About columns

1- ID : unique identifier of each booking

2- n_adults : Number of adults

3- n_children : Number of Children

4- weekend_nights : Number of weekend nights (Saturday or Sunday) the guest stayed or booked to stay at the hotel

5- week_nights : Number of week nights (Monday to Friday) the guest stayed or booked to stay at the hotel

6- meal_plan : Type of meal plan booked by the customer

7- car_parking_space : Does the customer require a car parking space? (0 - No, 1- Yes)

8- room_type: Type of room reserved by the customer. The values are ciphered (encoded) by INN Hotels.

9- lead_time: Number of days between the date of booking and the arrival date

10- year : Year of arrival date

11- month : Month of arrival date

12- date : Date of the month

13- market_segment : Market segment designation.

14- repeated_guest : Is the customer a repeated guest? (0 - No, 1- Yes)

15- previous_cancellations : Number of previous bookings that were canceled by the customer prior to the current booking

16- previous_bookings_not_canceled : Number of previous bookings not canceled by the customer prior to the current booking

17- avg_room_price : Average price per day of the reservation; prices of the rooms are dynamic. (in euros)

18- special_requests : Total number of special requests made by the customer (e.g. high floor, view from the room, etc)

19- status : Flag indicating if the booking was canceled or not.

Data includes occupancy rates, average daily rates, and revenue per available room.

Data on the average achieved hotel room rate by hotel category in Hong Kong in the past five years

No. of Hotel Room: Tourist Center: Tuxtla Gutiérrez data was reported at 29,317.000 Unit in 31 Mar 2024. This records an increase from the previous number of 29,301.000 Unit for 24 Mar 2024. No. of Hotel Room: Tourist Center: Tuxtla Gutiérrez data is updated weekly, averaging 24,465.000 Unit from May 2003 (Median) to 31 Mar 2024, with 1076 observations. The data reached an all-time high of 31,346.000 Unit in 31 May 2020 and a record low of 15,126.000 Unit in 06 Jul 2003. No. of Hotel Room: Tourist Center: Tuxtla Gutiérrez data remains active status in CEIC and is reported by Secretary of Tourism. The data is categorized under Global Database’s Mexico – Table MX.Q019: Number of Hotel Room: by Tourist Center. [COVID-19-IMPACT]

The dataset illustrates average number of hotel rooms and beds, average number and percentage of occupation By star rating in the United Arab Emirates from 1985 until 2005 and from 2010 until 2013.

This table presents an overview of of the capacity (type of accommodation, rooms, beds) in the Netherlands in all hotels, motels, boarding houses, apartments with hotel services, youth accommodation and bed & breakfasts with at least 5 sleeping places. The figures can be broken down by star rating. Figures are available for The Netherlands as a whole, and for the city of Amsterdam.

The breakdown by star rating is based on the opinion of the accommodation itself. The star rating does not have to be officially registered. The breakdown contains all types of accommodation mentioned above, not just hotels. The '5 stars' category contains 5 star hotels, but also for instance 5 star bed&breakfasts.

Break in series: Figures on guests and overnight stays per star rating for the years until 2015, that were published before, were based on offical registrations of the number of stars by the 'Bedrijfschap Horeca en Catering'. This official registration does no longer exist. Therefore, Statistics Netherlands started asking accommodations about their number of stars in its annual survey. For this reason, the figures in this table are not directly comparable with figures published about the years until 2015.

Data available from: 2017

Status of the figures: The figures for 2024 are provisional and al other figures are final.

Changes as of 11 July 2025: The provisional figures for May 2025 have been added.

When will new figures be published? Figures of a new month become available within three months after the end of that month, these are provisional figures. The figures for the complete year are revised one month after publication of the December figures, these are revised provisional figures. Two months later definite figures will be published.

This dataset can be used for the following applications and more:

** * Analyzing trends** Just as an example, you can see estimate how room occupancy must have been affected by the Covid 19 pandemic.

*** Sentiment Analysis / Opinion Mining** Using NLP techniques one can find out what the average user’s sentiment is towards each of the featured hotels in this dataset.

*** Topic / Aspect Extraction** Using categorization techniques one can quickly figure out how each of the hotels featured in this dataset fairs on attributes such as room quality, staff, food, check-in process, etc.

***Competitor Analysis** If you would like to find out what customers think about your competitors, a tailored dataset like the one featured in this blog post can enable you to do so with simple data analysis or visualization techniques.

No. of Hotel Room: Tourist Center: Culiacan data was reported at 12,033.000 Unit in 31 Mar 2024. This stayed constant from the previous number of 12,033.000 Unit for 24 Mar 2024. No. of Hotel Room: Tourist Center: Culiacan data is updated weekly, averaging 16,709.000 Unit from Jan 2006 (Median) to 31 Mar 2024, with 952 observations. The data reached an all-time high of 19,915.000 Unit in 28 Nov 2021 and a record low of 12,033.000 Unit in 31 Mar 2024. No. of Hotel Room: Tourist Center: Culiacan data remains active status in CEIC and is reported by Secretary of Tourism. The data is categorized under Global Database’s Mexico – Table MX.Q019: Number of Hotel Room: by Tourist Center. [COVID-19-IMPACT]

Customer behavior and booking possibilities have been radically changed by online hotel reservation channels. Cancellations or no-shows cause a significant number of hotel reservations to be canceled. Cancellations can be caused by a variety of factors, such as scheduling conflicts, changes in plans, etc. In many cases, this is made easier by the possibility of doing so free or at a low cost, which is beneficial for hotel guests but less desirable and possibly revenue-diminishing for hotels.

