Refactor technical indicators to return DataFrames and enhance documentation

- Updated all technical indicators to return pandas DataFrames instead of lists, improving consistency and usability.
- Modified the `calculate` method in `TechnicalIndicators` to directly return DataFrames with relevant indicator values.
- Enhanced the `data_integration.py` to utilize the new DataFrame outputs for better integration with charting.
- Updated documentation to reflect the new DataFrame-centric approach, including usage examples and output structures.
- Improved error handling to ensure empty DataFrames are returned when insufficient data is available.

These changes streamline the indicator calculations and improve the overall architecture, aligning with project standards for maintainability and performance.

components/charts/config/indicator_defs.py

@@ -11,6 +11,7 @@ from datetime import datetime, timezone
 from decimal import Decimal
 import json
 from enum import Enum
+import pandas as pd
 
 from data.common.indicators import TechnicalIndicators, IndicatorResult, create_default_indicators_config, validate_indicator_config
 from data.common.data_types import OHLCVCandle
@@ -475,7 +476,7 @@ def convert_database_candles_to_ohlcv(candles: List[Dict[str, Any]]) -> List[OHL
 
 def calculate_indicators(candles: List[Dict[str, Any]], 
                         indicator_configs: List[str],
-                        custom_configs: Optional[Dict[str, ChartIndicatorConfig]] = None) -> Dict[str, List[IndicatorResult]]:
+                        custom_configs: Optional[Dict[str, ChartIndicatorConfig]] = None) -> Dict[str, pd.DataFrame]:
     """
     Calculate technical indicators for chart display.
     
@@ -485,7 +486,7 @@ def calculate_indicators(candles: List[Dict[str, Any]],
         custom_configs: Optional custom indicator configurations
         
     Returns:
-        Dictionary mapping indicator names to their calculation results
+        Dictionary mapping indicator names to their calculation results as DataFrames
     """
     if not candles:
         logger.warning("Indicator Definitions: No candles provided for indicator calculation")
@@ -520,6 +521,7 @@ def calculate_indicators(candles: List[Dict[str, Any]],
     # Calculate indicators
     try:
         results = indicators_calc.calculate_multiple_indicators(ohlcv_candles, configs_to_calculate)
+        # results is now a dict of DataFrames
         logger.debug(f"Indicator Definitions: Calculated {len(results)} indicators successfully")
         return results