Book Image

Graph Data Science with Neo4j

By : Estelle Scifo
5 (1)
Book Image

Graph Data Science with Neo4j

5 (1)
By: Estelle Scifo

Overview of this book

Neo4j, along with its Graph Data Science (GDS) library, is a complete solution to store, query, and analyze graph data. As graph databases are getting more popular among developers, data scientists are likely to face such databases in their career, making it an indispensable skill to work with graph algorithms for extracting context information and improving the overall model prediction performance. Data scientists working with Python will be able to put their knowledge to work with this practical guide to Neo4j and the GDS library that offers step-by-step explanations of essential concepts and practical instructions for implementing data science techniques on graph data using the latest Neo4j version 5 and its associated libraries. You’ll start by querying Neo4j with Cypher and learn how to characterize graph datasets. As you get the hang of running graph algorithms on graph data stored into Neo4j, you’ll understand the new and advanced capabilities of the GDS library that enable you to make predictions and write data science pipelines. Using the newly released GDSL Python driver, you’ll be able to integrate graph algorithms into your ML pipeline. By the end of this book, you’ll be able to take advantage of the relationships in your dataset to improve your current model and make other types of elaborate predictions.
Table of Contents (16 chapters)
1
Part 1 – Creating Graph Data in Neo4j
4
Part 2 – Exploring and Characterizing Graph Data with Neo4j
8
Part 3 – Making Predictions on a Graph

Computing the graph degree distribution

After the number of nodes and edges, the node’s degree is one of the first metrics to compute when studying a new graph. It tells us whether the edges are equally split across nodes or if some nodes monopolize almost all connections, leaving the others disconnected. Now that we’ve defined the node’s degree, we will learn how to compute it with Cypher and draw the distribution using the NeoDash graph application.

Definition of a node’s degree

The degree of a node is the number of links connected to this node. For undirected graphs, there is only one degree, since we just count all the edges connected to a given node. For directed graphs, we can compute the node’s degree in three different ways:

  • Incoming degree: We count only the edges pointing toward the node
  • Outgoing degree: We count only the edges pointing outward of the node
  • Total degree: We count all edges attached to a node, regardless...