README.md

metadata

license: mit
language:
  - en
tags:
  - shipping
  - logistic
  - analytics

Shipping Events EU Dataset

Overview

This dataset contains simulated yet realistic shipment tracking records from various European locations. It reflects common logistics patterns, including parcel movements, delivery statuses, geographic attributes, carriers, delivery attempts, region types, transit performance, and service-level indicators. It is designed to be suitable for machine learning, analytics, research, and operational benchmarking. The dataset structure is aligned with real-world logistics data models and includes temporal, geographic, categorical, and status event features.

Each row represents a shipment with key delivery and transit attributes.

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Key Features

Column Group	Description
Order Information	Shipment ID, customer reference, carrier, service type
Location Details	Origin, destination, country, coordinates, region type
Time Attributes	Creation date, transit timestamps, SLA windows
Status Events	Delivery status text, codes, exception flags
Performance Fields	Time in transit, attempts, cost, distance, delays

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Example Columns

• order_id
• carrier
• service_type
• dest_city, dest_country
• transit_time_hours
• has_exception_flag
• route_distance_km
• shipping_cost
• last_status_message

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Usage

Load with Pandas

from datasets import load_dataset

ds = load_dataset("happyhackingspace/shipping-events-eu", split="train")
df = ds.to_pandas()
df.head()

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Notes

• Dataset is synthetic but modeled after realistic logistics structures.
• Includes occasional missing values, minor inconsistencies, and noisy entries to mimic real operational data.
• No personal or sensitive information is included.

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License

This dataset is free to use for research, analysis, and educational purposes.

For feedback or contributions, please use the repository discussion page.