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

Cross Gender Ties | Africa (Mauritania 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 Mauritania 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
• Format: CSV
• License: CC BY 4.0
• Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
MRT	58,953	2025	2026	Mauritania

Indicators or Resource Contents

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

Schema

Column	Type	Description	Example
source_record_id	string	Stable row identifier for tabular resources.	550c183f-7869-489a-9fe4-197350929e56:0
country_iso3	category	ISO3 country code.	MRT
country_name	category	Country name.	Mauritania
region_id	string	Source column.	VNM.27.21.15_1
region_name	string	Source column.	Thanh Đa
country	string	Source column.	VN
level	string	Source column.	gadm3
cgfr_5	float64	Source column.	0.4618
cgfr_10	float64	Source column.	0.4565
cgfr_25	float64	Source column.	0.4627
cgfr_50	float64	Source column.	0.4908
cgfr_75	float64	Source column.	0.5172
cgfr_100	float64	Source column.	0.545
cgfr_125	float64	Source column.	0.554
cgfr_150	float64	Source column.	0.5722
cgfr_175	float64	Source column.	0.5852
cgfr_200	float64	Source column.	0.5944
source_period_start_year	Int64	First year inferred from source resource metadata.	2025
source_period_end_year	Int64	Last year inferred from source resource metadata.	2026
source_period_label	category	Human-readable period inferred from source resource metadata.	2025-2026
source_provider	category	Publishing organization.	AI for Good at Meta
source_dataset	category	Source package title.	Cross Gender Ties
source_resource	category	Source resource title.	gadm3_cgfr.csv
source_package_id	category	CKAN package UUID.	b138131c-52d0-48c0-8351-ee1c21cadf34
source_resource_id	category	CKAN resource UUID.	550c183f-7869-489a-9fe4-197350929e56
source_url	category	Original source resource URL.	https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/re
license_id	category	Source license identifier.	cc-by
retrieved_at	category	UTC retrieval timestamp.	2026-08-18T00:06:00Z

Usage

from datasets import load_dataset

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

Filter to one country

sample_country = df[df["country_iso3"] == "MRT"]

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_mauritania_cross_gender_ties_7e655171_2026,
  title        = {Cross Gender Ties | Africa (Mauritania 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-mauritania-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

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Provenance: ingested 2026-08-18 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