Upload dataset nigerian_transport_and_logistics_reverse_logistics

.gitattributes

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README.md

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+
+---
+license: gpl
+dataset_name: nigerian_transport_and_logistics_reverse_logistics
+pretty_name: Nigeria Transport & Logistics – Reverse Logistics
+size_categories: [10K<n<1M]
+task_categories: [time-series-forecasting, tabular-regression, tabular-classification, other]
+tags: [nigeria, transport, logistics, mobility, fleet, supply-chain]
+language: [en]
+created: 2025-10-12
+---
+
+
+    # Nigeria Transport & Logistics – Reverse Logistics
+
+    Return reasons, refunds, reroute costs and restockability per return.
+
+    - **[category]** Logistics & Supply Chain
+    - **[rows]** ~130,000
+    - **[formats]** CSV + Parquet (snappy)
+    - **[geography]** Nigeria (major cities, corridors, ports, airports)
+
+    ## Schema
+
+    | column | dtype |
+|---|---|
+| return_id | object |
+| order_id | object |
+| reason | object |
+| pickup_time | object |
+| refund_ngn | float64 |
+| reroute_cost_ngn | float64 |
+| restockable | bool |
+
+    ## Usage
+
+    ```python
+    import pandas as pd
+    df = pd.read_parquet('data/nigerian_transport_and_logistics_reverse_logistics/nigerian_transport_and_logistics_reverse_logistics.parquet')
+    df.head()
+    ```
+
+    ```python
+    from datasets import load_dataset
+    ds = load_dataset('electricsheepafrica/nigerian_transport_and_logistics_reverse_logistics')
+    ds
+    ```
+
+    ## Notes
+
+    - Nigeria-specific parameters (fleets, roads, traffic, fuel prices)
+    - Time-of-day traffic effects and seasonal impacts where applicable
+    - Physical plausibility checks embedded during generation

nigerian_transport_and_logistics_reverse_logistics.csv

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nigerian_transport_and_logistics_reverse_logistics.parquet

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