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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

Using Quil for visualization

Quil (https://github.com/quil/quil) is a Clojure library that provides an enormous amount of flexibility to produce custom visualizations. It wraps Processing (https://processing.org/), a Java framework that's been actively developed for many years by visual artists and designers, which aims promote "software literacy in visual arts and visual literacy within technology".

Any visualization done with Quil involves creating a sketch. A sketch is processing's term for a running a program that consists of drawing instructions. Most API functions are available from the quil.core namespace. We'll include it in our code as q. Calling q/sketch without any arguments will cause an empty window to pop up (although it may be obscured by other windows).

Drawing to the sketch window

The default window size is 500px by 300px. We'd like our two-dimensional histogram to be square, so let's make the window 250px in both directions:

(q/sketch :size...
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