index_col=0)\n",
    "drop_index = []\n",
    "for i in target.index:\n",
    "    if i not in All.index:\n",
    "        drop_index.append(i)\n",
    "        print(i)\n",
    "target = target.drop(drop_index)\n",
    "part = All.loc[target.index]\n",
    "for c in part.columns:\n",
    "    if c == 'icdcode' or c == 'smiless':\n",
    "        continue\n",
    "    if part[c].isnull().sum() == len(part):\n",
    "        print(f'{c} is all null!')\n",
    "        drop_feature.append(c)\n",
    "    if part[c].nunique(dropna=True) == 1:  # 除去缺失值后的所有值一样 即方差为0\n",
    "        print(f'{c} is unique!')\n",
    "        drop_feature.append(c)\n",
    "\n",
    "part = part.drop(drop_feature, axis=1)\n",
    "sorted_columns = sorted(part.columns)\n",
    "part = part.reindex(columns=sorted_columns)\n",
    "part"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(33095, 49) (33095, 1) (8274, 49) (8274, 1)\n"
     ]
    }
   ],
   "source": [
    "strati = StratifiedShuffleSplit(n_splits=1, test_size=0.2, random_state=42)\n",
    "task = 'failure_reason'\n",
    "for train_index, test_index in strati.split(part, target[task]):\n",
    "    train_index = train_index.tolist()\n",
    "    test_index = test_index.tolist()\n",
    "    train_x = part.iloc[train_index]\n",
    "    train_y = target.iloc[train_index]\n",
    "    test_x = part.iloc[test_index]\n",
    "    test_y = target.iloc[test_index]\n",
    "    print(train_x.shape, train_y.shape, test_x.shape, test_y.shape)\n",
    "    train_x.to_csv(f'{task_name}/train_x.csv')\n",
    "    train_y.to_csv(f'{task_name}/train_y.csv')\n",
    "    test_x.to_csv(f'{task_name}/test_x.csv')\n",
    "    test_y.to_csv(f'{task_name}/test_y.csv')\n",
    "    # test_x.iloc[:10].to_csv(f'preview-set/{task_name}_input.csv')\n",
    "    # test_y.iloc[:10].to_csv(f'preview-set/{task_name}_output.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "failure_reason \n",
       "Others             0.529838\n",
       "poor enrollment    0.352893\n",
       "efficacy           0.071491\n",
       "safety             0.045777\n",
       "Name: count, dtype: float64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_y.value_counts()/len(train_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "failure_reason \n",
       "Others             0.529853\n",
       "poor enrollment    0.352913\n",
       "efficacy           0.071429\n",
       "safety             0.045806\n",
       "Name: count, dtype: float64"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_y.value_counts()/len(test_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## trial eligibility criteria design**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "30 5\n"
     ]
    }
   ],
   "source": [
    "features = feature_info[feature_info['trial eligibility criteria design**'] == 'Y'].index\n",
    "targets = feature_info[feature_info['trial eligibility criteria design**'] == '预测任务'].index\n",
    "print(len(features), len(targets))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "has_expanded_access not in selected feature!\n",
      "eligibility/gender not in selected feature!\n",
      "eligibility/healthy_volunteers not in selected feature!\n",
      "patient_data/sharing_ipd not in selected feature!\n",
      "eligibility/minimum_age not in selected feature!\n",
      "eligibility/maximum_age not in selected feature!\n",
      "eligibility/criteria/textblock not in selected feature!\n",
      "location/facility/address/city not in selected feature!\n",
      "enrollment not in selected feature!\n",
      "sponsors/lead_sponsor/agency_class not in selected feature!\n",
      "completion_date{type} not in selected feature!\n",
      "start_date{type} not in selected feature!\n",
      "enrollment{type} not in selected feature!\n",
      "responsible_party/responsible_party_type not in selected feature!\n",
      "biospec_retention not in selected feature!\n",
      "ipd_info_type-Statistical Analysis Plan (SAP) not in selected feature!\n",
      "ipd_info_type-Informed Consent Form (ICF) not in selected feature!\n",
      "ipd_info_type-Study Protocol not in selected feature!\n",
      "ipd_info_type-Clinical Study Report (CSR) not in selected feature!\n",
      "ipd_info_type-Analytic Code not in selected feature!\n",
      "study_design_info/masking_num not in selected feature!\n",
      "MaskingType-Participant not in selected feature!\n",
      "MaskingType-Care Provider not in selected feature!\n",
      "MaskingType-Investigator not in selected feature!\n",
      "MaskingType-Outcomes Assessor not in selected feature!\n",
      "Experimental Arm Number not in selected feature!\n",
      "Active Comparator Arm Number not in selected feature!\n",
      "Placebo Comparator Arm Number not in selected feature!\n",
      "No Intervention Arm Number not in selected feature!\n",
      "Other Arm Number not in selected feature!\n",
      "Sham Comparator Arm Number not in selected feature!\n",
      "Drug intervention Number not in selected feature!\n",
      "Procedure intervention Number not in selected feature!\n",
      "Biological intervention Number not in selected feature!\n",
      "Device intervention Number not in selected feature!\n",
      "Behavioral intervention Number not in selected feature!\n",
      "Other intervention Number not in selected feature!\n",
      "Dietary Supplement intervention Number not in selected feature!\n",
      "Genetic intervention Number not in selected feature!\n",
      "Radiation intervention Number not in selected feature!\n",
      "Diagnostic Test intervention Number not in selected feature!\n",
      "Combination Product intervention Number not in selected feature!\n",
      "location/facility/address/city-GDP not in selected feature!\n",
      "location/facility/address/city-Population not in selected feature!\n",
      "location/facility/address/city-Aging not in selected feature!\n",
      "smiless not in selected feature!\n",
      "4 36\n"
     ]
    }
   ],
   "source": [
    "add_feature = ['intervention/intervention_type', 'intervention/description', 'intervention/intervention_name', 'intervention/other_name', ]\n",
    "for feature in features:\n",
    "    if feature not in All.columns:\n",
    "        add_feature.append(feature)\n",
    "        print(feature, 'not in prepared data!')\n",
    "\n",
    "drop_feature = ['id_info/nct_id',  'number_of_arms', 'oversight_info/is_fda_regulated_drug', 'overall_status', 'eligibility/gender_description',\n",
    "'oversight_info/has_dmc', 'oversight_info/is_fda_regulated_device',  ] # \n",
    "for feature in All.columns:\n",
    "    if feature not in features:\n",
    "        drop_feature.append(feature)\n",
    "        print(feature, 'not in selected feature!')\n",
    "\n",
    "if 'arm_group/arm_group_type' not in drop_feature:\n",
    "    for i in drop_feature:\n",
    "        if 'Arm Number' in i:\n",
    "            drop_feature.remove(i)\n",
    "if 'intervention/intervention_type' not in drop_feature:\n",
    "    for i in drop_feature:\n",
    "        if 'intervention Number' in i:\n",
    "            drop_feature.remove(i)\n",
    "if 'location/facility/address/city' not in drop_feature:\n",
    "    drop_feature.remove('city-GDP')\n",
    "    drop_feature.remove('city-Population')\n",
    "    drop_feature.remove('city-Aging')\n",
    "if 'study_design_info/masking' not in drop_feature:\n",
    "    drop_feature.remove('MaskingType-Participant')\n",
    "    drop_feature.remove('MaskingType-Care Provider')\n",
    "    drop_feature.remove('MaskingType-Investigator')\n",
    "    drop_feature.remove('MaskingType-Outcomes Assessor')\n",
    "    drop_feature.remove('study_design_info/masking_num')\n",
    "if 'patient_data/ipd_info_type' not in drop_feature:\n",
    "    for i in drop_feature:\n",
    "        if 'ipd_info_type-' in i:\n",
    "            drop_feature.remove(i)\n",
    "    \n",
    "print(len(add_feature), len(drop_feature))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns = pd.read_csv('eligibility-criteria-design/test_x.csv', index_col=0).columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Behavioral intervention Number', 'Biological intervention Number',\n",
       "       'Combination Product intervention Number',\n",
       "       'Dietary Supplement intervention Number', 'Drug intervention Number',\n",
       "       'Experimental Arm Number', 'MaskingType-Care Provider',\n",
       "       'MaskingType-Investigator', 'MaskingType-Outcomes Assessor',\n",
       "       'MaskingType-Participant', 'Other Arm Number',\n",
       "       'Placebo Comparator Arm Number', 'Radiation intervention Number',\n",
       "       'biospec_descr/textblock', 'brief_summary/textblock', 'brief_title',\n",
       "       'condition', 'condition_browse/mesh_term',\n",
       "       'detailed_description/textblock', 'eligibility/sampling_method',\n",
       "       'eligibility/study_pop/textblock', 'icdcode',\n",
       "       'intervention/intervention_name', 'intervention/intervention_type',\n",
       "       'intervention_browse/mesh_term', 'ipd_info_type-Analytic Code',\n",
       "       'ipd_info_type-Statistical Analysis Plan (SAP)',\n",
       "       'ipd_info_type-Study Protocol', 'keyword', 'phase',\n",
       "       'study_design_info/allocation', 'study_design_info/intervention_model',\n",
       "       'study_design_info/intervention_model_description',\n",
       "       'study_design_info/masking', 'study_design_info/masking_num',\n",
       "       'study_design_info/observational_model',\n",
       "       'study_design_info/primary_purpose',\n",
       "       'study_design_info/time_perspective', 'study_type'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "eligibility/gender_description\n",
      "intervention/description\n",
      "intervention/other_name\n"
     ]
    }
   ],
   "source": [
    "for c in part.columns:\n",
    "    if c not in columns:\n",
    "        print(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "target = All_Ori[targets]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "只选择Completed部分的数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>eligibility/criteria/textblock</th>\n",
