electricsheepafrica/africa-swz-requirements-and-funding-data

---
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
- covid-19
- funding
- humanitarian-financial-tracking-service-fts
- swz
pretty_name: "Eswatini - Requirements and Funding Data"
dataset_info:
splits:
- name: train
num_examples: 21
- name: test
num_examples: 5
---

# Eswatini - Requirements and Funding Data

**Publisher:** OCHA Financial Tracking System (FTS) · **Source:** [HDX](https://data.humdata.org/dataset/swz-requirements-and-funding-data) · **License:** `cc-by-igo` · **Updated:** 2026-04-06

---

## Abstract

FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's [Financial Tracking Service](https://fts.unocha.org/) and is encoded as utf-8.

Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-04-06. Geographic scope: **SWZ**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Humanitarian and development data |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 27 |
| **Columns** | 6 (2 numeric, 4 categorical, 0 datetime) |
| **Train split** | 21 rows |
| **Test split** | 5 rows |
| **Geographic scope** | SWZ |
| **Publisher** | OCHA Financial Tracking System (FTS) |
| **HDX last updated** | 2026-04-06 |

---

## Variables

**Geographic** — `countrycode` (SWZ), `year` (range 2002.0–2026.0).

**Identifier / Metadata** — `name` (Not specified, Swaziland Drought Flash Appeal 2007, Humanitarian Crisis in Southern Africa - SWAZILAND (July 2003 - June 2004)), `esa_source` (HDX), `esa_processed` (2026-04-06).

**Other** — `funding` (range 20000.0–20772118.0).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-swz-requirements-and-funding-data")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `countrycode` | object | 0.0% | SWZ |
| `name` | object | 0.0% | Not specified, Swaziland Drought Flash Appeal 2007, Humanitarian Crisis in Southern Africa - SWAZILAND (July 2003 - June 2004) |
| `year` | int64 | 0.0% | 2002.0 – 2026.0 (mean 2012.963) |
| `funding` | int64 | 0.0% | 20000.0 – 20772118.0 (mean 4614191.0741) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-06 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 2002.0 | 2026.0 | 2012.963 | 2013.0 |
| `funding` | 20000.0 | 20772118.0 | 4614191.0741 | 2694140.0 |

---

## 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`. 8 column(s) with >80% missing values were removed: `id`, `code`, `typeid`, `typename`, `startdate`, `enddate`.... 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 Financial Tracking System (FTS) 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/swz-requirements-and-funding-data) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_swz_requirements_and_funding_data,
title = {Eswatini - Requirements and Funding Data},
author = {OCHA Financial Tracking System (FTS)},
year = {2026},
url = {https://data.humdata.org/dataset/swz-requirements-and-funding-data},
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:
- 现有采集
language:
- 英语
license: 知识共享署名4.0（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）
- 电羊非洲（Electric Sheep Africa）
- 新型冠状病毒肺炎（COVID-19）
- 资金
- 人道主义资金跟踪服务（FTS）
- SWZ（埃斯瓦蒂尼）
pretty_name: "埃斯瓦蒂尼——需求与资金数据"
dataset_info:
splits:
- name: 训练集
num_examples: 21
- name: 测试集
num_examples: 5
---

# 埃斯瓦蒂尼——需求与资金数据

**发布方：** 联合国人道主义事务协调厅（Office for the Coordination of Humanitarian Affairs, OCHA）资金跟踪系统（FTS） · **来源：** [HDX（人道主义数据交换平台）](https://data.humdata.org/dataset/swz-requirements-and-funding-data) · **许可协议：** `cc-by-igo` · **最后更新：** 2026-04-06

---

## 摘要

FTS发布由捐赠方与受援组织上报的人道主义资金流动数据，涵盖某一国的全部人道主义资金，以及已明确上报或可对应到人道主义应对计划中列明的资金需求的专项资金。本数据集数据源自联合国人道主义事务协调厅（Office for the Coordination of Humanitarian Affairs, OCHA）的[资金跟踪服务（Financial Tracking Service, FTS）](https://fts.unocha.org/)，编码格式为UTF-8。

本数据集每一行代表国家级汇总数据。数据最后一次在HDX平台更新的时间为2026年4月6日。地理覆盖范围：**SWZ（埃斯瓦蒂尼）**。

*本数据集已由[电羊非洲（Electric Sheep Africa）](https://huggingface.co/electricsheepafrica)整理为可直接用于机器学习的Parquet格式。*

---

## 数据集特征

| | |
|---|---|
| **领域** | 人道主义与发展数据 |
| **观测单元** | 国家级汇总数据 |
| **总行数** | 27 |
| **列数** | 6（2个数值型，4个分类型，0个日期时间型） |
| **训练集划分** | 21行 |
| **测试集划分** | 5行 |
| **地理覆盖范围** | SWZ |
| **发布方** | 联合国人道主义事务协调厅（Office for the Coordination of Humanitarian Affairs, OCHA）资金跟踪系统（FTS） |
| **HDX平台最后更新时间** | 2026-04-06 |

---

## 变量说明

**地理类变量** — `countrycode`（国家代码，取值为SWZ）、`year`（年份，取值范围2002.0–2026.0）。
**标识符与元数据类变量** — `name`（名称，示例值：未指定、2007年斯威士兰干旱紧急呼吁、南部非洲人道主义危机——斯威士兰（2003年7月-2004年6月））、`esa_source`（数据来源，取值为HDX）、`esa_processed`（数据处理时间，取值为2026-04-06）。
**其他类变量** — `funding`（资金额，取值范围20000.0–20772118.0）。

---

## 快速上手

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-swz-requirements-and-funding-data")
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 | 缺失率 | 取值范围/示例值 |
|---|---|---|---|
| `countrycode` | 字符串型（object） | 0.0% | SWZ |
| `name` | 字符串型（object） | 0.0% | 未指定、2007年斯威士兰干旱紧急呼吁、南部非洲人道主义危机——斯威士兰（2003年7月-2004年6月） |
| `year` | 整型（int64） | 0.0% | 2002.0 – 2026.0（均值为2012.963） |
| `funding` | 整型（int64） | 0.0% | 20000.0 – 20772118.0（均值为4614191.0741） |
| `esa_source` | 字符串型（object） | 0.0% | HDX |
| `esa_processed` | 字符串型（object） | 0.0% | 2026-04-06 |

---

## 数值型变量统计摘要

| 列名 | 最小值 | 最大值 | 均值 | 中位数 |
|---|---|---|---|---|
| `year` | 2002.0 | 2026.0 | 2012.963 | 2013.0 |
| `funding` | 20000.0 | 20772118.0 | 4614191.0741 | 2694140.0 |

---

## 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。列名统一转为小写并采用蛇形命名法（snake_case）进行标准化。将常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。删除了8列缺失率超过80%的字段：`id`、`code`、`typeid`、`typename`、`startdate`、`enddate`……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，并保存为采用Snappy压缩的Parquet格式文件。

---

## 数据集局限性

- 本数据集数据源自联合国人道主义事务协调厅（Office for the Coordination of Humanitarian Affairs, OCHA）资金跟踪系统（FTS），未经过电羊非洲（ESA）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。
- 如需了解发布方的方法论说明与免责声明，请参阅[HDX原始数据集页面](https://data.humdata.org/dataset/swz-requirements-and-funding-data)。

---

## 引用格式

bibtex
@dataset{hdx_africa_swz_requirements_and_funding_data,
title = {Eswatini - Requirements and Funding Data},
author = {OCHA Financial Tracking System (FTS)},
year = {2026},
url = {https://data.humdata.org/dataset/swz-requirements-and-funding-data},
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。*