Exploring guest review scores and their relationships with properties of Airbnb hosts/listings/neighbourhoods in London
Airbnb was founded in 2008 and has already become a very popular service for travellers around the world.
The number of Airbnb listings in London has grown significantly in the past few years, especially after it was legalized in 2015 .
The reputation of the service can be disrupted by fraud or can be increased by different improvements.
One hypothesis that we have is that guest review scores can be reliable factor to evaluate current status of attractiveness of the service in general, and increasing hosts reputation can be the reason for service reputation improvement.
The main goal of this analysis is trying to find any patterns and relationship of guest review scores between themselves and with different aspects of hosts and listings from Airbnb in London.
There is a relationship between different guest review score types and several Airbnb host/listing/neighbourhood properties in London, which can be used for further analysis and decisions how to improve hosts service and company's reputation in general
Code is reproducible with altair version 3.3.0
- Inside_Airbnb_London.ipynb
- Jupyter notebook with fully reproducible code for analysis
- LICENSE.md
- License file
- README.md
- File with repository description
- .gitignore
- File with ignored files/directories
Table of Contents links are not working on GitHub repository directly, they can be used after cloning repository locally or displaying Jupyter notebook via Jupyter NBViewer service
This project is licensed under the terms of the MIT license
Thanks to Inside Airbnb project for providing public Airbnb data