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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 Jun 2022
Publisher Packt
ISBN-13 9781801075541
Length 630 pages
Edition 1st Edition
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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 (18) Chapters Close

Preface 1. Chapter 1: Getting Started with Time Series Analysis 2. Chapter 2: Reading Time Series Data from Files FREE CHAPTER 3. Chapter 3: Reading Time Series Data from Databases 4. Chapter 4: Persisting Time Series Data to Files 5. Chapter 5: Persisting Time Series Data to Databases 6. Chapter 6: Working with Date and Time in Python 7. Chapter 7: Handling Missing Data 8. Chapter 8: Outlier Detection Using Statistical Methods 9. Chapter 9: Exploratory Data Analysis and Diagnosis 10. Chapter 10: Building Univariate Time Series Models Using Statistical Methods 11. Chapter 11: Additional Statistical Modeling Techniques for Time Series 12. Chapter 12: Forecasting Using Supervised Machine Learning 13. Chapter 13: Deep Learning for Time Series Forecasting 14. Chapter 14: Outlier Detection Using Unsupervised Machine Learning 15. Chapter 15: Advanced Techniques for Complex Time Series 16. Index 17. Other Books You May Enjoy

Detecting outliers with PyCaret

In this recipe, you will explore PyCaret for outlier detection. PyCaret (https://pycaret.org) is positioned as "an open-source, low-code machine learning library in Python that automates machine learning workflows". PyCaret acts as a wrapper for PyOD, which you used earlier in the previous recipes for outlier detection. What PyCaret does is simplify the entire process for rapid prototyping and testing with a minimal amount of code.

You will use PyCaret to examine multiple outlier detection algorithms, similar to the ones you used in earlier recipes, and see how PyCaret simplifies the process for you.

Getting ready

The recommended way to explore PyCaret is to create a new virtual Python environment just for PyCaret so it can install all the required dependencies without any conflicts or issues with your current environment. If you need a quick refresher on how to create a virtual Python environment, check out the Development environment...

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