grafify internally includes colour-blind compatible schemes for fill and colour/color aesthetics. Note that these only work for categorical variables. Use the brewer or viridis packages for numeric gradient scales.

scale_fill_grafify(palette = "all_grafify", reverse = FALSE, ...)

Arguments

palette

Name of the colour scheme. Default set to palette = "all_grafify". Provide names as above in quotes.

reverse

Whether the colour order should be reversed.

...

Additional parameters for scale_fill or scale_colour.

Value

ggplot scale_fill function for discrete colours.

Details

The default for scale_fill_grafify(), scale_colour_grafify() or scale_color_grafify() is a list of 55 colours as part of palette = "all_grafify".

Obviously, it is not recommended to use so many colours, but implementing this was easiest to prevent errors when using a lot of categorical variables.

Colours available can be seen quickly with plot_grafify_palette. There are eight palettes with 5-10 colours each, which are recommended. These can be called by naming the colour scheme using palette = argument. Additional options include "okabe_ito", "vibrant, "bright", "pale", "muted", "dark", "light", and "contrast". These are taken from Paul Taul, Mike Mol and Okabe Ito. scale_fill_grafify2 and scale_colour_grafify2 are identical except that when the number of categorical variables is fewer than the total number of colour shades in the palette (e.g. if you have 3 groups and the "okabe_ito" palette has 7 colours), these functions will pick the most 'distant' colours from the scheme than going sequentially. If you want colours assigned sequentially use scale_fill_grafify or scale_colour_grafify.

Examples

#add a grafify fill scheme to ggplot
ggplot(emmeans::neuralgia, aes(x = Treatment, y = Duration))+
geom_point(aes(fill = Treatment), shape = 21, size = 3,
position = position_jitter(0.15), alpha = 0.8)+
scale_fill_grafify(palette = "muted")+facet_wrap("Sex")

#reverse colour order
ggplot(emmeans::neuralgia, aes(x = Treatment, y = Duration))+
geom_point(aes(fill = Treatment), shape = 21, size = 3,
position = position_jitter(0.15), alpha = 0.8)+
scale_fill_grafify(palette = "muted", reverse = TRUE)+facet_wrap("Sex")