I have been receiving requests to release the Python code I wrote to produce the financial network discussed in my previous post titled PSE Correlation-Based Network. Well, here it is! 🙂
In this blog post, I explore the use of networks (minimum spanning trees), as presented by Bonanno et al. in 2003, to quantify relationships of assets listed in the Philippine Stock Exchange.
Metro Manila, Philippines. Generating and visualising a day’s worth of synthetic taxi data.
Sharing some Python recipes I wrote for mining, reading, manipulating, and plotting map data.
Let’s play a game! Can you guess which Philippine provinces these road networks belong to? The first one is easy peasy!
I was tasked to come up with a list of all the Python packages we need for this new server we are setting up. Sharing the list below, hoping you’ll find them useful.