Name: A Student'S Guide to Python for Physical Modeling: Second Edition (en Inglés)
Price: 135087.00 COP
Availability: InStock
Author: Jesse M. Kinder; Philip Nelson
ISBN: 9780691223650

portada A Student'S Guide to Python for Physical Modeling: Second Edition (en Inglés)

Formato

Libro Físico

Editorial

Princeton University Press

Autor

Jesse M. Kinder; Philip Nelson

Año

2021

Idioma

Inglés

N° páginas

240

Encuadernación

Tapa Blanda

ISBN13

9780691223650

N° edición

Categorías

Ciencias de la computación

A Student'S Guide to Python for Physical Modeling: Second Edition (en Inglés)

Jesse M. Kinder; Philip Nelson (Autor) · Princeton University Press · Tapa Blanda

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Reseña del libro "A Student'S Guide to Python for Physical Modeling: Second Edition (en Inglés)"

A fully updated tutorial on the basics of the Python programming language for science studentsPython is a computer programming language that has gained popularity throughout the sciences. This fully updated second 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 guide introduces a wide range of useful tools, including:Basic Python programming and scriptingNumerical arraysTwo- and three-dimensional graphicsAnimationMonte Carlo simulationsNumerical methods, including solving ordinary differential equationsImage processingNumerous code samples and exercises―with solutions―illustrate new ideas as they are introduced. This guide also includes supplemental online resources: code samples, data sets, tutorials, and more. This edition includes new material on symbolic calculations with SymPy, an introduction to Python libraries for data science and machine learning (pandas and sklearn), and a primer on Python classes and object-oriented programming. A new appendix also introduces command line tools and version control with Git.