This project analyses data provided by Airbnb (http://insideairbnb.com/get-the-data.html) for the city of Athens, Greece in order to answer the following questions:
-What factors affect the price of a listing? -Which neighborhoods have the most expensive and the cheapest listings? -Is there a seasonality on prices? Which season is better to visit Athens in order to pay less?
It turns out the number of bathrooms is the factor with the highest impact on the price of a listing. A relatively high impact have the number of bedrooms, accommodates, and beds as expected.
Monastiraki, Thiseio, and Plaka are the neighborhoods with the most expensive listings while Agios Nikolaos, Rizoupoli, and Sepolia have the cheapest listings.
Finally, March is the month with the lowest average prices.
A more detailed analysis on the results can be found here https://medium.com/@efimavridou/airbnb-in-athens-heres-what-you-need-to-know-based-on-data-e9595500214e
The code is written in Python 3.7.6, in Jupyter Notebook.
Libraries used: Modin.Pandas 0.7.3, Matplotlib 3.1.3.