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

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.

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.

Detailed categorization of Airbnb datasets including listings information, host profiles, guest reviews, pricing analysis, and availability calendars - providing comprehensive rental market data for researchers, investors, and short-term rental operators.

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!

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,...

Summary Review data and Listing ID (to facilitate time-based analytics and visualizations linked to a listing). This dataset can be used for NLP usecases, e.g. Exploratory Data Analysis (EDA), Text summarization, sentiment analysis, intent analysis and many more.

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.

he dataset used for this experiment consists of structured data where each row represents an individual Airbnb listing from the United States. The dataset contains approximately 50,000 rows and 15 columns, capturing detailed information about various Airbnb properties across different locations. Each row corresponds to a unique listing and includes features such as listing_id, host_id, city, property_type, room_type, price, number_of_reviews, and additional attributes that can potentially influence the listing price. The main objective of this experiment is to predict the listing price, which is a numeric and continuous variable, based on the provided input features. By utilizing various machine learning regression techniques, such as Random Forest Regressor or XGBoost, the goal is to model the relationships between the property features and the final listing price accurately. Preprocessing steps including handling missing values, encoding categorical variables, and outlier removal will be applied to ensure high data quality. The predictive models will be evaluated based on metrics such as Mean Squared Error (MSE) and R-squared (R²), ensuring robust and interpretable results.

Listings per region on Airbnb declined from 2020 to 2021. Globally in 2021, there were a total of 12.7 million listings.

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.

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.Data is aggregated per neighborhood (defined by AirBnB) and per room type (Entire flat / Private room / Shared room)

The New York City Airbnb 2019 Open Data is a dataset containing varius details about a listed unit, when the goal is to predict the rental price of a unit.

This dataset contains the details for units listed in NYC during 2019, was adapted from the following open kaggle dataset: https://www.kaggle.com/datasets/dgomonov/new-york-city-airbnb-open-data. This, in turn was downloaded from the Airbnb data repository http://insideairbnb.com/get-the-data.

This dataset is licensed under the CC0 1.0 Universal License (https://creativecommons.org/publicdomain/zero/1.0/).

The typical ML task in this dataset is to build a model that predicts the average rental price of a unit.

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.

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.

Explore our comprehensive Airbnb Open Data dataset, featuring detailed listings, reviews, and calendar entries from New York City. Perfect for data scientists and marketers.

Metrics that can be unearthed will be ones contained in the email booking invoice such as Hotel name, type of room, dates, check in and check out times, price paid, duration of stay. We can go back to 5 years of history.

We also have cancellation emails.

Any hotel vendor can be requested too. We will conduct a search in our database to see if it justifies a parser build to extract the data.

Please contact michelle@measurable.ai for a demo or more data samples.

Comprehensive Airbnb dataset for Miami, 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.

Dataset

This dataset was created by Keren PEREZ

Contents

Airbnb has a total of 6,132 employees that work for the company. 52.5% of Airbnb workers are male and 47.5% are female.