Resources & Further Reading

Here is a list of further resources.

Books (free online)

  • Kieran Healy, Data Visualization: A Practical Introduction. The book closest to this course: principles plus ggplot2 code, written for social scientists. The perceptual material in the Data Visualization section draws on Chapter 1.
  • Claus Wilke, Fundamentals of Data Visualization. The best single reference on which chart to use and why; code-free, so it pairs well with Healy. Wilke also wrote the colorblindr and cowplot packages used in this course.
  • Hadley Wickham et al., ggplot2: Elegant Graphics for Data Analysis. The grammar of graphics from its author; the reference once you’re past the basics.
  • Hadley Wickham et al., R for Data Science. For the wrangling (dplyr, tidyr) that comes before every good plot.
  • Rob Lovelace et al., Geocomputation with R . The standard reference for the spatial material in Applied Examples.

Books (print)

  • Edward Tufte, The Visual Display of Quantitative Information (1983). The classic behind data-ink, chartjunk, and the truthfulness principles cited throughout this course.
  • Alberto Cairo, How Charts Lie (2019) Chart literacy for consumers of graphs; excellent source of discussion examples.
  • Cole Nussbaumer Knaflic, Storytelling with Data (2015). Annotation and presentation-oriented; complements the Annotation & Storytelling page.
  • Jacques Bertin, Semiology of Graphics (1967). Where the idea of visual encoding channels began.

Key papers

Reference sites

Inspiration

Package index for this course

Purpose Packages
Core plotting ggplot2, patchwork
Data wrangling dplyr, tidyr, broom
Colors & themes viridis, ggthemes, colorspace, colorblindr, cowplot
Annotation ggrepel, gghighlight
Uncertainty ggdist, ggeffects, marginaleffects, margins
Tables gt, modelsummary
Interactive plotly, ggiraph, gganimate, leaflet, mapview
Spatial sf, terra, rnaturalearth, osmdata, blackmarbler, geodata, tidyterra
Export ragg, svglite
Data gapminder, vdemdata