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Clojure Data Analysis Cookbook - Second Edition

You're reading from   Clojure Data Analysis Cookbook - Second Edition Dive into data analysis with Clojure through over 100 practical recipes for every stage of the analysis and collection process

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781784390297
Length 372 pages
Edition 2nd Edition
Languages
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Author (1):
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Eric Richard Rochester Eric Richard Rochester
Author Profile Icon Eric Richard Rochester
Eric Richard Rochester
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Table of Contents (14) Chapters Close

Preface 1. Importing Data for Analysis FREE CHAPTER 2. Cleaning and Validating Data 3. Managing Complexity with Concurrent Programming 4. Improving Performance with Parallel Programming 5. Distributed Data Processing with Cascalog 6. Working with Incanter Datasets 7. Statistical Data Analysis with Incanter 8. Working with Mathematica and R 9. Clustering, Classifying, and Working with Weka 10. Working with Unstructured and Textual Data 11. Graphing in Incanter 12. Creating Charts for the Web Index

Introduction

We've seen Incanter (http://incanter.org/) earlier in this book, but we'll spend a lot more time with this library over the next few chapters. Incanter combines the power to do statistics using a fully-featured statistical language such as R (http://www.r-project.org/) with the ease and joy of Clojure.

Incanter's core data structure is the dataset, so we'll spend some time in this chapter to look at how to use them effectively. While learning basic tools in this manner is often not the most exciting way to spend your time, it can still be incredibly useful. At its most fundamental level, an Incanter dataset is a table of rows. Each row has the same set of columns, much like a spreadsheet. The data in each cell of an Incanter dataset can be a string or a numeric. However, some operations require the data to only be numeric.

First you'll learn how to populate and view datasets, then you'll learn different ways to query and project the parts of the...

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