Research of Factors Influencing Housing Trends of Seattle

Group Members

Shariful Alam (Anik), Connor Fink, Trevor Wong

Inspiration

We wanted to see/discover the relationships between the factors of Seattle and the price of houses throughout the area. We found it interesting to discover what factors contributed to the price and which factors were not as significant.

What it does

The program will plot the area of Seattle using a dataset full of houses in king county (but will only plot ones in Seattle) and display the average cost of a house per tract in Seattle which displays the relationship of cost in comparison to the area. The program also utilizes various other datasets to produce findings of facilities which contribute to house prices. Finally, the program features a machine learning model that can predict a future housing market with the training data.

How we built it

We used the knowledge obtained from class with matplotlib, pandas/geopandas, and the machine learning pipeline. We also used the genetic algorithm to procure more accurate and meaningful data when analyzing the relationship between house prices and facilities.

Challenges we ran into

One of the first few challenges we ran into was the lack of a relationship. We wanted to discover the relationship between a house price and bus stops initially but we discovered that there was not a clear relationship. To overcome this, we transitioned to find other relationships with other facilities other than bus stops. Another challenge was transitioning from ed workspace to vs code and github since there were various libraries to import and environments to install.

Accomplishments that we're proud of

One accomplishment we were proud of would be the fact that we could produce results that can benefit others with just our computers and our thoughts. Another would be using available geo special data and work with all of them for making decisions which was something we found interesting.

What we learned

We learned how to utilize our knowledge gained from this class to produce relevant results and also another thing we learned was how to code in a team environment. We were also able to learn more about the relationships of house prices in relation to the area around it but that was probably a given.

What's next for Research of Factors Influencing Housing Trends of Seattle

Possibly extending the program to work outside of Seattle or even scraping data from real time data to get more accurate results. This would open the opportunity to create a program that can be provided to many people in search of a home anywhere in the world as it would provide additional information not offered by real estate websites.