       "      <th>eligibility/gender</th>\n",
       "      <th>eligibility/minimum_age</th>\n",
       "      <th>eligibility/maximum_age</th>\n",
       "      <th>eligibility/healthy_volunteers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NCT00000102</th>\n",
       "      <td>\\n        Inclusion Criteria:\\r\\n\\r\\n         ...</td>\n",
       "      <td>All</td>\n",
       "      <td>14 Years</td>\n",
       "      <td>35 Years</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000107</th>\n",
       "      <td>\\n        Inclusion Criteria:\\r\\n\\r\\n         ...</td>\n",
       "      <td>All</td>\n",
       "      <td>17 Years</td>\n",
       "      <td>60 Years</td>\n",
       "      <td>Accepts Healthy Volunteers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000108</th>\n",
       "      <td>\\n        Inclusion Criteria:\\r\\n\\r\\n         ...</td>\n",
       "      <td>Female</td>\n",
       "      <td>50 Years</td>\n",
       "      <td>65 Years</td>\n",
       "      <td>Accepts Healthy Volunteers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000110</th>\n",
       "      <td>\\n        Inclusion Criteria:\\r\\n\\r\\n         ...</td>\n",
       "      <td>All</td>\n",
       "      <td>18 Years</td>\n",
       "      <td>49 Years</td>\n",
       "      <td>Accepts Healthy Volunteers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000113</th>\n",
       "      <td>\\n        Children between the ages of 6 and 1...</td>\n",
       "      <td>All</td>\n",
       "      <td>6 Years</td>\n",
       "      <td>12 Years</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06263335</th>\n",
       "      <td>\\n        Inclusion Criteria:\\r\\n\\r\\n         ...</td>\n",
       "      <td>All</td>\n",
       "      <td>18 Years</td>\n",
       "      <td>24 Years</td>\n",
       "      <td>Accepts Healthy Volunteers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06263686</th>\n",
       "      <td>\\n        Inclusion criteria\\r\\n\\r\\n          ...</td>\n",
       "      <td>All</td>\n",
       "      <td>20 Years</td>\n",
       "      <td>70 Years</td>\n",
       "      <td>Accepts Healthy Volunteers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06263725</th>\n",
       "      <td>\\n        Inclusion Criteria:\\r\\n\\r\\n         ...</td>\n",
       "      <td>Male</td>\n",
       "      <td>25 Years</td>\n",
       "      <td>45 Years</td>\n",
       "      <td>Accepts Healthy Volunteers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264089</th>\n",
       "      <td>\\n        Inclusion Criteria:\\r\\n\\r\\n         ...</td>\n",
       "      <td>All</td>\n",
       "      <td>18 Years</td>\n",
       "      <td>65 Years</td>\n",
       "      <td>Accepts Healthy Volunteers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264206</th>\n",
       "      <td>\\n        Inclusion Criteria:\\r\\n\\r\\n         ...</td>\n",
       "      <td>Female</td>\n",
       "      <td>18 Years</td>\n",
       "      <td>49 Years</td>\n",
       "      <td>Accepts Healthy Volunteers</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>136443 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                eligibility/criteria/textblock  \\\n",
       "NCT00000102  \\n        Inclusion Criteria:\\r\\n\\r\\n         ...   \n",
       "NCT00000107  \\n        Inclusion Criteria:\\r\\n\\r\\n         ...   \n",
       "NCT00000108  \\n        Inclusion Criteria:\\r\\n\\r\\n         ...   \n",
       "NCT00000110  \\n        Inclusion Criteria:\\r\\n\\r\\n         ...   \n",
       "NCT00000113  \\n        Children between the ages of 6 and 1...   \n",
       "...                                                        ...   \n",
       "NCT06263335  \\n        Inclusion Criteria:\\r\\n\\r\\n         ...   \n",
       "NCT06263686  \\n        Inclusion criteria\\r\\n\\r\\n          ...   \n",
       "NCT06263725  \\n        Inclusion Criteria:\\r\\n\\r\\n         ...   \n",
       "NCT06264089  \\n        Inclusion Criteria:\\r\\n\\r\\n         ...   \n",
       "NCT06264206  \\n        Inclusion Criteria:\\r\\n\\r\\n         ...   \n",
       "\n",
       "            eligibility/gender eligibility/minimum_age  \\\n",
       "NCT00000102                All                14 Years   \n",
       "NCT00000107                All                17 Years   \n",
       "NCT00000108             Female                50 Years   \n",
       "NCT00000110                All                18 Years   \n",
       "NCT00000113                All                 6 Years   \n",
       "...                        ...                     ...   \n",
       "NCT06263335                All                18 Years   \n",
       "NCT06263686                All                20 Years   \n",
       "NCT06263725               Male                25 Years   \n",
       "NCT06264089                All                18 Years   \n",
       "NCT06264206             Female                18 Years   \n",
       "\n",
       "            eligibility/maximum_age eligibility/healthy_volunteers  \n",
       "NCT00000102                35 Years                             No  \n",
       "NCT00000107                60 Years     Accepts Healthy Volunteers  \n",
       "NCT00000108                65 Years     Accepts Healthy Volunteers  \n",
       "NCT00000110                49 Years     Accepts Healthy Volunteers  \n",
       "NCT00000113                12 Years                             No  \n",
       "...                             ...                            ...  \n",
       "NCT06263335                24 Years     Accepts Healthy Volunteers  \n",
       "NCT06263686                70 Years     Accepts Healthy Volunteers  \n",
       "NCT06263725                45 Years     Accepts Healthy Volunteers  \n",
       "NCT06264089                65 Years     Accepts Healthy Volunteers  \n",
       "NCT06264206                49 Years     Accepts Healthy Volunteers  \n",
       "\n",
       "[136443 rows x 5 columns]"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target = target[All_Ori['overall_status'] == 'Completed'].dropna()\n",
    "target"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "target 是否要dropna 还是只需要文本dropna就可以？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(target.dropna())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "删nan太多的特征 全一样的特征 --> 划分训练测试"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "13 (136443, 66)\n",
      "intervention/intervention_name In the columns!\n",
      "intervention/intervention_type In the columns!\n",
      "(136443, 77)\n",
      "completion_date{type} is unique!\n",
      "start_date{type} is unique!\n",
      "overall_status is unique!\n",
      "eligibility/gender_based is unique!\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Behavioral intervention Number</th>\n",
       "      <th>Biological intervention Number</th>\n",
       "      <th>Combination Product intervention Number</th>\n",
       "      <th>Dietary Supplement intervention Number</th>\n",
       "      <th>Drug intervention Number</th>\n",
       "      <th>Experimental Arm Number</th>\n",
       "      <th>MaskingType-Care Provider</th>\n",
       "      <th>MaskingType-Investigator</th>\n",
       "      <th>MaskingType-Outcomes Assessor</th>\n",
       "      <th>MaskingType-Participant</th>\n",
       "      <th>...</th>\n",
       "      <th>phase</th>\n",
       "      <th>study_design_info/allocation</th>\n",
       "      <th>study_design_info/intervention_model</th>\n",
       "      <th>study_design_info/intervention_model_description</th>\n",
       "      <th>study_design_info/masking</th>\n",
       "      <th>study_design_info/masking_num</th>\n",
       "      <th>study_design_info/observational_model</th>\n",
       "      <th>study_design_info/primary_purpose</th>\n",
       "      <th>study_design_info/time_perspective</th>\n",
       "      <th>study_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NCT00000102</th>\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>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Phase 1/Phase 2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Double</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000107</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>...</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>Case-Control</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Observational</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000108</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Prevention</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000110</th>\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>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000113</th>\n",
       "      <td>0.0</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>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>Phase 3</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Triple (Participant, Investigator, Outcomes As...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06263335</th>\n",
       "      <td>0.0</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06263686</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single (Care Provider)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Basic Science</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06263725</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Basic Science</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264089</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Single Group Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264206</th>\n",
       "      <td>0.0</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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Non-Randomized</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>136443 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Behavioral intervention Number  Biological intervention Number  \\\n",
