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Scala for Data Science

You're reading from   Scala for Data Science Leverage the power of Scala with different tools to build scalable, robust data science applications

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Product type Paperback
Published in Jan 2016
Publisher
ISBN-13 9781785281372
Length 416 pages
Edition 1st Edition
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Author (1):
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Pascal Bugnion Pascal Bugnion
Author Profile Icon Pascal Bugnion
Pascal Bugnion
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Table of Contents (17) Chapters Close

Preface 1. Scala and Data Science FREE CHAPTER 2. Manipulating Data with Breeze 3. Plotting with breeze-viz 4. Parallel Collections and Futures 5. Scala and SQL through JDBC 6. Slick – A Functional Interface for SQL 7. Web APIs 8. Scala and MongoDB 9. Concurrency with Akka 10. Distributed Batch Processing with Spark 11. Spark SQL and DataFrames 12. Distributed Machine Learning with MLlib 13. Web APIs with Play 14. Visualization with D3 and the Play Framework A. Pattern Matching and Extractors Index

Chapter 14. Visualization with D3 and the Play Framework

In the previous chapter, we learned about the Play framework, a web framework for Scala. We built an API that returns a JSON array describing a user's GitHub repositories.

In this chapter, we will construct a fully-fledged web application that displays a table and a chart describing a user's repositories. We will learn to integrate D3.js, a JavaScript library for building data-driven web pages, with the Play framework. This will set you on the path to building compelling interactive visualizations that showcase results obtained with machine learning.

This chapter assumes that you are familiar with HTML, CSS, and JavaScript. We present references at the end of the chapter. You should also have read the previous chapter.

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