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Scientific computing with Python : high-performance scientific computing with NumPy, SciPy, and pandas / Claus Führer, Jan Erik Solem, Olivier Verdier.

Ebook Central College Complete Available online

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Format:
Book
Author/Creator:
Führer, Claus.
Contributor:
Solem, Jan Erik.
Verdier, Olivier.
Language:
English
Subjects (All):
Application software--Development.
Application software.
Python (Computer program language).
Physical Description:
1 online resource (ix, 375 p.) : ill.
Edition:
2nd ed.
Place of Publication:
Birmingham : Packt, 2021.
Summary:
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.
Contents:
Chapter 1: Getting Started
Chapter 2: Variables and Basic Types
Chapter 3: Container Types
Chapter 4: Linear Algebra - Arrays
Chapter 5: Advanced Array Concepts
Chapter 6: Plotting
Chapter 7: Functions
Chapter 8: Classes
Chapter 9: Iterating
Chapter 10: Series and Dataframes - Working with Pandas
Chapter 11: Communication by a Graphical User Interface
Chapter 12: Error and Exception Handling
Chapter 13: Namespaces, Scopes, and Modules
Chapter 14: Input and Output
Chapter 15: Testing
Chapter 16: Symbolic Computations - SymPy
Chapter 17: Interacting with the Operating System
Chapter 18: Python for Parallel Computing
Chapter 19: Comprehensive Examples
References
Index.
Notes:
First published December 2016.
ISBN:
9781838825102 (e-book)
9781838822323 (pbk.)

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