# Split Violin Plots

#### 2024-07-05

##Violin Plots

Therefore violin plots are a powerful tool to assist researchers to visualise data, particularly in the quality checking and exploratory parts of an analysis. Violin plots have many benefits:

• Greater flexibility for plotting variation than boxplots
• More familiarity to boxplot users than density plots
• Easier to directly compare data types than existing plots

As shown below for the iris dataset, violin plots show distribution information that the boxplot is unable to.

###General Set up

library("vioplot")

We set up the data with two categories (Sepal Width) as follows:

data(iris)
summary(iris$Sepal.Width) ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 2.000 2.800 3.000 3.057 3.300 4.400 table(iris$Sepal.Width > mean(iris$Sepal.Width)) ## ## FALSE TRUE ## 83 67 iris_large <- iris[iris$Sepal.Width > mean(iris$Sepal.Width), ] iris_small <- iris[iris$Sepal.Width <= mean(iris$Sepal.Width), ] ###Boxplots First we plot Sepal Length on its own: boxplot(Sepal.Length~Species, data=iris, col="grey") An indirect comparison can be achieved with par: { par(mfrow=c(2,1)) boxplot(Sepal.Length~Species, data=iris_small, col = "lightblue") boxplot(Sepal.Length~Species, data=iris_large, col = "palevioletred") par(mfrow=c(1,1)) } ### Violin Plots First we plot Sepal Length on its own: vioplot(Sepal.Length~Species, data=iris) An indirect comparison can be achieved with par: { par(mfrow=c(2,1)) vioplot(Sepal.Length~Species, data=iris_small, col = "lightblue", plotCentre = "line") vioplot(Sepal.Length~Species, data=iris_large, col = "palevioletred", plotCentre = "line") par(mfrow=c(1,1)) } An indirect comparison can be achieved with par: { par(mfrow=c(1,2)) vioplot(Sepal.Length~Species, data=iris_small, col = "lightblue", plotCentre = "line") vioplot(Sepal.Length~Species, data=iris_large, col = "palevioletred", plotCentre = "line") par(mfrow=c(1,1)) } ### Split Violin Plots A more direct comparision can be made with the side argument and add = TRUE on the second plot: vioplot(Sepal.Length~Species, data=iris_large, col = "palevioletred", plotCentre = "line", side = "right") vioplot(Sepal.Length~Species, data=iris_small, col = "lightblue", plotCentre = "line", side = "left", add = T) title(xlab = "Species", ylab = "Sepal Length") legend("topleft", fill = c("lightblue", "palevioletred"), legend = c("small", "large"), title = "Sepal Width") #### Custom axes labels Custom axes labels are supported for split violin plots. However, you must use these arguments on the first call of vioplot. vioplot(Sepal.Length~Species, data=iris_large, col = "palevioletred", plotCentre = "line", side = "right", xlab = "Iris species", ylab = "Length", main = "Sepals", names=paste("Iris", levels(iris$Species)))
vioplot(Sepal.Length~Species, data=iris_small, col = "lightblue", plotCentre = "line", side = "left", add = T)
legend("topleft", fill = c("lightblue", "palevioletred"), legend = c("small", "large"), title = "Width")

Note that this is disabled for the second vioplot call to avoid overlaying labels.

