Vaccines_Trial_Phases.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 430,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Installing libraries\n",
    "import pandas as pd\n",
    "import altair as alt\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import dateutil.parser\n",
    "import math\n",
    "from datetime import date\n",
    "from datetime import datetime, timedelta\n",
    "from vega_datasets import data\n",
    "import altair as alt\n",
    "import squarify \n",
    "import re\n",
    "import camelot\n",
    "import numpy as np\n",
    "alt.data_transformers.disable_max_rows()\n",
    "#alt.data_transformers.enable('json')\n",
    "pd.set_option('mode.chained_assignment', None)\n",
    "pd.set_option(\"display.max_rows\", 500)\n",
    "plt.rcParams['pdf.fonttype'] = 42\n",
    "plt.rcParams['ps.fonttype'] = 42\n",
    "\n",
    "today = date.today()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data sources\n",
    "\n",
    "This analysis is based on two different data sources that are structured differently and thus used to answer different questions as part of this analysis.\n",
    "\n",
    "In the dataset provided by the **WHO**, each row corresponds to one developer and their vaccine candidate. In this analysis, this dataset (called \"wf\") is used to \n",
    "* show how many vaccine candidates are in which phase\n",
    "* classify the vaccine candidates according to their type, and subsequently also phase\n",
    "\n",
    "\n",
    "In the dataset compiled by the **London School of Hygiene and Tropical Medicine (LSHTM)**, each row corresponds to a registered clinical trial -- accordingly, a developer team testing their vaccine in multiple phases in parallel will see multiple entries in this dataset. In this analysis, this dataset (called \"lf\") is used to\n",
    "* show trial sizes by company\n",
    "* provide estimates (min, max, median) of the clinical phases"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How many vaccine candidates are there in each phase? (WHO data question)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 431,
   "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>COVID-19 Vaccine developer/manufacturer</th>\n",
       "      <th>Vaccine platform</th>\n",
       "      <th>Preclinical</th>\n",
       "      <th>Phase 1</th>\n",
       "      <th>Phase 1/2</th>\n",
       "      <th>Phase 2</th>\n",
       "      <th>Phase 3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sinovac</td>\n",
       "      <td>Inactivated</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>x</td>\n",
       "      <td>NaN</td>\n",
       "      <td>x</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Wuhan Institute of Biological Products/Sinopharm</td>\n",
       "      <td>Inactivated</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>x</td>\n",
       "      <td>NaN</td>\n",
       "      <td>x</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Beijing Institute of Biological Products/Sinop...</td>\n",
       "      <td>Inactivated</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>x</td>\n",
       "      <td>NaN</td>\n",
       "      <td>x</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Bharat Biotech</td>\n",
       "      <td>Inactivated</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>x</td>\n",
       "      <td>NaN</td>\n",
       "      <td>x</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>University of Oxford/AstraZeneca</td>\n",
       "      <td>Non-Replicating Viral Vector</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>x</td>\n",
       "      <td>x</td>\n",
       "      <td>x</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             COVID-19 Vaccine developer/manufacturer  \\\n",
       "0                                            Sinovac   \n",
       "1   Wuhan Institute of Biological Products/Sinopharm   \n",
       "2  Beijing Institute of Biological Products/Sinop...   \n",
       "3                                     Bharat Biotech   \n",
       "4                   University of Oxford/AstraZeneca   \n",
       "\n",
       "               Vaccine platform Preclinical Phase 1 Phase 1/2 Phase 2 Phase 3  \n",
       "0                   Inactivated         NaN     NaN         x     NaN       x  \n",
       "1                   Inactivated         NaN     NaN         x     NaN       x  \n",
       "2                   Inactivated         NaN     NaN         x     NaN       x  \n",
       "3                   Inactivated         NaN     NaN         x     NaN       x  \n",
       "4  Non-Replicating Viral Vector         NaN     NaN         x       x       x  "
      ]
     },
     "execution_count": 431,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wf = pd.read_csv('data/WHO-VaccineCandidates_2020-11-12.csv', delimiter = ';') #delimiter= ';'\n",
    "wf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 432,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12215edd8>"
      ]
     },
     "execution_count": 432,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#the majority of developers only has one entry, thus only one vaccine candidate in the works\n",
    "wf['COVID-19 Vaccine developer/manufacturer'].value_counts().hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 433,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "187"
      ]
     },
     "execution_count": 433,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#number of unique teams\n",
    "wf['COVID-19 Vaccine developer/manufacturer'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 434,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "210"
      ]
     },
     "execution_count": 434,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(wf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 435,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "COVID-19 Vaccine developer/manufacturer    210\n",
       "Vaccine platform                           210\n",
       "Preclinical                                162\n",
       "Phase 1                                     29\n",
       "Phase 1/2                                   23\n",
       "Phase 2                                      9\n",
       "Phase 3                                     11\n",
       "Name: count, dtype: object"
      ]
     },
     "execution_count": 435,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#display count of elements (not unique counts)\n",
    "wf.describe().iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 436,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Phase</th>\n",
       "      <th>#_candidates-2020-11-26</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>COVID-19 Vaccine developer/manufacturer</td>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Vaccine platform</td>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Preclinical</td>\n",
       "      <td>162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Phase 1</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Phase 1/2</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Phase 2</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Phase 3</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Phase #_candidates-2020-11-26\n",
       "0  COVID-19 Vaccine developer/manufacturer                     210\n",
       "1                         Vaccine platform                     210\n",
       "2                              Preclinical                     162\n",
       "3                                  Phase 1                      29\n",
       "4                                Phase 1/2                      23\n",
       "5                                  Phase 2                       9\n",
       "6                                  Phase 3                      11"
      ]
     },
     "execution_count": 436,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "candidates_by_phase = wf.describe().iloc[0].rename_axis('Phase').reset_index(name='#_candidates-'+str(today))\n",
    "#candidates_by_phase = candidates_by_phase.drop([0,1])\n",
    "candidates_by_phase.to_csv('data/tracker-start.csv', index = False)\n",
    "candidates_by_phase"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 437,
   "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",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Phase</th>\n",
       "      <th>#_candidates-2020-11-26</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>COVID-19 Vaccine developer/manufacturer</td>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Vaccine platform</td>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Preclinical</td>\n",
       "      <td>162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Phase 1</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Phase 1/2</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Phase 2</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Phase 3</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Phase  #_candidates-2020-11-26\n",
       "0  COVID-19 Vaccine developer/manufacturer                      210\n",
       "1                         Vaccine platform                      210\n",
       "2                              Preclinical                      162\n",
       "3                                  Phase 1                       29\n",
       "4                                Phase 1/2                       23\n",
       "5                                  Phase 2                        9\n",
       "6                                  Phase 3                       11"
      ]
     },
     "execution_count": 437,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# make timeline\n",
    "candidates_phase_TL = pd.read_csv('data/tracker-start.csv')\n",
    "#candidates_phase_TL = candidates_phase_TL.merge(candidates_by_phase, left_on='Phase', right_on='Phase')\n",
    "candidates_phase_TL.to_csv('data/tracker-updated.csv')\n",
    "candidates_phase_TL"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## What vaccine types are investigated and how far along are they? (WHO data question)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 438,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Vaccine platform\n",
       "Protein Subunit                 70\n",
       "RNA                             28\n",
       "Non-Replicating Viral Vector    28\n",
       "Replicating Viral Vector        21\n",
       "Inactivated                     21\n",
       "DNA                             19\n",
       "VLP                             18\n",
       "Live Attenuated Virus            3\n",
       "T-cell based                     1\n",
       "Replicating Bacteria Vector      1\n",
       "Name: COVID-19 Vaccine developer/manufacturer, dtype: int64"
      ]
     },
     "execution_count": 438,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# number of developers pursuing different platforms\n",
    "wf.groupby(by='Vaccine platform')['COVID-19 Vaccine developer/manufacturer'].count().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 439,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>COVID-19 Vaccine developer/manufacturer</th>\n",
       "      <th>Preclinical</th>\n",
       "      <th>Phase 1</th>\n",
       "      <th>Phase 1/2</th>\n",
       "      <th>Phase 2</th>\n",
       "      <th>Phase 3</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vaccine platform</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DNA</th>\n",
       "      <td>19</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Inactivated</th>\n",
       "      <td>21</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Live Attenuated Virus</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Non-Replicating Viral Vector</th>\n",
       "      <td>28</td>\n",
       "      <td>19</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Protein Subunit</th>\n",
       "      <td>70</td>\n",
       "      <td>55</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RNA</th>\n",
       "      <td>28</td>\n",
       "      <td>22</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Replicating Bacteria Vector</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Replicating Viral Vector</th>\n",
       "      <td>21</td>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T-cell based</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VLP</th>\n",
       "      <td>18</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              COVID-19 Vaccine developer/manufacturer  \\\n",
       "Vaccine platform                                                        \n",
       "DNA                                                                19   \n",
       "Inactivated                                                        21   \n",
       "Live Attenuated Virus                                               3   \n",
       "Non-Replicating Viral Vector                                       28   \n",
       "Protein Subunit                                                    70   \n",
       "RNA                                                                28   \n",
       "Replicating Bacteria Vector                                         1   \n",
       "Replicating Viral Vector                                           21   \n",
       "T-cell based                                                        1   \n",
       "VLP                                                                18   \n",
       "\n",
       "                              Preclinical  Phase 1  Phase 1/2  Phase 2  \\\n",
       "Vaccine platform                                                         \n",
       "DNA                                    14        1          4        0   \n",
       "Inactivated                            14        2          7        0   \n",
       "Live Attenuated Virus                   3        0          0        0   \n",
       "Non-Replicating Viral Vector           19        6          3        4   \n",
       "Protein Subunit                        55       11          5        2   \n",
       "RNA                                    22        5          2        2   \n",
       "Replicating Bacteria Vector             1        0          0        0   \n",
       "Replicating Viral Vector               17        3          1        1   \n",
       "T-cell based                            1        0          0        0   \n",
       "VLP                                    16        1          1        0   \n",
       "\n",
       "                              Phase 3  \n",
       "Vaccine platform                       \n",
       "DNA                                 0  \n",
       "Inactivated                         4  \n",
       "Live Attenuated Virus               0  \n",
       "Non-Replicating Viral Vector        4  \n",
       "Protein Subunit                     1  \n",
       "RNA                                 2  \n",
       "Replicating Bacteria Vector         0  \n",
       "Replicating Viral Vector            0  \n",
       "T-cell based                        0  \n",
       "VLP                                 0  "
      ]
     },
     "execution_count": 439,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# what is counted is whether the entry is not NaN - not how many elements an entry consists of\n",
    "wf.groupby(by='Vaccine platform').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 440,
   "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>Vaccine platform</th>\n",
       "      <th>sum_candidates_by_type</th>\n",
       "      <th>Preclinical</th>\n",
       "      <th>Phase 1</th>\n",
       "      <th>Phase 1/2</th>\n",
       "      <th>Phase 2</th>\n",
       "      <th>Phase 3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Protein Subunit</td>\n",
