{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Necessary imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Importing the classes from 'gydelt'\n",
    "from gydelt.gydelt import GetData, ProcessData \n",
    "\n",
    "# Creating object of GetData\n",
    "GD = GetData()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reading from a file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>NumArticles</th>\n",
       "      <th>Counts</th>\n",
       "      <th>Themes</th>\n",
       "      <th>Locations</th>\n",
       "      <th>Persons</th>\n",
       "      <th>Organizations</th>\n",
       "      <th>ToneData</th>\n",
       "      <th>CAMEOEvents</th>\n",
       "      <th>Sources</th>\n",
       "      <th>SourceURLs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DRONES;NATURAL_DISASTER;NATURAL_DISASTER_ICY;U...</td>\n",
       "      <td>2#California, United States#US#USCA#36.17#-119...</td>\n",
       "      <td>steve chien;andrew thompson</td>\n",
       "      <td>artificial intelligence group;propulsion labor...</td>\n",
       "      <td>-1.16279069767442,1.62790697674419,2.790697674...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sify.com</td>\n",
       "      <td>http://www.sify.com/news/nasas-intelligent-und...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>SEIZE#85##1#Ireland#EI#EI#53#-8#EI;</td>\n",
       "      <td>TAX_FNCACT;TAX_FNCACT_CHILD;RAPE;WB_2024_ANTI_...</td>\n",
       "      <td>1#Ireland#EI#EI#53#-8#EI;1#Germany#GM#GM#51#9#...</td>\n",
       "      <td>claudia peersman;awais rashid</td>\n",
       "      <td>p networks;german research centre for artifici...</td>\n",
       "      <td>-4.33815350389321,1.33481646273637,5.672969966...</td>\n",
       "      <td>604376665,604109997</td>\n",
       "      <td>wired.co.uk</td>\n",
       "      <td>http://www.wired.co.uk/article/ai-interpol-tra...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>EPU_ECONOMY_HISTORIC;ECON_STOCKMARKET;EDUCATIO...</td>\n",
       "      <td>1#Japan#JA#JA#36#138#JA;4#Tokyo, Tokyo, Japan#...</td>\n",
       "      <td>tom foley</td>\n",
       "      <td>paxton center school;hampshire college in amhe...</td>\n",
       "      <td>4.13533834586466,5.26315789473684,1.1278195488...</td>\n",
       "      <td>604128888</td>\n",
       "      <td>thelandmark.com</td>\n",
       "      <td>http://www.thelandmark.com/news/2016-12-01/Pax...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UNGP_FORESTS_RIVERS_OCEANS;MEDIA_MSM;WB_566_EN...</td>\n",
       "      <td>3#Moss Landing, California, United States#US#U...</td>\n",
       "      <td>steve chien;andrew thompson</td>\n",
       "      <td>propulsion laboratory;net enterprises;monterey...</td>\n",
       "      <td>-1.03626943005181,2.2020725388601,3.2383419689...</td>\n",
       "      <td>604152212</td>\n",
       "      <td>clarksvilleonline.com</td>\n",
       "      <td>http://www.clarksvilleonline.com/2016/12/01/na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DRONES;NATURAL_DISASTER;NATURAL_DISASTER_ICY;U...</td>\n",
       "      <td>2#California, United States#US#USCA#36.17#-119...</td>\n",
       "      <td>andrew thompson;steve chien</td>\n",
       "      <td>artificial intelligence group;propulsion labor...</td>\n",
       "      <td>-1.30548302872063,2.088772845953,3.39425587467...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>newkerala.com</td>\n",
       "      <td>http://www.newkerala.com/news/2016/fullnews-14...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date  NumArticles                               Counts  \\\n",
       "0 2016-12-01            1                                  NaN   \n",
       "1 2016-12-01            1  SEIZE#85##1#Ireland#EI#EI#53#-8#EI;   \n",
       "2 2016-12-01            1                                  NaN   \n",
       "3 2016-12-01            1                                  NaN   \n",
       "4 2016-12-01            1                                  NaN   \n",
       "\n",
       "                                              Themes  \\\n",
       "0  DRONES;NATURAL_DISASTER;NATURAL_DISASTER_ICY;U...   \n",
