Matplotlib.axis.Tick.pickable() function in Python
Last Updated :
10 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.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
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
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:
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