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European Airbnb Listings Data
NLP / Natural Language Processing
Tags and Keywords
Trusted By
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Free
About
This dataset offers an in-depth look at Airbnb prices across several popular European cities, providing insights into the various factors that influence rental costs. It evaluates individual listings based on attributes such as room type, location, cleanliness ratings, guest satisfaction, number of bedrooms, and distance from city centres and metro stations. The data facilitates an understanding of how social dynamics and geographical elements impact pricing strategies, allowing for analysis of optimal profitability. It can be used by individuals and companies to gain insight into the cost of Airbnb listings and explore general trends or conduct deeper econometric analysis.
Columns
The dataset includes detailed information across various attributes for each listing, typically found in files for both weekdays and weekends. The key columns are:
- realSum: The total price of the Airbnb listing (Numeric).
- room_type: The classification of the room being offered (e.g., private, shared, entire home/apartment) (Categorical).
- room_shared: Indicates whether the room is shared (Boolean).
- room_private: Indicates whether the room is private (Boolean).
- person_capacity: The maximum number of people the room can accommodate (Numeric).
- host_is_superhost: Identifies if the host holds Superhost status (Boolean).
- multi: Indicates if the listing is for multiple rooms (Boolean).
- biz: Signifies if the listing is intended for business purposes (Boolean).
- cleanliness_rating: The rating of the listing's cleanliness (Numeric).
- guest_satisfaction_overall: The overall satisfaction rating from guests (Numeric).
- bedrooms: The number of bedrooms in the listing (Numeric).
- dist: The distance of the listing from the city centre (Numeric).
- metro_dist: The distance of the listing from the nearest metro station (Numeric).
- lng: The longitude coordinate for location identification (Numeric).
- lat: The latitude coordinate for location identification (Numeric).
- attr_index: (Numeric)
- attr_index_norm: (Numeric)
- rest_index: (Numeric)
- rest_index_norm: (Numeric)
Distribution
The dataset is provided in CSV format and includes separate files for weekday and weekend listings data for various European cities, such as Vienna and Amsterdam. For instance, the
amsterdam_weekdays.csv file is approximately 226.65 kB in size and contains 1103 records. While specific numbers for rows or records for all cities are not explicitly available, the structure is consistent across the included city data files.Usage
This dataset is ideal for:
- Gaining insight into Airbnb listing costs in prominent European cities.
- Exploring general trends in prices across Europe.
- Conducting deeper spatial econometric analysis to identify determinants of Airbnb prices.
- Analysing spatial trends in Airbnb prices to find favourable cities for hosting.
- Comparing weekday versus weekend booking patterns to project rental rates for vacationers and business travellers.
- Assessing the effectiveness of existing policy changes concerning vacation rentals.
- Calculating desired summary statistics, performing statistical analysis, and visualising results using GIS software.
Coverage
The dataset focuses on Airbnb listings in some of the most popular European cities. Geographic scope is defined by location coordinates (
lng and lat), and specific city data files are provided (e.g., for Vienna and Amsterdam). The time range covers both weekday and weekend booking patterns. There is no explicit demographic scope beyond general host and guest interactions, and no specific notes on data availability for particular groups or years are given.License
**CC0 1.0 Universal (CC0 1.0) - Public Domain
Who Can Use It
This dataset is valuable for:
- Individuals and companies seeking to understand Airbnb pricing dynamics.
- Researchers and analysts interested in spatial econometrics, market analysis, and urban studies.
- Data scientists looking to build predictive models for rental prices or identify key price determinants.
- Anyone interested in travel and accommodation trends within European cities.
Dataset Name Suggestions
- Airbnb Prices in European Cities
- European Airbnb Listings Data
- City Airbnb Price Determinants
- Europe Rental Price Analysis
Attributes
Original Data Source: European Airbnb Listings Data
QUALITY