--- license: other language: - en task_categories: - tabular-classification - tabular-regression multilinguality: multilingual size_categories: - n<1K tags: - "tabular" - "africa" - "open-data" - "official-statistics" - "nigeria" - "national-bureau-of-statistics-nigeria" - "economics" - "national-economy" - "nhk-report-october-2025" - "nhk-report-oct-2025-zip" - "0" - "document" - "nhk" - "report-doc" configs: - config_name: default data_files: - split: train path: data/train-00000-of-00001.parquet pretty_name: "National Household Kerosene Price Watch | Africa (National Bureau of Statistics, Nigeria)" --- # 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](https://huggingface.co/electricsheepafrica)* ![rows](https://img.shields.io/badge/rows-51-blue) ![countries](https://img.shields.io/badge/countries-1-green) ![period](https://img.shields.io/badge/period-2025-orange) ![indicators](https://img.shields.io/badge/indicators-0-purple) ![license](https://img.shields.io/badge/license-other-lightgrey) ## 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 ```python 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 ```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 - **Source:** [National Bureau of Statistics, Nigeria](https://microdata.nigerianstat.gov.ng/index.php/catalog/159/related-materials) - **Publisher:** National Bureau of Statistics, Nigeria - **Portal:** [https://microdata.nigerianstat.gov.ng](https://microdata.nigerianstat.gov.ng) - **Resource:** [NHK Report October 2025](https://microdata.nigerianstat.gov.ng/index.php/catalog/159/download/1329) - **License:** other-open - **Retrieved/generated:** `2026-07-19T04:19:14Z` - **Hugging Face repo:** [electricsheepafrica/africa-nigeria-national-household-kerosene-price-watch-291f6b7b](https://huggingface.co/datasets/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 ```bibtex @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. --- 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