Add README.md

README.md

@@ -1,26 +1,141 @@
 ---
+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:
-  features:
-  - name: 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
-    dtype: string
-  - name: esa_source
-    dtype: string
-  - name: esa_processed
-    dtype: string
   splits:
-  - name: train
-    num_bytes: 1179124
-    num_examples: 7257
-  - name: test
-    num_bytes: 294142
-    num_examples: 1815
-  download_size: 246732
-  dataset_size: 1473266
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
+    - 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.*