Cheatsheets are currently built and used exclusivley as a teaching tool. We want to try and change this and produce a cheat sheet that gives a roadmap to build a known product, but also is built as a function so users can input data into it to make the cheatsheet more personalized. This gives a versalility of a consistent format that people can share with each other, but has the added value of conveying a message through data driven visual changes.
The ggplot2 theme object is an amazing object you can specify nearly any part of the plot that is not conditonal on the data. What sets the theme object apart is that its structure is consistent, but the values in it change. In addition to change a theme it is a single function that too has a consistent call. The reoccuring challenge for users is to remember all the options that can be used in the theme call (there are approximately 220 unique options to calibrate at last count) or bookmark the help page for the theme and remember how you deciphered it last time.
This becomes a problem to pass all the information of the theme to someone who does not know what the values are set in your theme and attach instructions on it to let them recreate it without needing to open any web pages.
In writing the library ggedit we tried to make it easy to edit your theme so you don’t have to know too much about ggplots to make a large number of changes at once, for a quick clip see here. We had to make it easy to track those changes for people who are not versed in R, and plot.theme() was the outcome. In short think of the theme as a lot of small images that are combined to create a singel portrait.
Last week the updated version of ggedit was presented in RStudio::conf2017. First, a BIG thank you to the whole RStudio team for a great conference and being so awesome to answer the insane amount of questions I had (sorry!). For a quick intro to the package see the previous post.
Jonathan Sidi joined Metrum Researcg Group in 2016 after working for several years on problems in applied statistics, financial stress testing and economic forecasting in both industrial and academic settings.
To learn more about additional open-source software packages developed by Metrum Research Group please visit the Metrum website.