Is object named?
is_named()
checks that x
has names attributes, and that none of
the names are missing or empty (NA
or ""
). is_dictionaryish()
checks that an object is a dictionary: that it has actual names and
in addition that there are no duplicated names. have_name()
is a vectorised version of is_named()
.
is_named(x) is_dictionaryish(x) have_name(x)
x |
An object to test. |
is_named()
and is_dictionaryish()
are scalar predicates
and return TRUE
or FALSE
. have_name()
is vectorised and
returns a logical vector as long as the input.
# A data frame usually has valid, unique names is_named(mtcars) have_name(mtcars) is_dictionaryish(mtcars) # But data frames can also have duplicated columns: dups <- cbind(mtcars, cyl = seq_len(nrow(mtcars))) is_dictionaryish(dups) # The names are still valid: is_named(dups) have_name(dups) # For empty objects the semantics are slightly different. # is_dictionaryish() returns TRUE for empty objects: is_dictionaryish(list()) # But is_named() will only return TRUE if there is a names # attribute (a zero-length character vector in this case): x <- set_names(list(), character(0)) is_named(x) # Empty and missing names are invalid: invalid <- dups names(invalid)[2] <- "" names(invalid)[5] <- NA # is_named() performs a global check while have_name() can show you # where the problem is: is_named(invalid) have_name(invalid) # have_name() will work even with vectors that don't have a names # attribute: have_name(letters)
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