Welcome to the rResources page! This is a place to share resources and best practices related to R and reproducible research. The following are pages that have been assembled by Sarah Endicott to record my best practices and recommendations for reproducible research in R. I welcome you ideas and contributions!
Resources
Minimum requirements for “good” code
Recommendations for writing reproducible code with links to tools and more detailed resources
R Package Development
Links to R package development book and has my notes on additional steps for releasing a package on CRAN or GitHub
Git and GitHub for Reproducible Research
A tutorial walking through installation and use of Git and GitHub.
Setting up cloud processing with Azure Batch
A tutorial walking through how to setup Azure Batch cloud processing that LERS has access to.
Resources developed by others
R for Data Science
An intro to R that uses the tidyverse.
Geocomputation with R
Book for doing spatial stuff within R
Mastering Shiny
Learn to build interactive Shiny apps.
Advanced R
Learn more advanced concepts including functional and object oriented programming.
R packages
Learn to build R packages
Coding Resources For Ecologists
A list of resources for R collected by Craig Simpkins