Reproducibility

How to write a reproducible example.

You are most likely to get good help with your R problem if you provide a reproducible example. A reproducible example allows someone else to recreate your problem by just copying and pasting R code.

There are four things you need to include to make your example reproducible: required packages, data, code, and a description of your R environment.

• Packages should be loaded at the top of the script, so it's easy to see which ones the example needs.

• The easiest way to include data in an email is to use dput() to generate the R code to recreate it. For example, to recreate the mtcars dataset in R, I'd perform the following steps:

  1. Run dput(mtcars) in R
  2. Copy the output
  3. In my reproducible script, type mtcars <- then paste.

• Spend a little bit of time ensuring that your code is easy for others to read:

  • make sure you've used spaces and your variable names are concise, but informative

  • use comments to indicate where your problem lies

  • do your best to remove everything that is not related to the problem.
    The shorter your code is, the easier it is to understand.

• Include the output of sessionInfo() as a comment. This summarises your R environment and makes it easy to check if you're using an out-of-date package.

You can check you have actually made a reproducible example by starting up a fresh R session and pasting your script in.

Before putting all of your code in an email, consider putting it on http://gist.github.com/. It will give your code nice syntax highlighting, and you don't have to worry about anything getting mangled by the email system.