vioplot(Sepal.Length~Species, data=iris_large, col = "palevioletred", plotCentre = "line", side = "right")
vioplot(Sepal.Length~Species, data=iris_small, col = "lightblue", plotCentre = "line", side = "left", add = T, xlab = "Iris species", ylab = "Length", main = "Sepals", names=paste("Iris", levels(iris$Species))) ## Warning in vioplot.formula(Sepal.Length ~ Species, data = iris_small, col = "lightblue", : Warning: names can only be changed on first call of vioplot (when add = FALSE) ## Warning in vioplot.formula(Sepal.Length ~ Species, data = iris_small, col = "lightblue", : Warning: x-axis labels can only be changed on first call of vioplot (when add = FALSE) ## Warning in vioplot.formula(Sepal.Length ~ Species, data = iris_small, col = "lightblue", : Warning: y-axis labels can only be changed on first call of vioplot (when add = FALSE) ## Warning in vioplot.default(x, ...): Warning: names can only be changed on first call of vioplot (when add = FALSE) legend("topleft", fill = c("lightblue", "palevioletred"), legend = c("small", "large"), title = "Width") #### Median The line median option is more suitable for side by side comparisions but the point option is still available also: vioplot(Sepal.Length~Species, data=iris_large, col = "palevioletred", plotCentre = "point", side = "right", pchMed = 21, colMed = "palevioletred4", colMed2 = "palevioletred2") vioplot(Sepal.Length~Species, data=iris_small, col = "lightblue", plotCentre = "point", side = "left", pchMed = 21, colMed = "lightblue4", colMed2 = "lightblue2", add = T) title(xlab = "Species", ylab = "Sepal Length") legend("topleft", fill = c("lightblue", "palevioletred"), legend = c("small", "large"), title = "Sepal Width") It may be necessary to include a points command to fix the median being overwritten by the following plots: vioplot(Sepal.Length~Species, data=iris_large, col = "palevioletred", plotCentre = "point", side = "right", pchMed = 21, colMed = "palevioletred4", colMed2 = "palevioletred2") vioplot(Sepal.Length~Species, data=iris_small, col = "lightblue", plotCentre = "point", side = "left", pchMed = 21, colMed = "lightblue4", colMed2 = "lightblue2", add = T) points(1:length(levels(iris$Species)), as.numeric(sapply(levels(iris$Species), function(species) median(iris_large[grep(species, iris_large$Species),]$Sepal.Length))), pch = 21, col = "palevioletred4", bg = "palevioletred2") title(xlab = "Species", ylab = "Sepal Length") legend("topleft", fill = c("lightblue", "palevioletred"), legend = c("small", "large"), title = "Sepal Width") Similarly points could be added where a line has been used previously: vioplot(Sepal.Length~Species, data=iris_large, col = "palevioletred", plotCentre = "line", side = "right", pchMed = 21, colMed = "palevioletred4", colMed2 = "palevioletred2") vioplot(Sepal.Length~Species, data=iris_small, col = "lightblue", plotCentre = "line", side = "left", pchMed = 21, colMed = "lightblue4", colMed2 = "lightblue2", add = T) points(1:length(levels(iris$Species)), as.numeric(sapply(levels(iris$Species), function(species) median(iris_large[grep(species, iris_large$Species),]$Sepal.Length))), pch = 21, col = "palevioletred4", bg = "palevioletred2") points(1:length(levels(iris$Species)), as.numeric(sapply(levels(iris$Species), function(species) median(iris_small[grep(species, iris_small$Species),]$Sepal.Length))), pch = 21, col = "lightblue4", bg = "lightblue2") title(xlab = "Species", ylab = "Sepal Length") legend("topleft", fill = c("lightblue", "palevioletred"), legend = c("small", "large"), title = "Sepal Width") Here it is aesthetically pleasing and intuitive to interpret categorical differences in mean and variation in a continuous variable. ### Enchanced annotation demonstration. Here we add outliers and show annotation features. # add outliers to demo data iris2 <- iris iris2 <- rbind(iris2, c(7, 1, 0, 0, "setosa")) iris2 <- rbind(iris2, c(1, 10, 0, 0, "setosa")) iris2 <- rbind(iris2, c(9, 2, 0, 0, "versicolor")) iris2 <- rbind(iris2, c(2, 12, 0, 0, "versicolor")) iris2 <- rbind(iris2, c(10, 1, 0, 0, "virginica")) iris2 <- rbind(iris2, c(12, 7, 0, 0, "virginica")) iris2$Species <- factor(iris2$Species) iris2$Sepal.Length <- as.numeric(iris2$Sepal.Length) iris2$Sepal.Width <- as.numeric(iris2$Sepal.Width) table(iris2$Species)
##
##     setosa versicolor  virginica
##         52         52         52

Annotation on split violins are shown here. See the main violin plot vignette for details on these parameters.