       "1  TAX_FNCACT;TAX_FNCACT_CHILD;RAPE;WB_2024_ANTI_...   \n",
       "2  EPU_ECONOMY_HISTORIC;ECON_STOCKMARKET;EDUCATIO...   \n",
       "3  UNGP_FORESTS_RIVERS_OCEANS;MEDIA_MSM;WB_566_EN...   \n",
       "4  DRONES;NATURAL_DISASTER;NATURAL_DISASTER_ICY;U...   \n",
       "\n",
       "                                           Locations  \\\n",
       "0  2#California, United States#US#USCA#36.17#-119...   \n",
       "1  1#Ireland#EI#EI#53#-8#EI;1#Germany#GM#GM#51#9#...   \n",
       "2  1#Japan#JA#JA#36#138#JA;4#Tokyo, Tokyo, Japan#...   \n",
       "3  3#Moss Landing, California, United States#US#U...   \n",
       "4  2#California, United States#US#USCA#36.17#-119...   \n",
       "\n",
       "                         Persons  \\\n",
       "0    steve chien;andrew thompson   \n",
       "1  claudia peersman;awais rashid   \n",
       "2                      tom foley   \n",
       "3    steve chien;andrew thompson   \n",
       "4    andrew thompson;steve chien   \n",
       "\n",
       "                                       Organizations  \\\n",
       "0  artificial intelligence group;propulsion labor...   \n",
       "1  p networks;german research centre for artifici...   \n",
       "2  paxton center school;hampshire college in amhe...   \n",
       "3  propulsion laboratory;net enterprises;monterey...   \n",
       "4  artificial intelligence group;propulsion labor...   \n",
       "\n",
       "                                            ToneData          CAMEOEvents  \\\n",
       "0  -1.16279069767442,1.62790697674419,2.790697674...                  NaN   \n",
       "1  -4.33815350389321,1.33481646273637,5.672969966...  604376665,604109997   \n",
       "2  4.13533834586466,5.26315789473684,1.1278195488...            604128888   \n",
       "3  -1.03626943005181,2.2020725388601,3.2383419689...            604152212   \n",
       "4  -1.30548302872063,2.088772845953,3.39425587467...                  NaN   \n",
       "\n",
       "                 Sources                                         SourceURLs  \n",
       "0               sify.com  http://www.sify.com/news/nasas-intelligent-und...  \n",
       "1            wired.co.uk  http://www.wired.co.uk/article/ai-interpol-tra...  \n",
       "2        thelandmark.com  http://www.thelandmark.com/news/2016-12-01/Pax...  \n",
       "3  clarksvilleonline.com  http://www.clarksvilleonline.com/2016/12/01/na...  \n",
       "4          newkerala.com  http://www.newkerala.com/news/2016/fullnews-14...  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Reading from a csv file (obtained from GKG Exporter)\n",
    "data = GD.read_from_file(path='sample data/fromGKG.txt', parse_dates=['Date'])\n",
    "data.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preprocessing the data using the wrapper function present in the ProcessData"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Creating object of ProcessData\n",
    "PD = ProcessData(data_frame=data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Time taken for pre-processing the data --> 0.49 seconds\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>NumArticles</th>\n",
       "      <th>Counts</th>\n",
       "      <th>Themes</th>\n",
       "      <th>Locations</th>\n",
       "      <th>Persons</th>\n",
       "      <th>Organizations</th>\n",
       "      <th>ToneData</th>\n",
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       "      <th>SourceURLs</th>\n",
       "      <th>Countries</th>\n",
       "      <th>Tone</th>\n",
       "      <th>Positive Score</th>\n",
       "      <th>Negative Score</th>\n",
       "      <th>Polarity</th>\n",
       "      <th>Activity Reference Density</th>\n",
       "      <th>Self/Group Reference Density</th>\n",
       "      <th>Word Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DRONES;NATURAL_DISASTER;NATURAL_DISASTER_ICY;U...</td>\n",
       "      <td>2#California, United States#US#USCA#36.17#-119...</td>\n",
       "      <td>steve chien;andrew thompson</td>\n",
       "      <td>artificial intelligence group;propulsion labor...</td>\n",
       "      <td>-1.16279069767442,1.62790697674419,2.790697674...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sify.com</td>\n",
