electricsheepafrica/africa-south-sudan-south-sudan-coronavirus-covid-19-cases-4c3de890

South Sudan Coronavirus Covid 19 Cases | Africa (HERA - Humanitarian Emergency Response Africa)

2,632 rows - 1 Africa country/area - 2020 - 8 indicators - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

TL;DR

This dataset contains 2,632 rows from HERA - Humanitarian Emergency Response Africa, covering South Sudan Coronavirus Covid 19 Cases. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Health datasets help analysts monitor disease burden, service delivery, population health outcomes, and public-health program performance.

Source-provided context: Covid-19 cases (infections, recoveries, deaths and cumulative cases) at the national level in South Sudan since the beginning of the outbreak

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

Geographic Coverage

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

Indicators, Variables, Or Resource Contents

• —south-sudan-coronavirus-covid-19-cases-id-49976bbf - South Sudan: Coronavirus (Covid-19) Cases - id(sourceunitsunspecified)
• —south-sudan-coronavirus-covid-19-cases-infected-9fb9bd27 - South Sudan: Coronavirus (Covid-19) Cases - infected(sourceunitsunspecified)
• —south-sudan-coronavirus-covid-19-cases-cumulative-infected-74f824f9 - South Sudan: Coronavirus (Covid-19) Cases - cumulative infected(sourceunitsunspecified)
• —south-sudan-coronavirus-covid-19-cases-recovered-f56b215b - South Sudan: Coronavirus (Covid-19) Cases - recovered(sourceunitsunspecified)
• —south-sudan-coronavirus-covid-19-cases-cumulative-recovered-ff895149 - South Sudan: Coronavirus (Covid-19) Cases - cumulative recovered(sourceunitsunspecified)
• —south-sudan-coronavirus-covid-19-cases-deceased-e07dde1d - South Sudan: Coronavirus (Covid-19) Cases - deceased(sourceunitsunspecified)
• —south-sudan-coronavirus-covid-19-cases-cumulative-deceased-1f4fea46 - South Sudan: Coronavirus (Covid-19) Cases - cumulative deceased(sourceunitsunspecified)
• —south-sudan-coronavirus-covid-19-cases-active-cases-cc4d59ac - South Sudan: Coronavirus (Covid-19) Cases - active cases(sourceunitsunspecified)

Schema

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-south-sudan-south-sudan-coronavirus-covid-19-cases-4c3de890")
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: HERA - Humanitarian Emergency Response Africa
• —Publisher: HERA - Humanitarian Emergency Response Africa
• —Portal: https://data.humdata.org
• —Resource: SouthSudan_Covid19_cases_HXL_HERA.csv
• —License: CC BY 4.0
• —Retrieved/generated: 2026-08-10T19:50:30Z
• —Hugging Face repo: electricsheepafrica/africa-south-sudan-south-sudan-coronavirus-covid-19-cases-4c3de890

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

• —Compare health outcomes across geographies
• —Track changes over time
• —Join with population or facility data
• —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_coronavirus_covid_19_cases_4c3de890_2020,
  title        = {South Sudan Coronavirus Covid 19 Cases | Africa (HERA - Humanitarian Emergency Response Africa)},
  author       = {HERA - Humanitarian Emergency Response Africa},
  year         = {2020},
  url          = {https://data.humdata.org/dataset/south-sudan-coronavirus-covid-19-cases},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-south-sudan-south-sudan-coronavirus-covid-19-cases-4c3de890}}
}

License

Released under CC BY 4.0.

Original data is published by HERA - Humanitarian Emergency Response Africa. 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/south-sudan-coronavirus-covid-19-cases