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Overview

The SG Cars Trends API provides access to structured data about Singapore’s automotive market. This guide explains the core data models and their relationships.

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Core Data Models

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Car Registration Data

Car registration data represents monthly vehicle registration statistics by manufacturer, fuel type, and vehicle type.

{
  "month": "2024-01",
  "make": "Toyota",
  "fuel_type": "Petrol",
  "vehicle_type": "Passenger Cars",
  "number": 245
}

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Fields

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Fuel Types

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Vehicle Types

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COE Bidding Data

Certificate of Entitlement (COE) bidding data represents the results of Singapore’s vehicle quota auction system.

{
  "month": "2024-01",
  "bidding_no": 1,
  "vehicle_class": "Category A",
  "quota": 1000,
  "bids_success": 950,
  "bids_received": 1200,
  "premium": 85000
}

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Fields

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COE Categories

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COE PQP Data

Prevailing Quota Premium (PQP) data represents the benchmark COE prices used for vehicle valuation.

{
  "month": "2024-01",
  "vehicle_class": "Category A",
  "pqp": 87500
}

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Fields

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Months Data

Available data months for different data types.

{
  "month": "2024-01",
  "has_cars": true,
  "has_coe": true
}

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Fields

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Makes Data

Vehicle manufacturers/brands available in the dataset.

{
  "make": "Toyota",
  "total_registrations": 2450,
  "months_active": 12
}

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Fields

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Data Relationships

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Hierarchical Structure

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Data Aggregation

The API provides various aggregation levels:

1. Individual Records: Raw data points
2. Monthly Summaries: Aggregated by month
3. Make Summaries: Aggregated by manufacturer
4. Fuel Type Summaries: Aggregated by fuel type
5. Vehicle Type Summaries: Aggregated by vehicle type

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Data Quality and Updates

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Update Frequency

• Car Registration Data: Monthly (typically mid-month)
• COE Bidding Data: Bi-monthly (1st and 3rd Wednesday)
• COE PQP Data: Monthly (after COE bidding)

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Data Source

All data is sourced from Singapore’s Land Transport Authority (LTA) DataMall, ensuring accuracy and official validation.

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Data Validation

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Usage Patterns

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Common Queries

1. Monthly Trends: Get all data for a specific month
2. Make Comparison: Compare registrations across manufacturers
3. Fuel Type Analysis: Track adoption of different fuel types
4. COE Market Analysis: Monitor COE premium trends
5. Year-over-Year Growth: Compare same months across years

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Performance Considerations

• Indexing: Data is indexed on month, make, and fuel_type
• Caching: Frequently accessed data is cached with Redis
• Pagination: Large datasets are paginated for optimal performance

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Next Steps