Building Financial Networks
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! 🙂
Hypothetical Taxi Movements in MMla
Metro Manila, Philippines. Generating and visualising a day’s worth of synthetic taxi data.
Mining, reading, manipulating, and plotting map data
Sharing some Python recipes I wrote for mining, reading, manipulating, and plotting map data.
How well do you know your province?
Let’s play a game! Can you guess which Philippine provinces these road networks belong to? The first one is easy peasy!
Python Packages
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.
Philippine Elections Chatters
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
Assessing the Feasibility of Relief Operations
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.
The AlDub Phenomenon
The past few days/weeks, we have been seeing a lot of posts on our fB walls and Twitter feeds on #AlDub. AlDub is an “accidental” segment in Eat Bulaga that had people following the program for a little over a month now.
Tableau Colors in Matplotlib
I love the colors that Tableau uses in plotting. I was so happy I came across Randal Olson’s post titled “How to make beautiful data visualizations in Python with matplotlib.” … Continue reading