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

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

In 2007, a cash-strapped Brian Chesky came up with a shrewd way to pay his $1,200 San Francisco apartment rent. He would offer “Air bed and breakfast”, which consisted of three airbeds,...

Airbnb, a home sharing economy platform, gives users an alternative to traditional hotel accommodation by allowing them to rent accommodation from people who are willing to share their homes. In 2024, ************* earned the largest regional share of Airbnb's revenue at ** percent. Meanwhile, the Europe and the Middle East and Africa (EMEA) region ranked second at ** percent.

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.

************* was the region that brought in the highest amount of Airbnb’s worldwide revenue in 2024, at ************ U.S. dollars. As the company is based in the United States, this is not surprising. However, the Europe, Middle East, and Africa (EMEA) region was not too far behind with *********** U.S. dollars in revenue.************** also reported the highest average number of nights booked by region with Airbnb in 2024.

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.

The region with the most nights and experiences booked with Airbnb worldwide in 2024 was Europe, the Middle East, and Africa (or EMEA). That year, the EMEA region reported *** million bookings. Asia Pacific had the lowest number of bookings at ** million. The Asia Pacific region also had the lowest average number of nights per Airbnb booking in 2024.

What makes your data unique? - We have our proprietary AI to clean outliers and to calculate occupancy rate accurately.

How is the data generally sourced? - Web scraped data from Airbnb. Scraped on a weekly basis.

What are the primary use-cases or verticals of this Data Product? - Tourism & DMO: A one-page CSV will give you a clear picture of the private lodging sector in your entire country. - Property Management: Understand your market to expand your business strategically. - Short-term rental investor: Identify profitable areas.

Do you cover country X or city Y?

We have data coverage from the entire world. Therefore, if you can't find the exact dataset you need, feel free to drop us a message. Our clients have bought datasets like 1) Airbnb data by US zipcode 2) Airbnb data by European cities 3) Airbnb data by African countries.

gradio/NYC-Airbnb-Open-Data dataset hosted on Hugging Face and contributed by the HF Datasets community

Airbnb, a home sharing economy platform, gives users an alternative to traditional hotel accommodation by allowing them to rent accommodation from people who are willing to share their homes. In 2024, North America had the largest regional share of gross booking value at ** percent.

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, .tsv, and .xlsx.

Recall that CSV, TSV, and Excel files are three common formats for storing data. Three 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 data/airbnb_room_type.xlsx This is an Excel file containing data on Airbnb listing descriptions and room types.

listing_id: unique identifier of listing description: listing description room_type: Airbnb has three types of rooms: shared rooms, private rooms, and entire homes/apartments data/airbnb_last_review.tsv This is a TSV file containing data on Airbnb host names and review dates.

listing_id: unique identifier of listing host_name: name of listing host last_review: date when the listing was last reviewed

Airbnb® is an American company operating an online marketplace for lodging, primarily for vacation rentals. The purpose of this study is to perform an exploratory data analysis of the two datasets containing Airbnb® listings and across 10 major cities. We aim to use various data visualizations to gain valuable insight on the effects of pricing, covid, and more!

This dataset shows main information about rooms available on AirBnB. Information come from the open data website of Air Bnb wich covered major cities worldwide.For anonymizing data, precision of geo-coordinates point is 300m.

Comprehensive Airbnb dataset for Special Region of Jakarta, Indonesia 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 2025, Airbnbs in Perth, Western Australia, had the highest average occupancy rates across the Australian cities and regions represented, with an average occupancy of around ** percent. Airbnbs in the Surfers Paradise, Brisbane, and Gold Coast areas had the next highest occupancy rates that year.

Inside Airbnb is an independent, non-commercial set of tools and data that allows you to explore how Airbnb is really being used in cities around the world.By analyzing publicly available information about a city's Airbnb's listings, Inside Airbnb provides filters and key metrics so you can see how Airbnb is being used to compete with the residential housing market.With Inside Airbnb, you can ask fundamental questions about Airbnb in any neighbourhood, or across the city as a whole. Questions such as: "How many listings are in my neighbourhood and where are they?""How many houses and apartments are being rented out frequently to tourists and not to long-term residents?""How much are hosts making from renting to tourists (compare that to long-term rentals)?""Which hosts are running a business with multiple listings and where they?"The tools are presented simply, and can also be used to answer more complicated questions, such as: "Show me all the highly available listings in Bedford-Stuyvesant in Brooklyn, New York City, which are for the 'entire home or apartment' that have a review in the last 6 months AND booked frequently AND where the host has other listings."These questions (and the answers) get to the core of the debate for many cities around the world, with Airbnb claiming that their hosts only occasionally rent the homes in which they live.In addition, many city or state legislation or ordinances that address residential housing, short term or vacation rentals, and zoning usually make reference to allowed use, including: how many nights a dwelling is rented per yearminimum nights staywhether the host is presenthow many rooms are being rented in a buildingthe number of occupants allowed in a rentalwhether the listing is licensedThe Inside Airbnb tool or data can be used to answer some of these questions.The data behind the Inside Airbnb site is sourced from publicly available information from the Airbnb site.The data has been analyzed, cleansed and aggregated where appropriate to faciliate public discussion. Read more disclaimers here.If you would like to do further analysis or produce alternate visualisations of the data, it is available below under a Creative Commons CC0 1.0 Universal (CC0 1.0) "Public Domain Dedication" license.

This dataset is used in the introductory course Explore and Search for data in ODS Academy, Opendatasoft's training portal.Inside Airbnb is an independent, non-commercial set of tools and data that allows you to explore how Airbnb is really being used in cities around the world.By analyzing publicly available information about a city's Airbnb's listings, Inside Airbnb provides filters and key metrics so you can see how Airbnb is being used to compete with the residential housing market.With Inside Airbnb, you can ask fundamental questions about Airbnb in any neighbourhood, or across the city as a whole. Questions such as: "How many listings are in my neighbourhood and where are they?""How many houses and apartments are being rented out frequently to tourists and not to long-term residents?""How much are hosts making from renting to tourists (compare that to long-term rentals)?""Which hosts are running a business with multiple listings and where they?"The tools are presented simply, and can also be used to answer more complicated questions, such as: "Show me all the highly available listings in Bedford-Stuyvesant in Brooklyn, New York City, which are for the 'entire home or apartment' that have a review in the last 6 months AND booked frequently AND where the host has other listings."These questions (and the answers) get to the core of the debate for many cities around the world, with Airbnb claiming that their hosts only occasionally rent the homes in which they live.In addition, many city or state legislation or ordinances that address residential housing, short term or vacation rentals, and zoning usually make reference to allowed use, including: how many nights a dwelling is rented per yearminimum nights staywhether the host is presenthow many rooms are being rented in a buildingthe number of occupants allowed in a rentalwhether the listing is licensedThe Inside Airbnb tool or data can be used to answer some of these questions.The data behind the Inside Airbnb site is sourced from publicly available information from the Airbnb site.The data has been analyzed, cleansed and aggregated where appropriate to faciliate public discussion. Read more disclaimers here.If you would like to do further analysis or produce alternate visualisations of the data, it is available below under a Creative Commons CC0 1.0 Universal (CC0 1.0) "Public Domain Dedication" license.

Point data representing Airbnb listing for 44 cities across the world recorded between year 2015 - 2017. These listings are downloaded from Inside Airbnb (URL: http://insideairbnb.com/get-the-data.html), which is an independent, non-commercial set of tools and data that allow user to explore how Airbnb is being used in cities around the world.

Data Set Information

This data set describes the listing activity of Airbnb homestays in New Orleans, Louisiana, as part of the Inside Airbnb initiative. The data set was compiled on November 7, 2021. See the New Orleans Airbnb data visually here.

Some personally identifying information has been removed from the data uploaded here.

Contents

The following Airbnb activity is included in this New Orleans data set:

Listings, including full descriptions and average review score (new_orleans_airbnb_listings.csv) Reviews, including unique id for each reviewer and detailed comments (reviews.csv)

Acknowledgements

Data credit goes to Murray Cox and Inside Airbnb. The original source for this particular New Orleans data can be found here--where you can also find information on the different listing ids and their price and availability for different calendar dates (if you're interested in looking at how Airbnb rental listing price fluctuates over time).

Context

The data set can be used to answer some interesting questions, such as: - Can you predict how much a short-term rental in New Orleans should charge per night based on it's location and amenities? - Can you describe the vibe of each neighborhood in using listing descriptions? - What are the most common amenities to have among short-term rental listings in New Orleans? - What elements contribute to a popular or highly-rated listing? - Is there any noticeable difference in favorability among different NOLA neighborhood/areas and what could be the reason for it?

Furthermore, it's also important to note that Inside Airbnb (provider of dataset) is a mission driven activist project with the objective to provide data that quantifies the impact of short-term rentals on housing and residential communities; and also provides a platform to support advocacy for policies to protect cities from the impacts of short-term rentals.

According to travel guides, New Orleans is one of the top ten most-visited cities in the United States. It was severely affected by Hurricane Katrina in August 2005, which flooded more than 80% of the city, killed more than 1,800 people, and displaced thousands of residents, causing a population decline of over 50%. Since Katrina, major redevelopment efforts have led to a rebound in the city's population. Concerns about gentrification, new residents buying property in formerly closely knit communities, and displacement of longtime residents have all been a major discussion topic.

Bearing the given context in mind, this data set shared by Inside Airbnb also allows you to ask fundamental questions about Airbnb in any neighbourhood, or across the city as a whole, such as: - How many listings are in my neighbourhood and where are they? - How many houses and apartments are being rented out frequently to tourists and not to long-term residents? - How much are hosts making from renting to tourists (compare that to long-term rentals)? - Which hosts are running a business with multiple listings and where they?

The questions (and their answers) get to the core of the debate for many cities around the world, with Airbnb claiming that their hosts only occasionally rent the homes in which they live. In addition, many city or state legislation or ordinances that address residential housing, short term or vacation rentals, and zoning usually make reference to allowed use, including: - how many nights a dwelling is rented per year - minimum nights stay - whether the host is present - how many rooms are being rented in a building - the number of occupants allowed in a rental - whether the listing is licensed

(Visit their site for more details.)