Sidharth is a high school senior with a strong interest in math and programming. As a big basketball junkie, he spends a lot of his time developing tools that perform analysis on NBA statistics. He also has some experience in iOS development, autonomous robots, natural language processing, and machine learning. Sid has worked with teams at the Stanford Artificial Intelligence Lab as well as having done private contracting. Check out @sidharthrajaram on GitHub to take a look at some of his current and past projects.
Sometimes the data you want is stuck on a website, in the form of a table or paragraph. Whether it is for your machine learning project or just viewing site text, web scraping is an important skill to have. Using BeautifulSoup, we can create a simple Python web scraper that can be used to retrieve sports statistics or stock prices. We will begin with a preface about BeautifulSoup, Pandas, and other helpful libraries. Following that we’ll work through the implementation of some scrapers and then have a discussion about how to move forward with scraped data. This presentation should clear up doubts and hopefully spark new ideas in your heads.