Checks if row contains at least one value duplicated in its column

This function will return a vector, with the same length as the number of rows of the provided data frame. Each element of the vector will be logical value that states if any value from the row was duplicated in its column.

Usage

duplicates_across_cols(data, allow.na = FALSE)

Arguments

data

A data frame

allow.na

TRUE if we allow NAs in data. Default FALSE.

Value

A logical vector.

See also

paste

Examples

df <- data.frame(v1 = c(1, 1, 2, 3), v2 = c(4, 5, 5, 6))
duplicates_across_cols(df)
#> [1]  TRUE  TRUE  TRUE FALSE

library(magrittr)            # for piping operator

# you can use "assert_rows", "in_set", and this function to
# check if specified variables set and all subsets are keys for the data.

correct_df <- data.frame(id = 1:5, sub_id = letters[1:5], work_id = LETTERS[1:5])
correct_df %>%
  assert_rows(duplicates_across_cols, in_set(FALSE), id, sub_id, work_id)
#>   id sub_id work_id
#> 1  1      a       A
#> 2  2      b       B
#> 3  3      c       C
#> 4  4      d       D
#> 5  5      e       E
  # passes because each subset of correct_df variables is key

if (FALSE) {
incorrect_df <- data.frame(id = 1:5, sub_id = letters[1:5], age = c(10, 20, 20, 15, 30))
incorrect_df %>%
  assert_rows(duplicates_across_cols, in_set(FALSE), id, sub_id, age)
  # fails because age is not key of the data (age == 20 is placed twice)
}