Getting Started with NumPy
NumPy basics — arrays, statistics and analyzing data with the numerical computing foundation of Python.
Python is the reference tool for scientific and engineering applications. NASA and SpaceX use it extensively. But native Python is slow for massive computations on numerical collections. NumPy solves this problem.
NumPy (Numerical Python) was created by Travis Oliphant in 2005, combining Python's pre-existing numerical libraries. It works in tandem with Matplotlib for visualization.
NumPy revolves around a central structure: the ndarray (n-dimensional array). An ndarray is a collection of numbers organized in a single, indexable, multidimensional variable.
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What's inside
7 sections- 1 Table of Contents
- 2 Why NumPy?
- 3 Module 1 — Understanding NumPy Basics
- 4 Module 2 — Working with NumPy Arrays
- 5 Module 3 — Statistics with NumPy
- 6 Module 4 — Analyzing Data with NumPy
- 7 Reference Tables
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