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.*annotations_creators: - 无注释 language_creators: - 现有资源获取 language: - 英语（en） license: - CC-BY-4.0 multilinguality: - 单语言 size_categories: - 10000 < n < 100000 source_datasets: - 原始数据集 task_categories: - 表格分类 task_ids: - 无 tags: - 非洲 - 人道主义 - 人道主义数据交换（HDX） - electric-sheep-africa - 疾病 - 疫情暴发 - 死亡病例 - 性别 - 公共卫生 - 人道主义交换语言（HXL） - 西非 - MRT pretty_name: "毛里塔尼亚：冠状病毒（Covid-19）次国家级数据集" dataset_info: splits: - name: train num_examples: 8321 - name: test num_examples: 2080 # 毛里塔尼亚：冠状病毒（Covid-19）次国家级数据集 **发布方：** HERA - 人道主义应急响应非洲分部 · **数据源：** [人道主义数据交换（HDX）](https://data.humdata.org/dataset/mauritania_covid19_subnational) · **许可协议：** `cc-by` · **最后更新：** 2025-05-05 --- ## 摘要 本数据集包含毛里塔尼亚境内新冠疫情的次国家级统计数据，涵盖感染情况（新增病例、性别分布）、死亡病例及康复病例。请注意，部分日期的性别分布数据暂未完善，我们的团队正在加紧完善相关内容，感谢您的理解。 本数据集的每一行数据代表该国一级行政单元的观测统计结果。数据最后于2025-05-05在HDX平台更新。地理覆盖范围：**MRT（毛里塔尼亚国际标准化组织国家代码）**。 *本数据集已由[非洲电羊（Electric Sheep Africa）](https://huggingface.co/electricsheepafrica)整理为适配机器学习的Parquet格式。* --- ## 数据集特征 | | | |---|---| | **领域** | 公共卫生 | | **观测单元** | 一级行政单元观测样本 | | **总数据行数** | 10,402 | | **列数** | 3（0个数值型列、3个分类型列、0个日期时间型列） | | **训练集划分** | 8,321行 | | **测试集划分** | 2,080行 | | **地理覆盖范围** | MRT | | **发布方** | HERA - 人道主义应急响应非洲分部 | | **HDX最后更新时间** | 2025-05-05 | --- ## 变量说明 **地理与标识类变量** — `id_date_iso_3_pays_id_pays_region_id_region_contamines_deces_gueris_contamines_femme_contamines_homme_contamines_genre_non_specifie_source`，示例值：`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`。 **标识符与元数据字段** — `esa_source`（数据源：HDX）、`esa_processed`（数据处理完成日期：2026-04-04）。 --- ## 快速上手 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() --- ## 数据架构 | 列名 | 数据类型 | 空值占比 | 取值范围/示例值 | |---|---|---|---| | `id_date_iso_3_pays_id_pays_region_id_region_contamines_deces_gueris_contamines_femme_contamines_homme_contamines_genre_non_specifie_source` | 字符型 | 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` | 字符型 | 0.0% | HDX | | `esa_processed` | 字符型 | 0.0% | 2026-04-04 | --- ## 数值型字段统计摘要 | 列名 | 最小值 | 最大值 | 平均值 | 中位数 | |---|---|---|---|---| _无数值型字段。_ --- ## 数据整理流程 原始数据通过CKAN API从HDX平台下载，并转换为Parquet格式。字段名统一转换为小写并采用蛇形命名法（snake_case）进行标准化。将常见的缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。本数据集采用固定随机种子（42）按80/20的比例划分为训练集与测试集，并保存为Snappy压缩格式的Parquet文件。 --- ## 数据集局限性 - 本数据集数据源自HERA - 人道主义应急响应非洲分部，尚未由非洲电羊（Electric Sheep Africa）进行独立验证。 - 自动化清洗流程无法修正原始数据收集中的错报值、定义不一致或抽样偏差问题。 - 如需了解发布方的方法论说明与注意事项，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/mauritania_covid19_subnational)。 --- ## 引用格式 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)} } --- *[非洲电羊（Electric Sheep Africa）](https://huggingface.co/electricsheepafrica)——非洲机器学习数据集基础设施提供商，尼日利亚拉各斯。*