Fuzzy Match Genus Name — wcvp_fuzzy_match

Tries to fuzzy match the genus name to the 'WCVP' table (using the optional wcvpdata checklist by default when available).

Usage

wcvp_fuzzy_match_genus(df, target_df = NULL, max_dist = 1, method = "osa")

Arguments

df: tibble containing the species binomial split into the columns Orig.Genus and Orig.Species.
target_df: Optional custom target table. If NULL, the optional wcvpdata checklist is used when available; otherwise pass a backbone explicitly.
max_dist: Maximum edit distance used for fuzzy genus matching.
method: String distance method passed to fozziejoin (for example "osa").

Value

Returns a tibble with the additional logical column fuzzy_match_genus, indicating whether the genus was successfully matched (TRUE) or not (FALSE). Further, the additional column fuzzy_genus_dist returns the distance for every match.

Examples

# \donttest{
library(wcvpmatch)
df <- data.frame(Orig.Genus = "Opuntiaa", Orig.Species = "yanganucensis")
wcvp_fuzzy_match_genus(df)
#> ℹ Input was converted from <data.frame> to a <tibble>.
#>   See <https://tibble.tidyverse.org/> for more details.
#> # A tibble: 1 × 21
#>   Orig.Genus Orig.Species  fuzzy_match_genus Input.Name         Orig.Name Author
#>   <chr>      <chr>         <lgl>             <chr>              <chr>     <chr> 
#> 1 Opuntiaa   yanganucensis TRUE              Opuntiaa yanganuc… NA        ""    
#> # ℹ 15 more variables: Orig.Infraspecies <chr>, Infra.Rank <chr>, Rank <dbl>,
#> #   has_cf <lgl>, has_aff <lgl>, is_sp <lgl>, is_spp <lgl>, had_hybrid <lgl>,
#> #   rank_late <lgl>, rank_missing_infra <lgl>, had_na_author <lgl>,
#> #   implied_infra <lgl>, sorter <dbl>, fuzzy_genus_dist <dbl>,
#> #   Matched.Genus <chr>
# }