Group by date difference in R

I want to group within a group by date difference.

For example, if there are 7 cases in facility A, but the first 5 cases happened before 14 days of the last 2 cases, I want them to be in two different groups (see below example)

here is my code so far:

I am stuck on how to group them further by the date difference between individual observations.

>Solution :

Assuming we don’t already diff calculated, and that we need to convert start_date into something arithmetically useful.

data.table

library(data.table)
as.data.table(dat)[, start_date := as.Date(start_date, format = "%m/%d/%Y")
  ][, diff14 := cumsum(c(0, diff(start_date)) > 14), by = location
  ][, Group2 := rleid(location, diff14)][]
#       location     address start_date start_date_diff Group diff14 Group2
#         <char>      <char>     <Date>           <int> <int>  <int>  <int>
#  1: Facility A 123 main st 2022-02-07               0     1      0      1
#  2: Facility A 123 main st 2022-02-11               4     1      0      1
#  3: Facility A 123 main st 2022-02-11               0     1      0      1
#  4: Facility A 123 main st 2022-02-11               0     1      0      1
#  5: Facility A 123 main st 2022-02-12               1     1      0      1
#  6: Facility A 123 main st 2022-03-12              28     2      1      2
#  7: Facility A 123 main st 2022-03-17               5     2      1      2
#  8: Facility B  55 ford rd 2022-03-16               0     3      0      3
#  9: Facility B  55 ford rd 2022-03-16               0     3      0      3
# 10: Facility C  1 step ave 2022-03-16               0     4      0      4
# 11: Facility C  1 step ave 2022-03-20               4     4      0      4
# 12: Facility C  1 step ave 2022-03-22               2     4      0      4

dplyr

library(dplyr)
dat %>%
  mutate(start_date = as.Date(start_date, format = "%m/%d/%Y")) %>%
  group_by(location) %>%
  mutate(diff14 = cumsum(c(0, diff(start_date)) > 14)) %>%
  group_by(location, diff14) %>%
  mutate(Group2 = cur_group_id()) %>%
  ungroup()
# # A tibble: 12 x 7
#    location   address     start_date start_date_diff Group diff14 Group2
#    <chr>      <chr>       <date>               <int> <int>  <int>  <int>
#  1 Facility A 123 main st 2022-02-07               0     1      0      1
#  2 Facility A 123 main st 2022-02-11               4     1      0      1
#  3 Facility A 123 main st 2022-02-11               0     1      0      1
#  4 Facility A 123 main st 2022-02-11               0     1      0      1
#  5 Facility A 123 main st 2022-02-12               1     1      0      1
#  6 Facility A 123 main st 2022-03-12              28     2      1      2
#  7 Facility A 123 main st 2022-03-17               5     2      1      2
#  8 Facility B 55 ford rd  2022-03-16               0     3      0      3
#  9 Facility B 55 ford rd  2022-03-16               0     3      0      3
# 10 Facility C 1 step ave  2022-03-16               0     4      0      4
# 11 Facility C 1 step ave  2022-03-20               4     4      0      4
# 12 Facility C 1 step ave  2022-03-22               2     4      0      4