electricsheepafrica/africa-world-bank-environment-indicators-for-angola

---
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-classification
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- environment
- indicators
- ago
pretty_name: "Angola - Environment"
dataset_info:
splits:
- name: train
num_examples: 3660
- name: test
num_examples: 915
---

# Angola - Environment

**Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-environment-indicators-for-angola) · **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-angola) on HDX.

Natural and man-made environmental resources – fresh water, clean air, forests, grasslands, marine resources, and agro-ecosystems – provide sustenance and a foundation for social and economic development. The need to safeguard these resources crosses all borders. Today, the World Bank is one of the key promoters and financiers of environmental upgrading in the developing world. Data here cover forests, biodiversity, emissions, and pollution. Other indicators relevant to the environment are found under data pages for Agriculture & Rural Development, Energy & Mining, Infrastructure, and Urban Development.

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

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Water, sanitation and hygiene (wash) |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 4,576 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 3,660 rows |
| **Test split** | 915 rows |
| **Geographic scope** | AGO |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

**Geographic** — `country_name` (Angola), `country_iso3` (AGO), `year` (range 1960.0–2024.0).

**Outcome / Measurement** — `value` (range -6811617536.5373–37602827312.6533).

**Identifier / Metadata** — `indicator_name` (Aquaculture production (metric tons), Total fisheries production (metric tons), Capture fisheries production (metric tons)), `indicator_code` (ER.FSH.AQUA.MT, ER.FSH.PROD.MT, ER.FSH.CAPT.MT), `esa_source` (HDX), `esa_processed` (2026-04-17).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-environment-indicators-for-angola")
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% | Angola |
| `country_iso3` | object | 0.0% | AGO |
| `year` | int64 | 0.0% | 1960.0 – 2024.0 (mean 2001.068) |
| `indicator_name` | object | 0.0% | Aquaculture production (metric tons), Total fisheries production (metric tons), Capture fisheries production (metric tons) |
| `indicator_code` | object | 0.0% | ER.FSH.AQUA.MT, ER.FSH.PROD.MT, ER.FSH.CAPT.MT |
| `value` | float64 | 0.0% | -6811617536.5373 – 37602827312.6533 (mean 228617328.0039) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-17 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1960.0 | 2024.0 | 2001.068 | 2003.0 |
| `value` | -6811617536.5373 | 37602827312.6533 | 228617328.0039 | 7.0 |

---

## 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-environment-indicators-for-angola) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_environment_indicators_for_angola,
title = {Angola - Environment},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-environment-indicators-for-angola},
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.*

注释创建者：
- 无注释
语言创建者：
- 采集所得
语言：
- 英语
许可证：cc-by-4.0
多语言属性：
- 单语言
数据规模：
- 1000 < 样本量 < 10000
源数据集：
- 原创数据集
任务类别：
- 表格分类
- 表格回归
任务子类别：
- 无
标签：
- 非洲
- 人道主义
- HDX（Humanitarian Data Exchange）
- Electric Sheep Africa
- 环境
- 指标
- AGO
展示名称："安哥拉——环境"
数据集信息：
拆分：
- 名称：训练集
样本数：3660
- 名称：测试集
样本数：915

# 安哥拉——环境
**发布方**：世界银行集团（World Bank Group） · **来源**：[HDX（Humanitarian Data Exchange）](https://data.humdata.org/dataset/world-bank-environment-indicators-for-angola) · **许可证**：`cc-by` · **更新时间**：2026-03-27

---

## 摘要
本数据集包含源自世界银行[数据门户](http://data.worldbank.org/)的相关数据。HDX平台上还提供了一份[整合后的国家数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-angola)。

自然与人工环境资源——包括淡水、洁净空气、森林、草原、海洋资源以及农业生态系统——为社会与经济发展提供了支撑与基础。保护这些资源的需求无国界之分。如今，世界银行是发展中世界环境升级改造的核心推动者与融资方之一。本数据集涵盖森林、生物多样性、碳排放与污染相关数据。其他与环境相关的指标可在农业与农村发展、能源与矿业、基础设施以及城市发展的数据页面中查询。

本数据集的每一行均代表国家层面的汇总数据。HDX平台上的最新更新时间为2026-03-27。地理覆盖范围：**AGO**。

*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** | 水、卫生与个人卫生（Water, Sanitation and Hygiene，WASH） |
| **观测单元** | 国家层面汇总数据 |
| **总数据行数** | 4576 |
| **列数** | 8列（2列数值型，6列分类型，0列日期时间型） |
| **训练集拆分** | 3660行 |
| **测试集拆分** | 915行 |
| **地理覆盖范围** | AGO |
| **发布方** | 世界银行集团 |
| **HDX最后更新时间** | 2026-03-27 |

---

## 变量
**地理类变量** — `country_name`（国家名称：安哥拉）、`country_iso3`（国家ISO3代码：AGO）、`year`（年份：范围1960.0–2024.0）。

**结果/测量变量** — `value`（数值：范围-6811617536.5373–37602827312.6533）。

**标识符/元数据变量** — `indicator_name`（指标名称：水产养殖产量（公吨）、渔业总产量（公吨）、捕捞渔业产量（公吨））、`indicator_code`（指标代码：ER.FSH.AQUA.MT、ER.FSH.PROD.MT、ER.FSH.CAPT.MT）、`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-environment-indicators-for-angola")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

print(train.shape)
train.head()

---

## 数据模式
| 列名 | 数据类型 | 空值占比 | 取值范围/示例值 |
|---|---|---|---|
| `country_name` | 字符型 | 0.0% | 安哥拉 |
| `country_iso3` | 字符型 | 0.0% | AGO |
| `year` | 64位整数 | 0.0% | 1960.0 – 2024.0（平均值：2001.068） |
| `indicator_name` | 字符型 | 0.0% | 水产养殖产量（公吨）、渔业总产量（公吨）、捕捞渔业产量（公吨） |
| `indicator_code` | 字符型 | 0.0% | ER.FSH.AQUA.MT、ER.FSH.PROD.MT、ER.FSH.CAPT.MT |
| `value` | 64位浮点型 | 0.0% | -6811617536.5373 – 37602827312.6533（平均值：228617328.0039） |
| `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 | 平均值 | 中位数 |
|---|---|---|---|---|
| `year` | 1960.0 | 2024.0 | 2001.068 | 2003.0 |
| `value` | -6811617536.5373 | 37602827312.6533 | 228617328.0039 | 7.0 |

---

## 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。列名统一转换为小写并采用蛇形命名法（snake_case）标准化。将常见的缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。本数据集以80/20的比例划分为训练集与测试集，使用固定随机种子（42）进行拆分，并保存为Snappy压缩的Parquet格式文件。

---

## 局限性说明
- 本数据集源自世界银行集团，尚未由Electric Sheep Africa进行独立验证。
- 自动化清洗流程无法修正原始数据收集中的错报值、定义不一致问题或抽样偏差。
- 如需查看发布方提供的方法说明与免责声明，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/world-bank-environment-indicators-for-angola)。

---

## 引用格式
bibtex
@dataset{hdx_africa_world_bank_environment_indicators_for_angola,
title = {Angola - Environment},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-environment-indicators-for-angola},
note = {由Electric Sheep Africa（https://huggingface.co/electricsheepafrica）重新打包以适配机器学习场景}
}

---

*[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。*