       "      <td>74</td>\n",
       "      <td>55</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Non-Replicating Viral Vector</td>\n",
       "      <td>36</td>\n",
       "      <td>19</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>RNA</td>\n",
       "      <td>33</td>\n",
       "      <td>22</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Inactivated</td>\n",
       "      <td>27</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Replicating Viral Vector</td>\n",
       "      <td>22</td>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DNA</td>\n",
       "      <td>19</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>VLP</td>\n",
       "      <td>18</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Live Attenuated Virus</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Replicating Bacteria Vector</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>T-cell based</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Vaccine platform  sum_candidates_by_type  Preclinical  Phase 1  \\\n",
       "4               Protein Subunit                      74           55       11   \n",
       "3  Non-Replicating Viral Vector                      36           19        6   \n",
       "5                           RNA                      33           22        5   \n",
       "1                   Inactivated                      27           14        2   \n",
       "7      Replicating Viral Vector                      22           17        3   \n",
       "0                           DNA                      19           14        1   \n",
       "9                           VLP                      18           16        1   \n",
       "2         Live Attenuated Virus                       3            3        0   \n",
       "6   Replicating Bacteria Vector                       1            1        0   \n",
       "8                  T-cell based                       1            1        0   \n",
       "\n",
       "   Phase 1/2  Phase 2  Phase 3  \n",
       "4          5        2        1  \n",
       "3          3        4        4  \n",
       "5          2        2        2  \n",
       "1          7        0        4  \n",
       "7          1        1        0  \n",
       "0          4        0        0  \n",
       "9          1        0        0  \n",
       "2          0        0        0  \n",
       "6          0        0        0  \n",
       "8          0        0        0  "
      ]
     },
     "execution_count": 440,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "platforms = wf.groupby(by='Vaccine platform').count()\n",
    "platforms = platforms[['Preclinical', 'Phase 1', 'Phase 1/2', 'Phase 2', 'Phase 3']]\n",
    "platforms['Vaccine platform'] = platforms.index\n",
    "platforms['sum_candidates_by_type'] = platforms['Preclinical'] + platforms['Phase 1'] +platforms['Phase 1/2'] +platforms['Phase 2'] +platforms['Phase 3']\n",
    "platforms.sort_values(by='sum_candidates_by_type', ascending = False)\n",
    "platforms = platforms[['Vaccine platform','sum_candidates_by_type','Preclinical', 'Phase 1', 'Phase 1/2', 'Phase 2', 'Phase 3']].reset_index(drop=True)\n",
    "platforms.sort_values(by='sum_candidates_by_type', ascending =False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 441,
   "metadata": {},
   "outputs": [],
   "source": [
    "platform_plot = platforms.copy()\n",
    "platform_plot = platform_plot[['Vaccine platform','Preclinical', 'Phase 1', 'Phase 1/2', 'Phase 2', 'Phase 3']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 442,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# make stacked bar of counts per phase \n",
    "columns=['Preclinical','Phase 1', 'Phase 1/2', 'Phase 2', 'Phase 3']\n",
    "platform_plot.sort_values(by='Preclinical').plot(kind='barh', stacked=True, x='Vaccine platform')\n",
    "plt.savefig('charts/drafts/vaccine_types-'+str(today)+'.pdf', transparent = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How many trials does each research team run and what is their size? (LSHTM data question)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 443,
   "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>Institutes</th>\n",
       "      <th>Phase</th>\n",
       "      <th>Vaccine</th>\n",
       "      <th>Platform</th>\n",
       "      <th>N</th>\n",
       "      <th>Age (years)</th>\n",
       "      <th>N doses</th>\n",
       "      <th>Rand.</th>\n",
       "      <th>Design</th>\n",
       "      <th>Location</th>\n",
       "      <th>Start date</th>\n",
       "      <th>Primary completion date</th>\n",
       "      <th>Trial number</th>\n",
       "      <th>Status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Janssen Pharmaceutical Companies</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Janssen Ad26.COV2.S</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>60000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>USA, Argentina, Brazil, others</td>\n",
       "      <td>07/09/2020</td>\n",
       "      <td>10/03/2023</td>\n",
       "      <td>NCT04505722</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Beijing Institute of Biological Products/Wuhan...</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>WIBP/BIBP/Sinopharm vaccines</td>\n",
       "      <td>Inactivated</td>\n",
       "      <td>45000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Bahrain, Jordan, Egypt, UAE</td>\n",
       "      <td>16/07/2020</td>\n",
       "      <td>16/03/2021</td>\n",
       "      <td>NCT04510207</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BioNTech/Fosun Pharma/Pfizer</td>\n",
       "      <td>Phase II/III</td>\n",
       "      <td>BioNTech BNT162 (b1/b2)</td>\n",
       "      <td>RNA</td>\n",
       "      <td>43998</td>\n",
       "      <td>≥12</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind, dose-finding</td>\n",
       "      <td>USA, Argentina, Brazil, others</td>\n",
       "      <td>29/04/2020</td>\n",
       "      <td>13/06/2021</td>\n",
       "      <td>NCT04368728</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>University of Oxford/AstraZeneca</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Oxford ChAdOx1-S</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>40051</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>USA, Chile, Peru</td>\n",
       "      <td>28/08/2020</td>\n",
       "      <td>22/12/2020</td>\n",
       "      <td>NCT04516746</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CanSino Biological Inc/Beijing Institute of Bi...</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Cansino Ad5-nCoV</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>40000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Pakistan</td>\n",
       "      <td>15/09/2020</td>\n",
       "      <td>30/12/2021</td>\n",
       "      <td>NCT04526990</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Institutes         Phase  \\\n",
       "0                   Janssen Pharmaceutical Companies     Phase III   \n",
       "1  Beijing Institute of Biological Products/Wuhan...     Phase III   \n",
       "2                       BioNTech/Fosun Pharma/Pfizer  Phase II/III   \n",
       "3                   University of Oxford/AstraZeneca     Phase III   \n",
       "4  CanSino Biological Inc/Beijing Institute of Bi...     Phase III   \n",
       "\n",
       "                        Vaccine                      Platform      N  \\\n",
       "0           Janssen Ad26.COV2.S  Non-replicating viral vector  60000   \n",
       "1  WIBP/BIBP/Sinopharm vaccines                   Inactivated  45000   \n",
       "2       BioNTech BNT162 (b1/b2)                           RNA  43998   \n",
       "3              Oxford ChAdOx1-S  Non-replicating viral vector  40051   \n",
       "4              Cansino Ad5-nCoV  Non-replicating viral vector  40000   \n",
       "\n",
       "  Age (years) N doses Rand.                      Design  \\\n",
       "0         ≥18       1   Yes                Double-blind   \n",
       "1         ≥18       2   Yes                Double-blind   \n",
       "2         ≥12       2   Yes  Double-blind, dose-finding   \n",
       "3         ≥18       2   Yes                Double-blind   \n",
       "4         ≥18       1   Yes                Double-blind   \n",
       "\n",
       "                         Location  Start date Primary completion date  \\\n",
       "0  USA, Argentina, Brazil, others  07/09/2020              10/03/2023   \n",
       "1     Bahrain, Jordan, Egypt, UAE  16/07/2020              16/03/2021   \n",
       "2  USA, Argentina, Brazil, others  29/04/2020              13/06/2021   \n",
       "3                USA, Chile, Peru  28/08/2020              22/12/2020   \n",
       "4                        Pakistan  15/09/2020              30/12/2021   \n",
       "\n",
       "  Trial number      Status  \n",
       "0  NCT04505722  Recruiting  \n",
       "1  NCT04510207  Recruiting  \n",
       "2  NCT04368728  Recruiting  \n",
       "3  NCT04516746  Recruiting  \n",
       "4  NCT04526990  Recruiting  "
      ]
     },
     "execution_count": 443,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lf = pd.read_excel('data/VaC_LSHTM_Covid_vaccine_trials_11November2020.xlsx')\n",
    "lf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 444,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "105"
      ]
     },
     "execution_count": 444,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(lf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 445,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "University of Oxford/AstraZeneca                                                             9\n",
       "Sinovac/Instituto Butantan                                                                   7\n",
       "CanSino Biological Inc/Beijing Institute of Biotechnology                                    7\n",
       "Gamaleya Research Institute                                                                  5\n",
       "BioNTech/Fosun Pharma/Pfizer                                                                 5\n",
       "Janssen Pharmaceutical Companies                                                             4\n",
       "Novavax                                                                                      4\n",
       "Bharat Biotech/ICMR/National Institute of Virology                                           3\n",
       "Anhui Zhifei Longcom Biopharmaceutical/Chinese Academy of Sciences                           3\n",
       "Moderna/NIAID                                                                                3\n",
       "CureVac                                                                                      2\n",
       "Inovio Pharmaceuticals/International Vaccine Institute                                       2\n",
       "Beijing Institute of Biological Products/Wuhan Institute of Biological Products/Sinopharm    2\n",
       "PLA Academy of Military Sciences/Walvax Biotech                                              2\n",
       "Beijing Institute of Biological Products/Sinopharm                                           2\n",
       "Institute of Medical Biology,/Chinese Academy of Medical Sciences                            2\n",
       "Beijing Minhai Biotechnology Co Ltd                                                          2\n",
       "Instituto Finlay de Vacunas                                                                  2\n",
       "Wuhan Institute of Biological Products/Sinopharm                                             2\n",
       "Institut Pasteur/Themis/University of Pittsburg/Merck                                        2\n",
       "Osaka University/AnGes/Takara Bio                                                            2\n",
       "Beijing Wantai Biological Pharmacy/Xiamen University                                         1\n",
       "Clover Biopharmaceuticals Inc/GSK/Dynavax                                                    1\n",
       "West China Hospital,/Sichuan University                                                      1\n",
       "Adimmune Corporation                                                                         1\n",
       "SpyBiotech/Serum Institute of India                                                          1\n",
       "Chula Vaccine Research Center/University of Pennsylvania                                     1\n",
       "Kentucky Bioprocessing Inc                                                                   1\n",
       "PLA Academy of Military Sciences                                                             1\n",
       "FBRI SRC VB VECTOR,/Rospotrebnadzor, Koltsovo/(peptide)                                      1\n",
       "University Hospital Tübingen                                                                 1\n",
       "IAVI/Merck                                                                                   1\n",
       "Sanofi Pasteur/GSK                                                                           1\n",
       "Vaxart                                                                                       1\n",
       "Vaxine Pty/Medytox                                                                           1\n",
       "Research Institute for/Biological Safety Problems (inactivated)                              1\n",
       "Medigen Vaccine Biologics Corporation/NAID/Dynavax                                           1\n",
       "University of Queensland/CSL/Seqirus                                                         1\n",
       "Genexine Consortium                                                                          1\n",
       "Shenzhen Geno-Immune Medical Institute/(modified APC)                                        1\n",
       "Zydus Cadila Healthcare Limited (DNA)                                                        1\n",
       "ImmunityBio Inc/NantKwest Inc                                                                1\n",
       "Aivita Biomedical Inc                                                                        1\n",
       "Shenzhen Geno-Immune Medical Institute/(modified DC)                                         1\n",
       "Arcturus/Duke-NUS                                                                            1\n",
       "Israel Institute for Biological Research/Weizmann Institute of Science                       1\n",
       "Covaxx/University of Nebraska Medical Center                                                 1\n",
       "Symvivo                                                                                      1\n",
       "ReiThera/Leukocare/Univercells                                                               1\n",
       "Ludwig Maximilian University of Munich                                                       1\n",
       "Imperial College London                                                                      1\n",
       "Codagenix/Serum Institute of India                                                           1\n",
       "Entos Pharmaceuticals                                                                        1\n",
       "Medicago Inc/GSK/Dynavax                                                                     1\n",
       "Name: Institutes, dtype: int64"
      ]
     },
     "execution_count": 445,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lf['Institutes'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 446,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "54"
      ]
     },
     "execution_count": 446,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#number of research teams (not: single ones but counting conglomerates)\n",
