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

Forecasting univariate time series data with exponential smoothing

In this recipe, you will explore the exponential smoothing technique using the statsmodels library, which offers functionality similar to popular implementations from the R forecast package, such as ets() and HoltWinters(). In statsmodels, there are three different implementations (classes) of exponential smoothing, depending on the nature of the data you are working with:

SimpleExpSmoothing: Simple exponential smoothing is used when the time series process lacks seasonality and trend. This is also referred to as single exponential smoothing.
Holt: Holt's exponential smoothing is an enhancement of the simple exponential smoothing and is used when the time series process contains only trend (but no seasonality). It is referred to as double exponential smoothing.
ExponentialSmoothing: Holt-Winters' exponential smoothing is an enhancement of Holt's exponential smoothing and is used when the time series process...

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

Table of Contents (13) Chapters

Forecasting univariate time series data with exponential smoothing

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

Table of Contents (13) Chapters

Forecasting univariate time series data with exponential smoothing

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