intro_gdelt.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "349da07d-c042-4dcd-a95c-4e8146f0daeb",
   "metadata": {},
   "source": [
    "#  RIF Data Wrangling - GDELT"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9b184a5-4f4c-4a71-9f05-cc90d87482e6",
   "metadata": {},
   "source": [
    "In this notebook, We will go through how to use Google BigQuery to access the GDELT project data, and some simple usage cases.  \n",
    "\n",
    "Useful References:  \n",
    "- Google Cloud\n",
    "    - Google BigQuery: https://cloud.google.com/bigquery\n",
    "    - Authenticate with Google Cloud: https://hevodata.com/learn/bigquery-jupyter-notebook/#w5\n",
    "    - Google BigQuery Python Documantation: https://cloud.google.com/python/docs/reference/bigquery/latest/index.html\n",
    "    - Google BigQuery Python Samples:https://cloud.google.com/bigquery/docs/samples\n",
    "- GDELT\n",
    "    - Raw Data: http://data.gdeltproject.org/events/index.html\n",
    "    - A description of the data fields: http://data.gdeltproject.org/documentation/GDELT-Data_Format_Codebook.pdf\n",
    "    - The event codes are described in this document: http://gdeltproject.org/data/documentation/CAMEO.Manual.1.1b3.pdf\n",
    "    - CAMEO country codes are listed here: https://www.gdeltproject.org/data/lookups/CAMEO.country.txt\n",
    "    - FIPS country codes are listed here: https://www.gdeltproject.org/data/lookups/FIPS.country.txt"
   ]
  },
  {
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   "execution_count": 2,
   "id": "f3255a5c-6d38-4429-90af-79f5af17f0e1",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already up-to-date: google-cloud-bigquery[bqstorage,pandas] in /home/jovyan/.local/geoai-py3-0.8.0/lib/python3.6/site-packages (3.2.0)\n",
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     ]
    }
   ],
   "source": [
    "!pip install --upgrade 'google-cloud-bigquery[bqstorage,pandas]'\n",
    "!pip install db-dtypes\n",
    "!pip install basemap\n",
    "!pip install networkx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3e6be48d-273d-4128-982c-d3ab9abf18e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "import math\n",
    "\n",
    "import numpy as np\n",
    "import geopandas as gpd\n",
    "\n",
    "from google.cloud import bigquery\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.basemap import Basemap\n",
    "\n",
    "import networkx as nx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d4cd1ff1-8957-4947-8042-852919bfaac5",
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext google.cloud.bigquery"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8c036fa-0c65-461f-956e-eaf1cd44ea75",
   "metadata": {
    "tags": []
   },
   "source": [
    "## **Step 0**: Google BigQuery Account"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a65b6057-af76-4e80-8943-28a8d870b960",
   "metadata": {},
   "source": [
    "Authenticate with Google Cloud:  \n",
    "You need to authenticate your Python code to access Google Cloud resources. You can do this by creating a service account and downloading the JSON key file.  \n",
    "- Create a service account and download the JSON key file (reference: https://hevodata.com/learn/bigquery-jupyter-notebook/#w5):\n",
    "    - Go to the Google Cloud Console.\n",
    "    - Navigate to \"IAM & Admin\" > \"Service accounts.\"\n",
    "    - Click \"Create Service Account,\" fill out the details, and grant the necessary permissions (BigQuery User or Editor role).\n",
    "    - Create and download a JSON key file for the service account.\n",
    "- Set the GOOGLE_APPLICATION_CREDENTIALS environment variable to point to your JSON key file:  \n",
    "```python\n",
    "import os\n",
    "os.environ[\"GOOGLE_APPLICATION_CREDENTIALS\"] = \"path-to-CREDENTIALS.json\"\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "becbb40e-7d74-4415-889e-c1c08f21597a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Setting your Google application credentials\n",
    "os.environ[\"GOOGLE_APPLICATION_CREDENTIALS\"] = \"iguide-gdelt.json\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60897409-2535-4b83-9cdc-5f459dce6593",
   "metadata": {},
   "source": [
    "- Simple test (good to continue if you see a table output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "63e3dc76-e982-427c-9cc3-32e065c66c30",
   "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>plurality</th>\n",
       "      <th>count</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>139209</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>138866</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>137239</td>\n",
       "      <td>2006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>133285</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>132344</td>\n",
       "      <td>2004</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   plurality   count  year\n",
       "0          2  139209  2007\n",
       "1          2  138866  2008\n",
       "2          2  137239  2006\n",
       "3          2  133285  2005\n",
       "4          2  132344  2004"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Construct a BigQuery client object.\n",
    "client = bigquery.Client()\n",
    "sql = \"\"\"\n",
    "SELECT\n",
    "    plurality,\n",
    "    COUNT(1) AS count,\n",
    "    year\n",
    "FROM\n",
    "    `bigquery-public-data.samples.natality`\n",
    "WHERE\n",
    "    NOT IS_NAN(plurality) AND plurality > 1\n",
    "GROUP BY\n",
    "    plurality, year\n",
    "ORDER BY\n",
    "    count DESC\n",
    "\"\"\"\n",
    "df = client.query(sql).to_dataframe()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6eb83527-2a2b-4537-ad26-4fe5e2ab2866",
   "metadata": {
    "tags": []
   },
   "source": [
    "## BigQuery GDELT Dataset Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81cd50cb-3e5c-43cb-bf24-00a6d9a4be3b",
   "metadata": {
    "tags": []
   },
   "source": [
    "The database structure is project --> dataset --> table. The project id for the GDELT project in Google BigQuery is `\"gdelt-bq\"`.   \n",
    "\n",
    "### 1. Datasets and tables.  \n",
    "First, we investigate what datasets and tables are accessible."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "97686627-bc16-4caf-b19a-9263c5976a1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Project id of the GDELT project\n",
    "project_id = \"gdelt-bq\"\n",
    "\n",
    "# Create a BigQuery client object\n",
    "client = bigquery.Client(project=project_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "074d8ab4-e82b-40ef-9fd8-f9283213f813",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset: covid19\n",
      "Tables: onlinenews, onlinenewsgeo, tvnews\n",
      "--------\n",
      "Dataset: extra\n",
      "Tables: countries_by_media_50pct, countrygeolookup, countryinfo, countryinfo2, sourcesbycountry, toytonelookup\n",
      "--------\n",
      "Dataset: full\n",
      "Tables: crosswalk_geocountrycodetohuman, events, events_partitioned\n",
      "--------\n",
      "Dataset: gdeltv2\n",
      "Tables: academicliteraturegkg, cloudvision, cloudvision_partitioned, cloudvision_webentitygraph_20191020, domainsbycountry_alllangs_april2015, eventmentions, eventmentions_partitioned, events, events_partitioned, gal, gdg_partitioned, geg_g1, geg_gcnlapi, geg_gcnlapisent, geg_iatv, gegv2_iatv, gemg, gfg_linguistic1grams_20190831, gfg_linguistic2grams_20190831, gfg_linguisticinventory_20190901, gfg_outlet1grams_20190831, gfg_outlet2grams_20190831, gfg_partitioned, ggg, gkg, gkg_partitioned, gkg_socialoutlinks, gng, gqg, grg_dtn, grg_vcn, grg_vcn_nlpapi, gsg, gsg_docembed, gsg_iatvsentembed, iaradio_1grams, iaradio_2grams, iaradio_3grams, iaradio_4grams, iaradio_5grams, iatv_1grams, iatv_1gramsv2, iatv_2grams, iatv_2gramsv2, iatv_3gramsv2, iatv_4gramsv2, iatv_5gramsv2, iatv_aif_captime, iatv_aif_vidtime, iatv_lowerthird, iatv_lowerthirdclusters, iatv_showinventory, iatv_timeinventory, iatvgkg, readability, readability_iatv, vgeg_iatv, vgegv2_iatv, web_1grams, web_2grams, web_pos, webngrams\n",
      "--------\n",
      "Dataset: gdeltv2_ngrams\n",
      "Tables: arabic_trigram\n",
      "--------\n",
      "Dataset: hathitrustbooks\n",
      "Tables: 1800, 1801, 1802, 1803, 1804, 1805, 1806, 1807, 1808, 1809, 1810, 1811, 1812, 1813, 1814, 1815, 1816, 1817, 1818, 1819, 1820, 1821, 1822, 1823, 1824, 1825, 1826, 1827, 1828, 1829, 1830, 1831, 1832, 1833, 1834, 1835, 1836, 1837, 1838, 1839, 1840, 1841, 1842, 1843, 1844, 1845, 1846, 1847, 1848, 1849, 1850, 1851, 1852, 1853, 1854, 1855, 1856, 1857, 1858, 1859, 1860, 1861, 1862, 1863, 1864, 1865, 1866, 1867, 1868, 1869, 1870, 1871, 1872, 1873, 1874, 1875, 1876, 1877, 1878, 1879, 1880, 1881, 1882, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012\n",
      "--------\n",
      "Dataset: internetarchivebooks\n",
      "Tables: 1800, 1801, 1802, 1803, 1804, 1805, 1806, 1807, 1808, 1809, 1810, 1811, 1812, 1813, 1814, 1815, 1816, 1817, 1818, 1819, 1820, 1821, 1822, 1823, 1824, 1825, 1826, 1827, 1828, 1829, 1830, 1831, 1832, 1833, 1834, 1835, 1836, 1837, 1838, 1839, 1840, 1841, 1842, 1843, 1844, 1845, 1846, 1847, 1848, 1849, 1850, 1851, 1852, 1853, 1854, 1855, 1856, 1857, 1858, 1859, 1860, 1861, 1862, 1863, 1864, 1865, 1866, 1867, 1868, 1869, 1870, 1871, 1872, 1873, 1874, 1875, 1876, 1877, 1878, 1879, 1880, 1881, 1882, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923notxt, 1924notxt, 1925notxt, 1926notxt, 1927notxt, 1928notxt, 1929notxt, 1930notxt, 1931notxt, 1932notxt, 1933notxt, 1934notxt, 1935notxt, 1936notxt, 1937notxt, 1938notxt, 1939notxt, 1940notxt, 1941notxt, 1942notxt, 1943notxt, 1944notxt, 1945notxt, 1946notxt, 1947notxt, 1948notxt, 1949notxt, 1950notxt, 1951notxt, 1952notxt, 1953notxt, 1954notxt, 1955notxt, 1956notxt, 1957notxt, 1958notxt, 1959notxt, 1960notxt, 1961notxt, 1962notxt, 1963notxt, 1964notxt, 1965notxt, 1966notxt, 1967notxt, 1968notxt, 1969notxt, 1970notxt, 1971notxt, 1972notxt, 1973notxt, 1974notxt, 1975notxt, 1976notxt, 1977noftxt, 1978notxt, 1979notxt, 1980notxt, 1981notxt, 1982notxt, 1983notxt, 1984notxt, 1985notxt, 1986notxt, 1987notxt, 1988notxt, 1989notxt, 1990notxt, 1991notxt, 1992notxt, 1993notxt, 1994notxt, 1995notxt, 1996notxt, 1997notxt, 1998notxt, 1999notxt, 2000notxt, 2001notxt, 2002notxt, 2003notxt, 2004notxt, 2005notxt, 2006notxt, 2007notxt, 2008notxt, 2009notxt, 2010notxt, 2011notxt, 2012notxt, 2013notxt, 2014notxt\n",
      "--------\n",
      "Dataset: sample_views\n",
      "Tables: actor_combinations_by_year, actor_combinations_top1_by_year, country_date_count, country_date_matconf_numarts, country_date_matconfbyactiongeo, country_date_matconfbyactionhumangeo, country_date_protest_numarts, export7, export8, urls1\n",
      "--------\n"
     ]
    }
   ],
   "source": [
    "# List all datasets and tables in the GDELT project\n",
    "datasets = list(client.list_datasets())\n",
    "\n",
    "# Iterate through each dataset and list its tables\n",
    "for dataset in datasets:\n",
    "    print(\"Dataset: {}\".format(dataset.dataset_id))\n",
    "    tables = list(client.list_tables(dataset))\n",
    "    table_names = [table.table_id for table in tables]\n",
    "    print(\"Tables: {}\\n--------\".format(\", \".join(table_names)))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16448677-5207-46e1-81c7-e5486a110874",
   "metadata": {},
   "source": [
    "### 2. Tables in the dataset.  \n",
    "There are two ways to check tables in a certain dataset, you can use either use the BigQuery client library directly or bigquery magic function `%%bigquery`. The magic function `%%bigquery` takes SQL as input and generate the pandas table directly.\n",
    "\n",
    "a. BigQuery client library"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "832bf9f9-402b-4e20-b7db-90d947f608a4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crosswalk_geocountrycodetohuman\n",
      "events\n",
      "events_partitioned\n"
     ]
    }
   ],
   "source": [
    "# Check specific dataset\n",
    "dataset_ref = client.dataset(\"full\")\n",
    "dataset = client.get_dataset(dataset_ref)\n",
    "tables = list(client.list_tables(dataset))\n",
    "for table in tables:  \n",
    "    print(table.table_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9fb1f908-7bc5-4481-90bc-d696f051e065",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\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>table_catalog</th>\n",
       "      <th>table_schema</th>\n",
       "      <th>table_name</th>\n",
       "      <th>table_type</th>\n",
       "      <th>is_insertable_into</th>\n",
       "      <th>is_typed</th>\n",
       "      <th>creation_time</th>\n",
       "      <th>base_table_catalog</th>\n",
       "      <th>base_table_schema</th>\n",
       "      <th>base_table_name</th>\n",
       "      <th>snapshot_time_ms</th>\n",
       "      <th>ddl</th>\n",
       "      <th>default_collation_name</th>\n",
       "      <th>upsert_stream_apply_watermark</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>BASE TABLE</td>\n",
       "      <td>YES</td>\n",
       "      <td>NO</td>\n",
       "      <td>2016-05-19 16:21:47.091000+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaT</td>\n",
