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electricsheepafrica/africa-cabo-verde-cabo-verde-public-sector-53eb38b1

Cabo Verde - Public Sector | Africa (Cabo Verde official open data) 1,436 rows - 1 Africa country - 1976-2025 - Repackaged by Electric Sheep Africa TL;DR This dataset packages one official CSV resource from Cabo Verde 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: Cabo Verde - Public Sector Publisher: World Bank… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-cabo-verde-cabo-verde-public-sector-53eb38b1.

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Dataset Card

Cabo Verde - Public Sector | Africa (Cabo Verde official open data)

1,436 rows - 1 Africa country - 1976-2025 - Repackaged by Electric Sheep Africa

rows countries years indicators license

TL;DR

This dataset packages one official CSV resource from Cabo Verde 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
CPV1,43619762025Cabo Verde

Indicators or Resource Contents

  • —cabo-verde-public-sector-af3d3268 - Cabo Verde - Public Sector

Schema

ColumnTypeDescriptionExample
indicator_idstringStable indicator identifier.cabo-verde-public-sector-af3d3268
indicator_namestringHuman-readable indicator name.Cabo Verde - Public Sector
country_iso3stringISO3 country code.CPV
country_namestringCountry name.Cabo Verde
yearInt64Observation year.2020
valuefloat64Numeric observation value.1497436967.72219
unitstringMeasurement unit, when available.source_units_unspecified
dimension_country_namestringSource dimension.Cabo Verde
dimension_country_iso3stringSource dimension.CPV
dimension_indicator_namestringSource dimension.Net acquisition of financial assets (current LCU)
dimension_indicator_codestringSource dimension.GC.AST.TOTL.CN
source_period_start_yearInt64First year inferred from source resource metadata.``
source_period_end_yearInt64Last year inferred from source resource metadata.``
source_period_labelstringHuman-readable period inferred from source resource metadata.``
source_providercategoryPublishing organization.World Bank Group
source_datasetcategorySource package title.Cabo Verde - Public Sector
source_resourcecategorySource resource title.Public Sector Indicators for Cabo Verde
source_package_idcategoryCKAN package UUID.3c62ee8a-71b4-4977-9bec-5c2043a2c762
source_resource_idcategoryCKAN resource UUID.d1023f53-112d-4a43-880b-c6d55e1f57a5
source_urlcategoryOriginal source resource URL.https://data.humdata.org/dataset/3c62ee8a-71b4-4977-9bec-5c2043a2c762/re
license_idcategorySource license identifier.cc-by
retrieved_atcategoryUTC retrieval timestamp.2026-08-25T16:58:39Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-cabo-verde-cabo-verde-public-sector-53eb38b1")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

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

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_cabo_verde_cabo_verde_public_sector_53eb38b1_2025,
  title        = {Cabo Verde - Public Sector | Africa (Cabo Verde official open data)},
  author       = {World Bank Group},
  year         = {2025},
  url          = {https://data.humdata.org/dataset/world-bank-public-sector-indicators-for-cabo-verde},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-cabo-verde-cabo-verde-public-sector-53eb38b1}}
}

License

Released under CC BY 4.0.

Original data (c) World Bank Group. 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 2026-08-25 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/3c62ee8a-71b4-4977-9bec-5c2043a2c762/resource/d1023f53-112d-4a43-880b-c6d55e1f57a5/download/public-sector_cpv.csv