NumPy
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Introduction
NumPy is the fundamental package for scientific computing with Python, offering powerful N-dimensional arrays and numerical computing tools.
Listed on
July 22, 2026
What is NumPy?
NumPy is an open-source Python library that provides powerful N-dimensional array objects, along with comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. It is the de-facto standard for array computing in Python and forms the basis of many data science and machine learning libraries. NumPy is fast, versatile, and interoperable with a wide range of hardware and computing platforms.
How to use NumPy?
- To use NumPy, install it via pip or conda, then import it in your Python code with 'import numpy as np'. You can create arrays, perform vectorized operations, and leverage its mathematical functions. The official documentation and tutorials provide extensive guidance, and an interactive shell on the website allows trying examples in the browser.
Core features of NumPy
- Powerful N-dimensional arrays
- Fast vectorization, indexing, and broadcasting
- Comprehensive mathematical functions
- Random number generators
- Linear algebra routines
- Fourier transforms
- Interoperable with distributed, GPU, and sparse array libraries
- Open source under BSD license
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