You're reading from Graph Data Science with Neo4j Learn how to use Neo4j 5 with Graph Data Science library 2.0 and its Python driver for your project

Product type Paperback

Published in Jan 2023

Publisher Packt

ISBN-13 9781804612743

Length 288 pages

Edition 1st Edition

Languages

Python

Tools

Neo4j

Concepts

Data Science

Author (1):

Estelle Scifo

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Table of Contents (16) Chapters

Preface

1. Part 1 – Creating Graph Data in Neo4j

2. Chapter 1: Introducing and Installing Neo4j FREE CHAPTER

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

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Characterizing a Graph Dataset

Two graphs can differ in many ways, depending on their number of nodes or types of edges, for instance. But many more metrics exist to characterize them so that we can get an idea of the graph based on some numbers. Just as the mean value and standard deviation help in comprehending a numeric variable distribution, graph metrics help in understanding the graph topology: is it a highly connected graph? Are there isolated nodes?

In this chapter, we are going to learn about a few metrics for characterizing a graph. Focusing on the degree and degree distribution, this will be an opportunity for us to draw our first plot using the NeoDash graph application. We will also use the Neo4j Python driver to extract data from Neo4j into a DataFrame and perform some basic analysis of this data.

In this chapter, we’re going to cover the following main topics:

Characterizing a graph from its node and edge properties
Computing the graph degree...

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You're reading from Graph Data Science with Neo4j Learn how to use Neo4j 5 with Graph Data Science library 2.0 and its Python driver for your project

Table of Contents (16) Chapters

Characterizing a Graph Dataset

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Authors (2)