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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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Toc

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

You probably won't spend as much time to get the data as you will in trying to get it into shape. Raw data is often inconsistent, duplicated, or full of holes. Addresses might be missing, years and dates might be formatted in a thousand different ways, or names might be entered into the wrong fields. You'll have to fix these issues before the data is usable.

This is often an iterative, interactive process. If it's a very large dataset, I might create a sample to work with at this stage. Generally, I start by examining the data files. Once I find a problem, I try to code a solution, which I run on the dataset. After each change, I archive the data, either using a ZIP file or, if the data files are small enough, a version control system. Using a version control system is a good option because I can track the code to transform the data along with the data itself and I can also include comments about what I'm doing. Then, I take a look at the data again, and...

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