Upload dataset nigerian_transport_and_logistics_parking

README.md

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+
+---
+license: gpl
+dataset_name: nigerian_transport_and_logistics_parking
+pretty_name: Nigeria Transport & Logistics – Parking Data
+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 – Parking Data
+
+    Facility capacity/occupancy over time with violations per timestamp.
+
+    - **[category]** Traffic & Mobility Systems
+    - **[rows]** ~120,000
+    - **[formats]** CSV + Parquet (snappy)
+    - **[geography]** Nigeria (major cities, corridors, ports, airports)
+
+    ## Schema
+
+    | column | dtype |
+|---|---|
+| facility_id | object |
+| city | object |
+| timestamp | object |
+| capacity | int64 |
+| occupied | int64 |
+| occupancy_pct | float64 |
+| violation_count | int64 |
+
+    ## Usage
+
+    ```python
+    import pandas as pd
+    df = pd.read_parquet('data/nigerian_transport_and_logistics_parking/nigerian_transport_and_logistics_parking.parquet')
+    df.head()
+    ```
+
+    ```python
+    from datasets import load_dataset
+    ds = load_dataset('electricsheepafrica/nigerian_transport_and_logistics_parking')
+    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_parking.parquet

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