One workflow for building effective (and pretty) {ggplot2} data visualizations

a workshop on iteratively building ggplots

MEDS
R
ggplot2
data visualization
Author
Affiliation

Samantha Csik

Master of Environmental Data Science Program @ The Bren School (UCSB) & The National Center for Ecological Analysis and Synthesis

Published

March 16, 2023

A fuzzy monster in a beret and scarf, critiquing their own column graph on a canvas in front of them while other assistant monsters (also in berets) carry over boxes full of elements that can be used to customize a graph (like themes and geometric shapes). In the background is a wall with framed data visualizations. Stylized text reads "ggplot2: build a data masterpiece."

Art by Allison Horst


materials source code

Abstract

{ggplot2} has, in many ways, become the de facto tool for data visualization in R. And with the many extension packages available, there’s hardly a limit to what you can create. Building effective and visually-pleasing data visualizations is a skill that gets easier with practice, and following a somewhat structured workflow – at least at the start – can help you get there faster. This workshop covers one approach for doing so, though you’ll find what works best for you with time.

Audience

This workshop was originally developed for the Master of Environmental Data Science (MEDS) program, administered by the Bren School of Environmental Science & Management in partnership with the National Center for Ecological Analysis and Synthesis.