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Apache Spark for Data Science Cookbook

You're reading from  Apache Spark for Data Science Cookbook

Product type Book
Published in Dec 2016
Publisher
ISBN-13 9781785880100
Pages 392 pages
Edition 1st Edition
Languages
Author (1):
Padma Priya Chitturi Padma Priya Chitturi
Profile icon Padma Priya Chitturi

Table of Contents (17) Chapters

Apache Spark for Data Science Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Big Data Analytics with Spark 2. Tricky Statistics with Spark 3. Data Analysis with Spark 4. Clustering, Classification, and Regression 5. Working with Spark MLlib 6. NLP with Spark 7. Working with Sparkling Water - H2O 8. Data Visualization with Spark 9. Deep Learning on Spark 10. Working with SparkR

Creating scatter plots with Bokeh-Scala


In this section, we'll take a brief look at the most popular visualizing framework in Python, called Bokeh, and use its (also fast-evolving) Scala bindings to the framework. Breeze also has a visualization API called breeze-viz, which is built on JFreeChart. Bokeh is backed by a JavaScript visualization library, called BokehJS. The Scala bindings library bokeh-scala not only gives an easier way to construct glyphs (lines, circles, and so on) out of Scala objects, but also translates glyphs into a format that is understandable by the BokehJS JavaScript components. The various terms in Bokeh actually mean the following:

  • Glyph: All geometric shapes that we can think of--circles, squares, lines, and so on - are glyphs. This is just the UI representation and doesn't hold any data. All the properties related to this object just help us modify the UI properties: color, x, y, width and so on.

  • Plot: A plot is like a canvas on which we arrange various objects...

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