Stories

LinkSight: Data cleaning of Philippine location names made easy

We built a web app to semi-automate cleaning up inconsistently spelled names of Philippine barangays, municipalities, cities and provinces. Try it out.

Read More
How exposed is your barangay to different natural hazards?

The Philippines is one of the most at-risk and vulnerable countries in the world. But the geographical distribution of risks and vulnerabilities within the archipelago is uneven.

Read More
How far from the airport can you get in two hours? Mapping Travel Isochrones from NAIA

Want to know what time you should schedule your flight so your car ride home isn't longer than the actual flight? Click to find out!

Read More
When did everything ML get 'deep'? Using fasttext to examine semantic trends in 30 years of NIPS papers

We use word embeddings to look into the evolving landscape of research topics in NIPS, AI’s most prestigious conference, through the years.

Read More
Mind the gap: A gender parity analysis of UPCAT passers

What are the most female- and male-dominated degree courses in UP? Explore our interactive dashboard to find out.

Read More
Spread algorithmic Christmas cheer with our snowflake generator

What happened when we asked a physicist, a compute…ta scientist to make our company Christmas cards?

Read More
How We Simplified Time-Tracking with Slack, BigQuery, and a Power BI Dashboard

Also known as: time-tracking for lazy people who hate forms.

Read More
Kailan ka ikakasal? Four data-driven comebacks to use at your next family reunion

Actually, Tita, the number of Filipinos getting married has declined 15% in the past 10 years. It's part of a nationwide trend.

Read More
MAPPED: Danger Zones in Metro Manila's Roads

Which roads and intersections are the most accident prone for motorcycles? Where are pedestrians most vulnerable to be injured? Which routes are dangerous for both?

Read More
Avoid These 4 EDSA Southbound Chokepoints

We uncovered potential chokepoints on EDSA Southbound using Waze data to show you exactly where you shouldn’t be during weekdays.

Read More
Making Panel Discussions Memorable with Data Visualization

Minutes are the default method of documenting and summarizing meetings. But they’re also about as interesting to read as your social media's terms and conditions.

Read More
This is what 24 hours of Metro Manila holiday traffic looks like

We're excited to be working with the MMDA to use real-time Waze data to analyze, diagnose, and address traffic congestion in Metro Manila.

Read More
Connecting Our Roads to Our Budget: New Tools to Follow the Money

"Follow the money" from budgeting, to procurement, execution, and auditing by using the OnTrack matching framework to unify data siloes.

Read More
114 Years of Philippine Disasters, Visualized

To cope with being one of the most disaster-prone countries on earth, we need to get used to viewing disasters as part of a pattern over time.

Read More
Build your own maps with this open source D3 Philippine cartogram

Make your own Philippine cartogram with our free resource

Read More
Makeover Your Charts with These 5 Design Hacks

Small tweaks can make a big difference when it comes to data design. Here are five case studies from our recent data storytelling workshop.

Read More
Visualizing the Family Tree of Philippine Languages

What would it look like if you were to put all Philippine languages into one family tree?

Read More
The language landscape of the Philippines in 4 maps

With almost 200 unique languages, the Philippines is one of the most linguistically rich places on earth.

Read More
Dots are people too: Learnings from Information+

Our Data Designer, writes about what she learned from attending Information+, one of the few data visualization related conferences that targets both researchers and practitioners.

Read More
Off the map: An alternative way of visualizing the Philippine election results

Why did we use a cartogram instead of a normal map for visualizing the election results?

Read More
How voter turnout has changed in 1,611 Philippine towns & cities since 2007

We found places in the Philippines where the number of voters changed in surprising and dramatic ways between 2007 and 2013.

Read More
A second look at PNP crime statistics: Taking population into consideration

A look at the number of index crimes per 10,000 residents for 15 Philippine cities.

Read More
Voters or robots? Evaluating the Twitter popularity of the presidential candidates

How many of the tweets about the Philippine presidential candidates were likely posted by Twitter bots?

Read More
EVENT RECAP: Talks from our "Humans + Machines" artificial intelligence conference

We're sharing the presentations delivered by the four speakers at our Feb. 19 artificial intelligence conference in BGC.

Read More
5 Ways You Already Rely On Artificial Intelligence

Sure, Siri is a long way from being Scarlett Johansson. But she’s a real-world example of how artificial intelligence has crept into daily life.

Read More
Do the Current Presidential Candidates Make You Wanna 😂?

Which emojis do Filipino Twitter users use most often when talking about the top presidential candidates?

Read More
Bird Watching: Building a Twitter Big Data Pipeline with Python, Cassandra & Redis

We use some of our favorite tech to build a data ingestion, storage, and analysis infrastructure.

Read More
More than 57,000 Metro Manila Pedestrians Hit by Vehicles Since 2005

What types of vehicles have hit or killed the most pedestrians in Metro Manila over the past ten years?

Read More
The Most Accident-prone Streets and Cities in Metro Manila (2014)

Part of our continuing series on road safety. Which roads and cities reported the highest number of persons injured or killed in traffic incidents in 2014?

Read More
Building Beautiful Charts with Matplotlib

Our data science lead Stef Sy shows you how to generate colorful line, bar, scatter plots and more using just a few lines of code from the Matplotlib library

Read More
When Are You Most in Danger on the Road?

How likely is it that if you get in an accident on your daily commute, it will result in someone getting hurt or killed?

Read More
We Are Thinking Machines

The Thinking Machines team and philosophy.

Read More