R: Stat for histogram ridgeline plots

stat_binline {ggridges}

R Documentation

Stat for histogram ridgeline plots

Description

Works like stat_bin except that the output is a ridgeline describing the histogram rather than a set of counts.

Usage

stat_binline(mapping = NULL, data = NULL, geom = "density_ridges",
  position = "identity", ..., binwidth = NULL, bins = NULL,
  center = NULL, boundary = NULL, breaks = NULL, closed = c("right",
  "left"), pad = TRUE, draw_baseline = TRUE, na.rm = FALSE,
  show.legend = NA, inherit.aes = TRUE)

Arguments

`mapping`	Set of aesthetic mappings created by `aes()` or `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.
`data`	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.
`geom`	Use to override the default connection between `geom_histogram`/`geom_freqpoly` and `stat_bin`.
`position`	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.
`binwidth`	The width of the bins. Can be specified as a numeric value, or a function that calculates width from x. The default is to use `bins` bins that cover the range of the data. You should always override this value, exploring multiple widths to find the best to illustrate the stories in your data. The bin width of a date variable is the number of days in each time; the bin width of a time variable is the number of seconds.
`bins`	Number of bins. Overridden by `binwidth`. Defaults to 30
`center`	The center of one of the bins. Note that if center is above or below the range of the data, things will be shifted by an appropriate number of `width`s. To center on integers, for example, use `width = 1` and `center = 0`, even if `0` is outside the range of the data. At most one of `center` and `boundary` may be specified.
`boundary`	A boundary between two bins. As with `center`, things are shifted when `boundary` is outside the range of the data. For example, to center on integers, use `width = 1` and `boundary = 0.5`, even if `0.5` is outside the range of the data. At most one of `center` and `boundary` may be specified.
`breaks`	Alternatively, you can supply a numeric vector giving the bin boundaries. Overrides `binwidth`, `bins`, `center`, and `boundary`.
`closed`	One of `"right"` or `"left"` indicating whether right or left edges of bins are included in the bin.
`pad`	If `TRUE`, adds empty bins at either end of x. This ensures that the binline always goes back down to 0. Defaults to `TRUE`.
`draw_baseline`	If `FALSE`, removes lines along 0 counts. Defaults to `TRUE`.
`na.rm`	If `FALSE`, the default, missing values are removed with a warning. If `TRUE`, missing values are silently removed.
`show.legend`	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.
`inherit.aes`	If `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. `borders()`.

Examples

library(ggplot2)

ggplot(iris, aes(x = Sepal.Length, y = Species, group = Species, fill = Species)) +
  geom_density_ridges(stat = "binline", bins = 20, scale = 2.2) +
  scale_y_discrete(expand = c(0.01, 0)) +
  scale_x_continuous(expand = c(0.01, 0)) +
  theme_ridges()

ggplot(iris, aes(x = Sepal.Length, y = Species, group = Species, fill = Species)) +
  stat_binline(bins = 20, scale = 2.2, draw_baseline = FALSE) +
  scale_y_discrete(expand = c(0.01, 0)) +
  scale_x_continuous(expand = c(0.01, 0)) +
  scale_fill_grey() +
  theme_ridges() + theme(legend.position = 'none')

require(ggplot2movies)
require(viridis)
ggplot(movies[movies$year>1989,], aes(x = length, y = year, fill = factor(year))) +
   stat_binline(scale = 1.9, bins = 40) +
   theme_ridges() + theme(legend.position = "none") +
   scale_x_continuous(limits = c(1, 180), expand = c(0.01, 0)) +
   scale_y_reverse(expand = c(0.01, 0)) +
   scale_fill_viridis(begin = 0.3, discrete = TRUE, option = "B") +
   labs(title = "Movie lengths 1990 - 2005")

count_data <- data.frame(group = rep(letters[1:5], each = 10),
                         mean = rep(1:5, each = 10))
count_data$group <- factor(count_data$group, levels = letters[5:1])
count_data$count <- rpois(nrow(count_data), count_data$mean)
ggplot(count_data, aes(x = count, y = group, group = group)) +
  geom_density_ridges2(stat = "binline", aes(fill = group), binwidth = 1, scale = 0.95) +
  geom_text(stat = "bin",
          aes(y = group+0.9*..count../max(..count..),
          label = ifelse(..count..>0, ..count.., "")),
          vjust = 1.2, size = 3, color = "white", binwidth = 1) +
  theme_ridges(grid = FALSE) +
  scale_x_continuous(breaks = c(0:12), limits = c(-.5, 13), expand = c(0, 0)) +
  scale_y_discrete(expand = c(0.01, 0)) +
  scale_fill_cyclical(values = c("#0000B0", "#7070D0")) +
  guides(y = "none")

[Package ggridges version 0.5.0 Index]