electricsheepafrica/africa-democratic-republic-of-the-congo-coronavirus-covid-19-subnational

Democratic Republic of the Congo: Coronavirus (Covid-19) Subnational

Publisher: HERA - Humanitarian Emergency Response Africa · Source: HDX · License: cc-by · Updated: 2025-05-05

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Abstract

Subnational data about Covid-19 in Democratic Republic of the Congo - Infections, Deaths, Recoveries. Gender data are not available. Please note that the data available is from 2021-09-20. VACCINATION DATA AVAILABLE (1st & 2nd doses)

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2025-05-05. Geographic scope: COD.

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

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Dataset Characteristics

Domain	Public health
Unit of observation	First-level administrative unit observations
Rows (total)	9,072
Columns	3 (0 numeric, 3 categorical, 0 datetime)
Train split	7,257 rows
Test split	1,814 rows
Geographic scope	COD
Publisher	HERA - Humanitarian Emergency Response Africa
HDX last updated	2025-05-05

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Variables

Geographic — id_date_iso_3_pays_id_pays_region_id_region_contamines_deces_gueris_contamines_femme_contamines_homme_contamines_genre_non_specifie_nouveaux_individus_vaccines_1_dose_total_individus_vaccines_1_dose_nouveaux_individus_vaccines_2_doses_total_individus_vaccines_2_doses_source (1;19/09/2020;COD;République Démocratique du Congo;17;Bas Uele;222;0;0;0;0;0;0;;;;;OMS RDC;, 6052;01/05/2021;;;;Haut Lomami;225;0;0;0;0;0;0;;;;;Comité multisectoriel de la riposte à la Pandémie du Covid-19 en RDC;, 6046;30/04/2021;;;;Tshopo;246;11;0;0;;;11;;;;;Comité multisectoriel de la riposte à la Pandémie du Covid-19 en RDC;).

Identifier / Metadata — esa_source (HDX), esa_processed (2026-04-05).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-democratic-republic-of-the-congo-coronavirus-covid-19-subnational")
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
id_date_iso_3_pays_id_pays_region_id_region_contamines_deces_gueris_contamines_femme_contamines_homme_contamines_genre_non_specifie_nouveaux_individus_vaccines_1_dose_total_individus_vaccines_1_dose_nouveaux_individus_vaccines_2_doses_total_individus_vaccines_2_doses_source	object	0.0%	1;19/09/2020;COD;République Démocratique du Congo;17;Bas Uele;222;0;0;0;0;0;0;;;;;OMS RDC;, 6052;01/05/2021;;;;Haut Lomami;225;0;0;0;0;0;0;;;;;Comité multisectoriel de la riposte à la Pandémie du Covid-19 en RDC;, 6046;30/04/2021;;;;Tshopo;246;11;0;0;;;11;;;;;Comité multisectoriel de la riposte à la Pandémie du Covid-19 en RDC;
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-05

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Numeric Summary

Column	Min	Max	Mean	Median
No numeric columns.

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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 HERA - Humanitarian Emergency Response Africa and has not been independently validated by ESA.
• Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_africa_democratic_republic_of_the_congo_coronavirus_covid_19_subnational,
  title     = {Democratic Republic of the Congo: Coronavirus  (Covid-19) Subnational},
  author    = {HERA - Humanitarian Emergency Response Africa},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/democratic-republic-of-the-congo-coronavirus-covid-19-subnational},
  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.