2D Histograms in R

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


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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(
  fig %>% add_markers(alpha = 0.2),
  fig %>% add_histogram2d()
)

fig2
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Colorscale

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

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

fig
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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)
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