electricsheepafrica/africa-emissions-from-livestock-indirect-emissions-n2o-that-volatilises-manure-on-pasture

Emissions from Livestock — Indirect emissions (N2O that volatilises) (Manure on pasture) | Africa (FAOSTAT)

🌍 57,822 observations · 54 Africa countries · 1961–2050 · Repackaged by Electric Sheep Africa

TL;DR

This dataset contains 57,822 observations of Climate Change data across 54 Africa countries, spanning 1961–2050, covering 23 distinct indicators.

About the source

• Source: FAOSTAT (FAO)
• Publisher: Food and Agriculture Organization of the United Nations (FAO)
• License: cc-by-4.0
• Topic: Climate Change

Geographic coverage

54 Africa countries · top rows shown below, sorted by row count:

Country	Rows	First year	Last year
Egypt	1,495	1961	2050
Algeria	1,430	1961	2050
Tunisia	1,365	1961	2050
Mauritius	1,365	1961	2050
Morocco	1,326	1961	2050
Sao Tome and Principe	1,300	1961	2050
Somalia	1,300	1961	2050
Zimbabwe	1,300	1961	2050
South Africa	1,300	1961	2050
Madagascar	1,235	1961	2050
Niger	1,235	1961	2050
Nigeria	1,235	1961	2050
Senegal	1,235	1961	2050
Mali	1,235	1961	2050
Chad	1,235	1961	2050
...	39 more countries

Indicators (sample)

• Cattle, dairy
• Cattle, non-dairy
• Goats
• Cattle
• Sheep and Goats
• All Animals
• Chickens, broilers
• Chickens
• Poultry Birds
• Sheep

Schema

Column	Type	Description	Example
country_name	string	—	Algeria
country_m49	int64	—	12
item	string	—	Asses
year	int64	—	1961
value	float64	—	0.0214
unit	string	—	kt
flag	string	—	E

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-emissions-from-livestock-indirect-emissions-n2o-that-volatilises-manure-on-pasture")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

kenya = df[df["country_name"] == "KEN"]

Time-series for a single indicator

sample = (df[df["item"] == "Asses"]
          .sort_values("year"))
sample.plot(x="year", y="value", title="Asses")

Pivot to country × year matrix

matrix = (df[df["item"] == "Asses"]
          .pivot_table(index="year", columns="country_name", values="value"))
print(matrix.tail())

Citation

@misc{africa_emissions_from_livestock_indirect_emissions_n2o_that_volatilises_manure_on_pasture_2050,
  title        = {Emissions from Livestock — Indirect emissions (N2O that volatilises) (Manure on pasture) | Africa (FAOSTAT)},
  author       = {Food and Agriculture Organization of the United Nations (FAO)},
  year         = {2050},
  url          = {https://www.fao.org/faostat/en/#data/GLE},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-emissions-from-livestock-indirect-emissions-n2o-that-volatilises-manure-on-pasture}}
}

License

Released under cc-by-4.0.

Original data © Food and Agriculture Organization of the United Nations (FAO). 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 HuggingFace. 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 2026-06-17 via the Electric Sheep pipeline. Source URL: https://www.fao.org/faostat/en/#data/GLE