Update app.py

app.py

@@ -90,17 +90,17 @@ specialties = load_specialties()
 st.markdown("# 🩺🔍 Care Team Finder ")
 st.markdown("#### Search for Care Providers by Specialty and Location")
 
-if st.expander('🩺 Understand Provider Specialties 📝', expanded=False):
+if st.expander(label='🩺 Understand Provider Specialties 📝', expanded=False):
     st.markdown('''
-## Discover Care Providers by Specialty & Location: Quick Guide
-- **Code**: Unique ID identifies each specialty clearly. 🆔
-- **Grouping**: Broad category umbrella for general expertise area. 🏷️
-- **Classification**: Specifies type of practice within broader category. 🎯
-- **Specialization**: Details focus within classification for precise expertise. 🔍
-- **Definition**: Concise overview of the specialty's scope. 📖
-- **Notes**: Extra information or recent updates provided. 🗒️
-- **Display Name**: Commonly recognized name of the specialty. 🏷️
-- **Section**: Healthcare segment the specialty belongs to. 📚
+        ## Discover Care Providers by Specialty & Location: Quick Guide
+        - **Code**: Unique ID identifies each specialty clearly. 🆔
+        - **Grouping**: Broad category umbrella for general expertise area. 🏷️
+        - **Classification**: Specifies type of practice within broader category. 🎯
+        - **Specialization**: Details focus within classification for precise expertise. 🔍
+        - **Definition**: Concise overview of the specialty's scope. 📖
+        - **Notes**: Extra information or recent updates provided. 🗒️
+        - **Display Name**: Commonly recognized name of the specialty. 🏷️
+        - **Section**: Healthcare segment the specialty belongs to. 📚
     ''')
 
 # Allows users to select or search for a specialty
@@ -134,12 +134,14 @@ def process_files(specialty_codes, specific_state='MN'):
         #state_df = pd.read_csv(file, header=0)  # Assuming no header for simplicity
         
         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))
-    
+            try:
+                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))
+            except:
+                st.write('.')
     return results
 
 # Button to initiate the analysis