9781108745918-1108745911-Learning Scientific Programming with Python

Learning Scientific Programming with Python

ISBN-13: 9781108745918
ISBN-10: 1108745911
Edition: 2
Author: Christian Hill
Publication date: 2020
Publisher: Cambridge University Press
Format: Paperback 570 pages
FREE US shipping on ALL non-marketplace orders
Rent
35 days
from $26.93 USD
FREE shipping on RENTAL RETURNS
Marketplace
from $39.81 USD
Buy

From $39.81

Rent

From $26.93

Book details

ISBN-13: 9781108745918
ISBN-10: 1108745911
Edition: 2
Author: Christian Hill
Publication date: 2020
Publisher: Cambridge University Press
Format: Paperback 570 pages

Summary

Learning Scientific Programming with Python (ISBN-13: 9781108745918 and ISBN-10: 1108745911), written by authors Christian Hill, was published by Cambridge University Press in 2020. With an overall rating of 3.8 stars, it's a notable title among other Introductory & Beginning (Programming, Engineering, Mathematical Physics, Physics, Technology) books. You can easily purchase or rent Learning Scientific Programming with Python (Paperback) from BooksRun, along with many other new and used Introductory & Beginning books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $23.15.

Description

Learn to master basic programming tasks from scratch with real-life, scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to gain proficiency quickly. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving on to the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualization, this textbook also discusses the use of Jupyter Notebooks to build rich-media, shareable documents for scientific analysis. The second edition features a new chapter on data analysis with the pandas library and comprehensive updates, and new exercises and examples. A final chapter introduces more advanced topics such as floating-point precision and algorithm stability, and extensive online resources support further study. This textbook represents a targeted package for students requiring a solid foundation in Python programming.

Rate this book Rate this book

We would LOVE it if you could help us and other readers by reviewing the book