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.Axis.set_label_position() Function
The Axis.set_label_position() function in axis module of matplotlib library is used to set the label position.
Syntax: Axis.set_label_position(self, position)
Parameters: This method accepts the following parameters.
- position: This parameter is the position of label {‘top’, ‘bottom’,’left’,’right’}.
Return value: This method does not returns any value.
Below examples illustrate the matplotlib.axis.Axis.set_label_position() function in matplotlib.axis:
Example 1:
# Implementation of matplotlib function from matplotlib.axis import Axis
import numpy as np
import matplotlib.pyplot as plt
fig, ax2 = plt.subplots(sharex = True )
fig.subplots_adjust(left = 0.2 , wspace = 0.6 )
box = dict (facecolor = 'green' , pad = 5 , alpha = 0.2 )
ax2.plot( 20 * np.random.rand( 10 ))
ax2.set_xlabel( 'X - Label' , bbox = box)
ax2.set_xlim( 0 , 10 )
ax2.xaxis.set_label_position( "top" )
fig.suptitle("Matplotlib.axis.Axis.set_label_position()\ Function Example", fontsize = 12 , fontweight = 'bold' )
plt.show() |
Output:
Example 2:
# Implementation of matplotlib function from matplotlib.axis import Axis
import numpy as np
import matplotlib.pyplot as plt
fig, (ax1, ax2) = plt.subplots( 2 , 1 , sharex = True )
fig.subplots_adjust(left = 0.2 , wspace = 0.6 )
box = dict (facecolor = 'green' , pad = 5 , alpha = 0.2 )
np.random.seed( 19680801 )
ax1.plot( 2 * np.random.rand( 10 ))
ax1.set_title( 'Label is not aligned' )
ax1.set_ylabel( 'Default' , bbox = box)
ax1.set_ylim( 0 , 20 )
ax2.set_title( '\nLabel is aligned' )
ax2.plot( 20 * np.random.rand( 10 ))
ax2.set_ylabel( 'Adjusted' , bbox = box)
ax2.set_ylim( 0 , 20 )
ax2.yaxis.set_label_position( "right" )
fig.suptitle("Matplotlib.axis.Axis.set_label_position()\ Function Example", fontsize = 12 , fontweight = 'bold' )
plt.show() |
Output: