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electricsheepafrica/africa-nigeria-federation-account-allocation-committee-faac-disbursement-f8072e01

Federation Account Allocation Committee Faac Disbursement | Africa (National Bureau of Statistics, Nigeria) 1,349 rows - 1 Africa country/area - 2025 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 1,349 rows from National Bureau of Statistics, Nigeria, covering Federation Account Allocation Committee Faac Disbursement. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-nigeria-federation-account-allocation-committee-faac-disbursement-f8072e01.

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Dataset Card

Federation Account Allocation Committee Faac Disbursement | Africa (National Bureau of Statistics, Nigeria)

1,349 rows - 1 Africa country/area - 2025 - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

TL;DR

This dataset contains 1,349 rows from National Bureau of Statistics, Nigeria, covering Federation Account Allocation Committee Faac Disbursement. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Transport datasets help analysts examine mobility, infrastructure, passenger movement, logistics, and access to services.

Source-provided context: Document, Report [doc/rep]

How To Read This Dataset

  • —One row means: one source record from the original tabular resource, with Electric Sheep Africa provenance columns added where available.
  • —Primary geography column: country_iso3.
  • —Best time column: year.
  • —Time coverage basis: year.
  • —Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

DimensionValue
Rows1,349
Countries/areas1
First period2025
Last period2025
Indicators0
Columns80
Source formatZIP

Geographic Coverage

Top areas shown below, sorted by row count when available:

AreaRowsFirst yearLast yearName
NGA1,34920252025Nigeria

Indicators, Variables, Or Resource Contents

  • —This repo preserves one source tabular resource with its usable columns kept together.

Schema

ColumnTypeDescriptionExample
source_record_idstringStable row identifier assigned during Electric Sheep Africa engineering.nbs-nada-156-1349:disbursement-december-2025-xlsx:0
country_iso3stringISO3 country or area code.NGA
country_namestringCountry or area name.Nigeria
source_sheetstringSource column from the original resource.Disbursement December, 2025.xlsx::MONTHENTRY
yearint64Observation year.2025
column_1doubleSource column from the original resource.1.0
daystringSource column from the original resource.Jan
column_5doubleSource column from the original resource.1.0
source_period_start_yearint64Start year inferred from source metadata.2025
source_period_end_yearint64End year inferred from source metadata.2025
source_period_labelstringSource column from the original resource.2025
source_providerstringPublishing organization.National Bureau of Statistics, Nigeria
source_datasetstringSource dataset or package title.Federation Account Allocation Committee (FAAC) Disbursement
source_resourcestringSource resource title, table name, or file name.December 2025 FAAC Disbursement Report
source_package_idstringSource package identifier.NGA-NBS-FAAC
source_resource_idstringSource resource identifier.nbs-nada-156-1349
source_urlstringOriginal source URL or download URL.https://microdata.nigerianstat.gov.ng/index.php/catalog/156/download/...
license_idstringSource license identifier.other-open
retrieved_atstringUTC source retrieval timestamp from the Electric Sheep Africa pipeline.2026-07-19T04:13:01Z
s_ndoubleSource column from the original resource.``
beneficiariesstringSource column from the original resource.``
gross_statutory_allocationdoubleSource column from the original resource.``
deductionstringSource column from the original resource.``
net_statutory_allocationstringSource column from the original resource.``
electronic_money_transfer_levy_emtldoubleSource column from the original resource.``
othersstringSource column from the original resource.``
value_added_taxstringSource column from the original resource.``
totalstringSource column from the original resource.``
d_12doubleSource column from the original resource.``
edostringSource column from the original resource.``
d_18doubleSource column from the original resource.``
d_8133545146_98823doubleSource column from the original resource.``
d_3655388525_5245doubleSource column from the original resource.``
d_11788933672_5127doubleSource column from the original resource.``
d_1375175039_71doubleSource column from the original resource.``
d_510923032_41doubleSource column from the original resource.``
d_170793606_8doubleSource column from the original resource.``
d_9732041993_59273doubleSource column from the original resource.``
d_476507292_7277doubleSource column from the original resource.``
d_225236634_839674doubleSource column from the original resource.``
d_112618317_419837doubleSource column from the original resource.``
d_112618317_419837_2doubleSource column from the original resource.``
d_5598209963_7984doubleSource column from the original resource.``
d_0doubleSource column from the original resource.``
d_5598209963_7984_2doubleSource column from the original resource.``
d_18088887563_8785doubleSource column from the original resource.``
d_15919377567_5387doubleSource column from the original resource.``
d_12_2doubleSource column from the original resource.``
d_0_2doubleSource column from the original resource.``
d_1doubleSource column from the original resource.``
abiastringSource column from the original resource.``
d_1_2doubleSource column from the original resource.``
aba_northstringSource column from the original resource.``
d_269809525_42doubleSource column from the original resource.``
d_14036046_49doubleSource column from the original resource.``
d_8094285_7627doubleSource column from the original resource.``
d_8094285_7627_2doubleSource column from the original resource.``
d_154417759_04doubleSource column from the original resource.``
d_438263330_95doubleSource column from the original resource.``
column_12doubleSource column from the original resource.``
d_19doubleSource column from the original resource.``
d_26doubleSource column from the original resource.``
kanostringSource column from the original resource.``
kunchistringSource column from the original resource.``
d_285629121_94doubleSource column from the original resource.``
d_13209887_1doubleSource column from the original resource.``
d_8568873_6581doubleSource column from the original resource.``
d_8568873_6581_2doubleSource column from the original resource.``
d_165428541_87doubleSource column from the original resource.``
d_472836424_5681doubleSource column from the original resource.``
statestringSource column from the original resource.``
total_ecology_funddoubleSource column from the original resource.``
transfer_of_50_share_of_ecology_to_nddc_hyppadecdoubleSource column from the original resource.``
net_share_of_ecologydoubleSource column from the original resource.``
vatdoubleSource column from the original resource.``
total_net_allocationdoubleSource column from the original resource.``
statesstringSource column from the original resource.``
gross_statutory_allocation_ecologydoubleSource column from the original resource.``
local_government_councilsstringSource column from the original resource.``
total_ecologydoubleSource column from the original resource.``

