R Workflow Workshop resume July 9th! R packages

[eeholmes]

Enjoy the holiday next week and we'll be back on July 9th for 3 sessions on how to build R packages. Apologies to anyone who signed on today and found me missing!

R packaging is an essential part of R workflow, reproducibility and efficiency. It is important that the different team members understand how to use R packages and what can be done with them---even if you are not the coder on your team. R packages are at the core of an efficient R workflow and things like shiny applications, data packages and sharing work across teams. Understanding their structure will help the whole team work more efficiently together and contribute to their part of the package (code, documentation, data).

• July 9 Everyone: Intro to R packages for data and code. How to build an R package in RStudio. In the second half of the lecture, I will show you how to make an R data package and what that can do to allow data documentation, data revision tracking, data versioniong and data sharing.

• July 16 Everyone: Intro to Roxygen for documentation, pkgdown for package websites, and intro to GitHub Actions for automation. Even if you don't do the coding on your team, you should be aware of how documentation works so you can contribute and the tools for automating tasks like a project website so your team doesn't fall into inefficient workflows.

• July 23 Those writing R packages: Advanced topics for developers. How to set up a NAMESPACE, passing R CMD check, C++ code in your package, coding GitHub Actions workflows. I am going to pass on tips to help you understand how these things work so you don't waste hours figuring it out or fall back on hacky solutions (that will make you suffer down the line).