Getting Started with Matplotlib

Matplotlib is Python's most widely used plotting library. In this lesson, you'll learn how to import Matplotlib, understand its structure, and create your first plots.

Importing Matplotlib

The most common way to import Matplotlib is using the pyplot module with the alias plt:

The pyplot module provides a MATLAB-like interface for creating plots quickly. Let's break down what happened:

1. import matplotlib.pyplot as plt - Imports the plotting module
2. plt.plot(x, y) - Creates a line plot
3. plt.show() - Displays the plot

The Two Interfaces

Matplotlib offers two ways to create plots:

1. Pyplot Interface (Stateful)

Quick and simple, good for simple plots:

2. Object-Oriented Interface

More control, better for complex plots:

We'll primarily use the object-oriented approach in this course because:

• It's more explicit and readable
• It scales better for complex visualizations
• It's the recommended approach for production code

Understanding Figure Size

The figsize parameter controls the size of your plot in inches:

Basic Plot Elements

Every plot has several key elements:

Creating Multiple Plots

You can create multiple plots in one figure:

Saving Plots

To save your plot to a file, use savefig():

Practice: Your First Custom Plot

Key Takeaways

• Import Matplotlib with import matplotlib.pyplot as plt
• Use plt.subplots() to create figures and axes (object-oriented approach)
• Control figure size with figsize=(width, height) in inches
• Add titles with ax.set_title(), labels with ax.set_xlabel() and ax.set_ylabel()
• Add grids with ax.grid(True) and legends with ax.legend()
• Save plots with fig.savefig('filename.png', dpi=300)
• Always call plt.show() to display plots (or plt.tight_layout() before showing)

In the next lesson, we'll dive deeper into the Figure and Axes objects that form the core of Matplotlib.