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Python Real-World Projects

You're reading from   Python Real-World Projects Craft your Python portfolio with deployable applications

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Product type Paperback
Published in Sep 2023
Publisher Packt
ISBN-13 9781803246765
Length 478 pages
Edition 1st Edition
Languages
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Author (1):
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Steven F. Lott Steven F. Lott
Author Profile Icon Steven F. Lott
Steven F. Lott
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Table of Contents (20) Chapters Close

Preface 1. Chapter 1: Project Zero: A Template for Other Projects 2. Chapter 2: Overview of the Projects FREE CHAPTER 3. Chapter 3: Project 1.1: Data Acquisition Base Application 4. Chapter 4: Data Acquisition Features: Web APIs and Scraping 5. Chapter 5: Data Acquisition Features: SQL Database 6. Chapter 6: Project 2.1: Data Inspection Notebook 7. Chapter 7: Data Inspection Features 8. Chapter 8: Project 2.5: Schema and Metadata 9. Chapter 9: Project 3.1: Data Cleaning Base Application 10. Chapter 10: Data Cleaning Features 11. Chapter 11: Project 3.7: Interim Data Persistence 12. Chapter 12: Project 3.8: Integrated Data Acquisition Web Service 13. Chapter 13: Project 4.1: Visual Analysis Techniques 14. Chapter 14: Project 4.2: Creating Reports 15. Chapter 15: Project 5.1: Modeling Base Application 16. Chapter 16: Project 5.2: Simple Multivariate Statistics 17. Chapter 17: Next Steps 18. Other Books You Might Enjoy 19. Index

Chapter 4
Data Acquisition Features: Web APIs and Scraping

Data analysis often works with data from numerous sources, including databases, web services, and files prepared by other applications. In this chapter, you will be guided through two projects to add additional data sources to the baseline application from the previous chapter. These new sources include a web service query, and scraping data from a web page.

This chapter’s projects cover the following essential skills:

  • Using the requests package for Web API integration. We’ll look at the Kaggle API, which requires signing up to create an API token.

  • Using the Beautiful Soup package to parse an HTML web page.

  • Adding features to an existing application and extending the test suite to cover these new alternative data sources.

It’s important to recognize this application has a narrow focus on data acquisition. In later chapters, we’ll validate the data and convert it to a more useful form. This reflects...

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