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<!DOCTYPE html> |
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<html lang="en"> |
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<head> |
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<meta charset="UTF-8"> |
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<meta name="viewport" content="width=device-width, initial-scale=1.0"> |
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<title>Utility Data Analysis Dashboard</title> |
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<script src="https://cdn.tailwindcss.com"></script> |
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<script src="https://cdn.jsdelivr.net/npm/chart.js"></script> |
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<script src="https://kit.fontawesome.com/a076d05399.js" crossorigin="anonymous"></script> |
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<style> |
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.highlight-box { |
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border-left: 4px solid #3b82f6; |
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background-color: #f8fafc; |
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transition: all 0.3s ease; |
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} |
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.highlight-box:hover { |
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background-color: #eff6ff; |
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transform: translateY(-2px); |
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} |
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.data-card { |
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box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1), 0 2px 4px -1px rgba(0, 0, 0, 0.06); |
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transition: all 0.3s ease; |
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} |
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.data-card:hover { |
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box-shadow: 0 10px 15px -3px rgba(0, 0, 0, 0.1), 0 4px 6px -2px rgba(0, 0, 0, 0.05); |
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} |
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.tab-content { |
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display: none; |
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} |
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.tab-content.active { |
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display: block; |
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} |
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.tab-button { |
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transition: all 0.3s ease; |
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} |
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.tab-button.active { |
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border-bottom: 3px solid #3b82f6; |
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color: #3b82f6; |
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font-weight: 600; |
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} |
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</style> |
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</head> |
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<body class="bg-gray-50"> |
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<div class="container mx-auto px-4 py-8"> |
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<header class="mb-8"> |
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<h1 class="text-3xl font-bold text-gray-800 mb-2">Utility Consumption Analysis Dashboard</h1> |
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<p class="text-gray-600">Visual representation of utility consumption patterns with anomaly detection</p> |
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</header> |
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<div class="grid grid-cols-1 md:grid-cols-3 gap-6 mb-8"> |
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<div class="data-card bg-white rounded-lg p-6"> |
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<div class="flex items-center mb-4"> |
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<div class="p-3 rounded-full bg-blue-100 text-blue-600 mr-4"> |
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<i class="fas fa-tint text-xl"></i> |
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</div> |
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<div> |
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<h3 class="text-gray-500 text-sm font-medium">Water Consumption</h3> |
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<p class="text-2xl font-bold text-gray-800">Varies by property</p> |
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</div> |
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</div> |
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<p class="text-gray-600 text-sm">Shows steady increase with seasonal variations</p> |
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</div> |
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<div class="data-card bg-white rounded-lg p-6"> |
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<div class="flex items-center mb-4"> |
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<div class="p-3 rounded-full bg-yellow-100 text-yellow-600 mr-4"> |
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<i class="fas fa-bolt text-xl"></i> |
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</div> |
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<div> |
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<h3 class="text-gray-500 text-sm font-medium">Electricity Usage</h3> |
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<p class="text-2xl font-bold text-gray-800">Significant peaks</p> |
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</div> |
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</div> |
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<p class="text-gray-600 text-sm">Notable spikes in winter months for heating</p> |
