Searching for different kinds of missing values is really annoying. If you have values like -99 in your data, when they shouldn't be there, or they should be encoded as missing, it can be difficult to ascertain if they are there, and if so, where they are. miss_scan_count makes it easier for users to search for particular occurrences of these values across their variables.

miss_scan_count(data, search)

Arguments

data

data

search

values to search for

Value

a dataframe of the occurrences of the values you searched for

See also

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
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