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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

Summary

In this chapter, we learned the basics of time series, indexing, and distance functions. Although the theoretical knowledge included in this chapter remains valid and relevant no matter what programming language is used, alternative ways and packages to achieve the presented tasks in Python exist, as well as other programming languages. What remains unchanged is the validity of the approach – you must read a text file from disk in order to use its data, no matter the programming language – and the logical steps needed to perform a task, such as the visualization of a time series. This means that if you know an alternative way to load a text file from disk in Python, feel free to use it if it allows you to perform the next task at hand. If you are an amateur Python developer, I would suggest that you follow the book’s suggestions until you become more competent with Python. After all, the used Python packages are the most popular ones in the Python community...

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