Inspiration
We were inspired by the dataset on flood risk in different San Francisco census blocks groups. We wanted to further examine the relationships between different variables to see what kinds of conditions put people in risky situations.
What it does
We made a shiny application! You can look at graphs and regression tables there :)
How we built it
We created linear regression models in Python and R to analyze and display the relationships between different variables that are factored into calculating the Flood Health Index. We also learned to use Shiny (very hard)
Challenges we ran into
We struggled with creating predictive models of how one factor affects another, trying to make maps, etc.
Accomplishments that we're proud of
We are proud of having learned and applied new skills to our project.
What we learned
We learned how to use Shiny (Mary) and scikit-learn and pandas (Annie).
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