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electricsheepafrica/africa-nigeria-cost-of-healthy-diet-4436bde3

Cost of Healthy Diet | Africa (National Bureau of Statistics, Nigeria) 95 rows - 1 Africa country/area - 2025 - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 95 rows from National Bureau of Statistics, Nigeria, covering Cost of Healthy Diet. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples. What This Dataset Measures Health… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-nigeria-cost-of-healthy-diet-4436bde3.

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Dataset Card

Cost of Healthy Diet | Africa (National Bureau of Statistics, Nigeria)

95 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 95 rows from National Bureau of Statistics, Nigeria, covering Cost of Healthy Diet. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Health datasets help analysts monitor disease burden, service delivery, population health outcomes, and public-health program performance.

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
Rows95
Countries/areas1
First period2025
Last period2025
Indicators0
Columns37
Source formatZIP

Geographic Coverage

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

AreaRowsFirst yearLast yearName
NGA9520252025Nigeria

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-146-1381:cohd-december-2025-table-xlsx-co:0
country_iso3stringISO3 country or area code.NGA
country_namestringCountry or area name.Nigeria
source_sheetstringSource column from the original resource.CoHD_December 2025_Table.xlsx::CoHD by national average
yearint64Observation year.2025
statestringSource column from the original resource.Ekiti
cohd_averagedoubleSource column from the original resource.1820.240510168211
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.Cost Of Healthy Diet
source_resourcestringSource resource title, table name, or file name.Cost of Healthy Diet Report December 2025
source_package_idstringSource package identifier.NGA-NBS-COHD
source_resource_idstringSource resource identifier.nbs-nada-146-1381
source_urlstringOriginal source URL or download URL.https://microdata.nigerianstat.gov.ng/index.php/catalog/146/download/...
license_idstringSource license identifier.other-open
retrieved_atstringUTC source retrieval timestamp from the Electric Sheep Africa pipeline.2026-07-19T04:13:01Z
zonestringSource column from the original resource.``
cohd_urbandoubleSource column from the original resource.``
cohd_ruraldoubleSource column from the original resource.``
valuestringNumeric observation value.``
2025stringSource column from the original resource.``
2025_2stringSource column from the original resource.``
2025_3stringSource column from the original resource.``
2025_4stringSource column from the original resource.``
2025_5stringSource column from the original resource.``
2025_6stringSource column from the original resource.``
2025_7stringSource column from the original resource.``
2025_8stringSource column from the original resource.``
2025_9stringSource column from the original resource.``
2025_10stringSource column from the original resource.``
2025_11stringSource column from the original resource.``
2025_12stringSource column from the original resource.``
nationalstringSource column from the original resource.``
food_groupstringSource column from the original resource.``
daily_costdoubleSource column from the original resource.``

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-nigeria-cost-of-healthy-diet-4436bde3")
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

  • —Compare health outcomes across geographies
  • —Track changes over time
  • —Join with population or facility 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_cost_of_healthy_diet_4436bde3_2025,
  title        = {Cost of Healthy Diet | Africa (National Bureau of Statistics, Nigeria)},
  author       = {National Bureau of Statistics, Nigeria},
  year         = {2025},
  url          = {https://microdata.nigerianstat.gov.ng/index.php/catalog/146/related-materials},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-nigeria-cost-of-healthy-diet-4436bde3}}
}

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/146/related-materials