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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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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

Creating scatter plots with NVD3

If you've been following along from the previous recipes in this chapter, you'll now have a complete web application stack ready, and you can use it to create charts and graphs for the Web.

For this recipe, we'll create a scatter plot of the US census racial data that we saw in Chapter 6, Workin with Incanter DataSets, in the Grouping data with $group-by recipe. In fact, this will be the same recipe as we saw in Chapter 10, Working with Unstructured and Textual Data, only this time we'll create a web page.

To do this, we'll use the D3 JavaScript library (http://d3js.org/). D3 stands for Data-Driven Documents, and this library makes it easy to load data and create HTML and SVG structures from data. You can use it to transform data into tables or charts. It is pretty low-level though. With D3, we will create many of the actual elements. We'll do this in a later recipe, but for now, we'll use the NVD3 library (http://nvd3.org...

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