    "lf['Institutes'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 447,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Institutes\n",
       "Janssen Pharmaceutical Companies                                                             91295\n",
       "University of Oxford/AstraZeneca                                                             64487\n",
       "Beijing Institute of Biological Products/Wuhan Institute of Biological Products/Sinopharm    51000\n",
       "BioNTech/Fosun Pharma/Pfizer                                                                 44878\n",
       "Novavax                                                                                      44819\n",
       "CanSino Biological Inc/Beijing Institute of Biotechnology                                    42382\n",
       "Gamaleya Research Institute                                                                  40286\n",
       "Moderna/NIAID                                                                                30720\n",
       "Sinovac/Instituto Butantan                                                                   30438\n",
       "Bharat Biotech/ICMR/National Institute of Virology                                           26879\n",
       "Beijing Institute of Biological Products/Sinopharm                                            5128\n",
       "Wuhan Institute of Biological Products/Sinopharm                                              1864\n",
       "Institute of Medical Biology,/Chinese Academy of Medical Sciences                             1413\n",
       "Beijing Minhai Biotechnology Co Ltd                                                           1180\n",
       "Zydus Cadila Healthcare Limited (DNA)                                                         1048\n",
       "Israel Institute for Biological Research/Weizmann Institute of Science                        1040\n",
       "Anhui Zhifei Longcom Biopharmaceutical/Chinese Academy of Sciences                            1000\n",
       "CureVac                                                                                        975\n",
       "Instituto Finlay de Vacunas                                                                    716\n",
       "Sanofi Pasteur/GSK                                                                             440\n",
       "Institut Pasteur/Themis/University of Pittsburg/Merck                                          350\n",
       "Imperial College London                                                                        320\n",
       "PLA Academy of Military Sciences/Walvax Biotech                                                288\n",
       "Inovio Pharmaceuticals/International Vaccine Institute                                         280\n",
       "SpyBiotech/Serum Institute of India                                                            280\n",
       "IAVI/Merck                                                                                     252\n",
       "Research Institute for/Biological Safety Problems (inactivated)                                244\n",
       "University of Queensland/CSL/Seqirus                                                           216\n",
       "Genexine Consortium                                                                            210\n",
       "Aivita Biomedical Inc                                                                          180\n",
       "Medicago Inc/GSK/Dynavax                                                                       180\n",
       "Kentucky Bioprocessing Inc                                                                     180\n",
       "West China Hospital,/Sichuan University                                                        168\n",
       "Clover Biopharmaceuticals Inc/GSK/Dynavax                                                      150\n",
       "PLA Academy of Military Sciences                                                               144\n",
       "Shenzhen Geno-Immune Medical Institute/(modified APC)                                          100\n",
       "Shenzhen Geno-Immune Medical Institute/(modified DC)                                           100\n",
       "FBRI SRC VB VECTOR,/Rospotrebnadzor, Koltsovo/(peptide)                                        100\n",
       "Chula Vaccine Research Center/University of Pennsylvania                                        96\n",
       "Arcturus/Duke-NUS                                                                               92\n",
       "ReiThera/Leukocare/Univercells                                                                  90\n",
       "Entos Pharmaceuticals                                                                           72\n",
       "Adimmune Corporation                                                                            70\n",
       "Beijing Wantai Biological Pharmacy/Xiamen University                                            60\n",
       "Covaxx/University of Nebraska Medical Center                                                    60\n",
       "Osaka University/AnGes/Takara Bio                                                               60\n",
       "Codagenix/Serum Institute of India                                                              48\n",
       "Vaxart                                                                                          48\n",
       "Medigen Vaccine Biologics Corporation/NAID/Dynavax                                              45\n",
       "Vaxine Pty/Medytox                                                                              40\n",
       "University Hospital Tübingen                                                                    36\n",
       "ImmunityBio Inc/NantKwest Inc                                                                   35\n",
       "Ludwig Maximilian University of Munich                                                          30\n",
       "Symvivo                                                                                         12\n",
       "Name: N, dtype: int64"
      ]
     },
     "execution_count": 447,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#total trial size by institute, irrespective of phase\n",
    "lf.groupby(by='Institutes')['N'].sum().sort_values(ascending = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 448,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x122c382b0>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 448,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# distribution of trial sizes: The majority of research teams currently runs small trials\n",
    "lf.hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 449,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x122c51198>"
      ]
     },
     "execution_count": 449,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# number of research teams by phase\n",
    "lf.groupby(by='Phase')['Institutes'].nunique().plot(kind='bar')\n",
    "#plt.savefig('charts/drafts/Institutes_Phase.pdf', transparent = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 450,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Phase         Institutes                                                                               \n",
       "Phase I       Adimmune Corporation                                                                            70\n",
       "              Anhui Zhifei Longcom Biopharmaceutical/Chinese Academy of Sciences                              50\n",
       "              Beijing Minhai Biotechnology Co Ltd                                                            180\n",
       "              Beijing Wantai Biological Pharmacy/Xiamen University                                            60\n",
       "              BioNTech/Fosun Pharma/Pfizer                                                                   144\n",
       "              CanSino Biological Inc/Beijing Institute of Biotechnology                                      197\n",
       "              Clover Biopharmaceuticals Inc/GSK/Dynavax                                                      150\n",
       "              Codagenix/Serum Institute of India                                                              48\n",
       "              Covaxx/University of Nebraska Medical Center                                                    60\n",
       "              CureVac                                                                                        284\n",
       "              IAVI/Merck                                                                                     252\n",
       "              ImmunityBio Inc/NantKwest Inc                                                                   35\n",
       "              Imperial College London                                                                        320\n",
       "              Inovio Pharmaceuticals/International Vaccine Institute                                         120\n",
       "              Institut Pasteur/Themis/University of Pittsburg/Merck                                           90\n",
       "              Instituto Finlay de Vacunas                                                                     40\n",
       "              Janssen Pharmaceutical Companies                                                               250\n",
       "              Ludwig Maximilian University of Munich                                                          30\n",
       "              Medicago Inc/GSK/Dynavax                                                                       180\n",
       "              Medigen Vaccine Biologics Corporation/NAID/Dynavax                                              45\n",
       "              Moderna/NIAID                                                                                  120\n",
       "              PLA Academy of Military Sciences                                                               144\n",
       "              PLA Academy of Military Sciences/Walvax Biotech                                                288\n",
       "              ReiThera/Leukocare/Univercells                                                                  90\n",
       "              Shenzhen Geno-Immune Medical Institute/(modified APC)                                          100\n",
       "              Shenzhen Geno-Immune Medical Institute/(modified DC)                                           100\n",
       "              Symvivo                                                                                         12\n",
       "              University Hospital Tübingen                                                                    36\n",
       "              University of Queensland/CSL/Seqirus                                                           216\n",
       "              Vaxart                                                                                          48\n",
       "              Vaxine Pty/Medytox                                                                              40\n",
       "              West China Hospital,/Sichuan University                                                        168\n",
       "Phase I/II    Aivita Biomedical Inc                                                                          180\n",
       "              Anhui Zhifei Longcom Biopharmaceutical/Chinese Academy of Sciences                              50\n",
       "              Arcturus/Duke-NUS                                                                               92\n",
       "              Beijing Institute of Biological Products/Sinopharm                                            2128\n",
       "              Bharat Biotech/ICMR/National Institute of Virology                                             879\n",
       "              BioNTech/Fosun Pharma/Pfizer                                                                   736\n",
       "              CanSino Biological Inc/Beijing Institute of Biotechnology                                      696\n",
       "              Chula Vaccine Research Center/University of Pennsylvania                                        96\n",
       "              Entos Pharmaceuticals                                                                           72\n",
       "              FBRI SRC VB VECTOR,/Rospotrebnadzor, Koltsovo/(peptide)                                        100\n",
       "              Gamaleya Research Institute                                                                     76\n",
       "              Genexine Consortium                                                                            210\n",
       "              Inovio Pharmaceuticals/International Vaccine Institute                                         160\n",
       "              Institut Pasteur/Themis/University of Pittsburg/Merck                                          260\n",
       "              Institute of Medical Biology,/Chinese Academy of Medical Sciences                             1413\n",
       "              Instituto Finlay de Vacunas                                                                    676\n",
       "              Israel Institute for Biological Research/Weizmann Institute of Science                        1040\n",
       "              Janssen Pharmaceutical Companies                                                              1045\n",
       "              Kentucky Bioprocessing Inc                                                                     180\n",
       "              Novavax                                                                                       1419\n",
       "              Osaka University/AnGes/Takara Bio                                                               60\n",
       "              Research Institute for/Biological Safety Problems (inactivated)                                244\n",
       "              Sanofi Pasteur/GSK                                                                             440\n",
       "              Sinovac/Instituto Butantan                                                                    1718\n",
       "              SpyBiotech/Serum Institute of India                                                            280\n",
       "              University of Oxford/AstraZeneca                                                              3346\n",
       "              Wuhan Institute of Biological Products/Sinopharm                                              1264\n",
       "              Zydus Cadila Healthcare Limited (DNA)                                                         1048\n",
       "Phase II      Anhui Zhifei Longcom Biopharmaceutical/Chinese Academy of Sciences                             900\n",
       "              Beijing Minhai Biotechnology Co Ltd                                                           1000\n",
       "              CanSino Biological Inc/Beijing Institute of Biotechnology                                      989\n",
       "              CureVac                                                                                        691\n",
       "              Gamaleya Research Institute                                                                    110\n",
       "              Moderna/NIAID                                                                                  600\n",
       "              Novavax                                                                                       4400\n",
       "Phase II/III  BioNTech/Fosun Pharma/Pfizer                                                                 43998\n",
