Percentsge Stacked Bar Chart

Authors

[Editor] Hu Zheng;

[Contributors]

Modified

2026-01-17

Note

Hiplot website

This page is the tutorial for source code version of the Hiplot Percentsge Stacked Bar Chart 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/stacked-percentage-bar-chart?lang=en

Setup

System Requirements: Cross-platform (Linux/MacOS/Windows)
Programming language: R
Dependent packages: data.table; jsonlite; ggplot2; dplyr; tidyr; scales

# Install packages
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("dplyr", quietly = TRUE)) {
  install.packages("dplyr")
}
if (!requireNamespace("tidyr", quietly = TRUE)) {
  install.packages("tidyr")
}
if (!requireNamespace("scales", quietly = TRUE)) {
  install.packages("scales")
}

# Load packages
library(data.table)
library(jsonlite)
library(ggplot2)
library(dplyr)
library(tidyr)
library(scales)

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
 dplyr      * 1.1.4   2023-11-17 [1] RSPM
 ggplot2    * 4.0.1   2025-11-14 [1] RSPM
 jsonlite   * 2.0.0   2025-03-27 [1] RSPM
 scales     * 1.4.0   2025-04-24 [1] RSPM
 tidyr      * 1.3.2   2025-12-19 [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 case data represents the sales percentage of three different products in a shopping mall over the course of one week.

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

# convert data structure
data$total <- rowSums(data[, -1])
data_long <- gather(data, kinds, value, -days, -total)
data_long <- data_long %>%
  group_by(days) %>%
  mutate(percent = value / total * 100)
data_long[["days"]] <- factor(data_long[["days"]], levels = data[["days"]])

# View data
head(data)

       days goods1 goods2 goods3 total
1    Monday    150    300      0   450
2   Tuesday    200    250      0   450
3 Wednesday    300    100      0   400
4  Thursday    200    300      0   500
5    Friday    100    300      0   400
6  Saturday     50     50    400   500

Visualization

# Percentsge Stacked Bar Chart
p <- ggplot(data_long, aes(x = percent, y = days, fill = kinds)) +
  geom_bar(stat = "identity", position = "stack") +
  geom_text(aes(label = ifelse(percent != 0, paste0(round(percent), "%"), "")),
            position = position_stack(vjust = 0.5)) +
  labs(title = "Percentage Stacked Bar Chart", x = "Percentage", y = "Days") +
  scale_x_continuous(labels = percent_format(scale = 1)) +
  theme_bw() +
  theme(plot.title = element_text(hjust = 0.5)) +
  scale_fill_manual(values = c("#E64B35FF","#4DBBD5FF","#00A087FF"))

p