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New Orleans Airbnb Host and Listing Data
Data Science and Analytics
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Free
About
This dataset describes Airbnb homestay listing activity in New Orleans, Louisiana. Compiled on 7 November 2021, it is part of the Inside Airbnb initiative, which aims to quantify the impact of short-term rentals on housing and residential communities. The data includes listing details and reviews, with personally identifying information removed.
It offers insights into the New Orleans short-term rental market, a city significantly impacted by Hurricane Katrina and subsequent redevelopment efforts, which have raised concerns about gentrification and resident displacement. The dataset allows users to explore fundamental questions about Airbnb's presence, such as the number of listings in a neighbourhood, how many properties are rented to tourists versus long-term residents, host earnings, and the prevalence of hosts operating multiple listings. It can also inform discussions around city and state legislation concerning residential housing, short-term rentals, and zoning.
Columns
- id: Airbnb's unique identifier for each listing.
- name: The name given to the listing.
- description: A detailed account of the listing.
- neighborhood_overview: The host's description of the local area.
- host_id: Airbnb's unique identifier for the host or user.
- host_since: The date the host or user account was created. For hosts who also use Airbnb as guests, this may be their guest registration date.
- host_location: The self-reported location of the host.
- host_response_time: The average duration it takes for a host to reply to a message on the Airbnb platform.
- host_response_rate: The percentage of messages a host responds to on the Airbnb platform.
- host_acceptance_rate: The rate at which a host accepts booking requests.
Distribution
The dataset is provided in CSV format, including
new_orleans_airbnb_listings.csv and reviews.csv. Specific total row or record counts are not available within the provided information.However, details on value distribution for certain columns are present:
host_id: 5,752 unique values.host_location: 5,487 unique values, with 68% reporting 'New Orleans, Louisiana, United States', 12% from 'US', and 20% from 'Other'.host_response_time: 61% of hosts respond 'within an hour', with 26% being null.host_response_rate: 58% of hosts have a '100%' response rate, with 26% being null.host_acceptance_rate: 28% of hosts have a '100%' acceptance rate, with 24% being null.host_sincedates range from 13 December 2008 to 20 October 2021.
Usage
This dataset is ideal for:
- Predicting short-term rental charges in New Orleans based on location and amenities.
- Describing the 'vibe' of each neighbourhood using listing descriptions, suitable for Natural Language Processing (NLP) tasks.
- Identifying the most common amenities offered in short-term rental listings.
- Determining factors that contribute to popular or highly-rated listings.
- Analysing differences in favourability among different New Orleans neighbourhoods.
- Exploratory Data Analysis (EDA) and Regression modelling.
- Researching the impact of short-term rentals on housing affordability and community dynamics.
Coverage
The dataset focuses on New Orleans, Louisiana, United States. It covers a time range for host activity from 13 December 2008 to 20 October 2021, with the data compilation date being 7 November 2021. While not directly demographic, the context addresses concerns about gentrification and the displacement of longtime residents in the city.
License
CC-BY
Who Can Use It
- Data Scientists and Analysts: For data science projects, statistical analysis, machine learning model building, and deriving insights from listing and review data.
- Urban Planners and Policy Makers: To understand the spread of short-term rentals, their impact on local housing markets, and to inform regulations and zoning decisions.
- Researchers and Activists: Studying the socio-economic effects of tourism and short-term rentals on urban communities, particularly concerning housing and gentrification.
- Real Estate Professionals: To gain market intelligence on short-term rental trends, pricing, and amenities in New Orleans.
- Hospitality Industry Stakeholders: To analyse competition and market demand in the New Orleans accommodation sector.
Dataset Name Suggestions
- New Orleans Airbnb Listings and Reviews
- New Orleans Airbnb Host and Listing Data
- NOLA Airbnb Activity Dataset
- Inside Airbnb New Orleans
- New Orleans Short-Term Rental Analysis Data
Attributes
Original Data Source: New Orleans Airbnb Listings and Reviews
QUALITY