electricsheepafrica/africa-senegal-covid19-subnational

---
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
- other
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- disease
- epidemics-outbreaks
- fatalities
- health
- hxl
- west-africa
- sen
pretty_name: "Senegal : Coronavirus (Covid-19) Subnational"
dataset_info:
splits:
- name: train
num_examples: 5148
- name: test
num_examples: 1287
---

# Senegal : Coronavirus (Covid-19) Subnational

**Publisher:** HERA - Humanitarian Emergency Response Africa · **Source:** [HDX](https://data.humdata.org/dataset/senegal_covid19_subnational) · **License:** `cc-by` · **Updated:** 2025-05-05

---

## Abstract

Subnational data about Covid19 in Senegal- Infections (new cases), Deaths, Recoveries. Please note that the gender data is not available. Thank you for your understanding. For Senegal, the Not specified infected cases represent the confirmed contact cases, their location is not given by the government.

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

*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)** | 6,435 |
| **Columns** | 3 (0 numeric, 3 categorical, 0 datetime) |
| **Train split** | 5,148 rows |
| **Test split** | 1,287 rows |
| **Geographic scope** | SEN |
| **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_total_individus_vaccines_1_dose_source` (1;28/02/2020;SEN;Sénégal;12;Dakar;117;1;0;0;0;1;0;;;Ministère de la santé, 4287;09/12/2020;SEN;Sénégal;12;Tambacounda;128;;;;;;;;;Ministère de la santé, 4297;10/12/2020;SEN;Sénégal;12;Kolda;123;;;;;;;;;Ministère de la santé).

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

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-senegal-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_nouveaux_individus_vaccines_total_individus_vaccines_1_dose_source` | object | 0.0% | 1;28/02/2020;SEN;Sénégal;12;Dakar;117;1;0;0;0;1;0;;;Ministère de la santé, 4287;09/12/2020;SEN;Sénégal;12;Tambacounda;128;;;;;;;;;Ministère de la santé, 4297;10/12/2020;SEN;Sénégal;12;Kolda;123;;;;;;;;;Ministère de la santé |
| `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/senegal_covid19_subnational) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_senegal_covid19_subnational,
title = {Senegal : Coronavirus (Covid-19) Subnational},
author = {HERA - Humanitarian Emergency Response Africa},
year = {2025},
url = {https://data.humdata.org/dataset/senegal_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.*