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California Airbnb Property Data
Data Science and Analytics
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About
This data set provides extensive information about Airbnb properties listed in Los Angeles, California. It offers a wealth of details suitable for analyzing short-term rental trends, exploring traveller behaviour, and studying pricing dynamics within one of the most vibrant tourism markets in the U.S. Analysts can investigate how the short-term rental market shapes the local economy and influences housing availability.
Columns
- id: Unique identifier assigned to each property listing.
- name: Property listing name as provided by the host.
- host_id: Unique identifier assigned to the host of the property.
- host_since: Date on which the host joined Airbnb.
- host_response_time: Typical response time of the host to guest inquiries.
- host_is_superhost: Indicates whether the host holds Superhost status (True/False).
- neighbourhood_cleansed: Neighbourhood name where the property is located.
- latitude/longitude: Geographic coordinates for the property location.
- property_type: The type of property listed (e.g., Entire home, Private room).
- accommodates: Maximum number of guests the property can accommodate.
- bedrooms: Number of bedrooms in the property.
- price: Total price based on minimum nights required for booking.
- minimum_nights: Minimum number of nights required for a booking.
- availability_365: Number of days the property is available in the next 365 days.
- number_of_reviews: Total number of reviews received.
- review_scores_rating: Average rating score from guest reviews (maximum 5).
- instant_bookable: Indicates if instant booking is permitted (True/False).
Distribution
The data is contained within a file named
listings.csv, which has a size of 9.65 MB and includes 25 distinct columns. The data set currently holds over 45,500 valid records. Data availability varies across columns; for instance, metrics like bathrooms, beds, and price have approximately 18% missing values, while others like latitude and minimum_nights are 100% valid.Usage
Ideal applications include performing location-based analyses, identifying seasonal occupancy trends, and exploring the popularity of various amenities and property types. Users can analyze host insights, such as response times and Superhost status, to understand their impact on performance. The data is also valuable for investigating neighbourhood-level trends in pricing and guest reviews, which may help identify potential investment opportunities.
Coverage
Geographic Scope: Focused exclusively on Airbnb listings within Los Angeles, California.
Time Range: The information was collected as a snapshot on 04 September 2024.
Scope: Detailed listing characteristics, host performance metrics, geographic coordinates, pricing, and guest feedback for short-term rentals.
License
CC BY-SA 4.0
Who Can Use It
- Data Analysts and Scientists: For building predictive models related to pricing and occupancy rates.
- Real Estate Developers and Investors: To assess market viability, identify high-demand neighbourhoods, and understand the competitive landscape of short-term rentals.
- Academic Researchers: For studying the sociological and economic effects of the short-term rental industry on local housing markets and tourism.
Dataset Name Suggestions
- Los Angeles Airbnb Listings 2024
- LA Short-Term Rental Market Metrics
- California Airbnb Property Data
- Inside Airbnb Los Angeles September Snapshot
Attributes
Original Data Source: California Airbnb Property Data
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