R & github = open science

So, after birds/birdwatching my favourite thing in the world is R https://cran.r-project.org/

Why R? Well, number one, it lets me do pretty much any data manipulation, analysis, modelling, visualization task that I need to do. And number two, it’s free and supported by an amazing community of super smart people, which means it is getting better all the time. And three – because we all know that, in science, you haven’t got your analysis right until you’ve done it three times. In R you can write some code to do your [analysis/manipulation/visualization thing] and then just rerun that analysis. So next time my colleague/supervisor says ‘hey what if we just change that [small parameter]’ I no longer have to spend 3 months redoing everything manually, instead just tweek the code and hit run. Brilliant!

Combine R with github and you have #openscience! Advantages 1) Never lose code again when you change jobs/computer dies/dog ate it. 2) Easily revert to a previous version when you realise your late night coding session was fueled by a little too much wine/coffee 3) Copy the github url for your project’s repository into the methods section of your paper and Voila! transparent and reproducible science. Best thing since….R.

However, having travelled the long path from newbie to expeRt I know just how hard and confusing it can be to learn. So I’ve put together some of my favourite R sites for your neRding pleasure.

Tips for beginners – you don’t need to know each and every function or package – use google and copy code liberally!


http://adv-r.had.co.nz/  This site will take you into the upper echelons of R excellence. We took this on as a weekly ‘R club’, running through a chapter or so each week. Requires a basic  knowledge of R.

Learn to make plots in R: https://www.datacamp.com/community/blog/the-easiest-way-to-learn-ggplot2

oh and while we are on the topic of plotting, if you haven’t already, check out this awesome new resource!