Our d3 map of gun violence in the U.S.
Integrated Stripe donation link
Imagine a world where the number of mass shootings in the U.S. per year don't align with the number of days. With the recent Thousand Oaks shooting, we wanted to make something that would accurately predict the probability that a place has a mass shooting given a zipcode and future date.
What it does
When you type in a zipcode, the corresponding city is queried in the prediction results of our neural network in order to get a probability. This probability is scaled accordingly and represented as a red circle of varying size on our U.S. map. We also made a donation link that takes in credit card information and processes it.
How we built it
Challenges we ran into
We had lots of challenges with this project. d3.js was hard to jump right into, as it is such a huge library that correlates data with visualization. Cleaning the data was challenging as well, because people tend not to think twice before throwing data into a big csv. Sending data around files without the usage of a server was challenging, and we managed to bypass that with the stdlib api.
Accomplishments that we're proud of
A trained neural network that predicts the probability of a mass shooting given a zipcode. A beautiful topological map of the United States in d3. Integration of microservices through APIs we had never used before.
What we learned
Doing new things is hard, but ultimately worthwhile!
What's next for Ceasefire
We will be working on a better, real-time mapping of mass shootings data. We will also need to improve our neural network by tidying up our data more.