electricsheepafrica/africa-south-sudan-south-sudan-gender-ff919af1

South Sudan Gender | Africa (World Bank Group)

3,159 rows - 1 Africa country/area - 1960-2025 - 1 indicator - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 3,159 rows from World Bank Group, covering South Sudan Gender. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Demographic datasets help analysts understand population structure, household conditions, migration, gender, age, and settlement patterns.

Source-provided context: csv containing Gender indicators Indicators: Access to anti-retroviral drugs, Adjusted net enrollment rate, Adolescent fertility rate, Age at first marriage, Age population, Births attended by skilled health staff, Child employment in agriculture, Child employment in manufacturing, Child employment in services, Children in employment, Children out of school, Contraceptive prevalence, Contributing family workers, Educational attainment, Employers, Employment in agriculture, Employment in industry, Employment in services, Employment to population ratio, Female migrants, Fertility rate, Firms with female participation in ownership, Firms with female top manager, Gross intake ratio in first grade of primary education, Incidence of HIV, Labor force, Labor force participation rate, Life expectancy at age 60, Life expectancy at birth, Lifetime risk of maternal death, Literacy rate, Maternal leave benefits, Maternal mortality ratio, Mortality rate, Number of weeks of maternity leave.

How To Read This Dataset

• One row means: one indicator observation for one geography, time period, and optional source dimensions.
• Primary geography column: country_iso3.
• Best time column: year.
• Time coverage basis: year.
• Recommended join keys: country_iso3, year, indicator_id.

Coverage

Dimension	Value
Rows	3,159
Countries/areas	1
First period	1960
Last period	2025
Indicators	1
Columns	22
Source format	CSV

Geographic Coverage

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

Area	Rows	First year	Last year	Name
SSD	3,159	1960	2025	South Sudan

Indicators, Variables, Or Resource Contents

• south-sudan-gender-ca3d71cf - South Sudan - Gender(source_units_unspecified)

Schema

Column	Type	Description	Example
indicator_id	string	Stable source or Electric Sheep Africa indicator identifier.	south-sudan-gender-ca3d71cf
indicator_name	string	Human-readable indicator name.	South Sudan - Gender
country_iso3	string	ISO3 country or area code.	SSD
country_name	string	Country or area name.	South Sudan
year	int64	Observation year.	2024
value	double	Numeric observation value.	10.54944801
unit	string	Measurement unit, when supplied by the source.	source_units_unspecified
dimension_country_name	string	Source dimension retained during long-form normalization.	South Sudan
dimension_country_iso3	string	Source dimension retained during long-form normalization.	SSD
dimension_indicator_name	string	Source dimension retained during long-form normalization.	Firms with female top manager (% of firms)
dimension_indicator_code	string	Source dimension retained during long-form normalization.	IC.FRM.FEMM.ZS
source_period_start_year	int64	Start year inferred from source metadata.	2015
source_period_end_year	int64	End year inferred from source metadata.	2023
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2015-2023
source_provider	dictionary<values=string, indices=int8, ordered=0>	Publishing organization.	World Bank Group
source_dataset	dictionary<values=string, indices=int8, ordered=0>	Source dataset or package title.	South Sudan - Gender
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	Gender Indicators for South Sudan
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	2223c5e9-c4d8-4ddd-b9cb-dd71586d8135
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	daefee82-85b6-4436-89cd-09612bde5932
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.humdata.org/dataset/2223c5e9-c4d8-4ddd-b9cb-dd71586d8135...
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

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-south-sudan-south-sudan-gender-ff919af1")
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 "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

• 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

• Source: World Bank Group
• Publisher: World Bank Group
• Portal: https://data.humdata.org
• Resource: Gender Indicators for South Sudan
• License: CC BY 4.0
• Retrieved/generated: 2026-08-10T18:34:55Z
• Hugging Face repo: electricsheepafrica/africa-south-sudan-south-sudan-gender-ff919af1

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

• Build demographic profiles
• Normalize indicators per capita
• Join with service-delivery datasets
• Build time-series views and period-over-period comparisons
• Pivot to geography x period or indicator x period matrices
• 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_gender_ff919af1_2025,
  title        = {South Sudan Gender | Africa (World Bank Group)},
  author       = {World Bank Group},
  year         = {2025},
  url          = {https://data.humdata.org/dataset/world-bank-gender-indicators-for-south-sudan},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-south-sudan-south-sudan-gender-ff919af1}}
}

License

Released under CC BY 4.0.

Original data is published by World Bank Group. 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/world-bank-gender-indicators-for-south-sudan