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 from matplotlib.axis import Tick import numpy as np np.random.seed( 19680801 ) import matplotlib.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 from matplotlib.axis import Tick 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 ) 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: