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

Installing JupyterLab and JupyterLab extensions

Throughout this book, you can follow along using your favorite Python IDE (for example, PyCharm or Spyder) or text editor (for example, Visual Studio Code, Atom, or Sublime). There is another option based on the concept of notebooks that allows interactive learning through a web interface. More specifically, Jupyter Notebook or Jupyter Lab are the preferred methods for learning, experimenting, and following along with the recipes in this book. Interestingly, the name Jupyter is derived from the three programming languages: Julia, Python, and R. Alternatively, you can use Google's Colab, or Kaggle Notebooks. For more information, refer to the See also section from the Development environment setup recipe of this chapter. If you are not familiar with Jupyter Notebooks, you can get more information here: https://jupyter.org/.

In this recipe, you will install Jupyter Notebook, JupyterLab, and additional JupyterLab extensions.

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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

Installing JupyterLab and JupyterLab extensions

Authors (1)

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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

Installing JupyterLab and JupyterLab extensions

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Authors (1)

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