electricsheepafrica/africa-unhabitat-et-indicators

---
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-classification
- other
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- baseline-population
- education
- health
- hxl
- indicators
- transportation
- eth
pretty_name: "Ethiopia - Demographic, Health, Education and Transport indicators"
dataset_info:
splits:
- name: train
num_examples: 368
- name: test
num_examples: 92
---

# Ethiopia - Demographic, Health, Education and Transport indicators

**Publisher:** United Nations Human Settlements Programmes, Data and Analytics Section · **Source:** [HDX](https://data.humdata.org/dataset/unhabitat-et-indicators) · **License:** `cc-by-igo` · **Updated:** 2024-03-28

---

## Abstract

The urban indicators data available here are analyzed, compiled and published by UN-Habitat’s Global Urban Observatory which supports governments, local authorities and civil society organizations to develop urban indicators, data and statistics. Urban statistics are collected through household surveys and censuses conducted by national statistics authorities. Global Urban Observatory team analyses and compiles urban indicators statistics from surveys and censuses. Additionally, Local urban observatories collect, compile and analyze urban data for national policy development. Population statistics are produced by the United Nations Department of Economic and Social Affairs, World Urbanization Prospects.

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2024-03-28. Geographic scope: **ETH**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Public health |
| **Unit of observation** | First-level administrative unit observations |
| **Rows (total)** | 460 |
| **Columns** | 13 (5 numeric, 8 categorical, 0 datetime) |
| **Train split** | 368 rows |
| **Test split** | 92 rows |
| **Geographic scope** | ETH |
| **Publisher** | United Nations Human Settlements Programmes, Data and Analytics Section |
| **HDX last updated** | 2024-03-28 |

---

## Variables

**Geographic** — `category` (Population, Slum dwellers, Streets), `indicator_friendly` (Average annual rate of change of population – Total, Total population, Urban population – Countries), `type_data` (p, 1000, n), `latitude` (range 8.0–9.0333), `longitude` (range 38.0–38.7) and 3 others.

**Outcome / Measurement** — `value` (range 0.185–3226000.0).

**Identifier / Metadata** — `name` (Ethiopia, Addis Ababa, #country+name), `esa_source` (HDX), `esa_processed` (2026-04-10).

**Other** — `indicator` (avg_annual_rate_change_percentage_total, avg_annual_rate_change_percentage_urban, rural_population).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-unhabitat-et-indicators")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `category` | object | 0.0% | Population, Slum dwellers, Streets |
| `indicator` | object | 0.0% | avg_annual_rate_change_percentage_total, avg_annual_rate_change_percentage_urban, rural_population |
| `indicator_friendly` | object | 0.0% | Average annual rate of change of population – Total, Total population, Urban population – Countries |
| `type_data` | object | 0.0% | p, 1000, n |
| `latitude` | float64 | 0.2% | 8.0 – 9.0333 (mean 8.1193) |
| `longitude` | float64 | 0.2% | 38.0 – 38.7 (mean 38.0808) |
| `region_id` | float64 | 0.2% | 289.0 – 289.0 (mean 289.0) |
| `country_id` | object | 0.0% | ET, #country+code+v_iso2 |
| `name` | object | 0.0% | Ethiopia, Addis Ababa, #country+name |
| `year` | float64 | 0.2% | 1950.0 – 2050.0 (mean 2000.085) |
| `value` | float64 | 0.2% | 0.185 – 3226000.0 (mean 22612.3603) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-10 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `latitude` | 8.0 | 9.0333 | 8.1193 | 8.0 |
| `longitude` | 38.0 | 38.7 | 38.0808 | 38.0 |
| `region_id` | 289.0 | 289.0 | 289.0 | 289.0 |
| `year` | 1950.0 | 2050.0 | 2000.085 | 2004.0 |
| `value` | 0.185 | 3226000.0 | 22612.3603 | 30.19 |

---

## 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`. 5 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). 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 United Nations Human Settlements Programmes, Data and Analytics Section 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/unhabitat-et-indicators) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_unhabitat_et_indicators,
title = {Ethiopia - Demographic, Health, Education and Transport indicators},
author = {United Nations Human Settlements Programmes, Data and Analytics Section},
year = {2024},
url = {https://data.humdata.org/dataset/unhabitat-et-indicators},
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:
- 无标注
language_creators:
- 公开数据源采集
language:
- 英语
license: cc-by-4.0
multilinguality:
- 单语言
size_categories:
- 样本数少于1000
source_datasets:
- 原始数据集
task_categories:
- 表格分类
- 其他
task_ids: []
tags:
- 非洲
- 人道主义
- HDX（Humanitarian Data Exchange）
- 电羊非洲（Electric Sheep Africa）
- 基准人口（baseline-population）
- 教育
- 健康
- HXL（Humanitarian Exchange Language）
- 指标
- 交通
- ETH（埃塞俄比亚国家代码）
pretty_name: "埃塞俄比亚——人口、健康、教育与交通指标"
dataset_info:
splits:
- name: 训练集
num_examples: 368
- name: 测试集
num_examples: 92

