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electricsheepafrica/africa-south-sudan-regional-nutrition-dashboard-bad544a5

Regional Nutrition Dashboard | Africa (UNICEF Eastern and Southern Africa Regional Office (ESARO) (inactive)) 161 rows - 1 Africa country/area - detected - source table - Engineered by Electric Sheep Africa TL;DR This dataset contains 161 rows from UNICEF Eastern and Southern Africa Regional Office (ESARO) (inactive), covering Regional Nutrition Dashboard. 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-regional-nutrition-dashboard-bad544a5.

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Dataset Card

Regional Nutrition Dashboard | Africa (UNICEF Eastern and Southern Africa Regional Office (ESARO) (inactive))

161 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 161 rows from UNICEF Eastern and Southern Africa Regional Office (ESARO) (inactive), covering Regional Nutrition Dashboard. 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: Nutrition Country fact sheet for ESARO

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
Rows161
Countries/areas1
First perioddetected
Last perioddetected
Indicators0
Columns34
Source formatXLS

Geographic Coverage

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

AreaRowsFirst yearLast yearName
SSD161detecteddetectedSouth 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.9b3be18b-cee1-452b-a6c7-a49c5f3af2f1:angola: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.Angola
indicatorsstringSource column from the original resource.SAM in national policies (Y/N)
2012doubleSource column from the original resource.``
2013stringSource column from the original resource.``
2014stringSource column from the original resource.``
2015stringSource column from the original resource.``
2016stringSource column from the original resource.Yes
2017stringSource column from the original resource.Yes
nutridashstringSource column from the original resource.Nutridash
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.UNICEF Eastern and Southern Africa Regional Office (ESARO) (inactive)
source_datasetdictionary<values=string, indices=int8, ordered=0>Source dataset or package title.Regional Nutrition dashboard
source_resourcedictionary<values=string, indices=int8, ordered=0>Source resource title, table name, or file name.Country office Nutridash data for SAM meeting 12092018.xlsx
source_package_iddictionary<values=string, indices=int8, ordered=0>Source package identifier.ad3f20cc-0c8d-4547-8961-e677a492fb28
source_resource_iddictionary<values=string, indices=int8, ordered=0>Source resource identifier.9b3be18b-cee1-452b-a6c7-a49c5f3af2f1
source_urldictionary<values=string, indices=int8, ordered=0>Original source URL or download URL.https://data.humdata.org/dataset/ad3f20cc-0c8d-4547-8961-e677a492fb28...
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
sam_in_national_policies_y_nstringSource column from the original resource.``
yesstringSource column from the original resource.``
yes_2stringSource column from the original resource.``
yes_3stringSource column from the original resource.``
yes_4stringSource column from the original resource.``
yes_5stringSource column from the original resource.``
yes_6stringSource column from the original resource.``
nostringSource column from the original resource.``
rutf_on_the_essential_supplies_list_y_nstringSource column from the original resource.``
no_2stringSource column from the original resource.``
no_3stringSource column from the original resource.``

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-south-sudan-regional-nutrition-dashboard-bad544a5")
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_regional_nutrition_dashboard_bad544a5_2026,
  title        = {Regional Nutrition Dashboard | Africa (UNICEF Eastern and Southern Africa Regional Office (ESARO) (inactive))},
  author       = {UNICEF Eastern and Southern Africa Regional Office (ESARO) (inactive)},
  year         = {2026},
  url          = {https://data.humdata.org/dataset/regional-nutrition-dashboard},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-south-sudan-regional-nutrition-dashboard-bad544a5}}
}

License

Released under CC BY 4.0.

Original data is published by UNICEF Eastern and Southern Africa Regional Office (ESARO) (inactive). 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/regional-nutrition-dashboard