Merge pull request #1204 from tidymodels/no-more-fancy-maps

NAMESPACE

@@ -666,7 +666,6 @@ importFrom(magrittr,"%>%")
 importFrom(purrr,map)
 importFrom(purrr,map_chr)
 importFrom(purrr,map_dbl)
-importFrom(purrr,map_dfr)
 importFrom(purrr,map_lgl)
 importFrom(stats,as.formula)
 importFrom(stats,binomial)

R/dummy.R

@@ -354,7 +354,8 @@ get_dummy_columns <- function(x, one_hot) {
 tidy.step_dummy <- function(x, ...) {
   if (is_trained(x)) {
     if (length(x$levels) > 0) {
-      res <- purrr::map_dfr(x$levels, get_dummy_columns, x$one_hot, .id = "terms")
+      res <- purrr::map(x$levels, get_dummy_columns, x$one_hot)
+      res <- purrr::list_rbind(res, names_to = "terms")
     } else {
       res <- tibble(terms = character(), columns = character())
     }

R/dummy_extract.R

@@ -242,7 +242,8 @@ bake.step_dummy_extract <- function(object, new_data, ...) {
       sort(object$levels[[col_name]]),
       object$other
     )
-    indicators <- purrr::map_dfc(indicators, vec_cast, integer())
+    indicators <- purrr::map(indicators, vec_cast, integer())
+    indicators <- vctrs::vec_cbind(!!!indicators)
 
     ## use backticks for nonstandard factor levels here
     used_lvl <- gsub(paste0("^", col_name), "", colnames(indicators))
@@ -301,7 +302,8 @@ print.step_dummy_extract <-
 tidy.step_dummy_extract <- function(x, ...) {
   if (is_trained(x)) {
     if (length(x$levels) > 0) {
-      res <- purrr::map_dfr(x$levels, ~ list(columns = .x), FALSE, .id = "terms")
+      res <- purrr::map(x$levels, ~ tibble(columns = .x), FALSE)
+      res <- purrr::list_rbind(res, names_to = "terms")
     } else {
       res <- tibble(terms = character(), columns = character())
     }

R/filter_missing.R

@@ -134,7 +134,8 @@ print.step_filter_missing <-
   }
 
 filter_missing_fun <- function(x, threshold, wts) {
-  x_na <- purrr::map_dfc(x, is.na)
+  x_na <- purrr::map(x, is.na)
+  x_na <- vctrs::vec_cbind(!!!x_na)
   missing <- averages(x_na, wts = wts)
   removal_ind <- which(missing > threshold)
   names(x)[removal_ind]

R/holiday.R

@@ -136,7 +136,8 @@ bake.step_holiday <- function(object, new_data, ...) {
     )
 
     names(tmp) <- paste(col_name, names(tmp), sep = "_")
-    tmp <- purrr::map_dfc(tmp, vec_cast, integer())
+    tmp <- purrr::map(tmp, vec_cast, integer())
+    tmp <- vctrs::vec_cbind(!!!tmp)
 
     tmp <- check_name(tmp, new_data, object, names(tmp))
     new_data <- vec_cbind(new_data, tmp)

R/impute_mean.R

@@ -163,7 +163,8 @@ prep.step_impute_mean <- function(x, training, info = NULL, ...) {
     wts <- NULL
   }
 
-  trimmed <- purrr::map_dfc(training[, col_names], trim, x$trim)
+  trimmed <- purrr::map(training[, col_names], trim, x$trim)
+  trimmed <- vctrs::vec_cbind(!!!trimmed)
 
   means <- averages(trimmed, wts = wts)
   means <- purrr::map2(means, trimmed, cast)

R/percentile.R

@@ -196,7 +196,9 @@ tidy.step_percentile <- function(x, ...) {
         percentile = numeric()
       )
     } else {
-      res <- map_dfr(x$ref_dist, format_pctl, .id = "term")
+      res <- map(x$ref_dist, format_pctl)
+      res <- purrr::list_rbind(res, names_to = "terms")
+
     }
   } else {
     term_names <- sel2char(x$terms)

R/recipes-package.R

@@ -67,7 +67,6 @@
 #' @importFrom purrr map
 #' @importFrom purrr map_chr
 #' @importFrom purrr map_dbl
-#' @importFrom purrr map_dfr
 #' @importFrom purrr map_lgl
 #' @importFrom stats as.formula
 #' @importFrom stats binomial

R/time.R

@@ -165,7 +165,9 @@ get_time_features <- function(dt, feats) {
     decimal_day = function(x) hour(x) + (second(x) + minute(x) * 60) / 3600
   )
 
-  purrr::map_dfc(features[feats], ~.x(dt))
+  res <- purrr::map(features[feats], ~.x(dt))
+  res <- vctrs::vec_cbind(!!!res)
+  res
 }
 
 

R/tunable.R

@@ -3,7 +3,8 @@ tunable.recipe <- function(x, ...) {
   if (length(x$steps) == 0) {
     res <- no_param
   } else {
-    res <- purrr::map_dfr(x$steps, tunable)
+    res <- purrr::map(x$steps, tunable)
+    res <- vctrs::vec_rbind(!!!res)
     if (nrow(res) > 0) {
       res <- res[!is.na(res$name), ]
     }