Perform a random binomial draw for each row in R without rowwise()

I have an R data frame that I need to perform a random binomial draw for each row. The n = argument in the random binomial draw will be based on a value in a column of that row. Further, this operation should be within a case_when() based upon a conditional in the data.

Note: R's rowwise() function in tidyverse is much too slow, the data frame is too large and is being performed at each timestep in a simulation model. Is there a way to quickly and efficiently do this?

Example:

library(tidyverse)df = data.frame(condition = c("A","B","A","B","C"),                number = c(1000,1000,1000,1000,1))prob1 = 0.000517143prob2 = 0.000213472set.seed(1)df = df %>%   mutate(output = case_when(condition == "A" ~ sum(rbinom(n = number,                                                          size = 1,                                                          prob = prob1)),                            condition == "B" ~ sum(rbinom(n = number,                                                          size = 1,                                                          prob = prob2)),                            TRUE ~ 0))print(df)#>   condition number output#> 1         A   1000      0#> 2         B   1000      0#> 3         A   1000      0#> 4         B   1000      0#> 5         C      1      0

Here, it looks like the random binomial draws are being reused and returning all zeros.

For a check, here it is sampled repeatedly. Feasibly, the sum(df$output) should be around 2 each draw.

for(i in 1:10){  df = df %>%     mutate(output = case_when(condition == "A" ~ sum(rbinom(n = number,                                                            size = 1,                                                            prob = prob1)),                              condition == "B" ~ sum(rbinom(n = number,                                                            size = 1,                                                            prob = prob2)),                              TRUE ~ 0))  print(sum(df$output))}#> [1] 0#> [1] 0#> [1] 0#> [1] 0#> [1] 0#> [1] 0#> [1] 0#> [1] 0#> [1] 0#> [1] 0

Unsure of the way forward.