1_annotation_pipeline-12.21.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__author__      = \"Yibo HU\"\n",
    "\n",
    "Last_updated: 12/21/2020\n",
    "\n",
    "This is a jupyter notebook of the annotation pipeline\n",
    "modified from \n",
    "\n",
    "https://github.com/the-knightfury/SATP-Event-Classification-V1/tree/master/SourceCode\n",
    "\n",
    "Thanks to Shahreen\n",
    "\n",
    "\n",
    "For new updates in annotations, simply import the libraries below and run step 5 only."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-21T21:50:14.351032Z",
     "start_time": "2020-12-21T21:50:13.832993Z"
    }
   },
   "outputs": [],
   "source": [
    "# -*- coding: utf-8 -*-\n",
    "import requests\n",
    "from bs4 import BeautifulSoup\n",
    "import re\n",
    "import pandas as pd\n",
    "import sklearn\n",
    "import time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. crawler_terrorism_articles_tags"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "months = [\"jan\", \"feb\", \"mar\", \"apr\", \"may\", \"jun\", \"jul\", \"aug\", \"sep\", \"oct\", \"nov\", \"dec\"]\n",
    "countries = [\"bangladesh\", \"india\", \"pakistan\", \"bhutan\", \"nepal\", \"maldives\", \"afghanistan\", \"srilanka\"]\n",
    "years = [\"2019\", \"2018\", \"2017\", \"2016\", \"2015\", \"2014\", \"2013\", \"2012\", \"2011\", \"2010\"]\n",
    "\n",
    "# Saving News Content and The Country wise location in these 2 lists\n",
    "news_contents = []\n",
    "news_location = []\n",
    "\n",
    "for i in years:\n",
    "    print(\"year:\", i)\n",
    "    # Iterating over each country\n",
    "    for k in countries:\n",
    "        # Iterating over each month\n",
    "        print(\"\\tcountry:\", k)\n",
    "        for j in months:\n",
    "            print('\\t\\tmonths:', j)\n",
    "\n",
    "            url = \"https://www.satp.org/terrorist-activity/\"+ k + \"-\" + j + \"-\" + i\n",
    "\n",
    "            # Request\n",
    "            r1 = requests.get(url)\n",
    "\n",
    "            # We'll save in coverpage the cover page content\n",
    "            coverpage = r1.content\n",
    "\n",
    "            # Soup creation\n",
    "            soup1 = BeautifulSoup(coverpage, 'html.parser')\n",
    "\n",
    "            # News identification\n",
    "            coverpage_news = soup1.find_all('div', class_='more')\n",
    "\n",
    "            news_size = len(coverpage_news)\n",
    "\n",
    "            for paragraph_num in range(news_size):\n",
    "                paragraph = coverpage_news[paragraph_num].get_text()\n",
    "                paragraph = re.sub(\"^\\s+|\\s+$\", \"\", paragraph, flags=re.UNICODE)\n",
    "                paragraph = \" \".join(re.split(\"\\s+\", paragraph, flags=re.UNICODE)[:-2])\n",
    "                news_location.append(k)\n",
    "                news_contents.append(paragraph)\n",
    "\n",
    "        print(\"\\tcountry:\", k, ' ' ,len(news_contents))\n",
    "\n",
    "news_data = pd.DataFrame({'location': news_location,\n",
    "                          'news': news_contents})\n",
    "\n",
    "print(news_data.shape)\n",
    "\n",
    "# news_data.to_csv ('./Satp_Data/news_satp_2010.csv', index = False, header=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. process_data_for_annotation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def remove_special_characters(data, col_name):\n",
    "    spec_chars = [\"!\", '\"', \"#\", \"%\", \"&\", \"'\", \"*\", \"+\", \"-\", \"/\", \":\", \";\", \"<\", \"=\",\n",
    "                  \">\", \"?\", \"@\", \"[\", \"\\\\\", \"]\", \"^\", \"_\", \"`\", \"{\", \"|\", \"}\", \"~\", \"–\"]\n",
    "    for char in spec_chars:\n",
    "        data[col_name] = data[col_name].str.replace(char, ' ')\n",
    "    data[col_name] = data[col_name].str.split().str.join(\" \")\n",
    "    return data\n",
    "\n",
    "def probable_relevant_story(news, event_set, threshold):\n",
    "    tokenized = news.split(\" \")\n",
    "    count = 0\n",
    "    for t in tokenized:\n",
    "        if t in event_set:\n",
    "            count += 1\n",
    "        if count >= threshold:\n",
    "            return True\n",
    "    return False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "master_data_path = 'RawSATPData/master_2011To2015.csv'\n",
    "master_data = pd.read_csv(master_data_path, header=[0])  \n",
    "master_data = remove_special_characters(master_data, 'news')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "193"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "action_path = \"Data_Events/action.csv\" \n",
    "actions = pd.read_csv(action_path, header=None)   #  Here header should be None instead of [0] in the previous version\n",
    "actions_set = set(actions.iloc[:,0])\n",
    "len(actions_set)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Assume a threshold = 4 to select samples "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(21902, 5)\n"
     ]
    }
   ],
   "source": [
    "# Step - 1 : Pull Out All the Probable relevant story\n",
    "master_data['Relevance'] = master_data['news'].apply(probable_relevant_story, args = (actions_set, 4))\n",
    "print(master_data[master_data['Relevance'] == True].shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## save master data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>location</th>\n",
       "      <th>news</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>bangladesh</td>\n",
       "      <td>On January 1, in Jhenidah, Police arrested nin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>bangladesh</td>\n",
       "      <td>Police recovered a 7.6mm foreign pistol, a pip...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>bangladesh</td>\n",
