Inspiration
We were inspired to create our own methodology of using risk values to analyze and compare the data because we wanted to incorporate both the number and the severity of the cases to quantify how risky each product is.
What it does
It evaluates products' risk based on the number of complaints and the severity of the reported health outcomes. We also examined unique differences in high-risk products among different demographic groups.
How we built it
We used Python to clean and analyze our given data set.
Challenges we ran into
We are all beginners, so we ran into many technical challenges throughout building our project and debugging our code, but through persistence, we were able to figure everything out.
Accomplishments that we're proud of
We're all proud of making it through our first datathon!
What we learned
We learned a lot about how to better manage data and use Python to accomplish our goals.
What's next for SUPER BETA FUZZY WUZZY
Maybe Rice Datathon 2025? Time will tell.
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