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

[Frank S.]

Dear R users,

With this mail I send my third and last question I wanted to ask these days. First of all, many thanks

for the received support in my previous mails! My question is this: Starting from a series of (for example)

"k" different dates (all contained in vector "v"), 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])


I have tried:

dt_p <- list( )                        # Empty list to alocate data tables

for (i in 1:length(v)) {
  dt_p[[i]] <- dt[ !(id %in% dt_p[[1:(i-1)]]$id) &  # Remove subjects from previous dt_p's
         round((v[i] - fborn)/365.25, 2) >= 65, ][ , list(id, fborn, sex)]

 dt.names <- paste0("dt_p", 1:length(v))
 assign(dt.names[i], dt_p[[i]])         # Assign a name to each data table
 }

However, I cannot express correctly the previous data tables, because for the first data

table in the loop, there are not any previous. Consequently, I get an error message:

# Error in dt_p[[1:(i - 1)]] : no such index at level 1


I would be very grateful for anu suggestion!

Frank S.

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