# 埃塞俄比亚——人口、健康、教育与交通指标

**发布方**：联合国人类住区规划署（United Nations Human Settlements Programmes）数据与分析部门 · **来源**：[人道主义数据交换（HDX）](https://data.humdata.org/dataset/unhabitat-et-indicators) · **许可协议**：`cc-by-igo` · **最后更新时间**：2024-03-28

## 摘要
本数据集收录的城市指标数据由联合国人居署（UN-Habitat）全球城市观测站分析、整理并发布，该机构旨在协助各国政府、地方当局及民间社会组织开发城市指标、数据与统计资料。城市统计数据由各国统计主管部门通过家庭调查与人口普查收集，全球城市观测站团队会对来自调查与普查的城市指标统计数据进行分析与整理。此外，地方城市观测站也会为国家政策制定收集、整理并分析城市数据。人口统计数据由联合国经济和社会事务部世界城市化展望项目编制。

本数据集的每一行均代表一级行政单元的观测结果。本数据集最后一次在HDX平台更新的时间为2024-03-28。地理覆盖范围：**ETH（埃塞俄比亚国家代码）**。

*本数据集已由[电羊非洲（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** | 公共卫生 |
| **观测单元** | 一级行政单元 |
| **总行数** | 460 |
| **列数** | 13列（5个数值型、8个分类型、0个日期时间型） |
| **训练集划分** | 368行 |
| **测试集划分** | 92行 |
| **地理覆盖范围** | ETH（埃塞俄比亚） |
| **发布方** | 联合国人类住区规划署数据与分析部门 |
| **HDX平台最后更新时间** | 2024-03-28 |

## 变量
### 地理类变量
`category`（取值：人口、贫民窟居民、道路）、`indicator_friendly`（取值：总人口年度变化率、总人口、城市人口——国家层面）、`type_data`（取值：p、1000、n）、`latitude`（取值范围：8.0–9.0333）、`longitude`（取值范围：38.0–38.7）及另外3个变量。

### 结果/测量变量
`value`（取值范围：0.185–3226000.0）。

### 标识符/元数据变量
`name`（取值：埃塞俄比亚、亚的斯亚贝巴、#country+name）、`esa_source`（取值：HDX）、`esa_processed`（取值：2026-04-10）。

### 其他变量
`indicator`（取值：avg_annual_rate_change_percentage_total、avg_annual_rate_change_percentage_urban、rural_population）。

## 快速上手
python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-unhabitat-et-indicators")
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 |
|---|---|---|---|
| `category` | object | 0.0% | 人口、贫民窟居民、道路 |
| `indicator` | object | 0.0% | avg_annual_rate_change_percentage_total、avg_annual_rate_change_percentage_urban、rural_population |
| `indicator_friendly` | object | 0.0% | 总人口年度变化率、总人口、城市人口——国家层面 |
| `type_data` | object | 0.0% | p、1000、n |
| `latitude` | float64 | 0.2% | 8.0 – 9.0333（均值：8.1193） |
| `longitude` | float64 | 0.2% | 38.0 – 38.7（均值：38.0808） |
| `region_id` | float64 | 0.2% | 289.0 – 289.0（均值：289.0） |
| `country_id` | object | 0.0% | ET、#country+code+v_iso2 |
| `name` | object | 0.0% | 埃塞俄比亚、亚的斯亚贝巴、#country+name |
| `year` | float64 | 0.2% | 1950.0 – 2050.0（均值：2000.085） |
| `value` | float64 | 0.2% | 0.185 – 3226000.0（均值：22612.3603） |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-10 |

## 数值统计摘要
| 列名 | 最小值 | 最大值 | 均值 | 中位数 |
|---|---|---|---|---|
| `latitude` | 8.0 | 9.0333 | 8.1193 | 8.0 |
| `longitude` | 38.0 | 38.7 | 38.0808 | 38.0 |
| `region_id` | 289.0 | 289.0 | 289.0 | 289.0 |
| `year` | 1950.0 | 2050.0 | 2000.085 | 2004.0 |
| `value` | 0.185 | 3226000.0 | 22612.3603 | 30.19 |

## 数据整理流程
原始数据通过CKAN应用程序编程接口（CKAN API）从HDX平台下载并转换为Parquet格式。列名被统一转换为小写并标准化为蛇形命名法（snake_case）。常见的缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）被统一替换为`NaN`。基于解析成功率（阈值>85%），将5个列从字符串类型转换为数值型或日期时间型。本数据集以固定随机种子（42）按照80/20的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
- 本数据集源自联合国人类住区规划署数据与分析部门，未经过电羊非洲（ESA）的独立验证。
- 自动化数据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。
- 如需查看发布方提供的方法说明与注意事项，请参阅[HDX平台原始数据集页面](https://data.humdata.org/dataset/unhabitat-et-indicators)。

## 引用
bibtex
@dataset{hdx_africa_unhabitat_et_indicators,
title = {Ethiopia - Demographic, Health, Education and Transport indicators},
author = {United Nations Human Settlements Programmes, Data and Analytics Section},
year = {2024},
url = {https://data.humdata.org/dataset/unhabitat-et-indicators},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

*[电羊非洲（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。*