NoFreq_Final_drugs_with_side_effects_and_targets-.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "path_to_file = \"/Users/aditgupta/Google Drive/Research/T2D/Summer_2018/meddra_all_se.tsv.gz\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(path_to_file,delimiter=\"\\t\", header=None)\n",
    "df.rename(columns={0:'ID'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "      <th>ID</th>\n",
       "      <th>1</th>\n",
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       "      <th>5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>LLT</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>Hypertension</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>Hypertension</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>LLT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>LLT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               ID             1         2    3         4                 5\n",
       "67   CID100000085  CID000010917  C0020538  LLT  C0020538      Hypertension\n",
       "68   CID100000085  CID000010917  C0020538   PT  C0020538      Hypertension\n",
       "69   CID100000085  CID000010917  C0020649  LLT  C0020649       Hypotension\n",
       "70   CID100000085  CID000010917  C0020649   PT  C0020649       Hypotension\n",
       "111  CID100000085  CID000010917  C0043094  LLT  C0043094  Weight increased"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3 = df.loc[df[5].isin([\"Hypotension\", \"Hypertension\",\"Hypoglycaemia\", \"Hyperglycaemia\", \"Blood pressure increased\",\"Blood pressure decreased\", \"Blood glucose increased\", \"Blood glucose decreased\", \"Weight increased\", \"Weight decreased\", \"Hypocholesterolaemia\", \"Hypercholesterolaemia\"])]\n",
    "df3.head()\n",
    "#finds all samples with one of the four traits that we have data for in the 55k exome sequence sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "    <tr>\n",
       "      <th>170435</th>\n",
       "      <td>CID100005470</td>\n",
       "      <td>CID000021844</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>LLT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
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       "    <tr>\n",
       "      <th>170436</th>\n",
       "      <td>CID100005470</td>\n",
       "      <td>CID000021844</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170536</th>\n",
       "      <td>CID100005470</td>\n",
       "      <td>CID000444008</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>LLT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170537</th>\n",
       "      <td>CID100005470</td>\n",
       "      <td>CID000444008</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "    </tr>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "                  ID             1         2    3         4                 5\n",
       "170435  CID100005470  CID000021844  C0043094  LLT  C0043094  Weight increased\n",
       "170436  CID100005470  CID000021844  C0043094   PT  C0043094  Weight increased\n",
       "170536  CID100005470  CID000444008  C0043094  LLT  C0043094  Weight increased\n",
       "170537  CID100005470  CID000444008  C0043094   PT  C0043094  Weight increased"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3.loc[df3['ID'].isin([\"CID100005470\"])].head() #CID100005470 is the 'CID' identification number for tibolone to check whether sample is same from dataset with/without frequency\n",
    "#Since this 'CID' ID doesn't exist in the other dataset, we see that the datasets are different and thus the genes analyzed when using each dataset is different"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>1372</th>\n",
       "      <td>CID100000214</td>\n",
       "      <td>CID005280723</td>\n",
       "      <td>C0020615</td>\n",
       "      <td>LLT</td>\n",
       "      <td>C0020615</td>\n",
       "      <td>Hypoglycaemia</td>\n",
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       "    <tr>\n",
       "      <th>1373</th>\n",
       "      <td>CID100000214</td>\n",
       "      <td>CID005280723</td>\n",
       "      <td>C0020615</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020615</td>\n",
       "      <td>Hypoglycaemia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1665</th>\n",
       "      <td>CID100000214</td>\n",
       "      <td>CID006433212</td>\n",
       "      <td>C0020615</td>\n",
       "      <td>LLT</td>\n",
       "      <td>C0020615</td>\n",
       "      <td>Hypoglycaemia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1666</th>\n",
       "      <td>CID100000214</td>\n",
       "      <td>CID006433212</td>\n",
       "      <td>C0020615</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020615</td>\n",
       "      <td>Hypoglycaemia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2612</th>\n",
       "      <td>CID100000444</td>\n",
       "      <td>CID000000444</td>\n",
       "      <td>C0020615</td>\n",
       "      <td>LLT</td>\n",
       "      <td>C0020615</td>\n",
       "      <td>Hypoglycaemia</td>\n",
       "    </tr>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "                ID             1         2    3         4              5\n",
       "1372  CID100000214  CID005280723  C0020615  LLT  C0020615  Hypoglycaemia\n",
       "1373  CID100000214  CID005280723  C0020615   PT  C0020615  Hypoglycaemia\n",
       "1665  CID100000214  CID006433212  C0020615  LLT  C0020615  Hypoglycaemia\n",
       "1666  CID100000214  CID006433212  C0020615   PT  C0020615  Hypoglycaemia\n",
       "2612  CID100000444  CID000000444  C0020615  LLT  C0020615  Hypoglycaemia"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df[5].isin([\"Hypoglycaemia\"])].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>68</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>Hypertension</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>Weight decreased</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>CID100000137</td>\n",
       "      <td>CID000000137</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "    </tr>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "               ID             1         2   3         4                 5\n",
       "68   CID100000085  CID000010917  C0020538  PT  C0020538      Hypertension\n",
       "70   CID100000085  CID000010917  C0020649  PT  C0020649       Hypotension\n",
       "112  CID100000085  CID000010917  C0043094  PT  C0043094  Weight increased\n",
       "114  CID100000085  CID000010917  C0043096  PT  C0043096  Weight decreased\n",
       "197  CID100000137  CID000000137  C0020649  PT  C0020649       Hypotension"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4 = df3.loc[df[3].isin([\"PT\"])]\n",
    "df4.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "path_to_file = \"/Users/aditgupta/Google Drive/Research/T2D/Summer_2018/drug_names.tsv\"\n",
    "df5 = pd.read_csv(path_to_file,delimiter=\"\\t\", header=None)\n",
    "df5.rename(columns={0:'ID'}, inplace=True)\n",
    "df5.rename(columns={1:'drug_name'}, inplace=True)\n",
    "#drug names file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>drug_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>carnitine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CID100000119</td>\n",
       "      <td>gamma-aminobutyric</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CID100000137</td>\n",
       "      <td>5-aminolevulinic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CID100000143</td>\n",
       "      <td>leucovorin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CID100000146</td>\n",
       "      <td>5-methyltetrahydrofolate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>CID100000158</td>\n",
       "      <td>PGE2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>CID100000159</td>\n",
       "      <td>prostacyclin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>CID100000160</td>\n",
       "      <td>prostaglandin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>CID100000175</td>\n",
       "      <td>acetate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>CID100000187</td>\n",
       "      <td>acetylcholine</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ID                 drug_name\n",
       "0  CID100000085                 carnitine\n",
       "1  CID100000119        gamma-aminobutyric\n",
       "2  CID100000137          5-aminolevulinic\n",
       "3  CID100000143                leucovorin\n",
       "4  CID100000146  5-methyltetrahydrofolate\n",
       "5  CID100000158                      PGE2\n",
       "6  CID100000159              prostacyclin\n",
       "7  CID100000160             prostaglandin\n",
       "8  CID100000175                   acetate\n",
       "9  CID100000187             acetylcholine"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df5.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "      <th>ID</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>PT</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>drug_name</th>\n",
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       "      <th>0</th>\n",
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       "      <td>C0020538</td>\n",
       "      <td>Hypertension</td>\n",
       "      <td>carnitine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>carnitine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>carnitine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>Weight decreased</td>\n",
       "      <td>carnitine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CID100000137</td>\n",
       "      <td>CID000000137</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>5-aminolevulinic</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ID             1         2  PT         4                 5  \\\n",
       "0  CID100000085  CID000010917  C0020538  PT  C0020538      Hypertension   \n",
       "1  CID100000085  CID000010917  C0020649  PT  C0020649       Hypotension   \n",
       "2  CID100000085  CID000010917  C0043094  PT  C0043094  Weight increased   \n",
       "3  CID100000085  CID000010917  C0043096  PT  C0043096  Weight decreased   \n",
       "4  CID100000137  CID000000137  C0020649  PT  C0020649       Hypotension   \n",
       "\n",
       "          drug_name  \n",
       "0         carnitine  \n",
       "1         carnitine  \n",
       "2         carnitine  \n",
       "3         carnitine  \n",
       "4  5-aminolevulinic  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df6 = pd.merge(df4, df5, on='ID', how='outer')\n",
    "df6.rename(columns={3:'PT'}, inplace=True)\n",
    "df6.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>ID</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>PT</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>drug_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>CID100002118</td>\n",
       "      <td>CID000002118</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>alprazolam</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>CID100002118</td>\n",
       "      <td>CID000002118</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>alprazolam</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>CID100002118</td>\n",
       "      <td>CID000002118</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>Weight decreased</td>\n",
       "      <td>alprazolam</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               ID             1         2  PT         4                 5  \\\n",
       "155  CID100002118  CID000002118  C0020649  PT  C0020649       Hypotension   \n",
       "156  CID100002118  CID000002118  C0043094  PT  C0043094  Weight increased   \n",
       "157  CID100002118  CID000002118  C0043096  PT  C0043096  Weight decreased   \n",
       "\n",
       "      drug_name  \n",
       "155  alprazolam  \n",
       "156  alprazolam  \n",
       "157  alprazolam  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This contains all attributes\n",
    "df7 = df6[df6.PT.str.contains(\"NaN\") == False]\n",
    "df7.head()\n",
    "df7.loc[df7['drug_name'].isin([\"alprazolam\"])].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>ID</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>PT</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>drug_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>252</th>\n",
       "      <td>CID100002441</td>\n",
       "      <td>CID000002441</td>\n",
       "      <td>C0595883</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0595883</td>\n",
       "      <td>Blood glucose decreased</td>\n",
       "      <td>bromazepam</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>391</th>\n",
       "      <td>CID100002764</td>\n",
       "      <td>CID000002764</td>\n",
       "      <td>C0595883</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0595883</td>\n",
       "      <td>Blood glucose decreased</td>\n",
       "      <td>ciprofloxacin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>457</th>\n",
       "      <td>CID100002907</td>\n",
       "      <td>CID000002907</td>\n",
       "      <td>C0595883</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0595883</td>\n",
       "      <td>Blood glucose decreased</td>\n",
       "      <td>cyclophosphamide</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>746</th>\n",
       "      <td>CID100003454</td>\n",
       "      <td>CID000003454</td>\n",
       "      <td>C0595883</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0595883</td>\n",
       "      <td>Blood glucose decreased</td>\n",
       "      <td>ganciclovir</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1213</th>\n",
       "      <td>CID100004583</td>\n",
