Intro to Scraping Basketball Reference data

<p><em>A short tutorial on how to scrape data from&nbsp;</em><a href="https://www.basketball-reference.com/" rel="noopener ugc nofollow" target="_blank"><em>https://www.basketball-reference.com/</em></a><em>&nbsp;(or any other sports-reference.com site) with python</em></p> <p><img alt="" src="https://miro.medium.com/v2/resize:fit:700/0*UBWb9XbWbwIcpcZU" style="height:518px; width:700px" /></p> <p>Photo by&nbsp;<a href="https://unsplash.com/@echaparro?utm_source=medium&amp;utm_medium=referral" rel="noopener ugc nofollow" target="_blank">Edgar Chaparro</a>&nbsp;on&nbsp;<a href="https://unsplash.com/?utm_source=medium&amp;utm_medium=referral" rel="noopener ugc nofollow" target="_blank">Unsplash</a></p> <p>Sports-Reference.com is precisely where sports fandom and data science converge. It&rsquo;s a massive, structured warehouse of clean sports data. Thus, it&rsquo;s often the starting blocks for academic data science projects.</p> <p><a href="https://medium.com/analytics-vidhya/intro-to-scraping-basketball-reference-data-8adcaa79664a"><strong>Click Here</strong></a></p>