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complete.cases() -> vec_detect_complete() #1365

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Sep 9, 2024
Merged

complete.cases() -> vec_detect_complete() #1365

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2 changes: 1 addition & 1 deletion NAMESPACE
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Original file line number Diff line number Diff line change
Expand Up @@ -765,7 +765,6 @@ importFrom(purrr,map_dbl)
importFrom(purrr,map_lgl)
importFrom(stats,as.formula)
importFrom(stats,binomial)
importFrom(stats,complete.cases)
importFrom(stats,cov)
importFrom(stats,cov.wt)
importFrom(stats,lm)
Expand Down Expand Up @@ -794,4 +793,5 @@ importFrom(utils,install.packages)
importFrom(utils,object.size)
importFrom(vctrs,vec_cast)
importFrom(vctrs,vec_cbind)
importFrom(vctrs,vec_detect_complete)
importFrom(vctrs,vec_slice)
2 changes: 1 addition & 1 deletion R/case_weights.R
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Expand Up @@ -131,7 +131,7 @@ wt_calcs <- function(x, wts, statistic = "mean") {
wts <- rep(1L, nrow(x))
}

complete <- stats::complete.cases(x) & !is.na(wts)
complete <- vec_detect_complete(x) & !is.na(wts)
wts <- wts[complete]
x <- x[complete,,drop = FALSE]
res <- stats::cov.wt(x, wt = wts, cor = statistic == "cor")
Expand Down
2 changes: 1 addition & 1 deletion R/classdist.R
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Expand Up @@ -58,7 +58,7 @@
#'
#' @examplesIf rlang::is_installed(c("modeldata"))
#' data(penguins, package = "modeldata")
#' penguins <- penguins[complete.cases(penguins), ]
#' penguins <- penguins[vctrs::vec_detect_complete(penguins), ]
#' penguins$island <- NULL
#' penguins$sex <- NULL
#'
Expand Down
2 changes: 1 addition & 1 deletion R/classdist_shrunken.R
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Expand Up @@ -62,7 +62,7 @@
#' of the National Academy of Sciences_, 99(10), 6567-6572.
#' @examplesIf rlang::is_installed(c("modeldata"))
#' data(penguins, package = "modeldata")
#' penguins <- penguins[complete.cases(penguins), ]
#' penguins <- penguins[vctrs::vec_detect_complete(penguins), ]
#' penguins$island <- NULL
#' penguins$sex <- NULL
#'
Expand Down
2 changes: 1 addition & 1 deletion R/corr.R
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Expand Up @@ -185,7 +185,7 @@ corr_filter <-
method = "pearson") {
x <- correlations(x, wts = wts, use = use, method = method)

if (any(!complete.cases(x))) {
if (any(!vec_detect_complete(x))) {
all_na <- apply(x, 2, function(x) all(is.na(x)))
if (sum(all_na) >= nrow(x) - 1) {
cli::cli_warn(
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4 changes: 2 additions & 2 deletions R/impute_bag.R
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Expand Up @@ -248,14 +248,14 @@ bake.step_impute_bag <- function(object, new_data, ...) {
col_names <- names(object$models)
check_new_data(col_names, object, new_data)

missing_rows <- !complete.cases(new_data)
missing_rows <- !vec_detect_complete(new_data)
if (!any(missing_rows)) {
return(new_data)
}

old_data <- new_data
for (col_name in col_names) {
missing_rows <- !complete.cases(new_data[[col_name]])
missing_rows <- !vec_detect_complete(new_data[[col_name]])
if (!any(missing_rows)) {
next
}
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4 changes: 2 additions & 2 deletions R/impute_knn.R
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Expand Up @@ -221,7 +221,7 @@ bake.step_impute_knn <- function(object, new_data, ...) {
all_cols <- unique(unlist(object$columns, recursive = TRUE))
check_new_data(all_cols, object, new_data)

missing_rows <- !complete.cases(new_data)
missing_rows <- !vec_detect_complete(new_data)
if (!any(missing_rows)) {
return(new_data)
}
Expand All @@ -230,7 +230,7 @@ bake.step_impute_knn <- function(object, new_data, ...) {

old_data <- new_data
for (col_name in col_names) {
missing_rows <- !complete.cases(new_data[, col_name])
missing_rows <- !vec_detect_complete(new_data[, col_name])
if (!any(missing_rows)) {
next
}
Expand Down
6 changes: 3 additions & 3 deletions R/impute_linear.R
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Expand Up @@ -115,7 +115,7 @@ step_impute_linear_new <-