       "      <td>CID000149096</td>\n",
       "      <td>C0860801</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0595883</td>\n",
       "      <td>Blood glucose decreased</td>\n",
       "      <td>ofloxacin</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                ID             1         2  PT         4  \\\n",
       "252   CID100002441  CID000002441  C0595883  PT  C0595883   \n",
       "391   CID100002764  CID000002764  C0595883  PT  C0595883   \n",
       "457   CID100002907  CID000002907  C0595883  PT  C0595883   \n",
       "746   CID100003454  CID000003454  C0595883  PT  C0595883   \n",
       "1213  CID100004583  CID000149096  C0860801  PT  C0595883   \n",
       "\n",
       "                            5         drug_name  \n",
       "252   Blood glucose decreased        bromazepam  \n",
       "391   Blood glucose decreased     ciprofloxacin  \n",
       "457   Blood glucose decreased  cyclophosphamide  \n",
       "746   Blood glucose decreased       ganciclovir  \n",
       "1213  Blood glucose decreased         ofloxacin  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df7.loc[df7[5].isin([\"Blood glucose decreased\"])].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xml.etree.ElementTree as ET\n",
    "import lxml.html\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "path_to_file = '/Users/aditgupta/Google Drive/Research/T2D/Summer_2018/drugbank_full_database.xml'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "tree = ET.parse(path_to_file) #parses xml file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_id_and_name_from_target(target):\n",
    "    id = target.find(\"{http://www.drugbank.ca}id\").text\n",
    "    name = target.find(\"{http://www.drugbank.ca}name\").text\n",
    "    gene = target.find(\"*{http://www.drugbank.ca}gene-name\")\n",
    "    if gene is None:\n",
    "        gene_found = None\n",
    "    else:\n",
    "        gene_found= gene.text\n",
    "    return id, name, gene_found"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_drugs = tree.findall(\"{http://www.drugbank.ca}drug\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_results = []\n",
    "total_found = 0\n",
    "for drug in all_drugs:\n",
    "    drug_name = drug.find(\"{http://www.drugbank.ca}name\").text\n",
    "    drug_id = drug.find(\"{http://www.drugbank.ca}drugbank-id[@primary]\").text\n",
    "    element_containing_all_targets = drug.find(\"{http://www.drugbank.ca}targets\")\n",
    "    list_of_targets = element_containing_all_targets.findall(\"{http://www.drugbank.ca}target\")\n",
    "    for target in list_of_targets:\n",
    "        target_id, target_name, target_gene = get_id_and_name_from_target(target)\n",
    "        new_results.append([drug_name, drug_id, target_id, target_name, target_gene])\n",
    "    total_found += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "drug = all_drugs[0]\n",
    "element_containing_all_targets = drug.find(\"{http://www.drugbank.ca}targets\")\n",
    "list_of_targets = element_containing_all_targets.findall(\"{http://www.drugbank.ca}target\")\n",
    "target = list_of_targets[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%bash\n",
    "head -n 2500 /users/aditgupta/Google\\ Drive/Research/T2D/Summer_2018/drugbank_full_database.xml | tail -n 100 > output.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(new_results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.columns = [\"drug_name\", \"drug_id\", \"target_id\", \"target_name\", \"target_gene\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>drug_name</th>\n",
       "      <th>drug_id</th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_name</th>\n",
       "      <th>target_gene</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Lepirudin</td>\n",
       "      <td>DB00001</td>\n",
       "      <td>BE0000048</td>\n",
       "      <td>Prothrombin</td>\n",
       "      <td>F2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cetuximab</td>\n",
       "      <td>DB00002</td>\n",
       "      <td>BE0000767</td>\n",
       "      <td>Epidermal growth factor receptor</td>\n",
       "      <td>EGFR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Cetuximab</td>\n",
       "      <td>DB00002</td>\n",
       "      <td>BE0000901</td>\n",
       "      <td>Low affinity immunoglobulin gamma Fc region re...</td>\n",
       "      <td>FCGR3B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Cetuximab</td>\n",
       "      <td>DB00002</td>\n",
       "      <td>BE0002093</td>\n",
       "      <td>Complement C1r subcomponent</td>\n",
       "      <td>C1R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Cetuximab</td>\n",
       "      <td>DB00002</td>\n",
       "      <td>BE0002094</td>\n",
       "      <td>Complement C1q subcomponent subunit A</td>\n",
       "      <td>C1QA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   drug_name  drug_id  target_id  \\\n",
       "0  Lepirudin  DB00001  BE0000048   \n",
       "1  Cetuximab  DB00002  BE0000767   \n",
       "2  Cetuximab  DB00002  BE0000901   \n",
       "3  Cetuximab  DB00002  BE0002093   \n",
       "4  Cetuximab  DB00002  BE0002094   \n",
       "\n",
       "                                         target_name target_gene  \n",
       "0                                        Prothrombin          F2  \n",
       "1                   Epidermal growth factor receptor        EGFR  \n",
       "2  Low affinity immunoglobulin gamma Fc region re...      FCGR3B  \n",
       "3                        Complement C1r subcomponent         C1R  \n",
       "4              Complement C1q subcomponent subunit A        C1QA  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"drug_name\"] = df[\"drug_name\"].str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "indexed_df = df.set_index(\"drug_name\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>drug_id</th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_name</th>\n",
       "      <th>target_gene</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>drug_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>lepirudin</th>\n",
       "      <td>DB00001</td>\n",
       "      <td>BE0000048</td>\n",
       "      <td>Prothrombin</td>\n",
       "      <td>F2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cetuximab</th>\n",
       "      <td>DB00002</td>\n",
       "      <td>BE0000767</td>\n",
       "      <td>Epidermal growth factor receptor</td>\n",
       "      <td>EGFR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cetuximab</th>\n",
       "      <td>DB00002</td>\n",
       "      <td>BE0000901</td>\n",
       "      <td>Low affinity immunoglobulin gamma Fc region re...</td>\n",
       "      <td>FCGR3B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cetuximab</th>\n",
       "      <td>DB00002</td>\n",
       "      <td>BE0002093</td>\n",
       "      <td>Complement C1r subcomponent</td>\n",
       "      <td>C1R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cetuximab</th>\n",
       "      <td>DB00002</td>\n",
       "      <td>BE0002094</td>\n",
       "      <td>Complement C1q subcomponent subunit A</td>\n",
       "      <td>C1QA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           drug_id  target_id  \\\n",
       "drug_name                       \n",
       "lepirudin  DB00001  BE0000048   \n",
       "cetuximab  DB00002  BE0000767   \n",
       "cetuximab  DB00002  BE0000901   \n",
       "cetuximab  DB00002  BE0002093   \n",
       "cetuximab  DB00002  BE0002094   \n",
       "\n",
       "                                                 target_name target_gene  \n",
       "drug_name                                                                 \n",
       "lepirudin                                        Prothrombin          F2  \n",
       "cetuximab                   Epidermal growth factor receptor        EGFR  \n",
       "cetuximab  Low affinity immunoglobulin gamma Fc region re...      FCGR3B  \n",
       "cetuximab                        Complement C1r subcomponent         C1R  \n",
       "cetuximab              Complement C1q subcomponent subunit A        C1QA  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "indexed_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/aditgupta/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:1: DeprecationWarning: \n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n",
      "/Users/aditgupta/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:1: FutureWarning: \n",
      "Passing list-likes to .loc or [] with any missing label will raise\n",
      "KeyError in the future, you can use .reindex() as an alternative.\n",
      "\n",
      "See the documentation here:\n",
      "https://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate-loc-reindex-listlike\n",
      "  \"\"\"Entry point for launching an IPython kernel.\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",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>drug_id</th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_name</th>\n",
       "      <th>target_gene</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>drug_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>carnitine</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>carnitine</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>carnitine</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>carnitine</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5-aminolevulinic</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PGE2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PGE2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>prostacyclin</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>prostacyclin</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>prostaglandin</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 drug_id target_id target_name target_gene\n",
       "drug_name                                                 \n",
       "carnitine            NaN       NaN         NaN         NaN\n",
       "carnitine            NaN       NaN         NaN         NaN\n",
       "carnitine            NaN       NaN         NaN         NaN\n",
       "carnitine            NaN       NaN         NaN         NaN\n",
       "5-aminolevulinic     NaN       NaN         NaN         NaN\n",
       "PGE2                 NaN       NaN         NaN         NaN\n",
       "PGE2                 NaN       NaN         NaN         NaN\n",
       "prostacyclin         NaN       NaN         NaN         NaN\n",
       "prostacyclin         NaN       NaN         NaN         NaN\n",
       "prostaglandin        NaN       NaN         NaN         NaN"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "indexed_df.ix[df7[\"drug_name\"]].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/aditgupta/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:1: DeprecationWarning: \n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n",
      "/Users/aditgupta/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:1: FutureWarning: \n",
      "Passing list-likes to .loc or [] with any missing label will raise\n",
      "KeyError in the future, you can use .reindex() as an alternative.\n",
      "\n",
      "See the documentation here:\n",
      "https://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate-loc-reindex-listlike\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "target_lookup_table = indexed_df.ix[df7[\"drug_name\"]].dropna().groupby(\"drug_name\")[[\"target_id\", \"target_name\"]].agg(list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>target_id</th>\n",
       "      <th>target_name</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>drug_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>abacavir</th>\n",
       "      <td>[BE0004136, BE0009142, BE0004136, BE0009142, B...</td>\n",
       "      <td>[Reverse transcriptase/RNaseH, HLA class I his...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>abiraterone</th>\n",
       "      <td>[BE0000344, BE0000344, BE0000344]</td>\n",
       "      <td>[Steroid 17-alpha-hydroxylase/17,20 lyase, Ste...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>acamprosate</th>\n",
       "      <td>[BE0004797, BE0004852, BE0001192, BE0004797, B...</td>\n",
       "      <td>[GABA-A receptor (anion channel), Glutamate (N...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>acebutolol</th>\n",
       "      <td>[BE0000172, BE0000694, BE0000172, BE0000694]</td>\n",
       "      <td>[Beta-1 adrenergic receptor, Beta-2 adrenergic...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>acetaminophen</th>\n",
       "      <td>[BE0000262, BE0000017, BE0002194, BE0001023, B...</td>\n",
       "      <td>[Prostaglandin G/H synthase 2, Prostaglandin G...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                       target_id  \\\n",
       "drug_name                                                          \n",
       "abacavir       [BE0004136, BE0009142, BE0004136, BE0009142, B...   \n",
       "abiraterone                    [BE0000344, BE0000344, BE0000344]   \n",
       "acamprosate    [BE0004797, BE0004852, BE0001192, BE0004797, B...   \n",
       "acebutolol          [BE0000172, BE0000694, BE0000172, BE0000694]   \n",
       "acetaminophen  [BE0000262, BE0000017, BE0002194, BE0001023, B...   \n",
       "\n",
       "                                                     target_name  \n",
       "drug_name                                                         \n",
       "abacavir       [Reverse transcriptase/RNaseH, HLA class I his...  \n",
       "abiraterone    [Steroid 17-alpha-hydroxylase/17,20 lyase, Ste...  \n",
