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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

Installing and using the Neo4j Python driver

We can use the Neo4j Python driver to fetch data from Neo4j and analyze it from Python. In this section, we are going to plot the degree distribution using Python visualization packages.

Counting node labels and relationship types in Python

Let’s open the Neo4j_Driver notebook (https://github.com/PacktPublishing/Graph-Data-Science-with-Neo4J/blob/main/Chapter03/notebooks/Neo4j_Driver.ipynb). To install the Neo4j driver, run the following code in the first cell:

!pip install neo4j

Let’s instantiate the driver and fetch our first bit of data from Neo4j:

  1. First, import the required objects:
    from collections import defaultdict
    from neo4j import GraphDatabase
  2. Then, instantiate a driver object, providing it with the connection parameters:
    driver = GraphDatabase.driver(
        "bolt://localhost:7687",
        auth=("neo4j", "<PASSWORD>")
    )
  3. With...
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