electricsheepafrica/nigerian_transport_and_logistics_fuel_consumption

# Nigeria Transport & Logistics – Fuel Consumption

Trip-level fuel use, distance, payload, speed, elevation gain, and fuel cost by type.

- **[category]** Vehicle & Fleet Data
- **[rows]** ~200,000
- **[formats]** CSV + Parquet (snappy)
- **[geography]** Nigeria (major cities, corridors, ports, airports)

## Schema

| column | dtype |

|---|---| | trip_id | object | | vehicle_id | object | | fleet | object | | vehicle_type | object | | fuel_type | object | | start_time | object | | end_time | object | | distance_km | float64 | | avg_speed_kmh | float64 | | payload_kg | float64 | | elev_gain_m | float64 | | fuel_l | float64 | | l_per_100km | float64 | | cost_ngn | float64 | | fuel_price_ngn_l | float64 | | station_id | object |

## Usage

```python
import pandas as pd
df = pd.read_parquet('data/nigerian_transport_and_logistics_fuel_consumption/nigerian_transport_and_logistics_fuel_consumption.parquet')
df.head()
```

```python
from datasets import load_dataset
ds = load_dataset('electricsheepafrica/nigerian_transport_and_logistics_fuel_consumption')
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