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.
Value
A data frame with columns:
- tag
The tag character (e.g., a-z for Stata, A-Z for SAS, a-z/A-Z/0-9 for SPSS)
- n
Number of cases with this missing type
- code
The original missing value code: numeric SPSS codes (e.g., -9, -8) or native format codes (e.g., ".a" for Stata, ".A" for SAS)
- label
The value label for this missing type (if available)
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
if (FALSE) { # \dontrun{
# SPSS data
data <- read_spss("survey.sav")
na_frequencies(data$satisfaction)
# tag n code label
# 1 b 1774 -11 TNZ: SPLIT
# 2 c 63 -9 KEINE ANGABE
# 3 d 11 -8 WEISS NICHT
# 4 a 6 -42 DATENFEHLER: MFN
# Stata data
data <- read_stata("survey.dta")
na_frequencies(data$income)
# tag n code label
# 1 a 42 .a Not applicable
# 2 b 15 .b Refused
} # }