electricsheepafrica/africa-world-bank-education-indicators-for-central-african-republic

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- tabular-classification
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- education
- indicators
- caf
pretty_name: "Central African Republic - Education"
dataset_info:
splits:
- name: train
num_examples: 11257
- name: test
num_examples: 2814
---

# Central African Republic - Education

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

Education is one of the most powerful instruments for reducing poverty and inequality and lays a foundation for sustained economic growth. The World Bank compiles data on education inputs, participation, efficiency, and outcomes. Data on education are compiled by the United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics from official responses to surveys and from reports provided by education authorities in each country.

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

*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)** | 14,072 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 11,257 rows |
| **Test split** | 2,814 rows |
| **Geographic scope** | CAF |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

**Geographic** — `country_name` (Central African Republic), `country_iso3` (CAF), `year` (range 1960.0–2025.0).

**Outcome / Measurement** — `value` (range 0.0–2076374.0).

**Identifier / Metadata** — `indicator_name` (Population ages 15-64 (% of total population), Population ages 0-14 (% of total population), Number of infant deaths, male), `indicator_code` (SP.POP.1564.TO.ZS, SP.POP.0014.TO.ZS, SH.DTH.IMRT.MA), `esa_source` (HDX), `esa_processed` (2026-04-17).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-education-indicators-for-central-african-republic")
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% | Central African Republic |
| `country_iso3` | object | 0.0% | CAF |
| `year` | int64 | 0.0% | 1960.0 – 2025.0 (mean 1994.7003) |
| `indicator_name` | object | 0.0% | Population ages 15-64 (% of total population), Population ages 0-14 (% of total population), Number of infant deaths, male |
| `indicator_code` | object | 0.0% | SP.POP.1564.TO.ZS, SP.POP.0014.TO.ZS, SH.DTH.IMRT.MA |
| `value` | float64 | 0.0% | 0.0 – 2076374.0 (mean 106235.1946) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-17 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1960.0 | 2025.0 | 1994.7003 | 1996.0 |
| `value` | 0.0 | 2076374.0 | 106235.1946 | 1761.0 |

---

## 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`. 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-education-indicators-for-central-african-republic) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_education_indicators_for_central_african_republic,
title = {Central African Republic - Education},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-education-indicators-for-central-african-republic},
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: 无标注
language_creators: 公开抓取获取
language: 英语（en）
license: CC-BY 4.0
multilinguality: 单语言
size_categories: 10000 < 样本量 < 100000
source_datasets: 原创数据集
task_categories: 表格分类任务、表格回归任务
task_ids: 无
tags: 非洲、人道主义、HDX（人道主义数据交换，Humanitarian Data Exchange）、Electric Sheep Africa、教育、指标、CAF（中非共和国，Central African Republic）
pretty_name: "中非共和国 - 教育指标数据集"
dataset_info:
splits:
- name: train
num_examples: 11257
- name: test
num_examples: 2814

# 中非共和国 - 教育指标数据集

**发布方**：世界银行集团 · **来源**：[HDX（人道主义数据交换，Humanitarian Data Exchange）](https://data.humdata.org/dataset/world-bank-education-indicators-for-central-african-republic) · **授权协议**：`CC-BY` · **最后更新时间**：2026-03-27

---

## 摘要

本数据集包含来自世界银行[数据门户](http://data.worldbank.org/)的公开数据。HDX平台上同时存在一份整合后的中非共和国综合指标数据集，链接为：https://data.humdata.org/dataset/world-bank-combined-indicators-for-central-african-republic。

教育是减缓贫困与不平等最有效的工具之一，同时为可持续经济增长奠定坚实基础。世界银行会汇总教育投入、教育参与度、教育效率与教育成果相关的数据。联合国教育、科学及文化组织（United Nations Educational, Scientific and Cultural Organization，缩写：UNESCO）统计研究所会根据各国教育主管部门提交的官方调研反馈与报告，整理得到教育领域相关数据。

