What is Matplotlib?

Matplotlib is the core plotting library in Python.

• Flexible and powerful
• Works everywhere (scripts, notebooks)
• Backbone for many libraries (including Seaborn)

Matplotlib was started by John Hunter in 2002 to bring a MATLAB-like plotting interface to Python. It can export charts to almost every common format — PNG, SVG, PDF, and more — which is why it’s still the default choice for publication-quality figures, even with newer libraries around.

How a plot gets built

  flowchart LR
  A["Your data"] --> B["Figure (the canvas)"]
  B --> C["Axes (one plotting area)"]
  C --> D["Artists (lines, bars, ticks, text)"]
  E["plt.plot() - quick pyplot API"] -.-> C
  F["fig, ax = plt.subplots() - OO API"] -.-> C

Two common ways to plot

1) Pyplot (quick)

import matplotlib.pyplot as plt
 
plt.plot([1, 2, 3], [3, 2, 5])
plt.title("Quick plot")
plt.show()

import matplotlib.pyplot as plt
 
plt.plot([1, 2, 3], [3, 2, 5])
plt.title("Quick plot")
plt.show()

2) Object-oriented API (recommended)

import matplotlib.pyplot as plt
 
fig, ax = plt.subplots(figsize=(7, 4))
ax.plot([1, 2, 3], [3, 2, 5])
ax.set_title("OO plot")
ax.set_xlabel("x")
ax.set_ylabel("y")
plt.show()

import matplotlib.pyplot as plt
 
fig, ax = plt.subplots(figsize=(7, 4))
ax.plot([1, 2, 3], [3, 2, 5])
ax.set_title("OO plot")
ax.set_xlabel("x")
ax.set_ylabel("y")
plt.show()

Key terms

• Figure: the whole canvas
• Axes: the plotting area
• Artist: everything drawn on the figure

In this phase, we’ll focus on practical charts you need for analytics.

Next

Continue to Anatomy of a Plot to see exactly how Figure, Axes, ticks, and labels fit together.

🧪 Try It Yourself

Exercise 1 – Object-oriented basics

Exercise 2 – Labelling an Axes

Exercise 3 – A grid of Axes