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Time Series Analysis with Python Cookbook

You're reading from   Time Series Analysis with Python Cookbook Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation

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Product type Paperback
Published in Apr 2025
Publisher
ISBN-13 9781805124283
Length 98 pages
Edition 2nd Edition
Languages
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Author (1):
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Tarek A. Atwan Tarek A. Atwan
Author Profile Icon Tarek A. Atwan
Tarek A. Atwan
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Table of Contents (13) Chapters Close

1. Time Series Analysis with Python Cookbook, Second Edition: Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation FREE CHAPTER
2. Getting Started with Time Series Analysis 3. Reading Time Series Data from Files 4. Reading Time Series Data from Databases 5. Persisting Time Series Data to Files 6. Persisting Time Series Data to Databases 7. Working with Date and Time in Python 8. Handling Missing Data 9. Outlier Detection Using Statistical Methods 10. Exploratory Data Analysis and Diagnosis 11. Building Univariate Time Series Models Using Statistical Methods 12. Additional Statistical Modeling Techniques for Time Series 13. Outlier Detection Using Unsupervised Machine Learning

Working with Unix epoch timestamps

Epoch timestamps, sometimes referred to as Unix time or POSIX time, are a common way to store datetime in an integer format. This integer represents the number of seconds elapsed from a reference point, and in the case of a Unix-based timestamp, the reference point is January 1, 1970, at midnight (00:00:00 UTC). This arbitrary date and time represent the baseline, starting at 0. So, we just increment in seconds for every second beyond that time.

Many databases, applications, and systems store dates and times in numeric format, making it mathematically easier to work with, convert, increment, decrement, and so on. Note that in the case of the Unix epoch, it is based on UTC, which stands for Universal Time Coordinated. Using UTC is a clear choice when building applications used globally, making it easier to store dates and timestamps in a standardized format. This makes it easier to work with dates and times without worrying about daylight saving or different...

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