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  • Book Overview & Buying Scientific Computing with Python
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Scientific Computing with Python

Scientific Computing with Python - Second Edition

By : Claus Führer, Claus Fuhrer, Jan Erik Solem, Olivier Verdier
4.5 (15)
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Scientific Computing with Python

Scientific Computing with Python

4.5 (15)
By: Claus Führer, Claus Fuhrer, Jan Erik Solem, Olivier Verdier

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)
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20
About Packt
22
References
Symbolic Computations - SymPy

In this chapter, we will give a brief introduction to using Python for symbolic computations. There is powerful software on the market for performing symbolic computations, for example, Maple™ or Mathematica™. But sometimes, it might be favorable to make symbolic calculations in the language or framework you are used to. At this stage of the book, we assume that this language is Python, so we seek a tool in Python—the module SymPy.

A complete description of SymPy, if even possible, would fill an entire book, and that is not the purpose of this chapter. Instead, we will stake out a path into this tool by examining some guiding examples, giving a flavor of the potential of this tool as a complement to NumPy and SciPy.

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Scientific Computing with Python
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