electricsheepafrica/africa-world-bank-urban-development-indicators-for-kenya

---
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
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- development
- indicators
- ken
pretty_name: "Kenya - Urban Development"
dataset_info:
splits:
- name: train
num_examples: 527
- name: test
num_examples: 131
---

# Kenya - Urban Development

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

Cities can be tremendously efficient. It is easier to provide water and sanitation to people living closer together, while access to health, education, and other social and cultural services is also much more readily available. However, as cities grow, the cost of meeting basic needs increases, as does the strain on the environment and natural resources. Data on urbanization, traffic and congestion, and air pollution are from the United Nations Population Division, World Health Organization, International Road Federation, World Resources Institute, and other sources.

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

*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)** | 659 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 527 rows |
| **Test split** | 131 rows |
| **Geographic scope** | KEN |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

**Geographic** — `country_name` (Kenya), `country_iso3` (KEN), `year` (range 1960.0–2025.0).

**Outcome / Measurement** — `value` (range 0.0034–17998601.0).

**Identifier / Metadata** — `indicator_name` (Population in the largest city (% of urban population), Population in largest city, Population in urban agglomerations of more than 1 million), `indicator_code` (EN.URB.LCTY.UR.ZS, EN.URB.LCTY, EN.URB.MCTY), `esa_source` (HDX), `esa_processed` (2026-04-09).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-urban-development-indicators-for-kenya")
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% | Kenya |
| `country_iso3` | object | 0.0% | KEN |
| `year` | int64 | 0.0% | 1960.0 – 2025.0 (mean 1995.4082) |
| `indicator_name` | object | 0.0% | Population in the largest city (% of urban population), Population in largest city, Population in urban agglomerations of more than 1 million |
| `indicator_code` | object | 0.0% | EN.URB.LCTY.UR.ZS, EN.URB.LCTY, EN.URB.MCTY |
| `value` | float64 | 0.0% | 0.0034 – 17998601.0 (mean 1131347.3161) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-09 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1960.0 | 2025.0 | 1995.4082 | 1998.0 |
| `value` | 0.0034 | 17998601.0 | 1131347.3161 | 33.1546 |

---

## 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-urban-development-indicators-for-kenya) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_urban_development_indicators_for_kenya,
title = {Kenya - Urban Development},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-kenya},
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:
- 公开采集
language:
- 英语
license: CC BY 4.0
multilinguality:
- 单语言
size_categories:
- 样本量小于1000
source_datasets:
- 原始数据集
task_categories:
- 表格分类
- 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（非洲电羊团队）
- 发展
- 指标
- 肯尼亚（KEN）
pretty_name: "肯尼亚——城市发展"
dataset_info:
splits:
- name: train
num_examples: 527
- name: test
num_examples: 131
---

# 肯尼亚——城市发展

**发布方：** 世界银行集团 · **来源：** [HDX（人道主义数据交换平台）](https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-kenya) · **许可协议：** `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（人道主义数据交换平台）上同时发布有肯尼亚整合型国家数据集[链接](https://data.humdata.org/dataset/world-bank-combined-indicators-for-kenya)。

城市具备极高的运行效率：为聚居人群提供供水与卫生设施的难度更低，同时医疗、教育及其他社会文化服务的可及性也显著提升。但随着城市扩张，满足居民基本需求的成本不断攀升，对环境与自然资源的压力也随之加大。本数据集内的城市化、交通拥堵与空气污染相关数据，分别来自联合国人口司、世界卫生组织、国际道路联合会、世界资源研究所及其他权威机构。

本数据集的每一行均代表国家级汇总统计数据。数据集最近一次在HDX平台更新的时间为2026-03-27，地理覆盖范围为**肯尼亚（KEN）**。

*本数据集已由[Electric Sheep Africa（非洲电羊团队）](https://huggingface.co/electricsheepafrica)整理为适配机器学习的帕奎特（Parquet）格式。*

---

## 数据集特征

| | |
|---|---|
| **领域** | 公共卫生 |
| **观测单元** | 国家级汇总统计单元 |
| **总数据行数** | 659条 |
| **总列数** | 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** | 527条 |
| **测试集样本量** | 131条 |
| **地理覆盖范围** | 肯尼亚（KEN） |
| **发布方** | 世界银行集团 |
| **HDX平台更新时间** | 2026-03-27 |

---

## 变量说明

**地理类变量**：`country_name`（国家名称：肯尼亚）、`country_iso3`（国家ISO3代码：KEN）、`year`（年份范围：1960.0–2025.0）。

**结果/测量类变量**：`value`（指标数值，取值范围：0.0034–17998601.0）。

**标识符/元数据类变量**：`indicator_name`（指标名称：最大城市人口占城镇人口比例、最大城市人口、百万以上人口城镇集聚区人口）、`indicator_code`（指标代码：EN.URB.LCTY.UR.ZS、EN.URB.LCTY、EN.URB.MCTY）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理时间：2026-04-09）。

---

## 快速入门

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-urban-development-indicators-for-kenya")
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` | 字符串（object） | 0.0% | 肯尼亚 |
| `country_iso3` | 字符串（object） | 0.0% | KEN |
| `year` | 64位整数（int64） | 0.0% | 1960.0 – 2025.0（平均值：1995.4082） |
| `indicator_name` | 字符串（object） | 0.0% | 最大城市人口占城镇人口比例、最大城市人口、百万以上人口城镇集聚区人口 |
| `indicator_code` | 字符串（object） | 0.0% | EN.URB.LCTY.UR.ZS、EN.URB.LCTY、EN.URB.MCTY |
| `value` | 64位浮点数（float64） | 0.0% | 0.0034 – 17998601.0（平均值：1131347.3161） |
| `esa_source` | 字符串（object） | 0.0% | HDX |
| `esa_processed` | 字符串（object） | 0.0% | 2026-04-09 |

---

## 数值统计摘要

| 列名 | 最小值 | 最大值 | 平均值 | 中位数 |
|---|---|---|---|---|
| `year` | 1960.0 | 2025.0 | 1995.4082 | 1998.0 |
| `value` | 0.0034 | 17998601.0 | 1131347.3161 | 33.1546 |

---

## 数据整理流程

原始数据通过CKAN API从HDX平台下载，并转换为帕奎特（Parquet）格式。列名统一转换为小写并标准化为蛇形命名法（snake_case）。常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）被统一替换为`NaN`。本数据集以固定随机种子（42）按80/20的比例划分为训练集与测试集，并以Snappy压缩格式存储为帕奎特文件。

---

## 数据集局限性

- 数据源自世界银行集团，未经过Electric Sheep Africa（非洲电羊团队）的独立验证。
- 自动化清洗流程无法修正原始数据收集阶段的错报、定义不一致或抽样偏差问题。
- 如需查看发布方的方法说明与注意事项，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-kenya)。

---

## 引用

bibtex
@dataset{hdx_africa_world_bank_urban_development_indicators_for_kenya,
title = {Kenya - Urban Development},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-kenya},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

---

*[Electric Sheep Africa（非洲电羊团队）](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。*