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 Apr 2025

Publisher

ISBN-13 9781805124283

Length 98 pages

Edition 2nd Edition

Languages

Python

Concepts

Data Analysis

Author (1):

Tarek A. Atwan

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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

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So far, we have covered techniques to extract data from various sources. This was covered in Chapter 2, Reading Time Series Data from Files, and Chapter 3, Reading Time Series Data from Databases. Chapter 6, Working with Date and Time in Python, and Chapter 7, Handling Missing Data, covered several techniques to help prepare, clean, and adjust data.

You will continue to explore additional techniques to better understand the time series process behind the data. Before modeling the data or doing any further analysis, an important step is to inspect the data at hand. More specifically, there are specific time series characteristics that you need to check for, such as stationarity, effects of trend and seasonality, and autocorrelation, to name a few. These characteristics that describe the time series process you are working with need to be combined with domain knowledge behind the process itself.

This chapter will build on what...