electricsheepafrica/africa-south-sudan-global-subnational-population-statistics-b42041cc

Global Subnational Population Statistics | Africa (HDX)

18,981 rows - 1 Africa country/area - 2001-2025 - 3 indicators - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 18,981 rows from HDX, covering Global Subnational Population Statistics. 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: Latest COD population statistics compiled at the admin level. The CSV files contain subnational p-codes, their corresponding administrative names, source organization, and reference dates where available. These are constructed from individual country level population files, which can be found using this search on HDX.

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	18,981
Countries/areas	1
First period	2001
Last period	2025
Indicators	3
Columns	25
Source format	CSV

Geographic Coverage

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

Area	Rows	First year	Last year	Name
SSD	18,981	2001	2025	South Sudan

Indicators, Variables, Or Resource Contents

• global-subnational-population-statistics-age-min-67749537 - Global - Subnational Population Statistics - age min(source_units_unspecified)
• global-subnational-population-statistics-age-max-0d012c53 - Global - Subnational Population Statistics - age max(source_units_unspecified)
• global-subnational-population-statistics-population-af4e0fd7 - Global - Subnational Population Statistics - population(source_units_unspecified)

Schema

Column	Type	Description	Example
indicator_id	string	Stable source or Electric Sheep Africa indicator identifier.	global-subnational-population-statistics-age-min-67749537
indicator_name	string	Human-readable indicator name.	Global - Subnational Population Statistics - age min
country_iso3	string	ISO3 country or area code.	SSD
country_name	string	Country or area name.	South Sudan
year	int64	Observation year.	2021
value	double	Numeric observation value.	0.0
unit	string	Measurement unit, when supplied by the source.	source_units_unspecified
dimension_iso3	string	Source dimension retained during long-form normalization.	AFG
dimension_country	string	Source dimension retained during long-form normalization.	Afghanistan
dimension_population_group	string	Source dimension retained during long-form normalization.	F_00_04
dimension_gender	string	Source dimension retained during long-form normalization.	f
dimension_age_range	string	Source dimension retained during long-form normalization.	0-4
dimension_source	string	Source dimension retained during long-form normalization.	National Statistic and Information Authority (NSIA) Afghanistan
dimension_contributor	string	Source dimension retained during long-form normalization.	OCHA Afghanistan
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.	HDX
source_dataset	dictionary<values=string, indices=int8, ordered=0>	Source dataset or package title.	Global - Subnational Population Statistics
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	cod_population_admin0.csv
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	27e3d1c6-c57a-4159-85a4-adb6b7aca6b9
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	d4ea8fba-3d98-4d6e-85c8-84a5b0b4ebd9
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.humdata.org/dataset/27e3d1c6-c57a-4159-85a4-adb6b7aca6b9...
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-global-subnational-population-statistics-b42041cc")
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: HDX
• Publisher: HDX
• Portal: https://data.humdata.org
• Resource: cod_population_admin0.csv
• License: CC BY 4.0
• Retrieved/generated: 2026-08-10T19:01:00Z
• Hugging Face repo: electricsheepafrica/africa-south-sudan-global-subnational-population-statistics-b42041cc

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_global_subnational_population_statistics_b42041cc_2025,
  title        = {Global Subnational Population Statistics | Africa (HDX)},
  author       = {HDX},
  year         = {2025},
  url          = {https://data.humdata.org/dataset/cod-ps-global},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-south-sudan-global-subnational-population-statistics-b42041cc}}
}

License

Released under CC BY 4.0.

Original data is published by HDX. 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/cod-ps-global