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Duplicated rows, with their groups

Source: R/rule_lib.R
duplicate_rows.Rd

Returns the rows that share a combination of columns with at least one other row, grouped so the duplicates sit together. The counterpart of janitor::get_dupes().

Usage

duplicate_rows(data, columns = NULL)

Arguments

data

A data frame.

columns

Columns defining a duplicate (default: all of them).

Value

The duplicated rows, ordered by group, with a dupe_count column giving each group's size. Zero rows when there are none.

Details

rule_distinct_rows() tells you THAT there are duplicates, which is what a validation gate needs. This shows you WHICH, which is what fixing them needs – and a duplicate is usually a join that fanned out or a re-release appended rather than replaced, both of which are visible only once the offending rows are in front of you.

See also

rule_distinct_rows(), rule_unique()

Examples

df <- data.frame(id = c(1, 2, 2, 3, 3, 3),
                 value = c("a", "b", "b", "c", "d", "c"),
                 stringsAsFactors = FALSE)

# Duplicated on every column.
duplicate_rows(df)
#>   id value dupe_count
#> 1  2     b          2
#> 2  2     b          2
#> 3  3     c          2
#> 4  3     c          2

# Duplicated on the identifier alone, which catches more.
duplicate_rows(df, "id")
#>   id value dupe_count
#> 1  2     b          2
#> 2  2     b          2
#> 3  3     c          3
#> 4  3     d          3
#> 5  3     c          3

# No duplicates gives zero rows, not an error.
duplicate_rows(data.frame(x = 1:3))
#> [1] x          dupe_count
#> <0 rows> (or 0-length row.names)