Pollutant Data Visualizer

We wanted to make a functional tool that used historical pollutant data from the EPA's air quality API to allow the user to investigate trends in air quality over the years.

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Inspiration

Data visualization is important for being able to understand the scope of a problem, particularly in regards to climate change and other large, almost unimaginable issues.

What it does

Our Pollutant Data Visualizer allows a user to select a state and a county to get information on the amount of different pollutants in the air.

How we built it

We built this webpage by using HTML, JavaScript, and CSS (with Bootstrap) to lay out our project and give it the functionality we needed. Since we needed data on the air quality of different locations, we decided to use an EPA API that already has that information and we would pull this data based on the user selection of the state, county, and the date they wished to look at.

We used the library Chart.js to make the graphs to show the pollutants based on user selection.

Challenges we ran into

We ran into a lot of challenges working on this project, the biggest issue we had was learning the near libraries/APIs to use them correctly in what we wanted them to do. The API documentation was difficult to understand at times and had a lot of different limitations to it which added to the complexity of receiving the exact information we wanted.

Accomplishments that we're proud of

We're proud of being able to learn something new when building our project, like the air quality API and a graph creation library, and being able to include it into our project. We also learned a lot about Github collaboration while working on this project, which will be extremely useful for the future!

What we learned

We learned how to use the air quality API and chart.js.

What's next for Pollutant Data Visualizer

We planned on having a lot more features involved in our project, but we lost too much time learning these new libraries and getting the information we wanted. In addition to that, the things we wanted to add, like a download button to download the information to a CSV file and other graphical visualizations, took a lot of time to figure out how to accomplish it. So in the future, we would want to add these components to our project.

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