This vector contains common values of NA (missing), which is aimed to be used inside naniar functions miss_scan_count() and replace_with_na(). The current list of strings used can be found by printing out common_na_strings. It is a useful way to explore your data for possible missings, but I strongly warn against using this to replace NA values without very carefully looking at the incidence for each of the cases. Please note that common_na_strings uses \ around the "?", "." and "*" characters to protect against using their wildcard features in grep. Common NA numbers are in the data object common_na_numbers.

common_na_strings

Format

An object of class character of length 24.

Note

original discussion here https://github.com/njtierney/naniar/issues/168

Examples

dat_ms <- tibble::tribble(~x, ~y, ~z, 1, "A", -100, 3, "N/A", -99, NA, NA, -98, -99, "E", -101, -98, "F", -1) miss_scan_count(dat_ms, -99) miss_scan_count(dat_ms, c(-99,-98))
#> # A tibble: 3 x 2 #> Variable n #> <chr> <int> #> 1 x 2 #> 2 y 0 #> 3 z 2
miss_scan_count(dat_ms, c("-99","-98","N/A"))
#> # A tibble: 3 x 2 #> Variable n #> <chr> <int> #> 1 x 2 #> 2 y 1 #> 3 z 2
common_na_numbers
#> [1] -9 -99 -999 -9999 9999 66 77 88
miss_scan_count(dat_ms, common_na_strings)
#> # A tibble: 3 x 2 #> Variable n #> <chr> <int> #> 1 x 4 #> 2 y 4 #> 3 z 5