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
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