diff --git a/valid_variables_script2.R b/valid_variables_script2.R
index c13a9247a86b1e7703e1f7f252a5d3f35cc1a43d..22771bc38852b7368fdbe4127ec1ec76300e3648 100644
--- a/valid_variables_script2.R
+++ b/valid_variables_script2.R
@@ -131,51 +131,66 @@ is_number <- function(x){
 # Usa codebook param. Si algún cambia el codebook agradeceremos esto.
 check_values_format <- function(valid_columns, codebook_param){
   res <- ""
+  variables_out_of_range = "Variables out of range:"
   for(i in 1:length(valid_columns[[1]])){
-    print(i)
-    
+
     current_column <- valid_columns[[1]][[i]]
+    print(current_column)
     variable_type <- codebook_param$Variable.type[codebook$Harmonised.variable.name == current_column]
    
-    if(variable_type == "Continuous"){
+    if(!is.na(variable_type) && variable_type == "Continuous"){
       
       ################## ESTO PODRÍA IR EN UNA FUNC DIFERENTE #############
       
       ### parse del formato de una variable continua ##
       ## esta sentencia funciona codebook$Possible.values.format[codebook$Harmonised.variable.name == "CMXDE"] pruebala en el interprete.
       value_format <- strsplit(codebook_param$Possible.values.format[codebook_param$Harmonised.variable.name == current_column], " / ")[[1]]
-      high_limit <- as.numeric(sub("-.*", "", value_format[1]))
-      low_limit <- as.numeric(sub(".*-", "", value_format[1]))
+      high_limit <- gsub(",", ".", (sub("-.*", "", value_format[1])))
+      low_limit <- gsub(",", ".", (sub(".*-", "", value_format[1])))
       ### parse del formato de una variable continua ##
       
-      ds.dataFrameSubset(df.name = "data",
-                         V1.name = paste("data$", current_column, sep=""),
-                         V2.name = high_limit,
-                         Boolean.operator = "<=",
-                         newobj = "inRangeHigh",
-                         keep.NAs = TRUE,
-                         datasources = connections)
-      
-      
-      ds.dataFrameSubset(df.name = "inRangeHigh",
-                         V1.name = paste("inRangeHigh$", current_column, sep=""),
-                         V2.name = low_limit,
-                         Boolean.operator = ">=",
-                         newobj = "inRange",
-                         keep.NAs = TRUE,
-                         datasources = connections)
-      
-      summary <- ds.summary(paste("inRange$", current_column, sep=""))
-      if(ds.length(paste("data$", current_column, sep="")) > summary[[1]][[2]]){
-        res <- c(res, paste(current_column,  "does not follow the established format" , sep="\n"))
-      }
+      tryCatch(
+        error = function(cnd) {
+          if(grepl("list them with datashield.errors()",cnd))
+            error <- paste("Unable to analyse data" , datashield.errors() , sep = " ")
+          else
+            error <- paste("Unable to analyse data" , cnd, sep = " ")
+          print(error)
+          res <- c(res, error)
+        },
+        {
+          ds.dataFrameSubset(df.name = "data",
+                                   V1.name = paste("data$", current_column, sep=""),
+                                   V2.name = high_limit,
+                                   Boolean.operator = "<=",
+                                   newobj = "inRangeHigh",
+                                   keep.NAs = TRUE,
+                                   datasources = connections)
+          
+          
+          ds.dataFrameSubset(df.name = "inRangeHigh",
+                                   V1.name = paste("inRangeHigh$", current_column, sep=""),
+                                   V2.name = low_limit,
+                                   Boolean.operator = ">=",
+                                   newobj = "inRange",
+                                   keep.NAs = TRUE,
+                                   datasources = connections)
+          
+          summary <- ds.summary(paste("inRange$", current_column, sep=""))
+          if(ds.length(paste("data$", current_column, sep=""))[[1]] > summary[[1]][[2]]){
+            variables_out_of_range <- paste(variables_out_of_range, current_column, sep = " ")
+            print(paste(current_column,  "does not follow the established format", sep=" "))
+          }
+        }
+      )
       ################## FIN ESTO PODRÍA IR EN UNA FUNC DIFERENTE #############
       
-    }else if (variable_type == "Binary"){
-      
+    }else if (!is.na(variable_type) && (variable_type == "Categorical" || variable_type == "Binary")){
+      contingency_table <- ds.table(paste("data$",current_column))
+      counts <- contingency_table[[1]][[3]]
     }
   }
-  return (res)
+  return (variables_out_of_range)
 }
 
 
@@ -186,32 +201,30 @@ inp <- auxConnections[[2]]
 
 #Conexión a la base de datos
 
-ds.dim("data", datasources = connections)
-colnames <- ds.colnames("data")
-colnames
-
-# ds.dataFrameSubset(df.name = "data",
-#                    V1.name = "data$LBXAPTTA",
-#                    V2.name = "130",
-#                    Boolean.operator = "<=",
-#                    newobj = "inRangeHigh",
-#                    keep.NAs = TRUE,
-#                    datasources = connections)
-# 
-# lengthHigh <- ds.length(x='inRangeHigh$LBXAPTTA', datasources = connections)
-# 
-# 
-# ds.dataFrameSubset(df.name = "inRangeHigh",
-#                    V1.name = "inRangeHigh$LBXAPTTA",
-#                    V2.name = "11",
-#                    Boolean.operator = ">=",
-#                    newobj = "inRange",
-#                    keep.NAs = TRUE,
-#                    datasources = connections)
-# 
-# lengthBuenos <- ds.length(x='inRange$LBXAPTTA', datasources = connections)
-# 
-# summary <- ds.summary("inRange$LBXAPTTA")
+ # ds.dim("data", datasources = connections)
+ # colnames <- ds.colnames("data")
+ # colnames
+ # 
+ # ds.dataFrameSubset(df.name = "data",
+ #                    V1.name = "data$DMXBMI",
+ #                    V2.name = "130",
+ #                    Boolean.operator = "<=",
+ #                    newobj = "inRangeHigh",
+ #                    keep.NAs = TRUE,
+ #                    datasources = connections)
+ # 
+ # ds.dataFrameSubset(df.name = "inRangeHigh",
+ #                    V1.name = "inRangeHigh$DMXBMI",
+ #                    V2.name = "11",
+ #                    Boolean.operator = ">=",
+ #                    newobj = "inRange",
+ #                    keep.NAs = TRUE,
+ #                    datasources = connections)
+ # 
+ # summary <- ds.summary("inRange$DMXBMI")
+ # if(ds.length("data$DMXBMI")[[1]] > summary[[1]][[2]]){
+ #   res <- c(res, paste(current_column,  "does not follow the established format" , sep="\n"))
+ # }
 
 
 #----------------------------------------------------------------------------
@@ -228,5 +241,5 @@ res <- ""
 res <- check_values_format(valid_columns, codebook)
 print(res)
 
-
+datashield.logout(connections)