Python:Matplotlib .xlim()

The .xlim() function in matplotlib.pyplot is used to get or set the x-axis limits of the current plot. It helps control the visible range of data on the x-axis, zoom in on specific sections, or maintain consistent axis ranges across multiple plots.

The primary use cases for .xlim() include:

• Focusing on a particular range of x-values.
• Maintaining consistent axis scaling between multiple plots.
• Preventing automatic resizing that hides important data.

Syntax

matplotlib.pyplot.xlim(*args, **kwargs)

Parameters:

The function accepts the following keyword arguments:

• left or xmin (float, optional): Lower limit of the x-axis.
• right or xmax (float, optional): Upper limit of the x-axis.
• emit (bool, default: True): Whether observers are notified of the axis limit change (default: True).
• auto (bool, default: True): If True, turns on automatic scaling.

Return value:

The .xlim() function returns a tuple (xmin, xmax) representing the current x-axis limits.

Example 1: Setting Custom X-Axis Limits

This example shows how to set specific x-axis limits using .xlim():

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 20, 100)
y = np.sin(x)

plt.plot(x, y, color='purple', linewidth=2)
plt.title('Sine Wave with Custom X Limits')
plt.xlabel('X')
plt.ylabel('sin(x)')

# Set x-axis limits
plt.xlim(0, 10)

plt.grid(True)
plt.show()

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The output generated by this code will be:

This code plots a sine wave from 0 to 20 on the x-axis, but the plt.xlim(0, 10) command restricts the visible range to data between x = 0 and x = 10. As a result, only the first half of the sine wave is displayed. The curve appears smooth and purple, with grid lines and labeled axes for clarity.

Example 2: Getting Current X-Axis Limits

Calling .xlim() without arguments retrieves the current x-axis limits:

import matplotlib.pyplot as plt

plt.plot([0, 1, 2, 3], [10, 20, 25, 30])
print(plt.xlim())  # Outputs current x-axis limits
plt.show()

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The output generated by this code will be:

In this case, the output is:

(np.float64(-0.15), np.float64(3.15))

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This indicates that Matplotlib automatically adds a small margin around the plotted points for better visualization. The .xlim() function can also be applied after plotting to dynamically adjust the x-axis limits, as demonstrated in Example 1.