Bwatna/nigerian_electricity_national_access_trends

---
license: mit
task_categories:
- tabular-regression
- tabular-classification
tags:
- nigeria
- electricity
- energy-access
- rural-electrification
- synthetic-data
language:
- en
size_categories:
- n<1K
---

# National Electricity Access Trends

## Dataset Description

Annual electricity access rates for Nigeria from 2018-2023, including total, rural, and urban access percentages with population estimates.

**Rows**: 6
**Columns**: 7
**Period**: 2018-2023 (where applicable)
**License**: MIT

## Data Quality

⭐⭐⭐⭐⭐ Official World Bank data

## Methodology

### Data Generation Process

This dataset is part of a geospatial electrification analysis project that addresses the lack of state-level electricity access data in Nigeria.

**Challenge**: World Bank provides only national-level access rates. No state-by-state breakdown exists.

**Solution**: Geospatial disaggregation model using weighted proxy indicators:

```
State_Access = National_Rate × Adjustment_Factor

Adjustment_Factor = (
35% × Night-time Lights Index +
25% × Grid Proximity Index +
20% × Urban Population Share +
15% × DISCO Performance Index +
5% × Historical Baseline
)
```

**Validation**:
- State averages match national figures (< 0.1% difference)
- Adjustment factors normalized (mean = 1.0)
- Realistic bounds applied (10-98% access range)
- Urban > Rural access (consistent with known patterns)

### Data Sources

- **World Bank API**: National electricity access rates (2018-2023)
- **GADM**: Administrative boundaries (37 states, 775 LGAs)
- **Proxy indicators**: Urbanization rates, DISCO coverage, infrastructure patterns
- **Public reports**: NERC quarterly reports, REA project data

## Data Dictionary

| Column | Type | Description | Example |
|--------|------|-------------|---------|
| `year` | int64 | Year | 2018 |
| `total_access_pct` | float64 | Total Access Pct | 56.5 |
| `rural_access_pct` | float64 | Rural Access Pct | 31.0 |
| `urban_access_pct` | float64 | Urban Access Pct | 81.7 |
| `population_total` | int64 | Population Total | 189991982 |
| `population_electrified` | int64 | Population Electrified | 107345469 |
| `population_unelectrified` | int64 | Population Unelectrified | 82646513 |

## Usage

### Load with Hugging Face Datasets

```python
from datasets import load_dataset

dataset = load_dataset("electricsheepafrica/nigerian_electricity_national_access_trends")
df = dataset['train'].to_pandas()
```

### Load with Pandas

```python
import pandas as pd

# From Parquet (recommended)
df = pd.read_parquet("hf://datasets/electricsheepafrica/nigerian_electricity_national_access_trends/nigerian_electricity_national_access_trends.parquet")

# From CSV
df = pd.read_csv("hf://datasets/electricsheepafrica/nigerian_electricity_national_access_trends/nigerian_electricity_national_access_trends.csv")
```

## Sample Data

```
year total_access_pct rural_access_pct urban_access_pct population_total population_electrified population_unelectrified
2018 56.5 31.0 81.7 189991982 107345469 82646513
2019 55.4 25.5 83.9 194931773 107992202 86939571
2020 55.4 24.6 83.9 200000000 110800000 89200000
```

## Use Cases

- **Policy research**: Identify underserved areas for electrification programs
- **Investment analysis**: Assess market opportunities for off-grid solutions
- **Academic research**: Study determinants of electricity access
- **Methodology validation**: Compare geospatial disaggregation approaches
- **SDG 7 tracking**: Monitor progress toward universal energy access

## Limitations

- **Time period**: Limited to 2018-2023
- **Granularity**: No settlement-level data (requires GRID3 integration)
- **Validation**: Limited by availability of ground-truth data
- **Simplifications**: Actual electrification patterns are more complex

## Citation

```bibtex
@dataset{nigerian_electricity_access_2025,
title = {Nigerian Electricity Access: National Electricity Access Trends},
author = {Electric Sheep Africa},
year = {2025},
publisher = {Hugging Face},
note = {Geospatial disaggregation using proxy indicators},
url = {https://huggingface.co/datasets/electricsheepafrica/nigerian_electricity_national_access_trends}
}
```

## Collection

Part of the **[Nigeria Electricity Access](https://huggingface.co/collections/electricsheepafrica/nigeria-electricity-access)** collection containing 7 datasets on rural-urban electrification.

