Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
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

Arrow left icon
Product type Paperback
Published in Apr 2025
Publisher
ISBN-13 9781805124283
Length 98 pages
Edition 2nd Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Tarek A. Atwan Tarek A. Atwan
Author Profile Icon Tarek A. Atwan
Tarek A. Atwan
Arrow right icon
View More author details
Toc

Table of Contents (13) Chapters Close

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

Development environment setup

As we dive into the various recipes provided in this book, you will be creating different Python virtual environments to install all your dependencies without impacting other Python projects.

You can think of a virtual environment as isolated buckets or folders, each with a Python interpreter and associated libraries. The following diagram illustrates the concept behind isolated, self-contained virtual environments, each with a different Python interpreter and different versions of packages and libraries installed:

Figure 1.1: An example of three different Python virtual environments, one for each Python project

If you installed Anaconda then these environments are typically stored and contained in separate folders inside the envs subfolder within the main Anaconda (or Miniconda) folder installation. As an example, on macOS, you can find the envs folder under Users/<yourusername>/opt/anaconda3/envs/. On Windows OS, it may look more like C:\Users\...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime