electricsheepafrica/africa-unesco-data-for-burkina-faso

---
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
- demographics
- education
- indicators
- socioeconomics
- sustainable-development
- sustainable-development-goals-sdg
- bfa
pretty_name: "Burkina Faso - Education Indicators"
dataset_info:
splits:
- name: train
num_examples: 7008
- name: test
num_examples: 1752
---

# Burkina Faso - Education Indicators

**Publisher:** UNESCO · **Source:** [HDX](https://data.humdata.org/dataset/unesco-data-for-burkina-faso) · **License:** `cc-by-igo` · **Updated:** 2026-03-02

---

## Abstract

Education indicators for Burkina Faso.

Contains data from the UNESCO Institute for Statistics [bulk data service](http://data.uis.unesco.org) covering the following categories: SDG 4 Global and Thematic (made 2026 February), Other Policy Relevant Indicators (made 2026 February), Demographic and Socio-economic (made 2026 February)

Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-03-02. Geographic scope: **BFA**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Education |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 8,760 |
| **Columns** | 6 (2 numeric, 4 categorical, 0 datetime) |
| **Train split** | 7,008 rows |
| **Test split** | 1,752 rows |
| **Geographic scope** | BFA |
| **Publisher** | UNESCO |
| **HDX last updated** | 2026-03-02 |

---

## Variables

**Geographic** — `country_id` (BFA), `year` (range 1971.0–2025.0).

**Outcome / Measurement** — `value` (range 0.0–9682882.0).

**Identifier / Metadata** — `indicator_id` (GER.5T8, AIR.1.GLAST.M, AIR.1.GLAST.F), `esa_source` (HDX), `esa_processed` (2026-04-04).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-unesco-data-for-burkina-faso")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `indicator_id` | object | 0.0% | GER.5T8, AIR.1.GLAST.M, AIR.1.GLAST.F |
| `country_id` | object | 0.0% | BFA |
| `year` | int64 | 0.0% | 1971.0 – 2025.0 (mean 2011.7177) |
| `value` | float64 | 0.0% | 0.0 – 9682882.0 (mean 6790.2755) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-04 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1971.0 | 2025.0 | 2011.7177 | 2014.0 |
| `value` | 0.0 | 9682882.0 | 6790.2755 | 8.6192 |

---

## 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) with >80% missing values were removed: `magnitude`, `qualifier`. 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 UNESCO 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/unesco-data-for-burkina-faso) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_unesco_data_for_burkina_faso,
title = {Burkina Faso - Education Indicators},
author = {UNESCO},
year = {2026},
url = {https://data.humdata.org/dataset/unesco-data-for-burkina-faso},
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：爬取获取
语言：英语
许可协议：CC BY 4.0
多语言类型：单语言
数据规模：1000 < 样本数 < 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（人道主义数据交换平台）、Electric Sheep Africa、人口统计学、教育、指标、社会经济、可持续发展、可持续发展目标（Sustainable Development Goals，SDG）、布基纳法索（BFA）
友好名称："布基纳法索 - 教育指标"
数据集信息:
拆分:
- 名称: 训练集, 样本数: 7008
- 名称: 测试集, 样本数: 1752
---
# 布基纳法索 - 教育指标数据集

**发布方：联合国教科文组织（UNESCO） · 数据源：** [HDX](https://data.humdata.org/dataset/unesco-data-for-burkina-faso) · **许可协议：** `cc-by-igo` · **更新时间：** 2026-03-02

---

## 摘要
本数据集收录布基纳法索的教育指标数据。数据源自联合国教科文组织统计研究所[批量数据服务](http://data.uis.unesco.org)，涵盖以下类别：可持续发展目标4（SDG 4）全球与主题指标（2026年2月更新）、其他政策相关指标（2026年2月更新）、人口与社会经济指标（2026年2月更新）。本数据集的每一行均代表国家级汇总数据。数据最后于HDX平台更新于2026年3月2日。地理覆盖范围：**布基纳法索（BFA）**。*本数据集经[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
| 项目 | 详情 |
|---|---|
| **领域** | 教育 |
| **观测单元** | 国家级汇总数据 |
| **总行数** | 8760 |
| **列数** | 6列（2列数值型、4列分类型、0列日期型） |
| **训练集拆分** | 7008行 |
| **测试集拆分** | 1752行 |
| **地理覆盖范围** | 布基纳法索（BFA） |
| **发布方** | 联合国教科文组织（UNESCO） |
| **HDX平台最后更新时间** | 2026-03-02 |

---

## 变量说明
**地理类变量** — `country_id`（布基纳法索，BFA）、`year`（取值范围1971.0–2025.0）。
**结果/测量类变量** — `value`（取值范围0.0–9682882.0）。
**标识符/元数据类变量** — `indicator_id`（GER.5T8、AIR.1.GLAST.M、AIR.1.GLAST.F）、`esa_source`（HDX）、`esa_processed`（2026-04-04）。

---

## 快速上手
python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-unesco-data-for-burkina-faso")
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 |
|---|---|---|---|
| `indicator_id` | object | 0.0% | GER.5T8、AIR.1.GLAST.M、AIR.1.GLAST.F |
| `country_id` | object | 0.0% | 布基纳法索（BFA） |
| `year` | int64 | 0.0% | 1971.0 – 2025.0（均值2011.7177） |
| `value` | float64 | 0.0% | 0.0 – 9682882.0（均值6790.2755） |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-04 |

---

## 数值统计摘要
| 列名 | 最小值 | 最大值 | 均值 | 中位数 |
|---|---|---|---|---|
| `year` | 1971.0 | 2025.0 | 2011.7177 | 2014.0 |
| `value` | 0.0 | 9682882.0 | 6790.2755 | 8.6192 |

---

## 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。列名被统一转换为小写并采用蛇形命名法（snake_case）进行标准化。常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）被统一替换为`NaN`。删除了2个缺失值占比超过80%的列：`magnitude`与`qualifier`。本数据集使用固定随机种子（42）以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。

---

## 数据集局限性
- 数据源自联合国教科文组织，未经过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。
- 请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/unesco-data-for-burkina-faso)查看发布方提供的方法论说明与注意事项。

---

## 引用格式
bibtex
@dataset{hdx_africa_unesco_data_for_burkina_faso,
title = {布基纳法索 - 教育指标},
author = {UNESCO},
year = {2026},
url = {https://data.humdata.org/dataset/unesco-data-for-burkina-faso},
note = {经Electric Sheep Africa重新打包以适配机器学习（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。*