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

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- tabular-classification
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- agriculture-livestock
- aid-effectiveness
- climate-weather
- development
- economics
- education
- energy
- environment
- ago
pretty_name: "Angola - Economic, Social, Environmental, Health, Education, Development and Energy"
dataset_info:
splits:
- name: train
num_examples: 36303
- name: test
num_examples: 9075
---

# Angola - Economic, Social, Environmental, Health, Education, Development and Energy

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

---

## Abstract

Contains data from the World Bank's [data portal](http://data.worldbank.org/) covering the following topics which also exist as individual datasets on HDX: [Agriculture and Rural Development](https://data.humdata.org/dataset/world-bank-agriculture-and-rural-development-indicators-for-angola), [Aid Effectiveness](https://data.humdata.org/dataset/world-bank-aid-effectiveness-indicators-for-angola), [Economy and Growth](https://data.humdata.org/dataset/world-bank-economy-and-growth-indicators-for-angola), [Education](https://data.humdata.org/dataset/world-bank-education-indicators-for-angola), [Energy and Mining](https://data.humdata.org/dataset/world-bank-energy-and-mining-indicators-for-angola), [Environment](https://data.humdata.org/dataset/world-bank-environment-indicators-for-angola), [Financial Sector](https://data.humdata.org/dataset/world-bank-financial-sector-indicators-for-angola), [Health](https://data.humdata.org/dataset/world-bank-health-indicators-for-angola), [Infrastructure](https://data.humdata.org/dataset/world-bank-infrastructure-indicators-for-angola), [Social Protection and Labor](https://data.humdata.org/dataset/world-bank-social-protection-and-labor-indicators-for-angola), [Poverty](https://data.humdata.org/dataset/world-bank-poverty-indicators-for-angola), [Private Sector](https://data.humdata.org/dataset/world-bank-private-sector-indicators-for-angola), [Public Sector](https://data.humdata.org/dataset/world-bank-public-sector-indicators-for-angola), [Science and Technology](https://data.humdata.org/dataset/world-bank-science-and-technology-indicators-for-angola), [Social Development](https://data.humdata.org/dataset/world-bank-social-development-indicators-for-angola), [Urban Development](https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-angola), [Gender](https://data.humdata.org/dataset/world-bank-gender-indicators-for-angola), [Millenium development goals](https://data.humdata.org/dataset/world-bank-millenium-development-goals-indicators-for-angola), [Climate Change](https://data.humdata.org/dataset/world-bank-climate-change-indicators-for-angola), [External Debt](https://data.humdata.org/dataset/world-bank-external-debt-indicators-for-angola), [Trade](https://data.humdata.org/dataset/world-bank-trade-indicators-for-angola).

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** | Public health |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 45,379 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 36,303 rows |
| **Test split** | 9,075 rows |
| **Geographic scope** | AGO |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

**Geographic** — `country_name` (Angola), `country_iso3` (AGO), `year` (range 1960.0–2025.0).

**Outcome / Measurement** — `value` (range -6649199957600.0–101910674907423.0).

**Identifier / Metadata** — `indicator_name` (Population in urban agglomerations of more than 1 million (% of total population), Population in urban agglomerations of more than 1 million, Population in the largest city (% of urban population)), `indicator_code` (EN.URB.MCTY.TL.ZS, EN.URB.MCTY, EN.URB.LCTY.UR.ZS), `esa_source` (HDX), `esa_processed` (2026-04-16).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-combined-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 – 2025.0 (mean 2002.8068) |
| `indicator_name` | object | 0.0% | Population in urban agglomerations of more than 1 million (% of total population), Population in urban agglomerations of more than 1 million, Population in the largest city (% of urban population) |
| `indicator_code` | object | 0.0% | EN.URB.MCTY.TL.ZS, EN.URB.MCTY, EN.URB.LCTY.UR.ZS |
| `value` | float64 | 0.0% | -6649199957600.0 – 101910674907423.0 (mean 216536153849.5677) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-16 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1960.0 | 2025.0 | 2002.8068 | 2006.0 |
| `value` | -6649199957600.0 | 101910674907423.0 | 216536153849.5677 | 52.4687 |

