Datasets:
Download README.md from electricsheepafrica/africa-mauritania-mauritania-coronavirus-covid-19-subnational-0d787a8c: direct link, hf CLI and curl.
- Browser
- Download file 7.49 kB
-
https://huggingface.co/datasets/electricsheepafrica/africa-mauritania-mauritania-coronavirus-covid-19-subnational-0d787a8c/resolve/main/README.md
- Command line
-
hf download hf://datasets/electricsheepafrica/africa-mauritania-mauritania-coronavirus-covid-19-subnational-0d787a8c/README.md
-
curl -L -o README.md https://huggingface.co/datasets/electricsheepafrica/africa-mauritania-mauritania-coronavirus-covid-19-subnational-0d787a8c/resolve/main/README.md
license: cc-by-4.0
language:
- en
task_categories:
- tabular-regression
- time-series-forecasting
multilinguality: monolingual
size_categories:
- 10K<n<100K
tags:
- tabular
- xlsx
- africa
- mauritania
- official-statistics
- open-data
- health
configs:
- config_name: default
data_files:
- split: train
path: data/train-00000-of-00001.parquet
pretty_name: >-
Mauritania: Coronavirus (Covid-19) Subnational | Africa (Mauritania official
open data)
Mauritania: Coronavirus (Covid-19) Subnational | Africa (Mauritania official open data)
62,352 rows - 1 Africa country - 2020-2022 - Repackaged by Electric Sheep Africa
TL;DR
This dataset packages one official XLSX resource from Mauritania as
ML-ready Parquet. The source file is the provenance boundary; all usable
indicators or tabular columns from the resource stay together in this repo.
About the source
- Source: Mauritania: Coronavirus (Covid-19) Subnational
- Publisher: HERA - Humanitarian Emergency Response Africa
- Resource: MRT_Subnational_Covid19_HERA.xlsx
- Format:
XLSX - License: CC BY 4.0
- Packaging mode:
indicator_long
Geographic coverage
1 Africa country:
| Country | Rows | First year | Last year | Name |
|---|---|---|---|---|
MRT |
62,352 | 2020 | 2022 | Mauritania |
Indicators or Resource Contents
mauritania-coronavirus-covid-19-subnational-id-c9fa5cbc- Mauritania: Coronavirus (Covid-19) Subnational - idmauritania-coronavirus-covid-19-subnational-id-pays-554513a9- Mauritania: Coronavirus (Covid-19) Subnational - id paysmauritania-coronavirus-covid-19-subnational-id-region-1a0f17df- Mauritania: Coronavirus (Covid-19) Subnational - id regionmauritania-coronavirus-covid-19-subnational-contamines-59b19979- Mauritania: Coronavirus (Covid-19) Subnational - contaminesmauritania-coronavirus-covid-19-subnational-deces-6c9bec2e- Mauritania: Coronavirus (Covid-19) Subnational - decesmauritania-coronavirus-covid-19-subnational-gueris-6926b5df- Mauritania: Coronavirus (Covid-19) Subnational - guerismauritania-coronavirus-covid-19-subnational-contamines-femme-844abdf1- Mauritania: Coronavirus (Covid-19) Subnational - contamines femmemauritania-coronavirus-covid-19-subnational-contamines-homme-c1a0cf4d- Mauritania: Coronavirus (Covid-19) Subnational - contamines hommemauritania-coronavirus-covid-19-subnational-contamines-genre-non-specifi-4bc7647a- Mauritania: Coronavirus (Covid-19) Subnational - contamines genre non specifie
Schema
| Column | Type | Description | Example |
|---|---|---|---|
indicator_id |
string |
Stable indicator identifier. | mauritania-coronavirus-covid-19-subnational-id-c9fa5cbc |
indicator_name |
string |
Human-readable indicator name. | Mauritania: Coronavirus (Covid-19) Subnational - id |
country_iso3 |
string |
ISO3 country code. | MRT |
source_sheet |
string |
Workbook sheet name, when the source is a spreadsheet. | Feuil1 |
country_name |
string |
Country name. | Mauritania |
year |
Int64 |
Observation year. | 2020 |
value |
float64 |
Numeric observation value. | 1.0 |
unit |
string |
Measurement unit, when available. | source_units_unspecified |
dimension_iso_3 |
string |
Source dimension. | MRT |
dimension_pays |
string |
Source dimension. | Mauritanie |
dimension_region |
string |
Source dimension. | Adrar |
dimension_source |
string |
Source dimension. | Ministère de la Santé |
source_period_start_year |
Int64 |
First year inferred from source resource metadata. | `` |
source_period_end_year |
Int64 |
Last year inferred from source resource metadata. | `` |
source_period_label |
string |
Human-readable period inferred from source resource metadata. | `` |
source_provider |
category |
Publishing organization. | HERA - Humanitarian Emergency Response Africa |
source_dataset |
category |
Source package title. | Mauritania: Coronavirus (Covid-19) Subnational |
source_resource |
category |
Source resource title. | MRT_Subnational_Covid19_HERA.xlsx |
source_package_id |
category |
CKAN package UUID. | 0d899d93-91ba-4316-9f40-243b4452e752 |
source_resource_id |
category |
CKAN resource UUID. | fc962964-704d-4365-a52d-67463f095ec2 |
source_url |
category |
Original source resource URL. | https://data.humdata.org/dataset/0d899d93-91ba-4316-9f40-243b4452e752/re |
license_id |
category |
Source license identifier. | cc-by |
retrieved_at |
category |
UTC retrieval timestamp. | 2026-08-18T00:06:00Z |
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-mauritania-mauritania-coronavirus-covid-19-subnational-0d787a8c")
df = ds["train"].to_pandas()
print(df.head())
Filter to one country
sample_country = df[df["country_iso3"] == "MRT"]
Work with indicators
if "indicator_id" in df.columns:
print(df["indicator_id"].value_counts().head())
sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])
Citation
@misc{electric_sheep_africa_africa_mauritania_mauritania_coronavirus_covid_19_subnational_0d787a8c_2022,
title = {Mauritania: Coronavirus (Covid-19) Subnational | Africa (Mauritania official open data)},
author = {HERA - Humanitarian Emergency Response Africa},
year = {2022},
url = {https://data.humdata.org/dataset/mauritania_covid19_subnational},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritania-mauritania-coronavirus-covid-19-subnational-0d787a8c}}
}
License
Released under CC BY 4.0.
Original data (c) HERA - Humanitarian Emergency Response Africa. When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.
About Electric Sheep
Electric Sheep Africa is part of the Electric Sheep mission: a unified,
ML-ready data layer for Africa on Hugging Face. We pull data from authoritative
open sources, normalize the schemas, package as Parquet, and publish with
consistent dataset cards so researchers and developers can use load_dataset()
to start working in seconds.
Browse the full collection: huggingface.co/electricsheepafrica
Provenance: ingested 2026-08-18 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/0d899d93-91ba-4316-9f40-243b4452e752/resource/fc962964-704d-4365-a52d-67463f095ec2/download/mrt_subnational_covid19_hera.xlsx