       "      <td>The prosecution on January 1 filed a petition ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>bangladesh</td>\n",
       "      <td>Police banned all protests in Dhaka city from ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>bangladesh</td>\n",
       "      <td>Road Transport and Bridges Minister Obaidul Qu...</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>65078</th>\n",
       "      <td>2011</td>\n",
       "      <td>12</td>\n",
       "      <td>srilanka</td>\n",
       "      <td>President Mahinda Rajapakse said that the Army...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65079</th>\n",
       "      <td>2011</td>\n",
       "      <td>12</td>\n",
       "      <td>srilanka</td>\n",
       "      <td>Cabinet spokesman and Mass Media and Informati...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65080</th>\n",
       "      <td>2011</td>\n",
       "      <td>12</td>\n",
       "      <td>srilanka</td>\n",
       "      <td>Cabinet spokesman and Mass Media and Informati...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65081</th>\n",
       "      <td>2011</td>\n",
       "      <td>12</td>\n",
       "      <td>srilanka</td>\n",
       "      <td>An ally of Sri Lanka s governing United People...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65082</th>\n",
       "      <td>2011</td>\n",
       "      <td>12</td>\n",
       "      <td>srilanka</td>\n",
       "      <td>Mahinda Rajapakse recently told a media meetin...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>65083 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       year  month    location  \\\n",
       "0      2015      1  bangladesh   \n",
       "1      2015      1  bangladesh   \n",
       "2      2015      1  bangladesh   \n",
       "3      2015      1  bangladesh   \n",
       "4      2015      1  bangladesh   \n",
       "...     ...    ...         ...   \n",
       "65078  2011     12    srilanka   \n",
       "65079  2011     12    srilanka   \n",
       "65080  2011     12    srilanka   \n",
       "65081  2011     12    srilanka   \n",
       "65082  2011     12    srilanka   \n",
       "\n",
       "                                                    news  \n",
       "0      On January 1, in Jhenidah, Police arrested nin...  \n",
       "1      Police recovered a 7.6mm foreign pistol, a pip...  \n",
       "2      The prosecution on January 1 filed a petition ...  \n",
       "3      Police banned all protests in Dhaka city from ...  \n",
       "4      Road Transport and Bridges Minister Obaidul Qu...  \n",
       "...                                                  ...  \n",
       "65078  President Mahinda Rajapakse said that the Army...  \n",
       "65079  Cabinet spokesman and Mass Media and Informati...  \n",
       "65080  Cabinet spokesman and Mass Media and Informati...  \n",
       "65081  An ally of Sri Lanka s governing United People...  \n",
       "65082  Mahinda Rajapakse recently told a media meetin...  \n",
       "\n",
       "[65083 rows x 4 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "master_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "master_data.to_csv('Data_TagTog_NotAnnotated/master_2011to2015_probable_relevant_marked_data.csv', header=True, index=True, index_label='index')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. sample_data_for_annotation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# master_data = pd.read_csv('Data_TagTog_NotAnnotated/master_2011to2015_probable_relevant_marked_data.csv', header=[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "master_data['location'].value_counts().plot.bar(rot=45)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FdtEJEKrq7iRXA/cAe4ANVfXEAeiXJGkfZiQMquoLwBfa9fuZ5GigqvoR8Pp9LH8+cP5M9EWSNH1+A1mSZBhIkgwDSRKGgSQJw0CShGEgScIwkCRhGEiSMAwkSRgGkiQMA0kShoEkCcNAkoRhIEnCMJAkYRhIkjAMJEkYBpIk+giDJEcnuTHJPUnuTvKOVj8syfYk97W/h7Z6klycZDTJnUmO67qtta39fUnW9v+wJEnT0c+awR7gj6vqGOBEYEOSY4BzgRuqaiVwQ5sGOAVY2S7rgUuhEx7ARuAEOr+dvHFvgEiSZkfPYVBVD1bVl9v1vwfuBZYCa4AtrdkW4PR2fQ1wZXXcDCxJchRwMrC9qnZV1W5gO7C6135JkqZvRvYZJFkOvBy4BTiyqh5ssx4CjmzXlwIPdC22o9X2VZ/sftYnGUkyMjY2NhNdlyQxA2GQ5NnAJ4F/VVU/6J5XVQVUv/fRdXubqmq4qoaHhoZm6mYlacHrKwySPJ1OEHysqj7Vyt9tm39ofx9u9Z3A0V2LL2u1fdUlSbOkn6OJAlwO3FtV/6lr1jZg7xFBa4Fru+pnt6OKTgQebZuTrgdWJTm07The1WqSpFmyuI9lXwm8CbgryVda7d3ABcDVSdYB3wbe0OZdB5wKjAI/BM4BqKpdSd4H3NbavbeqdvXRL0nSNPUcBlX1JSD7mH3SJO0L2LCP29oMbO61L5Kk/vgNZEmSYSBJMgwkSRgGkiQMA0kShoEkCcNAkoRhIEnCMJAkYRhIkjAMJEkYBpIkDANJEoaBJAnDQJKEYSBJwjCQJGEYSJKYQ2GQZHWSbyQZTXLuoPsjSQvJnAiDJIuAjwCnAMcAZyU5ZrC9kqSFY06EAXA8MFpV91fV48BWYM2A+yRJC0aqatB9IMkZwOqq+pdt+k3ACVX1tgnt1gPr2+SLgW/Makd/3hHA9wbch7nCsRjnWIxzLMbNlbF4QVUNTSwuHkRPelVVm4BNg+7HXklGqmp40P2YCxyLcY7FOMdi3Fwfi7mymWgncHTX9LJWkyTNgrkSBrcBK5OsSHIQcCawbcB9kqQFY05sJqqqPUneBlwPLAI2V9XdA+7W/pgzm6zmAMdinGMxzrEYN6fHYk7sQJYkDdZc2UwkSRogw0CSZBjMtCQZdB/mCsdCk0ni+04zl8ZiznTkqS7JkiSHlDthSPKLSX5h0P2YS9opVxa0JMcmObyqfjKX3gQHIcmrkvxiVf1k0H3Za0H/Q2ZKkn8G/BXw2SS/vZDfCJOcBvw1nVOKnJNk0UJdQ0iyKsl5AFX1xEJ+A2znGrsR+HCSIxdyICRZBWwBXjDovnRbkP+MmZTknwJ/Bvx74MPAG+mcbG/BaUHwfuBddE48+EbgOQtxbSnJq+h8QFib5IMAC/kNEPg74PPAw8CfJ1k2lz4Vz5YkJwMfAM6qqluSHDxXnhNzohNPVW3V/5XAB6tqpKo+AdwEvL7NX2ifiF8B/Luqug34MvBc4MIkv5PkpYPt2qx7PvAndJ4fL0/yH+GngbCgNhm1N7tntMkvAHcD721rTr8xsI4NxmuBZ1bVzUmG6HyAvCrJhkG/RvyeQZ+SPA94DPhBK70JeG1Vnd3mH1xVjw2qf4OQ5BDgBmA7cDPw68DfAxcAtVDWFJIcWlW7kywHLgPuqqo/bPOWVNUjg+zfbEuyFhirquuS/DVwGvC7VfXJJE9bKGsKST4K/ArwYzprj98Hjmt/PwCdF8ls98s1gx4kWZbkuW3ye1X1aDV0zqT649buLOBfzOdPgt1jsXdNqKp+CLy+qt5TVdcBfwP8KvD0+RwEE54XVNXu9vdbdM62+8tJ3tPO0vt7SZ4+mJ4eeBOeF3vfZw6iMwavpPN8+Byd3y45aj4HwSTPi7fQ+ZD0maq6pKo+TufsC68CDhrUa8QwmKYkpwP/A1iX5IhJnsRPAD9J8mbgPcCtVfXE7PZydkwyFpXkaS0Uuk80eDhQwHx+8zudrrFotZ9uJqyq+4FTgd8DPgpcV1U/HkBXD7gneY18Gng58Cngj4A3A1+lcwqaeWmy5wVAVb2dzpryXkfQee8Y2GvEzUTT0LbxbQW+A+wAvgtsrarvdb3wXwp8CbiLzirw1wfS2QPsycZiQru3AuuAN1fVXbPe0VkwjbE4A/ggcNpT5Nxb0zbFa+TZwAbg5qr6YnvNPL39oNW8M43nxQbgHOCcQb5GDINpaGdUfTGdIyNeR2e1bhT4eFU93NocAnwCOHe+vvnB1GORZDHwPDpHFl22wMfiaW3H8Vo6a4r3DrC7B9STjMUnquqhJAdV1eNJFlfVnkH29UDbn+cF8GxgI3DFoF8jhsF+SPIPgIeAxW17+N76Pwd+A7ivqv48ycur6o75vNN4GmPx0qq6cz6/6Kf7vBhUP2eDYzFuGmPxsqr66lzZee4+gym0Y+evo3MI2F8k+aW986rqk8AXgaEknwb+Z9sZNl+DYDpj8b+SPH8eB8F0xuKmJEsH0tFZ0MNYPH8gHZ0F0xyLL7XXyMCDAICq8jLJBQidX1+7C3g1cCTwr4EHgWMntP0r4FvALw+6346FY+FYOBY9PYZBd2AuX+gc5bAJWMr4JrV30DlS5kVt+ijgHuBXBt1fx8KxcCwci14v7jOYRJIXAocC9wOXALdX1X/omv9OOqec+P2q+n9Jnl1V/2cwvT2wHItxjsU4x2LcfBmLOfGzl3NJktcBfwrsprPK9zHg4iSLqurPWrOrgfOAHwHMxX/sTHAsxjkW4xyLcfNpLAyDLkl+jc7XwX+7OkcFbQKOB34NuLl9k3gr8E/onIdnCZ0nwbzjWIxzLMY5FuPm21i4mahL++e+qKquaNNDdI7/PS3JPwT+LZ10P4F5/CUqcCy6ORbjHItx820sDIMuLcmfVVU/aNePAv4bcGpVPZjkBXR2Bj2rqh4dZF8PNMdinGMxzrEYN9/Gwu8ZdKmqJ6pq79lHAzwC7Gr/2DcC76bz9fk5/4/tl2MxzrEY51iMm29j4ZrBFJJcQedY4VU8BVb1DiTHYpxjMc6xGPdUHgvDYB+Szkm0gHvb35Oq6r7B9mowHItxjsU4x2LcfBgLw2AK6ZyK+raap2eZnA7HYpxjMc6xGPdUHgvDYApJUg4S4Fh0cyzGORbjnspjYRhIkjyaSJJkGEiSMAwkSRgGkiQMA0kShoEkCfj/B5F0zWwMd2MAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "master_data['year'].value_counts().plot.bar(rot=45)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sample 3000 rows each year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "relevant = master_data[master_data[\"Relevance\"] == True]\n",
    "grouped_df = relevant.groupby('year')\n",
    "# for key, item in grouped_df:\n",
    "#     print(grouped_df.get_group(key), \"\\n\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>location</th>\n",
       "      <th>news</th>\n",
       "      <th>Relevance</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2011</th>\n",
       "      <th>61704</th>\n",
       "      <td>2011</td>\n",
       "      <td>7</td>\n",
       "      <td>pakistan</td>\n",
       "      <td>The Inter Services Intelligence (ISI) official...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57597</th>\n",
       "      <td>2011</td>\n",
       "      <td>9</td>\n",
       "      <td>india</td>\n",
       "      <td>Calling Naxalism (Left Wing Extremism) a bigge...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57025</th>\n",
       "      <td>2011</td>\n",
       "      <td>8</td>\n",
       "      <td>india</td>\n",
       "      <td>The Indian Navy captured a hijacked Iranian fl...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54760</th>\n",
       "      <td>2011</td>\n",
       "      <td>4</td>\n",
       "      <td>india</td>\n",
       "      <td>Times of India reports that Chichgarh squad of...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53994</th>\n",
       "      <td>2011</td>\n",
       "      <td>2</td>\n",
       "      <td>india</td>\n",
       "      <td>Indian Express reports that the cadres of the ...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2015</th>\n",
       "      <th>3625</th>\n",
       "      <td>2015</td>\n",
       "      <td>6</td>\n",
       "      <td>india</td>\n",
       "      <td>Death toll rises to three as one more militant...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8755</th>\n",
       "      <td>2015</td>\n",
       "      <td>8</td>\n",
       "      <td>pakistan</td>\n",
       "      <td>Lahore High Court (LHC) issued a notice to the...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6061</th>\n",
       "      <td>2015</td>\n",
       "      <td>10</td>\n",
       "      <td>india</td>\n",
       "      <td>As there was early snowfall along the Line of ...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2769</th>\n",
       "      <td>2015</td>\n",
       "      <td>4</td>\n",
       "      <td>india</td>\n",
       "      <td>Chinar Corps General Officer Commanding (GOC) ...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8152</th>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>pakistan</td>\n",
       "      <td>The United States (US) has handed over 14 comb...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15000 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            year  month  location  \\\n",
       "year                                \n",
       "2011 61704  2011      7  pakistan   \n",
       "     57597  2011      9     india   \n",
       "     57025  2011      8     india   \n",
       "     54760  2011      4     india   \n",
       "     53994  2011      2     india   \n",
       "...          ...    ...       ...   \n",
       "2015 3625   2015      6     india   \n",
       "     8755   2015      8  pakistan   \n",
       "     6061   2015     10     india   \n",
       "     2769   2015      4     india   \n",
       "     8152   2015      5  pakistan   \n",
       "\n",
       "                                                         news  Relevance  \n",
       "year                                                                      \n",
       "2011 61704  The Inter Services Intelligence (ISI) official...       True  \n",
       "     57597  Calling Naxalism (Left Wing Extremism) a bigge...       True  \n",
       "     57025  The Indian Navy captured a hijacked Iranian fl...       True  \n",
       "     54760  Times of India reports that Chichgarh squad of...       True  \n",
       "     53994  Indian Express reports that the cadres of the ...       True  \n",
       "...                                                       ...        ...  \n",
       "2015 3625   Death toll rises to three as one more militant...       True  \n",
       "     8755   Lahore High Court (LHC) issued a notice to the...       True  \n",
