diff --git a/valid_variables_script.R b/valid_variables_script.R
index 3729199ffaaf3f20c3a2724fcfa70ccae221ce37..8a89e8528877042c45bf74b7064ff6d2cc7212d2 100644
--- a/valid_variables_script.R
+++ b/valid_variables_script.R
@@ -125,11 +125,11 @@ is_number <- function(x){
   
 }
 
-check_values_not_categoric <- function(values, colname){
+check_values_not_categoric <- function(values, colname , codebook_param){
   
   valid_vals <- values
   
-  possible_vals <- possible_values(colname)
+  possible_vals <- possible_values(colname, codebook_param)
   
   for(i in  1:length(values)){
     
@@ -194,21 +194,21 @@ check_values_not_categoric <- function(values, colname){
   return(valid_vals)
 }
 
-possible_values <- function(x){
+possible_values <- function(colname , codebook_param){
   
-  if(x=="LBXBEH" | x=="LBXBEHn" | x=="LBXBEM")
+  if(colname=="LBXBEH" | colname=="LBXBEHn" | colname=="LBXBEM")
     res <- t(as.data.frame(list(-20,20)))
   
   else{
     
-    possible_value <- subset(harmonised_data,harmonised_data$Harmonised.variable.name==x)[1,5]
-    res <- strsplit(x=possible_value,split="/")
+    possible_value <- subset(codebook_param,codebook_param$Harmonised.variable.name==colname)[1,5]
+    res <- strsplit(possible_value,split="/")
   }
   
   return(as.data.frame(res))
 }
 
-possible_values_categoric <- function(x){
+possible_values_categoric <- function(codebook_param){
   
   possible_value <- subset(harmonised_data,harmonised_data$Harmonised.variable.name==x)[1,4]
   res <- strsplit(x=possible_value,split="/")
@@ -238,16 +238,16 @@ get_values_from_quantiles <- function(x){
   
   data_summary <- ds.summary(x)
   
-  low_quantile <- data_summary[[1]][3][[1]][[1]]
+  low_quantile <- data_summary$HM$`quantiles & mean`[[1]]
   
-  high_quantile <- data_summary[[1]][3][[1]][[7]]
+  high_quantile <- data_summary$HM$`quantiles & mean`[[7]]
   
   return(list(low_quantile,high_quantile))
   
   
 }
 
-notify_error <- function(invalid_name_list,invalid_value_list,wrong_categoric, wrong_categoric_values, missing_numeric){
+notify_error <- function(invalid_name_list,invalid_value_list,wrong_categoric, wrong_categoric_values, missing_numeric, codebook_param){
   
   res <- ""
   
@@ -280,7 +280,7 @@ notify_error <- function(invalid_name_list,invalid_value_list,wrong_categoric, w
     res <- paste(res, "\n", sep="")
     
     for(i in 1:length(wrong_categoric)){
-      res <- paste(res, error_message_categoric(wrong_categoric[i], wrong_categoric_values[[i]]), sep=" ")
+      res <- paste(res, error_message_categoric(wrong_categoric[i], wrong_categoric_values[[i]], codebook_param), sep=" ")
     }
   }
   
@@ -302,13 +302,13 @@ notify_error <- function(invalid_name_list,invalid_value_list,wrong_categoric, w
   
 }
 
-error_message_categoric <- function(colname, invalid_values){
+error_message_categoric <- function(colname, invalid_values, codebook_param){
   
   res<- "\nValues in the field"
   res<- paste(res, colname, sep=" ")
   res<- paste(res, "should be", sep=" ")
   
-  range <- possible_values_categoric(colname)
+  range <- possible_values_categoric(colname , codebook_param)
   
   for(i in 1:nrow(range)){
     res <- paste(res, remove_space(range[i,1]), sep=" ")
@@ -392,7 +392,7 @@ error_message <- function(colname, invalid_values){
   
 }
 
-check_valid_values <- function(valid_colnames){
+check_valid_values <- function(valid_colnames , codebook_param){
   
   invalid_name_list <- c()
   cannot_analyse_list <- c()
@@ -405,24 +405,29 @@ check_valid_values <- function(valid_colnames){
   
   for(i in  1:(nrow(valid_colnames))){
     
+    data_available <- FALSE
     data_table <- "empty"
     colname <- valid_colnames[i, 1]
     
     if(grepl("DMRBORN",colname, fixed=TRUE) | (grepl("DAT",colname, fixed=TRUE)) | (grepl("ISO",colname, fixed=TRUE)) | (grepl("BEF", colname, fixed=TRUE))){
       next 
     }
+    
     column <- "data$"
     column <- paste(column, colname, sep="")
     
     tryCatch(
       error = function(cnd) {
-        print("Unable to analyse data")
+        print(paste("Unable to analyse data" , cnd , sep = " "))
         res <- FALSE
       },
+      {
       data_table <- as.data.frame(ds.table(column))
+      data_available <- TRUE
+      }
     )
     
-    if(data_table == "empty"){
+    if(data_available){
       
       cannot_analyse_list <- c(cannot_analyse_list, colname)
       
@@ -465,7 +470,7 @@ check_valid_values <- function(valid_colnames){
         else
           new_colname <- colname
         
-        valid <- check_values_not_categoric(values, new_colname)
+        valid <- check_values_not_categoric(values, new_colname , codebook_param)
         
         if (FALSE %in% valid){
           invalid_name_list <- c(invalid_name_list,colname)
@@ -485,7 +490,7 @@ check_valid_values <- function(valid_colnames){
   
   missing_numeric
   if(length(invalid_name_list)>0 | length(wrong_categoric)>0 | length(missing_numeric)>0){
-    res <- notify_error(invalid_name_list, invalid_values_list, wrong_categoric, wrong_categoric_values, missing_numeric)
+    res <- notify_error(invalid_name_list, invalid_values_list, wrong_categoric, wrong_categoric_values, missing_numeric, codebook_param)
   }else{
     res <- "All values are valid \n"
   }
@@ -538,25 +543,13 @@ valid_columns <- as.data.frame(check_valid_columns$colnames)
 
 
 result <- ""
-result<-check_valid_values(valid_columns)
+result<-check_valid_values(valid_columns, codebook)
 print(check_valid_columns)
 datashield.logout(connections) 
 cat(result)
 
-
-
-# ds.dataFrameSubset(df.name = "data", V1.name = "data$DMXWT", "400" , Boolean.operator = '>', newobj = "columna")
-# # 
-# ds.summary("columna$DMXWT")
-# ds.dim("columna$DMXWT")
-# ds.table("columna$DMXWT")
-
 file_name<- paste(hospital_name,"_invalid_values.txt", sep="")
 
-#ds.heatmapPlot("data$LBDSALSIA", "data$RFXHC_numeric",type="combine", datasources = connections)
-
-
-#setwd("C:/Users/victor/Desktop/TFG/r-analytics-master/invalid_values")
 dir.create("../invalid_values", showWarnings = FALSE)
 setwd("../invalid_values")