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.secondary_xaxis() function in axes module of matplotlib library is also used to add a second x-axis to this axes.
Syntax: Axes.secondary_xaxis(self, location, *, functions=None, **kwargs)
Parameters: This method accept the following parameters that are described below:
- location : This parameter is the position to put the secondary axis.
- functions : This parameter is used to specify the transform function and its inverse.
Returns: This method returns the following:
- ax : This return the axes._secondary_axes.SecondaryAxis.
Note: This function works in Matplotlib version >= 3.1
Below examples illustrate the matplotlib.axes.Axes.secondary_xaxis() function in matplotlib.axes:
Example 1:
Python3
# Implementation of matplotlib functionimport matplotlib.pyplot as pltimport numpy as np fig, ax = plt.subplots()ax.plot([1, 2, 3])ax.set_xlabel('X-Axis')ax.set_ylabel('Y-Axis')secax = ax.secondary_xaxis('top')secax.set_xlabel('Secondary-X-Axis')ax.set_title('matplotlib.axes.Axes.secondary_xaxis() Example', fontsize = 14, fontweight ='bold')plt.show() |
Output:
Example 2:
Python3
# Implementation of matplotlib functionimport matplotlib.pyplot as pltimport numpy as npimport datetimeimport matplotlib.dates as mdatesfrom matplotlib.transforms import Transformfrom matplotlib.ticker import ( AutoLocator, AutoMinorLocator)fig, ax = plt.subplots(constrained_layout = True)x = np.arange(0, 500, 2)y = np.sin(3 * x * np.pi / 180)ax.plot(x, y)ax.set_xlabel('Degree')ax.set_ylabel('Frequency')def val1(x): return x * np.pi / 180def val2(x): return x * 180 / np.pisecax = ax.secondary_xaxis('top', functions =(val1, val2))secax.set_xlabel('Radian')ax.set_title('matplotlib.axes.Axes.secondary_xaxis() Example', fontsize = 14, fontweight ='bold')plt.show() |
Output:
