electricsheepafrica/africa-rwanda-vaccinations-by-background-characteristics-2025-f3bec1e2

Vaccinations by Background Characteristics (2025) | Africa (Rwanda Data Sharing Platform - NISR)

26 rows - 1 Africa country/area - 2025-06-01-2025-11-30 - source table - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

TL;DR

This dataset contains 26 rows from Rwanda Data Sharing Platform - NISR, covering Vaccinations by Background Characteristics (2025). 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: Summary: This aggregated data table contains data on vaccinations by background characteristics. This data was collected in the 2025 Rwanda Demographic and Health Survey (2025 RDHS). It is part of the Key Indicators Report, which presents preliminary findings on fertility, family planning, maternal and child health, nutrition, knowledge about HIV/AIDS, mortality, and other selected indicators. Geographic Coverage: The 2025 Rwanda Demographic and Health Survey was a nation-wide survey (Rwanda). Time Period: Data collection took place from June to November 2025. Frequency: The Rwanda Demographic and Health Survey takes place every 5 years. The 2025 Rwanda Demographic and Health Survey follows those implemented in 1992, 2000, 2005, 2010, 2014-15, and 2019-20. Population/Units: This sample survey covered men aged 15-59 years, Women aged 15-49 and Children aged 0-5 years. The unit analysis of this survey are households and individuals.

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: not detected.
• —Time coverage basis: source metadata period.
• —Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Geographic Coverage

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

Indicators, Variables, Or Resource Contents

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

Schema

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-rwanda-vaccinations-by-background-characteristics-2025-f3bec1e2")
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"] == "RWA"]

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

• —No canonical year/date column was detected in the packaged table; use source metadata and domain context for temporal interpretation.
• —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: Rwanda Data Sharing Platform - NISR
• —Publisher: NISR
• —Portal: https://data.gov.rw/
• —Resource: dhs7_key_indicators_table10
• —License: CC BY 4.0
• —Retrieved/generated: 2026-07-18T10:37:44Z
• —Hugging Face repo: electricsheepafrica/africa-rwanda-vaccinations-by-background-characteristics-2025-f3bec1e2

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
• —Check missingness before modeling
• —Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_rwanda_vaccinations_by_background_characteristics_2025_f3bec1e2_2025,
  title        = {Vaccinations by Background Characteristics (2025) | Africa (Rwanda Data Sharing Platform - NISR)},
  author       = {NISR},
  year         = {2025},
  url          = {https://api.data.gov.rw/api/v1/datasets/public/c985952b-456e-41a8-b789-3a21afecf03a},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-rwanda-vaccinations-by-background-characteristics-2025-f3bec1e2}}
}

License

Released under CC BY 4.0.

Original data is published by NISR. 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://api.data.gov.rw/api/v1/datasets/public/c985952b-456e-41a8-b789-3a21afecf03a