electricsheepafrica/africa-world-bank-trade-indicators-for-comoros

---
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
- indicators
- trade
- com
pretty_name: "Comoros - Trade"
dataset_info:
splits:
- name: train
num_examples: 3024
- name: test
num_examples: 756
---

# Comoros - Trade

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

Trade is a key means to fight poverty and achieve the Millennium Development Goals, specifically by improving developing country access to markets, and supporting a rules based, predictable trading system. In cooperation with other international development partners, the World Bank launched the Transparency in Trade Initiative to provide free and easy access to data on country-specific trade policies.

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

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Poverty and economic vulnerability |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 3,780 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 3,024 rows |
| **Test split** | 756 rows |
| **Geographic scope** | COM |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

**Geographic** — `country_name` (Comoros), `country_iso3` (COM), `year` (range 1960.0–2024.0).

**Outcome / Measurement** — `value` (range -355581804.7657–56470704579.6046).

**Identifier / Metadata** — `indicator_name` (Merchandise imports (current US$), Merchandise exports (current US$), Merchandise imports by the reporting economy, residual (% of total merchandise imports)), `indicator_code` (TM.VAL.MRCH.CD.WT, TX.VAL.MRCH.CD.WT, TM.VAL.MRCH.RS.ZS), `esa_source` (HDX), `esa_processed` (2026-04-17).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-trade-indicators-for-comoros")
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% | Comoros |
| `country_iso3` | object | 0.0% | COM |
| `year` | int64 | 0.0% | 1960.0 – 2024.0 (mean 2002.6495) |
| `indicator_name` | object | 0.0% | Merchandise imports (current US$), Merchandise exports (current US$), Merchandise imports by the reporting economy, residual (% of total merchandise imports) |
| `indicator_code` | object | 0.0% | TM.VAL.MRCH.CD.WT, TX.VAL.MRCH.CD.WT, TM.VAL.MRCH.RS.ZS |
| `value` | float64 | 0.0% | -355581804.7657 – 56470704579.6046 (mean 331672073.1251) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-17 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1960.0 | 2024.0 | 2002.6495 | 2005.0 |
| `value` | -355581804.7657 | 56470704579.6046 | 331672073.1251 | 25.3664 |

---

## 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-trade-indicators-for-comoros) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_trade_indicators_for_comoros,
title = {Comoros - Trade},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-trade-indicators-for-comoros},
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:
- 公开数据源获取
language:
- 英语
license: CC BY 4.0
multilinguality:
- 单语言
size_categories:
- 1000<n<10000
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（非洲电羊团队）
- 指标
- 贸易
- COM（科摩罗）
pretty_name: "科摩罗——贸易数据集"
dataset_info:
splits:
- name: 训练集
num_examples: 3024
- name: 测试集
num_examples: 756
---

# 科摩罗——贸易数据集

**发布方：** 世界银行集团（World Bank Group） · **来源：** [HDX（Humanitarian Data Exchange）](https://data.humdata.org/dataset/world-bank-trade-indicators-for-comoros) · **许可证：** `cc-by` · **最后更新：** 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平台上另有一份[科摩罗综合国家指标数据集](https://data.humdata.org/dataset/world-bank-combined-indicators-for-comoros)。
贸易是对抗贫困、实现千年发展目标的关键途径，尤其是通过改善发展中国家的市场准入条件，以及支持基于规则的可预测贸易体系。世界银行与其他国际发展合作伙伴联合发起了贸易透明度倡议，旨在免费、便捷地提供各国专属贸易政策数据。
本数据集的每一行均代表国家级贸易汇总数据。HDX平台上的该数据集最后更新时间为2026-03-27。地理覆盖范围：**COM（科摩罗）**。

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

---

## 数据集特征

| | |
|---|---|
| **领域** | 贫困与经济脆弱性 |
| **观测单元** | 国家级汇总数据 |
| **总行数** | 3780 |
| **列数** | 8（2个数值型列，6个分类型列，0个日期时间型列） |
| **训练集划分** | 3024行 |
| **测试集划分** | 756行 |
| **地理覆盖范围** | COM（科摩罗） |
| **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：科摩罗）、`country_iso3`（国家ISO3代码：COM）、`year`（年份：取值范围1960.0–2024.0）。
**结果/测量变量** — `value`（贸易值：取值范围-355581804.7657–56470704579.6046）。
**标识符/元数据变量** — `indicator_name`（指标名称：商品进口额（现价美元）、商品出口额（现价美元）、报告经济体商品进口剩余额（占总商品进口的百分比））、`indicator_code`（指标代码：TM.VAL.MRCH.CD.WT、TX.VAL.MRCH.CD.WT、TM.VAL.MRCH.RS.ZS）、`esa_source`（数据来源：HDX）、`esa_processed`（数据处理时间：2026-04-17）。

---

## 快速上手

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-trade-indicators-for-comoros")
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` | object（字符串型） | 0.0% | 科摩罗 |
| `country_iso3` | object（字符串型） | 0.0% | COM |
| `year` | int64（64位整数型） | 0.0% | 1960.0 – 2024.0（均值为2002.6495） |
| `indicator_name` | object（字符串型） | 0.0% | 商品进口额（现价美元）、商品出口额（现价美元）、报告经济体商品进口剩余额（占总商品进口的百分比） |
| `indicator_code` | object（字符串型） | 0.0% | TM.VAL.MRCH.CD.WT、TX.VAL.MRCH.CD.WT、TM.VAL.MRCH.RS.ZS |
| `value` | float64（64位浮点型） | 0.0% | -355581804.7657 – 56470704579.6046（均值为331672073.1251） |
| `esa_source` | object（字符串型） | 0.0% | HDX |
| `esa_processed` | object（字符串型） | 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 | 2024.0 | 2002.6495 | 2005.0 |
| `value` | -355581804.7657 | 56470704579.6046 | 331672073.1251 | 25.3664 |

---

## 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`。本数据集以固定随机种子（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

- 本数据集源自世界银行集团，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中错报值、定义不一致或原始采集过程中的抽样偏差问题。
- 如需查看发布方的方法说明与注意事项，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/world-bank-trade-indicators-for-comoros)。

---

## 引用格式

bibtex
@dataset{hdx_africa_world_bank_trade_indicators_for_comoros,
title = {Comoros - Trade},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-trade-indicators-for-comoros},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

---

*[Electric Sheep Africa（非洲电羊团队）](https://huggingface.co/electricsheepafrica) — 非洲机器学习数据集基础设施。尼日利亚拉各斯。*