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# Heatmaps in R

How to make a heatmap in R with a matrix. Seven examples of colored and labeled heatmaps with custom colorscales.

Building AI apps or dashboards in R? Deploy them to Dash Enterprise for hyper-scalability and pixel-perfect aesthetic.
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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 Heatmap

library(plotly)
fig <- plot_ly(z = volcano, type = "heatmap")

fig


#### Categorical Axes

m <- matrix(rnorm(9), nrow = 3, ncol = 3)
fig <- plot_ly(
x = c("a", "b", "c"), y = c("d", "e", "f"),
z = m, type = "heatmap"
)

fig


#### Sequential Colorscales: Greys

The colors argument understands color brewer palettes (see RColorBrewer::brewer.pal.info for valid names).

fig <- plot_ly(z = volcano, colors = "Greys", type = "heatmap")

fig


#### Custom colorscales

The colors argument also accepts a color interpolation function like colorRamp()

fig <- plot_ly(z = volcano, colors = colorRamp(c("red", "green")), type = "heatmap")

fig


Or, you can do the scaling yourself and use the colorscale attribute directly...

vals <- unique(scales::rescale(c(volcano)))
o <- order(vals, decreasing = FALSE)
cols <- scales::col_numeric("Blues", domain = NULL)(vals)
colz <- setNames(data.frame(vals[o], cols[o]), NULL)
fig <- plot_ly(z = volcano, colorscale = colz, type = "heatmap")

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)
)
)
) 