# Install packages
if (!requireNamespace("data.table", quietly = TRUE)) {
install.packages("data.table")
}
if (!requireNamespace("jsonlite", quietly = TRUE)) {
install.packages("jsonlite")
}
if (!requireNamespace("GGally", quietly = TRUE)) {
install.packages("GGally")
}
# Load packages
library(data.table)
library(jsonlite)
library(GGally)Bivariate Chart
Note
Hiplot website
This page is the tutorial for source code version of the Hiplot Bivariate Chart plugin. You can also use the Hiplot website to achieve no code ploting. For more information please see the following link:
Display the bivariate.
Setup
System Requirements: Cross-platform (Linux/MacOS/Windows)
Programming language: R
Dependent packages:
data.table;jsonlite;GGally
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
GGally * 2.4.0 2025-08-23 [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
* ββ Packages attached to the search path.
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
Data Preparation
# Load data
data <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/bivariate/data.json")$exampleData$textarea[[1]])
data <- as.data.frame(data)
# View data
head(data) total_bill tip gender smoker day time size
1 16.99 1.01 Female No Sun Dinner 2
2 10.34 1.66 Male No Sun Dinner 3
3 21.01 3.50 Male No Sun Dinner 3
4 23.68 3.31 Male No Sun Dinner 2
5 24.59 3.61 Female No Sun Dinner 4
6 25.29 4.71 Male No Sun Dinner 4
Visualization
# Bivariate Chart
p <- ggbivariate(data, outcome = "smoker",
explanatory = c("day","time","gender","tip")) +
ggtitle("Bivariate") +
scale_fill_manual(values = c("#e04d39","#5bbad6")) +
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),
legend.position = "right",
legend.direction = "vertical",
legend.title = element_text(size = 10),
legend.text = element_text(size = 10))
p
