Web Scraping for Journalists: Investigating Data Stories with Python

Web Scraping for Journalists: Investigating Data Stories with Python Data journalism has transformed how newsrooms uncover stories. Instead of relying solely on press releases, journalists now extract structured data from government portals, corporate filings, and public databases. Why Journalists Need Web Scraping Public records are increasingly published online — court filings, campaign finance data, environmental reports. But they're rarely in convenient formats. Scraping lets you: Monitor government websites for policy changes Aggregate data across sources to find patterns Build datasets that don't exist from scattered public information Setting Up Your Investigative Toolkit import requests from bs4 import BeautifulSoup import pandas as pd import time class InvestigativeScraper : def __init__ ( self , api_key = None ): self . session = requests . Session () self . session . headers . update ({ ' User-Agent ' : ' DataJournalism/1.0 (research purposes) ' }) self . api_key = api_key s