Solving graph problems using networkX
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The document discusses using NetworkX, a Python library, to work with graph problems. It begins with an agenda that includes getting familiar with graphs, looking at examples of graphs, and using NetworkX. It then provides a brief, simplified history of graphs involving nodes and edges. The document explains that NetworkX makes it easy to create graphs from nodes and edges in Python and visualize graphs. It also discusses loading large graph datasets and performing analysis like finding high degree nodes.
Solving graph problems using networkX
- 1. Solving Graph problems using Network X
- 2. So What’s our Agenda ? 1. Getting to know Graphs 2. Looking at some cool Graphs 3. Playing around with Network X
- 3. The Wonderful Story of Graphs (TL;DR version)
- 4. In the beginning someone said … Let there be nodes.
- 5. Nodes remained in isolation for a long time until a mysterious force said. Let there be edges.
- 6. - Nodes became Happy at being connected to other Nodes through edges. - They wanted to give a name to this Union of nodes and edges, some mysterious person suggested ‘Graph’ is a cool name. So the Nodes and Edges lived happily ever after THE END
- 7. Need More Info? Wikipedia says “A graph is an ordered pair G = (V, E) comprising a set V of vertices or nodes together with a set E of edges. “
- 8. V = {1, 2, 3, 4, 5, 6} E = {{1, 2}, {1, 5}, {2, 3}, {2, 5}, {3, 4}, {4, 5}, {4, 6}}
- 13. Where else can we see applications of Graphs ?
- 14. & More
- 15. NetworkX : A friendly Python library
- 16. How to Create miserable lonely Nodes ?
- 17. That’s how you add Edges!
- 18. You Can Multitask , Multi add edges
- 20. Generating Graphs are Super Easy !!
- 21. Now good luck trying to draw that with hand
- 22. This is my favourite . So don’t ask me anything about it
- 23. We can add more details to Node and Edges.
- 24. Reading Graphs in other Formats
- 25. Matplotlib is not the right tool always
- 26. Alternatives for Better Visualization
- 27. Let’s try something ambitious now. A) Read 1 Crore lines of edge information from a dataset B) And find the node with the highest degree. C) Calculate how much time it took for loading the graph