       "acamprosate    [GABA-A receptor (anion channel), Glutamate (N...  \n",
       "acebutolol     [Beta-1 adrenergic receptor, Beta-2 adrenergic...  \n",
       "acetaminophen  [Prostaglandin G/H synthase 2, Prostaglandin G...  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target_lookup_table.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "df7 = df7.rename(columns={\"DrugName\":'drug_name'}, inplace=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "973"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df26 = df7[\"drug_name\"].unique() #all drugs that are yield one of the traits\n",
    "len(df26)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>PT</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>drug_name</th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_name</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>Hypertension</td>\n",
       "      <td>carnitine</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>carnitine</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>carnitine</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>Weight decreased</td>\n",
       "      <td>carnitine</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CID100000137</td>\n",
       "      <td>CID000000137</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>5-aminolevulinic</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ID             1         2  PT         4                 5  \\\n",
       "0  CID100000085  CID000010917  C0020538  PT  C0020538      Hypertension   \n",
       "1  CID100000085  CID000010917  C0020649  PT  C0020649       Hypotension   \n",
       "2  CID100000085  CID000010917  C0043094  PT  C0043094  Weight increased   \n",
       "3  CID100000085  CID000010917  C0043096  PT  C0043096  Weight decreased   \n",
       "4  CID100000137  CID000000137  C0020649  PT  C0020649       Hypotension   \n",
       "\n",
       "          drug_name target_id target_name  \n",
       "0         carnitine       NaN         NaN  \n",
       "1         carnitine       NaN         NaN  \n",
       "2         carnitine       NaN         NaN  \n",
       "3         carnitine       NaN         NaN  \n",
       "4  5-aminolevulinic       NaN         NaN  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df8 = pd.merge(df7, target_lookup_table, on='drug_name', how='outer')\n",
    "# contains all drug names, frequencies, side effects, target ids, target names\n",
    "df8.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\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>drug_name</th>\n",
       "      <th>drug_id</th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_name</th>\n",
       "      <th>target_gene</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3699</th>\n",
       "      <td>estradiol</td>\n",
       "      <td>DB00783</td>\n",
       "      <td>BE0000123</td>\n",
       "      <td>Estrogen receptor alpha</td>\n",
       "      <td>ESR1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3700</th>\n",
       "      <td>estradiol</td>\n",
       "      <td>DB00783</td>\n",
       "      <td>BE0000792</td>\n",
       "      <td>Estrogen receptor beta</td>\n",
       "      <td>ESR2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3701</th>\n",
       "      <td>estradiol</td>\n",
       "      <td>DB00783</td>\n",
       "      <td>BE0000956</td>\n",
       "      <td>Nuclear receptor subfamily 1 group I member 2</td>\n",
       "      <td>NR1I2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3702</th>\n",
       "      <td>estradiol</td>\n",
       "      <td>DB00783</td>\n",
       "      <td>BE0000849</td>\n",
       "      <td>Neuronal acetylcholine receptor subunit alpha-4</td>\n",
       "      <td>CHRNA4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3703</th>\n",
       "      <td>estradiol</td>\n",
       "      <td>DB00783</td>\n",
       "      <td>BE0003740</td>\n",
       "      <td>Nuclear receptor coactivator 2</td>\n",
       "      <td>NCOA2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3704</th>\n",
       "      <td>estradiol</td>\n",
       "      <td>DB00783</td>\n",
       "      <td>BE0003446</td>\n",
       "      <td>G-protein coupled estrogen receptor 1</td>\n",
       "      <td>GPER1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3705</th>\n",
       "      <td>estradiol</td>\n",
       "      <td>DB00783</td>\n",
       "      <td>BE0009014</td>\n",
       "      <td>ATP synthase subunit a</td>\n",
       "      <td>MT-ATP6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3706</th>\n",
       "      <td>estradiol</td>\n",
       "      <td>DB00783</td>\n",
       "      <td>BE0009015</td>\n",
       "      <td>Beclin-1</td>\n",
       "      <td>BECN1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3707</th>\n",
       "      <td>estradiol</td>\n",
       "      <td>DB00783</td>\n",
       "      <td>BE0000006</td>\n",
       "      <td>Estradiol 17-beta-dehydrogenase 2</td>\n",
       "      <td>HSD17B2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3708</th>\n",
       "      <td>estradiol</td>\n",
       "      <td>DB00783</td>\n",
       "      <td>BE0002088</td>\n",
       "      <td>Estrogen-related receptor gamma</td>\n",
       "      <td>ESRRG</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      drug_name  drug_id  target_id  \\\n",
       "3699  estradiol  DB00783  BE0000123   \n",
       "3700  estradiol  DB00783  BE0000792   \n",
       "3701  estradiol  DB00783  BE0000956   \n",
       "3702  estradiol  DB00783  BE0000849   \n",
       "3703  estradiol  DB00783  BE0003740   \n",
       "3704  estradiol  DB00783  BE0003446   \n",
       "3705  estradiol  DB00783  BE0009014   \n",
       "3706  estradiol  DB00783  BE0009015   \n",
       "3707  estradiol  DB00783  BE0000006   \n",
       "3708  estradiol  DB00783  BE0002088   \n",
       "\n",
       "                                          target_name target_gene  \n",
       "3699                          Estrogen receptor alpha        ESR1  \n",
       "3700                           Estrogen receptor beta        ESR2  \n",
       "3701    Nuclear receptor subfamily 1 group I member 2       NR1I2  \n",
       "3702  Neuronal acetylcholine receptor subunit alpha-4      CHRNA4  \n",
       "3703                   Nuclear receptor coactivator 2       NCOA2  \n",
       "3704            G-protein coupled estrogen receptor 1       GPER1  \n",
       "3705                           ATP synthase subunit a     MT-ATP6  \n",
       "3706                                         Beclin-1       BECN1  \n",
       "3707                Estradiol 17-beta-dehydrogenase 2     HSD17B2  \n",
       "3708                  Estrogen-related receptor gamma       ESRRG  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df[\"drug_name\"].isin([\"estradiol\"])]\n",
    "#use df to find target id and name for each drug (all info in seperate rows)\n",
    "#use df8 to combine all targets and ids into same row for a particular drug (all info in one row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>drug_name</th>\n",
       "      <th>drug_id</th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_name</th>\n",
       "      <th>target_gene</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5046</th>\n",
       "      <td>bupropion</td>\n",
       "      <td>DB01156</td>\n",
       "      <td>BE0000647</td>\n",
       "      <td>Sodium-dependent dopamine transporter</td>\n",
       "      <td>SLC6A3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5047</th>\n",
       "      <td>bupropion</td>\n",
       "      <td>DB01156</td>\n",
       "      <td>BE0000486</td>\n",
       "      <td>Sodium-dependent noradrenaline transporter</td>\n",
       "      <td>SLC6A2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5048</th>\n",
       "      <td>bupropion</td>\n",
       "      <td>DB01156</td>\n",
       "      <td>BE0003585</td>\n",
       "      <td>Neuronal acetylcholine receptor subunit alpha-3</td>\n",
       "      <td>CHRNA3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      drug_name  drug_id  target_id  \\\n",
       "5046  bupropion  DB01156  BE0000647   \n",
       "5047  bupropion  DB01156  BE0000486   \n",
       "5048  bupropion  DB01156  BE0003585   \n",
       "\n",
       "                                          target_name target_gene  \n",
       "5046            Sodium-dependent dopamine transporter      SLC6A3  \n",
       "5047       Sodium-dependent noradrenaline transporter      SLC6A2  \n",
       "5048  Neuronal acetylcholine receptor subunit alpha-3      CHRNA3  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df[\"drug_name\"].isin([\"bupropion\"])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>ID</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>PT</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>drug_name</th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>Hypertension</td>\n",
       "      <td>carnitine</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>carnitine</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>carnitine</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CID100000085</td>\n",
       "      <td>CID000010917</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>Weight decreased</td>\n",
       "      <td>carnitine</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ID             1         2  PT         4                 5  \\\n",
       "0  CID100000085  CID000010917  C0020538  PT  C0020538      Hypertension   \n",
       "1  CID100000085  CID000010917  C0020649  PT  C0020649       Hypotension   \n",
       "2  CID100000085  CID000010917  C0043094  PT  C0043094  Weight increased   \n",
       "3  CID100000085  CID000010917  C0043096  PT  C0043096  Weight decreased   \n",
       "\n",
       "   drug_name target_id target_name  \n",
       "0  carnitine       NaN         NaN  \n",
       "1  carnitine       NaN         NaN  \n",
       "2  carnitine       NaN         NaN  \n",
       "3  carnitine       NaN         NaN  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df8.loc[df8[\"drug_name\"].isin([\"carnitine\"])]\n",
    "#Smoothened homolog"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>drug_name</th>\n",
       "      <th>drug_id</th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_name</th>\n",
       "      <th>target_gene</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1299</th>\n",
       "      <td>amphetamine</td>\n",
       "      <td>DB00182</td>\n",
       "      <td>BE0000647</td>\n",
       "      <td>Sodium-dependent dopamine transporter</td>\n",
       "      <td>SLC6A3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1335</th>\n",
       "      <td>phentermine</td>\n",
       "      <td>DB00191</td>\n",
       "      <td>BE0000647</td>\n",
       "      <td>Sodium-dependent dopamine transporter</td>\n",
       "      <td>SLC6A3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1544</th>\n",
       "      <td>benzatropine</td>\n",
       "      <td>DB00245</td>\n",
       "      <td>BE0000647</td>\n",
       "      <td>Sodium-dependent dopamine transporter</td>\n",
       "      <td>SLC6A3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1734</th>\n",
       "      <td>venlafaxine</td>\n",
       "      <td>DB00285</td>\n",
       "      <td>BE0000647</td>\n",
       "      <td>Sodium-dependent dopamine transporter</td>\n",
       "      <td>SLC6A3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1741</th>\n",
       "      <td>atomoxetine</td>\n",
       "      <td>DB00289</td>\n",
       "      <td>BE0000647</td>\n",
       "      <td>Sodium-dependent dopamine transporter</td>\n",
       "      <td>SLC6A3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         drug_name  drug_id  target_id                            target_name  \\\n",
       "1299   amphetamine  DB00182  BE0000647  Sodium-dependent dopamine transporter   \n",
       "1335   phentermine  DB00191  BE0000647  Sodium-dependent dopamine transporter   \n",
       "1544  benzatropine  DB00245  BE0000647  Sodium-dependent dopamine transporter   \n",
       "1734   venlafaxine  DB00285  BE0000647  Sodium-dependent dopamine transporter   \n",
       "1741   atomoxetine  DB00289  BE0000647  Sodium-dependent dopamine transporter   \n",
       "\n",
       "     target_gene  \n",
       "1299      SLC6A3  \n",
       "1335      SLC6A3  \n",
       "1544      SLC6A3  \n",
       "1734      SLC6A3  \n",
       "1741      SLC6A3  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df[\"target_name\"].isin([\"Sodium-dependent dopamine transporter\"])].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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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>ID</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>PT</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>drug_name</th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>CID100000444</td>\n",
       "      <td>CID000000444</td>\n",
       "      <td>C0020443</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020443</td>\n",
       "      <td>Hypercholesterolaemia</td>\n",
       "      <td>bupropion</td>\n",
       "      <td>[BE0000647, BE0000486, BE0003585, BE0000647, B...</td>\n",
       "      <td>[Sodium-dependent dopamine transporter, Sodium...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>CID100000444</td>\n",
       "      <td>CID000000444</td>\n",
       "      <td>C0020456</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020456</td>\n",
       "      <td>Hyperglycaemia</td>\n",
       "      <td>bupropion</td>\n",
       "      <td>[BE0000647, BE0000486, BE0003585, BE0000647, B...</td>\n",
