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Hands-On Data Analysis with Scala

You're reading from  Hands-On Data Analysis with Scala

Product type Book
Published in May 2019
Publisher Packt
ISBN-13 9781789346114
Pages 298 pages
Edition 1st Edition
Languages
Author (1):
Rajesh Gupta Rajesh Gupta
Profile icon Rajesh Gupta

Table of Contents (14) Chapters

Preface 1. Section 1: Scala and Data Analysis Life Cycle
2. Scala Overview 3. Data Analysis Life Cycle 4. Data Ingestion 5. Data Exploration and Visualization 6. Applying Statistics and Hypothesis Testing 7. Section 2: Advanced Data Analysis and Machine Learning
8. Introduction to Spark for Distributed Data Analysis 9. Traditional Machine Learning for Data Analysis 10. Section 3: Real-Time Data Analysis and Scalability
11. Near Real-Time Data Analysis Using Streaming 12. Working with Data at Scale 13. Another Book You May Enjoy

Enriching

Data enrichment is the act of adding more information to raw data. Some examples of the enrichments are as follows:

  • Adding missing values
  • Adding lookup values
  • Joining with other datasets
  • Filtering
  • Aggregating

Continuing on the same example of using Person, let's say that the state element is optional. Given the zip information, we should be able to derive the value of state. In this specific case, we are performing the following two enrichments:

  • Looking up or deriving the value of state based on the zip value
  • Adding missing state value

Let's define a simple Scala function to map a US zip code to state. Please refer to Wikipedia (https://en.wikipedia.org/wiki/List_of_ZIP_code_prefixes) for more info on US ZIP codes:

  1. Define a Scala case class called Person with a method called cleanCopy to provide a clean copy of the object:
scala> case class Person...
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