geom_boxplot
Box and whiskers plot.
The lower and upper "hinges" correspond to the first and third quartiles
(the 25th and 75th percentiles). This differs slightly from the method used
by the boxplot
function, and may be apparent with small samples.
See boxplot.stats
for for more information on how hinge
positions are calculated for boxplot
.
Usage
geom_boxplot(mapping = NULL, data = NULL, stat = "boxplot", position = "dodge", ..., outlier.colour = NULL, outlier.color = NULL, outlier.shape = 19, outlier.size = 1.5, outlier.stroke = 0.5, notch = FALSE, notchwidth = 0.5, varwidth = FALSE, na.rm = FALSE, show.legend = NA, inherit.aes = TRUE)
stat_boxplot(mapping = NULL, data = NULL, geom = "boxplot", position = "dodge", ..., coef = 1.5, na.rm = FALSE, show.legend = NA, inherit.aes = TRUE)
Arguments
 mapping
 Set of aesthetic mappings created by
aes
oraes_
. If specified andinherit.aes = TRUE
(the default), it is combined with the default mapping at the top level of the plot. You must supplymapping
if there is no plot mapping.  data
 The data to be displayed in this layer. There are three
options:
If
NULL
, the default, the data is inherited from the plot data as specified in the call toggplot
.A
data.frame
, or other object, will override the plot data. All objects will be fortified to produce a data frame. Seefortify
for which variables will be created.A
function
will be called with a single argument, the plot data. The return value must be adata.frame.
, and will be used as the layer data.  position
 Position adjustment, either as a string, or the result of a call to a position adjustment function.
 ...
 other arguments passed on to
layer
. These are often aesthetics, used to set an aesthetic to a fixed value, likecolor = "red"
orsize = 3
. They may also be parameters to the paired geom/stat.  outlier.colour, outlier.color, outlier.shape, outlier.size, outlier.stroke
 Default aesthetics for outliers. Set to
NULL
to inherit from the aesthetics used for the box.In the unlikely event you specify both US and UK spellings of colour, the US spelling will take precedence.
 notch
 if
FALSE
(default) make a standard box plot. IfTRUE
, make a notched box plot. Notches are used to compare groups; if the notches of two boxes do not overlap, this suggests that the medians are significantly different.  notchwidth
 for a notched box plot, width of the notch relative to the body (default 0.5)
 varwidth
 if
FALSE
(default) make a standard box plot. IfTRUE
, boxes are drawn with widths proportional to the squareroots of the number of observations in the groups (possibly weighted, using theweight
aesthetic).  na.rm
 If
FALSE
(the default), removes missing values with a warning. IfTRUE
silently removes missing values.  show.legend
 logical. Should this layer be included in the legends?
NA
, the default, includes if any aesthetics are mapped.FALSE
never includes, andTRUE
always includes.  inherit.aes
 If
FALSE
, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g.borders
.  geom, stat
 Use to override the default connection between
geom_boxplot
andstat_boxplot
.  coef
 length of the whiskers as multiple of IQR. Defaults to 1.5
Details
The upper whisker extends from the hinge to the highest value that is within 1.5 * IQR of the hinge, where IQR is the interquartile range, or distance between the first and third quartiles. The lower whisker extends from the hinge to the lowest value within 1.5 * IQR of the hinge. Data beyond the end of the whiskers are outliers and plotted as points (as specified by Tukey).
In a notched box plot, the notches extend 1.58 * IQR / sqrt(n)
.
This gives a roughly 95
See McGill et al. (1978) for more details.
Aesthetics
geom_boxplot
understands the following aesthetics (required aesthetics are in bold):

lower

middle

upper

x

ymax

ymin

alpha

colour

fill

linetype

shape

size

weight
Computed variables
 width
 width of boxplot
 ymin
 lower whisker = smallest observation greater than or equal to lower hinge  1.5 * IQR
 lower
 lower hinge, 25% quantile
 notchlower
 lower edge of notch = median  1.58 * IQR / sqrt(n)
 middle
 median, 50% quantile
 notchupper
 upper edge of notch = median + 1.58 * IQR / sqrt(n)
 upper
 upper hinge, 75% quantile
 ymax
 upper whisker = largest observation less than or equal to upper hinge + 1.5 * IQR
References
McGill, R., Tukey, J. W. and Larsen, W. A. (1978) Variations of box plots. The American Statistician 32, 1216.
See Also
stat_quantile
to view quantiles conditioned on a
continuous variable, geom_jitter
for another way to look
at conditional distributions.
Examples
p < ggplot(mpg, aes(class, hwy))
p + geom_boxplot()
p + geom_boxplot() + geom_jitter(width = 0.2)
p + geom_boxplot() + coord_flip()
p + geom_boxplot(notch = TRUE)
p + geom_boxplot(varwidth = TRUE)
p + geom_boxplot(fill = "white", colour = "#3366FF")
# By default, outlier points match the colour of the box. Use
# outlier.colour to override
p + geom_boxplot(outlier.colour = "red", outlier.shape = 1)
# Boxplots are automatically dodged when any aesthetic is a factor
p + geom_boxplot(aes(colour = drv))
# You can also use boxplots with continuous x, as long as you supply
# a grouping variable. cut_width is particularly useful
ggplot(diamonds, aes(carat, price)) +
geom_boxplot()
ggplot(diamonds, aes(carat, price)) +
geom_boxplot(aes(group = cut_width(carat, 0.25)))
# It's possible to draw a boxplot with your own computations if you
# use stat = "identity":
y < rnorm(100)
df < data.frame(
x = 1,
y0 = min(y),
y25 = quantile(y, 0.25),
y50 = median(y),
y75 = quantile(y, 0.75),
y100 = max(y)
)
ggplot(df, aes(x)) +
geom_boxplot(
aes(ymin = y0, lower = y25, middle = y50, upper = y75, ymax = y100),
stat = "identity"
)