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
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
|
% Generated by roxygen2 (4.0.1): do not edit by hand
\name{geom_violin}
\alias{geom_violin}
\title{Violin plot.}
\usage{
geom_violin(mapping = NULL, data = NULL, stat = "ydensity",
position = "dodge", trim = TRUE, scale = "area", ...)
}
\arguments{
\item{trim}{If \code{TRUE} (default), trim the tails of the violins
to the range of the data. If \code{FALSE}, don't trim the tails.}
\item{scale}{if "area" (default), all violins have the same area (before trimming
the tails). If "count", areas are scaled proportionally to the number of
observations. If "width", all violins have the same maximum width.}
\item{mapping}{The aesthetic mapping, usually constructed with
\code{\link{aes}} or \code{\link{aes_string}}. Only needs to be set
at the layer level if you are overriding the plot defaults.}
\item{data}{A layer specific dataset - only needed if you want to override
the plot defaults.}
\item{stat}{The statistical transformation to use on the data for this
layer.}
\item{position}{The position adjustment to use for overlapping points
on this layer}
\item{...}{other arguments passed on to \code{\link{layer}}. This can
include aesthetics whose values you want to set, not map. See
\code{\link{layer}} for more details.}
}
\description{
Violin plot.
}
\section{Aesthetics}{
\Sexpr[results=rd,stage=build]{ggplot2:::rd_aesthetics("geom", "violin")}
}
\examples{
\donttest{
p <- ggplot(mtcars, aes(factor(cyl), mpg))
p + geom_violin()
qplot(factor(cyl), mpg, data = mtcars, geom = "violin")
p + geom_violin() + geom_jitter(height = 0)
p + geom_violin() + coord_flip()
qplot(factor(cyl), mpg, data = mtcars, geom = "violin") +
coord_flip()
# Scale maximum width proportional to sample size:
p + geom_violin(scale = "count")
# Scale maximum width to 1 for all violins:
p + geom_violin(scale = "width")
# Default is to trim violins to the range of the data. To disable:
p + geom_violin(trim = FALSE)
# Use a smaller bandwidth for closer density fit (default is 1).
p + geom_violin(adjust = .5)
# Add aesthetic mappings
# Note that violins are automatically dodged when any aesthetic is
# a factor
p + geom_violin(aes(fill = cyl))
p + geom_violin(aes(fill = factor(cyl)))
p + geom_violin(aes(fill = factor(vs)))
p + geom_violin(aes(fill = factor(am)))
# Set aesthetics to fixed value
p + geom_violin(fill = "grey80", colour = "#3366FF")
qplot(factor(cyl), mpg, data = mtcars, geom = "violin",
colour = I("#3366FF"))
# Scales vs. coordinate transforms -------
# Scale transformations occur before the density statistics are computed.
# Coordinate transformations occur afterwards. Observe the effect on the
# number of outliers.
library(plyr) # to access round_any
m <- ggplot(movies, aes(y = votes, x = rating,
group = round_any(rating, 0.5)))
m + geom_violin()
m + geom_violin() + scale_y_log10()
m + geom_violin() + coord_trans(y = "log10")
m + geom_violin() + scale_y_log10() + coord_trans(y = "log10")
# Violin plots with continuous x:
# Use the group aesthetic to group observations in violins
qplot(year, budget, data = movies, geom = "violin")
qplot(year, budget, data = movies, geom = "violin",
group = round_any(year, 10, floor))
}
}
|
