I would like to know which IDs are repeated at least a certain amount of times (eg: ≥3) in a given period of time (eg: ≤3 years). I have the following table as an example:
ID Date
1 2001-01-03
2 2001-02-28
3 2001-06-13
4 2002-04-05
5 2002-09-12
1 2002-12-12
3 2003-05-05
3 2003-05-06
4 2003-05-07
1 2003-06-04
2 2006-12-29
3 2007-04-05
1 2007-04-08
4 2007-09-12
1 2008-12-12
2 2009-01-23
3 2009-01-30
2 2009-04-05
1 2009-12-08
2 2010-01-04
2 2010-05-07
4 2012-01-02
5 2013-03-03
6 2014-01-01
I would like to obtain the following result:
ID Rep
1 TRUE
2 TRUE
3 TRUE
4 FALSE
5 FALSE
6 FALSE
If the ID is repeated at least 3 times in less than 3 years, no matter how many times it did so and when it did so, I want to get a TRUE result. If the ID is repeated less than 3 times, or more than 3 times but never in a period of less than 3 years, I would like to get a FALSE result.
I imagine this might be a fairly simple question for many of you. However, I will highly appreciate your help.
CodePudding user response:
You can use data.table
or dplyr
combined with diff()
; count the number of differences that are less than years(3) * 365.25, by ID
. If this meets or exceeds num
, return TRUE
yrs <- num <- 3
library(data.table)
setDT(data)[order(ID,Date)][,.("Rep" = sum(diff(Date)<(yrs*365.25))>=num),by="ID"]
# OR
library(dplyr)
data %>%
arrange(Date) %>%
group_by(ID) %>%
summarize(Rep = sum(diff(Date)<(yrs*365.25))>=num)
ID Rep
<num> <lgcl>
1: 1 TRUE
2: 2 TRUE
3: 3 TRUE
4: 4 FALSE
5: 5 FALSE
6: 6 FALSE