| 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")
... |
Other arguments passed on to |
start |
gray value at low end of palette |
end |
gray value at high end of palette |
na.value |
Colour to use for missing values |
Other colour scales: scale_color_brewer,
scale_color_distiller,
scale_colour_brewer,
scale_colour_distiller,
scale_fill_brewer,
scale_fill_distiller;
scale_color_continuous,
scale_color_gradient,
scale_colour_continuous,
scale_colour_gradient,
scale_fill_continuous,
scale_fill_gradient;
scale_color_discrete,
scale_color_hue,
scale_colour_discrete,
scale_colour_hue,
scale_fill_discrete,
scale_fill_hue;
scale_color_gradient2,
scale_colour_gradient2,
scale_fill_gradient2;
scale_color_gradientn,
scale_colour_gradientn,
scale_fill_gradientn
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")