Pregleda (30 dana / ukupno): 17 / 292
I’m a casual NBA fan: I don’t have time to watch the games but enjoy viewing the highlights on Instagram/Youtube (especially Shaqtin’ A Fool!); I sometimes read game articles and analyses (e.g. Blogtable). Apart from the game being an amazing visual spectacle, it’s fun to drink in the deluge of stats that each game brings. I’m not even talking about advanced stats and “ABPRmetrics“: there’s something exciting about seeing how many different statistical records can be broken on a given night.
As a data/stats person, I’ve been wanting to get my hands on NBA data and play around with it on my own. However, in my internet searching I didn’t come across any free easy-to-use datasets. The website Basketball-Reference.com is an excellent compendium of all the data I would want, but it was embedded within the webpage, not made available in an analysis-ready format. (Or at least, I couldn’t find it, or it wasn’t free.)
I have several tables that I would like to load as a sole data frame. Derived functions from read. table () have a lot of convenient features, but it...Read more »
Reusable modeling pipelines are a practical idea that gets re-developed many times in many contexts. wrapr supplies a particularly powerful pipeline notation, and a pipe-stage re-use system (notes here).... Read more »
by Mark Niemann-Ross, an author, educator, and writer who teaches about R and Raspberry Pi at LinkedIn Learning I spend a LOT of time at r-project.org, in particular the... Read more »
It’s mid-September and you’re wandering around your preferred supermarket when you stumble across the Christmas section. “Already”, you think. “It wasn’t like this back when I was a kid”....Read more »
Two years ago, we revealed something sensational: Santa Claus is a data scientist. The secret of his success does not lay in his hundred years of experience as a... Read more »
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