Maëlle's R blog

I was until recently subscribed to an email list, ALLSTAT, “A UK-based worldwide e-mail broadcast system for the statistical community, operated by ICSE for HEA Statistics.” created in 1998. That’s how I saw the ad for my previous job in Barcelona! Now, I dislike emails more and more so I unsubscribed, but I’d still check out the archives any time I need a job, since many messages are related to openings. Nowadays, I probably identify more as a research software engineer or data scientist than a statistician… which made me wonder, when did ALLSTAT start featuring data scientist jobs? How do their frequency compare to those of statisticians?

In this post, I’ll webscrape and analyse meta-data of ALLSTAT emails. It’ll also be the occasion for me to take the wonderful new polite package for a ride, that helps respectful webscraping!

Last time I blogged, I offered my obnoxious helpful advice for blog content and promotion. Today, let me again be the agony aunt you didn’t even write to! Imagine you have an R question, i.e. a question related to how you can do something with R, and your search engine efforts haven’t been too successful: where should you ask it to increase your chance of its getting answered? You could see this post as my future answer to stray suboptimal Twitter R questions, or as a more general version of Scott Chamberlain’s excellent talk about how to get help related to rOpenSci software in the 2017-03-07 rOpenSci comm call.

I think that the general journey to getting answers to your R questions is first trying your best to get answers locally in the documentation of R, then to use a search engine, and then to post a well-formulated question somewhere. My post is aimed at helping you find that somewhere. Note that it’s considered best practice to ask in one somewhere at once, and to then move on to another somewhere if you haven’t got any answer… or if someone kindly redirects you to a better venue!

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?