electricsheepafrica/africa-cpv-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
- hxl
- cpv
pretty_name: "Cape Verde - Requirements and Funding Data"
dataset_info:
splits:
- name: train
num_examples: 18
- name: test
num_examples: 4
---

# Cape Verde - Requirements and Funding Data

**Publisher:** OCHA Financial Tracking System (FTS) · **Source:** [HDX](https://data.humdata.org/dataset/cpv-requirements-and-funding-data) · **License:** `cc-by-igo` · **Updated:** 2025-12-31

---

## 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/), is encoded as utf-8 and the second row of the CSV contains [HXL](http://hxlstandard.org) tags.

Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2025-12-31. Geographic scope: **CPV**.

*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)** | 23 |
| **Columns** | 6 (2 numeric, 4 categorical, 0 datetime) |
| **Train split** | 18 rows |
| **Test split** | 4 rows |
| **Geographic scope** | CPV |
| **Publisher** | OCHA Financial Tracking System (FTS) |
| **HDX last updated** | 2025-12-31 |

---

## Variables

**Geographic** — `countrycode` (CPV, #country+code), `year` (range 2002.0–2025.0).

**Identifier / Metadata** — `name` (Not specified, #activity+appeal+name, West Africa 2007), `esa_source` (HDX), `esa_processed` (2026-04-08).

**Other** — `funding` (range 5334.0–4097899.0).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-cpv-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% | CPV, #country+code |
| `name` | object | 0.0% | Not specified, #activity+appeal+name, West Africa 2007 |
| `year` | float64 | 4.3% | 2002.0 – 2025.0 (mean 2013.4545) |
| `funding` | float64 | 8.7% | 5334.0 – 4097899.0 (mean 1071548.7619) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-08 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 2002.0 | 2025.0 | 2013.4545 | 2013.0 |
| `funding` | 5334.0 | 4097899.0 | 1071548.7619 | 653902.0 |

---

## 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`.... 2 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 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/cpv-requirements-and-funding-data) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_cpv_requirements_and_funding_data,
title = {Cape Verde - Requirements and Funding Data},
author = {OCHA Financial Tracking System (FTS)},
year = {2025},
url = {https://data.humdata.org/dataset/cpv-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:
- 采集自现有文本
language:
- 英语
license: CC-BY-4.0
multilinguality:
- 单语言
size_categories:
- 不足1000条
source_datasets:
- 原创数据集
task_categories:
- 表格分类
- 表格回归
task_ids: []
tags:
- 非洲
- 人道主义
- HDX（Humanitarian Data Exchange）
- electric-sheep-africa
- COVID-19
- 资金
- 人道主义财务跟踪服务（FTS）
- HXL（Humanitarian Exchange Language）
- CPV（佛得角）
pretty_name: "佛得角——需求与资金数据"
dataset_info:
splits:
- name: train
num_examples: 18
- name: test
num_examples: 4

# 佛得角——需求与资金数据
**发布方**：OCHA财务跟踪系统（OCHA Financial Tracking Service, FTS） · **来源**：[HDX（Humanitarian Data Exchange）](https://data.humdata.org/dataset/cpv-requirements-and-funding-data) · **许可协议**：`cc-by-igo` · **更新时间**：2025-12-31

---

## 摘要
OCHA财务跟踪系统（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。该数据集涵盖目标国家的全部人道主义资金，以及已明确上报或可与人道主义应对计划中列明的资金需求精准匹配的资金。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[财务跟踪服务（Financial Tracking Service, FTS）](https://fts.unocha.org/)，采用UTF-8编码，CSV文件的第二行包含[HXL（Humanitarian Exchange Language）](http://hxlstandard.org)标签。
本数据集中的每一行代表国家级汇总数据。数据最近一次在HDX平台更新的时间为2025-12-31。地理覆盖范围：**CPV（佛得角）**。
*本数据集由[Electric Sheep Africa](https://huggingface.co/electricsheepafrica)整理为可供机器学习使用的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** | 23 |
| **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** | 18条数据 |
| **测试集划分** | 4条数据 |
| **地理覆盖范围** | CPV（佛得角） |
| **发布方** | OCHA财务跟踪系统（FTS） |
| **HDX平台最后更新时间** | 2025-12-31 |

---

## 变量说明
**地理类** — `countrycode`（CPV，#country+code）、`year`（取值范围2002.0–2025.0）。
**标识符/元数据类** — `name`（未指定，#activity+appeal+name，例如西非2007）、`esa_source`（HDX）、`esa_processed`（2026-04-08）。
**其他类** — `funding`（取值范围5334.0–4097899.0）。

---

## 快速上手
python
from datasets import load_dataset

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

print(train.shape)
train.head()

---

## 数据Schema
| 列名 | 数据类型 | 空值占比 | 取值范围/示例值 |
|---|---|---|---|
| `countrycode` | 对象型（object） | 0.0% | CPV, #country+code |
| `name` | 对象型（object） | 0.0% | 未指定, #activity+appeal+name, 例如西非2007 |
| `year` | 浮点型（float64） | 4.3% | 2002.0 – 2025.0（均值为2013.4545） |
| `funding` | 浮点型（float64） | 8.7% | 5334.0 – 4097899.0（均值为1071548.7619） |
| `esa_source` | 对象型（object） | 0.0% | HDX |
| `esa_processed` | 对象型（object） | 0.0% | 2026-04-08 |

---

## 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 | 2025.0 | 2013.4545 | 2013.0 |
| `funding` | 5334.0 | 4097899.0 | 1071548.7619 | 653902.0 |

---

## 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。列名统一转换为小写并采用蛇形命名法（snake_case）进行标准化。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8个缺失值占比超过80%的列：`id`、`code`、`typeid`、`typename`、`startdate`、`enddate`……根据解析成功率（阈值为85%），将2列从字符串类型转换为数值型或日期时间型。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。

---

## 局限性说明
- 数据源自OCHA财务跟踪系统（FTS），未由Electric Sheep Africa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。
- 如需查看发布方提供的方法说明与免责声明，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/cpv-requirements-and-funding-data)。

---

## 引用格式
bibtex
@dataset{hdx_africa_cpv_requirements_and_funding_data,
title = {佛得角——需求与资金数据},
author = {OCHA财务跟踪系统（OCHA Financial Tracking Service, FTS）},
year = {2025},
url = {https://data.humdata.org/dataset/cpv-requirements-and-funding-data},
note = {由Electric Sheep Africa（https://huggingface.co/electricsheepafrica）重新打包以适配机器学习使用}
}

---

*[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。*