       "NCT00000102                             0.0                             0.0   \n",
       "NCT00000107                             NaN                             NaN   \n",
       "NCT00000108                             1.0                             0.0   \n",
       "NCT00000110                             0.0                             0.0   \n",
       "NCT00000113                             0.0                             0.0   \n",
       "...                                     ...                             ...   \n",
       "NCT06263335                             0.0                             0.0   \n",
       "NCT06263686                             0.0                             0.0   \n",
       "NCT06263725                             0.0                             0.0   \n",
       "NCT06264089                             0.0                             0.0   \n",
       "NCT06264206                             0.0                             0.0   \n",
       "\n",
       "             Combination Product intervention Number  \\\n",
       "NCT00000102                                      0.0   \n",
       "NCT00000107                                      NaN   \n",
       "NCT00000108                                      0.0   \n",
       "NCT00000110                                      0.0   \n",
       "NCT00000113                                      0.0   \n",
       "...                                              ...   \n",
       "NCT06263335                                      0.0   \n",
       "NCT06263686                                      0.0   \n",
       "NCT06263725                                      0.0   \n",
       "NCT06264089                                      0.0   \n",
       "NCT06264206                                      0.0   \n",
       "\n",
       "             Dietary Supplement intervention Number  Drug intervention Number  \\\n",
       "NCT00000102                                     0.0                       1.0   \n",
       "NCT00000107                                     NaN                       NaN   \n",
       "NCT00000108                                     0.0                       0.0   \n",
       "NCT00000110                                     0.0                       1.0   \n",
       "NCT00000113                                     0.0                       0.0   \n",
       "...                                             ...                       ...   \n",
       "NCT06263335                                     0.0                       0.0   \n",
       "NCT06263686                                     0.0                       0.0   \n",
       "NCT06263725                                     0.0                       0.0   \n",
       "NCT06264089                                     0.0                       0.0   \n",
       "NCT06264206                                     0.0                       0.0   \n",
       "\n",
       "             Experimental Arm Number  MaskingType-Care Provider  \\\n",
       "NCT00000102                      NaN                        0.0   \n",
       "NCT00000107                      NaN                        NaN   \n",
       "NCT00000108                      NaN                        NaN   \n",
       "NCT00000110                      NaN                        0.0   \n",
       "NCT00000113                      1.0                        0.0   \n",
       "...                              ...                        ...   \n",
       "NCT06263335                      1.0                        0.0   \n",
       "NCT06263686                      3.0                        1.0   \n",
       "NCT06263725                      2.0                        0.0   \n",
       "NCT06264089                      0.0                        0.0   \n",
       "NCT06264206                      1.0                        0.0   \n",
       "\n",
       "             MaskingType-Investigator  MaskingType-Outcomes Assessor  \\\n",
       "NCT00000102                       0.0                            0.0   \n",
       "NCT00000107                       NaN                            NaN   \n",
       "NCT00000108                       NaN                            NaN   \n",
       "NCT00000110                       0.0                            0.0   \n",
       "NCT00000113                       1.0                            1.0   \n",
       "...                               ...                            ...   \n",
       "NCT06263335                       0.0                            0.0   \n",
       "NCT06263686                       0.0                            0.0   \n",
       "NCT06263725                       0.0                            0.0   \n",
       "NCT06264089                       0.0                            0.0   \n",
       "NCT06264206                       0.0                            0.0   \n",
       "\n",
       "             MaskingType-Participant  ...            phase  \\\n",
       "NCT00000102                      0.0  ...  Phase 1/Phase 2   \n",
       "NCT00000107                      NaN  ...              NaN   \n",
       "NCT00000108                      NaN  ...              NaN   \n",
       "NCT00000110                      0.0  ...              NaN   \n",
       "NCT00000113                      1.0  ...          Phase 3   \n",
       "...                              ...  ...              ...   \n",
       "NCT06263335                      0.0  ...              NaN   \n",
       "NCT06263686                      0.0  ...              NaN   \n",
       "NCT06263725                      0.0  ...              NaN   \n",
       "NCT06264089                      0.0  ...              NaN   \n",
       "NCT06264206                      0.0  ...              NaN   \n",
       "\n",
       "             study_design_info/allocation  \\\n",
       "NCT00000102                           NaN   \n",
       "NCT00000107                           NaN   \n",
       "NCT00000108                    Randomized   \n",
       "NCT00000110                           NaN   \n",
       "NCT00000113                    Randomized   \n",
       "...                                   ...   \n",
       "NCT06263335                    Randomized   \n",
       "NCT06263686                    Randomized   \n",
       "NCT06263725                    Randomized   \n",
       "NCT06264089                           NaN   \n",
       "NCT06264206                Non-Randomized   \n",
       "\n",
       "             study_design_info/intervention_model  \\\n",
       "NCT00000102                   Parallel Assignment   \n",
       "NCT00000107                                   NaN   \n",
       "NCT00000108                   Parallel Assignment   \n",
       "NCT00000110                                   NaN   \n",
       "NCT00000113                   Parallel Assignment   \n",
       "...                                           ...   \n",
       "NCT06263335                   Parallel Assignment   \n",
       "NCT06263686                   Parallel Assignment   \n",
       "NCT06263725                   Parallel Assignment   \n",
       "NCT06264089               Single Group Assignment   \n",
       "NCT06264206                   Parallel Assignment   \n",
       "\n",
       "            study_design_info/intervention_model_description  \\\n",
       "NCT00000102                                              NaN   \n",
       "NCT00000107                                              NaN   \n",
       "NCT00000108                                              NaN   \n",
       "NCT00000110                                              NaN   \n",
       "NCT00000113                                              NaN   \n",
       "...                                                      ...   \n",
       "NCT06263335                                              NaN   \n",
       "NCT06263686                                              NaN   \n",
       "NCT06263725                                              NaN   \n",
       "NCT06264089                                              NaN   \n",
       "NCT06264206                                              NaN   \n",
       "\n",
       "                                     study_design_info/masking  \\\n",
       "NCT00000102                                             Double   \n",
       "NCT00000107                                                NaN   \n",
       "NCT00000108                                                NaN   \n",
       "NCT00000110                                             Single   \n",
       "NCT00000113  Triple (Participant, Investigator, Outcomes As...   \n",
       "...                                                        ...   \n",
       "NCT06263335                                  None (Open Label)   \n",
       "NCT06263686                             Single (Care Provider)   \n",
       "NCT06263725                                  None (Open Label)   \n",
       "NCT06264089                                  None (Open Label)   \n",
       "NCT06264206                                  None (Open Label)   \n",
       "\n",
       "            study_design_info/masking_num  \\\n",
       "NCT00000102                           2.0   \n",
       "NCT00000107                           NaN   \n",
       "NCT00000108                           NaN   \n",
       "NCT00000110                           1.0   \n",
       "NCT00000113                           3.0   \n",
       "...                                   ...   \n",
       "NCT06263335                           0.0   \n",
       "NCT06263686                           1.0   \n",
       "NCT06263725                           0.0   \n",
       "NCT06264089                           0.0   \n",
       "NCT06264206                           0.0   \n",
       "\n",
       "            study_design_info/observational_model  \\\n",
       "NCT00000102                                   NaN   \n",
       "NCT00000107                          Case-Control   \n",
       "NCT00000108                                   NaN   \n",
