Update app.py

app.py

@@ -718,11 +718,12 @@ CRITICAL RULES:
 1.  **DO NOT READ FILES:** You MUST NOT include `pd.read_csv`. The data is ALREADY loaded in the `dfs` variable. You MUST use this variable. Failure to do so will cause a fatal error.
 2.  **JSON OUTPUT ONLY:** Your script's ONLY output must be a single JSON object printed to stdout containing the raw data findings.
 3.  **BE PRECISE:** Use the exact, case-sensitive column names from the schema and robustly clean strings (`re.sub()`) before converting to numbers.
-4.  **JSON SERIALIZATION:** Before adding data to your final dictionary for JSON conversion, you MUST convert any pandas-specific types (like `int64`) to standard Python types using `.item()` for single values or `.tolist()` for lists.
+4.  **JSON SERIALIZATION:** For DataFrame-to-dict conversion, use `json.loads(df.to_json(orient='records'))` which handles type conversion automatically. For single numeric values, use `.item()`. Avoid manual type conversion loops which are error-prone.
 5.  **SINGLE JSON OUTPUT:** Print exactly ONE JSON object at the end of your script. Do not print debug statements or multiple JSON objects.
 6.  **VALID JSON STRUCTURE:** The output MUST be a dictionary/object, not an array or primitive value.
 7.  **SAFE DATA JOINING:** When joining/merging dataframes or looking up values across dataframes, ALWAYS check if matches exist before accessing with `.iloc[0]`. Use `.merge()` with `how='left'` or check `len(filtered_df) > 0` before accessing rows. Never assume keys will match exactly between dataframes.
 8.  **CONSISTENT COLUMN NAMES:** After aggregation or renaming, always use the NEW column names in subsequent operations. Track renamed columns carefully - if you rename 'Zone' to 'zone', use 'zone' everywhere after.
+9.  **SAFE ITERATION:** When iterating over mixed data structures, always check types before accessing attributes. Not all list items are dicts (some may be strings), not all values have `.items()`.
 
 --- USER'S SCENARIO ---
 {user_scenario}