faster than diagnose if emphasis is on diagnosing missing values. Also, only shows the columns with any missing values.

diagnose_missing(df, ...)

Arguments

df

dataframe

...

optional tidyselect

Value

tibble summary

Examples

diagnose_missing(tibble::tibble(x = c(NA, 1)))
#> # A tibble: 1 × 3
#>   column missings missing_ratio
#>   <chr>     <int>         <dbl>
#> 1 x             1           0.5