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state
stringclasses
37 values
lga
stringclasses
518 values
crop
stringclasses
8 values
season
stringclasses
7 values
area_ha
float64
100
50k
yield_t_ha
float64
0.1
20
production_t
float64
10
794k
quality_grade
stringclasses
3 values
Rivers
Rivers-LGA-13
yam
2025_wet
306.5
12.41
3,802.8
Grade A
Kwara
Kwara-LGA-10
cassava
2022_dry
100.1
10.93
1,093.3
Grade A
Taraba
Taraba-LGA-13
sorghum
2023_wet
624.2
0.97
608
Grade A
Katsina
Katsina-LGA-02
yam
2023_wet
545
6.43
3,503.9
Grade A
Enugu
Enugu-LGA-07
rice
2024_wet
2,591.8
3.03
7,855.6
Grade A
Imo
Imo-LGA-03
oil_palm
2024_dry
165.5
3.04
503.9
Grade A
Borno
Borno-LGA-13
yam
2022_dry
100
5
500
Grade B
Delta
Delta-LGA-09
cassava
2023_dry
777.6
12.3
9,564.8
Grade B
FCT
FCT-LGA-02
cassava
2023_wet
100
10.35
1,034.7
Grade B
Cross River
Cross River-LGA-03
cassava
2022_dry
2,253.2
9.22
20,778.7
Grade B
Ogun
Ogun-LGA-10
yam
2022_dry
1,622.1
9
14,600.1
Grade A
Kogi
Kogi-LGA-07
cocoa
2022_dry
100
0.52
52
Grade A
Abia
Abia-LGA-02
cocoa
2022_dry
439
0.45
197.1
Grade B
Cross River
Cross River-LGA-07
sorghum
2022_wet
105.3
2.01
211.2
Grade B
Adamawa
Adamawa-LGA-13
rice
2025_wet
681.4
1.88
1,280.9
Grade B
Kogi
Kogi-LGA-09
rice
2025_wet
211.8
2.57
544.8
Grade B
Bauchi
Bauchi-LGA-01
millet
2024_wet
156.5
1.54
241.8
Grade B
Abia
Abia-LGA-08
sorghum
2025_wet
100
1.82
181.6
Grade B
Taraba
Taraba-LGA-08
rice
2025_wet
1,322.5
4.05
5,350
Grade B
Kaduna
Kaduna-LGA-08
maize
2022_dry
484.7
2.1
1,016.6
Grade B
Edo
Edo-LGA-04
millet
2022_dry
100
0.98
98.4
Grade A
Kebbi
Kebbi-LGA-02
rice
2024_dry
1,530.1
3.21
4,917.5
Grade B
Katsina
Katsina-LGA-08
cocoa
2025_wet
524.7
0.33
171.2
Grade C
Ogun
Ogun-LGA-01
millet
2022_dry
505.5
1.03
518.6
Grade A
Oyo
Oyo-LGA-08
yam
2023_wet
944.2
10.82
10,212.6
Grade B
Ebonyi
Ebonyi-LGA-11
cassava
2022_wet
196.8
11.81
2,323.6
Grade B
Kogi
Kogi-LGA-14
millet
2025_wet
883.2
0.83
730.1
Grade C
Sokoto
Sokoto-LGA-11
yam
2022_dry
419
10.43
4,370.3
Grade B
Abia
Abia-LGA-07
cassava
2024_dry
1,047.1
12.13
12,696.7
Grade B
Imo
Imo-LGA-04
yam
2022_wet
1,227.8
12.57
15,433.5
Grade C
Yobe
Yobe-LGA-14
cassava
2023_wet
101.7
7.67
780.1
Grade B
Sokoto
Sokoto-LGA-04
cocoa
2024_dry
1,455.9
0.35
505.2
Grade B
Kebbi
Kebbi-LGA-14
rice
2024_wet
152.2
3.85
586.3
Grade A
Plateau
Plateau-LGA-13
sorghum
2025_wet
6,763.1
1.98
13,398.1
Grade B
Bauchi
Bauchi-LGA-14
cassava
2022_dry
275.2
11.62
3,198.9
Grade A
Bauchi
Bauchi-LGA-07
rice
2023_dry
100
2.4
240.1
Grade A
FCT
FCT-LGA-07
sorghum
2025_wet
176.6
0.52
92.3
Grade C
Cross River
Cross River-LGA-12
yam
2022_dry
138.1
12.27
1,693.5
Grade C
Ebonyi
Ebonyi-LGA-14
cassava
2024_dry
172.6
12.04
2,078.3
Grade A
Benue
Benue-LGA-12
