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Python Real-World Projects

You're reading from  Python Real-World Projects

Product type Book
Published in Sep 2023
Publisher Packt
ISBN-13 9781803246765
Pages 478 pages
Edition 1st Edition
Languages
Author (1):
Steven F. Lott Steven F. Lott
Profile icon Steven F. Lott

Table of Contents (20) Chapters

Preface 1. Chapter 1: Project Zero: A Template for Other Projects 2. Chapter 2: Overview of the Projects 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

16.1 Description

In Chapter 15, Project 5.1: Modeling Base Application we created an application to create a summary document with some core statistics. In that application, we looked at univariate statistics to characterize the data distributions. These statistics included measurements of the location, spread, and shape of a distribution. Functions like mean, median, mode, variance, and standard deviation were emphasized as ways to understand location and spread. The characterization of shape via skewness and kurtosis was left as an extra exercise for you.

The base application from the previous chapter needs to be expanded to include the multivariate statistics and diagrams that are essential for clarifying the relationships among variables. There are a vast number of possible functions to describe the relationships among two variables. See https://www.itl.nist.gov/div898/handbook/pmd/section8/pmd8.htm for some insight into the number of choices available.

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