Implement multi-timeframe support for indicators

- Enhanced the `UserIndicator` class to include an optional `timeframe` attribute for custom indicator timeframes.
- Updated the `get_indicator_data` method in `MarketDataIntegrator` to fetch and calculate indicators based on the specified timeframe, ensuring proper data alignment and handling.
- Modified the `ChartBuilder` to pass the correct DataFrame for plotting indicators with different timeframes.
- Added UI elements in the indicator modal for selecting timeframes, improving user experience.
- Updated relevant JSON templates to include the new `timeframe` field for all indicators.
- Refactored the `prepare_chart_data` function to ensure it returns a DataFrame with a `DatetimeIndex` for consistent calculations.

This commit enhances the flexibility and usability of the indicator system, allowing users to analyze data across various timeframes.

dashboard/components/data_analysis.py

@@ -562,21 +562,28 @@ def get_market_statistics(df: pd.DataFrame, symbol: str, timeframe: str) -> html
     """
     Generate a comprehensive market statistics component from a DataFrame.
     """
+    if df.empty:
+        return html.Div("No data available for statistics.", className="text-center text-muted")
+
     try:
-        volume_analyzer = VolumeAnalyzer()
+        # Get statistics
         price_analyzer = PriceMovementAnalyzer()
+        volume_analyzer = VolumeAnalyzer()
         
-        volume_stats = volume_analyzer.get_volume_statistics(df)
         price_stats = price_analyzer.get_price_movement_statistics(df)
+        volume_stats = volume_analyzer.get_volume_statistics(df)
         
-        if 'error' in volume_stats or 'error' in price_stats:
-            error_msg = volume_stats.get('error') or price_stats.get('error')
+        # Format key statistics for display
+        start_date = df.index.min().strftime('%Y-%m-%d %H:%M')
+        end_date = df.index.max().strftime('%Y-%m-%d %H:%M')
+        
+        # Check for errors from analyzers
+        if 'error' in price_stats or 'error' in volume_stats:
+            error_msg = price_stats.get('error') or volume_stats.get('error')
             return html.Div(f"Error generating statistics: {error_msg}", style={'color': 'red'})
             
         # Time range for display
-        start_date = df['timestamp'].min().strftime('%Y-%m-%d %H:%M')
-        end_date = df['timestamp'].max().strftime('%Y-%m-%d %H:%M')
-        days_back = (df['timestamp'].max() - df['timestamp'].min()).days
+        days_back = (df.index.max() - df.index.min()).days
         time_status = f"📅 Analysis Range: {start_date} to {end_date} (~{days_back} days)"
         
         return html.Div([

dashboard/components/indicator_modal.py

@@ -33,6 +33,27 @@ def create_indicator_modal():
                         placeholder='Select indicator type',
                     ), width=12)
                 ], className="mb-3"),
+                dbc.Row([
+                    dbc.Col(dbc.Label("Timeframe (Optional):"), width=12),
+                    dbc.Col(dcc.Dropdown(
+                        id='indicator-timeframe-dropdown',
+                        options=[
+                            {'label': 'Chart Timeframe', 'value': ''},
+                            {'label': "1 Second", 'value': '1s'},
+                            {'label': "5 Seconds", 'value': '5s'},
+                            {'label': "15 Seconds", 'value': '15s'},    
+                            {'label': "30 Seconds", 'value': '30s'},
+                            {'label': '1 Minute', 'value': '1m'},
+                            {'label': '5 Minutes', 'value': '5m'},
+                            {'label': '15 Minutes', 'value': '15m'},
+                            {'label': '1 Hour', 'value': '1h'},
+                            {'label': '4 Hours', 'value': '4h'},
+                            {'label': '1 Day', 'value': '1d'},
+                        ],
+                        value='',
+                        placeholder='Defaults to chart timeframe'
+                    ), width=12),
+                ], className="mb-3"),
                 dbc.Row([
                     dbc.Col(dbc.Label("Description (Optional):"), width=12),
                     dbc.Col(dcc.Textarea(