yam
2022_dry
1,900
15.32
29,109.9
Grade C
Kwara
Kwara-LGA-12
maize
2022_dry
265.2
1.71
452.3
Grade A
Rivers
Rivers-LGA-02
yam
2022_dry
100
13.74
1,373.7
Grade B
Imo
Imo-LGA-10
oil_palm
2023_wet
100
3.59
359
Grade B
Edo
Edo-LGA-08
oil_palm
2022_wet
353.8
3.47
1,225.9
Grade C
Oyo
Oyo-LGA-01
sorghum
2024_wet
100
1.18
118.1
Grade B
Oyo
Oyo-LGA-06
millet
2024_wet
246.1
0.68
166.9
Grade B
Bauchi
Bauchi-LGA-08
yam
2024_dry
393.3
10.91
4,289.5
Grade A
Yobe
Yobe-LGA-11
yam
2024_dry
1,338
5
6,689.9
Grade B
Niger
Niger-LGA-10
millet
2025_wet
100
0.48
48
Grade B
Lagos
Lagos-LGA-02
oil_palm
2023_wet
100
2.82
282.4
Grade B
Rivers
Rivers-LGA-09
maize
2023_dry
600.1
2.11
1,267.3
Grade B
Nasarawa
Nasarawa-LGA-14
cocoa
2022_wet
1,443.1
0.55
793.1
Grade A
Kogi
Kogi-LGA-04
cassava
2023_wet
919.9
8.12
7,468.3
Grade B
Gombe
Gombe-LGA-05
maize
2024_wet
492.6
1.98
974.7
Grade A
Kano
Kano-LGA-11
maize
2024_wet
759.9
1.94
1,474.7
Grade A
Borno
Borno-LGA-14
sorghum
2022_wet
353.7
0.87
307.7
Grade A
Sokoto
Sokoto-LGA-14
millet
2024_dry
100
1.37
137.1
Grade A
Ogun
Ogun-LGA-12
cassava
2025_wet
1,142.2
11.83
13,516.8
Grade A
Oyo
Oyo-LGA-06
yam
2024_wet
755.4
13.41
10,129.5
Grade B
Benue
Benue-LGA-07
cassava
2024_wet
227.2
10.55
2,395.9
Grade C
Akwa Ibom
Akwa Ibom-LGA-07
sorghum
2022_dry
335.1
1.8
604.7
Grade B
Cross River
Cross River-LGA-10
cocoa
2025_wet
194.5
0.55
106.8
Grade C
Ogun
Ogun-LGA-11
oil_palm
2022_dry
171.9
4.32
742.6
Grade B
Ebonyi
Ebonyi-LGA-08
cocoa
2025_wet
201.5
0.38
76.4
Grade B
Zamfara
Zamfara-LGA-12
sorghum
2024_wet
100
1.36
135.7
Grade A
Bayelsa
Bayelsa-LGA-01
cocoa
2025_wet
295.9
0.21
62.1
Grade A
Kano
Kano-LGA-12
oil_palm
2023_dry
100
1.04
104.4
Grade C
Cross River
Cross River-LGA-08
maize
2023_wet
1,291.6
4.44
5,732.1
Grade A
Plateau
Plateau-LGA-11
cassava
2024_dry
2,209.9
7.04
15,552.9
Grade B
Bayelsa
Bayelsa-LGA-08
yam
2022_wet
1,893.3
9.5
17,991.3
Grade C
Rivers
Rivers-LGA-13
maize
2023_dry
189.4
2.93
555.3
Grade B
Delta
Delta-LGA-10
oil_palm
2022_wet
100
4.31
430.6
Grade C
Ogun
Ogun-LGA-01
cassava
2024_dry
265.2
7.39
1,961.1
Grade C
FCT
FCT-LGA-07
maize
2022_dry
489.2
1.34
656.7
Grade B
Kano
Kano-LGA-06
cassava
2025_wet
100
8.6
859.9
Grade B
Bauchi
Bauchi-LGA-06
oil_palm
2023_dry
721.5
4.11
2,968.3
Grade B
Anambra
Anambra-LGA-14
yam
2024_wet
531.5
10.52
5,593.9
Grade C
Osun
Osun-LGA-06
cassava
2023_dry
343
12.04
4,129.1
Grade A
Abia
Abia-LGA-11
oil_palm
2023_wet
2,545.7
5.94
15,122.5
Grade B
Borno
Borno-LGA-03
sorghum
2023_wet
456.8
1.02
465
Grade B
Rivers
Rivers-LGA-14
cassava
2024_wet
356.8
12.55
4,479
Grade B
Gombe
Gombe-LGA-05
cocoa
2023_wet
100
0.29
28.5
Grade B
Lagos
Lagos-LGA-08
maize
2023_dry
371.6
1.52
564.9
Grade B
Abia
Abia-LGA-05
