Evenly spaced colours for discrete data

This is the default colour scale for categorical variables. It maps each level to an evenly spaced hue on the colour wheel. It does not generate colour-blind safe palettes.

scale_colour_hue(..., h = c(0, 360) + 15, c = 100, l = 65,
  h.start = 0, direction = 1, na.value = "grey50",
  aesthetics = "colour")

scale_fill_hue(..., h = c(0, 360) + 15, c = 100, l = 65, h.start = 0, direction = 1, na.value = "grey50", aesthetics = "fill")


Arguments passed on to discrete_scale


A palette function that when called with a single integer argument (the number of levels in the scale) returns the values that they should take.


One of:

  • NULL for no breaks

  • waiver() for the default breaks computed by the transformation object

  • A character vector of breaks

  • A function that takes the limits as input and returns breaks as output


A character vector that defines possible values of the scale and their order.


Should unused factor levels be omitted from the scale? The default, TRUE, uses the levels that appear in the data; FALSE uses all the levels in the factor.


Unlike continuous scales, discrete scales can easily show missing values, and do so by default. If you want to remove missing values from a discrete scale, specify na.translate = FALSE.


If na.translate = TRUE, what value aesthetic value should missing be displayed as? Does not apply to position scales where NA is always placed at the far right.


The name of the scale


The name of the scale. Used as the axis or legend title. If waiver(), the default, the name of the scale is taken from the first mapping used for that aesthetic. If NULL, the legend title will be omitted.


One of:

  • NULL for no labels

  • waiver() for the default labels computed by the transformation object

  • A character vector giving labels (must be same length as breaks)

  • A function that takes the breaks as input and returns labels as output


Vector of range expansion constants used to add some padding around the data, to ensure that they are placed some distance away from the axes. Use the convenience function expand_scale() to generate the values for the expand argument. The defaults are to expand the scale by 5% on each side for continuous variables, and by 0.6 units on each side for discrete variables.


A function used to create a guide or its name. See guides() for more info.


The position of the axis. "left" or "right" for vertical scales, "top" or "bottom" for horizontal scales


The super class to use for the constructed scale


range of hues to use, in [0, 360]


chroma (intensity of colour), maximum value varies depending on combination of hue and luminance.


luminance (lightness), in [0, 100]


hue to start at


direction to travel around the colour wheel, 1 = clockwise, -1 = counter-clockwise


Colour to use for missing values


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").

See Also

Other colour scales: scale_alpha, scale_colour_brewer, scale_colour_gradient, scale_colour_grey, scale_colour_viridis_d

  • scale_colour_hue
  • scale_fill_hue
  • scale_colour_discrete
  • scale_fill_discrete
  • scale_color_discrete
  • scale_color_hue
dsamp <- diamonds[sample(nrow(diamonds), 1000), ]
(d <- ggplot(dsamp, aes(carat, price)) + geom_point(aes(colour = clarity)))

# Change scale label
d + scale_colour_hue()
d + scale_colour_hue("clarity")
d + scale_colour_hue(expression(clarity[beta]))

# Adjust luminosity and chroma
d + scale_colour_hue(l = 40, c = 30)
d + scale_colour_hue(l = 70, c = 30)
d + scale_colour_hue(l = 70, c = 150)
d + scale_colour_hue(l = 80, c = 150)

# Change range of hues used
d + scale_colour_hue(h = c(0, 90))
d + scale_colour_hue(h = c(90, 180))
d + scale_colour_hue(h = c(180, 270))
d + scale_colour_hue(h = c(270, 360))

# Vary opacity
# (only works with pdf, quartz and cairo devices)
d <- ggplot(dsamp, aes(carat, price, colour = clarity))
d + geom_point(alpha = 0.9)
d + geom_point(alpha = 0.5)
d + geom_point(alpha = 0.2)

# Colour of missing values is controlled with na.value:
miss <- factor(sample(c(NA, 1:5), nrow(mtcars), replace = TRUE))
ggplot(mtcars, aes(mpg, wt)) + geom_point(aes(colour = miss))
ggplot(mtcars, aes(mpg, wt)) +
  geom_point(aes(colour = miss)) +
  scale_colour_hue(na.value = "black")
# }
Documentation reproduced from package ggplot2, version 3.2.0, License: GPL-2 | file LICENSE

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