Colour scales
For discrete colours use scale_colour_palette_d().
ggplot(diamonds[sample(nrow(diamonds), 1000), ], aes(carat, price)) +
geom_point(aes(colour = clarity)) +
scale_colour_palette_d(met_palettes$VanGogh3)
Continuous or binned colours can be used with continuous data. For continuous colours use scale_colour_palette_c(). For binned colours use scale_colour_palette_b().
hwy_mpg <- ggplot(mpg, aes(displ, hwy, colour = hwy)) +
geom_point()
hwy_mpg + scale_colour_palette_c(met_palettes$Greek)
hwy_mpg + scale_colour_palette_b(met_palettes$Greek)
Fill scales
For discrete fills use scale_fill_palette_d().
ggplot(diamonds, aes(x = price, fill = cut)) +
geom_histogram(position = "dodge", binwidth = 1000) +
scale_fill_palette_d(pnw_palettes$Sunset)
Continuous or binned fills can be used with continuous data. For continuous fills use scale_fill_palette_c(). For binned fills use scale_fill_palette_b().
eruptions <- ggplot(faithfuld, aes(waiting, eruptions, fill = density)) +
geom_tile()
eruptions + scale_fill_palette_c(viridis_palettes$mako)
eruptions + scale_fill_palette_b(viridis_palettes$mako)
Customizing scales
The scale_ functions can all pass arguments to the appropriate scale constructors in ggplot2 if you need to control the name, limits, breaks, labels, and so forth of colour and fill scales. The arguments are passed with ... to the appropriate scale constructor for each function:
ggplot2::discrete_scale() for scale_colour_palette_d() and scale_fill_palette_d()ggplot2::continuous_scale() for scale_colour_palette_c() and scale_fill_palette_c()ggplot2::binned_scale() for scale_colour_palette_b() and scale_fill_palette_b()
This is particularly useful when you need to change how colours are mapped to values in a scale. For example, a common problem when working with divergent colour palettes is getting the middle colour in a palette to align with a fixed value representing the mid-point of a continuous scale.
To demonstrate, say we have mean treatment outcome results from four groups in a clinical trial.
treatment_results <- data.frame(
group = LETTERS[1:4],
outcome = c(-0.5, -1.1, 1.9, 2.3)
)
We want to plot the outcomes as a diverging bar chart with divergent fills. By default, the fill scale’s mid-point is the mean of the four groups, but we want it to be zero.
ggplot(treatment_results, aes(x = group, y = outcome, fill = outcome)) +
geom_col() +
scale_fill_palette_c(met_palettes$Benedictus)
We can use the rescaler argument in ggplot2::continuous_scale(), which accepts a function used to scale the input values to the range [0, 1], to scale the fill values to have a mid-point of zero. For scaling the mid-point use scales::rescale_mid().
ggplot(treatment_results, aes(x = group, y = outcome, fill = outcome)) +
geom_col() +
scale_fill_palette_c(
met_palettes$Benedictus,
rescaler = ~ rescale_mid(.x, mid = 0)
)