---

## 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`. 14,542 exact duplicate rows were removed. 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-combined-indicators-for-angola) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_combined_indicators_for_angola,
title = {Angola - Economic, Social, Environmental, Health, Education, Development and Energy},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-combined-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.*

annotations_creators:
- 无注释
language_creators:
- 公开获取
language:
- 英语
license: 知识共享署名4.0（CC-BY-4.0）
multilinguality:
- 单语言
size_categories:
- 10000<样本量<100000
source_datasets:
- 原创数据集
task_categories:
- 表格分类任务
task_ids: []
tags:
- 非洲
- 人道主义
- 人类数据交换平台（Humanitarian Data Exchange, HDX）
- Electric Sheep Africa
- 农业与畜牧
- 援助有效性
- 气候与天气
- 发展
- 经济学
- 教育
- 能源
- 环境
- AGO（安哥拉ISO 3166-1 alpha-3代码）
pretty_name: "安哥拉——经济、社会、环境、健康、教育、发展与能源"
dataset_info:
splits:
- name: train
num_examples: 36303
- name: test
num_examples: 9075

---

# 安哥拉——经济、社会、环境、健康、教育、发展与能源

**发布方**：世界银行集团（World Bank Group） · **来源**：[人类数据交换平台（Humanitarian Data Exchange, HDX）](https://data.humdata.org/dataset/world-bank-combined-indicators-for-angola) · **许可协议**：`知识共享署名（CC-BY）` · **最后更新**：2026-03-27

---

## 摘要
本数据集包含来自世界银行[数据门户（World Bank Data Portal）](http://data.worldbank.org/)的多主题数据，这些主题在HDX平台上均设有对应的独立数据集：[农业与农村发展](https://data.humdata.org/dataset/world-bank-agriculture-and-rural-development-indicators-for-angola)、[援助有效性](https://data.humdata.org/dataset/world-bank-aid-effectiveness-indicators-for-angola)、[经济与增长](https://data.humdata.org/dataset/world-bank-economy-and-growth-indicators-for-angola)、[教育](https://data.humdata.org/dataset/world-bank-education-indicators-for-angola)、[能源与矿业](https://data.humdata.org/dataset/world-bank-energy-and-mining-indicators-for-angola)、[环境](https://data.humdata.org/dataset/world-bank-environment-indicators-for-angola)、[金融部门](https://data.humdata.org/dataset/world-bank-financial-sector-indicators-for-angola)、[健康](https://data.humdata.org/dataset/world-bank-health-indicators-for-angola)、[基础设施](https://data.humdata.org/dataset/world-bank-infrastructure-indicators-for-angola)、[社会保护与劳动](https://data.humdata.org/dataset/world-bank-social-protection-and-labor-indicators-for-angola)、[贫困](https://data.humdata.org/dataset/world-bank-poverty-indicators-for-angola)、[私营部门](https://data.humdata.org/dataset/world-bank-private-sector-indicators-for-angola)、[公共部门](https://data.humdata.org/dataset/world-bank-public-sector-indicators-for-angola)、[科学与技术](https://data.humdata.org/dataset/world-bank-science-and-technology-indicators-for-angola)、[社会发展](https://data.humdata.org/dataset/world-bank-social-development-indicators-for-angola)、[城市发展](https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-angola)、[性别平等](https://data.humdata.org/dataset/world-bank-gender-indicators-for-angola)、[千年发展目标](https://data.humdata.org/dataset/world-bank-millenium-development-goals-indicators-for-angola)、[气候变化](https://data.humdata.org/dataset/world-bank-climate-change-indicators-for-angola)、[外债](https://data.humdata.org/dataset/world-bank-external-debt-indicators-for-angola)、[贸易](https://data.humdata.org/dataset/world-bank-trade-indicators-for-angola)。

