Dark Mode
PromptCloud Indian Hotel Dataset
Data Science and Analytics
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset provides a pre-crawled collection of 6,000 Indian hotels listed on Booking.com, a prominent travel portal. It represents a subset derived from a much larger dataset of over 94,000 hotels. The data offers an opportunity for deep analysis of hotel properties in India, including their ratings and various property types, serving as a valuable resource for market insights and research within the travel sector.
Columns
address: The street address of the hotel.city: The city where the hotel is located.country: The country of the hotel.crawl_date: The date when the hotel data was extracted.hotel_brand: The brand name associated with the hotel.hotel_description: A textual description of the hotel and its offerings.hotel_facilities: A list of facilities provided by the hotel.hotel_star_rating: The star rating assigned to the hotel.image_count: The number of images available for the hotel.latitude: The geographical latitude coordinate of the hotel.locality: The specific locality or neighbourhood of the hotel.longitude: The geographical longitude coordinate of the hotel.pageurl: The Booking.com URL for the hotel's page.property_id: A unique identifier for the property.property_name: The name of the hotel.property_type: The classification of the hotel (e.g., hotel, guesthouse).province: The province or administrative division of the hotel's location.qts: The QTS (Quality Time Series) related to the hotel.room_count: The total number of rooms available at the hotel.room_type: The different types of rooms offered (e.g., Deluxe Double Room).similar_hotel: Information on hotels considered similar to the listed property.site_review_count: The total count of reviews on Booking.com.site_review_rating: The overall review rating on Booking.com.site_stay_review_rating: Detailed review ratings covering aspects like cleanliness, comfort, and location.sitename: The website name from which data was crawled (Booking.com).special_tag: Any special tags associated with the hotel.state: The state within India where the hotel is situated.uniq_id: A unique identifier for each dataset entry.zone: The geographical zone of the hotel.
Distribution
This dataset is provided in a CSV file format, named
booking_com-travel_sample.csv, with a file size of 12.24 MB. It is structured with 29 distinct columns and includes data for 6,000 individual Indian hotel properties.Usage
This dataset is ideal for analysing hotel property ratings and types within the Indian market. It can be utilised for market research to identify trends in hotel brands and facilities, geographical studies based on latitude and longitude data, and competitive analysis within the Indian hospitality sector. Researchers can also delve into review data to understand customer sentiment and preferences.
Coverage
The dataset's geographic scope is India, encompassing various cities such as New Delhi and Bangalore, and states including Maharashtra and Rajasthan. Specific localities like Paharganj are also detailed. The time range for data collection is concentrated between 16 August 2016 and 1 September 2016. While no specific demographic data is present, the hotel listings generally reflect the broader market using Booking.com.
Data availability notes:
hotel_brand,hotel_description,hotel_facilities,property_id,property_name,room_count, andspecial_taghave a notable percentage of missing values.hotel_star_rating,image_count,similar_hotel,site_review_count,site_review_rating, andsite_stay_review_ratingalso contain missing data, withsite_stay_review_ratinghaving a higher proportion.- Fields such as
locality,province, andzoneare largely missing. statehas a minimal number of missing entries.
License
CC BY-SA 4.0
Who Can Use It
- Data Analysts: For exploring property ratings, types, and market trends.
- Travel and Tourism Businesses: To gain insights into the Indian hotel market, competitor offerings, and customer review patterns.
- Academic Researchers: For studies on hospitality, online travel agencies, and regional market analysis.
- Developers: To build applications or tools that leverage hotel property information.
Dataset Name Suggestions
- Booking.com Indian Hotels Data 2016
- Indian Hospitality Market Snapshot
- Booking.com India Hotel Listings
- India Hotel Data Analysis
- PromptCloud Indian Hotel Dataset
Attributes
Original Data Source: PromptCloud Indian Hotel Dataset
QUALITY