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Matplotlib.axes.Axes.legend() in Python - GeeksforGeeks

Matplotlib.axes.Axes.legend() in Python

Last Updated : 12 Jul, 2025

Matplotlib

is a library in Python and it is numerical - mathematical extension for NumPy library. The

Axes Class

contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.

matplotlib.axes.Axes.legend() Function

The

Axes.legend() function

in axes module of matplotlib library is used to place a legend on the axes.

Syntax: Axes.legend(self, *args, **kwargs) Parameters: This method accepts the following parameters. Returns:This method returns the matplotlib.legend.Legend instance.

Below examples illustrate the matplotlib.axes.Axes.legend() function in matplotlib.axes:

Example 1: Python3
# Implementation of matplotlib function
import matplotlib.pyplot as plt

fig, ax = plt.subplots()

line1, = ax.plot([1, 2, 3],
                 label ="Line 1",
                 color ="black", 
                 linewidth = 4,
                 linestyle =':')

line2, = ax.plot([3, 2, 1], 
                 label ="Line 2",
                 color ="green", 
                 linewidth = 4)


first_legend = ax.legend(handles =[line1], 
                         loc ='upper center')

ax.add_artist(first_legend)

ax.legend(handles =[line2], loc ='lower center')

fig.suptitle('matplotlib.axes.Axes.legend() \
function Example\n', fontweight ="bold")

plt.show()
Output: Example 2: Python3
# Implementation of matplotlib function
import numpy as np
import matplotlib.pyplot as plt

np.random.seed(19680801)

fig, ax = plt.subplots()
for color in [ 'tab:green', 'tab:blue',
               'tab:orange']:
    n = 70
    x, y = np.random.rand(2, n)
    scale = 1000.0 * np.random.rand(n)
    ax.scatter(x, y, c = color, s = scale,
               label = color,
               alpha = 0.35)

ax.legend()
ax.grid(True)
fig.suptitle('matplotlib.axes.Axes.legend() function\
 Example\n', fontweight ="bold")

plt.show()
Output:

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