For loop is creating vector when I want a scalar

If you examine the code below, I'm trying to run a simulation where the data is sampled every year for 10 years for 100 orders. The simulation works fine for the first 10 years of order 1, but when it comes to order 2 it tacks the value onto order 1, i.e., creates a vector rather than gives me a scalar. This messes up my output and I don't know how to fix it.

dat <- data.frame(cbind(rnorm(30,600,sd=100),rnorm(30,300,sd=50),rnorm(30,200,sd=50),rnorm(30,600,sd=100)))
colnames(dat) <- c("unused","apr","oct","used")

  unused <- NULL
  deduct <- NULL
  carryover <- NULL
  used <- NULL
  apr <- NULL
  oct <- NULL
  available <- NULL

  #_____________________________________ Sample Data _____________________________________________________
  for (i in 1:100) {   #increment for orders
    for (k in 1:10){   #increment for years
      if(k==1) {
        subsample <- dat[sample(seq_along(dat[, 1]), size = 1,replace=TRUE), c("unused", "apr","oct","used")]
      } else {
        subsample <- dat[sample(seq_along(dat[, 1]), size = 1,replace=TRUE), c("apr","oct","used")]
      }
      if (k==1) unused[i] <-subsample$unused
      apr[i] <- subsample$apr
      oct[i] <- subsample$oct
      used[i] <- subsample$used
      #print(subsample)
      #_____________________________________ Use Data _____________________________________________________
      if (unused[i] > 200) {
        deduct[i] <- unused[i]-200
        carryover[i] <- 200
        available[i] <- carryover[i]+apr[i]+oct[i]
      }

      if (unused[i] <= 200) {
        deduct[i] <- 0
        carryover[i] <- unused[i]
        available[i] <- carryover[i]+apr[i]+oct[i]
      }

      #_____________________________________ Create unused for next year _______________________________
      unused <- available-used

    }
  }