The boxplot compactly displays the distribution of a continuous variable. It visualises five summary statistics (the median, two hinges and two whiskers), and all "outlying" points individually.

geom_boxplot(mapping = NULL, data = NULL, stat = "boxplot", position = "dodge", ..., outlier.colour = NULL, outlier.color = NULL, outlier.fill = NULL, outlier.shape = 19, outlier.size = 1.5, outlier.stroke = 0.5, outlier.alpha = NULL, 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)

- mapping
Set of aesthetic mappings created by

`aes`

or`aes_`

. If specified and`inherit.aes = TRUE`

(the default), it is combined with the default mapping at the top level of the plot. You must supply`mapping`

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 to`ggplot`

.A

`data.frame`

, or other object, will override the plot data. All objects will be fortified to produce a data frame. See`fortify`

for which variables will be created.A

`function`

will be called with a single argument, the plot data. The return value must be a`data.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, like`color = "red"`

or`size = 3`

. They may also be parameters to the paired geom/stat.- outlier.colour, outlier.color, outlier.fill, outlier.shape, outlier.size, outlier.stroke, outlier.alpha
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. If`TRUE`

, 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. If`TRUE`

, boxes are drawn with widths proportional to the square-roots of the number of observations in the groups (possibly weighted, using the`weight`

aesthetic).- na.rm
If

`FALSE`

, the default, missing values are removed with a warning. If`TRUE`

, missing values are silently removed.- show.legend
logical. Should this layer be included in the legends?

`NA`

, the default, includes if any aesthetics are mapped.`FALSE`

never includes, and`TRUE`

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`

and`stat_boxplot`

.- coef
length of the whiskers as multiple of IQR. Defaults to 1.5

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`

.

The upper whisker extends from the hinge to the largest value no further than 1.5 * IQR from the hinge (where IQR is the inter-quartile range, or distance between the first and third quartiles). The lower whisker extends from the hinge to the smallest value at most 1.5 * IQR of the hinge. Data beyond the end of the whiskers are called "outlying" points and are plotted individually.

In a notched box plot, the notches extend `1.58 * IQR / sqrt(n)`

.
This gives a roughly 95% confidence interval for comparing medians.
See McGill et al. (1978) for more details.

`geom_boxplot`

understands the following aesthetics (required aesthetics are in bold):

**x****lower****upper****middle****ymin****ymax**`alpha`

`colour`

`fill`

`group`

`linetype`

`shape`

`size`

`weight`

- 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

McGill, R., Tukey, J. W. and Larsen, W. A. (1978) Variations of box plots. The American Statistician 32, 12-16.

`geom_quantile`

for continuous x,
`geom_violin`

for a richer display of the distribution, and
`geom_jitter`

for a useful technique for small data.

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()#> Warning: Continuous x aesthetic -- did you forget aes(group=...)?ggplot(diamonds, aes(carat, price)) + geom_boxplot(aes(group = cut_width(carat, 0.25)), outlier.alpha = 0.1)# 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" )