Computes string-similarity metrics between two columns of a data frame or database table. Useful for profiling data quality and choosing comparison thresholds. Rows where either column is missing are omitted.
Arguments
- .data
A data frame or character table name. Table names require
con.- col_1, col_2
Column names (unquoted or character).
- con
A DBI connection from
DBI::dbConnect(). IfNULL, uses R-side computation.
Value
A tibble::tibble() with the two input columns and metric columns
jaro_winkler, jaro, levenshtein, jaccard, and cosine.
Unsupported SQL-backend metrics are present as NA. The result has S3
class il_comparator_score.
Details
With con = NULL, all metrics are computed in R with
stringdist::stringdist(). With a duckdb::duckdb() or PostgreSQL connection,
computation is pushed to SQL. SQL backends return the same column schema
but may leave unsupported metrics as NA: DuckDB currently computes
jaro_winkler, jaro, levenshtein, and jaccard; PostgreSQL computes
levenshtein and a jaro_winkler compatibility column backed by trigram
similarity().
Examples
df <- data.frame(
name_l = c('John', 'Jane', 'Bob'),
name_r = c('Jon', 'Janet', 'Bobby')
)
il_comparator_score(df, name_l, name_r)
#> # A tibble: 3 × 7
#> name_l name_r jaro_winkler jaro levenshtein jaccard cosine
#> <chr> <chr> <dbl> <dbl> <int> <dbl> <dbl>
#> 1 John Jon 0.933 0.917 1 0.25 0.408
#> 2 Jane Janet 0.96 0.933 1 0.75 0.866
#> 3 Bob Bobby 0.907 0.867 2 0.5 0.707