Anatomy of a Plot

Matplotlib anatomy

A typical plot has:

• Title
• X label / Y label
• Axes limits
• Ticks
• Legend (if multiple series)
• Grid (optional)

You can’t make a plot straight onto a blank Figure — a Figure is just the canvas. You always need at least one Axes (a plotting area) inside it before you can draw anything. Most of the customization methods you’ll use (set_title, set_xlim, set_xticks, …) live on that Axes object.

diagram The plot pipeline mermaid

  flowchart TD
  A["fig = plt.figure()"] --> B["ax = fig.add_subplot(...)"]
  B --> C["ax.plot(...) / ax.bar(...) / ..."]
  C --> D["ax.set_title() / set_xlabel() / set_ylabel()"]
  D --> E["ax.set_xlim() / set_xticks()"]
  E --> F["plt.show() or fig.savefig()"]

A Figure holds Axes; each Axes owns its own ticks, limits, labels, and plotted data.

The Figure + Axes model

Figure + Axes

import matplotlib.pyplot as plt
 
fig, ax = plt.subplots(figsize=(7, 4))
ax.plot([1, 2, 3, 4], [10, 6, 8, 4])
 
ax.set_title("Anatomy")
ax.set_xlabel("x")
ax.set_ylabel("y")
ax.grid(True, alpha=0.3)
 
plt.show()

Limits and ticks

Limits and ticks

import matplotlib.pyplot as plt
 
fig, ax = plt.subplots(figsize=(7, 4))
ax.plot([1, 2, 3, 4], [10, 6, 8, 4])
 
ax.set_xlim(0, 5)
ax.set_ylim(0, 12)
 
ax.set_xticks([1, 2, 3, 4])
ax.set_yticks([0, 4, 8, 12])
 
ax.set_title("Limits and ticks")
plt.tight_layout()
plt.show()

Visualize it

Every Matplotlib chart is built from the same nested parts: a Figure holds one or more Axes, and each Axes carries the title, the x/y labels, the ticks, and the plotted data. Here they are, labelled:

sketch The parts of a Matplotlib figure p5.js Pause Restart

A Figure holds one or more Axes; each Axes has a title, x/y labels, ticks, and the plotted data.

Tip

Use the object-oriented approach for consistent, reusable plotting.

From the book

McKinney notes that xlim, xticks, and similar methods all follow the same pattern: called with no arguments they return the current value (ax.get_xlim()); called with an argument they set it (ax.set_xlim([0, 10])). Once you know that pattern, you already know most of the Axes API.

Next

Continue to Line Plot to put the Figure + Axes model to work on your first real chart.

🧪 Try It Yourself

Exercise 1 – Set and read the title

pch.exerciseTag pch.exerciseTitle

Exercise 2 – Custom x-axis limits

pch.exerciseTag pch.exerciseTitle

Exercise 3 – Custom tick labels

pch.exerciseTag pch.exerciseTitle