Fig, ax = plt.subplots pattern in Matplotlib

Introduction

This pattern helps you create a figure and one or more plots (axes) in a clear and organized way.

When you want to draw one or more charts in a single window.

When you need to control the size or layout of your plots.

When you want to customize each plot separately.

When you want to save or show the whole figure with all plots.

When you want to add titles, labels, or legends to your plots.

Syntax

Matplotlib

fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(width, height))

fig is the whole figure or window that holds your plots.

ax is the plot area where you draw your data.

Examples

Create one plot with default size.

Matplotlib

fig, ax = plt.subplots()

Create one plot with width 8 inches and height 6 inches.

Matplotlib

fig, ax = plt.subplots(figsize=(8, 6))

Create a 2 by 2 grid of plots. axs is a 2D array of axes.

Matplotlib

fig, axs = plt.subplots(2, 2)

Create 3 plots stacked vertically with a tall figure size.

Matplotlib

fig, ax = plt.subplots(nrows=3, ncols=1, figsize=(5, 10))

Sample Program

This code creates a figure with one plot. It draws a line connecting points (1,4), (2,5), and (3,6). Then it adds a title and labels for the axes. Finally, it shows the plot window.

Matplotlib

import matplotlib.pyplot as plt

# Create a figure and one plot
fig, ax = plt.subplots(figsize=(6, 4))

# Draw a simple line
ax.plot([1, 2, 3], [4, 5, 6])

# Add title and labels
ax.set_title('Simple Line Plot')
ax.set_xlabel('X axis')
ax.set_ylabel('Y axis')

# Show the plot
plt.show()

Important Notes

If you create multiple plots, ax becomes an array or matrix of axes objects.

You can use fig to adjust the whole figure, like saving it or changing layout.

Always call plt.show() to display your plots when running scripts.

Summary

The fig, ax = plt.subplots() pattern creates a figure and plot(s) together.

fig is the container; ax is where you draw your data.

This pattern helps organize and customize your charts easily.