For each x value,
geom_ribbon displays a y interval defined
geom_area is a special case of
geom_ribbon, where the
ymin is fixed to 0.
geom_ribbon(mapping = NULL, data = NULL, stat = "identity",
position = "identity", ..., na.rm = FALSE, show.legend = NA,
inherit.aes = TRUE)
geom_area(mapping = NULL, data = NULL, stat = "identity",
position = "stack", na.rm = FALSE, 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
mapping if there is no plot mapping.
The data to be displayed in this layer. There are three
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.
function will be called with a single argument,
the plot data. The return value must be a
will be used as the layer data.
The statistical transformation to use on the data for this
layer, as a string.
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.
FALSE, the default, missing values are removed with
a warning. If
TRUE, missing values are silently removed.
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.
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.
An area plot is the continuous analog of a stacked bar chart (see
geom_bar), and can be used to show how composition of the
whole varies over the range of x. Choosing the order in which different
components is stacked is very important, as it becomes increasing hard to
see the individual pattern as you move up the stack. See
position_stack for the details of stacking algorithm.
geom_ribbon understands the following aesthetics (required aesthetics are in bold):
geom_bar for discrete intervals (bars),
geom_linerange for discrete intervals (lines),
geom_polygon for general polygons
# Generate data
huron <- data.frame
(year = 1875
, level = as.vector
h <- ggplot
(y = level
# Add aesthetic mappings
(ymin = level
, ymax = level
), fill = "grey70"
(y = level