EDA/Exploratory_Data_Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Explorative Data Analysis\n",
    "In this Notebook we show some example data analysis on the UN Security Council dataset. \n",
    "\n",
    "The first step is getting the data and data cleaning.\n",
    "\n",
    "## Data Loading\n",
    "Below we read all the data from our database, and put it in raw, uncleaned, Pandas dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "from sqlalchemy import create_engine\n",
    "from dotenv import load_dotenv\n",
    "\n",
    "# Read the DB info and credentials from our .env file\n",
    "load_dotenv(\"../Database/database.env\")\n",
    "DB_HOSTNAME = os.getenv('POSTGRES_HOSTNAME')\n",
    "DB_USERNAME = os.getenv('POSTGRES_USER')\n",
    "DB_PASSWORD = os.getenv('POSTGRES_PASSWORD')\n",
    "DB_NAME = os.getenv('POSTGRES_DB')\n",
    "\n",
    "engine = create_engine(f'postgresql+psycopg2://{DB_USERNAME}:{DB_PASSWORD}@{DB_HOSTNAME}/{DB_NAME}', echo=False)\n",
    "meetings_df = pd.read_sql_table('meeting', con=engine)\n",
    "resolutions_df = pd.read_sql_table('resolution', con=engine)\n",
    "vetoes_df = pd.read_sql_table('vetocasts', con=engine)\n",
    "states_df = pd.read_sql_table('state', con=engine)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## UN Security Council Meetings"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we take a look at all the meeting rows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "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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       "    }\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>meeting_id</th>\n",
       "      <th>topic</th>\n",
       "      <th>full_text</th>\n",
       "      <th>url</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>veto_used_in_meeting</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S/PV.49</td>\n",
       "      <td>The Spanish question</td>\n",
       "      <td>tau\\nwhich could be agreed to by all of us) an...</td>\n",
       "      <td>https://undocs.org/en/S/PV.49</td>\n",
       "      <td>26 June</td>\n",
       "      <td>1946</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S/PV.8436</td>\n",
       "      <td>The situation in the Middle East</td>\n",
       "      <td>United Nations\\nS/PV.8436\\nSecurity Council\\nS...</td>\n",
       "      <td>https://undocs.org/en/S/PV.8436</td>\n",
       "      <td>21 December</td>\n",
       "      <td>2018</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S/PV.8401</td>\n",
       "      <td>The situation in the Central African Republic</td>\n",
       "      <td>United Nations\\nS/PV.8401\\nSecurity Council\\nS...</td>\n",
       "      <td>https://undocs.org/en/S/PV.8401</td>\n",
       "      <td>15 November</td>\n",
       "      <td>2018</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S/PV.8398</td>\n",
       "      <td>The situation in Somalia</td>\n",
       "      <td>United Nations\\nS/PV.8398\\nSecurity Council\\nS...</td>\n",
       "      <td>https://undocs.org/en/S/PV.8398</td>\n",
       "      <td>14 November</td>\n",
       "      <td>2018</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S/PV.8400</td>\n",
       "      <td>Reports of the Secretary-General on the Sudan ...</td>\n",
       "      <td>United Nations\\nS/PV.8400\\nSecurity Council\\nS...</td>\n",
       "      <td>https://undocs.org/en/S/PV.8400</td>\n",
       "      <td>15 November</td>\n",
       "      <td>2018</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2609</th>\n",
       "      <td>S/PV.9054</td>\n",
       "      <td>Reports of the Secretary-General on the Sudan ...</td>\n",
       "      <td>United Nations\\nS/PV.9054\\nSecurity Council\\nS...</td>\n",
       "      <td>https://undocs.org/en/S/PV.9054</td>\n",
       "      <td>3 June</td>\n",
       "      <td>2022</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2610</th>\n",
       "      <td>S/PV.8979</td>\n",
       "      <td>Letter dated 28 February 2014 from the Perman...</td>\n",
       "      <td>United Nations\\nS/PV.8979\\nSecurity Council\\nS...</td>\n",
       "      <td>https://undocs.org/en/S/PV.8979</td>\n",
       "      <td>25 February</td>\n",
       "      <td>2022</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2611</th>\n",
       "      <td>S/PV.8981</td>\n",
       "      <td>The situation in the Middle East</td>\n",
       "      <td>United Nations\\nS/PV.8981\\nSecurity Council\\nS...</td>\n",
       "      <td>https://undocs.org/en/S/PV.8981</td>\n",
       "      <td>28 February</td>\n",
       "      <td>2022</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2612</th>\n",
       "      <td>S/PV.9025</td>\n",
       "      <td>The situation in Libya</td>\n",
       "      <td>United Nations\\nS/PV.9025\\nSecurity Council\\nS...</td>\n",
       "      <td>https://undocs.org/en/S/PV.9025</td>\n",
       "      <td>29 April</td>\n",
       "      <td>2022</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2613</th>\n",
       "      <td>S/PV.9044</td>\n",
       "      <td>The situation in Somalia</td>\n",
       "      <td>United Nations\\nS/PV.9044\\nSecurity Council\\nS...</td>\n",
       "      <td>https://undocs.org/en/S/PV.9044</td>\n",
       "      <td>26 May</td>\n",
       "      <td>2022</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2614 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     meeting_id                                              topic  \\\n",
       "0       S/PV.49                              The Spanish question    \n",
       "1     S/PV.8436                   The situation in the Middle East   \n",
       "2     S/PV.8401      The situation in the Central African Republic   \n",
       "3     S/PV.8398                           The situation in Somalia   \n",
       "4     S/PV.8400  Reports of the Secretary-General on the Sudan ...   \n",
       "...         ...                                                ...   \n",
       "2609  S/PV.9054  Reports of the Secretary-General on the Sudan ...   \n",
       "2610  S/PV.8979   Letter dated 28 February 2014 from the Perman...   \n",
       "2611  S/PV.8981                   The situation in the Middle East   \n",
       "2612  S/PV.9025                             The situation in Libya   \n",
       "2613  S/PV.9044                           The situation in Somalia   \n",
       "\n",
       "                                              full_text  \\\n",
       "0     tau\\nwhich could be agreed to by all of us) an...   \n",
       "1     United Nations\\nS/PV.8436\\nSecurity Council\\nS...   \n",
       "2     United Nations\\nS/PV.8401\\nSecurity Council\\nS...   \n",
       "3     United Nations\\nS/PV.8398\\nSecurity Council\\nS...   \n",
       "4     United Nations\\nS/PV.8400\\nSecurity Council\\nS...   \n",
       "...                                                 ...   \n",
       "2609  United Nations\\nS/PV.9054\\nSecurity Council\\nS...   \n",
       "2610  United Nations\\nS/PV.8979\\nSecurity Council\\nS...   \n",
       "2611  United Nations\\nS/PV.8981\\nSecurity Council\\nS...   \n",
       "2612  United Nations\\nS/PV.9025\\nSecurity Council\\nS...   \n",
       "2613  United Nations\\nS/PV.9044\\nSecurity Council\\nS...   \n",
       "\n",
       "                                  url         date  year  veto_used_in_meeting  \n",
       "0       https://undocs.org/en/S/PV.49     26 June   1946                  True  \n",
       "1     https://undocs.org/en/S/PV.8436  21 December  2018                 False  \n",
       "2     https://undocs.org/en/S/PV.8401  15 November  2018                 False  \n",
       "3     https://undocs.org/en/S/PV.8398  14 November  2018                 False  \n",
       "4     https://undocs.org/en/S/PV.8400  15 November  2018                 False  \n",
       "...                               ...          ...   ...                   ...  \n",
       "2609  https://undocs.org/en/S/PV.9054       3 June  2022                 False  \n",
       "2610  https://undocs.org/en/S/PV.8979  25 February  2022                  True  \n",
       "2611  https://undocs.org/en/S/PV.8981  28 February  2022                 False  \n",
       "2612  https://undocs.org/en/S/PV.9025     29 April  2022                 False  \n",
       "2613  https://undocs.org/en/S/PV.9044       26 May  2022                 False  \n",
       "\n",
       "[2614 rows x 7 columns]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meetings_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we only want to see the meetings in which a veto was used, we can leverage the last column `veto_used_in_meeting`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>meeting_id</th>\n",
       "      <th>topic</th>\n",
       "      <th>full_text</th>\n",
       "      <th>url</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>veto_used_in_meeting</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S/PV.49</td>\n",
       "      <td>The Spanish question</td>\n",
       "      <td>tau\\nwhich could be agreed to by all of us) an...</td>\n",
       "      <td>https://undocs.org/en/S/PV.49</td>\n",
       "      <td>26 June</td>\n",
       "      <td>1946</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>S/PV.8274</td>\n",
       "      <td>The situation in the Middle East, including th...</td>\n",
       "      <td>United Nations\\nS/PV.8274\\nSecurity Council\\nS...</td>\n",
       "      <td>https://undocs.org/en/S/PV.8274</td>\n",
       "      <td>1 June</td>\n",
       "      <td>2018</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>S/PV.8228</td>\n",
       "      <td>The situation in the Middle East</td>\n",
       "      <td>United Nations\\nS/PV.8228\\nSecurity Council\\nS...</td>\n",
       "      <td>https://undocs.org/en/S/PV.8228</td>\n",
       "      <td>10 April</td>\n",
       "      <td>2018</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>S/PV.188</td>\n",
       "      <td>The Greek question</td>\n",
       "      <td>NATIONS UNIES\\nSECURITY COUNCIL\\n-\\nOFFICIAL R...</td>\n",
       "      <td>https://undocs.org/en/S/PV.188</td>\n",
       "      <td>19 August</td>\n",
       "      <td>1947</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>S/PV.8190</td>\n",
       "      <td>The situation in the Middle East</td>\n",
       "      <td>United Nations\\nS/PV.8190\\nSecurity Council\\nS...</td>\n",
       "      <td>https://undocs.org/en/S/PV.8190</td>\n",
       "      <td>26 February</td>\n",
       "      <td>2018</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2365</th>\n",
       "      <td>S/PV.988</td>\n",
       "      <td>Complaint by Portugal (Goa)</td>\n",
       "      <td></td>\n",
       "      <td>https://undocs.org/en/S/PV.988</td>\n",
       "      <td>18 December</td>\n",
       "      <td>1961</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2376</th>\n",
       "      <td>S/PV.1704</td>\n",
       "      <td>Consideration of measures for the maintenance ...</td>\n",
       "      <td>UNITED NATIONS \\nMEETING: 21 MARCH 1973 \\nPANA...</td>\n",
       "      <td>https://undocs.org/en/S/PV.1704(OR)</td>\n",
       "      <td>21 March</td>\n",
       "      <td>1973</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2389</th>\n",
       "      <td>S/PV.2519</td>\n",
       "      <td>The situation in the Middle East</td>\n",
       "      <td>UNITED NATIONS \\nTHIRTY-NINTH \\nYEAR \\n2519’” ...</td>\n",
       "      <td>https://undocs.org/en/S/PV.2519(OR)</td>\n",
       "      <td>29 February</td>\n",
       "      <td>1984</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2447</th>\n",
       "      <td>S/PV.5488</td>\n",
       "      <td>Middle East situation, including the Palestini...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/PV.5488\\n \\n \\n \\nSec...</td>\n",
       "      <td>https://undocs.org/en/S/PV.5488</td>\n",
       "      <td>13 July</td>\n",
       "      <td>2006</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2500</th>\n",
       "      <td>S/PV.2476</td>\n",
       "      <td>Letter, 1 September 1983, from the United Stat...</td>\n",
       "      <td>UNITED NATIONS \\nSECURITY \\nOFFICIAL \\nRECORDS...</td>\n",
       "      <td>https://undocs.org/en/S/PV.2476(OR)</td>\n",
       "      <td>12 September</td>\n",
       "      <td>1983</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>158 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     meeting_id                                              topic  \\\n",
       "0       S/PV.49                              The Spanish question    \n",
       "21    S/PV.8274  The situation in the Middle East, including th...   \n",
       "53    S/PV.8228                   The situation in the Middle East   \n",
       "56     S/PV.188                                 The Greek question   \n",
       "62    S/PV.8190                   The situation in the Middle East   \n",
       "...         ...                                                ...   \n",
       "2365   S/PV.988                       Complaint by Portugal (Goa)    \n",
       "2376  S/PV.1704  Consideration of measures for the maintenance ...   \n",
       "2389  S/PV.2519                  The situation in the Middle East    \n",
       "2447  S/PV.5488  Middle East situation, including the Palestini...   \n",
       "2500  S/PV.2476  Letter, 1 September 1983, from the United Stat...   \n",
       "\n",
       "                                              full_text  \\\n",
       "0     tau\\nwhich could be agreed to by all of us) an...   \n",
       "21    United Nations\\nS/PV.8274\\nSecurity Council\\nS...   \n",
       "53    United Nations\\nS/PV.8228\\nSecurity Council\\nS...   \n",
       "56    NATIONS UNIES\\nSECURITY COUNCIL\\n-\\nOFFICIAL R...   \n",
       "62    United Nations\\nS/PV.8190\\nSecurity Council\\nS...   \n",
       "...                                                 ...   \n",
       "2365                                                      \n",
       "2376  UNITED NATIONS \\nMEETING: 21 MARCH 1973 \\nPANA...   \n",
       "2389  UNITED NATIONS \\nTHIRTY-NINTH \\nYEAR \\n2519’” ...   \n",
       "2447   \\nUnited Nations \\n \\nS/PV.5488\\n \\n \\n \\nSec...   \n",
       "2500  UNITED NATIONS \\nSECURITY \\nOFFICIAL \\nRECORDS...   \n",
       "\n",
       "                                      url           date  year  \\\n",
       "0           https://undocs.org/en/S/PV.49       26 June   1946   \n",
       "21        https://undocs.org/en/S/PV.8274         1 June  2018   \n",
       "53        https://undocs.org/en/S/PV.8228       10 April  2018   \n",
       "56         https://undocs.org/en/S/PV.188     19 August   1947   \n",
       "62        https://undocs.org/en/S/PV.8190    26 February  2018   \n",
       "...                                   ...            ...   ...   \n",
       "2365       https://undocs.org/en/S/PV.988   18 December   1961   \n",
       "2376  https://undocs.org/en/S/PV.1704(OR)      21 March   1973   \n",
       "2389  https://undocs.org/en/S/PV.2519(OR)   29 February   1984   \n",
       "2447      https://undocs.org/en/S/PV.5488        13 July  2006   \n",
       "2500  https://undocs.org/en/S/PV.2476(OR)  12 September   1983   \n",
       "\n",
       "      veto_used_in_meeting  \n",
       "0                     True  \n",
       "21                    True  \n",
       "53                    True  \n",
       "56                    True  \n",
       "62                    True  \n",
       "...                    ...  \n",
       "2365                  True  \n",
       "2376                  True  \n",
       "2389                  True  \n",
       "2447                  True  \n",
       "2500                  True  \n",
       "\n",
       "[158 rows x 7 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meetings_df.query('veto_used_in_meeting==True')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "vetoed_resolution    213\n",