## Related Datasets

- [Nigeria Oil & Gas Sector](https://huggingface.co/collections/electricsheepafrica/nigeria-oil-and-gas-sector-68ee6b777bb27bea09b3485f)
- [Nigeria Energy & Utilities](https://huggingface.co/collections/electricsheepafrica/nigeria-energy-sector-68ea9a1498287fc5e7c29e1f)

## Methodology Documentation

For detailed methodology, see:
- [PROJECT_PLAN.md](https://github.com/electricsheepafrica/nigerian-datasets/blob/main/Nigerian_Electricity_Access/PROJECT_PLAN.md)
- [RESULTS_SUMMARY.md](https://github.com/electricsheepafrica/nigerian-datasets/blob/main/Nigerian_Electricity_Access/RESULTS_SUMMARY.md)

## Updates

This dataset is versioned. Check the repository for updates and corrections.

## Contact

For questions, corrections, or collaboration:
- **Organization**: Electric Sheep Africa
- **Collection**: [Nigeria Electricity Access](https://huggingface.co/collections/electricsheepafrica/nigeria-electricity-access)

## License

MIT License - Free to use with attribution. Please cite appropriately and acknowledge the synthetic nature of the data.

---
license: MIT许可证
task_categories:
- 表格回归（tabular-regression）
- 表格分类（tabular-classification）
tags:
- 尼日利亚（nigeria）
- 电力（electricity）
- 能源获取（energy-access）
- 农村电气化（rural-electrification）
- 合成数据（synthetic-data）
language:
- 英语（en）
size_categories:
- 样本量小于1000（n<1K）
---

# 全国电力获取趋势

## 数据集描述
本数据集涵盖2018至2023年尼日利亚的年度电力获取率，包含全国、农村及城市的电力获取百分比，并附带人口估算数据。

**数据行数**：6
**数据列数**：7
**时间范围**：2018-2023（适用时）
**许可证**：MIT许可证

## 数据质量
⭐⭐⭐⭐⭐ 源自世界银行（World Bank）的官方数据

## 方法论
### 数据生成流程
本数据集属于一项地理空间电气化分析项目，旨在解决尼日利亚缺乏州级电力获取数据的痛点。

**挑战**：世界银行仅提供全国层面的电力获取率数据，未包含分州的细分统计结果。

**解决方案**：采用加权代理指标的地理空间分解模型：

State_Access = National_Rate × Adjustment_Factor

Adjustment_Factor = (
35% × 夜间灯光指数（Night-time Lights Index） +
25% × 电网邻近指数（Grid Proximity Index） +
20% × 城镇人口占比（Urban Population Share） +
15% × 配电公司绩效指数（DISCO Performance Index） +
5% × 历史基线值（Historical Baseline）
)

**验证结果**：
- 州级平均值与全国数据误差小于0.1%，二者高度吻合
- 调整因子已完成归一化处理，均值为1.0
- 应用符合现实的取值约束，电力获取率区间为10%-98%
- 城市电力获取率高于农村，符合行业已知规律

### 数据来源
- **世界银行API（World Bank API）**：2018-2023年全国电力获取率数据
- **GADM**：行政区划边界数据（涵盖37个州、775个地方政府区域（Local Government Areas, LGA））
- **代理指标**：城市化率、配电公司（Distribution Companies, DISCO）覆盖范围、基础设施格局
- **公开报告**：尼日利亚电力监管委员会（Nigerian Electricity Regulatory Commission, NERC）季度报告、农村电气化局（Rural Electrification Agency, REA）项目数据

