Understanding Figure and Axes

The Figure and Axes are the two most important objects in Matplotlib. Understanding them is key to creating any visualization.

The Hierarchy

Matplotlib organizes plots in a hierarchy:

Figure (the overall window/canvas)
└── Axes (an individual plot/chart)
    ├── XAxis (the x-axis)
    ├── YAxis (the y-axis)
    ├── Title
    ├── Lines, Bars, etc. (the actual data)
    └── Legend, Grid, etc.

Creating Figures and Axes

There are several ways to create figures and axes:

Method 1: plt.subplots() (Recommended)

Method 2: plt.figure() + add_subplot()

Figure Properties

The Figure object controls the overall appearance:

Axes Properties

Each Axes object has many customizable properties:

Working with Multiple Axes

Grid of Subplots

Shared Axes

Adjusting Spacing

Practice: Create a Multi-Panel Figure

Key Takeaways

• Figure is the overall container (like a canvas or window)
• Axes is an individual plot within the figure
• Use plt.subplots(rows, cols) to create figures with multiple axes
• Access axes in a grid using axes[row, col] indexing
• Customize figures with figsize, facecolor, dpi
• Customize axes with set_title(), set_xlabel(), set_xlim(), set_xticks()
• Use sharex=True or sharey=True for linked axes
• Use plt.tight_layout() for automatic spacing

In the next lesson, we'll explore the basic plotting commands you'll use most often.