       "      <td>[Sodium-dependent dopamine transporter, Sodium...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>CID100000444</td>\n",
       "      <td>CID000000444</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>Hypertension</td>\n",
       "      <td>bupropion</td>\n",
       "      <td>[BE0000647, BE0000486, BE0003585, BE0000647, B...</td>\n",
       "      <td>[Sodium-dependent dopamine transporter, Sodium...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>CID100000444</td>\n",
       "      <td>CID000000444</td>\n",
       "      <td>C0020615</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020615</td>\n",
       "      <td>Hypoglycaemia</td>\n",
       "      <td>bupropion</td>\n",
       "      <td>[BE0000647, BE0000486, BE0003585, BE0000647, B...</td>\n",
       "      <td>[Sodium-dependent dopamine transporter, Sodium...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>CID100000444</td>\n",
       "      <td>CID000000444</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>bupropion</td>\n",
       "      <td>[BE0000647, BE0000486, BE0003585, BE0000647, B...</td>\n",
       "      <td>[Sodium-dependent dopamine transporter, Sodium...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>CID100000444</td>\n",
       "      <td>CID000000444</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>bupropion</td>\n",
       "      <td>[BE0000647, BE0000486, BE0003585, BE0000647, B...</td>\n",
       "      <td>[Sodium-dependent dopamine transporter, Sodium...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>CID100000444</td>\n",
       "      <td>CID000000444</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>Weight decreased</td>\n",
       "      <td>bupropion</td>\n",
       "      <td>[BE0000647, BE0000486, BE0003585, BE0000647, B...</td>\n",
       "      <td>[Sodium-dependent dopamine transporter, Sodium...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>CID100000444</td>\n",
       "      <td>CID000000444</td>\n",
       "      <td>C0497247</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0497247</td>\n",
       "      <td>Blood pressure increased</td>\n",
       "      <td>bupropion</td>\n",
       "      <td>[BE0000647, BE0000486, BE0003585, BE0000647, B...</td>\n",
       "      <td>[Sodium-dependent dopamine transporter, Sodium...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              ID             1         2  PT         4  \\\n",
       "28  CID100000444  CID000000444  C0020443  PT  C0020443   \n",
       "29  CID100000444  CID000000444  C0020456  PT  C0020456   \n",
       "30  CID100000444  CID000000444  C0020538  PT  C0020538   \n",
       "31  CID100000444  CID000000444  C0020615  PT  C0020615   \n",
       "32  CID100000444  CID000000444  C0020649  PT  C0020649   \n",
       "33  CID100000444  CID000000444  C0043094  PT  C0043094   \n",
       "34  CID100000444  CID000000444  C0043096  PT  C0043096   \n",
       "35  CID100000444  CID000000444  C0497247  PT  C0497247   \n",
       "\n",
       "                           5  drug_name  \\\n",
       "28     Hypercholesterolaemia  bupropion   \n",
       "29            Hyperglycaemia  bupropion   \n",
       "30              Hypertension  bupropion   \n",
       "31             Hypoglycaemia  bupropion   \n",
       "32               Hypotension  bupropion   \n",
       "33          Weight increased  bupropion   \n",
       "34          Weight decreased  bupropion   \n",
       "35  Blood pressure increased  bupropion   \n",
       "\n",
       "                                            target_id  \\\n",
       "28  [BE0000647, BE0000486, BE0003585, BE0000647, B...   \n",
       "29  [BE0000647, BE0000486, BE0003585, BE0000647, B...   \n",
       "30  [BE0000647, BE0000486, BE0003585, BE0000647, B...   \n",
       "31  [BE0000647, BE0000486, BE0003585, BE0000647, B...   \n",
       "32  [BE0000647, BE0000486, BE0003585, BE0000647, B...   \n",
       "33  [BE0000647, BE0000486, BE0003585, BE0000647, B...   \n",
       "34  [BE0000647, BE0000486, BE0003585, BE0000647, B...   \n",
       "35  [BE0000647, BE0000486, BE0003585, BE0000647, B...   \n",
       "\n",
       "                                          target_name  \n",
       "28  [Sodium-dependent dopamine transporter, Sodium...  \n",
       "29  [Sodium-dependent dopamine transporter, Sodium...  \n",
       "30  [Sodium-dependent dopamine transporter, Sodium...  \n",
       "31  [Sodium-dependent dopamine transporter, Sodium...  \n",
       "32  [Sodium-dependent dopamine transporter, Sodium...  \n",
       "33  [Sodium-dependent dopamine transporter, Sodium...  \n",
       "34  [Sodium-dependent dopamine transporter, Sodium...  \n",
       "35  [Sodium-dependent dopamine transporter, Sodium...  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df8.loc[df8[\"drug_name\"].isin([\"bupropion\"])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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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>drug_name</th>\n",
       "      <th>drug_id</th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_name</th>\n",
       "      <th>target_gene</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3070</th>\n",
       "      <td>ethionamide</td>\n",
       "      <td>DB00609</td>\n",
       "      <td>BE0000332</td>\n",
       "      <td>Enoyl-[acyl-carrier-protein] reductase [NADH]</td>\n",
       "      <td>inhA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3071</th>\n",
       "      <td>ethionamide</td>\n",
       "      <td>DB00609</td>\n",
       "      <td>BE0000466</td>\n",
       "      <td>Catalase-peroxidase</td>\n",
       "      <td>katG</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        drug_name  drug_id  target_id  \\\n",
       "3070  ethionamide  DB00609  BE0000332   \n",
       "3071  ethionamide  DB00609  BE0000466   \n",
       "\n",
       "                                        target_name target_gene  \n",
       "3070  Enoyl-[acyl-carrier-protein] reductase [NADH]        inhA  \n",
       "3071                            Catalase-peroxidase        katG  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df[\"drug_name\"].isin([\"ethionamide\"])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "df11 = df['drug_name'].value_counts() #df11 is a series with number of targets given a drug\n",
    "df12 = df11.to_frame(name=None)\n",
    "df13 = df12.reset_index()\n",
    "df14 = df13.rename(columns={'drug_name':'number_of_targets'}, inplace=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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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>drug_name</th>\n",
       "      <th>number_of_targets</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>fostamatinib</td>\n",
       "      <td>300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>artenimol</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>copper</td>\n",
       "      <td>147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>nadh</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>zinc</td>\n",
       "      <td>124</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      drug_name  number_of_targets\n",
       "0  fostamatinib                300\n",
       "1     artenimol                192\n",
       "2        copper                147\n",
       "3          nadh                144\n",
       "4          zinc                124"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df15 = df14.rename(columns={'index':'drug_name'}, inplace=False)\n",
    "df15.head()\n",
    "#df15 is the number of targets given a drug"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>drug_name</th>\n",
       "      <th>number_of_targets</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2670</th>\n",
       "      <td>ethionamide</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        drug_name  number_of_targets\n",
       "2670  ethionamide                  2"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df15.loc[df15['drug_name'].isin([\"ethionamide\"])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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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>target_id</th>\n",
       "      <th>target_freq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BE0001072</td>\n",
       "      <td>137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BE0000048</td>\n",
       "      <td>112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BE0000756</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BE0000451</td>\n",
       "      <td>105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>BE0000442</td>\n",
       "      <td>104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>BE0004796</td>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>BE0000322</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>BE0001739</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>BE0000092</td>\n",
       "      <td>97</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   target_id  target_freq\n",
       "0  BE0001072          137\n",
       "1  BE0000048          112\n",
       "2  BE0000123          111\n",
       "3  BE0000756          108\n",
       "4  BE0000451          105\n",
       "5  BE0000442          104\n",
       "6  BE0004796          101\n",
       "7  BE0000322          100\n",
       "8  BE0001739           99\n",
       "9  BE0000092           97"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target_freq = df['target_id'].value_counts() #number of drugs that target a given target ID in a series\n",
    "df17 = target_freq.to_frame(name=None)\n",
    "df18 = df17.reset_index()\n",
    "df19 = df18.rename(columns={'target_id':'target_freq'}, inplace=False)\n",
    "df20 = df19.rename(columns={'index':'target_id'}, inplace=False)\n",
    "df20.head(10)\n",
    "#df20 shows the total number of drugs that target a given target ID in a dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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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>target_id</th>\n",
       "      <th>target_freq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>BE0000901</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     target_id  target_freq\n",
       "123  BE0000901           21"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df20.loc[df20['target_id'].isin([\"BE0000901\"])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 300)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "hist_plot = df15['number_of_targets'].hist(bins=15,grid=False, figsize=(10,8))\n",
    "hist_plot.set_xlabel('Number of Targets')\n",
    "hist_plot.set_ylabel('Frequency (of Drugs)')\n",
    "hist_plot.set_title('Histogram of the Number of Targets with respect to Frequency of Given Drugs')\n",
    "hist_plot.set_xlim(0,300)\n",
    "#This histogram shows a plot of the frequency of drugs and its respective target number\n",
    "#Most drugs fall in the first bin which have at most 2 targets "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "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>drug_name</th>\n",
       "      <th>number_of_targets</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1508</th>\n",
       "      <td>n-[(1s)-2-amino-1-phenylethyl]-5-(1h-pyrrolo[2...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1509</th>\n",
       "      <td>atiprimod</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1510</th>\n",
       "      <td>hyaluronidase</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1511</th>\n",
       "      <td>dicyclomine</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1512</th>\n",
       "      <td>alpha-(2,6-dichlorophenyl)-alpha-(2-acetyl-5-m...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              drug_name  number_of_targets\n",
       "1508  n-[(1s)-2-amino-1-phenylethyl]-5-(1h-pyrrolo[2...                  2\n",
       "1509                                          atiprimod                  2\n",
       "1510                                      hyaluronidase                  2\n",
       "1511                                        dicyclomine                  2\n",
       "1512  alpha-(2,6-dichlorophenyl)-alpha-(2-acetyl-5-m...                  2"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df10 = df15[(df15['number_of_targets'])<3]  \n",
    "df10.head()\n",
    "#all drugs that have a maximum of two targets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_freq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>137</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BE0000048</td>\n",
       "      <td>112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BE0000756</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BE0000451</td>\n",
       "      <td>105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>BE0000442</td>\n",
       "      <td>104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>BE0004796</td>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>BE0000322</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>BE0001739</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>BE0000092</td>\n",
       "      <td>97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>BE0000501</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>BE0000291</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>BE0000560</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>BE0000262</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>BE0000017</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    target_id  target_freq\n",
