Airbnb In NYC

Room Prices, Reviews, and Availability

By Huggingface Hub [source]

About this dataset

This dataset offers a unique and comprehensive look into the expansive Airbnb industry in New York City. We capture 20,000+ Airbnbs with its associated data such as descriptions, rates, reviews and availability. Professionals researching this industry will find it an invaluable resource in providing insight to the ever popular Airbnb market that can be used for their advantage.

This dataset showcases some of the most important attributes for each listing: host name, neighborhood group, location (latitude/longitude coordinates), room type, price per night, minimum nights required to book a stay at this listing , total number of reviews and ratings received by guests over time (including reviews per month and last review date), calculated host listing count (indicates how many listings are offered by each host) along with 365 days worth of availability score. With all these parameters one can understand dynamics of demand & supply & further utilize them accordingly to maximize returns or occupancy greeting never before seen transparency into NYC’s Airbnb scene

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How to use the dataset

This dataset can be used to gain a comprehensive understanding of the Airbnb market in New York City. The data offers descriptions, rates, reviews and availability for over 20,000 Airbnbs in NYC.

Here are few tips on how to use this dataset: - Use the latitude and longitude coordinates to visualize the variety of Airbnbs located across all five boroughs of New York City using mapping programs like Google Maps or ArcGIS. - Determine the versatile price ranges offered by Airbnb listings by looking at the “price” column available for each listing . - Analyze reviews scored by guests who have used an Airbnb in order to better understand customer experience with different services through columns such as “number_of_reviews” and “last_review.
4 Understand how often properties are made available for booking based on their popularity through columns like “availability_365 and reviews_per_month. . 5 Investigate listing host data by looking into their description (host name) as well as number of listings they have booked (calculated host listing count)

Research Ideas

• Determining the listings with the highest satisfaction ratings for potential customers to book.
• Analyzing neighborhood trends in prices, availability, and reviews to identify hot areas of competition within the Airbnb market.
• Predicting future prices throughput examining properties such as review scores and availability rate to provide forecast information to AirBnB owners

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

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.

Columns

File: train.csv | Column name | Description | |:-----------------------------------|:------------------------------------------------------------------------------------| | name | The name of the Airbnb listing. (String) | | host_name | The name of the host of the Airbnb listing. (String) | | neighbourhood_group | The neighbourhood group the Airbnb listing is located in. (String) | | latitude | The latitude coordinate of the Airbnb listing. (Float) | | longitude | The longitude coordinate of the Airbnb listing. (Float) | | room_type | The type of room offered by the Airbnb listing. (String) | | price | The price per night of the Airbnb listing. (Integer) | | minimum_nights | The minimum number of nights required for booking the Airbnb listing. (Integer) | | number_of_reviews | T...

The top 100 Airbnb markets in 2025 are: 1. Los angeles - Strict regulations, 11,250 listings, 67% occupancy rate, $213 daily rate. See other 99 places.

The top 100 Airbnb markets in 2025 are: 1. London - Lenient regulations, 51,638 listings, 73% occupancy rate, $190 daily rate. See other 99 places.

As of December 2024, Airbnb's global market capitalization was **** billion U.S. dollars, down from around **** billion U.S. dollars the previous year. The company's market capitalization peaked in 2021 at over *** billion U.S. dollars.

This dataset provides a snapshot of the Airbnb market in Albany, New York, as of September 5, 2024. Airbnb is a global platform that connects hosts with guests seeking short-term accommodations, offering diverse lodging options ranging from entire homes and apartments to single rooms and shared spaces. Albany, as the capital of New York State, has a unique Airbnb market shaped by its mix of government-related travel, tourism, and local events.

The data includes three files – calendar.csv, listings.csv, and reviews.csv – which together capture key aspects of Albany’s Airbnb ecosystem:

Listings: Details on property types, pricing, and host characteristics.

Calendar: Daily availability and pricing data.

Reviews: Guest feedback on individual listings.

Overall Structure & Analysis Potential:

This dataset offers a rich foundation for analyzing various aspects of the Albany Airbnb market, such as:

Availability & Pricing Trends: By combining calendar.csv and listings.csv, one can examine how pricing and availability fluctuate over time and across different types of listings.

Listing Characteristics: listings.csv provides an overview of the type, size, and features of listings in Albany, helping identify the most common accommodation types and pricing ranges.

Guest Feedback: reviews.csv allows for sentiment analysis and topic modeling to understand guest satisfaction and common issues.

Context

Welcome to New York City (NYC), one of the most-visited cities in the world. As a result, Since 2008 to 2019 there are many Airbnb listings to meet the high demand for temporary lodging for anywhere between a few nights to many months, guests and hosts have used Airbnb to expand on traveling possibilities and present more unique, personalized way of experiencing the world.

Content

This data file includes all needed information from guests name, id, date, neighborhood name and it's listing price to rooms and its type, using dataset you can perform and apply various data cleaning techniques and also to make predictions

You can find complete tutorial about this dataset in this notebook: https://www.kaggle.com/code/ebrahimelgazar/exploring-nyc-airbnb-market

You can find full notebook documentation on this GitHub link: https://github.com/EbGazar/Exploring-NYC-Airbnb-Market

Inspiration

• What is the average price, per night, of an Airbnb listing in NYC?
• How does the average price of an Airbnb listing, per month, compare to the private rental market?
• How many adverts are for private rooms?
• How do Airbnb listing prices compare across the five NYC boroughs?

