electricsheepafrica/africa-drc-democratic-republic-of-the-congo-corruption-perceptions-in-9ed8b46b

Democratic Republic of the Congo - Corruption Perceptions Index | Africa (DRC 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 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: Democratic Republic of the Congo - Corruption Perceptions Index
• —Publisher: Transparency International
• —Resource: cod_cpi.csv
• —Format: CSV
• —License: CC BY 4.0
• —Packaging mode: indicator_long

Geographic coverage

1 Africa country:

Indicators or Resource Contents

• —democratic-republic-of-the-congo-corruption-perceptions-index-score-e0e94624 - Democratic Republic of the Congo - Corruption Perceptions Index - score
• —democratic-republic-of-the-congo-corruption-perceptions-index-rank-bb4364ed - Democratic Republic of the Congo - Corruption Perceptions Index - rank
• —democratic-republic-of-the-congo-corruption-perceptions-index-sources-e8580b1a - Democratic Republic of the Congo - Corruption Perceptions Index - sources
• —democratic-republic-of-the-congo-corruption-perceptions-index-standarder-764ca47b - Democratic Republic of the Congo - Corruption Perceptions Index - standarderror
• —democratic-republic-of-the-congo-corruption-perceptions-index-lowerci-7f26d11e - Democratic Republic of the Congo - Corruption Perceptions Index - lowerci
• —democratic-republic-of-the-congo-corruption-perceptions-index-upperci-3314e023 - Democratic Republic of the Congo - Corruption Perceptions Index - upperci

Schema

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-drc-democratic-republic-of-the-congo-corruption-perceptions-in-9ed8b46b")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

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

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_drc_democratic_republic_of_the_congo_corruption_perceptions_in_9ed8b46b_2025,
  title        = {Democratic Republic of the Congo - Corruption Perceptions Index | Africa (DRC official open data)},
  author       = {Transparency International},
  year         = {2025},
  url          = {https://data.humdata.org/dataset/cod-corruption-perceptions-index},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-drc-democratic-republic-of-the-congo-corruption-perceptions-in-9ed8b46b}}
}

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

Provenance: ingested 2026-08-20 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/5f131823-f2c6-4e20-ac38-f874e62bdcfb/resource/48167918-0aa5-4278-b244-ae8dc23ddbb0/download/cod_cpi.csv