Solving Graph problems using Network X

So What’s our Agenda ?

1. Getting to know Graphs2. Looking at some cool Graphs3. Playing around with Network X

The Wonderful Story of Graphs(TL;DR version)

In the beginning someone said … Let there be nodes.

Nodes remained in isolation for a long time until a mysterious force said.

Let there be edges.

- 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

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. “

V = {1, 2, 3, 4, 5, 6}E = {{1, 2}, {1, 5}, {2, 3}, {2, 5}, {3, 4}, {4, 5}, {4, 6}}

Some Interesting Graphs

Where else can we see applications of Graphs ?

& More

NetworkX : A friendly Python library

How to Create miserable lonely Nodes ?

That’s how you add Edges!

You Can Multitask , Multi add edges

Just some housekeeping

Generating Graphs are Super Easy !!

Now good luck trying to draw that with hand

This is my favourite . So don’t ask me anything about it

We can add more details to Node and Edges.

Reading Graphs in other Formats

Matplotlib is not the right tool always

Alternatives for Better Visualization

Let’s try something ambitious now.

A) Read 1 Crore lines of edge information from a datasetB) And find the node with the highest degree.C) Calculate how much time it took for loading the graph