Plot density estimates for each continuous feature
Usage
plot_density(
data,
binary_as_factor = TRUE,
geom_density_args = list(),
scale_x = "continuous",
title = NULL,
ggtheme = theme_gray(),
theme_config = list(),
nrow = 4L,
ncol = 4L,
parallel = FALSE
)
Arguments
- data
input data
- binary_as_factor
treat binary as categorical? Default is
TRUE
.- geom_density_args
a list of other arguments to geom_density
- scale_x
scale of x axis. See scale_x_continuous for all options. Default is
continuous
.- title
plot title
- ggtheme
complete ggplot2 themes. The default is theme_gray.
- theme_config
a list of configurations to be passed to theme.
- nrow
number of rows per page. Default is 4.
- ncol
number of columns per page. Default is 4.
- parallel
enable parallel? Default is
FALSE
.
Examples
# Plot iris data
plot_density(iris, ncol = 2L)
# Add color to density area
plot_density(iris, geom_density_args = list("fill" = "black", "alpha" = 0.6), ncol = 2L)
# Plot skewed data on log scale
set.seed(1)
skew <- data.frame(replicate(4L, rbeta(1000, 1, 5000)))
plot_density(skew, ncol = 2L)
plot_density(skew, scale_x = "log10", ncol = 2L)