electricsheepafrica/africa-south-sudan-south-sudan-operational-presence-1038e69f

South Sudan Operational Presence | Africa (OCHA South Sudan)

6,242 rows - 1 Africa country/area - 2022 - source table - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 6,242 rows from OCHA South Sudan, covering South Sudan Operational Presence. 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: South Sudan: Who is doing what and where from January to June 2022 (Summary).

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

Coverage

Dimension	Value
Rows	6,242
Countries/areas	1
First period	2022
Last period	2022
Indicators	0
Columns	26
Source format	XLSX

Geographic Coverage

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

Area	Rows	First year	Last year	Name
SSD	6,242	2022	2022	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.	e7fafadb-8ce0-42b8-b088-e074e95c441a:january-to-june: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.	January to June
org_reporting	string	Source column from the original resource.	ACTED
org_reporting_name	string	Source column from the original resource.	Agency for Technical Cooperation and Development
org_reporting_type	string	Source column from the original resource.	INGO
name	string	Source column from the original resource.	CCCM
adm1_name	string	Source column from the original resource.	Central Equatoria
adm1_code	string	Source column from the original resource.	SS01
adm2_name	string	Source column from the original resource.	Juba
adm2_code	string	Source column from the original resource.	SS0101
date	string	Observation date.	January
reporting_or_implementing_org	string	Source column from the original resource.	Reporting Organization
source_period_start_year	int64	Start year inferred from source metadata.	2022
source_period_end_year	int64	End year inferred from source metadata.	2022
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2022
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: Operational Presence
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	ss_20220805_3w_op_january-june_2022.xlsx
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	531fe931-4b87-43e9-ae4c-a3e25a2bd388
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	e7fafadb-8ce0-42b8-b088-e074e95c441a
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.humdata.org/dataset/531fe931-4b87-43e9-ae4c-a3e25a2bd388...
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
year	int64	Observation year.	``

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-south-sudan-south-sudan-operational-presence-1038e69f")
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: OCHA South Sudan
• Publisher: OCHA South Sudan
• Portal: https://data.humdata.org
• Resource: ss_20220805_3w_op_january-june_2022.xlsx
• License: CC BY 4.0
• Retrieved/generated: 2026-08-10T18:25:26Z
• Hugging Face repo: electricsheepafrica/africa-south-sudan-south-sudan-operational-presence-1038e69f

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

@misc{electric_sheep_africa_africa_south_sudan_south_sudan_operational_presence_1038e69f_2022,
  title        = {South Sudan Operational Presence | Africa (OCHA South Sudan)},
  author       = {OCHA South Sudan},
  year         = {2022},
  url          = {https://data.humdata.org/dataset/south-sudan-operational-presence},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-south-sudan-south-sudan-operational-presence-1038e69f}}
}

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-operational-presence