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</div> |
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<div class="data-card bg-white rounded-lg p-6"> |
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<div class="flex items-center mb-4"> |
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<div class="p-3 rounded-full bg-red-100 text-red-600 mr-4"> |
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<i class="fas fa-fire text-xl"></i> |
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</div> |
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<div> |
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<h3 class="text-gray-500 text-sm font-medium">Heating Costs</h3> |
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<p class="text-2xl font-bold text-gray-800">Seasonal pattern</p> |
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</div> |
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</div> |
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<p class="text-gray-600 text-sm">Highest in winter months, lowest in summer</p> |
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</div> |
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</div> |
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<div class="bg-white rounded-lg shadow-md mb-8"> |
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<div class="flex border-b"> |
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<button class="tab-button active px-6 py-4 text-gray-700" onclick="openTab(event, 'water')">Water Usage</button> |
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<button class="tab-button px-6 py-4 text-gray-700" onclick="openTab(event, 'electricity')">Electricity</button> |
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<button class="tab-button px-6 py-4 text-gray-700" onclick="openTab(event, 'heating')">Heating</button> |
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<button class="tab-button px-6 py-4 text-gray-700" onclick="openTab(event, 'anomalies')">Anomalies</button> |
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</div> |
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<div id="water" class="tab-content active p-6"> |
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<h2 class="text-xl font-semibold mb-4 text-gray-800">Water Consumption Analysis</h2> |
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<div class="grid grid-cols-1 lg:grid-cols-2 gap-6"> |
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<div> |
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<canvas id="waterChart"></canvas> |
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</div> |
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<div> |
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<div class="highlight-box p-4 mb-4 rounded"> |
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<h3 class="font-medium text-blue-600 mb-2"><i class="fas fa-info-circle mr-2"></i>Key Observation</h3> |
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<p class="text-gray-700">The Páva property shows significantly lower water consumption compared to NagyLajos and Rozsnyay, suggesting either more efficient fixtures or different usage patterns.</p> |
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</div> |
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<div class="highlight-box p-4 rounded"> |
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<h3 class="font-medium text-blue-600 mb-2"><i class="fas fa-chart-line mr-2"></i>Trend Analysis</h3> |
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<p class="text-gray-700">All properties show a steady increase in water consumption over time, with Rozsnyay having the highest absolute consumption values.</p> |
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</div> |
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</div> |
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</div> |
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</div> |
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<div id="electricity" class="tab-content p-6"> |
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<h2 class="text-xl font-semibold mb-4 text-gray-800">Electricity Consumption Analysis</h2> |
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<div class="grid grid-cols-1 lg:grid-cols-2 gap-6"> |
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<div> |
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<canvas id="electricityChart"></canvas> |
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</div> |
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<div> |
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<div class="highlight-box p-4 mb-4 rounded"> |
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<h3 class="font-medium text-blue-600 mb-2"><i class="fas fa-bolt mr-2"></i>Peak Usage</h3> |
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<p class="text-gray-700">The Rozsnyay property shows extreme electricity consumption in 2018 (41,366 units), which appears to be a data anomaly or meter reading error.</p> |
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</div> |
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<div class="highlight-box p-4 rounded"> |
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<h3 class="font-medium text-blue-600 mb-2"><i class="fas fa-calendar-alt mr-2"></i>Seasonal Pattern</h3> |
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<p class="text-gray-700">Electricity usage tends to be higher in winter months across all properties, likely due to increased heating requirements.</p> |
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</div> |
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</div> |
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</div> |
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</div> |
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<div id="heating" class="tab-content p-6"> |
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<h2 class="text-xl font-semibold mb-4 text-gray-800">Heating Consumption Analysis</h2> |
