Learn R Programming

ggplot2 (version 3.4.0)

scale_colour_brewer: Sequential, diverging and qualitative colour scales from ColorBrewer

Description

The brewer scales provide sequential, diverging and qualitative colour schemes from ColorBrewer. These are particularly well suited to display discrete values on a map. See https://colorbrewer2.org for more information.

Usage

scale_colour_brewer(
  ...,
  type = "seq",
  palette = 1,
  direction = 1,
  aesthetics = "colour"
)

scale_fill_brewer( ..., type = "seq", palette = 1, direction = 1, aesthetics = "fill" )

scale_colour_distiller( ..., type = "seq", palette = 1, direction = -1, values = NULL, space = "Lab", na.value = "grey50", guide = "colourbar", aesthetics = "colour" )

scale_fill_distiller( ..., type = "seq", palette = 1, direction = -1, values = NULL, space = "Lab", na.value = "grey50", guide = "colourbar", aesthetics = "fill" )

scale_colour_fermenter( ..., type = "seq", palette = 1, direction = -1, na.value = "grey50", guide = "coloursteps", aesthetics = "colour" )

scale_fill_fermenter( ..., type = "seq", palette = 1, direction = -1, na.value = "grey50", guide = "coloursteps", aesthetics = "fill" )

Arguments

...

Other arguments passed on to discrete_scale(), continuous_scale(), or binned_scale(), for brewer, distiller, and fermenter variants respectively, to control name, limits, breaks, labels and so forth.

type

One of "seq" (sequential), "div" (diverging) or "qual" (qualitative)

palette

If a string, will use that named palette. If a number, will index into the list of palettes of appropriate type. The list of available palettes can found in the Palettes section.

direction

Sets the order of colours in the scale. If 1, the default, colours are as output by RColorBrewer::brewer.pal(). If -1, the order of colours is reversed.

aesthetics

Character string or vector of character strings listing the name(s) of the aesthetic(s) that this scale works with. This can be useful, for example, to apply colour settings to the colour and fill aesthetics at the same time, via aesthetics = c("colour", "fill").

values

if colours should not be evenly positioned along the gradient this vector gives the position (between 0 and 1) for each colour in the colours vector. See rescale() for a convenience function to map an arbitrary range to between 0 and 1.

space

colour space in which to calculate gradient. Must be "Lab" - other values are deprecated.

na.value

Colour to use for missing values

guide

Type of legend. Use "colourbar" for continuous colour bar, or "legend" for discrete colour legend.

Palettes

The following palettes are available for use with these scales:

Diverging

BrBG, PiYG, PRGn, PuOr, RdBu, RdGy, RdYlBu, RdYlGn, Spectral

Qualitative

Accent, Dark2, Paired, Pastel1, Pastel2, Set1, Set2, Set3

Sequential

Blues, BuGn, BuPu, GnBu, Greens, Greys, Oranges, OrRd, PuBu, PuBuGn, PuRd, Purples, RdPu, Reds, YlGn, YlGnBu, YlOrBr, YlOrRd

Modify the palette through the palette argument.

Details

The brewer scales were carefully designed and tested on discrete data. They were not designed to be extended to continuous data, but results often look good. Your mileage may vary.

See Also

Other colour scales: scale_alpha(), scale_colour_continuous(), scale_colour_gradient(), scale_colour_grey(), scale_colour_hue(), scale_colour_steps(), scale_colour_viridis_d()

Examples

Run this code
set.seed(596)
dsamp <- diamonds[sample(nrow(diamonds), 1000), ]
(d <- ggplot(dsamp, aes(carat, price)) +
  geom_point(aes(colour = clarity)))
d + scale_colour_brewer()

# Change scale label
d + scale_colour_brewer("Diamond\nclarity")

# Select brewer palette to use, see ?scales::brewer_pal for more details
d + scale_colour_brewer(palette = "Greens")
d + scale_colour_brewer(palette = "Set1")

# \donttest{
# scale_fill_brewer works just the same as
# scale_colour_brewer but for fill colours
p <- ggplot(diamonds, aes(x = price, fill = cut)) +
  geom_histogram(position = "dodge", binwidth = 1000)
p + scale_fill_brewer()
# the order of colour can be reversed
p + scale_fill_brewer(direction = -1)
# the brewer scales look better on a darker background
p +
  scale_fill_brewer(direction = -1) +
  theme_dark()
# }

# Use distiller variant with continous data
v <- ggplot(faithfuld) +
  geom_tile(aes(waiting, eruptions, fill = density))
v
v + scale_fill_distiller()
v + scale_fill_distiller(palette = "Spectral")

# or use blender variants to discretise continuous data
v + scale_fill_fermenter()

Run the code above in your browser using DataLab