rstatix (version 0.7.2)

cor_plot: Visualize Correlation Matrix Using Base Plot

Description

Provide a tibble-friendly framework to visualize a correlation matrix. Wrapper around the R base function corrplot(). Compared to corrplot(), it can handle directly the output of the functions cor_mat() (in rstatix), rcorr() (in Hmisc), correlate() (in corrr) and cor() (in stats).

The p-values contained in the outputs of the functions cor_mat() and rcorr() are automatically detected and used in the visualization.

Usage

cor_plot(
  cor.mat,
  method = "circle",
  type = "full",
  palette = NULL,
  p.mat = NULL,
  significant.level = 0.05,
  insignificant = c("cross", "blank"),
  label = FALSE,
  font.label = list(),
  ...
)

Arguments

cor.mat

the correlation matrix to visualize

method

Character, the visualization method of correlation matrix to be used. Currently, it supports seven methods, named "circle" (default), "square", "ellipse", "number", "pie", "shade" and "color". See examples for details.

The areas of circles or squares show the absolute value of corresponding correlation coefficients. Method "pie" and "shade" came from Michael Friendly's job (with some adjustment about the shade added on), and "ellipse" came from D.J. Murdoch and E.D. Chow's job, see in section References.

type

Character, "full" (default), "upper" or "lower", display full matrix, lower triangular or upper triangular matrix.

palette

character vector containing the color palette.

p.mat

matrix of p-value corresponding to the correlation matrix.

significant.level

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

insignificant

character, specialized insignificant correlation coefficients, "cross" (default), "blank". If "blank", wipe away the corresponding glyphs; if "cross", add crosses (X) on corresponding glyphs.

label

logical value. If TRUE, shows the correlation coefficient labels.

font.label

a list with one or more of the following elements: size (e.g., 1), color (e.g., "black") and style (e.g., "bold"). Used to customize the correlation coefficient labels. For example font.label = list(size = 1, color = "black", style = "bold").

...

additional options not listed (i.e. "tl.cex") here to pass to corrplot.

See Also

cor_as_symbols()

Examples

# Compute correlation matrix
#::::::::::::::::::::::::::::::::::::::::::
cor.mat <- mtcars %>%
  select(mpg, disp, hp, drat, wt, qsec) %>%
  cor_mat()

# Visualize correlation matrix
#::::::::::::::::::::::::::::::::::::::::::
# Full correlation matrix,
# insignificant correlations are marked by crosses
cor.mat %>% cor_plot()

# Reorder by correlation coefficient
# pull lower triangle and visualize
cor.lower.tri <- cor.mat %>%
  cor_reorder() %>%
  pull_lower_triangle()
cor.lower.tri %>% cor_plot()

# Change visualization methods
#::::::::::::::::::::::::::::::::::::::::::
cor.lower.tri %>%
  cor_plot(method = "pie")

cor.lower.tri %>%
  cor_plot(method = "color")

cor.lower.tri %>%
  cor_plot(method = "number")

# Show the correlation coefficient: label = TRUE
# Blank the insignificant correlation
#::::::::::::::::::::::::::::::::::::::::::
cor.lower.tri %>%
  cor_plot(
    method = "color",
    label = TRUE,
    insignificant = "blank"
  )

# Change the color palettes
#::::::::::::::::::::::::::::::::::::::::::

# Using custom color palette
# Require ggpubr: install.packages("ggpubr")
if(require("ggpubr")){
  my.palette <- get_palette(c("red", "white", "blue"), 200)
  cor.lower.tri %>%
   cor_plot(palette = my.palette)
}

# Using RcolorBrewer color palette
if(require("ggpubr")){
  my.palette <- get_palette("PuOr", 200)
  cor.lower.tri %>%
   cor_plot(palette = my.palette)
}