Vertical intervals: lines, crossbars & errorbars

Various ways of representing a vertical interval defined by x, ymin and ymax. Each case draws a single graphical object.

geom_crossbar(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  fatten = 2.5,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_errorbar(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_linerange(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_pointrange(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  fatten = 4,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

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. A function can be created from a formula (e.g. ~ head(.x, 10)).
stat	The statistical transformation to use on the data for this layer, as a string.
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 colour = "red" or size = 3. They may also be parameters to the paired geom/stat.
fatten	A multiplicative factor used to increase the size of the middle bar in geom_crossbar() and the middle point in geom_pointrange().
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().

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.

Aesthetics

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

• x or y

• ymin or xmin

• ymax or xmax

• alpha

• colour

• group

• linetype

• size

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

See also

stat_summary() for examples of these guys in use, geom_smooth() for continuous analogue, geom_errorbarh() for a horizontal error bar.

Examples

# Create a simple example dataset
df <- data.frame(
  trt = factor(c(1, 1, 2, 2)),
  resp = c(1, 5, 3, 4),
  group = factor(c(1, 2, 1, 2)),
  upper = c(1.1, 5.3, 3.3, 4.2),
  lower = c(0.8, 4.6, 2.4, 3.6)
)

p <- ggplot(df, aes(trt, resp, colour = group))
p + geom_linerange(aes(ymin = lower, ymax = upper))
p + geom_pointrange(aes(ymin = lower, ymax = upper))
p + geom_crossbar(aes(ymin = lower, ymax = upper), width = 0.2)
p + geom_errorbar(aes(ymin = lower, ymax = upper), width = 0.2)

# Flip the orientation by changing mapping
ggplot(df, aes(resp, trt, colour = group)) +
  geom_linerange(aes(xmin = lower, xmax = upper))

# Draw lines connecting group means
p +
  geom_line(aes(group = group)) +
  geom_errorbar(aes(ymin = lower, ymax = upper), width = 0.2)

# If you want to dodge bars and errorbars, you need to manually
# specify the dodge width
p <- ggplot(df, aes(trt, resp, fill = group))
p +
 geom_col(position = "dodge") +
 geom_errorbar(aes(ymin = lower, ymax = upper), position = "dodge", width = 0.25)

# Because the bars and errorbars have different widths
# we need to specify how wide the objects we are dodging are
dodge <- position_dodge(width=0.9)
p +
  geom_col(position = dodge) +
  geom_errorbar(aes(ymin = lower, ymax = upper), position = dodge, width = 0.25)

# When using geom_errorbar() with position_dodge2(), extra padding will be
# needed between the error bars to keep them aligned with the bars.
p +
geom_col(position = "dodge2") +
geom_errorbar(
  aes(ymin = lower, ymax = upper),
  position = position_dodge2(width = 0.5, padding = 0.5)
)