| --- |
| 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.* |