setdiff_ {cheapr}

Extra utilities

Description

Extra utilities

Usage

setdiff_(x, y, dups = TRUE)

intersect_(x, y, dups = TRUE)

cut_numeric(
  x,
  breaks,
  labels = NULL,
  include.lowest = FALSE,
  right = TRUE,
  dig.lab = 3L,
  ordered_result = FALSE,
  ...
)

x %in_% table

x %!in_% table

enframe_(x, name = "name", value = "value")

deframe_(x)

na_rm(x)

sample_(x, size = cpp_vec_length(x), replace = FALSE, prob = NULL)

Arguments

x

A vector or data frame.

y

A vector or data frame.

dups

Should duplicates be kept? Default is TRUE.

breaks

See ?cut.

labels

See ?cut.

include.lowest

See ?cut.

right

See ?cut.

dig.lab

See ?cut.

ordered_result

See ?cut.

...

Further arguments passed onto cut or set.seed.

table

See ?collapse::fmatch

name

The column name to assign the names of a vector.

value

The column name to assign the values of a vector.

size

See ?sample.

replace

See ?sample.

prob

See ?sample.

Details

intersect_() and setdiff_() are faster and more efficient alternatives to intersect() and setdiff() respectively.
enframe_() and deframe_() are faster alternatives to tibble::enframe() and tibble::deframe() respectively.
cut_numeric() is a faster and more efficient alternative to cut.default().

Value

⁠enframe()_⁠ converts a vector to a data frame.
⁠deframe()_⁠ converts a 1-2 column data frame to a vector.
intersect_() returns a vector of common values between x and y.
setdiff_() returns a vector of values in x but not y.
cut_numeric() places values of a numeric vector into buckets, defined through the breaks argument and returns a factor unless labels = FALSE, in which case an integer vector of break indices is returned.
⁠%in_%⁠ and ⁠%!in_%⁠ both return a logical vector signifying if the values of x exist or don't exist in table respectively.
na_rm() is a convenience function that removes NA values and empty rows in the case of data frames. For more advanced NA handling, see ?is_na.
sample_() is an alternative to sample() that natively samples data frame rows through sset(). It also does not have a special case when length(x) is 1.