gf_ecdf: Formula interace to empirical cumulative distribution

gf_ecdfR Documentation

Formula interace to empirical cumulative distribution


The empirical cumulative distribution function (ECDF) provides an alternative visualization of distribution. Compared to other visualizations that rely on density (like histograms or density plots) 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.


  object = NULL,
  gformula = NULL,
  data = NULL,
  n = NULL,
  geom = "step",
  stat = "ecdf",
  position = "identity",
  show.legend = NA, = NULL,
  inherit = TRUE,
  environment = parent.frame()



When chaining, this holds an object produced in the earlier portions of the chain. Most users can safely ignore this argument. See details and examples.


A formula with shape y ~ x. Faceting can be achieved by including | in the formula.


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)).


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.


Used for grouping.


If TRUE, pad the ecdf with additional points (-Inf, 0) and (Inf, 1)


if NULL, do not interpolate. If not NULL, this is the number of points to interpolate with.


Label for x-axis. See also gf_labs().


Label for y-axis. See also gf_labs().

title, subtitle, caption

Title, sub-title, and caption for the plot. See also gf_labs().


The geometric object to use to display the data, either as a ggproto Geom subclass or as a string naming the geom stripped of the geom_ prefix (e.g. "point" rather than "geom_point")


The statistical transformation to use on the data for this layer, either as a ggproto Geom subclass or as a string naming the stat stripped of the stat_ prefix (e.g. "count" rather than "stat_count")


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.


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.

If TRUE, display some minimal help.


A logical indicating whether default attributes are inherited.


An environment in which to look for variables not found in data.


Data <- data.frame(
  x = c(rnorm(100, 0, 1), rnorm(100, 0, 3), rt(100, df = 3)),
  g = gl(3, 100, labels = c("N(0, 1)", "N(0, 3)", "T(df = 3)") )
gf_ecdf( ~ x, data = Data)
# Don't go to positive/negative infinity
gf_ecdf( ~ x, data = Data, pad = FALSE)

# Multiple ECDFs
gf_ecdf( ~ x, data = Data, color = ~ g)

ggformula documentation built on Nov. 9, 2023, 5:08 p.m.