NBA data, Yan Holtz, and web-scraping.org

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Great work deserves to be shared. Especially in data science.
Each week, I'll curate three gems from the data science community:

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🗄️ Re: Remarkable Repository
💻 P:   Prolific Programmer
🏢 O:  Outstanding Organization

I hope you find them as valuable and insightful as I do.
You can find all recommendations in the GitHub repository at finnoh/repo!

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🗄️ Repository | Loads of data on NBA games, players, teams

People interested in basketball and data science, pay attention!

With this API you can access the API of the NBA, providing you with data on players, teams, and even games on a play-by-play basis. Build your own predictions for entire seasons of NBA games, simulate trades of your favourite player, or evaluate whether a player is over- or underpaid. All of this (and more) is possible with this data.

For an introduction to how the API works, see the documentation!

💻 Programmer | Course: Productive R Workflow

Currently, Yan Holtz works on an online course Productive R Workflow, for which you can enrol until the 26th of November. The course showcases how you can work with R more efficiently and presents a collection of nifty tricks and procedures that make your life easier. There are premium lessons, however some of the sessions are free to get you started!

If you want to learn more about data visualization, take a look at Yan’s Substack, Dataviz Universe. A good starting point is his article on a collection of R packages for data visualization!

You can also visit Yan Holtz on his personal website.

🏢 Organization | Learn how to web-scrape, find web-scraped papers

On web-scraping.org you can find anything related to web scraping with a focus on the domain of marketing. You can find existing web scraped datasets, a database of papers using web scraping to collect their data, as well as guides on how to scrape data and access APIs yourself.

Before you get started, take a look at this primer on the legality of web-scraping, Web Scraping and Crawling Are Perfectly Legal, Right? or my own thoughts on making a web-scraper more “fair”: Building an ethical web scraper?.

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