Using Google Solar Project's dataset, this project aims to understand the relationships between solar panel deployment and socioeconomic factors such as income, poverty, and unemployment.

With renewable energy being at the forefront of potential progress, the United States remains behind in implementing one of the most accessible modes of clean energy: solar energy. While it seems wasteful not to harness energy that comes to us at no cost, the solar panels needed to collect this energy can be quite costly, with an average gross price of $15,600 in Massachusetts [2]. This large price tag can deter many potential implementers, which is why Google established Google Project Sunroof, a program that encourages data analysis of solar panel costs and efficiency in the United States. Google Project Sunroof also took it upon themselves to create an extensive dataset of variables related to solar panel deployment. As a group, we hope to analyze and visualize this dataset to better understand where solar panel deployment is most used and would be viable in the US. By combining this data with other datasets of US demographics, we hope to find trends of overlap between where solar panels are viable, and which socioeconomic classes are being left behind in the transition to solar energy. Through this overlap, we can develop a better understanding of which people and places would benefit most from the prospect of solar panels in the US, and provide suggestions for homeowners and policymakers to increase energy efficiency and minimize our carbon footprints.