       "              University of Oxford/AstraZeneca                                                             13990\n",
       "Phase III     Beijing Institute of Biological Products/Sinopharm                                            3000\n",
       "              Beijing Institute of Biological Products/Wuhan Institute of Biological Products/Sinopharm    51000\n",
       "              Bharat Biotech/ICMR/National Institute of Virology                                           26000\n",
       "              CanSino Biological Inc/Beijing Institute of Biotechnology                                    40500\n",
       "              Gamaleya Research Institute                                                                  40100\n",
       "              Janssen Pharmaceutical Companies                                                             90000\n",
       "              Moderna/NIAID                                                                                30000\n",
       "              Novavax                                                                                      39000\n",
       "              Sinovac/Instituto Butantan                                                                   28720\n",
       "              University of Oxford/AstraZeneca                                                             47151\n",
       "              Wuhan Institute of Biological Products/Sinopharm                                               600\n",
       "Name: N, dtype: int64"
      ]
     },
     "execution_count": 450,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lf.groupby(by=['Phase', 'Institutes'])['N'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 451,
   "metadata": {},
   "outputs": [],
   "source": [
    "phase1 = lf[lf['Phase']=='Phase I'].groupby(by='Institutes')['N'].sum().sort_values(ascending=False).rename_axis('Institutes').reset_index(name='total_trial_size_by_phase')\n",
    "phase1['Phase'] = 'Phase I'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 452,
   "metadata": {},
   "outputs": [],
   "source": [
    "phase2 = lf[(lf['Phase']=='Phase II')|(lf['Phase']=='Phase I/II')].groupby(by='Institutes')['N'].sum().sort_values(ascending=False).rename_axis('Institutes').reset_index(name='total_trial_size_by_phase')\n",
    "phase2['Phase'] = 'Phase II'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 453,
   "metadata": {},
   "outputs": [],
   "source": [
    "phase3 = lf[(lf['Phase']=='Phase III')|(lf['Phase']=='Phase II/III')].groupby(by='Institutes')['N'].sum().sort_values(ascending=False).rename_axis('Institutes').reset_index(name='total_trial_size_by_phase')\n",
    "phase3['Phase'] = 'Phase III'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 454,
   "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>Institutes</th>\n",
       "      <th>total_trial_size_by_phase</th>\n",
       "      <th>Phase</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Imperial College London</td>\n",
       "      <td>320</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>PLA Academy of Military Sciences/Walvax Biotech</td>\n",
       "      <td>288</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CureVac</td>\n",
       "      <td>284</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>IAVI/Merck</td>\n",
       "      <td>252</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Janssen Pharmaceutical Companies</td>\n",
       "      <td>250</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>University of Queensland/CSL/Seqirus</td>\n",
       "      <td>216</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>CanSino Biological Inc/Beijing Institute of Bi...</td>\n",
       "      <td>197</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Beijing Minhai Biotechnology Co Ltd</td>\n",
       "      <td>180</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Medicago Inc/GSK/Dynavax</td>\n",
       "      <td>180</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>West China Hospital,/Sichuan University</td>\n",
       "      <td>168</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Clover Biopharmaceuticals Inc/GSK/Dynavax</td>\n",
       "      <td>150</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>PLA Academy of Military Sciences</td>\n",
       "      <td>144</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>BioNTech/Fosun Pharma/Pfizer</td>\n",
       "      <td>144</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Moderna/NIAID</td>\n",
       "      <td>120</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Inovio Pharmaceuticals/International Vaccine I...</td>\n",
       "      <td>120</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Shenzhen Geno-Immune Medical Institute/(modifi...</td>\n",
       "      <td>100</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Shenzhen Geno-Immune Medical Institute/(modifi...</td>\n",
       "      <td>100</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>ReiThera/Leukocare/Univercells</td>\n",
       "      <td>90</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Institut Pasteur/Themis/University of Pittsbur...</td>\n",
       "      <td>90</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Adimmune Corporation</td>\n",
       "      <td>70</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Covaxx/University of Nebraska Medical Center</td>\n",
       "      <td>60</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Beijing Wantai Biological Pharmacy/Xiamen Univ...</td>\n",
       "      <td>60</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Anhui Zhifei Longcom Biopharmaceutical/Chinese...</td>\n",
       "      <td>50</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Codagenix/Serum Institute of India</td>\n",
       "      <td>48</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Vaxart</td>\n",
       "      <td>48</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Medigen Vaccine Biologics Corporation/NAID/Dyn...</td>\n",
       "      <td>45</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Vaxine Pty/Medytox</td>\n",
       "      <td>40</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Instituto Finlay de Vacunas</td>\n",
       "      <td>40</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>University Hospital Tübingen</td>\n",
       "      <td>36</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>ImmunityBio Inc/NantKwest Inc</td>\n",
       "      <td>35</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Ludwig Maximilian University of Munich</td>\n",
       "      <td>30</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Symvivo</td>\n",
       "      <td>12</td>\n",
       "      <td>Phase I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Novavax</td>\n",
       "      <td>5819</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>University of Oxford/AstraZeneca</td>\n",
       "      <td>3346</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Beijing Institute of Biological Products/Sinop...</td>\n",
       "      <td>2128</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Sinovac/Instituto Butantan</td>\n",
       "      <td>1718</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>CanSino Biological Inc/Beijing Institute of Bi...</td>\n",
       "      <td>1685</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Institute of Medical Biology,/Chinese Academy ...</td>\n",
       "      <td>1413</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Wuhan Institute of Biological Products/Sinopharm</td>\n",
       "      <td>1264</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Zydus Cadila Healthcare Limited (DNA)</td>\n",
       "      <td>1048</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Janssen Pharmaceutical Companies</td>\n",
       "      <td>1045</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Israel Institute for Biological Research/Weizm...</td>\n",
       "      <td>1040</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Beijing Minhai Biotechnology Co Ltd</td>\n",
       "      <td>1000</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Anhui Zhifei Longcom Biopharmaceutical/Chinese...</td>\n",
       "      <td>950</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Bharat Biotech/ICMR/National Institute of Viro...</td>\n",
       "      <td>879</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>BioNTech/Fosun Pharma/Pfizer</td>\n",
       "      <td>736</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>CureVac</td>\n",
       "      <td>691</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Instituto Finlay de Vacunas</td>\n",
       "      <td>676</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Moderna/NIAID</td>\n",
       "      <td>600</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Sanofi Pasteur/GSK</td>\n",
       "      <td>440</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>SpyBiotech/Serum Institute of India</td>\n",
       "      <td>280</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>Institut Pasteur/Themis/University of Pittsbur...</td>\n",
       "      <td>260</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>Research Institute for/Biological Safety Probl...</td>\n",
       "      <td>244</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>Genexine Consortium</td>\n",
       "      <td>210</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>Gamaleya Research Institute</td>\n",
       "      <td>186</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>Kentucky Bioprocessing Inc</td>\n",
       "      <td>180</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>Aivita Biomedical Inc</td>\n",
       "      <td>180</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Inovio Pharmaceuticals/International Vaccine I...</td>\n",
       "      <td>160</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>FBRI SRC VB VECTOR,/Rospotrebnadzor, Koltsovo/...</td>\n",
       "      <td>100</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>Chula Vaccine Research Center/University of Pe...</td>\n",
       "      <td>96</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>Arcturus/Duke-NUS</td>\n",
       "      <td>92</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>Entos Pharmaceuticals</td>\n",
       "      <td>72</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>Osaka University/AnGes/Takara Bio</td>\n",
       "      <td>60</td>\n",
       "      <td>Phase II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>Janssen Pharmaceutical Companies</td>\n",
       "      <td>90000</td>\n",
       "      <td>Phase III</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>University of Oxford/AstraZeneca</td>\n",
       "      <td>61141</td>\n",
       "      <td>Phase III</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>Beijing Institute of Biological Products/Wuhan...</td>\n",
       "      <td>51000</td>\n",
       "      <td>Phase III</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>BioNTech/Fosun Pharma/Pfizer</td>\n",
       "      <td>43998</td>\n",
       "      <td>Phase III</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>CanSino Biological Inc/Beijing Institute of Bi...</td>\n",
       "      <td>40500</td>\n",
       "      <td>Phase III</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>Gamaleya Research Institute</td>\n",
       "      <td>40100</td>\n",
       "      <td>Phase III</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>Novavax</td>\n",
       "      <td>39000</td>\n",
       "      <td>Phase III</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>Moderna/NIAID</td>\n",
       "      <td>30000</td>\n",
       "      <td>Phase III</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>Sinovac/Instituto Butantan</td>\n",
       "      <td>28720</td>\n",
       "      <td>Phase III</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>Bharat Biotech/ICMR/National Institute of Viro...</td>\n",
       "      <td>26000</td>\n",
       "      <td>Phase III</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>Beijing Institute of Biological Products/Sinop...</td>\n",
       "      <td>3000</td>\n",
       "      <td>Phase III</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>Wuhan Institute of Biological Products/Sinopharm</td>\n",
       "      <td>600</td>\n",
       "      <td>Phase III</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           Institutes  \\\n",
       "0                             Imperial College London   \n",
       "1     PLA Academy of Military Sciences/Walvax Biotech   \n",
       "2                                             CureVac   \n",
       "3                                          IAVI/Merck   \n",
       "4                    Janssen Pharmaceutical Companies   \n",
       "5                University of Queensland/CSL/Seqirus   \n",
       "6   CanSino Biological Inc/Beijing Institute of Bi...   \n",
       "7                 Beijing Minhai Biotechnology Co Ltd   \n",
       "8                            Medicago Inc/GSK/Dynavax   \n",
       "9             West China Hospital,/Sichuan University   \n",
       "10          Clover Biopharmaceuticals Inc/GSK/Dynavax   \n",
       "11                   PLA Academy of Military Sciences   \n",
       "12                       BioNTech/Fosun Pharma/Pfizer   \n",
       "13                                      Moderna/NIAID   \n",
       "14  Inovio Pharmaceuticals/International Vaccine I...   \n",
       "15  Shenzhen Geno-Immune Medical Institute/(modifi...   \n",
       "16  Shenzhen Geno-Immune Medical Institute/(modifi...   \n",
       "17                     ReiThera/Leukocare/Univercells   \n",
       "18  Institut Pasteur/Themis/University of Pittsbur...   \n",
       "19                               Adimmune Corporation   \n",
       "20       Covaxx/University of Nebraska Medical Center   \n",
       "21  Beijing Wantai Biological Pharmacy/Xiamen Univ...   \n",
       "22  Anhui Zhifei Longcom Biopharmaceutical/Chinese...   \n",
       "23                 Codagenix/Serum Institute of India   \n",
       "24                                             Vaxart   \n",
       "25  Medigen Vaccine Biologics Corporation/NAID/Dyn...   \n",
       "26                                 Vaxine Pty/Medytox   \n",
       "27                        Instituto Finlay de Vacunas   \n",
       "28                       University Hospital Tübingen   \n",
       "29                      ImmunityBio Inc/NantKwest Inc   \n",
       "30             Ludwig Maximilian University of Munich   \n",
       "31                                            Symvivo   \n",
       "32                                            Novavax   \n",
       "33                   University of Oxford/AstraZeneca   \n",
       "34  Beijing Institute of Biological Products/Sinop...   \n",
       "35                         Sinovac/Instituto Butantan   \n",
       "36  CanSino Biological Inc/Beijing Institute of Bi...   \n",
       "37  Institute of Medical Biology,/Chinese Academy ...   \n",
       "38   Wuhan Institute of Biological Products/Sinopharm   \n",
       "39              Zydus Cadila Healthcare Limited (DNA)   \n",
       "40                   Janssen Pharmaceutical Companies   \n",
       "41  Israel Institute for Biological Research/Weizm...   \n",
       "42                Beijing Minhai Biotechnology Co Ltd   \n",
       "43  Anhui Zhifei Longcom Biopharmaceutical/Chinese...   \n",
       "44  Bharat Biotech/ICMR/National Institute of Viro...   \n",
       "45                       BioNTech/Fosun Pharma/Pfizer   \n",
       "46                                            CureVac   \n",
