Run a test suite of checks to test whether a data.frame or tibble
conforms to Darwin Core Standard.
While most users will only want to call suggest_workflow(),
the underlying check functions are exported for detailed work, or for
debugging. This function is useful for users experienced with
Darwin Core Standard or for final dataset checks.
Value
Invisibly returns the input data frame, but primarily called for the side-effect of running check functions on that input.
Details
check_dataset() is modelled after devtools::test(). It runs a
series of checks, then supplies a summary of passed/failed checks and
error messages.
Checks run by check_dataset() are the same that would
be run automatically by various set_ functions in a piped workflow. This
function allows users with only minor expected updates to check their entire
dataset without the need for set_ functions.
Examples
# \donttest{
df <- tibble::tibble(
scientificName = c("Crinia Signifera", "Crinia Signifera", "Litoria peronii"),
latitude = c(-35.27, -35.24, -35.83),
longitude = c(149.33, 149.34, 149.34),
eventDate = c("2010-10-14", "2010-10-14", "2010-10-14"),
status = c("present", "present", "present")
)
# Run a test suite of checks for Darwin Core Standard conformance
# Checks are only run on columns with names that match Darwin Core terms
df |>
check_dataset()
#> ℹ Testing data
#> ✔ | E P | Column
#> ⠙ | 0 scientificName
#> ✔ | 0 ✔ | scientificName [12ms]
#>
#> ⠙ | 0 eventDate
#> ✔ | 1 ✖ | eventDate [37ms]
#>
#>
#> ══ Results ═════════════════════════════════════════════════════════════════════
#>
#> [ Errors: 1 | Pass: 1 ]
#>
#> ℹ Checking Darwin Core compliance
#> ✖ Data does not meet minimum Darwin Core column requirements
#> ℹ Use `suggest_workflow()` to see more information.
#>
#>
#> ── Error in term ───────────────────────────────────────────────────────────────
#>
#> eventDate must be a Date vector, not a character.
#> ℹ Specify date format with lubridate functions e.g. `ymd()`, `mdy()`, or
#> `dmy()`.
#>
# }