Description Usage Arguments Details Examples
Create colour scales based on ColorBrewer colours.
1 2 3 4 5 6 7 8 9 | scale_colour_brewer(..., type = "seq", palette = 1)
scale_fill_brewer(..., type = "seq", palette = 1)
scale_colour_distiller(..., type = "seq", palette = 1, values = NULL,
space = "Lab", na.value = "grey50")
scale_fill_distiller(..., type = "seq", palette = 1, values = NULL,
space = "Lab", na.value = "grey50")
|
... |
Other arguments passed on to |
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 |
space |
colour space in which to calculate gradient. "Lab" usually best unless gradient goes through white. |
na.value |
Colour to use for missing values |
Note: this is an offshoot from ggplot2 with some added functions. I am not sure who the author is as the forum on which this appeared is now down. The functions of interest here are the bottom two, scale_colour_distiller and scale_fill_distiller which allow for nice brewer plots on continuous scales
ColorBrewer provides sequential, diverging and qualitative colour schemes which are particularly suited and tested to display discrete values (levels of a factor) on a map. ggplot2 can use those colours in discrete scales. It also allows to smoothly interpolate the colours to a continuous scale, although the original colour schemes (particularly the qualitative ones) were not intended for this. The perceptual result is left to the appreciation of the user.
See http://colorbrewer2.org for more information.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | dsamp <- diamonds[sample(nrow(diamonds), 1000), ]
(d <- qplot(carat, price, data=dsamp, colour=clarity))
# Change scale label
d + scale_colour_brewer()
d + scale_colour_brewer("clarity")
d + scale_colour_brewer(expression(clarity[beta]))
# Select brewer palette to use, see ?scales::brewer_pal for more details
d + scale_colour_brewer(type="seq")
d + scale_colour_brewer(type="seq", palette=3)
d + scale_colour_brewer(palette="Blues")
d + scale_colour_brewer(palette="Set1")
# scale_fill_brewer works just the same as
# scale_colour_brewer but for fill colours
ggplot(diamonds, aes(x=price, fill=cut)) +
geom_histogram(position="dodge", binwidth=1000) +
scale_fill_brewer()
# Generate map data
library(reshape2) # for melt
volcano3d <- melt(volcano)
names(volcano3d) <- c("x", "y", "z")
# Basic plot
v <- ggplot() + geom_tile(aes(x=x, y=y, fill=z), data=volcano3d)
v
v + scale_fill_distiller()
v + scale_fill_distiller(palette=2)
v + scale_fill_distiller(type="div")
v + scale_fill_distiller(palette="Spectral")
v + scale_fill_distiller(palette="Spectral", trans="reverse")
v + scale_fill_distiller(type="qual")
# Not appropriate for continuous data, issues a warning
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