Airbnb Listings In London
Explore How Airbnb is Used Across London
@kaggle.thedevastator_airbnb_listings_in_london_neighbourhoods_and_rev
Explore How Airbnb is Used Across London
@kaggle.thedevastator_airbnb_listings_in_london_neighbourhoods_and_rev
By Kelly Garrett [source]
Welcome to the Inside Airbnb London dataset - your ticket to discovering what's really happening with Airbnb in London! This set of tools and data allows you to explore insights into Airbnb’s behaviour in this fascinating city.
The data contained herein is drawn from publicly available information from the Airbnb website, and is published under a Creative Commons CC0 1.0 Universal (CC0 1.0) Public Domain Dedication. Find out more about various neighbourhoods' preferences for short-term rentals by examining the data found within this dataset: name, host_name, neighbourhood_group, latitude & longitude coordinates, room_type, price per night, minimum nights required for booking a listing, number of reviews left by other users and last date of review received plus reviews per month and calculated host listings count which provides an approximation of total active listings by individual hosts. You can even identify patterns in availability over time with the handy availability_365 feature that reports days open for bookings within 365 days! Last but not least stay up-to-date with the helpful ‘date’ column that tells us exactly when it was collected so you have access to accurate and current information. Dive into Inside Airbnb London now!
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
- Developing a predictive model to suggest desirable Airbnb listings for users based on their preferences.
- Analyzing the London neighbourhoods most popular with Airbnb users based off activity and reviews.
- Creating a tool to monitor changing trends in pricing and availability of London Airbnb listings over time
If you use this dataset in your research, please credit the original authors.
Data Source
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.
File: listings.csv
| Column name | Description |
|---|---|
| name | Name of the Airbnb listing. (String) |
| host_name | Name of the host of the Airbnb listing. (String) |
| neighbourhood_group | The neighbourhood group the listing is located in. (String) |
| latitude | The latitude coordinate of the listing. (Float) |
| longitude | The longitude coordinate of the listing. (Float) |
| room_type | The type of room offered by the listing. (String) |
| price | The price of the listing. (Integer) |
| minimum_nights | The minimum number of nights required for a booking. (Integer) |
| number_of_reviews | The total number of reviews for the listing. (Integer) |
| last_review | The date of the last review for the listing. (Date) |
| reviews_per_month | The average number of reviews per month for the listing. (Float) |
| calculated_host_listings_count | The total number of listings for the host across all their listings. (Integer) |
| availability_365 | The number of days the listing is available for booking in a year. (Integer) |
File: reviews.csv
| Column name | Description |
|---|---|
| last_review | The date of the last review for the listing. (Date) |
If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit Kelly Garrett.
CREATE TABLE listings (
"index" BIGINT,
"id" BIGINT,
"name" VARCHAR,
"host_id" BIGINT,
"host_name" VARCHAR,
"neighbourhood_group" VARCHAR,
"neighbourhood" VARCHAR,
"latitude" DOUBLE,
"longitude" DOUBLE,
"room_type" VARCHAR,
"price" BIGINT,
"minimum_nights" BIGINT,
"number_of_reviews" BIGINT,
"last_review" TIMESTAMP,
"reviews_per_month" DOUBLE,
"calculated_host_listings_count" BIGINT,
"availability_365" BIGINT
);CREATE TABLE neighbourhoods (
"index" BIGINT,
"neighbourhood_group" VARCHAR,
"neighbourhood" VARCHAR
);CREATE TABLE reviews (
"index" BIGINT,
"listing_id" BIGINT,
"date" TIMESTAMP
);Anyone who has the link will be able to view this.