Vertical intervals: lines, crossbars & errorbarsSource:
R/geom-linerange.R, and 1 more
Various ways of representing a vertical interval defined by
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 )
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
mappingif there is no plot mapping.
The data to be displayed in this layer. There are three options:
NULL, the default, the data is inherited from the plot data as specified in the call to
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.
functionwill 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
functioncan be created from a
~ head(.x, 10)).
The statistical transformation to use on the data for this layer, either as a
Geomsubclass or as a string naming the stat stripped of the
Position adjustment, either as a string naming the adjustment (e.g.
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.
A multiplicative factor used to increase the size of the middle bar in
geom_crossbar()and the middle point in
FALSE, the default, missing values are removed with a warning. If
TRUE, missing values are silently removed.
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
"y". See the Orientation section for more detail.
logical. Should this layer be included in the legends?
NA, the default, includes if any aesthetics are mapped.
FALSEnever includes, and
TRUEalways includes. It can also be a named logical vector to finely select the aesthetics to display.
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.
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
"y". The value gives the axis that the geom should run along,
"x" being the default orientation you would expect for the geom.
geom_linerange() understands the following aesthetics (required aesthetics are in bold):
geom_pointrange() also understands
size for the size of the points.
Learn more about setting these aesthetics in
stat_summary() for examples of these guys in use,
geom_smooth() for continuous analogue,
geom_errorbarh() for a horizontal error bar.
# 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) )