Dataset Viewer
Auto-converted to Parquet Duplicate
id
stringlengths
12
12
date
stringdate
2022-01-01 00:00:00
2025-03-30 00:00:00
state
stringclasses
37 values
value
float64
0
338
category
stringclasses
3 values
REC-00095494
2024-07-15
Cross River
148.93
B
REC-00996676
2023-11-29
Sokoto
5.19
A
REC-00666657
2022-02-20
Kebbi
127.57
C
REC-00437506
2024-07-13
Ogun
97.68
C
REC-00089814
2024-10-09
Osun
101.68
C
REC-00202492
2024-09-12
Ogun
113.41
A
REC-00311540
2023-11-02
Bauchi
123.88
A
REC-00334763
2024-06-17
Plateau
140.12
B
REC-00298839
2024-01-12
Oyo
217.01
C
REC-00294072
2024-06-07
Ondo
65.3
C
REC-00051602
2022-04-12
Borno
114.9
A
REC-00185981
2023-01-07
Bauchi
51.08
A
REC-00011436
2023-04-23
Ogun
102.35
B
REC-00737796
2023-03-22
Kogi
138.11
C
REC-00410203
2024-03-26
Kaduna
95.23
A
REC-00431239
2023-08-31
Gombe
170.45
B
REC-00128544
2024-03-16
Nasarawa
94.18
A
REC-00907448
2022-02-23
Kogi
63.79
C
REC-00363602
2023-04-01
Kebbi
98.73
A
REC-00342646
2025-01-20
Enugu
120.7
B
REC-00925245
2023-07-22
Kwara
0
B
REC-00188558
2024-08-24
Niger
142.29
A
REC-00230451
2023-12-20
Kwara
102.23
B
REC-00156836
2025-02-01
Ondo
97.87
B
REC-00979368
2024-07-12
Benue
21.58
B
REC-00261896
2024-04-06
Borno
76.8
A
REC-00299636
2023-09-22
Edo
73.37
B
REC-00505756
2022-12-06
Kwara
193.59
A
REC-00654077
2022-06-01
Sokoto
183.43
B
REC-00596858
2022-04-30
Jigawa
101.83
C
REC-00286505
2023-04-25
Kebbi
177.73
B
REC-00597781
2023-07-26
Lagos
12.54
B
REC-00909366
2022-12-24
Gombe
65.57
A
REC-00771127
2022-11-12
Abia
128.7
B
REC-00039683
2023-10-11
Katsina
64.12
B
REC-00295120
2022-07-09
Gombe
66.62
A
REC-00780815
2022-08-12
Enugu
56.16
A
REC-00282526
2024-08-08
Akwa Ibom
131.6
A
REC-00201025
2024-11-16
Kaduna
84.89
A
REC-00189868
2024-11-05
Ondo
144.76
A
REC-00375011
2023-11-16
Jigawa
72.57
B
REC-00799592
2023-08-20
Ogun
105.16
A
REC-00810276
2024-03-19
Nasarawa
86.51
A
REC-00305777
2025-03-09
Kaduna
52.13
C
REC-00802778
2022-06-29
Borno
120.61
A
REC-00671598
2025-03-06
Niger
66.03
B
REC-00900057
2023-04-24
Plateau
138.24
C
REC-00132689
2022-08-15
Bayelsa
131.89
A
REC-00992065
2023-09-24
Ekiti
83.37
A
REC-00854452
2024-05-13
Benue
38.26
B
REC-00448701
2024-11-13
Kogi
126.93
C
REC-00799454
2022-08-12
Yobe
58.79
C
REC-00638417
2024-01-06
Taraba
66.4
A
REC-00757527
2024-12-01
Benue
134.58
A
REC-00662505
2022-10-13
Jigawa
75.35
B
REC-00676824
2023-07-28
Ogun
63.25
A
REC-00030202
2022-02-01
Ebonyi
42.42
A
REC-00835439
2024-02-22
Plateau
85.2
B
REC-00156760
2023-12-27
Akwa Ibom
41.22
C
REC-00077440
2022-09-09
Kaduna
142.2
B
REC-00511277
2024-05-11
Osun
74.33
A
REC-00361625
2023-11-05
Kwara
187.77
C
REC-00893411
2023-02-19
Oyo
159.71
B
REC-00416732
2023-08-25
Sokoto
162.6
A
REC-00496896
2023-09-03
Cross River
168.84
A
REC-00146125
2022-01-06
Borno
