Welcome to this self-directed course on R and RStudio. Very little prior experience is assumed, but if you have some R experience, you are welcome to skip ahead. Each module is fairly self contained and accommpanied by a video on this playlist. Modules mostly follow the R for Reproducible Scientific Analysis course provided by the Software Carpentry community. Topics covered in each module include:
- Intro to RStudio
- Project management with RStudio
- Seeking help
- Data Structures
- Exploring data frames
- Subsetting data
- Flow control
- ggplot2
- Vectorization
- Functions
- Writing data
- dplyr
- tidyr
- Joining tables
- Writing good software
Start here for a short video walking you through the software you need for the course and giving you an overview of the material. You’ll want to install the following prior to starting this course:
On a related note, if you are a student (i.e. if you must have a ‘.edu’ email and a student ID card), you should check out the GitHub Student Developer Pack. It comes with all sorts of freebies and discounts for developer tools including things like training, GitHub Pro, JetBrains, Microsoft Azure, Codespaces, and GitKraken.