Test duplicated observations determined by key and index variables

• is_duplicated(): a logical scalar if the data exist duplicated observations.

• are_duplicated(): a logical vector, the same length as the row number of data.

• duplicates(): identical key-index data entries.

Usage

is_duplicated(data, key = NULL, index)

are_duplicated(data, key = NULL, index, from_last = FALSE)

duplicates(data, key = NULL, index)

Arguments

data

A data frame for creating a tsibble.

key

Variable(s) that uniquely determine time indices. NULL for empty key, and c() for multiple variables. It works with tidy selector (e.g. dplyr::starts_with()).

index

A variable to specify the time index variable.

from_last

TRUE does the duplication check from the last of identical elements.

Examples

harvest <- tibble(
  year = c(2010, 2011, 2013, 2011, 2012, 2014, 2014),
  fruit = c(rep(c("kiwi", "cherry"), each = 3), "cherry"),
  kilo = sample(1:10, size = 7)
)
is_duplicated(harvest, key = fruit, index = year)
#> [1] TRUE
are_duplicated(harvest, key = fruit, index = year)
#> [1] FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
are_duplicated(harvest, key = fruit, index = year, from_last = TRUE)
#> [1] FALSE FALSE FALSE FALSE FALSE  TRUE FALSE
duplicates(harvest, key = fruit, index = year)
#> # A tibble: 2 × 3
#>    year fruit   kilo
#>   <dbl> <chr>  <int>
#> 1  2014 cherry    10
#> 2  2014 cherry     4