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# Utils -------------------------------------------------------------------
#' @keywords internal
.prepare_data_clustering <- function(x,
include_factors = FALSE,
standardize = FALSE,
preprocess = TRUE,
...) {
if (isFALSE(preprocess)) {
return(x)
}
# include factors?
if (include_factors) {
# ordered factors to numeric
factors <- vapply(x, is.ordered, TRUE)
if (any(factors)) {
x[factors] <- sapply(
x[factors],
datawizard::to_numeric,
dummy_factors = FALSE,
preserve_levels = TRUE
)
}
# character and factors to dummies
factors <- sapply(x, function(i) is.character(i) | is.factor(i))
if (any(factors)) {
dummies <- lapply(x[factors], .factor_to_dummy)
x <- cbind(x[!factors], dummies)
}
} else {
# remove factors
x <- x[vapply(x, is.numeric, TRUE)]
}
# Remove all missing values from data, only use numerics
x <- stats::na.omit(x)
if (isTRUE(standardize)) {
x <- datawizard::standardize(x, ...)
# remove "dw_transformer" attribute
x[] <- lapply(x, as.numeric)
}
x
}
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