| geom_boxplot {ggplot2} | R Documentation |
Box and whiskers plot
geom_boxplot(mapping=NULL, data=NULL, stat="boxplot", position="dodge", outlier.colour="black", outlier.shape=16, outlier.size=2, ...)
mapping |
mapping between variables and aesthetics generated by aes |
data |
dataset used in this layer, if not specified uses plot dataset |
stat |
statistic used by this layer |
position |
position adjustment used by this layer |
outlier.colour |
colour for outlying points |
outlier.shape |
shape of outlying points |
outlier.size |
size of outlying points |
... |
other arguments |
This page describes geom_boxplot, see layer and qplot for how to create a complete plot from individual components.
A layer
The following aesthetics can be used with geom_boxplot. Aesthetics are mapped to variables in the data with the aes function: geom\_boxplot(\code{aes}(x = var))
x: x position (required)
lower: NULL (required)
upper: NULL (required)
middle: NULL (required)
ymin: bottom (vertical minimum) (required)
ymax: top (vertical maximum) (required)
weight: observation weight used in statistical transformation
colour: border colour
fill: internal colour
size: size
alpha: transparency
Hadley Wickham, http://had.co.nz/
stat_quantile: View quantiles conditioned on a continuous variable
geom_jitter: Another way to look at conditional distributions
## Not run:
p <- ggplot(mtcars, aes(factor(cyl), mpg))
p + geom_boxplot()
qplot(factor(cyl), mpg, data = mtcars, geom = "boxplot")
p + geom_boxplot() + geom_jitter()
p + geom_boxplot() + coord_flip()
qplot(factor(cyl), mpg, data = mtcars, geom = "boxplot") +
coord_flip()
p + geom_boxplot(outlier.colour = "green", outlier.size = 3)
# Add aesthetic mappings
# Note that boxplots are automatically dodged when any aesthetic is
# a factor
p + geom_boxplot(aes(fill = cyl))
p + geom_boxplot(aes(fill = factor(cyl)))
p + geom_boxplot(aes(fill = factor(vs)))
p + geom_boxplot(aes(fill = factor(am)))
# Set aesthetics to fixed value
p + geom_boxplot(fill="grey80", colour="#3366FF")
qplot(factor(cyl), mpg, data = mtcars, geom = "boxplot",
colour = I("#3366FF"))
# Scales vs. coordinate transforms -------
# Scale transformations occur before the boxplot statistics are computed.
# Coordinate transformations occur afterwards. Observe the effect on the
# number of outliers.
m <- ggplot(movies, aes(y = votes, x = rating,
group = round_any(rating, 0.5)))
m + geom_boxplot()
m + geom_boxplot() + scale_y_log10()
m + geom_boxplot() + coord_trans(y = "log10")
m + geom_boxplot() + scale_y_log10() + coord_trans(y = "log10")
# Boxplots with continuous x:
# Use the group aesthetic to group observations in boxplots
qplot(year, budget, data = movies, geom = "boxplot")
qplot(year, budget, data = movies, geom = "boxplot",
group = round_any(year, 10, floor))
## End(Not run)