       "state_id             213\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vetoes_df.count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### UN Security Council Discussed Resolutions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also take a look at the different resolutions discussed during the above mentioned meetings:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>draft_id</th>\n",
       "      <th>final_id</th>\n",
       "      <th>draft_url</th>\n",
       "      <th>final_url</th>\n",
       "      <th>status</th>\n",
       "      <th>draft_text</th>\n",
       "      <th>final_text</th>\n",
       "      <th>year</th>\n",
       "      <th>meeting_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>S/PV.49</td>\n",
       "      <td>None</td>\n",
       "      <td>https://undocs.org/en/S/PV.49</td>\n",
       "      <td>None</td>\n",
       "      <td>vetoed</td>\n",
       "      <td>tau\\nwhich could be agreed to by all of us) an...</td>\n",
       "      <td></td>\n",
       "      <td>1946</td>\n",
       "      <td>S/PV.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>S/2018/1143</td>\n",
       "      <td>S/RES/2450(2018)</td>\n",
       "      <td>https://undocs.org/en/S/2018/1143</td>\n",
       "      <td>https://undocs.org/en/S/RES/2450(2018)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2018/1143 \\n \\n \\nSec...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2450 (2018) \\n \\n...</td>\n",
       "      <td>2018</td>\n",
       "      <td>S/PV.8436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>S/2018/1025</td>\n",
       "      <td>S/RES/2446(2018)</td>\n",
       "      <td>https://undocs.org/en/S/2018/1025</td>\n",
       "      <td>https://undocs.org/en/S/RES/2446(2018)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2018/1025 \\n \\n \\nSec...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2446 (2018) \\n \\n...</td>\n",
       "      <td>2018</td>\n",
       "      <td>S/PV.8401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7</td>\n",
       "      <td>S/2018/1010</td>\n",
       "      <td>S/RES/2444(2018)</td>\n",
       "      <td>https://undocs.org/en/S/2018/1010</td>\n",
       "      <td>https://undocs.org/en/S/RES/2444(2018)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2018/1010 \\n \\n \\nSec...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2444 (2018) \\n \\n...</td>\n",
       "      <td>2018</td>\n",
       "      <td>S/PV.8398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>S/2018/1021</td>\n",
       "      <td>S/RES/2445(2018)</td>\n",
       "      <td>https://undocs.org/en/S/2018/1021</td>\n",
       "      <td>https://undocs.org/en/S/RES/2445(2018)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2018/1021 \\n \\n \\nSec...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2445 (2018) \\n \\n...</td>\n",
       "      <td>2018</td>\n",
       "      <td>S/PV.8400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2685</th>\n",
       "      <td>3017</td>\n",
       "      <td>S/2022/443</td>\n",
       "      <td>S/RES/2636(2022)</td>\n",
       "      <td>https://undocs.org/en/S/2022/443</td>\n",
       "      <td>https://undocs.org/en/S/RES/2636(2022)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2022/443 \\n \\n \\nSecu...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2636 (2022) \\n \\n...</td>\n",
       "      <td>2022</td>\n",
       "      <td>S/PV.9054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2686</th>\n",
       "      <td>3019</td>\n",
       "      <td>S/2022/155</td>\n",
       "      <td>None</td>\n",
       "      <td>https://undocs.org/en/S/2022/155</td>\n",
       "      <td>None</td>\n",
       "      <td>vetoed</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2022/155 \\n \\n \\nSecu...</td>\n",
       "      <td></td>\n",
       "      <td>2022</td>\n",
       "      <td>S/PV.8979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2687</th>\n",
       "      <td>3020</td>\n",
       "      <td>S/2022/158</td>\n",
       "      <td>S/RES/2624(2022)</td>\n",
       "      <td>https://undocs.org/en/S/2022/158</td>\n",
       "      <td>https://undocs.org/en/S/RES/2624(2022)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2022/158 \\n \\n \\nSecu...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2624 (2022) \\n \\n...</td>\n",
       "      <td>2022</td>\n",
       "      <td>S/PV.8981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2688</th>\n",
       "      <td>3021</td>\n",
       "      <td>S/2022/356</td>\n",
       "      <td>S/RES/2629(2022)</td>\n",
       "      <td>https://undocs.org/en/S/2022/356</td>\n",
       "      <td>https://undocs.org/en/S/RES/2629(2022)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2022/356 \\n \\n \\nSecu...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2629 (2022) \\n \\n...</td>\n",
       "      <td>2022</td>\n",
       "      <td>S/PV.9025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2689</th>\n",
       "      <td>3022</td>\n",
       "      <td>S/2022/412</td>\n",
       "      <td>S/RES/2632(2022)</td>\n",
       "      <td>https://undocs.org/en/S/2022/412</td>\n",
       "      <td>https://undocs.org/en/S/RES/2632(2022)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2022/412 \\n \\n \\nSecu...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2632 (2022) \\n \\n...</td>\n",
       "      <td>2022</td>\n",
       "      <td>S/PV.9044</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2690 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        id     draft_id          final_id                          draft_url  \\\n",
       "0        1      S/PV.49              None      https://undocs.org/en/S/PV.49   \n",
       "1        5  S/2018/1143  S/RES/2450(2018)  https://undocs.org/en/S/2018/1143   \n",
       "2        6  S/2018/1025  S/RES/2446(2018)  https://undocs.org/en/S/2018/1025   \n",
       "3        7  S/2018/1010  S/RES/2444(2018)  https://undocs.org/en/S/2018/1010   \n",
       "4        8  S/2018/1021  S/RES/2445(2018)  https://undocs.org/en/S/2018/1021   \n",
       "...    ...          ...               ...                                ...   \n",
       "2685  3017   S/2022/443  S/RES/2636(2022)   https://undocs.org/en/S/2022/443   \n",
       "2686  3019   S/2022/155              None   https://undocs.org/en/S/2022/155   \n",
       "2687  3020   S/2022/158  S/RES/2624(2022)   https://undocs.org/en/S/2022/158   \n",
       "2688  3021   S/2022/356  S/RES/2629(2022)   https://undocs.org/en/S/2022/356   \n",
       "2689  3022   S/2022/412  S/RES/2632(2022)   https://undocs.org/en/S/2022/412   \n",
       "\n",
       "                                   final_url   status  \\\n",
       "0                                       None   vetoed   \n",
       "1     https://undocs.org/en/S/RES/2450(2018)  adopted   \n",
       "2     https://undocs.org/en/S/RES/2446(2018)  adopted   \n",
       "3     https://undocs.org/en/S/RES/2444(2018)  adopted   \n",
       "4     https://undocs.org/en/S/RES/2445(2018)  adopted   \n",
       "...                                      ...      ...   \n",
       "2685  https://undocs.org/en/S/RES/2636(2022)  adopted   \n",
       "2686                                    None   vetoed   \n",
       "2687  https://undocs.org/en/S/RES/2624(2022)  adopted   \n",
       "2688  https://undocs.org/en/S/RES/2629(2022)  adopted   \n",
       "2689  https://undocs.org/en/S/RES/2632(2022)  adopted   \n",
       "\n",
       "                                             draft_text  \\\n",
       "0     tau\\nwhich could be agreed to by all of us) an...   \n",
       "1      \\nUnited Nations \\n \\nS/2018/1143 \\n \\n \\nSec...   \n",
       "2      \\nUnited Nations \\n \\nS/2018/1025 \\n \\n \\nSec...   \n",
       "3      \\nUnited Nations \\n \\nS/2018/1010 \\n \\n \\nSec...   \n",
       "4      \\nUnited Nations \\n \\nS/2018/1021 \\n \\n \\nSec...   \n",
       "...                                                 ...   \n",
       "2685   \\nUnited Nations \\n \\nS/2022/443 \\n \\n \\nSecu...   \n",
       "2686   \\nUnited Nations \\n \\nS/2022/155 \\n \\n \\nSecu...   \n",
       "2687   \\nUnited Nations \\n \\nS/2022/158 \\n \\n \\nSecu...   \n",
       "2688   \\nUnited Nations \\n \\nS/2022/356 \\n \\n \\nSecu...   \n",
       "2689   \\nUnited Nations \\n \\nS/2022/412 \\n \\n \\nSecu...   \n",
       "\n",
       "                                             final_text  year meeting_id  \n",
       "0                                                        1946    S/PV.49  \n",
       "1      \\nUnited Nations \\n \\nS/RES/2450 (2018) \\n \\n...  2018  S/PV.8436  \n",
       "2      \\nUnited Nations \\n \\nS/RES/2446 (2018) \\n \\n...  2018  S/PV.8401  \n",
       "3      \\nUnited Nations \\n \\nS/RES/2444 (2018) \\n \\n...  2018  S/PV.8398  \n",
       "4      \\nUnited Nations \\n \\nS/RES/2445 (2018) \\n \\n...  2018  S/PV.8400  \n",
       "...                                                 ...   ...        ...  \n",
       "2685   \\nUnited Nations \\n \\nS/RES/2636 (2022) \\n \\n...  2022  S/PV.9054  \n",
       "2686                                                     2022  S/PV.8979  \n",
       "2687   \\nUnited Nations \\n \\nS/RES/2624 (2022) \\n \\n...  2022  S/PV.8981  \n",
       "2688   \\nUnited Nations \\n \\nS/RES/2629 (2022) \\n \\n...  2022  S/PV.9025  \n",
       "2689   \\nUnited Nations \\n \\nS/RES/2632 (2022) \\n \\n...  2022  S/PV.9044  \n",
       "\n",
       "[2690 rows x 10 columns]"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "resolutions_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### All Data together in one dataframe\n",
    "For further data analysis, we will merge the above 2 dataframes into 1 Pandas dataframe.\n",
    "Relevant columns are `status` (`adopted`, `not adopted`, or `vetoed`), the column `vetoed_by` which only has a value whenever the status is `vetoed`. \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "meetings_and_resolutions_df = resolutions_df.merge(meetings_df, how=\"inner\", on=[\"meeting_id\",\"year\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The last column `veto_used_in_meeting` shows whether in the meeting a veto was cast. \n",
    "\n",
    "This may show `True` even though a resolution on that line was adopted. This only means that in the meeting there was more than one resolution discussed, and at least one other resolution was vetoed. You can also see that if a `draft resolution` is adopted, its final accepted id changes and takes the form `S/RES/XXX(YYYY)` where `YYYY` stands for the year.\n",
    "\n",
    "**Example**:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>meeting_id</th>\n",
       "      <th>draft_id</th>\n",
       "      <th>final_id</th>\n",
       "      <th>status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1605</th>\n",
       "      <td>S/PV.906</td>\n",
       "      <td>S/4523</td>\n",
       "      <td>None</td>\n",
       "      <td>vetoed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1606</th>\n",
       "      <td>S/PV.906</td>\n",
       "      <td>S/4519</td>\n",
       "      <td>None</td>\n",
       "      <td>not adopted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1607</th>\n",
       "      <td>S/PV.906</td>\n",
       "      <td>S/4525</td>\n",
       "      <td>S/RES/157(1960)</td>\n",
       "      <td>adopted</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     meeting_id draft_id         final_id       status\n",
       "1605   S/PV.906   S/4523             None       vetoed\n",
       "1606   S/PV.906   S/4519             None  not adopted\n",
       "1607   S/PV.906   S/4525  S/RES/157(1960)      adopted"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meetings_and_resolutions_df.query('meeting_id == \"S/PV.906\"')[['meeting_id', 'draft_id', 'final_id', 'status']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "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>meeting_id</th>\n",
       "      <th>draft_id</th>\n",
       "      <th>final_id</th>\n",
       "      <th>topic</th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>S/PV.8392</td>\n",
       "      <td>S/2018/989</td>\n",
       "      <td>S/RES/2443(2018)</td>\n",
       "      <td>The situation in Bosnia and Herzegovina</td>\n",
       "      <td>6 November</td>\n",
       "      <td>2018</td>\n",
       "      <td>adopted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>S/PV.8658</td>\n",
       "      <td>S/2019/859</td>\n",
       "      <td>S/RES/2496(2019)</td>\n",
       "      <td>The situation in Bosnia and Herzegovina</td>\n",
       "      <td>5 November</td>\n",
       "      <td>2019</td>\n",
       "      <td>adopted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>S/PV.8896</td>\n",
       "      <td>S/2021/913</td>\n",
       "      <td>S/RES/2604(2021)</td>\n",
       "      <td>The situation in Bosnia and Herzegovina</td>\n",
       "      <td>3 November</td>\n",
       "      <td>2021</td>\n",
       "      <td>adopted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>S/2020/108</td>\n",
       "      <td>S/2020/1080</td>\n",
       "      <td>S/RES/2549(2020)</td>\n",
       "      <td>The situation in Bosnia and Herzegovina</td>\n",
       "      <td>5 November</td>\n",
       "      <td>2020</td>\n",
       "      <td>adopted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>S/PV.7481</td>\n",
       "      <td>S/2015/508</td>\n",
       "      <td>None</td>\n",
       "      <td>The situation in Bosnia and Herzegovina</td>\n",
       "      <td>8 July</td>\n",
       "      <td>2015</td>\n",
       "      <td>vetoed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2576</th>\n",
       "      <td>S/PV.3909</td>\n",
       "      <td>S/1998/648</td>\n",
       "      <td>S/RES/1184(1998)</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "      <td>16 July</td>\n",
       "      <td>1998</td>\n",
       "      <td>adopted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2589</th>\n",
       "      <td>S/PV.5567</td>\n",
       "      <td>S/2006/900</td>\n",
       "      <td>S/RES/1722(2006)</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "      <td>21 November</td>\n",
       "      <td>2006</td>\n",
       "      <td>adopted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2592</th>\n",
       "      <td>S/PV.5782</td>\n",
       "      <td>S/2007/673</td>\n",
       "      <td>S/RES/1785(2007)</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "      <td>21 November</td>\n",
       "      <td>2007</td>\n",
       "      <td>adopted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2606</th>\n",
       "      <td>S/PV.7803</td>\n",
       "      <td>S/2016/935</td>\n",
       "      <td>S/RES/2315(2016)</td>\n",
       "      <td>The situation in Bosnia and Herzegovina</td>\n",
       "      <td>8 November</td>\n",
       "      <td>2016</td>\n",
       "      <td>adopted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2647</th>\n",
       "      <td>S/PV.4030</td>\n",
       "      <td>S/1999/834</td>\n",
       "      <td>S/RES/1256(1999)</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "      <td>3 August</td>\n",
       "      <td>1999</td>\n",
       "      <td>adopted</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>65 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      meeting_id     draft_id          final_id  \\\n",
       "35     S/PV.8392   S/2018/989  S/RES/2443(2018)   \n",
       "74     S/PV.8658   S/2019/859  S/RES/2496(2019)   \n",
       "162    S/PV.8896   S/2021/913  S/RES/2604(2021)   \n",
       "213   S/2020/108  S/2020/1080  S/RES/2549(2020)   \n",
       "493    S/PV.7481   S/2015/508              None   \n",
       "...          ...          ...               ...   \n",
       "2576   S/PV.3909   S/1998/648  S/RES/1184(1998)   \n",
       "2589   S/PV.5567   S/2006/900  S/RES/1722(2006)   \n",
       "2592   S/PV.5782   S/2007/673  S/RES/1785(2007)   \n",
       "2606   S/PV.7803   S/2016/935  S/RES/2315(2016)   \n",
       "2647   S/PV.4030   S/1999/834  S/RES/1256(1999)   \n",
       "\n",
       "                                         topic         date  year   status  \n",
       "35     The situation in Bosnia and Herzegovina   6 November  2018  adopted  \n",
