This function converts a variable into a factor, but preserves variable and value label attributes.
as_factor(x, ...)
to_factor(x, ...)
# S3 method for data.frame
as_factor(x, ..., add.non.labelled = FALSE)
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 tidyselect's select-helpers.
See 'Examples'.
Logical, if TRUE
, non-labelled values also
get value labels.
A factor, including variable and value labels. If x
is a data frame, the complete data frame x
will be returned,
where variables specified in ...
are coerced
to factors (including variable and value labels);
if ...
is not specified, applies to all variables in the
data frame.
as_factor
converts numeric values into a factor with numeric
levels. as_label
, however, converts a vector into
a factor and uses value labels as factor levels.
This function is intended for use with vectors that have value and variable
label attributes. Unlike as.factor
, as_factor
converts
a variable into a factor and preserves the value and variable label attributes.
Adding label attributes is automatically done by importing data sets
with one of the read_*
-functions, like read_spss
.
Else, value and variable labels can be manually added to vectors
with set_labels
and set_label
.
if (require("sjmisc") && require("magrittr")) {
data(efc)
# normal factor conversion, loses value attributes
x <- as.factor(efc$e42dep)
frq(x)
# factor conversion, which keeps value attributes
x <- as_factor(efc$e42dep)
frq(x)
# create partially labelled vector
x <- set_labels(
efc$e42dep,
labels = c(
`1` = "independent",
`4` = "severe dependency",
`9` = "missing value"
))
# only copy existing value labels
as_factor(x) %>% head()
get_labels(as_factor(x), values = "p")
# also add labels to non-labelled values
as_factor(x, add.non.labelled = TRUE) %>% head()
get_labels(as_factor(x, add.non.labelled = TRUE), values = "p")
# easily coerce specific variables in a data frame to factor
# and keep other variables, with their class preserved
as_factor(efc, e42dep, e16sex, c172code) %>% head()
# use select-helpers from dplyr-package
if (require("dplyr")) {
as_factor(efc, contains("cop"), c161sex:c175empl) %>% head()
}
}
#> Loading required package: sjmisc
#> Loading required package: magrittr
#> Error in as_factor(x, add.non.labelled = TRUE): Arguments in `...` must be used.
#> ✖ Problematic argument:
#> • add.non.labelled = TRUE
#> ℹ Did you misspell an argument name?