electricsheepafrica/africa-world-bank-agriculture-and-rural-development-indicators-for-kenya

---
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-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- agriculture-livestock
- development
- indicators
- ken
pretty_name: "Kenya - Agriculture and Rural Development"
dataset_info:
splits:
- name: train
num_examples: 1362
- name: test
num_examples: 340
---

# Kenya - Agriculture and Rural Development

**Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-agriculture-and-rural-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.

For the 70 percent of the world's poor who live in rural areas, agriculture is the main source of income and employment. But depletion and degradation of land and water pose serious challenges to producing enough food and other agricultural products to sustain livelihoods here and meet the needs of urban populations. Data presented here include measures of agricultural inputs, outputs, and productivity compiled by the UN's Food and Agriculture Organization.

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** | Food security and nutrition |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 1,703 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 1,362 rows |
| **Test split** | 340 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 0.1198–27043723857.2442).

**Identifier / Metadata** — `indicator_name` (Agriculture, forestry, and fishing, value added (% of GDP), Rural population, Rural population (% of total population)), `indicator_code` (NV.AGR.TOTL.ZS, SP.RUR.TOTL, SP.RUR.TOTL.ZS), `esa_source` (HDX), `esa_processed` (2026-04-09).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-agriculture-and-rural-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 1994.5144) |
| `indicator_name` | object | 0.0% | Agriculture, forestry, and fishing, value added (% of GDP), Rural population, Rural population (% of total population) |
| `indicator_code` | object | 0.0% | NV.AGR.TOTL.ZS, SP.RUR.TOTL, SP.RUR.TOTL.ZS |
| `value` | float64 | 0.0% | 0.1198 – 27043723857.2442 (mean 217526247.4179) |
| `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 | 1994.5144 | 1996.0 |
| `value` | 0.1198 | 27043723857.2442 | 217526247.4179 | 69.1704 |

---

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

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_agriculture_and_rural_development_indicators_for_kenya,
title = {Kenya - Agriculture and Rural Development},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-agriculture-and-rural-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:
- 无注释
language_creators:
- 公开获取
language:
- 英语
license: CC BY 4.0
multilinguality:
- 单语言
size_categories:
- 1000 < 样本量 < 10000
source_datasets:
- 原创数据集
task_categories:
- 表格回归
task_ids: []
tags:
- 非洲
- 人道主义
- HDX（Humanitarian Data Exchange，人道主义数据交换平台）
- 电动绵羊非洲（Electric Sheep Africa）
- 农业与畜牧业
- 发展
- 指标
- 肯尼亚（KEN）
pretty_name: "肯尼亚——农业与农村发展"
dataset_info:
splits:
- name: 训练集
num_examples: 1362
- name: 测试集
num_examples: 340

# 肯尼亚——农业与农村发展

**发布方：世界银行集团 · 来源：[HDX（Humanitarian Data Exchange，人道主义数据交换平台）](https://data.humdata.org/dataset/world-bank-agriculture-and-rural-development-indicators-for-kenya) · 许可协议：`cc-by` · 最后更新：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平台上另有一份[整合型国家数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-kenya)可供获取。

全球70%的贫困人口居住在农村地区，农业是其主要收入与就业来源。但土地与水资源的耗竭与退化，对保障足够的粮食及其他农产品供给、维持当地生计并满足城市人口需求构成了严峻挑战。本数据集收录的内容包括联合国粮食及农业组织（Food and Agriculture Organization，FAO）编制的农业投入、产出与生产力相关指标。

本数据集的每一行均代表国家级汇总数据。该数据集在HDX平台的最后更新时间为2026-03-27。地理覆盖范围：**肯尼亚（KEN）**。

本数据集由[电动绵羊非洲（Electric Sheep Africa）](https://huggingface.co/electricsheepafrica)整理为机器学习可用的Parquet格式。

---

## 数据集特征

| | |
|---|---|
| **领域** | 粮食安全与营养 |
| **观测单元** | 国家级汇总数据 |
| **总行数** | 1703 |
| **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** | 1362行 |
| **测试集拆分** | 340行 |
| **地理覆盖范围** | 肯尼亚（KEN） |
| **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：肯尼亚）、`country_iso3`（国家ISO3代码：KEN）、`year`（年份：取值范围1960.0–2025.0）。
**结果/测量变量** — `value`（指标数值：取值范围0.1198–27043723857.2442）。
**标识符/元数据变量** — `indicator_name`（指标名称：农业、林业与渔业增加值（占GDP百分比）、农村人口数、农村人口占总人口百分比）、`indicator_code`（指标代码：NV.AGR.TOTL.ZS、SP.RUR.TOTL、SP.RUR.TOTL.ZS）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理日期：2026-04-09）。

---

## 快速上手

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-agriculture-and-rural-development-indicators-for-kenya")
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：1994.5144） |
| `indicator_name` | 字符串（object） | 0.0% | 农业、林业与渔业增加值（占GDP百分比）、农村人口数、农村人口占总人口百分比 |
| `indicator_code` | 字符串（object） | 0.0% | NV.AGR.TOTL.ZS、SP.RUR.TOTL、SP.RUR.TOTL.ZS |
| `value` | 64位浮点数（float64） | 0.0% | 0.1198 – 27043723857.2442（平均值：217526247.4179） |
| `esa_source` | 字符串（object） | 0.0% | HDX |
| `esa_processed` | 字符串（object） | 0.0% | 2026-04-09 |

---

## 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 | 2025.0 | 1994.5144 | 1996.0 |
| `value` | 0.1198 | 27043723857.2442 | 217526247.4179 | 69.1704 |

---

## 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）。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压缩格式的Parquet文件存储。

---

## 数据集局限性

- 数据源自世界银行集团，未经过电动绵羊非洲（Electric Sheep Africa）的独立验证。
- 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。
- 如需查看发布方提供的官方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/world-bank-agriculture-and-rural-development-indicators-for-kenya)。

---

## 引用格式

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

---

*[电动绵羊非洲（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。*