       "74     The situation in Bosnia and Herzegovina   5 November  2019  adopted  \n",
       "162    The situation in Bosnia and Herzegovina   3 November  2021  adopted  \n",
       "213   The situation in Bosnia and Herzegovina   5 November   2020  adopted  \n",
       "493    The situation in Bosnia and Herzegovina      8 July   2015   vetoed  \n",
       "...                                        ...          ...   ...      ...  \n",
       "2576                    Bosnia and Herzegovina      16 July  1998  adopted  \n",
       "2589                    Bosnia and Herzegovina  21 November  2006  adopted  \n",
       "2592                    Bosnia and Herzegovina  21 November  2007  adopted  \n",
       "2606   The situation in Bosnia and Herzegovina   8 November  2016  adopted  \n",
       "2647                    Bosnia and Herzegovina     3 August  1999  adopted  \n",
       "\n",
       "[65 rows x 7 columns]"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meetings_and_resolutions_df[meetings_and_resolutions_df['topic'].str.contains(\"Bosnia\")][['meeting_id', 'draft_id', 'final_id', 'topic', 'date', 'year', 'status']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Veto Analysis\n",
    "In this section we will take a look at the usage of the veto votes by the different P5 members.\n",
    "\n",
    "To start, we'll need the 2 other data frames `vetoes_df` and `states_df` from our dataset to figure out what resolution has been vetoed, and by which members.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vetoed_resolution</th>\n",
       "      <th>state_id</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S/PV.49</td>\n",
       "      <td>5</td>\n",
       "      <td>Russia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S/2018/321</td>\n",
       "      <td>5</td>\n",
       "      <td>Russia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S/2018/156</td>\n",
       "      <td>5</td>\n",
       "      <td>Russia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S/2019/756</td>\n",
       "      <td>5</td>\n",
       "      <td>Russia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S/2019/186</td>\n",
       "      <td>5</td>\n",
       "      <td>Russia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>S/11713</td>\n",
       "      <td>3</td>\n",
       "      <td>France</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>S/11967</td>\n",
       "      <td>3</td>\n",
       "      <td>France</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>S/14459</td>\n",
       "      <td>3</td>\n",
       "      <td>France</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>S/14460/Rev.1</td>\n",
       "      <td>3</td>\n",
       "      <td>France</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>S/14461</td>\n",
       "      <td>3</td>\n",
       "      <td>France</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>216 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    vetoed_resolution  state_id    name\n",
       "0             S/PV.49         5  Russia\n",
       "1          S/2018/321         5  Russia\n",
       "2          S/2018/156         5  Russia\n",
       "3          S/2019/756         5  Russia\n",
       "4          S/2019/186         5  Russia\n",
       "..                ...       ...     ...\n",
       "211           S/11713         3  France\n",
       "212           S/11967         3  France\n",
       "213           S/14459         3  France\n",
       "214     S/14460/Rev.1         3  France\n",
       "215           S/14461         3  France\n",
       "\n",
       "[216 rows x 3 columns]"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vetoes_w_names_df = vetoes_df.merge(states_df, how=\"inner\", on=\"state_id\")\n",
    "vetoes_w_names_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now also see in which meetings what P5 members cast vetoes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vetoed_resolution</th>\n",
       "      <th>state_id</th>\n",
       "      <th>name</th>\n",
       "      <th>id</th>\n",
       "      <th>draft_id</th>\n",
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       "      <th>year</th>\n",
       "      <th>meeting_id</th>\n",
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       "      <th>full_text</th>\n",
       "      <th>url</th>\n",
       "      <th>date</th>\n",
       "      <th>veto_used_in_meeting</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S/PV.49</td>\n",
       "      <td>5</td>\n",
       "      <td>Russia</td>\n",
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       "      <td>S/PV.49</td>\n",
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       "      <td>vetoed</td>\n",
       "      <td>tau\\nwhich could be agreed to by all of us) an...</td>\n",
       "      <td></td>\n",
       "      <td>1946</td>\n",
       "      <td>S/PV.49</td>\n",
       "      <td>The Spanish question</td>\n",
       "      <td>tau\\nwhich could be agreed to by all of us) an...</td>\n",
       "      <td>https://undocs.org/en/S/PV.49</td>\n",
       "      <td>26 June</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S/2018/321</td>\n",
       "      <td>5</td>\n",
       "      <td>Russia</td>\n",
       "      <td>48</td>\n",
       "      <td>S/2018/321</td>\n",
       "      <td>None</td>\n",
       "      <td>https://undocs.org/en/S/2018/321</td>\n",
       "      <td>None</td>\n",
       "      <td>vetoed</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2018/321 \\n \\n \\nSecu...</td>\n",
       "      <td></td>\n",
       "      <td>2018</td>\n",
       "      <td>S/PV.8228</td>\n",
       "      <td>The situation in the Middle East</td>\n",
       "      <td>United Nations\\nS/PV.8228\\nSecurity Council\\nS...</td>\n",
       "      <td>https://undocs.org/en/S/PV.8228</td>\n",
       "      <td>10 April</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S/2018/156</td>\n",
       "      <td>5</td>\n",
       "      <td>Russia</td>\n",
       "      <td>62</td>\n",
       "      <td>S/2018/156</td>\n",
       "      <td>None</td>\n",
       "      <td>https://undocs.org/en/S/2018/156</td>\n",
       "      <td>None</td>\n",
       "      <td>vetoed</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2018/156 \\n \\n \\nSecu...</td>\n",
       "      <td></td>\n",
       "      <td>2018</td>\n",
       "      <td>S/PV.8190</td>\n",
       "      <td>The situation in the Middle East</td>\n",
       "      <td>United Nations\\nS/PV.8190\\nSecurity Council\\nS...</td>\n",
       "      <td>https://undocs.org/en/S/PV.8190</td>\n",
       "      <td>26 February</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S/2019/756</td>\n",
       "      <td>5</td>\n",
       "      <td>Russia</td>\n",
       "      <td>75</td>\n",
       "      <td>S/2019/756</td>\n",
       "      <td>None</td>\n",
       "      <td>https://undocs.org/en/S/2019/756</td>\n",
       "      <td>None</td>\n",
       "      <td>vetoed</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2019/756 \\n \\n \\nSecu...</td>\n",
       "      <td></td>\n",
       "      <td>2019</td>\n",
       "      <td>S/PV.8623</td>\n",
       "      <td>The situation in the Middle East</td>\n",
       "      <td>United Nations\\nS/PV.8623\\nSecurity Council\\nS...</td>\n",
       "      <td>https://undocs.org/en/S/PV.8623</td>\n",
       "      <td>19 September</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S/2019/186</td>\n",
       "      <td>5</td>\n",
       "      <td>Russia</td>\n",
       "      <td>93</td>\n",
       "      <td>S/2019/186</td>\n",
       "      <td>None</td>\n",
       "      <td>https://undocs.org/en/S/2019/186</td>\n",
       "      <td>None</td>\n",
       "      <td>vetoed</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2019/186 \\n \\n \\nSecu...</td>\n",
       "      <td></td>\n",
       "      <td>2019</td>\n",
       "      <td>S/PV.8476</td>\n",
       "      <td>The situation in the Bolivarian Republic of Ve...</td>\n",
       "      <td>United Nations\\nS/PV.8476\\nSecurity Council\\nS...</td>\n",
       "      <td>https://undocs.org/en/S/PV.8476</td>\n",
       "      <td>28 February</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>S/11713</td>\n",
       "      <td>3</td>\n",
       "      <td>France</td>\n",
       "      <td>1810</td>\n",
       "      <td>S/11713</td>\n",
       "      <td>None</td>\n",
       "      <td>https://undocs.org/en/S/11713</td>\n",
       "      <td>None</td>\n",
       "      <td>vetoed</td>\n",
       "      <td>Distr. \\nGENERAL \\nS/11713 \\n6 June 1975 \\nORI...</td>\n",
       "      <td></td>\n",
       "      <td>1975</td>\n",
       "      <td>S/PV.1829</td>\n",
       "      <td>The situation in Namibia</td>\n",
       "      <td>UNITED NATIONS \\nSECURITY COUNCIL \\nOFFICIAL \\...</td>\n",
       "      <td>https://undocs.org/en/S/PV.1829(OR)</td>\n",
       "      <td>06 June</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>S/11967</td>\n",
       "      <td>3</td>\n",
       "      <td>France</td>\n",
       "      <td>1817</td>\n",
       "      <td>S/11967</td>\n",
       "      <td>None</td>\n",
       "      <td>https://undocs.org/en/S/11967</td>\n",
       "      <td>None</td>\n",
       "      <td>vetoed</td>\n",
       "      <td>Distr. \\nGENERAL \\ns/=967 \\n5 February \\n1976 ...</td>\n",
       "      <td></td>\n",
       "      <td>1976</td>\n",
       "      <td>S/PV.1888</td>\n",
       "      <td>The situation in the Comoros</td>\n",
       "      <td>UNITED NATIONS \\nSECURITY COUNCIL \\nOFFICIAL \\...</td>\n",
       "      <td>https://undocs.org/en/S/PV.1888(OR)</td>\n",
       "      <td>06 February</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>S/14459</td>\n",
       "      <td>3</td>\n",
       "      <td>France</td>\n",
       "      <td>1843</td>\n",
       "      <td>S/14459</td>\n",
       "      <td>None</td>\n",
       "      <td>https://undocs.org/en/S/14459</td>\n",
       "      <td>None</td>\n",
       "      <td>vetoed</td>\n",
       "      <td>,, Y\\?i,q?zz Panama, Tunisia \\nand Uganda: \\nM...</td>\n",
       "      <td></td>\n",
       "      <td>1981</td>\n",
       "      <td>S/PV.2277</td>\n",
       "      <td>The situation in Namibia</td>\n",
       "      <td>UNITED NATIONS \\nTHIRTY-SIXTH \\nYEAR \\nNEW YOR...</td>\n",
       "      <td>https://undocs.org/en/S/PV.2277(OR)</td>\n",
       "      <td>30 April</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>S/14460/Rev.1</td>\n",
       "      <td>3</td>\n",
       "      <td>France</td>\n",
       "      <td>1844</td>\n",
       "      <td>S/14460/Rev.1</td>\n",
       "      <td>None</td>\n",
       "      <td>https://undocs.org/en/S/14460/Rev.1</td>\n",
       "      <td>None</td>\n",
       "      <td>vetoed</td>\n",
       "      <td>Distr. \\nGENERAL \\nS/l4460/Rev.l \\n29 April \\n...</td>\n",
       "      <td></td>\n",
       "      <td>1981</td>\n",
       "      <td>S/PV.2277</td>\n",
       "      <td>The situation in Namibia</td>\n",
       "      <td>UNITED NATIONS \\nTHIRTY-SIXTH \\nYEAR \\nNEW YOR...</td>\n",
       "      <td>https://undocs.org/en/S/PV.2277(OR)</td>\n",
       "      <td>30 April</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>S/14461</td>\n",
       "      <td>3</td>\n",
       "      <td>France</td>\n",
       "      <td>1845</td>\n",
       "      <td>S/14461</td>\n",
       "      <td>None</td>\n",
       "      <td>https://undocs.org/en/S/14461</td>\n",
       "      <td>None</td>\n",
       "      <td>vetoed</td>\n",
       "      <td>Distr. \\nGIW?IRAL \\ns/14461 \\n27 April \\n1981 ...</td>\n",
       "      <td></td>\n",
       "      <td>1981</td>\n",
       "      <td>S/PV.2277</td>\n",
       "      <td>The situation in Namibia</td>\n",
       "      <td>UNITED NATIONS \\nTHIRTY-SIXTH \\nYEAR \\nNEW YOR...</td>\n",
       "      <td>https://undocs.org/en/S/PV.2277(OR)</td>\n",
       "      <td>30 April</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>216 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    vetoed_resolution  state_id    name    id       draft_id final_id  \\\n",
       "0             S/PV.49         5  Russia     1        S/PV.49     None   \n",
       "1          S/2018/321         5  Russia    48     S/2018/321     None   \n",
       "2          S/2018/156         5  Russia    62     S/2018/156     None   \n",
       "3          S/2019/756         5  Russia    75     S/2019/756     None   \n",
       "4          S/2019/186         5  Russia    93     S/2019/186     None   \n",
       "..                ...       ...     ...   ...            ...      ...   \n",
       "211           S/11713         3  France  1810        S/11713     None   \n",
       "212           S/11967         3  France  1817        S/11967     None   \n",
       "213           S/14459         3  France  1843        S/14459     None   \n",
       "214     S/14460/Rev.1         3  France  1844  S/14460/Rev.1     None   \n",
       "215           S/14461         3  France  1845        S/14461     None   \n",
       "\n",
       "                               draft_url final_url  status  \\\n",
       "0          https://undocs.org/en/S/PV.49      None  vetoed   \n",
       "1       https://undocs.org/en/S/2018/321      None  vetoed   \n",
       "2       https://undocs.org/en/S/2018/156      None  vetoed   \n",
       "3       https://undocs.org/en/S/2019/756      None  vetoed   \n",
       "4       https://undocs.org/en/S/2019/186      None  vetoed   \n",
       "..                                   ...       ...     ...   \n",
       "211        https://undocs.org/en/S/11713      None  vetoed   \n",
       "212        https://undocs.org/en/S/11967      None  vetoed   \n",
       "213        https://undocs.org/en/S/14459      None  vetoed   \n",
       "214  https://undocs.org/en/S/14460/Rev.1      None  vetoed   \n",
       "215        https://undocs.org/en/S/14461      None  vetoed   \n",
       "\n",
       "                                            draft_text final_text  year  \\\n",
       "0    tau\\nwhich could be agreed to by all of us) an...             1946   \n",
       "1     \\nUnited Nations \\n \\nS/2018/321 \\n \\n \\nSecu...             2018   \n",
       "2     \\nUnited Nations \\n \\nS/2018/156 \\n \\n \\nSecu...             2018   \n",
       "3     \\nUnited Nations \\n \\nS/2019/756 \\n \\n \\nSecu...             2019   \n",
       "4     \\nUnited Nations \\n \\nS/2019/186 \\n \\n \\nSecu...             2019   \n",
       "..                                                 ...        ...   ...   \n",
       "211  Distr. \\nGENERAL \\nS/11713 \\n6 June 1975 \\nORI...             1975   \n",
       "212  Distr. \\nGENERAL \\ns/=967 \\n5 February \\n1976 ...             1976   \n",
       "213  ,, Y\\?i,q?zz Panama, Tunisia \\nand Uganda: \\nM...             1981   \n",
       "214  Distr. \\nGENERAL \\nS/l4460/Rev.l \\n29 April \\n...             1981   \n",
       "215  Distr. \\nGIW?IRAL \\ns/14461 \\n27 April \\n1981 ...             1981   \n",
       "\n",
       "    meeting_id                                              topic  \\\n",
       "0      S/PV.49                              The Spanish question    \n",
       "1    S/PV.8228                   The situation in the Middle East   \n",
       "2    S/PV.8190                   The situation in the Middle East   \n",
       "3    S/PV.8623                   The situation in the Middle East   \n",
       "4    S/PV.8476  The situation in the Bolivarian Republic of Ve...   \n",
       "..         ...                                                ...   \n",
       "211  S/PV.1829                          The situation in Namibia    \n",
       "212  S/PV.1888                      The situation in the Comoros    \n",
       "213  S/PV.2277                          The situation in Namibia    \n",
       "214  S/PV.2277                          The situation in Namibia    \n",
       "215  S/PV.2277                          The situation in Namibia    \n",
       "\n",
       "                                             full_text  \\\n",
