# Removes rows containing NA values in any mapped columns from the tidy dataset
removeRowsWithNA <- function(tidyTableDataList, skip_removal_warning = FALSE) {
tidyTableData <- tidyTableDataList %>% tibble::as_tibble()
hasNA <- tidyTableData %>% is.na()
naPerRow <- hasNA %>%
rowSums()
keepIdx <- naPerRow == 0
removed <- sum(naPerRow > 0)
if (removed != 0) {
naPerCol <- hasNA %>% colSums()
naColumns <- colnames(hasNA)[naPerCol > 0]
if (!skip_removal_warning) {
warning(paste0(
"NA values were detected in the following columns of ",
"the tidy dataset: ",
paste(naColumns, collapse = ", "), ". ",
removed, " row(s) in the tidy dataset were removed."
))
}
}
return(sapply(tidyTableDataList,
function(x) {
if (is.data.frame(x)) {
return(x %>% dplyr::filter(keepIdx))
}
return(x[keepIdx])
},
simplify = FALSE
))
}
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