I have a list:
ls <- list(c(\"a\", \"b\", \"c\"), c(\"1\", \"2\", \"3\"), c(\"foo\", \"bar\", \"baz\"))
ls
#> [[1]]
#> [1] \"a\" \"b\" \"c\"
#>
In the data.table
package, there's a transpose()
function which does exactly this. It is implemented in C
for speed.
require(data.table) # v1.9.6+
transpose(ls)
# [[1]]
# [1] "a" "1" "foo"
# [[2]]
# [1] "b" "2" "bar"
# [[3]]
# [1] "c" "3" "baz"
It also fills automatically with NA
in case the list elements are not of equal lengths, and also coerces automatically to the highest SEXPTYPE. You can provide a different value to the fill
argument if necessary. Check ?transpose
.
"list"s are R objects with no C equivalent, so manipulating them in C will gain efficiency only in terms of surrounding computations, since the actual transposing will need to come back and forth between R objects.
Arun's transpose
is a concise approach to this problem and, seemingly, can't get any better. I'll just provide some other alternatives just to show that transposing a "list" can be cranky and maybe adopting a different approach to achieve the final goal might be better.
map = function(x) .mapply(c, x, NULL)
lap = function(x) lapply(seq_along(x[[1]]), function(i) unlist(lapply(x, "[[", i)))
library(data.table)
DT = function(x) transpose(x)
# very simple C loop that proves that `data.table::transpose` is as good as it gets
loopC = inline::cfunction(sig = c(R_ls = "list"), body = '
SEXPTYPE tp = 0;
SEXP ans, tmp;
PROTECT(ans = allocVector(VECSXP, LENGTH(VECTOR_ELT(R_ls, 0))));
for(int i = 0; i < LENGTH(R_ls); i++) {
tmp = VECTOR_ELT(R_ls, i);
if(TYPEOF(tmp) > tp) tp = TYPEOF(tmp);
}
for(int i = 0; i < LENGTH(ans); i++) SET_VECTOR_ELT(ans, i, allocVector(tp, LENGTH(R_ls)));
switch(tp) {
case LGLSXP:
case INTSXP: {
for(int i = 0; i < LENGTH(R_ls); i++) {
PROTECT(tmp = coerceVector(VECTOR_ELT(R_ls, i), tp));
int *ptmp = INTEGER(tmp);
for(int j = 0; j < LENGTH(ans); j++) INTEGER(VECTOR_ELT(ans, j))[i] = ptmp[j];
UNPROTECT(1);
}
break;
}
case REALSXP: {
for(int i = 0; i < LENGTH(R_ls); i++) {
PROTECT(tmp = coerceVector(VECTOR_ELT(R_ls, i), tp));
double *ptmp = REAL(tmp);
for(int j = 0; j < LENGTH(ans); j++) REAL(VECTOR_ELT(ans, j))[i] = ptmp[j];
UNPROTECT(1);
}
break;
}
case STRSXP: {
for(int i = 0; i < LENGTH(R_ls); i++) {
PROTECT(tmp = coerceVector(VECTOR_ELT(R_ls, i), tp));
for(int j = 0; j < LENGTH(ans); j++) SET_STRING_ELT(VECTOR_ELT(ans, j), i, STRING_ELT(tmp, j));
UNPROTECT(1);
}
break;
}
}
UNPROTECT(1);
return(ans);
')
spl = function(x) split(unlist(x), rep(seq_along(x[[1]]), length(x)))
map(ls)
#[[1]]
#[1] "a" "1" "foo"
#
#[[2]]
#[1] "b" "2" "bar"
#
#[[3]]
#[1] "c" "3" "baz"
#
lap(ls)
#[[1]]
#[1] "a" "1" "foo"
#
#[[2]]
#[1] "b" "2" "bar"
#
#[[3]]
#[1] "c" "3" "baz"
#
DT(ls)
#[[1]]
#[1] "a" "1" "foo"
#
#[[2]]
#[1] "b" "2" "bar"
#
#[[3]]
#[1] "c" "3" "baz"
#
loopC(ls)
#[[1]]
#[1] "a" "1" "foo"
#
#[[2]]
#[1] "b" "2" "bar"
#
#[[3]]
#[1] "c" "3" "baz"
#
spl(ls)
#$`1`
#[1] "a" "1" "foo"
#
#$`2`
#[1] "b" "2" "bar"
#
#$`3`
#[1] "c" "3" "baz"
And a benchmark:
myls1 = rep_len(list(sample(1e3), runif(1e3), sample(letters, 1e3, T)), 1e3) #1e3 x 1e3
myls2 = rep_len(list(sample(1e5), runif(1e5), sample(letters, 1e5, T)), 1e1) #10 x 1e5
myls3 = rep_len(list(sample(1e1), runif(1e1), sample(letters, 1e1, T)), 1e5) #1e5 x 10
identical(map(myls1), lap(myls1))
#[1] TRUE
identical(map(myls1), DT(myls1))
#[1] TRUE
identical(map(myls1), loopC(myls1))
#[1] TRUE
identical(map(myls1), unname(spl(myls1)))
#[1] TRUE
microbenchmark::microbenchmark(map(myls1), lap(myls1), DT(myls1), loopC(myls1), spl(myls1),
map(myls2), lap(myls2), DT(myls2), loopC(myls2), spl(myls2),
map(myls3), lap(myls3), DT(myls3), loopC(myls3), spl(myls3),
times = 10)
#Unit: milliseconds
# expr min lq median uq max neval
# map(myls1) 1141.9477 1187.8107 1281.4314 1331.4490 1961.8452 10
# lap(myls1) 1082.7023 1104.6467 1182.8303 1219.5397 1695.6164 10
# DT(myls1) 378.0574 399.7339 433.4307 459.0293 495.2200 10
# loopC(myls1) 390.0305 392.5139 405.6461 480.7480 638.9145 10
# spl(myls1) 676.2639 756.1798 786.8639 821.7699 869.0219 10
# map(myls2) 1241.1010 1304.2250 1386.1915 1439.5182 1546.3835 10
# lap(myls2) 1823.2029 1922.1878 1965.6653 2006.6102 2161.9819 10
# DT(myls2) 471.5797 521.7380 554.2221 578.3043 887.1452 10
# loopC(myls2) 472.5713 494.9302 524.2538 591.0493 657.6087 10
# spl(myls2) 1108.1530 1117.7448 1212.0051 1297.8838 1336.8266 10
# map(myls3) 2005.1325 2178.3739 2214.1824 2451.7050 2539.5152 10
# lap(myls3) 1172.3033 1215.1297 1242.0294 1292.7345 1434.1707 10
# DT(myls3) 388.6679 393.5446 416.5494 479.1473 721.0758 10
# loopC(myls3) 389.4098 396.6768 404.9609 432.4390 451.8912 10
# spl(myls3) 675.7749 704.3328 767.0548 817.7189 937.1469 10