electricsheepafrica/africa-elite-consultation-1789-2021

Elite Consultation (1789 – 2021)

Publisher: V-Dem Institute · Source: OpenAfrica · License: cc-by · Updated: 2023-01-26

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Abstract

"The variable denotes the best estimate of the extent to which political elites consult other elites across the political spectrum and from relevant sectors of society and business when considering important policy changes. Higher scores mean more consultation."

Each row in this dataset represents tabular records. Data was last updated on OpenAfrica on 2023-01-26. Geographic scope: BENIN, BOTSWANA, CAPE-VERDE, ETHIOPIA, KENYA, NIGERIA, SENEGAL, SOUTH-AFRICA, and 4 others.

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

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Dataset Characteristics

Domain	Humanitarian and development data
Unit of observation	Tabular records
Rows (total)	1,477
Columns	5 (2 numeric, 3 categorical, 0 datetime)
Train split	1,181 rows
Test split	295 rows
Geographic scope	BENIN, BOTSWANA, CAPE-VERDE, ETHIOPIA, KENYA, NIGERIA, SENEGAL, SOUTH-AFRICA, and 4 others
Publisher	V-Dem Institute
OpenAfrica last updated	2023-01-26

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Variables

Identifier / Metadata — unnamed_1 (range 1789.0–2021.0), unnamed_2 (range -2.512–2.766), esa_source (HDX), esa_processed (2026-04-28).

Other — elite_consultation_1789_2021 (Ethiopia, Sudan, Benin).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-elite-consultation-1789-2021")
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
elite_consultation_1789_2021	object	0.1%	Ethiopia, Sudan, Benin
unnamed_1	float64	0.2%	1789.0 – 2021.0 (mean 1948.6377)
unnamed_2	float64	0.2%	-2.512 – 2.766 (mean -0.2759)
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-28

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Numeric Summary

Column	Min	Max	Mean	Median
unnamed_1	1789.0	2021.0	1948.6377	1954.5
unnamed_2	-2.512	2.766	-0.2759	-0.3

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Curation

Raw data was downloaded from OpenAfrica 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. 2 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). 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 V-Dem Institute and has not been independently validated by ESA.
• Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• This dataset spans 12 countries; geographic and methodological inconsistencies across national boundaries may affect cross-country comparability.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{openafrica_africa_elite_consultation_1789_2021,
  title     = {Elite Consultation (1789 – 2021)},
  author    = {V-Dem Institute},
  year      = {2023},
  url       = {https://open.africa/dataset/elite-consultation-1789-2021},
  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.