       "NCT00000110                                   NaN   \n",
       "NCT00000113                                   NaN   \n",
       "...                                           ...   \n",
       "NCT06263335                                   NaN   \n",
       "NCT06263686                                   NaN   \n",
       "NCT06263725                                   NaN   \n",
       "NCT06264089                                   NaN   \n",
       "NCT06264206                                   NaN   \n",
       "\n",
       "            study_design_info/primary_purpose  \\\n",
       "NCT00000102                         Treatment   \n",
       "NCT00000107                               NaN   \n",
       "NCT00000108                        Prevention   \n",
       "NCT00000110                         Treatment   \n",
       "NCT00000113                         Treatment   \n",
       "...                                       ...   \n",
       "NCT06263335                         Treatment   \n",
       "NCT06263686                     Basic Science   \n",
       "NCT06263725                     Basic Science   \n",
       "NCT06264089                         Treatment   \n",
       "NCT06264206                         Treatment   \n",
       "\n",
       "            study_design_info/time_perspective      study_type  \n",
       "NCT00000102                                NaN  Interventional  \n",
       "NCT00000107                                NaN   Observational  \n",
       "NCT00000108                                NaN  Interventional  \n",
       "NCT00000110                                NaN  Interventional  \n",
       "NCT00000113                                NaN  Interventional  \n",
       "...                                        ...             ...  \n",
       "NCT06263335                                NaN  Interventional  \n",
       "NCT06263686                                NaN  Interventional  \n",
       "NCT06263725                                NaN  Interventional  \n",
       "NCT06264089                                NaN  Interventional  \n",
       "NCT06264206                                NaN  Interventional  \n",
       "\n",
       "[136443 rows x 41 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "task_name = 'eligibility-criteria-design'\n",
    "drop_index = []\n",
    "for i in target.index:\n",
    "    if i not in All.index:\n",
    "        drop_index.append(i)\n",
    "        print(i)\n",
    "target = target.drop(drop_index)\n",
    "part = All.loc[target.index]\n",
    "print(len(add_feature), part.shape)\n",
    "for c in add_feature:\n",
    "    if c in part.columns:\n",
    "        print(c, 'In the columns!')\n",
    "    else:\n",
    "        part[c] = All_Ori[c].loc[target.index]\n",
    "print(part.shape)\n",
    "for c in part.columns:\n",
    "    if part[c].isnull().sum() == len(part):\n",
    "        print(f'{c} is all null!')\n",
    "        drop_feature.append(c)\n",
    "    if part[c].nunique(dropna=True) == 1:  # 除去缺失值后的所有值一样 即方差为0\n",
    "        print(f'{c} is unique!')\n",
    "        drop_feature.append(c)\n",
    "\n",
    "part = part.drop(drop_feature, axis=1)\n",
    "sorted_columns = sorted(part.columns)\n",
    "part = part.reindex(columns=sorted_columns)\n",
    "part"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(109154, 41) (109154, 5) (27289, 41) (27289, 5)\n"
     ]
    }
   ],
   "source": [
    "part = pd.concat([part, target], axis=1)\n",
    "train_index, test_index = train_test_split(part, test_size=0.2, random_state=42)\n",
    "train_x = train_index.drop(targets, axis=1)\n",
    "train_y = train_index[targets]\n",
    "test_x = test_index.drop(targets, axis=1)\n",
    "test_y = test_index[targets]\n",
    "print(train_x.shape, train_y.shape, test_x.shape, test_y.shape)\n",
    "train_x.to_csv(f'{task_name}/train_x.csv')\n",
    "train_y.to_csv(f'{task_name}/train_y.csv')\n",
    "test_x.to_csv(f'{task_name}/test_x.csv')\n",
    "test_y.to_csv(f'{task_name}/test_y.csv')\n",
    "test_x.iloc[:10].to_csv(f'preview-set/{task_name}_input.csv')\n",
    "test_y.iloc[:10].to_csv(f'preview-set/{task_name}_output.csv')\n",
    "part = part.drop(targets, axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## description-summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>detailed_description</th>\n",
       "      <th>brief_summary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NCT00000102</th>\n",
       "      <td>\\n      This protocol is designed to assess bo...</td>\n",
       "      <td>\\n      This study will test the ability of ex...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000105</th>\n",
       "      <td>\\n      Patients will receive each vaccine onc...</td>\n",
       "      <td>\\n      The purpose of this study is to learn ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000113</th>\n",
       "      <td>\\n      Myopia (nearsightedness) is an importa...</td>\n",
       "      <td>\\n      To evaluate whether progressive additi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000114</th>\n",
       "      <td>\\n      Retinitis pigmentosa (RP) is a group o...</td>\n",
       "      <td>\\n      To determine whether supplements of vi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000115</th>\n",
       "      <td>\\n      Uveitis, an intraocular inflammatory d...</td>\n",
       "      <td>\\n      To test the efficacy of acetazolamide ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264258</th>\n",
       "      <td>\\n      Youth with T1D who comply with inclusi...</td>\n",
       "      <td>\\n      The goal of this study is to evaluate ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264271</th>\n",
       "      <td>\\n      Education on carbohydrate counting and...</td>\n",
       "      <td>\\n      The study aims to elucidate whether pa...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264310</th>\n",
       "      <td>\\n      This is a Phase 2, Double-Blind, Place...</td>\n",
       "      <td>\\n      This Study Aims to Evaluate the Safety...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264323</th>\n",
       "      <td>\\n      QUALITY ASSURANCE PLAN:\\r\\n\\r\\n      M...</td>\n",
       "      <td>\\n      A prospective cohort study with 9 mont...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264336</th>\n",
       "      <td>\\n      Multiple sclerosis (MS) is an immune-m...</td>\n",
       "      <td>\\n      Nearly 1 million individuals in the Un...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>326273 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          detailed_description  \\\n",
       "NCT00000102  \\n      This protocol is designed to assess bo...   \n",
       "NCT00000105  \\n      Patients will receive each vaccine onc...   \n",
       "NCT00000113  \\n      Myopia (nearsightedness) is an importa...   \n",
       "NCT00000114  \\n      Retinitis pigmentosa (RP) is a group o...   \n",
       "NCT00000115  \\n      Uveitis, an intraocular inflammatory d...   \n",
       "...                                                        ...   \n",
       "NCT06264258  \\n      Youth with T1D who comply with inclusi...   \n",
       "NCT06264271  \\n      Education on carbohydrate counting and...   \n",
       "NCT06264310  \\n      This is a Phase 2, Double-Blind, Place...   \n",
       "NCT06264323  \\n      QUALITY ASSURANCE PLAN:\\r\\n\\r\\n      M...   \n",
       "NCT06264336  \\n      Multiple sclerosis (MS) is an immune-m...   \n",
       "\n",
       "                                                 brief_summary  \n",
       "NCT00000102  \\n      This study will test the ability of ex...  \n",
       "NCT00000105  \\n      The purpose of this study is to learn ...  \n",
       "NCT00000113  \\n      To evaluate whether progressive additi...  \n",
       "NCT00000114  \\n      To determine whether supplements of vi...  \n",
       "NCT00000115  \\n      To test the efficacy of acetazolamide ...  \n",
       "...                                                        ...  \n",
       "NCT06264258  \\n      The goal of this study is to evaluate ...  \n",
       "NCT06264271  \\n      The study aims to elucidate whether pa...  \n",
       "NCT06264310  \\n      This Study Aims to Evaluate the Safety...  \n",
       "NCT06264323  \\n      A prospective cohort study with 9 mont...  \n",
       "NCT06264336  \\n      Nearly 1 million individuals in the Un...  \n",
       "\n",
       "[326273 rows x 2 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "description_summary = All_Ori[['detailed_description/textblock', 'brief_summary/textblock']].dropna()\n",
    "description_summary.rename(columns={'detailed_description/textblock': 'detailed_description', 'brief_summary/textblock': 'brief_summary'}, inplace=True)\n",
    "description_summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Set: 261018 Test Set: 65255\n"
     ]
    }
   ],
   "source": [
    "train_set, test_set = train_test_split(description_summary, test_size=0.2, random_state=99)\n",
    "print(f'Train Set: {len(train_set)} Test Set: {len(test_set)}')\n",
    "train_set.to_csv('description-summary/train.csv')\n",
    "test_set.to_csv('description-summary/test.csv')\n",
    "test_set.iloc[:10].to_csv(f'preview-set/description-summary.csv')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## drug repurposing (in generator_target.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## drug dose "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['required_header/download_date', 'required_header/link_text',\n",
      "       'required_header/url', 'id_info/org_study_id', 'id_info/secondary_id',\n",
      "       'id_info/nct_id', 'brief_title', 'sponsors/lead_sponsor/agency',\n",
      "       'sponsors/lead_sponsor/agency_class', 'source',\n",
      "       ...\n",
      "       'expanded_access_info/expanded_access_type_intermediate',\n",
      "       'expanded_access_info/expanded_access_type_treatment',\n",
      "       'oversight_info/is_unapproved_device',\n",
