diff --git a/R/violin.R b/R/violin.R
index 2d17676..72e91cf 100644
--- a/R/violin.R
+++ b/R/violin.R
@@ -1,78 +1,91 @@
 violin <- function(x,...) UseMethod("violin")
 violin.default <- function(x, ...) stop("not implemented for this class")
 
 violin.bootstrap.list=function(x,...){
   ken=melt(kendall.bootstrap.list(x))
   colnames(ken)[2]="Task"
   cat("\n\nSummary Kendall's tau\n")
   ss=ken%>%group_by(Task)%>%
     summarise(mean=mean(value,na.rm=T),
               median=median(value,na.rm=T),
               q25=quantile(value,probs = .25,na.rm=T),
               q75=quantile(value,probs = .75,na.rm=T))%>%
     arrange(desc(median))
 
   print(as.data.frame(ss))
 
+  # drop task if no kendall could be computed
+    noResults <- sapply(split(ss,ss$Task), 
+                        function(x) all(is.na(x[,-1])))
+    if (any(noResults)) {
+      message("No Kendall's tau could be calculated for any bootstrap sample in task ", 
+              names(noResults)[noResults],
+              " because of missing variability. Task dropped from figure.")
+      ken <- ken %>% filter(Task %in% names(noResults)[!noResults])
+    
+    }
+  
   xAxisText <- element_blank()
 
   # Show task names as tick mark labels only for multi-task data set
   if (length(x$data) > 1) {
     xAxisText <- element_text(angle = 90, vjust = 0.5, hjust = 1)
   }
 
   ken%>%mutate(Task=factor(.data$Task,
                            levels=ss$Task))%>%
     ggplot(aes(Task,value))+
     geom_violin(alpha=.3,
                 color=NA,
+                na.rm=TRUE,
                 fill="blue")+
     geom_boxplot(width=0.1,
+                 na.rm=TRUE,
                  fill="white")+
     theme(axis.text.x = xAxisText,
           legend.position = "none")+
     ylab("Kendall's tau")+
     scale_y_continuous(limits=c(min(min(ken$value),0),
                                 max(max(ken$value),1)))
 }
 
 
 
 kendall.bootstrap.list=function(x){
   ken=lapply(1:length(x$bootsrappedRanks),function(Task){
     id=match(rownames( x$bootsrappedRanks[[Task]]),
              rownames(x$matlist[[Task]]) )
     sapply(x$bootsrappedRanks[[Task]],
            function(bootSample) suppressWarnings(kendall(bootSample,
                                                          x$matlist[[Task]]$rank[id])))
   } )
   names(ken)=names((x$bootsrappedRanks))
 
   if (sum(is.na(x))>0){
    cat("Bootstrap samples without variability in rankings (all algorithms ranked 1) excluded.\n Frequency of such samples by task:\n",fill = T)
     sapply(ken,function(x) sum(is.na(x)))
   }
 
 
   return(ken)
 
 }
 
 
 density.bootstrap.list=function(x,...){
   ken=melt(kendall.bootstrap.list(x))
   colnames(ken)[2]="Task"
 
   cat("\n\nSummary Kendall's tau\n")
   ss=ken%>%group_by(Task)%>%
     summarise(mean=mean(value,na.rm=T),
               median=median(value,na.rm=T),
               q25=quantile(value,probs = .25,na.rm=T),
               q75=quantile(value,probs = .75,na.rm=T))%>%
     arrange(desc(median))
 
   print(as.data.frame(ss))
 
   ggplot(ken)+
     geom_density(aes(value,fill=Task),alpha=.3,color=NA)
 }