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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

Visualization for communication

In the course of our work as data scientists, we may find ourselves needing to communicate with a wide variety of people. Our close colleagues and managers may be able to read and interpret our Incanter charts, but they're unlikely to impress the CEO. We may also have a role that requires us to communicate with the general public.

In either case, we should focus on making visualizations that are simple and powerful, but which don't sacrifice the integrity of the data. A lack of statistical training is no barrier to being able to understand subtle and nuanced arguments and we should respect our audience's intelligence. The challenge for us as data scientists is to find a representation that conveys the message effectively to them.

For the remainder of this chapter, we'll work on a visualization that aims to communicate a more complex set of data in a succinct and faithful way.

Note

The visualization we're going to create is a version of...

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