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Ship Performance Clustering Insights
Data Science and Analytics
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About
Operational data representing key metrics for various ship types, synthetically generated to be realistic. This data is designed for professionals and enthusiasts in maritime data analytics and machine learning to explore clustering, prediction, and optimisation challenges within the shipping industry. The purpose is to offer a platform for uncovering trends in ship performance, identifying patterns, and applying data-driven methods to solve real-world maritime problems, ultimately aiming to improve decision-making, enhance fuel efficiency, and reduce environmental impact.
Columns
- Date: The timestamp of the data entry.
- Ship_Type: The type of vessel (e.g., Tanker, Container Ship, Fish Carrier, Bulk Carrier).
- Route_Type: The classification of the shipping route (e.g., Short-haul, Long-haul, Transoceanic).
- Engine_Type: The type of propulsion engine used by the ship (e.g., Diesel, Heavy Fuel Oil).
- Maintenance_Status: The current maintenance condition of the vessel (e.g., Fair, Critical, Good).
- Speed_Over_Ground_knots: The average speed of the vessel over water, measured in knots.
- Engine_Power_kW: The engine's power output, measured in kilowatts.
- Distance_Traveled_nm: The total distance covered by the vessel, measured in nautical miles.
- Draft_meters: The draft of the vessel, measured in metres.
- Weather_Condition: The prevailing weather conditions during a voyage (e.g., Calm, Moderate, Rough).
- Cargo_Weight_tons: The weight of the cargo, measured in tons.
- Operational_Cost_USD: The total operational cost for each voyage, in US Dollars.
- Revenue_per_Voyage_USD: The revenue generated from each voyage, in US Dollars.
- Turnaround_Time_hours: The time taken for the vessel to turnaround, measured in hours.
- Efficiency_nm_per_kWh: A measure of energy efficiency, calculated as nautical miles per kilowatt-hour.
- Seasonal_Impact_Score: A score indicating the impact of seasonal factors.
- Weekly_Voyage_Count: The number of voyages completed in a week.
- Average_Load_Percentage: The average cargo load as a percentage of capacity.
Distribution
The dataset is provided in a CSV format (
Ship_Performance_Dataset.csv) with a size of 726.24 kB. It contains 2,736 rows and 18 columns, with features categorised as both numerical and categorical.Usage
- Exploratory Data Analysis (EDA): To identify trends and patterns in ship performance and operational efficiency.
- Clustering Analysis: To segment ships into groups based on performance metrics and other attributes.
- Optimisation: To analyse the trade-offs between operational costs and revenue to enhance profitability.
Coverage
The dataset is synthetically generated to represent operations in the Gulf of Guinea. The time range for the data entries spans from 4 June 2023 to 30 June 2024.
License
CC BY-SA 4.0
Who Can Use It
- Maritime Data Analysts: For exploring trends and identifying key performance indicators.
- Machine Learning Practitioners: For building clustering and prediction models to segment vessels or forecast performance.
- Maritime Industry Professionals: For understanding cost-revenue dynamics and optimising operational strategies.
Dataset Name Suggestions
- Vessel Performance Analytics Dataset
- Maritime Operations & Efficiency Data
- Ship Performance Clustering Insights
- Synthetic Maritime Voyage Metrics
Attributes
Original Data Source: Ship Performance Clustering Insights
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