Module 2 Overview

Module 2 — Indexing, Slicing & Views

Welcome

Indexing is how you select data out of an array, and it’s where NumPy has the most surprises for people coming from Python lists — especially around whether what you get back is a view (shares memory with the original) or a copy (independent). Getting this wrong is one of the most common sources of silent bugs in real NumPy code, so this module slows down and builds careful intuition before moving on.

Learning goals

• Index and slice 1-D and multi-D arrays, including negative indices and steps
• Build and combine boolean masks to filter data
• Use fancy (integer-array) indexing
• Know exactly when an operation returns a view vs. a copy — and why it matters
• Use np.newaxis and ... (Ellipsis) to index higher-dimensional arrays

Setup — run this first.