Colour related resources

rstudio

rstats

colour

Synthesis of links and resources on colours & data visualization

Author

Siobhon Egan

Published

August 2, 2022

As I need to reach for this information often I have decided to dedicate a solo post on all things colour related.

Figures are an important part of any publication. They are often the first thing readers look at and will help usually are the deciders as to whether non-specialists are going to read on…a good figure goes a long way! If you can spend the time it is well worth it (within reason of course). A good read on some do and dont’s for figures by Rougier et al. 2014 PLOS comp biol, while your at it check out this one by Mensh and Kording 2017.

🔗 General colour resources

GeoDataViz Toolkit
Your Friendly Guide to Colors in Data Visualisation by Lisa Charlotte Rost
Colorbrewer2
Color-hex
Coloring for colorblindness
Viz palette - love this resource!
CSS Colours
HTML colour names
HTML colour codes

🔗 R packages and resources

Viridis: One of my favourite colour palettes at the moment.
- Viridis Color Palette Generator
- ggplot2 and viridis
dehex: An R package containing simple functions and a Shiny app to help me train myself to ‘read’ a colour from its hex code.
prismatic: The goal of prismatic is to provide color manipulation tools in R, in a intuitive, low-dependency and functional way.
RColourBrewer
r-graph-gallery

Examples

Example for viridis to get 8 colours

library(viridis)

Loading required package: viridisLite

# get certain number of colours from viridis palette
newcols = viridis(8, option = "B")

RColour brewer - display colours and get their hex numbers

library(RColorBrewer)

# View a single RColorBrewer palette by specifying its name
display.brewer.pal(n = 8, name = 'Dark2')

# Hexadecimal color specification 
brewer.pal(n = 8, name = "Dark2")

[1] "#1B9E77" "#D95F02" "#7570B3" "#E7298A" "#66A61E" "#E6AB02" "#A6761D"
[8] "#666666"

More RColourbrewer palettes

# BrBG
display.brewer.pal(7,"BrBG")

brewer.pal(n = 7, name = "BrBG")

[1] "#8C510A" "#D8B365" "#F6E8C3" "#F5F5F5" "#C7EAE5" "#5AB4AC" "#01665E"

# Paired
display.brewer.pal(12,"Paired")

brewer.pal(n = 12, name = "Paired")

 [1] "#A6CEE3" "#1F78B4" "#B2DF8A" "#33A02C" "#FB9A99" "#E31A1C" "#FDBF6F"
 [8] "#FF7F00" "#CAB2D6" "#6A3D9A" "#FFFF99" "#B15928"

# Set2
display.brewer.pal(8,"Set2")

brewer.pal(n = 8, name = "Set2")

[1] "#66C2A5" "#FC8D62" "#8DA0CB" "#E78AC3" "#A6D854" "#FFD92F" "#E5C494"
[8] "#B3B3B3"

# Set3
display.brewer.pal(12,"Set3")

brewer.pal(n = 12, name = "Set3")

 [1] "#8DD3C7" "#FFFFB3" "#BEBADA" "#FB8072" "#80B1D3" "#FDB462" "#B3DE69"
 [8] "#FCCDE5" "#D9D9D9" "#BC80BD" "#CCEBC5" "#FFED6F"

Difference between discrete and continuous colours in a figure

library(viridis)
library(ggplot2)
p <- ggplot(mtcars, aes(wt, mpg))
p + geom_point(size=4, aes(colour = factor(cyl))) +
    scale_color_viridis(discrete=TRUE) +
    theme_bw()

p + geom_point(size=4, aes(colour = cyl)) +
    scale_color_viridis(discrete=FALSE) +
    theme_bw()

Show hex values of viridis palettes

library(scales)


Attaching package: 'scales'

The following object is masked from 'package:viridis':

    viridis_pal

show_col(viridis_pal()(20))

show_col(viridis_pal(option = 'A')(20))

show_col(viridis_pal(option = 'B')(20))

show_col(viridis_pal(option = 'C')(20))

show_col(viridis_pal(option = 'D')(20))

Make a vector with hex values of colours

# number of colours you want
q_colors =  15 # for no particular reason
v_colors =  viridis(q_colors, option = 'D')
v_colors

 [1] "#440154FF" "#481B6DFF" "#46337EFF" "#3F4889FF" "#365C8DFF" "#2E6E8EFF"
 [7] "#277F8EFF" "#21908CFF" "#1FA187FF" "#2DB27DFF" "#4AC16DFF" "#71CF57FF"
[13] "#9FDA3AFF" "#CFE11CFF" "#FDE725FF"