R/remove_labels.R
remove_labels.Rd
Use remove_var_label()
to remove variable label, remove_val_labels()
to remove value labels, remove_user_na()
to remove user defined missing
values (na_values and na_range) and remove_labels()
to remove all.
remove_labels(
x,
user_na_to_na = FALSE,
keep_var_label = FALSE,
user_na_to_tagged_na = FALSE
)
remove_var_label(x)
remove_val_labels(x)
remove_user_na(x, user_na_to_na = FALSE, user_na_to_tagged_na = FALSE)
A vector or a data frame.
Convert user defined missing values into NA
?
Keep variable label?
Convert user defined missing values into
tagged NA
? It could be applied only to numeric vectors. Note that integer
labelled vectors will be converted to double labelled vectors.
Be careful with remove_user_na()
and remove_labels()
, user defined
missing values will not be automatically converted to NA
, except if you
specify user_na_to_na = TRUE
.
user_na_to_na(x)
is an equivalent of
remove_user_na(x, user_na_to_na = TRUE)
.
If you prefer to convert variables with value labels into factors, use
to_factor()
or use unlabelled()
.
x <- labelled_spss(1:10, c(Good = 1, Bad = 8), na_values = c(9, 10))
var_label(x) <- "A variable"
x
#> <labelled_spss<integer>[10]>: A variable
#> [1] 1 2 3 4 5 6 7 8 9 10
#> Missing values: 9, 10
#>
#> Labels:
#> value label
#> 1 Good
#> 8 Bad
remove_labels(x)
#> [1] 1 2 3 4 5 6 7 8 9 10
remove_labels(x, user_na_to_na = TRUE)
#> [1] 1 2 3 4 5 6 7 8 NA NA
remove_user_na(x, user_na_to_na = TRUE)
#> <labelled<integer>[10]>: A variable
#> [1] 1 2 3 4 5 6 7 8 NA NA
#>
#> Labels:
#> value label
#> 1 Good
#> 8 Bad
remove_user_na(x, user_na_to_tagged_na = TRUE)
#> 'x' has been converted into a double vector.
#> <labelled<double>[10]>: A variable
#> [1] 1 2 3 4 5 6 7 8 NA(a) NA(b)
#>
#> Labels:
#> value label
#> 1 Good
#> 8 Bad