Violin plot.

Violin plot.

geom_violin(mapping = NULL, data = NULL,
    stat = "ydensity", position = "dodge", trim = TRUE,
    scale = "area", ...)
If TRUE (default), trim the tails of the violins to the range of the data. If FALSE, don't trim the tails.
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.
The aesthetic mapping, usually constructed with aes or aes_string. Only needs to be set at the layer level if you are overriding the plot defaults.
A layer specific dataset - only needed if you want to override the plot defaults.
The statistical transformation to use on the data for this layer.
The position adjustment to use for overlappling points on this layer
other arguments passed on to layer. This can include aesthetics whose values you want to set, not map. See layer for more details.

[results=rd,stage=build]{ggplot2:::rd_aesthetics("geom", "violin")} 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))

  • geom_violin
Documentation reproduced from package ggplot2, version, License: GPL-2

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