r How to check if values exist in a previous period (rolling) - r

Question

Here is my dataset:
structure(list(Date = structure(c(14609, 14609, 14609, 14609, 14699, 14699, 14699, 14699, 14790, 14790, 14790, 14790), class = "Date"),
ID = structure(c(5L, 4L, 6L, 10L, 9L, 3L, 10L, 8L, 7L, 1L,
10L, 2L), .Label = c("B00NYQ2", "B03J9L7", "B05DZD1", "B06HC42",
"B09V3X7", "B09YCC8", "X6114659", "X6478816", "X6556701",
"X6812555"), class = "factor"), Name = structure(c(10L, 4L,
9L, 8L, 7L, 3L, 8L, 6L, 2L, 5L, 8L, 1L), .Label = c("AIRA",
"BOUS", "CSCS", "EVF", "GTB", "JER", "MGB", "MPR", "NVB",
"TTNP"), class = "factor"), Score = c(55.075, 54.5, 53.325,
52.175, 70.275, 69.825, 60.15, 60.025, 56.175, 52.65, 52.175,
52.125), Score.rank = c(1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L)), .Names = c("Date", "ID", "Name", "Score", "Score.rank"), row.names = c(1L, 2L, 3L, 4L, 71L, 72L, 73L, 74L, 156L, 157L, 158L, 159L), class = "data.frame")
I'm trying to find which IDs come in and out when we go into a new period.
What i mean by that is..i want to compare if the ID was present in the previous period, denoted by "Date".
If it existed in the previous period (date), It should not return anything.
If it did not exist in the previous period, it should return "IN".
I also want to show that if does not exist in the next period, it should return an "OUT".
ie the this period's OUTs should be equal to next periods INs
my expected dataframe is supposed to look like this
Date ID Name Score Score.rank THIS PERIOD NEXT PERIOD
31/12/2009 B09V3X7 TTNP 55.075 1 OUT
31/12/2009 B06HC42 EVF 54.5 2 OUT
31/12/2009 B09YCC8 NVB 53.325 3 OUT
31/12/2009 X6812555 MPR 52.175 4
31/3/2010 X6556701 MGB 70.275 1 IN
31/3/2010 B05DZD1 CSCS 69.825 2 IN OUT
31/3/2010 X6812555 MPR 60.15 3
31/3/2010 X6478816 JER 60.025 4 IN OUT
30/6/2010 X6114659 BOUS 56.175 1 IN
30/6/2010 B00NYQ2 GTB 52.65 2 IN
30/6/2010 X6812555 MPR 52.175 3
30/6/2010 B03J9L7 AIRA 52.125 4 IN
Can somebody point me in the right direction as to how to do this?
Thanks in advance

Answer 1

Your description and example doesn't match, unfortunately.
Considering your description, it seems you want to tag entry and exit conditions for the IDs.
Which can be achieved as:
dft %>%
group_by(ID) %>%
dplyr::mutate( This_period = if_else(Date == min(Date), "IN", NULL) ) %>%
dplyr::mutate( Next_period = if_else(Date == max(Date), "OUT", NULL))
and returns:
#Source: local data frame [12 x 7]
#Groups: ID [10]
#
# Date ID Name Score Score.rank This_period Next_period
# <date> <fctr> <fctr> <dbl> <int> <chr> <chr>
#1 2009-12-31 B09V3X7 TTNP 55.075 1 IN OUT
#2 2009-12-31 B06HC42 EVF 54.500 2 IN OUT
#3 2009-12-31 B09YCC8 NVB 53.325 3 IN OUT
#4 2009-12-31 X6812555 MPR 52.175 4 IN <NA>
#5 2010-03-31 X6556701 MGB 70.275 1 IN OUT
#6 2010-03-31 B05DZD1 CSCS 69.825 2 IN OUT
#7 2010-03-31 X6812555 MPR 60.150 3 <NA> <NA>
#8 2010-03-31 X6478816 JER 60.025 4 IN OUT
#9 2010-06-30 X6114659 BOUS 56.175 1 IN OUT
#10 2010-06-30 B00NYQ2 GTB 52.650 2 IN OUT
#11 2010-06-30 X6812555 MPR 52.175 3 <NA> OUT
#12 2010-06-30 B03J9L7 AIRA 52.125 4 IN OUT
However, your example suggests you want to exclude the min(Date) from this_period check and the max(Date) from the Next_period check. Is it so? if yes, is score.rank somehow related to Date?
please clarify.