Idris - Python Data Analysis Cookbook
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![Ivan Idris [Ivan Idris] - NumPy Cookbook - Second Edition](/uploads/posts/book/119328/thumbs/ivan-idris-ivan-idris-numpy-cookbook-second.jpg)
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Copyright 2016 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: July 2016
Production reference: 1150716
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham B3 2PB, UK.
ISBN 978-1-78528-228-7
www.packtpub.com
Author
Ivan Idris
Reviewers
Bill Chambers
Alexey Grigorev
Dr. Vahid Mirjalili
Michele Usuelli
Commissioning Editor
Akram Hussain
Acquisition Editor
Prachi Bisht
Content Development Editor
Rohit Singh
Technical Editor
Vivek Pala
Copy Editor
Pranjali Chury
Project Coordinator
Izzat Contractor
Proofreader
Safis Editing
Indexer
Rekha Nair
Graphics
Jason Monteiro
Production Coordinator
Aparna Bhagat
Cover Work
Aparna Bhagat
Ivan Idris was born in Bulgaria to Indonesian parents. He moved to the Netherlands and graduated in experimental physics. His graduation thesis had a strong emphasis on applied computer science. After graduating, he worked for several companies as a software developer, data warehouse developer, and QA analyst.
His professional interests are business intelligence, big data, and cloud computing. He enjoys writing clean, testable code and interesting technical articles. He is the author of NumPy Beginner's Guide , NumPy Cookbook , Learning NumPy , and Python Data Analysis , all by Packt Publishing.
Bill Chambers is a data scientist from the UC Berkeley School of Information. He's focused on building technical systems and performing large-scale data analysis. At Berkeley, he has worked with everything from data science with Scala and Apache Spark to creating online Python courses for UC Berkeley's master of data science program. Prior to Berkeley, he was a business analyst at a software company where he was charged with the task of integrating multiple software systems and leading internal analytics and reporting. He contributed as a technical reviewer to the book Learning Pandas by Packt Publishing.
Alexey Grigorev is a skilled data scientist and software engineer with more than 5 years of professional experience. Currently, he works as a data scientist at Searchmetrics Inc. In his day-to-day job, he actively uses R and Python for data cleaning, data analysis, and modeling. He has contributed as a technical reviewer to other books on data analysis by Packt Publishing, such as Test-Driven Machine Learning and Mastering Data Analysis with R .
Dr. Vahid Mirjalili is a data scientist with a diverse background in engineering, mathematics, and computer science. Currently, he is working toward his graduate degree in computer science at Michigan State University. With his specialty in data mining, he is very interested in predictive modeling and getting insights from data. As a Python developer, he likes to contribute to the open source community. He has developed Python packages, such as PyClust, for data clustering. Furthermore, he is also focused on making tutorials for different directions of data science, which can be found at his Github repository at http://github.com/mirjalil/DataScience.
The other books that he has reviewed include Python Machine Learning by Sebastian Raschka and Python Machine Learning Cookbook by Parteek Joshi. Furthermore, he is currently working on a book focused on big data analysis, covering the algorithms specifically suited to analyzing massive datasets.
Michele Usuelli is a data scientist, writer, and R enthusiast specializing in the fields of big data and machine learning. He currently works for Microsoft and joined through the acquisition of Revolution Analytics, the leading R-based company that builds a big data package for R. Michele graduated in mathematical engineering, and before Revolution, he worked with a big data start-up and a big publishing company. He is the author of R Machine Learning Essentials and Building a Recommendation System with R .
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"Data analysis is Python's killer app" |
| -- Unknown |
This book is the follow-up to Python Data Analysis . The obvious question is, "what does this new book add?" as Python Data Analysis is pretty great (or so I like to believe) already. This book, Python Data Analysis Cookbook , is targeted at slightly more experienced Pythonistas. A year has passed, so we are using newer versions of software and software libraries that I didn't cover in Python Data Analysis . Also, I've had time to rethink and research, and as a result I decided the following:
- I need to have a toolbox in order to make my life easier and increase reproducibility. I called the toolbox dautil and made it available via PyPi (which can be installed with
pip/easy_install). - My soul-searching exercise led me to believe that I need to make it easier to obtain and install the required software. I published a Docker container (pydacbk) with some of the software we need via DockerHub. You can read more about the setup in ,
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