electricsheepafrica/africa-niger-niger-corruption-perceptions-index-8920a0be

Niger - Corruption Perceptions Index | Africa (Niger official open data)

84 rows - 1 Africa country - 2012-2025 - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one official CSV resource from Niger 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: Niger - Corruption Perceptions Index
• Publisher: Transparency International
• Resource: ner_cpi.csv
• Format: CSV
• License: CC BY 4.0
• Packaging mode: indicator_long

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
NER	84	2012	2025	Niger

Indicators or Resource Contents

• niger-corruption-perceptions-index-score-b5b1abb2 - Niger - Corruption Perceptions Index - score
• niger-corruption-perceptions-index-rank-a9e5e128 - Niger - Corruption Perceptions Index - rank
• niger-corruption-perceptions-index-sources-15a19094 - Niger - Corruption Perceptions Index - sources
• niger-corruption-perceptions-index-standarderror-45b47f1f - Niger - Corruption Perceptions Index - standarderror
• niger-corruption-perceptions-index-lowerci-d0f927da - Niger - Corruption Perceptions Index - lowerci
• niger-corruption-perceptions-index-upperci-1cb4d0f1 - Niger - Corruption Perceptions Index - upperci

Schema

Column	Type	Description	Example
indicator_id	string	Stable indicator identifier.	niger-corruption-perceptions-index-score-b5b1abb2
indicator_name	string	Human-readable indicator name.	Niger - Corruption Perceptions Index - score
country_iso3	string	ISO3 country code.	NER
country_name	string	Country name.	Niger
year	Int64	Observation year.	2025
value	float64	Numeric observation value.	31.0
unit	string	Measurement unit, when available.	source_units_unspecified
dimension_country	string	Source dimension.	Niger
dimension_iso3	string	Source dimension.	NER
dimension_region	string	Source dimension.	SSA
source_period_start_year	Int64	First year inferred from source resource metadata.	``
source_period_end_year	Int64	Last year inferred from source resource metadata.	``
source_period_label	string	Human-readable period inferred from source resource metadata.	``
source_provider	category	Publishing organization.	Transparency International
source_dataset	category	Source package title.	Niger - Corruption Perceptions Index
source_resource	category	Source resource title.	ner_cpi.csv
source_package_id	category	CKAN package UUID.	db343483-c92a-4b1f-a74f-e3ae36ed6c2b
source_resource_id	category	CKAN resource UUID.	e8cd8aad-4604-4efa-999c-5b60eb23eee6
source_url	category	Original source resource URL.	https://data.humdata.org/dataset/db343483-c92a-4b1f-a74f-e3ae36ed6c2b/re
license_id	category	Source license identifier.	cc-by
retrieved_at	category	UTC retrieval timestamp.	2026-08-14T00:35:21Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-niger-niger-corruption-perceptions-index-8920a0be")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "NER"]

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_niger_niger_corruption_perceptions_index_8920a0be_2025,
  title        = {Niger - Corruption Perceptions Index | Africa (Niger official open data)},
  author       = {Transparency International},
  year         = {2025},
  url          = {https://data.humdata.org/dataset/ner-corruption-perceptions-index},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-niger-niger-corruption-perceptions-index-8920a0be}}
}

License

Released under CC BY 4.0.

Original data (c) Transparency International. 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 2026-08-14 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/db343483-c92a-4b1f-a74f-e3ae36ed6c2b/resource/e8cd8aad-4604-4efa-999c-5b60eb23eee6/download/ner_cpi.csv