DescTools (version 0.99.37)

PlotViolin: Plot Violins Instead of Boxplots

Description

This function serves the same utility as side-by-side boxplots, only it provides more detail about the different distribution. It plots violins instead of boxplots. That is, instead of a box, it uses the density function to plot the density. For skewed distributions, the results look like "violins". Hence the name.

Usage

PlotViolin(x, ...)

# S3 method for default PlotViolin(x, ..., horizontal = FALSE, bw = "SJ", na.rm = FALSE, names = NULL, args.boxplot = NULL)

# S3 method for formula PlotViolin(formula, data, subset, na.action, ...)

Arguments

x

Either a sequence of variable names, or a data frame, or a model formula

horizontal

logical indicating if the densityplots should be horizontal; default FALSE means vertical arrangement.

bw

the smoothing bandwidth (method) being used by density. bw can also be a character string giving a rule to choose the bandwidth. See bw.nrd. The default, has been switched from "nrd0" to "SJ", following the general recommendation in Venables & Ripley (2002). In case of a method, the average computed bandwidth is used.

na.rm

logical, should NAs be omitted? The density-function can't do with missings. Defaults to FALSE.

names

a vector of names for the groups.

formula

a formula, such as y ~ grp, where y is a numeric vector of data values to be split into groups according to the grouping variable grp (usually a factor).

data

a data.frame (or list) from which the variables in formula should be taken.

subset

an optional vector specifying a subset of observations to be used for plotting.

na.action

a function which indicates what should happen when the data contain NAs. Defaults to getOption("na.action").

The dots are passed to polygon. Notably, you can set the color to red with col="red", and a border color with border="blue"

args.boxplot

list of arguments for a boxplot to be superposed to the densityplot. By default (NULL) a black boxplot will be drawn. Set this to NA to suppress the boxplot.

Value

If a boxplot was drawn then the function returns a list with the following components:

stats

a matrix, each column contains the extreme of the lower whisker, the lower hinge, the median, the upper hinge and the extreme of the upper whisker for one group/plot. If all the inputs have the same class attribute, so will this component.

n

a vector with the number of observations in each group.

conf

a matrix where each column contains the lower and upper extremes of the notch.

out

the values of any data points which lie beyond the extremes of the whiskers.

group

a vector of the same length as out whose elements indicate to which group the outlier belongs.

names

a vector of names for the groups.

References

The code is based on the boxplot function from R/base.

See Also

boxplot, PlotMultiDens , density

Examples

Run this code
# NOT RUN {
# make a "violin"
x <- c(rnorm(100), rnorm(50,5))

PlotViolin(x, col = "brown")

par(mfrow=c(1,2))
f <- factor(rep(1:5, 30))
# make a quintet. Note also choice of bandwidth
PlotViolin(x ~ f, col = SetAlpha("steelblue",0.3), bw = "SJ", main="Vertical")

# and the same, but in horizontal arrangement
PlotViolin(x ~ f, col = SetAlpha("steelblue",0.3), bw = "SJ", horizontal = TRUE, 
  las=1, main="Horizontal")


# example taken from boxplot
boxplot(count ~ spray, data = InsectSprays, col = "lightgray", main="Boxplot")
PlotViolin(count ~ spray, data = InsectSprays, col = "lightgray", main="Violinplot")


# groupwise densityplots defined the same way as in boxplot
boxplot(len ~ supp*dose, data = ToothGrowth,
        main = "Guinea Pigs' Tooth Growth",
        xlab = "Vitamin C dose mg", ylab = "tooth length",
        col=c("yellow", "orange"), lty=c(1,2)
)

b <- PlotViolin(len ~ supp*dose, data = ToothGrowth,
           main = "Guinea Pigs' Tooth Growth",
           xlab = "Vitamin C dose mg", ylab = "tooth length",
           col=c("yellow", "orange"), lty=c(1,2)
)
# use points, if the medians deserve special attention
points(x=1:6, y=b$stats[3,], pch=21, bg="white", col="black", cex=1.2)
# }

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