       "      <td>CREATE TABLE `gdelt-bq.full.events`\\n(\\n  GLOB...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>crosswalk_geocountrycodetohuman</td>\n",
       "      <td>BASE TABLE</td>\n",
       "      <td>YES</td>\n",
       "      <td>NO</td>\n",
       "      <td>2014-07-18 00:35:19.687000+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaT</td>\n",
       "      <td>CREATE TABLE `gdelt-bq.full.crosswalk_geocount...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NaT</td>\n",
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       "    <tr>\n",
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       "      <td>full</td>\n",
       "      <td>events_partitioned</td>\n",
       "      <td>BASE TABLE</td>\n",
       "      <td>YES</td>\n",
       "      <td>NO</td>\n",
       "      <td>2016-05-20 15:56:23.559000+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaT</td>\n",
       "      <td>CREATE TABLE `gdelt-bq.full.events_partitioned...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "  table_catalog table_schema                       table_name  table_type  \\\n",
       "0      gdelt-bq         full                           events  BASE TABLE   \n",
       "1      gdelt-bq         full  crosswalk_geocountrycodetohuman  BASE TABLE   \n",
       "2      gdelt-bq         full               events_partitioned  BASE TABLE   \n",
       "\n",
       "  is_insertable_into is_typed                    creation_time  \\\n",
       "0                YES       NO 2016-05-19 16:21:47.091000+00:00   \n",
       "1                YES       NO 2014-07-18 00:35:19.687000+00:00   \n",
       "2                YES       NO 2016-05-20 15:56:23.559000+00:00   \n",
       "\n",
       "  base_table_catalog base_table_schema base_table_name snapshot_time_ms  \\\n",
       "0               None              None            None              NaT   \n",
       "1               None              None            None              NaT   \n",
       "2               None              None            None              NaT   \n",
       "\n",
       "                                                 ddl default_collation_name  \\\n",
       "0  CREATE TABLE `gdelt-bq.full.events`\\n(\\n  GLOB...                   NULL   \n",
       "1  CREATE TABLE `gdelt-bq.full.crosswalk_geocount...                   NULL   \n",
       "2  CREATE TABLE `gdelt-bq.full.events_partitioned...                   NULL   \n",
       "\n",
       "  upsert_stream_apply_watermark  \n",
       "0                           NaT  \n",
       "1                           NaT  \n",
       "2                           NaT  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Do not put project=\"gdelt-bq\" in since this create a new table\n",
    "client = bigquery.Client()\n",
    "sql = \"\"\"\n",
    "SELECT * FROM `gdelt-bq`.full.INFORMATION_SCHEMA.TABLES;\n",
    "\"\"\"\n",
    "table_df_1 = client.query(sql).to_dataframe()\n",
    "table_df_1.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef3a8033-42de-466c-a6b2-ab6f66efa3dd",
   "metadata": {},
   "source": [
    "b. magic function `%%bigquery`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1ec3b255-2f04-4ba8-97cd-abd61b236b28",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Query complete after 0.01s: 100%|██████████| 1/1 [00:00<00:00, 396.29query/s]                          \n",
      "Downloading: 100%|██████████| 3/3 [00:01<00:00,  2.37rows/s]\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>table_catalog</th>\n",
       "      <th>table_schema</th>\n",
       "      <th>table_name</th>\n",
       "      <th>table_type</th>\n",
       "      <th>is_insertable_into</th>\n",
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       "      <th>base_table_catalog</th>\n",
       "      <th>base_table_schema</th>\n",
       "      <th>base_table_name</th>\n",
       "      <th>snapshot_time_ms</th>\n",
       "      <th>ddl</th>\n",
       "      <th>default_collation_name</th>\n",
       "      <th>upsert_stream_apply_watermark</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
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       "      <td>NaT</td>\n",
       "      <td>CREATE TABLE `gdelt-bq.full.events`\\n(\\n  GLOB...</td>\n",
       "      <td>NULL</td>\n",
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       "    </tr>\n",
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       "      <th>1</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>crosswalk_geocountrycodetohuman</td>\n",
       "      <td>BASE TABLE</td>\n",
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       "      <td>2014-07-18 00:35:19.687000+00:00</td>\n",
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       "      <td>None</td>\n",
       "      <td>NaT</td>\n",
       "      <td>CREATE TABLE `gdelt-bq.full.crosswalk_geocount...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <td>full</td>\n",
       "      <td>events_partitioned</td>\n",
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       "      <td>2016-05-20 15:56:23.559000+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaT</td>\n",
       "      <td>CREATE TABLE `gdelt-bq.full.events_partitioned...</td>\n",
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       "      <td>NaT</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  table_catalog table_schema                       table_name  table_type  \\\n",
       "0      gdelt-bq         full                           events  BASE TABLE   \n",
       "1      gdelt-bq         full  crosswalk_geocountrycodetohuman  BASE TABLE   \n",
       "2      gdelt-bq         full               events_partitioned  BASE TABLE   \n",
       "\n",
       "  is_insertable_into is_typed                    creation_time  \\\n",
       "0                YES       NO 2016-05-19 16:21:47.091000+00:00   \n",
       "1                YES       NO 2014-07-18 00:35:19.687000+00:00   \n",
       "2                YES       NO 2016-05-20 15:56:23.559000+00:00   \n",
       "\n",
       "  base_table_catalog base_table_schema base_table_name snapshot_time_ms  \\\n",
       "0               None              None            None              NaT   \n",
       "1               None              None            None              NaT   \n",
       "2               None              None            None              NaT   \n",
       "\n",
       "                                                 ddl default_collation_name  \\\n",
       "0  CREATE TABLE `gdelt-bq.full.events`\\n(\\n  GLOB...                   NULL   \n",
       "1  CREATE TABLE `gdelt-bq.full.crosswalk_geocount...                   NULL   \n",
       "2  CREATE TABLE `gdelt-bq.full.events_partitioned...                   NULL   \n",
       "\n",
       "  upsert_stream_apply_watermark  \n",
       "0                           NaT  \n",
       "1                           NaT  \n",
       "2                           NaT  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%bigquery\n",
    "SELECT * FROM `gdelt-bq.full.INFORMATION_SCHEMA.TABLES`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "373bb662-8da3-4c62-b832-8ce47e335e56",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Query complete after 0.00s: 100%|██████████| 1/1 [00:00<00:00, 336.06query/s]                          \n",
      "Downloading: 100%|██████████| 3/3 [00:01<00:00,  2.61rows/s]\n"
     ]
    }
   ],
   "source": [
    "%%bigquery table_df_2\n",
    "SELECT * FROM `gdelt-bq.full.INFORMATION_SCHEMA.TABLES`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "462cffbe-d5ab-4b78-bbbb-0da192e05865",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>table_catalog</th>\n",
       "      <th>table_schema</th>\n",
       "      <th>table_name</th>\n",
       "      <th>table_type</th>\n",
       "      <th>is_insertable_into</th>\n",
       "      <th>is_typed</th>\n",
       "      <th>creation_time</th>\n",
       "      <th>base_table_catalog</th>\n",
       "      <th>base_table_schema</th>\n",
       "      <th>base_table_name</th>\n",
       "      <th>snapshot_time_ms</th>\n",
       "      <th>ddl</th>\n",
       "      <th>default_collation_name</th>\n",
       "      <th>upsert_stream_apply_watermark</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>BASE TABLE</td>\n",
       "      <td>YES</td>\n",
       "      <td>NO</td>\n",
       "      <td>2016-05-19 16:21:47.091000+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaT</td>\n",
       "      <td>CREATE TABLE `gdelt-bq.full.events`\\n(\\n  GLOB...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>crosswalk_geocountrycodetohuman</td>\n",
       "      <td>BASE TABLE</td>\n",
       "      <td>YES</td>\n",
       "      <td>NO</td>\n",
       "      <td>2014-07-18 00:35:19.687000+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaT</td>\n",
       "      <td>CREATE TABLE `gdelt-bq.full.crosswalk_geocount...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events_partitioned</td>\n",
       "      <td>BASE TABLE</td>\n",
       "      <td>YES</td>\n",
       "      <td>NO</td>\n",
       "      <td>2016-05-20 15:56:23.559000+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaT</td>\n",
       "      <td>CREATE TABLE `gdelt-bq.full.events_partitioned...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  table_catalog table_schema                       table_name  table_type  \\\n",
       "0      gdelt-bq         full                           events  BASE TABLE   \n",
       "1      gdelt-bq         full  crosswalk_geocountrycodetohuman  BASE TABLE   \n",
       "2      gdelt-bq         full               events_partitioned  BASE TABLE   \n",
       "\n",
       "  is_insertable_into is_typed                    creation_time  \\\n",
       "0                YES       NO 2016-05-19 16:21:47.091000+00:00   \n",
       "1                YES       NO 2014-07-18 00:35:19.687000+00:00   \n",
       "2                YES       NO 2016-05-20 15:56:23.559000+00:00   \n",
       "\n",
       "  base_table_catalog base_table_schema base_table_name snapshot_time_ms  \\\n",
       "0               None              None            None              NaT   \n",
       "1               None              None            None              NaT   \n",
       "2               None              None            None              NaT   \n",
       "\n",
       "                                                 ddl default_collation_name  \\\n",
       "0  CREATE TABLE `gdelt-bq.full.events`\\n(\\n  GLOB...                   NULL   \n",
       "1  CREATE TABLE `gdelt-bq.full.crosswalk_geocount...                   NULL   \n",
       "2  CREATE TABLE `gdelt-bq.full.events_partitioned...                   NULL   \n",
       "\n",
       "  upsert_stream_apply_watermark  \n",
       "0                           NaT  \n",
       "1                           NaT  \n",
       "2                           NaT  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# bigquery result saved to pandas table\n",
    "table_df_2.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f813209b-cd6d-42b2-b1dd-99de5f590f82",
   "metadata": {},
   "source": [
    "### 3. Columns in the table."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84ee7371-a7cd-475c-877a-6add6f815471",
   "metadata": {},
   "source": [
    "Bigquery magic functions can be used to check dataset schema."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5904859b-6906-4102-b331-3b5d77399fe5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Query complete after 0.00s: 100%|██████████| 1/1 [00:00<00:00, 426.90query/s]                          \n",
      "Downloading: 100%|██████████| 58/58 [00:01<00:00, 43.76rows/s]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>table_catalog</th>\n",
       "      <th>table_schema</th>\n",
       "      <th>table_name</th>\n",
       "      <th>column_name</th>\n",
       "      <th>ordinal_position</th>\n",
       "      <th>is_nullable</th>\n",
       "      <th>data_type</th>\n",
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       "      <th>is_system_defined</th>\n",
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       "      <th>collation_name</th>\n",
       "      <th>column_default</th>\n",
       "      <th>rounding_mode</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gdelt-bq</td>\n",
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       "      <td>events</td>\n",
       "      <td>SQLDATE</td>\n",
       "      <td>2</td>\n",
       "      <td>YES</td>\n",
       "      <td>INT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
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       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
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       "      <th>2</th>\n",
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       "      <th>3</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
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       "      <td>Year</td>\n",
       "      <td>4</td>\n",
       "      <td>YES</td>\n",
