A variant on box and whiskers plot (in the style of Tukey, or not...)

Source: R/geom-boxplot2.R, R/stat-boxplot2.R

The boxplot compactly displays the distribution of a continuous variable. It displays five summary statistics (the median, two hinges and two whiskers), and all "outlying" points individually. geom_boxplot2() is a variant on the geom_boxplot function from the ggplot2 package. It allows users to set whisker limits based upon a confidence interval rather than a multiple of the IQR, allows to display outliers with jitter, and provides slightly different graphical styles when grouping/coloring is used.

geom_boxplot2(
  mapping = NULL,
  data = NULL,
  stat = "boxplot2",
  position = "dodge2",
  ...,
  median_symbol = TRUE,
  outlier.position = "jitter",
  outlier.colour = NULL,
  outlier.color = NULL,
  outlier.fill = NULL,
  outlier.shape = 21,
  outlier.size = 1.5,
  outlier.stroke = 0.5,
  outlier.alpha = NULL,
  whisker.cap = FALSE,
  notch = FALSE,
  notchwidth = 0.5,
  varwidth = FALSE,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

stat_boxplot2(
  mapping = NULL,
  data = NULL,
  geom = "boxplot2",
  position = "dodge2",
  ...,
  coef = 1.5,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

Set of aesthetic mappings created by 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. A function can be created from a formula (e.g. ~ head(.x, 10)).

position

Position adjustment, either as a string naming the adjustment (e.g. "jitter" to use position_jitter), or the result of a call to a position adjustment function. Use the latter if you need to change the settings of the adjustment.

...

Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.

median_symbol

a logical value indicating whether to use a symbol (TRUE) or a line (FALSE) to represent the median when a color aesthetic is used.

outlier.position

By default, outliers are displayed with a small degree of jitter. Sometimes it can be useful to hide the outliers, for example when overlaying the raw data points on top of the boxplot. Hiding the outliers can be achieved by setting outlier.position = NULL. Importantly, this does not remove the outliers, it only hides them, so the range calculated for the y-axis will be the same with outliers shown and outliers hidden. If needed, outliers can be displayed without jitter by setting outlier.position = 'identity'.

outlier.colour, outlier.color, outlier.fill, outlier.shape, outlier.size, outlier.stroke, outlier.alpha

Aesthetics for outliers inherited from the original geom_boxplot function but that are not used in geom_boxplot2. Instead, outliers inherits colors, shapes, sizes from the box aesthetics. These aesthetics were included to maintain code compatibility with call to geom_boxplot.

whisker.cap

If FALSE (default), the whiskers are simple segments. If TRUE, the end of the whiskers are delineated by orthogonal segments.

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 (defaults to notchwidth = 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.

orientation

The orientation of the layer. The default (NA) automatically determines the orientation from the aesthetic mapping. In the rare event that this fails it can be given explicitly by setting orientation to either "x" or "y". See the Orientation section for more detail.

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. It can also be a named logical vector to finely select the aesthetics to display.

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_boxplot2 and stat_boxplot2.

coef

Length of the whiskers as multiple of IQR (if lower than 50) or a confidence interval (if greater than or equal to 50). Defaults to 1.5.

Orientation

This geom treats each axis differently and, thus, can thus have two orientations. Often the orientation is easy to deduce from a combination of the given mappings and the types of positional scales in use. Thus, ggplot2 will by default try to guess which orientation the layer should have. Under rare circumstances, the orientation is ambiguous and guessing may fail. In that case the orientation can be specified directly using the orientation parameter, which can be either "x" or "y". The value gives the axis that the geom should run along, "x" being the default orientation you would expect for the geom.

Summary statistics

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.

By default, 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. If a coef argument is provided to the function call, the whiskers may extend to alternative limits. If coef is set to a value lower than 50, the value is used a multiplier to the IQR (default is 1.5 as explained above). If coef is set to value greater than or equal to 50, the whiskers extend to the limit of the coef confidence interval.

In a notched box plot, the notches extend 1.58 * IQR / sqrt(n). This gives a roughly 95 al. (1978) for more details.

Aesthetics

geom_boxplot2() understands the following aesthetics (required aesthetics are in bold):

  • x or y

  • lower or xlower

  • upper or xupper

  • middle or xmiddle

  • ymin or xmin

  • ymax or xmax

  • alpha

  • colour

  • fill

  • group

  • linetype

  • linewidth

  • shape

  • size

  • stroke

  • weight

Learn more about setting these aesthetics in vignette("ggplot2-specs").

Computed variables

width

width of boxplot

ymin

lower whisker = smallest observation greater than or equal to lower hinge - 1.5 * IQR or lower limit of the confidence interval

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 or upper limit of the confidence interval

References

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

See also

geom_boxplot for original ggplot2 geom function.

Examples

library(ggplot2)

p <- ggplot(mpg, aes(class, hwy))
p + geom_boxplot2()

p + geom_boxplot2(outlier.position = 'identity', coef = 90)

# Orientation follows the discrete axis
ggplot(mpg, aes(hwy, class)) + geom_boxplot2()


p + geom_boxplot2(notch = TRUE)
#> Notch went outside hinges
#> ℹ Do you want `notch = FALSE`?
#> Notch went outside hinges
#> ℹ Do you want `notch = FALSE`?

p + geom_boxplot2(whisker.cap = TRUE)

p + geom_boxplot2(varwidth = TRUE)

p + geom_boxplot2(fill = "white", colour = "#3366FF")


# Boxplots are automatically dodged when any aesthetic is a factor
p + geom_boxplot2(aes(colour = factor(drv)))


# Use the median_symbol argument to control how the median is drawn
p + geom_boxplot2(aes(colour = factor(drv)), median_symbol = FALSE)


# 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_boxplot2()
#> Warning: Continuous x aesthetic -- did you forget aes(group=...)?

ggplot(diamonds, aes(carat, price)) +
  geom_boxplot2(aes(group = cut_width(carat, 0.25)))

# Adjust the transparency of outliers using outlier.alpha
ggplot(diamonds, aes(carat, price)) +
  geom_boxplot2(aes(group = cut_width(carat, 0.25)), outlier.alpha = 0.1)
#> The following arguments are not used in geom_boxplot2:
#>   outlier.colour, outlier.color, outlier.fill, outlier.shape,
#>   outlier.size, outlier.stroke, and outlier.alpha


# 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_boxplot2(
   aes(ymin = y0, lower = y25, middle = y50, upper = y75, ymax = y100),
   stat = "identity"
 )