GGally (version 1.4.0)

ggcorr: ggcorr - Plot a correlation matrix with ggplot2

Description

Function for making a correlation matrix plot, using ggplot2. The function is directly inspired by Tian Zheng and Yu-Sung Su's corrplot function in the 'arm' package. Please visit http://github.com/briatte/ggcorr for the latest version of ggcorr, and see the vignette at https://briatte.github.io/ggcorr/ for many examples of how to use it.

Usage

ggcorr(data, method = c("pairwise", "pearson"), cor_matrix = NULL,
  nbreaks = NULL, digits = 2, name = "", low = "#3B9AB2",
  mid = "#EEEEEE", high = "#F21A00", midpoint = 0, palette = NULL,
  geom = "tile", min_size = 2, max_size = 6, label = FALSE,
  label_alpha = FALSE, label_color = "black", label_round = 1,
  label_size = 4, limits = c(-1, 1), drop = is.null(limits) ||
  identical(limits, FALSE), layout.exp = 0, legend.position = "right",
  legend.size = 9, ...)

Arguments

data

a data frame or matrix containing numeric (continuous) data. If any of the columns contain non-numeric data, they will be dropped with a warning.

method

a vector of two character strings. The first value gives the method for computing covariances in the presence of missing values, and must be (an abbreviation of) one of "everything", "all.obs", "complete.obs", "na.or.complete" or "pairwise.complete.obs". The second value gives the type of correlation coefficient to compute, and must be one of "pearson", "kendall" or "spearman". See cor for details. Defaults to c("pairwise", "pearson").

cor_matrix

the named correlation matrix to use for calculations. Defaults to the correlation matrix of data when data is supplied.

nbreaks

the number of breaks to apply to the correlation coefficients, which results in a categorical color scale. See 'Note'. Defaults to NULL (no breaks, continuous scaling).

digits

the number of digits to show in the breaks of the correlation coefficients: see cut for details. Defaults to 2.

name

a character string for the legend that shows the colors of the correlation coefficients. Defaults to "" (no legend name).

low

the lower color of the gradient for continuous scaling of the correlation coefficients. Defaults to "#3B9AB2" (blue).

mid

the midpoint color of the gradient for continuous scaling of the correlation coefficients. Defaults to "#EEEEEE" (very light grey).

high

the upper color of the gradient for continuous scaling of the correlation coefficients. Defaults to "#F21A00" (red).

midpoint

the midpoint value for continuous scaling of the correlation coefficients. Defaults to 0.

palette

if nbreaks is used, a ColorBrewer palette to use instead of the colors specified by low, mid and high. Defaults to NULL.

geom

the geom object to use. Accepts either "tile", "circle", "text" or "blank".

min_size

when geom has been set to "circle", the minimum size of the circles. Defaults to 2.

max_size

when geom has been set to "circle", the maximum size of the circles. Defaults to 6.

label

whether to add correlation coefficients to the plot. Defaults to FALSE.

label_alpha

whether to make the correlation coefficients increasingly transparent as they come close to 0. Also accepts any numeric value between 0 and 1, in which case the level of transparency is set to that fixed value. Defaults to FALSE (no transparency).

label_color

the color of the correlation coefficients. Defaults to "grey75".

label_round

the decimal rounding of the correlation coefficients. Defaults to 1.

label_size

the size of the correlation coefficients. Defaults to 4.

limits

bounding of color scaling for correlations, set limits = NULL or FALSE to remove

drop

if using nbreaks, whether to drop unused breaks from the color scale. Defaults to FALSE (recommended).

layout.exp

a multiplier to expand the horizontal axis to the left if variable names get clipped. Defaults to 0 (no expansion).

legend.position

where to put the legend of the correlation coefficients: see theme for details. Defaults to "bottom".

legend.size

the size of the legend title and labels, in points: see theme for details. Defaults to 9.

...

other arguments supplied to geom_text for the diagonal labels.

See Also

cor and corrplot in the arm package.

Examples

# NOT RUN {
# Basketball statistics provided by Nathan Yau at Flowing Data.
dt <- read.csv("http://datasets.flowingdata.com/ppg2008.csv")

# Default output.
ggcorr(dt[, -1])

# Labelled output, with coefficient transparency.
ggcorr(dt[, -1],
       label = TRUE,
       label_alpha = TRUE)

# Custom options.
ggcorr(
  dt[, -1],
  name = expression(rho),
  geom = "circle",
  max_size = 10,
  min_size = 2,
  size = 3,
  hjust = 0.75,
  nbreaks = 6,
  angle = -45,
  palette = "PuOr" # colorblind safe, photocopy-able
)

# Supply your own correlation matrix
ggcorr(
  data = NULL,
  cor_matrix = cor(dt[, -1], use = "pairwise")
)
# }