electricsheepafrica/africa-world-bank-energy-and-mining-indicators-for-south-sudan

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- development
- energy
- indicators
- ssd
pretty_name: "South Sudan - Energy and Mining"
dataset_info:
splits:
- name: train
num_examples: 307
- name: test
num_examples: 76
---

# South Sudan - Energy and Mining

**Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-energy-and-mining-indicators-for-south-sudan) · **License:** `cc-by` · **Updated:** 2026-03-27

---

## Abstract

Contains data from the World Bank's [data portal](http://data.worldbank.org/). There is also a [consolidated country dataset](https://data.humdata.org/dataset/world-bank-combined-indicators-for-south-sudan) on HDX.

The world economy needs ever-increasing amounts of energy to sustain economic growth, raise living standards, and reduce poverty. But today's trends in energy use are not sustainable. As the world's population grows and economies become more industrialized, nonrenewable energy sources will become scarcer and more costly. Data here on energy production, use, dependency, and efficiency are compiled by the World Bank from the International Energy Agency and the Carbon Dioxide Information Analysis Center.

Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-03-27. Geographic scope: **SSD**.

*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Demographics and population |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 384 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 307 rows |
| **Test split** | 76 rows |
| **Geographic scope** | SSD |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

**Geographic** — `country_name` (South Sudan), `country_iso3` (SSD), `year` (range 1970.0–2024.0).

**Outcome / Measurement** — `value` (range -1055.2268–5320757379.2486).

**Identifier / Metadata** — `indicator_name` (Adjusted savings: mineral depletion (current US$), Access to electricity, urban (% of urban population), Adjusted savings: energy depletion (current US$)), `indicator_code` (NY.ADJ.DMIN.CD, EG.ELC.ACCS.UR.ZS, NY.ADJ.DNGY.CD), `esa_source` (HDX), `esa_processed` (2026-04-10).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-energy-and-mining-indicators-for-south-sudan")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

print(train.shape)
train.head()
```

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `country_name` | object | 0.0% | South Sudan |
| `country_iso3` | object | 0.0% | SSD |
| `year` | int64 | 0.0% | 1970.0 – 2024.0 (mean 2012.2005) |
| `indicator_name` | object | 0.0% | Adjusted savings: mineral depletion (current US$), Access to electricity, urban (% of urban population), Adjusted savings: energy depletion (current US$) |
| `indicator_code` | object | 0.0% | NY.ADJ.DMIN.CD, EG.ELC.ACCS.UR.ZS, NY.ADJ.DNGY.CD |
| `value` | float64 | 0.0% | -1055.2268 – 5320757379.2486 (mean 84750678.3338) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-10 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1970.0 | 2024.0 | 2012.2005 | 2014.0 |
| `value` | -1055.2268 | 5320757379.2486 | 84750678.3338 | 4.2218 |

---

## Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (`N/A`, `null`, `none`, `-`, `unknown`, `no data`, `#N/A`) were unified to `NaN`. The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

---

## Limitations

- Data originates from World Bank Group and has not been independently validated by ESA.
- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/world-bank-energy-and-mining-indicators-for-south-sudan) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_energy_and_mining_indicators_for_south_sudan,
title = {South Sudan - Energy and Mining},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-energy-and-mining-indicators-for-south-sudan},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
```

---

*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*

annotations_creators:
- 无注释
language_creators:
- 现有资源爬取
language:
- 英语
license: CC-BY-4.0
multilinguality:
- 单语言
size_categories:
- 数据量少于1000条
source_datasets:
- 原始数据集
task_categories:
- 表格回归
task_ids: []
tags:
- 非洲
- 人道主义
- HDX（人道主义数据交换平台）
- Electric Sheep Africa
- 发展
- 能源
- 指标
- SSD
pretty_name: "南苏丹——能源与矿业"
dataset_info:
splits:
- name: train
num_examples: 307
- name: test
num_examples: 76

# 南苏丹——能源与矿业

**发布方**：世界银行集团 · **数据源**：[HDX（人道主义数据交换平台）](https://data.humdata.org/dataset/world-bank-energy-and-mining-indicators-for-south-sudan) · **许可证**：`cc-by` · **更新时间**：2026-03-27

---

## 摘要
本数据集包含来自世界银行[数据门户](http://data.worldbank.org/)的相关数据，HDX平台上还发布有一份整合后的国家综合数据集[《南苏丹世界银行综合指标集》](https://data.humdata.org/dataset/world-bank-combined-indicators-for-south-sudan)。

