electricsheepafrica/africa-kenya-pin-targeted-reached-by-location-and-cluster

---
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
- affected-population
- drought
- hxl
- people-in-need-pin
- ken
pretty_name: "Kenya Drought Related - People Affected, Targeted & Reached by Location"
dataset_info:
splits:
- name: train
num_examples: 20
- name: test
num_examples: 5
---

# Kenya Drought Related - People Affected, Targeted & Reached by Location

**Publisher:** OCHA Regional Office for Southern and Eastern Africa (ROSEA) · **Source:** [HDX](https://data.humdata.org/dataset/kenya-pin-targeted-reached-by-location-and-cluster) · **License:** `cc-by` · **Updated:** 2025-10-28

---

## Abstract

Drought affected areas and population in Kenya

Each row in this dataset represents tabular records. Data was last updated on HDX on 2025-10-28. Geographic scope: **KEN**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Natural hazards and disaster risk |
| **Unit of observation** | Tabular records |
| **Rows (total)** | 25 |
| **Columns** | 8 (4 numeric, 4 categorical, 0 datetime) |
| **Train split** | 20 rows |
| **Test split** | 5 rows |
| **Geographic scope** | KEN |
| **Publisher** | OCHA Regional Office for Southern and Eastern Africa (ROSEA) |
| **HDX last updated** | 2025-10-28 |

---

## Variables

**Geographic** — `location` (County, Mandera, Wajir), `operational_priority` (range 1.0–2.0).

**Outcome / Measurement** — `overall_affected` (range 0.0–1012168.0).

**Identifier / Metadata** — `unnamed_1` (admin1Pcode, KE009, KE008), `unnamed_4` (range 0.0–843624.0), `unnamed_5` (range 2463.0–515967.0), `esa_source` (HDX), `esa_processed` (2026-04-09).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-kenya-pin-targeted-reached-by-location-and-cluster")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `location` | object | 0.0% | County, Mandera, Wajir |
| `unnamed_1` | object | 0.0% | admin1Pcode, KE009, KE008 |
| `operational_priority` | float64 | 8.0% | 1.0 – 2.0 (mean 1.6522) |
| `overall_affected` | float64 | 8.0% | 0.0 – 1012168.0 (mean 276812.1739) |
| `unnamed_4` | float64 | 8.0% | 0.0 – 843624.0 (mean 185279.8261) |
| `unnamed_5` | float64 | 8.0% | 2463.0 – 515967.0 (mean 76666.5652) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-09 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `operational_priority` | 1.0 | 2.0 | 1.6522 | 2.0 |
| `overall_affected` | 0.0 | 1012168.0 | 276812.1739 | 170680.0 |
| `unnamed_4` | 0.0 | 843624.0 | 185279.8261 | 106116.0 |
| `unnamed_5` | 2463.0 | 515967.0 | 76666.5652 | 23478.0 |

---

## 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`. 4 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 OCHA Regional Office for Southern and Eastern Africa (ROSEA) 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/kenya-pin-targeted-reached-by-location-and-cluster) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_kenya_pin_targeted_reached_by_location_and_cluster,
title = {Kenya Drought Related - People Affected, Targeted & Reached by Location},
author = {OCHA Regional Office for Southern and Eastern Africa (ROSEA)},
year = {2025},
url = {https://data.humdata.org/dataset/kenya-pin-targeted-reached-by-location-and-cluster},
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:
- 现有资源获取
language:
- 英语
license:
- CC BY 4.0（知识共享署名4.0协议）
multilinguality:
- 单语言
size_categories:
- n<1K（样本量不足1000）
source_datasets:
- 原创数据集
task_categories:
- 表格分类
- 其他
task_ids: []
tags:
- 非洲
- 人道主义
- HDX
- Electric Sheep Africa
- 受影响人口
- 干旱
- HXL
- 有需求人口（People in Need, PIN）
- 肯尼亚（KEN）
pretty_name: "肯尼亚干旱相关——按地区划分的受影响、目标覆盖及已惠及人口"
dataset_info:
splits:
- name: train
num_examples: 20
- name: test
num_examples: 5

# 肯尼亚干旱相关——按地区划分的受影响、目标覆盖及已惠及人口

**发布方**：联合国人道主义事务协调厅（Office for the Coordination of Humanitarian Affairs, OCHA）南部与东部非洲区域办事处（ROSEA） · **来源**：[人道主义数据交换平台（Humanitarian Data Exchange, HDX）](https://data.humdata.org/dataset/kenya-pin-targeted-reached-by-location-and-cluster) · **授权协议**：`CC BY 4.0` · **更新时间**：2025-10-28

