3D-Scatter

Authors

[Editor] Hu Zheng;

[Contributors]

Modified

2026-01-17

Note

Hiplot website

This page is the tutorial for source code version of the Hiplot 3D-Scatter 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/scatter-3d?lang=en

3D scatter plot is to apply a number of quantitative variables to different coaxes in space and combine different variables into coordinates in space, so as to clearly explain the interaction between the three quantitative variables.

Setup

  • System Requirements: Cross-platform (Linux/MacOS/Windows)

  • Programming language: R

  • Dependent packages: data.table; jsonlite; plot3D; ggplotify

# Install packages
if (!requireNamespace("data.table", quietly = TRUE)) {
  install.packages("data.table")
}
if (!requireNamespace("jsonlite", quietly = TRUE)) {
  install.packages("jsonlite")
}
if (!requireNamespace("plot3D", quietly = TRUE)) {
  install.packages("plot3D")
}
if (!requireNamespace("ggplotify", quietly = TRUE)) {
  install.packages("ggplotify")
}

# Load packages
library(data.table)
library(jsonlite)
library(plot3D)
library(ggplotify)
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
 ggplotify  * 0.1.3   2025-09-20 [1] RSPM
 jsonlite   * 2.0.0   2025-03-27 [1] RSPM
 plot3D     * 1.4.2   2025-07-25 [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 are three variables and grouping.

# Load data
data <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/scatter-3d/data.json")$exampleData[[1]]$textarea[[1]])
data <- as.data.frame(data)

# Convert data structure
col_idx <- which(colnames(data) == "group")
data[, col_idx] <- as.factor(data[, col_idx])
shapes <- 19
shape_idx <- ""

# View data
head(data)
      temp    pressure dtime group
1 41.11057  0.49351190     1    G1
2 35.23429  0.76636476     2    G1
3 26.58407  0.63885937     3    G1
4 34.76097 -0.08106332     4    G1
5 25.76521 -0.31731579     5    G1
6 20.30115 -1.91132873     6    G1

Visualization

# 3D-Scatter
p <- as.ggplot(function() {
  plot3d <- scatter3D(data[, 1], data[, 2], data[, 3],
    pch = shapes, cex = 1,
    phi = 0, theta = 45, ticktype = "detailed",
    bty = "b2", colkey = FALSE, alpha = 1,
    xlab = colnames(data)[1], ylab = colnames(data)[2],
    zlab = colnames(data)[3],
    main = "3D-Scatter Plot",
    colvar = as.numeric(as.factor(data[, 4])),
    col = c("#e04d39","#5bbad6","#1e9f86")
  )
  
  legend("right", pch=19, legend = levels(data[, col_idx]),
         cex = 1.1, bty = 'n', xjust = 0.5, horiz = F,
         title = colnames(data)[col_idx],
         col = c("#e04d39","#5bbad6","#1e9f86"))
})

p
FigureΒ 1: 3D-Scatter

In the figure, temperature, pressure and time are respectively placed on x (horizontal axis), Y (vertical axis) and Z (perspective axis) to generate a THREE-DIMENSIONAL scatter plot, and the correlation between variables and their correlation degree can be intuitively found.