Convert variable into factor and keep value labels
This function converts a variable into a factor, but preserves variable and value label attributes.
as_factor(x, ...) to_factor(x, ...) ## S3 method for class 'data.frame' as_factor(x, ..., add.non.labelled = FALSE)
x |
A vector or data frame. |
... |
Optional, unquoted names of variables that should be selected for
further processing. Required, if |
add.non.labelled |
Logical, if |
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.
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.
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()
}
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