We looked through the provided datasets and noticed a pattern in racial distribution and healthcare outcomes.
What it does
Easily and simply represents data about racial inequities in healthcare.
How I built it
Challenges I ran into
As first timers we had no clue where to start. We tried to start in Flask then React, before finally ending up using the vega-lite package.
What I learned
We learned how to create an interactive webpage and visualize large sets of data. It was a new experience for all of us.
What's next for HealQuail
Future developments to extend HealQuail's ability to effect change:
- Interactive map: The website will include a US map with the locations geographically represented on it. Instead of selecting cities from a dropdown menu, users will be able to select cities from the map.
- Augmented external resources: The existing external resources are not specific to the given cities. In the future, after a city is selected, resources specific to that city will appear.
- Data analysis: While effective at visualization, our graphics do not do much analysis. We want to quantitatively measure how race disparities affect healthcare outcomes, such as through methods like Chi-Squared testing.
Running our Project:
Download the files in the NonReactVersion Folder and run the main.html file locally or open it in chrome. The data it needs is in the data subfolder.