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logistics-disruption-archive/LICENSE

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+CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
+
+The person who associated a work with this deed has dedicated the work to the
+public domain by waiving all of his or her rights to the work worldwide under
+copyright law, including all related and neighboring rights, to the extent
+allowed by law.
+
+You can copy, modify, distribute and perform the work, even for commercial
+purposes, all without asking permission.
+
+For more information: https://creativecommons.org/publicdomain/zero/1.0/

logistics-disruption-archive/README.md

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+---
+license: cc0-1.0
+task_categories:
+  - tabular-classification
+size_categories:
+  - 1K<n<10K
+---
+
+# Logistics Disruption Archive
+
+Supply chain disruption records for logistics research.
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("scm-resilience-data/logistics-disruption-archive")
+df = dataset["train"].to_pandas()
+```
+
+Or use the provided loader:
+
+```python
+from loader import load_data
+
+df = load_data()
+```
+
+## Schema
+
+### Metrics
+
+| Column | Type | Description |
+|--------|------|-------------|
+| supplier_diversity | float | Normalized metric |
+| delivery_consistency | float | Normalized metric |
+| inventory_buffer | float | Normalized metric |
+| chain_performance | float | Normalized metric |
+
+### Categorical Variables
+
+| Column | Type | Description |
+|--------|------|-------------|
+| sector | string | Categorical variable |
+| disruption_type | string | Categorical variable |
+
+## Statistics
+
+- **Rows**: 1000
+- **Columns**: 6
+
+## License
+
+CC0 1.0 Universal (Public Domain)
+
+---
+
+*Note: One thread breaks, the whole tapestry unravels.*

logistics-disruption-archive/data/train.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e31389ce577e30a4b649f81824141e998d9c2ba080f10eef0beedf56b7caf8b4
+size 41825

logistics-disruption-archive/loader.py

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+"""
+Data loader for logistics-disruption-archive
+"""
+
+import pandas as pd
+from pathlib import Path
+
+
+def load_data(split: str = "train") -> pd.DataFrame:
+    """
+    Load the dataset.
+    
+    Args:
+        split: Data split ("train" by default)
+    
+    Returns:
+        DataFrame with the loaded data
+    """
+    data_dir = Path(__file__).parent / "data"
+    parquet_path = data_dir / f"{split}.parquet"
+    
+    if not parquet_path.exists():
+        raise FileNotFoundError(f"Data file not found: {parquet_path}")
+    
+    return pd.read_parquet(parquet_path)
+
+
+def get_columns() -> list:
+    """Return list of column names."""
+    return ['supplier_diversity', 'delivery_consistency', 'inventory_buffer', 'chain_performance']
+
+
+if __name__ == "__main__":
+    df = load_data()
+    print(f"Loaded {len(df)} rows")
+    print(df.head())

logistics-disruption-archive/schema.json

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+{
+  "schema_version": "1.0",
+  "columns": {
+    "supplier_diversity": {
+      "type": "float",
+      "range": [
+        0.01183415048069798,
+        0.9803929813534208
+      ]
+    },
+    "delivery_consistency": {
+      "type": "float",
+      "range": [
+        0.0047510509637126875,
+        0.9570963417027043
+      ]
+    },
+    "inventory_buffer": {
+      "type": "float",
+      "range": [
+        0.08795114827260643,
+        0.9806550494296679
+      ]
+    },
+    "chain_performance": {
+      "type": "float",
+      "range": [
+        0.0,
+        0.6020969184712575
+      ]
+    },
+    "sector": {
+      "type": "string",
+      "values": [
+        "pharma",
+        "automotive",
+        "food",
+        "textiles",
+        "electronics"
+      ]
+    },
+    "disruption_type": {
+      "type": "string",
+      "values": [
+        "cyber",
+        "none",
+        "natural",
+        "pandemic",
+        "geopolitical"
+      ]
+    }
+  },
+  "note": "Normalized metrics for cross-domain analysis"
+}