Composing Custom Legends#

Composing custom legends piece-by-piece.

Note

For more information on creating and customizing legends, see the following pages:

Sometimes you don't want a legend that is explicitly tied to data that you have plotted. For example, say you have plotted 10 lines, but don't want a legend item to show up for each one. If you simply plot the lines and call ax.legend(), you will get the following:

import matplotlib.pyplot as plt
import numpy as np

import matplotlib as mpl
from matplotlib import cycler

# Fixing random state for reproducibility
np.random.seed(19680801)
N = 10
data = (np.geomspace(1, 10, 100) + np.random.randn(N, 100)).T
cmap = plt.cm.coolwarm
mpl.rcParams['axes.prop_cycle'] = cycler(color=cmap(np.linspace(0, 1, N)))

fig, ax = plt.subplots()
lines = ax.plot(data)
custom legends

Since the data does not have any labels, creating a legend requires us to define the icons and labels. In this case, we can compose a legend using Matplotlib objects that aren't explicitly tied to the data that was plotted. For example:

from matplotlib.lines import Line2D

custom_lines = [Line2D([0], [0], color=cmap(0.), lw=4),
                Line2D([0], [0], color=cmap(.5), lw=4),
                Line2D([0], [0], color=cmap(1.), lw=4)]

fig, ax = plt.subplots()
lines = ax.plot(data)
ax.legend(custom_lines, ['Cold', 'Medium', 'Hot'])
custom legends

There are many other Matplotlib objects that can be used in this way. In the code below we've listed a few common ones.

from matplotlib.lines import Line2D
from matplotlib.patches import Patch

legend_elements = [Line2D([0], [0], color='b', lw=4, label='Line'),
                   Line2D([0], [0], marker='o', color='w', label='Scatter',
                          markerfacecolor='g', markersize=15),
                   Patch(facecolor='orange', edgecolor='r',
                         label='Color Patch')]

# Create the figure
fig, ax = plt.subplots()
ax.legend(handles=legend_elements, loc='center')

plt.show()
custom legends

Total running time of the script: (0 minutes 1.658 seconds)

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