Histogram

Authors

[Editor] Hu Zheng;

[Contributors]

Modified

2026-01-17

Note

Hiplot website

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

Histogram refers to the distribution of continuous variable data by a series of vertical stripes or line segments with different heights.

Setup

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

# 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("ggthemes", quietly = TRUE)) {
  install.packages("ggthemes")
}

# Load packages
library(data.table)
library(jsonlite)
library(ggplot2)
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
 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 the data set (data on treatment outcomes of different treatment regimens).

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

# Convert data structure
data[, 2] <- factor(data[, 2], levels = unique(data[, 2]))

# View data
head(data)

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

Visualization

# Histogram
p <- ggplot(data, aes(x=Value, fill=Group2)) +
  geom_histogram(alpha = 1, bins = 12, col = "white") +
  ggtitle("Histogram Plot") +
  scale_fill_manual(values = c("#e04d39","#5bbad6","#1e9f86")) +
  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 width of the rectangle in the figure is proportional to and different from the spacing, and the vertical axis represents the frequency.