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

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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.update_units() Function

The Axis.update_units() function in axis module of matplotlib library is used to introspect data for units converter and update the axis.converter instance if necessary.

Syntax: Axis.update_units(self, data)

Parameters: This method accepts the following parameters.

data: This parameter is the data to be update.

Return value: This method return True if data is registered for unit conversion.

Below examples illustrate the matplotlib.axis.Axis.update_units() 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  
   
           
np.random.seed(10**7)  
zambiatek = np.random.randn(100)  
      
fig, ax = plt.subplots()  
ax.acorr(zambiatek, usevlines = True,  
         normed = True,  
         maxlags = 80, lw = 3)  
     
ax.grid(True)  
     
prop = {'xticks': np.array([-100., -50., 
                            0., 50., 100.]),  
        'yticks': np.array([-0.2,  0.2,  
                            0.6, 1., 1.4]),  
        'ylabel': None, 'xlabel': None}  
     
ax.update(prop)
 
w = Axis.update_units(ax.xaxis,[1,2,3,4,5])
print(w)
   
fig.suptitle("""matplotlib.axis.Axis.update_units()
function Example\n""", fontweight ="bold")  
     
plt.show()

Output:

False

Example 2

Python3

# Implementation of matplotlib function
from matplotlib.axis import Axis
import numpy as np   
import matplotlib.pyplot as plt   
     
     
xx = np.random.rand(16, 30)   
        
fig, ax = plt.subplots()   
        
m = ax.pcolor(xx)   
m.set_zorder(-20)
 
w = Axis.update_units(ax.xaxis,[1,2,3,4,5])
print(w)
   
fig.suptitle("""matplotlib.axis.Axis.update_units()
function Example\n""", fontweight ="bold")  
     
plt.show()