Figure and Axes Objects

What are Figure and Axes?

Figure = The whole image (like a canvas)
Axes = One chart inside the figure

Think of it like:

Figure = A piece of paper
Axes = A drawing on that paper

Simple Way (plt)

code.py

import matplotlib.pyplot as plt

plt.plot([1, 2, 3], [1, 4, 9])
plt.show()

This works but gives less control.

Better Way (fig, ax)

code.py

import matplotlib.pyplot as plt

# Create figure and axes
fig, ax = plt.subplots()

# Plot on the axes
ax.plot([1, 2, 3], [1, 4, 9])

plt.show()

This gives you more control!

Why Use fig, ax?

code.py

fig, ax = plt.subplots()

# Add title to axes
ax.set_title('My Chart')

# Add labels
ax.set_xlabel('X Axis')
ax.set_ylabel('Y Axis')

# Plot data
ax.plot([1, 2, 3], [1, 4, 9])

plt.show()

Set Figure Size

code.py

# figsize = (width, height) in inches
fig, ax = plt.subplots(figsize=(10, 6))

ax.plot([1, 2, 3], [1, 4, 9])
plt.show()

Multiple Charts in One Figure

code.py

# 1 row, 2 columns = 2 charts side by side
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 5))

# First chart
ax1.plot([1, 2, 3], [1, 4, 9])
ax1.set_title('Chart 1')

# Second chart
ax2.bar(['A', 'B', 'C'], [10, 20, 15])
ax2.set_title('Chart 2')

plt.show()

Grid of Charts

code.py

# 2 rows, 2 columns = 4 charts
fig, axes = plt.subplots(2, 2, figsize=(10, 8))

# Access each chart
axes[0, 0].plot([1, 2, 3], [1, 4, 9])
axes[0, 1].bar(['A', 'B'], [5, 10])
axes[1, 0].scatter([1, 2, 3], [3, 2, 1])
axes[1, 1].plot([1, 2, 3], [9, 4, 1])

plt.tight_layout()  # Prevent overlap
plt.show()

Key Methods

plt style	ax style
plt.title()	ax.set_title()
plt.xlabel()	ax.set_xlabel()
plt.ylabel()	ax.set_ylabel()
plt.xlim()	ax.set_xlim()
plt.ylim()	ax.set_ylim()

Recommended Pattern

code.py

import matplotlib.pyplot as plt

# Always start with this
fig, ax = plt.subplots(figsize=(8, 6))

# Create your chart
ax.plot(x, y)

# Customize
ax.set_title('Title')
ax.set_xlabel('X')
ax.set_ylabel('Y')

# Show or save
plt.show()

Key Points

Figure = whole image canvas
Axes = individual chart
fig, ax = plt.subplots() is the recommended way
Use figsize=(width, height) to set size
Multiple charts: plt.subplots(rows, cols)
plt.tight_layout() prevents overlapping

What's Next?

Learn to create line plots for showing trends over time.