      "       'clinical_results/outcome_list/outcome/analysis_list/analysis/ci_upper_limit_na_comment',\n",
      "       'expanded_access_info/expanded_access_type_individual',\n",
      "       'clinical_results/baseline/measure_list/measure/analyzed_list/analyzed/units',\n",
      "       'clinical_results/baseline/measure_list/measure/analyzed_list/analyzed/scope',\n",
      "       'clinical_results/baseline/measure_list/measure/analyzed_list/analyzed/count_list/count{group_id}',\n",
      "       'clinical_results/baseline/measure_list/measure/analyzed_list/analyzed/count_list/count{value}',\n",
      "       'oversight_info/is_ppsd'],\n",
      "      dtype='object', length=291)\n"
     ]
    }
   ],
   "source": [
    "print(All_Ori.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>phase</th>\n",
       "      <th>study_type</th>\n",
       "      <th>has_expanded_access</th>\n",
       "      <th>study_design_info/intervention_model</th>\n",
       "      <th>study_design_info/primary_purpose</th>\n",
       "      <th>eligibility/gender</th>\n",
       "      <th>eligibility/healthy_volunteers</th>\n",
       "      <th>oversight_info/has_dmc</th>\n",
       "      <th>study_design_info/allocation</th>\n",
       "      <th>patient_data/sharing_ipd</th>\n",
       "      <th>...</th>\n",
       "      <th>smiless</th>\n",
       "      <th>detailed_description/textblock</th>\n",
       "      <th>overall_status</th>\n",
       "      <th>study_design_info/masking</th>\n",
       "      <th>intervention/intervention_type</th>\n",
       "      <th>biospec_descr/textblock</th>\n",
       "      <th>eligibility/study_pop/textblock</th>\n",
       "      <th>study_design_info/intervention_model_description</th>\n",
       "      <th>eligibility/gender_based</th>\n",
       "      <th>eligibility/gender_description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NCT00000102</th>\n",
       "      <td>Phase 1/Phase 2</td>\n",
       "      <td>Interventional</td>\n",
       "      <td>No</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>All</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>\\n      This protocol is designed to assess bo...</td>\n",
       "      <td>Completed</td>\n",
       "      <td>Double</td>\n",
       "      <td>Drug</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000104</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Observational</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Female</td>\n",
       "      <td>Accepts Healthy Volunteers</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Completed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Procedure</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000105</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Observational</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All</td>\n",
       "      <td>Accepts Healthy Volunteers</td>\n",
       "      <td>Yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>\\n      Patients will receive each vaccine onc...</td>\n",
       "      <td>Terminated</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['Biological', 'Biological', 'Drug', 'Biologic...</td>\n",
       "      <td>\\n      analysis of blood samples before and 4...</td>\n",
       "      <td>\\n        -  Normal volunteers\\r\\n\\r\\n        ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000106</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "      <td>No</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>All</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unknown status</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Device</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000107</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Observational</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All</td>\n",
       "      <td>Accepts Healthy Volunteers</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Completed</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264297</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "      <td>No</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>All</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Undecided</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Recruiting</td>\n",
       "      <td>Triple (Participant, Care Provider, Investigator)</td>\n",
       "      <td>Procedure</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264310</th>\n",
       "      <td>Phase 2</td>\n",
       "      <td>Interventional</td>\n",
       "      <td>No</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>All</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>\\n      This is a Phase 2, Double-Blind, Place...</td>\n",
       "      <td>Not yet recruiting</td>\n",
       "      <td>Triple (Participant, Care Provider, Investigator)</td>\n",
       "      <td>['Drug', 'Drug']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Patients will be randomly assigned to one of f...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264323</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Observational</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All</td>\n",
       "      <td>Accepts Healthy Volunteers</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>\\n      QUALITY ASSURANCE PLAN:\\r\\n\\r\\n      M...</td>\n",
       "      <td>Completed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>\\n        Boxers training at one of seven boxi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264336</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "      <td>No</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>Treatment</td>\n",
       "      <td>All</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Randomized</td>\n",
       "      <td>Undecided</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>\\n      Multiple sclerosis (MS) is an immune-m...</td>\n",
       "      <td>Not yet recruiting</td>\n",
       "      <td>Single (Outcomes Assessor)</td>\n",
       "      <td>Behavioral</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264349</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Interventional</td>\n",
       "      <td>No</td>\n",
       "      <td>Parallel Assignment</td>\n",
       "      <td>Prevention</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Non-Randomized</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Not yet recruiting</td>\n",
       "      <td>None (Open Label)</td>\n",
       "      <td>Other</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Quasi-experimental - controlled, non-randomize...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Pregnant women (first trimester)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>483239 rows × 76 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       phase      study_type has_expanded_access  \\\n",
       "NCT00000102  Phase 1/Phase 2  Interventional                  No   \n",
       "NCT00000104              NaN   Observational                  No   \n",
       "NCT00000105              NaN   Observational                  No   \n",
       "NCT00000106              NaN  Interventional                  No   \n",
       "NCT00000107              NaN   Observational                  No   \n",
       "...                      ...             ...                 ...   \n",
       "NCT06264297              NaN  Interventional                  No   \n",
       "NCT06264310          Phase 2  Interventional                  No   \n",
       "NCT06264323              NaN   Observational                  No   \n",
       "NCT06264336              NaN  Interventional                  No   \n",
       "NCT06264349              NaN  Interventional                  No   \n",
       "\n",
       "            study_design_info/intervention_model  \\\n",
       "NCT00000102                  Parallel Assignment   \n",
       "NCT00000104                                  NaN   \n",
       "NCT00000105                                  NaN   \n",
       "NCT00000106                  Parallel Assignment   \n",
       "NCT00000107                                  NaN   \n",
       "...                                          ...   \n",
       "NCT06264297                  Parallel Assignment   \n",
       "NCT06264310                  Parallel Assignment   \n",
       "NCT06264323                                  NaN   \n",
       "NCT06264336                  Parallel Assignment   \n",
       "NCT06264349                  Parallel Assignment   \n",
       "\n",
       "            study_design_info/primary_purpose eligibility/gender  \\\n",
       "NCT00000102                         Treatment                All   \n",
       "NCT00000104                               NaN             Female   \n",
       "NCT00000105                               NaN                All   \n",
       "NCT00000106                         Treatment                All   \n",
       "NCT00000107                               NaN                All   \n",
       "...                                       ...                ...   \n",
       "NCT06264297                         Treatment                All   \n",
       "NCT06264310                         Treatment                All   \n",
       "NCT06264323                               NaN                All   \n",
       "NCT06264336                         Treatment                All   \n",
       "NCT06264349                        Prevention             Female   \n",
       "\n",
       "            eligibility/healthy_volunteers oversight_info/has_dmc  \\\n",
       "NCT00000102                             No                    NaN   \n",
       "NCT00000104     Accepts Healthy Volunteers                    NaN   \n",
       "NCT00000105     Accepts Healthy Volunteers                    Yes   \n",
       "NCT00000106                             No                    NaN   \n",
       "NCT00000107     Accepts Healthy Volunteers                    NaN   \n",
       "...                                    ...                    ...   \n",
       "NCT06264297                             No                     No   \n",
       "NCT06264310                             No                    Yes   \n",
       "NCT06264323     Accepts Healthy Volunteers                     No   \n",
       "NCT06264336                             No                     No   \n",
       "NCT06264349                             No                     No   \n",
       "\n",
       "            study_design_info/allocation patient_data/sharing_ipd  ...  \\\n",
       "NCT00000102                          NaN                      NaN  ...   \n",
       "NCT00000104                          NaN                      NaN  ...   \n",
       "NCT00000105                          NaN                      NaN  ...   \n",
       "NCT00000106                   Randomized                      NaN  ...   \n",
       "NCT00000107                          NaN                      NaN  ...   \n",
       "...                                  ...                      ...  ...   \n",
       "NCT06264297                   Randomized                Undecided  ...   \n",
       "NCT06264310                   Randomized                       No  ...   \n",
       "NCT06264323                          NaN                       No  ...   \n",
       "NCT06264336                   Randomized                Undecided  ...   \n",
       "NCT06264349               Non-Randomized                       No  ...   \n",
       "\n",
       "            smiless                     detailed_description/textblock  \\\n",
       "NCT00000102    None  \\n      This protocol is designed to assess bo...   \n",
       "NCT00000104    None                                                NaN   \n",
       "NCT00000105    None  \\n      Patients will receive each vaccine onc...   \n",
       "NCT00000106    None                                                NaN   \n",
       "NCT00000107    None                                                NaN   \n",
       "...             ...                                                ...   \n",
       "NCT06264297    None                                                NaN   \n",
       "NCT06264310    None  \\n      This is a Phase 2, Double-Blind, Place...   \n",
       "NCT06264323    None  \\n      QUALITY ASSURANCE PLAN:\\r\\n\\r\\n      M...   \n",
       "NCT06264336    None  \\n      Multiple sclerosis (MS) is an immune-m...   \n",
       "NCT06264349    None                                                NaN   \n",
       "\n",
       "                 overall_status  \\\n",
       "NCT00000102           Completed   \n",
       "NCT00000104           Completed   \n",
       "NCT00000105          Terminated   \n",
       "NCT00000106      Unknown status   \n",
       "NCT00000107           Completed   \n",
       "...                         ...   \n",
       "NCT06264297          Recruiting   \n",
       "NCT06264310  Not yet recruiting   \n",
       "NCT06264323           Completed   \n",
       "NCT06264336  Not yet recruiting   \n",
       "NCT06264349  Not yet recruiting   \n",
       "\n",
       "                                     study_design_info/masking  \\\n",
       "NCT00000102                                             Double   \n",
       "NCT00000104                                                NaN   \n",
       "NCT00000105                                                NaN   \n",
       "NCT00000106                                                NaN   \n",
       "NCT00000107                                                NaN   \n",
       "...                                                        ...   \n",
       "NCT06264297  Triple (Participant, Care Provider, Investigator)   \n",
       "NCT06264310  Triple (Participant, Care Provider, Investigator)   \n",
       "NCT06264323                                                NaN   \n",
       "NCT06264336                         Single (Outcomes Assessor)   \n",
       "NCT06264349                                  None (Open Label)   \n",
       "\n",
       "                                intervention/intervention_type  \\\n",
       "NCT00000102                                               Drug   \n",
       "NCT00000104                                          Procedure   \n",
       "NCT00000105  ['Biological', 'Biological', 'Drug', 'Biologic...   \n",
       "NCT00000106                                             Device   \n",
       "NCT00000107                                                NaN   \n",
       "...                                                        ...   \n",
       "NCT06264297                                          Procedure   \n",
       "NCT06264310                                   ['Drug', 'Drug']   \n",
       "NCT06264323                                                NaN   \n",
       "NCT06264336                                         Behavioral   \n",
       "NCT06264349                                              Other   \n",
       "\n",
       "                                       biospec_descr/textblock  \\\n",
       "NCT00000102                                                NaN   \n",
       "NCT00000104                                                NaN   \n",
       "NCT00000105  \\n      analysis of blood samples before and 4...   \n",
       "NCT00000106                                                NaN   \n",
       "NCT00000107                                                NaN   \n",
       "...                                                        ...   \n",
       "NCT06264297                                                NaN   \n",
       "NCT06264310                                                NaN   \n",
       "NCT06264323                                                NaN   \n",
       "NCT06264336                                                NaN   \n",
       "NCT06264349                                                NaN   \n",
       "\n",
       "                               eligibility/study_pop/textblock  \\\n",
       "NCT00000102                                                NaN   \n",
       "NCT00000104                                                NaN   \n",
       "NCT00000105  \\n        -  Normal volunteers\\r\\n\\r\\n        ...   \n",
       "NCT00000106                                                NaN   \n",
       "NCT00000107                                                NaN   \n",
       "...                                                        ...   \n",
       "NCT06264297                                                NaN   \n",
       "NCT06264310                                                NaN   \n",
       "NCT06264323  \\n        Boxers training at one of seven boxi...   \n",
       "NCT06264336                                                NaN   \n",
       "NCT06264349                                                NaN   \n",
       "\n",
       "              study_design_info/intervention_model_description  \\\n",
       "NCT00000102                                                NaN   \n",
       "NCT00000104                                                NaN   \n",
       "NCT00000105                                                NaN   \n",
       "NCT00000106                                                NaN   \n",
       "NCT00000107                                                NaN   \n",
       "...                                                        ...   \n",
       "NCT06264297                                                NaN   \n",
       "NCT06264310  Patients will be randomly assigned to one of f...   \n",
       "NCT06264323                                                NaN   \n",
       "NCT06264336                                                NaN   \n",
       "NCT06264349  Quasi-experimental - controlled, non-randomize...   \n",
       "\n",
       "            eligibility/gender_based    eligibility/gender_description  \n",
       "NCT00000102                      NaN                               NaN  \n",
       "NCT00000104                      NaN                               NaN  \n",
       "NCT00000105                      NaN                               NaN  \n",
       "NCT00000106                      NaN                               NaN  \n",
       "NCT00000107                      NaN                               NaN  \n",
       "...                              ...                               ...  \n",
       "NCT06264297                      NaN                               NaN  \n",
       "NCT06264310                      NaN                               NaN  \n",
       "NCT06264323                      NaN                               NaN  \n",
       "NCT06264336                      NaN                               NaN  \n",
       "NCT06264349                      Yes  Pregnant women (first trimester)  \n",
       "\n",
       "[483239 rows x 76 columns]"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw = pd.read_csv('raw_data.csv', index_col=0)\n",
    "All"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "label是GPT处理来的 详细内容在gpt_dose.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GPT</th>\n",
       "      <th>values</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nctid</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NCT00000271</th>\n",
       "      <td>- The dosage is 300 mg/day.\\n- None</td>\n",
       "      <td>[300.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000304</th>\n",
       "      <td>- The dosage is 75 mg/day.\\n- The dosage is 12...</td>\n",
       "      <td>[75.0, 120.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000308</th>\n",
       "      <td>1. The maximum dosage mentioned is 30 mg.\\n- T...</td>\n",
       "      <td>[30.0, 60.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000317</th>\n",
       "      <td>- Placebo plus relapse prevention counseling:\\...</td>\n",
       "      <td>[0.0, 4.0, 4.0, 4.0, 4.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000392</th>\n",
       "      <td>- Peptide T group: The dosage is 6 mg/day.\\n- ...</td>\n",
       "      <td>[6.0, 6.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06260072</th>\n",
       "      <td>- \"The dosage is 800 mg/day.\"\\n- \"None\"</td>\n",
       "      <td>[800.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06260891</th>\n",
       "      <td>- \"The dosage is 40 mg/day.\"</td>\n",
       "      <td>[40.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06261125</th>\n",
       "      <td>- The dosage is 12 mg/day.\\n- The dosage is 12...</td>\n",
       "      <td>[12.0, 12.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06263543</th>\n",
       "      <td>- The dosage is 1200 mg/day.</td>\n",
       "      <td>[1200.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264310</th>\n",
       "      <td>- \"The dosage is None.\"\\n- \"The dosage is 5.0 ...</td>\n",
       "      <td>[5.0, 7.5, 10.0]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13320 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                           GPT  \\\n",
       "nctid                                                            \n",
       "NCT00000271                - The dosage is 300 mg/day.\\n- None   \n",
       "NCT00000304  - The dosage is 75 mg/day.\\n- The dosage is 12...   \n",
       "NCT00000308  1. The maximum dosage mentioned is 30 mg.\\n- T...   \n",
       "NCT00000317  - Placebo plus relapse prevention counseling:\\...   \n",
       "NCT00000392  - Peptide T group: The dosage is 6 mg/day.\\n- ...   \n",
       "...                                                        ...   \n",
       "NCT06260072            - \"The dosage is 800 mg/day.\"\\n- \"None\"   \n",
       "NCT06260891                       - \"The dosage is 40 mg/day.\"   \n",
       "NCT06261125  - The dosage is 12 mg/day.\\n- The dosage is 12...   \n",
       "NCT06263543                       - The dosage is 1200 mg/day.   \n",
       "NCT06264310  - \"The dosage is None.\"\\n- \"The dosage is 5.0 ...   \n",
       "\n",
       "                                values  \n",
       "nctid                                   \n",
       "NCT00000271                    [300.0]  \n",
       "NCT00000304              [75.0, 120.0]  \n",
       "NCT00000308               [30.0, 60.0]  \n",
       "NCT00000317  [0.0, 4.0, 4.0, 4.0, 4.0]  \n",
       "NCT00000392                 [6.0, 6.0]  \n",
       "...                                ...  \n",
       "NCT06260072                    [800.0]  \n",
       "NCT06260891                     [40.0]  \n",
       "NCT06261125               [12.0, 12.0]  \n",
       "NCT06263543                   [1200.0]  \n",
       "NCT06264310           [5.0, 7.5, 10.0]  \n",
       "\n",
       "[13320 rows x 2 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dose = pd.read_csv('drug-dose-prediction/dose_label.csv', index_col=0)\n",
    "def get_num(x):\n",
    "    matchs = re.findall(r\"(\\d+\\.?\\d*)\\s*mg/day\",x)\n",
    "    \n",
    "    if len(matchs) >= 1:\n",
    "        matchs = [float(i) for i in matchs]\n",
    "        return matchs\n",
    "    return None\n",
    "\n",
    "def mg_select(value):\n",
    "    if type(value) == str:\n",
    "        if 'mg/day' in value:\n",
    "            # print(get_num(value))\n",
    "            return get_num(value)\n",
    "        else:\n",
    "            return None\n",
    "    elif type(value) == list:\n",
    "        lis = []\n",
    "        for i in value:\n",
    "            if 'mg/day' in i:\n",
    "                lis.extend(get_num(i))\n",
    "        if len(lis) > 0:\n",
    "            # print(lis)\n",
    "            return lis\n",
    "        else:\n",
    "            return None\n",
    "    return None\n",
    "\n",
    "dose['values'] = dose['GPT'].apply(mg_select)\n",
    "dose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "最大、最小、平均值 全部取log10后四舍五入取整"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_599252/1748578579.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dose['Max'] = dose['values'].apply(lambda x: round(math.log(max(x), 10)) if max(x) > 0 else 0)\n",
      "/tmp/ipykernel_599252/1748578579.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dose['Min'] = dose['values'].apply(lambda x: round(math.log(min(x), 10)) if min(x) > 0 else 0)\n",
      "/tmp/ipykernel_599252/1748578579.py:4: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dose['Avg'] = dose['values'].apply(lambda x: round(math.log(sum(x)/len(x), 10)) if len(x) != 0 and sum(x)>0 else 0)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GPT</th>\n",
       "      <th>values</th>\n",
       "      <th>Max</th>\n",
       "      <th>Min</th>\n",
       "      <th>Avg</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nctid</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>NCT00000271</th>\n",
       "      <td>- The dosage is 300 mg/day.\\n- None</td>\n",
       "      <td>[300.0]</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000304</th>\n",
       "      <td>- The dosage is 75 mg/day.\\n- The dosage is 12...</td>\n",
       "      <td>[75.0, 120.0]</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000308</th>\n",
       "      <td>1. The maximum dosage mentioned is 30 mg.\\n- T...</td>\n",
       "      <td>[30.0, 60.0]</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000317</th>\n",
       "      <td>- Placebo plus relapse prevention counseling:\\...</td>\n",
       "      <td>[0.0, 4.0, 4.0, 4.0, 4.0]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000392</th>\n",
       "      <td>- Peptide T group: The dosage is 6 mg/day.\\n- ...</td>\n",
       "      <td>[6.0, 6.0]</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06260072</th>\n",
       "      <td>- \"The dosage is 800 mg/day.\"\\n- \"None\"</td>\n",
       "      <td>[800.0]</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06260891</th>\n",
       "      <td>- \"The dosage is 40 mg/day.\"</td>\n",
       "      <td>[40.0]</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06261125</th>\n",
       "      <td>- The dosage is 12 mg/day.\\n- The dosage is 12...</td>\n",
       "      <td>[12.0, 12.0]</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06263543</th>\n",
       "      <td>- The dosage is 1200 mg/day.</td>\n",
       "      <td>[1200.0]</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264310</th>\n",
       "      <td>- \"The dosage is None.\"\\n- \"The dosage is 5.0 ...</td>\n",
       "      <td>[5.0, 7.5, 10.0]</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12790 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                           GPT  \\\n",
       "nctid                                                            \n",
       "NCT00000271                - The dosage is 300 mg/day.\\n- None   \n",
       "NCT00000304  - The dosage is 75 mg/day.\\n- The dosage is 12...   \n",
       "NCT00000308  1. The maximum dosage mentioned is 30 mg.\\n- T...   \n",
       "NCT00000317  - Placebo plus relapse prevention counseling:\\...   \n",
       "NCT00000392  - Peptide T group: The dosage is 6 mg/day.\\n- ...   \n",
       "...                                                        ...   \n",
       "NCT06260072            - \"The dosage is 800 mg/day.\"\\n- \"None\"   \n",
       "NCT06260891                       - \"The dosage is 40 mg/day.\"   \n",
       "NCT06261125  - The dosage is 12 mg/day.\\n- The dosage is 12...   \n",
       "NCT06263543                       - The dosage is 1200 mg/day.   \n",
       "NCT06264310  - \"The dosage is None.\"\\n- \"The dosage is 5.0 ...   \n",
       "\n",
       "                                values  Max  Min  Avg  \n",
       "nctid                                                  \n",
       "NCT00000271                    [300.0]    2    2    2  \n",
       "NCT00000304              [75.0, 120.0]    2    2    2  \n",
       "NCT00000308               [30.0, 60.0]    2    1    2  \n",
       "NCT00000317  [0.0, 4.0, 4.0, 4.0, 4.0]    1    0    1  \n",
       "NCT00000392                 [6.0, 6.0]    1    1    1  \n",
       "...                                ...  ...  ...  ...  \n",
       "NCT06260072                    [800.0]    3    3    3  \n",
       "NCT06260891                     [40.0]    2    2    2  \n",
       "NCT06261125               [12.0, 12.0]    1    1    1  \n",
       "NCT06263543                   [1200.0]    3    3    3  \n",
       "NCT06264310           [5.0, 7.5, 10.0]    1    1    1  \n",
       "\n",
       "[12790 rows x 5 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dose = dose.dropna()\n",
    "dose['Max'] = dose['values'].apply(lambda x: round(math.log(max(x), 10)) if max(x) > 0 else 0)\n",
    "dose['Min'] = dose['values'].apply(lambda x: round(math.log(min(x), 10)) if min(x) > 0 else 0)\n",
    "dose['Avg'] = dose['values'].apply(lambda x: round(math.log(sum(x)/len(x), 10)) if len(x) != 0 and sum(x)>0 else 0)\n",
    "dose"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "大于3的全部分为3，小于0的算到0， 变成四分类任务"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Avg\n",
       "2    5451\n",
       "3    4232\n",
       "1    2366\n",
       "0     741\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def avg2map(x):\n",
    "    if x >=3:\n",
    "        return 3\n",
    "    elif x <=0:\n",
    "        return 0\n",
    "    else:\n",
    "        return x\n",
    "    \n",
    "dose['Avg'].apply(avg2map).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_599252/1950419342.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  dose['Avg'] = dose['Avg'].apply(avg2map)\n"
     ]
    }
   ],
   "source": [
    "dose['Avg'] = dose['Avg'].apply(avg2map)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Max\n",
       " 2    5148\n",
       " 3    4501\n",
       " 1    2190\n",
       " 0     623\n",
       " 4     277\n",
       "-1      44\n",
       " 5       5\n",
       "-2       2\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dose['Max'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Min\n",
       " 2    5179\n",
       " 3    3190\n",
       " 1    2972\n",
       " 0    1141\n",
       "-1     150\n",
       " 4     143\n",
       "-2      10\n",
       " 5       4\n",
       "-3       1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dose['Min'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_avg(x):\n",
