# 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("reshape2", quietly = TRUE)) {
install.packages("reshape2")
}
if (!requireNamespace("ggthemes", quietly = TRUE)) {
install.packages("ggthemes")
}
# Load packages
library(data.table)
library(jsonlite)
library(ggplot2)
library(reshape2)
library(ggthemes)Multiple Barplot&Line
Note
Hiplot website
This page is the tutorial for source code version of the Hiplot Multiple Barplot&Line plugin. You can also use the Hiplot website to achieve no code ploting. For more information please see the following link:
Displaying multiple bar or line plot in one diagram.
Setup
System Requirements: Cross-platform (Linux/MacOS/Windows)
Programming language: R
Dependent packages:
data.table;jsonlite;ggplot2;reshape2;ggthemes
sessioninfo::session_info("attached")β Session info βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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
β Packages βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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
reshape2 * 1.4.5 2025-11-12 [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
* ββ Packages attached to the search path.
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
Data Preparation
Data frame with multiple columns data (Numeric).
# Load data
data <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/barplot-line-multiple/data.json")$exampleData$textarea[[1]])
data <- as.data.frame(data)
# convert data structure
data_melt <- melt(data, id.vars = colnames(data)[1])
data_melt[, 1] <- factor(data_melt[, 1], level = unique(data_melt[, 1]))
# View data
head(data) age height weight math biology english chinese
1 12 158 100 120 90 115 140
2 15 160 110 145 80 120 120
3 18 175 120 132 95 118 110
4 20 176 121 124 99 118 136
5 21 176 120 135 98 114 150
6 22 177 124 140 87 110 150
Visualization
1. Multiple Line
# Multiple Line
p <- ggplot(data = data_melt, aes(x = age, y = value, group = variable,
colour = variable)) +
geom_line(alpha = 1, size = 1) +
geom_point(aes(shape = variable), alpha = 1, size = 3) +
labs(title = "Line (Multiple)", x = "X Lable", y = "Value") +
scale_color_manual(values = c("#3B4992FF","#EE0000FF","#008B45FF","#631879FF",
"#008280FF","#BB0021FF")) +
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
2. Multiple Barplot
# Multiple Barplot
p <- ggplot(data = data_melt, aes(x = age, y = value, fill = variable)) +
geom_bar(stat = "identity", position = position_dodge(), colour = "black",
alpha = 1) +
labs(title = "", x = "X Lable", y = "Value") +
scale_fill_manual(values = c("#3B4992FF","#EE0000FF","#008B45FF","#631879FF",
"#008280FF","#BB0021FF")) +
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
