airbnb

Paris Airbnb Analysis: A data-driven exploration of Airbnb listings in Paris, France. This project leverages various datasets to uncover trends, analyze property distribution across neighborhoods, and visualize the spatial distribution of listings.

Paris Airbnb Analysis

Datasets

This project uses the following datasets:

1. listings.csv: Detailed information about Airbnb listings in Paris, including descriptions, number of rooms, price per night, and other relevant features.
2. listings_summary.csv: A summary version of the listings.csv dataset with fewer columns.
3. reviews.csv: Detailed information about user reviews for Paris listings, including review date, text, and user names.
4. reviews_summary.csv: A summary version of the reviews.csv dataset with fewer columns.
5. neighbourhoods.geojson: Geospatial data for Paris neighborhoods, including names and boundaries.
6. calendar.csv: Information about future availability and pricing for each Paris listing.

Questions Addressed

The project aims to answer the following questions:

1. What are the most popular neighborhoods for Airbnb listings in Paris?
2. How have the number of reviews evolved over the years?
3. Can we visualize the spatial distribution of Airbnb listings in Paris using a map?

Dependencies

To run the code and visualize the results, the following Python libraries are required:

• pandas
• numpy
• matplotlib
• seaborn
• folium (for map visualization)

Usage

To run the project, first ensure that you have installed the required dependencies. Then, open the Jupyter Notebook or Python script containing the code and execute it.

License

This project is licensed under the MIT License. See the LICENSE file for more information.