# 安装包
if (!requireNamespace("data.table", quietly = TRUE)) {
install.packages("data.table")
}
if (!requireNamespace("jsonlite", quietly = TRUE)) {
install.packages("jsonlite")
}
if (!requireNamespace("ggplot2", quietly = TRUE)) {
install.packages("ggplot2")
}
if (!requireNamespace("ggalt", quietly = TRUE)) {
remotes::install_github("hrbrmstr/ggalt")
}
# 加载包
library(data.table)
library(jsonlite)
library(ggplot2)
library(ggalt)分组哑铃图
注记
Hiplot 网站
本页面为 Hiplot Group Dumbbell 插件的源码版本教程,您也可以使用 Hiplot 网站实现无代码绘图,更多信息请查看以下链接:
环境配置
系统: Cross-platform (Linux/MacOS/Windows)
编程语言: R
依赖包:
data.table;jsonlite;ggplot2;ggalt
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 2026-01-18
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
ggalt * 0.6.1 2025-11-02 [1] Github (hrbrmstr/ggalt@8941f8c)
ggplot2 * 4.0.1 2025-11-14 [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.
──────────────────────────────────────────────────────────────────────────────
数据准备
# 加载数据
data <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/group-dumbbell/data.json")$exampleData$textarea[[1]])
data <- as.data.frame(data)
# 整理数据格式
data <- data[order(data[["group"]], data[["y1952"]]),]
data[["country"]] <- factor(data[["country"]], levels = data[["country"]])
# 查看数据
head(data) country y1952 y2007 group
13 Haiti 37.579 60.916 A
2 Bolivia 40.414 65.554 A
12 Guatemala 42.023 70.259 A
11 El Salvador 45.262 71.878 A
9 Dominican Republic 45.928 72.235 A
10 Ecuador 48.357 74.994 A
可视化
# 分组哑铃图
p <- ggplot(data = data, aes(x = y1952, xend = y2007, y = country, color = group)) +
geom_dumbbell(size = 1, size_xend = 2, size_x = 2) +
theme_bw()
p
