{
"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": {
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" <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": {
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" <th>Word Count</th>\n",
" </tr>\n",
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" <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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" <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": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\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>...</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>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,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
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