data(iris)
summary(iris2$Sepal.Width) ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 1.000 2.800 3.000 3.151 3.400 12.000 table(iris2$Sepal.Width > mean(iris2$Sepal.Width)) ## ## FALSE TRUE ## 97 59 iris_large <- iris2[iris2$Sepal.Width > mean(iris2$Sepal.Width), ] iris_small <- iris2[iris2$Sepal.Width <= mean(iris2$Sepal.Width), ] attach(iris_large) ## The following objects are masked from iris_small (pos = 3): ## ## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species ## The following objects are masked from iris_large (pos = 4): ## ## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species ## The following objects are masked from iris2 (pos = 5): ## ## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species ## The following objects are masked from iris (pos = 6): ## ## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species ## The following objects are masked from iris_small (pos = 7): ## ## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species ## The following objects are masked from iris_large (pos = 8): ## ## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species ## The following objects are masked from iris2 (pos = 9): ## ## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species ## The following objects are masked from iris (pos = 10): ## ## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species vioplot(Sepal.Length~Species, data=iris_large, plotCentre = "line", side = "right", col=c("lightgreen", "lightblue", "palevioletred"), ylim = c(min(iris2$Sepal.Length) * 0.9, max(iris2$Sepal.Length) * 1.1), names=c("setosa", "versicolor", "virginica")) Sepal.medians <- sapply(unique(Species), function(sp) median(iris_large$Sepal.Length[Species == sp]))
# highlights medians
points(x = c(1:length(Sepal.medians)), y = Sepal.medians, pch = 21, cex = 1.25, lwd = 2,
col = "white", bg = c("forestgreen", "lightblue4", "palevioletred4"))
# plots outliers above 2 SD
add_outliers(unlist(iris_large$Sepal.Length), iris2$Species, cutoff = 2,
col = c("palegreen3", "lightblue3", "palevioletred3"), bars = "grey85", lwd = 2,
fill = "grey85")
legend("bottomright", legend=c("setosa", "versicolor", "virginica"),
fill=c("palegreen3", "lightblue3", "palevioletred3"), cex = 0.6)
add_labels(unlist(iris2$Sepal.Length), iris2$Species, height = 0.5, cex = 0.8)

attach(iris_small)
## The following objects are masked from iris_large (pos = 3):
##
##     Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species
## The following objects are masked from iris_small (pos = 4):
##
##     Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species
## The following objects are masked from iris_large (pos = 5):
##
##     Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species
## The following objects are masked from iris2 (pos = 6):
##
##     Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species
## The following objects are masked from iris (pos = 7):
##
##     Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species
## The following objects are masked from iris_small (pos = 8):
##
##     Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species
## The following objects are masked from iris_large (pos = 9):
##
##     Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species
## The following objects are masked from iris2 (pos = 10):
##
##     Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species
## The following objects are masked from iris (pos = 11):
##
##     Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species
vioplot(Sepal.Length~Species, data=iris_small, plotCentre = "line", side = "left", add = T, col=c("palegreen1", "lightblue1", "palevioletred1"), ylim = c(min(Sepal.Length) * 0.9, max(Sepal.Length) * 1.1),
names=c("setosa", "versicolor", "virginica"))
## Warning in vioplot.formula(Sepal.Length ~ Species, data = iris_small, plotCentre = "line", : Warning: names can only be changed on first call of vioplot (when add = FALSE)
## Warning in vioplot.default(x, ...): Warning: names can only be changed on first call of vioplot (when add = FALSE)
Sepal.medians <- sapply(unique(Species), function(sp) median(iris_small$Sepal.Length[Species == sp])) # highlights medians points(x = c(1:length(Sepal.medians)), y = Sepal.medians, pch = 21, cex = 1.25, lwd = 2, col = "white", bg = c("forestgreen", "lightblue4", "palevioletred4")) # plots outliers above 2 SD add_outliers(unlist(iris2$Sepal.Length), iris2$Species, cutoff = 2, col = c("palegreen3", "lightblue3", "palevioletred3"), bars = "grey85", lwd = 2, fill = "grey50") legend("bottomright", legend=c("setosa", "versicolor", "virginica"), fill=c("lightgreen", "lightblue", "palevioletred"), cex = 0.6) add_labels(unlist(iris2$Sepal.Length), iris2\$Species, height = 0.5, cex = 0.8)

title(xlab = "Species", ylab = "Sepal Length")
These extensions to vioplot here are based on those provided here: