polite

I’ve just finished teaching blogging with R Markdown at R-Ladies Bangalore. This has two consequences: I need to calm down a bit after the stress of live demoing & co, and I am inspired to, well, blog with R Markdown! As I’ve just read a fascinating book about the beanie baby bubble and as I’ve seen rvest is getting an update, I’ve decided to harvest Beaniepedia. Both of these things show I spend too much time on Twitter, as the book has been tweeted about by Vicki Boykis, and the package changes have been tweeted about by Hadley Wickham.

It’s October, time for spooky Twitter names! If you’re on this social media platform, you might have noticed some of your friends switching their names to something spooky and punny. Last year I was “Maelstrom Salmon”, which I find scary but is arguably not that funny. Anyhow, what if you want to switch your name but have no inspiration? In this post, we shall explore R’s abilities to help us with that with the help of webscraping, phonetic spelling and string distance algorithms, and the magic of randomness!

What can a kaka, a kakapo, an European rabbit and a grey heron have in common? Well, they might co-habit in the bookshelf of an R user, since they’re all animals on the covers of popular R books: “R Packages”, “R for Data Science”, “Text mining with R” and “Efficient R programming”, respectively. Their publisher, O’Reilly, has now based its brand on covers featuring beautiful gravures of animals.

Recently, while wondering what the name of R for Data Science bird was again (I thought it was a kea!), I was thrilled to find the whole O’Reilly menagerie, i.e. a list of books and corresponding animals! The website also features a link to “A short history of the O’Reilly animals” that was an amazing read. In it was noted that “The animals are in trouble.”, with a few examples of endangered species. It inspired me to actually try and assess the conservation status of O’Reilly animals using responsible webscraping, taxonomic name resolving and IUCN Redlist API querying…

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!