jonkeane commented on code in PR #12818:
URL: https://github.com/apache/arrow/pull/12818#discussion_r845378529
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r/R/dplyr-mutate.R:
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@@ -112,7 +113,15 @@ mutate.Dataset <- mutate.ArrowTabular <-
mutate.RecordBatchReader <- mutate.arro
transmute.arrow_dplyr_query <- function(.data, ...) {
dots <- check_transmute_args(...)
- dplyr::mutate(.data, !!!dots, .keep = "none")
+ has_null <- vapply(dots, quo_is_null, logical(1))
+ .data <- dplyr::mutate(.data, !!!dots, .keep = "none")
+ if (is_empty(dots) | any(has_null)) return(.data)
+
+ ## keeping with: https://github.com/tidyverse/dplyr/issues/6086
+ cur_exprs <- vapply(dots, as_label, character(1))
+ new_col_names <- names(dots)
+ transmute_order <- ifelse(nzchar(new_col_names), new_col_names, cur_exprs)
Review Comment:
`dplyr::coalesce` works here (and since this is a dplyr function, we can be
pretty sure dplyr is already installed), but generally we try to shy away from
using dplyr as a dependency.
So I would say let's get the names from `cur_exprs` but then do the more
base `transmute_order[is.na(names(...))] <- ...` assignment style. IMO it also
is slightly more explicit about what we're doing (replacing anything that
doesn't have a name with a name-like representation of itself)
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