Count duplicates at each observation

For every value in a vector or data frame, duplicate_tally() counts how often it appears in total. Tallies are presented next to each value.

For summary statistics, call audit() on the results.

Usage

duplicate_tally(x, ignore = NULL, colname_end = "n")

Arguments

x

Vector or data frame.

ignore

Optionally, a vector of values that should not be checked. In the test result columns, they will be marked NA.

colname_end

String. Name ending of the logical test result columns. Default is "n".

Value

A tibble (data frame). It has all the columns from x, and to each of these columns' right, the corresponding tally column.

The tibble has the scr_dup_detect class, which is recognized by the audit() generic.

Details

This function is not very informative with many input values that only have a few characters each. Many of them may have duplicates just by chance. For example, in R's built-in iris data set, 99% of values have duplicates.

In general, the fewer values and the more characters per value, the more significant the results.

Summaries with audit()

There is an S3 method for the audit() generic, so you can call audit() following duplicate_tally(). It returns a tibble with summary statistics.

See also

• duplicate_count() for a frequency table.

• duplicate_count_colpair() to check each combination of columns for duplicates.

• janitor::get_dupes() to search for duplicate rows.

Examples

# Tally duplicate values in a data frame...
duplicate_tally(x = pigs4)
#> # A tibble: 5 × 6
#>   snout snout_n tail  tail_n wings wings_n
#>   <chr>   <int> <chr>  <int> <chr>   <int>
#> 1 4.73        1 6.88       1 6.09        1
#> 2 8.13        2 7.33       1 8.27        1
#> 3 4.22        2 5.17       3 4.40        1
#> 4 4.22        2 7.57       1 5.92        1
#> 5 5.17        3 8.13       2 5.17        3

# ...or in a single vector:
duplicate_tally(x = pigs4$snout)
#> # A tibble: 5 × 2
#>   value value_n
#>   <chr>   <int>
#> 1 4.73        1
#> 2 8.13        1
#> 3 4.22        2
#> 4 4.22        2
#> 5 5.17        1

# Summary statistics with `audit()`:
pigs4 %>%
  duplicate_tally() %>%
  audit()
#> # A tibble: 4 × 8
#>   term     mean    sd median   min   max na_count na_rate
#>   <chr>   <dbl> <dbl>  <dbl> <dbl> <dbl>    <dbl>   <dbl>
#> 1 snout_n  2    0.707      2     1     3        0       0
#> 2 tail_n   1.6  0.894      1     1     3        0       0
#> 3 wings_n  1.4  0.894      1     1     3        0       0
#> 4 .total   1.67 0.816      1     1     3        0       0

# Any values can be ignored:
pigs4 %>%
  duplicate_tally(ignore = c(8.131, 7.574))
#> # A tibble: 5 × 6
#>   snout snout_n tail  tail_n wings wings_n
#>   <chr>   <int> <chr>  <int> <chr>   <int>
#> 1 4.73        1 6.88       1 6.09        1
#> 2 8.13        2 7.33       1 8.27        1
#> 3 4.22        2 5.17       3 4.40        1
#> 4 4.22        2 7.57       1 5.92        1
#> 5 5.17        3 8.13       2 5.17        3