122.23
A
REC-00927665
2022-05-19
Rivers
106.65
A
REC-00985285
2022-10-19
Oyo
85.89
B
REC-00848860
2022-06-14
FCT
143.09
A
REC-00362027
2022-03-21
Ebonyi
61.5
A
REC-00242078
2024-03-12
Benue
82.24
B
REC-00459274
2022-06-13
Anambra
81.99
B
REC-00217869
2022-03-17
Niger
90.65
B
REC-00960014
2023-01-25
Enugu
75.64
A
REC-00641912
2024-06-12
Kogi
83.41
A
REC-00948910
2024-07-16
Yobe
187.93
A
REC-00506174
2024-04-25
Ebonyi
164.96
A
REC-00721323
2024-08-25
Ondo
188.41
C
REC-00818036
2022-07-15
Kwara
0
B
REC-00168640
2023-09-20
Ebonyi
162.43
A
REC-00718295
2024-09-29
Borno
142.34
B
REC-00223129
2022-04-13
Bauchi
139.28
A
REC-00850788
2023-11-10
Imo
79.03
A
REC-00882304
2022-12-06
Gombe
133.86
A
REC-00206936
2022-06-25
Anambra
137.96
A
REC-00458502
2022-04-02
FCT
168.76
A
REC-00426245
2023-05-04
Gombe
135.84
A
REC-00433275
2022-10-26
Edo
72.96
B
REC-00112430
2023-09-09
Borno
87.41
B
REC-00023685
2023-06-05
Anambra
109.08
B
REC-00924952
2023-09-14
Lagos
102.5
C
REC-00198061
2025-01-26
Taraba
143.6
A
REC-00916286
2023-01-02
Ebonyi
67.1
A
REC-00936903
2024-03-14
Kwara
112.04
B
REC-00133291
2025-02-15
Kwara
57.74
A
REC-00394047
2023-06-17
Ekiti
0
B
REC-00222009
2022-12-27
Ondo
103.21
A
REC-00251426
2025-01-29
Bauchi
106.39
A
REC-00581205
2022-05-16
Ogun
71.15
C
REC-00627807
2024-10-21
Jigawa
166.99
A
End of preview. Expand in Data Studio

Africa Synth Agriculture Loans Credit 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 – Loans Credit Dataset Description Synthetic Agricultural Finance & Insurance data for Nigeria agriculture sector. Category: Agricultural Finance & InsuranceRows: 120,000Format: 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-loans-credit-nigeria.

Dataset Profile

Field Value
Hugging Face repo electricsheepafrica/africa-synth-agriculture-loans-credit-nigeria
Sector agriculture_food
Topic tags nigeria, agriculture, food-systems, synthetic, agricultural-finance-and-insurance
Modalities text
Formats parquet
Size category 100K<n<1M
Countries Nigeria
ISO3 coverage NGA
Last modified on HF 2026-04-14 22:23:07+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-loans-credit-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_loans_credit_nigeria_2026,
  title        = {Africa Synth Agriculture Loans Credit Nigeria | Africa (Electric Sheep Africa metadata inventory)},
  author       = {Public dataset metadata},
  year         = {2026},
  url          = {https://huggingface.co/datasets/electricsheepafrica/africa-synth-agriculture-loans-credit-nigeria},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-synth-agriculture-loans-credit-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.

Downloads last month
38

Collections including electricsheepafrica/africa-synth-agriculture-loans-credit-nigeria