Data quality score

Rolls several signals into a single 0-100 score and a letter grade. The components are completeness (share of non-missing cells), row uniqueness (penalises duplicate rows), and column variability (penalises constant, single-value columns). If an outlier_rate is supplied it adds a cleanliness component. Components are averaged with the supplied weights.

Usage

data_quality_score(
  df,
  missing = NULL,
  outlier_rate = NULL,
  weights = c(completeness = 0.4, uniqueness = 0.2, variability = 0.2, cleanliness = 0.2)
)

Arguments

df

A data frame.

missing

Optional result of analyze_missing(); computed if NULL.

outlier_rate

Optional fraction (0-1) of numeric cells flagged as outliers; if supplied, a cleanliness component is included.

weights

Optional named numeric vector of component weights. Missing components are dropped and the rest renormalised.

Value

A list with score (0-100), grade (a letter), and components (a named numeric vector of the component scores).

Examples

data_quality_score(iris)
#> $score
#> [1] 99.8
#> 
#> $grade
#> [1] "A"
#> 
#> $components
#> completeness   uniqueness  variability 
#>        100.0         99.3        100.0 
#>