Authors: Jesse M. Kinder & Philip Nelson

Students wishing to master Python and Anaconda for data modeling have a new resource available: A Students’ Guide to Python for Physical Modeling was released by Princeton University Press on Friday, September 18, 2015.

Basic Python programming and scripting
  • Numerical arrays
  • Two- and three-dimensional graphics
  • Monte Carlo simulations
  • Numerical methods, including solving ordinary differential equations
  • Image processing
  • Animation
  •  

    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.

     

    Jesse M. Kinder earned his PhD in physics and astronomy at the University of Pennsylvania, completed a postdoctoral fellowship in quantum chemistry at Cornell University, and taught physics at Case Western Reserve University. He currently works as a consultant in Rio Rancho, New Mexico. Philip Nelson is professor of physics at the University of Pennsylvania. He is the author ofBiological Physics and Physical Models of Living Systems.

    Endorsements:

    “Kinder and Nelson’s engaging introduction to scientific programming in Python is careful and thorough, and focuses on actual essentials. Bread-and-butter concepts and techniques, belonging in every computational scientist’s toolbox, are presented with well-thought-out examples drawn from daily research practice. This is a clever text, inviting students to take that most important step: to dive right in and start coding.”–Cornelis Storm, Eindhoven University of Technology

    “Kinder and Nelson have written a friendly and succinct, yet surprisingly comprehensive, introduction to scientific programming in Python. It’s written not just for computational scientists, but for anyone who needs to plot and analyze experimental data, numerically solve equations, or learn the basics of programming. Even students who have experience in programming will appreciate the thought-provoking exercises and guidelines for getting the most out of Python.” –Vinothan N. Manoharan, Harvard University

    “This book is tailor-made for physical scientists beginning to do computation. More than in any other programming book I’ve read, the authors are conscientious—they anticipate and troubleshoot the areas of confusion readers might encounter. Kinder and Nelson carefully and effectively guide readers toward the goal of formulating a computational problem and solving it.”–Justin Bois, California Institute of Technology

    “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

    An instructor’s guide and ebook is also available. See more information and order from Princeton University Press.


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