electricsheepafrica/africa-world-bank-social-development-indicators-for-central-african-republic

Central African Republic - Social Development

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.

Data here cover child labor, gender issues, refugees, and asylum seekers. Children in many countries work long hours, often combining studying with work for pay. The data on their paid work are from household surveys conducted by the International Labour Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. Gender disparities are measured using a compilation of data on key topics such as education, health, labor force participation, and political participation. Data on refugees are from the United Nations High Commissioner for Refugees complemented by statistics on Palestinian refugees under the mandate of the United Nations Relief and Works Agency.

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

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

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Dataset Characteristics

Domain	Public health
Unit of observation	Country-level aggregates
Rows (total)	835
Columns	8 (2 numeric, 6 categorical, 0 datetime)
Train split	668 rows
Test split	167 rows
Geographic scope	CAF
Publisher	World Bank Group
HDX last updated	2026-03-27

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Variables

Geographic — country_name (Central African Republic), country_iso3 (CAF), year (range 1960.0–2025.0).

Outcome / Measurement — value (range 0.0595–184.201).

Identifier / Metadata — indicator_name (Life expectancy at birth, male (years), Life expectancy at birth, female (years), Adolescent fertility rate (births per 1,000 women ages 15-19)), indicator_code (SP.DYN.LE00.MA.IN, SP.DYN.LE00.FE.IN, SP.ADO.TFRT), esa_source (HDX), esa_processed (2026-04-14).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-world-bank-social-development-indicators-for-central-african-republic")
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%	Central African Republic
country_iso3	object	0.0%	CAF
year	int64	0.0%	1960.0 – 2025.0 (mean 2001.8623)
indicator_name	object	0.0%	Life expectancy at birth, male (years), Life expectancy at birth, female (years), Adolescent fertility rate (births per 1,000 women ages 15-19)
indicator_code	object	0.0%	SP.DYN.LE00.MA.IN, SP.DYN.LE00.FE.IN, SP.ADO.TFRT
value	float64	0.0%	0.0595 – 184.201 (mean 51.5363)
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-14

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Numeric Summary

Column	Min	Max	Mean	Median
year	1960.0	2025.0	2001.8623	2004.0
value	0.0595	184.201	51.5363	54.055

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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_social_development_indicators_for_central_african_republic,
  title     = {Central African Republic - Social Development},
  author    = {World Bank Group},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/world-bank-social-development-indicators-for-central-african-republic},
  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.