Since boxplots have become the de facto standard for
plotting the distribution of data most users are familiar with these and
the formula input for dataframes. However this input is not available in
the standard vioplot package. Thus it has been restored
here for enhanced backwards compatibility with boxplot.
As shown below for the iris dataset, violin plots show
distribution information taking formula input that boxplot
implements but vioplot is unable to. This demonstrates the
customisation demonstrated in the
main vioplot vignette using vioplot syntax with the formula method
commonly used for boxplot, t.test, and
lm.
Whereas performing the same function does not work with
vioplot (0.2).
devtools::install_version("vioplot", version = "0.2")
library("vioplot")
vioplot(Sepal.Length~Species, data = iris)Error in min(data) : invalid 'type' (language) of argument
Another concern we see here is that the vioplot defaults
are not aesthetically pleasing, with a rather glaring colour scheme
unsuitable for professional or academic usage. Thus the plot default
colours have been changed as shown here:
Plot colours can be further customised as with the original vioplot
package using the col argument:
However the vioplot (0.2) function is unable to colour
each violin separately, thus this is enabled with a vectorised
col in vioplot (0.3):
vioplot(Sepal.Length~Species, data = iris, main = "Sepal Length", col=c("lightgreen", "lightblue", "palevioletred"))
legend("topleft", legend=c("setosa", "versicolor", "virginica"), fill=c("lightgreen", "lightblue", "palevioletred"), cex = 0.5)
Colours can also be customised for the violin fill and border
separately using the col and border
arguments:
vioplot(Sepal.Length~Species, data = iris, main = "Sepal Length", col="lightblue", border="royalblue")
Similarly, the arguments lineCol and
rectCol specify the colours of the boxplot outline and
rectangle fill. For simplicity the box and whiskers of the boxplot will
always have the same colour.
vioplot(Sepal.Length~Species, data = iris, main = "Sepal Length", rectCol="palevioletred", lineCol="violetred")
The same applies to the colour of the median point with
colMed:
### Combined customisation
These can be customised colours can be combined:
vioplot(Sepal.Length~Species, data = iris, main = "Sepal Length", col="lightblue", border="royalblue", rectCol="palevioletred", lineCol="violetred", colMed="violet")
These colour and shape settings can also be customised separately for each violin:
vioplot(Sepal.Length~Species, data = iris, main="Sepal Length", col=c("lightgreen", "lightblue", "palevioletred"), border=c("darkolivegreen4", "royalblue4", "violetred4"), rectCol=c("forestgreen", "blue", "palevioletred3"), lineCol=c("darkolivegreen", "royalblue", "violetred4"), colMed=c("green", "cyan", "magenta"), pchMed=c(15, 17, 19))
Here we demonstrate additional annotation features to display outliers and group sizes.
Note that y-axes limits need to be adjusted to avoid overlaying text.
## The following objects are masked from iris_small:
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species## The following objects are masked from iris_large:
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species## The following objects are masked from iris2:
##
## 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, Speciesvioplot(Sepal.Length~Species, data = iris, main = "Sepal Length", ylab = "",
col=c("lightgreen", "lightblue", "palevioletred"), ylim = c(0, max(Sepal.Length) * 1.1))
legend("bottomright", legend=c("setosa", "versicolor", "virginica"),
fill=c("lightgreen", "lightblue", "palevioletred"), cex = 0.8)
add_labels(unlist(iris$Sepal.Length), iris$Species, height = 0.5, cex = 0.8)
#### Plotting outliers and medians
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$Species)##
## setosa versicolor virginica
## 52 52 52This adds outliers to the plot.
## The following objects are masked from iris (pos = 3):
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species## The following objects are masked from iris_small:
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species## The following objects are masked from iris_large:
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species## The following objects are masked from iris2 (pos = 6):
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species## The following objects are masked from iris (pos = 7):
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Speciesvioplot(Sepal.Length~Species, data = iris2, main = "Sepal Length",
col=c("lightgreen", "lightblue", "palevioletred"), ylim = c(min(Sepal.Length) * 0.9, max(Sepal.Length) * 1.1))
Sepal.medians <- sapply(unique(Species), function(sp) median(Sepal.Length[Species == sp]))
# highlights medians
points(x = c(1:length(Sepal.medians)), y = Sepal.medians, pch = 21, cex = 1.25, lwd = 2,
col = "white", bg = c("forestgreen", "lightblue4", "palevioletred4"))
# plots outliers above 2 SD
add_outliers(unlist(iris2$Sepal.Length), iris2$Species, cutoff = 2,
col = "black", bars = "grey85", lwd = 2,
fill = c("palegreen3", "lightblue3", "palevioletred3"))
legend("bottomright", legend=c("setosa", "versicolor", "virginica"),
fill=c("lightgreen", "lightblue", "palevioletred"), cex = 0.6)
add_labels(unlist(iris2$Sepal.Length), iris2$Species, height = 0.5, cex = 0.8)
Annotation on split violins are shown here. See the split violin plot
vignette for details on these parameters.
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.000 2.800 3.000 3.151 3.400 12.000##
## FALSE TRUE
## 97 59iris_large <- iris2[iris2$Sepal.Width > mean(iris2$Sepal.Width), ]
iris_small <- iris2[iris2$Sepal.Width <= mean(iris2$Sepal.Width), ]
attach(iris_large)## The following objects are masked from iris2 (pos = 3):
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species## The following objects are masked from iris (pos = 4):
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species## The following objects are masked from iris_small:
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species## The following objects are masked from iris_large (pos = 6):
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species## The following objects are masked from iris2 (pos = 7):
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species## The following objects are masked from iris (pos = 8):
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Speciesvioplot(Sepal.Length~Species, data=iris_large, plotCentre = "line", side = "right", col=c("lightgreen", "lightblue", "palevioletred"), ylim = c(min(iris2$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 iris2 (pos = 4):
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species## The following objects are masked from iris (pos = 5):
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species## The following objects are masked from iris_small (pos = 6):
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species## The following objects are masked from iris_large (pos = 7):
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species## The following objects are masked from iris2 (pos = 8):
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Species## The following objects are masked from iris (pos = 9):
##
## Petal.Length, Petal.Width, Sepal.Length, Sepal.Width, Speciesvioplot(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)
# add legend and titles
legend("topleft", fill = c("lightblue2", "lightblue3"), legend = c("small", "large"), title = "Sepal Width")
title(xlab = "Species", ylab = "Sepal Length")