fix lints

R/data_partition.R

@@ -130,26 +130,26 @@ data_partition <- function(data,
   })
 
   # we need to move all list elements one level higher.
-  if (!is.null(group)) {
+  if (is.null(group)) {
+    training_sets <- training_sets[[1]]
+  } else {
     # for grouped training sets, we need to row-bind all sampled training
     # sets from each group. currently, we have a list of data frames,
     # grouped by "group"; but we want one data frame per proportion that
     # contains sampled rows from all groups.
     training_sets <- lapply(seq_along(proportion), function(p) {
       do.call(rbind, lapply(training_sets, function(i) i[[p]]))
     })
-  } else {
-    # else, just move first list element one level higher
-    training_sets <- training_sets[[1]]
   }
 
   # use probabilies as element names
   names(training_sets) <- sprintf("p_%g", proportion)
 
   # remove all training set id's from data, add remaining data (= test set)
+  all_ids <- lapply(training_sets, data_extract, select = row_id, as_data_frame = FALSE)
   out <- c(
     training_sets,
-    list(test = data[-unlist(lapply(training_sets, data_extract, select = row_id, as_data_frame = FALSE), use.names = FALSE), ])
+    list(test = data[-unlist(all_ids, use.names = FALSE), ])
   )
 
   lapply(out, `row.names<-`, NULL)

R/data_to_long.R

@@ -77,9 +77,10 @@ data_to_long <- function(data,
                          ignore_case = FALSE,
                          regex = FALSE,
                          ...,
-                         cols) {
+                         cols) { # nolint
 
   # Prefer "cols" over "select" for compat with tidyr::pivot_longer
+  # nolint start
   if (!missing(cols)) {
     select <- substitute(cols)
     cols <- .select_nse(
@@ -106,6 +107,7 @@ data_to_long <- function(data,
       )
     }
   }
+  # nolint end
 
   # nothing to select?
   if (length(cols) == 0L) {

R/data_to_wide.R

@@ -194,22 +194,22 @@ data_to_wide <- function(data,
   if (!is.null(values_fill)) {
     if (length(values_fill) == 1L) {
       if (is.numeric(new_data[[values_from]])) {
-        if (!is.numeric(values_fill)) {
-          insight::format_error(paste0("`values_fill` must be of type numeric."))
-        } else {
+        if (is.numeric(values_fill)) {
           new_data <- convert_na_to(new_data, replace_num = values_fill)
+        } else {
+          insight::format_error(paste0("`values_fill` must be of type numeric."))
         }
       } else if (is.character(new_data[[values_from]])) {
-        if (!is.character(values_fill)) {
-          insight::format_error(paste0("`values_fill` must be of type character."))
-        } else {
+        if (is.character(values_fill)) {
           new_data <- convert_na_to(new_data, replace_char = values_fill)
+        } else {
+          insight::format_error(paste0("`values_fill` must be of type character."))
         }
       } else if (is.factor(new_data[[values_from]])) {
-        if (!is.factor(values_fill)) {
-          insight::format_error(paste0("`values_fill` must be of type factor."))
-        } else {
+        if (is.factor(values_fill)) {
           new_data <- convert_na_to(new_data, replace_fac = values_fill)
+        } else {
+          insight::format_error(paste0("`values_fill` must be of type factor."))
         }
       }
     } else {