electricsheepafrica/africa-south-africa-stats-sa-census-geographic-levels-cae3ed74

Stats SA Census geographic levels | Africa (South Africa official open data)

5 rows - 1 Africa country - not-applicable - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one official CSV resource from South Africa as ML-ready Parquet. The source file is the provenance boundary; all usable indicators or tabular columns from the resource stay together in this repo.

About the source

• Source: Stats SA Census geographic levels
• Publisher: Statistics South Africa
• Resource: Stats SA Census geographic levels
• Format: CSV
• License: Other open license
• Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
ZAF	5	n/a	n/a	South Africa

Indicators or Resource Contents

• This source file is packaged as a normalized tabular resource.

Schema

Column	Type	Description	Example
source_record_id	Int64	Stable row identifier for tabular resources.	0
country_iso3	category	ISO3 country code.	ZAF
country_name	category	Country name.	South Africa
geolevelid	int64	Source column.	1
geoleveldesc	string	Source column.	National
source_period_start_year	Int64	First year inferred from source resource metadata.	``
source_period_end_year	Int64	Last year inferred from source resource metadata.	``
source_period_label	category	Human-readable period inferred from source resource metadata.	``
source_provider	category	Publishing organization.	Statistics South Africa
source_dataset	category	Source package title.	Stats SA Census geographic levels
source_resource	category	Source resource title.	Stats SA Census geographic levels
source_package_id	category	CKAN package UUID.	stats-sa-census-geographic-levels-stats-sa-census-f828f77766d3d7
source_resource_id	category	CKAN resource UUID.	stats-sa-census-f828f77766d3d7
source_url	category	Original source resource URL.	https://disseminationapi-a2f6fff8f7a3f3ff.z01.azurefd.net/api/GeoLevels/
license_id	category	Source license identifier.	other-open
retrieved_at	category	UTC retrieval timestamp.	2026-07-22T20:13:23Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-south-africa-stats-sa-census-geographic-levels-cae3ed74")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "ZAF"]

Work with indicators

if "indicator_id" in df.columns:
    print(df["indicator_id"].value_counts().head())
    sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])

Citation

@misc{electric_sheep_africa_africa_south_africa_stats_sa_census_geographic_levels_cae3ed74_2026,
  title        = {Stats SA Census geographic levels | Africa (South Africa official open data)},
  author       = {Statistics South Africa},
  year         = {2026},
  url          = {https://census.statssa.gov.za},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-south-africa-stats-sa-census-geographic-levels-cae3ed74}}
}

License

Released under Other open license.

Original data (c) Statistics South Africa. When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.

About Electric Sheep

Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on Hugging Face. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.

Browse the full collection: huggingface.co/electricsheepafrica

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Provenance: ingested 2026-07-22 via the Electric Sheep pipeline. Source URL: https://disseminationapi-a2f6fff8f7a3f3ff.z01.azurefd.net/api/GeoLevels/getAll/