Building an Interactive Network Graph to Understand Communities
summary
Claims that an HR org chart can be improved by Clustering Attributed Graphs and a working toolkit that generates synthetic people, computes graph layouts, and surfaces neighborhoods. Implementation uses Python libraries: networkx, Faker for synthetic profiles, Plotly and pyviz/gravis for exploration, embeddings (node2vec style) and Dash + Cytoscape to build an interactive dashboard. Example dataset runs ~150 generated people, attributes become extra nodes, the dashboard renders and supports dragging and filtering — the prototype works live in a notebook and as a simple web app.
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chapters (9)
- 0:00Network graphs and people data
- 15:33Fake people data generation
- 39:51Synthetic data methods
- 40:55Building graph with NetworkX
- 56:13Interactive visualization with Plotly
- 1:01:10Exploring with PyVis and Gravis
- 1:06:51Adding graph attributes
- 1:11:08Dash app for network graphs
- 1:28:48Q&A
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