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_xticks() Function
The Axes.set_xticks() function in axes module of matplotlib library is used to Set the x ticks with list of ticks.
Syntax: Axes.set_xticks(self, ticks, minor=False)
Parameters: This method accepts the following parameters.
- ticks : This parameter is the list of x-axis tick locations.
- minor : This parameter is used whether set major ticks or to set minor ticks
Return value: This method does not returns any value.
Below examples illustrate the matplotlib.axes.Axes.set_xticks() function in matplotlib.axes:
Example 1:
# Implementation of matplotlib function import numpy as np import matplotlib.pyplot as plt from matplotlib.patches import Polygon def func(x): return (x - 4 ) * (x - 6 ) * (x - 5 ) + 100 a, b = 2 , 9 # integral limits x = np.linspace( 0 , 10 ) y = func(x) fig, ax = plt.subplots() ax.plot(x, y, "k" , linewidth = 2 ) ax.set_ylim(bottom = 0 ) # Make the shaded region ix = np.linspace(a, b) iy = func(ix) verts = [(a, 0 ), * zip (ix, iy), (b, 0 )] poly = Polygon(verts, facecolor = 'green' , edgecolor = '0.5' , alpha = 0.4 ) ax.add_patch(poly) ax.text( 0.5 * (a + b), 30 , r "$\int_a ^ b f(x)\mathrm{d}x$" , horizontalalignment = 'center' , fontsize = 20 ) fig.text( 0.9 , 0.05 , '$x$' ) fig.text( 0.1 , 0.9 , '$y$' ) ax.spines[ 'right' ].set_visible( False ) ax.spines[ 'top' ].set_visible( False ) ax.set_xticks((a, b)) fig.suptitle('matplotlib.axes.Axes.set_xticks()\ function Example\n\n', fontweight = "bold" ) fig.canvas.draw() plt.show() |
Output:
Example 2:
# Implementation of matplotlib function import numpy as np import matplotlib.pyplot as plt # Fixing random state for reproducibility np.random.seed( 19680801 ) x = np.linspace( 0 , 2 * np.pi, 100 ) y = np.sin(x) y2 = y + 0.2 * np.random.normal(size = x.shape) fig, ax = plt.subplots() ax.plot(x, y) ax.plot(x, y2) ax.set_xticks([ 0 , np.pi, 2 * np.pi]) ax.spines[ 'left' ].set_bounds( - 1 , 1 ) ax.spines[ 'right' ].set_visible( False ) ax.spines[ 'top' ].set_visible( False ) fig.suptitle('matplotlib.axes.Axes.set_xticks() \ function Example\n\n', fontweight = "bold" ) fig.canvas.draw() plt.show() |
Output: