electricsheepafrica/nigerian_transport_and_logistics_eta_accuracy

# Nigeria Transport & Logistics – ETA Accuracy

Predicted vs actual ETA with minute error and related trip identifiers.

- **[category]** Customer & Service
- **[rows]** ~130,000
- **[formats]** CSV + Parquet (snappy)
- **[geography]** Nigeria (major cities, corridors, ports, airports)

## Schema

| column | dtype |

|---|---| | order_id | object | | route_id | object | | predicted_eta | object | | actual_eta | object | | eta_error_min | int64 |

## Usage

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

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