electricsheepafrica/africa-total-covid-19-tests-performed-by-country

Total COVID-19 Tests Performed by Country

Publisher: HDX · Source: HDX · License: cc-by · Updated: 2025-09-08

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Abstract

'Our World in Data' is compiling COVID-19 testing data over time for many countries around the world. They are adding further data in the coming days as more details become available for other countries. In some cases figures refer to the number of tests, in other cases to the number of individuals who have been tested. Refer to documentation provided here.

Each row in this dataset represents time-series observations. Data was last updated on HDX on 2025-09-08. Geographic scope: ARG, AUS, AUT, BHR, BEL, BOL, CAN, CHL, and 55 others.

Curated into ML-ready Parquet format by Electric Sheep Africa.

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Dataset Characteristics

Domain	Public health
Unit of observation	Time-series observations
Rows (total)	77
Columns	6 (2 numeric, 4 categorical, 0 datetime)
Train split	61 rows
Test split	15 rows
Geographic scope	ARG, AUS, AUT, BHR, BEL, BOL, CAN, CHL, and 55 others
Publisher	HDX
HDX last updated	2025-09-08

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Variables

Geographic — entity (Armenia, Mexico, Philippines), year (range 34.0–59.0).

Outcome / Measurement — total_covid_19_tests (range 222.0–320000.0).

Identifier / Metadata — code (ARM, SVK, MEX), esa_source (HDX), esa_processed (2026-04-06).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-total-covid-19-tests-performed-by-country")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

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Schema

Column	Type	Null %	Range / Sample Values
entity	object	0.0%	Armenia, Mexico, Philippines
code	object	23.4%	ARM, SVK, MEX
year	int64	0.0%	34.0 – 59.0 (mean 56.5065)
total_covid_19_tests	int64	0.0%	222.0 – 320000.0 (mean 30387.961)
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-06

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Numeric Summary

Column	Min	Max	Mean	Median
year	34.0	59.0	56.5065	58.0
total_covid_19_tests	222.0	320000.0	30387.961	8603.0

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Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (N/A, null, none, -, unknown, no data, #N/A) were unified to NaN. The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

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Limitations

• Data originates from HDX and has not been independently validated by ESA.
• Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• The following columns have >20% missing values and should be treated with caution in modelling: code.
• This dataset spans 63 countries; geographic and methodological inconsistencies across national boundaries may affect cross-country comparability.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_africa_total_covid_19_tests_performed_by_country,
  title     = {Total COVID-19 Tests Performed by Country},
  author    = {HDX},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/total-covid-19-tests-performed-by-country},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

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Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.