electricsheepafrica/africa-mauritania-covid19-subnational

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- tabular-classification
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- disease
- epidemics-outbreaks
- fatalities
- gender
- health
- hxl
- west-africa
- mrt
pretty_name: "Mauritania: Coronavirus (Covid-19) Subnational"
dataset_info:
splits:
- name: train
num_examples: 8321
- name: test
num_examples: 2080
---

# Mauritania: Coronavirus (Covid-19) Subnational

**Publisher:** HERA - Humanitarian Emergency Response Africa · **Source:** [HDX](https://data.humdata.org/dataset/mauritania_covid19_subnational) · **License:** `cc-by` · **Updated:** 2025-05-05

---

## Abstract

Subnational data about Covid19 in Mauritania - Infections (new cases, gender), Deaths, Recoveries. Please note that the gender data is not available yet for every day, our teams are working on it. Thank you for your understanding.

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

*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)** | 10,402 |
| **Columns** | 3 (0 numeric, 3 categorical, 0 datetime) |
| **Train split** | 8,321 rows |
| **Test split** | 2,080 rows |
| **Geographic scope** | MRT |
| **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_source` (1;13/03/2020;MRT;Mauritanie;6;Adrar;59;0;0;0;0;0;0;Ministère de la Santé , 6948;22/07/2021;MRT;Mauritanie;6;Dakhlet Nouadhibou;62;;;;;;;Agence Mauritanienne d'information, 6930;20/07/2021;MRT;Mauritanie;6;Non spécifié;72;0;1;99;0;0;0;Agence Mauritanienne d'information).

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

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritania-covid19-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_source` | object | 0.0% | 1;13/03/2020;MRT;Mauritanie;6;Adrar;59;0;0;0;0;0;0;Ministère de la Santé , 6948;22/07/2021;MRT;Mauritanie;6;Dakhlet Nouadhibou;62;;;;;;;Agence Mauritanienne d'information, 6930;20/07/2021;MRT;Mauritanie;6;Non spécifié;72;0;1;99;0;0;0;Agence Mauritanienne d'information |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-04 |

---

## 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/mauritania_covid19_subnational) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_mauritania_covid19_subnational,
title = {Mauritania: Coronavirus (Covid-19) Subnational},
author = {HERA - Humanitarian Emergency Response Africa},
year = {2025},
url = {https://data.humdata.org/dataset/mauritania_covid19_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.*