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.
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