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How to write a reproducible example

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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 This summarises your R environment and makes it easy to check if you're using an out-of-date package.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.

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