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Java Data Analysis

You're reading from   Java Data Analysis Data mining, big data analysis, NoSQL, and data visualization

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787285651
Length 412 pages
Edition 1st Edition
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Author (1):
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John R. Hubbard John R. Hubbard
Author Profile Icon John R. Hubbard
John R. Hubbard
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Data Analysis FREE CHAPTER 2. Data Preprocessing 3. Data Visualization 4. Statistics 5. Relational Databases 6. Regression Analysis 7. Classification Analysis 8. Cluster Analysis 9. Recommender Systems 10. NoSQL Databases 11. Big Data Analysis with Java A. Java Tools Index

Data points and datasets


In data analysis, it is convenient to think of the data as points of information. For example, in a collection of biographical data, each data point would contain information about one person. Consider the following data point:

("Adams", "John", "M", 26, 704601929)

It could represent a 26-year-old male named John Adams with ID number 704601929.

We call the individual data values in a data point fields (or attributes). Each of these values has its own type. The preceding example has five fields: three text and two numeric.

The sequence of data types for the fields of a data point is called its type signature. The type signature for the preceding example is (text, text, text, numeric, numeric). In Java, that type signature would be (String, String, String, int, int).

A dataset is a set of data points, all of which have the same type signature. For example, we could have a dataset that represents a group of people, each point representing a unique member of the group. Since...

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