Inspiration
While it is widely known that our world’s path towards climate catastrophe is a threat to all life on earth, the communities that are most vulnerable to these changes are often overlooked. That is why we have focused our tool, PollutionPlot, to draw attention to these inequities.
What it does
Our team has created an interactive data visualization tool that allows you to see air quality metrics and median household incomes placed side-by-side for most counties in any given state.
How we built it
Our graphing tool is constructed using Python Pandas and Matplotlib, referencing two national 2019 datasets from the EPA and USDA. The tool is housed in a Flask-powered web app and hosted with Heroku.
Challenges we ran into
Our team had little prior experience with data projects of this scale, and thus, we had to conquer the learning curves of Pandas, Matplotlib, and working with large datasets overnight. This resulted in us having to scale down our project in order to focus on polish, but we're extremely happy with the results.
Accomplishments that we're proud of
We're particularly proud of the presentation and design of our site. We aimed to make the tool easy to use and mess-free while being displayed in a clean and appealing manner.
What we learned
Our team learned the basics of data cleaning and graphing, as well as how to locate trends in the data and portray them in a meaningful way. Additionally, we beefed up our skills with web development, with each team member having only constructed between 0-3 previous web projects.
What's next for PollutionPlot
Our team hopes to discover even more correlations by incorporating other datasets such as education level and demographics. We also hope to increase interactivity, such as more custom filters and multiple display options. Finally, we recognize the limitations of our current graph design and data choices, and we hope to remedy some of these by shifting away from a county-by-county basis and more towards a deeper dive into specific U.S. cities.
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