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.grid() Function
The Axis.grid() function in axis module of matplotlib library is used to Configure the grid lines.
Syntax: Axis.grid(self, b=None, which=’major’, **kwargs)
Parameters: This method accepts the following parameters.
- b : This parameter is an optional parameter, whether to show the grid lines or not.
- which : This parameter is also an optional parameter and it is the grid lines to apply the changes on.
Return value: This method does not return any value.
Below examples illustrate the matplotlib.axis.Axis.grid() function in matplotlib.axis:
Example 1:
Python3
# Implementation of matplotlib function from matplotlib.axis import Axis import matplotlib.pyplot as plt import numpy as np fig, ax = plt.subplots() ax.plot([1, 2, 3]) ax.xaxis.grid() fig.suptitle("Matplotlib.axis.Axis.grid()\ 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 x = np.arange(-5, 5, 0.01) y1 = -3 * x*x + 10 * x + 10y2 = 3 * x*x + x fig, [ax, ax1] = plt.subplots(2, 1, sharex = True) 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.xaxis.grid(True, color ="black") ax.set_title('\n Grid in X-axis', fontsize = 12, fontweight ='bold') ax1.plot(x, y1, x, y2, color ='black') ax1.fill_between(x, y1, y2, where = y2 >y1, facecolor ='green', alpha = 0.8) ax1.fill_between(x, y1, y2, where = y2 <= y1, facecolor ='black', alpha = 0.8) ax1.yaxis.grid(True, color ="black") ax1.set_title('Grid in y-axis', fontsize = 12, fontweight ='bold') fig.suptitle("Matplotlib.axis.Axis.grid()\ Function Example", fontsize = 12, fontweight ='bold') plt.show() |
Output:
