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.Tick.pickable() Function
The Tick.pickable() function in axis module of matplotlib library is used to return whether the artist is pickable or not. 
 
Syntax: Tick.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.Tick.pickable() function in matplotlib.axis:
Example 1:
Python3
| # Implementation of matplotlib function frommatplotlib.axis importTick importnumpy as np   np.random.seed(19680801)   importmatplotlib.pyplot as plt              volume =np.random.rayleigh(27, size =100)   amount =np.random.poisson(10, size =100)   ranking =np.random.normal(size =100)   price =np.random.uniform(1, 10, size =100)          fig, ax =plt.subplots()          scatter =ax.scatter(volume *2, amount *3,                        c =ranking **3,                         s =(price *5)**2,                        vmin =-4, vmax =4,                         cmap ="Spectral")            ax.text(60, 30, "Value return : "        +str(Tick.pickable(ax)),            fontweight ="bold",            fontsize =16)  fig.suptitle('matplotlib.axis.Tick.pickable() \ function Example', fontweight ="bold")       plt.show()   | 
Output: 
 
Example 2:
Python3
| # Implementation of matplotlib function frommatplotlib.axis importTick importnumpy as np   importmatplotlib.pyplot as plt   importmatplotlib.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)    fig, axes1 =plt.subplots()   axes1.bxp(result)         axes1.text(2, 30000,              "Value return : "           +str(Tick.pickable(axes1)),               fontweight ="bold")  fig.suptitle('matplotlib.axis.Tick.pickable() \ function Example', fontweight ="bold")       plt.show()   | 
Output: 
 

 
                                    








