laply | R Documentation |
For each element of a list, apply function then combine results into an array.
laply(
.data,
.fun = NULL,
...,
.progress = "none",
.inform = FALSE,
.drop = TRUE,
.parallel = FALSE,
.paropts = NULL
)
.data |
list to be processed |
.fun |
function to apply to each piece |
... |
other arguments passed on to |
.progress |
name of the progress bar to use, see
|
.inform |
produce informative error messages? This is turned off by default because it substantially slows processing speed, but is very useful for debugging |
.drop |
should extra dimensions of length 1 in the output be
dropped, simplifying the output. Defaults to |
.parallel |
if |
.paropts |
a list of additional options passed into
the |
laply
is similar in spirit to sapply
except
that it will always return an array, and the output is transposed with
respect sapply
- each element of the list corresponds to a row,
not a column.
if results are atomic with same type and dimensionality, a vector, matrix or array; otherwise, a list-array (a list with dimensions)
This function splits lists by elements.
If there are no results, then this function will return a vector of
length 0 (vector()
).
Hadley Wickham (2011). The Split-Apply-Combine Strategy for Data Analysis. Journal of Statistical Software, 40(1), 1-29. https://www.jstatsoft.org/v40/i01/.
Other list input:
l_ply()
,
ldply()
,
llply()
Other array output:
aaply()
,
daply()
,
maply()
laply(baseball, is.factor)
# cf
ldply(baseball, is.factor)
colwise(is.factor)(baseball)
laply(seq_len(10), identity)
laply(seq_len(10), rep, times = 4)
laply(seq_len(10), matrix, nrow = 2, ncol = 2)
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