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

Niger - Trade

Publisher: World Bank Group · Source: HDX · License: cc-by · Updated: 2026-03-27

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Abstract

Contains data from the World Bank's data portal. There is also a consolidated country dataset 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: NER.

Curated into ML-ready Parquet format by Electric Sheep Africa.

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Dataset Characteristics

Domain	Poverty and economic vulnerability
Unit of observation	Country-level aggregates
Rows (total)	5,314
Columns	8 (2 numeric, 6 categorical, 0 datetime)
Train split	4,251 rows
Test split	1,062 rows
Geographic scope	NER
Publisher	World Bank Group
HDX last updated	2026-03-27

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Variables

Geographic — country_name (Niger), country_iso3 (NER), year (range 1960.0–2024.0).

Outcome / Measurement — value (range -2817582856.7198–2607213140795.38).

Identifier / Metadata — indicator_name (Imports of goods and services (current US$), Exports of goods and services (% of GDP), Merchandise exports (current US$)), indicator_code (NE.IMP.GNFS.CD, NE.EXP.GNFS.ZS, TX.VAL.MRCH.CD.WT), esa_source (HDX), esa_processed (2026-04-12).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-world-bank-trade-indicators-for-niger")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

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Schema

Column	Type	Null %	Range / Sample Values
country_name	object	0.0%	Niger
country_iso3	object	0.0%	NER
year	int64	0.0%	1960.0 – 2024.0 (mean 1998.4563)
indicator_name	object	0.0%	Imports of goods and services (current US$), Exports of goods and services (% of GDP), Merchandise exports (current US$)
indicator_code	object	0.0%	NE.IMP.GNFS.CD, NE.EXP.GNFS.ZS, TX.VAL.MRCH.CD.WT
value	float64	0.0%	-2817582856.7198 – 2607213140795.38 (mean 4674983619.4956)
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-12

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Numeric Summary

Column	Min	Max	Mean	Median
year	1960.0	2024.0	1998.4563	2001.0
value	-2817582856.7198	2607213140795.38	4674983619.4956	22.3

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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.

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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 for the publisher's own methodology notes and caveats.

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Citation

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

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Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.