Maëlle's R blog

This year I had the chance to speak at two R-Ladies meetups (I might have invited myself to those meetups to make the most of being in town, create your own happiness!), one in Cape Town in March, one in Seattle in May. It was a blast both times! I gave the same talk twice, and decided it was about time to write it up.

My talk in March was aimed at pairing, well tripleting, with Marie Dussault’s talk about setting up your blogdown website, and Stephanie Kovalchik’s talk about sports blogging so it is not about these topics. What it is is my non data-driven, quite personal view on blog content and promotion, which hopefully features some useful tips for any wannabe R blogger!

It’s nearly been two years since I defended my PhD thesis! On top of allowing me to call myself doctor, having a PhD in statistics gives me the honour to feature in the data of the Mathematics Genealogy Project. Today, I decided to webscrape my mathematical ancestors.

I couldn’t miss the fun Twitter hashtag #BadStockPhotosOfMyJob thanks to a tweet by Julia Silge and another one by Colin Fay. The latter inspired me to actually go and look for what makes a data science photo… What characterizes “data science” stock photos?

Remember my blog post about automatic tools for improving R packages? One of these tools is Jim Hester’s lintr, a package that performs static code analysis. In my experience it mostly helps identifying too long code lines and missing space, although it’s a bit more involved than that. In any case, lintr helps you maintain good code style, and as mentioned in that now old post of mine, you can add a lintr unit test to your package which will ensure you don’t get lazy over time.

Now say your package has a lintr unit test and lives on GitHub. What happens if someone makes a pull request and writes looong code lines? Continuous integration builds will fail but not only that… The contributor will get to know Lintr Bot, lintr’s Hester (Easter) egg!

One week ago I was in Cape Town for the local satRday conference, where I had the honor to be one of the two keynote speakers, the other one being sports analytics extraordinaire Stephanie Kovalchik (You can read Stephanie Kovalchik’s account of the conference in this blog post). It was a fantastic experience! The event was very well organized, and 100% corresponds to its description as a “one day conference packed with R goodness”. You can watch all talks on Youtube. In my talk, I presented rOpenSci onboarding system of packages and… wore a hard hat!

It’d be a bit hard for me to really write a good recap of satRday that’d do it justice! Instead, I’ll use rtweet and a bit of html hacking to storrrify it (like Storify, but in R) using my live tweets!