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A. J. Henley and Dave Wolf

Learn Data Analysis with Python Lessons in Coding

A. J. Henley

Washington, D.C., District of Columbia, USA

Dave Wolf

Sterling Business Advantage, LLC, Adamstown, Maryland, USA

Any source code or other supplementary material referenced by the author in this book is available to readers on GitHub via the books product page, located at www.apress.com/9781484234853 . For more detailed information, please visit http://www.apress.com/source-code .

ISBN 978-1-4842-3485-3 e-ISBN 978-1-4842-3486-0

https://doi.org/10.1007/978-1-4842-3486-0

Library of Congress Control Number: 2018933537

A.J. Henley and Dave Wolf 2018

This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed.

Trademarked names, logos, and images may appear in this book. Rather than use a trademark symbol with every occurrence of a trademarked name, logo, or image we use the names, logos, and images only in an editorial fashion and to the benefit of the trademark owner, with no intention of infringement of the trademark. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights.

While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein.

Printed on acid-free paper

Distributed to the book trade worldwide by Springer Science+Business Media New York, 233 Spring Street, 6th Floor, New York, NY 10013. Phone 1-800-SPRINGER, fax (201) 348-4505, email orders-ny@springer-sbm.com, or visit www.springeronline.com. Apress Media, LLC is a California LLC and the sole member (owner) is Springer Science + Business Media Finance Inc (SSBM Finance Inc). SSBM Finance Inc is a Delaware corporation.

Table of Contents

Index

About the Authors and About the Technical Reviewer

About the Authors

A. J. Henley

is a technology educator with over 20 years experience as a developer, designer, and systems engineer. He is an instructor at both Howard University and Montgomery College.

Dave Wolf

is a certified Project Management Professional (PMP) with over 20 years experience as a software developer, analyst, and trainer. His latest projects include collaboratively developing training materials and programming bootcamps for Java and Python.

About the Technical Reviewer

Michael Thomas

has worked in software development for more than 20 years as an individual contributor, team lead, program manager, and vice president of engineering. Michael has more than ten years of experience working with mobile devices. His current focus is in the medical sector, using mobile devices to accelerate information transfer between patients and health-care providers.

A.J. Henley and Dave Wolf 2018

A.J. Henley and Dave Wolf Learn Data Analysis with Python

1. How to Use This Book

A. J. Henley 1 and Dave Wolf 2

(1)

Washington, D.C., District of Columbia, USA

(2)

Sterling Business Advantage, LLC, Adamstown, Maryland, USA

If you are already using Python for data analysis, just browse this books table of contents. You will probably find a bunch of things that you wish you knew how to do in Python. If so, feel free to turn directly to that chapter and get to work. Each lesson is, as much as possible, self-contained.

Be warned! This book is more a workbook than a textbook.

If you arent using Python for data analysis, begin at the beginning. If you work your way through the whole workbook, you should have a better of idea of how to use Python for data analysis when you are done.

If you know nothing at all about data analysis, this workbook might not be the place to start. However, give it a try and see how it works for you.

Installing Jupyter Notebook

The fastest way to install and use Python is to do what you already know how to do, and you know how to use your browser. Why not use Jupyter Notebook?

What Is Jupyter Notebook?

Jupyter Notebook is an interactive Python shell that runs in your browser. When installed through Anaconda, it is easy to quickly set up a Python development environment. Since its easy to set up and easy to run, it will be easy to learn Python.

Jupyter Notebook turns your browser into a Python development environment. The only thing you have to install is Anaconda. In essence, it allows you to enter a few lines of Python code, press CTRL+Enter, and execute the code. You enter the code in cells and then run the currently selected cell. There are also options to run all the cells in your notebook. This is useful if you are developing a larger program.

What Is Anaconda?

Anaconda is the easiest way to ensure that you dont spend all day installing Jupyter. Simply download the Anaconda package and run the installer. The Anaconda software package contains everything you need to create a Python development environment. Anaconda comes in two versionsone for Python 2.7 and one for Python 3.x. For the purposes of this guide, install the one for Python 2.7.

Anaconda is an open source data-science platform. It contains over 100 packages for use with Python, R, and Scala. You can download and install Anaconda quickly with minimal effort. Once installed, you can update the packages or Python version or create environments for different projects.

Getting Started

1. Download and install Anaconda at https://www.anaconda.com/download .
2. Once youve installed Anaconda, youre ready to create your first notebook. Run the Jupyter Notebook application that was installed as part of Anaconda.
3. Your browser will open to the following address: http://localhost:8888 . If youre running Internet Explorer, close it. Use Firefox or Chrome for best results. From there, browse to http://localhost:8888 .

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