maply(.data, .fun = NULL, ..., .expand = TRUE, .progress = "none",
.inform = FALSE, .drop = TRUE, .parallel = FALSE, .paropts = NULL)
.fun
create_progress_bar
TRUE
TRUE
, apply function in parallel, using parallel
backend provided by foreachforeach
function when parallel computation
is enabled. This is important if (for example) your code relies on
external data or packages: use the .e
vector()
).m*ply
functions are the plyr
version of mapply
,
specialised according to the type of output they produce. These functions
are just a convenient wrapper around a*ply
with margins = 1
and .fun
wrapped in splat
.aaply
;
daply
; laply
maply(cbind(mean = 1:5, sd = 1:5), rnorm, n = 5)
maply(expand.grid(mean = 1:5, sd = 1:5), rnorm, n = 5)
maply(cbind(1:5, 1:5), rnorm, n = 5)
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