Baselight

Indian Hotels On Goibibo

4,000 Indian hotels on Goibibo

@kaggle.promptcloudhq_hotels_on_goibibo

About this Dataset

Indian Hotels On Goibibo

Context

This is a pre-crawled dataset, taken as subset of a bigger dataset (more than 33344 hotels) that was created by extracting data from goibibo.com, a leading travel site from India.

Content

This dataset has following fields:

  • address
  • area - The sub-city region that this hotel is located in, geographically.
  • city
  • country - Always India.
  • crawl_date
  • guest_recommendation - How many guests that stayed here have recommended this hotels to others on the site.
  • hotel_brand - The chain that owns this hotel, if this hotel is part of a chain.
  • hotel_category
  • hotel_description - A hotel description, as provided by the lister.
  • hotel_facilities -
  • hotel_star_rating - The out-of-five star rating of this hotel.
  • image_count - The number of images provided with the listing.
  • latitude
  • locality
  • longitude
  • pageurl
  • point_of_interest - Nearby locations of interest.
  • property_name
  • property_type - The type of property. Usually a hotel.
  • province
  • qts - Crawl timestamp.
  • query_time_stamp - Copy of qts.
  • review_count_by_category - Reviews for the hotel, broken across several different categories.
  • room_area
  • room_count
  • room_facilities
  • room_type
  • similar_hotel
  • site_review_count - The number of reviews for this hotel left on the site by users.
  • site_review_rating - The overall rating for this hotel by users.
  • site_stay_review_rating
  • sitename - Always goibibo.com
  • state
  • uniq_id

Acknowledgements

This dataset was created by PromptCloud's in-house web-crawling service.

Inspiration

  • Try exploring some of the amenity categories. What do you see?

  • Try applying some natural language processing algorithms to the hotel descriptions. What are the some common words and phrases? How do they relate to the amenities the hotel offers?

  • What can you discover by drilling down further into hotels in different regions?

Tables

Goibibo Com Travel Sample

@kaggle.promptcloudhq_hotels_on_goibibo.goibibo_com_travel_sample
  • 2.59 MB
  • 4000 rows
  • 36 columns
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CREATE TABLE goibibo_com_travel_sample (
  "additional_info" VARCHAR,
  "address" VARCHAR,
  "area" VARCHAR,
  "city" VARCHAR,
  "country" VARCHAR,
  "crawl_date" TIMESTAMP,
  "guest_recommendation" DOUBLE,
  "hotel_brand" VARCHAR,
  "hotel_category" VARCHAR,
  "hotel_description" VARCHAR,
  "hotel_facilities" VARCHAR,
  "hotel_star_rating" BIGINT,
  "image_count" BIGINT,
  "latitude" DOUBLE,
  "locality" VARCHAR,
  "longitude" DOUBLE,
  "pageurl" VARCHAR,
  "point_of_interest" VARCHAR,
  "property_id" VARCHAR,
  "property_name" VARCHAR,
  "property_type" VARCHAR,
  "province" VARCHAR,
  "qts" VARCHAR,
  "query_time_stamp" VARCHAR,
  "review_count_by_category" VARCHAR,
  "room_area" VARCHAR,
  "room_count" BIGINT,
  "room_facilities" VARCHAR,
  "room_type" VARCHAR,
  "similar_hotel" VARCHAR,
  "site_review_count" DOUBLE,
  "site_review_rating" DOUBLE,
  "site_stay_review_rating" VARCHAR,
  "sitename" VARCHAR,
  "state" VARCHAR,
  "uniq_id" VARCHAR
);