electricsheepafrica/africa-emissions-from-pre-and-post-agricultural-production-energy-use-total

Emissions from pre and post agricultural production — Energy Use (Total) | Africa (FAOSTAT)

🌍 7,459 observations · 52 Africa countries · 1990–2023 · Repackaged by Electric Sheep Africa

TL;DR

This dataset contains 7,459 observations of Climate Change data across 52 Africa countries, spanning 1990–2023, covering 7 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

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

Country	Rows	First year	Last year
South Africa	223	1990	2023
Zimbabwe	222	1990	2023
Eswatini	199	1990	2023
Mozambique	199	1990	2023
Gabon	198	1990	2023
Côte d'Ivoire	187	1990	2023
Egypt	187	1990	2023
Morocco	183	1990	2023
Benin	183	1990	2023
Senegal	178	1990	2023
Nigeria	171	1990	2023
Tunisia	169	1990	2023
Togo	169	1990	2023
Algeria	166	1990	2023
Cameroon	166	1990	2023
...	37 more countries

Indicators (sample)

• Pre- and post-production
• Energy Use (Pre- and Post-Production)
• Food Household Consumption
• Food Retail
• Food Packaging
• Food Processing
• Food Transport

Schema

Column	Type	Description	Example
country_name	string	—	Algeria
country_m49	int64	—	12
item	string	—	Food Processing
year	int64	—	2009
value	float64	—	16030.0
unit	string	—	TJ
flag	string	—	E

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-emissions-from-pre-and-post-agricultural-production-energy-use-total")
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"] == "Food Processing"]
          .sort_values("year"))
sample.plot(x="year", y="value", title="Food Processing")

Pivot to country × year matrix

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

Citation

@misc{africa_emissions_from_pre_and_post_agricultural_production_energy_use_total_2023,
  title        = {Emissions from pre and post agricultural production — Energy Use (Total) | Africa (FAOSTAT)},
  author       = {Food and Agriculture Organization of the United Nations (FAO)},
  year         = {2023},
  url          = {https://www.fao.org/faostat/en/#data/GPP},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-emissions-from-pre-and-post-agricultural-production-energy-use-total}}
}

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/GPP