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 )
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 |
mapping |
additional aesthetic to be used, for example to indicate weights (see examples) |
types |
custom types of plots to use, see |
... |
additional arguments passed to |
rowbar_args |
additional arguments passed to |
Joseph Larmarange
# 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"))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.