R/NA_inspect.R

In lauzingaretti/LinkHD: LinkHD: a versatile framework to explore and integrate heterogeneous data

#'@title NA_inspect
#'@description This function inspects your datasets (stored int a list)
#' in order to evaluate if your data contains na values.
#'@param dat list with your datasets. It can be the same list generated by ReadData function.
#'@export NA_inspect
#'@return List with missing values information or message if your data doesn't have missing
#'@author Laura M Zingatetti
#'
#' @examples
#' {
#'data('Ruminotypes')
#'Data<-Ruminotypes$`16_S`
#'#13 indicates the number of columns with missing values.
#'Columns<-sample(1:ncol(Data),13)
#'for (i in Columns){
#'n<-sample(1:30,1)
#'Data[sample(1:nrow(Data),n),i]<-NA
#'}
#'
#'Data_1<-list("16_S"=Ruminotypes$`16_S`,"16_S_NA"=Data)
#'NA_inspect(Data_1)
#' }
#'
#' @name NA_inspect
#' @rdname NA_inspect




NA_inspect<-function (dat){

  if(!is.list(dat)){
    stop("check data into a list")
  }

  wherenans<-function(x) sapply(x, function(y) which(is.na(y)))

  dat2<-lapply(dat,wherenans)

  counts<-lapply(dat2,function(m){sapply(m ,function(x) length(x))})

  dataswithna<-lapply(counts,function(x) unique(x))

  tableswithna<-lapply(dataswithna, function(x) isTRUE(any(x!=0)))


  if(any((unlist(tableswithna)))){
    index<- which((unlist(tableswithna)))
    datosnas<-lapply(index,function(x) dat[[x]])
    indices_<-lapply(index,function(x) dat2[[x]])
    porc_<-lapply(index,function(x) counts[[x]]/dim(dat[[x]])[1])
    tot_<-lapply(index,function(x) sum(counts[[x]])/(dim(dat[[x]])[1]*dim(dat[[x]])[2]))
    totales<-lapply(index,function(x) sum(counts[[x]]))
    message(cat("you have nans in the next datasets:" ,  names(datosnas)))
    return(list("Nans_by_col_perc"=porc_, "Total_nans_perc"=tot_,"Num_nas"=totales))

  }
  else{
    message("there are no missing values in your data ")
    return(message("you can continue with further analysis"))
  }

}