Network Science, Game of Thrones and US Airports
summary
Hands‑on tutorial that loads the repo https://github.com/MridulS/pydata-networkx and uses NetworkX, Pandas, Matplotlib to build graphs from the Game of Thrones text and a US domestic flights table, computes degree/weighted/betweenness/PageRank centralities, and plots results. Claims: Eddard Stark most central (Book 1) shifting to Jon Snow by Book 5 and Stannis showing high betweenness; US network finds Anchorage high betweenness and an average shortest path around ≈3.17 after removing isolated anomalies.
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chapters (22)
- 0:00Introduction
- 1:20What defines a graph
- 3:16NetworkX library
- 6:49Academic collaboration networks
- 11:29Measuring influence with centrality
- 15:43Random vs real-world networks
- 18:57Network connectivity and subgraphs
- 21:30Shortest path algorithms
- 22:52Six degrees of separation
- 29:20Game of Thrones character networks
- 33:38Most important GoT character
- 40:18Betweenness centrality role
- 43:15PageRank significance
- 49:42Community detection explained
- 54:03US airports passenger traffic
- 59:14Busiest US flight routes
- 1:01:01US airport locations and connectivity
- 1:04:15PageRank for airports
- 1:07:11Anchorage's air travel role
- 1:11:04Optimizing flight paths
- 1:17:07United Airlines hub analysis
- 1:24:19Summary
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