electricsheepafrica/africa-world-bank-combined-indicators-for-kenya
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---
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
- ken
pretty_name: "Kenya - Economic, Social, Environmental, Health, Education, Development and Energy"
dataset_info:
splits:
- name: train
num_examples: 50507
- name: test
num_examples: 12626
---
# Kenya - Economic, Social, Environmental, Health, Education, Development and Energy
**Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-combined-indicators-for-kenya) · **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-kenya), [Aid Effectiveness](https://data.humdata.org/dataset/world-bank-aid-effectiveness-indicators-for-kenya), [Economy and Growth](https://data.humdata.org/dataset/world-bank-economy-and-growth-indicators-for-kenya), [Education](https://data.humdata.org/dataset/world-bank-education-indicators-for-kenya), [Energy and Mining](https://data.humdata.org/dataset/world-bank-energy-and-mining-indicators-for-kenya), [Environment](https://data.humdata.org/dataset/world-bank-environment-indicators-for-kenya), [Financial Sector](https://data.humdata.org/dataset/world-bank-financial-sector-indicators-for-kenya), [Health](https://data.humdata.org/dataset/world-bank-health-indicators-for-kenya), [Infrastructure](https://data.humdata.org/dataset/world-bank-infrastructure-indicators-for-kenya), [Social Protection and Labor](https://data.humdata.org/dataset/world-bank-social-protection-and-labor-indicators-for-kenya), [Poverty](https://data.humdata.org/dataset/world-bank-poverty-indicators-for-kenya), [Private Sector](https://data.humdata.org/dataset/world-bank-private-sector-indicators-for-kenya), [Public Sector](https://data.humdata.org/dataset/world-bank-public-sector-indicators-for-kenya), [Science and Technology](https://data.humdata.org/dataset/world-bank-science-and-technology-indicators-for-kenya), [Social Development](https://data.humdata.org/dataset/world-bank-social-development-indicators-for-kenya), [Urban Development](https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-kenya), [Gender](https://data.humdata.org/dataset/world-bank-gender-indicators-for-kenya), [Millenium development goals](https://data.humdata.org/dataset/world-bank-millenium-development-goals-indicators-for-kenya), [Climate Change](https://data.humdata.org/dataset/world-bank-climate-change-indicators-for-kenya), [External Debt](https://data.humdata.org/dataset/world-bank-external-debt-indicators-for-kenya), [Trade](https://data.humdata.org/dataset/world-bank-trade-indicators-for-kenya).
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)** | 63,134 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 50,507 rows |
| **Test split** | 12,626 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 -1499489438000.0–17126020000000.0).
**Identifier / Metadata** — `indicator_name` (Domestic credit to private sector (% of GDP), Net migration, Population in urban agglomerations of more than 1 million), `indicator_code` (SM.POP.NETM, EN.URB.LCTY, EN.URB.LCTY.UR.ZS), `esa_source` (HDX), `esa_processed` (2026-04-09).
---
## Quick Start
```python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-world-bank-combined-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 1998.7385) |
| `indicator_name` | object | 0.0% | Domestic credit to private sector (% of GDP), Net migration, Population in urban agglomerations of more than 1 million |
| `indicator_code` | object | 0.0% | SM.POP.NETM, EN.URB.LCTY, EN.URB.LCTY.UR.ZS |
| `value` | float64 | 0.0% | -1499489438000.0 – 17126020000000.0 (mean 64249205521.7281) |
| `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 | 1998.7385 | 2002.0 |
| `value` | -1499489438000.0 | 17126020000000.0 | 64249205521.7281 | 45.7805 |
---
## 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`. 18,262 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-kenya) for the publisher's own methodology notes and caveats.
---
## Citation
```bibtex
@dataset{hdx_africa_world_bank_combined_indicators_for_kenya,
title = {Kenya - 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-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:
- 爬取获取
language:
- 英语
license: CC-BY 4.0
multilinguality:
- 单语言
size_categories:
- 10K<n<100K
source_datasets:
- 原始数据集
task_categories:
- 表格分类
task_ids: []
tags:
- 非洲
- 人道主义
- HDX（Humanitarian Data Exchange）
- 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
- 肯尼亚
pretty_name: "肯尼亚——经济、社会、环境、健康、教育、发展与能源"
dataset_info:
splits:
- name: 训练集
num_examples: 50507
- name: 测试集
num_examples: 12626
---
# 肯尼亚——经济、社会、环境、健康、教育、发展与能源
**发布方：** 世界银行集团 · **来源：** [HDX（Humanitarian Data Exchange）](https://data.humdata.org/dataset/world-bank-combined-indicators-for-kenya) · **许可证：** `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/)的多领域数据，涵盖以下主题（这些主题在HDX平台上均有独立数据集）：[农业与农村发展](https://data.humdata.org/dataset/world-bank-agriculture-and-rural-development-indicators-for-kenya)、[援助有效性](https://data.humdata.org/dataset/world-bank-aid-effectiveness-indicators-for-kenya)、[经济与增长](https://data.humdata.org/dataset/world-bank-economy-and-growth-indicators-for-kenya)、[教育](https://data.humdata.org/dataset/world-bank-education-indicators-for-kenya)、[能源与矿业](https://data.humdata.org/dataset/world-bank-energy-and-mining-indicators-for-kenya)、[环境](https://data.humdata.org/dataset/world-bank-environment-indicators-for-kenya)、[金融部门](https://data.humdata.org/dataset/world-bank-financial-sector-indicators-for-kenya)、[健康](https://data.humdata.org/dataset/world-bank-health-indicators-for-kenya)、[基础设施](https://data.humdata.org/dataset/world-bank-infrastructure-indicators-for-kenya)、[社会保护与劳动](https://data.humdata.org/dataset/world-bank-social-protection-and-labor-indicators-for-kenya)、[贫困](https://data.humdata.org/dataset/world-bank-poverty-indicators-for-kenya)、[私营部门](https://data.humdata.org/dataset/world-bank-private-sector-indicators-for-kenya)、[公共部门](https://data.humdata.org/dataset/world-bank-public-sector-indicators-for-kenya)、[科学与技术](https://data.humdata.org/dataset/world-bank-science-and-technology-indicators-for-kenya)、[社会发展](https://data.humdata.org/dataset/world-bank-social-development-indicators-for-kenya)、[城市发展](https://data.humdata.org/dataset/world-bank-urban-development-indicators-for-kenya)、[性别平等](https://data.humdata.org/dataset/world-bank-gender-indicators-for-kenya)、[千年发展目标](https://data.humdata.org/dataset/world-bank-millenium-development-goals-indicators-for-kenya)、[气候变化](https://data.humdata.org/dataset/world-bank-climate-change-indicators-for-kenya)、[外债](https://data.humdata.org/dataset/world-bank-external-debt-indicators-for-kenya)、[贸易](https://data.humdata.org/dataset/world-bank-trade-indicators-for-kenya)。
本数据集每一行均代表国家级聚合数据。HDX平台上的最新更新时间为2026-03-27。地理覆盖范围：**肯尼亚（KEN）**。
*本数据集已由[Electric Sheep Africa（ESA）](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** | 国家级聚合数据 |
| **总行数** | 63,134 |
| **列数** | 8（2个数值型，6个分类型，0个日期时间型） |
| **训练集划分** | 50,507行 |
| **测试集划分** | 12,626行 |
| **地理覆盖范围** | KEN（肯尼亚） |
| **发布方** | 世界银行集团 |
| **HDX最后更新时间** | 2026-03-27 |
---
## 变量
**地理类** — `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** — `value`（指标数值范围：-1499489438000.0–17126020000000.0）。
**标识符/元数据类** — `indicator_name`（指标名称：例如私人部门国内信贷占GDP百分比、净移民、百万以上人口城市聚集区人口）、`indicator_code`（指标代码：例如SM.POP.NETM、EN.URB.LCTY、EN.URB.LCTY.UR.ZS）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理时间：2026-04-09）。
---
## 快速上手
python
from datasets import load_dataset
ds = load_dataset('electricsheepafrica/africa-world-bank-combined-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 | 范围/示例值 |
|---|---|---|---|
| `country_name` | `object` | 0.0% | 肯尼亚 |
| `country_iso3` | `object` | 0.0% | KEN |
| `year` | `int64` | 0.0% | 1960.0 – 2025.0（均值：1998.7385） |
| `indicator_name` | `object` | 0.0% | 私人部门国内信贷占GDP百分比、净移民、百万以上人口城市聚集区人口 |
| `indicator_code` | `object` | 0.0% | SM.POP.NETM、EN.URB.LCTY、EN.URB.LCTY.UR.ZS |
| `value` | `float64` | 0.0% | -1499489438000.0 – 17126020000000.0（均值：64249205521.7281） |
| `esa_source` | `object` | 0.0% | HDX |
| `esa_processed` | `object` | 0.0% | 2026-04-09 |
---
## 数值统计摘要
| 列名 | 最小值 | 最大值 | 均值 | 中位数 |
|---|---|---|---|---|
| `year` | 1960.0 | 2025.0 | 1998.7385 | 2002.0 |
| `value` | -1499489438000.0 | 17126020000000.0 | 64249205521.7281 | 45.7805 |
---
## 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（snake_case）。将常见的缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。移除了18,262条完全重复的行。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（ESA）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、定义不一致或抽样偏差问题。
- 请查阅[原始HDX数据集页面](https://data.humdata.org/dataset/world-bank-combined-indicators-for-kenya)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_combined_indicators_for_kenya,
title = {Kenya - 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-kenya},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
---
*[Electric Sheep Africa（ESA）](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。*
提供机构：
electricsheepafrica