lm_wrap <- function(vars, dat, wts = NULL, call = caller_env(2)) {
dat <- as.data.frame(dat[, c(vars$y, vars$x)])
complete <- stats::complete.cases(dat)
complete <- vec_detect_complete(dat)
dat <- dat[complete, ]
wts <- wts[complete]
if (nrow(dat) == 0) {
Expand Down Expand Up @@ -200,14 +200,14 @@ bake.step_impute_linear <- function(object, new_data, ...) {
col_names <- names(object$models)
check_new_data(col_names, object, new_data)

missing_rows <- !complete.cases(new_data)
missing_rows <- !vec_detect_complete(new_data)
if (!any(missing_rows)) {
return(new_data)
}

old_data <- new_data
for (col_name in col_names) {
missing_rows <- !complete.cases(new_data[[col_name]])
missing_rows <- !vec_detect_complete(new_data[[col_name]])
if (!any(missing_rows)) {
next
}
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4 changes: 2 additions & 2 deletions R/misc.R
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Expand Up @@ -206,7 +206,7 @@ strings2factors <- function(x, info) {

# ------------------------------------------------------------------------------

# `complete.cases` fails on list columns. This version counts a list column
# `vec_detect_complete` fails on list columns. This version counts a list column
# as missing if _all_ values are missing. For if a list vector element is a
# data frame with one missing value, that element of the list column will
# be counted as complete.
Expand All @@ -218,7 +218,7 @@ n_complete_rows <- function(x) {
x[[pos_list_col]] <- purrr::map_lgl(x[[pos_list_col]], flatten_na)
}

sum(complete.cases(x))
sum(vec_detect_complete(x))
}

flatten_na <- function(x) {
Expand Down
2 changes: 1 addition & 1 deletion R/recipes-package.R
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Expand Up @@ -71,7 +71,6 @@
#' @importFrom purrr map_lgl
#' @importFrom stats as.formula
#' @importFrom stats binomial
#' @importFrom stats complete.cases
#' @importFrom stats cov
#' @importFrom stats cov.wt
#' @importFrom stats lm
Expand Down Expand Up @@ -99,6 +98,7 @@
#' @importFrom utils object.size
#' @importFrom vctrs vec_cast
#' @importFrom vctrs vec_cbind
#' @importFrom vctrs vec_detect_complete
#' @importFrom vctrs vec_slice
## usethis namespace: end
NULL
2 changes: 1 addition & 1 deletion man/step_classdist.Rd
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2 changes: 1 addition & 1 deletion man/step_classdist_shrunken.Rd
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10 changes: 5 additions & 5 deletions tests/testthat/test-dummy.R
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Expand Up @@ -15,7 +15,7 @@ sacr$city[sample(1:nrow(sacr), 20)] <- NA_character_
sacr_missing <- sacr

sacr$city[is.na(sacr$city)] <- "missing"
sacr <- sacr[complete.cases(sacr), -3]
sacr <- sacr[vec_detect_complete(sacr), -3]

sacr_fac <- sacr
sacr_fac$city <- factor(sacr_fac$city)
Expand Down Expand Up @@ -167,10 +167,10 @@ test_that("tests for NA values in factor", {
)

expect_true(
all(complete.cases(factors_data_0) == complete.cases(sacr_missing[, "city"]))
all(vec_detect_complete(factors_data_0) == vec_detect_complete(sacr_missing[, "city"]))
)
expect_true(
all(complete.cases(factors_data_1) == complete.cases(sacr_missing[, "city"]))
all(vec_detect_complete(factors_data_1) == vec_detect_complete(sacr_missing[, "city"]))
)
})

Expand All @@ -189,10 +189,10 @@ test_that("tests for NA values in ordered factor", {
)

expect_true(
all(complete.cases(factors_data_0) == complete.cases(sacr_ordered[, "city"]))
all(vec_detect_complete(factors_data_0) == vec_detect_complete(sacr_ordered[, "city"]))
)
expect_true(
all(complete.cases(factors_data_1) == complete.cases(sacr_ordered[, "city"]))
all(vec_detect_complete(factors_data_1) == vec_detect_complete(sacr_ordered[, "city"]))
)
})

Expand Down
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