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-nigeria-federation-account-allocation-committee-faac-disbursement-f8072e01")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

python
print(df.info())
print(df.head())

Filter By Geography

python
if "country_iso3" in df.columns:
    sample = df[df["country_iso3"] == "NGA"]

Time-Series Pattern

python
if "value" in df.columns and "year" in df.columns:
    trend = df.sort_values("year")

Pivot For Analysis

python
if {"indicator_id", "year", "value"}.issubset(df.columns):
    matrix = df.pivot_table(index="year", columns="indicator_id", values="value")
    print(matrix.tail())

Data Quality Notes

  • —Canonical time field: year.
  • —Missing values are preserved rather than silently imputed.
  • —Column names are standardized for machine use; source meanings are preserved where known.
  • —Always confirm source methodology, units, and collection definitions before policy, production, or redistribution-sensitive use.

Source And Provenance

Transformations Applied

  • —Converted the source table to Parquet for efficient analytics and ML workflows.
  • —Added or preserved source provenance columns where available.
  • —Standardized README metadata, dataset loading configuration, schema documentation, and citation format.
  • —Preserved source-reported values without analytical imputation.

Suggested Analyses

  • —Track mobility over time
  • —Compare routes or geographies
  • —Join with economic and population data
  • —Build time-series views and period-over-period comparisons
  • —Check missingness before modeling
  • —Use country_iso3 as the safest geography join key when present

Citation

bibtex
@misc{electric_sheep_africa_africa_nigeria_federation_account_allocation_committee_faac_disbursement_f8072e0_2025,
  title        = {Federation Account Allocation Committee Faac Disbursement | Africa (National Bureau of Statistics, Nigeria)},
  author       = {National Bureau of Statistics, Nigeria},
  year         = {2025},
  url          = {https://microdata.nigerianstat.gov.ng/index.php/catalog/156/related-materials},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-nigeria-federation-account-allocation-committee-faac-disbursement-f8072e01}}
}

License

Released under other-open.

Original data is published by National Bureau of Statistics, Nigeria. Electric Sheep Africa engineering standardizes the data for discovery, loading, and analysis on Hugging Face. Cite both the original source and this ML-ready dataset when used.

About Electric Sheep Africa

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


Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://microdata.nigerianstat.gov.ng/index.php/catalog/156/related-materials