       "      <td>http://www.sify.com/news/nasas-intelligent-und...</td>\n",
       "      <td>United States</td>\n",
       "      <td>-1.162791</td>\n",
       "      <td>1.627907</td>\n",
       "      <td>2.790698</td>\n",
       "      <td>4.418605</td>\n",
       "      <td>24.186047</td>\n",
       "      <td>1.162791</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>SEIZE#85##1#Ireland#EI#EI#53#-8#EI;</td>\n",
       "      <td>TAX_FNCACT;TAX_FNCACT_CHILD;RAPE;WB_2024_ANTI_...</td>\n",
       "      <td>1#Ireland#EI#EI#53#-8#EI;1#Germany#GM#GM#51#9#...</td>\n",
       "      <td>claudia peersman;awais rashid</td>\n",
       "      <td>p networks;german research centre for artifici...</td>\n",
       "      <td>-4.33815350389321,1.33481646273637,5.672969966...</td>\n",
       "      <td>604376665,604109997</td>\n",
       "      <td>wired.co.uk</td>\n",
       "      <td>http://www.wired.co.uk/article/ai-interpol-tra...</td>\n",
       "      <td>Ireland;France;Germany</td>\n",
       "      <td>-4.338154</td>\n",
       "      <td>1.334816</td>\n",
       "      <td>5.672970</td>\n",
       "      <td>7.007786</td>\n",
       "      <td>21.357063</td>\n",
       "      <td>0.556174</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>EPU_ECONOMY_HISTORIC;ECON_STOCKMARKET;EDUCATIO...</td>\n",
       "      <td>1#Japan#JA#JA#36#138#JA;4#Tokyo, Tokyo, Japan#...</td>\n",
       "      <td>tom foley</td>\n",
       "      <td>paxton center school;hampshire college in amhe...</td>\n",
       "      <td>4.13533834586466,5.26315789473684,1.1278195488...</td>\n",
       "      <td>604128888</td>\n",
       "      <td>thelandmark.com</td>\n",
       "      <td>http://www.thelandmark.com/news/2016-12-01/Pax...</td>\n",
       "      <td>Japan</td>\n",
       "      <td>4.135338</td>\n",
       "      <td>5.263158</td>\n",
       "      <td>1.127820</td>\n",
       "      <td>6.390977</td>\n",
       "      <td>25.939850</td>\n",
       "      <td>0.751880</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UNGP_FORESTS_RIVERS_OCEANS;MEDIA_MSM;WB_566_EN...</td>\n",
       "      <td>3#Moss Landing, California, United States#US#U...</td>\n",
       "      <td>steve chien;andrew thompson</td>\n",
       "      <td>propulsion laboratory;net enterprises;monterey...</td>\n",
       "      <td>-1.03626943005181,2.2020725388601,3.2383419689...</td>\n",
       "      <td>604152212</td>\n",
       "      <td>clarksvilleonline.com</td>\n",
       "      <td>http://www.clarksvilleonline.com/2016/12/01/na...</td>\n",
       "      <td>United States;France</td>\n",
       "      <td>-1.036269</td>\n",
       "      <td>2.202073</td>\n",
       "      <td>3.238342</td>\n",
       "      <td>5.440415</td>\n",
       "      <td>25.259067</td>\n",
       "      <td>1.683938</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DRONES;NATURAL_DISASTER;NATURAL_DISASTER_ICY;U...</td>\n",
       "      <td>2#California, United States#US#USCA#36.17#-119...</td>\n",
       "      <td>andrew thompson;steve chien</td>\n",
       "      <td>artificial intelligence group;propulsion labor...</td>\n",
       "      <td>-1.30548302872063,2.088772845953,3.39425587467...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>newkerala.com</td>\n",
       "      <td>http://www.newkerala.com/news/2016/fullnews-14...</td>\n",
       "      <td>United States</td>\n",
       "      <td>-1.305483</td>\n",
       "      <td>2.088773</td>\n",
       "      <td>3.394256</td>\n",
       "      <td>5.483029</td>\n",
       "      <td>25.587467</td>\n",
       "      <td>1.827676</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date  NumArticles                               Counts  \\\n",
       "0 2016-12-01            1                                  NaN   \n",
       "1 2016-12-01            1  SEIZE#85##1#Ireland#EI#EI#53#-8#EI;   \n",
       "2 2016-12-01            1                                  NaN   \n",
       "3 2016-12-01            1                                  NaN   \n",
       "4 2016-12-01            1                                  NaN   \n",
       "\n",
