Introduction to Python for Science and Engineering

David J. Pine

ISBN 10: 1032673907 / ISBN 13: 9781032673905

Published by CRC Press, 2024

About this Item

Introduction to Python for Science and Engineering | David J. Pine | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | CRC Press | EAN 9781032673905 | Verantwortliche Person für die EU: Taylor & Francis Verlag GmbH, Kaufingerstr. 24, 80331 München, gpsr[at]taylorandfrancis[dot]com | Anbieter: preigu.

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Bibliographic Details

• Title: Introduction to Python for Science and Engineering
• Publisher: CRC Press
• Publication Date: 2024
• Language: English
• ISBN 10: 1032673907
• ISBN 13: 9781032673905
• Binding: Taschenbuch
• Edition: 2nd Edition
• Condition: Neu
• Dimensions: 234W x 156H x 24D millimeters 234 millimeters width by 156 millimeters height by 24 millimeters depth
• Weight: 670 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Introduction to Python for Science and Engineering offers a quick and incisive introduction to the Python programming language for use in any science or engineering discipline. The approach is pedagogical and “bottom up,” which means starting with examples and extracting more general principles from that experience. No prior programming experience is assumed.

Readers will learn the basics of Python syntax, data structures, input and output, conditionals and loops, user-defined functions, plotting, animation, and visualization. They will also learn how to use Python for numerical analysis, including curve fitting, random numbers, linear algebra, solutions to nonlinear equations, numerical integration, solutions to differential equations, and fast Fourier transforms.

Readers learn how to interact and program with Python using JupyterLab and Spyder, two simple and widely used integrated development environments.

All the major Python libraries for science and engineering are covered, including NumPy, SciPy, Matplotlib, and Pandas. Other packages are also introduced, including Numba, which can render Python numerical calculations as fast as compiled computer languages such as C but without their complex overhead.

About the Author

David J. Pine has taught physics and chemical engineering for over 40 years at four different institutions: Cornell University (as a graduate student), Haverford College, UCSB, and NYU, where he is a Professor of Physics, Mathematics, and Chemical & Biomolecular Engineering. He has taught a broad spectrum of courses, including numerical methods. He does research on optical materials and in experimental soft-matter physics, which is concerned with materials such as polymers, emulsions, and colloids.