electricsheepafrica/africa-kenya-gcf-funded-activities

---
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
- climate-weather
- funding
- ken
pretty_name: "Kenya - GCF Funded Activities"
dataset_info:
splits:
- name: train
num_examples: 20
- name: test
num_examples: 5
---

# Kenya - GCF Funded Activities

**Publisher:** Green Climate Fund · **Source:** [HDX](https://data.humdata.org/dataset/kenya-gcf-funded-activities) · **License:** `cc-by` · **Updated:** 2026-02-12

---

## Abstract

This dataset provides a list of climate funded activities showing the modality, project, name of entity, countries funded, the sector, theme, project size, ESS Category and FA financing.

Each row in this dataset represents country-level aggregates. Temporal coverage is indicated by the `approval_date`, `completion_date` column(s). Geographic scope: **KEN**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Climate and environment |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 25 |
| **Columns** | 20 (1 numeric, 17 categorical, 2 datetime) |
| **Train split** | 20 rows |
| **Test split** | 5 rows |
| **Geographic scope** | KEN |
| **Publisher** | Green Climate Fund |
| **HDX last updated** | 2026-02-12 |

---

## Variables

**Geographic** — `modality` (FP), `entity` (Acumen, IUCN, IFAD), `country_codes` (KEN, KEN, RWA, TZA, UGA, KEN, RWA), `ess_category`.

**Temporal** — `approval_date`, `completion_date`.

**Outcome / Measurement** — `countries` (Kenya, Kenya, Rwanda, Tanzania, Uganda, Kenya, Rwanda).

**Identifier / Metadata** — `ref` (FP005, FP177, FP276), `project_name` (KawiSafi Ventures Fund, Cooling Facility, GCF's investment into the Global Green Bond Initiative (GGBI) (previously known as Green and Resilience Debt Platform (GRDP)), `esa_source`, `esa_processed`.

**Other** — `board_meeting` (B.27, B.30, B.42), `sector` (Private, Public), `theme` (Cross-cutting, Mitigation, Adaptation), `project_size` (Large, Medium, Micro), `fa_financing` (range 9526603.26–287425149.7) and 4 others.

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-kenya-gcf-funded-activities")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `ref` | object | 0.0% | FP005, FP177, FP276 |
| `modality` | object | 0.0% | FP |
| `project_name` | object | 0.0% | KawiSafi Ventures Fund, Cooling Facility, GCF's investment into the Global Green Bond Initiative (GGBI) (previously known as Green and Resilience Debt Platform (GRDP) |
| `entity` | object | 0.0% | Acumen, IUCN, IFAD |
| `countries` | object | 0.0% | Kenya, Kenya, Rwanda, Tanzania, Uganda, Kenya, Rwanda |
| `country_codes` | object | 0.0% | KEN, KEN, RWA, TZA, UGA, KEN, RWA |
| `board_meeting` | object | 0.0% | B.27, B.30, B.42 |
| `sector` | object | 0.0% | Private, Public |
| `theme` | object | 0.0% | Cross-cutting, Mitigation, Adaptation |
| `project_size` | object | 0.0% | Large, Medium, Micro |
| `approval_date` | datetime64[ns] | 0.0% | |
| `completion_date` | datetime64[ns] | 24.0% | |
| `ess_category` | object | 0.0% | |
| `fa_financing` | float64 | 0.0% | 9526603.26 – 287425149.7 (mean 109902359.032) |
| `result_areas` | object | 0.0% | |
| `status` | object | 0.0% | |
| `project_url` | object | 0.0% | |
| `api_url` | object | 0.0% | |
| `esa_source` | object | 0.0% | |
| `esa_processed` | object | 0.0% | |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `fa_financing` | 9526603.26 | 287425149.7 | 109902359.032 | 80000000.0 |

---

## 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`. 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 Green Climate Fund and has not been independently validated by ESA.
- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
- The following columns have >20% missing values and should be treated with caution in modelling: `completion_date`.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/kenya-gcf-funded-activities) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_kenya_gcf_funded_activities,
title = {Kenya - GCF Funded Activities},
author = {Green Climate Fund},
year = {2026},
url = {https://data.humdata.org/dataset/kenya-gcf-funded-activities},
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:
- 现有文本采集
language:
- 英语
license: CC-BY 4.0
multilinguality:
- 单语言
size_categories:
- 样本量小于1000
source_datasets:
- 原创数据集
task_categories:
- 表格分类任务
- 表格回归任务
task_ids: []
tags:
- 非洲
- 人道主义
- 人道主义数据交换（HDX）
- 电动绵羊非洲（Electric Sheep Africa）
- 气候与天气
- 资助
- 肯尼亚（KEN）
pretty_name: "肯尼亚——绿色气候基金（Green Climate Fund）资助项目"
dataset_info:
splits:
- name: train
num_examples: 20
- name: test
num_examples: 5
---

# 肯尼亚——绿色气候基金资助项目

**发布方：绿色气候基金（Green Climate Fund） · **数据源：[人道主义数据交换（HDX）](https://data.humdata.org/dataset/kenya-gcf-funded-activities) · **许可证：`cc-by` · **更新时间：2026-02-12**

---

## 摘要

本数据集收录气候资助项目清单，涵盖资助模式、项目信息、实施实体名称、受资助国家、所属领域、主题、项目规模、环境与社会保障（ESS）类别以及融资额度等信息。

本数据集每一行均代表国家层面的汇总统计数据。时间覆盖范围由`approval_date`（批准日期）、`completion_date`（竣工日期）两列标注。地理范围：**肯尼亚（KEN）**。

