diff --git a/R/subset.R b/R/subset.R
index 67f5762..9f8285f 100644
--- a/R/subset.R
+++ b/R/subset.R
@@ -1,111 +1,119 @@
 subset <- function(x,...) UseMethod("subset")
 subset.default <- function(x, ...) base::subset(x, ...)
 
 
 subset.comparedRanks.list=function(x,
                                    tasks,...){
   res=x[tasks]
   class(res)="comparedRanks.list"
   res
 }
 
 subset.list=function(x,
                      tasks,...){
   x[tasks]
 }
 
 subset.aggregated.list=function(x,
                                 tasks,...){
   call=match.call(expand.dots = T)
   if (!is.null(as.list(call$top))) stop("Subset of algorithms only sensible for single task challenges.")
   matlist=x$matlist[tasks]
   res=list(matlist=matlist,
            call=list(x$call,call),
            data=x$data,
            FUN =  . %>% (x$FUN) %>%  (call)
   )
 
   class(res)=class(x)
   res
 
 }
 
 which.top=function(object,
                    top){
   mat=object$mat[object$mat$rank<=top,]
   rownames(mat)#[order(mat$rank)]
 }
 
 
 
 subset.ranked.list <- function(x,
                                top,
                                tasks,...) {
   
 #  if (!missing(tasks) & length(x$matlist) == 1) stop("Subset of tasks only sensible for multi task challenges.")
   if (!missing(top) & length(x$matlist) != 1)  stop("Subset of algorithms only sensible for single-task challenges. Otherwise no consensus ranking is possible.")
   
   if (!missing(top)){
     taskMat <- x$matlist[[1]]
     taskData <- x$data[[1]]
     objectTop=x
     objectTop$matlist[[1]]=taskMat[taskMat$rank<=top,]
     
     taskMatRowNames <- rownames(objectTop$matlist[[1]])
     attribute <- attr(objectTop$data,"algorithm")
     
     selectedRowNames <- taskData[[attribute]] %in% taskMatRowNames
     objectTop$data[[1]] <- taskData[selectedRowNames,]
     if (is.factor(objectTop$data[[1]][[attribute]])) objectTop$data[[1]][[attribute]] <- droplevels(objectTop$data[[1]][[attribute]])
     
     objectTop$fulldata=x$data
     return(objectTop)
   } else if (!missing(tasks)){
+    
+    if (is.character(tasks) && any(!tasks%in%names(x$matlist))) {
+      stop("There is/are no task(s) called ",paste(tasks[!tasks%in%names(x$matlist)],collapse = " and "),".")  
+    }
     res=list(matlist=x$matlist[tasks],
              data=x$data[tasks],
              call=x$call,
              FUN=x$FUN,
              FUN.list=x$FUN.list
     )
     
     attrib=attributes(x$data)
     attrib$names=attr(res$data,"names")
     attributes(res$data)=attrib
     class(res)=c("ranked.list","list")
     return(res)
   }
 }
 
 
 
 
 subset.bootstrap.list=function(x,
                                top,
                                tasks, ...) {
   
  # if (!missing(tasks) & length(x$matlist) == 1) stop("Subset of tasks only sensible for multi task challenges.")
   if (!missing(top) & length(x$matlist) != 1)  stop("Subset of algorithms only sensible for single-task challenges. Otherwise no consensus ranking is possible.")
   
   if (!missing(top)){
     objectTop <- subset.ranked.list(x, top = top)
     
     objectTop$bootsrappedRanks[[1]] <- objectTop$bootsrappedRanks[[1]][rownames(objectTop$matlist[[1]]),]
     objectTop$bootsrappedAggregate[[1]] <- objectTop$bootsrappedAggregate[[1]][rownames(objectTop$matlist[[1]]),]
     return(objectTop)
   } else if (!missing(tasks)){
+    if (is.character(tasks) && any(!tasks%in%names(x$matlist))) {
+      stop("There is/are no task(s) called ",paste(tasks[!tasks%in%names(x$matlist)],collapse = " and "),".")  
+    }
+    
     res=list(bootsrappedRanks=x$bootsrappedRanks[tasks],
              bootsrappedAggregate=x$bootsrappedAggregate[tasks],
              matlist=x$matlist[tasks],
              data=x$data[tasks],
              FUN=x$FUN
     )
     
     attrib=attributes(x$data)
     attrib$names=attr(res$data,"names")
     attributes(res$data)=attrib
     class(res)="bootstrap.list"
     return(res)
   }
 }