rr-automation

This lesson teaches some tips and tricks that will make life easier with RMarkdown if one is using it in the context of a typical research project, which will likely involve multiple sources of raw data that are then combined to create multiple intermediate datasets which then get combined to generate figures and tables.

Before the lesson starts

• Make sure that participants have the following packages installed:

  • knitr
  • tidyverse
  • testthat
  • rmarkdown and knitr (in RStudio pushing the knit HTML button the first time will prompt to have these packages installed)

• Distribute a Zip file that only contains the content of the example-manuscript folder from this repository.

• Explain what the handout file contains

People and credits

This lesson was first created at the 1. Reproducible Science Curriculum Hackathon. The corresponding author is François Michonneau (@fmichonneau). See the commit log for other contributors.

Please post feedback and issues with the lesson on the repository's issue tracker. For instructor questions about teaching this lesson, you can also contact the corresponding author directly.