       "0   BE0001072          137\n",
       "1   BE0000048          112\n",
       "2   BE0000123          111\n",
       "3   BE0000756          108\n",
       "4   BE0000451          105\n",
       "5   BE0000442          104\n",
       "6   BE0004796          101\n",
       "7   BE0000322          100\n",
       "8   BE0001739           99\n",
       "9   BE0000092           97\n",
       "10  BE0000501           91\n",
       "11  BE0000291           81\n",
       "12  BE0000560           79\n",
       "13  BE0000262           78\n",
       "14  BE0000017           77"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df21 = df20[(df20['target_freq'])>1]  #all targets that have at least two drugs targeting it\n",
    "df21.head(15)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\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>target_id</th>\n",
       "      <th>target_freq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2118</th>\n",
       "      <td>BE0000466</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      target_id  target_freq\n",
       "2118  BE0000466            2"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df21.loc[df21['target_id'].isin([\"BE0000466\"])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 140)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hist_plot_target = df20['target_freq'].hist(bins=10,grid=False, figsize=(10,9))\n",
    "hist_plot_target.set_xlabel('Number of drugs')\n",
    "hist_plot_target.set_ylabel('Frequency (number of targets that have at most the given number of drugs targeting it from its respective bin)')\n",
    "hist_plot_target.set_title('Frequency of the Number of drugs targeting a given target')\n",
    "hist_plot_target.set_xlim(0,140)\n",
    "#contains the target frequncies that have x (x-axis) number of drugs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "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>ID</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>PT</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>drug_name</th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_name</th>\n",
       "      <th>number_of_targets</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CID100000596</td>\n",
       "      <td>CID000006252</td>\n",
       "      <td>C0020456</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020456</td>\n",
       "      <td>Hyperglycaemia</td>\n",
       "      <td>cytarabine</td>\n",
       "      <td>[BE0000113, BE0000113, BE0000113, BE0000113]</td>\n",
       "      <td>[DNA polymerase beta, DNA polymerase beta, DNA...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CID100000596</td>\n",
       "      <td>CID000006252</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>Hypertension</td>\n",
       "      <td>cytarabine</td>\n",
       "      <td>[BE0000113, BE0000113, BE0000113, BE0000113]</td>\n",
       "      <td>[DNA polymerase beta, DNA polymerase beta, DNA...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CID100000596</td>\n",
       "      <td>CID000006252</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>cytarabine</td>\n",
       "      <td>[BE0000113, BE0000113, BE0000113, BE0000113]</td>\n",
       "      <td>[DNA polymerase beta, DNA polymerase beta, DNA...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CID100000596</td>\n",
       "      <td>CID000006252</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>cytarabine</td>\n",
       "      <td>[BE0000113, BE0000113, BE0000113, BE0000113]</td>\n",
       "      <td>[DNA polymerase beta, DNA polymerase beta, DNA...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CID100000813</td>\n",
       "      <td>CID000000813</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>potassium</td>\n",
       "      <td>[BE0000732, BE0000732, BE0000732]</td>\n",
       "      <td>[Sodium/potassium-transporting ATPase subunit ...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ID             1         2  PT         4                 5  \\\n",
       "0  CID100000596  CID000006252  C0020456  PT  C0020456    Hyperglycaemia   \n",
       "1  CID100000596  CID000006252  C0020538  PT  C0020538      Hypertension   \n",
       "2  CID100000596  CID000006252  C0020649  PT  C0020649       Hypotension   \n",
       "3  CID100000596  CID000006252  C0043094  PT  C0043094  Weight increased   \n",
       "4  CID100000813  CID000000813  C0020649  PT  C0020649       Hypotension   \n",
       "\n",
       "    drug_name                                     target_id  \\\n",
       "0  cytarabine  [BE0000113, BE0000113, BE0000113, BE0000113]   \n",
       "1  cytarabine  [BE0000113, BE0000113, BE0000113, BE0000113]   \n",
       "2  cytarabine  [BE0000113, BE0000113, BE0000113, BE0000113]   \n",
       "3  cytarabine  [BE0000113, BE0000113, BE0000113, BE0000113]   \n",
       "4   potassium             [BE0000732, BE0000732, BE0000732]   \n",
       "\n",
       "                                         target_name  number_of_targets  \n",
       "0  [DNA polymerase beta, DNA polymerase beta, DNA...                  2  \n",
       "1  [DNA polymerase beta, DNA polymerase beta, DNA...                  2  \n",
       "2  [DNA polymerase beta, DNA polymerase beta, DNA...                  2  \n",
       "3  [DNA polymerase beta, DNA polymerase beta, DNA...                  2  \n",
       "4  [Sodium/potassium-transporting ATPase subunit ...                  1  "
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df16 = pd.merge(df8, df10, on='drug_name', how='inner')\n",
    "df16.head(15) #df16 is a dataframe that includes all drugs integrated with df10. \n",
    "#Only includes drugs that have a maximum of two targets\n",
    "df17 = df16\n",
    "df17.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>PT</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>drug_name</th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_name</th>\n",
       "      <th>number_of_targets</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CID100000596</td>\n",
       "      <td>CID000006252</td>\n",
       "      <td>C0020456</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020456</td>\n",
       "      <td>Hyperglycaemia</td>\n",
       "      <td>cytarabine</td>\n",
       "      <td>[BE0000113, BE0000113, BE0000113, BE0000113]</td>\n",
       "      <td>[DNA polymerase beta, DNA polymerase beta, DNA...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CID100000596</td>\n",
       "      <td>CID000006252</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>Hypertension</td>\n",
       "      <td>cytarabine</td>\n",
       "      <td>[BE0000113, BE0000113, BE0000113, BE0000113]</td>\n",
       "      <td>[DNA polymerase beta, DNA polymerase beta, DNA...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CID100000596</td>\n",
       "      <td>CID000006252</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>cytarabine</td>\n",
       "      <td>[BE0000113, BE0000113, BE0000113, BE0000113]</td>\n",
       "      <td>[DNA polymerase beta, DNA polymerase beta, DNA...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CID100000596</td>\n",
       "      <td>CID000006252</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>cytarabine</td>\n",
       "      <td>[BE0000113, BE0000113, BE0000113, BE0000113]</td>\n",
       "      <td>[DNA polymerase beta, DNA polymerase beta, DNA...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CID100000813</td>\n",
       "      <td>CID000000813</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>potassium</td>\n",
       "      <td>[BE0000732, BE0000732, BE0000732]</td>\n",
       "      <td>[Sodium/potassium-transporting ATPase subunit ...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ID             1         2  PT         4                 5  \\\n",
       "0  CID100000596  CID000006252  C0020456  PT  C0020456    Hyperglycaemia   \n",
       "1  CID100000596  CID000006252  C0020538  PT  C0020538      Hypertension   \n",
       "2  CID100000596  CID000006252  C0020649  PT  C0020649       Hypotension   \n",
       "3  CID100000596  CID000006252  C0043094  PT  C0043094  Weight increased   \n",
       "4  CID100000813  CID000000813  C0020649  PT  C0020649       Hypotension   \n",
       "\n",
       "    drug_name                                     target_id  \\\n",
       "0  cytarabine  [BE0000113, BE0000113, BE0000113, BE0000113]   \n",
       "1  cytarabine  [BE0000113, BE0000113, BE0000113, BE0000113]   \n",
       "2  cytarabine  [BE0000113, BE0000113, BE0000113, BE0000113]   \n",
       "3  cytarabine  [BE0000113, BE0000113, BE0000113, BE0000113]   \n",
       "4   potassium             [BE0000732, BE0000732, BE0000732]   \n",
       "\n",
       "                                         target_name  number_of_targets  \n",
       "0  [DNA polymerase beta, DNA polymerase beta, DNA...                  2  \n",
       "1  [DNA polymerase beta, DNA polymerase beta, DNA...                  2  \n",
       "2  [DNA polymerase beta, DNA polymerase beta, DNA...                  2  \n",
       "3  [DNA polymerase beta, DNA polymerase beta, DNA...                  2  \n",
       "4  [Sodium/potassium-transporting ATPase subunit ...                  1  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df16.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>PT</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>drug_name</th>\n",
       "      <th>number_of_targets</th>\n",
       "      <th>sample_num</th>\n",
       "      <th>target_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CID100000596</td>\n",
       "      <td>CID000006252</td>\n",
       "      <td>C0020456</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020456</td>\n",
       "      <td>Hyperglycaemia</td>\n",
       "      <td>cytarabine</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>BE0000113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CID100000596</td>\n",
       "      <td>CID000006252</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>Hypertension</td>\n",
       "      <td>cytarabine</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>BE0000113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>CID100000596</td>\n",
       "      <td>CID000006252</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>cytarabine</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>BE0000113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>CID100000596</td>\n",
       "      <td>CID000006252</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>cytarabine</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>BE0000113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>CID100000813</td>\n",
       "      <td>CID000000813</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>potassium</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>BE0000732</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              ID             1         2  PT         4                 5  \\\n",
       "0   CID100000596  CID000006252  C0020456  PT  C0020456    Hyperglycaemia   \n",
       "4   CID100000596  CID000006252  C0020538  PT  C0020538      Hypertension   \n",
       "8   CID100000596  CID000006252  C0020649  PT  C0020649       Hypotension   \n",
       "12  CID100000596  CID000006252  C0043094  PT  C0043094  Weight increased   \n",
       "16  CID100000813  CID000000813  C0020649  PT  C0020649       Hypotension   \n",
       "\n",
       "     drug_name  number_of_targets  sample_num  target_id  \n",
       "0   cytarabine                  2           0  BE0000113  \n",
       "4   cytarabine                  2           0  BE0000113  \n",
       "8   cytarabine                  2           0  BE0000113  \n",
       "12  cytarabine                  2           0  BE0000113  \n",
       "16   potassium                  1           0  BE0000732  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res = df16.set_index(['ID',1,2,'PT', 4,5, 'drug_name','number_of_targets', ])['target_id'].apply(pd.Series).stack()\n",
    "res2 = res.reset_index()\n",
    "res2.columns = ['ID',1,2,'PT', 4,5, 'drug_name','number_of_targets','sample_num','target_id']\n",
    "res3 = res2\n",
    "df27 = res3.drop_duplicates(subset = ['ID', 1, 2, 5,'drug_name', 'target_id'])\n",
    "df27.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "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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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_freq</th>\n",
       "      <th>ID</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>PT</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>drug_name</th>\n",
       "      <th>number_of_targets</th>\n",
       "      <th>sample_num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BE0001072</td>\n",
       "      <td>137.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BE0000048</td>\n",
       "      <td>112.0</td>\n",
       "      <td>CID100002232</td>\n",
       "      <td>CID000092721</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>argatroban</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111.0</td>\n",
       "      <td>CID100005470</td>\n",
       "      <td>CID000021844</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>tibolone</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111.0</td>\n",
       "      <td>CID100005470</td>\n",
       "      <td>CID000444008</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>tibolone</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111.0</td>\n",
       "      <td>CID100005516</td>\n",
