Schedule

Authors

Affiliation

Before the workshop

Please setup your machine and accounts before the workshop. We encourage participants to complete these steps about a week ahead such that issues can be ironed out with local adminstrators or with the organizers by mail or video conferences.

We do not have the capacity to setup your machine while the workshop is running.

During the workshop

Each day, the workshop will be a mixture of lectures and practicals from:

From	To	What
09:00	09:15	Welcome coffee
09:15	12:30	Course work with a coffee break
12:30	13:30	Lunch break
13:30	17:00	Course work with a coffee break

Please join us for the welcome coffee to test your R set-up and to pose questions. All times refer to local Luxembourg time (Central European Time, UTC+01:00).

After the workshop

Participants should plan some time in the week following the workshop to complete assignments. We aim to limit the workload after the course but if you’re missing segments, get stuck with an assignment.

Detailed program

Date	Time	Session	Who	Notes
10-Feb	09:15	Introduction and refresher	RK	About the course
	09:30	Project setup	RK
	10:15	Datasaurus practical	RK	Rstudio, git
	10:30	Coffee break
	11:15	Quarto	RK	Guided tutorial
	12:30	Lunch break
	13:30	Importing data	RK
	14:30	Tidy data w/ exercise	RK	Interactive tutorial
	15:00	Coffee break
	15:15	Importing data	RK	readr, readxl
	15:45	Importing practical	RK
	16:15	String manipulation	RK	stringr
	17:00	End of day
11-Feb	09:15	Review of practicals	RK
	09:30	Data transformation	MZ	dplyr
	10:30	Coffee break
	10:45	Grouping and summarizing	MZ	dplyr
	11:30	dplyr Practicals	MZ
	12:30	Lunch break
	13:30	Joins and pivots	RK	dplyr, tidyr
	15:00		RK	Practical
	17:00	End of day
12-Feb	09:15	Review of practicals	RK
	09:35	Visualization	RK	ggplot
	10:30	Coffee break
	11:45	Functional programming	RK	purrr
	12:30	Lunch break
	13:30	Tidy models	RK	broom, interactive
	14:30	Coffee break
	14:45	Concluding practical	All	Assessed
	17:00	End of day
13-Feb	09:15	Advanced Programming	RK	tidyeval
	10:00	What's new in the tidyverse in 2025	RK
	10:30	Coffee break	All
	10:45	Bring Your Own Data	All
	16:00	Closing session	All

• Day 1 will cover the conceptual differences in the tidyverse to base R, setting up your work environment, loading data via the readr package and basic cleaning of text using regular expressions.
• Day 2 will introduce tidying and organising data via the tidyr and dplyr packRKes as well as ggplot2 for visualisation.
• Day 3 will look at functional programming tools using the purrrpackage, which greatly simplifies repeating operations. RMarkdown documents enable reproducible and automated reporting. Many statistical packages have complicated and idiosyncratic data structures. Thebroompackage helps to convert them to consistent data structures. We also take a look at using the tidyverse functions in your own development code.
• Participants are encouraged to bring their own data for analysis or convert existing code to tidyverse on Day 4.