👉 The `findarticles` function in Python's `feedparser` library is used to scrape and return articles from a specified news feed, such as Google News. It takes parameters like `q` for the search query, `from_` and `to_` to limit the search results to articles from a specific date range, and `count` to specify the number of articles to retrieve. The function returns a list of `FeedArticle` objects, each containing metadata about the article like title, URL, author, and publication date. To apply mathematical operations on this data, you can leverage Python's built-in functions or libraries like NumPy for calculations such as averaging the publication dates, finding the average word count per article, or even applying statistical tests to compare article performance across different topics or time periods. For example, you could calculate the average number of likes or shares per article to gauge its popularity or use linear regression to explore trends in article engagement over time.
