【2015】Mastering Python Scientific Computing

Book 图书名称： Mastering Python Scientific Computing
Author 作者： Hemant Kumar Mehta
Publisher 出版社： Packt Publishing
Page 页数： 301
Publishing Date 出版时间： Sep 23, 2015                         
Language 语言： English
Size 大小： 3 MB
Format 格式： pdf 文字版
ISBN: 978-1-78328-882-3
Edition: 第1版 搜索过论坛，没有该文档


A complete guide for Python programmers to master scientific computing using Python APIs and tools
About This Book

    The basics of scientific computing to advanced concepts involving parallel and large scale computation are all covered.
    Most of the Python APIs and tools used in scientific computing are discussed in detail
    The concepts are discussed with suitable example programs

Who This Book Is For

If you are a Python programmer and want to get your hands on scientific computing, this book is for you. The book expects you to have had exposure to various concepts of Python programming.
What You Will Learn

    Fundamentals and components of scientific computing
    Scientific computing data management
    Performing numerical computing using NumPy and SciPy
    Concepts and programming for symbolic computing using SymPy
    Using the plotting library matplotlib for data visualization
    Data analysis and visualization using Pandas, matplotlib, and IPython
    Performing parallel and high performance computing
    Real-life case studies and best practices of scientific computing

In Detail

In today's world, along with theoretical and experimental work, scientific computing has become an important part of scientific disciplines. Numerical calculations, simulations and computer modeling in this day and age form the vast majority of both experimental and theoretical papers. In the scientific method, replication and reproducibility are two important contributing factors. A complete and concrete scientific result should be reproducible and replicable. Python is suitable for scientific computing. A large community of users, plenty of help and documentation, a large collection of scientific libraries and environments, great performance, and good support makes Python a great choice for scientific computing.

At present Python is among the top choices for developing scientific workflow and the book targets existing Python developers to master this domain using Python. The main things to learn in the book are the concept of scientific workflow, managing scientific workflow data and performing computation on this data using Python.

The book discusses NumPy, SciPy, SymPy, matplotlib, Pandas and IPython with several example programs.

== Table of contents ==
n/a


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