Reproducible Data Processing and Visualization

in R and tidyverse

Author

Ian Hussey

Published

April 5, 2026

Introduction

This Open Source eBook provides materials for the semester-long Master’s seminar course “Reproducible Data Processing and Visualization in R” that I teach at the University of Bern’s Institute of Psychology.

How to use this book

This book is made up of individual Quarto (.qmd) workbooks. Many of the exercises are easiest to complete in your own local copy of these .qmd files.

I suggest that you download a .zip of the contents of this book’s code and data from GitHub to run the code locally, complete the exercises, etc.

You can also copy and paste the code for any chapter directly from the website. Click the “</> Code” button on the top right of each page to see the full .qmd file’s code. You can copy and paste this into a .qmd file. However, it’s probably easier to download all the .qmd files and data as mentioned above.

Learning to code is a practice skill. Almost anyone can become competent in writing reproducible code for data processing and visualization with practice. More than anything else, completing this course requires that you practice in your own time, using not only the examples provided but also ones you create yourself. Take real data sets from your own studies, or the thousands available on the Open Science Framework (osf.io), or create simulated messy datasets with my R package {truffle} and practice.

Other learning resources

There are many excellent Open Source resources to learn R and {tidyverse} for data processing and visualization. Readers are encouraged to seek them out to support the materials already provided in this book. I can particularly recommend the following ones:

Citation

If you use this book, please cite it as:

Hussey, I. (2026). Reproducible data processing and visualization in R and tidyverse. wrangling.tidyver.se doi: 10.5281/zenodo.19427860

DOI

Contributing

If you are interested in contributing to or adapting this eBook, all code and data are available on GitHub.