Format precautions output as bullet points and normalize occurrences output

frontend/app.py

@@ -197,37 +197,31 @@ else:
 
     # --- Functions for Symptom Detection ---
     def precaution(label):
-        dataset_precau = pd.read_csv("disease_precaution.csv", encoding='latin1') # Make sure this file is in the same directory
-        label = str(label)
-        label = label.lower() 
-
+        dataset_precau = pd.read_csv("disease_precaution.csv", encoding='latin1')  # Make sure this file is in the same directory
+        label = str(label).lower()
+    
         dataset_precau["Disease"] = dataset_precau["Disease"].str.lower()
-        # Filter the DataFrame for the given label
         filtered_precautions = dataset_precau[dataset_precau["Disease"] == label]
-
-        # Check if any precautions were found
+    
         if not filtered_precautions.empty:
-            # Extract precaution columns
             precautions = filtered_precautions[["Precaution_1", "Precaution_2", "Precaution_3", "Precaution_4"]]
-            return precautions.values.tolist()  # Convert DataFrame to a list of lists
+            precautions_list = precautions.values.flatten().tolist()  # Flatten the DataFrame to a list of strings
+            return "\n".join(f"- {precaution}" for precaution in precautions_list)  # Join the list into a single string with bullet points
         else:
-            return []  # Return an empty list if no matching label is found
+            return "No precautions found."
 
     def occurance(label):
         dataset_occur = pd.read_csv("disease_riskFactors.csv", encoding='latin1')
-        label = str(label)
-        label = label.lower() 
-
+        label = str(label).lower()
+    
         dataset_occur["DNAME"] = dataset_occur["DNAME"].str.lower()
-        # Filter the DataFrame for the given label
         filtered_occurrence = dataset_occur[dataset_occur["DNAME"] == label]
-
-        # Check if any occurrences were found
-        if not filtered_occurrence.empty:
-            occurrences = filtered_occurrence["OCCUR"].tolist()  # Convert Series to list
-            return occurrences
+    
+        occurrences = filtered_occurrence["OCCUR"].tolist()  # Convert Series to list
+        if occurrences:
+            return "\n".join(occurrences)  # Join the list into a single string with newlines
         else:
-            return []  # Return an empty list if no matching label is found
+            return "No occurrences found."
 
     if page == "Home":
         st.markdown("## Welcome to Medi Scape")