London's Airbnb
Airbnb listings in London
About this dataset
This dataset provides information on Airbnbs in London. Each row represents one listing, and there are a variety of columns with information on the listing, such as the name, host, price, etc.
This dataset could be used to study patterns in Airbnb pricing, to understand how Airbnbs are being used in London, or to compare different neighborhoods in London
How to use the dataset
If you're looking for information on Airbnbs in London, this dataset is a great place to start. It provides information on the listings and reviews for Airbnb in the city of London.
Airbnb is a popular vacation rental platform that allows travelers to find and book accommodations around the world. With over 3 million listings in more than 65,000 cities, Airbnb has something for everyone.
London is one of the most popular tourist destinations in the world, and Airbnb offers a unique way to experience the city. With so many different neighborhoods to choose from, there's an Airbnb listing for everyone.
This dataset includes information on the listing price, minimum nights required, number of reviews, and more. With this data, you can begin to understand how people are using Airbnb in London and what factors affect pricing. So whether you're looking for a place to stay during your next trip or just curious about how Airbnb is being used in different cities, this dataset is for you!
Research Ideas
- If there's a relationship between the price per listing and how long it is available on Airbnb, this could be used to recommend lower prices for listings that are unlikely to stay booked for very long periods of time.
- There might be a relationship between the number of reviews per month and the calculated host listings count. If there is, this information could be used to help improve customer satisfaction by either recommending that hosts with lots of listings receive more reviews or that they stagger their listing availabilities so that they can provide better service.
- The neighbourhood data could be used to cluster listings into areas with similar characteristics, which would then allow customers to easily find similar listings in different areas of the city based on their preferences
Acknowledgements
This dataset is brought to you by Kelly Garrett. If you use it in your research, please cite her Data Source
License
> License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
> No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.
Columns
File: listings.csv
| Column name |
Description |
| name |
The name of the listing. (String) |
| host_name |
The name of the host. (String) |
| neighbourhood_group |
The neighbourhood group the listing is in. (String) |
| latitude |
The latitude of the listing. (Float) |
| longitude |
The longitude of the listing. (Float) |
| room_type |
The type of room. (String) |
| price |
The price of the listing. (Integer) |
| minimum_nights |
The minimum number of nights required to stay at the listing. (Integer) |
| number_of_reviews |
The number of reviews for the listing. (Integer) |
| last_review |
The date of the last review. (Date) |
| reviews_per_month |
The number of reviews per month. (Float) |
| calculated_host_listings_count |
The number of listings the host has. (Integer) |
| availability_365 |
The number of days the listing is available in a year. (Integer) |
File: reviews.csv
| Column name |
Description |
| last_review |
The date of the last review. (String) |
File: neighbourhoods.csv
| Column name |
Description |
| neighbourhood_group |
The neighbourhood group the listing is in. (String) |