Update app.py

app.py

@@ -4,21 +4,34 @@ import os
 import glob
 
 # Load the provider specialty dataset CSV
-@st.cache_resource
+@st.cache(allow_output_mutation=True)
 def load_specialties(csv_file='Provider-Specialty.csv'):
     return pd.read_csv(csv_file)
 
 specialties = load_specialties()
 
 # User interface for specialty selection
-st.title('Provider Specialty Analyzer')
+st.title('🔍 Provider Specialty Analyzer')
+
+# Markdown outline for the fields description
+st.markdown("""
+## Specialty Fields Description 📋
+- **Code**: Unique identifier for the specialty.
+- **Grouping**: General category the specialty belongs to.
+- **Classification**: More detailed classification within the grouping.
+- **Specialization**: Further specialization details if applicable.
+- **Definition**: Brief description of the specialty.
+- **Notes**: Any additional notes or historical information.
+- **Display Name**: The common name used to display the specialty.
+- **Section**: The section of healthcare the specialty falls under.
+""")
 
 # Dropdown for selecting a specialty
 specialty_options = specialties['Display Name'].unique()
-selected_specialty = st.selectbox('Select a Specialty', options=specialty_options)
+selected_specialty = st.selectbox('Select a Specialty 📂', options=specialty_options)
 
 # Display specialties matching the selected option or search keyword
-search_keyword = st.text_input('Or search for a keyword in specialties')
+search_keyword = st.text_input('Or search for a keyword in specialties 🔍')
 if search_keyword:
     filtered_specialties = specialties[specialties.apply(lambda row: row.astype(str).str.contains(search_keyword, case=False).any(), axis=1)]
 else:
@@ -36,12 +49,12 @@ def process_state_files(specialty_code):
         state_df = pd.read_csv(file, names=['Code', 'Grouping', 'Classification', 'Specialization', 'Definition', 'Notes', 'Display Name', 'Section'])
         filtered_df = state_df[state_df['Code'] == specialty_code]
         if not filtered_df.empty:
-            results.append((os.path.basename(file), filtered_df))
+            results.append((os.path.basename(file).split('.')[0], filtered_df))
     
     return results
 
 # Show DataFrame UI for files matching the specialty code in the selected state
-if st.button('Analyze Text Files for Selected Specialty'):
+if st.button('Analyze Text Files for Selected Specialty 📊'):
     specialty_code = specialties[specialties['Display Name'] == selected_specialty].iloc[0]['Code']
     state_data = process_state_files(specialty_code)
     if state_data:
@@ -49,5 +62,4 @@ if st.button('Analyze Text Files for Selected Specialty'):
             st.subheader(f"Providers in {state} with Specialty '{selected_specialty}':")
             st.dataframe(df)
     else:
-        st.write("No matching records found in text files for the selected specialty.")
-
+        st.write("No matching records found in text files for the selected specialty. 🚫")