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electricsheepafrica/africa-namibia-cross-gender-ties-3a3525eb

Cross Gender Ties | Africa (Namibia official open data) 1,291 rows - 1 Africa country - 2024-2026 - Repackaged by Electric Sheep Africa TL;DR This dataset packages one official CSV resource from Namibia 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: Cross Gender Ties Publisher: AI for Good at Meta Resource:… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-namibia-cross-gender-ties-3a3525eb.

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Dataset Card

Cross Gender Ties | Africa (Namibia official open data)

1,291 rows - 1 Africa country - 2024-2026 - Repackaged by Electric Sheep Africa

rows countries years indicators license

TL;DR

This dataset packages one official CSV resource from Namibia 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

Geographic coverage

1 Africa country:

CountryRowsFirst yearLast yearName
NAM1,29120242026Namibia

Indicators or Resource Contents

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

Schema

ColumnTypeDescriptionExample
source_record_idstringStable row identifier for tabular resources.59f1ec01-e145-4373-863d-cd9214a2792a:0
country_iso3categoryISO3 country code.NAM
country_namecategoryCountry name.Namibia
region_idstringSource column.CZ031
region_namestringSource column.Jihočeský kraj
countrystringSource column.CZ
levelstringSource column.nuts3_2024
cgfr_5float64Source column.0.5652
cgfr_10float64Source column.0.5415
cgfr_25float64Source column.0.5317
cgfr_50float64Source column.0.5434
cgfr_75float64Source column.0.5581
cgfr_100float64Source column.0.5717
cgfr_125float64Source column.0.5836
cgfr_150float64Source column.0.594
cgfr_175float64Source column.0.603
cgfr_200float64Source column.0.6107
source_period_start_yearInt64First year inferred from source resource metadata.2024
source_period_end_yearInt64Last year inferred from source resource metadata.2026
source_period_labelcategoryHuman-readable period inferred from source resource metadata.2024-2026
source_providercategoryPublishing organization.AI for Good at Meta
source_datasetcategorySource package title.Cross Gender Ties
source_resourcecategorySource resource title.nuts3_2024_cgfr.csv
source_package_idcategoryCKAN package UUID.b138131c-52d0-48c0-8351-ee1c21cadf34
source_resource_idcategoryCKAN resource UUID.59f1ec01-e145-4373-863d-cd9214a2792a
source_urlcategoryOriginal source resource URL.https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/re
license_idcategorySource license identifier.cc-by
retrieved_atcategoryUTC retrieval timestamp.2026-08-30T05:38:32Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-namibia-cross-gender-ties-3a3525eb")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

python
sample_country = df[df["country_iso3"] == "NAM"]

Work with indicators

python
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

bibtex
@misc{electric_sheep_africa_africa_namibia_cross_gender_ties_3a3525eb_2026,
  title        = {Cross Gender Ties | Africa (Namibia official open data)},
  author       = {AI for Good at Meta},
  year         = {2026},
  url          = {https://data.humdata.org/dataset/cross-gender-ties},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-namibia-cross-gender-ties-3a3525eb}}
}

License

Released under CC BY 4.0.

Original data (c) AI for Good at Meta. 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


Provenance: ingested 2026-08-30 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/59f1ec01-e145-4373-863d-cd9214a2792a/download/nuts32024cgfr.csv