Colour

Data to help with plots

dt1 <- expand.grid(x = 1:5, y = 1:5) |>
  mutate(A = sample(letters[1:5], 25, replace = TRUE),
         B = runif(25))
p1 <- dt1 |> ggplot(aes(x, y, color = A)) + geom_point(size = 10)
p1

p2 <- dt1 |> ggplot(aes(x, y, color = B)) + geom_point(size = 10)
p2

Generate some RGB colours

rgb(0.9, 0.1, 0.5, 1.0)

## [1] "#E61A80FF"

rgb(1,1,1,0.5)

## [1] "#FFFFFF80"

rgb(0,1,1,1)

## [1] "#00FFFFFF"

colours_rgb <- c(rgb(1, 0, 0), rgb(0.5, 0.5, 0), rgb(0, 0.7, 0), rgb(0, 0.5, 0.5), rgb(0, 0, 1) )
p1 + scale_color_manual(values = colours_rgb)

# p2 + scale_color_manual(values = colours_rgb, breaks = (0:5)/5) # error

Generate some HCL colours

See: https://hclwizard.org/why-hcl/

hcl(0, 35, 85)

## [1] "#FFC5D0"

hcl(50, 0, 85)

## [1] "#D4D4D4"

colours_hcl <- hcl((0:4)*360/5, 40, 85) # h is 0-360, c and l are 0-100, but not all values correspond to colours the computer can display
p1 + scale_color_manual(values = colours_hcl)

Get colours from a palette

p1 + scale_color_brewer(palette = "Greens")  # discrete colours, dicrete data

p2 + scale_color_fermenter(palette = "Greens") # discrete colours, continuous data

p2 + scale_color_distiller(palette = "Greens") # continuous colours, continuous data

p1 + scale_color_brewer(palette = "Set1")  # discrete colours, dicrete data

p2 + scale_color_fermenter(palette = "Set1") # discrete colours, continuous data

p2 + scale_color_distiller(palette = "Set1") # continuous colours, continuous data

More palettes: see help for scale_colour_brewer and pick among: diverging, qualitative, sequential

Easy recommendation

Viridis

# library(viridisLite)
p1 + scale_color_viridis_d(begin = 0, end = 1)  # discrete

p2 + scale_color_viridis_b(begin = 0, end = 1)  # binned

p2 + scale_color_viridis_c(begin = 0, end = 1)  # continuous