       "      <td>CID003005572</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>toremifene</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   target_id  target_freq            ID             1         2   PT  \\\n",
       "0  BE0001072        137.0           NaN           NaN       NaN  NaN   \n",
       "1  BE0000048        112.0  CID100002232  CID000092721  C0020649   PT   \n",
       "2  BE0000123        111.0  CID100005470  CID000021844  C0043094   PT   \n",
       "3  BE0000123        111.0  CID100005470  CID000444008  C0043094   PT   \n",
       "4  BE0000123        111.0  CID100005516  CID003005572  C0043094   PT   \n",
       "\n",
       "          4                 5   drug_name  number_of_targets  sample_num  \n",
       "0       NaN               NaN         NaN                NaN         NaN  \n",
       "1  C0020649       Hypotension  argatroban                1.0         0.0  \n",
       "2  C0043094  Weight increased    tibolone                1.0         0.0  \n",
       "3  C0043094  Weight increased    tibolone                1.0         0.0  \n",
       "4  C0043094  Weight increased  toremifene                2.0         0.0  "
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df28 = pd.merge(df21, df27, on='target_id', how='outer')\n",
    "df28.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_freq</th>\n",
       "      <th>ID</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>PT</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>drug_name</th>\n",
       "      <th>number_of_targets</th>\n",
       "      <th>sample_num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BE0000048</td>\n",
       "      <td>112.0</td>\n",
       "      <td>CID100002232</td>\n",
       "      <td>CID000092721</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>argatroban</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111.0</td>\n",
       "      <td>CID100005470</td>\n",
       "      <td>CID000021844</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>tibolone</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111.0</td>\n",
       "      <td>CID100005470</td>\n",
       "      <td>CID000444008</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>tibolone</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111.0</td>\n",
       "      <td>CID100005516</td>\n",
       "      <td>CID003005572</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>toremifene</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111.0</td>\n",
       "      <td>CID100040973</td>\n",
       "      <td>CID000040973</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>Hypertension</td>\n",
       "      <td>desogestrel</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   target_id  target_freq            ID             1         2  PT         4  \\\n",
       "1  BE0000048        112.0  CID100002232  CID000092721  C0020649  PT  C0020649   \n",
       "2  BE0000123        111.0  CID100005470  CID000021844  C0043094  PT  C0043094   \n",
       "3  BE0000123        111.0  CID100005470  CID000444008  C0043094  PT  C0043094   \n",
       "4  BE0000123        111.0  CID100005516  CID003005572  C0043094  PT  C0043094   \n",
       "5  BE0000123        111.0  CID100040973  CID000040973  C0020538  PT  C0020538   \n",
       "\n",
       "                  5    drug_name  number_of_targets  sample_num  \n",
       "1       Hypotension   argatroban                1.0         0.0  \n",
       "2  Weight increased     tibolone                1.0         0.0  \n",
       "3  Weight increased     tibolone                1.0         0.0  \n",
       "4  Weight increased   toremifene                2.0         0.0  \n",
       "5      Hypertension  desogestrel                2.0         1.0  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df29 = df28.dropna(axis=0)\n",
    "df29.head()\n",
    "#df29 contains all drugs that have at most two targets and all targets that have at least two drugs targeting it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['argatroban', 'tibolone', 'toremifene', 'desogestrel', 'buspirone',\n",
       "       'domperidone', 'droperidol', 'prochlorperazine', 'tetrabenazine',\n",
       "       'cyclobenzaprine', 'donepezil', 'azelastine', 'carbinoxamine',\n",
       "       'cetirizine', 'clemastine', 'diphenhydramine', 'hydroxyzine',\n",
       "       'ketotifen', 'loratadine', 'cyclizine', 'furosemide', 'cevimeline',\n",
       "       'dicyclomine', 'trospium', 'ergonovine', 'naphazoline',\n",
       "       'flurbiprofen', 'ketorolac', 'meloxicam', 'nabumetone',\n",
       "       'oxaprozin', 'rofecoxib', 'salsalate', 'tolmetin', 'parecoxib',\n",
       "       'etoricoxib', 'nepafenac', 'piroxicam', 'methacholine',\n",
       "       'guanfacine', 'methyldopa', 'moxonidine', 'dexmedetomidine',\n",
       "       'bicalutamide', 'nilutamide', 'glipizide', 'nateglinide',\n",
       "       'repaglinide', 'telmisartan', 'acebutolol', 'atenolol',\n",
       "       'betaxolol', 'bisoprolol', 'carteolol', 'levobunolol',\n",
       "       'metoprolol', 'nadolol', 'pirbuterol', 'metipranolol', 'nebivolol',\n",
       "       'indacaterol', 'protriptyline', 'diethylpropion', 'reboxetine',\n",
       "       'desvenlafaxine', 'lorcaserin', 'fluvoxamine', 'cyclophosphamide',\n",
       "       'ifosfamide', 'mephenytoin', 'ritonavir', 'rifaximin', 'erlotinib',\n",
       "       'warfarin', 'modafinil', 'lisdexamfetamine', 'zaleplon',\n",
       "       'methohexital', 'esmolol', 'fondaparinux', 'rivaroxaban',\n",
       "       'apixaban', 'oxymorphone', 'hydrocodone', 'alfentanil',\n",
       "       'edrophonium', 'neostigmine', 'rivastigmine', 'sitagliptin',\n",
       "       'vildagliptin', 'linagliptin', 'alogliptin', 'methylprednisolone',\n",
       "       'budesonide', 'clobetasone', 'desoximetasone', 'flunisolide',\n",
       "       'fluocinonide', 'prednisolone', 'prednisone', 'triamcinolone',\n",
       "       'desonide', 'betamethasone', 'rimexolone', 'ciclesonide',\n",
       "       'methylergometrine', 'etravirine', 'gemfibrozil', 'alprazolam',\n",
       "       'clobazam', 'lorazepam', 'alosetron', 'dolasetron', 'granisetron',\n",
       "       'tropisetron', 'palonosetron', 'etoposide', 'mitoxantrone',\n",
       "       'teniposide', 'dexrazoxane', 'valrubicin', 'frovatriptan',\n",
       "       'almotriptan', 'norethisterone', 'tranylcypromine', 'rasagiline',\n",
       "       'mexiletine', 'prilocaine', 'riluzole', 'oxcarbazepine',\n",
       "       'fosphenytoin', 'ranolazine', 'methotrexate', 'trimethoprim',\n",
       "       'gefitinib', 'methocarbamol', 'papaverine', 'fospropofol',\n",
       "       'ivermectin', 'vecuronium', 'cisatracurium', 'mirabegron',\n",
       "       'raltitrexed', 'paricalcitol', 'doxercalciferol', 'didanosine',\n",
       "       'benazepril', 'cilazapril', 'fosinopril', 'ramipril',\n",
       "       'rescinnamine', 'trandolapril', 'perindopril', 'cefaclor',\n",
       "       'cefditoren', 'aliskiren', 'eplerenone', 'phencyclidine',\n",
       "       'omeprazole', 'regadenoson', 'potassium', 'magnesium', 'bretylium',\n",
       "       'nilotinib', 'gemifloxacin', 'gliclazide', 'abacavir', 'efavirenz',\n",
       "       'nevirapine', 'stavudine', 'delavirdine', 'zalcitabine',\n",
       "       'zidovudine', 'emtricitabine', 'capsaicin', 'tadalafil',\n",
       "       'avanafil', 'tacrolimus', 'bupivacaine', 'mepivacaine',\n",
       "       'ropivacaine', 'degarelix', 'cetrorelix', 'fluvastatin',\n",
       "       'pravastatin', 'pentostatin', 'metyrapone', 'candesartan',\n",
       "       'irbesartan', 'losartan', 'valsartan', 'eprosartan', 'olmesartan',\n",
       "       'colchicine', 'vinorelbine', 'vincristine', 'vinflunine',\n",
       "       'irinotecan', 'bosentan', 'ambrisentan', 'macitentan',\n",
       "       'cefpodoxime', 'crizotinib', 'eribulin', 'fluconazole',\n",
       "       'voriconazole', 'posaconazole', 'perampanel', 'ivacaftor',\n",
       "       'ethionamide', 'nabilone', 'rimonabant', 'amikacin', 'tobramycin',\n",
       "       'pamidronate', 'risedronate', 'ibandronate', 'aminoglutethimide',\n",
       "       'anastrozole', 'letrozole', 'testolactone', 'exemestane',\n",
       "       'cabazitaxel', 'aprepitant', 'anagrelide', 'cilostazol',\n",
       "       'milrinone', 'entacapone', 'tolcapone', 'ethosuximide',\n",
       "       'trimethadione', 'methsuximide', 'chlorthalidone', 'torasemide',\n",
       "       'chlorpropamide', 'tolbutamide', 'indapamide', 'metolazone',\n",
       "       'polythiazide', 'vemurafenib', 'trametinib', 'baclofen',\n",
       "       'vigabatrin', 'amprenavir', 'indinavir', 'saquinavir',\n",
       "       'fosamprenavir', 'atazanavir', 'tipranavir', 'darunavir',\n",
       "       'auranofin', 'levetiracetam', 'allopurinol', 'febuxostat',\n",
       "       'temsirolimus', 'everolimus', 'ruxolitinib', 'conivaptan',\n",
       "       'tolvaptan', 'clopidogrel', 'prasugrel', 'ticagrelor',\n",
       "       'hydroxyurea', 'cinacalcet', 'tirofiban', 'diltiazem',\n",
       "       'lercanidipine', 'nitroglycerin', 'nitroprusside', 'lanreotide',\n",
       "       'liraglutide', 'exenatide', 'ofatumumab', 'meropenem',\n",
       "       'olsalazine', 'lansoprazole', 'pantoprazole', 'rabeprazole',\n",
       "       'esomeprazole', 'imiquimod', 'ixabepilone', 'riociguat',\n",
       "       'itraconazole', 'gemeprost', 'travoprost', 'azathioprine',\n",
       "       'rufinamide', 'terbinafine', 'clindamycin', 'lincomycin',\n",
       "       'boceprevir', 'pregabalin', 'carbidopa', 'lomitapide', 'aztreonam',\n",
       "       'halcinonide', 'vismodegib', 'amifostine', 'sofosbuvir',\n",
       "       'nelarabine', 'oxytocin', 'raltegravir', 'dolutegravir',\n",
       "       'hydralazine', 'dantrolene', 'procarbazine', 'dapagliflozin',\n",
       "       'empagliflozin', 'canagliflozin', 'cytarabine', 'bortezomib',\n",
       "       'ivabradine', 'pentamidine', 'nitazoxanide', 'thiabendazole',\n",
       "       'abiraterone', 'nicorandil', 'doxapram', 'rimantadine',\n",
       "       'metformin', 'tesamorelin', 'adefovir', 'belinostat', 'tolazamide',\n",
       "       'miglustat', 'pegaptanib', 'tiagabine', 'pirfenidone',\n",
       "       'lubiprostone', 'foscarnet', 'cidofovir'], dtype=object)"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df29['drug_name'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "331"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df29['drug_name'].unique()) #There are 204 unique drugs that have at least two targets and fit \n",
    "#the criteria that a target must have at least two drugs targeting it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "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>target_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BE0001072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BE0000048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BE0000123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BE0000756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BE0000451</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   target_id\n",
       "0  BE0001072\n",
       "1  BE0000048\n",
       "2  BE0000123\n",
       "3  BE0000756\n",
       "4  BE0000451"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df34 = df21.drop('target_freq', axis=1)\n",
    "df34.head()\n",
    "#"
   ]
  },
  {
   "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>target_id</th>\n",
       "      <th>target_name</th>\n",
       "      <th>target_gene</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BE0001072</td>\n",
       "      <td>Cyclin-dependent kinase 2</td>\n",
       "      <td>CDK2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>BE0000048</td>\n",
       "      <td>Prothrombin</td>\n",
       "      <td>F2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>Estrogen receptor alpha</td>\n",
       "      <td>ESR1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>360</th>\n",
       "      <td>BE0000756</td>\n",
       "      <td>D(2) dopamine receptor</td>\n",
       "      <td>DRD2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>468</th>\n",
       "      <td>BE0000451</td>\n",
       "      <td>5-hydroxytryptamine receptor 2A</td>\n",
       "      <td>HTR2A</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     target_id                      target_name target_gene\n",
       "0    BE0001072        Cyclin-dependent kinase 2        CDK2\n",
       "137  BE0000048                      Prothrombin          F2\n",
       "249  BE0000123          Estrogen receptor alpha        ESR1\n",
       "360  BE0000756           D(2) dopamine receptor        DRD2\n",
       "468  BE0000451  5-hydroxytryptamine receptor 2A       HTR2A"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df35 = pd.merge(df34, indexed_df, on='target_id', how='outer')\n",
    "df36 = df35.drop('drug_id', axis=1)\n",
    "df37 = df36.drop_duplicates()\n",
    "df37.head()\n",
    "#a dataframe with target_id, target_name, and the target_gene\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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>target_id</th>\n",
       "      <th>target_freq</th>\n",
       "      <th>ID</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>PT</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>drug_name</th>\n",
       "      <th>number_of_targets</th>\n",
       "      <th>sample_num</th>\n",
       "      <th>target_name</th>\n",
       "      <th>target_gene</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BE0000048</td>\n",
       "      <td>112.0</td>\n",
       "      <td>CID100002232</td>\n",
