#' 
#' @title generates subset tables from a data frame
#' @description This is an internal function called by the function 'subsetByClassDS'
#' @details The function generates subsets if the input of 'subsetByClassDS' is a data frame 
#' and if the number variables(columns) to subset by are greater than 1; i.e. this 
#' function is called if the user specified more than one variable or no variable to subset by
#' (if no variables are specified the function 'subsetByClassDS' produces a subset for each category
#' in each variable).
#' @param df a data frame.
#' @param iter the indices of columns to loop trough.
#' @param filter the minimum number of observations (i.e. rows) that are allowed.
#' @return a list which contains the subsets, their names and an integer that indicates how many columns were
#' not factors.
#' @keywords internal
#' @author Gaye, A.
#'
subsetByClassHelper2 <- function(df=NULL, iter=NULL, filter=NULL){
  # various counters and temporary variables to hold info
  subsets <- list()
  names.of.subsets <- c()
  count <- 0  
  nonfactorvars <- 0
  ncols <- length(colnames(df))
  for(i in iter){
    var <- df[,i]
    varname <- colnames(df)[i]
    if(is.factor(var)){        
      # get the levels
      categories <- levels(var)
      # loop through the levels and generate a dataset for each level
      # if the number of observations for that level > 0 and < 'filter'
      for(j in 1:length(categories)){
        indices <- which(var == as.numeric(categories[j]))
        if(!(length(indices) < filter)){
          count <- count+1
          subD <- df[indices,]
          subsets[[count]] <- subD
          name.of.subD <- paste(varname,".level_", categories[j], sep="")
          names.of.subsets <- append(names.of.subsets, name.of.subD)
        }else{
          # if any one category has between 1 and 'filter' number of observation turn subset content into missing values
          count <- count+1
          if(length(indices) == 0){
            subsets[[count]] <- df[-c(1:dim(df)[1]),]
            name.of.subD <- paste(varname,".level_", categories[j], "_EMPTY",sep="")
          }else{
            subD <- df[indices,]
            subD[] <- NA
            subsets[[count]] <- subD
            name.of.subD <- paste(varname,".level_", categories[j], "_INVALID",sep="")
          }
          colnames(subsets[[count]]) <- colnames(df)
          names.of.subsets <- append(names.of.subsets, name.of.subD) 
        }
      }
      names(subsets) <- names.of.subsets
    }else{
      # if a variable is not a factor increment the below counter
      nonfactorvars <- nonfactorvars + 1
    }
  }
  return(list(subsets, nonfactorvars))
}