Correlation matrix with ggally


This post explains how to build a correlogram with the ggally R package. It provides several reproducible examples with explanation and R code.

Correlogram section Data to Viz

Scatterplot matrix with ggpairs()

The ggpairs() function of the GGally package allows to build a great scatterplot matrix.

Scatterplots of each pair of numeric variable are drawn on the left part of the figure. Pearson correlation is displayed on the right. Variable distribution is available on the diagonal.

Visualize correlation with ggcorr()

The ggcorr() function allows to visualize the correlation of each pair of variable as a square. Note that the method argument allows to pick the correlation type you desire.

Split by group

It is possible to use ggplot2 aesthetics on the chart, for instance to color each category.

# Quick display of two cabapilities of GGally, to assess the distribution and correlation of variables 
library(GGally)
 
# From the help page:
data(flea)
ggpairs(flea, columns = 2:4, ggplot2::aes(colour=species))

Change plot types

Change the type of plot used on each part of the correlogram. This is done with the upper and lower argument. 

# Quick display of two cabapilities of GGally, to assess the distribution and correlation of variables 
library(GGally)
 
# From the help page:
data(tips, package = "reshape")
ggpairs(
  tips[, c(1, 3, 4, 2)],
  upper = list(continuous = "density", combo = "box_no_facet"),
  lower = list(continuous = "points", combo = "dot_no_facet")
)

Related chart types
Scatter
Heatmap
Correlogram
Bubble
Connected scatter
Density 2d



Contact

This document is a work by Yan Holtz. Any feedback is highly encouraged. You can fill an issue on Github, drop me a message on Twitter, or send an email pasting yan.holtz.data with gmail.com.

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