Randomising qualitative colours for large sets in ggplot

Question

If you're mapping qualitatively to colour for a large number of groups, ggplot's automatic colour assignment plots very similar colours adjacently, making it hard to see which refer to which key etc. To illustrate:

require(ggplot2); require(stringr) df = data.frame(x = letters, y = sample(20:100,26), lab=word("apple ball cat dog elephant frog goat hat ice jackal king lion mango nest owl parrot queen rabbit ship tomato umbrella van watch xylophone yatch zebra", 1:26)) p = ggplot(df, aes(x, y, fill=lab)) + geom_bar(stat="identity") p + scale_fill_discrete() 

Its possible to mix up some random colours manually:

cols = rainbow(26, s=.6, v=.9)[sample(1:26,26)] p + scale_fill_manual(values=cols) 

.. resulting in more useful breakup of the rainbow, but this seems clumsy, still leaves some colours clumped together and is generally not ideal. Does ggplot have a native method to achieve something like this (but hopefully better)?

Answer 1

Producing a good palette for that many colours is indeed a difficult task. However, there is one solution which may be helpful. Some time ago I forked this repo and found a reference to iWantHue. As far as I can see, the resulting palette is already mixed, so that neighbouring colours look distinguishable.

For instance, for your example I have

Just in case, the palette is

"#89C5DA", "#DA5724", "#74D944", "#CE50CA", "#3F4921", "#C0717C", "#CBD588", "#5F7FC7",  "#673770", "#D3D93E", "#38333E", "#508578", "#D7C1B1", "#689030", "#AD6F3B", "#CD9BCD",  "#D14285", "#6DDE88", "#652926", "#7FDCC0", "#C84248", "#8569D5", "#5E738F", "#D1A33D",  "#8A7C64", "#599861"