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

Data for the Covid-19 Data Explorer | Africa (Zimbabwe official open data)

2 rows - 1 Africa country - not-applicable - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one official CSV resource from Zimbabwe as ML-ready Parquet. The source file is the provenance boundary; all usable indicators or tabular columns from the resource stay together in this repo.

About the source

• Source: Data for the Covid-19 Data Explorer
• Publisher: HDX
• Resource: Covid-19 Data Explorer - global data
• Format: CSV
• License: CC BY 4.0
• Packaging mode: tabular_resource

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
ZWE	2	n/a	n/a	Zimbabwe

Indicators or Resource Contents

• This source file is packaged as a normalized tabular resource.

Schema

Column	Type	Description	Example
source_record_id	string	Stable row identifier for tabular resources.	be01de02-8fb0-4e03-875c-8f71a78aaaba:0
country_iso3	category	ISO3 country code.	ZWE
country_name	category	Country name.	Zimbabwe
cumulative_cases	string	Source column.	#affected+infected
cumulative_deaths	string	Source column.	#affected+killed
requiredfunding	string	Source column.	#value+funding+hrp+required+usd
funding	string	Source column.	#value+funding+hrp+total+usd
percentfunded	string	Source column.	#value+funding+hrp+pct
cbpffunding	string	Source column.	#value+cbpf+funding+total+usd
cbpffundinggmempty	string	Source column.	#value+cbpf+funding+gmempty+total+usd
cbpffundinggm0	string	Source column.	#value+cbpf+funding+gm0+total+usd
cbpffundinggm1	string	Source column.	#value+cbpf+funding+gm1+total+usd
cbpffundinggm2	string	Source column.	#value+cbpf+funding+gm2+total+usd
cbpffundinggm3	string	Source column.	#value+cbpf+funding+gm3+total+usd
cbpffundinggm4	string	Source column.	#value+cbpf+funding+gm4+total+usd
cerffunding	string	Source column.	#value+cerf+funding+total+usd
cerffundinggmempty	string	Source column.	#value+cerf+funding+gmempty+total+usd
cerffundinggm0	string	Source column.	#value+cerf+funding+gm0+total+usd
cerffundinggm1	string	Source column.	#value+cerf+funding+gm1+total+usd
cerffundinggm2	string	Source column.	#value+cerf+funding+gm2+total+usd
cerffundinggm3	string	Source column.	#value+cerf+funding+gm3+total+usd
cerffundinggm4	string	Source column.	#value+cerf+funding+gm4+total+usd
cbpfcontributions	string	Source column.	#value+cbpf+contributions+total+usd
cerfcontributions	string	Source column.	#value+cerf+contributions+total+usd
totaldosesadministered	string	Source column.	#capacity+doses+administered+total
peopleinneed	string	Source column.	#affected+inneed
numcountriesinneed	string	Source column.	#meta+countries+inneed+num
of_visas_pending_or_denied	string	Source column.	#access+visas+pct
of_travel_authorizations_or_movements_denied	string	Source column.	#access+travel+pct
number_of_incidents_reported_since_start_of_year	string	Source column.	#event+year+todate+num
of_cerf_projects_affected_by_insecurity_and_inaccessibil	string	Source column.	#activity+cerf+project+insecurity+pct
of_cbpf_projects_affected_by_insecurity_and_inaccessibil	string	Source column.	#activity+cbpf+project+insecurity+pct
vaccinations_postponed	string	Source column.	#vaccination+postponed+num
covax_delivered_doses	string	Source column.	#capacity+doses+delivered+covax
other_delivered_doses	string	Source column.	#capacity+doses+delivered+others
total_delivered_doses	string	Source column.	#capacity+doses+delivered+total
nochildrensam	string	Source column.	#affected+children+sam
dosesallocated	string	Source column.	#capacity+doses+forecast+covax
worldbankfinancingapproved	string	Source column.	#value+financing+worldbank+approved
gavicdsearlyaccessapproved	string	Source column.	#value+financing+gavi+earlyaccess+approved
gavicdsneedsapproved	string	Source column.	#value+financing+gavi+needs+approved
gavicdsearlyaccessdisbursed	string	Source column.	#value+financing+gavi+earlyaccess+disbursed
gavicdsneedsdisbursed	string	Source column.	#value+financing+gavi+needs+disbursed
worldbankgavifinancingtotal	string	Source column.	#value+financing+approved
foodinsecurityp3	string	Source column.	#affected+food+ipc+p3plus+num
no_closed_countries	string	Source column.	#status+country+closed
no_affected_learners	string	Source column.	#affected+learners
percentage_affected_learners	string	Source column.	#affected+learners+pct
source_period_start_year	Int64	First year inferred from source resource metadata.	``
source_period_end_year	Int64	Last year inferred from source resource metadata.	``
source_period_label	string	Human-readable period inferred from source resource metadata.	``
source_provider	category	Publishing organization.	HDX
source_dataset	category	Source package title.	Data for the Covid-19 Data Explorer
source_resource	category	Source resource title.	Covid-19 Data Explorer - global data
source_package_id	category	CKAN package UUID.	548470a1-998b-4575-82d5-18217653bde5
source_resource_id	category	CKAN resource UUID.	be01de02-8fb0-4e03-875c-8f71a78aaaba
source_url	category	Original source resource URL.	https://docs.google.com/spreadsheets/d/e/2PACX-1vT9_g7AItbqJwDkPi55VyVhq
license_id	category	Source license identifier.	cc-by
retrieved_at	category	UTC retrieval timestamp.	2026-08-24T16:01:50Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-zimbabwe-data-for-the-covid-19-data-explorer-2e1e7caf")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

sample_country = df[df["country_iso3"] == "ZWE"]

Work with indicators

if "indicator_id" in df.columns:
    print(df["indicator_id"].value_counts().head())
    sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])

Citation

@misc{electric_sheep_africa_africa_zimbabwe_data_for_the_covid_19_data_explorer_2e1e7caf_2026,
  title        = {Data for the Covid-19 Data Explorer | Africa (Zimbabwe official open data)},
  author       = {HDX},
  year         = {2026},
  url          = {https://data.humdata.org/dataset/covid-19-data-visual-inputs},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-zimbabwe-data-for-the-covid-19-data-explorer-2e1e7caf}}
}

License

Released under CC BY 4.0.

Original data (c) HDX. When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.

About Electric Sheep

Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on Hugging Face. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.

Browse the full collection: huggingface.co/electricsheepafrica

---

Provenance: ingested 2026-08-24 via the Electric Sheep pipeline. Source URL: https://docs.google.com/spreadsheets/d/e/2PACX-1vT9_g7AItbqJwDkPi55VyVhqOdB81c3FePhqAoFlIL9160mxqtqg-OofaoTZtdq39BATa37PYQ4813k/pub?gid=1260889797&single=true&output=csv