How to change the date in the data frame - r

Question

I have a lot data frame, like this
ID 1 2 3 4 5 type c new_ee first_ee_t
A 20051110 20051111 20051114 20051208 20060105 DATE 1 none none
A NA 1 3 24 2 diff_date 2 1 20051110
B 20050422 20050613 20050711 20071023 NA DATE 1 none none
B NA 52 28 834 999 diff_date 2 1 20050422
C 20021206 20040224 20040423 20040507 20040528 DATE 1 none none
C NA 445 59 14 21 diff_date 2 1 20021206
D 20030708 20050228 20050228 20050815 20050915 DATE 1 none none
D NA 601 0 168 31 diff_date 2 1 20030708
E 20000123 20040306 20060919 20060919 20060920 DATE 1 none none
E NA 1504 927 0 1 diff_date 2 1 20000123
F 20070413 NA NA NA NA DATE 1 none none
F NA 999 999 999 999 diff_date 2 0 0
G 20020318 20020411 NA NA NA DATE 1 none none
G NA 24 999 999 999 diff_date 2 0 0
I have to change first_ee_t variable. if the ID first - second time >365 then the first_ee_t variable change second time
if the first-second time and second-third time >365 the change third time
such as
ID 1 2 3 4 5 type c new_ee first_ee_t
A 20051110 20051111 20051114 20051208 20060105 DATE 1 none none
A NA 1 3 24 2 diff_date 2 1 20051110
B 20050422 20050613 20050711 20071023 NA DATE 1 none none
B NA 52 28 834 999 diff_date 2 1 20050422
C 20021206 20040224 20040423 20040507 20040528 DATE 1 none none
C NA 445 59 14 21 diff_date 2 1 20040224
D 20030708 20050228 20050228 20050815 20050915 DATE 1 none none
D NA 601 0 168 31 diff_date 2 1 20050228
E 20000123 20040306 20060919 20060919 20060920 DATE 1 none none
E NA 1504 927 0 1 diff_date 2 1 20060919
F 20070413 NA NA NA NA DATE 1 none none
F NA 999 999 999 999 diff_date 2 0 0
G 20020318 20020411 NA NA NA DATE 1 none none
G NA 24 999 999 999 diff_date 2 0 0

Answer 1

Assuming your expected output above has a few errors, I think this is what you are after
#first, here's the data in a copy/paste-able form
dd <-
structure(list(ID = structure(c(1L, 1L, 2L, 2L, 3L, 3L, 4L, 4L,
5L, 5L, 6L, 6L, 7L, 7L), .Label = c("A", "B", "C", "D", "E",
"F", "G"), class = "factor"), X1 = c(20051110L, NA, 20050422L,
NA, 20021206L, NA, 20030708L, NA, 20000123L, NA, 20070413L, NA,
20020318L, NA), X2 = c(20051111L, 1L, 20050613L, 52L, 20040224L,
445L, 20050228L, 601L, 20040306L, 1504L, NA, 999L, 20020411L,
24L), X3 = c(20051114L, 3L, 20050711L, 28L, 20040423L, 59L, 20050228L,
0L, 20060919L, 927L, NA, 999L, NA, 999L), X4 = c(20051208L, 24L,
20071023L, 834L, 20040507L, 14L, 20050815L, 168L, 20060919L,
0L, NA, 999L, NA, 999L), X5 = c(20060105L, 2L, NA, 999L, 20040528L,
21L, 20050915L, 31L, 20060920L, 1L, NA, 999L, NA, 999L), type = structure(c(1L,
2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L), .Label = c("DATE",
"diff_date"), class = "factor"), c = c(1L, 2L, 1L, 2L, 1L, 2L,
1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L), new_ee = structure(c(3L, 2L,
3L, 2L, 3L, 2L, 3L, 2L, 3L, 2L, 3L, 1L, 3L, 1L), .Label = c("0",
"1", "none"), class = "factor"), first_ee_t = c("none", "20051110",
"none", "20050422", "none", "20021206", "none", "20030708", "none",
"20000123", "none", "0", "none", "0")), .Names = c("ID", "X1",
"X2", "X3", "X4", "X5", "type", "c", "new_ee", "first_ee_t"), row.names = c(NA,
-14L), class = "data.frame")
And how, here's the code that will do the transformation
result<-unsplit(lapply(split(dd, dd$ID), function(x) {
if (all(is.na(x[1,4:6]))) {
x[2, "first_ee_t"]<-0
} else {
first<-min(which(x[2,2:6]<365))
if(is.finite(first)) {
x[2,"first_ee_t"]<-x[1, first]
}
}
x
}), dd$ID)
This is assuming that each ID has exactly two rows and that the second row always contains the datediffs and the first always contains the dates themselves.
This does produce a warning in the case of ID F who seems to have no values that satisfy the requirements so that row is left untouched.