Python

In this project in LIS 440: Navigating the Data Revolution, I used Python’s Pandas library to investigate housing inequality in four US states: California, Kansas, Maine, and Wisconsin. I cleaned and analyzed rental data, calculated averages, and visualized trends over time using bar charts. By comparing minimum wage levels, affordable rent thresholds, and actual rental costs, I highlighted the gap between wages and housing affordability. My final reflection connected these findings to larger systemic issues and policy implications.