From R User to R Programmer
posit::conf(2024)
by Emma Rand and Ian Lyttle
🗓️ August 12, 2024
⏰ 09:00 - 17:00
🏨 Quinault
✍️ pos.it/programming_r_24
Description
This is a one-day, hands-on workshop for those who have embraced the tidyverse and want to improve their R programming skills and, especially, reduce the amount of duplication in their code. The two main ways to reduce duplication are creating functions and using iteration. We will use a tidyverse approach to cover function design and iteration with {purrr}.
- Master the art of writing functions that do one thing well, adhere to existing conventions and can be fluently combined together to solve more complex problems.
- Learn how to perform the same action on many objects using code which is succinct and easy to read.
Audience
This workshop is for you if you…
- have experience equivalent to an introductory data science course using tidyverse
- feel comfortable with the Whole game chapter of R for Data Science (2nd Edition) by Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund.
Please note
These materials are under active development, which will likely continue until the start of the workshop. Given this context: if you have a concern, please file an issue.
Prework
In short:
- Install current versions of R & RStudio
install.packages(c("devtools", "tidyverse", "palmerpenguins", "here"))
More details on our pre-requisites page.
Schedule
| Time | Activity |
|---|---|
| 09:00 - 10:30 | Functions 1 |
| 10:30 - 11:00 | Coffee break |
| 11:00 - 12:30 | Functions 2 |
| 12:30 - 13:30 | Lunch break |
| 13:30 - 15:00 | Iteration 1 |
| 15:00 - 15:30 | Coffee break |
| 15:30 - 17:00 | Iteration 2 |
Instructors
Emma Rand
University of York
Emma Rand is a Professor in the Department of Biology at the University of York where she specializes in teaching data science and reproducibility, particularly to those who do not see themselves as programmers. She leads a UKRI funded project called Cloud-SPAN which trains researchers in cloud-based high performance computing for ’omics. She is a Software Sustainability Institute Fellow, a Teaching team lead for R Forwards and delivers data science training for the Biochemical Society.
Ian Lyttle
Data Scientist, Schneider Electric
Ian Lyttle is a Data Scientist at Schneider Electric. His technical interests include visualization, interactivity, and functional programming. He is a community contributor to tidyverse and r-lib, and maintains CRAN packages including {vegawidget} and {boxr}. He has delivered tutorials on a variety of R topics at UseR!, Uncoast Unconf, and the Iowa State University Graphics Group.
This work is licensed under a Creative Commons Attribution 4.0 International License.