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Description

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.

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

Reallife case studies and best practices of scientific computing

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

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Amazon verified reviews

ruben Dec 02, 2015

I have read this book good experience very useful and interesting All the that I have read like this were very theoricalthis books has applications that we can aplyVery nice experience. I could aply this to my classes in mechatronics and electronicsThanks

Amazon Verified review

ram krishn mishra Sep 28, 2015

Really This book is very useful ...General topic related to scientific computing and provided an appropriate context by Dr. Hemant Mehta sir which is fully practical oriented.

SuJo Dec 02, 2015

This book has huge potential, and like a few of the fellow reviewers I also agree that it could have used a lot more discussion in a few of the advanced areas. However, since the bulk of this book delivers on Scientific Computing I was really satisfied overall with the book. The real-life case studies and best practices were what sealed the deal for me. The previous 8 chapters are great, but Chapter 10 made me feel like I accomplished something, while also ending with friendly reminders or gotcha's. Security is something that you don't find covered in most programming books, but this book did indeed offer some guidance on it in Chapter 10. I guess I really enjoyed the final chapter a lot, but this book is something I'll have to read over a few dozen times to allow the deep technical aspects sink into my cranium a lot more.

Winston Nov 30, 2015

Mastering Python Scientific Computing is a book for anyone from a newbie python programmer to advanced users. Python is a very powerful programming language whose uses strength from web development to scientific computing. This book does a very good job explaining pythons uses for scientific programming by showing readers how to use NumPy and SciPy to perform scientific calculations.The reader will leave this book armed with the knowledge to take their use of Python for scientific programming to the next level. Further reading of Python libraries like NumPy, SciPy, Pandas, Matplotlib, and IPython is needed for true mastery.

Tim Crothers Nov 30, 2015

I had high hopes for this book as there aren't a lot of solid resources for using Python for scientific computing. Unfortunately in the end the author tried to cover too much and as a result the information is very surface level with insufficient depth to be useful in most cases, no "mastery" will be gained from it. There are a few gems (hence the 3 stars) and the book does an okay job of covering the topics germane to scientific computing so is useful for those looking to understand the options at a high level. I find that more specific books on topics like NumPy, pandas, and SciPy are far more useful for mastering than the simple treatment they are given here.

Mastering Python Scientific Computing: A complete guide for Python programmers to master scientific computing using Python APIs and tools

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