       "                                              Themes  \\\n",
       "0  DRONES;NATURAL_DISASTER;NATURAL_DISASTER_ICY;U...   \n",
       "1  TAX_FNCACT;TAX_FNCACT_CHILD;RAPE;WB_2024_ANTI_...   \n",
       "2  EPU_ECONOMY_HISTORIC;ECON_STOCKMARKET;EDUCATIO...   \n",
       "3  UNGP_FORESTS_RIVERS_OCEANS;MEDIA_MSM;WB_566_EN...   \n",
       "4  DRONES;NATURAL_DISASTER;NATURAL_DISASTER_ICY;U...   \n",
       "\n",
       "                                           Locations  \\\n",
       "0  2#California, United States#US#USCA#36.17#-119...   \n",
       "1  1#Ireland#EI#EI#53#-8#EI;1#Germany#GM#GM#51#9#...   \n",
       "2  1#Japan#JA#JA#36#138#JA;4#Tokyo, Tokyo, Japan#...   \n",
       "3  3#Moss Landing, California, United States#US#U...   \n",
       "4  2#California, United States#US#USCA#36.17#-119...   \n",
       "\n",
       "                         Persons  \\\n",
       "0    steve chien;andrew thompson   \n",
       "1  claudia peersman;awais rashid   \n",
       "2                      tom foley   \n",
       "3    steve chien;andrew thompson   \n",
       "4    andrew thompson;steve chien   \n",
       "\n",
       "                                       Organizations  \\\n",
       "0  artificial intelligence group;propulsion labor...   \n",
       "1  p networks;german research centre for artifici...   \n",
       "2  paxton center school;hampshire college in amhe...   \n",
       "3  propulsion laboratory;net enterprises;monterey...   \n",
       "4  artificial intelligence group;propulsion labor...   \n",
       "\n",
       "                                            ToneData          CAMEOEvents  \\\n",
       "0  -1.16279069767442,1.62790697674419,2.790697674...                  NaN   \n",
       "1  -4.33815350389321,1.33481646273637,5.672969966...  604376665,604109997   \n",
       "2  4.13533834586466,5.26315789473684,1.1278195488...            604128888   \n",
       "3  -1.03626943005181,2.2020725388601,3.2383419689...            604152212   \n",
       "4  -1.30548302872063,2.088772845953,3.39425587467...                  NaN   \n",
       "\n",
       "                 Sources                                         SourceURLs  \\\n",
       "0               sify.com  http://www.sify.com/news/nasas-intelligent-und...   \n",
       "1            wired.co.uk  http://www.wired.co.uk/article/ai-interpol-tra...   \n",
       "2        thelandmark.com  http://www.thelandmark.com/news/2016-12-01/Pax...   \n",
       "3  clarksvilleonline.com  http://www.clarksvilleonline.com/2016/12/01/na...   \n",
       "4          newkerala.com  http://www.newkerala.com/news/2016/fullnews-14...   \n",
       "\n",
       "                Countries      Tone  Positive Score  Negative Score  Polarity  \\\n",
       "0           United States -1.162791        1.627907        2.790698  4.418605   \n",
       "1  Ireland;France;Germany -4.338154        1.334816        5.672970  7.007786   \n",
       "2                   Japan  4.135338        5.263158        1.127820  6.390977   \n",
       "3    United States;France -1.036269        2.202073        3.238342  5.440415   \n",
       "4           United States -1.305483        2.088773        3.394256  5.483029   \n",
       "\n",
       "   Activity Reference Density  Self/Group Reference Density Word Count  \n",
       "0                   24.186047                      1.162791       None  \n",
       "1                   21.357063                      0.556174       None  \n",
       "2                   25.939850                      0.751880       None  \n",
       "3                   25.259067                      1.683938       None  \n",
       "4                   25.587467                      1.827676       None  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calling the wrapper function to pre-process the whole data\n",
    "processed_data_1 = PD.pre_process()\n",
    "processed_data_1.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Flattening a column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Time taken for flattening the column(s) --> 0.58 seconds\n"
     ]
    },
    {
     "data": {
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       "<div>\n",
