3D Scatter Plotting in Python using Matplotlib

A 3D Scatter Plot is a mathematical diagram that visualizes data points in three dimensions, allowing us to observe relationships between three variables of a dataset. Matplotlib provides a built-in toolkit called mplot3d, which enables three-dimensional plotting. To create a 3D Scatter Plot, we use the ax.scatter3D() function from Matplotlib's mplot3d module. This function requires three sets of values—X, Y, and Z coordinates—to define the position of each point in the 3D space. Example:

The following example demonstrates how to create a simple 3D scatter plot using ax.scatter3D().

Output:

Explanation: In this example, we generate three sets of random data and use scatter3D() to visualize them in a 3D space. The points are marked in red with circular markers.

Installation and setup

Before proceeding, ensure you have Matplotlib installed. If not, install it using:

pip install matplotlib

Now, let's explore various examples to understand how 3D scatter plots work.

Example 1: 3D Scatter Plot with Color Mapping

To enhance visualization, we can use color mapping based on the Z-values of the data points.

Output:

Explanation: In this example, colors of the points are assigned based on the Z-values using the viridis colormap, making it easier to interpret variations in the dataset.

Example 2: 3D Scatter Plot with Different Markers and Sizes

To improve visualization, we can use different markers and vary the size of the points based on another dataset.

Output:

Explanation: Here, we adjust marker sizes randomly to improve visualization and use the coolwarm colormap to enhance the color distribution.

Example 3: Customization and additional features

This example demonstrates how to create a 3D surface plot using matplotlib and numpy while incorporating customization options to enhance visualization. The code plots a 3D function and applies various modifications, such as adjusting the viewing angle, enabling the grid and changing the background color.

Output:

Explanation: This code creates a 3D surface plot using Matplotlib. It generates X, Y coordinates using meshgrid. The surface is plotted with a viridis colormap. Customizations include adjusting the viewing angle, enabling the grid and changing the background color for better visualization.