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 Jun 2022

Publisher Packt

ISBN-13 9781801075541

Length 630 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Data Analysis

Author (1):

Tarek A. Atwan

View More author details

Table of Contents (18) Chapters

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

Why subscribe?

17. Other Books You May Enjoy

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 installation. Installing Anaconda 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 3 at https://www.sublimetext.com/3
Atom at https://atom.io/
PyCharm Community Edition at https://www.jetbrains.com/pycharm/download/

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

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 (18) Chapters

Technical requirements

Authors (1)

Personalised recommendations for you

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 (18) Chapters

Technical requirements

Unlock this book and the full library FREE for 7 days

Authors (1)

Personalised recommendations for you