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.
- labels : This parameter is the list of labels to show next to the artists.
- handles : This parameter is the list of Artists (lines, patches) to be added to the legend.
Returns:This method returns the matplotlib.legend.Legend instance.
Below examples illustrate the matplotlib.axes.Axes.legend() function in matplotlib.axes:
Example 1:
# 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:
# 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:
Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.
To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.