electricsheepafrica/africa-south-sudan-south-sudan-integrated-food-security-phase-classification-e9152d34

South Sudan Integrated Food Security Phase Classification | Africa (OCHA South Sudan)

134 rows - 1 Africa country/area - detected - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 134 rows from OCHA South Sudan, covering South Sudan Integrated Food Security Phase Classification. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Agriculture datasets help analysts examine production, prices, inputs, land use, food systems, and rural economic activity.

Source-provided context: South Sudan Integrated Food Security Phase classification and population by state and County. The Integrated Food Security Phase Classification (IPC), also known as IPC scale, is a tool for improving food security analysis and decision-making. It is a standardized scale that integrates food security, nutrition and livelihood information into a statement about the nature and severity of a crisis and implications for strategic response. The IPC was originally developed for use in Somalia by the United Nations Food and Agriculture Organization's Food Security Analysis Unit (FSAU). Several national governments and international agencies, including CARE International, European Commission Joint Research Centre (EC JRC), Food and Agricultural Organization of the United Nations (FAO), USAID/FEWS NET, Oxfam GB, Save the Children UK/US, and United Nations World Food Programme (WFP), have been working together to adapt it to other food security contexts

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: source_period_start_year.
• Recommended join keys: country_iso3 where available plus source-specific keys.

Coverage

Dimension	Value
Rows	134
Countries/areas	1
First period	detected
Last period	detected
Indicators	0
Columns	45
Source format	XLSX

Geographic Coverage

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

Area	Rows	First year	Last year	Name
SSD	134	detected	detected	South Sudan

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.	ffdc3b97-34f1-4e2a-ab31-ed3700b9fc81:pop-summary:0
country_iso3	dictionary<values=string, indices=int8, ordered=0>	ISO3 country or area code.	SSD
country_name	dictionary<values=string, indices=int8, ordered=0>	Country or area name.	South Sudan
source_sheet	string	Source column from the original resource.	POP_SUMMARY
state	string	Source column from the original resource.	Central Equatoria
mid_2017_population_nbs	double	Source column from the original resource.	1398316.1691963284
minimal	double	Source column from the original resource.	545000.0
stressed	double	Source column from the original resource.	345000.0
crisis	double	Source column from the original resource.	480000.0
emergency	double	Source column from the original resource.	30000.0
catastrophe	double	Source column from the original resource.	0.0
of_crisis_emergency_humanitarian_catastrophe	double	Source column from the original resource.	0.3647243815346272
state_2	string	Source column from the original resource.	Central Equatoria
mid_2017_population_nbs_2	double	Source column from the original resource.	1398316.1691963284
minimal_2	double	Source column from the original resource.	475000.0
stressed_2	double	Source column from the original resource.	385000.0
crisis_2	double	Source column from the original resource.	495000.0
emergency_2	double	Source column from the original resource.	45000.0
catastrophe_2	string	Source column from the original resource.	0
of_crisis_emergency_humanitarian_catastrophe_2	string	Source column from the original resource.	0.38617875691901704
state_3	string	Source column from the original resource.	Central Equatoria
mid_2017_population_nbs_3	double	Source column from the original resource.	1398316.1691963284
minimal_3	double	Source column from the original resource.	435000.0
stressed_3	double	Source column from the original resource.	470000.0
crisis_3	double	Source column from the original resource.	465000.0
emergency_3	double	Source column from the original resource.	30000.0
catastrophe_3	double	Source column from the original resource.	0.0
of_crisis_emergency_humanitarian_catastrophe_3	double	Source column from the original resource.	0.3539971938424323
source_period_start_year	int64	Start year inferred from source metadata.	``
source_period_end_year	int64	End year inferred from source metadata.	``
source_period_label	string	Source column from the original resource.	``
source_provider	dictionary<values=string, indices=int8, ordered=0>	Publishing organization.	OCHA South Sudan
source_dataset	dictionary<values=string, indices=int8, ordered=0>	Source dataset or package title.	South Sudan - Integrated Food Security Phase classification and popul...
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	IPC_Populations_by_State_County.xlsx
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	efb5d747-54b4-485b-8408-e0b77f341fff
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	ffdc3b97-34f1-4e2a-ab31-ed3700b9fc81
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.humdata.org/dataset/efb5d747-54b4-485b-8408-e0b77f341fff...
license_id	dictionary<values=string, indices=int8, ordered=0>	Source license identifier.	cc-by
retrieved_at	dictionary<values=string, indices=int8, ordered=0>	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-08-10T18:18:23Z
state_county	string	Source column from the original resource.	``
famine	double	Source column from the original resource.	``
state_county_2	string	Source column from the original resource.	``
famine_2	double	Source column from the original resource.	``
state_county_3	string	Source column from the original resource.	``
famine_3	double	Source column from the original resource.	``

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-south-sudan-south-sudan-integrated-food-security-phase-classification-e9152d34")
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"] == "SSD"]

Time-Series Pattern

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

• 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

• Source: OCHA South Sudan
• Publisher: OCHA South Sudan
• Portal: https://data.humdata.org
• Resource: IPC_Populations_by_State_County.xlsx
• License: CC BY 4.0
• Retrieved/generated: 2026-08-10T20:01:47Z
• Hugging Face repo: electricsheepafrica/africa-south-sudan-south-sudan-integrated-food-security-phase-classification-e9152d34

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

• Track production or price movements
• Compare regions or commodities
• Join with climate and trade 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

@misc{electric_sheep_africa_africa_south_sudan_south_sudan_integrated_food_security_phase_classification_e91_2026,
  title        = {South Sudan Integrated Food Security Phase Classification | Africa (OCHA South Sudan)},
  author       = {OCHA South Sudan},
  year         = {2026},
  url          = {https://data.humdata.org/dataset/south-sudan-integrated-food-security-phase-classification-and-population-by-state-and-county},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-south-sudan-south-sudan-integrated-food-security-phase-classification-e9152d34}}
}

License

Released under CC BY 4.0.

Original data is published by OCHA South Sudan. 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.

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Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://data.humdata.org/dataset/south-sudan-integrated-food-security-phase-classification-and-population-by-state-and-county