*本数据集已由[电动绵羊非洲（Electric Sheep Africa）](https://huggingface.co/electricsheepafrica)整理为适配机器学习的Parquet格式文件。*

---

## 数据集特征

| | |
|---|---|
| **领域** | 气候与环境 |
| **观测单元** | 国家层面汇总统计数据 |
| **总行数** | 25 |
| **列数** | 20（1个数值型列、17个分类列、2个日期时间列） |
| **训练集划分** | 20条数据 |
| **测试集划分** | 5条数据 |
| **地理范围** | 肯尼亚（KEN） |
| **发布方** | 绿色气候基金（Green Climate Fund） |
| **HDX最后更新时间** | 2026-02-12 |

---

## 变量分类

**地理类变量** — `modality`（资助模式，FP）、`entity`（实施实体，如阿卡门（Acumen）、世界自然保护联盟（IUCN）、国际农业发展基金（IFAD））、`country_codes`（国家代码，如KEN、RWA、TZA、UGA）、`ess_category`（环境与社会保障类别）。
**时间类变量** — `approval_date`（批准日期）、`completion_date`（竣工日期）。
**结果/测量类变量** — `countries`（受资助国家，如肯尼亚、卢旺达、坦桑尼亚、乌干达）。
**标识符/元数据类变量** — `ref`（项目编号，如FP005、FP177、FP276）、`project_name`（项目名称，如KawiSafi Ventures Fund、冷却设施、绿色气候基金对全球绿色债券倡议（Global Green Bond Initiative, GGBI，前身为绿色与韧性债务平台（Green and Resilience Debt Platform, GRDP））的投资）、`esa_source`、`esa_processed`。
**其他变量** — `board_meeting`（董事会会议编号，如B.27、B.30、B.42）、`sector`（领域类型，如私营、公共）、`theme`（主题，如跨领域、减缓、适应）、`project_size`（项目规模，如大型、中型、微型）、`fa_financing`（融资金额，范围为9526603.26–287425149.7）以及另外4个变量。

---

## 快速上手

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-kenya-gcf-funded-activities")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

print(train.shape)
train.head()

---

## 数据架构

| 列名 | 数据类型 | 缺失率 | 取值范围/示例值 |
|---|---|---|---|
| `ref` | 字符串（object） | 0.0% | FP005、FP177、FP276 |
| `modality` | 字符串（object） | 0.0% | FP |
| `project_name` | 字符串（object） | 0.0% | KawiSafi Ventures Fund、冷却设施、绿色气候基金对全球绿色债券倡议（GGBI，前身为绿色与韧性债务平台（GRDP））的投资 |
| `entity` | 字符串（object） | 0.0% | 阿卡门（Acumen）、世界自然保护联盟（IUCN）、国际农业发展基金（IFAD） |
| `countries` | 字符串（object） | 0.0% | 肯尼亚、卢旺达、坦桑尼亚、乌干达 |
| `country_codes` | 字符串（object） | 0.0% | KEN、RWA、TZA、UGA |
| `board_meeting` | 字符串（object） | 0.0% | B.27、B.30、B.42 |
| `sector` | 字符串（object） | 0.0% | 私营、公共 |
| `theme` | 字符串（object） | 0.0% | 跨领域、减缓、适应 |
| `project_size` | 字符串（object） | 0.0% | 大型、中型、微型 |
| `approval_date` | datetime64[ns] | 0.0% | 无示例 |
| `completion_date` | datetime64[ns] | 24.0% | 无示例 |
| `ess_category` | 字符串（object） | 0.0% | 无示例 |
| `fa_financing` | float64 | 0.0% | 9526603.26 – 287425149.7（均值为109902359.032） |
| `result_areas` | 字符串（object） | 0.0% | 无示例 |
| `status` | 字符串（object） | 0.0% | 无示例 |
| `project_url` | 字符串（object） | 0.0% | 无示例 |
| `api_url` | 字符串（object） | 0.0% | 无示例 |
| `esa_source` | 字符串（object） | 0.0% | 无示例 |
| `esa_processed` | 字符串（object） | 0.0% | 无示例 |

---

## 数值型变量统计摘要

| 列名 | 最小值 | 最大值 | 均值 | 中位数 |
|---|---|---|---|---|
| `fa_financing` | 9526603.26 | 287425149.7 | 109902359.032 | 80000000.0 |

---

## 数据整理流程

原始数据通过CKAN API从HDX下载，并转换为Parquet格式。所有列名均转换为小写格式，并统一采用蛇形命名法（snake_case）进行规范。将常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。基于解析成功率（阈值>85%），将2列从字符串类型转换为数值型或日期时间类型。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，并以Snappy压缩格式保存为Parquet文件。

---

## 数据集局限性

- 数据源自绿色气候基金，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。
- 以下列缺失率超过20%，在建模过程中需谨慎使用：`completion_date`（竣工日期）。
- 请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/kenya-gcf-funded-activities)查看发布方提供的方法说明与注意事项。

---

## 引用格式

bibtex
@dataset{hdx_africa_kenya_gcf_funded_activities,
title = {肯尼亚——绿色气候基金资助项目},
author = {绿色气候基金（Green Climate Fund)},
year = {2026},
url = {https://data.humdata.org/dataset/kenya-gcf-funded-activities},
note = {由电动绵羊非洲（Electric Sheep Africa）重新打包以适配机器学习场景 (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提供商。尼日利亚拉各斯。*