Python Data Science Handbook, 2nd Edition

Chapter 35. Three-Dimensional Plotting in Matplotlib

Matplotlib was initially designed with only two-dimensional plotting in mind. Around the time of the 1.0 release, some three-dimensional plotting utilities were built on top of Matplotlib’s two-dimensional display, and the result is a convenient (if somewhat limited) set of tools for three-dimensional data visualization. Three-dimensional plots are enabled by importing the mplot3d toolkit, included with the main Matplotlib installation:

In [1]: from mpl_toolkits import mplot3d

Once this submodule is imported, a three-dimensional axes can be created by passing the keyword projection='3d' to any of the normal axes creation routines, as shown here (see Figure 35-1).

In [2]: %matplotlib inline
        import numpy as np
        import matplotlib.pyplot as plt

In [3]: fig = plt.figure()
        ax = plt.axes(projection='3d')

With this three-dimensional axes enabled, we can now plot a variety of three-dimensional plot types. Three-dimensional plotting is one of the functionalities that benefits immensely from viewing figures interactively rather than statically, in the notebook; recall that to use interactive figures, you can use %matplotlib notebook rather than %matplotlib inline when running this code.

Figure 35-1. An empty three-dimensional axes

Three-Dimensional Points and Lines

The most basic three-dimensional plot is a line or collection of scatter ...