Calculating hotel occupancy with R (Last updated: 2025-06-30)

Posted on data.table, rbloggers, rstats

Putting patientcounter to the test by calculating hotel occupancy.

I saw a question on reddit today which can be answered using {patientcounter}

The asker wants to know how to work out how many folk are in a hotel, at any given time, based on check in and check out dates.

Here’s the setup:

check_in_date <- c('2010-01-01', '2010-01-02' ,'2010-01-01',                     '2010-01-08', '2010-01-08', '2010-01-15',                     '2010-01-15', '2010-01-16', '2010-01-19', '2010-01-22')  check_out_date <- c('2010-01-07', '2010-01-04' ,'2010-01-09',                      '2010-01-21', '2010-01-11', '2010-01-22',                     NA, '2010-01-20', '2010-01-25', '2010-01-29')  #NB - the original question has a string instead of the NA value.  # patientcounter can handle the NA, but not the string.  Person = c("John", "Smith", "Alex", "Peter", "Will", "Matt", "Tim", "Kevin", "Tom", "Adam") 

Make the dataframe:

checkin <- as.POSIXct(as.Date(check_in_date)) # make it a datetime checkout <- as.POSIXct(as.Date(check_out_date))  # make it a datetime hotel <- data.frame(checkin, checkout, Person)  hotel 

##       checkin   checkout Person ## 1  2010-01-01 2010-01-07   John ## 2  2010-01-02 2010-01-04  Smith ## 3  2010-01-01 2010-01-09   Alex ## 4  2010-01-08 2010-01-21  Peter ## 5  2010-01-08 2010-01-11   Will ## 6  2010-01-15 2010-01-22   Matt ## 7  2010-01-15       <NA>    Tim ## 8  2010-01-16 2010-01-20  Kevin ## 9  2010-01-19 2010-01-25    Tom ## 10 2010-01-22 2010-01-29   Adam 

Now for patientcounter to do it’s thing…it’s designed for this exact task - getting a census, or count, of people / goods/ items in or at a place at a point in time.

The interval_census function does the work:

#remotes::install_github("johnmackintosh/patientcounter") library(patientcounter) # calculate the number of occupants per day occupancy <- interval_census(hotel,                 identifier = "Person",                 admit = "checkin",                 discharge  = "checkout",                  time_unit = '1 day',                 results = 'total') # grab the date and count columns: occupancy[,.(base_date, N)] 

##      base_date N ##  1: 2010-01-01 2 ##  2: 2010-01-02 3 ##  3: 2010-01-03 3 ##  4: 2010-01-04 2 ##  5: 2010-01-05 2 ##  6: 2010-01-06 2 ##  7: 2010-01-07 1 ##  8: 2010-01-08 3 ##  9: 2010-01-09 2 ## 10: 2010-01-10 2 ## 11: 2010-01-11 1 ## 12: 2010-01-12 1 ## 13: 2010-01-13 1 ## 14: 2010-01-14 1 ## 15: 2010-01-15 3 ## 16: 2010-01-16 4 ## 17: 2010-01-17 4 ## 18: 2010-01-18 4 ## 19: 2010-01-19 5 ## 20: 2010-01-20 4 ## 21: 2010-01-21 3 ## 22: 2010-01-22 3 ## 23: 2010-01-23 3 ## 24: 2010-01-24 3 ## 25: 2010-01-25 2 ## 26: 2010-01-26 2 ## 27: 2010-01-27 2 ## 28: 2010-01-28 2 ##      base_date N 

Job Done :)

There were several answers, and maybe a package is overkill, but this function is fast and scales well. It’s also pretty flexible and has applications outside of healthcare.

Hey, just a heads up! We’ve updated this content with the latest info, and we even put together some extra stuff specifically for our friends in Japan. If you’re interested, feel free to click the link below to check out the full article! https://www.johnmackintosh.net/jp/article/58/hotel-occupancy-rate-calculation。