Boxplot

Authors

[Editor] Hu Zheng;

[Contributors]

Modified

2026-01-17

Note

Hiplot website

This page is the tutorial for source code version of the Hiplot Boxplot 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/boxplot?lang=en

The box plot is a method of visualizing the distribution characteristics of a set of data by means of a quartile graph.

Setup

System Requirements: Cross-platform (Linux/MacOS/Windows)
Programming language: R
Dependent packages: data.table; jsonlite; ggpubr; ggthemes

# Install packages
if (!requireNamespace("data.table", quietly = TRUE)) {
  install.packages("data.table")
}
if (!requireNamespace("jsonlite", quietly = TRUE)) {
  install.packages("jsonlite")
}
if (!requireNamespace("ggpubr", quietly = TRUE)) {
  install.packages("ggpubr")
}
if (!requireNamespace("ggthemes", quietly = TRUE)) {
  install.packages("ggthemes")
}

# Load packages
library(data.table)
library(jsonlite)
library(ggpubr)
library(ggthemes)

sessioninfo::session_info("attached")

─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.5.2 (2025-10-31)
 os       Ubuntu 24.04.3 LTS
 system   x86_64, linux-gnu
 ui       X11
 language (EN)
 collate  C.UTF-8
 ctype    C.UTF-8
 tz       UTC
 date     2026-01-17
 pandoc   3.1.3 @ /usr/bin/ (via rmarkdown)
 quarto   1.8.27 @ /usr/local/bin/quarto

─ Packages ───────────────────────────────────────────────────────────────────
 package    * version date (UTC) lib source
 data.table * 1.18.0  2025-12-24 [1] RSPM
 ggplot2    * 4.0.1   2025-11-14 [1] RSPM
 ggpubr     * 0.6.2   2025-10-17 [1] RSPM
 ggthemes   * 5.2.0   2025-11-30 [1] RSPM
 jsonlite   * 2.0.0   2025-03-27 [1] RSPM

 [1] /home/runner/work/_temp/Library
 [2] /opt/R/4.5.2/lib/R/site-library
 [3] /opt/R/4.5.2/lib/R/library
 * ── Packages attached to the search path.

──────────────────────────────────────────────────────────────────────────────

Data Preparation

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

# Load data
data <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/boxplot/data.json")$exampleData$textarea[[1]])
data <- as.data.frame(data)

# convert data structure
groups <- unique(data[, 2])
my_comparisons <- combn(groups, 2, simplify = FALSE)
my_comparisons <- lapply(my_comparisons, as.character)

# View data
head(data)

  Value Group1 Group2
1   4.2    low treat1
2  11.5    low treat1
3   7.3    low treat1
4   5.8    low treat1
5   6.4    low treat1
6  10.0    low treat1

Visualization

# Boxplot
p <- ggboxplot(data, x = "Group1", y = "Value", notch = F, facet.by = "Group2",
               add = "point", color = "Group1", xlab = "Group2", ylab = "Value",
               palette = c("#e04d39","#5bbad6","#1e9f86"),
               title = "Box Plot") +
  stat_compare_means(comparisons = my_comparisons, label = "p.format", 
                     method = "t.test") +
  scale_y_continuous(expand = expansion(mult = c(0.1, 0.1))) +
  theme_stata() +
  theme(text = element_text(family = "Arial"),
        plot.title = element_text(size = 12,hjust = 0.5),
        axis.title = element_text(size = 12),
        axis.text = element_text(size = 10),
        axis.text.x = element_text(angle = 0, hjust = 0.5,vjust = 1),
        legend.position = "right",
        legend.direction = "vertical",
        legend.title = element_text(size = 10),
        legend.text = element_text(size = 10))

p

The abscissa represents several different sets of data, and the ordinate represents the quartile of each set of data respectively. The upper, middle and lower horizontal lines of the box represent the upper, median and lower quartile respectively; The values represented by the upper and lower line segments respectively exponential the maximum and minimum values of the data, and the points outside the box represent outliers. The above figure indicates the P value between two variables. It can be considered that in treatment plan 1, there is a significant difference in efficacy between the middle-dose group and the low-dose group, and so on.