How to append a single labeled tick to X-axis using matplotlib?

To append a single labeled tick to X-axis using matplotlib, you can use set_xticks() and set_xticklabels() methods to add a custom tick at any position on the axis.

Steps

• Set the figure size and adjust the padding between and around the subplots.

• Create x and y data points using numpy.

• Plot x and y data points using plot() method.

• Set xticks at a single point.

• Set the tick label for single tick point.

• To display the figure, use show() method.

Example

import numpy as np
import matplotlib.pyplot as plt

# Set the figure size
plt.rcParams["figure.figsize"] = [7.00, 3.50]
plt.rcParams["figure.autolayout"] = True

# Create x and y data points
x = np.linspace(-5, 5, 50)
y = np.sin(x)

# Plot x and y data points
fig, ax = plt.subplots(1, 1)
p = ax.plot(x, y)

# Set xticks at a point
ax.set_xticks([-1.075])

# Set xticklabels for the point
ax.set_xticklabels(["$\bf{It\ is -\!1.075\ label}$"])

# Display the plot
plt.show()

Output

It will produce the following output −

Adding Multiple Custom Ticks

You can also add multiple custom ticks by providing lists to both methods ?

import numpy as np
import matplotlib.pyplot as plt

# Create data
x = np.linspace(-5, 5, 50)
y = np.sin(x)

# Plot
fig, ax = plt.subplots(figsize=(8, 4))
ax.plot(x, y)

# Add multiple custom ticks
ax.set_xticks([-2, 0, 2])
ax.set_xticklabels(['Min Point', 'Zero', 'Max Point'])

plt.show()

Conclusion

Use set_xticks() to specify tick positions and set_xticklabels() to set custom labels. This technique is useful for highlighting specific points or adding meaningful labels to your plots.