Create correlation heatmap for discrete features — plot

This function creates a correlation heatmap for all discrete categories.

Usage

plot_correlation(
  data,
  type = c("all", "discrete", "continuous"),
  maxcat = 20L,
  cor_args = list(),
  geom_text_args = list(),
  title = NULL,
  ggtheme = theme_gray(),
  theme_config = list(legend.position = "bottom", axis.text.x = element_text(angle = 90)),
  plotly = FALSE
)

Arguments

data: input data
type: column type to be included in correlation calculation. "all" for all columns, "discrete" for discrete features, "continuous" for continuous features.
maxcat: maximum categories allowed for each discrete feature. The default is 20.
cor_args: a list of other arguments to cor
geom_text_args: a list of other arguments to geom_text
title: plot title
ggtheme: complete ggplot2 themes. The default is theme_gray.
theme_config: a list of configurations to be passed to theme.
plotly: if TRUE, convert to interactive plotly object (requires the plotly package). Default is FALSE.

Value

invisibly return the ggplot object

Details

For discrete features, the function first dummifies all categories, then calculates the correlation matrix (see cor) and plots it.

Examples

plot_correlation(iris)

plot_correlation(iris, type = "c")

plot_correlation(airquality, cor_args = list("use" = "pairwise.complete.obs"))