Matplotlib.axes.Axes.axvspan() in Python

Matplotlib is a library in Python and it is numerical - mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute. The Axes.axvspan() function in axes module of matplotlib library is used to add a vertical span (rectangle) across the axis.

Syntax:

Axes.axvspan(self, xmin, xmax, ymin=0, ymax=1, **kwargs)

Parameters: This method accept the following parameters that are described below:

• xmin: This parameter indicates the first X-axis coordinate of the vertical span rectangle in data units.
• xmax: This parameter indicates the second X-axis coordinate of the vertical span rectangle in data units.
• ymin: This parameter indicates the first Y-axis coordinate of the vertical span rectangle in relative Y-axis units .
• ymax: This parameter indicates the second Y-axis coordinate of the vertical span rectangle in relative Y-axis units.

Returns: This returns the vertical span (rectangle) from (xmin, ymin) to (xmax, ymax).

Below examples illustrate the matplotlib.axes.Axes.axhspan() function in matplotlib.axes: Example-1: Python3

# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np

fig, ax = plt.subplots()

ax.axvspan(1.5, 2.5, facecolor ='g', alpha = 0.7)

ax.set_title('matplotlib.axes.Axes.axvspan() Example')

plt.show()

Output: Example-2: Python3

# Implementation of matplotlib function
import numpy as np
import matplotlib.pyplot as plt

t = np.arange(-3, 4, .1)
s = np.sin(np.pi * t)

fig, ax = plt.subplots()
ax.plot(t, s, color ='black')
ax.axhline(y = 1, color ='black')
ax.axvline(x = 1, color ='black')
ax.axvline(x = 0, ymin = 0.75, linewidth = 8,
           color ='green')
ax.axhline(y =.5, xmin = 0.25, xmax = 0.75,
           color ='black')

ax.axhspan(0.25, 0.75, facecolor ='green', alpha = 0.7)
ax.axvspan(1.25, 1.55, facecolor ='0.5', alpha = 0.5)

ax.set_title('matplotlib.axes.Axes.axvspan() Example')

plt.show()

Output: