Series in Computational Physics
Steven A. Gottlieb and Rubin H. Landau, Series Editors
Introduction to Python for Science and Engineering
This guide offers a quick and incisive introduction to Python programming for anyone. The author has carefully developed a concise approach to using Python in any discipline of science and engineering, with plenty of examples, practical hints, and insider tips.
Readers will see why Python is such a widely appealing program, and learn the basics of syntax, data structures, input and output, plotting, conditionals and loops, user-defined functions, curve fitting, numerical routines, animation, and visualization. The author teaches by example and assumes no programming background for the reader.
David J. Pine is the Silver Professor and Professor of Physics at New York University, and Chair of the Department of Chemical and Biomolecular Engineering at the NYU Tandon School of Engineering. He is an elected fellow of the American Physical Society and American Association for the Advancement of Science (AAAS), and is a Guggenheim Fellow.
David J. Pine is the Silver Professor and Professor of Physics at New York University, as well as Chair of the Department of Chemical and Biomolecular Engineering at the NYU Tandon School of Engineering. He earned his PhD in physics from Cornell University and has been invited professor at ESPCI in Paris, France, and the University of Strasbourg. He has also served as a visiting scientist at Exxon Research and Engineering. He is recipient of numerous honors, including Fellow of the American Association for the Advancement of Science, Guggenheim Fellow, and Fellow of the American Physical Society.
Title: Introduction to Python for Science and Engineering (Series in Computational Physics)
Author: Pine, David J.
ISBN: 9781138583894
Binding:
Publisher: Taylor & Francis Ltd
Publication Date: 2018-12-05
Number of Pages: 368
Weight: 0.5802 kg
A comprehensive introduction and a practical guide to the Python programming language for scientists and engineers. Chapters intuitively introduce programming concepts around scientific problems. This approach resonates with scientists and engineers and helps them understand programming paradigms faster. --Ana Bell, PhD, Electrical Engineering and Computer Science, Massachusetts Institute of Technology