diff --git a/R/app_server.R b/R/app_server.R
index afd75f0..0100fcd 100644
--- a/R/app_server.R
+++ b/R/app_server.R
@@ -20,7 +20,7 @@ app_server <- function( input, output, session ) {
   db_data <- dplyr::tbl(pool,
                         dbplyr::in_schema("TEXT_MINING",
                                           get_golem_config("trust_name"))) %>%
-    tidy_all_trusts(conn = pool, trust_id = get_golem_config("trust_name"))
+    tidy_all_trusts(conn = pool)
   
   # vector of sentiment names
   
@@ -30,6 +30,12 @@ app_server <- function( input, output, session ) {
     dplyr::pull() %>%
     sort()
   
+  # find out if there is data in the table
+  
+  data_exists <- db_data %>%
+    dplyr::tally() %>% 
+    dplyr::pull(n) > 0
+  
   # store values of demographics and location_1 from last 3 years
   
   interpolate_date <- Sys.Date()
@@ -47,11 +53,9 @@ app_server <- function( input, output, session ) {
   
   output$filter_location_1 <- renderUI({
     
-    if(!isTruthy(get_golem_config("location_1"))){
+    req(get_golem_config("location_1"))
+    req(data_exists)
       
-      return()
-    }
-    
     location_1_choices <- date_filter() %>%
       dplyr::distinct(location_1) %>%
       dplyr::mutate(location_1 = dplyr::na_if(location_1, "Unknown")) %>%
@@ -69,12 +73,9 @@ app_server <- function( input, output, session ) {
   
   output$filter_location_2 <- renderUI({
     
-    if(!isTruthy(get_golem_config("location_2"))){
-      
-      return()
-    }
-    
-    
+    req(get_golem_config("location_2"))
+    req(data_exists)
+
     location_2_choices <- date_filter()
     
     if(isTruthy(input$select_location_1)){ # filter by location_1 if exists
@@ -99,11 +100,9 @@ app_server <- function( input, output, session ) {
   
   output$filter_location_3 <- renderUI({
     
-    if(!isTruthy(get_golem_config("location_3"))){
+    req(get_golem_config("location_3"))
+    req(data_exists)
       
-      return()
-    }
-    
     location_3_choices <- date_filter()
     
     if(isTruthy(input$select_location_1)){ # filter by location_1 if exists
@@ -150,6 +149,7 @@ app_server <- function( input, output, session ) {
       dplyr::filter(date > !!input$date_range[1],
                     date < !!input$date_range[2])
   })
+  
   filter_data <- reactive({
     
     if(get_golem_config("trust_name") == "demo_trust"){
diff --git a/R/tidy_data.R b/R/tidy_data.R
index 614edb7..4248569 100644
--- a/R/tidy_data.R
+++ b/R/tidy_data.R
@@ -12,13 +12,23 @@
 #' Chris Beeley
 #' @section Last updated date:
 #' 2021-04-25
-tidy_all_trusts <- function(data, conn, trust_id) {
+tidy_all_trusts <- function(data, conn) {
   
-  data %>%  
-    dplyr::mutate(category = dplyr::case_when(
-      is.null(comment_txt) ~ NA_character_,
-      is.na(comment_txt) ~ NA_character_,
-      comment_txt %in% c("NULL", "NA", "N/A") ~ NA_character_,
-      TRUE ~ category
-    ))
+  # this line only works if there is data in the table
+  
+  if(data %>%
+     dplyr::tally() %>% 
+     dplyr::pull(n) > 0) {
+    
+    data %>%  
+      dplyr::mutate(category = dplyr::case_when(
+        is.null(comment_txt) ~ NA_character_,
+        is.na(comment_txt) ~ NA_character_,
+        comment_txt %in% c("NULL", "NA", "N/A") ~ NA_character_,
+        TRUE ~ category
+      ))
+  } else {
+    
+    data
+  }
 }
diff --git a/app.R b/app.R
index abf966f..e40688e 100644
--- a/app.R
+++ b/app.R
@@ -2,7 +2,7 @@
 # To deploy, run: rsconnect::deployApp()
 # Or use the blue button on top of this file
 
-Sys.setenv("R_CONFIG_ACTIVE" = "trust_a")
+Sys.setenv("R_CONFIG_ACTIVE" = "trust_b")
 
 pkgload::load_all(export_all = FALSE,
                   helpers = FALSE,
diff --git a/man/tidy_all_trusts.Rd b/man/tidy_all_trusts.Rd
index db745be..e95c68f 100644
--- a/man/tidy_all_trusts.Rd
+++ b/man/tidy_all_trusts.Rd
@@ -4,7 +4,7 @@
 \alias{tidy_all_trusts}
 \title{Tidy patient experience data}
 \usage{
-tidy_all_trusts(data, conn, trust_id)
+tidy_all_trusts(data, conn)
 }
 \arguments{
 \item{data}{dataframe or SQL object, that you can make with get_px_exp()}