Count observations over rolling 30 days windows with restrictions - r

Question

My idea is to count observations (grouped by Id's) within 30 days windows. My problem is that I want to introduce an exception in the counting process: if during the 30 days analyzed there is an observation that will be discarded (because n> 1) the count is only constructed with the data not discarded. (n is the variable that counts the number of observations within 30 days windows).
Example
id date
1 1/1/2021
1 22/1/2021
1 1/2/2021
Code:
test<-test%>%
group_by(id)%>%
mutate(n=sapply(seq(length(date)),
function(x) sum(between(date[1:x],date[x]-days(30),date[x]))))
id date n
1 1/1/2021 1
1 22/1/2021 2
1 1/2/2021 2
1 3/3/2021 2
1 2/2/2021 3
1 7/7/2021 1
Expected result:
id date n nexpected
1 1/1/2021 1 1
1 22/1/2021 2 2
1 1/2/2021 2 1
1 3/3/2021 2 2
1 2/2/2021 3 1
1 7/7/2021 1 1
Alternative explanation
I just want to keep an observation (grouped by ID) for every 30 days. I want to do this by creating a variable that tells me which observations are left inside (1) and which ones are outside (0) of the filter.

Answer 1

Not sure this is what you want, but lubridate::floor_date is often useful in those situations:
library(tidyverse)
library(lubridate)
test %>%
mutate(date = dmy(date)) %>%
group_by(id, floor = floor_date(date, 'month')) %>%
mutate(n = row_number())
id date floor n
<int> <date> <date> <int>
1 1 2021-01-01 2021-01-01 1
2 1 2021-01-22 2021-01-01 2
3 1 2021-02-01 2021-02-01 1