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

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Hugging Face2026-04-05 更新2026-04-12 收录
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https://hf-mirror.com/datasets/electricsheepafrica/africa-democratic-republic-of-the-congo-coronavirus-covid-19-subnational
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--- annotations_creators: - no-annotation language_creators: - found language: - en license: cc-by-4.0 multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - original task_categories: - tabular-classification task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - central-africa - disease - epidemics-outbreaks - fatalities - health - hxl - cod pretty_name: "Democratic Republic of the Congo: Coronavirus (Covid-19) Subnational" dataset_info: splits: - name: train num_examples: 7257 - name: test num_examples: 1814 --- # Democratic Republic of the Congo: Coronavirus (Covid-19) Subnational **Publisher:** HERA - Humanitarian Emergency Response Africa · **Source:** [HDX](https://data.humdata.org/dataset/democratic-republic-of-the-congo-coronavirus-covid-19-subnational) · **License:** `cc-by` · **Updated:** 2025-05-05 --- ## 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](https://huggingface.co/electricsheepafrica).* --- ## 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 | --- ## 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). --- ## Quick Start ```python 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() ``` --- ## 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 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| _No numeric columns._ --- ## 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. --- ## 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](https://data.humdata.org/dataset/democratic-republic-of-the-congo-coronavirus-covid-19-subnational) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @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)} } ``` --- *[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*
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electricsheepafrica
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