CoolFace
Datasetpublic

electricsheepafrica/africa-drc-congo-dem-rep-environment-9b29113f

Congo, Dem. Rep. - Environment | Africa (DRC official open data) 4,653 rows - 1 Africa country - 1960-2025 - 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: Congo, Dem. Rep. - Environment Publisher: World Bank Group… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-drc-congo-dem-rep-environment-9b29113f.

sourceHugging Facecc-by-4.0updated 1mo agoView on Hugging Face
0likes36downloads
Dataset Card

Congo, Dem. Rep. - Environment | Africa (DRC official open data)

4,653 rows - 1 Africa country - 1960-2025 - Repackaged by Electric Sheep Africa

rows countries years indicators license

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

Geographic coverage

1 Africa country:

CountryRowsFirst yearLast yearName
COD4,65319602025DRC

Indicators or Resource Contents

  • —congo-dem-rep-environment-150658c6 - Congo, Dem. Rep. - Environment

Schema

ColumnTypeDescriptionExample
indicator_idstringStable indicator identifier.congo-dem-rep-environment-150658c6
indicator_namestringHuman-readable indicator name.Congo, Dem. Rep. - Environment
country_iso3stringISO3 country code.COD
country_namestringCountry name.DRC
yearInt64Observation year.2023
valuefloat64Numeric observation value.15.480763018019
unitstringMeasurement unit, when available.source_units_unspecified
dimension_country_namestringSource dimension.Congo, Dem. Rep.
dimension_country_iso3stringSource dimension.COD
dimension_indicator_namestringSource dimension.Agricultural land (% of land area)
dimension_indicator_codestringSource dimension.AG.LND.AGRI.ZS
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.Congo, Dem. Rep. - Environment
source_resourcecategorySource resource title.Environment Indicators for Congo, Dem. Rep.
source_package_idcategoryCKAN package UUID.ee7f6ab9-8275-4a1b-96d9-99261208477d
source_resource_idcategoryCKAN resource UUID.c5a0d4d1-3d8b-4c2d-9a8d-ddb0a14cf0e7
source_urlcategoryOriginal source resource URL.https://data.humdata.org/dataset/ee7f6ab9-8275-4a1b-96d9-99261208477d/re
license_idcategorySource license identifier.cc-by
retrieved_atcategoryUTC retrieval timestamp.2026-08-20T11:38:57Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-drc-congo-dem-rep-environment-9b29113f")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

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

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_drc_congo_dem_rep_environment_9b29113f_2025,
  title        = {Congo, Dem. Rep. - Environment | Africa (DRC official open data)},
  author       = {World Bank Group},
  year         = {2025},
  url          = {https://data.humdata.org/dataset/world-bank-environment-indicators-for-congo-dem-rep},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-drc-congo-dem-rep-environment-9b29113f}}
}

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 2026-08-20 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/ee7f6ab9-8275-4a1b-96d9-99261208477d/resource/c5a0d4d1-3d8b-4c2d-9a8d-ddb0a14cf0e7/download/environment_cod.csv