Type: Package
Title: Visualization of a Correlation Matrix using 'ggplot2'
Version: 0.1.4.1
Description: The 'ggcorrplot' package can be used to visualize easily a correlation matrix using 'ggplot2'. It provides a solution for reordering the correlation matrix and displays the significance level on the plot. It also includes a function for computing a matrix of correlation p-values.
License: GPL-2
URL: http://www.sthda.com/english/wiki/ggcorrplot-visualization-of-a-correlation-matrix-using-ggplot2
BugReports: https://github.com/kassambara/ggcorrplot/issues
Depends: R (≥ 3.3), ggplot2 (≥ 3.3.6)
Imports: reshape2, stats
Suggests: testthat (≥ 3.0.0), knitr, spelling, vdiffr (≥ 1.0.0)
Encoding: UTF-8
Language: en-US
RoxygenNote: 7.1.0
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2023-09-05 15:45:33 UTC; hornik
Author: Alboukadel Kassambara [aut, cre], Indrajeet Patil ORCID iD [ctb] (Twitter: @patilindrajeets)
Maintainer: Alboukadel Kassambara <alboukadel.kassambara@gmail.com>
Repository: CRAN
Date/Publication: 2023-09-05 15:50:48 UTC

Visualization of a correlation matrix using ggplot2

Description

Usage

ggcorrplot(
  corr,
  method = c("square", "circle"),
  type = c("full", "lower", "upper"),
  ggtheme = ggplot2::theme_minimal,
  title = "",
  show.legend = TRUE,
  legend.title = "Corr",
  show.diag = NULL,
  colors = c("blue", "white", "red"),
  outline.color = "gray",
  hc.order = FALSE,
  hc.method = "complete",
  lab = FALSE,
  lab_col = "black",
  lab_size = 4,
  p.mat = NULL,
  sig.level = 0.05,
  insig = c("pch", "blank"),
  pch = 4,
  pch.col = "black",
  pch.cex = 5,
  tl.cex = 12,
  tl.col = "black",
  tl.srt = 45,
  digits = 2,
  as.is = FALSE
)

cor_pmat(x, ...)

Arguments

corr

the correlation matrix to visualize

method

character, the visualization method of correlation matrix to be used. Allowed values are "square" (default), "circle".

type

character, "full" (default), "lower" or "upper" display.

ggtheme

ggplot2 function or theme object. Default value is 'theme_minimal'. Allowed values are the official ggplot2 themes including theme_gray, theme_bw, theme_minimal, theme_classic, theme_void, .... Theme objects are also allowed (e.g., 'theme_classic()').

title

character, title of the graph.

show.legend

logical, if TRUE the legend is displayed.

legend.title

a character string for the legend title. lower triangular, upper triangular or full matrix.

show.diag

NULL or logical, whether display the correlation coefficients on the principal diagonal. If NULL, the default is to show diagonal correlation for type = "full" and to remove it when type is one of "upper" or "lower".

colors

a vector of 3 colors for low, mid and high correlation values.

outline.color

the outline color of square or circle. Default value is "gray".

hc.order

logical value. If TRUE, correlation matrix will be hc.ordered using hclust function.

hc.method

the agglomeration method to be used in hclust (see ?hclust).

lab

logical value. If TRUE, add correlation coefficient on the plot.

lab_col, lab_size

size and color to be used for the correlation coefficient labels. used when lab = TRUE.

p.mat

matrix of p-value. If NULL, arguments sig.level, insig, pch, pch.col, pch.cex is invalid.

sig.level

significant level, if the p-value in p-mat is bigger than sig.level, then the corresponding correlation coefficient is regarded as insignificant.

insig

character, specialized insignificant correlation coefficients, "pch" (default), "blank". If "blank", wipe away the corresponding glyphs; if "pch", add characters (see pch for details) on corresponding glyphs.

pch

add character on the glyphs of insignificant correlation coefficients (only valid when insig is "pch"). Default value is 4.

pch.col, pch.cex

the color and the cex (size) of pch (only valid when insig is "pch").

tl.cex, tl.col, tl.srt

the size, the color and the string rotation of text label (variable names).

digits

Decides the number of decimal digits to be displayed (Default: '2').

as.is

A logical passed to melt.array. If TRUE, dimnames will be left as strings instead of being converted using type.convert.

x

numeric matrix or data frame

...

other arguments to be passed to the function cor.test.

Value

Examples

# Compute a correlation matrix
data(mtcars)
corr <- round(cor(mtcars), 1)
corr

# Compute a matrix of correlation p-values
p.mat <- cor_pmat(mtcars)
p.mat

# Visualize the correlation matrix
# --------------------------------
# method = "square" or "circle"
ggcorrplot(corr)
ggcorrplot(corr, method = "circle")

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

# Types of correlogram layout
# --------------------------------
# Get the lower triangle
ggcorrplot(corr,
  hc.order = TRUE, type = "lower",
  outline.color = "white"
)
# Get the upeper triangle
ggcorrplot(corr,
  hc.order = TRUE, type = "upper",
  outline.color = "white"
)

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

# Add correlation coefficients
# --------------------------------
# argument lab = TRUE
ggcorrplot(corr,
  hc.order = TRUE, type = "lower",
  lab = TRUE,
  ggtheme = ggplot2::theme_dark(),
)

# Add correlation significance level
# --------------------------------
# Argument p.mat
# Barring the no significant coefficient
ggcorrplot(corr,
  hc.order = TRUE,
  type = "lower", p.mat = p.mat
)
# Leave blank on no significant coefficient
ggcorrplot(corr,
  p.mat = p.mat, hc.order = TRUE,
  type = "lower", insig = "blank"
)

# Changing number of digits for correlation coeffcient
# --------------------------------
ggcorrplot(cor(mtcars),
  type = "lower",
  insig = "blank",
  lab = TRUE,
  digits = 3
)