Annotate Subplots in a Figure with A, B, C using Matplotlib

To annotate subplots in a figure with A, B, and C using Matplotlib, you can add text labels to each subplot using the text() method with appropriate positioning coordinates.

Steps to Annotate Subplots

• Set the figure size and adjust the padding between and around the subplots
• Create a figure and a set of subplots with nrows=1 and ncols=3
• Make a 1D iterator over the axes array using flat
• Iterate through each axes and display data as an image
• Use text() method to place letters A, B, and C on each subplot
• Display the figure using show() method

Example

Here's how to create three subplots with A, B, C annotations ?

import numpy as np
import matplotlib.pyplot as plt
import string

plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

fig, axs = plt.subplots(1, 3)
axs = axs.flat

for index, ax in enumerate(axs):
    ax.imshow(np.random.randn(4, 4), interpolation='nearest', cmap="copper")
    ax.text(0.45, 1.1, string.ascii_uppercase[index],
            transform=ax.transAxes,
            size=20, weight='bold')

plt.show()

Key Parameters

The text() method uses several important parameters ?

• Position (0.45, 1.1): x=0.45 centers horizontally, y=1.1 places above the subplot
• transform=ax.transAxes: Uses axes coordinates (0-1 range) instead of data coordinates
• string.ascii_uppercase[index]: Gets letters A, B, C automatically
• size=20, weight='bold': Makes the annotation prominent and readable

Alternative Positioning

You can position annotations in different locations ?

import numpy as np
import matplotlib.pyplot as plt
import string

fig, axs = plt.subplots(1, 3, figsize=(10, 4))
positions = [(0.05, 0.95), (0.05, 0.05), (0.95, 0.95)]  # Top-left, bottom-left, top-right

for index, ax in enumerate(axs):
    ax.imshow(np.random.randn(4, 4), interpolation='nearest', cmap="viridis")
    x, y = positions[index]
    ax.text(x, y, string.ascii_uppercase[index],
            transform=ax.transAxes,
            size=16, weight='bold',
            bbox=dict(boxstyle="round,pad=0.3", facecolor="white", alpha=0.8))

plt.tight_layout()
plt.show()

Output

Conclusion

Use ax.text() with transform=ax.transAxes for consistent positioning across subplots. The string.ascii_uppercase module provides an easy way to automatically generate sequential letters for annotation.