This past spring the Data & Visualization Services Department hosted a six-part workshop series on the R programming language. Our goals for the workshop series is to introduce R as a language for modern data manipulation. We do this by highlighting a basic set of packages that enable functional and practical data science. We approach R using the free RStudio IDE, an intent to make reproducible literate code, and a bias towards the tidyverse. This tool-set provides a context that enables and reinforces workflows, analysis and reporting. The tidy data approach is good for highlighting work best verified through the lens of reproducible research.
Special Thanks to Dr. Mine Çetinkaya-Rundel who notably provided two sessions. The R-Markdown session is very informative. The session on Shiny is a great primer. See the links below.
Note: Due to some video difficulties many of the videos are from the previous semester. All other links are up to date.
The following listicle includes links to each workshop’s resources. Whenever possible we include links to a streaming video recording, slides and lecture notes, shareable datasets and R code.
- Introduction to R: Data Transformations, Analysis, and Data Structures
- Getting Started with R Markdown with Mine Çetinkaya-Rundel
- Introduction to Shiny
- Reproducibility: Data Management, Git, and RStudio
- Visualization in R using ggplot2
- Mapping with R
This workshop series is intended to be iterative and recursive. We recommend starting with the Introduction to R. Proceed through the remaining four workshops in any order of most interest, but save the Shiny workshop for last.
As you work through the discussion and hands-on exercises, we invite you to consider how these techniques and tools relate to your personal research projects. If you have questions about the content of a workshop or are ready to consult about your research, please attend our walk-in consultation hours or send us an email.