scale_hue: Evenly spaced colours for discrete data

In SahaRahul/ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics

Description

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.

Usage

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

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

Arguments

...	Arguments passed on to discrete_scale breaks 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 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. na.value 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. aesthetics The names of the aesthetics that this scale works with scale_name The name of the 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 name The name of the scale. Used as 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 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. guide A function used to create a guide or its name. See guides() for more info. position The position of the axis. "left" or "right" for vertical scales, "top" or "bottom" for horizontal scales 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

See Also

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

Examples

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")

SahaRahul/ggplot2 documentation built on May 17, 2019, 1:46 p.m.