# publicjrnold/ggthemes

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 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 ##' Calculate components of a five-number summary##'##' The five number summary of a sample is the minimum, first quartile,##' median, third quartile, and maximum.##'##' @section Aesthetics:##' \Sexpr[results=rd,stage=build]{ggthemes:::rd_aesthetics("stat_fivenumber", ggthemes:::StatFivenumber)}##'##' @param na.rm If \code{FALSE} (the default), removes missing values with##' a warning. If \code{TRUE} silently removes missing values.##' @inheritParams ggplot2::stat_identity##' @return A data frame with additional columns:##' \item{width}{width of boxplot}##' \item{ymin}{minimum}##' \item{lower}{lower hinge, 25\% quantile}##' \item{notchlower}{lower edge of notch = median - 1.58 * IQR / sqrt(n)}##' \item{middle}{median, 50\% quantile}##' \item{notchupper}{upper edge of notch = median + 1.58 * IQR / sqrt(n)}##' \item{upper}{upper hinge, 75\% quantile}##' \item{ymax}{maximum}##' @seealso \code{\link{stat_boxplot}}##' @exportstat_fivenumber <- function (mapping = NULL, data = NULL,                             geom = "boxplot", position = "dodge",                             na.rm = FALSE, ...) {  StatFivenumber$new(mapping = mapping, data = data, geom = geom, position = position, na.rm = na.rm, ...)}StatFivenumber <- proto(ggplot2:::Stat, { objname <- "fivenumber" required_aes <- c("x", "y") default_geom <- function(.) GeomBoxplot calculate_groups <- function(., data, na.rm = FALSE, width = NULL, ...) { data <- remove_missing(data, na.rm, c("y", "weight"), name="stat_fivenumber", finite = TRUE) data$weight <- data$weight %||% 1 width <- width %||% resolution(data$x) * 0.75    .super\$calculate_groups(., data, na.rm = na.rm, width = width, ...)  }  calculate <- function(., data, scales, width=NULL, na.rm = FALSE, ...) {    with(data, {      qs <- c(0, 0.25, 0.5, 0.75, 1)      if (length(unique(weight)) != 1) {        try_require("quantreg")        stats <- as.numeric(coef(rq(y ~ 1, weights = weight, tau=qs)))      } else {        stats <- as.numeric(quantile(y, qs))      }      names(stats) <- c("ymin", "lower", "middle", "upper", "ymax")      if (length(unique(x)) > 1) width <- diff(range(x)) * 0.9      df <- as.data.frame(as.list(stats))      transform(df,        x = if (is.factor(x)) x[1] else mean(range(x)),        width = width      )    })  }})
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