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_coords() Function
The Axis.set_label_coords() function in axis module of matplotlib library is used to set the coordinates of the label.
Syntax: Axis.set_label_coords(self, x, y, transform=None)
Parameters: This method accepts the following parameters.
- x,y: These parameter are the coordinates of the label.
Return value: This method does not returns any value.
Below examples illustrate the matplotlib.axis.Axis.set_label_coords() function in matplotlib.axis:
Example 1:
Python3
# 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 ) Axis.set_label_coords(ax2.xaxis, 0.5 , 0.95 ) fig.suptitle("Matplotlib.axis.Axis.set_label_coords()\ Function Example", fontsize = 12 , fontweight = 'bold' ) plt.show() |
Output:
Example 2:
Python3
# 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 ) Axis.set_label_coords(ax2.yaxis, 1.1 , 0.5 ) fig.suptitle("Matplotlib.axis.Axis.set_label_coords()\ Function Example", fontsize = 12 , fontweight = 'bold' ) plt.show() |
Output: