04_mark_phase.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "PGHOST=\"localhost\"\n",
    "PGDATABASE=\"aact\"\n",
    "PGUSER=\"postgres\"\n",
    "PGPASSWORD=\"postgres\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import psycopg2\n",
    "import sys, os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pandas.io.sql as psql\n",
    "import pickle as pkl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "conn_string = \"host=\"+ PGHOST +\" port=\"+ \"5432\" +\" dbname=\"+ PGDATABASE +\" user=\" + PGUSER \\\n",
    "+\" password=\"+ PGPASSWORD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "conn=psycopg2.connect(conn_string)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "cursor = conn.cursor()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "cursor.execute(\"select * from ctgov.studies;\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_data(schema, table):\n",
    "\n",
    "    \n",
    "    sql_command = \"SELECT * FROM {};\".format(str(table))\n",
    "    print (sql_command)\n",
    "\n",
    "    # Load the data\n",
    "    \n",
    "    data = pd.read_sql(sql_command, conn)\n",
    "\n",
    "    print(data.shape)\n",
    "    return (data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os, sys, re, pandas as pd, numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/media/thomas/642d0db5-2c98-4156-b591-1a3572c5868c/anaconda3/envs/py310/lib/python3.10/site-packages/pandas/io/sql.py:762: UserWarning: pandas only support SQLAlchemy connectable(engine/connection) ordatabase string URI or sqlite3 DBAPI2 connectionother DBAPI2 objects are not tested, please consider using SQLAlchemy\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "pd_phase = pd.read_sql(\"select nct_id, phase from ctgov.studies\", conn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd_phase.set_index(\"nct_id\", inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<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>phase</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nct_id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NCT02262806</th>\n",
       "      <td>Phase 2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT02261909</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT03185507</th>\n",
       "      <td>Phase 1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT04086134</th>\n",
       "      <td>Not Applicable</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT02260362</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT04086290</th>\n",
       "      <td>Phase 1/Phase 2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT04086264</th>\n",
       "      <td>Phase 1/Phase 2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT04086251</th>\n",
       "      <td>Not Applicable</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT02263274</th>\n",
       "      <td>Not Applicable</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCT02262832</th>\n",
       "      <td>Phase 3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>432597 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       phase\n",
       "nct_id                      \n",
       "NCT02262806          Phase 2\n",
       "NCT02261909             None\n",
       "NCT03185507          Phase 1\n",
       "NCT04086134   Not Applicable\n",
       "NCT02260362             None\n",
       "...                      ...\n",
       "NCT04086290  Phase 1/Phase 2\n",
       "NCT04086264  Phase 1/Phase 2\n",
       "NCT04086251   Not Applicable\n",
       "NCT02263274   Not Applicable\n",
       "NCT02262832          Phase 3\n",
       "\n",
       "[432597 rows x 1 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_phase"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "phase          \n",
       "Not Applicable     153118\n",
       "Phase 2             52857\n",
       "Phase 1             38739\n",
       "Phase 3             35610\n",
       "Phase 4             30183\n",
       "Phase 1/Phase 2     13225\n",
       "Phase 2/Phase 3      6286\n",
       "Early Phase 1        4349\n",
       "dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_phase.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd_phase.to_csv(\"annotations/phase.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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