The research is analyzing house price data for the purpose of identifying the most significant house price determinants. The business case is helping buyers, sellers, and investors make informed real estate decisions through an understanding of price variation drivers.
I built an interactive dashboard with filters by building type and zoning using Python, Dash, and Plotly. The platform allows for the analysis of sale price distributions, time trends, and structural aspects like basement area, lot size, and building condition.
New houses are costly, but a number of the older houses appreciate in value
Increased sale values are linked with better condition scores and larger basements
Single-family homes dominate in the higher price brackets, but other types offer better price-per-area value
Zoning and lot size have an effect, but diminishing returns apply
