Clinton W. Brownley - Foundations for Analytics with Python
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Many of Excels 750 million users would like to do more with their data, such as repeating similar analyses over hundreds of files or combining the data in many files for analysis at one time. This practical guide shows ambitious non-programmers how to automate and scale data processing and analysis of different data formats with Python, using business-relevant examples with complete, easy-to-read code.
Beginning with the basics of Python, author Clinton Brownley shows you how to deal with Excel, CSV, and text files in Python, leading up to scheduling scripts to automatically gather and process information without human intervention. More practical than many other introductions to Python, this book gives you skills you can immediately apply in your job.
- Automate and scale data processing with only a knowledge of Excel
- Get an excellent, practical introduction to scripting languages in general
- Learn techniques through real-world business examples, including three in-depth projects
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by Clinton W. Brownley
Copyright 2016 Clinton Brownley. All rights reserved.
Printed in the United States of America.
Published by OReilly Media, Inc. , 1005 Gravenstein Highway North, Sebastopol, CA 95472.
OReilly books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles ( http://safaribooksonline.com ). For more information, contact our corporate/institutional sales department: 800-998-9938 or corporate@oreilly.com .
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- Interior Designer: David Futato
- Cover Designer: Karen Montgomery
- Illustrator: Rebecca Demarest
- January -4712: First Edition
- 2016-04-05: First Early Release
See http://oreilly.com/catalog/errata.csp?isbn=0636920038375 for release details.
The OReilly logo is a registered trademark of OReilly Media, Inc. Foundations for Analytics with Python, the cover image, and related trade dress are trademarks of OReilly Media, Inc.
While the publisher and the author(s) have used good faith efforts to ensure that the information and instructions contained in this work are accurate, the publisher and the author(s) disclaim all responsibility for errors or omissions, including without limitation responsibility for damages resulting from the use of or reliance on this work. Use of the information and instructions contained in this work is at your own risk. If any code samples or other technology this work contains or describes is subject to open source licenses or the intellectual property rights of others, it is your responsibility to ensure that your use thereof complies with such licenses and/or rights.
063-6-920-03837-5
[FILL IN]
This book is intended to take a reader who deals with data in spreadsheets on a regular basis, but has never written a line of code. The opening chapters will get you set up with the Python environment, and teach you how to get the computer to look at data and take simple actions with it. Soon, youll learn to do things with data in spreadsheets (CSV files) and databases.
At first this will feel like a step backwards, especially if youre a power user of Excel. Painstakingly telling Python how to loop through every cell in a column when you used to select and paste feels slow and frustrating (especially when you have to go back three times to find a typo). But as you become more proficient, youll start to see where Python really shines, especially in automating tasks that you currently do over and over.
This book is written so that you can work through it from beginning to end and feel confident that you can write code that works and does what you expect at the end. Its probably a good idea to type out the code at first, so that you get used to things like tabs and closing your parentheses and quotes, but all the code is available online (see Using Code Examples, below) and you may wind up referring to those links to copy and paste as you do your own work in the future. Thats fine! Knowing when to cut-and-paste is part of being an efficient programmer! Reading the book as you go through the examples will teach you why and how the code samples work.
Good luck on your journey to becoming a programmer!
The following typographical conventions are used in this book:
ItalicIndicates new terms, URLs, email addresses, filenames, and file extensions.
Constant widthUsed for program listings, as well as within paragraphs to refer to program elements such as variable or function names, databases, data types, environment variables, statements, and keywords.
Constant width boldShows commands or other text that should be typed literally by the user.
Constant width italicShows text that should be replaced with user-supplied values or by values determined by context.
This element signifies a tip or suggestion.
This element signifies a general note.
This element signifies a warning or caution.
This is an early release copy of The Enterprise Data Lake. The text, figures, and examples are a work in progress, and several chapters are yet to be written. We are releasing the book before it is finished because we hope that it is already useful in its current form and because we would love your feedback in order to create the best possible finished product.
If you find any errors or glaring omissions, if you find anything confusing, or if you have any ideas for improving the book, please email the editor at tmcgovern@oreilly.com
Supplemental material (virtual machine, data, scripts, and custom command-line tools, etc.) is available for download at https://github.com/cbrownley/foundations-for-analytics-with-python.
This book is here to help you get your job done. In general, if example code is offered with this book, you may use it in your programs and documentation. You do not need to contact us for permission unless youre reproducing a significant portion of the code. For example, writing a program that uses several chunks of code from this book does not require permission. Selling or distributing a CD-ROM of examples from OReilly books does require permission. Answering a question by citing this book and quoting example code does not require permission. Incorporating a significant amount of example code from this book into your products documentation does require permission.
We appreciate, but do not require, attribution. An attribution usually includes the title, author, publisher, and ISBN. For example: Foundations for Analytics with Python by Clinton Brownley (OReilly). Copyright 2016 Clinton Brownley, 978-1-491-92253-8.
If you feel your use of code examples falls outside fair use or the permission given above, feel free to contact us at .
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