electricsheepafrica/africa-world-bank-private-sector-indicators-for-eritrea

Eritrea - Private Sector

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.

Private markets drive economic growth, tapping initiative and investment to create productive jobs and raise incomes. Trade is also a driver of economic growth as it integrates developing countries into the world economy and generates benefits for their people. Data on the private sector and trade are from the World Bank Group's Private Participation in Infrastructure Project Database, Enterprise Surveys, and Doing Business Indicators, as well as from the International Monetary Fund's Balance of Payments database and International Financial Statistics, the UN Commission on Trade and Development, the World Trade Organization, and various other sources.

Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-03-27. Geographic scope: ERI.

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

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Dataset Characteristics

Domain	Market and price monitoring
Unit of observation	Country-level aggregates
Rows (total)	1,204
Columns	8 (2 numeric, 6 categorical, 0 datetime)
Train split	963 rows
Test split	240 rows
Geographic scope	ERI
Publisher	World Bank Group
HDX last updated	2026-03-27

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Variables

Geographic — country_name (Eritrea), country_iso3 (ERI), year (range 1990.0–2024.0).

Outcome / Measurement — value (range 0.0–1235733661.0).

Identifier / Metadata — indicator_name (Export unit value index (2015 = 100), Merchandise imports (current US$), Import unit value index (2015 = 100)), indicator_code (TX.UVI.MRCH.XD.WD, TM.VAL.MRCH.CD.WT, TM.UVI.MRCH.XD.WD), esa_source (HDX), esa_processed (2026-04-16).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-world-bank-private-sector-indicators-for-eritrea")
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%	Eritrea
country_iso3	object	0.0%	ERI
year	int64	0.0%	1990.0 – 2024.0 (mean 2008.6877)
indicator_name	object	0.0%	Export unit value index (2015 = 100), Merchandise imports (current US$), Import unit value index (2015 = 100)
indicator_code	object	0.0%	TX.UVI.MRCH.XD.WD, TM.VAL.MRCH.CD.WT, TM.UVI.MRCH.XD.WD
value	float64	0.0%	0.0 – 1235733661.0 (mean 37955435.287)
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-16

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Numeric Summary

Column	Min	Max	Mean	Median
year	1990.0	2024.0	2008.6877	2009.0
value	0.0	1235733661.0	37955435.287	21.8076

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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_private_sector_indicators_for_eritrea,
  title     = {Eritrea - Private Sector},
  author    = {World Bank Group},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/world-bank-private-sector-indicators-for-eritrea},
  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.