Subplots vs subplot in matplotlib: Key Differences and Usage

In matplotlib, subplot creates a single plot in a grid by specifying its position, while subplots creates a full grid of plots and returns figure and axes objects for easier management. subplots is more flexible for multiple plots, whereas subplot is simpler for adding one plot at a time.

Quick Comparison

Here is a quick side-by-side comparison of subplot and subplots in matplotlib.

Feature	subplot	subplots
Purpose	Create one plot in a grid	Create multiple plots in a grid at once
Return Value	Single Axes object	Figure and array of Axes objects
Syntax Complexity	Simpler for single plot	More flexible for multiple plots
Usage Style	Add plots one by one	Create all plots together
Best For	Quick single plot in grid	Multiple plots with shared settings
Axes Management	Manual	Automatic and easier

Key Differences

The subplot function is used to add a single plot to a figure by specifying the number of rows, columns, and the plot position. It returns one Axes object, which you can use to plot your data. This method is straightforward when you want to add plots one at a time.

On the other hand, subplots creates a full grid of plots in one call. It returns a Figure object and an array of Axes objects, which makes it easier to manage multiple plots together. This is especially useful when you want to customize or share properties across plots.

Using subplots is generally more modern and flexible. It supports features like shared axes and automatic layout adjustment, which subplot does not handle as smoothly. However, for very simple cases with just one plot, subplot can be quicker to write.

Code Comparison

Here is how you create a 2x2 grid of plots using subplot by adding each plot individually.

python

import matplotlib.pyplot as plt

plt.figure(figsize=(8,6))

plt.subplot(2, 2, 1)
plt.plot([1, 2, 3], [1, 4, 9])
plt.title('Plot 1')

plt.subplot(2, 2, 2)
plt.plot([1, 2, 3], [2, 3, 4])
plt.title('Plot 2')

plt.subplot(2, 2, 3)
plt.plot([1, 2, 3], [5, 6, 7])
plt.title('Plot 3')

plt.subplot(2, 2, 4)
plt.plot([1, 2, 3], [7, 8, 9])
plt.title('Plot 4')

plt.tight_layout()
plt.show()

Output

A 2x2 grid of four line plots with titles Plot 1, Plot 2, Plot 3, and Plot 4 arranged in order.

subplots Equivalent

Here is how to create the same 2x2 grid of plots using subplots with easier axes management.

python

import matplotlib.pyplot as plt

fig, axs = plt.subplots(2, 2, figsize=(8,6))

axs[0, 0].plot([1, 2, 3], [1, 4, 9])
axs[0, 0].set_title('Plot 1')

axs[0, 1].plot([1, 2, 3], [2, 3, 4])
axs[0, 1].set_title('Plot 2')

axs[1, 0].plot([1, 2, 3], [5, 6, 7])
axs[1, 0].set_title('Plot 3')

axs[1, 1].plot([1, 2, 3], [7, 8, 9])
axs[1, 1].set_title('Plot 4')

plt.tight_layout()
plt.show()

Output

A 2x2 grid of four line plots with titles Plot 1, Plot 2, Plot 3, and Plot 4 arranged in order.

When to Use Which

Choose subplot when you want to quickly add a single plot to a figure and don't need to manage multiple axes at once. It is simple and direct for small tasks.

Choose subplots when you plan to create multiple plots together, want easier control over all axes, or need features like shared axes and automatic layout. It is the better choice for organized and scalable plotting.

Key Takeaways

subplot creates one plot at a time by position in a grid.

subplots creates a full grid and returns figure and axes for easier control.

subplots is more flexible and preferred for multiple plots.

Use subplot for quick single plots, subplots for complex layouts.

subplots supports shared axes and better layout management.