Description Usage Arguments Details Author(s) Examples
View source: R/factor_nosort.r
This function generates factors more quickly, without leveraging
fastmatch
. The speed increase with fastmatch
for ICD-9 codes
was about 33
using Rcpp
, and a hashed matching algorithm.
1 | factor_nosort(x, levels = NULL, labels = levels)
|
x |
An object of atomic type |
levels |
An optional character vector of levels. Is coerced to the same
type as |
labels |
A set of labels used to rename the levels, if desired. |
NaN
s are converted to NA
when used on numeric values. Extracted
from https://github.com/kevinushey/Kmisc.git
These feature from base R are missing: exclude = NA, ordered =
is.ordered(x), nmax = NA
I don't think there is any requirement for factor levels to be sorted in advance, especially not for ICD-9 codes where a simple alphanumeric sorting will likely be completely wrong.
Kevin Ushey, adapted by Jack Wasey
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ## Not run:
pts <- icd:::random_unordered_patients(1e7)
u <- unique.default(pts$code)
# this shows that stringr (which uses stringi) sort takes 50% longer than
# built-in R sort.
microbenchmark::microbenchmark(sort(u), str_sort(u))
# this shows that \code{factor_} is about 50% faster than \code{factor} for
# big vectors of strings
# without sorting is much faster:
microbenchmark::microbenchmark(factor(pts$code),
# factor_(pts$code),
factor_nosort(pts$code),
times = 25
)
## End(Not run)
|
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