🎨 Matplotlib Foundations: Figure, Axes & Axis

The Art Gallery Analogy 🖼️

Imagine you’re setting up an art gallery. Before you hang any paintings, you need:

1. A Wall → This is the Figure (the entire canvas)
2. Picture Frames → These are the Axes (where plots actually live)
3. Frame Rulers → These are the Axis (the numbered lines on edges)

Let’s explore each one!

1. The Figure Object 📋

What is a Figure?

Think of a Figure as a blank wall in your art gallery.

• It’s the entire window that holds everything
• You can’t paint directly on the wall—you need frames first!
• One wall can hold many picture frames

Simple Example

import matplotlib.pyplot as plt

# Create your "wall" (Figure)
fig = plt.figure()

# Set wall size (width, height in inches)
fig = plt.figure(figsize=(8, 6))

What Can You Do With a Figure?

Real Life Example 🏠

import matplotlib.pyplot as plt

# Create a wall (Figure)
fig = plt.figure(figsize=(6, 4))

# Wall is empty right now!
# We need frames (Axes) to draw on

plt.show()

Result: An empty window appears. It’s like walking into an empty gallery!

2. The Axes Object 🖼️

What is Axes?

Axes is the picture frame where your actual drawing lives.

• This is where you put your lines, bars, scatter points
• One Figure can have many Axes (like a wall with many frames)
• The “s” in Axes is NOT plural—it’s just the name!

The Magic Trick ✨

import matplotlib.pyplot as plt

# Create wall + frame together!
fig, ax = plt.subplots()

# Now draw on the frame
ax.plot([1, 2, 3], [1, 4, 9])
plt.show()

Multiple Frames on One Wall

Want 2 charts side by side? Easy!

import matplotlib.pyplot as plt

# 1 row, 2 columns of frames
fig, (ax1, ax2) = plt.subplots(1, 2)

ax1.plot([1, 2, 3], [1, 2, 3])
ax1.set_title("Line Going Up")

ax2.bar([1, 2, 3], [3, 1, 2])
ax2.set_title("Some Bars")

plt.show()

What Can Axes Do?

3. Figure vs Axes: The Big Difference 🎯

This confuses everyone! Let’s clear it up:

graph TD
    A[Figure = The Wall] --> B[Axes 1<br/>Picture Frame]
    A --> C[Axes 2<br/>Picture Frame]
    A --> D[Axes 3<br/>Picture Frame]
    B --> E[Your Plot Lives Here!]
    C --> F[Another Plot Here!]
    D --> G[And Another Here!]

Side-by-Side Comparison

The Golden Rule 🌟

Figure = Container (the wall)

Axes = Where you actually draw (the frame)

Visual Story

Imagine you want to show your friend 4 different charts:

import matplotlib.pyplot as plt

# One wall, 4 frames (2 rows × 2 cols)
fig, axes = plt.subplots(2, 2)

# axes is now a 2×2 grid!
axes[0, 0].plot([1, 2], [1, 2])
axes[0, 1].bar([1, 2], [2, 1])
axes[1, 0].scatter([1, 2], [2, 1])
axes[1, 1].pie([30, 70])

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

Result: 4 charts in one window—like hanging 4 paintings on one wall!

4. The Axis Object 📏

What is Axis?

Axis (no “e” at the end!) is the ruler on the edge of your frame.

• The X-axis runs left-to-right (horizontal)
• The Y-axis runs bottom-to-top (vertical)
• Each Axes has two Axis objects

Quick Picture

        Y-Axis (vertical ruler)
           ↑
           │
           │    [Your Plot]
           │
           └──────────────→ X-Axis (horizontal ruler)

Accessing Axis Objects

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.plot([1, 2, 3], [1, 4, 9])

# Get the rulers
x_axis = ax.xaxis
y_axis = ax.yaxis

# Change tick marks
ax.set_xticks([1, 2, 3])
ax.set_yticks([0, 5, 10])

plt.show()

Common Axis Tweaks

Example: Customizing Your Rulers

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.plot([1, 2, 3, 4], [10, 20, 15, 25])

# X-axis customization
ax.set_xlabel("Months")
ax.set_xticks([1, 2, 3, 4])
ax.set_xticklabels(['Jan', 'Feb', 'Mar', 'Apr'])

# Y-axis customization
ax.set_ylabel("Sales ($)")
ax.set_ylim(0, 30)

plt.show()

🎯 Putting It All Together

Here’s the complete picture:

graph TD
    F[FIGURE<br/>The Wall] --> A1[AXES 1<br/>Picture Frame]
    F --> A2[AXES 2<br/>Picture Frame]
    A1 --> X1[X-AXIS<br/>Bottom Ruler]
    A1 --> Y1[Y-AXIS<br/>Left Ruler]
    A1 --> P1[YOUR PLOT<br/>Lines & Dots]
    A2 --> X2[X-AXIS<br/>Bottom Ruler]
    A2 --> Y2[Y-AXIS<br/>Left Ruler]
    A2 --> P2[YOUR PLOT<br/>Bars & Pies]

The Complete Code Story

import matplotlib.pyplot as plt

# 1. Create Figure (the wall)
fig = plt.figure(figsize=(10, 4))

# 2. Add Axes (picture frames)
ax1 = fig.add_subplot(1, 2, 1)
ax2 = fig.add_subplot(1, 2, 2)

# 3. Draw on Axes
ax1.plot([1, 2, 3], [1, 4, 9])
ax2.bar(['A', 'B', 'C'], [5, 3, 7])

# 4. Customize Axis (rulers)
ax1.set_xlabel("X Values")
ax1.set_ylabel("Y Values")
ax2.set_xlabel("Categories")
ax2.set_ylabel("Counts")

# 5. Add titles
ax1.set_title("My Line Plot")
ax2.set_title("My Bar Chart")

plt.tight_layout()
plt.show()

🚀 Quick Reference

💡 Pro Tips

1. Use plt.subplots() — It creates Figure AND Axes together!
2. Remember: ax.plot() not fig.plot() — You draw on frames, not walls
3. tight_layout() — Prevents your frames from overlapping
4. Axes ≠ Axis — Axes is the frame, Axis is the ruler

🎉 You Did It!

Now you understand the three building blocks of every Matplotlib chart:

1. Figure — Your canvas (the wall)
2. Axes — Your drawing area (the frame)
3. Axis — Your measurement guides (the rulers)

Every chart you’ll ever make uses these three pieces. You’ve just unlocked the foundation of data visualization!

Happy plotting! 📊✨