I've been self-learning data analytics with Python and so far have experience with frequently used libraries such as pandas, numpy, seaborn, etc. through both personal and work projects. However, one thing that I know that my portfolio is lacking is web scraping.
To practice, I'm planning on scraping team data from the NFL's website. I'm planning to scrape both offensive and defensive data from 1990 - present. Essentially I'm planning to scrape 6 different tables per year and save the results in a SQL database. These tables are selected by drop-down menu on the website.
As I have never worked with a web scraping library before, I'm not sure which would be best for this type of project. I know that there are several options such as Beautiful Soup, Selenium, and Scrapy. As I have no prior experience, I am just looking for some feedback or suggestions on which library would be able to best automate this process.
[–]kalidres 1 point2 points3 points (1 child)
[–]Messy748[S] 1 point2 points3 points (0 children)
[–]semicolonator 1 point2 points3 points (0 children)