electricsheepafrica/nigerian_transport_and_logistics_road_condition

# Nigeria Transport & Logistics – Road Condition

Road segment condition: IRI roughness, potholes, wear and lane markings.

- **[category]** Infrastructure & Environment
- **[rows]** ~140,000
- **[formats]** CSV + Parquet (snappy)
- **[geography]** Nigeria (major cities, corridors, ports, airports)

## Schema

| column | dtype |

|---|---| | timestamp | object | | segment_id | object | | lat | float64 | | lon | float64 | | surface_type | object | | roughness_iri | float64 | | potholes_count | int64 | | wear_level_pct | float64 | | lane_marking_visibility_pct | float64 |

## Usage

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

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