Maëlle's R blog

Showcase of my (mostly R) work/fun

Are #python users more likely to get into Slytherin?

This post requires some familiarity with the Harry Potter books but I’m committed to making this blog friendly to everyone, even Muggles/Nomajes.

Have you seen Mark Sellors’ blog post series about writing command line utilities in R? It’s a great one but I was a bit puzzled by his using randomness to assign houses in his sorting hat example (he added a new method based on name digest-ing in the meantime).

This prompted a reply by David Hood who later came up with R code to assign you to a Hogwarts house based on your Twitter activity!

I was thrilled to see David Hood’s sorting hat Github repo and thought it’d be the perfect occasion to answer that fascinating question: are #python users more likely to get into Slytherin than #rstats users?

Another note: I do not care about any Python vs. R fights except for Quidditch games, so go away trolls.

My #Best9of2017 tweets

You’ve probably seen people posting their #Best9of2017, primarily on Instagram I’d say. I’m not an Instagram user, although I do have an account to spy on my younger sister and cousins, so I don’t even have 9 Instagram posts in total but I do love the collage people get to show off… So what about my best 9 tweets of 2017?

Where have you been? Getting my Github activity

On my pretty and up-to-date CV, one of the first things one sees is my Github username, linking to my Github profile. What does a potential employer look at there? Hopefully not my non informative commit messages… My imitating a red Ampelmann, my being part of several organizations, my pinned repositories described with emojis… But how would they know where&how I’ve mostly been active without too much effort?

A considerable part of my Github work happens in organizations: I’m a co-editor at rOpenSci onboarding of packages, I contribute content to the R Weekly newsletter, etc. Although my profile shows the organizations I belong to, one would need to dig into them for a while before seeing how much or how little I’ve done. Which is fine most of the time but less so when trying to profile myself for jobs, right? Let’s try and fetch some Github data to create a custom profile.

Note: yep I’m looking for a job and ResearchGate’s suggestions are not helpful! Do you need an enthusiastic remote data scientist or research software engineer for your team? I’m available up to 24 hours a week! I care a lot about science, health, open source and community. Ideally I’d like to keep working in something close to public research but we can talk!

Possum magic: mapping an Australian children's book

Our brand-new baby received a fantastic picture book as a gift: Possum magic, a classic for Aussie kids. Thanks, Miles! In that book, Hush the possum and her Grandma Poss encounter different Australian animals and travel across well eat their way through the country. It is an adorable story with great illustrations! Reading it will make you feel like travelling to Australia, for instance to useR! 2018, except you shouldn’t because it is a very scary country:

However, you can travel and learn geography without leaving the comfort of a snake-free home… by mapping Hush’s adventures! Which is what I decided to do.

How to develop good R packages (for open science)

I was invited to an exciting ecology & R hackathon in my capacity as a co-editor for rOpenSci onboarding system of packages. It also worked well geographically since this hackathon was to take place in Ghent (Belgium) which is not too far away from my new city, Nancy (France). The idea was to have me talk about my “top tips on how to design and develop high-quality, user-friendly R software” in the context of open science, and then be a facilitator at the hackathon.

The talk topic sounded a bit daunting but as soon as I started preparing the talk I got all excited gathering resources – and as you may imagine since I was asked to talk about my tips I did not need to try & be 100% exhaustive. I was not starting from scratch obviously: we at rOpenSci already have well-formed opinions about such software, and I had given a talk about automatic tools for package improvement whose content was part of my top tips.

As I’ve done in the past with my talks, I chose to increase the impact/accessibility of my work by sharing it on this blog. I’ll also share this post on the day of the hackathon to provide my audience with a more structured document than my slides, in case they want to keep some trace of what I said (and it helped me build a good narrative for the talk!). Most of these tips will be useful for package development in general, and a few of them specific to scientific software.