Update app.py

app.py

@@ -41,7 +41,7 @@ if search_keyword:
 else:
     filtered_specialties = specialties[specialties['Display Name'] == selected_specialty]
 
-st.dataframe(filtered_specialties)
+st.dataframe(filtered_specialties[['Code', 'Grouping', 'Classification', 'Specialization', 'Definition']])
 
 # State selection UI with default selection for testing
 state_files = find_state_files()
@@ -58,9 +58,12 @@ def process_files(specialty_codes, specific_state='MN'):
     
     for file in [file_to_process] if use_specific_state else state_files:
         state_df = pd.read_csv(file, header=None)  # Assuming no header for simplicity
-        filtered_df = state_df[state_df[47].isin(specialty_codes)]  # Assuming the code is in the 48th column
-        if not filtered_df.empty:
-            results.append((os.path.basename(file).replace('.csv', ''), filtered_df))
+        for code in specialty_codes:
+            filtered_df = state_df[state_df[47].isin([code])]  # Match against 48th column, adjust as needed
+            if not filtered_df.empty:
+                # Enhance the display to include 'Code', 'Grouping', and 'Classification' information
+                display_info = specialties[specialties['Code'] == code][['Code', 'Grouping', 'Classification']].iloc[0].to_dict()
+                results.append((os.path.basename(file).replace('.csv', ''), display_info, filtered_df))
     
     return results
 
@@ -69,8 +72,9 @@ if st.button('Analyze Text Files for Selected Specialty 🔍'):
     specialty_codes = filtered_specialties['Code'].tolist()
     state_data = process_files(specialty_codes, selected_state if use_specific_state else None)
     if state_data:
-        for state, df in state_data:
+        for state, info, df in state_data:
             st.subheader(f"Providers in {state} with Specialties related to '{search_keyword or selected_specialty}':")
+            st.markdown(f"**Code**: {info['Code']}, **Grouping**: {info['Grouping']}, **Classification**: {info['Classification']}")
             st.dataframe(df)
     else:
         st.write("No matching records found in text files for the selected specialties.")