RegEx resources

Updated: 📆 2018-04-06.

Regular Expressions, RegEx, regexps– call them what you like, but no matter how you slice it, they’re useful af. After all, data spelunking is all about patterns, and that’s precisely what regexps are for: (wo)manhandling patterns in strings. Good Sirs Wickham and Grolemund, in their masterful tome, r4ds, describe them thusly:

They [regexps] take a little while to get your head around, but once you understand them, you’ll find them extremely useful.1

There are helpful string-related R packages 📦, stringr (which is built on top of the more comprehensive stringi package) comes to mind. But, at some point in your computing life, you’re gonna need to get down with regular expressions.

🆕 An RStudio addin by Garrick Aden-Buie, RegExplain, looks like it will be an invaluable companion to go along with the other resources collected here.

Below you’ll find a collection of some of the Regex-related links I’ve tweeted 🐦:

Awesome new stringr cheat sheet from RStudio

Tada 🎉

As always, by all means let me know if you’ve written something you think I should add: chirp my way (🐦 @dataandme), comment– you know the drill.

1. Wickham, Hadley and Garrett Grolemund. 2016. R for Data Science. Sebastopol: O’Reilly Media. Web. http://r4ds.had.co.nz/strings.html#matching-patterns-with-regular-expressions 20 September, 2017.

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