Frequency Table of Missing Value Types

Shows a breakdown of the different types of missing values in a variable that was read with read_spss(), read_stata(), read_sas(), or read_xpt() and contains tagged NAs.

Usage

na_frequencies(x, ...)

Arguments

x

A numeric vector with tagged NAs, or a data frame.

...

For a data frame: the variables to tabulate (tidyselect). If empty, every numeric variable with missing values is tabulated.

Value

A data frame with one row per missing type, ordered by code like the missing block of frequency() (system missing last, listed only when it occurs):

code

The original missing value code: numeric for SPSS codes (e.g., -9, -8), character for native format codes (e.g., ".a" for Stata, ".A" for SAS)

label

The value label for this missing type (if available)

n

Number of cases with this missing type

prc

Percent of all cases

tag

The internal tag character of the tagged NA

For a data frame, a first column variable names the variable. Without any missing values the (empty) result is returned invisibly with a message.

See also

read_spss(), read_stata(), read_sas(), read_xpt(), untag_na(), strip_tags()

Other data-import: read_por(), read_sas(), read_spss(), read_stata(), read_xlsx(), read_xpt(), strip_tags(), untag_na()

Examples

# \donttest{
if (requireNamespace("haven", quietly = TRUE)) {
  # Declare -9/-8 as distinct tagged missing types, then inspect them
  x <- set_na(c(1, 2, -9, 3, -8, -9), -9, -8)
  na_frequencies(x)
  #   code label n      prc tag
  # 1   -9  <NA> 2 33.33333   a
  # 2   -8  <NA> 1 16.66667   b
}
#>   code label n      prc tag
#> 1   -9  <NA> 2 33.33333   a
#> 2   -8  <NA> 1 16.66667   b
# }