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license: other
language:
- en
task_categories:
- tabular-classification
- tabular-regression
- time-series-forecasting
multilinguality: monolingual
size_categories:
- 1K<n<10K
tags:
- tabular
- africa
- un-comtrade
- international-merchandise-trade
- trade
- exports-imports
- hs
- bilateral
- time-series
pretty_name: "Benin — Exports by Trading Partner | Africa (UN Comtrade)"
---
# Benin — Exports by Trading Partner | Africa (UN Comtrade)
🌍 **6,848 observations** · **1 Africa countries** · **2000–2023** · *Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*
    
## TL;DR
This dataset contains **6,848 observations** of `International merchandise trade` data across **1 Africa countries**, spanning **2000–2023**, covering **192 distinct indicators**.
## About the source
- **Source:** [UN Comtrade](https://comtradeplus.un.org/)
- **Publisher:** United Nations Statistics Division (UN Comtrade)
- **License:** [other](https://comtradeplus.un.org/TermsOfUse)
- **Topic:** International merchandise trade
## Geographic coverage
1 Africa countries · top rows shown below, sorted by row count:
| Country | Rows | First year | Last year |
|---------|-----:|-----------:|----------:|
| `Benin` | 6,848 | 2000 | 2023 |
## Indicators (sample)
- `Afghanistan` — Afghanistan
- `Albania` — Albania
- `Algeria` — Algeria
- `American Samoa` — American Samoa
- `Andorra` — Andorra
- `Angola` — Angola
- `Anguilla` — Anguilla
- `Antigua and Barbuda` — Antigua and Barbuda
- `Areas, nes` — Areas, nes
- `Argentina` — Argentina
- _... and 182 more indicators_
## Schema
| Column | Type | Description | Example |
|--------|------|-------------|---------|
| `country_name` | `string` | — | `Benin` |
| `country_iso3` | `string` | — | `BEN` |
| `partner_name` | `string` | — | `Afghanistan` |
| `partner_iso3` | `string` | — | `AFG` |
| `year` | `int64` | — | `2000` |
| `flow` | `string` | — | `exports` |
| `trade_value_usd` | `float64` | — | `84867.0` |
## Usage
```python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-comtrade-benin-exports-by-partner")
df = ds["train"].to_pandas()
print(df.head())
```
### Filter to one country
```python
kenya = df[df["country_name"] == "KEN"]
```
### Time-series for a single indicator
```python
sample = (df[df["partner_name"] == "Afghanistan"]
.sort_values("year"))
sample.plot(x="year", y="trade_value_usd", title="Afghanistan")
```
### Pivot to country × year matrix
```python
matrix = (df[df["partner_name"] == "Afghanistan"]
.pivot_table(index="year", columns="country_name", values="trade_value_usd"))
print(matrix.tail())
```
## Citation
```bibtex
@misc{africa_comtrade_benin_exports_by_partner_2023,
title = {Benin — Exports by Trading Partner | Africa (UN Comtrade)},
author = {United Nations Statistics Division (UN Comtrade)},
year = {2023},
url = {https://comtradeplus.un.org/},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-comtrade-benin-exports-by-partner}}
}
```
## License
Released under [other](https://comtradeplus.un.org/TermsOfUse).
Original data © United Nations Statistics Division (UN Comtrade). When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.
## About Electric Sheep
Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on HuggingFace. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use `load_dataset()` to start working in seconds.
Browse the full collection: [huggingface.co/electricsheepafrica](https://huggingface.co/electricsheepafrica)
---
_Provenance: ingested 2026-06-17 via the Electric Sheep pipeline. Source URL: https://comtradeplus.un.org/_
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