Datasets:

electricsheepafrica
/

africa-comtrade-central-african-rep-exports-by-partner

license: other
language:
  - en
task_categories:
  - tabular-classification
  - tabular-regression
  - time-series-forecasting
multilinguality: monolingual
size_categories:
  - n<1K
tags:
  - tabular
  - africa
  - un-comtrade
  - international-merchandise-trade
  - trade
  - exports-imports
  - hs
  - bilateral
  - time-series
pretty_name: Central African Rep. — Exports by Trading Partner | Africa (UN Comtrade)

Central African Rep. — Exports by Trading Partner | Africa (UN Comtrade)

🌍 925 observations · 1 Africa countries · 2000–2023 · Repackaged by Electric Sheep Africa

TL;DR

This dataset contains 925 observations of International merchandise trade data across 1 Africa countries, spanning 2000–2023, covering 119 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
`Central African Rep.`	925	2000	2023

Indicators (sample)

Afghanistan — Afghanistan
Albania — Albania
Algeria — Algeria
Andorra — Andorra
Angola — Angola
Areas, nes — Areas, nes
Argentina — Argentina
Australia — Australia
Austria — Austria
Bangladesh — Bangladesh
... and 109 more indicators

Schema

Column	Type	Description	Example
`country_name`	`string`	—	`Central African Rep.`
`country_iso3`	`string`	—	`CAF`
`partner_name`	`string`	—	`Dem. Rep. of the Congo`
`partner_iso3`	`string`	—	`COD`
`year`	`int64`	—	`2001`
`flow`	`string`	—	`exports`
`trade_value_usd`	`float64`	—	`289412.0`

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-comtrade-central-african-rep-exports-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"] == "Dem. Rep. of the Congo"]
          .sort_values("year"))
sample.plot(x="year", y="trade_value_usd", title="Dem. Rep. of the Congo")

Pivot to country × year matrix

matrix = (df[df["partner_name"] == "Dem. Rep. of the Congo"]
          .pivot_table(index="year", columns="country_name", values="trade_value_usd"))
print(matrix.tail())

Citation

@misc{africa_comtrade_central_african_rep_exports_by_partner_2023,
  title        = {Central African Rep. — 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-central-african-rep-exports-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/