#' Empirical Cumulative Distribution Function #' #' The empirical cumulative distribution function (ECDF) provides an alternative #' visualisation of distribution. Compared to other visualisations that rely on #' density (like \code{\link{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. #' #' @inheritParams layer #' @inheritParams geom_point #' @param na.rm If \code{FALSE} (the default), removes missing values with #' a warning. If \code{TRUE} silently removes missing values. #' @param n if NULL, do not interpolate. If not NULL, this is the number #' of points to interpolate with. #' @param pad If \code{TRUE}, pad the ecdf with additional points (-Inf, 0) #' and (Inf, 1) #' @section Computed variables: #' \describe{ #' \item{x}{x in data} #' \item{y}{cumulative density corresponding x} #' } #' @export #' @examples #' 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)) + stat_ecdf() stat_ecdf <- function(mapping = NULL, data = NULL, geom = "step", position = "identity", ..., n = NULL, pad = TRUE, na.rm = FALSE, show.legend = NA, inherit.aes = TRUE) { layer( data = data, mapping = mapping, stat = StatEcdf, geom = geom, position = position, show.legend = show.legend, inherit.aes = inherit.aes, params = list( n = n, pad = pad, na.rm = na.rm, ... ) ) } #' @rdname ggplot2-ggproto #' @format NULL #' @usage NULL #' @export StatEcdf <- ggproto("StatEcdf", Stat, compute_group = function(data, scales, n = NULL, pad = TRUE) { # If n is NULL, use raw values; otherwise interpolate if (is.null(n)) { x <- unique(data$x) } else { x <- seq(min(data$x), max(data$x), length.out = n) } if (pad) { x <- c(-Inf, x, Inf) } y <- ecdf(data$x)(x) data.frame(x = x, y = y) }, default_aes = aes(y = ..y..), required_aes = c("x") )