       "      <td>INT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>FractionDate</td>\n",
       "      <td>5</td>\n",
       "      <td>YES</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
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       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Code</td>\n",
       "      <td>6</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Name</td>\n",
       "      <td>7</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1CountryCode</td>\n",
       "      <td>8</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
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       "      <td>&lt;NA&gt;</td>\n",
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       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>gdelt-bq</td>\n",
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       "      <td>9</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1EthnicCode</td>\n",
       "      <td>10</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>gdelt-bq</td>\n",
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       "      <td>Actor1Religion1Code</td>\n",
       "      <td>11</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
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       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
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       "      <th>11</th>\n",
       "      <td>gdelt-bq</td>\n",
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       "      <td>Actor1Religion2Code</td>\n",
       "      <td>12</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
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       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>gdelt-bq</td>\n",
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       "      <td>events</td>\n",
       "      <td>Actor1Type1Code</td>\n",
       "      <td>13</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Type2Code</td>\n",
       "      <td>14</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Type3Code</td>\n",
       "      <td>15</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Code</td>\n",
       "      <td>16</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Name</td>\n",
       "      <td>17</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2CountryCode</td>\n",
       "      <td>18</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2KnownGroupCode</td>\n",
       "      <td>19</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2EthnicCode</td>\n",
       "      <td>20</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Religion1Code</td>\n",
       "      <td>21</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Religion2Code</td>\n",
       "      <td>22</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Type1Code</td>\n",
       "      <td>23</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Type2Code</td>\n",
       "      <td>24</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Type3Code</td>\n",
       "      <td>25</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>IsRootEvent</td>\n",
       "      <td>26</td>\n",
       "      <td>YES</td>\n",
       "      <td>INT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>EventCode</td>\n",
       "      <td>27</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>EventBaseCode</td>\n",
       "      <td>28</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>EventRootCode</td>\n",
       "      <td>29</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>QuadClass</td>\n",
       "      <td>30</td>\n",
       "      <td>YES</td>\n",
       "      <td>INT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>GoldsteinScale</td>\n",
       "      <td>31</td>\n",
       "      <td>YES</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>NumMentions</td>\n",
       "      <td>32</td>\n",
       "      <td>YES</td>\n",
       "      <td>INT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>NumSources</td>\n",
       "      <td>33</td>\n",
       "      <td>YES</td>\n",
       "      <td>INT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>NumArticles</td>\n",
       "      <td>34</td>\n",
       "      <td>YES</td>\n",
       "      <td>INT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>AvgTone</td>\n",
       "      <td>35</td>\n",
       "      <td>YES</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Geo_Type</td>\n",
       "      <td>36</td>\n",
       "      <td>YES</td>\n",
       "      <td>INT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Geo_FullName</td>\n",
       "      <td>37</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Geo_CountryCode</td>\n",
       "      <td>38</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Geo_ADM1Code</td>\n",
       "      <td>39</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Geo_Lat</td>\n",
       "      <td>40</td>\n",
       "      <td>YES</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Geo_Long</td>\n",
       "      <td>41</td>\n",
       "      <td>YES</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Geo_FeatureID</td>\n",
       "      <td>42</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Geo_Type</td>\n",
       "      <td>43</td>\n",
       "      <td>YES</td>\n",
       "      <td>INT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Geo_FullName</td>\n",
       "      <td>44</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Geo_CountryCode</td>\n",
       "      <td>45</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Geo_ADM1Code</td>\n",
       "      <td>46</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Geo_Lat</td>\n",
       "      <td>47</td>\n",
       "      <td>YES</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Geo_Long</td>\n",
       "      <td>48</td>\n",
       "      <td>YES</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Geo_FeatureID</td>\n",
       "      <td>49</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>ActionGeo_Type</td>\n",
       "      <td>50</td>\n",
       "      <td>YES</td>\n",
       "      <td>INT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>ActionGeo_FullName</td>\n",
       "      <td>51</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>ActionGeo_CountryCode</td>\n",
       "      <td>52</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>ActionGeo_ADM1Code</td>\n",
       "      <td>53</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>ActionGeo_Lat</td>\n",
       "      <td>54</td>\n",
       "      <td>YES</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>ActionGeo_Long</td>\n",
       "      <td>55</td>\n",
       "      <td>YES</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>ActionGeo_FeatureID</td>\n",
       "      <td>56</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>DATEADDED</td>\n",
       "      <td>57</td>\n",
       "      <td>YES</td>\n",
       "      <td>INT64</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>SOURCEURL</td>\n",
       "      <td>58</td>\n",
       "      <td>YES</td>\n",
       "      <td>STRING</td>\n",
       "      <td>NEVER</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>None</td>\n",
       "      <td>NO</td>\n",
       "      <td>NO</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NULL</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   table_catalog table_schema table_name            column_name  \\\n",
       "0       gdelt-bq         full     events          GLOBALEVENTID   \n",
       "1       gdelt-bq         full     events                SQLDATE   \n",
       "2       gdelt-bq         full     events              MonthYear   \n",
       "3       gdelt-bq         full     events                   Year   \n",
       "4       gdelt-bq         full     events           FractionDate   \n",
       "5       gdelt-bq         full     events             Actor1Code   \n",
       "6       gdelt-bq         full     events             Actor1Name   \n",
       "7       gdelt-bq         full     events      Actor1CountryCode   \n",
       "8       gdelt-bq         full     events   Actor1KnownGroupCode   \n",
       "9       gdelt-bq         full     events       Actor1EthnicCode   \n",
       "10      gdelt-bq         full     events    Actor1Religion1Code   \n",
       "11      gdelt-bq         full     events    Actor1Religion2Code   \n",
       "12      gdelt-bq         full     events        Actor1Type1Code   \n",
       "13      gdelt-bq         full     events        Actor1Type2Code   \n",
       "14      gdelt-bq         full     events        Actor1Type3Code   \n",
       "15      gdelt-bq         full     events             Actor2Code   \n",
       "16      gdelt-bq         full     events             Actor2Name   \n",
       "17      gdelt-bq         full     events      Actor2CountryCode   \n",
       "18      gdelt-bq         full     events   Actor2KnownGroupCode   \n",
       "19      gdelt-bq         full     events       Actor2EthnicCode   \n",
       "20      gdelt-bq         full     events    Actor2Religion1Code   \n",
       "21      gdelt-bq         full     events    Actor2Religion2Code   \n",
       "22      gdelt-bq         full     events        Actor2Type1Code   \n",
       "23      gdelt-bq         full     events        Actor2Type2Code   \n",
       "24      gdelt-bq         full     events        Actor2Type3Code   \n",
       "25      gdelt-bq         full     events            IsRootEvent   \n",
       "26      gdelt-bq         full     events              EventCode   \n",
       "27      gdelt-bq         full     events          EventBaseCode   \n",
       "28      gdelt-bq         full     events          EventRootCode   \n",
       "29      gdelt-bq         full     events              QuadClass   \n",
       "30      gdelt-bq         full     events         GoldsteinScale   \n",
       "31      gdelt-bq         full     events            NumMentions   \n",
       "32      gdelt-bq         full     events             NumSources   \n",
       "33      gdelt-bq         full     events            NumArticles   \n",
       "34      gdelt-bq         full     events                AvgTone   \n",
       "35      gdelt-bq         full     events         Actor1Geo_Type   \n",
       "36      gdelt-bq         full     events     Actor1Geo_FullName   \n",
       "37      gdelt-bq         full     events  Actor1Geo_CountryCode   \n",
       "38      gdelt-bq         full     events     Actor1Geo_ADM1Code   \n",
       "39      gdelt-bq         full     events          Actor1Geo_Lat   \n",
       "40      gdelt-bq         full     events         Actor1Geo_Long   \n",
       "41      gdelt-bq         full     events    Actor1Geo_FeatureID   \n",
       "42      gdelt-bq         full     events         Actor2Geo_Type   \n",
       "43      gdelt-bq         full     events     Actor2Geo_FullName   \n",
       "44      gdelt-bq         full     events  Actor2Geo_CountryCode   \n",
       "45      gdelt-bq         full     events     Actor2Geo_ADM1Code   \n",
       "46      gdelt-bq         full     events          Actor2Geo_Lat   \n",
       "47      gdelt-bq         full     events         Actor2Geo_Long   \n",
       "48      gdelt-bq         full     events    Actor2Geo_FeatureID   \n",
       "49      gdelt-bq         full     events         ActionGeo_Type   \n",
       "50      gdelt-bq         full     events     ActionGeo_FullName   \n",
       "51      gdelt-bq         full     events  ActionGeo_CountryCode   \n",
       "52      gdelt-bq         full     events     ActionGeo_ADM1Code   \n",
       "53      gdelt-bq         full     events          ActionGeo_Lat   \n",
       "54      gdelt-bq         full     events         ActionGeo_Long   \n",
       "55      gdelt-bq         full     events    ActionGeo_FeatureID   \n",
       "56      gdelt-bq         full     events              DATEADDED   \n",
       "57      gdelt-bq         full     events              SOURCEURL   \n",
       "\n",
       "    ordinal_position is_nullable data_type is_generated generation_expression  \\\n",
       "0                  1         YES     INT64        NEVER                  None   \n",
       "1                  2         YES     INT64        NEVER                  None   \n",
       "2                  3         YES     INT64        NEVER                  None   \n",
       "3                  4         YES     INT64        NEVER                  None   \n",
       "4                  5         YES   FLOAT64        NEVER                  None   \n",
       "5                  6         YES    STRING        NEVER                  None   \n",
       "6                  7         YES    STRING        NEVER                  None   \n",
       "7                  8         YES    STRING        NEVER                  None   \n",
       "8                  9         YES    STRING        NEVER                  None   \n",
       "9                 10         YES    STRING        NEVER                  None   \n",
       "10                11         YES    STRING        NEVER                  None   \n",
       "11                12         YES    STRING        NEVER                  None   \n",
