Conference presentation about the colorspace toolbox for manipulating and assessing color palettes at useR! 2019 in Toulouse: Slides, video, replication materials, and working paper.

Abstract

(Authors: Achim Zeileis, Jason C. Fisher, Kurt Hornik, Ross Ihaka, Claire D. McWhite, Paul Murrell, Reto Stauffer, Claus O. Wilke)

The R package “colorspace” (http://colorspace.R-Forge.R-project.org/) provides a flexible toolbox for selecting individual colors or color palettes, manipulating these colors, and employing them in statistical graphics and data visualizations. In particular, the package provides a broad range of color palettes based on the HCL (Hue-Chroma-Luminance) color space. The three HCL dimensions have been shown to match those of the human visual system very well, thus facilitating intuitive selection of color palettes through trajectories in this space.

Namely, general strategies for three types of palettes are provided: (1) Qualitative for coding categorical information, i.e., where no particular ordering of categories is available and every color should receive the same perceptual weight. (2) Sequential for coding ordered/numeric information, i.e., going from high to low (or vice versa). (3) Diverging for coding ordered/numeric information around a central neutral value, i.e., where colors diverge from neutral to two extremes.

To aid selection and application of these palettes the package provides scales for use with ggplot2; shiny (and tcltk) apps for interactive exploration (see also http://hclwizard.org/); visualizations of palette properties; accompanying manipulation utilities (like desaturation and lighten/darken), and emulation of color vision deficiencies.

Resources

Links to: PDF slides, YouTube video, R code, arXiv working paper.

Furthermore, replication code for the introductory example (influenza risk map) was already provided in the recent endrainbow blog post.