electricsheepafrica/africa-world-bank-trade-indicators-for-equatorial-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
- indicators
- trade
- gnq
pretty_name: "Equatorial Guinea - Trade"
dataset_info:
splits:
- name: train
num_examples: 1642
- name: test
num_examples: 410
---

# Equatorial Guinea - Trade

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

*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)** | 2,053 |
| **Columns** | 8 (2 numeric, 6 categorical, 0 datetime) |
| **Train split** | 1,642 rows |
| **Test split** | 410 rows |
| **Geographic scope** | GNQ |
| **Publisher** | World Bank Group |
| **HDX last updated** | 2026-03-27 |

---

## Variables

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

**Outcome / Measurement** — `value` (range -296425138.5126–7316668417922.37).

**Identifier / Metadata** — `indicator_name` (Merchandise imports (current US$), Merchandise exports (current US$), Merchandise trade (% of GDP)), `indicator_code` (TM.VAL.MRCH.CD.WT, TX.VAL.MRCH.CD.WT, TG.VAL.TOTL.GD.ZS), `esa_source` (HDX), `esa_processed` (2026-04-16).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-world-bank-trade-indicators-for-equatorial-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% | Equatorial Guinea |
| `country_iso3` | object | 0.0% | GNQ |
| `year` | int64 | 0.0% | 1960.0 – 2024.0 (mean 2002.4993) |
| `indicator_name` | object | 0.0% | Merchandise imports (current US$), Merchandise exports (current US$), Merchandise trade (% of GDP) |
| `indicator_code` | object | 0.0% | TM.VAL.MRCH.CD.WT, TX.VAL.MRCH.CD.WT, TG.VAL.TOTL.GD.ZS |
| `value` | float64 | 0.0% | -296425138.5126 – 7316668417922.37 (mean 38533137012.5435) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-16 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `year` | 1960.0 | 2024.0 | 2002.4993 | 2004.0 |
| `value` | -296425138.5126 | 7316668417922.37 | 38533137012.5435 | 22.3814 |

---

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

---

## Citation

```bibtex
@dataset{hdx_africa_world_bank_trade_indicators_for_equatorial_guinea,
title = {Equatorial Guinea - Trade},
author = {World Bank Group},
year = {2026},
url = {https://data.humdata.org/dataset/world-bank-trade-indicators-for-equatorial-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.*