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Updated Assessing marine restoration efforts PNRR MER WP4 — Economics & cost-effectiveness DOI 10.1038/s41586-020-2649-2

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Overview

A foundational paper describing NumPy, the core array-programming library that underpins scientific computing in Python.

Authors

Charles R. Harris
- Funding acquisition
- Formal analysis
- Investigation
- Methodology
K. Jarrod Millman 0000-0002-5263-5070
Stéfan J. van der Walt ★ 0000-0001-9276-1891

Funding

European Commission · Award 101059607

Abstract

Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It plays an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics.

Full description

NumPy provides the fundamental N-dimensional array object and numerical routines that underpin the wider Python scientific-computing ecosystem — SciPy, pandas, scikit-learn and many domain-specific libraries build on it. Published in Nature in 2020, this paper documents the library's design, capabilities and its role across research fields from astronomy to marine science.

Cite this paper

Open access

Harris, C. R., Millman, K. J., & van der Walt, S. J. (2020). Array programming with NumPy. Nature, 585(7825), 357-362. https://doi.org/10.1038/s41586-020-2649-2

Publisher: Springer Nature · CC-BY-NC-SA-4.0

Cited by: 22,058 · via OpenAlex

DOI: 10.1038/s41586-020-2649-2