I have a data table like below. All columns are in characters.
Table:
V29 V30 V31 V32 V33 V34 V35 V36 V37 V38 .... V69
044 N 005 E 026 044 N 006
Expanding your data a little bit:
x <- read.table(stringsAsFactors=FALSE, header=TRUE, as.is=TRUE, colClasses="character", text="
V29 V30 V31 V32 V33 V34 V35 V36 V37 V38 V29a V30a V31a V32a V33a V34a V35a V36a V37a V38a
044 N 005 E 026 044 N 006 E 011 044 N 005 E 026 044 N 006 E 011
044 N 005 E 026 044 N 006 E 011 044 N 005 E 026 044 N 006 E 011 ")
The answer:
sapply(split.default(x, (seq_len(ncol(x))-1) %/% 5),
function(s) paste(apply(s, 1, paste0, collapse = ""), collapse = "-"))
# 0 1 2
# "044N005E026-044N005E026" "044N006E011-044N006E011" "044N005E026-044N005E026"
# 3
# "044N006E011-044N006E011"
This can easily be assigned to a column of the same frame.
Explanation:
to break a frame up by 5 columns, split
comes to mind, but the default use of split(...)
will use split.data.frame
which splits by row, not column, so we use split.default
(which works by column). From there, you can see how we're grouping things:
(seq_len(ncol(x))-1) %/% 5
# [1] 0 0 0 0 0 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3
For each of these groups, we get a 5-column frame:
split.default(x, (seq_len(ncol(x))-1) %/% 5)
# $`0`
# V29 V30 V31 V32 V33
# 1 44 N 5 E 26
# 2 44 N 5 E 26
# $`1`
# V34 V35 V36 V37 V38
# 1 44 N 6 E 11
# 2 44 N 6 E 11
### truncated for brevity
So we use sapply
to do something to each of these frames, returning it (in this case) simplified. (If we specify simplify=FALSE
or if not all of them are the same length, then it will be returned unsimplified, as a list
instead of a vector
).
The function we apply to each frame is apply(., 1, paste0, collapse0)
which will return a vector of the 5-column pastes, something like:
apply(s, 1, paste0, collapse = "")
# $`0`
# [1] ""044N005E026" "044N005E026""
Because we want them combined, we surround it as paste(apply(...), collapse = "-")
.