       "47                        Instituto Finlay de Vacunas   \n",
       "48                                      Moderna/NIAID   \n",
       "49                                 Sanofi Pasteur/GSK   \n",
       "50                SpyBiotech/Serum Institute of India   \n",
       "51  Institut Pasteur/Themis/University of Pittsbur...   \n",
       "52  Research Institute for/Biological Safety Probl...   \n",
       "53                                Genexine Consortium   \n",
       "54                        Gamaleya Research Institute   \n",
       "55                         Kentucky Bioprocessing Inc   \n",
       "56                              Aivita Biomedical Inc   \n",
       "57  Inovio Pharmaceuticals/International Vaccine I...   \n",
       "58  FBRI SRC VB VECTOR,/Rospotrebnadzor, Koltsovo/...   \n",
       "59  Chula Vaccine Research Center/University of Pe...   \n",
       "60                                  Arcturus/Duke-NUS   \n",
       "61                              Entos Pharmaceuticals   \n",
       "62                  Osaka University/AnGes/Takara Bio   \n",
       "63                   Janssen Pharmaceutical Companies   \n",
       "64                   University of Oxford/AstraZeneca   \n",
       "65  Beijing Institute of Biological Products/Wuhan...   \n",
       "66                       BioNTech/Fosun Pharma/Pfizer   \n",
       "67  CanSino Biological Inc/Beijing Institute of Bi...   \n",
       "68                        Gamaleya Research Institute   \n",
       "69                                            Novavax   \n",
       "70                                      Moderna/NIAID   \n",
       "71                         Sinovac/Instituto Butantan   \n",
       "72  Bharat Biotech/ICMR/National Institute of Viro...   \n",
       "73  Beijing Institute of Biological Products/Sinop...   \n",
       "74   Wuhan Institute of Biological Products/Sinopharm   \n",
       "\n",
       "    total_trial_size_by_phase      Phase  \n",
       "0                         320    Phase I  \n",
       "1                         288    Phase I  \n",
       "2                         284    Phase I  \n",
       "3                         252    Phase I  \n",
       "4                         250    Phase I  \n",
       "5                         216    Phase I  \n",
       "6                         197    Phase I  \n",
       "7                         180    Phase I  \n",
       "8                         180    Phase I  \n",
       "9                         168    Phase I  \n",
       "10                        150    Phase I  \n",
       "11                        144    Phase I  \n",
       "12                        144    Phase I  \n",
       "13                        120    Phase I  \n",
       "14                        120    Phase I  \n",
       "15                        100    Phase I  \n",
       "16                        100    Phase I  \n",
       "17                         90    Phase I  \n",
       "18                         90    Phase I  \n",
       "19                         70    Phase I  \n",
       "20                         60    Phase I  \n",
       "21                         60    Phase I  \n",
       "22                         50    Phase I  \n",
       "23                         48    Phase I  \n",
       "24                         48    Phase I  \n",
       "25                         45    Phase I  \n",
       "26                         40    Phase I  \n",
       "27                         40    Phase I  \n",
       "28                         36    Phase I  \n",
       "29                         35    Phase I  \n",
       "30                         30    Phase I  \n",
       "31                         12    Phase I  \n",
       "32                       5819   Phase II  \n",
       "33                       3346   Phase II  \n",
       "34                       2128   Phase II  \n",
       "35                       1718   Phase II  \n",
       "36                       1685   Phase II  \n",
       "37                       1413   Phase II  \n",
       "38                       1264   Phase II  \n",
       "39                       1048   Phase II  \n",
       "40                       1045   Phase II  \n",
       "41                       1040   Phase II  \n",
       "42                       1000   Phase II  \n",
       "43                        950   Phase II  \n",
       "44                        879   Phase II  \n",
       "45                        736   Phase II  \n",
       "46                        691   Phase II  \n",
       "47                        676   Phase II  \n",
       "48                        600   Phase II  \n",
       "49                        440   Phase II  \n",
       "50                        280   Phase II  \n",
       "51                        260   Phase II  \n",
       "52                        244   Phase II  \n",
       "53                        210   Phase II  \n",
       "54                        186   Phase II  \n",
       "55                        180   Phase II  \n",
       "56                        180   Phase II  \n",
       "57                        160   Phase II  \n",
       "58                        100   Phase II  \n",
       "59                         96   Phase II  \n",
       "60                         92   Phase II  \n",
       "61                         72   Phase II  \n",
       "62                         60   Phase II  \n",
       "63                      90000  Phase III  \n",
       "64                      61141  Phase III  \n",
       "65                      51000  Phase III  \n",
       "66                      43998  Phase III  \n",
       "67                      40500  Phase III  \n",
       "68                      40100  Phase III  \n",
       "69                      39000  Phase III  \n",
       "70                      30000  Phase III  \n",
       "71                      28720  Phase III  \n",
       "72                      26000  Phase III  \n",
       "73                       3000  Phase III  \n",
       "74                        600  Phase III  "
      ]
     },
     "execution_count": 454,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trials_df = pd.concat([phase1,phase2,phase3], ignore_index = True)\n",
    "trials_df"
   ]
  },
  {
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   "execution_count": 455,
   "metadata": {},
   "outputs": [
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",
      "text/plain": [
       "<VegaLite 3 object>\n",
       "\n",
       "If you see this message, it means the renderer has not been properly enabled\n",
       "for the frontend that you are using. For more information, see\n",
       "https://altair-viz.github.io/user_guide/troubleshooting.html\n"
      ]
     },
     "execution_count": 455,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alt.Chart(trials_df).mark_square().encode(\n",
    "    alt.Y('Phase:N', sort=None),\n",
    "    alt.X('Institutes:N'),\n",
    "    size='total_trial_size_by_phase:Q',\n",
    "    color='Phase:N',\n",
    "    tooltip=['N:Q']\n",
    ").properties(width=700, height = 400)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 456,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.vegalite.v3+json": {
       "$schema": "https://vega.github.io/schema/vega-lite/v3.4.0.json",
       "config": {
        "mark": {
         "tooltip": null
        },
        "view": {
         "height": 300,
         "width": 400
        }
       },
       "data": {
        "name": "data-ea9a003a4f483548bc78269cb4bb0ee1"
       },
       "datasets": {
        "data-ea9a003a4f483548bc78269cb4bb0ee1": [
         {
          "Institutes": "Janssen Pharmaceutical Companies",
          "Phase": "Phase III",
          "total_trial_size_by_phase": 90000
         },
         {
          "Institutes": "University of Oxford/AstraZeneca",
          "Phase": "Phase III",
          "total_trial_size_by_phase": 61141
         },
         {
          "Institutes": "Beijing Institute of Biological Products/Wuhan Institute of Biological Products/Sinopharm",
          "Phase": "Phase III",
          "total_trial_size_by_phase": 51000
         },
         {
          "Institutes": "BioNTech/Fosun Pharma/Pfizer",
          "Phase": "Phase III",
          "total_trial_size_by_phase": 43998
         },
         {
          "Institutes": "CanSino Biological Inc/Beijing Institute of Biotechnology",
          "Phase": "Phase III",
          "total_trial_size_by_phase": 40500
         },
         {
          "Institutes": "Gamaleya Research Institute",
          "Phase": "Phase III",
          "total_trial_size_by_phase": 40100
         },
         {
          "Institutes": "Novavax",
          "Phase": "Phase III",
          "total_trial_size_by_phase": 39000
         },
         {
          "Institutes": "Moderna/NIAID",
          "Phase": "Phase III",
          "total_trial_size_by_phase": 30000
         },
         {
          "Institutes": "Sinovac/Instituto Butantan",
          "Phase": "Phase III",
          "total_trial_size_by_phase": 28720
         },
         {
          "Institutes": "Bharat Biotech/ICMR/National Institute of Virology",
          "Phase": "Phase III",
          "total_trial_size_by_phase": 26000
         },
         {
          "Institutes": "Beijing Institute of Biological Products/Sinopharm",
          "Phase": "Phase III",
          "total_trial_size_by_phase": 3000
         },
         {
          "Institutes": "Wuhan Institute of Biological Products/Sinopharm",
          "Phase": "Phase III",
          "total_trial_size_by_phase": 600
         }
        ]
       },
       "encoding": {
        "size": {
         "field": "total_trial_size_by_phase",
         "type": "quantitative"
        },
        "tooltip": [
         {
          "field": "total_trial_size_by_phase",
          "type": "quantitative"
         },
         {
          "field": "Institutes",
          "type": "nominal"
         }
        ],
        "x": {
         "field": "Phase",
         "type": "nominal"
        },
        "y": {
         "field": "Institutes",
         "sort": null,
         "type": "nominal"
        }
       },
       "mark": "square",
       "width": 400
      },
      "image/png": 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",
      "text/plain": [
       "<VegaLite 3 object>\n",
       "\n",
       "If you see this message, it means the renderer has not been properly enabled\n",
       "for the frontend that you are using. For more information, see\n",
       "https://altair-viz.github.io/user_guide/troubleshooting.html\n"
      ]
     },
     "execution_count": 456,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#make sorted phase three as addition for easier charting!\n",
    "\n",
    "alt.Chart(phase3).mark_square().encode(\n",
    "    alt.X('Phase:N'),\n",
    "    alt.Y('Institutes:N', sort=None),\n",
    "    size='total_trial_size_by_phase:Q',\n",
    "    tooltip=['total_trial_size_by_phase:Q', 'Institutes:N']\n",
    ").properties(width=400)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 457,
   "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>Institutes</th>\n",
       "      <th>total_trial_size_by_phase</th>\n",
       "      <th>Phase</th>\n",
       "      <th>total_trial_size_by_phase_ROUNDED</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Janssen Pharmaceutical Companies</td>\n",
       "      <td>90000</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>90000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>University of Oxford/AstraZeneca</td>\n",
       "      <td>61141</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>61000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Beijing Institute of Biological Products/Wuhan...</td>\n",
       "      <td>51000</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>51000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BioNTech/Fosun Pharma/Pfizer</td>\n",
       "      <td>43998</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>44000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CanSino Biological Inc/Beijing Institute of Bi...</td>\n",
       "      <td>40500</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Gamaleya Research Institute</td>\n",
       "      <td>40100</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Novavax</td>\n",
       "      <td>39000</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>39000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Moderna/NIAID</td>\n",
       "      <td>30000</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Sinovac/Instituto Butantan</td>\n",
       "      <td>28720</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>29000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Bharat Biotech/ICMR/National Institute of Viro...</td>\n",
       "      <td>26000</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>26000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Beijing Institute of Biological Products/Sinop...</td>\n",
       "      <td>3000</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>3000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Wuhan Institute of Biological Products/Sinopharm</td>\n",
       "      <td>600</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           Institutes  \\\n",
       "0                    Janssen Pharmaceutical Companies   \n",
       "1                    University of Oxford/AstraZeneca   \n",
       "2   Beijing Institute of Biological Products/Wuhan...   \n",
       "3                        BioNTech/Fosun Pharma/Pfizer   \n",
       "4   CanSino Biological Inc/Beijing Institute of Bi...   \n",
       "5                         Gamaleya Research Institute   \n",
       "6                                             Novavax   \n",
       "7                                       Moderna/NIAID   \n",
       "8                          Sinovac/Instituto Butantan   \n",
       "9   Bharat Biotech/ICMR/National Institute of Viro...   \n",
       "10  Beijing Institute of Biological Products/Sinop...   \n",
       "11   Wuhan Institute of Biological Products/Sinopharm   \n",
       "\n",
       "    total_trial_size_by_phase      Phase  total_trial_size_by_phase_ROUNDED  \n",
       "0                       90000  Phase III                              90000  \n",
       "1                       61141  Phase III                              61000  \n",
       "2                       51000  Phase III                              51000  \n",
       "3                       43998  Phase III                              44000  \n",
       "4                       40500  Phase III                              40000  \n",
       "5                       40100  Phase III                              40000  \n",
       "6                       39000  Phase III                              39000  \n",
       "7                       30000  Phase III                              30000  \n",
       "8                       28720  Phase III                              29000  \n",
       "9                       26000  Phase III                              26000  \n",
       "10                       3000  Phase III                               3000  \n",
       "11                        600  Phase III                               1000  "
      ]
     },
     "execution_count": 457,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# round to nearest thousand\n",
    "phase3['total_trial_size_by_phase_ROUNDED'] = phase3['total_trial_size_by_phase'].round(decimals=-3)\n",
    "phase3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 458,
   "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>Institutes</th>\n",
       "      <th>Phase</th>\n",
       "      <th>Vaccine</th>\n",
