ggbivariate is a variant of ggduo for plotting an outcome variable with several potential explanatory variables.

ggbivariate(
  data,
  outcome,
  explanatory = NULL,
  mapping = NULL,
  types = NULL,
  ...,
  rowbar_args = NULL
)

Arguments

data

dataset to be used, can have both categorical and numerical variables

outcome

name or position of the outcome variable (one variable only)

explanatory

names or positions of the explanatory variables (if NULL, will take all variables other than outcome)

mapping

additional aesthetic to be used, for example to indicate weights (see examples)

types

custom types of plots to use, see ggduo

...

additional arguments passed to ggduo (see examples)

rowbar_args

additional arguments passed to ggally_rowbar (see examples)

Author

Joseph Larmarange

Examples

# Small function to display plots only if it's interactive p_ <- GGally::print_if_interactive data(tips, package = "reshape") p_(ggbivariate(tips, "smoker", c("day", "time", "sex", "tip")))
# Personalize plot title and legend title p_(ggbivariate( tips, "smoker", c("day", "time", "sex", "tip"), title = "Custom title" ) + labs(fill = "Smoker ?"))
# Customize fill colour scale p_(ggbivariate(tips, "smoker", c("day", "time", "sex", "tip")) + scale_fill_brewer(type = "qual"))
# Customize labels p_(ggbivariate( tips, "smoker", c("day", "time", "sex", "tip"), rowbar_args = list( colour = "white", size = 4, fontface = "bold", label_format = scales::label_percent(accurary = 1) ) ))
# Choose the sub-plot from which get legend p_(ggbivariate(tips, "smoker"))
p_(ggbivariate(tips, "smoker", legend = 3))
# Use mapping to indicate weights d <- as.data.frame(Titanic) p_(ggbivariate(d, "Survived", mapping = aes(weight = Freq)))
# outcome can be numerical p_(ggbivariate(tips, outcome = "tip", title = "tip"))