vis_cor: Visualise correlations amongst variables in your data as a...

In ropensci/visdat: Preliminary Visualisation of Data

Visualise correlations amongst variables in your data as a heatmap

Description

Visualise correlations amongst variables in your data as a heatmap

Usage

vis_cor(
  data,
  cor_method = "pearson",
  na_action = "pairwise.complete.obs",
  facet,
  ...
)

Arguments

data	data.frame
cor_method	correlation method to use, from cor: "a character string indicating which correlation coefficient (or covariance) is to be computed. One of "pearson" (default), "kendall", or "spearman": can be abbreviated."
na_action	The method for computing covariances when there are missing values present. This can be "everything", "all.obs", "complete.obs", "na.or.complete", or "pairwise.complete.obs" (default). This option is taken from the cor function argument use.,
facet	bare unqouted variable to use for facetting
...	extra arguments you may want to pass to cor

Value

ggplot2 object

Examples

vis_cor(airquality)
vis_cor(airquality, facet = Month)
vis_cor(mtcars)
## Not run: 
# this will error
vis_cor(iris)

## End(Not run)

ropensci/visdat documentation built on July 20, 2024, 4:46 a.m.