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This vector contains common number values of NA (missing), which is aimed to be used inside naniar functions miss_scan_count() and replace_with_na(). The current list of numbers can be found by printing out common_na_numbers. 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. Common NA strings are in the data object common_na_strings.

Usage

common_na_numbers

Format

An object of class numeric of length 8.

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)
#> # A tibble: 3 × 2
#>   Variable     n
#>   <chr>    <int>
#> 1 x            1
#> 2 y            0
#> 3 z            1
miss_scan_count(dat_ms, c("-99","-98","N/A"))
#> # A tibble: 3 × 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_numbers)
#> # A tibble: 3 × 2
#>   Variable     n
#>   <chr>    <int>
#> 1 x            2
#> 2 y            0
#> 3 z            2