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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

Common igraph issues

While igraph is a powerful library for graph data and its analysis, much of its power comes from the fact that Python acts as an interface to igraph’s implementation behind the scenes, which is in C. Because of this, igraph comes with some quirks, which you need to bear in mind when using its features. In the following subsections we will take you through some common problems users come across when working with igraph in Python.

No nodes in the graph

Some graph and network science libraries in Python can be created directly from a list of tuples, an edgelist. In igraph, because of how node indexing is implemented in C, nodes have to be added to a Graph object before edges can connect them together. In the next steps, we will demonstrate this problem and the subsequent errors that arise:

  1. We can first read in edge data from musae_git_edges.csv as our example graph to load into igraph, using the inbuilt csv module. This file has headers, so we...
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