This function inspects a named list of data frames and suggests relationships based on shared column names, ID-like columns, observed key coverage, and observed key uniqueness.
Usage
suggest_relationships(
df_list,
min_score = 0.65,
max_composite_cols = 4,
copy = FALSE,
object_name = "relationships",
quiet = FALSE
)Arguments
- df_list
A named list of data frames.
- min_score
Minimum score required to keep a suggested relationship. Defaults to `0.65`.
- max_composite_cols
Maximum number of columns allowed in a composite key candidate. Defaults to `4`.
- copy
Logical. If `TRUE`, copy paste-ready R code to the clipboard using the `clipr` package, if available.
- object_name
Name to use when generating paste-ready R code. Defaults to `"relationships"`.
- quiet
Logical. If `FALSE`, print a short message about how many relationships were suggested.
Details
The returned object is a nested list in the same format expected by [create_erd()]. A data frame with diagnostic information is stored in the `"suggestions"` attribute.
Examples
employees <- data.frame(
emp_id = c(1, 2, 3),
name = c("Alice", "Bob", "Charlie")
)
assignments <- data.frame(
emp_id = c(1, 1, 2),
task = c("A", "B", "C")
)
relationships <- suggest_relationships(
list(
employees = employees,
assignments = assignments
)
)
#> Suggested 1 relationship(s).
relationships
#> $employees
#> $employees$assignments
#> $employees$assignments$emp_id
#> [1] "emp_id"
#>
#> $employees$assignments$relationship
#> [1] "||" "0<"
#>
#>
#>
#> attr(,"suggestions")
#> from_table to_table from_columns to_columns relationship_left
#> 1 employees assignments emp_id emp_id ||
#> relationship_right score coverage_from_to coverage_to_from coverage_mean
#> 1 0< 0.925 0.6666667 1 0.8333333
#> from_unique to_unique n_columns
#> 1 TRUE FALSE 1