       "      <th>Platform</th>\n",
       "      <th>N</th>\n",
       "      <th>Age (years)</th>\n",
       "      <th>N doses</th>\n",
       "      <th>Rand.</th>\n",
       "      <th>Design</th>\n",
       "      <th>Location</th>\n",
       "      <th>Start date</th>\n",
       "      <th>Primary completion date</th>\n",
       "      <th>Trial number</th>\n",
       "      <th>Status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Janssen Pharmaceutical Companies</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Janssen Ad26.COV2.S</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>60000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>USA, Argentina, Brazil, others</td>\n",
       "      <td>07/09/2020</td>\n",
       "      <td>10/03/2023</td>\n",
       "      <td>NCT04505722</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Beijing Institute of Biological Products/Wuhan...</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>WIBP/BIBP/Sinopharm vaccines</td>\n",
       "      <td>Inactivated</td>\n",
       "      <td>45000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Bahrain, Jordan, Egypt, UAE</td>\n",
       "      <td>16/07/2020</td>\n",
       "      <td>16/03/2021</td>\n",
       "      <td>NCT04510207</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BioNTech/Fosun Pharma/Pfizer</td>\n",
       "      <td>Phase II/III</td>\n",
       "      <td>BioNTech BNT162 (b1/b2)</td>\n",
       "      <td>RNA</td>\n",
       "      <td>43998</td>\n",
       "      <td>≥12</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind, dose-finding</td>\n",
       "      <td>USA, Argentina, Brazil, others</td>\n",
       "      <td>29/04/2020</td>\n",
       "      <td>13/06/2021</td>\n",
       "      <td>NCT04368728</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>University of Oxford/AstraZeneca</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Oxford ChAdOx1-S</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>40051</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>USA, Chile, Peru</td>\n",
       "      <td>28/08/2020</td>\n",
       "      <td>22/12/2020</td>\n",
       "      <td>NCT04516746</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CanSino Biological Inc/Beijing Institute of Bi...</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Cansino Ad5-nCoV</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>40000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Pakistan</td>\n",
       "      <td>15/09/2020</td>\n",
       "      <td>30/12/2021</td>\n",
       "      <td>NCT04526990</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Gamaleya Research Institute</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Gamaleya Gam-COVID-Vac</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>40000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Russia</td>\n",
       "      <td>07/09/2020</td>\n",
       "      <td>01/05/2021</td>\n",
       "      <td>NCT04530396</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Moderna/NIAID</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Moderna mRNA-1273</td>\n",
       "      <td>RNA</td>\n",
       "      <td>30000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>USA</td>\n",
       "      <td>27/07/2020</td>\n",
       "      <td>27/10/2022</td>\n",
       "      <td>NCT04470427</td>\n",
       "      <td>Active, not recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Novavax</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Novavax NVX-CoV2373</td>\n",
       "      <td>Protein subunit</td>\n",
       "      <td>30000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>USA, Mexico, Puerto Rico</td>\n",
       "      <td>01/11/2020</td>\n",
       "      <td>31/03/2021</td>\n",
       "      <td>NCT04611802</td>\n",
       "      <td>Not yet recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Janssen Pharmaceutical Companies</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Janssen Ad26.COV2.S</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>30000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>USA, Belgium, Colombia, others</td>\n",
       "      <td>06/11/2020</td>\n",
       "      <td>10/05/2021</td>\n",
       "      <td>NCT04614948</td>\n",
       "      <td>Not yet recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Bharat Biotech/ICMR/National Institute of Viro...</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Bharat COVAXIN</td>\n",
       "      <td>Inactivated</td>\n",
       "      <td>26000</td>\n",
       "      <td>Pending</td>\n",
       "      <td>Pending</td>\n",
       "      <td>Pending</td>\n",
       "      <td>Pending</td>\n",
       "      <td>Pending</td>\n",
       "      <td>10/11/2020</td>\n",
       "      <td>Pending</td>\n",
       "      <td>Pending</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Sinovac/Instituto Butantan</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Sinovac CoronaVac</td>\n",
       "      <td>Inactivated</td>\n",
       "      <td>13060</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>21/07/2020</td>\n",
       "      <td>30/09/2021</td>\n",
       "      <td>NCT04456595</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Sinovac/Instituto Butantan</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Sinovac CoronaVac</td>\n",
       "      <td>Inactivated</td>\n",
       "      <td>13000</td>\n",
       "      <td>18–59</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Turkey</td>\n",
       "      <td>14/09/2020</td>\n",
       "      <td>15/02/2021</td>\n",
       "      <td>NCT04582344</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>University of Oxford/AstraZeneca</td>\n",
       "      <td>Phase II/III</td>\n",
       "      <td>Oxford ChAdOx1-S</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>12390</td>\n",
       "      <td>≥5</td>\n",
       "      <td>1 or 2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Single-blind</td>\n",
       "      <td>UK</td>\n",
       "      <td>28/05/2020</td>\n",
       "      <td>31/08/2021</td>\n",
       "      <td>NCT04400838</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Novavax</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Novavax NVX-CoV2373</td>\n",
       "      <td>Protein subunit</td>\n",
       "      <td>9000</td>\n",
       "      <td>18–84</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>UK</td>\n",
       "      <td>28/09/2020</td>\n",
       "      <td>31/01/2021</td>\n",
       "      <td>NCT04583995</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Beijing Institute of Biological Products/Wuhan...</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>WIBP/BIBP/Sinopharm vaccines</td>\n",
       "      <td>Inactivated</td>\n",
       "      <td>6000</td>\n",
       "      <td>18–60</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Peru</td>\n",
       "      <td>10/09/2020</td>\n",
       "      <td>31/12/2020</td>\n",
       "      <td>NCT04612972</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>University of Oxford/AstraZeneca</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Oxford ChAdOx1-S</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>5000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>1 or 2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Single-blind</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>02/06/2020</td>\n",
       "      <td>30/09/2021</td>\n",
       "      <td>NCT04536051</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Beijing Institute of Biological Products/Sinop...</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>BIBP/Sinopharm BBIBP-CorV</td>\n",
       "      <td>Inactivated</td>\n",
       "      <td>3000</td>\n",
       "      <td>18–85</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>16/09/2020</td>\n",
       "      <td>01/12/2021</td>\n",
       "      <td>NCT04560881</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>University of Oxford/AstraZeneca</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Oxford ChAdOx1-S</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>2000</td>\n",
       "      <td>18–55</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Single-blind</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>01/05/2020</td>\n",
       "      <td>31/10/2021</td>\n",
       "      <td>ISRCTN89951424</td>\n",
       "      <td>No longer recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Sinovac/Instituto Butantan</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Sinovac CoronaVac</td>\n",
       "      <td>Inactivated</td>\n",
       "      <td>1620</td>\n",
       "      <td>18–59</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Indonesia</td>\n",
       "      <td>10/08/2020</td>\n",
       "      <td>31/01/2021</td>\n",
       "      <td>NCT04508075</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>University of Oxford/AstraZeneca</td>\n",
       "      <td>Phase II/III</td>\n",
       "      <td>Oxford ChAdOx1-S</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>1600</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Single-blind</td>\n",
       "      <td>India</td>\n",
       "      <td>24/08/2020</td>\n",
       "      <td>24/03/2021</td>\n",
       "      <td>CTRI/2020/08/027170</td>\n",
       "      <td>Active, not recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Sinovac/Instituto Butantan</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Sinovac CoronaVac</td>\n",
       "      <td>Inactivated</td>\n",
       "      <td>1040</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>China</td>\n",
       "      <td>31/10/2020</td>\n",
       "      <td>28/11/2020</td>\n",
       "      <td>NCT04617483</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Wuhan Institute of Biological Products/Sinopharm</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>WIBP vaccine</td>\n",
       "      <td>Inactivated</td>\n",
       "      <td>600</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Morocco</td>\n",
       "      <td>02/09/2020</td>\n",
       "      <td>31/12/2020</td>\n",
       "      <td>ChiCTR2000039000</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>CanSino Biological Inc/Beijing Institute of Bi...</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Cansino Ad5-nCoV</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>500</td>\n",
       "      <td>18–85</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Russia</td>\n",
       "      <td>11/09/2020</td>\n",
       "      <td>30/11/2020</td>\n",
       "      <td>NCT04540419</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>University of Oxford/AstraZeneca</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Oxford ChAdOx1-S</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>100</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>No</td>\n",
       "      <td>Open-label</td>\n",
       "      <td>Russia</td>\n",
       "      <td>26/08/2020</td>\n",
       "      <td>05/03/2021</td>\n",
       "      <td>NCT04540393</td>\n",
       "      <td>Not yet recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>Gamaleya Research Institute</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Gamaleya Gam-COVID-Vac</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>100</td>\n",
       "      <td>18–60</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Belarus</td>\n",
       "      <td>28/09/2020</td>\n",
       "      <td>28/03/2021</td>\n",
       "      <td>NCT04564716</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           Institutes         Phase  \\\n",
       "0                    Janssen Pharmaceutical Companies     Phase III   \n",
       "1   Beijing Institute of Biological Products/Wuhan...     Phase III   \n",
       "2                        BioNTech/Fosun Pharma/Pfizer  Phase II/III   \n",
       "3                    University of Oxford/AstraZeneca     Phase III   \n",
       "4   CanSino Biological Inc/Beijing Institute of Bi...     Phase III   \n",
       "5                         Gamaleya Research Institute     Phase III   \n",
       "6                                       Moderna/NIAID     Phase III   \n",
       "7                                             Novavax     Phase III   \n",
       "8                    Janssen Pharmaceutical Companies     Phase III   \n",
       "9   Bharat Biotech/ICMR/National Institute of Viro...     Phase III   \n",
       "10                         Sinovac/Instituto Butantan     Phase III   \n",
       "11                         Sinovac/Instituto Butantan     Phase III   \n",
       "12                   University of Oxford/AstraZeneca  Phase II/III   \n",
       "13                                            Novavax     Phase III   \n",
       "14  Beijing Institute of Biological Products/Wuhan...     Phase III   \n",
       "15                   University of Oxford/AstraZeneca     Phase III   \n",
       "17  Beijing Institute of Biological Products/Sinop...     Phase III   \n",
       "19                   University of Oxford/AstraZeneca     Phase III   \n",
       "21                         Sinovac/Instituto Butantan     Phase III   \n",
       "22                   University of Oxford/AstraZeneca  Phase II/III   \n",
       "29                         Sinovac/Instituto Butantan     Phase III   \n",
       "38   Wuhan Institute of Biological Products/Sinopharm     Phase III   \n",
       "42  CanSino Biological Inc/Beijing Institute of Bi...     Phase III   \n",
       "79                   University of Oxford/AstraZeneca     Phase III   \n",
       "80                        Gamaleya Research Institute     Phase III   \n",
       "\n",
       "                         Vaccine                      Platform      N  \\\n",
       "0            Janssen Ad26.COV2.S  Non-replicating viral vector  60000   \n",
       "1   WIBP/BIBP/Sinopharm vaccines                   Inactivated  45000   \n",
       "2        BioNTech BNT162 (b1/b2)                           RNA  43998   \n",
       "3               Oxford ChAdOx1-S  Non-replicating viral vector  40051   \n",
       "4               Cansino Ad5-nCoV  Non-replicating viral vector  40000   \n",
       "5         Gamaleya Gam-COVID-Vac  Non-replicating viral vector  40000   \n",
       "6              Moderna mRNA-1273                           RNA  30000   \n",
       "7            Novavax NVX-CoV2373               Protein subunit  30000   \n",
       "8            Janssen Ad26.COV2.S  Non-replicating viral vector  30000   \n",
       "9                 Bharat COVAXIN                   Inactivated  26000   \n",
       "10             Sinovac CoronaVac                   Inactivated  13060   \n",
       "11             Sinovac CoronaVac                   Inactivated  13000   \n",
       "12              Oxford ChAdOx1-S  Non-replicating viral vector  12390   \n",
       "13           Novavax NVX-CoV2373               Protein subunit   9000   \n",
       "14  WIBP/BIBP/Sinopharm vaccines                   Inactivated   6000   \n",
       "15              Oxford ChAdOx1-S  Non-replicating viral vector   5000   \n",
       "17     BIBP/Sinopharm BBIBP-CorV                   Inactivated   3000   \n",
       "19              Oxford ChAdOx1-S  Non-replicating viral vector   2000   \n",
       "21             Sinovac CoronaVac                   Inactivated   1620   \n",
       "22              Oxford ChAdOx1-S  Non-replicating viral vector   1600   \n",
       "29             Sinovac CoronaVac                   Inactivated   1040   \n",
       "38                  WIBP vaccine                   Inactivated    600   \n",
       "42              Cansino Ad5-nCoV  Non-replicating viral vector    500   \n",
