electricsheepafrica/africa-world-bank-energy-and-mining-indicators-for-equatorial-guinea

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- development
- energy
- indicators
- gnq
pretty_name: "Equatorial Guinea - Energy and Mining"
dataset_info:
splits:
- name: train
num_examples: 877
- name: test
num_examples: 219
---

# Equatorial Guinea - Energy and Mining

**Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-energy-and-mining-indicators-for-equatorial-guinea) · **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-equatorial-guinea) 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: **GNQ**.

*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)** | 1,097 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 877 rows |
| **Test split** | 219 rows |
| **Geographic scope** | GNQ |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

**Geographic** — `country_name` (Equatorial Guinea), `country_iso3` (GNQ), `year` (range 1970.0–2024.0).

**Outcome / Measurement** — `value` (range -361610000.0–7274410650.219).

**Identifier / Metadata** — `indicator_name` (Adjusted savings: mineral depletion (current US$), Adjusted savings: mineral depletion (% of GNI), Mineral rents (% of GDP)), `indicator_code` (NY.ADJ.DMIN.CD, NY.ADJ.DMIN.GN.ZS, NY.GDP.MINR.RT.ZS), `esa_source` (HDX), `esa_processed` (2026-04-17).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-energy-and-mining-indicators-for-equatorial-guinea")
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% | Equatorial Guinea |
| `country_iso3` | object | 0.0% | GNQ |
| `year` | int64 | 0.0% | 1970.0 – 2024.0 (mean 2003.8696) |
| `indicator_name` | object | 0.0% | Adjusted savings: mineral depletion (current US$), Adjusted savings: mineral depletion (% of GNI), Mineral rents (% of GDP) |
| `indicator_code` | object | 0.0% | NY.ADJ.DMIN.CD, NY.ADJ.DMIN.GN.ZS, NY.GDP.MINR.RT.ZS |
| `value` | float64 | 0.0% | -361610000.0 – 7274410650.219 (mean 56562829.3083) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-17 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1970.0 | 2024.0 | 2003.8696 | 2006.0 |
| `value` | -361610000.0 | 7274410650.219 | 56562829.3083 | 8.0103 |

---

## 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-equatorial-guinea) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_energy_and_mining_indicators_for_equatorial_guinea,
title = {Equatorial Guinea - Energy and Mining},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-energy-and-mining-indicators-for-equatorial-guinea},
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:
- 公开数据源获取
language:
- 英语
license: CC BY 4.0
multilinguality:
- 单语言
size_categories:
- 1000 < 样本量 < 10000
source_datasets:
- 原始数据集
task_categories:
- 表格回归
task_ids: []
tags:
- 非洲
- 人道主义
- 人类数据交换平台（Humanitarian Data Exchange，HDX）
- Electric Sheep Africa
- 发展
- 能源
- 指标
- GNQ
pretty_name: "赤道几内亚——能源与矿业"
dataset_info:
splits:
- name: 训练集
num_examples: 877
- name: 测试集
num_examples: 219

# 赤道几内亚——能源与矿业

**发布方:** 世界银行集团 · **来源:** [人类数据交换平台（Humanitarian Data Exchange，HDX）](https://data.humdata.org/dataset/world-bank-energy-and-mining-indicators-for-equatorial-guinea) · **许可协议:** `CC BY` · **最后更新:** 2026-03-27

---

## 摘要

本数据集包含源自世界银行[数据门户（data.worldbank.org）](http://data.worldbank.org/)的数据。人类数据交换平台（HDX）上还提供了[赤道几内亚综合国家数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-equatorial-guinea)。

世界经济需要持续增长的能源供给以维持经济增长、提升生活水平并减少贫困。但当前的能源使用趋势不具备可持续性。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昂。本数据集收录的能源生产、使用、依赖度与效率相关数据，由世界银行基于国际能源署与二氧化碳信息分析中心的资料汇编而成。

本数据集每一行代表国家层面的汇总数据。该数据集在HDX平台的最后更新时间为2026-03-27。地理覆盖范围：**GNQ**。本数据集已由[Electric Sheep Africa](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 |
| **观测单元** | 国家层面汇总数据 |
| **总样本量** | 1097条 |
| **列数** | 8列（2个数值型、6个分类型、0个日期时间型） |
| **训练集样本量** | 877条 |
| **测试集样本量** | 219条 |
| **地理覆盖范围** | GNQ |
| **发布方** | 世界银行集团 |
| **HDX平台最后更新时间** | 2026-03-27 |

---

## 变量说明

**地理类** — `country_name`（国家名称：赤道几内亚）、`country_iso3`（国家ISO3代码：GNQ）、`year`（年份范围：1970.0–2024.0）。

**结果/测量类** — `value`（数值范围：-361610000.0–7274410650.219）。

**标识符/元数据类** — `indicator_name`（调整后的储蓄：矿产消耗（现价美元）、调整后的储蓄：矿产消耗（占国民总收入百分比）、矿产租金（占GDP百分比）），`indicator_code`（NY.ADJ.DMIN.CD、NY.ADJ.DMIN.GN.ZS、NY.GDP.MINR.RT.ZS），`esa_source`（数据来源：HDX），`esa_processed`（数据处理时间：2026-04-17）。

---

## 快速上手

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-energy-and-mining-indicators-for-equatorial-guinea")
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` | 字符型 | 0.0% | 赤道几内亚 |
| `country_iso3` | 字符型 | 0.0% | GNQ |
| `year` | 64位整型 | 0.0% | 1970.0 – 2024.0（均值：2003.8696） |
| `indicator_name` | 字符型 | 0.0% | 调整后的储蓄：矿产消耗（现价美元）、调整后的储蓄：矿产消耗（占国民总收入百分比）、矿产租金（占GDP百分比） |
| `indicator_code` | 字符型 | 0.0% | NY.ADJ.DMIN.CD、NY.ADJ.DMIN.GN.ZS、NY.GDP.MINR.RT.ZS |
| `value` | 64位浮点型 | 0.0% | -361610000.0 – 7274410650.219（均值：56562829.3083） |
| `esa_source` | 字符型 | 0.0% | HDX |
| `esa_processed` | 字符型 | 0.0% | 2026-04-17 |

---

## 数值型变量统计摘要

| 列名 | 最小值 | 最大值 | 均值 | 中位数 |
|---|---|---|---|---|
| `year` | 1970.0 | 2024.0 | 2003.8696 | 2006.0 |
| `value` | -361610000.0 | 7274410650.219 | 56562829.3083 | 8.0103 |

---

## 数据整理

原始数据通过CKAN API从HDX平台下载并转换为Parquet格式。列名统一转换为小写并标准化为蛇形命名法。常见的缺失值标记（`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压缩格式的Parquet文件保存。

---

## 局限性

- 数据源自世界银行集团，未由Electric Sheep Africa进行独立验证。
- 自动化清洗无法修正原始数据收集中的错报值、定义不一致或抽样偏差问题。
- 请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/world-bank-energy-and-mining-indicators-for-equatorial-guinea)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_equatorial_guinea,
title = {Equatorial Guinea - Energy and Mining},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-energy-and-mining-indicators-for-equatorial-guinea},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

---

*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — 非洲机器学习数据集基础设施，尼日利亚拉各斯。*