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.
The 2016 VP Race
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
Network Growth of “The Silent Majority”
The membership expansion was so fast, we got curious about its network growth dynamics. We decided to “visualize” the mushrooming of the online society.
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.
Machine Learning and the Smart City
On 19 February 2016, I participated as speaker at the Humans+Machines conference organized by the Thinking Machines. Below is a copy of the slide deck I used.
How Voters Combine Candidates on the Ballot: The Case of the Philippine Senatorial Elections
In the Philippines, senators are nationally elected officials, and citizens vote for 12 candidates every three years. The country’s electoral features include a weak party system, a low-information environment for … Continue reading
Twitter Users as Seismographs
The idea that Twitter users generate volumes of earthquake-related tweets at the onset of an earthquake is hardly new [link], but it’s always fun to work with data from home … Continue reading
