Book Image

Graph Data Modeling in Python

By : Gary Hutson, Matt Jackson
Book Image

Graph Data Modeling in Python

By: Gary Hutson, Matt Jackson

Overview of this book

Graphs have become increasingly integral to powering the products and services we use in our daily lives, driving social media, online shopping recommendations, and even fraud detection. With this book, you’ll see how a good graph data model can help enhance efficiency and unlock hidden insights through complex network analysis. Graph Data Modeling in Python will guide you through designing, implementing, and harnessing a variety of graph data models using the popular open source Python libraries NetworkX and igraph. Following practical use cases and examples, you’ll find out how to design optimal graph models capable of supporting a wide range of queries and features. Moreover, you’ll seamlessly transition from traditional relational databases and tabular data to the dynamic world of graph data structures that allow powerful, path-based analyses. As well as learning how to manage a persistent graph database using Neo4j, you’ll also get to grips with adapting your network model to evolving data requirements. By the end of this book, you’ll be able to transform tabular data into powerful graph data models. In essence, you’ll build your knowledge from beginner to advanced-level practitioner in no time.
Table of Contents (16 chapters)
Part 1: Getting Started with Graph Data Modeling
Part 2: Making the Graph Transition
Part 3: Storing and Productionizing Graphs
Part 4: Graphing Like a Pro

The most popular TV show – a real-world use case

In this section, we will be taking on the very fortunate position or role of a Facebook data scientist to determine, among other things, what the most popular TV show in our dataset is. This will test the knowledge we have gained so far and will take you through a typical use case that gets asked of a graph data scientist.

In order to do this, we will first be taking a look into the general properties of the mutual likes graph. This will start with an examination of what the graph structure looks like, moving on to a few other considerations you may want to take into account, such as a concept known as degree centrality.

Here, you will put your newly acquired skills to work. We will first start by examining the structure of the graph, we will then perform the connectedness of the entities in the graph, and then we will look at the top degree nodes in the graph.

We will be looking at the following steps to achieve our...