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

Product type Paperback

Published in Jan 2026

Last Updated in Jul 2025

Publisher

ISBN-13 9781805124283

Length 98 pages

Edition 2nd Edition

Languages

Python

Concepts

Data Analysis

Author (1):

Tarek A. Atwan

View More author details

Table of Contents (13) Chapters

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

Providing a format argument to DateTime

When working with datasets extracted from different data sources, you may encounter date columns stored in string format, whether from files or databases. In the previous recipe, Working with DatetimeIndex, you explored the pandas.to_datetime() function that can parse various date formats with minimal input. However, you will want more granular control to ensure that the date is parsed correctly. For example, you will now be introduced to the strptime and strftime methods and see how you can specify formatting in pandas.to_datetime() to handle different date formats.

In this recipe, you will learn how to parse strings that represent dates to a datetime or date object (an instance of the class datetime.datetime or datetime.date).

How to do it…

Python's datetime module contains the strptime() method to create datetime or date from a string that contains a date. You will first explore how you can do this in Python and then extend this...