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="Halal Restaurant Data Viewer")  
   
 # URLs for the logos  
 MAIN_LOGO_URL = "https://islamictrusthk.org/assets/images/top-logo.png"  
@@ -70,46 +70,6 @@ def display_tiles(df, cols):
             st.markdown(f"**E-mail:** {row['E-mail']}")  
             st.markdown("---")  
   
-# Function to detect the format and standardize the data  
-def standardize_data(df):  
-    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',  
-            'Cert. No': 'Cert No',  
-            'Company Name': 'Company Name',  
-            'Address': 'Address',  
-            'Region': 'Region',  
-            'Factory Type': 'Factory Type',  
-            'Contact': 'Contact',  
-            'Phone': 'Phone',  
-            'E-mail': 'E-mail',  
-            'Status': 'Status',  
-            'Member Since': 'Member Since'  
-        })  
-        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, []  
-  
-    return df, required_columns  
-  
 # Initialize session state  
 if 'df' not in st.session_state:  
     st.session_state.df = None  
@@ -120,8 +80,8 @@ if 'login_attempt' not in st.session_state:
   
 # List of valid usernames and passwords  
 user_credentials = {  
-    'user1': 'password1',  
-    'user2': 'password2'  
+    'ubaid': 'Password@123',  
+    'bot': 'Trust@123'  
 }  
   
 # Authentication function  
@@ -149,7 +109,7 @@ if not st.session_state.authenticated:
 else:  
     st.write("User authenticated successfully")  
     st.image(MAIN_LOGO_URL, use_column_width=True)  
-    st.title("Restaurant Data Viewer")  
+    st.title("Hong Kong Halal Restaurant Data Viewer")  
   
     # File upload logic  
     with st.sidebar:  
@@ -168,10 +128,7 @@ else:
   
                 st.success(f"File '{uploaded_file.name}' uploaded successfully.")  
                 df = load_data(file_path)  
-                df, required_columns = standardize_data(df)  
-                if df is not None:  
-                    st.session_state.df = df  
-                    st.session_state.required_columns = required_columns  
+                st.session_state.df = df  
             except Exception as e:  
                 st.error(f"An error occurred: {e}")  
   
@@ -189,10 +146,7 @@ else:
                 try:  
                     file_path = os.path.join(UPLOAD_DIR, selected_file)  
                     df = load_data(file_path)  
-                    df, required_columns = standardize_data(df)  
-                    if df is not None:  
-                        st.session_state.df = df  
-                        st.session_state.required_columns = required_columns  
+                    st.session_state.df = df  
                 except Exception as e:  
                     st.error(f"An error occurred: {e}")  
         else:  
@@ -202,12 +156,19 @@ else:
     if st.session_state.df is not None:  
         df = st.session_state.df  
   
+        # Define required columns  
+        required_columns = [  
+            'Issued Date', 'Expiry Date', 'Cert. No', 'Company Name', 'Address', 'Region',   
+            'Factory Type', 'Contact', 'Phone', 'E-mail', 'Status', 'Member Since'  
+        ]  
+  
         # Verify required columns  
-        missing_columns = verify_columns(df, st.session_state.required_columns)  
+        missing_columns = verify_columns(df, required_columns)  
         if missing_columns:  
             st.error(f"The following required columns are missing from the uploaded file: {', '.join(missing_columns)}")  
         else:  
             # Format the date columns to remove time  
+            df = format_date_column(df, 'Issued Date')  
             df = format_date_column(df, 'Expiry Date')  
   
             # Display the dataframe  
@@ -223,11 +184,11 @@ else:
                 # Filter by Company Name  
                 company_name_filter = st.text_input("Company Name contains")  
             with col2:  
-                # Filter by Location  
-                location_filter = st.multiselect("Region", df['Region'].drop_duplicates())  
+                # Filter by Region  
+                region_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())  
+                # Filter by Factory Type  
+                factory_type_filter = st.multiselect("Factory Type", df['Factory Type'].drop_duplicates())  
             with col4:  
                 # Filter by Expiry Date  
                 expiry_date_filter = st.date_input("Expiry Date", [])  
@@ -237,10 +198,10 @@ else:
   
             if company_name_filter:  
                 filtered_df = filtered_df[filtered_df['Company Name'].str.contains(company_name_filter, case=False, na=False)]  
-            if location_filter:  
-                filtered_df = filtered_df[filtered_df['Region'].isin(location_filter)]  
-            if restaurant_type_filter:  
-                filtered_df = filtered_df[filtered_df['Factory Type'].isin(restaurant_type_filter)]  
+            if region_filter:  
+                filtered_df = filtered_df[filtered_df['Region'].isin(region_filter)]  
+            if factory_type_filter:  
+                filtered_df = filtered_df[filtered_df['Factory Type'].isin(factory_type_filter)]  
             if expiry_date_filter:  
                 if len(expiry_date_filter) == 1:  
                     filtered_df = filtered_df[filtered_df['Expiry Date'] == expiry_date_filter[0]]  
@@ -264,4 +225,4 @@ else:
                     mime='text/csv',  
                 )  
             else:  
-                st.info("No data matches the filter criteria.") 
+                st.info("No data matches the filter criteria.")