Validate Variable Relationship

Determines the relationship between two variables in a data.frame: one-to-one, one-to-many, many-to-one, or many-to-many.

Usage

validate_var_relationship(.data, var1, var2)

# S3 method for class 'validate_var_rel'
print(x, ...)

Arguments

.data

A data.frame or tibble.

var1

Character string: name of the first variable.

var2

Character string: name of the second variable.

x

An object to print.

...

Additional arguments (currently unused).

Value

An S3 object of class validate_var_rel containing:

table_name

Name of the input table

var1, var2

Names of the variables analyzed

relation

Character string: "one-to-one", "one-to-many", "many-to-one", or "many-to-many"

var1_unique

Number of distinct values in var1

var2_unique

Number of distinct values in var2

n_combinations

Number of unique (var1, var2) pairs

var1_has_dups

Does any var1 value map to multiple var2 values?

var2_has_dups

Does any var2 value map to multiple var1 values?

Details

Only accepts variables of type character, integer, or factor. Numeric (double) variables are not allowed due to floating-point comparison issues.

See also

Other join validation: compare_tables(), validate_join(), validate_primary_keys()

Examples

df <- data.frame(
  person_id = c(1L, 2L, 3L, 4L),
  department = c("Sales", "Sales", "Engineering", "Engineering"),
  country = c("US", "US", "US", "UK")
)
validate_var_relationship(df, "person_id", "department")
#> 
#> ── Variable Relationship Validation ────────────────────────────────────────────
#> Table: df
#> Variables: person_id ↔ department
#> 
#>   Metric                                Value
#>   ────────────────────────────────────  ─────
#>   Unique values in person_id                4
#>   Unique values in department               2
#>   Unique (person_id, department) pairs      4
#> 
#> person_id → department: one-to-one
#> department → person_id: one-to-many
#> 
#> Relationship: MANY-TO-ONE