       "0    tau\\nwhich could be agreed to by all of us) an...   \n",
       "1    United Nations\\nS/PV.8228\\nSecurity Council\\nS...   \n",
       "2    United Nations\\nS/PV.8190\\nSecurity Council\\nS...   \n",
       "3    United Nations\\nS/PV.8623\\nSecurity Council\\nS...   \n",
       "4    United Nations\\nS/PV.8476\\nSecurity Council\\nS...   \n",
       "..                                                 ...   \n",
       "211  UNITED NATIONS \\nSECURITY COUNCIL \\nOFFICIAL \\...   \n",
       "212  UNITED NATIONS \\nSECURITY COUNCIL \\nOFFICIAL \\...   \n",
       "213  UNITED NATIONS \\nTHIRTY-SIXTH \\nYEAR \\nNEW YOR...   \n",
       "214  UNITED NATIONS \\nTHIRTY-SIXTH \\nYEAR \\nNEW YOR...   \n",
       "215  UNITED NATIONS \\nTHIRTY-SIXTH \\nYEAR \\nNEW YOR...   \n",
       "\n",
       "                                     url          date  veto_used_in_meeting  \n",
       "0          https://undocs.org/en/S/PV.49      26 June                   True  \n",
       "1        https://undocs.org/en/S/PV.8228      10 April                  True  \n",
       "2        https://undocs.org/en/S/PV.8190   26 February                  True  \n",
       "3        https://undocs.org/en/S/PV.8623  19 September                  True  \n",
       "4        https://undocs.org/en/S/PV.8476   28 February                  True  \n",
       "..                                   ...           ...                   ...  \n",
       "211  https://undocs.org/en/S/PV.1829(OR)      06 June                   True  \n",
       "212  https://undocs.org/en/S/PV.1888(OR)  06 February                   True  \n",
       "213  https://undocs.org/en/S/PV.2277(OR)     30 April                   True  \n",
       "214  https://undocs.org/en/S/PV.2277(OR)     30 April                   True  \n",
       "215  https://undocs.org/en/S/PV.2277(OR)     30 April                   True  \n",
       "\n",
       "[216 rows x 18 columns]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_data_vetoed_df = meetings_and_resolutions_df.merge(vetoes_df, how=\"inner\", left_on=\"draft_id\", right_on=\"vetoed_resolution\")\n",
    "all_data_vetoed_w_state_names_df = vetoes_df.merge(states_df, how=\"inner\", on=\"state_id\")\n",
    "all_data_vetoed_df\n",
    "\n",
    "vetoed_resolutions_df=vetoes_w_names_df.merge(all_data_vetoed_df, how=\"inner\",left_on=[\"vetoed_resolution\",\"vetoed_resolution\",\"state_id\"],right_on=[\"vetoed_resolution\",\"draft_id\",\"state_id\"])\n",
    "vetoed_resolutions_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following example shows a UN Security Council Meeting where a resolution was discussed, vetoed by 2 P5 members:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
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       "      <th>4</th>\n",
       "      <td>S/2019/186</td>\n",
       "      <td>5</td>\n",
       "      <td>Russia</td>\n",
       "      <td>93</td>\n",
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       "      <td>S/2019/186</td>\n",
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       "      <td>93</td>\n",
       "      <td>S/2019/186</td>\n",
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      "text/plain": [
       "    vetoed_resolution  state_id    name  id    draft_id final_id  \\\n",
       "4          S/2019/186         5  Russia  93  S/2019/186     None   \n",
       "165        S/2019/186         4   China  93  S/2019/186     None   \n",
       "\n",
       "                            draft_url final_url  status  \\\n",
       "4    https://undocs.org/en/S/2019/186      None  vetoed   \n",
       "165  https://undocs.org/en/S/2019/186      None  vetoed   \n",
       "\n",
       "                                            draft_text final_text  year  \\\n",
       "4     \\nUnited Nations \\n \\nS/2019/186 \\n \\n \\nSecu...             2019   \n",
       "165   \\nUnited Nations \\n \\nS/2019/186 \\n \\n \\nSecu...             2019   \n",
       "\n",
       "    meeting_id                                              topic  \\\n",
       "4    S/PV.8476  The situation in the Bolivarian Republic of Ve...   \n",
       "165  S/PV.8476  The situation in the Bolivarian Republic of Ve...   \n",
       "\n",
       "                                             full_text  \\\n",
       "4    United Nations\\nS/PV.8476\\nSecurity Council\\nS...   \n",
       "165  United Nations\\nS/PV.8476\\nSecurity Council\\nS...   \n",
       "\n",
       "                                 url         date  veto_used_in_meeting  \n",
       "4    https://undocs.org/en/S/PV.8476  28 February                  True  \n",
       "165  https://undocs.org/en/S/PV.8476  28 February                  True  "
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     },
     "execution_count": 10,
     "metadata": {},
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   "source": [
    "vetoed_resolutions_df.query('meeting_id==\"S/PV.8476\"')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now would like to get an overview of who are the most prominent veto casters according to our dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name\n",
      "China     16\n",
      "France    11\n",
      "Russia    88\n",
      "UK        22\n",
      "USA       76\n",
      "dtype: int64\n"
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of Vetoes Cast by Permanent Members over the years\"},\"xaxis\":{\"gridcolor\":\"#E1E5ED\",\"linecolor\":\"black\",\"showgrid\":true,\"tickfont\":{\"color\":\"#4D5663\"},\"title\":{\"font\":{\"color\":\"#4D5663\"},\"text\":\"Permanent UNSC Members\"},\"zerolinecolor\":\"#E1E5ED\"},\"yaxis\":{\"gridcolor\":\"#E1E5ED\",\"linecolor\":\"black\",\"showgrid\":true,\"tickfont\":{\"color\":\"#4D5663\"},\"title\":{\"font\":{\"color\":\"#4D5663\"},\"text\":\"# Resolutions Vetoed\"},\"zerolinecolor\":\"#E1E5ED\"}},                        {\"showLink\": true, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\", \"responsive\": true}                    ).then(function(){\n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(vetoes_w_names_df.groupby('name').size())\n",
    "\n",
    "# cufflinks are required, else we end up with an error \"AttributeError: 'Series' object has no attribute 'iplot'\"\n",
    "import cufflinks as cf\n",
    "cf.go_offline()\n",
    "cf.set_config_file(offline=False, world_readable=True)\n",
    "\n",
    "vetoes_w_names_df.groupby('name').count()['vetoed_resolution'].iplot(\n",
    "    kind='bar',\n",
    "    yTitle='# Resolutions Vetoed',\n",
    "    linecolor='black',\n",
    "    opacity=0.8,\n",
    "    title='Number of Vetoes Cast by Permanent Members over the years',\n",
    "    xTitle='Permanent UNSC Members'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Text Pre-processing\n",
    "In this part we'll pre-process the text so we can use it for further analysis. Since this is all text analysis, we will only look at text data after 1994. We know that the text from OCR'd transcripts prior to 1994 is not reliable. Further we will use language detection, and delete records that are not recognized as valid English.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 1: Only keep the features (columns) and rows we're really interested in\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>draft_id</th>\n",
       "      <th>final_id</th>\n",
       "      <th>status</th>\n",
       "      <th>draft_text</th>\n",
       "      <th>final_text</th>\n",
       "      <th>year</th>\n",
       "      <th>meeting_id</th>\n",
       "      <th>topic</th>\n",
       "      <th>full_text</th>\n",
       "      <th>veto_used_in_meeting</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>S/2018/1143</td>\n",
       "      <td>S/RES/2450(2018)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2018/1143 \\n \\n \\nSec...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2450 (2018) \\n \\n...</td>\n",
       "      <td>2018</td>\n",
       "      <td>S/PV.8436</td>\n",
       "      <td>The situation in the Middle East</td>\n",
       "      <td>United Nations\\nS/PV.8436\\nSecurity Council\\nS...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>S/2018/1025</td>\n",
       "      <td>S/RES/2446(2018)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2018/1025 \\n \\n \\nSec...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2446 (2018) \\n \\n...</td>\n",
       "      <td>2018</td>\n",
       "      <td>S/PV.8401</td>\n",
       "      <td>The situation in the Central African Republic</td>\n",
       "      <td>United Nations\\nS/PV.8401\\nSecurity Council\\nS...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7</td>\n",
       "      <td>S/2018/1010</td>\n",
       "      <td>S/RES/2444(2018)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2018/1010 \\n \\n \\nSec...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2444 (2018) \\n \\n...</td>\n",
       "      <td>2018</td>\n",
       "      <td>S/PV.8398</td>\n",
       "      <td>The situation in Somalia</td>\n",
       "      <td>United Nations\\nS/PV.8398\\nSecurity Council\\nS...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>S/2018/1021</td>\n",
       "      <td>S/RES/2445(2018)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2018/1021 \\n \\n \\nSec...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2445 (2018) \\n \\n...</td>\n",
       "      <td>2018</td>\n",
       "      <td>S/PV.8400</td>\n",
       "      <td>Reports of the Secretary-General on the Sudan ...</td>\n",
       "      <td>United Nations\\nS/PV.8400\\nSecurity Council\\nS...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>9</td>\n",
       "      <td>S/2018/990</td>\n",
       "      <td>S/RES/2442(2018)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2018/990 \\n \\n \\nSecu...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2442 (2018) \\n \\n...</td>\n",
       "      <td>2018</td>\n",
       "      <td>S/PV.8391</td>\n",
       "      <td>The situation in Somalia</td>\n",
       "      <td>United Nations\\nS/PV.8391\\nSecurity Council\\nS...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2661</th>\n",
       "      <td>2993</td>\n",
       "      <td>S/2016/241</td>\n",
       "      <td>S/RES/2274(2016)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2016/241 \\n \\n \\nSecu...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2274 (2016) \\n \\n...</td>\n",
       "      <td>2016</td>\n",
       "      <td>S/PV.7645</td>\n",
       "      <td>The situation in Afghanistan</td>\n",
       "      <td>*1607042*\\n16-07042 (E)\\nThis record contains ...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2663</th>\n",
       "      <td>2995</td>\n",
       "      <td>S/1994/96</td>\n",
       "      <td>S/RES/896(1994)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>UNITED\\nUNITED\\nS\\nNATIONS\\nNATIONS\\nSecurity ...</td>\n",
       "      <td>UNITED\\nUNITED\\nS\\nNATIONS\\nNATIONS\\nSecurity ...</td>\n",
       "      <td>1994</td>\n",
       "      <td>S/PV.3332</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>UNITED\\nS\\nNATIONS\\nSecurity Council \\nPROVISI...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2664</th>\n",
       "      <td>2996</td>\n",
       "      <td>S/2006/1013</td>\n",
       "      <td>S/RES/1735(2006)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2006/1013\\n \\n \\n \\nS...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/1735 (2006)\\n \\n ...</td>\n",
       "      <td>2006</td>\n",
       "      <td>S/PV.5609</td>\n",
       "      <td>Peace and security — terrorist acts</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/PV.5609\\n \\n \\n \\nSec...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2665</th>\n",
       "      <td>2997</td>\n",
       "      <td>S/2004/774</td>\n",
       "      <td>S/RES/1565(2004)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>United Nations\\nS/2004/774\\n \\nSecurity Counci...</td>\n",
       "      <td>United Nations\\nS/RES/1565 (2004)\\n \\nSecurity...</td>\n",
       "      <td>2004</td>\n",
       "      <td>S/PV.5048</td>\n",
       "      <td>Democratic Republic of the Congo</td>\n",
       "      <td>United Nations\\nS/PV.5048\\n \\nSecurity Council...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2666</th>\n",
       "      <td>2998</td>\n",
       "      <td>S/2007/430</td>\n",
       "      <td>S/RES/1765(2007)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2007/430\\n \\n \\n \\nSe...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/1765 (2007)\\n \\n ...</td>\n",
       "      <td>2007</td>\n",
       "      <td>S/PV.5716</td>\n",
       "      <td>Côte d'Ivoire</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/PV.5716\\n \\n \\n \\nSec...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1758 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        id     draft_id          final_id   status  \\\n",
       "1        5  S/2018/1143  S/RES/2450(2018)  adopted   \n",
       "2        6  S/2018/1025  S/RES/2446(2018)  adopted   \n",
       "3        7  S/2018/1010  S/RES/2444(2018)  adopted   \n",
       "4        8  S/2018/1021  S/RES/2445(2018)  adopted   \n",
       "5        9   S/2018/990  S/RES/2442(2018)  adopted   \n",
       "...    ...          ...               ...      ...   \n",
       "2661  2993   S/2016/241  S/RES/2274(2016)  adopted   \n",
       "2663  2995    S/1994/96   S/RES/896(1994)  adopted   \n",
       "2664  2996  S/2006/1013  S/RES/1735(2006)  adopted   \n",
       "2665  2997   S/2004/774  S/RES/1565(2004)  adopted   \n",
       "2666  2998   S/2007/430  S/RES/1765(2007)  adopted   \n",
       "\n",
       "                                             draft_text  \\\n",
       "1      \\nUnited Nations \\n \\nS/2018/1143 \\n \\n \\nSec...   \n",
       "2      \\nUnited Nations \\n \\nS/2018/1025 \\n \\n \\nSec...   \n",
       "3      \\nUnited Nations \\n \\nS/2018/1010 \\n \\n \\nSec...   \n",
       "4      \\nUnited Nations \\n \\nS/2018/1021 \\n \\n \\nSec...   \n",
       "5      \\nUnited Nations \\n \\nS/2018/990 \\n \\n \\nSecu...   \n",
       "...                                                 ...   \n",
       "2661   \\nUnited Nations \\n \\nS/2016/241 \\n \\n \\nSecu...   \n",
       "2663  UNITED\\nUNITED\\nS\\nNATIONS\\nNATIONS\\nSecurity ...   \n",
       "2664   \\nUnited Nations \\n \\nS/2006/1013\\n \\n \\n \\nS...   \n",
       "2665  United Nations\\nS/2004/774\\n \\nSecurity Counci...   \n",
       "2666   \\nUnited Nations \\n \\nS/2007/430\\n \\n \\n \\nSe...   \n",
       "\n",
       "                                             final_text  year meeting_id  \\\n",
       "1      \\nUnited Nations \\n \\nS/RES/2450 (2018) \\n \\n...  2018  S/PV.8436   \n",
       "2      \\nUnited Nations \\n \\nS/RES/2446 (2018) \\n \\n...  2018  S/PV.8401   \n",
       "3      \\nUnited Nations \\n \\nS/RES/2444 (2018) \\n \\n...  2018  S/PV.8398   \n",
       "4      \\nUnited Nations \\n \\nS/RES/2445 (2018) \\n \\n...  2018  S/PV.8400   \n",
       "5      \\nUnited Nations \\n \\nS/RES/2442 (2018) \\n \\n...  2018  S/PV.8391   \n",
       "...                                                 ...   ...        ...   \n",
       "2661   \\nUnited Nations \\n \\nS/RES/2274 (2016) \\n \\n...  2016  S/PV.7645   \n",
       "2663  UNITED\\nUNITED\\nS\\nNATIONS\\nNATIONS\\nSecurity ...  1994  S/PV.3332   \n",
       "2664   \\nUnited Nations \\n \\nS/RES/1735 (2006)\\n \\n ...  2006  S/PV.5609   \n",
       "2665  United Nations\\nS/RES/1565 (2004)\\n \\nSecurity...  2004  S/PV.5048   \n",
       "2666   \\nUnited Nations \\n \\nS/RES/1765 (2007)\\n \\n ...  2007  S/PV.5716   \n",
       "\n",
       "                                                  topic  \\\n",
       "1                      The situation in the Middle East   \n",
       "2         The situation in the Central African Republic   \n",
       "3                              The situation in Somalia   \n",
       "4     Reports of the Secretary-General on the Sudan ...   \n",
       "5                              The situation in Somalia   \n",
       "...                                                 ...   \n",
