data-vis-cor: Return data used to create vis_cor plot

In ropensci/visdat: Preliminary Visualisation of Data

Return data used to create vis_cor plot

Description

Return data used to create vis_cor plot

Create a tidy dataframe of correlations suitable for plotting

Usage

data_vis_cor(x, ...)

## Default S3 method:
data_vis_cor(x, ...)

## S3 method for class 'data.frame'
data_vis_cor(
  x,
  cor_method = "pearson",
  na_action = "pairwise.complete.obs",
  ...
)

## S3 method for class 'grouped_df'
data_vis_cor(x, ...)

Arguments

x	data.frame
...	extra arguments (currently unused)
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.

Value

data frame

tidy dataframe of correlations

Examples

data_vis_cor(airquality)

## Not run: 
#return vis_dat data for each group
library(dplyr)
airquality %>%
  group_by(Month) %>%
  data_vis_cor()

## End(Not run)
data_vis_cor(airquality)

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