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

Visualizing Graph Data

Graphs are special objects. Unlike images, there is no simple way to visualize them. The preceding chapters have demonstrated how we can extract information from a graph dataset: node importance using centrality metrics (for example, degree) or node clusters with community detection algorithms (for example, the Louvain algorithm). We have also already used some tools to visualize the content of our graph: neodash to draw charts from data stored in Neo4j, and Neo4j Browser, which is able to draw a graph with nodes and relationships in a dynamic way. Neo4j Browser is very convenient to see the result of a Cypher query, but it is not intended for data analysis visualization. Typically, it does not let us configure node color based on a node property.

In this chapter, we will focus on graph data visualization. We will first learn why it is challenging and what the graph visualization techniques are. We will first create static but customizable images of a graph...