ggplot2: scale_brewer – R documentation

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scale_brewer

Sequential, diverging and qualitative colour scales from colorbrewer.org

Description

The brewer scales provides 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.

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.

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 arguement.

Note

The distiller scales extend brewer to continuous scales by smoothly interpolating 7 colours from any palette to a continuous scale. The fermenter scales provide binned versions of the brewer scales.

Examples

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")


# 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 discretize continuous data
v + scale_fill_fermenter()

ggplot2

Create Elegant Data Visualisations Using the Grammar of Graphics

v3.3.3

MIT + file LICENSE

Authors

Hadley Wickham [aut] (<https://orcid.org/0000-0003-4757-117X>), Winston Chang [aut] (<https://orcid.org/0000-0002-1576-2126>), Lionel Henry [aut], Thomas Lin Pedersen [aut, cre] (<https://orcid.org/0000-0002-5147-4711>), Kohske Takahashi [aut], Claus Wilke [aut] (<https://orcid.org/0000-0002-7470-9261>), Kara Woo [aut] (<https://orcid.org/0000-0002-5125-4188>), Hiroaki Yutani [aut] (<https://orcid.org/0000-0002-3385-7233>), Dewey Dunnington [aut] (<https://orcid.org/0000-0002-9415-4582>), RStudio [cph, fnd]

Initial release