3.6 Enhance market statistics with comprehensive data analysis features
- Updated `register_chart_callbacks` to include enhanced market statistics. - Implemented new data analysis callbacks in `dashboard/callbacks/data_analysis.py` for volume and price movement analysis. - Created `VolumeAnalyzer` and `PriceMovementAnalyzer` classes for detailed statistical calculations. - Integrated data analysis components into the market statistics layout, providing users with insights on volume trends and price movements. - Improved error handling and logging for data analysis operations. - Updated documentation to reflect the new features and usage guidelines.
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Vasily.onl
@@ -92,30 +92,145 @@ def register_chart_callbacks(app):
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logger.error(f"Chart callback: Error loading strategy indicators: {e}")
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return [], []
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# Market statistics callback
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# Enhanced market statistics callback with comprehensive analysis
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@app.callback(
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Output('market-stats', 'children'),
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[Input('symbol-dropdown', 'value'),
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Input('timeframe-dropdown', 'value'),
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Input('interval-component', 'n_intervals')]
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)
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def update_market_stats(symbol, n_intervals):
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"""Update market statistics."""
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def update_market_stats(symbol, timeframe, n_intervals):
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"""Update comprehensive market statistics with analysis."""
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try:
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# Get real market statistics from database
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stats = get_market_statistics(symbol)
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# Import analysis classes
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from dashboard.components.data_analysis import VolumeAnalyzer, PriceMovementAnalyzer
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# Get basic market statistics
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basic_stats = get_market_statistics(symbol, timeframe)
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# Create analyzers for comprehensive analysis
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volume_analyzer = VolumeAnalyzer()
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price_analyzer = PriceMovementAnalyzer()
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# Get analysis for 7 days
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volume_analysis = volume_analyzer.get_volume_statistics(symbol, timeframe, 7)
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price_analysis = price_analyzer.get_price_movement_statistics(symbol, timeframe, 7)
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# Create enhanced statistics layout
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return html.Div([
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html.H3("Market Statistics"),
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html.H3("📊 Enhanced Market Statistics"),
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# Basic Market Data
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html.Div([
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html.H4("💹 Current Market Data", style={'color': '#2c3e50', 'margin-bottom': '10px'}),
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html.Div([
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html.Strong(f"{key}: "),
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html.Span(value, style={'color': '#27ae60' if '+' in str(value) else '#e74c3c' if '-' in str(value) else '#2c3e50'})
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], style={'margin': '5px 0'}) for key, value in stats.items()
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])
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html.Div([
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html.Strong(f"{key}: "),
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html.Span(value, style={
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'color': '#27ae60' if '+' in str(value) else '#e74c3c' if '-' in str(value) else '#2c3e50',
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'font-weight': 'bold'
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})
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], style={'margin': '5px 0'}) for key, value in basic_stats.items()
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])
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], style={'border': '1px solid #bdc3c7', 'padding': '15px', 'margin': '10px 0', 'border-radius': '5px', 'background-color': '#f8f9fa'}),
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# Volume Analysis Section
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create_volume_analysis_section(volume_analysis),
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# Price Movement Analysis Section
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create_price_movement_section(price_analysis),
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# Additional Market Insights
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html.Div([
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html.H4("🔍 Market Insights", style={'color': '#2c3e50', 'margin-bottom': '10px'}),
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html.Div([
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html.P(f"📈 Analysis Period: 7 days | Timeframe: {timeframe}", style={'margin': '5px 0'}),
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html.P(f"🎯 Symbol: {symbol}", style={'margin': '5px 0'}),
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html.P("💡 Statistics update automatically with chart changes", style={'margin': '5px 0', 'font-style': 'italic'})
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])
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], style={'border': '1px solid #3498db', 'padding': '15px', 'margin': '10px 0', 'border-radius': '5px', 'background-color': '#ebf3fd'})
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])
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except Exception as e:
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logger.error(f"Chart callback: Error updating market stats: {e}")
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return html.Div("Error loading market statistics")
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logger.error(f"Chart callback: Error updating enhanced market stats: {e}")
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return html.Div([
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html.H3("Market Statistics"),
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html.P(f"Error loading statistics: {str(e)}", style={'color': '#e74c3c'})
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])
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def create_volume_analysis_section(volume_stats):
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"""Create volume analysis section for market statistics."""
