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

...	Arguments passed on to `discrete_scale` `palette` 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 (e.g., `scales::hue_pal()`). `breaks` One of: `NULL` for no breaks `waiver()` for the default breaks (the scale limits) A character vector of breaks A function that takes the limits as input and returns breaks as output `limits` A character vector that defines possible values of the scale and their order. `drop` 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. `na.translate` 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`. `scale_name` The name of the scale that should be used for error messages associated with this scale. `name` 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. `labels` 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 `expand` For position scales, a 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 `expansion()` 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. `guide` A function used to create a guide or its name. See `guides()` for more information. `position` For position scales, The position of the axis. `left` or `right` for y axes, `top` or `bottom` for x axes. `super` The super class to use for the constructed scale
h	range of hues to use, in [0, 360]
c	chroma (intensity of colour), maximum value varies depending on combination of hue and luminance.
l	luminance (lightness), in [0, 100]
h.start	hue to start at
direction	direction to travel around the colour wheel, 1 = clockwise, -1 = counter-clockwise
na.value	Colour to use for missing values
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")`.

Examples

# \donttest{
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")
# }

Arguments

See also

Examples