Python for Scientists (3rd Edition)
By John M. Stewart and Michael Mommert
(2023, Cambridge University Press, 300 pages, ISBN-13: 978-1009014809)
Python for Scientists by John M. Stewart and Michael Mommert is a must-have guide for scientists and researchers who want to utilize Python for their work. This book covers a broad range of topics, from the basics of programming to advanced data analysis and modeling techniques, making it an essential resource for those in scientific fields.
What Will You Learn?
With this book, you will gain the knowledge needed to successfully use Python in scientific research, including practical examples and methodologies to apply Python to your projects. Topics covered include:
- Python Basics: Master Python’s core concepts and syntax.
- Working with Arrays and Matrices: Learn to manipulate complex data structures.
- Data Visualization: Present your data in meaningful ways.
- Statistical Analysis: Conduct thorough and accurate data analysis.
- Solving Differential Equations: Apply Python to solve scientific equations.
- Signal Processing: Use Python for signal analysis and interpretation.
- Modeling and Simulations: Build models and simulations to test scientific theories.
Who Should Read This Book?
- Scientists and Researchers: A practical guide to help you solve scientific problems, analyze data, and model systems using Python.
- Students and Graduate Students: A valuable addition to your studies, with practical examples and assignments to enhance your learning.
- Engineers: Learn how to apply Python to engineering projects, including signal processing and modeling.
- Data Analysts: Gain useful techniques and tools for effective data analysis and visualization.
About the Authors
John M. Stewart was Emeritus Reader in Gravitational Physics at the University of Cambridge and authored key works in gravitational theory, including Non-equilibrium Relativistic Kinetic Theory and Advanced General Relativity.
Michael Mommert is an Assistant Professor for Computer Vision at the University of St. Gallen, Switzerland. His expertise combines computer vision and Earth observation, creating efficient learning methods for various applications.
For scientists, engineers, and students looking to optimize their research with Python, Python for Scientists is a highly recommended resource. Visit ThinkJava.net to explore more books and resources for using Python in research and data analysis.
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