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       "    .dataframe thead tr:only-child th {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>NumArticles</th>\n",
       "      <th>Counts</th>\n",
       "      <th>Themes</th>\n",
       "      <th>Locations</th>\n",
       "      <th>Persons</th>\n",
       "      <th>Organizations</th>\n",
       "      <th>ToneData</th>\n",
       "      <th>CAMEOEvents</th>\n",
       "      <th>Sources</th>\n",
       "      <th>...</th>\n",
       "      <th>United Kingdom</th>\n",
       "      <th>United States</th>\n",
       "      <th>Uruguay</th>\n",
       "      <th>Uzbekistan</th>\n",
       "      <th>Venezuela</th>\n",
       "      <th>Vietnam</th>\n",
       "      <th>Western Sahara</th>\n",
       "      <th>Yemen</th>\n",
       "      <th>Zambia</th>\n",
       "      <th>Zimbabwe</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DRONES;NATURAL_DISASTER;NATURAL_DISASTER_ICY;U...</td>\n",
       "      <td>2#California, United States#US#USCA#36.17#-119...</td>\n",
       "      <td>steve chien;andrew thompson</td>\n",
       "      <td>artificial intelligence group;propulsion labor...</td>\n",
       "      <td>-1.16279069767442,1.62790697674419,2.790697674...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sify.com</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>SEIZE#85##1#Ireland#EI#EI#53#-8#EI;</td>\n",
       "      <td>TAX_FNCACT;TAX_FNCACT_CHILD;RAPE;WB_2024_ANTI_...</td>\n",
       "      <td>1#Ireland#EI#EI#53#-8#EI;1#Germany#GM#GM#51#9#...</td>\n",
       "      <td>claudia peersman;awais rashid</td>\n",
       "      <td>p networks;german research centre for artifici...</td>\n",
       "      <td>-4.33815350389321,1.33481646273637,5.672969966...</td>\n",
       "      <td>604376665,604109997</td>\n",
       "      <td>wired.co.uk</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>EPU_ECONOMY_HISTORIC;ECON_STOCKMARKET;EDUCATIO...</td>\n",
       "      <td>1#Japan#JA#JA#36#138#JA;4#Tokyo, Tokyo, Japan#...</td>\n",
       "      <td>tom foley</td>\n",
       "      <td>paxton center school;hampshire college in amhe...</td>\n",
       "      <td>4.13533834586466,5.26315789473684,1.1278195488...</td>\n",
       "      <td>604128888</td>\n",
       "      <td>thelandmark.com</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UNGP_FORESTS_RIVERS_OCEANS;MEDIA_MSM;WB_566_EN...</td>\n",
       "      <td>3#Moss Landing, California, United States#US#U...</td>\n",
       "      <td>steve chien;andrew thompson</td>\n",
       "      <td>propulsion laboratory;net enterprises;monterey...</td>\n",
       "      <td>-1.03626943005181,2.2020725388601,3.2383419689...</td>\n",
       "      <td>604152212</td>\n",
       "      <td>clarksvilleonline.com</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DRONES;NATURAL_DISASTER;NATURAL_DISASTER_ICY;U...</td>\n",
       "      <td>2#California, United States#US#USCA#36.17#-119...</td>\n",
       "      <td>andrew thompson;steve chien</td>\n",
       "      <td>artificial intelligence group;propulsion labor...</td>\n",
       "      <td>-1.30548302872063,2.088772845953,3.39425587467...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>newkerala.com</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 154 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date  NumArticles                               Counts  \\\n",
       "0 2016-12-01            1                                  NaN   \n",
       "1 2016-12-01            1  SEIZE#85##1#Ireland#EI#EI#53#-8#EI;   \n",
       "2 2016-12-01            1                                  NaN   \n",
       "3 2016-12-01            1                                  NaN   \n",
       "4 2016-12-01            1                                  NaN   \n",
       "\n",
       "                                              Themes  \\\n",
       "0  DRONES;NATURAL_DISASTER;NATURAL_DISASTER_ICY;U...   \n",
       "1  TAX_FNCACT;TAX_FNCACT_CHILD;RAPE;WB_2024_ANTI_...   \n",
       "2  EPU_ECONOMY_HISTORIC;ECON_STOCKMARKET;EDUCATIO...   \n",
       "3  UNGP_FORESTS_RIVERS_OCEANS;MEDIA_MSM;WB_566_EN...   \n",
