Visualization of earthquakes in the San Francisco Bay Area. Grey value indicates the magnitude of the most recent quake (top), all quakes in the past 24 hrs (bottom), and max quake each day for the past 30 days (middle).
Made using a Raspberry Pi Zero W and a Pimoroni Inky wHAT, mounted in an 8 inch square frame.
With Tictrac, you can collect data from various online accounts (see the image below supported services), visualize them over time, compare them to one another and set personal goals. You can also manually log and track data that is not already captured by another service.
There is a lot to like about this application. First, the idea is empowering — let folks determine what data they want to track and then visualize it so that they can draw inspiration and insights from it. Second, the way it leverages twitter is clever.
Lately I’ve been collecting and analysing Twitter data. I’ve been looking at networks formed by friends and followers of a set of people, tracking the path of tweets and generally building on my python skills.
I’m working toward a pretty ambitious goal but, inspired by the arc diagrams in the NYTWrites project, I decided to take a short break and render out one of my own.
The diagram shows all twitter users mentioned in tweets by @Odopod, sorted by the number of times they have been mentioned. The arcs link nodes that were mentioned in a tweet with other users and the width of the arc indicates the number of links. The size of the nodes represent the number of links a node has associated to it.