In this mini course, we will explore the programming language and environment R. We will integrate R with command line towards the end of this course to show you how to use R within shell scripts and execute R code via an HPC, using the Alabama Supercomputer as an example.
To use R, we will be mainly working within the GUI environment of RStudio. Although R can be run and loaded from the command line, RStudio includes a set of integrated tools designed to help you be more productive with R, such as a console, syntax-highlighting editor that supports direct code execution, tools for plotting, history, debugging and workspace management. This is also known as an IDE or integrated development environment.
The content is meant to be self-guided, with several walk through tutorial lecture videos, as well as exercises to practice on your own. Still, it is worth noting that this mini course is designed for complete novices to R! Each of the 7 modules will go at a slow pace with lots of repetition and call backs to previous module videos. Each module has specific learning objectives listed so you know what to expect. This can be completed at your own pace - over 3 days or 3 months - whatever works best for you! And feel free to skip some modules - you do NOT have to do every one of these.
We have generated this tutorial as an R Project, which means it contains all of the input data, scripts, and outputs in a single place. Using R Projects is a wise practice and more importantly, it is a reproducible practice. All script files (with the exception of R Notebooks) have paths automatically set relative to the R Project directory.
Clone this repository and generate your R Notebooks or R Scripts for each module inside of the existing R Project directory. You should be able to use relative paths when referencing saved data objects provided with the package (R Notebook paths will be relative to the location the notebook is saved). Click to learn more about the benefits, creation, and maintenance of an R Project.
R Cheatsheet - Print this out and keep in your workspace as you are learning. More cheatsheets as you get more advanced can be found here.
We have found two great R tutorials. There are SO many out there, that we just couldn’t decide, so we have provided you with two options - one that you would need to download and can do within RStudio on your computer. Alternatively, you can complete the web-based one we were able to find. EITHER should be sufficient to get you started with the basics.
swirl::install_course("The R Programming Environment") on
the R consoleswirl().A great companion text for learning R that we recomend is the book R in Action. Suggested readings will be provided for each topic.
Optional: Alternative to R in Action are several FREE R Textbooks.
Two that we like are: * YaRrr! The Pirate’s Guide
to R
* Hands-On
Programming with R
Additional resources can be found at the end of this mini course. This page also includes links to practice data you can download to continue your R learning.