       "4  DRONES;NATURAL_DISASTER;NATURAL_DISASTER_ICY;U...   \n",
       "\n",
       "                                           Locations  \\\n",
       "0  2#California, United States#US#USCA#36.17#-119...   \n",
       "1  1#Ireland#EI#EI#53#-8#EI;1#Germany#GM#GM#51#9#...   \n",
       "2  1#Japan#JA#JA#36#138#JA;4#Tokyo, Tokyo, Japan#...   \n",
       "3  3#Moss Landing, California, United States#US#U...   \n",
       "4  2#California, United States#US#USCA#36.17#-119...   \n",
       "\n",
       "                         Persons  \\\n",
       "0    steve chien;andrew thompson   \n",
       "1  claudia peersman;awais rashid   \n",
       "2                      tom foley   \n",
       "3    steve chien;andrew thompson   \n",
       "4    andrew thompson;steve chien   \n",
       "\n",
       "                                       Organizations  \\\n",
       "0  artificial intelligence group;propulsion labor...   \n",
       "1  p networks;german research centre for artifici...   \n",
       "2  paxton center school;hampshire college in amhe...   \n",
       "3  propulsion laboratory;net enterprises;monterey...   \n",
       "4  artificial intelligence group;propulsion labor...   \n",
       "\n",
       "                                            ToneData          CAMEOEvents  \\\n",
       "0  -1.16279069767442,1.62790697674419,2.790697674...                  NaN   \n",
       "1  -4.33815350389321,1.33481646273637,5.672969966...  604376665,604109997   \n",
       "2  4.13533834586466,5.26315789473684,1.1278195488...            604128888   \n",
       "3  -1.03626943005181,2.2020725388601,3.2383419689...            604152212   \n",
       "4  -1.30548302872063,2.088772845953,3.39425587467...                  NaN   \n",
       "\n",
       "                 Sources    ...    United Kingdom United States  Uruguay  \\\n",
       "0               sify.com    ...               NaN           1.0      NaN   \n",
       "1            wired.co.uk    ...               NaN           NaN      NaN   \n",
       "2        thelandmark.com    ...               NaN           NaN      NaN   \n",
       "3  clarksvilleonline.com    ...               NaN           1.0      NaN   \n",
       "4          newkerala.com    ...               NaN           1.0      NaN   \n",
       "\n",
       "   Uzbekistan  Venezuela  Vietnam  Western Sahara  Yemen Zambia  Zimbabwe  \n",
       "0         NaN        NaN      NaN             NaN    NaN    NaN       NaN  \n",
       "1         NaN        NaN      NaN             NaN    NaN    NaN       NaN  \n",
       "2         NaN        NaN      NaN             NaN    NaN    NaN       NaN  \n",
       "3         NaN        NaN      NaN             NaN    NaN    NaN       NaN  \n",
       "4         NaN        NaN      NaN             NaN    NaN    NaN       NaN  \n",
       "\n",
       "[5 rows x 154 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Flattening(One-hot Encoding) the 'Countries' column\n",
    "processed_data_2 = PD.flat_column(columns=['Countries'])\n",
    "processed_data_2.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Sample Usecase - To plot the average 'Tone' over a month for articles with mentions of both countries - India and China"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "67 records have the mentions of both India and China\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>NumArticles</th>\n",
       "      <th>Counts</th>\n",
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       "      <th>...</th>\n",
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       "      <th>United States</th>\n",
       "      <th>Uruguay</th>\n",
       "      <th>Uzbekistan</th>\n",
       "      <th>Venezuela</th>\n",
       "      <th>Vietnam</th>\n",
       "      <th>Western Sahara</th>\n",
       "      <th>Yemen</th>\n",
       "      <th>Zambia</th>\n",
       "      <th>Zimbabwe</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>2016-12-03</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GENERAL_GOVERNMENT;SOVEREIGNTY;TAX_FNCACT;TAX_...</td>\n",
       "      <td>1#Vietnam, Republic Of#VM#VM#16#106#VM;4#Dongh...</td>\n",
