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country_name
stringclasses
44 values
country_iso3
stringclasses
44 values
year
int64
1.95k
2.02k
Ten year age-group with the highest population
stringclasses
4 values
Algeria
DZA
1,950
0-9
Algeria
DZA
1,951
0-9
Algeria
DZA
1,952
0-9
Algeria
DZA
1,953
0-9
Algeria
DZA
1,954
0-9
Algeria
DZA
1,955
0-9
Algeria
DZA
1,956
0-9
Algeria
DZA
1,957
0-9
Algeria
DZA
1,958
0-9
Algeria
DZA
1,959
0-9
Algeria
DZA
1,960
0-9
Algeria
DZA
1,961
0-9
Algeria
DZA
1,962
0-9
Algeria
DZA
1,963
0-9
Algeria
DZA
1,964
0-9
Algeria
DZA
1,965
0-9
Algeria
DZA
1,966
0-9
Algeria
DZA
1,967
0-9
Algeria
DZA
1,968
0-9
Algeria
DZA
1,969
0-9
Algeria
DZA
1,970
0-9
Algeria
DZA
1,971
0-9
Algeria
DZA
1,972
0-9
Algeria
DZA
1,973
0-9
Algeria
DZA
1,974
0-9
Algeria
DZA
1,975
0-9
Algeria
DZA
1,976
0-9
Algeria
DZA
1,977
0-9
Algeria
DZA
1,978
0-9
Algeria
DZA
1,979
0-9
Algeria
DZA
1,980
0-9
Algeria
DZA
1,981
0-9
Algeria
DZA
1,982
0-9
Algeria
DZA
1,983
0-9
Algeria
DZA
1,984
0-9
Algeria
DZA
1,985
0-9
Algeria
DZA
1,986
0-9
Algeria
DZA
1,987
0-9
Algeria
DZA
1,988
0-9
Algeria
DZA
1,989
0-9
Algeria
DZA
1,990
0-9
Algeria
DZA
1,991
0-9
Algeria
DZA
1,992
0-9
Algeria
DZA
1,993
0-9
Algeria
DZA
1,994
0-9
Algeria
DZA
1,995
0-9
Algeria
DZA
1,996
0-9
Algeria
DZA
1,997
10-19
Algeria
DZA
1,998
10-19
Algeria
DZA
1,999
10-19
Algeria
DZA
2,000
10-19
Algeria
DZA
2,001
10-19
Algeria
DZA
2,002
10-19
Algeria
DZA
2,003
10-19
Algeria
DZA
2,004
10-19
Algeria
DZA
2,005
10-19
Algeria
DZA
2,006
10-19
Algeria
DZA
2,007
20-29
Algeria
DZA
2,008
20-29
Algeria
DZA
2,009
20-29
Algeria
DZA
2,010
20-29
Algeria
DZA
2,011
20-29
Algeria
DZA
2,012
0-9
Algeria
DZA
2,013
0-9
Algeria
DZA
2,014
0-9
Algeria
DZA
2,015
0-9
Algeria
DZA
2,016
0-9
Algeria
DZA
2,017
0-9
Algeria
DZA
2,018
0-9
Algeria
DZA
2,019
0-9
Algeria
DZA
2,020
0-9
Algeria
DZA
2,021
0-9
Algeria
DZA
2,022
0-9
Algeria
DZA
2,023
0-9
Angola
AGO
1,950
0-9
Angola
AGO
1,951
0-9
Angola
AGO
1,952
0-9
Angola
AGO
1,953
0-9
Angola
AGO
1,954
0-9
Angola
AGO
1,955
0-9
Angola
AGO
1,956
0-9
Angola
AGO
1,957
0-9
Angola
AGO
1,958
0-9
Angola
AGO
1,959
0-9
Angola
AGO
1,960
0-9
Angola
AGO
1,961
0-9
Angola
AGO
1,962
0-9
Angola
AGO
1,963
0-9
Angola
AGO
1,964
0-9
Angola
AGO
1,965
0-9
Angola
AGO
1,966
0-9
Angola
AGO
1,967
0-9
Angola
AGO
1,968
0-9
Angola
AGO
1,969
0-9
Angola
AGO
1,970
0-9
Angola
AGO
1,971
0-9
Angola
AGO
1,972
0-9
Angola
AGO
1,973
0-9
Angola
AGO
1,974
0-9
Angola
AGO
1,975
0-9
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Age Group With The Largest Population | Africa (Our World in Data) | Africa (Electric Sheep Africa metadata inventory)

Size category: 1K<n<10K - Formats: parquet - Sector: demographics_social - Engineered by Electric Sheep Africa

size sector downloads license

TL;DR

This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.

What This Dataset Covers

Public datasets help analysts inspect structured evidence, build reproducible workflows, and compare patterns across domains.

Dataset context from the existing Hugging Face card: Age Group With The Largest Population | Africa (Our World in Data) 🌍 3,996 observations · 54 Africa countries · 1950–2023 · Repackaged by Electric Sheep Africa TL;DR This dataset contains 3,996 observations of Age Group With The Largest Population data across 54 Africa countries, spanning 1950–2023. About the source Source: Our World in Data Publisher: Our World in Data License: cc-by-4.0 Topic: Age Group With The Largest Population… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-owid-age-group-with-the-largest-population.

Dataset Profile

Field Value
Hugging Face repo electricsheepafrica/africa-owid-age-group-with-the-largest-population
Sector demographics_social
Topic tags tabular, our-world-in-data, age-group-with-the-largest-population, owid, long-run-series, time-series
Modalities text, tabular
Formats parquet
Size category 1K<n<10K
Countries Africa-wide or source-defined African coverage
ISO3 coverage not declared
Last modified on HF 2026-06-01 18:37:33+00:00
Inventory snapshot 2026-07-16T16:00:34Z

How To Read This Dataset

  • Start from the repository files and the dataset viewer when available.
  • Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
  • Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
  • Preserve missing values until you have a defensible imputation rule.

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-owid-age-group-with-the-largest-population")
print(ds)

split_name = next(iter(ds))
table = ds[split_name]
print(table.features)
print(table[:3])

Convert To Pandas When Tabular

from datasets import Dataset

first_split = ds[next(iter(ds))]
if isinstance(first_split, Dataset):
    df = first_split.to_pandas()
    print(df.head())

Data Quality Notes

  • This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
  • Exact schema, row counts, and source files should be inspected in the repository data files.
  • Metadata gaps from the inventory: country, upstream_publisher.
  • Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.

Source And Provenance

Suggested Analyses

  • Inspect schema and missingness before modeling.
  • Profile variables by geography, time, and subgroup columns where present.
  • Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
  • Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.

Citation

@misc{electric_sheep_africa_africa_owid_age_group_with_the_largest_population_2026,
  title        = {Age Group With The Largest Population | Africa (Our World in Data) | Africa (Electric Sheep Africa metadata inventory)},
  author       = {Public dataset metadata},
  year         = {2026},
  url          = {https://huggingface.co/datasets/electricsheepafrica/africa-owid-age-group-with-the-largest-population},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-owid-age-group-with-the-largest-population}}
}

License

Released under CC BY 4.0.

Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.

About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.


Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: catalog/esa_metadata_inventory/master_metadata.jsonl.

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