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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

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Product type Paperback
Published in Jun 2022
Publisher Packt
ISBN-13 9781801075541
Length 630 pages
Edition 1st Edition
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Author (1):
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Tarek A. Atwan Tarek A. Atwan
Author Profile Icon Tarek A. Atwan
Tarek A. Atwan
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Table of Contents (18) Chapters Close

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 17. Other Books You May Enjoy

Reading third-party financial data using APIs

In this recipe, you will use a very useful library, pandas-datareader, which provides remote data access so that you can extract data from multiple data sources, including Yahoo Finance, Quandl, and Alpha Vantage, to name a few. The library not only fetches the data but also returns the data as a pandas DataFrame and the index as a DatetimeIndex.

Getting ready

For this recipe, you will need to install pandas-datareader.

To install it using conda, run the following command:

>>> conda install -c anaconda pandas-datareader -y

To install it using pip, run the following command:

>>> pip install pandas-datareader 

How to do it…

In this recipe, you will use the Yahoo API to pull stock data for Microsoft and Apple. Let's get started:

  1. Let's start by importing the necessary libraries:
    import pandas as pd
    import datetime
    import matplotlib.pyplot as plt
    import pandas_datareader.data...
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