We will create a customized hotels dataset tailored to your specific requirements. Data points may include hotel names, location details, pricing information, amenity lists, guest ratings, occupancy rates, and other relevant metrics.

Utilize our hotels datasets for a variety of applications to boost strategic planning and market analysis. Analyzing these datasets can help organizations understand guest preferences and market trends within the hospitality industry, allowing for more precise operational adjustments and marketing strategies. You can choose to access the complete dataset or a customized subset based on your business needs.

Popular use cases include: optimizing booking strategies, enhancing guest experience, and competitive benchmarking.

The hospitality industry is booming in the last 10 years of India. It is due to growing business opportunities and IT presence in the cities of India, especially metro cities. Here the data is scrapped from MakeMyTrip booking site, which includes price and other information of hotels in different cities of the country. Data was scrapped on 19th August 2023. Only nearly 100 hotels have been added for each city. Other cities will be updated soon.

Available cities🏙️: - Bangalore - Chennai - Hyderabad - Mumbai - Delhi - Kolkata

Data Source: MakeMyTrip🔗

Data Scraping code: GitHub🔗

Columns in dataset: - Hotel Name - Rating - Rating Description - Reviews - Star rating - Location - Nearest Landmark - Distance to the Landmark - Price - Tax

Please Note: 1. Price given here is for one night (base room). 2. Tax given here is slapped on top of the price payable. Therefore, total amount = Price + Tax

The USA Hotels Dataset from Booking.com is a rich collection of data related to hotels across the United States, extracted from Booking.com. This dataset includes essential information about hotel listings, such as hotel names, locations, prices, star ratings, customer reviews, and amenities offered. It's an ideal resource for researchers, data analysts, and businesses looking to explore the hospitality industry, analyze customer preferences, and understand pricing patterns in the U.S. hotel market.

Access 3 million+ US hotel reviews — submit your request today.

Key Features:

• Hotel Information: Includes hotel names, addresses, star ratings, and descriptions.
• Pricing Data: Nightly rates, discounts, and price variations by room type and season.
• Customer Reviews: Aggregated ratings and detailed user feedback from verified guests.
• Amenities: Detailed list of amenities provided by each hotel (e.g., Wi-Fi, parking, spa, swimming pool).
• Geographical Information: Hotel locations including city, state, and proximity to major landmarks.

Use Cases:

• Sentiment Analysis: Analyze customer reviews to gauge hotel service quality and guest satisfaction.
• Price Analysis: Compare pricing across different hotels, locations, and time periods to identify trends.
• Recommendation Systems: Build recommendation engines based on customer ratings, reviews, and preferences.
• Tourism and Hospitality Research: Understand patterns in hotel demand and services across various U.S. cities.

The average price of accommodation in hotels and similar lodging establishments in the Brazilian City of Rio de Janeiro in amounted to 117 U.S. dollars in February 2024. The average price of hotel rooms reached the highest peak of the previous year in January, at 115 U.S. dollars.

As a result of the coronavirus (COVID-19) pandemic the hotel industry has taken a hit in 2020. In May 2020, the average daily rate (ADR) of hotels in Europe was ***** U.S. dollars. Daily hotel prices were lowest in the Asia Pacific region during the same month.

Hotel rate changes worldwide

In each region, corporate average daily hotel rates are forecast to increase by 2020. Asia’s rates are predicted to be higher than the global average, increasing by about ***** percent. Latin America should see a smaller rise of about *** percent, due to the more modest growth in demand within this region. However, these rates were forecast prior to the coronavirus (COVID-19) pandemic therefore will be subject to change.

Hotel occupancy rate

Average daily rates in the hotel industry tend to change throughout the year as they are closely linked to hotel occupancy rates. Specific regions are visited more frequently during certain times of year. For instance, hotel rooms in the Americas were rented more frequently during the summer months, compared to the colder winter months in 2019.

Graph and download economic data for Producer Price Index by Industry: Hotels and Motels, Except Casino Hotels (PCU721110721110) from Dec 2003 to Sep 2025 about casino, hotel, PPI, industry, inflation, price index, indexes, price, and USA.

Dataset is about easily finding an ideal hotel and comparing prices from different websites. Hence deciding the best hotel search comparing accommodation prices. Also refining search results, simply filter by price, distance (e.g. from the beach), star category, facilities, and more. It shows the average rating and extensive reviews from other booking sites, e.g. Hotels.com, Expedia, Agoda, leading hotels, etc. The dataset includes hotel budgets from luxury suites to the heavenly paradise resorts. https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F8355503%2F892a4d89a1795973d64403c1fc9beace%2FHotels%20rev.PNG?generation=1698592504477953&alt=media" alt=""> It includes a large variety of rooms and locations across different popular cities and holiday destinations in the USA.

Dataset

This dataset was created by ShreyasBagwe1015

Released under Apache 2.0

Contents

Expedia Group, Inc. is an American online travel shopping company for consumer and small business travel.

👉🏻 Expedia is the world’s largest online travel agency (OTA) and powers search results for millions of travel shoppers every day. In this competitive market matching users to hotel inventory is very important since users easily jump from website to website. As such, having the best ranking of hotels (“sort”) for specific users with the best integration of price competitiveness gives an OTA the best chance of winning the sale.

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👉🏻 Expedia has provided a dataset that includes shopping and purchase data and information on price competitiveness. The data are organized around a set of “search result impressions”, or the ordered list of hotels that the user sees after they search for a hotel on the Expedia website. In addition to impressions from the existing algorithm, the data contain impressions where the hotels were randomly sorted, to avoid the position bias of the existing algorithm. The user response is provided as a click on a hotel or/and a purchase of a hotel room.

