This video is introducing the networkx python library to visualize how the institutional owners of the Dow Jones Industrial average are connected.

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Network analysis/ Network Graphs is a hot topic in all data related fields in specific in Data Science but also in finance.
I am going over step by step tutorial how you can visualize and improve a Graph to get nice insights.
This includes: Arranging node size depended on the node degree, edge width dependend on the edge attributes and other beautifications to make a nice network graph.

I personally think this topic is highly interesting and relevant. Possible future content could be interactive network graphs (e.g. on the S&P 500).

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wikiepdia link:
https://en.wikipedia.org/wiki/Dow_Jon...

0:00 - 01:29 Brief introduction on the Graph we are building
01:29 - 06:59 Example of only 2 assets (watch for better understanding)
06:59 - 08:02 Getting DJ tickers
08:02 - 09:52 Get all institutional owners for all DJ components
09:52 - 11:20 Create the basic Graph
11:20 - 13:05 Change node colors
13:05 - 16:18 Node size depending on Node degree
16:18 - 19:41 Edge width dependent on edge attributes (invested amount)
19:41 - 20:40 Final amendments/ Thanks for watching :-)