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if not volume_stats or volume_stats.get('total_volume', 0) == 0:
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return html.Div([
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html.H4("📊 Volume Analysis", style={'color': '#2c3e50', 'margin-bottom': '10px'}),
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html.P("No volume data available for analysis", style={'color': '#e74c3c'})
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], style={'border': '1px solid #e74c3c', 'padding': '15px', 'margin': '10px 0', 'border-radius': '5px', 'background-color': '#fdeded'})
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return html.Div([
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html.H4("📊 Volume Analysis (7 days)", style={'color': '#2c3e50', 'margin-bottom': '10px'}),
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html.Div([
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html.Div([
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html.Strong("Total Volume: "),
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html.Span(f"{volume_stats.get('total_volume', 0):,.2f}", style={'color': '#27ae60'})
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], style={'margin': '5px 0'}),
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html.Div([
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html.Strong("Average Volume: "),
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html.Span(f"{volume_stats.get('average_volume', 0):,.2f}", style={'color': '#2c3e50'})
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], style={'margin': '5px 0'}),
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html.Div([
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html.Strong("Volume Trend: "),
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html.Span(
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volume_stats.get('volume_trend', 'Neutral'),
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style={'color': '#27ae60' if volume_stats.get('volume_trend') == 'Increasing' else '#e74c3c' if volume_stats.get('volume_trend') == 'Decreasing' else '#f39c12'}
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)
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], style={'margin': '5px 0'}),
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html.Div([
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html.Strong("High Volume Periods: "),
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html.Span(f"{volume_stats.get('high_volume_periods', 0)}", style={'color': '#2c3e50'})
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], style={'margin': '5px 0'})
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])
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], style={'border': '1px solid #27ae60', 'padding': '15px', 'margin': '10px 0', 'border-radius': '5px', 'background-color': '#eafaf1'})
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def create_price_movement_section(price_stats):
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"""Create price movement analysis section for market statistics."""
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if not price_stats or price_stats.get('total_returns') is None:
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return html.Div([
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html.H4("📈 Price Movement Analysis", style={'color': '#2c3e50', 'margin-bottom': '10px'}),
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html.P("No price movement data available for analysis", style={'color': '#e74c3c'})
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], style={'border': '1px solid #e74c3c', 'padding': '15px', 'margin': '10px 0', 'border-radius': '5px', 'background-color': '#fdeded'})
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return html.Div([
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html.H4("📈 Price Movement Analysis (7 days)", style={'color': '#2c3e50', 'margin-bottom': '10px'}),
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html.Div([
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html.Div([
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html.Strong("Total Return: "),
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html.Span(
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f"{price_stats.get('total_returns', 0):+.2f}%",
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style={'color': '#27ae60' if price_stats.get('total_returns', 0) >= 0 else '#e74c3c'}
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)
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], style={'margin': '5px 0'}),
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html.Div([
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html.Strong("Volatility: "),
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html.Span(f"{price_stats.get('volatility', 0):.2f}%", style={'color': '#2c3e50'})
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], style={'margin': '5px 0'}),
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html.Div([
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html.Strong("Bullish Periods: "),
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html.Span(f"{price_stats.get('bullish_periods', 0)}", style={'color': '#27ae60'})
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], style={'margin': '5px 0'}),
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html.Div([
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html.Strong("Bearish Periods: "),
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html.Span(f"{price_stats.get('bearish_periods', 0)}", style={'color': '#e74c3c'})
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], style={'margin': '5px 0'}),
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html.Div([
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html.Strong("Trend Strength: "),
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html.Span(
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price_stats.get('trend_strength', 'Neutral'),
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style={'color': '#27ae60' if 'Strong' in str(price_stats.get('trend_strength', '')) else '#f39c12'}
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)
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], style={'margin': '5px 0'})
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])
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], style={'border': '1px solid #3498db', 'padding': '15px', 'margin': '10px 0', 'border-radius': '5px', 'background-color': '#ebf3fd'})
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logger.info("Chart callback: Chart callbacks registered successfully")
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49
dashboard/callbacks/data_analysis.py
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49
dashboard/callbacks/data_analysis.py
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@@ -0,0 +1,49 @@
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"""
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Data analysis callbacks for the dashboard.
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"""
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from dash import Output, Input, html, dcc
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import dash_mantine_components as dmc
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from utils.logger import get_logger
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from dashboard.components.data_analysis import (
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VolumeAnalyzer,
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PriceMovementAnalyzer,
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create_volume_analysis_chart,
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create_price_movement_chart,
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create_volume_stats_display,
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create_price_stats_display
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)
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logger = get_logger("data_analysis_callbacks")
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def register_data_analysis_callbacks(app):
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"""Register data analysis related callbacks."""
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logger.info("🚀 STARTING to register data analysis callbacks...")
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# Initial callback to populate charts on load
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@app.callback(
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[Output('analysis-chart-container', 'children'),
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Output('analysis-stats-container', 'children')],
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[Input('analysis-type-selector', 'value'),
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Input('analysis-period-selector', 'value')],
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prevent_initial_call=False
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)
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def update_data_analysis(analysis_type, period):
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"""Update data analysis with statistical cards only (no duplicate charts)."""
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logger.info(f"🎯 DATA ANALYSIS CALLBACK TRIGGERED! Type: {analysis_type}, Period: {period}")
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# Return placeholder message since we're moving to enhanced market stats
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info_msg = html.Div([
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html.H4("📊 Statistical Analysis"),
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html.P("Data analysis has been integrated into the Market Statistics section above."),
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html.P("The enhanced statistics now include volume analysis, price movement analysis, and trend indicators."),
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html.P("Change the symbol and timeframe in the main chart to see updated analysis."),
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html.Hr(),
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html.Small("This section will be updated with additional analytical tools in future versions.")
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], style={'border': '2px solid #17a2b8', 'padding': '20px', 'margin': '10px', 'background-color': '#d1ecf1'})
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return info_msg, html.Div()
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logger.info("✅ Data analysis callbacks registered successfully")
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