Upload dataset folder

README.md

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+---
+license: cc-by-4.0
+language:
+- en
+task_categories:
+- tabular-classification
+- tabular-regression
+multilinguality: monolingual
+size_categories:
+- 10K<n<100K
+tags:
+- tabular
+- csv
+- africa
+- congo
+- official-statistics
+- open-data
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-00000-of-00001.parquet
+pretty_name: "Cross Gender Ties | Africa (Congo official open data)"
+---
+
+# Cross Gender Ties | Africa (Congo official open data)
+
+34,238 rows - 1 Africa country - 2025-2026 - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)
+
+![rows](https://img.shields.io/badge/rows-34238-blue)
+![countries](https://img.shields.io/badge/countries-1-green)
+![years](https://img.shields.io/badge/years-2025-2026-orange)
+![indicators](https://img.shields.io/badge/indicators-0-purple)
+![license](https://img.shields.io/badge/license-cc-by-4.0-lightgrey)
+
+## TL;DR
+
+This dataset packages one official `CSV` resource from **Congo** 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](https://data.humdata.org/dataset/cross-gender-ties)
+- **Publisher:** AI for Good at Meta
+- **Resource:** [geoboundaries_adm2_cgfr.csv](https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/4d0a6cbb-1f0a-49ea-8027-fa65b12a0fd5/download/geoboundaries_adm2_cgfr.csv)
+- **Format:** `CSV`
+- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
+- **Packaging mode:** `tabular_resource`
+
+## Geographic coverage
+
+1 Africa country:
+
+| Country | Rows | First year | Last year | Name |
+|---------|-----:|-----------:|----------:|------|
+| `COG` | 34,238 | 2025 | 2026 | `Congo` |
+
+## 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. | `4d0a6cbb-1f0a-49ea-8027-fa65b12a0fd5:0` |
+| `country_iso3` | `category` | ISO3 country code. | `COG` |
+| `country_name` | `category` | Country name. | `Congo` |
+| `region_id` | `string` | Source column. | `56859067B26511615248896` |
+| `region_name` | `string` | Source column. | `Barra do Piraí` |
+| `country` | `string` | Source column. | `BR` |
+| `level` | `string` | Source column. | `geoboundaries_adm2` |
+| `cgfr_5` | `float64` | Source column. | `0.6453` |
+| `cgfr_10` | `float64` | Source column. | `0.6065` |
+| `cgfr_25` | `float64` | Source column. | `0.587` |
+| `cgfr_50` | `float64` | Source column. | `0.5811` |
+| `cgfr_75` | `float64` | Source column. | `0.5842` |
+| `cgfr_100` | `float64` | Source column. | `0.5904` |
+| `cgfr_125` | `float64` | Source column. | `0.598` |
+| `cgfr_150` | `float64` | Source column. | `0.6062` |
+| `cgfr_175` | `float64` | Source column. | `0.6146` |
+| `cgfr_200` | `float64` | Source column. | `0.6224` |
+| `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. | `geoboundaries_adm2_cgfr.csv` |
+| `source_package_id` | `category` | CKAN package UUID. | `b138131c-52d0-48c0-8351-ee1c21cadf34` |
+| `source_resource_id` | `category` | CKAN resource UUID. | `4d0a6cbb-1f0a-49ea-8027-fa65b12a0fd5` |
+| `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. | `2026-08-16T12:36:20Z` |
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("electricsheepafrica/africa-congo-cross-gender-ties-df2c2d69")
+df = ds["train"].to_pandas()
+print(df.head())
+```
+
+### Filter to one country
+
+```python
+sample_country = df[df["country_iso3"] == "COG"]
+```
+
+### 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_congo_cross_gender_ties_df2c2d69_2026,
+  title        = {Cross Gender Ties | Africa (Congo 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-congo-cross-gender-ties-df2c2d69}}
+}
+```
+
+## License
+
+Released under [CC BY 4.0](https://creativecommons.org/licenses/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](https://huggingface.co/electricsheepafrica)
+
+---
+
+Provenance: ingested 2026-08-16 via the Electric Sheep pipeline. Source URL:
+https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/4d0a6cbb-1f0a-49ea-8027-fa65b12a0fd5/download/geoboundaries_adm2_cgfr.csv

data/train-00000-of-00001.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b4cb2e846a3d2eba5ff78173871ba2a3c516a353359de69ba29746950813ac2b
+size 1649144

