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Hypothetical Shipping Logistics Data
Data Science and Analytics
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About
This dataset provides details on international shipments processed through a port, containing 260,000 hypothetical items packed for shipment. It includes information such as the product name, its price, weight, length, width, and height, along with the date it was shipped and its destination port. This dataset is designed for educational and research purposes, facilitating activities like data analysis, machine learning model development, container optimisation problems, and data visualisation. It is important to note that this is a simulated dataset, not based on any actual real-world shipments, making its values purely hypothetical. Conclusions drawn from its analysis should be regarded as theoretical and not representative of actual international shipping operations.
Columns
- name: The name of the item being shipped, for example, 'Hiking Boots' or 'Medium Box'.
- price ($): The price of the item in US dollars, ranging from 1.00 to over 1.9 million.
- weight (kg): The weight of the item in kilograms, with values from 0.05 kg up to approximately 25,000 kg.
- length (m): The length of the item in meters, ranging from 0.05 m to 30.00 m.
- width (m): The width of the item in meters, with values from 0.01 m to 6.00 m.
- height (m): The height of the item in meters, from 0.01 m to 5.99 m.
- shipment date: The date when the item arrived at the port for shipment, covering a period from 12th March 2023 to 28th March 2023.
- destination port: The port where the item is destined to be sent, such as the Port of Busan (South Korea) or the Port of Tianjin (China).
Distribution
The dataset is provided as a CSV file named
shipping_data.csv, with a size of 20.44 MB. It comprises 260,000 records, detailing 8 distinct columns. The majority of the columns have 264,000 valid entries, with minimal missing data for 'shipment date' (1%) and 'weight'/'length' (0%).Usage
This dataset is ideal for:
- Educational and research projects in logistics, supply chain management, and data science.
- Data analysis to identify trends and patterns in simulated shipping data.
- Machine learning applications, such as developing predictive models for shipment pricing, weight estimation, or destination forecasting.
- Container loading optimisation studies, given the item dimensions.
- Data visualisation exercises to explore global shipping routes and item characteristics.
Coverage
- Geographic: The dataset covers international shipments with specified destination ports, including major hubs like the Port of Busan (South Korea) and the Port of Tianjin (China).
- Time Range: The shipment dates span from 12th March 2023 to 28th March 2023.
- Demographic: Not applicable, as the dataset focuses on product shipments rather than human populations.
- Notes: This data is entirely hypothetical and does not reflect actual real-world shipping activities or volumes.
License
CC0: Public Domain
Who Can Use It
- Students and Academics: For learning purposes, coursework, and non-commercial research projects related to logistics, data science, and operations management.
- Data Scientists and Analysts: To develop and test algorithms for supply chain forecasting, route optimisation, and inventory management in a simulated environment.
- Educators: As a teaching resource to illustrate concepts in data collection, cleaning, analysis, and visualisation without the need for real-world, sensitive data.
- Software Developers: For building and testing applications that model shipping processes or visualise logistical data.
Dataset Name Suggestions
- Simulated Global Port Shipment Data
- International Maritime Cargo Dataset
- Hypothetical Shipping Logistics Data
- Port Operations Simulation Data
- Global Freight Dimensions Dataset
Attributes
Original Data Source: Hypothetical Shipping Logistics Data
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