Appended to impressions are the following: 1) Hotel characteristics 2) Location attractiveness of hotels 3) User’s aggregate purchase history 4) Competitive OTA information

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How much does a city trip with your sweetheart cost in Valentine's Day(2025)? Which popular tourist destinations are more budget friendly in Europe? I gathered a dataset which consists of search results from more than 15 cities and 600 hotels in Europe.

I searched booking.com, filtered the results for 2 adults, 5-star hotel, private bathroom, more than 7.0 points in reviews. I preferred to present the prices in USD for enabling future comparisons.

Happy Valentines.

As of October 2024, the city with the most expensive hotel rate in the United States was Boston. Visitors to the East Coast city could expect to pay 320 U.S. dollars for a doube room during that period. Meanwhile, New York ranked third with an average rate of 284 U.S. dollars.

Description :

This dataset contains a snapshot of 2,300+ hotel listings from Gujarat, India, captured on a single day. It's designed for travel recommendation systems, pricing analysis, and exploratory data science projects.

Each Record Provides :

• Hotel Name
• Location (City, Nearby Places)
• Rating & Review Text
• Discounted and Actual Prices
• Facilities like Spa, Pool, Restaurant, etc.
• Destination Name

Ideal for :

• Hotel recommendation systems
• Tourism and pricing analytics
• Facility-based hotel clustering
• Feature engineering and EDA
• Machine learning model training

A hotel dataset that includes ratings and prices typically consists of information about various hotels and their corresponding attributes. Below is a general description of what such a dataset might include:

1. Hotel Information: Hotel ID: A unique identifier for each hotel in the dataset. Hotel Name:The name or title of the hotel. Location:The geographical location or address of the hotel, including details such as city, state, and country.

2.Rating Information: User Ratings:** Ratings provided by users or guests who have stayed at the hotel. Ratings can be on a numerical scale (e.g., 1 to 5 stars) or in another format. Average Rating:The overall average rating of the hotel based on user reviews.

3.Price Information: Room Prices:The cost of different types of rooms offered by the hotel. This may include standard rooms, suites, and other accommodation options. Price Range: The range of prices for different room types.

This type of dataset is valuable for various purposes, such as helping users find hotels that match their preferences based on ratings and prices, conducting data analysis on the hospitality industry, and training machine learning models for predicting hotel ratings or prices based on certain features. Researchers, data analysts, and businesses in the travel and hospitality sector may find such datasets useful for different analyses and decision-making processes.

This Dataset contains information about hotels in Yerevan, you need to predict the price of a hotel per day for 2 adults,data taken from booking.com website.

Here about the description of the columns:

Hotel Names: The names of various hotels or accommodations.

Star Rating: The rating system typically used to indicate the quality or level of luxury of a hotel, often ranging from 1 to 5 stars.

Rating: The overall customer rating or satisfaction score of the hotel, often based on reviews or surveys.

Free Parking: Indicates whether the hotel provides complimentary parking facilities for guests.

Fitness Centre: Specifies whether the hotel has a gym or fitness center available for guests.

Spa and Wellness Centre: Indicates if the hotel offers spa services and wellness facilities.

Airport Shuttle: Specifies whether the hotel provides transportation to and from the airport for guests.

Staff: Refers to the quality and friendliness of the hotel staff.

Facilities: Describes the range and quality of amenities available at the hotel.

Location: Refers to the convenience and desirability of the hotel's location.

Comfort: Reflects the overall comfort level of the rooms and bedding.

Cleanliness: Indicates the cleanliness and hygiene standards of the hotel.

Price Per Day ($): The cost of staying at the hotel (2 adults) per day (in dollars in this case).

The average price of accommodation in hotels and similar lodging establishments in Mexico City in amounted to 110 U.S. dollars in February 2024. The average price of hotel rooms reached the highest peak of the previous year in October, at 119 U.S. dollars.

Hotel Price Index: Hotel Price Index (HPI): Coefficient of variation of the national overall index. Monthly. National.

The OTA, booking websites have a ton of information like pricing, promotions, occupancy reviews, etc about hotels. Our data as a service offering helps our customers get this data through web scraping. The data is refreshed every day and delivered to our customers via Amazon S3, The most common use cases are competitive intelligence and marketing spend optimization.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Lodging Away from Home in U.S. City Average (CUUR0000SEHB) from Dec 1997 to Sep 2025 about lodging, urban, consumer, CPI, housing, inflation, price index, indexes, price, and USA.

The average price of hotel rooms in Buenos Aires, Argentina reached the highest peak of 2023 in November, at over 150 U.S. dollars. In the first two months of the following year, the hotel prices in the South American country stood at around 134 and 109 dollars, respectively.

** Problem Statement:**

 Usually the hotel prices these days are very high during the year due to the Ramadan season, but this year we have COVID-19. We want to know how COVID-19 affects hotel prices, and Is there a relationship between the services provided and the prices?

** Dataset Description:**

This data has been scraping from booking website in KSA and it is contain the important features for The hotel. Hotel_name The Description of the hotel name price The price of hotels in SR 'saudi riyal' Are The distance from the center is in meters and kilometers| Review people rate the hotel based on the price,proximity to the center and services provided facilities Most popular facilities. checklist_facilities services that are provided for a particular purpose. U hotel link