A fully updated tutorial on the basics of the Python programming language for science students
Python is a computer programming language that is rapidly gaining popularity throughout the sciences. This fully updated edition of A Student's Guide to Python for Physical Modeling aims to help you, the student, teach yourself enough of the Python programming language to get started with physical modeling. You will learn how to install an open-source Python programming environment and use it to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; and simulation. No prior programming experience is assumed.
This tutorial focuses on fundamentals and introduces a wide range of useful techniques, including:
- Basic Python programming and scripting
- Numerical arrays
- Two- and three-dimensional graphics
- Monte Carlo simulations
- Numerical methods, including solving ordinary differential equations
- Image processing
Numerous code samples and exercises--with solutions—illustrate new ideas as they are introduced. Web-based resources also accompany this guide and include code samples, data sets, and more. This current edition brings the discussion of the Python language, Spyder development environment, and Anaconda distribution up to date. In addition, a new appendix introduces Jupyter notebooks.
Princeton University Press; January 2018
- ISBN 9781400889426
- Read online, or download in secure PDF format
- Title: A Student's Guide to Python for Physical Modeling
- Author: Jesse M. Kinder; Philip Nelson
Imprint: Princeton University Press
In The Press
Praise for the previous edition: "Like patient driving instructors, Kinder and Nelson guide the hands of novice programming students from the get-go, helping them to avoid obstacles and crashes. By the end of the book, students should be racing around confidently like pros, using Python to solve scientific problems of data analysis, modeling, and visualization. A great textbook for a first course in modern scientific programming in any context, and one that I'll be using myself."—Garnet Kin-Lic Chan, Princeton University
About The Author
Jesse M. Kinder is assistant professor of physics at the Oregon Institute of Technology. Philip Nelson is professor of physics at the University of Pennsylvania. His books include From Photon to Neuron (Princeton) and Physical Models of Living Systems.