gghistogram: Grob function: histogram

In hadley/ggplot1: Before there was ggplot2

Description

Conceptually, the histogram is one of the most complicated of the grob functions, becuase it takes a 1D data set and makes it two dimensional. This necessitates an extra step, the pre_histogram function which bins the data and returns the bins with their counts. This data is then used my grob_histogram to plot the points.

Usage

gghistogram(plot, aesthetics = list(), scale = "prob", ...,
  data = NULL)

Arguments

plot	the plot object to modify
aesthetics	named list of aesthetic mappings, see details for more information
scale	scale of y-axis
...	other options, see details for more information
data	data source, if not specified the plot default will be used

Details

Aesthetic mappings that this grob function understands:

• x:x position (required)

• weight: observation weights

These can be specified in the plot defaults (see ggplot) or in the aesthetics argument. If you want to modify the position of the points or any axis options, you will need to add a position scale to the plot. These functions start with ps, eg. pscontinuous or pscategorical

Other options:

• breaks:breaks argument passed to hist

• scale:scale argument passed to hist

• any other aesthetic setting passed on to ggrect

Examples

library(ggplot2movies)
m <- ggplot(movies, aesthetics=list(x=rating))
gghistogram(m)
gghistogram(m, breaks=100)

m <- ggplot(movies, Action ~ Comedy, aesthetics=list(x=rating), margins=TRUE)
gghistogram(m)
gghistogram(m, scale="freq")
gghistogram(m, colour="darkgreen", fill="white")
ggdensity(gghistogram(m, colour="darkgreen", fill="white"))

hadley/ggplot1 documentation built on Aug. 19, 2019, 2:42 p.m.