       "     6061   As there was early snowfall along the Line of ...       True  \n",
       "     2769   Chinar Corps General Officer Commanding (GOC) ...       True  \n",
       "     8152   The United States (US) has handed over 14 comb...       True  \n",
       "\n",
       "[15000 rows x 5 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample_df = relevant.groupby('year').apply(lambda x: x.sample(3000))\n",
    "sample_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sample_df['year'].value_counts().plot.bar(rot=45)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sample_df['location'].value_counts().plot.bar(rot=45)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Relevance:\n",
      "\n",
      "True    15000\n",
      "Name: Relevance, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print('Relevance:\\n')\n",
    "print(sample_df['Relevance'].value_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sample 60% from each location (Total 9000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "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></th>\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>location</th>\n",
       "      <th>news</th>\n",
       "      <th>Relevance</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>location</th>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">afghanistan</th>\n",
       "      <th rowspan=\"4\" valign=\"top\">2015</th>\n",
       "      <th>10529</th>\n",
       "      <td>2015</td>\n",
       "      <td>7</td>\n",
       "      <td>afghanistan</td>\n",
       "      <td>Another senior Afghan Government official quot...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10523</th>\n",
       "      <td>2015</td>\n",
       "      <td>3</td>\n",
       "      <td>afghanistan</td>\n",
       "      <td>Tehreek e Taliban Pakistan (TTP) splinter grou...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10527</th>\n",
       "      <td>2015</td>\n",
       "      <td>7</td>\n",
       "      <td>afghanistan</td>\n",
       "      <td>Maulvi Shahidullah Shahid, a former Tehreek e ...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10525</th>\n",
       "      <td>2015</td>\n",
       "      <td>3</td>\n",
       "      <td>afghanistan</td>\n",
       "      <td>A US drone strike killed 11 Tehreek e Taliban ...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <th>64582</th>\n",
       "      <td>2011</td>\n",
       "      <td>9</td>\n",
       "      <td>afghanistan</td>\n",
       "      <td>The NATO led International Security Assistance...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">srilanka</th>\n",
       "      <th>2012</th>\n",
       "      <th>52294</th>\n",
       "      <td>2012</td>\n",
       "      <td>1</td>\n",
       "      <td>srilanka</td>\n",
       "      <td>Cabinet Spokesman and Media Minister Keheliya ...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <th>36942</th>\n",
       "      <td>2013</td>\n",
       "      <td>6</td>\n",
       "      <td>srilanka</td>\n",
       "      <td>Meanwhile, President Mahinda Rajapaksa, addres...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <th>23277</th>\n",
       "      <td>2014</td>\n",
       "      <td>11</td>\n",
       "      <td>srilanka</td>\n",
       "      <td>Sri Lanka’s Permanent Representative to the Un...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <th>36829</th>\n",
       "      <td>2013</td>\n",
       "      <td>4</td>\n",
       "      <td>srilanka</td>\n",
       "      <td>A man engaged in de mining in Muhamalai of Jaf...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <th>22849</th>\n",
       "      <td>2014</td>\n",
       "      <td>1</td>\n",
       "      <td>srilanka</td>\n",
       "      <td>The 18th anniversary of the deadliest suicide ...</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9000 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        year  month     location  \\\n",
       "location    year                                   \n",
       "afghanistan 2015 10529  2015      7  afghanistan   \n",
       "                 10523  2015      3  afghanistan   \n",
       "                 10527  2015      7  afghanistan   \n",
       "                 10525  2015      3  afghanistan   \n",
       "            2011 64582  2011      9  afghanistan   \n",
       "...                      ...    ...          ...   \n",
       "srilanka    2012 52294  2012      1     srilanka   \n",
       "            2013 36942  2013      6     srilanka   \n",
       "            2014 23277  2014     11     srilanka   \n",
       "            2013 36829  2013      4     srilanka   \n",
       "            2014 22849  2014      1     srilanka   \n",
       "\n",
       "                                                                     news  \\\n",
       "location    year                                                            \n",
       "afghanistan 2015 10529  Another senior Afghan Government official quot...   \n",
       "                 10523  Tehreek e Taliban Pakistan (TTP) splinter grou...   \n",
       "                 10527  Maulvi Shahidullah Shahid, a former Tehreek e ...   \n",
       "                 10525  A US drone strike killed 11 Tehreek e Taliban ...   \n",
       "            2011 64582  The NATO led International Security Assistance...   \n",
       "...                                                                   ...   \n",
       "srilanka    2012 52294  Cabinet Spokesman and Media Minister Keheliya ...   \n",
       "            2013 36942  Meanwhile, President Mahinda Rajapaksa, addres...   \n",
       "            2014 23277  Sri Lanka’s Permanent Representative to the Un...   \n",
