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Our paper with Paul Murrell about color palettes in base R is now published in The :rstats: Journal:

Coloring in R's Blind Spot

https://doi.org/10.32614/RJ-2023-071

#rstats #dataviz #color

Screenshot: Coloring in R’s Blind Spot Abstract: Prior to version 4.0.0 R had a poor default color palette (using highly saturated red, green, blue, etc.) and provided very few alternative palettes, most of which also had poor perceptual properties (like the infamous rainbow palette). Starting with version 4.0.0 R gained a new and much improved default palette and, in addition, a selection of more than 100 well-established palettes are now available via the functions palette.colors() and hcl.colors(). The former provides a range of popular qualitative palettes for categorical data while the latter closely approximates many popular sequential and diverging palettes by systematically varying the perceptual hue, chroma, and luminance (HCL) properties in the palette. This paper provides a mix of contributions including an overview of the new color functions and the palettes they provide along with advice about which palettes are appropriate for specific tasks, especially with regard to making them accessible to viewers with color vision deficiencies.
Screenshot Figure 7: New qualitative palettes in base R available from the palette.colors() function. The label above each swatch shows the argument to provide to palette.colors() to produce the set of colors. The palette at top-left is the new default that is also produced by palette(). The "Okabe-Ito" palette is the default that is produced by palette.colors() (with no arguments).
Screenshot Figure 6: Hue, chroma, and luminance paths for the "YlGnBu" (left) and "Viridis" (right) palettes. These plots are created by the colorspace::specplot() function. For "YlGnBu" we can see that hue changes from blue to yellow, luminance increases monotonically, and chroma has a small peak in the blue range and then decreases with luminance. "Viridis", on the other hand, has almost the same trajectory for both hue and luminance, but chroma increases for the light colors.
Screenshot Table 1: An overview of the new palette functionality: For each main type of palette, the Purpose row describes what sort of data the type of palette is appropriate for, the Generate row gives the functions that can be used to generate palettes of that type, the List row names the functions that can be used to list available palettes, and the Robust row identifies two or three good default palettes of that type. Qualitative: Purpose: Categorical data Generate: palette.colors(), hcl.colors() List: palette.pals(), hcl.pals("qualitative") Robust: "Okabe-Ito", "R4" Sequential: Purpose: Ordered or numeric data (high → low) Generate: hcl.colors() List: hcl.pals("sequential") Robust: "Blues 3", "YlGnBu", "Viridis" Diverging: Purpose: Ordered or numeric data with a central value (high ← neutral → low) Generate: hcl.colors() List: hcl.pals("diverging"), hcl.pals("divergingx") Robust: "Purple-Green", "Blue-Red 3"

Coloring in R's Blind Spot

The R Journal
#dataviz #RStats #color

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