Repository to accompany the substack Graphs For Data Science
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All the code is runnable in 
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Graphs 101 - A deep look at the airline transportation network - Graphs 101 - Airline Network.ipynb
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Understanding DBSCAN and K-NN with Random Geometric Graphs - Random Networks.ipynb
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Searching Graphs: Or how to get turn by turn directions from Open Street Map - Search.ipynb
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Graph Embeddings 101: From word2vec to node2vec, and beyond - node2vec.ipynb
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Node Centrality: Degree, Closeness, and Betweenness Centrality - Node Centrality.ipynb
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Graph Components: Strongly and Weakly Connected Components - Components.ipynb
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Bitcoin Transaction Network: Networks on the blockchain - Blockchain.ipynb
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Erdős-Rényi Model and Clustering Coefficient - ER and Clustering Coefficient.ipynb
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The Watts-Strogatz Model and the Small World Effect - WS and the Small World Effect.ipynb
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Barabasi-Albert Model and Preferential Attachment - BA Model and Preferential Attachment.ipynb
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Network Assortativity and the Configurational Model - Degree Correlations and the Configurational Model.ipynb
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Community Structure and Network Modularity - Community Detection.ipynb
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Neighborhood Overlap and Edge Weights - Edge Weight and Network structure.ipynb
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Prim's Minimum Spanning Tree Algorithm - Prim's MST Algorithm.ipynb
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Kahn's Algorithm for Topological Sorting - Topological Sorting.ipynb
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