Cheaply check whether .data is conformable with an xmap_tbl

validate_apply_xmap() checks the same two conditions apply_xmap() requires before transforming .data – every keys_from key has a matching .xmap$.from link, and no values_from column has a missing value – and returns a single logical, without building the offending-rows/columns detail objects that diagnose_apply_xmap() does. It's the primitive to reach for when you only need a pass/fail answer – e.g. checking many .data/.xmap group pairs with dplyr::mutate() or purrr::map2_lgl() before applying any of them. Reach for diagnose_apply_xmap() once validate_apply_xmap() says something failed and you need to know why; apply_xmap() checks the same conditions at transform time and aborts with a message pointing at the offending condition.

Usage

validate_apply_xmap(
  .data,
  .xmap,
  values_from,
  keys_from = names(.xmap$.from),
  ...
)

Arguments

.data

The dataset to transform.

.xmap

An xmap_tbl object.

values_from

A tidyselect expression of columns in .data with values to transform

keys_from

A tidyselect expression specifies the column in .data to match with .xmap$from

...

(reserved)

Value

A single logical.

Examples

abc_xmap <- demo$abc_links |>
  as_xmap_tbl(from = "lower", to = "upper", weight_by = "share")
abc_data <- tibble::tibble(
  lower = unique(demo$abc_links$lower),
  count = runif(length(unique(demo$abc_links$lower)), min = 100, max = 500)
)
validate_apply_xmap(abc_data, abc_xmap, values_from = count)
#> [1] TRUE