Matplotlib.artist.Artist.pickable() in Python

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Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Artist class contains Abstract base class for objects that render into a FigureCanvas. All visible elements in a figure are subclasses of Artist.

matplotlib.artist.Artist.pickable() method

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

Syntax: Artist.pickable(self)

Parameters: This method does not accept any parameters.

Returns: This method return whether the artist is pickable.

Below examples illustrate the matplotlib.artist.Artist.pickable() function in matplotlib:

Example 1:

# Implementation of matplotlib function 
from matplotlib.artist import Artist 
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(Artist.pickable(ax)),   
        fontweight ="bold",   
        fontsize = 18)  
          
fig.suptitle('matplotlib.artist.Artist.pickable() function\ 
 Example', fontweight ="bold")  
  
plt.show() 

Output:

Example 2:

# Implementation of matplotlib function 
from matplotlib.artist import Artist 
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(Artist.pickable(axes1)),   
           fontweight ="bold")  
          
fig.suptitle('matplotlib.artist.Artist.pickable()\ 
 function Example', fontweight ="bold")  
  
plt.show() 