NumPy Basics

NumPy Basics#

Why Do I Need This?#

You’ve been using Python lists, and they work fine for small things. But try running Euler’s method with 10,000 timesteps:

# With lists: slow and painful
velocities = [0.0] * 10000
for i in range(1, 10000):
    velocities[i] = velocities[i-1] + 0.1 * some_formula

Now imagine doing this for a 2D grid with 1 million points. Lists will take forever.

NumPy arrays are built for this. They’re:

  • 10-100x faster than lists for numerical operations

  • Designed for mathematical formulas (no loops needed!)

  • The foundation of all scientific Python

If you’re solving differential equations, processing data, or doing any serious computation, you’ll use NumPy. It’s not optional.

What You’ll Learn#

Creating Arrays#

How to make arrays of zeros, evenly-spaced grids, and 2D matrices. These are the building blocks for every numerical method.

Array Operations#

The superpower: doing math on entire arrays at once. Write formulas that apply to thousands of values without a single loop.

Useful Functions#

A reference for common tasks: checking array shape, reshaping, random numbers, sorting, searching, and more.

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