The empirical cumulative distribution function (ECDF) provides an alternative
visualisation of distribution. Compared to other visualisations that rely on
geom_histogram()), the ECDF doesn't require any
tuning parameters and handles both continuous and categorical variables.
The downside is that it requires more training to accurately interpret,
and the underlying visual tasks are somewhat more challenging.
mapping = NULL,
data = NULL,
geom = "step",
position = "identity",
n = NULL,
pad = TRUE,
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. A
function can be created
~ head(.x, 10)).
The geometric object to use display the data
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.
if NULL, do not interpolate. If not NULL, this is the number
of points to interpolate with.
TRUE, pad the ecdf with additional points (-Inf, 0)
and (Inf, 1)
FALSE (the default), removes missing values with
a warning. If
TRUE silently removes missing values.
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
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.
The statistic relies on the aesthetics assignment to guess which variable to
use as the input and which to use as the output. Either x or y must be provided
and one of them must be unused. The ECDF will be calculated on the given aesthetic
and will be output on the unused one.
cumulative density corresponding x
df <- data.frame(
x = c(rnorm(100, 0, 3), rnorm(100, 0, 10)),
g = gl(2, 100)
ggplot(df, aes(x)) +
stat_ecdf(geom = "step")
# Don't go to positive/negative infinity
ggplot(df, aes(x)) +
stat_ecdf(geom = "step", pad = FALSE)
# Multiple ECDFs
ggplot(df, aes(x, colour = g)) +