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Airbnb Host and Pricing Data Milan
Data Science and Analytics
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About
Airbnb listing activity and associated metrics within Milan, Italy, for the year 2021 are detailed in this file. It provides granular insights into the short-term rental market, enabling analysis of host behaviour, geographical availability, and pricing strategies. Since 2008, guests and hosts have utilized the platform to expand travel possibilities; this file captures that activity within a major European urban centre, offering essential data for making market predictions and drawing conclusions about the local real estate and tourism landscape.
Columns
- id: The unique identifier assigned to the apartment.
- name: The title or name of the apartment listing.
- host_id: The unique identifier for the host.
- host_name: The name of the host managing the listing.
- neighbourhood: The specific district or area in Milan where the apartment is located.
- latitude: The latitudinal geographic coordinate of the property.
- longitude: The longitudinal geographic coordinate of the property.
- room_type: The classification of the accommodation (e.g., Entire home/apt, Private room).
- price: The cost per night for one adult.
- minimum_nights: The minimum number of nights required to book the property.
- number_of_reviews: The total count of reviews the listing has received.
- last_review: The date on which the most recent review was submitted.
- reviews_per_month: The average number of reviews the listing receives on a monthly basis.
- calculated_host_listings_count: The total number of listings managed by the specific host on the platform.
- availability_365: The number of days the apartment is available for booking throughout a 365-day year.
Distribution
The file is provided in CSV format with a file size of approximately 2.39 MB. It is structured with 15 columns and contains approximately 18,300 records representing valid individual listings in Milan.
Usage
- Price Prediction: Modelling rental prices based on location, amenities, and room type.
- Location Analysis: Identifying the busiest hosting areas and traffic differences between neighbourhoods.
- Host Behaviour: Analysing the difference between professional property managers (multiple listings) and individual hosts.
- Tourism Trends: Understanding seasonal availability and demand through review frequency.
- Sentiment Analysis: Evaluating guest satisfaction through review volume and frequency.
Coverage
- Geographic: The data is strictly focused on Milan, Italy, covering various neighbourhoods such as Buenos Aires-Venezia and Duomo.
- Time Range: The metrics and listing details are specific to the year 2021.
- Demographic: Covers a wide range of hosts and accommodation types, from single private rooms to entire apartments.
License
CC0: Public Domain
Who Can Use It
- Data Scientists: For training predictive models on real estate pricing.
- Market Analysts: To assess the saturation and competition within the Milan short-term rental market.
- Urban Planners: To study the impact of short-term rentals on housing availability.
- Travel Industry Professionals: To understand accommodation preferences and availability trends.
Dataset Name Suggestions
- Milan Airbnb Listings 2021
- Milan Short-Term Rental Metrics
- 2021 Milan Accommodation Data
- Airbnb Host and Pricing Data Milan
Attributes
Original Data Source: Airbnb Host and Pricing Data Milan
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