Beanplot

Authors

[Editor] Hu Zheng;

[Contributors]

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:

https://hiplot.cn/basic/beanplot?lang=en

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

# Install packages
if (!requireNamespace("ggplotify", quietly = TRUE)) {
  install.packages("ggplotify")
}
if (!requireNamespace("beanplot", quietly = TRUE)) {
  install.packages("beanplot")
}

# Load packages
library(ggplotify)
library(beanplot)

Data Preparation

The loaded data is data set (data on treatment outcomes of different treatment regimens).

# Load data
data <- read.table("files/Hiplot/011-beanplot-data.txt", header = T)

# convert data structure
GroupOrder <- as.numeric(factor(data[, 2], levels = unique(data[, 2])))
data[, 2] <- paste0(data[,2], " ", as.numeric(factor(data[, 3])))
data <- cbind(data, GroupOrder)

# 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
p <- as.ggplot(function() {
  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
FigureΒ 1: Beanplot