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=1, ...)
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
: minimum of interval (required)
ymax
: maximum of interval (required)
weight
: observation weight used in statistical transformation
colour
: border colour
fill
: internal colour
size
: size
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)