       "12                13         YES    STRING        NEVER                  None   \n",
       "13                14         YES    STRING        NEVER                  None   \n",
       "14                15         YES    STRING        NEVER                  None   \n",
       "15                16         YES    STRING        NEVER                  None   \n",
       "16                17         YES    STRING        NEVER                  None   \n",
       "17                18         YES    STRING        NEVER                  None   \n",
       "18                19         YES    STRING        NEVER                  None   \n",
       "19                20         YES    STRING        NEVER                  None   \n",
       "20                21         YES    STRING        NEVER                  None   \n",
       "21                22         YES    STRING        NEVER                  None   \n",
       "22                23         YES    STRING        NEVER                  None   \n",
       "23                24         YES    STRING        NEVER                  None   \n",
       "24                25         YES    STRING        NEVER                  None   \n",
       "25                26         YES     INT64        NEVER                  None   \n",
       "26                27         YES    STRING        NEVER                  None   \n",
       "27                28         YES    STRING        NEVER                  None   \n",
       "28                29         YES    STRING        NEVER                  None   \n",
       "29                30         YES     INT64        NEVER                  None   \n",
       "30                31         YES   FLOAT64        NEVER                  None   \n",
       "31                32         YES     INT64        NEVER                  None   \n",
       "32                33         YES     INT64        NEVER                  None   \n",
       "33                34         YES     INT64        NEVER                  None   \n",
       "34                35         YES   FLOAT64        NEVER                  None   \n",
       "35                36         YES     INT64        NEVER                  None   \n",
       "36                37         YES    STRING        NEVER                  None   \n",
       "37                38         YES    STRING        NEVER                  None   \n",
       "38                39         YES    STRING        NEVER                  None   \n",
       "39                40         YES   FLOAT64        NEVER                  None   \n",
       "40                41         YES   FLOAT64        NEVER                  None   \n",
       "41                42         YES    STRING        NEVER                  None   \n",
       "42                43         YES     INT64        NEVER                  None   \n",
       "43                44         YES    STRING        NEVER                  None   \n",
       "44                45         YES    STRING        NEVER                  None   \n",
       "45                46         YES    STRING        NEVER                  None   \n",
       "46                47         YES   FLOAT64        NEVER                  None   \n",
       "47                48         YES   FLOAT64        NEVER                  None   \n",
       "48                49         YES    STRING        NEVER                  None   \n",
       "49                50         YES     INT64        NEVER                  None   \n",
       "50                51         YES    STRING        NEVER                  None   \n",
       "51                52         YES    STRING        NEVER                  None   \n",
       "52                53         YES    STRING        NEVER                  None   \n",
       "53                54         YES   FLOAT64        NEVER                  None   \n",
       "54                55         YES   FLOAT64        NEVER                  None   \n",
       "55                56         YES    STRING        NEVER                  None   \n",
       "56                57         YES     INT64        NEVER                  None   \n",
       "57                58         YES    STRING        NEVER                  None   \n",
       "\n",
       "   is_stored is_hidden is_updatable is_system_defined is_partitioning_column  \\\n",
       "0       None        NO         None                NO                     NO   \n",
       "1       None        NO         None                NO                     NO   \n",
       "2       None        NO         None                NO                     NO   \n",
       "3       None        NO         None                NO                     NO   \n",
       "4       None        NO         None                NO                     NO   \n",
       "5       None        NO         None                NO                     NO   \n",
       "6       None        NO         None                NO                     NO   \n",
       "7       None        NO         None                NO                     NO   \n",
       "8       None        NO         None                NO                     NO   \n",
       "9       None        NO         None                NO                     NO   \n",
       "10      None        NO         None                NO                     NO   \n",
       "11      None        NO         None                NO                     NO   \n",
       "12      None        NO         None                NO                     NO   \n",
       "13      None        NO         None                NO                     NO   \n",
       "14      None        NO         None                NO                     NO   \n",
       "15      None        NO         None                NO                     NO   \n",
       "16      None        NO         None                NO                     NO   \n",
       "17      None        NO         None                NO                     NO   \n",
       "18      None        NO         None                NO                     NO   \n",
       "19      None        NO         None                NO                     NO   \n",
       "20      None        NO         None                NO                     NO   \n",
       "21      None        NO         None                NO                     NO   \n",
       "22      None        NO         None                NO                     NO   \n",
       "23      None        NO         None                NO                     NO   \n",
       "24      None        NO         None                NO                     NO   \n",
       "25      None        NO         None                NO                     NO   \n",
       "26      None        NO         None                NO                     NO   \n",
       "27      None        NO         None                NO                     NO   \n",
       "28      None        NO         None                NO                     NO   \n",
       "29      None        NO         None                NO                     NO   \n",
       "30      None        NO         None                NO                     NO   \n",
       "31      None        NO         None                NO                     NO   \n",
       "32      None        NO         None                NO                     NO   \n",
       "33      None        NO         None                NO                     NO   \n",
       "34      None        NO         None                NO                     NO   \n",
       "35      None        NO         None                NO                     NO   \n",
       "36      None        NO         None                NO                     NO   \n",
       "37      None        NO         None                NO                     NO   \n",
       "38      None        NO         None                NO                     NO   \n",
       "39      None        NO         None                NO                     NO   \n",
       "40      None        NO         None                NO                     NO   \n",
       "41      None        NO         None                NO                     NO   \n",
       "42      None        NO         None                NO                     NO   \n",
       "43      None        NO         None                NO                     NO   \n",
       "44      None        NO         None                NO                     NO   \n",
       "45      None        NO         None                NO                     NO   \n",
       "46      None        NO         None                NO                     NO   \n",
       "47      None        NO         None                NO                     NO   \n",
       "48      None        NO         None                NO                     NO   \n",
       "49      None        NO         None                NO                     NO   \n",
       "50      None        NO         None                NO                     NO   \n",
       "51      None        NO         None                NO                     NO   \n",
       "52      None        NO         None                NO                     NO   \n",
       "53      None        NO         None                NO                     NO   \n",
       "54      None        NO         None                NO                     NO   \n",
       "55      None        NO         None                NO                     NO   \n",
       "56      None        NO         None                NO                     NO   \n",
       "57      None        NO         None                NO                     NO   \n",
       "\n",
       "    clustering_ordinal_position collation_name column_default rounding_mode  \n",
       "0                          <NA>           NULL           NULL          None  \n",
       "1                          <NA>           NULL           NULL          None  \n",
       "2                          <NA>           NULL           NULL          None  \n",
       "3                          <NA>           NULL           NULL          None  \n",
       "4                          <NA>           NULL           NULL          None  \n",
       "5                          <NA>           NULL           NULL          None  \n",
       "6                          <NA>           NULL           NULL          None  \n",
       "7                          <NA>           NULL           NULL          None  \n",
       "8                          <NA>           NULL           NULL          None  \n",
       "9                          <NA>           NULL           NULL          None  \n",
       "10                         <NA>           NULL           NULL          None  \n",
       "11                         <NA>           NULL           NULL          None  \n",
       "12                         <NA>           NULL           NULL          None  \n",
       "13                         <NA>           NULL           NULL          None  \n",
       "14                         <NA>           NULL           NULL          None  \n",
       "15                         <NA>           NULL           NULL          None  \n",
       "16                         <NA>           NULL           NULL          None  \n",
       "17                         <NA>           NULL           NULL          None  \n",
       "18                         <NA>           NULL           NULL          None  \n",
       "19                         <NA>           NULL           NULL          None  \n",
       "20                         <NA>           NULL           NULL          None  \n",
       "21                         <NA>           NULL           NULL          None  \n",
       "22                         <NA>           NULL           NULL          None  \n",
       "23                         <NA>           NULL           NULL          None  \n",
       "24                         <NA>           NULL           NULL          None  \n",
       "25                         <NA>           NULL           NULL          None  \n",
       "26                         <NA>           NULL           NULL          None  \n",
       "27                         <NA>           NULL           NULL          None  \n",
       "28                         <NA>           NULL           NULL          None  \n",
       "29                         <NA>           NULL           NULL          None  \n",
       "30                         <NA>           NULL           NULL          None  \n",
       "31                         <NA>           NULL           NULL          None  \n",
       "32                         <NA>           NULL           NULL          None  \n",
       "33                         <NA>           NULL           NULL          None  \n",
       "34                         <NA>           NULL           NULL          None  \n",
       "35                         <NA>           NULL           NULL          None  \n",
       "36                         <NA>           NULL           NULL          None  \n",
       "37                         <NA>           NULL           NULL          None  \n",
