R Best Practices
The goal of this training is to build better practices with programming in R, in order to enhance your productivity in research, and to minimize the time you spend on fixing, rewriting and debugging your R scripts.
To achieve this, you will learn how to start using R projects, and how to integrate version control with Github into your projects.
We’ll look at syntax conventions and debugging tools, and we practice upgrading quick-and-dirty scripts to versatile R code.
To this end, we explain the theory and provide examples and hands-on to consolidate best practices in R.
The idea is to learn how to create clean, readable, versatile and reproducible R workflows, which help boosting your scientific productivity and collaboration.
Learning outcomes
When you complete this training you will
- know how to create and use R projects
- be able to store or publish your R project in GitHub
- be able to debug your code with R Studio tools
- know how to make your code reproducible and communicate it
- have an idea of style guidelines and their importance
- be able to make your code cleaner, more compact and more readable
- know the difference between some useful file formats
- know about literate programming
Schedule
Total duration: 4 hours
Training materials
- You will need to fork the repository of the course.
Prerequisites
You will need some experience with R, an RStudio installation and a GitHub account.
Trainers
- Mariana Montes (mariana.montes@kuleuven.be)