How can i filter rows by one condition (id) which are repeated in two days

Question

i have a df, which containing 4 columns:

1. microbiological data (mo),
2. sample_date,
3. and patient id (pid_code),
4. id (for each rows).

Its looks like this:

id	mo	sample_date	pid_code
1	Staphylococcus epidermidis	2019-12-13	120
2	Staphylococcus epidermidis	2019-12-14	120
3	Staphylococcus capitis	2020-01-13	131
4	Staphylococcus hominis	2021-11-14	155
5	Staphylococcus hominis	2021-11-17	155
6	Micrococcus luteus	2023-06-06	133
7	Micrococcus luteus	2023-06-07	133

i want to filter those rows where the pid_code and mo is same, and repeated in 2 days.

So i want to get back these rows.

id	mo	sample_date	pid_code
1	Staphylococcus epidermidis	2019-12-13	120
2	Staphylococcus epidermidis	2019-12-14	120
6	Micrococcus luteus	2023-06-06	133
7	Micrococcus luteus	2023-06-07	133

Do you have something advise? Thanks

Answer 1

Here is a dplyr solution:

library(dplyr)
df %>% 
  filter(any(abs(difftime(sample_date, lag(sample_date), units = "days")) <= 2), .by=c(mo, pid_code))

              id          mo sample_date pid_code
1 Staphylococcus epidermidis  2019-12-13      120
2 Staphylococcus epidermidis  2019-12-14      120
6    Micrococcus      luteus  2023-06-06      133
7    Micrococcus      luteus  2023-06-07      133