ggcorrplot: Visualization of a correlation matrix using ggplot2
The easiest way to visualize acorrelation matrix in R is to use the packagecorrplot.
In our previous article we also provided aquick-start guide for visualizing a correlation matrix using ggplot2.
Another solution is to use the functionggcorr() inggally package. However, the ggally package doesn’t provide any option for reordering the correlation matrix or for displaying the significance level.
In this article, we’ll describe the R packageggcorrplot for displaying easily a correlation matrix using ‘ggplot2’.
ggcorrplot main features
It provides a solution forreordering the correlation matrix and displays thesignificance level on the correlogram. It includes also a function for computing a matrix ofcorrelation p-values. It’s inspired from the packagecorrplot.
Installation and loading
ggcorrplot can be installed from CRAN as follow:
install.packages("ggcorrplot")Or, install the latest version from GitHub:
# Installif(!require(devtools)) install.packages("devtools")devtools::install_github("kassambara/ggcorrplot")Loading:
library(ggcorrplot)Getting started
Compute a correlation matrix
Themtcars data set will be used in the following R code. The functioncor_pmat() [inggcorrplot] computes a matrix of correlation p-values.
# Compute a correlation matrixdata(mtcars)corr<- round(cor(mtcars), 1)head(corr[, 1:6])## mpg cyl disp hp drat wt## mpg 1.0 -0.9 -0.8 -0.8 0.7 -0.9## cyl -0.9 1.0 0.9 0.8 -0.7 0.8## disp -0.8 0.9 1.0 0.8 -0.7 0.9## hp -0.8 0.8 0.8 1.0 -0.4 0.7## drat 0.7 -0.7 -0.7 -0.4 1.0 -0.7## wt -0.9 0.8 0.9 0.7 -0.7 1.0# Compute a matrix of correlation p-valuesp.mat<- cor_pmat(mtcars)head(p.mat[, 1:4])## mpg cyl disp hp## mpg 0.000000e+00 6.112687e-10 9.380327e-10 1.787835e-07## cyl 6.112687e-10 0.000000e+00 1.803002e-12 3.477861e-09## disp 9.380327e-10 1.803002e-12 0.000000e+00 7.142679e-08## hp 1.787835e-07 3.477861e-09 7.142679e-08 0.000000e+00## drat 1.776240e-05 8.244636e-06 5.282022e-06 9.988772e-03## wt 1.293959e-10 1.217567e-07 1.222311e-11 4.145827e-05Correlation matrix visualization
# Visualize the correlation matrix# --------------------------------# method = "square" (default)ggcorrplot(corr)
# method = "circle"ggcorrplot(corr, method = "circle")
# Reordering the correlation matrix# --------------------------------# using hierarchical clusteringggcorrplot(corr, hc.order = TRUE, outline.col = "white")
# Types of correlogram layout# --------------------------------# Get the lower triangleggcorrplot(corr, hc.order = TRUE, type = "lower", outline.col = "white")
# Get the upeper triangleggcorrplot(corr, hc.order = TRUE, type = "upper", outline.col = "white")
# Change colors and theme# --------------------------------# Argument colorsggcorrplot(corr, hc.order = TRUE, type = "lower", outline.col = "white", ggtheme = ggplot2::theme_gray, colors = c("#6D9EC1", "white", "#E46726"))
# Add correlation coefficients# --------------------------------# argument lab = TRUEggcorrplot(corr, hc.order = TRUE, type = "lower", lab = TRUE)
# Add correlation significance level# --------------------------------# Argument p.mat# Barring the no significant coefficientggcorrplot(corr, hc.order = TRUE, type = "lower", p.mat = p.mat)
# Leave blank on no significant coefficientggcorrplot(corr, p.mat = p.mat, hc.order = TRUE, type = "lower", insig = "blank")
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