本数据集的每一行均代表国家级汇总数据。HDX平台上的最新数据更新时间为2026年3月27日。地理覆盖范围：**AGO（安哥拉ISO 3166-1 alpha-3代码）**。

*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

| 分类项 | 详情 |
|---|---|
| **领域** | 公共卫生 |
| **观测单元** | 国家级汇总数据 |
| **总数据行数** | 45,379 |
| **列数** | 8（2个数值型列、6个分类型列、0个日期时间型列） |
| **训练集划分** | 36,303条数据 |
| **测试集划分** | 9,075条数据 |
| **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 |

---

## 字段说明

### 地理类字段
`country_name`（国家名称：安哥拉）、`country_iso3`（国家ISO3代码：AGO）、`year`（年份范围：1960.0–2025.0）。

### 结果/测量类字段
`value`（指标数值，取值范围：-6649199957600.0–101910674907423.0）。

### 标识符/元数据类字段
`indicator_name`（指标名称：百万以上人口都市圈人口占总人口比例、百万以上人口都市圈人口、最大城市人口占城镇人口比例）、`indicator_code`（指标代码：EN.URB.MCTY.TL.ZS、EN.URB.MCTY、EN.URB.LCTY.UR.ZS）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理时间：2026-04-16）。

---

## 快速上手

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-combined-indicators-for-angola")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

print(train.shape)
train.head()

> 代码说明：从`datasets`库导入数据加载工具，加载由Electric Sheep Africa发布的安哥拉世界银行合并指标数据集，将训练集与测试集转换为Pandas DataFrame格式，打印训练集数据形状并查看训练集前5条样本。

---

## 数据结构

| 列名 | 数据类型 | 空值占比 | 取值范围/示例值 |
|---|---|---|---|
| `country_name` | 字符串（object） | 0.0% | 安哥拉 |
| `country_iso3` | 字符串（object） | 0.0% | AGO |
| `year` | 64位整数（int64） | 0.0% | 1960.0 – 2025.0（均值：2002.8068） |
| `indicator_name` | 字符串（object） | 0.0% | 百万以上人口都市圈人口占总人口比例、百万以上人口都市圈人口、最大城市人口占城镇人口比例 |
| `indicator_code` | 字符串（object） | 0.0% | EN.URB.MCTY.TL.ZS、EN.URB.MCTY、EN.URB.LCTY.UR.ZS |
| `value` | 64位浮点数（float64） | 0.0% | -6649199957600.0 – 101910674907423.0（均值：216536153849.5677） |
| `esa_source` | 字符串（object） | 0.0% | HDX |
| `esa_processed` | 字符串（object） | 0.0% | 2026-04-16 |

---

## 数值型字段统计

| 列名 | 最小值 | 最大值 | 均值 | 中位数 |
|---|---|---|---|---|
| `year` | 1960.0 | 2025.0 | 2002.8068 | 2006.0 |
| `value` | -6649199957600.0 | 101910674907423.0 | 216536153849.5677 | 52.4687 |

---

## 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标准化为蛇形命名法。将常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。删除了14,542条完全重复的行。采用固定随机种子（42）将数据集按80/20的比例划分为训练集与测试集，并保存为Snappy压缩的Parquet格式文件。

---

## 数据集局限性
- 本数据集源自世界银行集团，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阶段的错报值、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-combined-indicators-for-angola)获取发布方提供的方法论说明与免责条款。

---

## 引用格式

bibtex
@dataset{hdx_africa_world_bank_combined_indicators_for_angola,
title = {安哥拉——经济、社会、环境、健康、教育、发展与能源},
author = {世界银行集团},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-combined-indicators-for-angola},
note = {由Electric Sheep Africa重新打包以适配机器学习场景（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。*