Advanced Data Visualization with ggplot2

Rice University Workshop (March 2021)

by Allison Horst

Workshop guide

Available here: https://allisonhorst.github.io/rice-data-viz/

Workshop outline

• Conceptual hierarchy of data viz
• ggplot2 basics review
  • Aesthetic mapping
  • Themes
  • Labels
  • Facets (& facet grids vs facet wraps)
  • Getting things in order (e.g. fct_reorder)
• Advanced customization in ggplot2
  • scales for thoughtful breaks and labels
  • …and color schemes (+ paletteer!)
  • In the weeds of themes (gridlines, panel colors, margins, etc.)
  • Direct annotation (as an alternative to legends)
  • Repulsive labels (e.g. ggrepel)
  • Highlighting for clarity (e.g. with gghighlight)
• Compound figures with patchwork
• A few new graph types to consider
  • Marginal plot
  • Beeswarm plots with ggbeeswarm
  • Heatmaps with geom_tile()
  • A map! in ggplot2
• Export & save your graphs
• Keep learning

Workshop prep:

There are two ways you can get the workshop materials:

1. Create a free RStudio Cloud account, and access the materials here: https://rstudio.cloud/project/2256278. If you use this option, make sure to click “Make permanent copy” or your work will be deleted when you close the project.

2. Fork & clone this repo to work locally.

Required packages:

Make sure you have recent versions of the following packages installed for the workshop:

General use packages:

• tidyverse
• here
• janitor

Specifically for plots:

• patchwork
• ggrepel
• gghighlight
• paletteer
• ggExtra
• ggbeeswarm

Spatial data simplified:

• sf

And for another dataset we’ll explore:

• gapminder