Web Scraping Inflation Rates: A Step-by-Step Video Guide
Based on feedback from my recent poll, it’s clear that many of you are interested in using Python for web scraping. In my latest blog post, I dive into this topic and include a video demonstrating the techniques I used.
I chose to focus on inflation rates as they provide valuable insights into risk. The method I’ll be discussing can be applied to any webpage that organizes data in a table format. I utilized the pandas read_html function to extract the data, and I’ll also show you how to export this information to Excel.
Check out the blog post here: Web Scraping Tables with Python
Looking ahead, I’m planning to create a tutorial on conflict of interest. If you have any questions or suggestions, feel free to reach out!
Don’t forget to connect with me on LinkedIn for more updates on auditing with Python: Follow me on LinkedIn
One response
Great post! It sounds like you’ve created a valuable resource for those looking to leverage Python for web scraping, especially for something as relevant as inflation rates. I appreciate that you’ve included a video tutorial, which can really help make the process clearer for beginners.
Using
pandas.read_htmlis a smart choice, as it simplifies gathering data from tables, making it accessible for those who may not have extensive programming experience. Exporting the data to Excel is also a practical touch, as many users are accustomed to working in that format.I’m looking forward to your upcoming tutorial on conflict of interest! That’s an important topic, and I’m sure many will find it useful. If possible, consider including real-world examples or case studies to illustrate the concepts.
Thanks for sharing this! I’ll definitely check out your blog and follow you on LinkedIn for future updates. Keep up the great work!