    "    return sum(x)/len(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th {\n",
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       "    }\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>Avg</th>\n",
       "      <th>Max</th>\n",
       "      <th>Min</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nctid</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NCT00000271</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000304</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000308</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000317</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000392</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06260072</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06260891</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06261125</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06263543</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264310</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12790 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Avg  Max  Min\n",
       "nctid                     \n",
       "NCT00000271    2    2    2\n",
       "NCT00000304    2    2    2\n",
       "NCT00000308    2    2    1\n",
       "NCT00000317    1    1    0\n",
       "NCT00000392    1    1    1\n",
       "...          ...  ...  ...\n",
       "NCT06260072    3    3    3\n",
       "NCT06260891    2    2    2\n",
       "NCT06261125    1    1    1\n",
       "NCT06263543    3    3    3\n",
       "NCT06264310    1    1    1\n",
       "\n",
       "[12790 rows x 3 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target = dose[['Avg', 'Max', 'Min']]\n",
    "target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>smiless</th>\n",
       "      <th>intervention_browse/mesh_term</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nctid</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NCT00000271</th>\n",
       "      <td>['CNCCCN1C2=CC=CC=C2CCC2=CC=CC=C12']</td>\n",
       "      <td>Desipramine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000304</th>\n",
       "      <td>['C[C@H](N)CC1=CC=CC=C1', 'C[C@H](N)CC1=CC=CC=...</td>\n",
       "      <td>['Amphetamine', 'Dextroamphetamine']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000308</th>\n",
       "      <td>['C[C@H](N)CC1=CC=CC=C1', 'C[C@H](N)CC1=CC=CC=...</td>\n",
       "      <td>['Amphetamine', 'Dextroamphetamine']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000317</th>\n",
       "      <td>['CC1=C(CCN2CCC(CC2)C2=NOC3=C2C=CC(F)=C3)C(=O)...</td>\n",
       "      <td>Risperidone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT00000392</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06260072</th>\n",
       "      <td>['[MgH2]']</td>\n",
       "      <td>Riboflavin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06260891</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Zinc</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06261125</th>\n",
       "      <td>['COC1=C(C=C2C(OC3=CC=C(NC(=O)NC4CC4)C(Cl)=C3)...</td>\n",
       "      <td>Lenvatinib</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06263543</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Sacituzumab govitecan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT06264310</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12790 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                       smiless  \\\n",
       "nctid                                                            \n",
       "NCT00000271               ['CNCCCN1C2=CC=CC=C2CCC2=CC=CC=C12']   \n",
       "NCT00000304  ['C[C@H](N)CC1=CC=CC=C1', 'C[C@H](N)CC1=CC=CC=...   \n",
       "NCT00000308  ['C[C@H](N)CC1=CC=CC=C1', 'C[C@H](N)CC1=CC=CC=...   \n",
       "NCT00000317  ['CC1=C(CCN2CCC(CC2)C2=NOC3=C2C=CC(F)=C3)C(=O)...   \n",
       "NCT00000392                                                NaN   \n",
       "...                                                        ...   \n",
       "NCT06260072                                         ['[MgH2]']   \n",
       "NCT06260891                                                NaN   \n",
       "NCT06261125  ['COC1=C(C=C2C(OC3=CC=C(NC(=O)NC4CC4)C(Cl)=C3)...   \n",
       "NCT06263543                                                NaN   \n",
       "NCT06264310                                                NaN   \n",
       "\n",
       "                    intervention_browse/mesh_term  \n",
       "nctid                                              \n",
       "NCT00000271                           Desipramine  \n",
       "NCT00000304  ['Amphetamine', 'Dextroamphetamine']  \n",
       "NCT00000308  ['Amphetamine', 'Dextroamphetamine']  \n",
       "NCT00000317                           Risperidone  \n",
       "NCT00000392                                   NaN  \n",
       "...                                           ...  \n",
       "NCT06260072                            Riboflavin  \n",
       "NCT06260891                                  Zinc  \n",
       "NCT06261125                            Lenvatinib  \n",
       "NCT06263543                 Sacituzumab govitecan  \n",
       "NCT06264310                                   NaN  \n",
       "\n",
       "[12790 rows x 2 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# target = pd.read_csv('drug-dose-prediction/dose_target.csv', index_col=0).dropna()\n",
    "task_name = 'drug-dose-prediction'\n",
    "drop_index = []\n",
    "for i in target.index:\n",
    "    if i not in All.index:\n",
    "        drop_index.append(i)\n",
    "        print(i)\n",
    "target = target.drop(drop_index)\n",
    "part1 = All.loc[target.index, ['smiless']]\n",
    "part2 = All_Ori.loc[target.index, 'intervention_browse/mesh_term']\n",
    "part = pd.concat([part1, part2], axis=1)\n",
    "part"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Avg    0\n",
       "Max    0\n",
       "Min    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "划分训练测试"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(10232, 2) (10232, 3) (2558, 2) (2558, 3)\n"
     ]
    }
   ],
   "source": [
    "targets = ['Max', 'Min', 'Avg']\n",
    "part = pd.concat([part, target], axis=1)\n",
    "train_index, test_index = train_test_split(part, test_size=0.2, random_state=42)\n",
    "train_x = train_index.drop(targets, axis=1)\n",
    "train_y = train_index[targets]\n",
    "test_x = test_index.drop(targets, axis=1)\n",
    "test_y = test_index[targets]\n",
    "print(train_x.shape, train_y.shape, test_x.shape, test_y.shape)\n",
    "train_x.to_csv(f'{task_name}/train_x.csv')\n",
    "train_y.to_csv(f'{task_name}/train_y_cls.csv')\n",
    "test_x.to_csv(f'{task_name}/test_x.csv')\n",
    "test_y.to_csv(f'{task_name}/test_y_cls.csv')\n",
    "test_x.iloc[:10].to_csv(f'preview-set/{task_name}_input.csv')\n",
    "test_y.iloc[:10].to_csv(f'preview-set/{task_name}_output_cls.csv')\n",
    "part = part.drop(targets, axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "分层采样"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(10232, 2) (10232, 3) (2558, 2) (2558, 3)\n"
     ]
    }
   ],
   "source": [
    "strati = StratifiedShuffleSplit(n_splits=1, test_size=0.2, random_state=42)\n",
    "targets = ['Avg', ]\n",
    "task_name = 'drug-dose-prediction'\n",
    "for task in targets:\n",
    "    for train_index, test_index in strati.split(part, target[task]):\n",
    "        train_index = train_index.tolist()\n",
    "        test_index = test_index.tolist()\n",
    "        train_x = part.iloc[train_index]\n",
    "        train_y = target.iloc[train_index]\n",
    "        test_x = part.iloc[test_index]\n",
    "        test_y = target.iloc[test_index]\n",
    "        print(train_x.shape, train_y.shape, test_x.shape, test_y.shape)\n",
    "        train_x.to_csv(f'{task_name}/{task}_train_x.csv')\n",
    "        train_y.to_csv(f'{task_name}/{task}_train_y.csv')\n",
    "        test_x.to_csv(f'{task_name}/{task}_test_x.csv')\n",
    "        test_y.to_csv(f'{task_name}/{task}_test_y.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 输出小部分数据，head 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# tasks = ['trial-duration-prediction']\n",
    "# task_name = 'adverse-event-rate-prediction'\n",
    "# task = \"serious_adverse_rate\"\n",
    "# pd.read_csv(f'{task_name}/{task}_test_x.csv', index_col=0).iloc[:10].to_csv(f'preview-set/{task}_input.csv')\n",
    "# pd.read_csv(f'{task_name}/{task}_test_y.csv', index_col=0).iloc[:10].to_csv(f'preview-set/{task}_output.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 画图 跳过"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Clinical Trial/smiless 0\n",
      "Clinical Trial/intervention_browse/mesh_term 1\n"
     ]
    },
    {
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     "metadata": {},
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   ],
   "source": [
    "tasks = [task for task in os.listdir('preview-set') if 'input' in task]\n",
    "# tasks = ['serious_adverse_rate_input.csv']\n",
    "created_nodes = {}\n",
    "for task in tasks:\n",
    "    df = pd.read_csv(f'preview-set/{task}', index_col=0)\n",
    "    feature_names = [c for c in df.columns if (' ' not in c) and '-' not in c]\n",
    "    dot = Digraph(comment='Feature Hierarchy')\n",
    "    # dot.attr(rankdir='LR')\n",
    "    # dot.attr('node', shape='box', style='filled', width=2)\n",
    "    edges = []\n",
    "    # feature_names = sorted(feature_info['feature_name'].to_list())\n",
    "    for name in feature_names:\n",
    "        name = 'Clinical Trial/' + name \n",
    "        print(name, len(created_nodes))\n",
    "        if 'textblock' in name:\n",
    "            name = name.replace('\\textblock', '')\n",
    "        create_hierarchy_graph(dot, edges, name, created_nodes)\n",
    "\n",
    "    dot = dot.unflatten(stagger=20)\n",
    "    dot.render(f'feature_fig/{task[:-9]}', format='pdf', cleanup=True)\n",
    "    display(dot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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