Update app.py

app.py

@@ -4,7 +4,7 @@ import numpy as np
 import os  
   
 # Configure the page to be mobile-friendly  
-st.set_page_config(layout="centered", page_title="Restaurant Data Viewer")  
+st.set_page_config(layout="centered", page_title="Hong Kong Halal Restaurant Data Viewer")  
   
 # URLs for the logos  
 MAIN_LOGO_URL = "https://islamictrusthk.org/assets/images/top-logo.png"  
@@ -72,12 +72,23 @@ def display_tiles(df, cols):
   
 # Function to detect the format and standardize the data  
 def standardize_data(df):  
-    format_1_columns = {'Issued Date', 'Expiry Date', 'Cert. No', 'Company Name', 'Address', 'Region',   
-                        'Factory Type', 'Contact', 'Phone', 'E-mail', 'Status', 'Member Since'}  
-    format_2_columns = {'Name', 'Address', 'Tel', 'Cuisine', 'Expiry DateDD/MM/YY', 'Location', 'Restaurant Type',   
-                        'Website', 'Directions'}  
+    format_1_columns = {'Name', 'Address', 'Tel', 'Cuisine', 'Expiry Date', 'Location', 'Restaurant Type', 'Website', 'Directions'}  
+    format_2_columns = {'Issued Date', 'Expiry Date', 'Cert. No', 'Company Name', 'Address', 'Region', 'Factory Type', 'Contact', 'Phone', 'E-mail', 'Status', 'Member Since'}  
       
     if format_1_columns.issubset(df.columns):  
+        df = df.rename(columns={  
+            'Name': 'Company Name',  
+            'Address': 'Address',  
+            'Tel': 'Phone',  
+            'Cuisine': 'Factory Type',  
+            'Expiry Date': 'Expiry Date',  
+            'Location': 'Region',  
+            'Restaurant Type': 'Factory Type',  
+            'Website': 'Website',  
+            'Directions': 'Directions'  
+        })  
+        required_columns = ['Company Name', 'Address', 'Phone', 'Factory Type', 'Expiry Date', 'Region', 'Website', 'Directions']  
+    elif format_2_columns.issubset(df.columns):  
         df = df.rename(columns={  
             'Issued Date': 'Issued Date',  
             'Expiry Date': 'Expiry Date',  
@@ -92,20 +103,7 @@ def standardize_data(df):
             'Status': 'Status',  
             'Member Since': 'Member Since'  
         })  
-        required_columns = list(format_1_columns)  
-    elif format_2_columns.issubset(df.columns):  
-        df = df.rename(columns={  
-            'Name': 'Company Name',  
-            'Address': 'Address',  
-            'Tel': 'Phone',  
-            'Cuisine': 'Factory Type',  
-            'Expiry DateDD/MM/YY': 'Expiry Date',  
-            'Location': 'Region',  
-            'Restaurant Type': 'Factory Type',  
-            'Website': 'Website',  
-            'Directions': 'Directions'  
-        })  
-        required_columns = list(format_1_columns)  # Use the same required columns for consistency  
+        required_columns = ['Issued Date', 'Expiry Date', 'Cert No', 'Company Name', 'Address', 'Region', 'Factory Type', 'Contact', 'Phone', 'E-mail', 'Status', 'Member Since']  
     else:  
         st.error("Unsupported file format")  
         return None, []  
@@ -226,7 +224,7 @@ else:
                 company_name_filter = st.text_input("Company Name contains")  
             with col2:  
                 # Filter by Location  
-                location_filter = st.multiselect("Location", df['Region'].drop_duplicates())  
+                location_filter = st.multiselect("Region", df['Region'].drop_duplicates())  
             with col3:  
                 # Filter by Restaurant Type  
                 restaurant_type_filter = st.multiselect("Factory Type", df['Factory Type'].drop_duplicates())