⚡ Optimize DataFrame to dict conversion in _get_stock_stats_bulk

Replaced the inefficient `iterrows()` loop with vectorized operations:
`df.set_index("Date")[indicator].fillna("N/A").astype(str).to_dict()`

This change improves performance while maintaining the exact original behavior for NaN values and string conversion.

Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>

tradingagents/dataflows/y_finance.py

@@ -253,18 +253,8 @@ def _get_stock_stats_bulk(
     df[indicator]  # This triggers stockstats to calculate the indicator
     
     # Create a dictionary mapping date strings to indicator values
-    result_dict = {}
+    # Optimized: replaced iterrows() with vectorized operations for performance
-    for _, row in df.iterrows():
+    return df.set_index("Date")[indicator].fillna("N/A").astype(str).to_dict()
-        date_str = row["Date"]
-        indicator_value = row[indicator]
-        
-        # Handle NaN/None values
-        if pd.isna(indicator_value):
-            result_dict[date_str] = "N/A"
-        else:
-            result_dict[date_str] = str(indicator_value)
-    
-    return result_dict
 
 
 def get_stockstats_indicator(