scale_colour_grey {ggplot2} | R Documentation |
Based on gray.colors
scale_colour_grey(..., start = 0.2, end = 0.8, na.value = "red") scale_fill_grey(..., start = 0.2, end = 0.8, na.value = "grey50") scale_color_grey(..., start = 0.2, end = 0.8, na.value = "red")
start |
gray value at low end of palette |
end |
gray value at high end of palette |
... |
Other arguments passed on to
|
na.value |
Colour to use for missing values |
Other colour scales: scale_color_brewer
,
scale_color_continuous
,
scale_color_discrete
,
scale_color_gradient
,
scale_color_gradient2
,
scale_color_gradientn
,
scale_color_hue
,
scale_colour_brewer
,
scale_colour_continuous
,
scale_colour_discrete
,
scale_colour_gradient
,
scale_colour_gradient2
,
scale_colour_gradientn
,
scale_colour_hue
,
scale_fill_brewer
,
scale_fill_continuous
,
scale_fill_discrete
,
scale_fill_gradient
,
scale_fill_gradient2
,
scale_fill_gradientn
,
scale_fill_hue
p <- qplot(mpg, wt, data=mtcars, colour=factor(cyl)) p + scale_colour_grey() p + scale_colour_grey(end = 0) # You may want to turn off the pale grey background with this scale p + scale_colour_grey() + theme_bw() # Colour of missing values is controlled with na.value: miss <- factor(sample(c(NA, 1:5), nrow(mtcars), rep = TRUE)) qplot(mpg, wt, data = mtcars, colour = miss) + scale_colour_grey() qplot(mpg, wt, data = mtcars, colour = miss) + scale_colour_grey(na.value = "green")