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-05

    Correlation matrix visualization

    # Visualize the correlation matrix# --------------------------------# method = "square" (default)ggcorrplot(corr)

    ggcorrplot R package: Visualization of a correlation matrix using ggplot2

    # method = "circle"ggcorrplot(corr, method = "circle")

    ggcorrplot R package: Visualization of a correlation matrix using ggplot2

    # Reordering the correlation matrix# --------------------------------# using hierarchical clusteringggcorrplot(corr, hc.order = TRUE, outline.col = "white")

    ggcorrplot R package: Visualization of a correlation matrix using ggplot2

    # Types of correlogram layout# --------------------------------# Get the lower triangleggcorrplot(corr, hc.order = TRUE, type = "lower",     outline.col = "white")

    ggcorrplot R package: Visualization of a correlation matrix using ggplot2

    # Get the upeper triangleggcorrplot(corr, hc.order = TRUE, type = "upper",     outline.col = "white")

    ggcorrplot R package: Visualization of a correlation matrix using ggplot2

    # Change colors and theme# --------------------------------# Argument colorsggcorrplot(corr, hc.order = TRUE, type = "lower",   outline.col = "white",   ggtheme = ggplot2::theme_gray,   colors = c("#6D9EC1", "white", "#E46726"))

    ggcorrplot R package: Visualization of a correlation matrix using ggplot2

    # Add correlation coefficients# --------------------------------# argument lab = TRUEggcorrplot(corr, hc.order = TRUE, type = "lower",   lab = TRUE)

    ggcorrplot R package: Visualization of a correlation matrix using ggplot2

    # Add correlation significance level# --------------------------------# Argument p.mat# Barring the no significant coefficientggcorrplot(corr, hc.order = TRUE,    type = "lower", p.mat = p.mat)

    ggcorrplot R package: Visualization of a correlation matrix using ggplot2

    # Leave blank on no significant coefficientggcorrplot(corr, p.mat = p.mat, hc.order = TRUE,    type = "lower", insig = "blank")

    ggcorrplot R package: Visualization of a correlation matrix using ggplot2


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