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

Multi-plot example – scatterplot matrix plots


In this section, we will learn how to have several plots in the same figure.

The key new method that allows multiple plots in the same figure is fig.subplot(nrows, ncols, plotIndex). This method, an overloaded version of the fig.subplot method we have been using up to now, both sets the number of rows and columns in the figure and returns a specific subplot. It takes three arguments:

  • nrows: The number of rows of subplots in the figure

  • ncols: The number of columns of subplots in the figure

  • plotIndex: The index of the plot to return

Users familiar with MATLAB or matplotlib will note that the .subplot method is identical to the eponymous methods in these frameworks. This might seem a little complex, so let's look at an example (you will find the code for this in BreezeDemo.scala):

import breeze.plot._

def subplotExample {
  val data = HWData.load
  val fig = new Figure("Subplot example")

  // upper subplot: plot index '0' refers to the first plot...