Datasetpublic

electricsheepafrica/africa-gambia-immunization-campaigns-impacted-due-to-covid-19-d0859dd7

Immunization Campaigns Impacted due to COVID-19 | Africa (Gambia official open data) 169 rows - 1 Africa country - 2018-2024 - Repackaged by Electric Sheep Africa TL;DR This dataset packages one official CSV resource from Gambia 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: Immunization Campaigns Impacted due to… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-gambia-immunization-campaigns-impacted-due-to-covid-19-d0859dd7.

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Dataset Card

Immunization Campaigns Impacted due to COVID-19 | Africa (Gambia official open data)

169 rows - 1 Africa country - 2018-2024 - Repackaged by Electric Sheep Africa

TL;DR

This dataset packages one official CSV resource from Gambia 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: Immunization Campaigns Impacted due to COVID-19
—Publisher: World Health Organization
—Resource: Immunization Campaigns Impacted
—Format: CSV
—License: CC BY 4.0
—Packaging mode: indicator_long

Geographic coverage

1 Africa country:

Country	Rows	First year	Last year	Name
`GMB`	169	2018	2024	`Gambia`

Indicators or Resource Contents

—immunization-campaigns-impacted-due-to-covid-19-780f258d - Immunization Campaigns Impacted due to COVID-19

Schema

Column	Type	Description	Example
`indicator_id`	`string`	Stable indicator identifier.	`immunization-campaigns-impacted-due-to-covid-19-780f258d`
`indicator_name`	`string`	Human-readable indicator name.	`Immunization Campaigns Impacted due to COVID-19`
`country_iso3`	`string`	ISO3 country code.	`GMB`
`country_name`	`string`	Country name.	`Gambia`
`year`	`Int64`	Observation year.	`2021`
`value`	`float64`	Numeric observation value.	`2642395.0`
`unit`	`string`	Measurement unit, when available.	`source_units_unspecified`
`dimension_iso3`	`string`	Source dimension.	`AFG`
`dimension_country`	`string`	Source dimension.	`Afghanistan`
`dimension_campaign_vaccine`	`string`	Source dimension.	`bivalent Oral Poliovirus`
`dimension_planned_end_date`	`string`	Source dimension.	`2021-11-01`
`dimension_status`	`string`	Source dimension.	`On track`
`dimension_target_age_group`	`string`	Source dimension.	`0-5y`
`dimension_campaign_type`	`string`	Source dimension.	`Preventive`
`dimension_geographic_scale`	`string`	Source dimension.	`Subnational`
`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.	`World Health Organization`
`source_dataset`	`category`	Source package title.	`Immunization Campaigns Impacted due to COVID-19`
`source_resource`	`category`	Source resource title.	`Immunization Campaigns Impacted`
`source_package_id`	`category`	CKAN package UUID.	`d0e1806d-e1ed-4b60-bd4a-6a36dfb8053a`
`source_resource_id`	`category`	CKAN resource UUID.	`ed6827b6-fa77-4d9c-9129-2ab98377b016`
`source_url`	`category`	Original source resource URL.	`https://docs.google.com/spreadsheets/d/e/2PACX-1vT8m53T3ITzFdJWWKkdRRVRj`
`license_id`	`category`	Source license identifier.	`cc-by`
`retrieved_at`	`category`	UTC retrieval timestamp.	`2026-08-16T14:41:19Z`

Usage

python

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-gambia-immunization-campaigns-impacted-due-to-covid-19-d0859dd7")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

python

sample_country = df[df["country_iso3"] == "GMB"]

Work with indicators

python

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

bibtex

@misc{electric_sheep_africa_africa_gambia_immunization_campaigns_impacted_due_to_covid_19_d0859dd7_2024,
  title        = {Immunization Campaigns Impacted due to COVID-19 | Africa (Gambia official open data)},
  author       = {World Health Organization},
  year         = {2024},
  url          = {https://data.humdata.org/dataset/immunization-campaigns-impacted},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-gambia-immunization-campaigns-impacted-due-to-covid-19-d0859dd7}}
}

License

Released under CC BY 4.0.

Original data (c) World Health Organization. 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 2026-08-16 via the Electric Sheep pipeline. Source URL: https://docs.google.com/spreadsheets/d/e/2PACX-1vT8m53T3ITzFdJWWKkdRRVRjezgt6MeeU5c2tJWl9SNff7SYn3iJ97DZZtYSmYI67-vH7cqze1VE0/pub?gid=2141885116&single=true&output=csv