Complete
vec_detect_complete()
detects "complete" observations. An observation is
considered complete if it is non-missing. For most vectors, this implies that
vec_detect_complete(x) == !vec_equal_na(x)
.
For data frames and matrices, a row is only considered complete if all
elements of that row are non-missing. To compare, !vec_equal_na(x)
detects
rows that are partially complete (they have at least one non-missing value).
vec_detect_complete(x)
x |
A vector |
A record type vector is considered complete if any field is non-missing.
A logical vector with the same size as x
.
x <- c(1, 2, NA, 4, NA) # For most vectors, this is identical to `!vec_equal_na(x)` vec_detect_complete(x) !vec_equal_na(x) df <- data_frame( x = x, y = c("a", "b", NA, "d", "e") ) # This returns `TRUE` where all elements of the row are non-missing. # Compare that with `!vec_equal_na()`, which detects rows that have at # least one non-missing value. df2 <- df df2$all_non_missing <- vec_detect_complete(df) df2$any_non_missing <- !vec_equal_na(df) df2
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