Black Lives Matter. Please consider donating to Black Girls Code today.

2D Histograms in R

How to make a 2D histogram in R. A 2D histogram is a visualization of a bivariate distribution.

Building AI apps or dashboards in R? Deploy them to Dash Enterprise for hyper-scalability and pixel-perfect aesthetic.
10% of the Fortune 500 uses Dash Enterprise to productionize AI & data science apps. Find out if your company is using Dash Enterprise

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.

Basic 2D Histogram

2D histograms require x/y, but in contrast to heatmaps, z is optional. If z is not provided, binning occurs in the browser (see here for a list of binning options).

# install.packages('mvtnorm')

s <- matrix(c(1, -.75, -.75, 1), ncol = 2)
obs <- mvtnorm::rmvnorm(500, sigma = s)
fig <- plot_ly(x = obs[,1], y = obs[,2])
fig2 <- subplot(
  fig %>% add_markers(alpha = 0.2),
  fig %>% add_histogram2d()



If z is not provided, the only way to control coloring is through the colorscale attribute

fig <- fig %>% add_histogram2d(colorscale = "Blues")


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

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:


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


app <- Dash$new()

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