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Graph Data Modeling in Python

You're reading from   Graph Data Modeling in Python A practical guide to curating, analyzing, and modeling data with graphs

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781804618035
Length 236 pages
Edition 1st Edition
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Authors (2):
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Gary Hutson Gary Hutson
Author Profile Icon Gary Hutson
Gary Hutson
Matt Jackson Matt Jackson
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Matt Jackson
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Table of Contents (16) Chapters Close

Preface 1. Part 1: Getting Started with Graph Data Modeling
2. Chapter 1: Introducing Graphs in the Real World FREE CHAPTER 3. Chapter 2: Working with Graph Data Models 4. Part 2: Making the Graph Transition
5. Chapter 3: Data Model Transformation – Relational to Graph Databases 6. Chapter 4: Building a Knowledge Graph 7. Part 3: Storing and Productionizing Graphs
8. Chapter 5: Working with Graph Databases 9. Chapter 6: Pipeline Development 10. Chapter 7: Refactoring and Evolving Schemas 11. Part 4: Graphing Like a Pro
12. Chapter 8: Perfect Projections 13. Chapter 9: Common Errors and Debugging 14. Index 15. Other Books You May Enjoy

Working with Graph Data Models

This chapter will move you toward taking what you have learned hitherto and moving from a business problem through to how to obtain the data and then to getting that data graph ready. In this chapter, the aim is to teach you the fundamental skills needed to start working with graph data models at pace.

It will focus on many of the key skills to get up to speed with working with graph data models and many of the attributes of a graph structure. In the following sections, the aim will be to get you familiar with igraph and how to use it to ingest data into your graph.

From there, we'll move on to building your understanding of how to model nodes and edges in a graph. This will culminate in working on a use case to cement and reinforce what you will learn in this chapter.

The use case will touch on the key techniques needed to model a graph structure and what is meant by degree centrality.

In this chapter, we’re going to cover the...

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