Intermediate-level programming with R

This lesson is for learners that are comfortable programming in R and want to learn some of R’s powerful tools for analyzing and visualizing data, literate programming, and debugging code.

The data used in this lesson are the citations and altmetrics for the PLOS journals from 2003-2010. The data set was compiled by Priem et al. 2012 (publication, code).

This lesson starts with a quick review of the basics of the Unix shell and programming with R.

Prerequisites

Learners should be familiar working in the Unix shell and basic programming with R, e.g. writing functions.

Getting ready

You’ll need to install the following packages: rmarkdown, dplyr, ggplot2, and testit.

Topics

1. Setting up a project
2. Inspecting a file
3. Using RStudio
4. Importing and inspecting data
5. R conditional statements
6. R loops

7. Functions in R

8. Writing in Markdown
9. Writing in R Markdown
10. Using knitr chunk options

11. R Markdown output options

12. Subsetting data with dplyr
13. Using pipes with dplyr

14. Summarizing data with dplyr

15. Starting with ggplot2 - Map data to plot aesthetics
16. Control data mapping with scales
17. Creating subplots with facets
18. Creating different plots with geoms

19. Customizing plot appearance with themes

20. Debugging with debug
21. Debugging with browser

22. Debugging with recover

23. Defensive programming with stopifnot

24. Testing with testit

Other Resources

• Reference
• Discussion
• Instructor’s Guide