Our next R course is at University of Queensland (Australia) from 18th Feburary 2020. Beginner, intermediate and advanced classes available.
RColorBrewer package makes choosing colours for your graphs easy.
If you follow the link on the help page for the handy
you can get to a web app that lets you choose the type of palette (linear, diverging, qualitative),
the number of colours and other options, like palettes that will be visable to people who are red-green colour
blind (about 4% of the population).
This all extremely useful, but
palettes are generally limited to a maximum of 10 different colours. What if you want to have a continuous scale?
Here I run through how to make a colour ramp from a Brewer palette.
Note though, that the designers of
RColorBrewer limited the number of colours as a deliberate choice.
The colour palettes are mainly designed for maps, and in general, people can't keep more than about 7
categories in their head at any one time. Hence, before you create your figure, think about how you want to represent on your figure. For instance, say you are plotting elevation. Choosing a few colours will emphasis zones in elevation, for instance, maybe you want to represent different vegetation zones that change with altitude. Whereas, a continuous palette will obviously represent the data as more of a gradient.
library(RColorBrewer) bluecols <- brewer.pal(9, 'Blues')
Which just makes a pie with nine different shades of blue. ### A colour ramp We can use the
colorRampPalette() function to create a new function, here
newcol() takes a single integer as an argument, which outputs the colour ramp using our blue palette.
newcol <- colorRampPalette(bluecols) ncols <- 100 bluecols2 <- newcol(ncols)#apply the function to get 100 colours
And that is it. We now have the
RColorBrewer palette with 100 different shades of blue.