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

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

Detecting outliers using COPOD

COPOD is an exciting algorithm based on a paper published in September 2020, which you can read here: https://arxiv.org/abs/2009.09463.

The PyOD library offers many algorithms based on the latest research papers, which can be broken down into linear models, proximity-based models, probabilistic models, ensembles, and neural networks.

COPOD falls under probabilistic models and is labeled as a parameter-free algorithm. The only parameter it takes is the contamination factor, which defaults to 0.1. The COPOD algorithm is inspired by statistical methods, making it a fast and highly interpretable model. The algorithm is based on copula, a function generally used to model dependence between independent random variables that are not necessarily normally distributed. In time series forecasting, copulas have been used in univariate and multivariate forecasting, which is popular in financial risk modeling. The term copula stems from the copula function joining (coupling...