       "38                         <NA>           NULL           NULL          None  \n",
       "39                         <NA>           NULL           NULL          None  \n",
       "40                         <NA>           NULL           NULL          None  \n",
       "41                         <NA>           NULL           NULL          None  \n",
       "42                         <NA>           NULL           NULL          None  \n",
       "43                         <NA>           NULL           NULL          None  \n",
       "44                         <NA>           NULL           NULL          None  \n",
       "45                         <NA>           NULL           NULL          None  \n",
       "46                         <NA>           NULL           NULL          None  \n",
       "47                         <NA>           NULL           NULL          None  \n",
       "48                         <NA>           NULL           NULL          None  \n",
       "49                         <NA>           NULL           NULL          None  \n",
       "50                         <NA>           NULL           NULL          None  \n",
       "51                         <NA>           NULL           NULL          None  \n",
       "52                         <NA>           NULL           NULL          None  \n",
       "53                         <NA>           NULL           NULL          None  \n",
       "54                         <NA>           NULL           NULL          None  \n",
       "55                         <NA>           NULL           NULL          None  \n",
       "56                         <NA>           NULL           NULL          None  \n",
       "57                         <NA>           NULL           NULL          None  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%bigquery\n",
    "SELECT * FROM `gdelt-bq.full.INFORMATION_SCHEMA.COLUMNS`\n",
    "WHERE table_name = 'events';"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d96be092-0ed4-43da-9458-f61e634e6f76",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Query complete after 0.00s: 100%|██████████| 1/1 [00:00<00:00, 395.61query/s]                          \n",
      "Downloading: 100%|██████████| 58/58 [00:01<00:00, 42.96rows/s]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>table_catalog</th>\n",
       "      <th>table_schema</th>\n",
       "      <th>table_name</th>\n",
       "      <th>column_name</th>\n",
       "      <th>field_path</th>\n",
       "      <th>data_type</th>\n",
       "      <th>description</th>\n",
       "      <th>collation_name</th>\n",
       "      <th>rounding_mode</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>GLOBALEVENTID</td>\n",
       "      <td>GLOBALEVENTID</td>\n",
       "      <td>INT64</td>\n",
       "      <td>Unique ID for each event</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>SQLDATE</td>\n",
       "      <td>SQLDATE</td>\n",
       "      <td>INT64</td>\n",
       "      <td>Date the event took place in YYYYMMDD format</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>MonthYear</td>\n",
       "      <td>MonthYear</td>\n",
       "      <td>INT64</td>\n",
       "      <td>Alternative formatting of the event date, in Y...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Year</td>\n",
       "      <td>Year</td>\n",
       "      <td>INT64</td>\n",
       "      <td>Alternative formatting of the event date, in Y...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>FractionDate</td>\n",
       "      <td>FractionDate</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>Alternative formatting of the event date, comp...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Code</td>\n",
       "      <td>Actor1Code</td>\n",
       "      <td>STRING</td>\n",
       "      <td>The complete raw CAMEO code for Actor1 (includ...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Name</td>\n",
       "      <td>Actor1Name</td>\n",
       "      <td>STRING</td>\n",
       "      <td>The actual name of the Actor 1. In the case of...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1CountryCode</td>\n",
       "      <td>Actor1CountryCode</td>\n",
       "      <td>STRING</td>\n",
       "      <td>The 3-character CAMEO code for the country aff...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1KnownGroupCode</td>\n",
       "      <td>Actor1KnownGroupCode</td>\n",
       "      <td>STRING</td>\n",
       "      <td>If Actor1 is a known IGO/NGO/rebel organizatio...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1EthnicCode</td>\n",
       "      <td>Actor1EthnicCode</td>\n",
       "      <td>STRING</td>\n",
       "      <td>If the source document specifies the ethnic af...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Religion1Code</td>\n",
       "      <td>Actor1Religion1Code</td>\n",
       "      <td>STRING</td>\n",
       "      <td>If the source document specifies the religious...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Religion2Code</td>\n",
       "      <td>Actor1Religion2Code</td>\n",
       "      <td>STRING</td>\n",
       "      <td>If multiple religious codes are specified for ...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Type1Code</td>\n",
       "      <td>Actor1Type1Code</td>\n",
       "      <td>STRING</td>\n",
       "      <td>The 3-character CAMEO code of the CAMEO “type”...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Type2Code</td>\n",
       "      <td>Actor1Type2Code</td>\n",
       "      <td>STRING</td>\n",
       "      <td>If multiple type/role codes are specified for ...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Type3Code</td>\n",
       "      <td>Actor1Type3Code</td>\n",
       "      <td>STRING</td>\n",
       "      <td>If multiple type/role codes are specified for ...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Code</td>\n",
       "      <td>Actor2Code</td>\n",
       "      <td>STRING</td>\n",
       "      <td>The complete raw CAMEO code for Actor2 (includ...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Name</td>\n",
       "      <td>Actor2Name</td>\n",
       "      <td>STRING</td>\n",
       "      <td>The actual name of the Actor2. In the case of ...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2CountryCode</td>\n",
       "      <td>Actor2CountryCode</td>\n",
       "      <td>STRING</td>\n",
       "      <td>The 3-character CAMEO code for the country aff...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2KnownGroupCode</td>\n",
       "      <td>Actor2KnownGroupCode</td>\n",
       "      <td>STRING</td>\n",
       "      <td>If Actor2 is a known IGO/NGO/rebel organizatio...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2EthnicCode</td>\n",
       "      <td>Actor2EthnicCode</td>\n",
       "      <td>STRING</td>\n",
       "      <td>If the source document specifies the ethnic af...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Religion1Code</td>\n",
       "      <td>Actor2Religion1Code</td>\n",
       "      <td>STRING</td>\n",
       "      <td>If the source document specifies the religious...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Religion2Code</td>\n",
       "      <td>Actor2Religion2Code</td>\n",
       "      <td>STRING</td>\n",
       "      <td>If multiple religious codes are specified for ...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Type1Code</td>\n",
       "      <td>Actor2Type1Code</td>\n",
       "      <td>STRING</td>\n",
       "      <td>The 3-character CAMEO code of the CAMEO “type”...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Type2Code</td>\n",
       "      <td>Actor2Type2Code</td>\n",
       "      <td>STRING</td>\n",
       "      <td>If multiple type/role codes are specified for ...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Type3Code</td>\n",
       "      <td>Actor2Type3Code</td>\n",
       "      <td>STRING</td>\n",
       "      <td>If multiple type/role codes are specified for ...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>IsRootEvent</td>\n",
       "      <td>IsRootEvent</td>\n",
       "      <td>INT64</td>\n",
       "      <td>The system codes every event found in an entir...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>EventCode</td>\n",
       "      <td>EventCode</td>\n",
       "      <td>STRING</td>\n",
       "      <td>This is the raw CAMEO action code describing t...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>EventBaseCode</td>\n",
       "      <td>EventBaseCode</td>\n",
       "      <td>STRING</td>\n",
       "      <td>CAMEO event codes are defined in a three-level...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>EventRootCode</td>\n",
       "      <td>EventRootCode</td>\n",
       "      <td>STRING</td>\n",
       "      <td>Similar to EventBaseCode, this defines the roo...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>QuadClass</td>\n",
       "      <td>QuadClass</td>\n",
       "      <td>INT64</td>\n",
       "      <td>The entire CAMEO event taxonomy is ultimately ...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>GoldsteinScale</td>\n",
       "      <td>GoldsteinScale</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>Each CAMEO event code is assigned a numeric sc...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>NumMentions</td>\n",
       "      <td>NumMentions</td>\n",
       "      <td>INT64</td>\n",
       "      <td>This is the total number of mentions of this e...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>NumSources</td>\n",
       "      <td>NumSources</td>\n",
       "      <td>INT64</td>\n",
       "      <td>This is the total number of information source...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>NumArticles</td>\n",
       "      <td>NumArticles</td>\n",
       "      <td>INT64</td>\n",
       "      <td>This is the total number of source documents c...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>AvgTone</td>\n",
       "      <td>AvgTone</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>This is the average “tone” of all documents co...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Geo_Type</td>\n",
       "      <td>Actor1Geo_Type</td>\n",
       "      <td>INT64</td>\n",
       "      <td>Location of Actor1.  This field specifies the ...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Geo_FullName</td>\n",
       "      <td>Actor1Geo_FullName</td>\n",
       "      <td>STRING</td>\n",
       "      <td>Location of Actor1.  This is the full human-re...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Geo_CountryCode</td>\n",
       "      <td>Actor1Geo_CountryCode</td>\n",
       "      <td>STRING</td>\n",
       "      <td>Location of Actor1.  This is the 2-character F...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Geo_ADM1Code</td>\n",
       "      <td>Actor1Geo_ADM1Code</td>\n",
       "      <td>STRING</td>\n",
       "      <td>Location of Actor1.  This is the 2-character F...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Geo_Lat</td>\n",
       "      <td>Actor1Geo_Lat</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>Location of Actor1.  This is the centroid lati...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Geo_Long</td>\n",
       "      <td>Actor1Geo_Long</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>Location of Actor1.  This is the centroid long...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor1Geo_FeatureID</td>\n",
       "      <td>Actor1Geo_FeatureID</td>\n",
       "      <td>STRING</td>\n",
       "      <td>Location of Actor1.  This is the GNS or GNIS F...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Geo_Type</td>\n",
       "      <td>Actor2Geo_Type</td>\n",
       "      <td>INT64</td>\n",
       "      <td>Location of Actor2.  This field specifies the ...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Geo_FullName</td>\n",
       "      <td>Actor2Geo_FullName</td>\n",
       "      <td>STRING</td>\n",
       "      <td>Location of Actor2.  This is the full human-re...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Geo_CountryCode</td>\n",
       "      <td>Actor2Geo_CountryCode</td>\n",
       "      <td>STRING</td>\n",
       "      <td>Location of Actor2.  This is the 2-character F...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Geo_ADM1Code</td>\n",
       "      <td>Actor2Geo_ADM1Code</td>\n",
       "      <td>STRING</td>\n",
       "      <td>Location of Actor2.  This is the 2-character F...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Geo_Lat</td>\n",
       "      <td>Actor2Geo_Lat</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>Location of Actor2.  This is the centroid lati...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Geo_Long</td>\n",
       "      <td>Actor2Geo_Long</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>Location of Actor2.  This is the centroid long...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>Actor2Geo_FeatureID</td>\n",
       "      <td>Actor2Geo_FeatureID</td>\n",
       "      <td>STRING</td>\n",