       "79              Oxford ChAdOx1-S  Non-replicating viral vector    100   \n",
       "80        Gamaleya Gam-COVID-Vac  Non-replicating viral vector    100   \n",
       "\n",
       "   Age (years)  N doses    Rand.                      Design  \\\n",
       "0          ≥18        1      Yes                Double-blind   \n",
       "1          ≥18        2      Yes                Double-blind   \n",
       "2          ≥12        2      Yes  Double-blind, dose-finding   \n",
       "3          ≥18        2      Yes                Double-blind   \n",
       "4          ≥18        1      Yes                Double-blind   \n",
       "5          ≥18        2      Yes                Double-blind   \n",
       "6          ≥18        2      Yes                Double-blind   \n",
       "7          ≥18        2      Yes                Double-blind   \n",
       "8          ≥18        2      Yes                Double-blind   \n",
       "9      Pending  Pending  Pending                     Pending   \n",
       "10         ≥18        2      Yes                Double-blind   \n",
       "11       18–59        2      Yes                Double-blind   \n",
       "12          ≥5   1 or 2      Yes                Single-blind   \n",
       "13       18–84        2      Yes                Double-blind   \n",
       "14       18–60        2      Yes                Double-blind   \n",
       "15         ≥18   1 or 2      Yes                Single-blind   \n",
       "17       18–85        2      Yes                Double-blind   \n",
       "19       18–55        1      Yes                Single-blind   \n",
       "21       18–59        2      Yes                Double-blind   \n",
       "22         ≥18        2      Yes                Single-blind   \n",
       "29         ≥18        2      Yes                Double-blind   \n",
       "38         ≥18        2      Yes                Double-blind   \n",
       "42       18–85        1      Yes                Double-blind   \n",
       "79         ≥18        2       No                  Open-label   \n",
       "80       18–60        2      Yes                Double-blind   \n",
       "\n",
       "                          Location  Start date Primary completion date  \\\n",
       "0   USA, Argentina, Brazil, others  07/09/2020              10/03/2023   \n",
       "1      Bahrain, Jordan, Egypt, UAE  16/07/2020              16/03/2021   \n",
       "2   USA, Argentina, Brazil, others  29/04/2020              13/06/2021   \n",
       "3                 USA, Chile, Peru  28/08/2020              22/12/2020   \n",
       "4                         Pakistan  15/09/2020              30/12/2021   \n",
       "5                           Russia  07/09/2020              01/05/2021   \n",
       "6                              USA  27/07/2020              27/10/2022   \n",
       "7         USA, Mexico, Puerto Rico  01/11/2020              31/03/2021   \n",
       "8   USA, Belgium, Colombia, others  06/11/2020              10/05/2021   \n",
       "9                          Pending  10/11/2020                 Pending   \n",
       "10                          Brazil  21/07/2020              30/09/2021   \n",
       "11                          Turkey  14/09/2020              15/02/2021   \n",
       "12                              UK  28/05/2020              31/08/2021   \n",
       "13                              UK  28/09/2020              31/01/2021   \n",
       "14                            Peru  10/09/2020              31/12/2020   \n",
       "15                          Brazil  02/06/2020              30/09/2021   \n",
       "17                       Argentina  16/09/2020              01/12/2021   \n",
       "19                          Brazil  01/05/2020              31/10/2021   \n",
       "21                       Indonesia  10/08/2020              31/01/2021   \n",
       "22                           India  24/08/2020              24/03/2021   \n",
       "29                           China  31/10/2020              28/11/2020   \n",
       "38                         Morocco  02/09/2020              31/12/2020   \n",
       "42                          Russia  11/09/2020              30/11/2020   \n",
       "79                          Russia  26/08/2020              05/03/2021   \n",
       "80                         Belarus  28/09/2020              28/03/2021   \n",
       "\n",
       "           Trial number                  Status  \n",
       "0           NCT04505722              Recruiting  \n",
       "1           NCT04510207              Recruiting  \n",
       "2           NCT04368728              Recruiting  \n",
       "3           NCT04516746              Recruiting  \n",
       "4           NCT04526990              Recruiting  \n",
       "5           NCT04530396              Recruiting  \n",
       "6           NCT04470427  Active, not recruiting  \n",
       "7           NCT04611802      Not yet recruiting  \n",
       "8           NCT04614948      Not yet recruiting  \n",
       "9               Pending              Recruiting  \n",
       "10          NCT04456595              Recruiting  \n",
       "11          NCT04582344              Recruiting  \n",
       "12          NCT04400838              Recruiting  \n",
       "13          NCT04583995              Recruiting  \n",
       "14          NCT04612972              Recruiting  \n",
       "15          NCT04536051              Recruiting  \n",
       "17          NCT04560881              Recruiting  \n",
       "19       ISRCTN89951424    No longer recruiting  \n",
       "21          NCT04508075              Recruiting  \n",
       "22  CTRI/2020/08/027170  Active, not recruiting  \n",
       "29          NCT04617483              Recruiting  \n",
       "38     ChiCTR2000039000              Recruiting  \n",
       "42          NCT04540419              Recruiting  \n",
       "79          NCT04540393      Not yet recruiting  \n",
       "80          NCT04564716              Recruiting  "
      ]
     },
     "execution_count": 458,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# explore data in more granular detail\n",
    "lf[(lf['Phase']=='Phase III')|(lf['Phase']=='Phase II/III')].sort_values(by='N', ascending = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How long will trials take, according to researchers estimates? (LSHTM data question)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 459,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Institutes</th>\n",
       "      <th>Phase</th>\n",
       "      <th>Vaccine</th>\n",
       "      <th>Platform</th>\n",
       "      <th>N</th>\n",
       "      <th>Age (years)</th>\n",
       "      <th>N doses</th>\n",
       "      <th>Rand.</th>\n",
       "      <th>Design</th>\n",
       "      <th>Location</th>\n",
       "      <th>Start date</th>\n",
       "      <th>Primary completion date</th>\n",
       "      <th>Trial number</th>\n",
       "      <th>Status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Janssen Pharmaceutical Companies</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Janssen Ad26.COV2.S</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>60000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>USA, Argentina, Brazil, others</td>\n",
       "      <td>07/09/2020</td>\n",
       "      <td>10/03/2023</td>\n",
       "      <td>NCT04505722</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Beijing Institute of Biological Products/Wuhan...</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>WIBP/BIBP/Sinopharm vaccines</td>\n",
       "      <td>Inactivated</td>\n",
       "      <td>45000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Bahrain, Jordan, Egypt, UAE</td>\n",
       "      <td>16/07/2020</td>\n",
       "      <td>16/03/2021</td>\n",
       "      <td>NCT04510207</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BioNTech/Fosun Pharma/Pfizer</td>\n",
       "      <td>Phase II/III</td>\n",
       "      <td>BioNTech BNT162 (b1/b2)</td>\n",
       "      <td>RNA</td>\n",
       "      <td>43998</td>\n",
       "      <td>≥12</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind, dose-finding</td>\n",
       "      <td>USA, Argentina, Brazil, others</td>\n",
       "      <td>29/04/2020</td>\n",
       "      <td>13/06/2021</td>\n",
       "      <td>NCT04368728</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>University of Oxford/AstraZeneca</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Oxford ChAdOx1-S</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>40051</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>USA, Chile, Peru</td>\n",
       "      <td>28/08/2020</td>\n",
       "      <td>22/12/2020</td>\n",
       "      <td>NCT04516746</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CanSino Biological Inc/Beijing Institute of Bi...</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Cansino Ad5-nCoV</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>40000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Pakistan</td>\n",
       "      <td>15/09/2020</td>\n",
       "      <td>30/12/2021</td>\n",
       "      <td>NCT04526990</td>\n",
       "      <td>Recruiting</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Institutes         Phase  \\\n",
       "0                   Janssen Pharmaceutical Companies     Phase III   \n",
       "1  Beijing Institute of Biological Products/Wuhan...     Phase III   \n",
       "2                       BioNTech/Fosun Pharma/Pfizer  Phase II/III   \n",
       "3                   University of Oxford/AstraZeneca     Phase III   \n",
       "4  CanSino Biological Inc/Beijing Institute of Bi...     Phase III   \n",
       "\n",
       "                        Vaccine                      Platform      N  \\\n",
       "0           Janssen Ad26.COV2.S  Non-replicating viral vector  60000   \n",
       "1  WIBP/BIBP/Sinopharm vaccines                   Inactivated  45000   \n",
       "2       BioNTech BNT162 (b1/b2)                           RNA  43998   \n",
       "3              Oxford ChAdOx1-S  Non-replicating viral vector  40051   \n",
       "4              Cansino Ad5-nCoV  Non-replicating viral vector  40000   \n",
       "\n",
       "  Age (years) N doses Rand.                      Design  \\\n",
       "0         ≥18       1   Yes                Double-blind   \n",
       "1         ≥18       2   Yes                Double-blind   \n",
       "2         ≥12       2   Yes  Double-blind, dose-finding   \n",
       "3         ≥18       2   Yes                Double-blind   \n",
       "4         ≥18       1   Yes                Double-blind   \n",
       "\n",
       "                         Location  Start date Primary completion date  \\\n",
       "0  USA, Argentina, Brazil, others  07/09/2020              10/03/2023   \n",
       "1     Bahrain, Jordan, Egypt, UAE  16/07/2020              16/03/2021   \n",
       "2  USA, Argentina, Brazil, others  29/04/2020              13/06/2021   \n",
       "3                USA, Chile, Peru  28/08/2020              22/12/2020   \n",
       "4                        Pakistan  15/09/2020              30/12/2021   \n",
       "\n",
       "  Trial number      Status  \n",
       "0  NCT04505722  Recruiting  \n",
       "1  NCT04510207  Recruiting  \n",
       "2  NCT04368728  Recruiting  \n",
       "3  NCT04516746  Recruiting  \n",
       "4  NCT04526990  Recruiting  "
      ]
     },
     "execution_count": 459,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# prep: calculate time ranges: min, max, median\n",
    "tf = lf.copy()\n",
    "tf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 460,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 105 entries, 0 to 104\n",
      "Data columns (total 14 columns):\n",
      "Institutes                 105 non-null object\n",
      "Phase                      105 non-null object\n",
      "Vaccine                    105 non-null object\n",
      "Platform                   105 non-null object\n",
      "N                          105 non-null int64\n",
      "Age (years)                105 non-null object\n",
      "N doses                    105 non-null object\n",
      "Rand.                      105 non-null object\n",
      "Design                     105 non-null object\n",
      "Location                   105 non-null object\n",
      "Start date                 105 non-null object\n",
      "Primary completion date    105 non-null object\n",
      "Trial number               105 non-null object\n",
      "Status                     105 non-null object\n",
      "dtypes: int64(1), object(13)\n",
      "memory usage: 11.6+ KB\n"
     ]
    }
   ],
   "source": [
    "#convert columns to time \n",
    "tf.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 461,
   "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>Institutes</th>\n",
       "      <th>Phase</th>\n",
       "      <th>Vaccine</th>\n",
       "      <th>Platform</th>\n",
       "      <th>N</th>\n",
       "      <th>Age (years)</th>\n",
       "      <th>N doses</th>\n",
       "      <th>Rand.</th>\n",
       "      <th>Design</th>\n",
       "      <th>Location</th>\n",
       "      <th>Start date</th>\n",
       "      <th>Primary completion date</th>\n",
       "      <th>Trial number</th>\n",
       "      <th>Status</th>\n",
       "      <th>parsed_start</th>\n",
       "      <th>parsed_primary_completion</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Janssen Pharmaceutical Companies</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Janssen Ad26.COV2.S</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>60000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>USA, Argentina, Brazil, others</td>\n",
       "      <td>07/09/2020</td>\n",
       "      <td>10/03/2023</td>\n",
       "      <td>NCT04505722</td>\n",
       "      <td>Recruiting</td>\n",
       "      <td>2020-09-07</td>\n",
       "      <td>2023-03-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Beijing Institute of Biological Products/Wuhan...</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>WIBP/BIBP/Sinopharm vaccines</td>\n",
       "      <td>Inactivated</td>\n",
       "      <td>45000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Bahrain, Jordan, Egypt, UAE</td>\n",
       "      <td>16/07/2020</td>\n",
       "      <td>16/03/2021</td>\n",
       "      <td>NCT04510207</td>\n",
       "      <td>Recruiting</td>\n",
       "      <td>2020-07-16</td>\n",
       "      <td>2021-03-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BioNTech/Fosun Pharma/Pfizer</td>\n",
       "      <td>Phase II/III</td>\n",
       "      <td>BioNTech BNT162 (b1/b2)</td>\n",
       "      <td>RNA</td>\n",
       "      <td>43998</td>\n",
       "      <td>≥12</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind, dose-finding</td>\n",
       "      <td>USA, Argentina, Brazil, others</td>\n",
       "      <td>29/04/2020</td>\n",
       "      <td>13/06/2021</td>\n",
       "      <td>NCT04368728</td>\n",
       "      <td>Recruiting</td>\n",
       "      <td>2020-04-29</td>\n",
       "      <td>2021-06-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>University of Oxford/AstraZeneca</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Oxford ChAdOx1-S</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>40051</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>USA, Chile, Peru</td>\n",
       "      <td>28/08/2020</td>\n",
       "      <td>22/12/2020</td>\n",
       "      <td>NCT04516746</td>\n",
       "      <td>Recruiting</td>\n",
       "      <td>2020-08-28</td>\n",
