electricsheepafrica/africa-world-bank-environment-indicators-for-guinea

---
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-classification
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- environment
- indicators
- gin
pretty_name: "Guinea - Environment"
dataset_info:
splits:
- name: train
num_examples: 3644
- name: test
num_examples: 911
---

# Guinea - Environment

**Publisher:** World Bank Group · **Source:** [HDX](https://data.humdata.org/dataset/world-bank-environment-indicators-for-guinea) · **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-guinea) on HDX.

Natural and man-made environmental resources – fresh water, clean air, forests, grasslands, marine resources, and agro-ecosystems – provide sustenance and a foundation for social and economic development. The need to safeguard these resources crosses all borders. Today, the World Bank is one of the key promoters and financiers of environmental upgrading in the developing world. Data here cover forests, biodiversity, emissions, and pollution. Other indicators relevant to the environment are found under data pages for Agriculture & Rural Development, Energy & Mining, Infrastructure, and Urban Development.

Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-03-27. Geographic scope: **GIN**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Water, sanitation and hygiene (wash) |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 4,555 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 3,644 rows |
| **Test split** | 911 rows |
| **Geographic scope** | GIN |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

**Geographic** — `country_name` (Guinea), `country_iso3` (GIN), `year` (range 1960.0–2024.0).

**Outcome / Measurement** — `value` (range -2315136539.9555–1772473946.3116).

**Identifier / Metadata** — `indicator_name` (Total fisheries production (metric tons), Capture fisheries production (metric tons), Aquaculture production (metric tons)), `indicator_code` (ER.FSH.PROD.MT, ER.FSH.CAPT.MT, ER.FSH.AQUA.MT), `esa_source` (HDX), `esa_processed` (2026-04-09).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-environment-indicators-for-guinea")
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% | Guinea |
| `country_iso3` | object | 0.0% | GIN |
| `year` | int64 | 0.0% | 1960.0 – 2024.0 (mean 2001.1717) |
| `indicator_name` | object | 0.0% | Total fisheries production (metric tons), Capture fisheries production (metric tons), Aquaculture production (metric tons) |
| `indicator_code` | object | 0.0% | ER.FSH.PROD.MT, ER.FSH.CAPT.MT, ER.FSH.AQUA.MT |
| `value` | float64 | 0.0% | -2315136539.9555 – 1772473946.3116 (mean 1199541.3247) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-09 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1960.0 | 2024.0 | 2001.1717 | 2003.0 |
| `value` | -2315136539.9555 | 1772473946.3116 | 1199541.3247 | 2.2434 |

---

## 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-environment-indicators-for-guinea) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_environment_indicators_for_guinea,
title = {Guinea - Environment},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-environment-indicators-for-guinea},
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.*

注释创建者：
- 无注释
语言创建方式：
- 发现式
语言：
- 英语
许可证：
- CC BY 4.0
多语言属性：
- 单语言
数据规模：
- 1000 < 样本量 < 10000
源数据集：
- 原创数据集
任务类别：
- 表格分类
- 表格回归
任务子项：
- 无
标签：
- 非洲
- 人道主义
- HDX
- Electric Sheep Africa
- 环境
- 指标
- GIN
展示名称："几内亚 - 环境"
数据集信息：
数据划分：
- 训练集：3644条样本
- 测试集：911条样本

# 几内亚 - 环境

**发布方**：世界银行集团 · **数据源**：[HDX](https://data.humdata.org/dataset/world-bank-environment-indicators-for-guinea) · **许可证**：`CC-BY` · **更新时间**：2026-03-27

---

## 摘要
本数据集数据源自世界银行[官方数据门户](http://data.worldbank.org/)。HDX平台上还提供了[整合版国家数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-guinea)。

自然与人工环境资源——淡水、洁净空气、森林、草原、海洋资源以及农业生态系统——为社会与经济发展提供支撑与根基。保护此类资源的需求无国界。如今，世界银行是发展中地区环境升级的核心推动者与融资方之一。本数据集涵盖森林、生物多样性、碳排放与污染相关数据。其他与环境相关的指标可在农业与农村发展、能源与矿业、基础设施以及城市发展的数据页面中获取。

本数据集的每一行均代表国家级汇总数据。数据最后于2026-03-27在HDX平台更新。地理覆盖范围：**GIN**。

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

---

## 数据集特征

| | |
|---|---|
| **领域** | 水、环境卫生与个人卫生（WASH） |
| **观测单元** | 国家级汇总数据 |
| **总样本行数** | 4555 |
| **列数** | 8列（2个数值列，6个分类列，0个日期时间列） |
| **训练集划分** | 3644行 |
| **测试集划分** | 911行 |
| **地理覆盖范围** | GIN |
| **发布方** | 世界银行集团 |
| **HDX最后更新时间** | 2026-03-27 |

---

## 变量说明

**地理类变量** — `country_name`（国家名称：几内亚）、`country_iso3`（国家ISO3代码：GIN）、`year`（年份：范围1960.0–2024.0）。

**结果/测量类变量** — `value`（指标数值：范围-2315136539.9555–1772473946.3116）。

**标识符/元数据类变量** — `indicator_name`（指标名称：渔业总产量（公吨）、捕捞渔业产量（公吨）、水产养殖产量（公吨））、`indicator_code`（指标代码：ER.FSH.PROD.MT、ER.FSH.CAPT.MT、ER.FSH.AQUA.MT）、`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-world-bank-environment-indicators-for-guinea")
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 | 空值占比 | 取值范围/示例值 |
|---|---|---|---|
| `country_name` | 字符串 | 0.0% | 几内亚 |
| `country_iso3` | 字符串 | 0.0% | GIN |
| `year` | 整数型 | 0.0% | 1960.0 – 2024.0（均值2001.1717） |
| `indicator_name` | 字符串 | 0.0% | 渔业总产量（公吨）、捕捞渔业产量（公吨）、水产养殖产量（公吨） |
| `indicator_code` | 字符串 | 0.0% | ER.FSH.PROD.MT、ER.FSH.CAPT.MT、ER.FSH.AQUA.MT |
| `value` | 浮点型 | 0.0% | -2315136539.9555 – 1772473946.3116（均值1199541.3247） |
| `esa_source` | 字符串 | 0.0% | HDX |
| `esa_processed` | 字符串 | 0.0% | 2026-04-09 |

---

## 数值型变量统计摘要

| 列名 | 最小值 | 最大值 | 均值 | 中位数 |
|---|---|---|---|---|
| `year` | 1960.0 | 2024.0 | 2001.1717 | 2003.0 |
| `value` | -2315136539.9555 | 1772473946.3116 | 1199541.3247 | 2.2434 |

---

## 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。常见的缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）均被统一替换为`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压缩的Parquet格式存储。

---

## 数据集局限性
- 数据源自世界银行集团，尚未由Electric Sheep Africa（ESA）进行独立验证。
- 自动化清洗流程无法修正原始数据集中的错报值、定义不一致问题或采样偏差。
- 有关发布方的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-environment-indicators-for-guinea)。

---

## 引用格式
bibtex
@dataset{hdx_africa_world_bank_environment_indicators_for_guinea,
title = {Guinea - Environment},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-environment-indicators-for-guinea},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

---

*[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。*