       "      <td>Location of Actor2.  This is the GNS or GNIS F...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>ActionGeo_Type</td>\n",
       "      <td>ActionGeo_Type</td>\n",
       "      <td>INT64</td>\n",
       "      <td>Location of Event.  This field specifies the g...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>ActionGeo_FullName</td>\n",
       "      <td>ActionGeo_FullName</td>\n",
       "      <td>STRING</td>\n",
       "      <td>Location of Event.  This is the full human-rea...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>ActionGeo_CountryCode</td>\n",
       "      <td>ActionGeo_CountryCode</td>\n",
       "      <td>STRING</td>\n",
       "      <td>Location of Event.  This is the 2-character FI...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>ActionGeo_ADM1Code</td>\n",
       "      <td>ActionGeo_ADM1Code</td>\n",
       "      <td>STRING</td>\n",
       "      <td>Location of Event.  This is the 2-character FI...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>ActionGeo_Lat</td>\n",
       "      <td>ActionGeo_Lat</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>Location of Event.  This is the centroid latit...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>ActionGeo_Long</td>\n",
       "      <td>ActionGeo_Long</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>Location of Event.  This is the centroid longi...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>ActionGeo_FeatureID</td>\n",
       "      <td>ActionGeo_FeatureID</td>\n",
       "      <td>STRING</td>\n",
       "      <td>Location of Event.  This is the GNS or GNIS Fe...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>DATEADDED</td>\n",
       "      <td>DATEADDED</td>\n",
       "      <td>INT64</td>\n",
       "      <td>This field stores the date the event was added...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>full</td>\n",
       "      <td>events</td>\n",
       "      <td>SOURCEURL</td>\n",
       "      <td>SOURCEURL</td>\n",
       "      <td>STRING</td>\n",
       "      <td>This field is only present in the daily event ...</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   table_catalog table_schema table_name            column_name  \\\n",
       "0       gdelt-bq         full     events          GLOBALEVENTID   \n",
       "1       gdelt-bq         full     events                SQLDATE   \n",
       "2       gdelt-bq         full     events              MonthYear   \n",
       "3       gdelt-bq         full     events                   Year   \n",
       "4       gdelt-bq         full     events           FractionDate   \n",
       "5       gdelt-bq         full     events             Actor1Code   \n",
       "6       gdelt-bq         full     events             Actor1Name   \n",
       "7       gdelt-bq         full     events      Actor1CountryCode   \n",
       "8       gdelt-bq         full     events   Actor1KnownGroupCode   \n",
       "9       gdelt-bq         full     events       Actor1EthnicCode   \n",
       "10      gdelt-bq         full     events    Actor1Religion1Code   \n",
       "11      gdelt-bq         full     events    Actor1Religion2Code   \n",
       "12      gdelt-bq         full     events        Actor1Type1Code   \n",
       "13      gdelt-bq         full     events        Actor1Type2Code   \n",
       "14      gdelt-bq         full     events        Actor1Type3Code   \n",
       "15      gdelt-bq         full     events             Actor2Code   \n",
       "16      gdelt-bq         full     events             Actor2Name   \n",
       "17      gdelt-bq         full     events      Actor2CountryCode   \n",
       "18      gdelt-bq         full     events   Actor2KnownGroupCode   \n",
       "19      gdelt-bq         full     events       Actor2EthnicCode   \n",
       "20      gdelt-bq         full     events    Actor2Religion1Code   \n",
       "21      gdelt-bq         full     events    Actor2Religion2Code   \n",
       "22      gdelt-bq         full     events        Actor2Type1Code   \n",
       "23      gdelt-bq         full     events        Actor2Type2Code   \n",
       "24      gdelt-bq         full     events        Actor2Type3Code   \n",
       "25      gdelt-bq         full     events            IsRootEvent   \n",
       "26      gdelt-bq         full     events              EventCode   \n",
       "27      gdelt-bq         full     events          EventBaseCode   \n",
       "28      gdelt-bq         full     events          EventRootCode   \n",
       "29      gdelt-bq         full     events              QuadClass   \n",
       "30      gdelt-bq         full     events         GoldsteinScale   \n",
       "31      gdelt-bq         full     events            NumMentions   \n",
       "32      gdelt-bq         full     events             NumSources   \n",
       "33      gdelt-bq         full     events            NumArticles   \n",
       "34      gdelt-bq         full     events                AvgTone   \n",
       "35      gdelt-bq         full     events         Actor1Geo_Type   \n",
       "36      gdelt-bq         full     events     Actor1Geo_FullName   \n",
       "37      gdelt-bq         full     events  Actor1Geo_CountryCode   \n",
       "38      gdelt-bq         full     events     Actor1Geo_ADM1Code   \n",
       "39      gdelt-bq         full     events          Actor1Geo_Lat   \n",
       "40      gdelt-bq         full     events         Actor1Geo_Long   \n",
       "41      gdelt-bq         full     events    Actor1Geo_FeatureID   \n",
       "42      gdelt-bq         full     events         Actor2Geo_Type   \n",
       "43      gdelt-bq         full     events     Actor2Geo_FullName   \n",
       "44      gdelt-bq         full     events  Actor2Geo_CountryCode   \n",
       "45      gdelt-bq         full     events     Actor2Geo_ADM1Code   \n",
       "46      gdelt-bq         full     events          Actor2Geo_Lat   \n",
       "47      gdelt-bq         full     events         Actor2Geo_Long   \n",
       "48      gdelt-bq         full     events    Actor2Geo_FeatureID   \n",
       "49      gdelt-bq         full     events         ActionGeo_Type   \n",
       "50      gdelt-bq         full     events     ActionGeo_FullName   \n",
       "51      gdelt-bq         full     events  ActionGeo_CountryCode   \n",
       "52      gdelt-bq         full     events     ActionGeo_ADM1Code   \n",
       "53      gdelt-bq         full     events          ActionGeo_Lat   \n",
       "54      gdelt-bq         full     events         ActionGeo_Long   \n",
       "55      gdelt-bq         full     events    ActionGeo_FeatureID   \n",
       "56      gdelt-bq         full     events              DATEADDED   \n",
       "57      gdelt-bq         full     events              SOURCEURL   \n",
       "\n",
       "               field_path data_type  \\\n",
       "0           GLOBALEVENTID     INT64   \n",
       "1                 SQLDATE     INT64   \n",
       "2               MonthYear     INT64   \n",
       "3                    Year     INT64   \n",
       "4            FractionDate   FLOAT64   \n",
       "5              Actor1Code    STRING   \n",
       "6              Actor1Name    STRING   \n",
       "7       Actor1CountryCode    STRING   \n",
       "8    Actor1KnownGroupCode    STRING   \n",
       "9        Actor1EthnicCode    STRING   \n",
       "10    Actor1Religion1Code    STRING   \n",
       "11    Actor1Religion2Code    STRING   \n",
       "12        Actor1Type1Code    STRING   \n",
       "13        Actor1Type2Code    STRING   \n",
       "14        Actor1Type3Code    STRING   \n",
       "15             Actor2Code    STRING   \n",
       "16             Actor2Name    STRING   \n",
       "17      Actor2CountryCode    STRING   \n",
       "18   Actor2KnownGroupCode    STRING   \n",
       "19       Actor2EthnicCode    STRING   \n",
       "20    Actor2Religion1Code    STRING   \n",
       "21    Actor2Religion2Code    STRING   \n",
       "22        Actor2Type1Code    STRING   \n",
       "23        Actor2Type2Code    STRING   \n",
       "24        Actor2Type3Code    STRING   \n",
       "25            IsRootEvent     INT64   \n",
       "26              EventCode    STRING   \n",
       "27          EventBaseCode    STRING   \n",
       "28          EventRootCode    STRING   \n",
       "29              QuadClass     INT64   \n",
       "30         GoldsteinScale   FLOAT64   \n",
       "31            NumMentions     INT64   \n",
       "32             NumSources     INT64   \n",
       "33            NumArticles     INT64   \n",
       "34                AvgTone   FLOAT64   \n",
       "35         Actor1Geo_Type     INT64   \n",
       "36     Actor1Geo_FullName    STRING   \n",
       "37  Actor1Geo_CountryCode    STRING   \n",
       "38     Actor1Geo_ADM1Code    STRING   \n",
       "39          Actor1Geo_Lat   FLOAT64   \n",
       "40         Actor1Geo_Long   FLOAT64   \n",
       "41    Actor1Geo_FeatureID    STRING   \n",
       "42         Actor2Geo_Type     INT64   \n",
       "43     Actor2Geo_FullName    STRING   \n",
       "44  Actor2Geo_CountryCode    STRING   \n",
       "45     Actor2Geo_ADM1Code    STRING   \n",
       "46          Actor2Geo_Lat   FLOAT64   \n",
       "47         Actor2Geo_Long   FLOAT64   \n",
       "48    Actor2Geo_FeatureID    STRING   \n",
       "49         ActionGeo_Type     INT64   \n",
       "50     ActionGeo_FullName    STRING   \n",
       "51  ActionGeo_CountryCode    STRING   \n",
       "52     ActionGeo_ADM1Code    STRING   \n",
       "53          ActionGeo_Lat   FLOAT64   \n",
       "54         ActionGeo_Long   FLOAT64   \n",
       "55    ActionGeo_FeatureID    STRING   \n",
       "56              DATEADDED     INT64   \n",
       "57              SOURCEURL    STRING   \n",
       "\n",
       "                                          description collation_name  \\\n",
       "0                            Unique ID for each event           NULL   \n",
       "1        Date the event took place in YYYYMMDD format           NULL   \n",
       "2   Alternative formatting of the event date, in Y...           NULL   \n",
       "3   Alternative formatting of the event date, in Y...           NULL   \n",
       "4   Alternative formatting of the event date, comp...           NULL   \n",
       "5   The complete raw CAMEO code for Actor1 (includ...           NULL   \n",
       "6   The actual name of the Actor 1. In the case of...           NULL   \n",
       "7   The 3-character CAMEO code for the country aff...           NULL   \n",
       "8   If Actor1 is a known IGO/NGO/rebel organizatio...           NULL   \n",
       "9   If the source document specifies the ethnic af...           NULL   \n",
       "10  If the source document specifies the religious...           NULL   \n",
       "11  If multiple religious codes are specified for ...           NULL   \n",
       "12  The 3-character CAMEO code of the CAMEO “type”...           NULL   \n",
       "13  If multiple type/role codes are specified for ...           NULL   \n",
       "14  If multiple type/role codes are specified for ...           NULL   \n",
       "15  The complete raw CAMEO code for Actor2 (includ...           NULL   \n",
       "16  The actual name of the Actor2. In the case of ...           NULL   \n",
       "17  The 3-character CAMEO code for the country aff...           NULL   \n",
       "18  If Actor2 is a known IGO/NGO/rebel organizatio...           NULL   \n",
       "19  If the source document specifies the ethnic af...           NULL   \n",
       "20  If the source document specifies the religious...           NULL   \n",
       "21  If multiple religious codes are specified for ...           NULL   \n",
       "22  The 3-character CAMEO code of the CAMEO “type”...           NULL   \n",
       "23  If multiple type/role codes are specified for ...           NULL   \n",
       "24  If multiple type/role codes are specified for ...           NULL   \n",
       "25  The system codes every event found in an entir...           NULL   \n",
       "26  This is the raw CAMEO action code describing t...           NULL   \n",
       "27  CAMEO event codes are defined in a three-level...           NULL   \n",
       "28  Similar to EventBaseCode, this defines the roo...           NULL   \n",
       "29  The entire CAMEO event taxonomy is ultimately ...           NULL   \n",
       "30  Each CAMEO event code is assigned a numeric sc...           NULL   \n",
       "31  This is the total number of mentions of this e...           NULL   \n",
       "32  This is the total number of information source...           NULL   \n",
       "33  This is the total number of source documents c...           NULL   \n",
       "34  This is the average “tone” of all documents co...           NULL   \n",
       "35  Location of Actor1.  This field specifies the ...           NULL   \n",
       "36  Location of Actor1.  This is the full human-re...           NULL   \n",
       "37  Location of Actor1.  This is the 2-character F...           NULL   \n",
       "38  Location of Actor1.  This is the 2-character F...           NULL   \n",
