Display an outcome using several potential explanatory variables

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)
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"))