Python Plot Subplot: How to Create Multiple Plots Side by Side

When working with data visualization in Python using Matplotlib, creating multiple plots side by side can be a valuable tool for comparison and analysis. The `subplots` function is a powerful feature that allows you to create a figure with multiple subplots. In this article, we will explore how to use the `subplots` function to create multiple plots side by side in Python.

To start, you need to import the `matplotlib.pyplot` module, which provides functions for creating and customizing plots. Then, you can create a figure using the `figure` function and specify the size of the figure using the `figsize` argument. In this example, we will create a 10x10 inch figure.

Next, you need to create subplots using the `subplots` function. This function takes several arguments, including the number of rows (`nrows`) and columns (`ncols`) for the subplots, as well as options for sharing x- and y-axis scales. In this example, we will create a 2x2 grid of subplots.

Once you have created the subplots, you can customize each subplot individually by assigning it to an axes object using the `subplots` function. For example, you can plot data on each subplot using the `plot` function or create a histogram using the `hist` function.

Finally, you need to display the plots using the `show` function. This will launch an event loop and look for all currently active figures, which includes our subplots.

Here is some sample code that demonstrates how to create multiple plots side by side using the `subplots` function:

```

import matplotlib.pyplot as plt

fig = plt.figure(constrained_layout=True, figsize=(10, 10))

subplots = fig.subfigures(2, 2)

ax0 = subplots'0, 0'.subplots(2, 1)

ax1 = subplots'0, 1'.subplots(2, 1)

ax2 = subplots'1, 0'.subplots(2, 1)

ax3 = subplots'1, 1'.subplots(2, 1)

# Plot data on each subplot

ax0.plot('1, 2, 3')

ax1.plot('4, 5, 6')

ax2.plot('7, 8, 9')

ax3.plot('10, 11, 12')

plt.show()

```

This code creates a 2x2 grid of subplots and plots data on each subplot. The resulting plot will have four panels, each showing a different set of data.

In conclusion, the `subplots` function is a powerful tool for creating multiple plots side by side in Python using Matplotlib. By following these steps, you can create complex visualizations that allow you to compare and analyze different sets of data.

Python plot subplot