       "39  Location of Actor1.  This is the centroid lati...           NULL   \n",
       "40  Location of Actor1.  This is the centroid long...           NULL   \n",
       "41  Location of Actor1.  This is the GNS or GNIS F...           NULL   \n",
       "42  Location of Actor2.  This field specifies the ...           NULL   \n",
       "43  Location of Actor2.  This is the full human-re...           NULL   \n",
       "44  Location of Actor2.  This is the 2-character F...           NULL   \n",
       "45  Location of Actor2.  This is the 2-character F...           NULL   \n",
       "46  Location of Actor2.  This is the centroid lati...           NULL   \n",
       "47  Location of Actor2.  This is the centroid long...           NULL   \n",
       "48  Location of Actor2.  This is the GNS or GNIS F...           NULL   \n",
       "49  Location of Event.  This field specifies the g...           NULL   \n",
       "50  Location of Event.  This is the full human-rea...           NULL   \n",
       "51  Location of Event.  This is the 2-character FI...           NULL   \n",
       "52  Location of Event.  This is the 2-character FI...           NULL   \n",
       "53  Location of Event.  This is the centroid latit...           NULL   \n",
       "54  Location of Event.  This is the centroid longi...           NULL   \n",
       "55  Location of Event.  This is the GNS or GNIS Fe...           NULL   \n",
       "56  This field stores the date the event was added...           NULL   \n",
       "57  This field is only present in the daily event ...           NULL   \n",
       "\n",
       "   rounding_mode  \n",
       "0           None  \n",
       "1           None  \n",
       "2           None  \n",
       "3           None  \n",
       "4           None  \n",
       "5           None  \n",
       "6           None  \n",
       "7           None  \n",
       "8           None  \n",
       "9           None  \n",
       "10          None  \n",
       "11          None  \n",
       "12          None  \n",
       "13          None  \n",
       "14          None  \n",
       "15          None  \n",
       "16          None  \n",
       "17          None  \n",
       "18          None  \n",
       "19          None  \n",
       "20          None  \n",
       "21          None  \n",
       "22          None  \n",
       "23          None  \n",
       "24          None  \n",
       "25          None  \n",
       "26          None  \n",
       "27          None  \n",
       "28          None  \n",
       "29          None  \n",
       "30          None  \n",
       "31          None  \n",
       "32          None  \n",
       "33          None  \n",
       "34          None  \n",
       "35          None  \n",
       "36          None  \n",
       "37          None  \n",
       "38          None  \n",
       "39          None  \n",
       "40          None  \n",
       "41          None  \n",
       "42          None  \n",
       "43          None  \n",
       "44          None  \n",
       "45          None  \n",
       "46          None  \n",
       "47          None  \n",
       "48          None  \n",
       "49          None  \n",
       "50          None  \n",
       "51          None  \n",
       "52          None  \n",
       "53          None  \n",
       "54          None  \n",
       "55          None  \n",
       "56          None  \n",
       "57          None  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%bigquery\n",
    "SELECT * FROM `gdelt-bq.full.INFORMATION_SCHEMA.COLUMN_FIELD_PATHS`\n",
    "WHERE table_name = 'events';"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74e33037-668c-40c1-bfd4-bcbd3f4eadea",
   "metadata": {},
   "source": [
    "## Case 1: Mapping with GDELT: USA Related Events in 2022"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4cc293ba-0cd6-41e6-b075-45b0c81e149d",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%bigquery\n",
    "SELECT *\n",
    "FROM `gdelt-bq.full.events`\n",
    "LIMIT 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8be42418-e32a-4a6b-9b12-4d095d5d26e2",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Query complete after 0.00s: 100%|██████████| 1/1 [00:00<00:00, 602.46query/s] \n",
      "Downloading: 100%|██████████| 431/431 [00:01<00:00, 384.29rows/s]\n"
     ]
    }
   ],
   "source": [
    "%%bigquery usa_event_df\n",
    "SELECT Actor1CountryCode, Actor2CountryCode, count(*) as count\n",
    "FROM `gdelt-bq.full.events`\n",
    "WHERE ((Actor1CountryCode = 'USA' and Actor2CountryCode IS NOT NULL) \n",
    "       or (Actor2CountryCode = 'USA' and Actor1CountryCode IS NOT NULL)) \n",
    "       and Actor1CountryCode != Actor2CountryCode\n",
    "       and Year = 2022\n",
    "GROUP BY 1,2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6074c6d8-cb98-48a6-86f0-40dcef52ebb3",
   "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>Actor1CountryCode</th>\n",
       "      <th>Actor2CountryCode</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>USA</td>\n",
       "      <td>GRC</td>\n",
       "      <td>8819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>PHL</td>\n",
       "      <td>USA</td>\n",
       "      <td>7808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>VCT</td>\n",
       "      <td>USA</td>\n",
       "      <td>570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SAM</td>\n",
       "      <td>USA</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>USA</td>\n",
       "      <td>SWE</td>\n",
       "      <td>3219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>426</th>\n",
       "      <td>USA</td>\n",
       "      <td>GNB</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>SAU</td>\n",
       "      <td>USA</td>\n",
       "      <td>10874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>LVA</td>\n",
       "      <td>USA</td>\n",
       "      <td>707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>ASA</td>\n",
       "      <td>USA</td>\n",
       "      <td>104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>BGR</td>\n",
       "      <td>USA</td>\n",
       "      <td>854</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>431 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Actor1CountryCode Actor2CountryCode  count\n",
       "0                 USA               GRC   8819\n",
       "1                 PHL               USA   7808\n",
       "2                 VCT               USA    570\n",
       "3                 SAM               USA      4\n",
       "4                 USA               SWE   3219\n",
       "..                ...               ...    ...\n",
       "426               USA               GNB     30\n",
       "427               SAU               USA  10874\n",
       "428               LVA               USA    707\n",
       "429               ASA               USA    104\n",
       "430               BGR               USA    854\n",
       "\n",
       "[431 rows x 3 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "usa_event_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "e3cd090f-c5ee-4585-b347-3e9c8a715e42",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a new column with the sorted Actor1CountryCode and Actor2CountryCode\n",
    "usa_event_df['sorted_pair'] = usa_event_df.apply(lambda row: tuple(sorted([row['Actor1CountryCode'], row['Actor2CountryCode']])), axis=1)\n",
    "\n",
    "# Group by the sorted pair and sum the counts\n",
    "grouped_df = usa_event_df.groupby('sorted_pair').agg({'count': 'sum'}).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2242e25d-f57b-40f8-99c5-7d75066c15c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "max_val = np.log10(grouped_df['count'].max())\n",
    "\n",
    "def get_alpha(count):\n",
    "    '''\n",
    "    Convert a count to an alpha val.\n",
    "    Log-scaled\n",
    "    '''\n",
    "    scale = np.log10(count)\n",
    "    return (scale/max_val) * 0.25"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "fdda436e-e455-48e4-a23e-8f07fd25cb71",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/geoai-0.8.0/lib/python3.6/site-packages/ipykernel_launcher.py:7: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n",
      "\n",
      "  import sys\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x1296 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18,18))\n",
    "\n",
    "# Load the world shape map\n",
    "world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))\n",
    "\n",
    "# Country centroids\n",
    "world['centroid'] = world.centroid\n",
    "centroids = world.set_index('iso_a3')['centroid']\n",
    "\n",
    "event_map = Basemap(projection='moll',\n",
    "                    llcrnrlat=-80,urcrnrlat=80,\n",
    "                    llcrnrlon=-180,urcrnrlon=180, \n",
    "                    lon_0=0, lat_0=0)\n",
    "\n",
    "event_map.drawcoastlines()\n",
    "event_map.drawcountries()\n",
    "event_map.fillcontinents(color='0.6')\n",
    "event_map.drawmapboundary()\n",
    "\n",
    "# Assuming grouped_df is defined somewhere before this\n",
    "for index, row in grouped_df.iterrows():\n",
    "    country1, country2 = row['sorted_pair']\n",
    "    if country1 in centroids.index and country2 in centroids.index:\n",
    "        point1 = centroids.loc[country1]\n",
    "        point2 = centroids.loc[country2]\n",
    "        \n",
    "        # Convert centroids to lat-long for Basemap\n",
    "        lon1, lat1 = point1.xy\n",
    "        lon2, lat2 = point2.xy\n",
    "        \n",
    "        line_alpha = get_alpha(row['count'])\n",
    "        \n",
    "        event_map.drawgreatcircle(lon1[0], lat1[0], lon2[0], lat2[0], \n",
    "                                  linewidth=2,\n",
    "                                  color='r',\n",
    "                                  alpha=line_alpha)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2012797-9ff9-41f4-aedb-a26db0fd5b3a",
   "metadata": {},
   "source": [
    "## Case2: Entity Connection Graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "4a51ebe7-eeee-40f6-86f3-b3b31b781c34",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Query complete after 0.00s: 100%|██████████| 1/1 [00:00<00:00, 382.34query/s]                          \n",
      "Downloading: 100%|██████████| 13/13 [00:01<00:00, 10.71rows/s]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>table_catalog</th>\n",
       "      <th>table_schema</th>\n",
       "      <th>table_name</th>\n",
       "      <th>column_name</th>\n",
       "      <th>field_path</th>\n",
       "      <th>data_type</th>\n",
       "      <th>description</th>\n",
       "      <th>collation_name</th>\n",
       "      <th>rounding_mode</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>gdeltv2</td>\n",
       "      <td>geg_gcnlapi</td>\n",
       "      <td>date</td>\n",
       "      <td>date</td>\n",
       "      <td>TIMESTAMP</td>\n",
       "      <td>None</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>gdeltv2</td>\n",
       "      <td>geg_gcnlapi</td>\n",
       "      <td>url</td>\n",
       "      <td>url</td>\n",
       "      <td>STRING</td>\n",
       "      <td>None</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>gdeltv2</td>\n",
       "      <td>geg_gcnlapi</td>\n",
       "      <td>lang</td>\n",
       "      <td>lang</td>\n",
       "      <td>STRING</td>\n",
       "      <td>None</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>gdeltv2</td>\n",
       "      <td>geg_gcnlapi</td>\n",
       "      <td>polarity</td>\n",
       "      <td>polarity</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>None</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>gdeltv2</td>\n",
       "      <td>geg_gcnlapi</td>\n",
       "      <td>magnitude</td>\n",
       "      <td>magnitude</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>None</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>gdeltv2</td>\n",
       "      <td>geg_gcnlapi</td>\n",
       "      <td>score</td>\n",
       "      <td>score</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>None</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>gdeltv2</td>\n",
       "      <td>geg_gcnlapi</td>\n",
       "      <td>entities</td>\n",
       "      <td>entities</td>\n",
       "      <td>ARRAY&lt;STRUCT&lt;name STRING, type STRING, mid STR...</td>\n",
       "      <td>None</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>gdeltv2</td>\n",
       "      <td>geg_gcnlapi</td>\n",
       "      <td>entities</td>\n",
       "      <td>entities.name</td>\n",
       "      <td>STRING</td>\n",
       "      <td>None</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>gdeltv2</td>\n",
       "      <td>geg_gcnlapi</td>\n",
       "      <td>entities</td>\n",
       "      <td>entities.type</td>\n",
       "      <td>STRING</td>\n",
       "      <td>None</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>gdeltv2</td>\n",
       "      <td>geg_gcnlapi</td>\n",
       "      <td>entities</td>\n",
       "      <td>entities.mid</td>\n",
       "      <td>STRING</td>\n",
       "      <td>None</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>gdeltv2</td>\n",
