Data Visualization with ggplot2
Workshop 30 - Winter Semester 2026-27
Overview
Core ggplot2 grammar, clean figure design, plotting mistakes, uncertainty, model-based plots, and publication-ready figures.
Effective data visualization is central to communicating research findings accurately and persuasively. This session takes participants from basic exploratory plots to publication-quality figures using R's ggplot2 ecosystem.
Topics Covered
- The Grammar of Graphics: Layers, aesthetics (
aes), geoms, scales, coordinates, and facets - Common Plotting Pitfalls: Dynamite plots (bar charts with error bars), truncated axes, misleading dual axes, and color choice
- Visualizing Distributions & Uncertainty: Raincloud plots, violin plots, boxplots, and credible/confidence intervals
- Model-Based Visualizations: Plotting predictions, marginal effects, and interactions from linear and mixed-effects models (
marginaleffects,ggeffects) - Polishing for Publication: Theme customisation, font styling, accessible colour scales (viridis, ColorBrewer), multi-panel figures with
patchworkorcowplot, and high-resolution exports
Session Details
- Date: 18 November 2026
- Time: 14:00 - 15:30
- Location: House of Prominence, Attic (Top floor), Luxemburger Str. 299, Cologne
- Speaker: Job Schepens
Related CRC 1252 Workshops
- Workshop 07: Coding in R Basics — Getting started with R
- Workshop 20: Advanced R: Working with Data Frames — Wrangling data into tidy format for plotting
- Workshop 27: lme4 Model Criticism — Evaluating and interpreting mixed-effects models
- Workshop 31: Data Visualization with Other Tools — Alternative visualization tools in Python and web technologies