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electricsheepafrica/africa-south-sudan-a-prospective-evaluation-of-nutrition-protocol-adaptations-20638fe1

A Prospective Evaluation of Nutrition Protocol Adaptations | Africa (Johns Hopkins School of Public Health) 221 rows - 1 Africa country/area - detected - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 221 rows from Johns Hopkins School of Public Health, covering A Prospective Evaluation of Nutrition Protocol Adaptations. 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-south-sudan-a-prospective-evaluation-of-nutrition-protocol-adaptations-20638fe1.

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A Prospective Evaluation of Nutrition Protocol Adaptations | Africa (Johns Hopkins School of Public Health)

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

rows countries period indicators license

TL;DR

This dataset contains 221 rows from Johns Hopkins School of Public Health, covering A Prospective Evaluation of Nutrition Protocol Adaptations. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Official statistics datasets help analysts inspect public data as published by governments, national statistical systems, and regional data portals.

Source-provided context: codebook with variable descriptions

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: source_period_start_year.
  • —Time coverage basis: sourceperiodstart_year.
  • —Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

DimensionValue
Rows221
Countries/areas1
First perioddetected
Last perioddetected
Indicators0
Columns19
Source formatXLSX

Geographic Coverage

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

AreaRowsFirst yearLast yearName
SSD221detecteddetectedSouth Sudan

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.b1f8252c-3b4a-49a1-8bfe-92760ca3ae6a:sheet1:0
country_iso3dictionary<values=string, indices=int8, ordered=0>ISO3 country or area code.SSD
country_namedictionary<values=string, indices=int8, ordered=0>Country or area name.South Sudan
source_sheetstringSource column from the original resource.Sheet1
positionint64Source column from the original resource.1
variable_namestringSource column from the original resource.id
variable_typestringSource column from the original resource.str7
variable_descriptionstringSource column from the original resource.child's id assigned at enrollment into study
source_period_start_yearint64Start year inferred from source metadata.``
source_period_end_yearint64End year inferred from source metadata.``
source_period_labelstringSource column from the original resource.``
source_providerdictionary<values=string, indices=int8, ordered=0>Publishing organization.Johns Hopkins School of Public Health
source_datasetdictionary<values=string, indices=int8, ordered=0>Source dataset or package title.A Prospective Evaluation of Nutrition Protocol Adaptations in the Con...
source_resourcedictionary<values=string, indices=int8, ordered=0>Source resource title, table name, or file name.ssd_cmam_prospective_codebook.xlsx
source_package_iddictionary<values=string, indices=int8, ordered=0>Source package identifier.c7cd7d86-1563-425d-813e-83cab3e18e07
source_resource_iddictionary<values=string, indices=int8, ordered=0>Source resource identifier.b1f8252c-3b4a-49a1-8bfe-92760ca3ae6a
source_urldictionary<values=string, indices=int8, ordered=0>Original source URL or download URL.https://data.humdata.org/dataset/c7cd7d86-1563-425d-813e-83cab3e18e07...
license_iddictionary<values=string, indices=int8, ordered=0>Source license identifier.cc-by
retrieved_atdictionary<values=string, indices=int8, ordered=0>UTC source retrieval timestamp from the Electric Sheep Africa pipeline.2026-08-10T18:18:23Z

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-south-sudan-a-prospective-evaluation-of-nutrition-protocol-adaptations-20638fe1")
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"] == "SSD"]

Time-Series Pattern

python
if "value" in df.columns and "source_period_start_year" in df.columns:
    trend = df.sort_values("source_period_start_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: source_period_start_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

  • —Profile the distribution of values
  • —Compare categories or geographies
  • —Join with complementary public datasets
  • —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_south_sudan_a_prospective_evaluation_of_nutrition_protocol_adaptations_20_2026,
  title        = {A Prospective Evaluation of Nutrition Protocol Adaptations | Africa (Johns Hopkins School of Public Health)},
  author       = {Johns Hopkins School of Public Health},
  year         = {2026},
  url          = {https://data.humdata.org/dataset/ssd-aah-final-dataset},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-south-sudan-a-prospective-evaluation-of-nutrition-protocol-adaptations-20638fe1}}
}

License

Released under CC BY 4.0.

Original data is published by Johns Hopkins School of Public Health. 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://data.humdata.org/dataset/ssd-aah-final-dataset