桑基图

作者

[编辑] 郑虎;

[审核] .

修改于

2026-01-27

注记

Hiplot 网站

本页面为 Hiplot Sankey 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:

https://hiplot.cn/basic/sankey?lang=zh_cn

桑基图是一种流量图，其中箭头的宽度与流量成比例。

环境配置

  • 系统: Cross-platform (Linux/MacOS/Windows)

  • 编程语言: R

  • 依赖包: data.table; jsonlite; ggalluvial; ggplot2

# 安装包
if (!requireNamespace("data.table", quietly = TRUE)) {
  install.packages("data.table")
}
if (!requireNamespace("jsonlite", quietly = TRUE)) {
  install.packages("jsonlite")
}
if (!requireNamespace("ggalluvial", quietly = TRUE)) {
  install.packages("ggalluvial")
}
if (!requireNamespace("ggplot2", quietly = TRUE)) {
  install.packages("ggplot2")
}

# 加载包
library(data.table)
library(jsonlite)
library(ggalluvial)
library(ggplot2)
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     2026-01-27
 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
 ggalluvial * 0.12.5  2023-02-22 [1] RSPM
 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

载入数据为 4 个变量及每4种变量组合下的频数。

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

# 整理数据格式
value <- "Freq"
axis <- c("Class", "Sex")
usr_axis <- c()
for (i in seq_len(length(axis))) {
  usr_axis <- c(usr_axis, axis[i])
  assign(paste0("axis", i), axis[i])
}
index_axis <- match(usr_axis, colnames(data))
index_value <- match(value, colnames(data))
data1 <- data[, c(index_value, index_axis)]
## 定义带颜色
nlevels <- as.numeric(apply(data1[, -1], 2, function(data) {
  return(length(unique(data)))
}))
band_color <- c("#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#8DD3C7", "#FFFFB3")
## 重命名数据
data_rename <- data1
colnames(data_rename) <- c(
  "value",
  paste("axis", seq_len(length(usr_axis)), sep = "")
)

# 查看数据
head(data)
  Class    Sex   Age Survived Freq
1   1st   Male Child       No    0
2   2nd   Male Child       No    0
3   3rd   Male Child       No   35
4  Crew   Male Child       No    0
5   1st Female Child       No    0
6   2nd Female Child       No    0

可视化

# 桑基图
p <- ggplot(data_rename, aes(y = value, axis1 = axis1, axis2 = axis2)) +
  geom_alluvium(alpha = 1, aes(fill = data1[, colnames(data1) == "Sex"]),
                width = 0, reverse = FALSE) +
  scale_x_discrete(limits = usr_axis, expand = c(0.02, 0.1)) +
  ylab("") +
  scale_fill_discrete(name = "Sex") +
  coord_flip() +
  geom_stratum(alpha = 1, width = 1 / 8, reverse = FALSE, fill = band_color,
               color = "white") +
  geom_text(stat = "stratum", infer.label = TRUE, reverse = FALSE) +
  ggtitle("Sankey plot") +
  guides(fill = guide_legend(title = "Sex")) +
  scale_fill_manual(values = c("#00468BFF", "#ED0000FF")) +
  theme_bw() +
  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
图 1: 桑基图

female 分流的颜色为蓝色，male 分流的颜色为红色，蓝色分流出去的宽度和等于 female 的总宽度。