       "      <td>CID000092721</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>argatroban</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Prothrombin</td>\n",
       "      <td>F2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111.0</td>\n",
       "      <td>CID100005470</td>\n",
       "      <td>CID000021844</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>tibolone</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Estrogen receptor alpha</td>\n",
       "      <td>ESR1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111.0</td>\n",
       "      <td>CID100005470</td>\n",
       "      <td>CID000444008</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>tibolone</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Estrogen receptor alpha</td>\n",
       "      <td>ESR1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111.0</td>\n",
       "      <td>CID100005516</td>\n",
       "      <td>CID003005572</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>toremifene</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Estrogen receptor alpha</td>\n",
       "      <td>ESR1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111.0</td>\n",
       "      <td>CID100040973</td>\n",
       "      <td>CID000040973</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>Hypertension</td>\n",
       "      <td>desogestrel</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Estrogen receptor alpha</td>\n",
       "      <td>ESR1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   target_id  target_freq            ID             1         2  PT         4  \\\n",
       "0  BE0000048        112.0  CID100002232  CID000092721  C0020649  PT  C0020649   \n",
       "1  BE0000123        111.0  CID100005470  CID000021844  C0043094  PT  C0043094   \n",
       "2  BE0000123        111.0  CID100005470  CID000444008  C0043094  PT  C0043094   \n",
       "3  BE0000123        111.0  CID100005516  CID003005572  C0043094  PT  C0043094   \n",
       "4  BE0000123        111.0  CID100040973  CID000040973  C0020538  PT  C0020538   \n",
       "\n",
       "                  5    drug_name  number_of_targets  sample_num  \\\n",
       "0       Hypotension   argatroban                1.0         0.0   \n",
       "1  Weight increased     tibolone                1.0         0.0   \n",
       "2  Weight increased     tibolone                1.0         0.0   \n",
       "3  Weight increased   toremifene                2.0         0.0   \n",
       "4      Hypertension  desogestrel                2.0         1.0   \n",
       "\n",
       "               target_name target_gene  \n",
       "0              Prothrombin          F2  \n",
       "1  Estrogen receptor alpha        ESR1  \n",
       "2  Estrogen receptor alpha        ESR1  \n",
       "3  Estrogen receptor alpha        ESR1  \n",
       "4  Estrogen receptor alpha        ESR1  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df38 = pd.merge(df29, df37, on='target_id', how='outer')\n",
    "df39 = df38.dropna(axis=0)\n",
    "df39.head()\n",
    "#df39 shows the same data as df39 but also includes the names of drug targets. \n",
    "#Includes all samples (drugs and targets) where drugs have at least two targets\n",
    "#and targets have at least two drugs targeting it\n",
    "\n",
    "#genes --> HTR2A, ESR1, DRD2, ...\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_freq</th>\n",
       "      <th>ID</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>PT</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>drug_name</th>\n",
       "      <th>number_of_targets</th>\n",
       "      <th>sample_num</th>\n",
       "      <th>target_name</th>\n",
       "      <th>target_gene</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1391</th>\n",
       "      <td>BE0000466</td>\n",
       "      <td>2.0</td>\n",
       "      <td>CID102761171</td>\n",
       "      <td>CID002761171</td>\n",
       "      <td>C0020615</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020615</td>\n",
       "      <td>Hypoglycaemia</td>\n",
       "      <td>ethionamide</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Catalase-peroxidase</td>\n",
       "      <td>katG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1392</th>\n",
       "      <td>BE0000466</td>\n",
       "      <td>2.0</td>\n",
       "      <td>CID102761171</td>\n",
       "      <td>CID002761171</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>Weight decreased</td>\n",
       "      <td>ethionamide</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Catalase-peroxidase</td>\n",
       "      <td>katG</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      target_id  target_freq            ID             1         2  PT  \\\n",
       "1391  BE0000466          2.0  CID102761171  CID002761171  C0020615  PT   \n",
       "1392  BE0000466          2.0  CID102761171  CID002761171  C0043096  PT   \n",
       "\n",
       "             4                 5    drug_name  number_of_targets  sample_num  \\\n",
       "1391  C0020615     Hypoglycaemia  ethionamide                2.0         1.0   \n",
       "1392  C0043096  Weight decreased  ethionamide                2.0         1.0   \n",
       "\n",
       "              target_name target_gene  \n",
       "1391  Catalase-peroxidase        katG  \n",
       "1392  Catalase-peroxidase        katG  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df39.loc[df39['target_gene'].isin([\"katG\"])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['BE0000048', 'BE0000123', 'BE0000756', 'BE0000451', 'BE0000442',\n",
       "       'BE0000322', 'BE0000092', 'BE0000501', 'BE0000291', 'BE0000560',\n",
       "       'BE0000262', 'BE0000017', 'BE0000045', 'BE0000289', 'BE0000132',\n",
       "       'BE0000215', 'BE0000694', 'BE0000486', 'BE0000533', 'BE0000749',\n",
       "       'BE0000956', 'BE0000575', 'BE0000795', 'BE0000172', 'BE0000216',\n",
       "       'BE0000770', 'BE0000426', 'BE0000854', 'BE0000794', 'BE0000572',\n",
       "       'BE0000020', 'BE0000647', 'BE0000581', 'BE0000090', 'BE0002050',\n",
       "       'BE0000071', 'BE0004797', 'BE0001594', 'BE0000420', 'BE0000311',\n",
       "       'BE0000742', 'BE0000797', 'BE0000557', 'BE0002196', 'BE0000393',\n",
       "       'BE0000197', 'BE0000659', 'BE0000330', 'BE0002180', 'BE0000767',\n",
       "       'BE0000267', 'BE0000487', 'BE0002345', 'BE0002198', 'BE0000738',\n",
       "       'BE0000685', 'BE0001012', 'BE0000118', 'BE0000324', 'BE0000779',\n",
       "       'BE0000250', 'BE0000221', 'BE0000576', 'BE0000270', 'BE0000329',\n",
       "       'BE0002346', 'BE0004643', 'BE0000668', 'BE0000641', 'BE0003721',\n",
       "       'BE0000924', 'BE0000732', 'BE0000014', 'BE0000366', 'BE0000163',\n",
       "       'BE0000453', 'BE0004136', 'BE0003624', 'BE0001023', 'BE0000182',\n",
       "       'BE0000695', 'BE0000177', 'BE0000203', 'BE0000574', 'BE0000429',\n",
       "       'BE0002214', 'BE0001246', 'BE0000062', 'BE0000143', 'BE0000280',\n",
       "       'BE0000971', 'BE0000521', 'BE0002393', 'BE0000915', 'BE0000246',\n",
       "       'BE0000233', 'BE0000640', 'BE0001195', 'BE0000332', 'BE0000061',\n",
       "       'BE0000279', 'BE0000776', 'BE0002090', 'BE0000736', 'BE0000026',\n",
       "       'BE0000384', 'BE0000436', 'BE0002089', 'BE0000156', 'BE0000483',\n",
       "       'BE0000502', 'BE0000207', 'BE0000419', 'BE0000634', 'BE0000870',\n",
       "       'BE0000217', 'BE0004854', 'BE0000631', 'BE0002425', 'BE0001154',\n",
       "       'BE0002226', 'BE0002204', 'BE0002386', 'BE0000253', 'BE0002408',\n",
       "       'BE0000165', 'BE0000110', 'BE0000325', 'BE0000509', 'BE0000095',\n",
       "       'BE0001155', 'BE0001391', 'BE0000293', 'BE0000414', 'BE0000043',\n",
       "       'BE0000679', 'BE0000134', 'BE0000994', 'BE0000556', 'BE0003528',\n",
       "       'BE0000857', 'BE0000066', 'BE0000744', 'BE0000064', 'BE0000644',\n",
       "       'BE0000944', 'BE0002147', 'BE0000349', 'BE0000155', 'BE0001415',\n",
       "       'BE0000030', 'BE0003578', 'BE0000875', 'BE0002375', 'BE0000359',\n",
       "       'BE0000713', 'BE0004145', 'BE0002340', 'BE0000610', 'BE0000077',\n",
       "       'BE0001143', 'BE0005802', 'BE0003559', 'BE0000577', 'BE0000743',\n",
       "       'BE0004701', 'BE0000368', 'BE0000356', 'BE0002151', 'BE0000951',\n",
       "       'BE0000232', 'BE0004744', 'BE0000790', 'BE0004659', 'BE0000457',\n",
       "       'BE0002403', 'BE0001040', 'BE0000257', 'BE0000546', 'BE0003474',\n",
       "       'BE0000844', 'BE0004855', 'BE0005831', 'BE0000060', 'BE0000439',\n",
       "       'BE0000739', 'BE0004909', 'BE0001192', 'BE0004753', 'BE0000113',\n",
       "       'BE0002348', 'BE0004631', 'BE0000907', 'BE0001002', 'BE0002517',\n",
       "       'BE0002674', 'BE0000548', 'BE0000731', 'BE0000993', 'BE0000344',\n",
       "       'BE0000469', 'BE0002347', 'BE0003580', 'BE0000690', 'BE0002449',\n",
       "       'BE0003583', 'BE0000630', 'BE0000254', 'BE0000625', 'BE0000312',\n",
       "       'BE0008667', 'BE0000091', 'BE0008670', 'BE0009094', 'BE0003518',\n",
       "       'BE0000477', 'BE0002129', 'BE0000466', 'BE0000896', 'BE0000249',\n",
       "       'BE0002397', 'BE0000765', 'BE0003582', 'BE0000343', 'BE0000700',\n",
       "       'BE0001109'], dtype=object)"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df39['target_id'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>target_id</th>\n",
       "      <th>target_freq</th>\n",
       "      <th>ID</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>PT</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>drug_name</th>\n",
       "      <th>number_of_targets</th>\n",
       "      <th>sample_num</th>\n",
       "      <th>target_name</th>\n",
       "      <th>target_gene</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BE0000048</td>\n",
       "      <td>112.0</td>\n",
       "      <td>CID100002232</td>\n",
       "      <td>CID000092721</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>argatroban</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Prothrombin</td>\n",
       "      <td>F2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111.0</td>\n",
       "      <td>CID100005470</td>\n",
       "      <td>CID000021844</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>tibolone</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Estrogen receptor alpha</td>\n",
       "      <td>ESR1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111.0</td>\n",
       "      <td>CID100005516</td>\n",
       "      <td>CID003005572</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>toremifene</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Estrogen receptor alpha</td>\n",
       "      <td>ESR1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111.0</td>\n",
       "      <td>CID100040973</td>\n",
       "      <td>CID000040973</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>Hypertension</td>\n",
       "      <td>desogestrel</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Estrogen receptor alpha</td>\n",
       "      <td>ESR1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111.0</td>\n",
       "      <td>CID100040973</td>\n",
       "      <td>CID000040973</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>desogestrel</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Estrogen receptor alpha</td>\n",
       "      <td>ESR1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>BE0000123</td>\n",
       "      <td>111.0</td>\n",
       "      <td>CID100040973</td>\n",
       "      <td>CID000040973</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>Weight decreased</td>\n",
       "      <td>desogestrel</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Estrogen receptor alpha</td>\n",
       "      <td>ESR1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>BE0000756</td>\n",
       "      <td>108.0</td>\n",
       "      <td>CID100002477</td>\n",
       "      <td>CID000002477</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>Hypertension</td>\n",
       "      <td>buspirone</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>D(2) dopamine receptor</td>\n",
       "      <td>DRD2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>BE0000756</td>\n",
       "      <td>108.0</td>\n",
       "      <td>CID100002477</td>\n",
       "      <td>CID000002477</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>buspirone</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>D(2) dopamine receptor</td>\n",
       "      <td>DRD2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>BE0000756</td>\n",
       "      <td>108.0</td>\n",
       "      <td>CID100002477</td>\n",
       "      <td>CID000002477</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>buspirone</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>D(2) dopamine receptor</td>\n",
       "      <td>DRD2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>BE0000756</td>\n",
       "      <td>108.0</td>\n",
       "      <td>CID100002477</td>\n",
       "      <td>CID000002477</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043096</td>\n",
       "      <td>Weight decreased</td>\n",
       "      <td>buspirone</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>D(2) dopamine receptor</td>\n",
       "      <td>DRD2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>BE0000756</td>\n",
       "      <td>108.0</td>\n",
       "      <td>CID100003151</td>\n",
       "      <td>CID000003151</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>domperidone</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>D(2) dopamine receptor</td>\n",
       "      <td>DRD2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>BE0000756</td>\n",
       "      <td>108.0</td>\n",
       "      <td>CID100003168</td>\n",
       "      <td>CID000003168</td>\n",
       "      <td>C0020456</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020456</td>\n",
       "      <td>Hyperglycaemia</td>\n",
       "      <td>droperidol</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>D(2) dopamine receptor</td>\n",
       "      <td>DRD2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>BE0000756</td>\n",
       "      <td>108.0</td>\n",
       "      <td>CID100003168</td>\n",
       "      <td>CID000003168</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020538</td>\n",
       "      <td>Hypertension</td>\n",
       "      <td>droperidol</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>D(2) dopamine receptor</td>\n",
       "      <td>DRD2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>BE0000756</td>\n",
       "      <td>108.0</td>\n",
       "      <td>CID100003168</td>\n",
       "      <td>CID000003168</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>droperidol</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>D(2) dopamine receptor</td>\n",
       "      <td>DRD2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>BE0000756</td>\n",
       "      <td>108.0</td>\n",
       "      <td>CID100003168</td>\n",
       "      <td>CID000003168</td>\n",
       "      <td>C0497247</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0497247</td>\n",
       "      <td>Blood pressure increased</td>\n",
       "      <td>droperidol</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>D(2) dopamine receptor</td>\n",
       "      <td>DRD2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>BE0000756</td>\n",
       "      <td>108.0</td>\n",
       "      <td>CID100004917</td>\n",
       "      <td>CID000004917</td>\n",
       "      <td>C0020456</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020456</td>\n",
       "      <td>Hyperglycaemia</td>\n",
       "      <td>prochlorperazine</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>D(2) dopamine receptor</td>\n",
       "      <td>DRD2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>BE0000756</td>\n",
       "      <td>108.0</td>\n",
       "      <td>CID100004917</td>\n",
       "      <td>CID000004917</td>\n",
       "      <td>C0020615</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020615</td>\n",
       "      <td>Hypoglycaemia</td>\n",
       "      <td>prochlorperazine</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>D(2) dopamine receptor</td>\n",
       "      <td>DRD2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>BE0000756</td>\n",
       "      <td>108.0</td>\n",
       "      <td>CID100004917</td>\n",
       "      <td>CID000004917</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>prochlorperazine</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>D(2) dopamine receptor</td>\n",
       "      <td>DRD2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>BE0000756</td>\n",
       "      <td>108.0</td>\n",
       "      <td>CID100004917</td>\n",
       "      <td>CID000004917</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0043094</td>\n",
       "      <td>Weight increased</td>\n",
       "      <td>prochlorperazine</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>D(2) dopamine receptor</td>\n",
       "      <td>DRD2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>BE0000756</td>\n",
       "      <td>108.0</td>\n",
       "      <td>CID100006018</td>\n",
       "      <td>CID000006018</td>\n",
       "      <td>C0857353</td>\n",
       "      <td>PT</td>\n",
       "      <td>C0020649</td>\n",
       "      <td>Hypotension</td>\n",
       "      <td>tetrabenazine</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>D(2) dopamine receptor</td>\n",
       "      <td>DRD2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    target_id  target_freq            ID             1         2  PT  \\\n",
       "0   BE0000048        112.0  CID100002232  CID000092721  C0020649  PT   \n",
       "1   BE0000123        111.0  CID100005470  CID000021844  C0043094  PT   \n",
       "3   BE0000123        111.0  CID100005516  CID003005572  C0043094  PT   \n",
       "4   BE0000123        111.0  CID100040973  CID000040973  C0020538  PT   \n",
       "5   BE0000123        111.0  CID100040973  CID000040973  C0043094  PT   \n",
       "6   BE0000123        111.0  CID100040973  CID000040973  C0043096  PT   \n",
       "7   BE0000756        108.0  CID100002477  CID000002477  C0020538  PT   \n",
       "8   BE0000756        108.0  CID100002477  CID000002477  C0020649  PT   \n",
       "9   BE0000756        108.0  CID100002477  CID000002477  C0043094  PT   \n",
       "10  BE0000756        108.0  CID100002477  CID000002477  C0043096  PT   \n",
       "11  BE0000756        108.0  CID100003151  CID000003151  C0020649  PT   \n",
       "12  BE0000756        108.0  CID100003168  CID000003168  C0020456  PT   \n",
       "13  BE0000756        108.0  CID100003168  CID000003168  C0020538  PT   \n",
       "14  BE0000756        108.0  CID100003168  CID000003168  C0020649  PT   \n",
       "15  BE0000756        108.0  CID100003168  CID000003168  C0497247  PT   \n",
       "16  BE0000756        108.0  CID100004917  CID000004917  C0020456  PT   \n",
       "17  BE0000756        108.0  CID100004917  CID000004917  C0020615  PT   \n",
       "18  BE0000756        108.0  CID100004917  CID000004917  C0020649  PT   \n",
       "19  BE0000756        108.0  CID100004917  CID000004917  C0043094  PT   \n",
       "20  BE0000756        108.0  CID100006018  CID000006018  C0857353  PT   \n",
       "\n",
       "           4                         5         drug_name  number_of_targets  \\\n",
       "0   C0020649               Hypotension        argatroban                1.0   \n",
       "1   C0043094          Weight increased          tibolone                1.0   \n",
       "3   C0043094          Weight increased        toremifene                2.0   \n",
       "4   C0020538              Hypertension       desogestrel                2.0   \n",
       "5   C0043094          Weight increased       desogestrel                2.0   \n",
       "6   C0043096          Weight decreased       desogestrel                2.0   \n",
       "7   C0020538              Hypertension         buspirone                2.0   \n",
       "8   C0020649               Hypotension         buspirone                2.0   \n",
       "9   C0043094          Weight increased         buspirone                2.0   \n",
       "10  C0043096          Weight decreased         buspirone                2.0   \n",
       "11  C0020649               Hypotension       domperidone                2.0   \n",
       "12  C0020456            Hyperglycaemia        droperidol                2.0   \n",
       "13  C0020538              Hypertension        droperidol                2.0   \n",
       "14  C0020649               Hypotension        droperidol                2.0   \n",
       "15  C0497247  Blood pressure increased        droperidol                2.0   \n",
       "16  C0020456            Hyperglycaemia  prochlorperazine                1.0   \n",
       "17  C0020615             Hypoglycaemia  prochlorperazine                1.0   \n",
       "18  C0020649               Hypotension  prochlorperazine                1.0   \n",
       "19  C0043094          Weight increased  prochlorperazine                1.0   \n",
       "20  C0020649               Hypotension     tetrabenazine                2.0   \n",
       "\n",
       "    sample_num              target_name target_gene  \n",
       "0          0.0              Prothrombin          F2  \n",
       "1          0.0  Estrogen receptor alpha        ESR1  \n",
       "3          0.0  Estrogen receptor alpha        ESR1  \n",
       "4          1.0  Estrogen receptor alpha        ESR1  \n",
       "5          1.0  Estrogen receptor alpha        ESR1  \n",
       "6          1.0  Estrogen receptor alpha        ESR1  \n",
       "7          1.0   D(2) dopamine receptor        DRD2  \n",
       "8          1.0   D(2) dopamine receptor        DRD2  \n",
       "9          1.0   D(2) dopamine receptor        DRD2  \n",
       "10         1.0   D(2) dopamine receptor        DRD2  \n",
       "11         0.0   D(2) dopamine receptor        DRD2  \n",
       "12         0.0   D(2) dopamine receptor        DRD2  \n",
       "13         0.0   D(2) dopamine receptor        DRD2  \n",
       "14         0.0   D(2) dopamine receptor        DRD2  \n",
       "15         0.0   D(2) dopamine receptor        DRD2  \n",
       "16         0.0   D(2) dopamine receptor        DRD2  \n",
       "17         0.0   D(2) dopamine receptor        DRD2  \n",
       "18         0.0   D(2) dopamine receptor        DRD2  \n",
       "19         0.0   D(2) dopamine receptor        DRD2  \n",
       "20         1.0   D(2) dopamine receptor        DRD2  "
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "np.set_printoptions(threshold=np.inf)\n",
    "df40 = df39\n",
    "df41 = df40.drop_duplicates(subset = ['target_name','target_freq', 5,'drug_name', 'target_id', 'target_gene', 'number_of_targets'])\n",
    "df41.head(20)\n",
    "#df41 is the final atrtribute list. It includes all data and all attribtues that fits under our criteria\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['F2', 'ESR1', 'DRD2', 'HTR2A', 'HRH1', 'CA2', 'CHRM1', 'ADRA1A',\n",
       "       'HTR1A', 'CHRM2', 'PTGS2', 'PTGS1', 'CHRM3', 'ADRA2A', 'AR',\n",
       "       'PPARG', 'ADRB2', 'SLC6A2', 'HTR2C', 'SLC6A4', 'NR1I2', 'ADRA1B',\n",
       "       'GABRA1', 'ADRB1', 'F10', 'OPRM1', 'ACHE', 'DPP4', 'NR3C1',\n",
       "       'ADRA2B', 'DRD1', 'SLC6A3', 'DRD3', 'KCNH2', 'gag-pol', 'PPARA',\n",
       "       'OPRD1', 'HTR3A', 'TOP2A', 'HTR1B', 'PGR', 'MAOB', 'HTR2B',\n",
       "       'SCN5A', 'HTR1D', 'DHFR', 'BCHE', 'EGFR', 'CA1', 'PDE4B', 'GABRB3',\n",
       "       'MAOA', 'CHRNA2', 'SHBG', 'ADRB3', 'SLC18A2', 'TYMS', 'VDR', 'PNP',\n",
       "       'ACE', 'pbpA', 'REN', 'HSD11B1', 'GABRB2', 'pbp3', 'NR3C2',\n",
       "       'GRIN3A', 'AHR', 'ADORA2A', 'ATP1A1', 'ABL1', 'gyrA', 'VEGFA',\n",
       "       'KIT', 'pol', 'penA', 'TRPV1', 'PDE5A', 'FKBP1A', 'SCN10A',\n",
       "       'GNRHR', 'HMGCR', 'parC', 'ADA', 'camC', 'AGTR1', 'TUBB',\n",
       "       'SERPINC1', 'TOP1', 'EDNRA', 'ftsI', 'MET', 'BCL2', 'ERG11',\n",
       "       'GRIA1', 'CFTR', 'inhA', 'CNR1', 'rpsL', 'FDPS', 'CYP19A1', 'TSPO',\n",
       "       'TUBB1', 'TACR1', 'PDE3A', 'COMT', 'SIGMAR1', 'CACNA1G', 'SLC12A1',\n",
       "       'ABCC8', 'SLC12A3', 'BRAF', 'MAP2K1', 'GABBR1', 'PDE10A', 'TOP2B',\n",
       "       'IKBKB', 'CACNA1B', 'XDH', 'MTOR', 'ABAT', 'JAK2', 'AVPR1A',\n",
       "       'P2RY12', 'RRM1', 'CASR', 'CNR2', 'ITGB3', 'TUBA4A', 'AVPR2',\n",
       "       'GLRA3', 'EDNRB', 'CACNG1', 'LHCGR', 'LTF', 'NPR1', 'SSTR2',\n",
       "       'GLP1R', 'MS4A1', 'dacB', 'PTGER1', 'KCNJ1', 'IFNG', 'SSTR5',\n",
       "       'ATP4A', 'TLR7', 'TUBB3', 'SLC7A11', 'GUCY1A2', 'CYP51A1',\n",
       "       'PTGER3', 'ALK', 'VKORC1', 'JAK1', 'GABBR2', 'PTGFR', 'HPRT1',\n",
       "       'SCN9A', 'GPR55', 'PGD', 'SQLE', 'rplJ', 'NS3/4A', 'PTGER2',\n",
       "       'CACNA1A', 'DDC', 'SULT1E1', 'MTTP', 'MAP2K2', 'pbpC', 'SMO',\n",
       "       'ENPP1', 'NS5b', 'JUN', 'rpoB', 'POLA1', 'MAPT', 'OXTR', 'BDKRB1',\n",
       "       'P4HA1', 'ITGA2B', 'RYR1', 'GRM5', 'SLC5A2', 'POLB', 'PSMB5',\n",
       "       'HCN2', 'PRDX5', 'AOC3', 'TRDMT1', 'por', 'frdA', 'CYP11B1',\n",
       "       'SV2A', 'CYP17A1', 'ABCC9', 'PSMB1', 'NISCH', 'TERT', 'KCNK9', 'M',\n",
       "       'PRKAB1', 'GHRHR', 'P', 'HDAC1', 'TOP1MT', 'SFRP4', 'TLR8', 'UGCG',\n",
       "       'NRP1', 'katG', 'ALPPL2', 'SLC6A1', 'FURIN', 'CLCN2', 'KCNK3',\n",
       "       'UL54', 'FPGS', 'RAC1'], dtype=object)"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gene_analysis = df41['target_gene'].unique()\n",
    "gene_analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "df42 = df41.loc[df41[5].isin([\"Hyperglycaemia\",\"Blood glucose increased\"])]\n",
    "gene_analysis = df42['target_gene'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['DRD2', 'HTR2A', 'CA2', 'CHRM1', 'ADRA1A', 'PTGS2', 'PTGS1',\n",
       "       'CHRM3', 'ADRA2A', 'AR', 'PPARG', 'ADRB2', 'SLC6A2', 'SLC6A4',\n",
       "       'NR1I2', 'ADRA1B', 'GABRA1', 'ADRB1', 'ACHE', 'DPP4', 'NR3C1',\n",
       "       'SLC6A3', 'KCNH2', 'gag-pol', 'HTR3A', 'TOP2A', 'HTR1B', 'SCN5A',\n",
       "       'HTR1D', 'BCHE', 'PNP', 'ACE', 'pbpA', 'HSD11B1', 'NR3C2', 'ABL1',\n",
       "       'gyrA', 'VEGFA', 'KIT', 'pol', 'penA', 'PDE5A', 'FKBP1A', 'SCN10A',\n",
       "       'GNRHR', 'parC', 'AGTR1', 'TUBB', 'EDNRA', 'ftsI', 'BCL2', 'ERG11',\n",
       "       'CFTR', 'rpsL', 'TSPO', 'TUBB1', 'TACR1', 'PDE3A', 'COMT',\n",
       "       'SLC12A1', 'ABCC8', 'SLC12A3', 'MAP2K1', 'GABBR1', 'XDH', 'MTOR',\n",
       "       'AVPR1A', 'TUBA4A', 'AVPR2', 'EDNRB', 'CACNG1', 'LTF', 'SSTR2',\n",
       "       'SSTR5', 'ATP4A', 'TLR7', 'CYP51A1', 'GABBR2', 'NS3/4A', 'CACNA1A',\n",
       "       'MAP2K2', 'SMO', 'JUN', 'rpoB', 'POLA1', 'MAPT', 'POLB', 'PSMB5',\n",
       "       'TRDMT1', 'frdA', 'CYP17A1', 'PSMB1', 'GHRHR', 'TLR8', 'SLC6A1',\n",
       "       'UL54'], dtype=object)"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df42['target_gene'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "string_to_write = \"\\n\".join(gene_analysis)\n",
    "with open(\"analysis_gene5.txt\", \"w\") as f:\n",
    "    f.write(string_to_write)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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