Looping through data tables (or data frames) by removing previous individuals

Enviat el: dilluns, 3 d'octubre de 2016 21:38:05
Per a: Frank S.
A/c: r-help at r-project.org
Tema: Re: Looping through data tables (or data frames) by removing previous individuals

On Mon, 3 Oct 2016, Frank S. wrote:

> Dear R users,
>
>

[deleted]

> I want to get a list of "k" data tables (or data frames) so that each
> contains those individuals who for the first time are at least 65,
> looping on each of the dates of vector "v". Let's consider the following
> example with 5 individuals:
>
>
> dt <- data.table(
>   id = 1:5,
>   fborn = as.Date(c("1935-07-25", "1942-10-05", "1942-09-07", "1943-09-07", "1943-12-31")),
>   sex = as.factor(rep(c(0, 1), c(2, 3)))
>   )
>
> v <- seq(as.Date("2006-01-01"), as.Date("2009-01-01"), by ="year") # k=4
>
>
> I would expect to obtain k=4 data tables so that:
> dt_p1: contains id = 1 (he is for the first time at least 65 on date v[1])
> dt_p2: is NULL (no subject reach for the first time 65 on date v[2])
> dt_p3: contains id = 2 & id = 3 (they are for the first time at least 65 on v[3])
> dt_p4: contains id = 4 & id = 5 (they are for the first time at least 65 on v[4])
>
>

Here is a start (using a data.frame for dt):

> vp <- as.POSIXlt( c( as.Date("1000-01-01"), v ))
> vp$year <- vp$year-65
> dt.cut <- as.numeric(cut(as.POSIXlt(dt$fborn),vp))
> split(dt,factor(dt.cut, 1:length(v)))
$`1`
   id      fborn sex
1  1 1935-07-25   0

$`2`
[1] id    fborn sex
<0 rows> (or 0-length row.names)

$`3`
   id      fborn sex
2  2 1942-10-05   0
3  3 1942-09-07   1

$`4`
   id      fborn sex
4  4 1943-09-07   1
5  5 1943-12-31   1


See
   ?as.POSIXlt
   ?cut.POSIXt
   ?split

HTH,

Chuck