Please share your thoughts on this book with others by leaving a review on the site that you bought it from. If you purchased the book from Amazon, please leave us an honest review on this book's Amazon page. This is vital so that other potential readers can see and use your unbiased opinion to make purchasing decisions, we can understand what our customers think about our products, and our authors can see your feedback on the title that they have worked with Packt to create. It will only take a few minutes of your time, but is valuable to other potential customers, our authors, and Packt. Thank you!
Scientific Computing with Python - Second Edition
By :
Scientific Computing with Python - Second Edition
By:
Overview of this book
Python has tremendous potential within the scientific computing domain. This updated edition of Scientific Computing with Python features new chapters on graphical user interfaces, efficient data processing, and parallel computing to help you perform mathematical and scientific computing efficiently using Python.
This book will help you to explore new Python syntax features and create different models using scientific computing principles. The book presents Python alongside mathematical applications and demonstrates how to apply Python concepts in computing with the help of examples involving Python 3.8. You'll use pandas for basic data analysis to understand the modern needs of scientific computing, and cover data module improvements and built-in features. You'll also explore numerical computation modules such as NumPy and SciPy, which enable fast access to highly efficient numerical algorithms. By learning to use the plotting module Matplotlib, you will be able to represent your computational results in talks and publications. A special chapter is devoted to SymPy, a tool for bridging symbolic and numerical computations.
By the end of this Python book, you'll have gained a solid understanding of task automation and how to implement and test mathematical algorithms within the realm of scientific computing.
Table of Contents (23 chapters)
Preface
Getting Started
Free Chapter
Variables and Basic Types
Container Types
Linear Algebra - Arrays
Advanced Array Concepts
Plotting
Functions
Classes
Iterating
Series and Dataframes - Working with Pandas
Communication by a Graphical User Interface
Error and Exception Handling
Namespaces, Scopes, and Modules
Input and Output
Testing
Symbolic Computations - SymPy
Interacting with the Operating System
Python for Parallel Computing
Comprehensive Examples
About Packt
Other Books You May Enjoy
References
Customer Reviews