Non-Fungible Tokens (NFTs) have become a hot topic in recent times, with a market that's both fascinating and complex. In this blog post, we'll walk through the steps to build an NFT Network Analysis project using data sourced from Moonstream. By the end of this guide, we'll have an interactive graph that visualizes the relationships between different NFT projects and their owners.

Step 1: Understanding the Business Case

Before diving into the technicalities, it's crucial to understand the business case. The aim is to identify influential NFT owners, often referred to as 'whales,' and analyze their involvement in various projects. The goal is to gain insights into potential future trends within the NFT market.

Step 2: Data Collection

The foundation of any data science project is the dataset. In this case, Moonstream provides a comprehensive NFT dataset with over 7 million transactions. The dataset is stored in an SQLite database, which simplifies the data retrieval process. Moonstream is a reliable source for NFT data.

Step 3: Data Exploration

To get a feel for the data, we begin by listing the top NFT projects. This step involves exploring the various projects, understanding their diversity, and creating a mapping dictionary for future reference.

Step 4: Identifying Top Owners

The next step involves identifying top NFT owners. We focus on the owners associated with the top projects, considering them as potential 'whales.' The process includes grouping owners by the number of projects they hold and filtering for those who own a significant chunk of the top projects.

If you wish to access the source code, here is the link to the repository.

Step 5: Gathering NFTs Owned by Top Owners

Once the top owners are identified, we compile a list of NFTs owned by these individuals. This step involves extracting relevant information, such as the NFT address, token ID, and owner, creating a comprehensive table for further analysis.

Step 6: Creating an Edge Table for Network Analysis

To perform network analysis, we create an edge table using NetworkX. This step involves counting the common ownership of NFTs between different projects, ultimately forming a graph that visualizes the relationships.

Step 7: Visualization with PyVis Network

Using PyVis Network, we generate an interactive visualization of the NFT network. The graph represents NFT projects as nodes and their common ownership as edges. The resulting visualization provides valuable insights into the connectivity and relationships within the NFT market.