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

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 setup...

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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

Detecting outliers with PyCaret

Getting ready

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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

Detecting outliers with PyCaret

Getting ready

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