plt.subplot vs plt.subplots

Understanding the difference between plt.subplot (singular) and plt.subplots (plural) is essential for effective Matplotlib usage.

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plt.subplot (MATLAB Style)

plt.subplot creates a single subplot in a grid layout:

import matplotlib.pyplot as plt

plt.subplot(2, 2, 1)  # Create the first subplot in a 2x2 grid
plt.plot([1, 2, 3, 4])

plt.subplot(2, 2, 2)  # Create the second subplot
plt.plot([4, 3, 2, 1])

plt.subplot(2, 2, 3)  # Create the third subplot
plt.plot([1, 1, 1, 1])

plt.subplot(2, 2, 4)  # Create the fourth subplot
plt.plot([1, 2, 1, 2])

plt.show()

Syntax: plt.subplot(nrows, ncols, index)

• Index starts at 1 (not 0)
• Counts left-to-right, top-to-bottom

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plt.subplots (OOP Style)

plt.subplots creates a Figure and all Axes objects at once:

import matplotlib.pyplot as plt

fig, axes = plt.subplots(2, 2, figsize=(4, 4))

axes[0, 0].plot([1, 2, 3, 4])
axes[0, 1].plot([4, 3, 2, 1])
axes[1, 0].plot([1, 1, 1, 1])
axes[1, 1].plot([1, 2, 1, 2])

plt.show()

print(type(axes))   # numpy.ndarray
print(axes.shape)   # (2, 2)
print(axes.dtype)   # object

Returns: A Figure object and a NumPy array of Axes objects.

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Unpacking Axes

You can unpack the axes array for cleaner code:

import matplotlib.pyplot as plt

fig, ((ax0, ax1), (ax2, ax3)) = plt.subplots(2, 2, figsize=(4, 4))

ax0.plot([1, 2, 3, 4])
ax1.plot([4, 3, 2, 1])
ax2.plot([1, 1, 1, 1])
ax3.plot([1, 2, 1, 2])

plt.show()

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Axes Shape Behavior

The returned axes array shape depends on the grid dimensions:

# Single axes returns an Axes object, not an array
fig, ax = plt.subplots()
print(type(ax))  # AxesSubplot

# 1xN or Nx1 returns a 1D array
fig, axes = plt.subplots(1, 3)
print(axes.shape)  # (3,)

# NxM returns a 2D array
fig, axes = plt.subplots(2, 3)
print(axes.shape)  # (2, 3)

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The squeeze Keyword

Use squeeze=False to always get a 2D array:

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0.001, 1, 100)

# Without squeeze=False: shape is (3,)
fig, axs = plt.subplots(1, 3, figsize=(12, 3))
axs[0].plot(x, x**2)
axs[1].plot(x, np.sin(x))
axs[2].plot(x, np.exp(x))

# With squeeze=False: shape is (1, 3)
fig, axs = plt.subplots(1, 3, figsize=(12, 3), squeeze=False)
axs[0, 0].plot(x, x**2)
axs[0, 1].plot(x, np.sin(x))
axs[0, 2].plot(x, np.exp(x))

plt.tight_layout()
plt.show()

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Comparison Summary

Feature	plt.subplot	plt.subplots
Style	MATLAB	OOP
Returns	Axes	(Figure, Axes array)
Index starts at	1	0
Creates	One axes at a time	All axes at once
Flexibility	Limited	High

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Key Takeaways

• plt.subplot: singular, MATLAB style, 1-based indexing
• plt.subplots: plural, OOP style, returns Figure and Axes array
• Use plt.subplots for new code
• Use squeeze=False for consistent array shapes