rmehta42/Airbnb-Listing-Price

This repository analyzes NYC Airbnb listing data to surface pricing, availability, neighborhood activity, and listing characteristics. Intended users include data analysts, researchers, policymakers, hosts, and urban planners seeking empirical insights into the short‑term rental market. Key features: - Data cleaning and preprocessing, including handling missing/inconsistent values - Exploratory data analysis and visualizations (matplotlib, seaborn) - Statistical analysis linking price and availability to borough, room type, minimum nights, and review activity - Reproducible Jupyter notebooks and processed datasets Tools: Python, pandas, NumPy, scikit‑learn, Jupyter, SQL. Notable findings: Manhattan shows highest median prices; entire-home listings cost more than private rooms; some neighborhoods have high listing density but low annual availability; review activity correlates with pricing. Repo layout: data/, notebooks/, outputs/. Install with pip install -r requirements.txt.