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Extract original rows from key groups where concatenation would be required

collapse_candidates.Rd

collapse_candidates() identifies key groups (defined by ...) where at least one column selected by .concat contains more than one distinct value within the group (respecting na_rm). It returns the original input rows belonging to those groups.

This is useful for auditing or reviewing duplicates before applying collapse_by_keys().

Usage

collapse_candidates(.data, ..., .keys = NULL, .concat = NULL, na_rm = TRUE)

Arguments

.data

A data frame or tibble.

...

Key columns defining groups (tidyeval).

.keys

Optional alternative to …for programmatic key selection. Accepts either (i) a character vector of column names or (ii) a tidyselect expression evaluated in.data. If supplied, .keystakes precedence over…

.concat

A tidyselect specification of columns to check for divergence (and hence potential concatenation). Must not be NULL.

na_rm

Logical. If TRUE, ignore NA values when assessing distinctness within a group. If FALSE, NA participates in distinctness.

Value

A tibble containing only the input rows that belong to key groups where at least one .concat column is divergent (i.e., concatenation would be needed).

Examples

library(dplyr)
library(tibble)

df <- tibble(
  exam.num_collec  = c(1, 1, 1, 2, 2),
  mat.matrice      = c("SER", "SER", "SER", "PLAS", "PLAS"),
  spe.denomination = c("E. coli", "E. coli", "E. coli", "S. aureus", "S. aureus"),
  commentaire      = c("first", NA, "repeat", "ok", "ok"),
  source_info      = c("labA", "labA", "labB", "labC", NA)
)

# Return the original rows from groups where commentaire and/or source_info would be concatenated
candidates <- df %>%
  collapse_candidates(
    exam.num_collec, mat.matrice, spe.denomination,
    .concat = c(commentaire, source_info),
    na_rm = TRUE
  )

candidates
#> # A tibble: 3 × 5
#>   exam.num_collec mat.matrice spe.denomination commentaire source_info
#>             <dbl> <chr>       <chr>            <chr>       <chr>      
#> 1               1 SER         E. coli          first       labA       
#> 2               1 SER         E. coli          NA          labA       
#> 3               1 SER         E. coli          repeat      labB       

candidates2 <- df %>%
  collapse_candidates(
    .keys = c("exam.num_collec", "mat.matrice", "spe.denomination"),
    .concat = c(commentaire, source_info),
    na_rm = TRUE
  )

candidates2
#> # A tibble: 3 × 5
#>   exam.num_collec mat.matrice spe.denomination commentaire source_info
#>             <dbl> <chr>       <chr>            <chr>       <chr>      
#> 1               1 SER         E. coli          first       labA       
#> 2               1 SER         E. coli          NA          labA       
#> 3               1 SER         E. coli          repeat      labB       

identical(candidates, candidates2)
#> [1] TRUE

candidates3 <- df %>%
  collapse_candidates(
    .keys = matches("^exam\\."),
    .concat = c(commentaire, source_info),
    na_rm = TRUE
  )

candidates3
#> # A tibble: 3 × 5
#>   exam.num_collec mat.matrice spe.denomination commentaire source_info
#>             <dbl> <chr>       <chr>            <chr>       <chr>      
#> 1               1 SER         E. coli          first       labA       
#> 2               1 SER         E. coli          NA          labA       
#> 3               1 SER         E. coli          repeat      labB