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Uptaded documentation on rows_append and rows_insert, issue #6864 #6942

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Uptaded documentation on rows_append and rows_insert, issue #6864 #6942

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9 changes: 6 additions & 3 deletions R/rows.R
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Original file line number Diff line number Diff line change
Expand Up @@ -9,8 +9,10 @@
#' `in_place` for selected backends.
#'
#' * `rows_insert()` adds new rows (like `INSERT`). By default, key values in
#' `y` must not exist in `x`.
#' * `rows_append()` works like `rows_insert()` but ignores keys.
#' `y` must not exist in `x`. Adds rows to a dataset without overwriting existing
# rows or introducing complete duplicates based on key columns.
#' * `rows_append()` works like `rows_insert()` but ignores keys.
# Attaches new rows to the end of a dataset without any checks for duplicates.
#' * `rows_update()` modifies existing rows (like `UPDATE`). Key values in `y`
#' must be unique, and, by default, key values in `y` must exist in `x`.
#' * `rows_patch()` works like `rows_update()` but only overwrites `NA` values.
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#' # and will throw an error. Alternatively, you can ignore rows in `y`
#' # containing keys that conflict with keys in `x` with `conflict = "ignore"`,
#' # or you can use `rows_append()` to ignore keys entirely.
#' # For instance, if you're adding a customer record and don't want to insert a new row if a customer with the same ID already exists, choose this function.
#' try(rows_insert(data, tibble(a = 3, b = "z")))
#' rows_insert(data, tibble(a = 3, b = "z"), conflict = "ignore")
#' rows_append(data, tibble(a = 3, b = "z"))
#'
#'If you're merging datasets and aren't concerned about potential overlaps or repeated rows, this function is ideal.
#' # Update
#' rows_update(data, tibble(a = 2:3, b = "z"))
#' rows_update(data, tibble(b = "z", a = 2:3), by = "a")
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