| 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 |
Schedule
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:
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 | Key concepts in R | RK | NA |
|
| 10:15 | Project setup | RK | RStudio, git, renv |
|
| 10:30 | Coffee break | NA |
||
| 11:15 | Datasaurus practical | RK | Guided tutorial |
|
| 12:30 | Lunch break | NA |
||
| 13:30 | Quarto | RK | knitr, rmarkdown |
|
| 14:30 | Tidy data w/ exercise | RK | Interactive tutorial |
|
| 15:00 | Coffee break | NA |
||
| 15:15 | Importing data | RK | readr, readxl |
|
| 15:45 | Importing practical | RK | NA |
|
| 16:15 | String manipulation | RK | stringr |
|
| 17:00 | End of day | NA |
||
| 11-Feb | 09:15 | Review of practicals | RK | NA |
| 09:30 | Data transformation | MZ | dplyr |
|
| 10:30 | Coffee break | NA |
||
| 10:45 | Grouping and summarizing | MZ | dplyr |
|
| 11:30 | dplyr Practicals | MZ | NA |
|
| 12:30 | Lunch break | NA |
||
| 13:30 | Joins and pivots | RK | dplyr, tidyr |
|
| 15:00 | RK | Practical |
||
| 17:00 | End of day | NA |
||
| 12-Feb | 09:15 | Review of practicals | RK | NA |
| 09:35 | Visualization | RK | ggplot |
|
| 10:30 | Coffee break | NA |
||
| 11:45 | Functional programming | RK | purrr |
|
| 12:30 | Lunch break | NA |
||
| 13:30 | Tidy models | RK | broom, interactive |
|
| 14:30 | Coffee break | NA |
||
| 14:45 | Concluding practical | All | Assessed |
|
| 17:00 | End of day | NA |
||
| 13-Feb | 09:15 | Advanced Programming | RK | tidyeval |
| 10:00 | What's new in the tidyverse in 2024 | RK | NA |
|
| 10:30 | Coffee break | All | NA |
|
| 10:45 | Bring Your Own Data | All | NA |
|
| 16:00 | Closing session | All | NA |
- Day 1 will cover the conceptual differences in the
tidyverseto baseR, setting up your work environment, loading data via thereadrpackage and basic cleaning of text using regular expressions. - Day 2 will introduce tidying and organising data via the
tidyranddplyrpackRKes as well asggplot2for 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 thetidyversefunctions in your own development code. - Participants are encouraged to bring their own data for analysis or convert existing code to tidyverse on Day 4.