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<div class="grid grid-cols-1 lg:grid-cols-2 gap-6"> |
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<div> |
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<canvas id="heatingChart"></canvas> |
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</div> |
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<div> |
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<div class="highlight-box p-4 mb-4 rounded"> |
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<h3 class="font-medium text-blue-600 mb-2"><i class="fas fa-temperature-low mr-2"></i>Winter Peaks</h3> |
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<p class="text-gray-700">Heating consumption shows clear seasonal patterns with peaks in December-February and lowest usage in June-August.</p> |
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</div> |
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<div class="highlight-box p-4 rounded"> |
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<h3 class="font-medium text-blue-600 mb-2"><i class="fas fa-exclamation-triangle mr-2"></i>Notable Spikes</h3> |
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<p class="text-gray-700">The Rozsnyay property shows unusually high heating consumption in 2016-2017, reaching up to 10,381 units, significantly higher than other properties.</p> |
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</div> |
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</div> |
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</div> |
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</div> |
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<div id="anomalies" class="tab-content p-6"> |
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<h2 class="text-xl font-semibold mb-4 text-gray-800">Anomaly Detection</h2> |
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<div class="grid grid-cols-1 lg:grid-cols-2 gap-6"> |
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<div> |
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<canvas id="anomalyChart"></canvas> |
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</div> |
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<div> |
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<div class="highlight-box p-4 mb-4 rounded"> |
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<h3 class="font-medium text-blue-600 mb-2"><i class="fas fa-search mr-2"></i>Detected Anomalies</h3> |
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<ul class="list-disc pl-5 text-gray-700 space-y-2"> |
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<li>Rozsnyay May 2018: Extreme electricity reading (41,366 units)</li> |
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<li>Páva October 2018: Negative heating value (-12,981 units)</li> |
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<li>NagyLajos April 2012: Missing utility data for most categories</li> |
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<li>Rozsnyay April 2018: All meters reset to 0.00</li> |
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</ul> |
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</div> |
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<div class="highlight-box p-4 rounded"> |
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<h3 class="font-medium text-blue-600 mb-2"><i class="fas fa-lightbulb mr-2"></i>Recommendations</h3> |
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<p class="text-gray-700">Verify meter readings during anomaly periods and investigate potential data entry errors. Consider implementing automated anomaly detection for future data collection.</p> |
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</div> |
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</div> |
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</div> |
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</div> |
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</div> |
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<div class="bg-white rounded-lg shadow-md p-6 mb-8"> |
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<h2 class="text-xl font-semibold mb-4 text-gray-800">Comparative Analysis by Property</h2> |
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<div class="overflow-x-auto"> |
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<table class="min-w-full divide-y divide-gray-200"> |
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<thead class="bg-gray-50"> |
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<tr> |
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<th class="px-6 py-3 text-left text-xs font-medium text-gray-500 uppercase tracking-wider">Property</th> |
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<th class="px-6 py-3 text-left text-xs font-medium text-gray-500 uppercase tracking-wider">Avg Water (M)</th> |
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<th class="px-6 py-3 text-left text-xs font-medium text-gray-500 uppercase tracking-wider">Avg Water (H)</th> |
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<th class="px-6 py-3 text-left text-xs font-medium text-gray-500 uppercase tracking-wider">Avg Electricity</th> |
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<th class="px-6 py-3 text-left text-xs font-medium text-gray-500 uppercase tracking-wider">Avg Heating</th> |
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<th class="px-6 py-3 text-left text-xs font-medium text-gray-500 uppercase tracking-wider">Notes</th> |
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</tr> |
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</thead> |
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<tbody class="bg-white divide-y divide-gray-200"> |
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<tr> |
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<td class="px-6 py-4 whitespace-nowrap text-sm font-medium text-gray-900">NagyLajos</td> |
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<td class="px-6 py-4 whitespace-nowrap text-sm text-gray-500">72.45</td> |