       "            2013 36829  A man engaged in de mining in Muhamalai of Jaf...   \n",
       "            2014 22849  The 18th anniversary of the deadliest suicide ...   \n",
       "\n",
       "                        Relevance  \n",
       "location    year                   \n",
       "afghanistan 2015 10529       True  \n",
       "                 10523       True  \n",
       "                 10527       True  \n",
       "                 10525       True  \n",
       "            2011 64582       True  \n",
       "...                           ...  \n",
       "srilanka    2012 52294       True  \n",
       "            2013 36942       True  \n",
       "            2014 23277       True  \n",
       "            2013 36829       True  \n",
       "            2014 22849       True  \n",
       "\n",
       "[9000 rows x 5 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample_df = sample_df.groupby('location').apply(lambda x: x.sample(frac = 0.6))\n",
    "sample_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Relevance:\n",
      "\n",
      "True    9000\n",
      "Name: Relevance, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print('Relevance:\\n')\n",
    "print(sample_df['Relevance'].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sample_df['location'].value_counts().plot.bar(rot=45)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sample_df.to_csv(\"Data_TagTog_NotAnnotated/sampled_9000_relevant_data.csv\", header=True, index = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4. create_data_for_annotation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_10.tsv (500, 5)\n",
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_11.tsv (500, 5)\n",
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_12.tsv (500, 5)\n",
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_13.tsv (500, 5)\n",
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_14.tsv (500, 5)\n",
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_15.tsv (500, 5)\n",
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_16.tsv (500, 5)\n",
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_17.tsv (500, 5)\n",
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_18.tsv (500, 5)\n",
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_19.tsv (500, 5)\n",
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_20.tsv (500, 5)\n",
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_21.tsv (500, 5)\n",
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_22.tsv (500, 5)\n",
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_23.tsv (500, 5)\n",
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_24.tsv (500, 5)\n",
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_25.tsv (500, 5)\n",
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_26.tsv (500, 5)\n",
      "Data_TagTog_NotAnnotated/TagTog_Data/news_satp_27.tsv (500, 5)\n"
     ]
    }
   ],
   "source": [
    "sample_df = pd.read_csv('Data_TagTog_NotAnnotated/sampled_9000_relevant_data.csv', header=[0])\n",
    "sample_df.drop(columns=[\"Relevance\"], inplace=True)\n",
    "\n",
    "chunk_size = int(sample_df.shape[0] / 18)\n",
    "i = 10\n",
    "for start in range(0, sample_df.shape[0], chunk_size):\n",
    "    df_subset = sample_df.iloc[start:start + chunk_size]\n",
    "    filename = 'Data_TagTog_NotAnnotated/TagTog_Data/news_satp_%s.tsv'%i\n",
    "    df_subset.to_csv(filename, index=False, header=True, sep='\\t')\n",
    "    i += 1\n",
    "    print(filename, df_subset.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 5. retrieve_data_from_tagtog"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-21T21:50:16.962828Z",
     "start_time": "2020-12-21T21:50:16.943496Z"
    }
   },
   "outputs": [],
   "source": [
    "from io import StringIO\n",
    "from pandarallel import pandarallel\n",
    "\n",
    "tagtogAPIUrl = \"https://www.tagtog.net/-api/documents/v1\"\n",
    "USERNAME = 'ssp180002'\n",
    "PASSWORD = '1234567'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-21T21:50:18.277181Z",
     "start_time": "2020-12-21T21:50:18.257645Z"
    },
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "def get_doc_id(url = tagtogAPIUrl, project = None, folder = None):\n",
    "    auth = requests.auth.HTTPBasicAuth(username=USERNAME, password=PASSWORD)\n",
    "    params = {'project':project, 'owner': USERNAME, 'search':folder, 'page':'1', 'output':'csv'}\n",
    "    response = requests.get(url, params=params, auth=auth)\n",
    "    content = response.text.split('\\n')\n",
    "    return [i.split(',')[0] for i in content]\n",
    "\n",
    "def get_data(ids, url=tagtogAPIUrl, project = None,folder = None):\n",
    " \n",
    "    # Get entities\n",
    "    \n",
    "    auth = requests.auth.HTTPBasicAuth(username=USERNAME, password=PASSWORD)\n",
    "    params = {'project': project, 'owner': USERNAME, 'search': folder, 'page': '1',\n",
    "              'output': 'entitiestsv','ids': ids}\n",
    "\n",
    "    entitiestsv = requests.get(url, params=params, auth=auth)\n",
    "    \n",
    "    stringIO = StringIO(entitiestsv.text)\n",
    "    df = pd.read_csv(stringIO , sep=\"\\t\", names = ['text','annotated'])\n",
    "\n",
    "    index, year, month, country = df.text[1], df.text[3], df.text[5], df.text[7]\n",
    "    news = df.text[9:].str.cat().encode(\"ascii\", \"ignore\").decode()\n",
    "\n",
    "    target = df[df.annotated == 'Target-1']['text'].tolist()\n",
    "    source = df[df.annotated == 'Source-1']['text'].tolist()\n",
    "    action = df[df.annotated == 'Action-1']['text'].tolist()\n",
    "    location = df[df.annotated == 'Location-1']['text'].tolist()\n",
    "    date = df[df.annotated == 'Date-1']['text'].tolist()\n",
    "    \n",
    "       \n",
    "    # Get is_relevant and action_type\n",
    "    \n",
    "    auth = requests.auth.HTTPBasicAuth(username=USERNAME, password=PASSWORD)\n",
    "    params = {'project': project, 'owner': USERNAME, 'search': 'folder:pool', 'page': '1',\n",
    "              'output': 'ann.json','ids': ids}\n",
    "    response = requests.get(url, params=params, auth=auth)\n",
    "    json_data = response.json()\n",
    "\n",
    "    \n",
    "    # if no labels or not confirmed, return None\n",
    "    if 'm_1' not in json_data['metas']:\n",
    "        print('No labels', index)\n",
    "        return\n",
    "    else:\n",
    "        is_relevant =  json_data['metas']['m_1']['value']\n",
    "\n",
    "    if json_data['anncomplete'] == False:\n",
    "        print('Not confirmed', index)\n",
    "        return\n",
    "    \n",
    "\n",
    "    action_type = None\n",
    "    if json_data['entities']:\n",
    "        df2 = pd.json_normalize(json_data['entities'])\n",
    "        if  'fields.f_17.value' in df2.columns:\n",
    "            df2 = df2[['fields.f_17.value']].rename(columns={\"fields.f_17.value\": \"action_type\"})\n",
    "            df2 = df2.dropna()\n",
    "            if len(df2)==0:\n",
    "                action_type = \"NotSpecified\"\n",
    "            else: \n",
    "                action_type = df2.action_type.tolist()\n",
    "    \n",
    "\n",
    "    return [ids, index, is_relevant, target,\tsource,\taction,\taction_type, location,\tdate, country,\tyear,\tnews]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Parallelly retrieve annotations\n",
    "\n",
    "<big> Now we can retrieve annotations from folder p1 to the latest p15. Here I only show the process of getting p2-p15 because p1 use a different group of keys.  Let's ignore p1 but just use the original file by Shahreen.</big>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-21T21:50:39.275467Z",
     "start_time": "2020-12-21T21:50:25.674870Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: Pandarallel will run on 36 workers.\n",
      "INFO: Pandarallel will use Memory file system to transfer data between the main process and workers.\n",
      "\n",
      "----- p15 -----\n",
      "\n"
     ]
    }
   ],
   "source": [
    "pandarallel.initialize()\n",
    "\n",
    "for i in range(15,16):\n",
    "    p = 'p%s'%i\n",
    "    print('\\n----- %s -----\\n'%p)\n",
    "    project_list = ['demo', 'satp_news_data_500_'+ p]\n",
    "    folder_list = ['folder:pool/Practice', 'folder:pool']\n",
    "    \n",
    "    # Get item ids from the TagTog API\n",
    "    doc_id = get_doc_id(tagtogAPIUrl, project_list[1], folder_list[1])\n",
    "    # ignore the first row (header) and the final row (null)\n",
    "    doc_id = doc_id[1:-1] \n",
    "    \n",
    "\n",
    "    s = pd.Series(doc_id).parallel_apply(get_data, args = (tagtogAPIUrl, project_list[1], folder_list[1])).dropna()\n",
    "    df_all = pd.DataFrame(item for item in s)\n",
    "    df_all.columns = ['id','index','is_relevant', 'target', 'source', 'action', 'action_type' , 'location', 'date','country', 'year', 'news']\n",
    "    \n",
    "#     df_all.to_csv('Data_TagTog_Annotated/'+ p +'.csv', header=True, index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Concatenation of all the annotations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-21T21:50:39.353390Z",
     "start_time": "2020-12-21T21:50:39.276752Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "p1 p2 p3 p4 p5 p6 p7 p8 p9 p10 p11 p12 p13 p14 p15 "
     ]
    }
   ],
   "source": [
    "df_list=[]\n",
    "for i in range(1,16):\n",
    "    p = 'p%s'%i\n",
    "    print('%s'%p, end = ' ')\n",
    "    df = pd.read_csv('Data_TagTog_Annotated/'+ p +'.csv', header=[0]) \n",
    "    df_list.append(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-21T21:50:39.379938Z",
     "start_time": "2020-12-21T21:50:39.354347Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>is_relevant</th>\n",
       "      <th>target</th>\n",
       "      <th>source</th>\n",
       "      <th>action</th>\n",
       "      <th>action_type</th>\n",
       "      <th>location</th>\n",
       "      <th>date</th>\n",
       "      <th>country</th>\n",
       "      <th>year</th>\n",
       "      <th>news</th>\n",
       "      <th>index</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>32355</td>\n",
       "      <td>True</td>\n",
       "      <td>['Rangers', 'Rangers', 'Military Police']</td>\n",
       "      <td>['Lashkar e Jhangvi LeJ', 'militants', 'milita...</td>\n",
       "      <td>['killing', 'killed', 'gunned']</td>\n",
       "      <td>['Armed Assault', 'Armed Assault', 'Armed Assa...</td>\n",
       "      <td>['Karachi']</td>\n",
       "      <td>['December 6']</td>\n",
       "      <td>pakistan</td>\n",
       "      <td>2016</td>\n",
       "      <td>Two Lashkar e Jhangvi LeJ militants Asim alias...</td>\n",
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       "      <th>1</th>\n",
       "      <td>32398</td>\n",
       "      <td>True</td>\n",
       "      <td>['Security Forces', 'SFs', 'civilians']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['killed', 'fighting', 'wounded', 'fighting', ...</td>\n",
       "      <td>['Unknown', 'Unknown', 'Unknown', 'Unknown', '...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['December 20']</td>\n",
       "      <td>pakistan</td>\n",
       "      <td>2016</td>\n",
       "      <td>The Commander Southern Command Lieutenant Gene...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>29171</td>\n",
       "      <td>True</td>\n",
       "      <td>['Naga', 'Naga', 'Nagas', 'Naga']</td>\n",
       "      <td>['Manipur Naga Peopleâ€™s Front', 'MNPF', 'MNP...</td>\n",
       "      <td>['explosion', 'exploded', 'bomb', 'attack']</td>\n",
       "      <td>['Bombing/Explosion', 'Bombing/Explosion', 'Bo...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['August 30']</td>\n",
       "      <td>india</td>\n",
       "      <td>2016</td>\n",
       "      <td>Meanwhile the underground organization Manipur...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>25445</td>\n",
       "      <td>True</td>\n",
       "      <td>['Artisan Restaurant', 'foreigners', 'hostages']</td>\n",
       "      <td>['attackers', 'suicide fighters', 'suicide sol...</td>\n",
       "      <td>['gun battle', 'killing', 'injuring']</td>\n",
       "      <td>['Armed Assault', 'Armed Assault', 'Armed Assa...</td>\n",
       "      <td>['Dhaka']</td>\n",
       "      <td>['August', '27th']</td>\n",
       "      <td>bangladesh</td>\n",
       "      <td>2016</td>\n",
       "      <td>Islamic State IS in the latest issue of its on...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>31739</td>\n",
       "      <td>True</td>\n",
       "      <td>['Muttahida Qaumi Movement', 'MQM', 'MQM']</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['shot']</td>\n",
       "      <td>['Assassination']</td>\n",
       "      <td>['Naeemabad', 'Korangi', 'Karachi', 'Sindh']</td>\n",
       "      <td>['June 19']</td>\n",
       "      <td>pakistan</td>\n",
       "      <td>2016</td>\n",
       "      <td>A senior Muttahida Qaumi Movement MQM worker i...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7485</th>\n",
       "      <td>10483</td>\n",
       "      <td>False</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>nepal</td>\n",
       "      <td>2015</td>\n",
       "      <td>Clashes between demonstrators and Police leave...</td>\n",
       "      <td>a9qjjlMsQqy8XtuhYUJ6QMLlDz88-news_satp_15.tsv_46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7486</th>\n",
       "      <td>42333</td>\n",
       "      <td>False</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>india</td>\n",
       "      <td>2012</td>\n",
       "      <td>The death toll in the ongoing clashes between ...</td>\n",
       "      <td>a6U4BlcbFbLRZKmdIMjCcxSEV7ni-news_satp_15.tsv_35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7487</th>\n",
       "      <td>21314</td>\n",
       "      <td>False</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>pakistan</td>\n",
       "      <td>2014</td>\n",
       "      <td>An unnamed security official revealed that Fro...</td>\n",
       "      <td>aBikefqUY7LvQEJe5Sn96IE92aEK-news_satp_15.tsv_39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7488</th>\n",
       "      <td>58183</td>\n",
       "      <td>True</td>\n",
       "      <td>['Police', 'Police']</td>\n",
       "      <td>['militants']</td>\n",
       "      <td>['grenade', 'grenade', 'exploded']</td>\n",
       "      <td>['Bombing/Explosion', 'Bombing/Explosion', 'Bo...</td>\n",
       "      <td>['Srinagar']</td>\n",
       "      <td>['October 16']</td>\n",
       "      <td>india</td>\n",
       "      <td>2011</td>\n",
       "      <td>Police said that militants hurled a grenade on...</td>\n",
       "      <td>a8iR07wYXkm9CV3iPTxqGE4CaaMC-news_satp_15.tsv_52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7489</th>\n",
       "      <td>33926</td>\n",
       "      <td>False</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>pakistan</td>\n",
       "      <td>2013</td>\n",
       "      <td>A recently constituted task force on missing p...</td>\n",
       "      <td>aB.Fjm9WSEjgxfMeoHm8U_dDssXq-news_satp_15.tsv_41</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7490 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         id  is_relevant                                            target  \\\n",
       "0     32355         True         ['Rangers', 'Rangers', 'Military Police']   \n",
       "1     32398         True           ['Security Forces', 'SFs', 'civilians']   \n",
       "2     29171         True                 ['Naga', 'Naga', 'Nagas', 'Naga']   \n",
       "3     25445         True  ['Artisan Restaurant', 'foreigners', 'hostages']   \n",
       "4     31739         True        ['Muttahida Qaumi Movement', 'MQM', 'MQM']   \n",
       "...     ...          ...                                               ...   \n",
       "7485  10483        False                                                []   \n",
       "7486  42333        False                                                []   \n",
       "7487  21314        False                                                []   \n",
       "7488  58183         True                              ['Police', 'Police']   \n",
       "7489  33926        False                                                []   \n",
       "\n",
       "                                                 source  \\\n",
       "0     ['Lashkar e Jhangvi LeJ', 'militants', 'milita...   \n",
       "1                                                   NaN   \n",
       "2     ['Manipur Naga Peopleâ€™s Front', 'MNPF', 'MNP...   \n",
       "3     ['attackers', 'suicide fighters', 'suicide sol...   \n",
       "4                                                   NaN   \n",
       "...                                                 ...   \n",
       "7485                                                 []   \n",
       "7486                                                 []   \n",
       "7487                                                 []   \n",
       "7488                                      ['militants']   \n",
       "7489                                                 []   \n",
       "\n",
       "                                                 action  \\\n",
