Airbnb Listing Analysis — Python

Overview

Exploratory data analysis on Airbnb listing data to uncover pricing trends, location-based performance, and availability insights.

Problem Statement

Hosts and analysts need to understand pricing dynamics and demand patterns to make data-driven listing decisions.

Tools Used

• Python (Pandas, NumPy, Matplotlib, Seaborn)
• Jupyter Notebook

Key Findings

• Identified high-demand neighbourhoods and peak pricing periods
• Analyzed correlation between listing features and price
• Found availability and review patterns by room type

How to Run

pip install pandas numpy matplotlib seaborn jupyter notebook Airbnb_Analysis.ipynb