---

## 摘要
本数据集涵盖肯尼亚干旱受影响地区及受影响人口。
数据集中每一行均代表一条表格记录。该数据最后一次在人道主义数据交换平台（Humanitarian Data Exchange, HDX）更新时间为2025-10-28。地理覆盖范围：**肯尼亚（KEN）**。
*本数据集已由[Electric Sheep Africa](https://huggingface.co/electricsheepafrica)整理为可供机器学习直接使用的Parquet格式。*

---

## 数据集特征
| | |
|---|---|
| **领域** | 自然灾害与灾害风险 |
| **观测单元** | 表格记录 |
| **总数据行数** | 25 |
| **列数** | 8（4个数值型、4个分类型、0个日期时间型） |
| **训练集拆分样本量** | 20 |
| **测试集拆分样本量** | 5 |
| **地理覆盖范围** | 肯尼亚（KEN） |
| **发布方** | 联合国人道主义事务协调厅南部与东部非洲区域办事处（OCHA ROSEA） |
| **HDX最后更新时间** | 2025-10-28 |

---

## 变量说明
**地理类变量**：`location`（地区：县、曼德拉郡、瓦吉尔郡）、`operational_priority`（业务优先级，取值范围1.0–2.0）。
**结果/测量类变量**：`overall_affected`（总受影响人口，取值范围0.0–1012168.0）。
**标识符/元数据类变量**：`unnamed_1`（行政1级编码，admin1Pcode、KE009、KE008）、`unnamed_4`（取值范围0.0–843624.0）、`unnamed_5`（取值范围2463.0–515967.0）、`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-kenya-pin-targeted-reached-by-location-and-cluster")
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 | 缺失率 | 取值范围/示例值 |
|---|---|---|---|
| `location` | 字符串型（object） | 0.0% | 县、曼德拉郡、瓦吉尔郡 |
| `unnamed_1` | 字符串型（object） | 0.0% | admin1Pcode、KE009、KE008 |
| `operational_priority` | 浮点型（float64） | 8.0% | 1.0 – 2.0（均值1.6522） |
| `overall_affected` | 浮点型（float64） | 8.0% | 0.0 – 1012168.0（均值276812.1739） |
| `unnamed_4` | 浮点型（float64） | 8.0% | 0.0 – 843624.0（均值185279.8261） |
| `unnamed_5` | 浮点型（float64） | 8.0% | 2463.0 – 515967.0（均值76666.5652） |
| `esa_source` | 字符串型（object） | 0.0% | HDX |
| `esa_processed` | 字符串型（object） | 0.0% | 2026-04-09 |

---

## 数值型变量统计
| 列名 | 最小值 | 最大值 | 均值 | 中位数 |
|---|---|---|---|---|
| `operational_priority` | 1.0 | 2.0 | 1.6522 | 2.0 |
| `overall_affected` | 0.0 | 1012168.0 | 276812.1739 | 170680.0 |
| `unnamed_4` | 0.0 | 843624.0 | 185279.8261 | 106116.0 |
| `unnamed_5` | 2463.0 | 515967.0 | 76666.5652 | 23478.0 |

---

## 数据整理流程
原始数据通过CKAN API从人道主义数据交换平台（Humanitarian Data Exchange, HDX）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。常见缺失值标记（`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4列从字符串类型转换为数值型或日期时间型。本数据集采用固定随机种子（42）按80/20比例划分为训练集与测试集，并保存为Snappy压缩的Parquet格式。

---

## 局限性说明
- 数据源自联合国人道主义事务协调厅南部与东部非洲区域办事处（OCHA ROSEA），并未经Electric Sheep Africa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方法论说明与免责条款，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/kenya-pin-targeted-reached-by-location-and-cluster)。

---

## 引用格式
bibtex
@dataset{hdx_africa_kenya_pin_targeted_reached_by_location_and_cluster,
title = {Kenya Drought Related - People Affected, Targeted & Reached by Location},
author = {OCHA Regional Office for Southern and Eastern Africa (ROSEA)},
year = {2025},
url = {https://data.humdata.org/dataset/kenya-pin-targeted-reached-by-location-and-cluster},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

---

*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — 非洲的机器学习数据集基础设施。尼日利亚拉各斯。*