Python Data Science Handbook, 2nd Edition

Chapter 30. Customizing Colorbars

Plot legends identify discrete labels of discrete points. For continuous labels based on the color of points, lines, or regions, a labeled colorbar can be a great tool. In Matplotlib, a colorbar is drawn as a separate axes that can provide a key for the meaning of colors in a plot. Because the book is printed in black and white, this chapter has an accompanying online supplement where you can view the figures in full color. We’ll start by setting up the notebook for plotting and importing the functions we will use:

In [1]: import matplotlib.pyplot as plt
        plt.style.use('seaborn-white')

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

As we have seen several times already, the simplest colorbar can be created with the plt.colorbar function (see Figure 30-1).

In [3]: x = np.linspace(0, 10, 1000)
        I = np.sin(x) * np.cos(x[:, np.newaxis])

        plt.imshow(I)
        plt.colorbar();

Note

Full-color figures are available in the supplemental materials on GitHub.

We’ll now discuss a few ideas for customizing these colorbars and using them effectively in various situations.

Figure 30-1. A simple colorbar legend

Customizing Colorbars

The colormap can be specified using the cmap argument to the plotting function that is creating the visualization (see Figure 30-2).

In [4]: plt.imshow(I, cmap='Blues');

Figure 30-2. A blue-scale colormap

The names of available colormaps ...