# Continuous Color Scales and Color Bars in ggplot2

How to make Continuous Color Scales and Color Bars in ggplot2 with 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.

## Default colour scale

library(plotly)
library(ggplot2)

df <- data.frame(
x = runif(100),
y = runif(100),
z1 = rnorm(100),
z2 = abs(rnorm(100))
)

p <- ggplot(df, aes(x, y)) +
geom_point(aes(colour = z2))

ggplotly(p)


## Diverging colour scales

library(plotly)
library(ggplot2)

df <- data.frame(
x = runif(100),
y = runif(100),
z1 = rnorm(100),
z2 = abs(rnorm(100))
)

p <- ggplot(df, aes(x, y)) +
geom_point(aes(colour = z1)) +

ggplotly(p)


library(plotly)
library(ggplot2)

df <- data.frame(
x = runif(100),
y = runif(100),
z1 = rnorm(100),
z2 = abs(rnorm(100))
)

p <- ggplot(df, aes(x, y)) +
geom_point(aes(colour = z1)) +

ggplotly(p)


You can achievethe same result with the following aesthetic setup:

library(plotly)
library(ggplot2)

p <- ggplot(faithfuld, aes(waiting, eruptions)) +
geom_raster(aes(fill = density)) +

ggplotly(p)


## Adjust colour choices with low and high

library(plotly)
library(ggplot2)

df <- data.frame(
x = runif(100),
y = runif(100),
z1 = rnorm(100),
z2 = abs(rnorm(100))
)

p <- ggplot(df, aes(x, y)) +
geom_point(aes(colour = z2)) +
scale_colour_gradient(low = "white", high = "black")

ggplotly(p)


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)
)
)
) 