duplicate_detect {scrutiny}

Detect duplicate values

Description

duplicate_detect() is superseded because it's less informative than duplicate_tally() and duplicate_count(). Use these functions instead.

For every value in a vector or data frame, duplicate_detect() tests whether there is at least one identical value. Test results are presented next to every value.

This function is a blunt tool designed for initial data checking. Don't put too much weight on its results.

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

Usage

duplicate_detect(x, ignore = NULL, colname_end = "dup", numeric_only)

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 "dup".

numeric_only

[Deprecated] No longer used: All values are coerced to character.

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.

Value

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

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

Summaries with audit()

There is an S3 method for the audit() generic, so you can call audit() following duplicate_detect(). It returns a tibble with these columns —

• term: The original data frame's variables.

• dup_count: Number of "duplicated" values of that term variable: those which have at least one duplicate anywhere in the data frame.

• total: Number of all non-NA values of that term variable.

• dup_rate: Rate of "duplicated" values of that term variable.

The final row, .total, summarizes across all other rows: It adds up the dup_count and total_count columns, and calculates the mean of the dup_rate column.

See Also

• duplicate_tally() to count instances of a value instead of just stating whether it is duplicated.

• 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

# Find duplicate values in a data frame...
duplicate_detect(x = pigs4)

# ...or in a single vector:
duplicate_detect(x = pigs4$snout)

# Summary statistics with `audit()`:
pigs4 %>%
  duplicate_detect() %>%
  audit()

# Any values can be ignored:
pigs4 %>%
  duplicate_detect(ignore = c(8.131, 7.574))