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Clojure for Data Science

You're reading from   Clojure for Data Science Statistics, big data, and machine learning for Clojure programmers

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Product type Paperback
Published in Sep 2015
Publisher
ISBN-13 9781784397180
Length 608 pages
Edition 1st Edition
Languages
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Author (1):
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Henry Garner Henry Garner
Author Profile Icon Henry Garner
Henry Garner
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Table of Contents (12) Chapters Close

Preface 1. Statistics FREE CHAPTER 2. Inference 3. Correlation 4. Classification 5. Big Data 6. Clustering 7. Recommender Systems 8. Network Analysis 9. Time Series 10. Visualization Index

Chapter 10. Visualization

 

"Numbers have an important story to tell. They rely on you to give them a clear and convincing voice."

 
 --Stephen Few

Every chapter in this book has made use of visualization in some way, primarily using Incanter. Incanter is an effective tool to produce a wide variety of charts as we work, and these are often the ones we'll reach out for first while trying to understand a dataset. This initial phase is often called exploratory data analysis and, at this stage, we're interested in summarizing statistics such as the distribution of numerical data, the counts of the categorical data, and how the attributes in our data are correlated.

Having found a meaningful way to interpret data, we'll often want to communicate it to others. One of the most important tools for communication is visualization, and we may be required to convey subtle or complicated ideas to people without a strong analytical background. In this chapter...

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