R - Automatically stack every nth column of a data frame and save them as new objects

Here are some alternatives. No packages are used.

1) aperm Create a 3d array a, permute the dimensions and reshape into a matrix m and then convert that to a data frame. This one only works if all values are of the same type. (2) and (3) do not have this limitation.

k <- 3
nr <- nrow(DF)
nc <- ncol(DF)
unames <- unique(names(DF))

a <- array(as.matrix(DF), c(nr, k, nc/k))
m <- matrix(aperm(a, c(1, 3, 2)),, k, dimnames = list(NULL, unames))
as.data.frame(m, stringsAsFactors = FALSE)

giving:

   A  B  C
1 a1 b1 c1
2 a2 b2 c2
3 a3 b3 c3
4 a4 b4 c4
5 a5 b5 c5
6 a6 b6 c6
7 a7 b7 c7
8 a8 b8 c8

If we are in the situation given in the question's EDIT then replace unames with the following where DF2 is DF with the revised names as per Note at end:

unames <- unique(sub("\\d*$", "", names(DF2)))

2) lapply This generalizes the code in the question. unames is defined above:

L <- lapply(split(as.list(DF), names(DF)), unlist)
as.data.frame(L, stringsAsFactors = FALSE)

giving:

   A  B  C
1 a1 b1 c1
2 a2 b2 c2
3 a3 b3 c3
4 a4 b4 c4
5 a5 b5 c5
6 a6 b6 c6
7 a7 b7 c7
8 a8 b8 c8

With the input shown in the question's EDIT it could be done like this where DF2 is given reproducibly in the Note at the end.

names0 <- sub("\\d*$", "", names(DF2))   # names without the trailing digits
L <- lapply(split(as.list(DF2), names0), unlist)
as.data.frame(L, stringsAsFactors = FALSE)

3) reshape nc and unames are from above. varying is a list with k components such as that the ith component contains the index vector c(i, i+k, ...). It seems that reshape does not like duplicated names so we have given it setNames(DF, 1:nc) as the input. This solution does have the advantage of also generating the index vectors time and id which relate the output to the input data.

varying <- split(1:nc, names(DF))
reshape(setNames(DF, 1:nc), dir = "long", varying = varying, v.names = unames)

giving:

    time  A  B  C id
1.1    1 a1 b1 c1  1
2.1    1 a2 b2 c2  2
3.1    1 a3 b3 c3  3
4.1    1 a4 b4 c4  4
1.2    2 a5 b5 c5  1
2.2    2 a6 b6 c6  2
3.2    2 a7 b7 c7  3
4.2    2 a8 b8 c8  4

With the input shown in the question's EDIT it actually simplifies. We no longer need to use setNames(DF, 1:nc) but can just use the data frame as is as input. Also, we can use varying=TRUE (also see @thelatemail's comment) instead of calculating a complex argument for varying. The input DF2 is as shown in the Note at the end and names0 is as in (2) above.

reshape(DF2, dir = "long", varying = TRUE, v.names = unique(names0))

Note:

Lines <- "      A      B      C      A      B      C 
1    a1     b1     c1     a5     b5     c5
2    a2     b2     c2     a6     b6     c6
3    a3     b3     c3     a7     b7     c7
4    a4     b4     c4     a8     b8     c8"
DF <- read.table(text = Lines, as.is = TRUE, check.names = FALSE)

DF2 <- setNames(DF, c("A1", "B1", "C1", "A2", "B2", "C2")) # test input

Upate: A number of simplifications. Also added DF2 in Note at end and discuss in each alternative how to modify the code to deal with it. (A general method might be just to reduce DF2 to DF as I discussed in the comments below.)