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Matplotlib.axis.Axis.set_label() function in Python

  • Last Updated : 05 Jun, 2020

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. It is an amazing visualization library in Python for 2D plots of arrays and used for working with the broader SciPy stack.

Matplotlib.axis.Axis.set_label() Function

The Axis.set_label() function in axis module of matplotlib library is used to set the label that will be displayed in the legend. 
 

Syntax: Axis.set_label(self, s) 

Parameters: This method accepts the following parameters. 

  • s: This parameter is converted to a string by calling str.

Return value: This method return the picking behavior of the artist. 



Below examples illustrate the matplotlib.axis.Axis.set_label() function in matplotlib.axis:

Example 1:

Python3




# Implementation of matplotlib function
from matplotlib.axis import Axis
import matplotlib.pyplot as plt  
import numpy as np  
from matplotlib.collections import EllipseCollection  
       
x = np.arange(5)  
y = np.arange(7)  
X, Y = np.meshgrid(x**2, y**3)  
       
XY = np.column_stack((X.ravel(), Y.ravel()))  
       
fig, ax = plt.subplots()  
       
ec = EllipseCollection(5, 7, 5, units ='y',  
                       offsets = XY * 0.5,  
                       transOffset = ax.transData,  
                       cmap ="plasma")  
      
ec.set_array((X * Y + X * X).ravel())  
      
ax.add_collection(ec)  
ax.autoscale_view()  
      
ax.set_xlabel('X')  
ax.set_ylabel('y')  
      
cbar = plt.colorbar(ec)  
cbar.set_label('X + Y')    
  
fig.suptitle('matplotlib.axis.Axis.set_label() \
function Example\n', fontweight ="bold")  
    
plt.show() 

Output: 
 

Example 2:

Python3




# Implementation of matplotlib function
from matplotlib.axis import Axis
import matplotlib.pyplot as plt  
import numpy as np  
       
np.random.seed(19680801)  
       
n = 100000
x = np.random.standard_normal(n)  
y = 2 * np.random.standard_normal(n)  
z =[1, 2, 3, 4]  
       
fig, ax = plt.subplots()  
hb = ax.hexbin(x, y, 
               gridsize = 50
               bins ='log'
               cmap ='bone')    
      
cb = fig.colorbar(hb, ax = ax)  
cb.set_label('log')    
  
fig.suptitle('matplotlib.axis.Axis.set_label() \
function Example\n', fontweight ="bold")  
    
plt.show() 

Output: 
 

 

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