Returns a tidy summary of each variable's structure, missingness, uniqueness, and suitability for use in regression models.
Examples
dissect(data_birthwt)
#> # A tibble: 10 × 6
#> Variable Type `Missing (%)` Unique Levels Compatibility
#> <chr> <chr> <chr> <int> <chr> <chr>
#> 1 low integer 0% 2 - maybe
#> 2 age integer 0% 24 - compatible
#> 3 lwt integer 0% 75 - compatible
#> 4 race integer 0% 3 - compatible
#> 5 smoke integer 0% 2 - maybe
#> 6 ptl integer 0% 4 - compatible
#> 7 ht integer 0% 2 - maybe
#> 8 ui integer 0% 2 - maybe
#> 9 ftv integer 0% 6 - compatible
#> 10 bwt integer 0% 131 - compatible
#>
#> Interpretation notes:
#> - compatible: ready to use in regression
#> - maybe: require transformation to factor or check no of levels
#> - incompatible: not usable as-is (e.g., all NA, <2 levels)