Comprehensive Airbnb dataset repository offering detailed vacation rental analytics worldwide including property listings, pricing trends, host information, review sentiment analysis, and occupancy rates for short-term rental market intelligence and investment research.

Leverage our Airbnb dataset to gain comprehensive insights into global short-term rental markets. Track property details, pricing trends, reviews, availability, and amenities to optimize pricing strategies, conduct market research, or enhance travel-related applications. Data points may include listing ID, host ID, property type, price, number of reviews, ratings, availability, and more. The dataset is available as a full dataset or a customized subset tailored to your specific needs.

Description

This dataset 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 traveler behavior, and studying pricing dynamics within one of the most vibrant tourism markets in the U.S.

Dataset Context and Purpose

As Airbnb continues to impact urban rental markets, this dataset allows analysts, researchers, and real estate professionals to investigate how the short-term rental market shapes the local economy and influences housing availability. Users can leverage this dataset to perform location-based analysis, identify seasonal occupancy trends, and explore the popularity of amenities and property types.

Content

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_name:Name of the host associated with the property.

host_since:Date on which the host joined Airbnb.

host_response_time: Typical response time of the host to guest inquiries.

host_response_rate:Percentage of guest inquiries that the host responded to.

host_is_superhost: Indicates whether the host is a Superhost (True/False).

neighbourhood_cleansed: Neighborhood name where the property is located.

neighbourhood_group_cleansed: Standardized neighborhood group or district where the property is located.

latitude: Geographic latitude coordinate.

longitude: Geographic longitude coordinate.

property_type: Type of property.

room_type: Type of room offered (e.g., Entire home/apt, Private room, Shared room).

accommodates: Maximum number of guests that the property can accommodate.

bathrooms: Number of bathrooms in the property.

bedrooms: Number of bedrooms in the property.

beds: Number of beds 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 for booking in the next 365 days.

number_of_reviews: Total number of reviews received for the property.

review_scores_rating: Average rating score based on guest reviews (5 is maximum value).

license: License, if applicable.

instant_bookable: Indicates whether guests can book the property instantly (True/False).

Inspiration

• Host Insights: Analyze host behavior, response times, and Superhost status to understand their impact on guest satisfaction and property performance.
• Property Characteristics: Identify popular property types, room types, and amenities, and how they correlate with pricing and occupancy rates.
• Neighborhood Analysis: Explore neighborhood-level trends in pricing, occupancy, and guest reviews to identify popular areas and potential investment opportunities.
• Pricing Strategies: Analyze factors influencing pricing, such as property type, location, amenities, and seasonality.

Source

This dataset is part of Inside Airbnb, Los Angeles California on September 04, 2024. Link found here

Comprehensive Airbnb dataset for Curitiba, Brazil providing detailed vacation rental analytics including property listings, pricing trends, host information, review sentiment analysis, and occupancy rates for short-term rental market intelligence and investment research.

In New York City, one of the United States’ most iconic destinations, Airbnb has established itself as a key player in the accommodation market. In 2025, Airbnb customers booked an average of ** nights per stay, with an average price of *** U.S. dollars per night. Meanwhile, the average income per property was ***** U.S. dollars that year. Are Airbnb rentals expensive in New York City? As of early 2024, the most expensive Airbnb properties per night in the United States were in *************. This was followed by *************************. In comparison, the average cost of a night’s stay at an Airbnb property in New York City is less than half of the cost of a night in *************. How many Airbnb properties are there in New York City? In early 2024, the Airbnb market in New York City offered more than **** thousand properties accommodating to the different needs of visitors to the city. There are various types of Airbnb properties in New York City, the most common of which were entire homes and apartments, followed by private rooms. The majority of Airbnb listings also catered for longer-term stays, in light of city regulations on housing.

The majority of guests on Airbnb are women. Most Airbnb guests are aged 25 to 34.

Comprehensive Airbnb dataset for New York, United States providing detailed vacation rental analytics including property listings, pricing trends, host information, review sentiment analysis, and occupancy rates for short-term rental market intelligence and investment research.

These are the Airbnb statistics on gross revenue by country.

Comprehensive Airbnb dataset for Winter Park, United States providing detailed vacation rental analytics including property listings, pricing trends, host information, review sentiment analysis, and occupancy rates for short-term rental market intelligence and investment research.

The top 19 Airbnb markets in 2025 are: 1. Charlotte - Lenient regulations, 3,199 listings, 61% occupancy rate, $159 daily rate. See other 18 places.

This is the complete breakdown of how much revenue Airbnb makes in commission from listings in each region.

The top 32 Airbnb markets in 2025 are: 1. Austin - Lenient regulations, 9,610 listings, 60% occupancy rate, $176 daily rate. See other 31 places.

Welcome to New York City, one of the most-visited cities in the world. There are many Airbnb listings in New York City to meet the high demand for temporary lodging for travelers, which can be anywhere between a few nights to many months. In this project, we will take a closer look at the New York Airbnb market by combining data from multiple file types like .csv.

This files containing data on 2019 Airbnb listings are available to you:

data/airbnb_price.csv This is a CSV file containing data on Airbnb listing prices and locations.

listing_id: unique identifier of listing price: nightly listing price in USD nbhood_full: name of borough and neighborhood where listing is located

New York City accounted for ****** Airbnb listings in late 2024. Meanwhile, Los Angeles had ****** listings, making it the city with the most Airbnb listings in the ranking.