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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