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NYC Airbnb Listings & Metrics
Data Science and Analytics
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About
The listing activity and metrics for Airbnb properties in New York City for the year 2023. It captures key information about hosts, locations, pricing, and availability. This dataset is significant for understanding the short-term rental market dynamics in NYC, offering insights into one of the world's most valuable start-ups and its impact on the hotel, restaurant, and catering (HORECA) industry. The data covers the period from 2011 to 2023.
Columns
- id: A unique identifier for the Airbnb listing.
- name: The name of the listing.
- host_id: A unique identifier for the host or user.
- host_name: The name of the host, typically their first name.
- neighbourhood_group: The main borough or neighbourhood group (e.g., Manhattan, Brooklyn) geocoded from latitude and longitude.
- neighbourhood: The specific neighbourhood within the group.
- latitude: The latitude coordinate of the listing.
- longitude: The longitude coordinate of the listing.
- room_type: The type of space being offered (e.g., Entire home/apt, Private room).
- price: The price of the listing per night.
- minimum_nights: The minimum number of nights required for a stay.
- number_of_reviews: The total count of reviews a listing has received.
- last_review: The date of the most recent review.
- reviews_per_month: The average number of reviews the listing receives per month.
- calculated_host_listings_count: The total count of listings a host has.
- availability_365: The number of days the listing is available for booking out of 365.
- number_of_reviews_ltm: The number of reviews the listing received in the last twelve months (ltm).
- license: The license number for the listing, where applicable.
Distribution
The data is provided in a single CSV file named
NYC-Airbnb-2023.csv with a size of 6.64 MB. The dataset is structured with 18 columns. The sources do not provide a specific row count, but metrics indicate a valid count of 42.9k records for most columns.Usage
This dataset is ideal for a variety of analytical and business purposes. Key use cases include:
- Analysing pricing trends across different NYC boroughs and neighbourhoods.
- Understanding the relationship between availability, price, and number of reviews.
- Identifying the most popular types of accommodations.
- Market research for the travel, hospitality, and real estate industries.
- Building predictive models for rental pricing or booking frequency.
Coverage
The dataset's geographical scope is New York City (NYC), covering its main neighbourhood groups including Manhattan and Brooklyn. The temporal coverage spans from 2011 to 2023, with a focus on metrics from 2023.
License
CC0: Public Domain
Who Can Use It
- Data Scientists and Analysts: For market trend analysis, price modelling, and geographical visualisation.
- Real Estate Investors: To identify lucrative areas for short-term rental properties.
- Urban Planners and Policymakers: To study the impact of short-term rentals on housing and local economies.
- Business Strategists: For competitive analysis within the hospitality sector.
- Academic Researchers: For studies on the sharing economy and its effects on urban environments.
Dataset Name Suggestions
- NYC Airbnb Listings & Metrics 2023
- New York City Short-Term Rental Data 2023
- Airbnb Host and Listing Activity in NYC (2011-2023)
- NYC Hospitality Market: Airbnb Analytics
- Manhattan & Brooklyn Airbnb Trends 2023
Attributes
Original Data Source: NYC Airbnb Listings & Metrics
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