#' Remove columns filled only with NA (missing value)
#'
#' @param df the dataframe to be cleaned
#' @examples
#' \donttest{
#'library(tidyverse)
#'
#'idbank_list = get_idbank_list() #idbank list
#'
#'idbank_empl = idbank_list %>%
#' filter(nomflow == "EMPLOI-SALARIE-TRIM-NATIONAL") %>% #employment
#' mutate(title = get_insee_title(idbank)) %>%
#' separate(title, sep = " - ", into = paste0("title", 1:5), fill = "right") %>%
#' clean_table()
#' }
#' @export
clean_table = function(df){
df[, colSums(is.na(df)) != nrow(df)]
}
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