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# Mp26 : A Quick Introduction to NetworkX

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### Mp26 : A Quick Introduction to NetworkX

1. 1. A Quick Introduction to NetworkX Putra Manggala Montreal-Python 26 December 19, 2011
2. 2. NETWORKX. A Python package to analyze networks and graphs. Many algorithms implemented (Combinatorics, Network analysis, Network ﬂows, etc). Easy visualization via Matplotlib.
3. 3. NETWORKS/GRAPHS. Networks/Graphs consist of: Vertices/Nodes: Singletons in your model. Edges: Connections between the vertices.
4. 4. GRAPH EXAMPLE 1. A toy graph with 5 nodes.
5. 5. GRAPH EXAMPLE 2. All the graphs with 6 nodes or less. 1 1 http://networkx.lanl.gov/examples/drawing/atlas.html
6. 6. GRAPH EXAMPLE 3. A network of books about US politics published around the time of the 2004 presidential election and sold by the online bookseller Amazon.com. 2 Edges between books represent frequent copurchasing of books by the same buyers. 2 http://www-personal.umich.edu/ mejn/netdata/
7. 7. GRAPH EXAMPLE 3. Nodes.
8. 8. GRAPH EXAMPLE 3. Edges.
9. 9. GRAPH EXAMPLE 3. Visualization of the dataset.
10. 10. GRAPH EXAMPLE 3 - CLIQUE ANALYSIS. Clique analysis. 3 3 A clique is a set of nodes in which every node is connected to every other node.
11. 11. GRAPH EXAMPLE 3 - CLIQUE ANALYSIS. Clique analysis. 3 Some simple statistics on the cliques: 3 A clique is a set of nodes in which every node is connected to every other node.
12. 12. GRAPH EXAMPLE 3 - CLIQUE ANALYSIS. Some intuition for the cliques: They are the set of books that are often bought together by the same buyer (at any one time!)
13. 13. GRAPH EXAMPLE 3 - CLIQUE ANALYSIS. Some intuition for the cliques: They are the set of books that are often bought together by the same buyer (at any one time!)
14. 14. GRAPH EXAMPLE 3 - CLIQUE ANALYSIS. Visualization of the ones often bought in bulk.
15. 15. GRAPH EXAMPLE 3 - CLIQUE ANALYSIS. Visualization of the ones often bought in bulk.
16. 16. REFERENCES https://github.com/drewconway/NetworkX_ Intro_Materials. http://networkx.lanl.gov/ http: //github.com/pmangg/NetworkX_MontrealPython Networks, Crowds, and Markets: Reasoning About a Highly Connected World (Easley and Kleinberg 2010).