       "      <td>geg_gcnlapi</td>\n",
       "      <td>entities</td>\n",
       "      <td>entities.wikipediaUrl</td>\n",
       "      <td>STRING</td>\n",
       "      <td>None</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>gdeltv2</td>\n",
       "      <td>geg_gcnlapi</td>\n",
       "      <td>entities</td>\n",
       "      <td>entities.numMentions</td>\n",
       "      <td>INT64</td>\n",
       "      <td>None</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>gdelt-bq</td>\n",
       "      <td>gdeltv2</td>\n",
       "      <td>geg_gcnlapi</td>\n",
       "      <td>entities</td>\n",
       "      <td>entities.avgSalience</td>\n",
       "      <td>FLOAT64</td>\n",
       "      <td>None</td>\n",
       "      <td>NULL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   table_catalog table_schema   table_name column_name             field_path  \\\n",
       "0       gdelt-bq      gdeltv2  geg_gcnlapi        date                   date   \n",
       "1       gdelt-bq      gdeltv2  geg_gcnlapi         url                    url   \n",
       "2       gdelt-bq      gdeltv2  geg_gcnlapi        lang                   lang   \n",
       "3       gdelt-bq      gdeltv2  geg_gcnlapi    polarity               polarity   \n",
       "4       gdelt-bq      gdeltv2  geg_gcnlapi   magnitude              magnitude   \n",
       "5       gdelt-bq      gdeltv2  geg_gcnlapi       score                  score   \n",
       "6       gdelt-bq      gdeltv2  geg_gcnlapi    entities               entities   \n",
       "7       gdelt-bq      gdeltv2  geg_gcnlapi    entities          entities.name   \n",
       "8       gdelt-bq      gdeltv2  geg_gcnlapi    entities          entities.type   \n",
       "9       gdelt-bq      gdeltv2  geg_gcnlapi    entities           entities.mid   \n",
       "10      gdelt-bq      gdeltv2  geg_gcnlapi    entities  entities.wikipediaUrl   \n",
       "11      gdelt-bq      gdeltv2  geg_gcnlapi    entities   entities.numMentions   \n",
       "12      gdelt-bq      gdeltv2  geg_gcnlapi    entities   entities.avgSalience   \n",
       "\n",
       "                                            data_type description  \\\n",
       "0                                           TIMESTAMP        None   \n",
       "1                                              STRING        None   \n",
       "2                                              STRING        None   \n",
       "3                                             FLOAT64        None   \n",
       "4                                             FLOAT64        None   \n",
       "5                                             FLOAT64        None   \n",
       "6   ARRAY<STRUCT<name STRING, type STRING, mid STR...        None   \n",
       "7                                              STRING        None   \n",
       "8                                              STRING        None   \n",
       "9                                              STRING        None   \n",
       "10                                             STRING        None   \n",
       "11                                              INT64        None   \n",
       "12                                            FLOAT64        None   \n",
       "\n",
       "   collation_name rounding_mode  \n",
       "0            NULL          None  \n",
       "1            NULL          None  \n",
       "2            NULL          None  \n",
       "3            NULL          None  \n",
       "4            NULL          None  \n",
       "5            NULL          None  \n",
       "6            NULL          None  \n",
       "7            NULL          None  \n",
       "8            NULL          None  \n",
       "9            NULL          None  \n",
       "10           NULL          None  \n",
       "11           NULL          None  \n",
       "12           NULL          None  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%bigquery\n",
    "SELECT * FROM `gdelt-bq.gdeltv2.INFORMATION_SCHEMA.COLUMN_FIELD_PATHS`\n",
    "WHERE table_name = 'geg_gcnlapi';"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "7d25ab4b-96ea-4528-8914-12b6a2885276",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Query complete after 0.00s: 100%|██████████| 10/10 [00:00<00:00, 3087.45query/s]                       \n",
      "Downloading: 100%|██████████| 1500/1500 [00:01<00:00, 1263.98rows/s]\n"
     ]
    }
   ],
   "source": [
    "%%bigquery entity_graph\n",
    "SELECT Source, Target, Count RawCount, \"Undirected\" Type, ( Count/SUM(Count) OVER () ) Weight FROM (\n",
    "SELECT a.entity Source, b.entity Target, COUNT(*) as Count\n",
    "FROM (\n",
    " (SELECT url, entities.name entity FROM `gdelt-bq.gdeltv2.geg_gcnlapi`, unnest(entities) entities \n",
    "  where entities.mid is not null and entities.type = 'PERSON'\n",
    "  and date >= \"2019-02-05 00:00:00\" AND date < \"2019-02-06 00:00:00\")\n",
    ") a\n",
    "JOIN (\n",
    " (SELECT url, entities.name entity FROM `gdelt-bq.gdeltv2.geg_gcnlapi`, unnest(entities) entities \n",
    "  where entities.mid is not null and entities.type = 'PERSON'\n",
    "  and date >= \"2019-02-05 00:00:00\" AND date < \"2019-02-06 00:00:00\")\n",
    ") b\n",
    "ON a.url=b.url\n",
    "WHERE a.entity<b.entity\n",
    "GROUP BY 1,2\n",
    "ORDER BY 3 DESC\n",
    "LIMIT 1500\n",
    ")\n",
    "order by Count Desc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "aec34067-4734-413d-87aa-372e8f81a083",
   "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>Source</th>\n",
       "      <th>Target</th>\n",
       "      <th>RawCount</th>\n",
       "      <th>Type</th>\n",
       "      <th>Weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Nancy Pelosi</td>\n",
       "      <td>Stacey Abrams</td>\n",
       "      <td>1120</td>\n",
       "      <td>Undirected</td>\n",
       "      <td>0.005300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Elizabeth Warren</td>\n",
       "      <td>Kamala Harris</td>\n",
       "      <td>1030</td>\n",
       "      <td>Undirected</td>\n",
       "      <td>0.004875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Cory Booker</td>\n",
       "      <td>Kamala Harris</td>\n",
       "      <td>976</td>\n",
       "      <td>Undirected</td>\n",
       "      <td>0.004619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Cory Booker</td>\n",
       "      <td>Elizabeth Warren</td>\n",
       "      <td>909</td>\n",
       "      <td>Undirected</td>\n",
       "      <td>0.004302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kamala Harris</td>\n",
       "      <td>Kirsten Gillibrand</td>\n",
       "      <td>888</td>\n",
       "      <td>Undirected</td>\n",
       "      <td>0.004203</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Source              Target  RawCount        Type    Weight\n",
       "0      Nancy Pelosi       Stacey Abrams      1120  Undirected  0.005300\n",
       "1  Elizabeth Warren       Kamala Harris      1030  Undirected  0.004875\n",
       "2       Cory Booker       Kamala Harris       976  Undirected  0.004619\n",
       "3       Cory Booker    Elizabeth Warren       909  Undirected  0.004302\n",
       "4     Kamala Harris  Kirsten Gillibrand       888  Undirected  0.004203"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "entity_graph.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "8d8bf936-fed3-4240-b8ff-97e52ad19e90",
   "metadata": {},
   "outputs": [],
   "source": [
    "entity_graph_filtered = entity_graph[(entity_graph['Source'] == 'Donald Trump') | (entity_graph['Target'] == 'Donald Trump')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "5f3c23e8-3702-48e9-940a-b4a2dbfde332",
   "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>Source</th>\n",
       "      <th>Target</th>\n",
       "      <th>RawCount</th>\n",
       "      <th>Type</th>\n",
       "      <th>Weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Donald Trump</td>\n",
       "      <td>Nancy Pelosi</td>\n",
       "      <td>799</td>\n",
       "      <td>Undirected</td>\n",
       "      <td>0.003781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Donald Trump</td>\n",
       "      <td>Kamala Harris</td>\n",
       "      <td>727</td>\n",
       "      <td>Undirected</td>\n",
       "      <td>0.003441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Donald Trump</td>\n",
       "      <td>Elizabeth Warren</td>\n",
       "      <td>682</td>\n",
       "      <td>Undirected</td>\n",
       "      <td>0.003228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Donald Trump</td>\n",
       "      <td>Stacey Abrams</td>\n",
       "      <td>682</td>\n",
       "      <td>Undirected</td>\n",
       "      <td>0.003228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Donald Trump</td>\n",
       "      <td>Kirsten Gillibrand</td>\n",
       "      <td>635</td>\n",
       "      <td>Undirected</td>\n",
       "      <td>0.003005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>757</th>\n",
       "      <td>Angela Merkel</td>\n",
       "      <td>Donald Trump</td>\n",
       "      <td>97</td>\n",
       "      <td>Undirected</td>\n",
       "      <td>0.000459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>814</th>\n",
       "      <td>Donald Trump</td>\n",
       "      <td>God</td>\n",
       "      <td>95</td>\n",
       "      <td>Undirected</td>\n",
       "      <td>0.000450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>863</th>\n",
       "      <td>Donald Trump</td>\n",
       "      <td>Juan Guaido</td>\n",
       "      <td>93</td>\n",
       "      <td>Undirected</td>\n",
       "      <td>0.000440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1284</th>\n",
       "      <td>Bush</td>\n",
       "      <td>Donald Trump</td>\n",
       "      <td>86</td>\n",
       "      <td>Undirected</td>\n",
       "      <td>0.000407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1433</th>\n",
       "      <td>Donald Trump</td>\n",
       "      <td>Marco Rubio</td>\n",
       "      <td>83</td>\n",
       "      <td>Undirected</td>\n",
       "      <td>0.000393</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>61 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Source              Target  RawCount        Type    Weight\n",
       "7      Donald Trump        Nancy Pelosi       799  Undirected  0.003781\n",
       "13     Donald Trump       Kamala Harris       727  Undirected  0.003441\n",
       "17     Donald Trump    Elizabeth Warren       682  Undirected  0.003228\n",
       "18     Donald Trump       Stacey Abrams       682  Undirected  0.003228\n",
       "24     Donald Trump  Kirsten Gillibrand       635  Undirected  0.003005\n",
       "...             ...                 ...       ...         ...       ...\n",
       "757   Angela Merkel        Donald Trump        97  Undirected  0.000459\n",
       "814    Donald Trump                 God        95  Undirected  0.000450\n",
       "863    Donald Trump         Juan Guaido        93  Undirected  0.000440\n",
       "1284           Bush        Donald Trump        86  Undirected  0.000407\n",
       "1433   Donald Trump         Marco Rubio        83  Undirected  0.000393\n",
       "\n",
       "[61 rows x 5 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "entity_graph_filtered"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "3c5bb535-f26e-4b2c-b352-d769d512396d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = nx.Graph()\n",
    "\n",
    "for index, row in entity_graph_filtered.iterrows():\n",
    "    g.add_edge(row['Source'], row['Target'], weight=row['Weight'])\n",
    "\n",
    "# Set up with a white background and no grid lines\n",
    "plt.figure(figsize=(20, 15))\n",
    "plt.title('People most associated in global news with Donald Trump', y=0.97, fontsize=20, fontweight='bold')\n",
    "cf = plt.gcf()\n",
    "ax = cf.gca()\n",
    "ax.set_axis_off()\n",
    "\n",
    "# Getting the largest connected component\n",
    "connected_components = (g.subgraph(c) for c in nx.connected_components(g))\n",
    "gmax = max(connected_components, key=len)\n",
    "\n",
    "d = nx.degree(gmax)\n",
    "b = nx.betweenness_centrality(gmax).items()\n",
    "\n",
    "# # Use a circular layout\n",
    "pos = nx.circular_layout(gmax)\n",
    "\n",
    "edge_weights = nx.get_edge_attributes(gmax, 'weight')\n",
    "normalized_weights = [weight/max(edge_weights.values()) for weight in edge_weights.values()]\n",
    "\n",
    "nx.draw_networkx_edges(gmax, pos, nodelist=[v[0] for v in b], alpha=0.9, width=normalized_weights*20)\n",
    "nx.draw_networkx_nodes(gmax, pos, nodelist=[v[0] for v in b], node_size=[v[1] * 20 for v in d],\n",
    "                       node_color=[math.log(1 + v[1] * 20) for v in b], cmap=plt.cm.Blues)\n",
    "nx.draw_networkx_labels(gmax, pos, labels={v[0]: v[0] for v in b})\n",
    "\n",
    "# Display the graph\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "83232fd6-25ac-42ca-bc19-93e905ecd9cb",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "geoai-Python3",
   "language": "python",
   "name": "geoai-py3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}