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Time Series Analysis with Python Cookbook

You're reading from  Time Series Analysis with Python Cookbook

Product type Book
Published in Jun 2022
Publisher Packt
ISBN-13 9781801075541
Pages 630 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Tarek A. Atwan Tarek A. Atwan
Profile icon Tarek A. Atwan

Table of Contents (18) Chapters

Preface Chapter 1: Getting Started with Time Series Analysis Chapter 2: Reading Time Series Data from Files Chapter 3: Reading Time Series Data from Databases Chapter 4: Persisting Time Series Data to Files Chapter 5: Persisting Time Series Data to Databases Chapter 6: Working with Date and Time in Python Chapter 7: Handling Missing Data Chapter 8: Outlier Detection Using Statistical Methods Chapter 9: Exploratory Data Analysis and Diagnosis Chapter 10: Building Univariate Time Series Models Using Statistical Methods Chapter 11: Additional Statistical Modeling Techniques for Time Series Chapter 12: Forecasting Using Supervised Machine Learning Chapter 13: Deep Learning for Time Series Forecasting Chapter 14: Outlier Detection Using Unsupervised Machine Learning Chapter 15: Advanced Techniques for Complex Time Series Index Other Books You May Enjoy

Technical requirements

You can download the Jupyter notebooks and the requisite datasets from the GitHub repository to follow along:

In this chapter and beyond, you will extensively use pandas 1.4.2 (released April 2, 2022). There will be four additional libraries that you will be using:

  • NumPy (≥ 1.20.3)
  • Matplotlib (≥ 3.5.0)
  • statsmodels (≥ 0.11.0)
  • scikit-learn (≥ 1.0.1)
  • SciPy (≥ 1.7.1)

If you are using pip, then you can install these packages from your terminal with the following command:

pip install matplotlib numpy statsmodels scikit-learn scipy

If you are using conda, then you can install these packages with the following command:

conda install matplotlib...
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