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<td class="px-6 py-4 whitespace-nowrap text-sm text-gray-500">80.32</td> |
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<td class="px-6 py-4 whitespace-nowrap text-sm text-gray-500">14,123</td> |
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<td class="px-6 py-4 whitespace-nowrap text-sm text-gray-500">2,144</td> |
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<td class="px-6 py-4 whitespace-nowrap text-sm text-gray-500">Most consistent usage</td> |
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</tr> |
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<tr> |
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<td class="px-6 py-4 whitespace-nowrap text-sm font-medium text-gray-900">Rozsnyay</td> |
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<td class="px-6 py-4 whitespace-nowrap text-sm text-gray-500">182.34</td> |
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<td class="px-6 py-4 whitespace-nowrap text-sm text-gray-500">236.47</td> |
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<td class="px-6 py-4 whitespace-nowrap text-sm text-gray-500">7,611</td> |
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<td class="px-6 py-4 whitespace-nowrap text-sm text-gray-500">3,898</td> |
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<td class="px-6 py-4 whitespace-nowrap text-sm text-gray-500">Highest water usage</td> |
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</tr> |
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<tr> |
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<td class="px-6 py-4 whitespace-nowrap text-sm font-medium text-gray-900">Páva</td> |
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<td class="px-6 py-4 whitespace-nowrap text-sm text-gray-500">159.22</td> |
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<td class="px-6 py-4 whitespace-nowrap text-sm text-gray-500">162.45</td> |
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<td class="px-6 py-4 whitespace-nowrap text-sm text-gray-500">44,527</td> |
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<td class="px-6 py-4 whitespace-nowrap text-sm text-gray-500">4,100</td> |
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<td class="px-6 py-4 whitespace-nowrap text-sm text-gray-500">Most anomalies</td> |
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</tr> |
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</tbody> |
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</table> |
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</div> |
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</div> |
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<div class="bg-white rounded-lg shadow-md p-6"> |
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<h2 class="text-xl font-semibold mb-4 text-gray-800">Key Insights</h2> |
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<div class="grid grid-cols-1 md:grid-cols-2 gap-6"> |
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<div class="highlight-box p-6 rounded-lg"> |
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<h3 class="text-lg font-medium text-blue-600 mb-3"><i class="fas fa-chart-pie mr-2"></i>Consumption Patterns</h3> |
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<ul class="list-disc pl-5 text-gray-700 space-y-2"> |
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<li>Water consumption shows the most consistent upward trend across all properties</li> |
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<li>Electricity usage has the most variability with significant seasonal patterns</li> |
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<li>Heating costs are predictably highest in winter months but show property-specific patterns</li> |
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</ul> |
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</div> |
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<div class="highlight-box p-6 rounded-lg"> |
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<h3 class="text-lg font-medium text-blue-600 mb-3"><i class="fas fa-exclamation-circle mr-2"></i>Data Quality Issues</h3> |
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<ul class="list-disc pl-5 text-gray-700 space-y-2"> |
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<li>Several instances of missing data (empty cells in original dataset)</li> |
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<li>Extreme values that may represent meter reading errors</li> |
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<li>Negative values in heating costs that require verification</li> |
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<li>Meter resets (sudden drops to zero) that need investigation</li> |
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</ul> |
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</div> |
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</div> |
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</div> |
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</div> |
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<script> |
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function openTab(evt, tabName) { |
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var i, tabcontent, tabbuttons; |
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tabcontent = document.getElementsByClassName("tab-content"); |
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for (i = 0; i < tabcontent.length; i++) { |
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tabcontent[i].classList.remove("active"); |
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} |
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tabbuttons = document.getElementsByClassName("tab-button"); |
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for (i = 0; i < tabbuttons.length; i++) { |
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tabbuttons[i].classList.remove("active"); |
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} |
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document.getElementById(tabName).classList.add("active"); |
