sjmisc (version 2.6.3)

replace_na: Replace NA with specific values

Description

This function replaces (tagged) NA's of a variable, data frame or list of variables with value.

Usage

replace_na(x, ..., value, na.label = NULL, tagged.na = NULL)

Arguments

x

A vector or data frame.

...

Optional, unquoted names of variables that should be selected for further processing. Required, if x is a data frame (and no vector) and only selected variables from x should be processed. You may also use functions like : or dplyr's select_helpers. See 'Examples' or package-vignette.

value

Value that will replace the NA's.

na.label

Optional character vector, used to label the the former NA-value (i.e. adding a labels attribute for value to x).

tagged.na

Optional single character, specifies a tagged_na value that will be replaced by value. Herewith it is possible to replace only specific NA values of x.

Value

x, where NA's are replaced with value. If x is a data frame, the complete data frame x will be returned, with replaced NA's for variables specified in ...; if ... is not specified, applies to all variables in the data frame.

Details

While regular NA values can only be completely replaced with a single value, tagged_na allows to differentiate between different qualitative values of NAs. Tagged NAs work exactly like regular R missing values except that they store one additional byte of information: a tag, which is usually a letter ("a" to "z") or character number ("0" to "9"). Therewith it is possible to replace only specific NA values, while other NA values are preserved.

See Also

set_na for setting NA values, rec for general recoding of variables and recode_to for re-shifting value ranges.

Examples

# NOT RUN {
library(sjlabelled)
data(efc)
table(efc$e42dep, useNA = "always")
table(replace_na(efc$e42dep, value = 99), useNA = "always")

# the original labels
get_labels(replace_na(efc$e42dep, value = 99))
# NA becomes "99", and is labelled as "former NA"
get_labels(replace_na(efc$e42dep, value = 99, na.label = "former NA"),
           include.values = "p")

dummy <- data.frame(
  v1 = efc$c82cop1,
  v2 = efc$c83cop2,
  v3 = efc$c84cop3
)
# show original distribution
lapply(dummy, table, useNA = "always")
# show variables, NA's replaced with 99
lapply(replace_na(dummy, v2, v3, value = 99), table, useNA = "always")

library(haven)
x <- labelled(c(1:3, tagged_na("a", "c", "z"), 4:1),
              c("Agreement" = 1, "Disagreement" = 4, "First" = tagged_na("c"),
                "Refused" = tagged_na("a"), "Not home" = tagged_na("z")))
# get current NA values
x
get_na(x)

# replace only the NA, which is tagged as NA(c)
replace_na(x, value = 2, tagged.na = "c")
get_na(replace_na(x, value = 2, tagged.na = "c"))

table(x)
table(replace_na(x, value = 2, tagged.na = "c"))

# tagged NA also works for non-labelled class
# init vector
x <- c(1, 2, 3, 4)
# set values 2 and 3 as NA, will automatically become
# tagged NAs by 'set_na()'.
x <- set_na(x, na = c(2, 3))
# see result
x
# now replace only NA tagged with 2 with value 5
replace_na(x, value = 5, tagged.na = "2")

# }