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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

11.1 Description

In the previous chapters, particularly those starting with Chapter 9, Project 3.1: Data Cleaning Base Application, the question of ”persistence” was dealt with casually. The previous chapters all wrote the cleaned samples into a file in ND JSON format. This saved delving into the alternatives and the various choices available. It’s time to review the previous projects and consider the choice of file format for persistence.

What’s important is the overall flow of data from acquisition to analysis. The conceptual flow of data is shown in Figure 11.1.

Figure 11.1: Data Analysis Pipeline
Figure 11.1: Data Analysis Pipeline

This differs from the diagram shown in Chapter 2, Overview of the Projects, where the stages were not quite as well defined. Some experience with acquiring and cleaning data helps to clarify the considerations around saving and working with data.

The diagram shows a few of the many choices for persisting interim data. A more complete list of...

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