Datasets:

electricsheepafrica
/

africa-comtrade-benin-imports-by-partner

license: other
language:
  - en
task_categories:
  - tabular-classification
  - tabular-regression
  - time-series-forecasting
multilinguality: monolingual
size_categories:
  - 10K<n<100K
tags:
  - tabular
  - africa
  - un-comtrade
  - international-merchandise-trade
  - trade
  - exports-imports
  - hs
  - bilateral
  - time-series
pretty_name: Benin — Imports by Trading Partner | Africa (UN Comtrade)

Benin — Imports by Trading Partner | Africa (UN Comtrade)

🌍 12,237 observations · 1 Africa countries · 2000–2023 · Repackaged by Electric Sheep Africa

TL;DR

This dataset contains 12,237 observations of International merchandise trade data across 1 Africa countries, spanning 2000–2023, covering 232 distinct indicators.

About the source

Source: UN Comtrade
Publisher: United Nations Statistics Division (UN Comtrade)
License: other
Topic: International merchandise trade

Geographic coverage

1 Africa countries · top rows shown below, sorted by row count:

Country	Rows	First year	Last year
`Benin`	12,237	2000	2023

Indicators (sample)

Afghanistan — Afghanistan
Albania — Albania
Algeria — Algeria
American Samoa — American Samoa
Andorra — Andorra
Angola — Angola
Anguilla — Anguilla
Antarctica — Antarctica
Antigua and Barbuda — Antigua and Barbuda
Areas, nes — Areas, nes
... and 222 more indicators

Schema

Column	Type	Description	Example
`country_name`	`string`	—	`Benin`
`country_iso3`	`string`	—	`BEN`
`partner_name`	`string`	—	`Argentina`
`partner_iso3`	`string`	—	`ARG`
`year`	`int64`	—	`2000`
`flow`	`string`	—	`imports`
`trade_value_usd`	`float64`	—	`105985.0`

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-comtrade-benin-imports-by-partner")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

kenya = df[df["country_name"] == "KEN"]

Time-series for a single indicator

sample = (df[df["partner_name"] == "Argentina"]
          .sort_values("year"))
sample.plot(x="year", y="trade_value_usd", title="Argentina")

Pivot to country × year matrix

matrix = (df[df["partner_name"] == "Argentina"]
          .pivot_table(index="year", columns="country_name", values="trade_value_usd"))
print(matrix.tail())

Citation

@misc{africa_comtrade_benin_imports_by_partner_2023,
  title        = {Benin — Imports 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-imports-by-partner}}
}

License

Released under other.

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

Provenance: ingested 2026-06-17 via the Electric Sheep pipeline. Source URL: https://comtradeplus.un.org/