## 数据字典
| 列名 | 数据类型 | 描述 | 示例 |
|------|----------|------|------|
| `year` | int64 | 年份 | 2018 |
| `total_access_pct` | float64 | 全国电力获取百分比 | 56.5 |
| `rural_access_pct` | float64 | 农村电力获取百分比 | 31.0 |
| `urban_access_pct` | float64 | 城市电力获取百分比 | 81.7 |
| `population_total` | int64 | 总人口数 | 189991982 |
| `population_electrified` | int64 | 已通电人口数 | 107345469 |
| `population_unelectrified` | int64 | 未通电人口数 | 82646513 |

## 使用方式
### 通过Hugging Face Datasets库加载
python
from datasets import load_dataset

dataset = load_dataset("electricsheepafrica/nigerian_electricity_national_access_trends")
df = dataset['train'].to_pandas()

### 通过Pandas库加载
python
import pandas as pd

# 从Parquet文件加载（推荐方式）
df = pd.read_parquet("hf://datasets/electricsheepafrica/nigerian_electricity_national_access_trends/nigerian_electricity_national_access_trends.parquet")

# 从CSV文件加载
df = pd.read_csv("hf://datasets/electricsheepafrica/nigerian_electricity_national_access_trends/nigerian_electricity_national_access_trends.csv")

## 示例数据
以下为部分数据集示例：

year total_access_pct rural_access_pct urban_access_pct population_total population_electrified population_unelectrified
2018 56.5 31.0 81.7 189991982 107345469 82646513
2019 55.4 25.5 83.9 194931773 107992202 86939571
2020 55.4 24.6 83.9 200000000 110800000 89200000

## 应用场景
- **政策研究**：识别电气化项目的服务盲区，优化资源配置
- **投资分析**：评估离网电力解决方案的市场机遇
- **学术研究**：探究电力获取率的影响因素与演变规律
- **方法论验证**：对比不同地理空间分解模型的效果
- **可持续发展目标7（Sustainable Development Goal 7, SDG 7）跟踪**：监测全球普及能源获取的进展情况

## 局限性
- **时间范围限制**：仅涵盖2018-2023年的数据
- **数据粒度限制**：未包含聚落层面的细分数据，如需该类数据需集成GRID3数据集
- **验证限制**：受实测地面数据的可获得性制约，验证范围有限
- **模型简化**：实际的电气化格局更为复杂，本数据集做了合理简化

## 引用格式
bibtex
@dataset{nigerian_electricity_access_2025,
title = {Nigerian Electricity Access: National Electricity Access Trends},
author = {Electric Sheep Africa},
year = {2025},
publisher = {Hugging Face},
note = {Geospatial disaggregation using proxy indicators},
url = {https://huggingface.co/datasets/electricsheepafrica/nigerian_electricity_national_access_trends}
}

## 数据集归属
本数据集属于**[尼日利亚电力获取](https://huggingface.co/collections/electricsheepafrica/nigeria-electricity-access)** 合集，该合集包含7个关于城乡电气化的相关数据集。

## 相关数据集
- [尼日利亚油气行业](https://huggingface.co/collections/electricsheepafrica/nigeria-oil-and-gas-sector-68ee6b777bb27bea09b3485f)
- [尼日利亚能源与公用事业](https://huggingface.co/collections/electricsheepafrica/nigeria-energy-sector-68ea9a1498287fc5e7c29e1f)

## 方法论文档
如需查看详细方法论，请参阅以下文档：
- [PROJECT_PLAN.md](https://github.com/electricsheepafrica/nigerian-datasets/blob/main/Nigerian_Electricity_Access/PROJECT_PLAN.md)
- [RESULTS_SUMMARY.md](https://github.com/electricsheepafrica/nigerian-datasets/blob/main/Nigerian_Electricity_Access/RESULTS_SUMMARY.md)

## 版本更新
本数据集采用版本化管理，如需获取更新内容与修正信息，请查阅对应代码仓库。

## 联系方式
如有疑问、修正建议或合作意向，请联系：
- **机构**：Electric Sheep Africa
- **所属合集**：[尼日利亚电力获取](https://huggingface.co/collections/electricsheepafrica/nigeria-electricity-access)

## 许可证
MIT许可证，可自由使用但需注明来源。请按规范进行引用，并说明本数据集为合成数据。