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# Matplotlib.axes.Axes.set_xticks() in Python

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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