全球经济为维持增长、提升生活水平并减少贫困，需要持续增长的能源供给。但当前的能源使用趋势并不具备可持续性。随着全球人口增长与经济工业化程度加深，不可再生能源将愈发稀缺且成本高企。本数据集收录的能源生产、使用、依赖度与效率相关数据，由世界银行整合自国际能源署与二氧化碳信息分析中心。

本数据集的每一行均代表国家层面的汇总数据。HDX平台上该数据集的最后更新时间为2026-03-27。地理覆盖范围：**SSD（南苏丹ISO 3位国家代码）**。

*本数据集已由[Electric Sheep Africa（电羊非洲团队）](https://huggingface.co/electricsheepafrica)整理为适用于机器学习的Parquet格式。*

---

## 数据集特征

| | |
|---|---|
| **领域** | 人口与人口统计学 |
| **观测单元** | 国家层面汇总数据 |
| **总数据行数** | 384 |
| **列数** | 8列（2个数值型、6个分类型、0个日期时间型） |
| **训练集划分** | 307行 |
| **测试集划分** | 76行 |
| **地理覆盖范围** | SSD（南苏丹） |
| **发布方** | 世界银行集团 |
| **HDX平台最后更新时间** | 2026-03-27 |

---

## 字段说明

**地理类字段**：`country_name`（国家名称：南苏丹）、`country_iso3`（ISO 3位国家代码：SSD）、`year`（年份范围：1970.0–2024.0）。

**结果/测量类字段**：`value`（数值范围：-1055.2268–5320757379.2486）。

**标识符/元数据类字段**：`indicator_name`（指标名称，如：调整后储蓄：矿产消耗（当前美元价）、城市电力接入率（占城市人口百分比）、调整后储蓄：能源消耗（当前美元价））、`indicator_code`（指标代码：NY.ADJ.DMIN.CD、EG.ELC.ACCS.UR.ZS、NY.ADJ.DNGY.CD）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理时间：2026-04-10）。

---

## 快速上手
python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-energy-and-mining-indicators-for-south-sudan")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

print(train.shape)
train.head()

---

## 数据结构
| 列名 | 数据类型 | 空值占比 | 取值范围/示例值 |
|---|---|---|---|
| `country_name` | 对象类型 | 0.0% | 南苏丹 |
| `country_iso3` | 对象类型 | 0.0% | SSD |
| `year` | int64类型 | 0.0% | 1970.0 – 2024.0（均值2012.2005） |
| `indicator_name` | 对象类型 | 0.0% | 调整后储蓄：矿产消耗（当前美元价）、城市电力接入率（占城市人口百分比）、调整后储蓄：能源消耗（当前美元价） |
| `indicator_code` | 对象类型 | 0.0% | NY.ADJ.DMIN.CD、EG.ELC.ACCS.UR.ZS、NY.ADJ.DNGY.CD |
| `value` | float64类型 | 0.0% | -1055.2268 – 5320757379.2486（均值84750678.3338） |
| `esa_source` | 对象类型 | 0.0% | HDX |
| `esa_processed` | 对象类型 | 0.0% | 2026-04-10 |

---

## 数值型字段统计
| 列名 | 最小值 | 最大值 | 均值 | 中位数 |
|---|---|---|---|---|
| `year` | 1970.0 | 2024.0 | 2012.2005 | 2014.0 |
| `value` | -1055.2268 | 5320757379.2486 | 84750678.3338 | 4.2218 |

---

## 数据整理流程
原始数据通过CKAN API从HDX平台下载，并转换为Parquet格式。列名统一转为小写并适配蛇形命名法。常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）均被统一替换为`NaN`。本数据集以固定随机种子（42）按80/20比例划分为训练集与测试集，并以Snappy压缩的Parquet格式存储。

---

## 局限性说明
- 本数据集源自世界银行集团，尚未由Electric Sheep Africa（ESA）进行独立验证。
- 自动化清洗流程无法修正原始数据集中的错报值、定义不一致问题或采样偏差。
- 请查阅[HDX平台原始数据集页面](https://data.humdata.org/dataset/world-bank-energy-and-mining-indicators-for-south-sudan)以获取发布方提供的方法说明与注意事项。

---

## 引用格式
bibtex
@dataset{hdx_africa_world_bank_energy_and_mining_indicators_for_south_sudan,
title = {South Sudan - Energy and Mining},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-energy-and-mining-indicators-for-south-sudan},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

---

*[Electric Sheep Africa（电羊非洲团队）](https://huggingface.co/electricsheepafrica)——非洲机器学习数据集基础设施提供商，总部位于尼日利亚拉各斯。*