# Install packages
if (!requireNamespace("ggplotify", quietly = TRUE)) {
install.packages("ggplotify")
}if (!requireNamespace("beanplot", quietly = TRUE)) {
install.packages("beanplot")
}
# Load packages
library(ggplotify)
library(beanplot)
Beanplot
Note
Hiplot website
This page is the tutorial for source code version of the Hiplot Beanplot
plugin. You can also use the Hiplot website to achieve no code ploting. For more information please see the following link:
The beanplot is a method of visualizing the distribution characteristics.
Setup
System Requirements: Cross-platform (Linux/MacOS/Windows)
Programming language: R
Dependent packages:
ggplotify
;beanplot
Data Preparation
The loaded data is data set (data on treatment outcomes of different treatment regimens).
# Load data
<- read.table("files/Hiplot/011-beanplot-data.txt", header = T)
data
# convert data structure
<- as.numeric(factor(data[, 2], levels = unique(data[, 2])))
GroupOrder 2] <- paste0(data[,2], " ", as.numeric(factor(data[, 3])))
data[, <- cbind(data, GroupOrder)
data
# View data
head(data)
Y X Group GroupOrder
1 4.2 low 1 treat1 1
2 11.5 low 1 treat1 1
3 7.3 low 1 treat1 1
4 5.8 low 1 treat1 1
5 6.4 low 1 treat1 1
6 10.0 low 1 treat1 1
Visualization
# Beanplot
<- as.ggplot(function() {
p beanplot(Y ~ reorder(X, GroupOrder, mean), data = data, ll = 0.04,
main = "Bean Plot", ylab = "Y", xlab = "X", side = "both",
border = NA, horizontal = F,
col = list(c("#2b70c4", "#2b70c4"),c("#e9c216", "#e9c216")),
beanlines = "mean", overallline = "mean", kernel = "gaussian")
legend("bottomright", fill = c("#2b70c4", "#e9c216"),
legend = levels(factor(data[, 3])))
})
p
