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

  • Last Updated : 11 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.pickable() Function

The Axis.pickable() function in axis module of matplotlib library is used to return whether the artist is pickable or not. 
 

Syntax: Axis.pickable(self) 

Parameters: This method does not accept any parameters. 

Return value: This method return whether the artist is pickable. 



Below examples illustrate the matplotlib.axis.Axis.pickable() function in matplotlib.axis:
Example 1:

Python3




# Implementation of matplotlib function
from matplotlib.axis import Axis
import numpy as np  
np.random.seed(19680801)  
import matplotlib.pyplot as plt  
       
    
volume = np.random.rayleigh(27, size = 40)  
amount = np.random.poisson(10, size = 40)  
ranking = np.random.normal(size = 40)  
price = np.random.uniform(1, 10, size = 40)  
       
fig, ax = plt.subplots()  
       
scatter = ax.scatter(volume * 2, amount * 3,  
                     c = ranking * 3,   
                     s = 0.3*(price * 3)**2,  
                     vmin = -4, vmax = 4,   
                     cmap = "Spectral")  
      
legend1 = ax.legend(*scatter.legend_elements(num = 5),  
                    loc ="upper left",  
                    title ="Ranking")  
      
ax.add_artist(legend1)  
      
ax.text(60, 30, "Value return : "
        + str(Axis.pickable(ax)),   
        fontweight ="bold",   
        fontsize = 18)
  
fig.suptitle('matplotlib.axis.Axis.pickable() \
function Example\n', fontweight ="bold")  
    
plt.show() 

Output: 
 

Example 2:

Python3




# Implementation of matplotlib function
from matplotlib.axis import Axis
import numpy as np  
import matplotlib.pyplot as plt  
import matplotlib.cbook as cbook  
       
    
np.random.seed(10**7)  
data = np.random.lognormal(size =(10, 4),  
                           mean = 4.5,  
                           sigma = 4.75)  
      
labels = ['G1', 'G2', 'G3', 'G4']  
       
result = cbook.boxplot_stats(data,   
                             labels = labels,   
                             bootstrap = 1000)  
       
for n in range(len(result)):  
    result[n]['med'] = np.median(data)  
    result[n]['mean'] *= 0.1
      
fig, axes1 = plt.subplots()  
axes1.bxp(result)  
      
axes1.text(2, 30000,  
           "Value return : " 
           + str(Axis.pickable(axes1)),   
           fontweight ="bold")  
  
fig.suptitle('matplotlib.axis.Axis.pickable() \
function Example\n', fontweight ="bold")  
    
plt.show() 

Output: 
 

 

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