Composing Custom Legends in Python Matplotlib

Introduction

The Python Matplotlib library provides a flexible way to create and customize legends in a plot. Legends are an essential component of any plot, as they provide a clear and concise explanation of the data represented in the plot. This lab will guide you through the process of composing custom legends using Matplotlib objects.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.

Plotting Lines

In this step, we will plot a set of lines using the Matplotlib library. First, we create some random data using NumPy. Next, we set the color cycle using the cycler function to specify the color map. Finally, we plot the data using the plot function and call legend() to generate the legend.

import matplotlib.pyplot as plt
import numpy as np

## Set random state for reproducibility
np.random.seed(19680801)

## Create random data
N = 10
data = (np.geomspace(1, 10, 100) + np.random.randn(N, 100)).T

## Set color cycle
cmap = plt.cm.coolwarm
plt.rcParams['axes.prop_cycle'] = cycler(color=cmap(np.linspace(0, 1, N)))

## Plot data and generate legend
fig, ax = plt.subplots()
lines = ax.plot(data)
ax.legend()

Composing Custom Legend

In this step, we will create a custom legend using Matplotlib objects. First, we import the Line2D class from the matplotlib.lines module. Next, we create a list of Line2D objects with custom color, width, and label attributes. Finally, we plot the data again using the plot function and call legend() with the custom lines and corresponding labels.

## Import Line2D class
from matplotlib.lines import Line2D

## Create custom lines
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)]

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

Composing Custom Legend with Different Matplotlib Objects

In this step, we will create a custom legend using different Matplotlib objects, including Line2D and Patch. First, we import the Patch class from the matplotlib.patches module. Next, we create a list of Line2D and Patch objects with custom attributes. Finally, we call legend() with the custom objects and corresponding labels.

## Import Line2D and Patch classes
from matplotlib.lines import Line2D
from matplotlib.patches import Patch

## Create legend elements
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')]

## Plot data and generate custom legend
fig, ax = plt.subplots()
ax.legend(handles=legend_elements, loc='center')

Summary

In this lab, we learned how to create custom legends using Matplotlib objects. We started by plotting a set of lines and generating a default legend. Next, we composed a custom legend using Line2D objects with custom attributes. Finally, we created a custom legend using different Matplotlib objects, including Line2D and Patch. By using custom legends, we can provide a clear and concise explanation of the data represented in a plot.

Composing Custom Legends