       "      <td>2020-12-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CanSino Biological Inc/Beijing Institute of Bi...</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Cansino Ad5-nCoV</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>40000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Pakistan</td>\n",
       "      <td>15/09/2020</td>\n",
       "      <td>30/12/2021</td>\n",
       "      <td>NCT04526990</td>\n",
       "      <td>Recruiting</td>\n",
       "      <td>2020-09-15</td>\n",
       "      <td>2021-12-30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Institutes         Phase  \\\n",
       "0                   Janssen Pharmaceutical Companies     Phase III   \n",
       "1  Beijing Institute of Biological Products/Wuhan...     Phase III   \n",
       "2                       BioNTech/Fosun Pharma/Pfizer  Phase II/III   \n",
       "3                   University of Oxford/AstraZeneca     Phase III   \n",
       "4  CanSino Biological Inc/Beijing Institute of Bi...     Phase III   \n",
       "\n",
       "                        Vaccine                      Platform      N  \\\n",
       "0           Janssen Ad26.COV2.S  Non-replicating viral vector  60000   \n",
       "1  WIBP/BIBP/Sinopharm vaccines                   Inactivated  45000   \n",
       "2       BioNTech BNT162 (b1/b2)                           RNA  43998   \n",
       "3              Oxford ChAdOx1-S  Non-replicating viral vector  40051   \n",
       "4              Cansino Ad5-nCoV  Non-replicating viral vector  40000   \n",
       "\n",
       "  Age (years) N doses Rand.                      Design  \\\n",
       "0         ≥18       1   Yes                Double-blind   \n",
       "1         ≥18       2   Yes                Double-blind   \n",
       "2         ≥12       2   Yes  Double-blind, dose-finding   \n",
       "3         ≥18       2   Yes                Double-blind   \n",
       "4         ≥18       1   Yes                Double-blind   \n",
       "\n",
       "                         Location  Start date Primary completion date  \\\n",
       "0  USA, Argentina, Brazil, others  07/09/2020              10/03/2023   \n",
       "1     Bahrain, Jordan, Egypt, UAE  16/07/2020              16/03/2021   \n",
       "2  USA, Argentina, Brazil, others  29/04/2020              13/06/2021   \n",
       "3                USA, Chile, Peru  28/08/2020              22/12/2020   \n",
       "4                        Pakistan  15/09/2020              30/12/2021   \n",
       "\n",
       "  Trial number      Status parsed_start parsed_primary_completion  \n",
       "0  NCT04505722  Recruiting   2020-09-07                2023-03-10  \n",
       "1  NCT04510207  Recruiting   2020-07-16                2021-03-16  \n",
       "2  NCT04368728  Recruiting   2020-04-29                2021-06-13  \n",
       "3  NCT04516746  Recruiting   2020-08-28                2020-12-22  \n",
       "4  NCT04526990  Recruiting   2020-09-15                2021-12-30  "
      ]
     },
     "execution_count": 461,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf['parsed_start'] = [re.sub(r'(\\d\\d)\\/(\\d\\d)\\/(\\d\\d\\d\\d)','\\g<3>-\\g<2>-\\g<1>', date) for date in tf['Start date']]\n",
    "tf['parsed_primary_completion'] = [re.sub(r'(\\d\\d)\\/(\\d\\d)\\/(\\d\\d\\d\\d)','\\g<3>-\\g<2>-\\g<1>', date) for date in tf['Primary completion date']]\n",
    "tf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 462,
   "metadata": {},
   "outputs": [],
   "source": [
    "tf['parsed_start'] = [datetime.strptime(date, '%Y-%m-%d') for date in tf['parsed_start']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 463,
   "metadata": {},
   "outputs": [],
   "source": [
    "for date in tf['parsed_primary_completion']:\n",
    "    try:\n",
    "        tf['parsed_primary_completion'] = datetime.strptime(date, '%Y-%m-%d')\n",
    "    except:\n",
    "        pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 464,
   "metadata": {},
   "outputs": [],
   "source": [
    "# calculate time ranges: min, max, median\n",
    "tf['timespan'] = tf['parsed_primary_completion'] - tf['parsed_start'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 465,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Institutes</th>\n",
       "      <th>Phase</th>\n",
       "      <th>Vaccine</th>\n",
       "      <th>Platform</th>\n",
       "      <th>N</th>\n",
       "      <th>Age (years)</th>\n",
       "      <th>N doses</th>\n",
       "      <th>Rand.</th>\n",
       "      <th>Design</th>\n",
       "      <th>Location</th>\n",
       "      <th>Start date</th>\n",
       "      <th>Primary completion date</th>\n",
       "      <th>Trial number</th>\n",
       "      <th>Status</th>\n",
       "      <th>parsed_start</th>\n",
       "      <th>parsed_primary_completion</th>\n",
       "      <th>timespan</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Janssen Pharmaceutical Companies</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Janssen Ad26.COV2.S</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>60000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>USA, Argentina, Brazil, others</td>\n",
       "      <td>07/09/2020</td>\n",
       "      <td>10/03/2023</td>\n",
       "      <td>NCT04505722</td>\n",
       "      <td>Recruiting</td>\n",
       "      <td>2020-09-07</td>\n",
       "      <td>2021-12-30</td>\n",
       "      <td>479 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Beijing Institute of Biological Products/Wuhan...</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>WIBP/BIBP/Sinopharm vaccines</td>\n",
       "      <td>Inactivated</td>\n",
       "      <td>45000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Bahrain, Jordan, Egypt, UAE</td>\n",
       "      <td>16/07/2020</td>\n",
       "      <td>16/03/2021</td>\n",
       "      <td>NCT04510207</td>\n",
       "      <td>Recruiting</td>\n",
       "      <td>2020-07-16</td>\n",
       "      <td>2021-12-30</td>\n",
       "      <td>532 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BioNTech/Fosun Pharma/Pfizer</td>\n",
       "      <td>Phase II/III</td>\n",
       "      <td>BioNTech BNT162 (b1/b2)</td>\n",
       "      <td>RNA</td>\n",
       "      <td>43998</td>\n",
       "      <td>≥12</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind, dose-finding</td>\n",
       "      <td>USA, Argentina, Brazil, others</td>\n",
       "      <td>29/04/2020</td>\n",
       "      <td>13/06/2021</td>\n",
       "      <td>NCT04368728</td>\n",
       "      <td>Recruiting</td>\n",
       "      <td>2020-04-29</td>\n",
       "      <td>2021-12-30</td>\n",
       "      <td>610 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>University of Oxford/AstraZeneca</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Oxford ChAdOx1-S</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>40051</td>\n",
       "      <td>≥18</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>USA, Chile, Peru</td>\n",
       "      <td>28/08/2020</td>\n",
       "      <td>22/12/2020</td>\n",
       "      <td>NCT04516746</td>\n",
       "      <td>Recruiting</td>\n",
       "      <td>2020-08-28</td>\n",
       "      <td>2021-12-30</td>\n",
       "      <td>489 days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CanSino Biological Inc/Beijing Institute of Bi...</td>\n",
       "      <td>Phase III</td>\n",
       "      <td>Cansino Ad5-nCoV</td>\n",
       "      <td>Non-replicating viral vector</td>\n",
       "      <td>40000</td>\n",
       "      <td>≥18</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Double-blind</td>\n",
       "      <td>Pakistan</td>\n",
       "      <td>15/09/2020</td>\n",
       "      <td>30/12/2021</td>\n",
       "      <td>NCT04526990</td>\n",
       "      <td>Recruiting</td>\n",
       "      <td>2020-09-15</td>\n",
       "      <td>2021-12-30</td>\n",
       "      <td>471 days</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Institutes         Phase  \\\n",
       "0                   Janssen Pharmaceutical Companies     Phase III   \n",
       "1  Beijing Institute of Biological Products/Wuhan...     Phase III   \n",
       "2                       BioNTech/Fosun Pharma/Pfizer  Phase II/III   \n",
       "3                   University of Oxford/AstraZeneca     Phase III   \n",
       "4  CanSino Biological Inc/Beijing Institute of Bi...     Phase III   \n",
       "\n",
       "                        Vaccine                      Platform      N  \\\n",
       "0           Janssen Ad26.COV2.S  Non-replicating viral vector  60000   \n",
       "1  WIBP/BIBP/Sinopharm vaccines                   Inactivated  45000   \n",
       "2       BioNTech BNT162 (b1/b2)                           RNA  43998   \n",
       "3              Oxford ChAdOx1-S  Non-replicating viral vector  40051   \n",
       "4              Cansino Ad5-nCoV  Non-replicating viral vector  40000   \n",
       "\n",
       "  Age (years) N doses Rand.                      Design  \\\n",
       "0         ≥18       1   Yes                Double-blind   \n",
       "1         ≥18       2   Yes                Double-blind   \n",
       "2         ≥12       2   Yes  Double-blind, dose-finding   \n",
       "3         ≥18       2   Yes                Double-blind   \n",
       "4         ≥18       1   Yes                Double-blind   \n",
       "\n",
       "                         Location  Start date Primary completion date  \\\n",
       "0  USA, Argentina, Brazil, others  07/09/2020              10/03/2023   \n",
       "1     Bahrain, Jordan, Egypt, UAE  16/07/2020              16/03/2021   \n",
       "2  USA, Argentina, Brazil, others  29/04/2020              13/06/2021   \n",
       "3                USA, Chile, Peru  28/08/2020              22/12/2020   \n",
       "4                        Pakistan  15/09/2020              30/12/2021   \n",
       "\n",
       "  Trial number      Status parsed_start parsed_primary_completion timespan  \n",
       "0  NCT04505722  Recruiting   2020-09-07                2021-12-30 479 days  \n",
       "1  NCT04510207  Recruiting   2020-07-16                2021-12-30 532 days  \n",
       "2  NCT04368728  Recruiting   2020-04-29                2021-12-30 610 days  \n",
       "3  NCT04516746  Recruiting   2020-08-28                2021-12-30 489 days  \n",
       "4  NCT04526990  Recruiting   2020-09-15                2021-12-30 471 days  "
      ]
     },
     "execution_count": 465,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 466,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        text-align: right;\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>stat_measure</th>\n",
       "      <th>duration_days</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>mean</td>\n",
       "      <td>511 days 02:17:08.571428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>std</td>\n",
       "      <td>67 days 04:02:00.545199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>min</td>\n",
       "      <td>363 days 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>25%</td>\n",
       "      <td>460 days 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>50%</td>\n",
       "      <td>495 days 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>75%</td>\n",
       "      <td>554 days 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>max</td>\n",
       "      <td>684 days 00:00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  stat_measure             duration_days\n",
       "1         mean  511 days 02:17:08.571428\n",
       "2          std   67 days 04:02:00.545199\n",
       "3          min         363 days 00:00:00\n",
       "4          25%         460 days 00:00:00\n",
       "5          50%         495 days 00:00:00\n",
       "6          75%         554 days 00:00:00\n",
       "7          max         684 days 00:00:00"
      ]
     },
     "execution_count": 466,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "timespans = tf['timespan'].describe().rename_axis('stat_measure').reset_index(name='duration_days')\n",
    "timespans=timespans.drop([0])\n",
    "timespans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 467,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>stat_measure</th>\n",
       "      <th>duration_days</th>\n",
       "      <th>months_rounded</th>\n",
       "      <th>months</th>\n",
       "      <th>years</th>\n",
       "      <th>days</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>mean</td>\n",
       "      <td>511 days 02:17:08.571428</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>1.399331</td>\n",
       "      <td>511.095238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>std</td>\n",
       "      <td>67 days 04:02:00.545199</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.183900</td>\n",
       "      <td>67.168062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>min</td>\n",
       "      <td>363 days 00:00:00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.993860</td>\n",
       "      <td>363.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>25%</td>\n",
       "      <td>460 days 00:00:00</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>1.259437</td>\n",
       "      <td>460.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>50%</td>\n",
       "      <td>495 days 00:00:00</td>\n",
       "      <td>16.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.355264</td>\n",
       "      <td>495.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>75%</td>\n",
       "      <td>554 days 00:00:00</td>\n",
       "      <td>18.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1.516800</td>\n",
       "      <td>554.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>max</td>\n",
       "      <td>684 days 00:00:00</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1.872728</td>\n",
       "      <td>684.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  stat_measure             duration_days  months_rounded  months     years  \\\n",
       "1         mean  511 days 02:17:08.571428            17.0    17.0  1.399331   \n",
       "2          std   67 days 04:02:00.545199             2.0     2.0  0.183900   \n",
       "3          min         363 days 00:00:00            12.0    12.0  0.993860   \n",
       "4          25%         460 days 00:00:00            15.0    15.0  1.259437   \n",
       "5          50%         495 days 00:00:00            16.0    16.0  1.355264   \n",
       "6          75%         554 days 00:00:00            18.0    18.0  1.516800   \n",
       "7          max         684 days 00:00:00            22.0    22.0  1.872728   \n",
       "\n",
       "         days  \n",
       "1  511.095238  \n",
       "2   67.168062  \n",
       "3  363.000000  \n",
       "4  460.000000  \n",
       "5  495.000000  \n",
       "6  554.000000  \n",
       "7  684.000000  "
      ]
     },
     "execution_count": 467,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#https://www.datasciencemadesimple.com/difference-two-dates-days-weeks-months-years-pandas-python-2/\n",
    "timespans['months_rounded'] = round(timespans['duration_days']/np.timedelta64(1,'M'))\n",
    "timespans['months'] = round(timespans['duration_days']/np.timedelta64(1,'M'))\n",
    "timespans['years'] = timespans['duration_days']/np.timedelta64(1,'Y')\n",
    "timespans['days'] = timespans['duration_days']/np.timedelta64(1,'D')\n",
    "timespans.to_csv('data/data-exports/timespans-'+str(today)+'.csv', index = False)\n",
    "timespans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 468,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize as bar chart\n",
    "timespans.plot(kind='barh', y='months', x='stat_measure', legend = False, xticks=[6,12,18,24])\n",
    "plt.savefig('charts/drafts/trial-duration-'+str(today)+'.pdf', transparent = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}