A B   C
  A B   C             1 j i 100
1 j i 100     -->     2 j i 100
2 K P 101             3 K P 101
                      4 K P 101

A   B   C
[1,] "j" "i" "100"
[2,] "j" "i" "100"
[3,] "K" "P" "101"
[4,] "K" "P" "101"

df <- data.frame(a=1:2, b=letters[1:2])
df[rep(seq_len(nrow(df)), each=2),]

library(plyr)
rep.row <- function(r, n){
  colwise(function(x) rep(x, n))(r)
}

library(mefa)
rep(mtcars,10)

mefa:::rep.data.frame(mtcars)

rep(df, each=N)

rep(df, times=N)

> data <- data.frame(a=letters[1:3], b=letters[4:6])
> data
  a b
1 a d
2 b e
3 c f
> as.data.frame(lapply(data, rep, 2))
  a b
1 a d
2 b e
3 c f
4 a d
5 b e
6 c f

N=2
rep(1:4, each = N)

rep.data.frame <- function(x, times) {
    rnames <- attr(x, "row.names")
    x <- lapply(x, rep.int, times = times)
    class(x) <- "data.frame"
    if (!is.numeric(rnames))
        attr(x, "row.names") <- make.unique(rep.int(rnames, times))
    else
        attr(x, "row.names") <- .set_row_names(length(rnames) * times)
    x
}

library(Lahman)
library(microbenchmark)
microbenchmark(
    mefa:::rep.data.frame(Batting, 10),
    rep.data.frame(Batting, 10),
    Batting[rep.int(seq_len(nrow(Batting)), 10), ],
    times = 10
)
#> Unit: milliseconds
#>                                            expr       min       lq     mean   median        uq       max neval cld
#>              mefa:::rep.data.frame(Batting, 10) 127.77786 135.3480 198.0240 148.1749  278.1066  356.3210    10  a
#>                     rep.data.frame(Batting, 10)  79.70335  82.8165 134.0974  87.2587  191.1713  307.4567    10  a
#>  Batting[rep.int(seq_len(nrow(Batting)), 10), ] 895.73750 922.7059 981.8891 956.3463 1018.2411 1127.3927    10   b

df$index = 1:nrow(df)
df = rbind(df,df)
df = df[order(df$index),][,-ncol(df)]

library(dplyr)
df <- data_frame(x = 1:2, y = c("a", "b"))
df %>% slice(rep(1:n(), each = 2))