Built-in Continuous Color Scales in R

A reference for the built-in named continuous (sequential, diverging and cyclical) color scales in Plotly.

New to Plotly?

Plotly is a free and open-source graphing library for R. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

Using Built-In Continuous Color Scales

Plotly R supports a large number of built-in continuous color scales. These can be viewed and used with the 'RColorBrewer' package.

When using continuous color scales, you will often want to configure various aspects of its range and colorbar.

Discrete Color Sequences

Plotly also comes with some built-in discrete color sequences.

Supported Built-In Continuous Color Scales

You can use any of the following names as string values to set colorscale arguments. These strings are case-sensitive.

library("RColorBrewer")
brewer.pal.info

##          maxcolors category colorblind
## BrBG            11      div       TRUE
## PiYG            11      div       TRUE
## PRGn            11      div       TRUE
## PuOr            11      div       TRUE
## RdBu            11      div       TRUE
## RdGy            11      div      FALSE
## RdYlBu          11      div       TRUE
## RdYlGn          11      div      FALSE
## Spectral        11      div      FALSE
## Accent           8     qual      FALSE
## Dark2            8     qual       TRUE
## Paired          12     qual       TRUE
## Pastel1          9     qual      FALSE
## Pastel2          8     qual      FALSE
## Set1             9     qual      FALSE
## Set2             8     qual       TRUE
## Set3            12     qual      FALSE
## Blues            9      seq       TRUE
## BuGn             9      seq       TRUE
## BuPu             9      seq       TRUE
## GnBu             9      seq       TRUE
## Greens           9      seq       TRUE
## Greys            9      seq       TRUE
## Oranges          9      seq       TRUE
## OrRd             9      seq       TRUE
## PuBu             9      seq       TRUE
## PuBuGn           9      seq       TRUE
## PuRd             9      seq       TRUE
## Purples          9      seq       TRUE
## RdPu             9      seq       TRUE
## Reds             9      seq       TRUE
## YlGn             9      seq       TRUE
## YlGnBu           9      seq       TRUE
## YlOrBr           9      seq       TRUE
## YlOrRd           9      seq       TRUE

Built-in color scales are stored as a string of CSS colors:

library("RColorBrewer")
brewer.pal(n = 8, name = "YlGn")

## [1] "#FFFFE5" "#F7FCB9" "#D9F0A3" "#ADDD8E" "#78C679" "#41AB5D" "#238443"
## [8] "#005A32"

Built-In Sequential Color scales

A collection of predefined sequential colorscales is provided in the 'RColorBrewer' package. Sequential color scales are appropriate for most continuous data, but in some cases it can be helpful to use a diverging or cyclical color scale (see below).

Here are all the built-in sequential scales in the 'RColorBrewer' package:

library("RColorBrewer")
display.brewer.all(type = 'seq')

Built-In Diverging Color scales

A collection of predefined diverging color scales is provided in the 'RColorBrewer' package. Diverging color scales are appropriate for continuous data that has a natural midpoint or an otherwise informative special value, such as 0 altitude, or the boiling point of a liquid. These scales are intended to be used when explicitly setting the midpoint of the scale.

Here are all the built-in diverging scales in the 'RColorBrewer' package:

library("RColorBrewer")
display.brewer.all(type = 'div')

What About Dash?

Dash for R is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash for R at https://dashr.plot.ly/installation.

Everywhere in this page that you see fig, you can display the same figure in a Dash for R application by passing it to the figure argument of the Graph component from the built-in dashCoreComponents package like this:

library(plotly)

fig <- plot_ly() 
# fig <- fig %>% add_trace( ... )
# fig <- fig %>% layout( ... ) 

library(dash)
library(dashCoreComponents)
library(dashHtmlComponents)

app <- Dash$new()
app$layout(
    htmlDiv(
        list(
            dccGraph(figure=fig) 
        )
     )
)

app$run_server(debug=TRUE, dev_tools_hot_reload=FALSE)