---
license: mit
task_categories:
- tabular-regression
- tabular-classification
tags:
- nigeria
- education
- africa
- synthetic-data
- community-socioeconomic
language:
- en
size_categories:
- 100K<n<1M
pretty_name: Nigeria Education - Community Socioeconomic
---

# Nigeria - Community Socioeconomic

## Dataset Description

Regional community-level socioeconomic indicators and demographics.

## Dataset Information

- **Country**: Nigeria
- **Dataset Name**: community_socioeconomic
- **Total Records**: 100,000
- **Total Columns**: 8
- **File Size**: 5.04 MB
- **Format**: Parquet (full data), CSV (sample)
- **Generated**: 2025-10-21T23:15:32.123723

## Schema

| Column | Data Type | Description |
|--------|-----------|-------------|
| `community_id` | object | Community Id |
| `region_id` | object | Region Id |
| `poverty_rate` | float64 | Poverty Rate |
| `unemployment_rate` | float64 | Unemployment Rate |
| `average_income` | float64 | Average Income |
| `infrastructure_score` | float64 | Infrastructure Score |
| `num_health_facilities` | float64 | Num Health Facilities |
| `country` | object | Country |

## Sample Data

The dataset includes a 10,000-row sample in CSV format for quick exploration.

## Data Quality

- **Validation Status**: ✅ Passed
- **Missing Data**: ~2-5% (realistic pattern)
- **Data Type Enforcement**: Strict
- **Cross-Dataset Consistency**: Maintained

## Dependencies

- `regional_education_access`

## Usage Example

### Python (Pandas)
```python
import pandas as pd

# Load full dataset
df = pd.read_parquet('community_socioeconomic_full.parquet')
print(f"Loaded {len(df):,} records")
print(df.head())

# Load sample
df_sample = pd.read_csv('community_socioeconomic_sample.csv')
print(df_sample.describe())
```

### Python (Hugging Face Datasets)
```python
from datasets import load_dataset

# Load from Hugging Face
dataset = load_dataset('nigeria-education-community_socioeconomic')
df = dataset['train'].to_pandas()
```

## Data Generation

This dataset was generated using statistical distributions based on:
- UNICEF education statistics for Nigeria
- World Bank development indicators
- Nigerian Ministry of Education data
- Realistic probability distributions

**Note**: This is synthetic data generated for research and testing purposes.

## Related Datasets

This dataset is part of the **Nigeria Education Datasets Collection** (45 datasets total).

Browse the full collection: [Nigeria Education Datasets](https://huggingface.co/collections/nigeria-education)

## Citation

```bibtex
@dataset{nigeria_community_socioeconomic_2025,
  title={Nigeria Education Dataset: Community Socioeconomic},
  author={[Your Name/Organization]},
  year={2025},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/nigeria-education-community_socioeconomic}
}
```

## License

[Specify your license]

## Contact

[Your contact information]

---

**Part of**: Nigeria Education Datasets Collection  
**Total Datasets**: 45  
**Country**: Nigeria 🇳🇬