electricsheepafrica/africa-nigeria-national-household-kerosene-price-watch-291f6b7b

National Household Kerosene Price Watch | Africa (National Bureau of Statistics, Nigeria)

51 rows - 1 Africa country/area - 2025 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 51 rows from National Bureau of Statistics, Nigeria, covering National Household Kerosene Price Watch. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Economic datasets help analysts examine production, prices, public finance, trade flows, market conditions, and macroeconomic change.

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

Dimension	Value
Rows	51
Countries/areas	1
First period	2025
Last period	2025
Indicators	0
Columns	27
Source format	ZIP

Geographic Coverage

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

Area	Rows	First year	Last year	Name
NGA	51	2025	2025	Nigeria

Indicators, Variables, Or Resource Contents

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

Schema

Column	Type	Description	Example
source_record_id	string	Stable row identifier assigned during Electric Sheep Africa engineering.	nbs-nada-159-1329:0
country_iso3	string	ISO3 country or area code.	NGA
country_name	string	Country or area name.	Nigeria
year	int64	Observation year.	2025
north_central	string	Source column from the original resource.	Abuja
d_2242_674201064777	double	Source column from the original resource.	2875.0
d_1790_5719366323756	double	Source column from the original resource.	1655.9835
d_2702_800502298753	double	Source column from the original resource.	2153.49191666667
d_50_946211487155026	double	Source column from the original resource.	30.043078126483152
d_20_5168588917426	double	Source column from the original resource.	-25.09593333333322
north_central_2	string	Source column from the original resource.	Abuja
d_6176_202336834174	double	Source column from the original resource.	6600.75
d_7861_645143417122	double	Source column from the original resource.	8301.92575
d_10045_895609535155	double	Source column from the original resource.	9813.9676666667
d_27_783630859337308	double	Source column from the original resource.	18.21314671077008
d_62_65489797221451	double	Source column from the original resource.	48.679584390663166
source_period_start_year	int64	Start year inferred from source metadata.	2025
source_period_end_year	int64	End year inferred from source metadata.	2025
source_period_label	string	Source column from the original resource.	2025
source_provider	string	Publishing organization.	National Bureau of Statistics, Nigeria
source_dataset	string	Source dataset or package title.	National Household Kerosene Price Watch
source_resource	string	Source resource title, table name, or file name.	NHK Report October 2025
source_package_id	string	Source package identifier.	NGA-NBS-NHK
source_resource_id	string	Source resource identifier.	nbs-nada-159-1329
source_url	string	Original source URL or download URL.	https://microdata.nigerianstat.gov.ng/index.php/catalog/159/download/...
license_id	string	Source license identifier.	other-open
retrieved_at	string	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-07-19T04:13:01Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-nigeria-national-household-kerosene-price-watch-291f6b7b")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

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

Filter By Geography

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

Time-Series Pattern

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

Pivot For Analysis

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

• Source: National Bureau of Statistics, Nigeria
• Publisher: National Bureau of Statistics, Nigeria
• Portal: https://microdata.nigerianstat.gov.ng
• Resource: NHK Report October 2025
• License: other-open
• Retrieved/generated: 2026-07-19T04:19:14Z
• Hugging Face repo: electricsheepafrica/africa-nigeria-national-household-kerosene-price-watch-291f6b7b

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

• Build time-series dashboards
• Compare economic indicators
• Join with population or sector 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

@misc{electric_sheep_africa_africa_nigeria_national_household_kerosene_price_watch_291f6b7b_2025,
  title        = {National Household Kerosene Price Watch | Africa (National Bureau of Statistics, Nigeria)},
  author       = {National Bureau of Statistics, Nigeria},
  year         = {2025},
  url          = {https://microdata.nigerianstat.gov.ng/index.php/catalog/159/related-materials},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-nigeria-national-household-kerosene-price-watch-291f6b7b}}
}

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.

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Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://microdata.nigerianstat.gov.ng/index.php/catalog/159/related-materials