electricsheepafrica/africa-somalia-data-for-the-covid-19-data-explorer-2e1e7caf

Data for the Covid 19 Data Explorer | Africa (HDX)

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

TL;DR

This dataset contains 2 rows from HDX, covering Data for the Covid 19 Data Explorer. 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: Global data that drives the Covid-19 Data Explorer

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

Coverage

Dimension	Value
Rows	2
Countries/areas	1
First period	detected
Last period	detected
Indicators	0
Columns	59
Source format	CSV

Geographic Coverage

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

Area	Rows	First year	Last year	Name
SOM	2	detected	detected	Somalia

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.	be01de02-8fb0-4e03-875c-8f71a78aaaba:0
country_iso3	dictionary<values=string, indices=int8, ordered=0>	ISO3 country or area code.	SOM
country_name	dictionary<values=string, indices=int8, ordered=0>	Country or area name.	Somalia
cumulative_cases	string	Source column from the original resource.	#affected+infected
cumulative_deaths	string	Source column from the original resource.	#affected+killed
requiredfunding	string	Source column from the original resource.	#value+funding+hrp+required+usd
funding	string	Source column from the original resource.	#value+funding+hrp+total+usd
percentfunded	string	Source column from the original resource.	#value+funding+hrp+pct
cbpffunding	string	Source column from the original resource.	#value+cbpf+funding+total+usd
cbpffundinggmempty	string	Source column from the original resource.	#value+cbpf+funding+gmempty+total+usd
cbpffundinggm0	string	Source column from the original resource.	#value+cbpf+funding+gm0+total+usd
cbpffundinggm1	string	Source column from the original resource.	#value+cbpf+funding+gm1+total+usd
cbpffundinggm2	string	Source column from the original resource.	#value+cbpf+funding+gm2+total+usd
cbpffundinggm3	string	Source column from the original resource.	#value+cbpf+funding+gm3+total+usd
cbpffundinggm4	string	Source column from the original resource.	#value+cbpf+funding+gm4+total+usd
cerffunding	string	Source column from the original resource.	#value+cerf+funding+total+usd
cerffundinggmempty	string	Source column from the original resource.	#value+cerf+funding+gmempty+total+usd
cerffundinggm0	string	Source column from the original resource.	#value+cerf+funding+gm0+total+usd
cerffundinggm1	string	Source column from the original resource.	#value+cerf+funding+gm1+total+usd
cerffundinggm2	string	Source column from the original resource.	#value+cerf+funding+gm2+total+usd
cerffundinggm3	string	Source column from the original resource.	#value+cerf+funding+gm3+total+usd
cerffundinggm4	string	Source column from the original resource.	#value+cerf+funding+gm4+total+usd
cbpfcontributions	string	Source column from the original resource.	#value+cbpf+contributions+total+usd
cerfcontributions	string	Source column from the original resource.	#value+cerf+contributions+total+usd
totaldosesadministered	string	Source column from the original resource.	#capacity+doses+administered+total
peopleinneed	string	Source column from the original resource.	#affected+inneed
numcountriesinneed	string	Source column from the original resource.	#meta+countries+inneed+num
of_visas_pending_or_denied	string	Source column from the original resource.	#access+visas+pct
of_travel_authorizations_or_movements_denied	string	Source column from the original resource.	#access+travel+pct
number_of_incidents_reported_since_start_of_year	string	Source column from the original resource.	#event+year+todate+num
of_cerf_projects_affected_by_insecurity_and_inaccessibil	string	Source column from the original resource.	#activity+cerf+project+insecurity+pct
of_cbpf_projects_affected_by_insecurity_and_inaccessibil	string	Source column from the original resource.	#activity+cbpf+project+insecurity+pct
vaccinations_postponed	string	Source column from the original resource.	#vaccination+postponed+num
covax_delivered_doses	string	Source column from the original resource.	#capacity+doses+delivered+covax
other_delivered_doses	string	Source column from the original resource.	#capacity+doses+delivered+others
total_delivered_doses	string	Source column from the original resource.	#capacity+doses+delivered+total
nochildrensam	string	Source column from the original resource.	#affected+children+sam
dosesallocated	string	Source column from the original resource.	#capacity+doses+forecast+covax
worldbankfinancingapproved	string	Source column from the original resource.	#value+financing+worldbank+approved
gavicdsearlyaccessapproved	string	Source column from the original resource.	#value+financing+gavi+earlyaccess+approved
gavicdsneedsapproved	string	Source column from the original resource.	#value+financing+gavi+needs+approved
gavicdsearlyaccessdisbursed	string	Source column from the original resource.	#value+financing+gavi+earlyaccess+disbursed
gavicdsneedsdisbursed	string	Source column from the original resource.	#value+financing+gavi+needs+disbursed
worldbankgavifinancingtotal	string	Source column from the original resource.	#value+financing+approved
foodinsecurityp3	string	Source column from the original resource.	#affected+food+ipc+p3plus+num
no_closed_countries	string	Source column from the original resource.	#status+country+closed
no_affected_learners	string	Source column from the original resource.	#affected+learners
percentage_affected_learners	string	Source column from the original resource.	#affected+learners+pct
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.	Data for the Covid-19 Data Explorer
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	Covid-19 Data Explorer - global data
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	548470a1-998b-4575-82d5-18217653bde5
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	be01de02-8fb0-4e03-875c-8f71a78aaaba
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://docs.google.com/spreadsheets/d/e/2PACX-1vT9_g7AItbqJwDkPi55Vy...
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.	2026-08-10T14:51:11Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-somalia-data-for-the-covid-19-data-explorer-2e1e7caf")
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"] == "SOM"]

Time-Series Pattern

if "value" in df.columns and "number_of_incidents_reported_since_start_of_year" in df.columns:
    trend = df.sort_values("number_of_incidents_reported_since_start_of_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: number_of_incidents_reported_since_start_of_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: Covid-19 Data Explorer - global data
• License: CC BY 4.0
• Retrieved/generated: 2026-08-10T15:55:55Z
• Hugging Face repo: electricsheepafrica/africa-somalia-data-for-the-covid-19-data-explorer-2e1e7caf

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_somalia_data_for_the_covid_19_data_explorer_2e1e7caf_2026,
  title        = {Data for the Covid 19 Data Explorer | Africa (HDX)},
  author       = {HDX},
  year         = {2026},
  url          = {https://data.humdata.org/dataset/covid-19-data-visual-inputs},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-somalia-data-for-the-covid-19-data-explorer-2e1e7caf}}
}

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/covid-19-data-visual-inputs