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Clojure for Data Science

You're reading from  Clojure for Data Science

Product type Book
Published in Sep 2015
Publisher
ISBN-13 9781784397180
Pages 608 pages
Edition 1st Edition
Languages
Author (1):
Henry Garner Henry Garner
Profile icon Henry Garner

Table of Contents (18) Chapters

Clojure for Data Science
Credits
About the Author
Acknowledgments
About the Reviewer
www.PacktPub.com
Preface
1. Statistics 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 [250 250])

Since we have 5 bins for...

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