California Wildfires and Housing

Inspiration

Both of us grew up in very different parts of the world, but have devastatingly seen the impact of climate change on our surroundings, community, and environment. Since one of us is from the west coast, we wanted to explore a topic that is very impactful to the area: wildfires. Wildfires impact many factors, including housing. Taking inspiration from Fannie Mae's challenge, we wanted to explore how Californian wildfires impact the mortgage and housing situation in the state.

What it does

Using various libraries in Python and R, our team analyzed environmental and financial data to provide insight into the correlation between mortgage values and wildfires in California. We wanted to make this information clear, so we are presenting it in a slideshow format.

How we built it

In R, we used libraries like tidyverse, terra, tigris, etc. to plot geospatial, time, and quantitative data.

Challenges we ran into

We faced challenges finding data since this is a niche topic for a certain state. However, we were able to combine various sources to provide insightful correlations.

Accomplishments that we're proud of

We are proud of the way we worked together and discussed potential ideas. We also are proud that we chose to explore various types of data.

What we learned

We learned a lot about the various libraries used for data visualization. This project has made us more excited to explore how geospatial data can be combined with different forms of quantitative data.

What's next for California Wildfires and Housing

We want to explore how the impacts of wildfires on housing vary for different parts of California. Are there certain counties that recover faster than others? How do financial factors play a roll in this?

Built With

• api
• python
• r