electricsheepafrica/africa-equal-access-to-power-2021-for-select-african-countries

Equal Access to Power, 2021, for select African countries

Publisher: The Charter Project · Source: OpenAfrica · License: cc-by · Updated: 2023-04-11

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Abstract

Based on expert assessments, it combines information on the extent to which all social groups can influence and participate in policy-making. It ranges from 0 to 1 (most equal).

Each row in this dataset represents tabular records. Data was last updated on OpenAfrica on 2023-04-11. Geographic scope: BENIN, BOTSWANA, CAPE-VERDE, ETHIOPIA, KENYA, NIGERIA, SENEGAL, SOUTH-AFRICA, and 3 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)	1,476
Columns	7 (4 numeric, 3 categorical, 0 datetime)
Train split	1,180 rows
Test split	295 rows
Geographic scope	BENIN, BOTSWANA, CAPE-VERDE, ETHIOPIA, KENYA, NIGERIA, SENEGAL, SOUTH-AFRICA, and 3 others
Publisher	The Charter Project
OpenAfrica last updated	2023-04-11

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Variables

Identifier / Metadata — unnamed_1 (range 1789.0–2021.0), unnamed_2 (range 0.017–0.925), unnamed_3 (range 0.003–0.806), unnamed_4 (range 0.062–0.973), esa_source (HDX) and 1 others.

Other — equal_access_to_power_1900_2021 (Ethiopia, Sudan, Benin).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-equal-access-to-power-2021-for-select-african-countries")
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
equal_access_to_power_1900_2021	object	0.1%	Ethiopia, Sudan, Benin
unnamed_1	float64	0.1%	1789.0 – 2021.0 (mean 1948.6377)
unnamed_2	float64	0.1%	0.017 – 0.925 (mean 0.3288)
unnamed_3	float64	0.1%	0.003 – 0.806 (mean 0.2116)
unnamed_4	float64	0.1%	0.062 – 0.973 (mean 0.4706)
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	0.017	0.925	0.3288	0.175
unnamed_3	0.003	0.806	0.2116	0.076
unnamed_4	0.062	0.973	0.4706	0.365

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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. 4 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 The Charter Project 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 11 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_equal_access_to_power_2021_for_select_african_countries,
  title     = {Equal Access to Power, 2021, for select African countries},
  author    = {The Charter Project},
  year      = {2023},
  url       = {https://open.africa/dataset/equal-access-to-power-2021-for-select-african-countries},
  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.