Python for Scientists, 9781009014809
Paperback
Unlock scientific Python: code, math, data, and efficient techniques.

Python for Scientists

  • Paperback

    304 pages

  • Release Date

    30 September 2023

Summary

Python for Scientists: Mastering Scientific Computing

The third edition of this practical introduction to Python has been thoroughly updated, with all code migrated to Jupyter notebooks.

The text starts with a detailed introduction to the basics of the Python language, without assuming any prior knowledge. Building upon each other, the most important Python packages for numerical math (NumPy), symbolic math (SymPy), and plotting (Matplotlib) are introduced, with brand new ch…

Book Details

ISBN-13:9781009014809
ISBN-10:1009014803
Author:John M. Stewart, Michael Mommert
Publisher:Cambridge University Press
Imprint:Cambridge University Press
Format:Paperback
Number of Pages:304
Edition:3rd
Release Date:30 September 2023
Weight:524g
Dimensions:243mm x 169mm x 16mm
What They're Saying

Critics Review

‘This volume provides an important update to the resources available to physicists and other scientists who manipulate quantitative data for one of their most common tasks: computation … The focus is on providing the practicing scientist a clear, concise guide to an important resource, and the author has chosen his topics appropriately. Both Python and this book deserve wide circulation.’ Computing Reviews‘I highly recommend this book as a practical guide to real-life scientific programming. The book is well written, interspersed with great humor, and is presented from the viewpoint of a researcher who wants others to avoid suffering the same pitfalls and mistakes that he experienced.’ The Leading Edge‘… this book is still an excellent starting point to put you on the tracks to master the language and enjoy the marvels of the latest version of Python.’ Adhemar Bultheel, European Mathematical Society (euro-math-soc.eu)‘The book is well written, and would be a very good choice for a course for scientists learning Python. It would also be an excellent choice for self-study. … Highly recommended.’ R. Bharath, Choice

About The Author

John M. Stewart

John M. Stewart was Emeritus Reader in Gravitational Physics at the University of Cambridge, and a Life Fellow at King’s College, Cambridge before his death in 2016. He was the author of ‘Non-equilibrium Relativistic Kinetic Theory (Springer, 1971) and ‘Advanced General Relativity’ (Cambridge, 1991), and he translated and edited Hans Stephani’s ‘General Relativity’ (Cambridge, 1990).

Michael Mommert is Assistant Professor for Computer Vision at the University of St. Gallen, Switzerland, where he combines computer vision and Earth observation to implement efficient learning methods for a wide range of use cases. Before, he was a Solar System Astronomer and actively wrote scientific open-source code for this community.

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