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Learning Scientific Programming with Python

Learning Scientific Programming with Python

by Christian Hill (Author)

  • Used

    Paperback 2016

    $3.52
Synopsis

Learn to master basic programming tasks from scratch with real-life scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to quickly gain proficiency. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving onto the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualisation, this textbook also discusses the use of IPython notebooks to build rich-media, shareable documents for scientific analysis. Including a final chapter introducing challenging topics such as floating-point precision and algorithm stability, and with extensive online resources to support advanced study, this textbook represents a targeted package for students requiring a solid foundation in Python programming.

$3.52

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More Information

Format: Paperback
 Pages: 460
 Publisher: Cambridge University Press
Published: 29 Mar 2016
ISBN 10: 110742822X
ISBN 13: 9781107428225

Media Reviews
'This book is well illustrated and is supported by an extensive collection of resources online in the book's website, scipython.com. This site has code listings and solutions to exercises. I would readily recommend this book to any student (or even a colleague) who wishes to achieve a solid foundation in Python programming.' Vasudevan Lakshminarayanan, Contemporary Physics
Author Bio
Christian Hill is a physicist and physical chemist at University College London and the University of Oxford. He has over twenty years' experience of programming in the physical sciences and has been programming in Python for ten years. His research uses Python to produce, analyse, process, curate and visualise large data sets for the prediction of the properties of planetary atmospheres.