use apply instead of loop after replicating data

Question

I am using this code:

df1 <- data.frame(
      x1 = 'a'
      , x2 = 'b'
      , y = 0
)


df1 <- do.call("rbind", replicate(10, df1, simplify = FALSE))

for (row in 1:nrow(df1)) {
    df1[row,]$y = (row - 1) 
}

df1

Can this be improved by using an apply family function instead of the loop? Thanks!

@dww - not sure what the point of your comment is ... but they are more efficient - hence my question ... — cs0815, Feb 17 '19 at 19:15
My point was that you seemed to be under the (common) misconception that apply is not a loop. Moreover, re. performance see, for example, ["Is R's apply family more than syntactic sugar?"](https://stackoverflow.com/a/2276001/2761575) and ["it is an already long debunked myth that for loops are any slower than lapply"](https://stackoverflow.com/a/42440872/2761575) — dww, Feb 17 '19 at 19:26

score 1 · Accepted Answer · answered Feb 17 '19 at 18:10

1

What about this solution?

df1 <- data.frame(
    x1 = 'a'
    , x2 = 'b'
    , y = 0
)


df1 <- do.call("rbind", replicate(10, df1, simplify = FALSE))


df1$y <- sapply(1:nrow(df1), function(i)as.numeric(row.names(df1))[i]-1)

answered Feb 17 '19 at 18:10

Henry Cyranka

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No need for `sapply` (which is a hidden loop). A vectorized solution is available. See comment above by @utubun. – Parfait Feb 17 '19 at 20:48

use apply instead of loop after replicating data

1 Answers1