# Amazing interactive 3D scatter plots - R software and data visualization

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:

`install.packages(c("rgl", "car"))`

Note that, on Linux operating system, the **rgl** package can be installed as follow:

**sudo apt-get install r-cran-rgl**

Load the packages:

`library("car")`

# Prepare the data

We’ll use the *iris* data set in the following examples :

```
data(iris)
head(iris)
```

```
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

## Default plot

`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)
```

# Axes

## 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))
```

# Export images

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:

`rgl.postscript("plot.pdf",fmt="pdf")`

# See also

The function **Identify3d()**[ *car* package] allows to label points interactively with the mouse.

# Infos

This analysis has been performed using **R software** (ver. 3.1.2) and **car** (ver. 2.0-25)

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