Web scraping is an automated method for extracting data from websites, often using Python and packages like Requests, Beautiful Soup, and pandas to handle the collection and parsing of HTML tables, such as those found on the Worldometer site. The process involves sending an HTTP request to a target web page, parsing the HTML content to locate table structures, and then extracting and storing data in a pandas DataFrame for analysis. This data often requires cleaning, such as renaming columns, handling missing values, and converting data types to ensure accuracy and usability. Once cleaned, the data can be exported to a CSV file for further analysis. Although web scraping can be straightforward, it can become complex when dealing with dynamic content or changing website structures. To simplify this, services like the Bright Data Web Scraper API offer automated solutions that address various challenges, including handling JavaScript-rendered pages and CAPTCHA verification.