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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

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

Technical requirements

In this chapter, you will be primarily using the command line. For macOS and Linux, this will be the default Terminal (bash or zsh), while on a Windows OS, you will use the Anaconda Prompt, which comes as part of the Anaconda or Miniconda installation. Installing Anaconda or Miniconda will be discussed in the following Getting ready section.

We will use Visual Studio Code for the IDE, which is available for free at https://code.visualstudio.com. It supports Linux, Windows, and macOS.

Other valid alternative options that will allow you to follow along include the following:

Sublime Text at https://www.sublimetext.com
Spyder at https://www.spyder-ide.org
PyCharm Community Edition at https://www.jetbrains.com/pycharm/download/
Jupyter Notebook at https://jupyter.org

The source code for this chapter is available at https://github.com/PacktPublishing/Time-Series-Analysis-with-Python-Cookbook

The rest of the chapter is locked

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Authors (1)

Tarek A. Atwan

Tarek A. Atwan

Tarek A. Atwan is a data analytics expert with over 16 years of international consulting experience, providing subject matter expertise in data science, machine learning operations, data engineering, and business intelligence. He has taught multiple hands-on coding boot camps, courses, and workshops on various topics, including data science, data visualization, Python programming, time series forecasting, and blockchain at various universities in the United States. He is regarded as a data science mentor and advisor, working with executive leaders in numerous industries to solve complex problems using a data-driven approach.

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