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StayZilla 2016 Indian Hospitality Data
Healthcare Providers & Services Utilization
Tags and Keywords
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About
Detailed information on lodging listings extracted from StayZilla.com, an Indian property-sharing platform that operated between 2005 and 2017. The data captures vital attributes of approximately 1,200 property listings, including location, pricing, offered amenities, and detailed textual descriptions. This selection represents a curated sample derived from a larger crawl that documented over 61,000 properties on the site.
Columns
This collection consists of 33 fields providing rich detail on each listing:
- additional_info: Special notes or considerations pertinent to the booking or stay.
- amenities: A list of facilities available at the property, typically pipe (|) delimited.
- check_in_date, check_out_date: Specific dates related to the booking inquiry or crawl.
- city, country: The specific location of the property (country is predominantly India).
- crawl_date, qts, query_time_stamp: Metadata indicating when the property data was extracted.
- description: The primary textual description of the listing provided by the host.
- highlight_value: Specific features or benefits emphasized for the property.
- hotel_star_rating: The official out-of-five star rating, applicable mainly to hotel-type listings.
- image_count, image_urls: Quantity and URLs for images associated with the listing.
- internet: Specifies whether Internet access is available (e.g., 'Free Internet').
- landmark: Points of interest or reference points near the property.
- latitude, longitude: Geographical coordinates for mapping the property location.
- occupancy: Details regarding the number of adults and children allowed for the stay (e.g., '2 Adults 2 Kids').
- pageurl: The direct URL to the listing on the StayZilla website.
- property_address, property_id, property_name: Identification and location details.
- property_type: Categorisation of the listing (e.g., Hotel, House, Resort).
- room_price: The quoted price for the room or stay.
- room_types: Specifications regarding beds and baths (e.g., 'Double Non-A/C Rooms').
- search_term: The term used during the data extraction process.
- service_value: Verification status of the property (e.g., 'Verified', 'Not Verified').
- similar_hotel: Names of listings considered similar by the platform.
- sitename: The source domain (
www.stayzilla.com). - things_to_do, things_to_note: Nearby activities and special information provided by the lister.
- uniq_id: A unique record identifier.
Distribution
The data is available in a CSV file format and is approximately 2.31 MB in size. It comprises 33 distinct fields and includes 1,207 individual property records.
Usage
This data product is perfectly suited for academic research and market analysis focusing on the travel and hospitality technology sector in South Asia. Users can analyse regional variations in pricing and property types. It enables geospatial research to map the spread of short-term rental properties across different Indian cities. Furthermore, the dataset supports natural language processing (NLP) studies on consumer descriptions and listing features. Insights can be generated by comparing this market structure to similar datasets from Western hospitality platforms.
Coverage
The dataset's scope is strongly focused on India, containing properties located in 157 unique cities, with high concentrations in regions like Lucknow and New Delhi. The content reflects a snapshot of the StayZilla platform listings, primarily captured on July 20, 2016. A significant majority of the listings are categorized as Hotels (73%).
License
CC BY-SA 4.0
Who Can Use It
- Economists and Market Researchers: To study the dynamics of the Indian short-term rental market during a period of rapid growth.
- Data Scientists: For developing predictive models on property pricing or star ratings, and for text-mining property descriptions.
- Urban Planners: To understand the geographic distribution and density of hospitality services in urban areas.
Dataset Name Suggestions
- StayZilla 2016 Indian Hospitality Data
- Property Attributes from StayZilla Sample
- Archived Indian Rental Market Data
Attributes
Original Data Source: StayZilla 2016 Indian Hospitality Data
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