Getting an Edge with Network Analysis with Python
summary
Uses Python and networkx to load a public Venmo dataset, build a 700k-scale directed graph, extract a 40-node / 78-edge subgraph and isolate a 18,360-node component. Runs community detection (five communities colored), computes PageRank and betweenness to rank influencers, and shows node/edge attributes (names, genders, transaction counts) driving visualization. Demonstrates which concrete metrics and steps produce the reported results and where networkx struggles with scale.
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chapters (9)
- 0:00Start
- 0:18Introduction
- 2:03What Is a Network and Why Should We Care
- 4:58Types of Networks
- 6:33Recap
- 7:11Networkx
- 16:10Weekly Connected Components
- 17:10Create a Sub Graph
- 18:25Node Attributes
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