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Graph Data Science with Neo4j

You're reading from  Graph Data Science with Neo4j

Product type Book
Published in Jan 2023
Publisher Packt
ISBN-13 9781804612743
Pages 288 pages
Edition 1st Edition
Languages
Author (1):
Estelle Scifo Estelle Scifo
Profile icon Estelle Scifo

Table of Contents (16) Chapters

Preface 1. Part 1 – Creating Graph Data in Neo4j
2. Chapter 1: Introducing and Installing Neo4j 3. Chapter 2: Importing Data into Neo4j to Build a Knowledge Graph 4. Part 2 – Exploring and Characterizing Graph Data with Neo4j
5. Chapter 3: Characterizing a Graph Dataset 6. Chapter 4: Using Graph Algorithms to Characterize a Graph Dataset 7. Chapter 5: Visualizing Graph Data 8. Part 3 – Making Predictions on a Graph
9. Chapter 6: Building a Machine Learning Model with Graph Features 10. Chapter 7: Automatically Extracting Features with Graph Embeddings for Machine Learning 11. Chapter 8: Building a GDS Pipeline for Node Classification Model Training 12. Chapter 9: Predicting Future Edges 13. Chapter 10: Writing Your Custom Graph Algorithms with the Pregel API in Java 14. Index 15. Other Books You May Enjoy

Visualizing a small graph with networkx and matplotlib

When the graph is small enough, such as the ones represented in the previous screenshots (Figure 5.2 and 5.3), it can be convenient to visualize them using the matplotlib plotting library. In this section, we are going to reproduce the visualizations displayed previously.

When dealing with graphs in Python, fortunately, we do not have to create our own data structure and implement our algorithms. As with many other tasks, we can just pip install a package developed by the fantastic open source community around Python. For graphs, the most used package is called networkx. Let’s go ahead and go through our next Jupyter notebook.

Visualizing a graph with known coordinates

In this section, we are going to draw a graph representing a part of the road network around the Colosseum in Rome. This data was extracted using the osmnx package, but we are not going to detail its extraction process here, even if osmnx makes it...

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