cor_plot: Correlation matrix plot

In Rkabacoff/qacr: Functions to Facilitate Data Science Projects

Description

Create a correlation matrix for all quantitative variables in a data frame.

Usage

cor_plot(
  data,
  method = c("pearson", "kendall", "spearman"),
  sort = FALSE,
  axis_text_size = 12,
  number_text_size = 3,
  legend = FALSE
)

Arguments

data	data frame
method	a character string indicating which correlation coefficient is to be computed. One of "pearson" (default), "kendall", or "spearman".
sort	logical. If TRUE, reorder variables to place variables with similar correlation patterns together.
axis_text_size	size for axis labels (default=12).
number_text_size	size for correlation coefficient labels (default=3).
legend	logical, if TRUE the legend is displayed. (default=FALSE)

Details

The cor_plot function will only select quantitative variables from a data frame. Categorical variables are ignored. The correlation matrix is presented as a lower triangle matrix. Missing values are deleted in listwise fashion.

Value

a ggplot graph

Note

This function is a wrapper for the ggcorrplot function.

Examples

cor_plot(cars74)
cor_plot(cars74, sort=TRUE)
cor_plot(coffee, axis_text_size=8,
         number_text_size=2, sort=TRUE,
         legend=TRUE)

Rkabacoff/qacr documentation built on March 20, 2021, 3:03 p.m.