Splitting a large data frame into smaller segments

I have the following data frame and I want to break it up into 10 different data frames. I want to break the initial 100 row data frame into 10 data frames of 10 rows. I could do the following and get the desired results.

df = data.frame(one=c(rnorm(100)), two=c(rnorm(100)), three=c(rnorm(100)))

df1 = df[1:10,]
df2 = df[11:20,]
df3 = df[21:30,]
df4 = df[31:40,]
df5 = df[41:50,]
...

Of course, this isn't an elegant way to perform this task when the initial data frames are larger or if there aren't an easy number of segments that it can be broken down into.

So given the above, let's say we have the following data frame.

df = data.frame(one=c(rnorm(1123)), two=c(rnorm(1123)), three=c(rnorm(1123)))

Now I want to split it into new data frames comprised of 200 rows, and the final data frame with the remaining rows. What would be a more elegant (aka 'quick') way to perform this task.

 > str(split(df, (as.numeric(rownames(df))-1) %/% 200))
List of 6
 $ 0:'data.frame':  200 obs. of  3 variables:
  ..$ one  : num [1:200] -1.592 1.664 -1.231 0.269 0.912 ...
  ..$ two  : num [1:200] 0.639 -0.525 0.642 1.347 1.142 ...
  ..$ three: num [1:200] -0.45 -0.877 0.588 1.188 -1.977 ...
 $ 1:'data.frame':  200 obs. of  3 variables:
  ..$ one  : num [1:200] -0.0017 1.9534 0.0155 -0.7732 -1.1752 ...
  ..$ two  : num [1:200] -0.422 0.869 0.45 -0.111 0.073 ...
  ..$ three: num [1:200] -0.2809 1.31908 0.26695 0.00594 -0.25583 ...
 $ 2:'data.frame':  200 obs. of  3 variables:
  ..$ one  : num [1:200] -1.578 0.433 0.277 1.297 0.838 ...
  ..$ two  : num [1:200] 0.913 0.378 0.35 -0.241 0.783 ...
  ..$ three: num [1:200] -0.8402 -0.2708 -0.0124 -0.4537 0.4651 ...
 $ 3:'data.frame':  200 obs. of  3 variables:
  ..$ one  : num [1:200] 1.432 1.657 -0.72 -1.691 0.596 ...
  ..$ two  : num [1:200] 0.243 -0.159 -2.163 -1.183 0.632 ...
  ..$ three: num [1:200] 0.359 0.476 1.485 0.39 -1.412 ...
 $ 4:'data.frame':  200 obs. of  3 variables:
  ..$ one  : num [1:200] -1.43 -0.345 -1.206 -0.925 -0.551 ...
  ..$ two  : num [1:200] -1.343 1.322 0.208 0.444 -0.861 ...
  ..$ three: num [1:200] 0.00807 -0.20209 -0.56865 1.06983 -0.29673 ...
 $ 5:'data.frame':  123 obs. of  3 variables:
  ..$ one  : num [1:123] -1.269 1.555 -0.19 1.434 -0.889 ...
  ..$ two  : num [1:123] 0.558 0.0445 -0.0639 -1.934 -0.8152 ...
  ..$ three: num [1:123] -0.0821 0.6745 0.6095 1.387 -0.382 ...

If some code might have changed the rownames it would be safer to use:

 split(df, (seq(nrow(df))-1) %/% 200) 

require(ff)
df <- data.frame(one=c(rnorm(1123)), two=c(rnorm(1123)), three=c(rnorm(1123)))
for(i in chunk(from = 1, to = nrow(df), by = 200)){
  print(df[min(i):max(i), ])
}

If you can generate a vector that defines the groups, you can split anything:

f <- rep(seq_len(ceiling(1123 / 200)),each = 200,length.out = 1123)
> df1 <- split(df,f = f)
> lapply(df1,dim)
$`1`
[1] 200   3

$`2`
[1] 200   3

$`3`
[1] 200   3

$`4`
[1] 200   3

$`5`
[1] 200   3

$`6`
[1] 123   3