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Time Series Indexing

You're reading from   Time Series Indexing Implement iSAX in Python to index time series with confidence

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781838821951
Length 248 pages
Edition 1st Edition
Languages
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Author (1):
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Mihalis Tsoukalos Mihalis Tsoukalos
Author Profile Icon Mihalis Tsoukalos
Mihalis Tsoukalos
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Table of Contents (11) Chapters Close

Preface 1. Chapter 1: An Introduction to Time Series and the Required Python Knowledge 2. Chapter 2: Implementing SAX FREE CHAPTER 3. Chapter 3: iSAX – The Required Theory 4. Chapter 4: iSAX – The Implementation 5. Chapter 5: Joining and Comparing iSAX Indexes 6. Chapter 6: Visualizing iSAX Indexes 7. Chapter 7: Using iSAX to Approximate MPdist 8. Chapter 8: Conclusions and Next Steps 9. Index 10. Other Books You May Enjoy

Implementing SAX

This chapter is about the Symbolic Aggregate Approximation (SAX) component of the iSAX index and is divided into two parts – the first part with the theoretical knowledge, and the second part with the code to compute SAX and the practical examples. At the end of the chapter, you will see how to calculate some handy statistical quantities that can give you a higher overview of your time series and plot a histogram of your data.

In this chapter, we will cover the following main topics:

  • The required theory
  • An introduction to SAX
  • Developing a Python package
  • Working with the SAX package
  • Counting the SAX representations of a time series
  • The tsfresh Python package
  • Creating a histogram of a time series
  • Calculating the percentiles of a time series
You have been reading a chapter from
Time Series Indexing
Published in: Jun 2023
Publisher: Packt
ISBN-13: 9781838821951
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