Split violin plots
R-bloggers 2013-06-25
Summary:
Violin plots are useful for comparing distributions. When data are grouped by a factor with two levels (e.g. males and females), you can split the violins in half to see the difference between groups. Consider a 2 x 2 factorial experiment: treatments A and B are crossed with groups 1 and 2, with N=1000.
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# Simulate datan.each <- 1000A1 <- rnorm(n.each, 2, 1)A2 <- rnorm(n.each, 1.5, 2)B1 <- rnorm(n.each, 4, 1.5)B2 <- rnorm(n.each, 0, 1)values <- c(A1, A2, B1, B2)treatment <- rep(c("A", "B"), each=n.each*2)group <- rep(c(1, 2, 1, 2), each=n.each)Boxplots are often used:
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par(bty="n")boxplot(values ~ group*treatment, main="Box plot", col=rep(c("purple", "lightblue"), 2))
This gives us a rough comparison of the distribution in each group, but sometimes it’s nice to visualize the kernel density estimates instead.
I recently ran into this issue and tweaked the vioplot() function from the vioplot package by Daniel Adler to make split violin plots. With vioplot2(), the side argument specifies whether to plot the density on “both”, the “left”, or the “right” side.
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require(vioplot)require(devtools)require(digest)source_gist("https://gist.github.com/mbjoseph/5852613")plot(x=NULL, y=NULL, xlim = c(0.5, 2.5), ylim=c(min(values), max(values)), type="n", ann=FALSE, axes=F)axis(1, at=c(1, 2), labels=c("A", "B"))axis(2)for (i in unique(treatment)) { for (j in unique(group)){ vioplot2(values[which(treatment == i & group == j)], at = ifelse(i == "A", 1, 2), side = ifelse(j == 1,</