2D Histograms in R

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

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')
library(plotly)

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(
)

fig2


Colorscale

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

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

fig


Z Matrix

If you want more control for the binning algorithm, you can supply a 2D table or matrix to z. In this case, the R package will impose it's colorscale default (and the colors argument can be used to control the colorscale from R):

cnt <- with(diamonds, table(cut, clarity))
fig <- plot_ly(diamonds, x = ~cut, y = ~clarity, z = ~cnt)

fig


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)
)
)
)