       "2661                       The situation in Afghanistan   \n",
       "2663                                            Georgia   \n",
       "2664                Peace and security — terrorist acts   \n",
       "2665                   Democratic Republic of the Congo   \n",
       "2666                                      Côte d'Ivoire   \n",
       "\n",
       "                                              full_text  veto_used_in_meeting  \n",
       "1     United Nations\\nS/PV.8436\\nSecurity Council\\nS...                 False  \n",
       "2     United Nations\\nS/PV.8401\\nSecurity Council\\nS...                 False  \n",
       "3     United Nations\\nS/PV.8398\\nSecurity Council\\nS...                 False  \n",
       "4     United Nations\\nS/PV.8400\\nSecurity Council\\nS...                 False  \n",
       "5     United Nations\\nS/PV.8391\\nSecurity Council\\nS...                 False  \n",
       "...                                                 ...                   ...  \n",
       "2661  *1607042*\\n16-07042 (E)\\nThis record contains ...                 False  \n",
       "2663  UNITED\\nS\\nNATIONS\\nSecurity Council \\nPROVISI...                 False  \n",
       "2664   \\nUnited Nations \\n \\nS/PV.5609\\n \\n \\n \\nSec...                 False  \n",
       "2665  United Nations\\nS/PV.5048\\n \\nSecurity Council...                 False  \n",
       "2666   \\nUnited Nations \\n \\nS/PV.5716\\n \\n \\n \\nSec...                 False  \n",
       "\n",
       "[1758 rows x 11 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pre_processed_df = meetings_and_resolutions_df.copy()\n",
    "\n",
    "# Convert the year column to be numeric instead of string\n",
    "pre_processed_df['year']=pd.to_numeric(pre_processed_df['year'])\n",
    "\n",
    "# Get rid of the columns we won't use now\n",
    "pre_processed_df.drop(['draft_url','final_url','url','date'], axis=1,inplace=True)\n",
    "\n",
    "# Get rid of rows where we do not have the meeting transcript from...\n",
    "pre_processed_df = pre_processed_df[~pre_processed_df.full_text.isnull()]\n",
    "\n",
    "# ..and keep only the rows where the year is at least 1994\n",
    "pre_processed_df = pre_processed_df[pre_processed_df.year >= 1994]\n",
    "\n",
    "pre_processed_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 2: Cleaning of Text\n",
    "Here we clean text from metadata like headers, footers, words between parenthesis, and other items showing up often as noise and do not bring immediate value to the semantics of the text."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>meeting_id</th>\n",
       "      <th>text_cleaned</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S/PV.8436</td>\n",
       "      <td>security : the situation in the middle east re...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S/PV.8401</td>\n",
       "      <td>security : the situation in the central africa...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S/PV.8398</td>\n",
       "      <td>security : the situation in somalia letter dat...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S/PV.8400</td>\n",
       "      <td>security : reports of the secretary-general on...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>S/PV.8391</td>\n",
       "      <td>security : the situation in somalia report of ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2661</th>\n",
       "      <td>S/PV.7645</td>\n",
       "      <td>0506 .  security : the situation in afghanista...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2663</th>\n",
       "      <td>S/PV.3332</td>\n",
       "      <td>united s nations securityjanuaryoriginal: engl...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2664</th>\n",
       "      <td>S/PV.5609</td>\n",
       "      <td>security this record contains the text of spee...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2665</th>\n",
       "      <td>S/PV.5048</td>\n",
       "      <td>security this record contains the text of spee...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2666</th>\n",
       "      <td>S/PV.5716</td>\n",
       "      <td>security this record contains the text of spee...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1758 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     meeting_id                                       text_cleaned\n",
       "1     S/PV.8436  security : the situation in the middle east re...\n",
       "2     S/PV.8401  security : the situation in the central africa...\n",
       "3     S/PV.8398  security : the situation in somalia letter dat...\n",
       "4     S/PV.8400  security : reports of the secretary-general on...\n",
       "5     S/PV.8391  security : the situation in somalia report of ...\n",
       "...         ...                                                ...\n",
       "2661  S/PV.7645  0506 .  security : the situation in afghanista...\n",
       "2663  S/PV.3332  united s nations securityjanuaryoriginal: engl...\n",
       "2664  S/PV.5609  security this record contains the text of spee...\n",
       "2665  S/PV.5048  security this record contains the text of spee...\n",
       "2666  S/PV.5716  security this record contains the text of spee...\n",
       "\n",
       "[1758 rows x 2 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import re\n",
    "\n",
    "# Convert strings to lowercase\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['full_text'].apply(\n",
    "    lambda x: x.lower()\n",
    ")\n",
    "\n",
    "pre_processed_df[['meeting_id','text_cleaned']]\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: x.replace('united nations', '')\n",
    ")\n",
    "\n",
    "# Common words that show up too often\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: x.replace('draft', '')\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: x.replace('council', '')\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: x.replace('resolution', '')\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: x.replace('security council', '')\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: x.replace('secretary general', '')\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: x.replace('international', '')\n",
    ")\n",
    "\n",
    "\n",
    "# Remove meeting numbers\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('s\\/pv\\.\\d{1,4}', '', x)\n",
    ")\n",
    "\n",
    "# Remove draft resolution identifiers\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('(s\\/\\d{4}\\/\\d{1,4})', '', x)\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('[a-z]+\\-[a-z]+ year', '', x)\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('\\d{1,5}st meeting', '', x)\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('\\d{1,5}nd meeting', '', x)\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('\\d{1,5}rd meeting', '', x)\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('\\d{1,5}th meeting', '', x)\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('(monday|tuesday|wednesday|thursday|friday|saturday|sunday),.*', '', x)\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('(january|february|march|april|may|june|july|august|september|october|november|december),.*', '', x)\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: x.replace('new york', '')\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: x.replace('provisional', '')\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: x.replace('president', '')\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('mr\\. .*', '', x)\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('ms\\. .*', '', x)\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('mrs\\. .*', '', x)\n",
    ")\n",
    "\n",
    "# Remove what's between parenthesis...speakers do not use parenthesis verbally, so consider it as metadata\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('\\(.*\\)', '', x)\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: x.replace('members:', '')\n",
    ")\n",
    "\n",
    "# Get rid of the member countries in the header..they are always suffixed with dots... .\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('.{4,80}(\\.\\s)+', '', x)\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: x.replace('agenda', '')\n",
    ")\n",
    "\n",
    "#--\n",
    "# Remove dates\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('\\d{1,2}\\/\\d{1,2}\\/\\d{4}', '', x)\n",
    ")\n",
    "\n",
    "# Remove items like 18-02468 and *1802468*\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('\\d{1,2}\\-\\d{1,30}', '', x)\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('\\*\\d+\\*', '', x)\n",
    ")\n",
    "\n",
    "# Remove items like 2/2 - potentially we may see 10/20 for a very long transcript?\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('\\d{1,2}\\/\\d{1,2}', '', x)\n",
    ")\n",
    "\n",
    "\n",
    "# Remove timestamps\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('\\d{1,2}\\.\\d{1,2} a\\.m\\.', '', x)\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('\\d{1,2}\\.\\d{1,2} p\\.m\\.', '', x)\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('\\d{1,2}\\:\\d{1,2} a\\.m\\.', '', x)\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('\\d{1,2}\\:\\d{1,2} p\\.m\\.', '', x)\n",
    ")\n",
    "\n",
    "\n",
    "\n",
    "# Put it all on one line now...\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: x.replace('\\n', ' ')\n",
    ")\n",
    "\n",
    "\n",
    "# Strip leading and trailing spaces\n",
    "#pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "#    lambda x: x.strip()\n",
    "#)\n",
    "\n",
    "\n",
    "# Convert multiple spaces to a single one\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: ' '.join(x.split())\n",
    ")\n",
    "\n",
    "\n",
    "# Get rid of the footer always present in its various variations\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: x.replace('this record contains the text of speeches delivered in english and of the translation of the final text will be printed in the official records they should be incorporated in a copy of the record and sent under the signature of a member of the delegation concerned to the chief of the verbatim reporting service, room u-', '')\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('this record contains the.*the official records.*reporting service', '', x)\n",
    ")\n",
    "\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('this record contains the.*the official records.*to the chief, verbatim', '', x)\n",
    ")\n",
    "\n",
    "# Remove standalone numbers\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: re.sub('\\s\\d{1,6}\\s', '', x)\n",
    ")\n",
    "\n",
    "# Remove some more of the footer...\n",
    "pre_processed_df['text_cleaned'] = pre_processed_df['text_cleaned'].apply(\n",
    "    lambda x: x.replace('corrected records will be reissued electronically on the official', '')\n",
    ")\n",
    "\n",
    "\n",
    "pre_processed_df[['meeting_id','text_cleaned']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 3: Expand Contractions\n",
    "Contractions are where we mean to write \"Should have\" but use \"Should've\". Or \"Don't\" for \"Do not\", \"It's\" and \"It is\".\n",
    "We will add it as a new feature in the dataframe instead of overwriting the original field. We will do this also for the next steps, so we can always go back to a specific stage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>text_cleaned</th>\n",
       "      <th>no_contraction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>security : the situation in the middle east re...</td>\n",
       "      <td>[security, :, the, situation, in, the, middle,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>security : the situation in the central africa...</td>\n",
       "      <td>[security, :, the, situation, in, the, central...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>security : the situation in somalia letter dat...</td>\n",
       "      <td>[security, :, the, situation, in, somalia, let...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>security : reports of the secretary-general on...</td>\n",
       "      <td>[security, :, reports, of, the, secretary-gene...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>security : the situation in somalia report of ...</td>\n",
       "      <td>[security, :, the, situation, in, somalia, rep...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2661</th>\n",
       "      <td>0506 .  security : the situation in afghanista...</td>\n",
       "      <td>[0506, ., security, :, the, situation, in, afg...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2663</th>\n",
       "      <td>united s nations securityjanuaryoriginal: engl...</td>\n",
       "      <td>[united, s, nations, securityjanuaryoriginal:,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2664</th>\n",
       "      <td>security this record contains the text of spee...</td>\n",
       "      <td>[security, this, record, contains, the, text, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2665</th>\n",
       "      <td>security this record contains the text of spee...</td>\n",
       "      <td>[security, this, record, contains, the, text, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2666</th>\n",
       "      <td>security this record contains the text of spee...</td>\n",
       "      <td>[security, this, record, contains, the, text, ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1758 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           text_cleaned  \\\n",
       "1     security : the situation in the middle east re...   \n",
       "2     security : the situation in the central africa...   \n",
       "3     security : the situation in somalia letter dat...   \n",
       "4     security : reports of the secretary-general on...   \n",
       "5     security : the situation in somalia report of ...   \n",
       "...                                                 ...   \n",
       "2661  0506 .  security : the situation in afghanista...   \n",
       "2663  united s nations securityjanuaryoriginal: engl...   \n",
       "2664  security this record contains the text of spee...   \n",
       "2665  security this record contains the text of spee...   \n",
       "2666  security this record contains the text of spee...   \n",
       "\n",
       "                                         no_contraction  \n",
       "1     [security, :, the, situation, in, the, middle,...  \n",
       "2     [security, :, the, situation, in, the, central...  \n",
       "3     [security, :, the, situation, in, somalia, let...  \n",
       "4     [security, :, reports, of, the, secretary-gene...  \n",
       "5     [security, :, the, situation, in, somalia, rep...  \n",
       "...                                                 ...  \n",
       "2661  [0506, ., security, :, the, situation, in, afg...  \n",
       "2663  [united, s, nations, securityjanuaryoriginal:,...  \n",
       "2664  [security, this, record, contains, the, text, ...  \n",
       "2665  [security, this, record, contains, the, text, ...  \n",
       "2666  [security, this, record, contains, the, text, ...  \n",
       "\n",
       "[1758 rows x 2 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import contractions\n",
    "pre_processed_df['no_contraction'] = pre_processed_df['text_cleaned'].apply(lambda x: [contractions.fix(word) for word in x.split()])\n",
    "pre_processed_df[['text_cleaned','no_contraction']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will add it also as a string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "pre_processed_df['no_contraction_as_str'] = [' '.join(map(str, l)) for l in pre_processed_df['no_contraction']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 4: Language Detection\n",
    "The language used in the UN Security Council is English. Some OCR'd text is not properly recognizable as English language. We will run a language detection on the data and if it's not english, delete the record from the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning : `load_model` does not return WordVectorModel or SupervisedModel any more, but a `FastText` object which is very similar.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>meeting_id</th>\n",
       "      <th>topic</th>\n",
       "      <th>lang</th>\n",
       "      <th>veto_used_in_meeting</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1124</th>\n",
       "      <td>S/PV.4256</td>\n",
       "      <td>Croatia</td>\n",
       "      <td>ru</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     meeting_id    topic lang  veto_used_in_meeting\n",
       "1124  S/PV.4256  Croatia   ru                 False"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import fasttext\n",
    "pretrained_model = \"../lid.176.bin\" \n",
    "model = fasttext.load_model(pretrained_model)\n",
    "\n",
    "langs = []\n",
    "for sentence in pre_processed_df['no_contraction_as_str']:\n",
    "    lang = model.predict(sentence)[0]\n",
    "    langs.append(str(lang)[11:13])\n",
    "\n",
    "pre_processed_df['lang'] = langs\n",
    "pre_processed_df[['meeting_id','topic','lang','veto_used_in_meeting']].query('lang != \"en\"')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's remove those rows which do are not in English:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "pre_processed_df.drop(pre_processed_df[pre_processed_df.lang != \"en\"].index, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 5: Tokenization\n",
    "Now we can use a tokenizer to split each individual word into a token. We will use TextBlob's tokenize function to the \"no_contraction_as_str\" column and, as before, create a new column for our \"tokenized\" text."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>tokenized</th>\n",
       "      <th>no_contraction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[security, the, situation, in, the, middle, ea...</td>\n",
       "      <td>[security, :, the, situation, in, the, middle,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[security, the, situation, in, the, central, a...</td>\n",
       "      <td>[security, :, the, situation, in, the, central...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>[security, the, situation, in, somalia, letter...</td>\n",
       "      <td>[security, :, the, situation, in, somalia, let...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>[security, reports, of, the, secretary-general...</td>\n",
       "      <td>[security, :, reports, of, the, secretary-gene...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>[security, the, situation, in, somalia, report...</td>\n",
       "      <td>[security, :, the, situation, in, somalia, rep...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2661</th>\n",
       "      <td>[0506, security, the, situation, in, afghanist...</td>\n",
       "      <td>[0506, ., security, :, the, situation, in, afg...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2663</th>\n",
       "      <td>[united, s, nations, securityjanuaryoriginal, ...</td>\n",
       "      <td>[united, s, nations, securityjanuaryoriginal:,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2664</th>\n",
       "      <td>[security, this, record, contains, the, text, ...</td>\n",
       "      <td>[security, this, record, contains, the, text, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2665</th>\n",
       "      <td>[security, this, record, contains, the, text, ...</td>\n",
       "      <td>[security, this, record, contains, the, text, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2666</th>\n",
       "      <td>[security, this, record, contains, the, text, ...</td>\n",
       "      <td>[security, this, record, contains, the, text, ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1757 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              tokenized  \\\n",
       "1     [security, the, situation, in, the, middle, ea...   \n",
       "2     [security, the, situation, in, the, central, a...   \n",
       "3     [security, the, situation, in, somalia, letter...   \n",
       "4     [security, reports, of, the, secretary-general...   \n",
       "5     [security, the, situation, in, somalia, report...   \n",
       "...                                                 ...   \n",
       "2661  [0506, security, the, situation, in, afghanist...   \n",
       "2663  [united, s, nations, securityjanuaryoriginal, ...   \n",
       "2664  [security, this, record, contains, the, text, ...   \n",
       "2665  [security, this, record, contains, the, text, ...   \n",
       "2666  [security, this, record, contains, the, text, ...   \n",
       "\n",
       "                                         no_contraction  \n",
       "1     [security, :, the, situation, in, the, middle,...  \n",
       "2     [security, :, the, situation, in, the, central...  \n",
       "3     [security, :, the, situation, in, somalia, let...  \n",
       "4     [security, :, reports, of, the, secretary-gene...  \n",
       "5     [security, :, the, situation, in, somalia, rep...  \n",
       "...                                                 ...  \n",
       "2661  [0506, ., security, :, the, situation, in, afg...  \n",
       "2663  [united, s, nations, securityjanuaryoriginal:,...  \n",
       "2664  [security, this, record, contains, the, text, ...  \n",
       "2665  [security, this, record, contains, the, text, ...  \n",
       "2666  [security, this, record, contains, the, text, ...  \n",
       "\n",
       "[1757 rows x 2 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from textblob import TextBlob\n",
    "\n",
    "try:\n",
    "    pre_processed_df['tokenized'] = pre_processed_df['no_contraction_as_str'].apply(lambda x: TextBlob(x).words)\n",
    "except nltk.LookupError:\n",
    "    import nltk\n",
    "    nltk.download('punkt')\n",
    "    \n",
    "pre_processed_df['tokenized'] = pre_processed_df['no_contraction_as_str'].apply(lambda x: TextBlob(x).words)\n",
    "pre_processed_df[['tokenized', 'no_contraction']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 6: Remove Punctuation\n",
    "As a next step, we remove punctuation (commas, dots, ...) since they do not really add anything for text analysis:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1       [security, the, situation, in, the, middle, ea...\n",
       "2       [security, the, situation, in, the, central, a...\n",
       "3       [security, the, situation, in, somalia, letter...\n",
       "4       [security, reports, of, the, secretary-general...\n",
       "5       [security, the, situation, in, somalia, report...\n",
       "                              ...                        \n",
       "2661    [0506, security, the, situation, in, afghanist...\n",
       "2663    [united, s, nations, securityjanuaryoriginal, ...\n",
       "2664    [security, this, record, contains, the, text, ...\n",
       "2665    [security, this, record, contains, the, text, ...\n",
       "2666    [security, this, record, contains, the, text, ...\n",
       "Name: no_punctuation, Length: 1757, dtype: object"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import string\n",
    "\n",
    "pre_processed_df['no_punctuation'] = pre_processed_df['tokenized'].apply(lambda x: [word for word in x if word not in string.punctuation])\n",
    "pre_processed_df['no_punctuation']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 7: Removing Stopwords\n",
    "Stopwords are those words and that do not add (much) meaning to a sentence. In the English language common stopwords include “you, he, she, in, a, has, are, etc.”. We will then also remove them from our text.\n",
    "\n",
    "First, we need to import the NLTK stopwords library and set our stopwords to “english”. We are going to add a new column “no_stopwords” which will remove the stopwords from the \"no_punctuation\" feature."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>draft_id</th>\n",
       "      <th>final_id</th>\n",
       "      <th>status</th>\n",
       "      <th>draft_text</th>\n",
       "      <th>final_text</th>\n",
       "      <th>year</th>\n",
       "      <th>meeting_id</th>\n",
       "      <th>topic</th>\n",
       "      <th>full_text</th>\n",
       "      <th>veto_used_in_meeting</th>\n",
       "      <th>text_cleaned</th>\n",
       "      <th>no_contraction</th>\n",
       "      <th>no_contraction_as_str</th>\n",
       "      <th>lang</th>\n",
       "      <th>tokenized</th>\n",
       "      <th>no_punctuation</th>\n",
       "      <th>no_stopwords</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>S/2018/1143</td>\n",
       "      <td>S/RES/2450(2018)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2018/1143 \\n \\n \\nSec...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2450 (2018) \\n \\n...</td>\n",
       "      <td>2018</td>\n",
       "      <td>S/PV.8436</td>\n",
       "      <td>The situation in the Middle East</td>\n",
       "      <td>United Nations\\nS/PV.8436\\nSecurity Council\\nS...</td>\n",
       "      <td>False</td>\n",
       "      <td>security : the situation in the middle east re...</td>\n",
       "      <td>[security, :, the, situation, in, the, middle,...</td>\n",
       "      <td>security : the situation in the middle east re...</td>\n",
       "      <td>en</td>\n",
       "      <td>[security, the, situation, in, the, middle, ea...</td>\n",
       "      <td>[security, the, situation, in, the, middle, ea...</td>\n",
       "      <td>[security, situation, middle, east, report, se...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>S/2018/1025</td>\n",
       "      <td>S/RES/2446(2018)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2018/1025 \\n \\n \\nSec...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2446 (2018) \\n \\n...</td>\n",
       "      <td>2018</td>\n",
       "      <td>S/PV.8401</td>\n",
       "      <td>The situation in the Central African Republic</td>\n",
       "      <td>United Nations\\nS/PV.8401\\nSecurity Council\\nS...</td>\n",
       "      <td>False</td>\n",
       "      <td>security : the situation in the central africa...</td>\n",
       "      <td>[security, :, the, situation, in, the, central...</td>\n",
       "      <td>security : the situation in the central africa...</td>\n",
       "      <td>en</td>\n",
       "      <td>[security, the, situation, in, the, central, a...</td>\n",
       "      <td>[security, the, situation, in, the, central, a...</td>\n",
       "      <td>[security, situation, central, african, republ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7</td>\n",
       "      <td>S/2018/1010</td>\n",
       "      <td>S/RES/2444(2018)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2018/1010 \\n \\n \\nSec...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2444 (2018) \\n \\n...</td>\n",
       "      <td>2018</td>\n",
       "      <td>S/PV.8398</td>\n",
       "      <td>The situation in Somalia</td>\n",
       "      <td>United Nations\\nS/PV.8398\\nSecurity Council\\nS...</td>\n",
       "      <td>False</td>\n",
       "      <td>security : the situation in somalia letter dat...</td>\n",
       "      <td>[security, :, the, situation, in, somalia, let...</td>\n",
       "      <td>security : the situation in somalia letter dat...</td>\n",
       "      <td>en</td>\n",
       "      <td>[security, the, situation, in, somalia, letter...</td>\n",
       "      <td>[security, the, situation, in, somalia, letter...</td>\n",
       "      <td>[security, situation, somalia, letter, datedno...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>S/2018/1021</td>\n",
       "      <td>S/RES/2445(2018)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2018/1021 \\n \\n \\nSec...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2445 (2018) \\n \\n...</td>\n",
       "      <td>2018</td>\n",
       "      <td>S/PV.8400</td>\n",
       "      <td>Reports of the Secretary-General on the Sudan ...</td>\n",
       "      <td>United Nations\\nS/PV.8400\\nSecurity Council\\nS...</td>\n",
       "      <td>False</td>\n",
       "      <td>security : reports of the secretary-general on...</td>\n",
       "      <td>[security, :, reports, of, the, secretary-gene...</td>\n",
       "      <td>security : reports of the secretary-general on...</td>\n",
       "      <td>en</td>\n",
       "      <td>[security, reports, of, the, secretary-general...</td>\n",
       "      <td>[security, reports, of, the, secretary-general...</td>\n",
       "      <td>[security, reports, secretary-general, sudan, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>9</td>\n",
       "      <td>S/2018/990</td>\n",
       "      <td>S/RES/2442(2018)</td>\n",
       "      <td>adopted</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/2018/990 \\n \\n \\nSecu...</td>\n",
       "      <td>\\nUnited Nations \\n \\nS/RES/2442 (2018) \\n \\n...</td>\n",
       "      <td>2018</td>\n",
       "      <td>S/PV.8391</td>\n",
       "      <td>The situation in Somalia</td>\n",
       "      <td>United Nations\\nS/PV.8391\\nSecurity Council\\nS...</td>\n",
       "      <td>False</td>\n",
       "      <td>security : the situation in somalia report of ...</td>\n",
       "      <td>[security, :, the, situation, in, somalia, rep...</td>\n",
       "      <td>security : the situation in somalia report of ...</td>\n",
       "      <td>en</td>\n",
       "      <td>[security, the, situation, in, somalia, report...</td>\n",
       "      <td>[security, the, situation, in, somalia, report...</td>\n",
       "      <td>[security, situation, somalia, report, secreta...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id     draft_id          final_id   status  \\\n",
       "1   5  S/2018/1143  S/RES/2450(2018)  adopted   \n",
       "2   6  S/2018/1025  S/RES/2446(2018)  adopted   \n",
       "3   7  S/2018/1010  S/RES/2444(2018)  adopted   \n",
       "4   8  S/2018/1021  S/RES/2445(2018)  adopted   \n",
       "5   9   S/2018/990  S/RES/2442(2018)  adopted   \n",
       "\n",
       "                                          draft_text  \\\n",
       "1   \\nUnited Nations \\n \\nS/2018/1143 \\n \\n \\nSec...   \n",
       "2   \\nUnited Nations \\n \\nS/2018/1025 \\n \\n \\nSec...   \n",
       "3   \\nUnited Nations \\n \\nS/2018/1010 \\n \\n \\nSec...   \n",
       "4   \\nUnited Nations \\n \\nS/2018/1021 \\n \\n \\nSec...   \n",
       "5   \\nUnited Nations \\n \\nS/2018/990 \\n \\n \\nSecu...   \n",
       "\n",
       "                                          final_text  year meeting_id  \\\n",
       "1   \\nUnited Nations \\n \\nS/RES/2450 (2018) \\n \\n...  2018  S/PV.8436   \n",
       "2   \\nUnited Nations \\n \\nS/RES/2446 (2018) \\n \\n...  2018  S/PV.8401   \n",
       "3   \\nUnited Nations \\n \\nS/RES/2444 (2018) \\n \\n...  2018  S/PV.8398   \n",
       "4   \\nUnited Nations \\n \\nS/RES/2445 (2018) \\n \\n...  2018  S/PV.8400   \n",
       "5   \\nUnited Nations \\n \\nS/RES/2442 (2018) \\n \\n...  2018  S/PV.8391   \n",
       "\n",
       "                                               topic  \\\n",
       "1                   The situation in the Middle East   \n",
       "2      The situation in the Central African Republic   \n",
       "3                           The situation in Somalia   \n",
       "4  Reports of the Secretary-General on the Sudan ...   \n",
       "5                           The situation in Somalia   \n",
       "\n",
       "                                           full_text  veto_used_in_meeting  \\\n",
       "1  United Nations\\nS/PV.8436\\nSecurity Council\\nS...                 False   \n",
       "2  United Nations\\nS/PV.8401\\nSecurity Council\\nS...                 False   \n",
       "3  United Nations\\nS/PV.8398\\nSecurity Council\\nS...                 False   \n",
       "4  United Nations\\nS/PV.8400\\nSecurity Council\\nS...                 False   \n",
       "5  United Nations\\nS/PV.8391\\nSecurity Council\\nS...                 False   \n",
       "\n",
       "                                        text_cleaned  \\\n",
       "1  security : the situation in the middle east re...   \n",
       "2  security : the situation in the central africa...   \n",
       "3  security : the situation in somalia letter dat...   \n",
       "4  security : reports of the secretary-general on...   \n",
       "5  security : the situation in somalia report of ...   \n",
       "\n",
       "                                      no_contraction  \\\n",
       "1  [security, :, the, situation, in, the, middle,...   \n",
       "2  [security, :, the, situation, in, the, central...   \n",
       "3  [security, :, the, situation, in, somalia, let...   \n",
       "4  [security, :, reports, of, the, secretary-gene...   \n",
       "5  [security, :, the, situation, in, somalia, rep...   \n",
       "\n",
       "                               no_contraction_as_str lang  \\\n",
       "1  security : the situation in the middle east re...   en   \n",
       "2  security : the situation in the central africa...   en   \n",
       "3  security : the situation in somalia letter dat...   en   \n",
       "4  security : reports of the secretary-general on...   en   \n",
       "5  security : the situation in somalia report of ...   en   \n",
       "\n",
       "                                           tokenized  \\\n",
       "1  [security, the, situation, in, the, middle, ea...   \n",
       "2  [security, the, situation, in, the, central, a...   \n",
       "3  [security, the, situation, in, somalia, letter...   \n",
       "4  [security, reports, of, the, secretary-general...   \n",
       "5  [security, the, situation, in, somalia, report...   \n",
       "\n",
       "                                      no_punctuation  \\\n",
       "1  [security, the, situation, in, the, middle, ea...   \n",
       "2  [security, the, situation, in, the, central, a...   \n",
       "3  [security, the, situation, in, somalia, letter...   \n",
       "4  [security, reports, of, the, secretary-general...   \n",
       "5  [security, the, situation, in, somalia, report...   \n",
       "\n",
       "                                        no_stopwords  \n",
       "1  [security, situation, middle, east, report, se...  \n",
       "2  [security, situation, central, african, republ...  \n",
       "3  [security, situation, somalia, letter, datedno...  \n",
       "4  [security, reports, secretary-general, sudan, ...  \n",
       "5  [security, situation, somalia, report, secreta...  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from nltk.corpus import stopwords\n",
    "\n",
    "try:\n",
    "    stop_words = set(stopwords.words('english'))\n",
    "except LookupError:\n",
    "    nltk.download('stopwords')\n",
    "    stop_words = set(stopwords.words('english'))\n",
    "\n",
    "pre_processed_df['no_stopwords'] = pre_processed_df['no_punctuation'].apply(lambda x: [word for word in x if word not in stop_words])\n",
    "pre_processed_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 8: Lemmatization\n",
    "We now want to reduce the tokens by transforming all words to their lemma (ie: different words with the same meaning, become 1 word, the root of the word). Lemmatization does the same as stemming, but lemmatization uses the context for better accuracy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1       [security, situation, middle, east, report, se...\n",
       "2       [security, situation, central, african, republ...\n",
       "3       [security, situation, somalia, letter, datedno...\n",
       "4       [security, report, secretary-general, sudan, s...\n",
       "5       [security, situation, somalia, report, secreta...\n",
       "                              ...                        \n",
       "2661    [0506, security, situation, afghanistan, repor...\n",
       "2663    [united, nation, securityjanuaryoriginal, engl...\n",
       "2664    [security, record, contains, text, speech, del...\n",
       "2665    [security, record, contains, text, speech, del...\n",
       "2666    [security, record, contains, text, speech, del...\n",
       "Name: lemmatized_text, Length: 1757, dtype: object"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# https://textblob.readthedocs.io/en/dev/quickstart.html#words-inflection-and-lemmatization\n",
    "# Different lemmatization approaches @ https://www.machinelearningplus.com/nlp/lemmatization-examples-python/#comparingnltktextblobspacypatternandstanfordcorenlp\n",
    "\n",
    "# If the below doesn't work, execute the following command on your terminal: `python -m textblob.download_corpora`\n",
    "from textblob import Word\n",
    "\n",
    "try:\n",
    "    pre_processed_df['lemmatized_text'] = pre_processed_df['no_stopwords'].apply(lambda x: [Word(word).lemmatize() for word in x])\n",
    "except LookupError:\n",
    "    import nltk\n",
    "    nltk.download('wordnet')\n",
    "    pre_processed_df['lemmatized_text'] = pre_processed_df['no_stopwords'].apply(lambda x: [Word(word).lemmatize() for word in x])\n",
    "    \n",
    "pre_processed_df['lemmatized_text']\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Word Count\n",
    "Veto votes do not have to be defended or explained, yet they typically spark longer discussions. We want to add a feature to our dataframe with the amount of words in the text, and validate if the assumption of more talking for a veto is true or false.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count      52.000000\n",
       "mean     3349.711538\n",
       "std      1842.557912\n",
       "min        90.000000\n",
       "25%      1896.250000\n",
       "50%      3165.500000\n",
       "75%      4696.750000\n",
       "max      8141.000000\n",
       "Name: lemmatized_text_word_count, dtype: float64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pre_processed_df['lemmatized_text_word_count'] = pre_processed_df['lemmatized_text'].apply(lambda x: len(x))\n",
    "pre_processed_df.query('veto_used_in_meeting==True')['lemmatized_text_word_count'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count     1705.000000\n",
       "mean      1386.558358\n",
       "std       3013.728225\n",
       "min          0.000000\n",
       "25%        124.000000\n",
       "50%        218.000000\n",
       "75%       1186.000000\n",
       "max      32044.000000\n",
       "Name: lemmatized_text_word_count, dtype: float64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pre_processed_df.query('veto_used_in_meeting==False')['lemmatized_text_word_count'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking at the mean and the standard deviation, one could conclude that the assumption is true. The average amount of words in a non-veto meeting is less than half the amount compared to the amount of words in a veto meeting. However, there is at least one meeting without a veto which reached 32044 words.  IIf we look for meetings that count more words than the maximal word count from meetings with veto, we find 56 meetings with a lot of speech, despite the lack of veto usage.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of meetings with more words than the max amount of words in meetings with veto: 49\n",
      "Total amount of meetings without veto: id                            1757\n",
      "draft_id                      1757\n",
      "final_id                      1694\n",
      "status                        1757\n",
      "draft_text                    1757\n",
      "final_text                    1757\n",
      "year                          1757\n",
      "meeting_id                    1757\n",
      "topic                         1757\n",
      "full_text                     1757\n",
      "veto_used_in_meeting          1757\n",
      "text_cleaned                  1757\n",
      "no_contraction                1757\n",
      "no_contraction_as_str         1757\n",
      "lang                          1757\n",
      "tokenized                     1757\n",
      "no_punctuation                1757\n",
      "no_stopwords                  1757\n",
      "lemmatized_text               1757\n",
      "lemmatized_text_word_count    1757\n",
      "dtype: int64\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>meeting_id</th>\n",
       "      <th>year</th>\n",
       "      <th>topic</th>\n",
       "      <th>veto_used_in_meeting</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>S/PV.8305</td>\n",
       "      <td>2018</td>\n",
       "      <td>Children and armed conflict</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>S/PV.8199</td>\n",
       "      <td>2018</td>\n",
       "      <td>The situation in Afghanistan</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>S/PV.8514</td>\n",
       "      <td>2019</td>\n",
       "      <td>Women and peace and security</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>S/PV.8473</td>\n",
       "      <td>2019</td>\n",
       "      <td>Cooperation between the United Nations and reg...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>S/PV.8649</td>\n",
       "      <td>2019</td>\n",
       "      <td>Women and peace and security</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>S/PV.8496</td>\n",
       "      <td>2019</td>\n",
       "      <td>Threats to international peace and security ca...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>316</th>\n",
       "      <td>S/PV.7247</td>\n",
       "      <td>2014</td>\n",
       "      <td>Maintenance of international peace and security</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>S/PV.7139</td>\n",
       "      <td>2014</td>\n",
       "      <td>The situation in Afghanistan</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>456</th>\n",
       "      <td>S/PV.7533</td>\n",
       "      <td>2015</td>\n",
       "      <td>Women and peace and security</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>550</th>\n",
       "      <td>S/PV.6453</td>\n",
       "      <td>2010</td>\n",
       "      <td>Women and peace and security</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>833</th>\n",
       "      <td>S/PV.3367</td>\n",
       "      <td>1994</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>850</th>\n",
       "      <td>S/PV.3428</td>\n",
       "      <td>1994</td>\n",
       "      <td>The situation in the former Yugoslavia</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>872</th>\n",
       "      <td>S/PV.3607</td>\n",
       "      <td>1995</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>893</th>\n",
       "      <td>S/PV.3514</td>\n",
       "      <td>1995</td>\n",
       "      <td>Aggression against non-nuclear weapon states</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>894</th>\n",
       "      <td>S/PV.3512</td>\n",
       "      <td>1995</td>\n",
       "      <td>The situation in the former Yugoslavia</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>914</th>\n",
       "      <td>S/PV.3679</td>\n",
       "      <td>1996</td>\n",
       "      <td>Angola</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>S/PV.3890</td>\n",
       "      <td>1998</td>\n",
       "      <td>Peace and security — nuclear tests by India an...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1050</th>\n",
       "      <td>S/PV.7272</td>\n",
       "      <td>2014</td>\n",
       "      <td>Threats to international peace and security ca...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1052</th>\n",
       "      <td>S/PV.7268</td>\n",
       "      <td>2014</td>\n",
       "      <td>Peace and security in Africa - Ebola</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1199</th>\n",
       "      <td>S/PV.4720 (Resumption 1)</td>\n",
       "      <td>2003</td>\n",
       "      <td>Small arms — West Africa</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1362</th>\n",
       "      <td>S/PV.5916   (Resumption 1)</td>\n",
       "      <td>2008</td>\n",
       "      <td>Women and peace and security</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1446</th>\n",
       "      <td>S/PV.6581</td>\n",
       "      <td>2011</td>\n",
       "      <td>Children and armed conflict</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1478</th>\n",
       "      <td>S/PV.6838</td>\n",
       "      <td>2012</td>\n",
       "      <td>Children and armed conflict</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1493</th>\n",
       "      <td>S/PV.7044</td>\n",
       "      <td>2013</td>\n",
       "      <td>Women and peace and security</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1503</th>\n",
       "      <td>S/PV.6935</td>\n",
       "      <td>2013</td>\n",
       "      <td>The situation in Afghanistan</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1509</th>\n",
       "      <td>S/PV.6903</td>\n",
       "      <td>2013</td>\n",
       "      <td>Peacekeeping operations</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1516</th>\n",
       "      <td>S/PV.7317</td>\n",
       "      <td>2014</td>\n",
       "      <td>Peacekeeping operations</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1567</th>\n",
       "      <td>S/PV.8111</td>\n",
       "      <td>2017</td>\n",
       "      <td>Maintenance of international peace and security</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1574</th>\n",
       "      <td>S/PV.8051</td>\n",
       "      <td>2017</td>\n",
       "      <td>United Nations peacekeeping operations</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1836</th>\n",
       "      <td>S/PV.3723</td>\n",
       "      <td>1996</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1872</th>\n",
       "      <td>S/PV.4084+Corr.1</td>\n",
       "      <td>1999</td>\n",
       "      <td>Iraq-Kuwait</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1915</th>\n",
       "      <td>S/PV.4484</td>\n",
       "      <td>2002</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>S/PV.6216</td>\n",
       "      <td>2009</td>\n",
       "      <td>Civilians in armed conflict</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061</th>\n",
       "      <td>S/PV.7351</td>\n",
       "      <td>2014</td>\n",
       "      <td>Threats to international peace and security</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2068</th>\n",
       "      <td>S/PV.7228</td>\n",
       "      <td>2014</td>\n",
       "      <td>Peacekeeping operations</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2087</th>\n",
       "      <td>S/PV.7466</td>\n",
       "      <td>2015</td>\n",
       "      <td>Children and armed conflict</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2088</th>\n",
       "      <td>S/PV.7450</td>\n",
       "      <td>2015</td>\n",
       "      <td>Protection of civilians in armed conflict</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2092</th>\n",
       "      <td>S/PV.7847</td>\n",
       "      <td>2016</td>\n",
       "      <td>Maintenance of international peace and security</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2103</th>\n",
       "      <td>S/PV.7816</td>\n",
       "      <td>2016</td>\n",
       "      <td>Cooperation between the United Nations and reg...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2252</th>\n",
       "      <td>S/PV.3595</td>\n",
       "      <td>1995</td>\n",
       "      <td>Federal Republic of Yugoslavia (Serbia and Mon...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2256</th>\n",
       "      <td>S/PV.3379</td>\n",
       "      <td>1994</td>\n",
       "      <td>South Africa</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2291</th>\n",
       "      <td>S/PV.3868+Corr.1+Corr.2</td>\n",
       "      <td>1998</td>\n",
       "      <td>Kosovo (Federal Republic of Yugoslavia)</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2358</th>\n",
       "      <td>S/PV.5359 (Resumption 1)</td>\n",
       "      <td>2006</td>\n",
       "      <td>Great Lakes region</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2368</th>\n",
       "      <td>S/PV.6046</td>\n",
       "      <td>2008</td>\n",
       "      <td>Somalia</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2421</th>\n",
       "      <td>S/PV.7403</td>\n",
       "      <td>2015</td>\n",
       "      <td>The situation in Afghanistan</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2436</th>\n",
       "      <td>S/PV.7882</td>\n",
       "      <td>2017</td>\n",
       "      <td>Threats to international peace and security ca...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2509</th>\n",
       "      <td>S/PV.4037\\n      (Resumption 1)\\n</td>\n",
       "      <td>1999</td>\n",
       "      <td>Children and armed conflict</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2654</th>\n",
       "      <td>S/PV.7837</td>\n",
       "      <td>2016</td>\n",
       "      <td>Non-proliferation of weapons of mass destruction</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2661</th>\n",
       "      <td>S/PV.7645</td>\n",
       "      <td>2016</td>\n",
       "      <td>The situation in Afghanistan</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 meeting_id  year  \\\n",
       "39                                S/PV.8305  2018   \n",
       "51                                S/PV.8199  2018   \n",
       "55                                S/PV.8514  2019   \n",
       "77                                S/PV.8473  2019   \n",
       "103                               S/PV.8649  2019   \n",
       "111                               S/PV.8496  2019   \n",
       "316                               S/PV.7247  2014   \n",
       "371                               S/PV.7139  2014   \n",
       "456                               S/PV.7533  2015   \n",
       "550                               S/PV.6453  2010   \n",
       "833                               S/PV.3367  1994   \n",
       "850                               S/PV.3428  1994   \n",
       "872                               S/PV.3607  1995   \n",
       "893                               S/PV.3514  1995   \n",
       "894                               S/PV.3512  1995   \n",
       "914                               S/PV.3679  1996   \n",
       "998                               S/PV.3890  1998   \n",
       "1050                              S/PV.7272  2014   \n",
       "1052                              S/PV.7268  2014   \n",
       "1199               S/PV.4720 (Resumption 1)  2003   \n",
       "1362             S/PV.5916   (Resumption 1)  2008   \n",
       "1446                              S/PV.6581  2011   \n",
       "1478                              S/PV.6838  2012   \n",
       "1493                              S/PV.7044  2013   \n",
       "1503                              S/PV.6935  2013   \n",
       "1509                              S/PV.6903  2013   \n",
       "1516                              S/PV.7317  2014   \n",
       "1567                              S/PV.8111  2017   \n",
       "1574                              S/PV.8051  2017   \n",
       "1836                              S/PV.3723  1996   \n",
       "1872                       S/PV.4084+Corr.1  1999   \n",
       "1915                              S/PV.4484  2002   \n",
       "2013                              S/PV.6216  2009   \n",
       "2061                              S/PV.7351  2014   \n",
       "2068                              S/PV.7228  2014   \n",
       "2087                              S/PV.7466  2015   \n",
       "2088                              S/PV.7450  2015   \n",
       "2092                              S/PV.7847  2016   \n",
       "2103                              S/PV.7816  2016   \n",
       "2252                              S/PV.3595  1995   \n",
       "2256                              S/PV.3379  1994   \n",
       "2291                S/PV.3868+Corr.1+Corr.2  1998   \n",
       "2358               S/PV.5359 (Resumption 1)  2006   \n",
       "2368                              S/PV.6046  2008   \n",
       "2421                              S/PV.7403  2015   \n",
       "2436                              S/PV.7882  2017   \n",
       "2509  S/PV.4037\\n      (Resumption 1)\\n      1999   \n",
       "2654                              S/PV.7837  2016   \n",
       "2661                              S/PV.7645  2016   \n",
       "\n",
       "                                                  topic  veto_used_in_meeting  \n",
       "39                          Children and armed conflict                 False  \n",
       "51                         The situation in Afghanistan                 False  \n",
       "55                         Women and peace and security                 False  \n",
       "77    Cooperation between the United Nations and reg...                 False  \n",
       "103                        Women and peace and security                 False  \n",
       "111   Threats to international peace and security ca...                 False  \n",
       "316     Maintenance of international peace and security                 False  \n",
       "371                        The situation in Afghanistan                 False  \n",
       "456                        Women and peace and security                 False  \n",
       "550                        Women and peace and security                 False  \n",
       "833                              Bosnia and Herzegovina                 False  \n",
       "850              The situation in the former Yugoslavia                 False  \n",
       "872                              Bosnia and Herzegovina                 False  \n",
       "893        Aggression against non-nuclear weapon states                 False  \n",
       "894              The situation in the former Yugoslavia                 False  \n",
       "914                                              Angola                 False  \n",
       "998   Peace and security — nuclear tests by India an...                 False  \n",
       "1050  Threats to international peace and security ca...                 False  \n",
       "1052               Peace and security in Africa - Ebola                 False  \n",
       "1199                           Small arms — West Africa                 False  \n",
       "1362                       Women and peace and security                 False  \n",
       "1446                        Children and armed conflict                 False  \n",
       "1478                        Children and armed conflict                 False  \n",
       "1493                       Women and peace and security                 False  \n",
       "1503                       The situation in Afghanistan                 False  \n",
       "1509                            Peacekeeping operations                 False  \n",
       "1516                            Peacekeeping operations                 False  \n",
       "1567    Maintenance of international peace and security                 False  \n",
       "1574             United Nations peacekeeping operations                 False  \n",
       "1836                             Bosnia and Herzegovina                 False  \n",
       "1872                                        Iraq-Kuwait                 False  \n",
       "1915                             Bosnia and Herzegovina                 False  \n",
       "2013                        Civilians in armed conflict                 False  \n",
       "2061        Threats to international peace and security                 False  \n",
       "2068                            Peacekeeping operations                 False  \n",
       "2087                        Children and armed conflict                 False  \n",
       "2088          Protection of civilians in armed conflict                 False  \n",
       "2092    Maintenance of international peace and security                 False  \n",
       "2103  Cooperation between the United Nations and reg...                 False  \n",
       "2252  Federal Republic of Yugoslavia (Serbia and Mon...                 False  \n",
       "2256                                       South Africa                 False  \n",
       "2291            Kosovo (Federal Republic of Yugoslavia)                 False  \n",
       "2358                                 Great Lakes region                 False  \n",
       "2368                                            Somalia                 False  \n",
       "2421                       The situation in Afghanistan                 False  \n",
       "2436  Threats to international peace and security ca...                 False  \n",
       "2509                        Children and armed conflict                 False  \n",
       "2654   Non-proliferation of weapons of mass destruction                 False  \n",
       "2661                       The situation in Afghanistan                 False  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pre_processed_df.query('lemmatized_text_word_count>8141')['meeting_id'].count()\n",
    "print(f\"Number of meetings with more words than the max amount of words in meetings with veto: {pre_processed_df.query('lemmatized_text_word_count>8141')['meeting_id'].count()}\")\n",
    "print(f\"Total amount of meetings without veto: {pre_processed_df.count()}\")\n",
    "pre_processed_df.query('lemmatized_text_word_count>8141')[['meeting_id', 'year', 'topic', 'veto_used_in_meeting']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "56 Meetings out of a total of 1635 in scope in our dataset (post 1994!) shows the majority of the meeting transcripts without veto have less words than the ones with a veto.\n",
    "\n",
    "As such, we conclude that there is some correlation between word count and the use of vetos in a UNSC meeting. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of meetings with veto with more words than the max amount of words in meetings without veto: 49\n",
      "Total amount of meetings without veto: id                            1757\n",
      "draft_id                      1757\n",
      "final_id                      1694\n",
      "status                        1757\n",
      "draft_text                    1757\n",
      "final_text                    1757\n",
      "year                          1757\n",
      "meeting_id                    1757\n",
      "topic                         1757\n",
      "full_text                     1757\n",
      "veto_used_in_meeting          1757\n",
      "text_cleaned                  1757\n",
      "no_contraction                1757\n",
      "no_contraction_as_str         1757\n",
      "lang                          1757\n",
      "tokenized                     1757\n",
      "no_punctuation                1757\n",
      "no_stopwords                  1757\n",
      "lemmatized_text               1757\n",
      "lemmatized_text_word_count    1757\n",
      "dtype: int64\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>meeting_id</th>\n",
       "      <th>year</th>\n",
       "      <th>topic</th>\n",
       "      <th>veto_used_in_meeting</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S/PV.8398</td>\n",
       "      <td>2018</td>\n",
       "      <td>The situation in Somalia</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>S/PV.8310</td>\n",
       "      <td>2018</td>\n",
       "      <td>Reports of the Secretary-General on the Sudan ...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>S/PV.8274</td>\n",
       "      <td>2018</td>\n",
       "      <td>The situation in the Middle East, including th...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>S/PV.8274</td>\n",
       "      <td>2018</td>\n",
       "      <td>The situation in the Middle East, including th...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>S/PV.8273</td>\n",
       "      <td>2018</td>\n",
       "      <td>Reports of the Secretary-General on the Sudan ...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2642</th>\n",
       "      <td>S/PV.7643</td>\n",
       "      <td>2016</td>\n",
       "      <td>United Nations peacekeeping operations</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2654</th>\n",
       "      <td>S/PV.7837</td>\n",
       "      <td>2016</td>\n",
       "      <td>Non-proliferation of weapons of mass destruction</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2657</th>\n",
       "      <td>S/PV.4972</td>\n",
       "      <td>2004</td>\n",
       "      <td>Middle East situation, including the Palestini...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2661</th>\n",
       "      <td>S/PV.7645</td>\n",
       "      <td>2016</td>\n",
       "      <td>The situation in Afghanistan</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2663</th>\n",
       "      <td>S/PV.3332</td>\n",
       "      <td>1994</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>412 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     meeting_id  year                                              topic  \\\n",
       "3     S/PV.8398  2018                           The situation in Somalia   \n",
       "13    S/PV.8310  2018  Reports of the Secretary-General on the Sudan ...   \n",
       "19    S/PV.8274  2018  The situation in the Middle East, including th...   \n",
       "20    S/PV.8274  2018  The situation in the Middle East, including th...   \n",
       "21    S/PV.8273  2018  Reports of the Secretary-General on the Sudan ...   \n",
       "...         ...   ...                                                ...   \n",
       "2642  S/PV.7643  2016             United Nations peacekeeping operations   \n",
       "2654  S/PV.7837  2016   Non-proliferation of weapons of mass destruction   \n",
       "2657  S/PV.4972  2004  Middle East situation, including the Palestini...   \n",
       "2661  S/PV.7645  2016                       The situation in Afghanistan   \n",
       "2663  S/PV.3332  1994                                            Georgia   \n",
       "\n",
       "      veto_used_in_meeting  \n",
       "3                    False  \n",
       "13                   False  \n",
       "19                    True  \n",
       "20                    True  \n",
       "21                   False  \n",
       "...                    ...  \n",
       "2642                 False  \n",
       "2654                 False  \n",
       "2657                 False  \n",
       "2661                 False  \n",
       "2663                 False  \n",
       "\n",
       "[412 rows x 4 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(f\"Number of meetings with veto with more words than the max amount of words in meetings without veto: {pre_processed_df.query('lemmatized_text_word_count>8141')['meeting_id'].count()}\")\n",
    "print(f\"Total amount of meetings without veto: {pre_processed_df.count()}\")\n",
    "pre_processed_df.query('lemmatized_text_word_count>1635')[['meeting_id', 'year', 'topic', 'veto_used_in_meeting']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Word Frequency\n",
    "Here we will quickly analyze if there is a possible correlation between the most commonly used words and veto or not.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Word Frequency across all meetings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "words_in_meetings = pre_processed_df['lemmatized_text']\n",
    "\n",
    "allwords_in_meetings = []\n",
    "for wordlist in words_in_meetings:\n",
    "    allwords_in_meetings += wordlist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from nltk.probability import FreqDist\n",
    "from wordcloud import WordCloud, ImageColorGenerator\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "mostcommon = FreqDist(allwords_in_meetings).most_common(100)\n",
    "\n",
    "wordcloud = WordCloud(background_color='white').generate(' '.join(dict(mostcommon)))\n",
    "fig = plt.figure(figsize=(10,10), facecolor='white')\n",
    "plt.imshow(wordcloud, interpolation=\"bilinear\")\n",
    "plt.axis('off')\n",
    "plt.title('Top 100 Most Common Words in Meetings', fontsize=32)\n",
    "\n",
    "plt.tight_layout(pad=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Make the dataframe accessible in other Notebooks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stored 'pre_processed_df' (DataFrame)\n"
     ]
    }
   ],
   "source": [
    "%store pre_processed_df"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}