electricsheepafrica/africa-congo-congo-brazzaville-risk-assessment-indicators-772d53bd

Congo Brazzaville - Risk Assessment Indicators | Africa (Congo official open data)

89 rows - 1 Africa country - not-applicable - Repackaged by Electric Sheep Africa

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: Congo Brazzaville - Risk Assessment Indicators
• Publisher: HeiGIT (Heidelberg Institute for Geoinformation Technology)
• Resource: COG_ADM2_coping.csv
• Format: CSV
• License: CC BY-SA
• Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
COG	89	n/a	n/a	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.	a792c454-5280-48f3-bb4a-c960e2a0988c:0
country_iso3	category	ISO3 country code.	COG
country_name	category	Country name.	Congo
adm2_pcode	string	Source column.	CG0901
access_pop_education_5km	int64	Source column.	0
access_pop_education_10km	int64	Source column.	0
access_pop_education_20km	int64	Source column.	0
access_pop_hospitals_30min	int64	Source column.	0
access_pop_hospitals_1h	int64	Source column.	54
access_pop_hospitals_2h	int64	Source column.	3387
access_pop_primary_healthcare_30min	int64	Source column.	0
access_pop_primary_healthcare_1h	int64	Source column.	0
access_pop_primary_healthcare_2h	int64	Source column.	0
education_count	int64	Source column.	0
hospitals_count	int64	Source column.	0
primary_healthcare_count	int64	Source column.	0
adm_pcode	string	Source column.	CG0901
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.	HeiGIT (Heidelberg Institute for Geoinformation Technology)
source_dataset	category	Source package title.	Congo Brazzaville - Risk Assessment Indicators
source_resource	category	Source resource title.	COG_ADM2_coping.csv
source_package_id	category	CKAN package UUID.	95c237ac-894f-470f-b7fc-5e20dd8cd111
source_resource_id	category	CKAN resource UUID.	a792c454-5280-48f3-bb4a-c960e2a0988c
source_url	category	Original source resource URL.	https://hot.storage.heigit.org/heigit-hdx-public/risk_assessment_inputs/
license_id	category	Source license identifier.	cc-by-sa
retrieved_at	category	UTC retrieval timestamp.	2026-08-16T12:36:20Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-congo-congo-brazzaville-risk-assessment-indicators-772d53bd")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "COG"]

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_congo_congo_brazzaville_risk_assessment_indicators_772d53bd_2026,
  title        = {Congo Brazzaville - Risk Assessment Indicators | Africa (Congo official open data)},
  author       = {HeiGIT (Heidelberg Institute for Geoinformation Technology)},
  year         = {2026},
  url          = {https://data.humdata.org/dataset/congo-brazzaville---risk-assessment-indicators},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-congo-congo-brazzaville-risk-assessment-indicators-772d53bd}}
}

License

Released under CC BY-SA.

Original data (c) HeiGIT (Heidelberg Institute for Geoinformation Technology). 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 2026-08-16 via the Electric Sheep pipeline. Source URL: https://hot.storage.heigit.org/heigit-hdx-public/risk_assessment_inputs/cog/COG_ADM2_coping.csv