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Python for Scientists
— —
John M. Stewart (University of Cambridge)
Python for Scientists by John M. Stewart (University of Cambridge) at Abbey's Bookshop,

Python for Scientists

John M. Stewart (University of Cambridge)


Cambridge University Press

Mathematics & Sciences;
Numerical analysis;
Computing: general;
Programming & scripting languages: general


273 pages

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Scientific Python is a significant public domain alternative to expensive proprietary software packages. This book teaches from scratch everything the working scientist needs to know using copious, downloadable, useful and adaptable code snippets. Readers will discover how easy it is to implement and test non-trivial mathematical algorithms and will be guided through the many freely available add-on modules. A range of examples, relevant to many different fields, illustrate the language's capabilities. The author also shows how to use pre-existing legacy code (usually in Fortran77) within the Python environment, thus avoiding the need to master the original code. In this new edition, several chapters have been re-written to reflect the IPython notebook style. With an extended index, an entirely new chapter discussing SymPy and a substantial increase in the number of code snippets, researchers and research students will be able to quickly acquire all the skills needed for using Python effectively.

By:   John M. Stewart (University of Cambridge)
Imprint:   Cambridge University Press
Country of Publication:   United Kingdom
Edition:   2nd Revised edition
Dimensions:   Height: 245mm,  Width: 174mm,  Spine: 14mm
Weight:   550g
ISBN:   9781316641231
ISBN 10:   1316641236
Pages:   273
Publication Date:   July 2017
Audience:   College/higher education ,  Professional and scholarly ,  Primary ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active

1. Introduction; 2. Getting started with IPython; 3. A short Python tutorial; 4. NumPy; 5. Two-dimensional graphics; 6. Multi-dimensional graphics; 7. SymPy, a computer algebra system; 8. Ordinary differential equations; 9. Partial differential equations - a pseudospectral approach; 10. Case study - multigrid; Appendix A. Installing a Python environment; Appendix B. Fortran77 subroutines for pseudospectral methods; References; Hints for using the index; Index.

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

Review of previous edition: '... the practitioner who wants to learn Python will love it. This is the type of book I have been looking for to learn Python ... concise, yet practical.' Adhemar Bultheel, European Mathematical Society (

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