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. Note that the searches are done with regular
expressions, which are special ways of searching for text. See the
example below to see how to look for characters like ?
.
Examples
dat_ms <- tibble::tribble(~x, ~y, ~z, ~specials,
1, "A", -100, "?",
3, "N/A", -99, "!",
NA, NA, -98, ".",
-99, "E", -101, "*",
-98, "F", -1, "-")
miss_scan_count(dat_ms,-99)
#> # A tibble: 4 × 2
#> Variable n
#> <chr> <int>
#> 1 x 1
#> 2 y 0
#> 3 z 1
#> 4 specials 0
miss_scan_count(dat_ms,c(-99,-98))
#> # A tibble: 4 × 2
#> Variable n
#> <chr> <int>
#> 1 x 2
#> 2 y 0
#> 3 z 2
#> 4 specials 0
miss_scan_count(dat_ms,c("-99","-98","N/A"))
#> # A tibble: 4 × 2
#> Variable n
#> <chr> <int>
#> 1 x 2
#> 2 y 1
#> 3 z 2
#> 4 specials 0
miss_scan_count(dat_ms, "\\?")
#> # A tibble: 4 × 2
#> Variable n
#> <chr> <int>
#> 1 x 0
#> 2 y 0
#> 3 z 0
#> 4 specials 1
miss_scan_count(dat_ms, "\\!")
#> # A tibble: 4 × 2
#> Variable n
#> <chr> <int>
#> 1 x 0
#> 2 y 0
#> 3 z 0
#> 4 specials 1
miss_scan_count(dat_ms, "\\.")
#> # A tibble: 4 × 2
#> Variable n
#> <chr> <int>
#> 1 x 0
#> 2 y 0
#> 3 z 0
#> 4 specials 1
miss_scan_count(dat_ms, "\\*")
#> # A tibble: 4 × 2
#> Variable n
#> <chr> <int>
#> 1 x 0
#> 2 y 0
#> 3 z 0
#> 4 specials 1
miss_scan_count(dat_ms, "-")
#> # A tibble: 4 × 2
#> Variable n
#> <chr> <int>
#> 1 x 2
#> 2 y 0
#> 3 z 5
#> 4 specials 1
miss_scan_count(dat_ms,common_na_strings)
#> # A tibble: 4 × 2
#> Variable n
#> <chr> <int>
#> 1 x 4
#> 2 y 4
#> 3 z 5
#> 4 specials 5