How to sample without replacement within groups in R - r

Question

I have a data frame which contains a 'year' variable with values between 1 and 100000 repeating multiple times. I have another data frame with 1000 'loss amounts' with an associated probability for each loss. I'd like to merge loss amounts onto the year data frame by sampling from the loss amounts table. I want to sample without replacement within each level of the year variable e.g. within each level of the year variable the loss amounts should be unique.
Reproducible example below where I can only get it to sample without replacement across the full 'year' dataset and not just within the different levels of the year variable as required. Is there a way of doing this (ideally without using loops as I need the code to run quickly)
#mean frequency
freq <- 100
years <- 100000
#create data frame with number of losses in each year
num_losses <- rpois(years, freq)
year <- tibble(index=1:length(num_losses), num=num_losses)
year <- map2(year$index, year$num, function(x, y) rep(x, y)) %>% unlist() %>% tibble(year = .)
#lookup table with loss amounts
lookup <- tibble(prob = runif(1000, 0, 1), amount = rgamma(1000, shape = 1.688, scale = 700000)) %>%
mutate(total_prob = cumsum(prob)/sum(prob),
pdf = total_prob - lag(total_prob),
pdf = ifelse(is.na(pdf), total_prob, pdf))
#add on amounts to year table by sampling from lookup table
sample_from_lookup <- function(number){
amount <- sample(lookup$amount, number, replace = FALSE, prob = lookup$pdf)
}
amounts <- sample_from_lookup(nrow(year))
year <- tibble(year = year$year, amount = amounts)

Answer 1

According to your description, maybe you can try replicate within your sample_from_lookup, i.e.,
sample_from_lookup <- function(number){
amount <- replicate(number,
sample(lookup$amount,
1,
replace = FALSE,
prob = lookup$pdf))
}
In this case, you need to set size 1 to your sample function.

Answer 2

I ended up using split to break the 'year' data into groups within a list. Then running the(slightly amended) sample_from_lookup function on each element of the list using map. Amended code below.
#mean frequency
freq <- 5
years <- 100
#create data frame with number of losses in each year
num_losses <- rpois(years, freq)
year <- tibble(index=1:length(num_losses), num=num_losses)
year <- map2(year$index, year$num, function(x, y) rep(x, y)) %>% unlist() %>% tibble(year = .)
year_split = split(year, year$year)
#lookup table
lookup <- tibble(prob = runif(1000, 0, 1), amount = rgamma(1000, shape = 1.688, scale = 700000)) %>%
mutate(total_prob = cumsum(prob)/sum(prob),
pdf = total_prob - lag(total_prob),
pdf = ifelse(is.na(pdf), total_prob, pdf))
#add on amounts to year table by sampling from lookup table
sample_from_lookup <- function(x){
number = NROW(x)
amount <- sample(lookup$amount, number, replace = FALSE, prob = lookup$pdf)
}
amounts <- map(year_split, sample_from_lookup) %>% unlist() %>% tibble(amount = .)
year <- tibble(year = year$year, amount = amounts$amount)