       "      <td>marco polo;longji dragon;zonghe guangbo jiaoto...</td>\n",
       "      <td>artificial intelligence laboratory;google;inst...</td>\n",
       "      <td>1.01102104016759,2.36815739138355,1.3571363512...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>wn.com</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>2016-12-12</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TAX_FNCACT;TAX_FNCACT_LEADER;ENV_OIL;TAX_ECON_...</td>\n",
       "      <td>1#China#CH#CH#35#105#CH;1#Mexico#MX#MX#23#-102...</td>\n",
       "      <td>unknown</td>\n",
       "      <td>broadcom;ericsson;ibm;facebook;visa;artificial...</td>\n",
       "      <td>1.36570561456753,3.33839150227618,1.9726858877...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sharesinv.com</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>2016-12-14</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>unknown</td>\n",
       "      <td>3#University Of Louisville, Kentucky, United S...</td>\n",
       "      <td>deepmind alphago;demis hassabis;david kenny;jo...</td>\n",
       "      <td>houston methodist research institute;cybersecu...</td>\n",
       "      <td>0.916380297823597,3.55097365406644,2.634593356...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>techrepublic.com</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>2016-12-19</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TECH_AUTOMATION;WB_1921_PRIVATE_SECTOR_DEVELOP...</td>\n",
       "      <td>1#China#CH#CH#35#105#CH;2#New York, United Sta...</td>\n",
       "      <td>paul allen;jon talton;bill gates</td>\n",
       "      <td>boeing;allen institute for artificial intellig...</td>\n",
       "      <td>-0.900900900900901,2.5025025025025,3.403403403...</td>\n",
       "      <td>609815768,609817195,609817718,609649509</td>\n",
       "      <td>crosscut.com</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>2016-12-21</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>unknown</td>\n",
       "      <td>1#United States#US#US#38#-97#US;1#China#CH#CH#...</td>\n",
       "      <td>baidu facebook;gabriele ketterl</td>\n",
       "      <td>ibm;united states artificial intelligence mach...</td>\n",
       "      <td>0.809716599190283,3.96761133603239,3.157894736...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>openpr.com</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 154 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date  NumArticles Counts  \\\n",
       "48  2016-12-03            1    NaN   \n",
       "138 2016-12-12            1    NaN   \n",
       "165 2016-12-14            1    NaN   \n",
       "214 2016-12-19            1    NaN   \n",
       "231 2016-12-21            1    NaN   \n",
       "\n",
       "                                                Themes  \\\n",
       "48   GENERAL_GOVERNMENT;SOVEREIGNTY;TAX_FNCACT;TAX_...   \n",
       "138  TAX_FNCACT;TAX_FNCACT_LEADER;ENV_OIL;TAX_ECON_...   \n",
       "165                                            unknown   \n",
       "214  TECH_AUTOMATION;WB_1921_PRIVATE_SECTOR_DEVELOP...   \n",
       "231                                            unknown   \n",
       "\n",
       "                                             Locations  \\\n",
       "48   1#Vietnam, Republic Of#VM#VM#16#106#VM;4#Dongh...   \n",
       "138  1#China#CH#CH#35#105#CH;1#Mexico#MX#MX#23#-102...   \n",
       "165  3#University Of Louisville, Kentucky, United S...   \n",
       "214  1#China#CH#CH#35#105#CH;2#New York, United Sta...   \n",
       "231  1#United States#US#US#38#-97#US;1#China#CH#CH#...   \n",
       "\n",
       "                                               Persons  \\\n",
       "48   marco polo;longji dragon;zonghe guangbo jiaoto...   \n",
       "138                                            unknown   \n",
       "165  deepmind alphago;demis hassabis;david kenny;jo...   \n",
       "214                   paul allen;jon talton;bill gates   \n",
       "231                    baidu facebook;gabriele ketterl   \n",
       "\n",
       "                                         Organizations  \\\n",
       "48   artificial intelligence laboratory;google;inst...   \n",
