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James Church - Learning Haskell Data Analysis

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James Church Learning Haskell Data Analysis
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Learning Haskell Data Analysis: summary, description and annotation

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Analyze, manipulate, and process datasets of varying sizes efficiently using Haskell

About This Book
  • Create portable databases using SQLite3 and use these databases to quickly pull large amounts of data into your Haskell programs.
  • Visualize data using EasyPlot and create publication-ready charts
  • An easy-to-follow guide to analyze real-world data using the most commonly used statistical techniques
Who This Book Is For

If you are a developer, analyst, or data scientist who wants to learn data analysis methods using Haskell and its libraries, then this book is for you. Prior experience with Haskell and a basic knowledge of data science will be beneficial.

What You Will Learn
  • Learn the essential tools of Haskell needed to handle large data
  • Migrate your data to a database and learn to interact with your data quickly
  • Clean data with the power of Regular Expressions
  • Plot data with the Gnuplot tool and the EasyPlot library
  • Formulate a hypothesis test to evaluate the significance of your data
  • Evaluate the variance between columns of data using a correlation statistic and perform regression analysis
In Detail

Haskell is trending in the field of data science by providing a powerful platform for robust data science practices. This book provides you with the skills to handle large amounts of data, even if that data is in a less than perfect state. Each chapter in the book helps to build a small library of code that will be used to solve a problem for that chapter. The book starts with creating databases out of existing datasets, cleaning that data, and interacting with databases within Haskell in order to produce charts for publications. It then moves towards more theoretical concepts that are fundamental to introductory data analysis, but in a context of a real-world problem with real-world data. As you progress in the book, you will be relying on code from previous chapters in order to help create new solutions quickly. By the end of the book, you will be able to manipulate, find, and analyze large and small sets of data using your own Haskell libraries.

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Learning Haskell Data Analysis

Learning Haskell Data Analysis

Copyright 2015 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: May 2015

Production reference: 1250515

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham B3 2PB, UK.

ISBN 978-1-78439-470-7

www.packtpub.com

Credits

Author

James Church

Reviewers

Joseph Adams

William Kong

Samuli Thomasson

Commissioning Editor

Ashwin Nair

Acquisition Editor

Shaon Basu

Content Development Editor

Parita Khedekar

Technical Editor

Gaurav Suri

Copy Editors

Aditya Nair

Vedangi Narvekar

Project Coordinator

Milton Dsouza

Proofreaders

Stephen Copestake

Safis Editing

Indexer

Priya Sane

Graphics

Sheetal Aute

Jason Monteiro

Abhinash Sahu

Production Coordinator

Shantanu N. Zagade

Cover Work

Shantanu N. Zagade

About the Author

James Church is an assistant professor of computer science at the University of West Georgia. James completed his PhD in computer science from the University of Mississippi under the advisement of Dr. Yixin Chen, with a research focus on computational geometry.

While at the University of Mississippi, he learned the skills necessary for data analysis in his side job, where he worked as a database administrator and analyst for the Marijuana Potency Monitoring Program (MPMP) led by Dr. Mahmoud ElSohly. The software written by James is used by the laboratory to store and track the chemical composition of marijuana samples. This data is provided to the United States National Institute on Drug Abuse to report marijuana potency.

The knowledge gained through his experience as an analyst for the MPMP (as well as other companies) was turned into a data analysis course for undergraduates at the University of Mississippi. This course was taught using the languages of Python and R.

James enjoys spending time with his wife, Michelle Allen, teaching, and playing board games with his friends.

I would like to thank the reviewers for testing and reshaping the code in these pages into something readable. While I made every attempt to write the best possible book on this topic, I'm sure that mistakes will be found. All mistakes are my own.

I would like to thank Michelle Allen. Your support made this book possible (Michelle drew the sketch of the airplane found in , Building a Recommendation Engine ).

I would like to thank Dr. Yixin Chen, Dr. Dawn Wilkins, Dr. Conrad Cunningham, and the faculty of computer and information science at the University of Mississippi.

Finally, thanks, mom and dad.

About the Reviewers

Joseph Adams is a keen programmer, writing in Go, Haskell, Python, Java, and a few more programming languages. His interests include the designing of programming languages, especially the functional and esoteric ones, as well as the application of unusual data structures. When not programming, he enjoys reading books ranging from topics such as philosophy to logic and advanced mathematics. Joseph also regularly attends international computer conferences and has even spoken on his Scheme to Go compiler at Free and Open Source Software Developers' European Meeting (FOSDEM).

He has a number of public repositories on GitHub that you should definitely check out by visiting http://github.com/jcla1. He also blogs quite regularly at http://jcla1.com.

William Kong studied at the University of Waterloo, Canada, and holds a bachelor of mathematics degree with a specialization in mathematical finance and a minor in statistics. He has an extensive experience in the Haskell and R programming languages and has worked as a SAS statistical programmer and modeler in the financial risk modeling industry.

William's concentrations have been mainly in the fields of optimization, statistics, and computational mathematics. His current interests lie in the practical application of novel programming paradigms and languages, such as the ever-functional Haskell and the latest newcomer, Julia.

My gratitude goes out to my parents for their support and understanding during my long hours at my computer, reviewing and testing code. I must also acknowledge instrumental help from Learn You a Haskell for Great Good: A Beginner's Guide , No Starch Press and Real World Haskell , O'Reilly Media , which were an invaluable source of knowledge throughout the editing process.

Samuli Thomasson is a Haskell enthusiast who has written software in Haskell for over 3 years, mostly as a hobby and partly for his studies and work. He has built multiple web applications and miscellaneous tools, many of which were written in Haskell. He is currently interested in functional programming, distributed systems, data science, mathematics, and philosophy. He is a student at the Department of Computer Science in the University of Helsinki, and he also works in the Finnish software industry. While pursuing his budding career, he is actively searching for the best topics to learn and specialize in.

He lives in Helsinki, Finland, with his friends. You can take a look at his website by visiting http://funktionaali.com.

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