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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 time deltas

When working with time-series data, you may need to perform some calculations on your datetime columns, such as adding or subtracting. Examples can include adding 30 days to purchase datetime to determine when the return policy expires for a product or when a warranty ends. For example, the Timedelta class makes it possible to derive new datetime objects by adding or subtracting at different ranges or increments, such as seconds, daily, and weekly. This includes time zone-aware calculations.

In this recipe, you will explore two practical approaches in pandas to capture date/time differences – the pandas.Timedelta class and the pandas.to_timedelta function.

How to do it…

In this recipe, you will work with hypothetical sales data for a retail store. You will generate the sales DataFrame, which will contain items purchased from the store and the purchase date. You will then explore different scenarios using the Timedelta class and the to_timedelta...

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