Amazing interactive 3D scatter plots - R software and data visualization
- Install and load required packages
- Prepare the data
- The function scatter3d
- Basic 3D scatter plots
- Plot the points by groups
- Add text labels for the points
- Export images
- See also
I recently posted an article describing how to make easily a 3D scatter plot in R using the package scatterplot3d.
This R tutorial describes how to perform an interactive 3d graphics using R software and the function scatter3d from the package car.
The function scatter3d() uses the rgl package to draw and animate 3D scatter plots.
Install and load required packages
The packages rgl and car are required for this tutorial:
Note that, on Linux operating system, the rgl package can be installed as follow:
sudo apt-get install r-cran-rgl
Load the packages:
Prepare the data
We’ll use the iris data set in the following examples :
Sepal.Length Sepal.Width Petal.Length Petal.Width Species 1 5.1 3.5 1.4 0.2 setosa 2 4.9 3.0 1.4 0.2 setosa 3 4.7 3.2 1.3 0.2 setosa 4 4.6 3.1 1.5 0.2 setosa 5 5.0 3.6 1.4 0.2 setosa 6 5.4 3.9 1.7 0.4 setosa
sep.l <- iris$Sepal.Length sep.w <- iris$Sepal.Width pet.l <- iris$Petal.Length
iris data set gives the measurements of the variables sepal length and width, petal length and width, respectively, for 50 flowers from each of 3 species of iris. The species are Iris setosa, versicolor, and virginica.
The function scatter3d
The simplified formats are:
scatter3d(formula, data) scatter3d(x, y, z)
- x, y, z are respectively the coordinates of points to be plotted. The arguments y and z can be optional depending on the structure of x.
- formula: a model formula of form y ~ x + z. If you want to plot the points by groups, you can use y ~ x + z | g where g is a factor dividing the data into groups
- data: data frame within which to evaluate the formula
Basic 3D scatter plots
library(car) # 3D plot with the regression plane scatter3d(x = sep.l, y = pet.l, z = sep.w)
Note that, the plot can be manually rotated by holding down on the mouse or touchpad. It can be also zoomed using the scroll wheel on a mouse or pressing ctrl + using the touchpad on a PC or two fingers (up or down) on a mac.
Change point colors and remove the regression surface:
scatter3d(x = sep.l, y = pet.l, z = sep.w, point.col = "blue", surface=FALSE)
Plot the points by groups
scatter3d(x = sep.l, y = pet.l, z = sep.w, groups = iris$Species)
Remove the surfaces
- To remove the grids only, the argument grid = FALSE can be used as follow:
scatter3d(x = sep.l, y = pet.l, z = sep.w, groups = iris$Species, grid = FALSE)
Note that, the display of the surface(s) can be changed using the argument fit. Possible values for fit are “linear”, “quadratic”, “smooth” and “additive”
scatter3d(x = sep.l, y = pet.l, z = sep.w, groups = iris$Species, grid = FALSE, fit = "smooth")
- Remove surfaces. The argument surface = FALSE is used.
scatter3d(x = sep.l, y = pet.l, z = sep.w, groups = iris$Species, grid = FALSE, surface = FALSE)
Add concentration ellipsoids
scatter3d(x = sep.l, y = pet.l, z = sep.w, groups = iris$Species, surface=FALSE, ellipsoid = TRUE)
Remove the grids from the ellipsoids:
scatter3d(x = sep.l, y = pet.l, z = sep.w, groups = iris$Species, surface=FALSE, grid = FALSE, ellipsoid = TRUE)
Change point colors by groups
The argument surface.col is used. surface.col is a vector of colors for the regression planes.
For multi-group plots, the colors are used for the regression surfaces and for the points in the several groups.
scatter3d(x = sep.l, y = pet.l, z = sep.w, groups = iris$Species, surface=FALSE, grid = FALSE, ellipsoid = TRUE, surface.col = c("#999999", "#E69F00", "#56B4E9"))
Read more about colors in R: colors in R
It’s also possible to use color palettes from the RColorBrewer package:
library("RColorBrewer") colors <- brewer.pal(n=3, name="Dark2") scatter3d(x = sep.l, y = pet.l, z = sep.w, groups = iris$Species, surface=FALSE, grid = FALSE, ellipsoid = TRUE, surface.col = colors)
Change axis labels:
The arguments xlab, ylab and zlab are used:
scatter3d(x = sep.l, y = pet.l, z = sep.w, point.col = "blue", surface=FALSE, xlab = "Sepal Length (cm)", ylab = "Petal Length (cm)", zlab = "Sepal Width (cm)")
Remove axis scales
axis.scales = FALSE
scatter3d(x = sep.l, y = pet.l, z = sep.w, point.col = "blue", surface=FALSE, axis.scales = FALSE)
Change axis colors
By default, different colors are used for the 3 axes. The argument axis.col is used to specify colors for the 3 axes:
scatter3d(x = sep.l, y = pet.l, z = sep.w, groups = iris$Species, surface=FALSE, grid = FALSE, ellipsoid = TRUE, axis.col = c("black", "black", "black"))
Add text labels for the points
The arguments below are used:
- labels: text labels for the points, one for each point
- id.n: Number of relatively extreme points to identify automatically
scatter3d(x = sep.l, y = pet.l, z = sep.w, surface=FALSE, labels = rownames(iris), id.n=nrow(iris))
The plot can be saved as png or pdf.
- The function rgl.snapshot() is used to save the screenshot as png file:
rgl.snapshot(filename = "plot.png")
- The function rgl.postscript() is used to saves the screenshot to a file in ps, eps, tex, pdf, svg or pgf format:
The function Identify3d()[ car package] allows to label points interactively with the mouse.
This analysis has been performed using R software (ver. 3.1.2) and car (ver. 2.0-25)
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