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Python for Chemists by Christian Hill (2023, Trade Paperback)

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About this product

Product Identifiers

PublisherCambridge University Press

ISBN-101009102044

ISBN-139781009102049

eBay Product ID (ePID)26060634593

Product Key Features

Book TitlePython for Chemists

Number of Pages572 Pages

LanguageEnglish

Publication Year2023

TopicPhysics / Mathematical & Computational

IllustratorYes

GenreScience

AuthorChristian Hill

FormatTrade Paperback

Dimensions

Item Height0.3 in

Item Length9.6 in

Item Width6.7 in

Additional Product Features

LCCN2023-021044

Reviews'This book is a very useful addition to the library of python books, and is squarely directed at chemists, covering all the main aspects of python that they will find useful, without getting bogged down in programming detail. The clear focus on chemistry examples from the start means that students will be able to quickly perform useful, Python-based tasks without having to invest time in learning abstract syntax. Python for chemists will be a valuable resource for chemists who wish to add an element of programming to their skills base.' John McGrady, University of Oxford

Dewey Edition23/eng/20230927

Dewey Decimal542/.85133

Table Of Content1. Introduction; 2. Basic Python usage; 3. Strings; 4. Lists and loops; 5. Comparisons and flow control; 6. Functions; 7. Data structures; 8. File input/output; 9. Basic numpy; 10. Graph plotting with Matplotlib; 11. The steady-state approximation; 12. Liquid-vapour equilibrium; 13. Jupyter notebook; 14. LaTeX; 15. Chemistry databases and file formats; 16. More NumPy and Matplotlib; 17. Thermodynamic cycles; 18. Vectors, matrices and linear algebra; 19. Linear least squares fitting I; 20. Linear least squares fitting II; 21. Numerical integration; 22. Optimization with scipy.optimize; 23. Vibrational spectroscopy; 24. The morse oscillator; 25. Solving ordinary differential equations; 26. The oregonator; 27. Root-finding with scipy.optimize; 28. Rotational spectroscopy; 29. Peak finding; 30. Fitting the vibrational spectrum of CO; 31. pandas; 32. Simulating a powder diffraction spectrum; 33. The Hückel approximation; 34. Nonlinear fitting and constrained optimization; 35. SymPy; 36. Molecular orbital theory for H2+; 37. Approximations of the helium atom electronic energy; 38. Computational chemistry with Psi4 and Python; 39. Atomic structure; 40. Solutions.

SynopsisThis accessible and self-contained guide provides a comprehensive introduction to the popular programming language Python, with a focus on applications in chemistry and chemical physics. Ideally suited to students and researchers of chemistry learning to employ Python for problem-solving in their research, this fast-paced primer first builds a solid foundation in the programming language before progressing to advanced concepts and applications in chemistry. The required syntax and data structures are established, and then applied to solve problems computationally. Popular numerical packages are described in detail, including NumPy, SciPy, Matplotlib, SymPy, and pandas. End of chapter problems are included throughout, with worked solutions available within the book. Additional resources, datasets, and Jupyter Notebooks are provided on a companion website, allowing readers to reinforce their understanding and gain confidence applying their knowledge through a hands-on approach., This accessible and self-contained guide provides a comprehensive introduction to the popular programming language, Python, with a focus on applications in chemistry and chemical physics. End of chapter problems are included throughout, with worked solutions available, and additional resources are provided on a companion website.

LC Classification NumberQD39.3.E46