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Matplotlib.axes.Axes.set_xticks() in Python

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  • Last Updated : 19 Apr, 2020
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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:


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