       "0                       ['killing', 'killed', 'gunned']   \n",
       "1     ['killed', 'fighting', 'wounded', 'fighting', ...   \n",
       "2           ['explosion', 'exploded', 'bomb', 'attack']   \n",
       "3                 ['gun battle', 'killing', 'injuring']   \n",
       "4                                              ['shot']   \n",
       "...                                                 ...   \n",
       "7485                                                 []   \n",
       "7486                                                 []   \n",
       "7487                                                 []   \n",
       "7488                 ['grenade', 'grenade', 'exploded']   \n",
       "7489                                                 []   \n",
       "\n",
       "                                            action_type  \\\n",
       "0     ['Armed Assault', 'Armed Assault', 'Armed Assa...   \n",
       "1     ['Unknown', 'Unknown', 'Unknown', 'Unknown', '...   \n",
       "2     ['Bombing/Explosion', 'Bombing/Explosion', 'Bo...   \n",
       "3     ['Armed Assault', 'Armed Assault', 'Armed Assa...   \n",
       "4                                     ['Assassination']   \n",
       "...                                                 ...   \n",
       "7485                                                NaN   \n",
       "7486                                                NaN   \n",
       "7487                                                NaN   \n",
       "7488  ['Bombing/Explosion', 'Bombing/Explosion', 'Bo...   \n",
       "7489                                                NaN   \n",
       "\n",
       "                                          location                date  \\\n",
       "0                                      ['Karachi']      ['December 6']   \n",
       "1                                              NaN     ['December 20']   \n",
       "2                                              NaN       ['August 30']   \n",
       "3                                        ['Dhaka']  ['August', '27th']   \n",
       "4     ['Naeemabad', 'Korangi', 'Karachi', 'Sindh']         ['June 19']   \n",
       "...                                            ...                 ...   \n",
       "7485                                            []                  []   \n",
       "7486                                            []                  []   \n",
       "7487                                            []                  []   \n",
       "7488                                  ['Srinagar']      ['October 16']   \n",
       "7489                                            []                  []   \n",
       "\n",
       "         country  year                                               news  \\\n",
       "0       pakistan  2016  Two Lashkar e Jhangvi LeJ militants Asim alias...   \n",
       "1       pakistan  2016  The Commander Southern Command Lieutenant Gene...   \n",
       "2          india  2016  Meanwhile the underground organization Manipur...   \n",
       "3     bangladesh  2016  Islamic State IS in the latest issue of its on...   \n",
       "4       pakistan  2016  A senior Muttahida Qaumi Movement MQM worker i...   \n",
       "...          ...   ...                                                ...   \n",
       "7485       nepal  2015  Clashes between demonstrators and Police leave...   \n",
       "7486       india  2012  The death toll in the ongoing clashes between ...   \n",
       "7487    pakistan  2014  An unnamed security official revealed that Fro...   \n",
       "7488       india  2011  Police said that militants hurled a grenade on...   \n",
       "7489    pakistan  2013  A recently constituted task force on missing p...   \n",
       "\n",
       "                                                 index  \n",
       "0                                                  NaN  \n",
       "1                                                  NaN  \n",
       "2                                                  NaN  \n",
       "3                                                  NaN  \n",
       "4                                                  NaN  \n",
       "...                                                ...  \n",
       "7485  a9qjjlMsQqy8XtuhYUJ6QMLlDz88-news_satp_15.tsv_46  \n",
       "7486  a6U4BlcbFbLRZKmdIMjCcxSEV7ni-news_satp_15.tsv_35  \n",
       "7487  aBikefqUY7LvQEJe5Sn96IE92aEK-news_satp_15.tsv_39  \n",
       "7488  a8iR07wYXkm9CV3iPTxqGE4CaaMC-news_satp_15.tsv_52  \n",
       "7489  aB.Fjm9WSEjgxfMeoHm8U_dDssXq-news_satp_15.tsv_41  \n",
       "\n",
       "[7490 rows x 12 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_total = pd.concat(df_list).reset_index(drop=True)\n",
    "df_total"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " ## Running Performances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-21T21:50:42.379174Z",
     "start_time": "2020-12-21T21:50:42.079861Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-7-09c4084b8dd4>:5: MatplotlibDeprecationWarning: Using a string of single character colors as a color sequence is deprecated since 3.2 and will be removed two minor releases later. Use an explicit list instead.\n",
      "  plt.bar(range(len(num_list)), num_list,color='rgb',tick_label=name_list, width=0.5)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "name_list = ['Previous','Parallel']\n",
    "num_list = [407,13]\n",
    "plt.bar(range(len(num_list)), num_list,color='rgb',tick_label=name_list, width=0.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": false,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "261px"
   },
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}