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)

Arguments

x	An object to test.

Value

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.

Examples

# A data frame usually has valid, unique names
is_named(mtcars)
#> [1] TRUE
have_name(mtcars)
#>  [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
is_dictionaryish(mtcars)
#> [1] TRUE

# But data frames can also have duplicated columns:
dups <- cbind(mtcars, cyl = seq_len(nrow(mtcars)))
is_dictionaryish(dups)
#> [1] FALSE

# The names are still valid:
is_named(dups)
#> [1] TRUE
have_name(dups)
#>  [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE


# For empty objects the semantics are slightly different.
# is_dictionaryish() returns TRUE for empty objects:
is_dictionaryish(list())
#> [1] TRUE

# 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)
#> [1] TRUE


# 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)
#> [1] FALSE
have_name(invalid)
#>  [1]  TRUE FALSE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE

# have_name() will work even with vectors that don't have a names
# attribute:
have_name(letters)
#>  [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
#> [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
#> [25] FALSE FALSE