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electricsheepafrica/africa-drc-cross-gender-ties-7e655171

Cross Gender Ties | Africa (DRC official open data) 58,953 rows - 1 Africa country - 2025-2026 - Repackaged by Electric Sheep Africa TL;DR This dataset packages one official CSV resource from DRC 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: gadm3_cgfr.csv… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-drc-cross-gender-ties-7e655171.

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Dataset Card

Cross Gender Ties | Africa (DRC official open data)

58,953 rows - 1 Africa country - 2025-2026 - Repackaged by Electric Sheep Africa

rows countries years indicators license

TL;DR

This dataset packages one official CSV resource from DRC 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
COD58,95320252026DRC

Indicators or Resource Contents

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

Schema

ColumnTypeDescriptionExample
source_record_idstringStable row identifier for tabular resources.550c183f-7869-489a-9fe4-197350929e56:0
country_iso3categoryISO3 country code.COD
country_namecategoryCountry name.DRC
region_idstringSource column.VNM.27.21.15_1
region_namestringSource column.Thanh Đa
countrystringSource column.VN
levelstringSource column.gadm3
cgfr_5float64Source column.0.4618
cgfr_10float64Source column.0.4565
cgfr_25float64Source column.0.4627
cgfr_50float64Source column.0.4908
cgfr_75float64Source column.0.5172
cgfr_100float64Source column.0.545
cgfr_125float64Source column.0.554
cgfr_150float64Source column.0.5722
cgfr_175float64Source column.0.5852
cgfr_200float64Source column.0.5944
source_period_start_yearInt64First year inferred from source resource metadata.2025
source_period_end_yearInt64Last year inferred from source resource metadata.2026
source_period_labelcategoryHuman-readable period inferred from source resource metadata.2025-2026
source_providercategoryPublishing organization.AI for Good at Meta
source_datasetcategorySource package title.Cross Gender Ties
source_resourcecategorySource resource title.gadm3_cgfr.csv
source_package_idcategoryCKAN package UUID.b138131c-52d0-48c0-8351-ee1c21cadf34
source_resource_idcategoryCKAN resource UUID.550c183f-7869-489a-9fe4-197350929e56
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.2026-08-20T11:38:57Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-drc-cross-gender-ties-7e655171")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

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

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_drc_cross_gender_ties_7e655171_2026,
  title        = {Cross Gender Ties | Africa (DRC 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-drc-cross-gender-ties-7e655171}}
}

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 2026-08-20 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/550c183f-7869-489a-9fe4-197350929e56/download/gadm3_cgfr.csv