Book Image

Java Data Analysis

By : John R. Hubbard
Book Image

Java Data Analysis

By: John R. Hubbard

Overview of this book

Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the aim of discovering useful information. Java is one of the most popular languages to perform your data analysis tasks. This book will help you learn the tools and techniques in Java to conduct data analysis without any hassle. After getting a quick overview of what data science is and the steps involved in the process, you’ll learn the statistical data analysis techniques and implement them using the popular Java APIs and libraries. Through practical examples, you will also learn the machine learning concepts such as classification and regression. In the process, you’ll familiarize yourself with tools such as Rapidminer and WEKA and see how these Java-based tools can be used effectively for analysis. You will also learn how to analyze text and other types of multimedia. Learn to work with relational, NoSQL, and time-series data. This book will also show you how you can utilize different Java-based libraries to create insightful and easy to understand plots and graphs. By the end of this book, you will have a solid understanding of the various data analysis techniques, and how to implement them using Java.
Table of Contents (20 chapters)
Java Data Analysis
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Index

Generating test datasets


Generating numerical test data is easy with Java. It boils down to using a java.util.Random object to generate random numbers.

Listing 2-13 Generating random numeric data

This program generates the following CSV file of eight rows and five columns of random decimal values.

Figure 2-9 Test data file

Metadata

Metadata is data about data. For example, the preceding generated file could be described as eight lines of comma-separated decimal numbers, five per line. That's metadata. It's the kind of information you would need, for example, to write a program to read that file.

That example is quite simple: the data is unstructured and the values are all the same type. Metadata about structured data must also describe that structure.

The metadata of a dataset may be included in the same file as the data itself. The preceding example could be modified with a header line like this:

Figure 2-10 Test data file fragment with metadata in header

Note

When reading a data file in Java, you...