Our mission is to dive into this dataset of house sale prices for King County. For this project we deployed diferent tasks such as data loading, visualization, calculating returns, and portfolio analysis, tailored to the real estate domain.
This dataset comprises one-year data (from May 2014 to May 2015) of house sale prices across King County. It features 21 different columns, providing a comprehensive overview of the real estate market:
id: A unique identifier for a house.
date: The date on which the house was sold.
price: The sale price of the house (prediction target).
bedrooms: Number of bedrooms in the house.
bathrooms: Number of bathrooms in the house, per bedroom.
sqft_living: Square footage of the interior living space.
sqft_lot: Square footage of the land space.
floors: Number of floors (levels) in the house.
waterfront: Whether the house has a waterfront view.
view: Number of times the house has been viewed.
condition: The overall condition of the house.
grade: The overall grade given to the house, based on the King County grading system.
sqft_above: Square footage of the house apart from the basement.
sqft_basement: Square footage of the basement.
yr_built: The year the house was built.
yr_renovated: The year the house was renovated.
zipcode: ZIP code area.
lat: Latitude coordinate.
long: Longitude coordinate.
sqft_living15: The interior living space for the nearest 15 neighbors in 2015.
sqft_lot15: The land spaces for the nearest 15 neighbors in 2015.
Price: Our primary focus is to understand which features most significantly impact the house price. Additionally, we aim to explore properties valued at $650K and above for more detailed insights.
Ailla Souza
Karla Espinoza
Luis Quinaz
Marçal Morera