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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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Toc

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

Our recommendation system

Now that we have our data in a Python graph, let’s go one step further and design a more robust recommendation process, typically carried out with graph data.

Let’s take on the role of a solutions engineer or data scientist and write a game recommendation system based on our Steam data. Recommendation systems are used heavily in customer-facing applications, to show the user a product that they may be interested in. Product recommendations are often based on what behaviorally similar users have played and purchased.

Generic MySQL to igraph methods

This time, we will write a set of reusable, generic methods to create an igraph graph from columns in a MySQL table. The functions will be designed to create a heterogeneous, bipartite, directed graph, given a set of column names.

Let’s start by writing a main function, mysql_to_graph(). The method will need to accept a MySQL table name, the table, source, and target column names...

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