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evt.currentTarget.classList.add("active"); |
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} |
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const waterCtx = document.getElementById('waterChart').getContext('2d'); |
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const waterChart = new Chart(waterCtx, { |
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type: 'line', |
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data: { |
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labels: ['2012', '2013', '2014', '2015', '2016', '2017', '2018', '2019', '2020', '2021', '2022', '2023', '2024'], |
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datasets: [ |
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{ |
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label: 'NagyLajos (M)', |
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data: [55, 96.7, null, null, null, null, null, null, null, null, null, null, null], |
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borderColor: '#3b82f6', |
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backgroundColor: 'rgba(59, 130, 246, 0.1)', |
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tension: 0.3, |
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fill: true |
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}, |
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{ |
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label: 'Rozsnyay (M)', |
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data: [null, null, null, null, 158.11, 197.19, 205.49, null, null, null, null, null, null], |
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borderColor: '#10b981', |
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backgroundColor: 'rgba(16, 185, 129, 0.1)', |
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tension: 0.3, |
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fill: true |
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}, |
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{ |
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label: 'Páva (M)', |
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data: [null, null, null, null, null, null, null, 3.65, 111.92, 168.11, 214.17, 261.17, 309.29], |
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borderColor: '#f59e0b', |
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backgroundColor: 'rgba(245, 158, 11, 0.1)', |
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tension: 0.3, |
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fill: true |
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} |
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] |
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}, |
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options: { |
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responsive: true, |
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plugins: { |
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title: { |
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display: true, |
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text: 'Water Meter (M) Consumption Over Time', |
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font: { |
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size: 16 |
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} |
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}, |
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tooltip: { |
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mode: 'index', |
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intersect: false |
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} |
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}, |
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scales: { |
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y: { |
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beginAtZero: true, |
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title: { |
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display: true, |
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text: 'Consumption (units)' |
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} |
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} |
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} |
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} |
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}); |
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const electricityCtx = document.getElementById('electricityChart').getContext('2d'); |
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|
const electricityChart = new Chart(electricityCtx, { |
|
|
type: 'line', |
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|
data: { |
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labels: ['2012', '2013', '2014', '2015', '2016', '2017', '2018', '2019', '2020', '2021', '2022', '2023', '2024'], |
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datasets: [ |
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{ |
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label: 'NagyLajos', |
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data: [12937, 15423, null, null, null, null, null, null, null, null, null, null, null], |
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borderColor: '#3b82f6', |
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backgroundColor: 'rgba(59, 130, 246, 0.1)', |
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tension: 0.3, |
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fill: true |
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}, |
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{ |
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label: 'Rozsnyay', |
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data: [null, null, null, null, 6110, 8624, 9074, null, null, null, null, null, null], |
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borderColor: '#10b981', |
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backgroundColor: 'rgba(16, 185, 129, 0.1)', |
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tension: 0.3, |
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fill: true, |
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pointBackgroundColor: function(context) { |
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return context.raw > 40000 ? '#ef4444' : '#10b981'; |
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}, |
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pointRadius: function(context) { |
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return context.raw > 40000 ? 7 : 3; |
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} |
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}, |
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{ |
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label: 'Páva', |
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data: [null, null, null, null, null, null, null, 41464, 44527, 45588, 47217, 48567, 50302], |
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borderColor: '#f59e0b', |
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backgroundColor: 'rgba(245, 158, 11, 0.1)', |
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tension: 0.3, |
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fill: true |
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} |
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] |
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}, |
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options: { |
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responsive: true, |
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plugins: { |
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title: { |
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display: true, |
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text: 'Electricity Consumption Over Time', |
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font: { |
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size: 16 |
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} |
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}, |
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tooltip: { |
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mode: 'index', |
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intersect: false |
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}, |
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annotation: { |
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annotations: { |
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anomaly: { |
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type: 'box', |
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xMin: '2018', |
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xMax: '2018', |
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yMin: 0, |
|
|
yMax: 45000, |
|
|
backgroundColor: 'rgba(239, 68, 68, 0.1)', |
|
|
borderColor: 'rgba(239, 68, 68, 0.5)', |
|
|
borderWidth: 1, |
|
|
label: { |
|
|
content: 'Anomaly', |
|
|
enabled: true, |
|
|
position: 'top' |
|
|
} |
|
|
} |
|
|
} |
|
|
} |
|
|
}, |
|
|
scales: { |
|
|
y: { |
|
|
beginAtZero: true, |
|
|
title: { |
|
|
display: true, |
|
|
text: 'Consumption (units)' |
|
|
} |
|
|
} |
|
|
} |
|
|
} |
|
|
}); |
|
|
|
|
|
|
|
|
const heatingCtx = document.getElementById('heatingChart').getContext('2d'); |
|
|
const heatingChart = new Chart(heatingCtx, { |
|
|
type: 'bar', |
|
|
data: { |
|
|
labels: ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'], |
|
|
datasets: [ |
|
|
{ |
|
|
label: 'NagyLajos (2013)', |
|
|
data: [2009, 2276, 2357, 2440, 2454, 2454, 2454, 2454, 2454, 2454, 2454, 2508], |
|
|
backgroundColor: 'rgba(59, 130, 246, 0.7)' |
|
|
}, |
|
|
{ |
|
|
label: 'Rozsnyay (2017)', |
|
|
data: [9839, 10204, 10307, 10307, 10307, 10307, 10307, 10307, 10307, 10307, 10307, 10337], |
|
|
backgroundColor: 'rgba(16, 185, 129, 0.7)' |
|
|
}, |
|
|
{ |
|
|
label: 'Páva (2023)', |
|
|
data: [437.939, 438.538, 439.38, 439.741, 439.741, 439.741, 439.741, 439.741, 439.741, 439.741, 439.741, 440.181], |
|
|
backgroundColor: 'rgba(245, 158, 11, 0.7)' |
|
|
} |
|
|
] |
|
|
}, |
|
|
options: { |
|
|
responsive: true, |
|
|
plugins: { |
|
|
title: { |
|
|
display: true, |
|
|
text: 'Monthly Heating Consumption Comparison', |
|
|
font: { |
|
|
size: 16 |
|
|
} |
|
|
}, |
|
|
tooltip: { |
|
|
mode: 'index', |
|
|
intersect: false |
|
|
} |
|
|
}, |
|
|
scales: { |
|
|
y: { |
|
|
beginAtZero: true, |
|
|
title: { |
|
|
display: true, |
|
|
text: 'Consumption (units)' |
|
|
} |
|
|
} |
|
|
} |
|
|
} |
|
|
}); |
|
|
|
|
|
|
|
|
const anomalyCtx = document.getElementById('anomalyChart').getContext('2d'); |
|
|
const anomalyChart = new Chart(anomalyCtx, { |
|
|
type: 'scatter', |
|
|
data: { |
|
|
datasets: [ |
|
|
{ |
|
|
label: 'Normal Readings', |
|
|
data: [ |
|
|
{x: 2012, y: 12937}, |
|
|
{x: 2012, y: 13050}, |
|
|
{x: 2013, y: 14496}, |
|
|
{x: 2016, y: 6343}, |
|
|
{x: 2017, y: 7213}, |
|
|
{x: 2020, y: 44227}, |
|
|
{x: 2021, y: 45246}, |
|
|
{x: 2022, y: 47217} |
|
|
], |
|
|
backgroundColor: '#3b82f6' |
|
|
}, |
|
|
{ |
|
|
label: 'Anomalies', |
|
|
data: [ |
|
|
{x: 2018, y: 41366}, |
|
|
{x: 2018, y: 0}, |
|
|
{x: 2018, y: 0}, |
|
|
{x: 2018, y: 0}, |
|
|
{x: 2018, y: 0}, |
|
|
{x: 2018, y: 0} |
|
|
], |
|
|
backgroundColor: '#ef4444', |
|
|
pointRadius: 8 |
|
|
} |
|
|
] |
|
|
}, |
|
|
options: { |
|
|
responsive: true, |
|
|
plugins: { |
|
|
title: { |
|
|
display: true, |
|
|
text: 'Electricity Consumption Anomalies', |
|
|
font: { |
|
|
size: 16 |
|
|
} |
|
|
}, |
|
|
tooltip: { |
|
|
callbacks: { |
|
|
label: function(context) { |
|
|
let label = context.dataset.label || ''; |
|
|
if (label) { |
|
|
label += ': '; |
|
|
} |
|
|
if (context.parsed.y !== null) { |
|
|
label += context.parsed.y.toLocaleString() + ' units'; |
|
|
} |
|
|
return label; |
|
|
} |
|
|
} |
|
|
} |
|
|
}, |
|
|
scales: { |
|
|
y: { |
|
|
title: { |
|
|
display: true, |
|
|
text: 'Consumption (units)' |
|
|
} |
|
|
}, |
|
|
x: { |
|
|
title: { |
|
|
display: true, |
|
|
text: 'Year' |
|
|
} |
|
|
} |
|
|
} |
|
|
} |
|
|
}); |
|
|
</script> |
|
|
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</html> |
