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!
We take a peek at the data on the controversial Philippine VP race that prompted many Pinoy academics to download, visualise, and analyse the 2016 election results in the wake of the allegations of systematic cheating
The plots below show the Mention Network of Twitter users (bots and humans) discussing the Philippine Elections. Building a network such as the ones here can help one to visualize (and even … Continue reading
Given the level of risk that we, as a country, are exposed to (e.g. from earthquakes and typhoons), it is easy to see that there is a compelling need for our government to set up effective disaster preparedness and relief response plans, especially considering the fact that we can never be immune to natural disasters.