Inspiration
To learn and improve in computer/data science
What it does
We cleaned, analyzed, and visualized FDA and Census data to provide recommendations about allocation of FDA funds for mammography equipment
How we built it
We made this project in Jupyter Notebook, utilizing Python, Pandas, and other data science packages.
Challenges we ran into
Misaligned columns in our given data and general syntax issues
Accomplishments that we're proud of
We made informed conclusions and recommendations, bringing in outside data sets to help strengthen our arguments and overall project.
What we learned
We learned about the data science pipeline and new Python packaged
What's next for Grant, Seyaul, Gavin, Matthew - Beginner's Track
In the future, we could bring in geographical and socioeconomic data to determine areas most impacted by a lack of mammography accessibility.
Log in or sign up for Devpost to join the conversation.