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REC-00984034
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REC-00611298
2022-03-18
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REC-00126798
2023-12-12
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REC-00998362
2023-04-11
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REC-00808698
2022-04-09
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REC-00475838
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Rivers
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REC-00526985
2022-11-30
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REC-00036893
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REC-00338250
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REC-00570336
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REC-00309170
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2022-03-30
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REC-00337674
2024-02-23
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REC-00648553
2025-01-29
Yobe
153.33
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REC-00183479
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Osun
144.98
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REC-00907333
2025-02-20
Kogi
90.3
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REC-00315625
2024-06-13
Ogun
111.01
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REC-00919455
2022-05-29
Akwa Ibom
167.05
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REC-00883644
2024-01-28
Ebonyi
128.36
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REC-00170352
2024-12-08
Kogi
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REC-00915827
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Anambra
112.69
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REC-00379463
2024-04-27
Gombe
88.24
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REC-00638980
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Lagos
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REC-00958729
2022-04-30
Osun
149.39
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REC-00169074
2024-09-01
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REC-00503338
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REC-00871861
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REC-00136416
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Anambra
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REC-00699148
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Ondo
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REC-00969960
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Imo
89.93
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REC-00307755
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Ebonyi
33.06
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REC-00169059
2023-10-05
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91.43
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REC-00168715
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Abia
121.74
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REC-00334330
2023-11-11
Sokoto
147.38
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REC-00798579
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Gombe
172.26
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REC-00813074
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Akwa Ibom
198.7
A
End of preview. Expand in Data Studio

Africa Synth Agriculture Food Aid Nigeria | Africa (Electric Sheep Africa metadata inventory)

Size category: 10K<n<100K - Formats: parquet - Sector: agriculture_food - Engineered by Electric Sheep Africa

size sector downloads license

TL;DR

This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.

What This Dataset Covers

Public datasets help analysts inspect structured evidence, build reproducible workflows, and compare patterns across domains.

Dataset context from the existing Hugging Face card: ⚠️ Synthetic dataset — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference. Nigeria Agriculture – Food Aid Dataset Description Synthetic Food Security & Nutrition data for Nigeria agriculture sector. Category: Food Security & NutritionRows: 80,000Format: CSV, ParquetLicense: MITSynthetic: Yes (generated using reference data from FAO, NBS, NiMet, FMARD) Dataset Structure Schema… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-agriculture-food-aid-nigeria.

Dataset Profile

Field Value
Hugging Face repo electricsheepafrica/africa-synth-agriculture-food-aid-nigeria
Sector agriculture_food
Topic tags nigeria, agriculture, food-systems, synthetic, food-security-and-nutrition
Modalities text
Formats parquet
Size category 10K<n<100K
Countries Nigeria
ISO3 coverage NGA
Last modified on HF 2026-04-14 22:22:24+00:00
Inventory snapshot 2026-07-16T16:00:34Z

How To Read This Dataset

  • Start from the repository files and the dataset viewer when available.
  • Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
  • Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
  • Preserve missing values until you have a defensible imputation rule.

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-synth-agriculture-food-aid-nigeria")
print(ds)

split_name = next(iter(ds))
table = ds[split_name]
print(table.features)
print(table[:3])

Convert To Pandas When Tabular

from datasets import Dataset

first_split = ds[next(iter(ds))]
if isinstance(first_split, Dataset):
    df = first_split.to_pandas()
    print(df.head())

Data Quality Notes

  • This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
  • Exact schema, row counts, and source files should be inspected in the repository data files.
  • Metadata gaps from the inventory: upstream_publisher, language.
  • Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.

Source And Provenance

Suggested Analyses

  • Inspect schema and missingness before modeling.
  • Profile variables by geography, time, and subgroup columns where present.
  • Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
  • Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.

Citation

@misc{electric_sheep_africa_africa_synth_agriculture_food_aid_nigeria_2026,
  title        = {Africa Synth Agriculture Food Aid Nigeria | Africa (Electric Sheep Africa metadata inventory)},
  author       = {Public dataset metadata},
  year         = {2026},
  url          = {https://huggingface.co/datasets/electricsheepafrica/africa-synth-agriculture-food-aid-nigeria},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-synth-agriculture-food-aid-nigeria}}
}

License

Released under mit.

Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.

About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.


Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: catalog/esa_metadata_inventory/master_metadata.jsonl.

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