Book Image

Scala for Data Science

By : Pascal Bugnion
Book Image

Scala for Data Science

By: Pascal Bugnion

Overview of this book

Scala is a multi-paradigm programming language (it supports both object-oriented and functional programming) and scripting language used to build applications for the JVM. Languages such as R, Python, Java, and so on are mostly used for data science. It is particularly good at analyzing large sets of data without any significant impact on performance and thus Scala is being adopted by many developers and data scientists. Data scientists might be aware that building applications that are truly scalable is hard. Scala, with its powerful functional libraries for interacting with databases and building scalable frameworks will give you the tools to construct robust data pipelines. This book will introduce you to the libraries for ingesting, storing, manipulating, processing, and visualizing data in Scala. Packed with real-world examples and interesting data sets, this book will teach you to ingest data from flat files and web APIs and store it in a SQL or NoSQL database. It will show you how to design scalable architectures to process and modelling your data, starting from simple concurrency constructs such as parallel collections and futures, through to actor systems and Apache Spark. As well as Scala’s emphasis on functional structures and immutability, you will learn how to use the right parallel construct for the job at hand, minimizing development time without compromising scalability. Finally, you will learn how to build beautiful interactive visualizations using web frameworks. This book gives tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed with building data science and data engineering solutions.
Table of Contents (22 chapters)
Scala for Data Science
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Drawing plots with NVD3


D3 is a library that offers low-level components for building interactive visualizations in JavaScript. By offering the low-level components, it gives a huge degree of flexibility to the developer. The learning curve can, however, be quite steep. In this example, we will use NVD3, a library which provides pre-made graphs for D3. This can greatly speed up initial development. We will place the code in the file repoGraph.js and expose a single method, build, which takes, as arguments, a model and a div and draws a pie chart in that div. The pie chart will aggregate language use across all the user's repositories.

The code for generating a pie chart is nearly identical to the example given in the NVD3 documentation, available at http://nvd3.org/examples/pie.html. The data passed to the graph must be available as an array of objects. Each object must contain a label field and a size field. The label field identifies the language, and the size field is the total size of...