本数据集的每一行数据均代表国家级汇总统计结果。该数据集在HDX平台的最后更新时间为2026-03-27，地理覆盖范围：**CAF（中非共和国）**。

*本数据集由[Electric Sheep Africa（电羊非洲团队）](https://huggingface.co/electricsheepafrica)整理为适配机器学习的Parquet格式。*

---

## 数据集特征

| 分类项 | 详情 |
|---|---|
| **所属领域** | 教育 |
| **观测单元** | 国家级汇总统计数据 |
| **总数据行数** | 14072条 |
| **总数据列数** | 8列（2列数值型，6列分类型，0列日期时间型） |
| **训练集划分** | 11257条数据 |
| **测试集划分** | 2814条数据 |
| **地理覆盖范围** | CAF（中非共和国） |
| **发布方** | 世界银行集团 |
| **HDX平台最后更新时间** | 2026-03-27 |

---

## 变量说明

**地理类变量**：`country_name`（国家名称：中非共和国）、`country_iso3`（国家ISO3代码：CAF）、`year`（年份范围：1960.0–2025.0）。
**结果/测量类变量**：`value`（指标数值，取值范围：0.0–2076374.0）。
**标识/元数据类变量**：`indicator_name`（指标名称，包含：15-64岁人口占总人口比例、0-14岁人口占总人口比例、男性婴儿死亡数）、`indicator_code`（指标代码，包含：SP.POP.1564.TO.ZS、SP.POP.0014.TO.ZS、SH.DTH.IMRT.MA）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理时间：2026-04-17）。

---

## 快速上手示例

python
from datasets import load_dataset

# 加载目标数据集
ds = load_dataset("electricsheepafrica/africa-world-bank-education-indicators-for-central-african-republic")
# 将训练集、测试集转换为Pandas DataFrame格式
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

# 打印训练集数据形状
print(train.shape)
# 查看训练集前5条数据
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` | 字符型 | 0.0% | 中非共和国 |
| `country_iso3` | 字符型 | 0.0% | CAF |
| `year` | 64位整数型 | 0.0% | 1960.0 – 2025.0（均值：1994.7003） |
| `indicator_name` | 字符型 | 0.0% | 15-64岁人口占总人口比例、0-14岁人口占总人口比例、男性婴儿死亡数 |
| `indicator_code` | 字符型 | 0.0% | SP.POP.1564.TO.ZS、SP.POP.0014.TO.ZS、SH.DTH.IMRT.MA |
| `value` | 64位浮点型 | 0.0% | 0.0 – 2076374.0（均值：106235.1946） |
| `esa_source` | 字符型 | 0.0% | HDX |
| `esa_processed` | 字符型 | 0.0% | 2026-04-17 |

---

## 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 | 2025.0 | 1994.7003 | 1996.0 |
| `value` | 0.0 | 2076374.0 | 106235.1946 | 1761.0 |

---

## 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。所有列名均转换为小写，并标准化为蛇形命名法（snake_case）。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）按照80/20的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

- 本数据集原始数据来源于世界银行集团，Electric Sheep Africa并未对其进行独立验证。
- 自动化数据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，或原始数据采集阶段存在的抽样偏差。
- 如需了解发布方提供的方法论说明与使用注意事项，请参阅[HDX平台原始数据集页面](https://data.humdata.org/dataset/world-bank-education-indicators-for-central-african-republic)。

---

## 引用格式

bibtex
@dataset{hdx_africa_world_bank_education_indicators_for_central_african_republic,
title = {Central African Republic - Education},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-education-indicators-for-central-african-republic},
note = {由Electric Sheep Africa（https://huggingface.co/electricsheepafrica）重新打包为机器学习适配格式}
}

---

*[Electric Sheep Africa（电羊非洲团队）](https://huggingface.co/electricsheepafrica) — 非洲机器学习数据集基础设施提供商，总部位于尼日利亚拉各斯。*