Python Tutorial

Matplotlib is a Python library that extends the NumPy library with numerical and mathematical functions. Pyplot is a state-based interface to a MATLAB-like Matplotlib module.

Ticks are data point symbols that appear on axes. Matplotlib's default tick locators and formatters are intended to be useful in a wide range of circumstances. Tick placements and labels can be explicitly specified to fit specific requirements.

A list object is passed as an argument to the xticks() and yticks() functions. The list components represent the points on the appropriate action where ticks will be displayed.

matplotlib.pyplot.xticks() Function

To acquire and set the current tick locations and labels of the x-axis, use the annotate() method of the matplotlib library's pyplot module.

Syntax:

The Parameters Used:

Ticks: This argument contains a list of xtick positions. and a parameter that is optional. If an empty list is supplied as an argument, all xticks are removed.
Labels: This parameter comprises labels that will be placed at the specified tick places. It is also an optional parameter.
**kwargs: This parameter controls the appearance of the labels using Text attributes.

Return Type:

The xticks() function in Matplotlib returns:

locs: The xtick location list.
labels: A collection of xlabel text items.

Examples

Show How to use the matplotlib.pyplot.xticks() Function in matplotlib.pyplot:

Example 1: Using matplotlib.pyplot.xticks.

Code:

import numpy as np
import matplotlib.pyplot as plt
x = [1, 2, 3, 4]
y = [95, 38, 54, 35]
labels = ['Geeks1', 'Geeks2', 'Geeks3', 'Geeks4']  
plt.plot(x, y)  
# The rotation of the tick can be specified.
# Labels might be in degrees or with keywords.
plt.xticks(x, labels, rotation ='vertical')  
# Pad margins to prevent markers from being clipped by the axes.
plt.margins(0.2) 
# Adjust the spacing to avoid tick-label clipping.
plt.subplots_adjust(bottom = 0.15)
plt.show()

Output:

Example 2:

Code:

import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import inset_axes, zoomed_inset_axes
def get_demo_image():
    from matplotlib.cbook import get_sample_data
    import numpy as np
    f = get_sample_data("axes_grid / bivariate_normal.npy", 
                        asfileobj = False)
    z = np.load(f) 
    # z is a numpy array of 15x15
    return z, (3, 19, 4, 13)
fig, ax = plt.subplots(figsize =[5, 4])
Z, extent = get_demo_image()
ax.set(aspect = 1,
       xlim =(0, 65),
       ylim =(0, 50))
axins = zoomed_inset_axes(ax, zoom = 2, 
                          loc ='upper right')
im = axins.imshow(Z, extent = extent, 
                  interpolation ="nearest",
                  origin ="upper")
plt.xlabel('X-axis') 
plt.ylabel('Y-axis') 
plt.xticks(visible = False)
plt.show()

Output:

Conclusion

Matplotlib is a Python library that extends the NumPy library with numerical and mathematical functions. Pyplot is a state-based interface to the Matplotlib module, which is similar to MATLAB.
Ticks are axes-based data point symbols. In all of our previous examples, Matplotlib has automatically taken over the job of spacing points on the axis. The default tick locators and formatters in Matplotlib are meant to be useful in a variety of situations.
Tick placements and labels can be explicitly specified to fit specific requirements. The xticks() and yticks() procedures use a list object as an argument. At the action points represented by the list components, ticks will be displayed.

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