As a Data Scientist, your job is to build a Machine Learning model to help the Hotel Owners better understand if the customer is going to honor the reservation or cancel it ?

Dataset Description The file contains the different attributes of customers' reservation details. The detailed data dictionary is given below Booking_ID: unique identifier of each booking No of adults: Number of adults No of children: Number of Children noofweekend_nights: Number of weekend nights (Saturday or Sunday) the guest stayed or booked to stay at the hotel noofweek_nights: Number of week nights (Monday to Friday) the guest stayed or booked to stay at the hotel typeofmeal_plan: Type of meal plan booked by the customer: requiredcarparking_space: Does the customer require a car parking space? (0 - No, 1- Yes) roomtypereserved: Type of room reserved by the customer. The values are ciphered (encoded) by INN Hotels. lead_time: Number of days between the date of booking and the arrival date arrival_year: Year of arrival date arrival_month: Month of arrival date arrival_date: Date of the month Market segment type: Market segment designation. repeated_guest: Is the customer a repeated guest? (0 - No, 1- Yes) noofprevious_cancellations: Number of previous bookings that were canceled by the customer prior to the current booking noofpreviousbookingsnot_canceled: Number of previous bookings not canceled by the customer prior to the current booking avgpriceper_room: Average price per day of the reservation; prices of the rooms are dynamic. (in euros) noofspecial_requests: Total number of special requests made by the customer (e.g. high floor, view from the room, etc) booking_status: Flag indicating if the booking was canceled or not.

No. of Hotel Room: Tourist Center: San Felipe data was reported at 5,789.000 Unit in 31 Mar 2024. This stayed constant from the previous number of 5,789.000 Unit for 24 Mar 2024. No. of Hotel Room: Tourist Center: San Felipe data is updated weekly, averaging 4,673.000 Unit from Jan 2008 (Median) to 31 Mar 2024, with 826 observations. The data reached an all-time high of 6,251.000 Unit in 30 Jun 2019 and a record low of 2,506.000 Unit in 03 Jan 2016. No. of Hotel Room: Tourist Center: San Felipe data remains active status in CEIC and is reported by Secretary of Tourism. The data is categorized under Global Database’s Mexico – Table MX.Q019: Number of Hotel Room: by Tourist Center. [COVID-19-IMPACT]

No. of Hotel Room: Tourist Center: Valladolid data was reported at 7,706.000 Unit in 28 Apr 2024. This records an increase from the previous number of 7,676.000 Unit for 21 Apr 2024. No. of Hotel Room: Tourist Center: Valladolid data is updated weekly, averaging 4,585.000 Unit from Jan 2005 (Median) to 28 Apr 2024, with 961 observations. The data reached an all-time high of 7,902.000 Unit in 03 Dec 2023 and a record low of 3,250.000 Unit in 28 Oct 2007. No. of Hotel Room: Tourist Center: Valladolid data remains active status in CEIC and is reported by Secretary of Tourism. The data is categorized under Global Database’s Mexico – Table MX.Q019: Number of Hotel Room: by Tourist Center. [COVID-19-IMPACT]

Hong Kong Average Achieved Hotel Room Rate: All Hotels data was reported at 1,567.000 HKD in Oct 2018. This records an increase from the previous number of 1,305.000 HKD for Sep 2018. Hong Kong Average Achieved Hotel Room Rate: All Hotels data is updated monthly, averaging 1,130.500 HKD from Jul 1998 (Median) to Oct 2018, with 244 observations. The data reached an all-time high of 1,678.000 HKD in Oct 2012 and a record low of 552.000 HKD in Feb 1999. Hong Kong Average Achieved Hotel Room Rate: All Hotels data remains active status in CEIC and is reported by Hong Kong Tourism Board. The data is categorized under Global Database’s Hong Kong SAR – Table HK.Q023: Hotel Statistics: Average Achieved Hotel Room Rate.

Colombia Hotel Rates: Real Index data was reported at 11.631 2005=100 in May 2020. This records an increase from the previous number of 10.021 2005=100 for Apr 2020. Colombia Hotel Rates: Real Index data is updated monthly, averaging 127.868 2005=100 from Jul 2004 (Median) to May 2020, with 191 observations. The data reached an all-time high of 221.798 2005=100 in Dec 2019 and a record low of 10.021 2005=100 in Apr 2020. Colombia Hotel Rates: Real Index data remains active status in CEIC and is reported by National Administrative Department of Statistics. The data is categorized under Global Database’s Colombia – Table CO.Q002: Hotel Rates and Average Room Rate Index: 2005=100.

