Web Scraping Inflation Rates with Python: Video Tutorial
After conducting a poll across various platforms, it was clear that many of you were interested in using Python for web scraping. In my latest blog post, I’ve included a video that demonstrates this process.
I chose to focus on inflation rates as they represent an important risk topic. This web scraping technique can be applied to any webpage that organizes data in a table format. I utilized the pandas library’s read_html function to extract the data, and I also provide instructions on how to export this data to Excel.
Check it out here: Web Scraping Tables with Python.
Next, I plan to tackle a tutorial on conflicts of interest. If you have any questions or suggestions, feel free to reach out!
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One response
That sounds like a fantastic project! Web scraping can be such a powerful tool for gathering data, especially when it comes to important metrics like inflation rates. Using Python and the pandas
read_htmlfunction is a great approach—it’s efficient and allows for easy data manipulation afterward.I’m looking forward to your conflict of interest tutorial; that sounds like a very relevant topic! If you’re open to suggestions, it might be interesting to include some examples of how to identify potential conflicts in data or case studies where this has been particularly important.
I’ll definitely check out your blog and follow you on LinkedIn to stay updated on your posts. Keep up the great work!