Nothing
#' @keywords internal
#'
Clean_DB <- function(data, cutout = NULL, col_cut_thresh = 10^3, IDcol = c(2,5), startcol = 10,
pattern.out = c(), init.cutout = c(), track_deleted = TRUE, verbose = TRUE) {
Nuisance_int <- Nuisance(data, startcol = startcol,
missing.pattern = toupper(pattern.out), partial.pattern = "")
#column cutout
DB <- data %>% dplyr::select( - rownames(Nuisance_int)[which(
Nuisance_int$Non_definiti > col_cut_thresh )])
if(is.null(cutout)){
cutout <- cutout.default(data, startcol = startcol, init.cutout = init.cutout, pattern.out = pattern.out)
}
cols_in <- names(DB)[which(!names(DB) %in% cutout)]
DB <- DB %>% dplyr::select(cols_in)
#row cutout
deleted <- data.frame(matrix(nrow = 0, ncol = length(IDcol)))
names(deleted) <- names(data)[IDcol]
for (j in c(startcol:ncol(DB))){
deleted.new <- DB %>% dplyr::filter((!!rlang::sym(names(DB)[j])) %in% pattern.out) %>%
dplyr::select(IDcol)
DB <- DB %>% dplyr::anti_join(deleted.new, colnames(deleted.new))
if (nrow(deleted.new) > 0 & verbose == TRUE){
cat("deleted", nrow(deleted.new), "units whose field", names(DB)[j], "is missing \n")
}
deleted <- rbind(deleted, deleted.new)
}
if(track_deleted == TRUE){
res <- list (data = DB, deleted = deleted)
} else res <- DB
return(res)
}
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