       "138  broadcom;ericsson;ibm;facebook;visa;artificial...   \n",
       "165  houston methodist research institute;cybersecu...   \n",
       "214  boeing;allen institute for artificial intellig...   \n",
       "231  ibm;united states artificial intelligence mach...   \n",
       "\n",
       "                                              ToneData  \\\n",
       "48   1.01102104016759,2.36815739138355,1.3571363512...   \n",
       "138  1.36570561456753,3.33839150227618,1.9726858877...   \n",
       "165  0.916380297823597,3.55097365406644,2.634593356...   \n",
       "214  -0.900900900900901,2.5025025025025,3.403403403...   \n",
       "231  0.809716599190283,3.96761133603239,3.157894736...   \n",
       "\n",
       "                                 CAMEOEvents           Sources    ...     \\\n",
       "48                                       NaN            wn.com    ...      \n",
       "138                                      NaN     sharesinv.com    ...      \n",
       "165                                      NaN  techrepublic.com    ...      \n",
       "214  609815768,609817195,609817718,609649509      crosscut.com    ...      \n",
       "231                                      NaN        openpr.com    ...      \n",
       "\n",
       "    United Kingdom United States  Uruguay  Uzbekistan  Venezuela  Vietnam  \\\n",
       "48             NaN           1.0      NaN         NaN        NaN      1.0   \n",
       "138            NaN           NaN      NaN         NaN        NaN      NaN   \n",
       "165            NaN           1.0      NaN         NaN        NaN      NaN   \n",
       "214            NaN           1.0      NaN         NaN        NaN      NaN   \n",
       "231            1.0           1.0      NaN         NaN        NaN      NaN   \n",
       "\n",
       "     Western Sahara  Yemen Zambia  Zimbabwe  \n",
       "48              NaN    NaN    NaN       NaN  \n",
       "138             NaN    NaN    NaN       NaN  \n",
       "165             NaN    NaN    NaN       NaN  \n",
       "214             NaN    NaN    NaN       NaN  \n",
       "231             NaN    NaN    NaN       NaN  \n",
       "\n",
       "[5 rows x 154 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# How can flattening(one-hot encoding) be useful ?\n",
    "include_India = processed_data_2['India'] == 1\n",
    "include_China = processed_data_2['China'] == 1\n",
    "\n",
    "# It makes filtering way more simpler (in case of the data that GDELT provides)\n",
    "required_data = processed_data_2[include_India & include_China]\n",
    "\n",
    "print('\\n{} records have the mentions of both India and China'.format(required_data.shape[0]))\n",
    "required_data.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1c5ce41e898>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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YpG+/sE5jBvTWwjunKa9/L6fHAj6FYAZ0g5r6Jr23pVyzczMVwemRsPDN885S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\nSeoJAzNJkqSe+BS9zdGaeasN2AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c5ce3ee8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Also, since each component of 'ToneData' has been seperated, visualization becomes a lot more simpler\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "%matplotlib inline\n",
    "\n",
    "# Resampling the 'Tone' (first component of 'ToneData') on Monthly basis\n",
    "resampled = required_data[['Date', 'Tone']].resample(rule='M', on='Date').apply(np.mean)\n",
    "\n",
    "# Plotting the resampled data\n",
    "resampled.plot(figsize=(10, 7), kind='line')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Saving the processed data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Success: Data frame saved as - C:\\Users\\Mrinal Jain\\gydelt\\tutorial\\Result(2017-08-29 14.52.09).csv\n"
     ]
    }
   ],
   "source": [
    "# Saving the data frame (using the function in ProcessData)\n",
    "PD.save_data_frame()\n",
    "\n",
    "# (or)\n",
    "# GD.save_data_frame(data_frame=processed_data_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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