electricsheepafrica/africa-emissions-from-fires-emissions-n2o

Emissions from Fires — Emissions (N2O) | Africa (FAOSTAT)

🌍 16,560 observations · 54 Africa countries · 1990–2024 · Repackaged by Electric Sheep Africa

TL;DR

This dataset contains 16,560 observations of Climate Change data across 54 Africa countries, spanning 1990–2024, covering 9 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
Algeria	315	1990	2024
Angola	315	1990	2024
Benin	315	1990	2024
Botswana	315	1990	2024
Burkina Faso	315	1990	2024
Burundi	315	1990	2024
Cabo Verde	315	1990	2024
Cameroon	315	1990	2024
Central African Republic	315	1990	2024
Chad	315	1990	2024
Comoros	315	1990	2024
Congo	315	1990	2024
Côte d'Ivoire	315	1990	2024
Democratic Republic of the Congo	315	1990	2024
Djibouti	315	1990	2024
...	39 more countries

Indicators (sample)

• Forest fires
• Humid tropical forest
• Other forest
• Savanna fires
• Closed shrubland
• Grassland
• Open shrubland
• Savanna
• Woody savanna

Schema

Column	Type	Description	Example
country_name	string	—	Algeria
country_m49	int64	—	12
item	string	—	Forest fires
year	int64	—	1990
value	float64	—	0.146
unit	string	—	kt
flag	string	—	E

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-emissions-from-fires-emissions-n2o")
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"] == "Forest fires"]
          .sort_values("year"))
sample.plot(x="year", y="value", title="Forest fires")

Pivot to country × year matrix

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

Citation

@misc{africa_emissions_from_fires_emissions_n2o_2024,
  title        = {Emissions from Fires — Emissions (N2O) | Africa (FAOSTAT)},
  author       = {Food and Agriculture Organization of the United Nations (FAO)},
  year         = {2024},
  url          = {https://www.fao.org/faostat/en/#data/GI},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-emissions-from-fires-emissions-n2o}}
}

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/GI