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Matplotlib.artist.Artist.pickable() in Python

Last Updated : 12 Jul, 2025
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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: Python3 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: Python3 1==
# 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()
Output:

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