Martins - IPython notebook essentials: compute scientific data and execute code interactively with NumPy and SciPy
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Copyright 2014 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
First published: November 2014
Production reference: 1141114
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham B3 2PB, UK.
ISBN 978-1-78398-834-1
www.packtpub.com
Cover image by Duraid Fatouhi (<>)
Author
L. Felipe Martins
Reviewers
Sagar Ahire
Steven D. Essinger, Ph.D.
David Selassie Opoku
Commissioning Editor
Pramila Balan
Acquisition Editor
Nikhil Karkal
Content Development Editor
Sumeet Sawant
Technical Editor
Menza Mathew
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Proofreaders
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Indexers
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Cover Work
Komal Ramchandani
L. Felipe Martins holds a PhD in Applied Mathematics from Brown University and has worked as a researcher and educator for more than 20 years. His research is mainly in the field of applied probability. He has been involved in developing code for the open source homework system WeBWorK, where he wrote a library for the visualization of systems of differential equations. He was supported by an NSF grant for this project. Currently, he is an associate professor in the Department of Mathematics at Cleveland State University, Cleveland, Ohio, where he has developed several courses in Applied Mathematics and Scientific Computing. His current duties include coordinating all first-year Calculus sessions.
He is the author of the blog, All Things Computing (http://fxmartins.com).
Sagar Ahire is a Master's student in Computer Science. He primarily studies Natural Language Processing using statistical techniques and relies heavily on Pythonspecifically, the IPython ecosystem for scientific computing. You can find his work at github.com/DJSagarAhire.
I'd like to thank the community of Python for coming together to develop such an amazing ecosystem around the language itself. Apart from that, I'd like to thank my parents and teachers for supporting me and teaching me new things. Finally, I'd like to thank Packt Publishing for approaching me to work on this book; it has been a wonderful learning experience.
Steven D. Essinger, Ph.D. is a data scientist of Recommender Systems and is working in the playlist team at Pandora in Oakland, California. He holds a PhD in Electrical Engineering and focuses on the development of novel, end-to-end computational pipelines employing machine-learning techniques. Steve has previously worked in the field of biological sciences, developing Bioinformatics pipelines for ecologists. He has also worked as a RF systems engineer and holds numerous patents in wireless product design and RFID.
Steve may be reached via LinkedIn at https://www.linkedin.com/in/sessinger.
David Selassie Opoku is a developer and an aspiring data scientist. He is currently a technology teaching fellow at the Meltwater Entrepreneurial School of Technology, Ghana, where he teaches and mentors young entrepreneurs in software development skills and best practices.
David is a graduate of Swarthmore College, Pennsylvania, with a BA in Biology, and he is also a graduate of the New Jersey Institute of Technology with an MS in Computer Science.
David has had the opportunity to work with the Boyce Thompson Institute for Plant Research, the Eugene Lang Center for Civic and Social Responsibility, UNICEF Health Section, and a tech start-up in New York City. He loves Jesus, spending time with family and friends, and tinkering with data and systems.
David may be reached via LinkedIn at https://www.linkedin.com/in/sdopoku.
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"To my wife, Ieda Rodrigues, and my wonderful daughters, Laura and Diana."
The world of computing has seen an incredible revolution in the past 30 years. Not so long ago, high-performance computations required expensive hardware; proprietary software costing hundreds, if not thousands, of dollars; knowledge of computer languages such as FORTRAN, C, or C++; and familiarity with specialized libraries. Even after obtaining the proper hardware and software, just setting up a working environment for advanced scientific computing and data handling was a serious challenge. Many engineers and scientists were forced to become operating systems wizards just to be able to maintain the toolset required by their daily computational work.
Scientists, engineers, and programmers were quick to address this issue. Hardware costs decreased as performance went up, and there was a great push to develop scripting languages that allowed integration of disparate libraries through multiple platforms. It was in this environment that Python was being developed in the late 1980s, under the leadership of Guido Van Rossum. From the beginning, Python was designed to be a cutting-edge, high-level computer language with a simple enough structure that its basics could be quickly learned even by programmers who are not experts.
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