Marginal distribution with ggplot2 and ggExtra



This post explains how to add marginal distributions to the X and Y axis of a ggplot2 scatterplot. It can be done using histogram, boxplot or density plot using the ggExtra library.

Scatter section About scatter

Basic use of ggMarginal()


Here are 3 examples of marginal distribution added on X and Y axis of a scatterplot. The ggExtra library makes it a breeze thanks to the ggMarginal() function. Three main types of distribution are available: histogram, density and boxplot.

# library
library(ggplot2)
library(ggExtra)
 
# The mtcars dataset is proposed in R
head(mtcars)
 
# classic plot :
p <- ggplot(mtcars, aes(x=wt, y=mpg, color=cyl, size=cyl)) +
      geom_point() +
      theme(legend.position="none")
 
# with marginal histogram
p1 <- ggMarginal(p, type="histogram")
 
# marginal density
p2 <- ggMarginal(p, type="density")
 
# marginal boxplot
p3 <- ggMarginal(p, type="boxplot")

More customization


Three additional examples to show possible customization:

# library
library(ggplot2)
library(ggExtra)
 
# The mtcars dataset is proposed in R
head(mtcars)
 
# classic plot :
p <- ggplot(mtcars, aes(x=wt, y=mpg, color=cyl, size=cyl)) +
      geom_point() +
      theme(legend.position="none")
 
# Set relative size of marginal plots (main plot 10x bigger than marginals)
p1 <- ggMarginal(p, type="histogram", size=10)
 
# Custom marginal plots:
p2 <- ggMarginal(p, type="histogram", fill = "slateblue", xparams = list(  bins=10))
 
# Show only marginal plot for x axis
p3 <- ggMarginal(p, margins = 'x', color="purple", size=4)

Related chart types


Scatter
Heatmap
Correlogram
Bubble
Connected scatter
Density 2d



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