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Mauritania: Greenhouse Gas and Air Pollutant Emissions | Africa (Mauritania official open data)

17,160 rows - 1 Africa country - 2024-2026 - Repackaged by Electric Sheep Africa

rows countries years indicators license

TL;DR

This dataset packages one official CSV resource from Mauritania 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:

Country Rows First year Last year Name
MRT 17,160 2024 2026 Mauritania

Indicators or Resource Contents

  • mauritania-greenhouse-gas-and-air-pollutant-emissions-month-b56c2abe - Mauritania: Greenhouse Gas and Air Pollutant Emissions - month
  • mauritania-greenhouse-gas-and-air-pollutant-emissions-emissionsquantity-5efae8ac - Mauritania: Greenhouse Gas and Air Pollutant Emissions - emissionsquantity

Schema

Column Type Description Example
indicator_id string Stable indicator identifier. mauritania-greenhouse-gas-and-air-pollutant-emissions-month-b56c2abe
indicator_name string Human-readable indicator name. Mauritania: Greenhouse Gas and Air Pollutant Emissions - month
country_iso3 string ISO3 country code. MRT
country_name string Country name. Mauritania
year Int64 Observation year. 2024
value float64 Numeric observation value. 8.0
unit string Measurement unit, when available. source_units_unspecified
dimension_id string Source dimension. ghs-fua_729
dimension_name string Source dimension. Kaédi Urban Area, MRT
dimension_country string Source dimension. MRT
dimension_alternatenames string Source dimension. ['Kaédi']
dimension_sector string Source dimension. agriculture
dimension_gas string Source dimension. co2e_20yr
source_period_start_year Int64 First year inferred from source resource metadata. 2015
source_period_end_year Int64 Last year inferred from source resource metadata. 2021
source_period_label category Human-readable period inferred from source resource metadata. 2015-2021
source_provider category Publishing organization. Climate TRACE
source_dataset category Source package title. Mauritania: Greenhouse Gas and Air Pollutant Emissions
source_resource category Source resource title. mrt_co2e_20yr_city.csv
source_package_id category CKAN package UUID. 6d927dde-4366-4dc3-9b81-c4716a278cdd
source_resource_id category CKAN resource UUID. b3567dce-fbee-4a7f-ab80-383f0c487bb0
source_url category Original source resource URL. https://data.humdata.org/dataset/6d927dde-4366-4dc3-9b81-c4716a278cdd/re
license_id category Source license identifier. cc-by
retrieved_at category UTC retrieval timestamp. 2026-08-18T00:06:00Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritania-mauritania-greenhouse-gas-and-air-pollutant-emissions-daa995f7")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "MRT"]

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_mauritania_mauritania_greenhouse_gas_and_air_pollutant_emissions_daa995f7_2026,
  title        = {Mauritania: Greenhouse Gas and Air Pollutant Emissions | Africa (Mauritania official open data)},
  author       = {Climate TRACE},
  year         = {2026},
  url          = {https://data.humdata.org/dataset/mrt-climate-trace},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritania-mauritania-greenhouse-gas-and-air-pollutant-emissions-daa995f7}}
}

License

Released under CC BY 4.0.

Original data (c) Climate TRACE. 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 2026-08-18 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/6d927dde-4366-4dc3-9b81-c4716a278cdd/resource/b3567dce-fbee-4a7f-ab80-383f0c487bb0/download/mrt_co2e_20yr_city.csv

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