metadata/source_snapshot.json

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+{
+  "columns": [
+    "source_record_id",
+    "country_iso3",
+    "country_name",
+    "region_id",
+    "region_name",
+    "country",
+    "level",
+    "cgfr_5",
+    "cgfr_10",
+    "cgfr_25",
+    "cgfr_50",
+    "cgfr_75",
+    "cgfr_100",
+    "cgfr_125",
+    "cgfr_150",
+    "cgfr_175",
+    "cgfr_200",
+    "source_period_start_year",
+    "source_period_end_year",
+    "source_period_label",
+    "source_provider",
+    "source_dataset",
+    "source_resource",
+    "source_package_id",
+    "source_resource_id",
+    "source_url",
+    "license_id",
+    "retrieved_at"
+  ],
+  "generated_at": "2026-08-16T12:55:10Z",
+  "indicator_count": 0,
+  "mode": "tabular_resource",
+  "repo_id": "electricsheepafrica/africa-congo-cross-gender-ties-df2c2d69",
+  "rows": 34238,
+  "source": {
+    "api_base_url": "https://data.humdata.org/api/3/action",
+    "country_iso3": "COG",
+    "country_name": "Congo",
+    "group_names": "afg,alb,dza,and,ago,arg,arm,aus,aut,aze,bhs,bhr,bgd,brb,blr,bel,blz,ben,btn,bol,bih,bwa,bra,brn,bgr,bfa,bdi,cpv,khm,cmr,can,caf,tcd,chl,hkg,col,com,cog,cri,civ,hrv,cub,cze,cod,dnk,dji,dom,ecu,egy,slv,gnq,eri,est,swz,eth,fji,fin,fra,gab,gmb,geo,deu,gha,grc,grd,gtm,gin,gnb,guy,hti,hnd,hun,isl,ind,idn,irq,irl,isr,ita,jam,jpn,jor,kaz,ken,kir,xkx,kwt,kgz,lao,lva,lbn,lso,lbr,lby,ltu,lux,mdg,mwi,mys,mdv,mli,mlt,mrt,mus,mex,fsm,mng,mne,mar,moz,mmr,nam,npl,nld,nzl,nic,ner,nga,mkd,nor,omn,pak,pan,png,pry,per,phl,pol,prt,qat,kor,mda,rou,rus,rwa,lca,vct,wsm,stp,sau,sen,srb,sle,sgp,svk,svn,slb,som,zaf,ssd,esp,lka,sdn,sur,swe,che,syr,twn,tjk,tha,tls,tgo,ton,tto,tun,tkm,tur,uga,ukr,are,gbr,tza,usa,ury,uzb,vut,ven,vnm,yem,zmb,zwe",
+    "license_id": "cc-by",
+    "license_title": "Creative Commons Attribution International (CC BY)",
+    "license_url": "http://www.opendefinition.org/licenses/cc-by",
+    "organization_name": "meta",
+    "organization_title": "AI for Good at Meta",
+    "package_id": "b138131c-52d0-48c0-8351-ee1c21cadf34",
+    "package_name": "cross-gender-ties",
+    "package_notes": "A global dataset of cross-gender friendship links at the subnational level spanning nearly 200 countries and territories, constructed from more than a trillion friendship ties among Facebook users. Citation for data: - Bailey, M., Johnston, D., Kuchler, T., Kumar, A., & Stroebel, J. (2025). “Cross-Gender Social Ties Around the World.” AEA Papers and Proceedings (Vol. 115, pp. 132-138). [(Paper available here)](https://pages.stern.nyu.edu/~jstroebe/PDF/BJKKS_GenderTies.pdf)",
+    "package_page_url": "https://data.humdata.org/dataset/cross-gender-ties",
+    "package_title": "Cross Gender Ties",
+    "portal_url": "https://data.humdata.org",
+    "resource_description": "Data as of January 25th, 2026. Each row represents a 2nd-level administrative division (ADM2) as defined by the geoBoundaries taxonomy.",
+    "resource_format": "CSV",
+    "resource_id": "4d0a6cbb-1f0a-49ea-8027-fa65b12a0fd5",
+    "resource_last_modified": "2026-01-27T23:35:33.927234",
+    "resource_name": "geoboundaries_adm2_cgfr.csv",
+    "resource_position": "5",
+    "resource_url": "https://data.humdata.org/dataset/b138131c-52d0-48c0-8351-ee1c21cadf34/resource/4d0a6cbb-1f0a-49ea-8027-fa65b12a0fd5/download/geoboundaries_adm2_cgfr.csv",
+    "tag_names": "economics,gender,men,social media data,socioeconomics,women"
+  },
+  "year_max": 2026,
+  "year_min": 2025
+}