Matplotlib.axes.Axes.set_frame_on() 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.

matplotlib.axes.Axes.set_frame_on() Function

The Axes.set_frame_on() function in axes module of matplotlib library is used to set whether the axes rectangle patch is drawn or not.

Syntax: Axes.set_axis_on(self)

Parameters: This method accept only one parameters.

b: This parameter contains a boolean value and it is used for drawing the axes rectangle patch.

Returns:This method does not returns anything.

Note: If True is used, it does not effect any thing.
Below examples illustrate the matplotlib.axes.Axes.set_frame_on() function in matplotlib.axes:

Example 1:

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

x = np.arange(-5, 5, 0.01)
y1 = -3 * x*x + 10 * x + 10
y2 = 3 * x*x + x

fig, ax = plt.subplots()
ax.plot(x, y1, x, y2, color ='black')
ax.fill_between(x, y1, y2, where = y2 >y1,
               facecolor ='green', alpha = 0.8)
ax.fill_between(x, y1, y2, where = y2 <= y1,
               facecolor ='black', alpha = 0.8)

ax.set_frame_on(False)
ax.set_title('matplotlib.axes.Axes.set_frame_on() Example')
plt.show()

Output:

Example 2:

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

x = np.arange(16)
y = np.sin(x / 3)

fig, ax = plt.subplots()

ax.step(x, y + 2, label ='pre (default)')
ax.plot(x, y + 2, 'o--', color ='black', alpha = 0.3)

ax.step(x, y + 1, where ='mid', label ='mid')
ax.plot(x, y + 1, 'o--', color ='black', alpha = 0.3)

ax.step(x, y, where ='post', label ='post')
ax.plot(x, y, 'o--', color ='black', alpha = 0.3)

ax.grid(axis ='x', color ='0.95')
ax.legend(title ='Parameter where:')
ax.set_frame_on(False)
ax.set_title('matplotlib.axes.Axes.set_frame_on() Example')
plt.show()

Output: