Matplotlib.axes.Axes.set_xticks() in Python

Last Updated : 19 Apr, 2020

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() 