yam
2023_dry
678.6
9.18
6,233.2
Grade B
Nasarawa
Nasarawa-LGA-14
maize
2025_wet
5,263.7
2.66
14,009.3
Grade A
Plateau
Plateau-LGA-10
rice
2024_wet
222.4
3.55
790.3
Grade B
Yobe
Yobe-LGA-04
millet
2022_wet
1,932.8
0.79
1,528.2
Grade B
Ogun
Ogun-LGA-09
oil_palm
2023_dry
1,011.5
3.82
3,862.7
Grade C
Osun
Osun-LGA-13
maize
2024_wet
3,892.9
2.28
8,890.3
Grade B
Ondo
Ondo-LGA-03
yam
2024_wet
100
10.42
1,042.4
Grade A
Bayelsa
Bayelsa-LGA-01
yam
2023_wet
333.9
10.65
3,555.8
Grade C
Sokoto
Sokoto-LGA-08
maize
2022_wet
110.6
1.7
188.3
Grade B
Ondo
Ondo-LGA-03
maize
2022_dry
1,574.4
1.93
3,038.4
Grade B
Rivers
Rivers-LGA-06
maize
2024_dry
831
1.64
1,363.2
Grade B
Osun
Osun-LGA-14
sorghum
2024_dry
31,196.5
1.86
58,159.4
Grade C
Zamfara
Zamfara-LGA-11
maize
2023_wet
1,031.4
2.22
2,289.4
Grade A
Edo
Edo-LGA-10
cocoa
2022_wet
1,855.3
0.34
627.9
Grade B
Ogun
Ogun-LGA-11
millet
2025_wet
106.9
1.8
192.8
Grade A
Rivers
Rivers-LGA-08
cassava
2023_dry
100
12.3
1,229.8
Grade C
Ebonyi
Ebonyi-LGA-04
oil_palm
2024_wet
100
2.86
285.5
Grade A
End of preview. Expand in Data Studio

Africa Synth Agriculture Seasonal Crop Yields Nigeria | Africa (Electric Sheep Africa metadata inventory)

Size category: 100K<n<1M - 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 – Seasonal Crop Yields Dataset Description State/LGA-level yields by crop, season, area, production, and quality grade. Category: Crop Production & YieldsRows: 140,000Format: CSV, ParquetLicense: MITSynthetic: Yes (generated using reference data from FAO, NBS, NiMet, FMARD) Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-agriculture-seasonal-crop-yields-nigeria.

Dataset Profile

Field Value
Hugging Face repo electricsheepafrica/africa-synth-agriculture-seasonal-crop-yields-nigeria
Sector agriculture_food
Topic tags nigeria, agriculture, food-systems, synthetic, crop-production-and-yields
Modalities tabular, text
Formats parquet
Size category 100K<n<1M
Countries Nigeria
ISO3 coverage NGA
Last modified on HF 2026-04-14 22:23:45+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-seasonal-crop-yields-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_seasonal_crop_yields_nigeria_2026,
  title        = {Africa Synth Agriculture Seasonal Crop Yields Nigeria | Africa (Electric Sheep Africa metadata inventory)},
  author       = {Public dataset metadata},
  year         = {2026},
  url          = {https://huggingface.co/datasets/electricsheepafrica/africa-synth-agriculture-seasonal-crop-yields-nigeria},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-synth-agriculture-seasonal-crop-yields-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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