Matplotlib.axis.Axis.set_label_text() function in Python

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_text() Function

The Axis.set_label_text() function in axis module of matplotlib library is used to set the text value of the axis label.

Syntax: Axis.set_label_text(self, label, fontdict=None, **kwargs)

Parameters: This method accepts the following parameters. 

• label : This parameter is the Text string.
• fontdict : This parameter is the Text properties.

Return value: This method does not returns any value. 

Below examples illustrate the matplotlib.axis.Axis.set_label_text() 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.xaxis.set_label_text('X - Label', bbox=box)
ax2.set_xlim(0, 10)

fig.suptitle("Matplotlib.axis.Axis.set_label_text()\
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.yaxis.set_label_text('Default', bbox=box)
ax1.set_ylim(0, 20)

ax2.set_title('\nLabel is aligned')
ax2.plot(20*np.random.rand(10))
ax2.yaxis.set_label_text('Adjusted', bbox=box)
ax2.yaxis.set_label_position('right')
ax2.set_ylim(0, 20)

fig.suptitle("Matplotlib.axis.Axis.set_label_text()\
Function Example", fontsize = 12, fontweight ='bold')

plt.show()

Output: