notes.md

NumPy Notes

Hands-on array computing. Conceptual linear algebra: ../math/math.md. Runnable examples: study.py.

Official reference: NumPy module structure.

Contents

• Core idea
• Basics
• Types
• Array (ndarray)

Core idea

• NumPy’s main object is the homogeneous multidimensional array — many like-typed items in one block
• Dimensions of an array are called axes

Basics

• One axis can hold coordinates along one dimension
• Length of an axis = number of elements on that axis
  • Example: [6, 7, 8] has length 3

Types

• Element types can be specified (beyond plain Python scalars)
• Use NumPy dtypes such as numpy.float64, numpy.int16 for fixed-width numeric storage

Array (ndarray)

• ndarray (also exposed as array) is NumPy’s array class
• Build matrices (and higher-rank tensors) with chosen shapes and dtypes
• Creation helpers and indexing practice are in study.py