IHIS: Average Room Rates per Hotel: Mussoorie data was reported at 5,467.000 INR in 2017. This records a decrease from the previous number of 5,670.000 INR for 2016. IHIS: Average Room Rates per Hotel: Mussoorie data is updated yearly, averaging 2,997.000 INR from Mar 1999 (Median) to 2017, with 13 observations. The data reached an all-time high of 6,078.000 INR in 2010 and a record low of 656.000 INR in 2006. IHIS: Average Room Rates per Hotel: Mussoorie data remains active status in CEIC and is reported by The Federation of Hotel & Restaurant Associations of India. The data is categorized under India Premium Database’s Hotel Sector – Table IN.QHD004: Indian Hotel Industry Survey: Average Room Rates per Hotel: by Cities.

China Hotel Room Occupancy Rate: Total data was reported at 50.690 % in 2023. This records an increase from the previous number of 38.350 % for 2022. China Hotel Room Occupancy Rate: Total data is updated yearly, averaging 56.180 % from Dec 1999 (Median) to 2023, with 25 observations. The data reached an all-time high of 61.030 % in 2006 and a record low of 38.350 % in 2022. China Hotel Room Occupancy Rate: Total data remains active status in CEIC and is reported by Ministry of Culture and Tourism. The data is categorized under Global Database’s China – Table CN.QHA: Star-Rated Hotel: Room Occupancy Rate.

Hong Kong Average Achieved Hotel Room Rate: High Tariff A data was reported at 2,428.000 HKD in Oct 2018. This records an increase from the previous number of 2,059.000 HKD for Sep 2018. Hong Kong Average Achieved Hotel Room Rate: High Tariff A data is updated monthly, averaging 1,929.500 HKD from Jul 1998 (Median) to Oct 2018, with 244 observations. The data reached an all-time high of 2,721.000 HKD in Oct 2012 and a record low of 969.000 HKD in Aug 2003. Hong Kong Average Achieved Hotel Room Rate: High Tariff A data remains active status in CEIC and is reported by Hong Kong Tourism Board. The data is categorized under Global Database’s Hong Kong SAR – Table HK.Q023: Hotel Statistics: Average Achieved Hotel Room Rate.

IHIS: Average Room Rates per Hotel: Mysore data was reported at 1,149.000 INR in 2017. This records a decrease from the previous number of 4,354.000 INR for 2016. IHIS: Average Room Rates per Hotel: Mysore data is updated yearly, averaging 1,613.500 INR from Mar 1999 (Median) to 2017, with 16 observations. The data reached an all-time high of 4,634.000 INR in 2011 and a record low of 660.000 INR in 2001. IHIS: Average Room Rates per Hotel: Mysore data remains active status in CEIC and is reported by The Federation of Hotel & Restaurant Associations of India. The data is categorized under India Premium Database’s Hotel Sector – Table IN.QHD004: Indian Hotel Industry Survey: Average Room Rates per Hotel: by Cities.

Number of Hotel Rooms: Goa data was reported at 4,402.000 Unit in 2020. This records a decrease from the previous number of 4,961.000 Unit for 2019. Number of Hotel Rooms: Goa data is updated yearly, averaging 4,649.500 Unit from Dec 2004 (Median) to 2020, with 14 observations. The data reached an all-time high of 7,464.000 Unit in 2004 and a record low of 3,627.000 Unit in 2005. Number of Hotel Rooms: Goa data remains active status in CEIC and is reported by Ministry of Tourism. The data is categorized under India Premium Database’s Hotel Sector – Table IN.QHA004: Number of Hotel Rooms: by States.

India IHIS: Average Room Rates Per Hotel: Five-Star Deluxe data was reported at 8,638.000 INR in 2017. This records an increase from the previous number of 8,494.000 INR for 2016. India IHIS: Average Room Rates Per Hotel: Five-Star Deluxe data is updated yearly, averaging 8,112.000 INR from Mar 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 10,717.000 INR in 2008 and a record low of 3,820.000 INR in 2003. India IHIS: Average Room Rates Per Hotel: Five-Star Deluxe data remains active status in CEIC and is reported by Federation of Hotel & Restaurant Associations of India. The data is categorized under India Premium Database’s Hotel Sector – Table IN.QHD003: Indian Hotel Industry Survey: Average Room Rates per Hotel.

Macau Hotel Room Rate: All Type of Hotels data was reported at 1,385.300 MOP in Oct 2018. This records an increase from the previous number of 1,340.500 MOP for Sep 2018. Macau Hotel Room Rate: All Type of Hotels data is updated monthly, averaging 1,298.680 MOP from Jan 2007 (Median) to Oct 2018, with 142 observations. The data reached an all-time high of 1,848.400 MOP in Feb 2014 and a record low of 622.850 MOP in Mar 2007. Macau Hotel Room Rate: All Type of Hotels data remains active status in CEIC and is reported by Macau Government Tourism Office. The data is categorized under Global Database’s Macau SAR – Table MO.Q012: Average Hotel Room Rate.