miss_scan_count {naniar}

Search and present different kinds of missing values

Description

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 ⁠?⁠.

Usage

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

pct_miss_case() prop_miss_case() pct_miss_var() prop_miss_var() pct_complete_case() prop_complete_case() pct_complete_var() prop_complete_var() miss_prop_summary() miss_case_summary() miss_case_table() miss_summary() miss_var_prop() miss_var_run() miss_var_span() miss_var_summary() miss_var_table()

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)
miss_scan_count(dat_ms,c(-99,-98))
miss_scan_count(dat_ms,c("-99","-98","N/A"))
miss_scan_count(dat_ms, "\\?")
miss_scan_count(dat_ms, "\\!")
miss_scan_count(dat_ms, "\\.")
miss_scan_count(dat_ms, "\\*")
miss_scan_count(dat_ms, "-")
miss_scan_count(dat_ms,common_na_strings)