Personal data analysis project exploring Airbnb listings in Madrid using Python and Pandas.

The project focused on cleaning, validating, and exploring a real-world dataset to identify patterns in Airbnb listings, pricing, and location.

I used Python and Pandas to prepare the data, handle inconsistencies, perform exploratory analysis, and extract meaningful insights from the dataset. The analysis included comparing average prices across Madrid neighborhoods and identifying geographic patterns in listing prices.

The visualization shown here highlights the 10 most expensive neighborhoods for entire-home Airbnb listings based on average price.

Skills demonstrated: Python, Pandas, data cleaning, exploratory data analysis, data interpretation, and data visualization.

This project is part of my independent data analytics portfolio and demonstrates my ability to turn raw datasets into structured analysis and clear, actionable insights