electricsheepafrica/africa-demographics-benin
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--- annotations_creators: - no-annotation language_creators: - found language: - en license: other multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - original task_categories: - tabular-classification - other task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - demographics - health - ben pretty_name: "Benin - Subnational Demographic and Health Data" dataset_info: splits: - name: train num_examples: 1302 - name: test num_examples: 325 --- # Benin - Subnational Demographic and Health Data **Publisher:** The DHS Program · **Source:** [HDX](https://data.humdata.org/dataset/dhs-subnational-data-for-benin) · **License:** `hdx-other` · **Updated:** 2026-02-24 --- ## Abstract Contains data from the [DHS data portal](https://api.dhsprogram.com/). There is also a dataset containing [Benin - National Demographic and Health Data](https://data.humdata.org/dataset/dhs-data-for-benin) on HDX. The DHS Program Application Programming Interface (API) provides software developers access to aggregated indicator data from The Demographic and Health Surveys (DHS) Program. The API can be used to create various applications to help analyze, visualize, explore and disseminate data on population, health, HIV, and nutrition from more than 90 countries. Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-02-24. Geographic scope: **BEN**. *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)** | 1,628 | | **Columns** | 30 (14 numeric, 16 categorical, 0 datetime) | | **Train split** | 1,302 rows | | **Test split** | 325 rows | | **Geographic scope** | BEN | | **Publisher** | The DHS Program | | **HDX last updated** | 2026-02-24 | --- ## Variables **Geographic** — `iso3` (BEN), `location` (Atacora/Donga, Borgou/Alibori, Mono/Couffo), `dhs_countrycode` (BJ), `countryname` (Benin), `surveyyear` (range 1996.0–2017.0) and 8 others. **Outcome / Measurement** — `value` (range 0.0–203.0), `istotal` (range 0.0–0.0). **Identifier / Metadata** — `dataid` (range 29760.0–7978800.0), `indicatorid` (RH_DELP_C_DHF, CH_DIAT_C_ORT, CM_ECMR_C_U5M), `characteristicid` (range 387001.0–387018.0), `characteristiclabel` (Atacora/Donga, Borgou/Alibori, Mono/Couffo), `ispreferred` (range 0.0–1.0) and 3 others. **Other** — `indicator` (Place of delivery: Health facility, Treatment of diarrhea: Either ORS or RHF, Under-five mortality rate), `precision` (range 0.0–1.0), `indicatororder` (range 11763080.0–260321010.0), `characteristicorder` (range 1387001.0–1387018.0), `denominatorweighted` (range 19.0–4854.0) and 2 others. --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-demographics-benin") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() ``` --- ## Schema | Column | Type | Null % | Range / Sample Values | |---|---|---|---| | `iso3` | object | 0.0% | BEN | | `location` | object | 0.0% | Atacora/Donga, Borgou/Alibori, Mono/Couffo | | `dataid` | int64 | 0.0% | 29760.0 – 7978800.0 (mean 3804204.4472) | | `indicator` | object | 0.0% | Place of delivery: Health facility, Treatment of diarrhea: Either ORS or RHF, Under-five mortality rate | | `value` | float64 | 0.0% | 0.0 – 203.0 (mean 35.355) | | `precision` | int64 | 0.0% | 0.0 – 1.0 (mean 0.9165) | | `dhs_countrycode` | object | 0.0% | BJ | | `countryname` | object | 0.0% | Benin | | `surveyyear` | int64 | 0.0% | 1996.0 – 2017.0 (mean 2009.4152) | | `surveyid` | object | 0.0% | BJ2017DHS, BJ2006DHS, BJ2012DHS | | `indicatorid` | object | 0.0% | RH_DELP_C_DHF, CH_DIAT_C_ORT, CM_ECMR_C_U5M | | `indicatororder` | int64 | 0.0% | 11763080.0 – 260321010.0 (mean 97976826.3391) | | `indicatortype` | object | 0.0% | I | | `characteristicid` | int64 | 0.0% | 387001.0 – 387018.0 (mean 387009.2254) | | `characteristicorder` | int64 | 0.0% | 1387001.0 – 1387018.0 (mean 1387009.2254) | | `characteristiccategory` | object | 0.0% | Region | | `characteristiclabel` | object | 0.0% | Atacora/Donga, Borgou/Alibori, Mono/Couffo | | `byvariableid` | int64 | 0.0% | 0.0 – 631001.0 (mean 10950.0522) | | `byvariablelabel` | object | 70.5% | | | `istotal` | int64 | 0.0% | 0.0 – 0.0 (mean 0.0) | | `ispreferred` | int64 | 0.0% | 0.0 – 1.0 (mean 0.8679) | | `sdrid` | object | 0.0% | | | `regionid` | object | 0.0% | | | `surveyyearlabel` | float64 | 54.1% | 1996.0 – 2006.0 (mean 2003.246) | | `surveytype` | object | 0.0% | | | `denominatorweighted` | float64 | 25.1% | 19.0 – 4854.0 (mean 1040.3525) | | `denominatorunweighted` | float64 | 25.1% | 25.0 – 4080.0 (mean 1045.7582) | | `levelrank` | float64 | 30.1% | 1.0 – 1.0 (mean 1.0) | | `esa_source` | object | 0.0% | | | `esa_processed` | object | 0.0% | | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `dataid` | 29760.0 | 7978800.0 | 3804204.4472 | 4045764.5 | | `value` | 0.0 | 203.0 | 35.355 | 23.1 | | `precision` | 0.0 | 1.0 | 0.9165 | 1.0 | | `surveyyear` | 1996.0 | 2017.0 | 2009.4152 | 2012.0 | | `indicatororder` | 11763080.0 | 260321010.0 | 97976826.3391 | 93906230.0 | | `characteristicid` | 387001.0 | 387018.0 | 387009.2254 | 387009.0 | | `characteristicorder` | 1387001.0 | 1387018.0 | 1387009.2254 | 1387009.0 | | `byvariableid` | 0.0 | 631001.0 | 10950.0522 | 0.0 | | `istotal` | 0.0 | 0.0 | 0.0 | 0.0 | | `ispreferred` | 0.0 | 1.0 | 0.8679 | 1.0 | | `surveyyearlabel` | 1996.0 | 2006.0 | 2003.246 | 2006.0 | | `denominatorweighted` | 19.0 | 4854.0 | 1040.3525 | 853.0 | | `denominatorunweighted` | 25.0 | 4080.0 | 1045.7582 | 871.5 | | `levelrank` | 1.0 | 1.0 | 1.0 | 1.0 | --- ## 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`. 2 column(s) with >80% missing values were removed: `cilow`, `cihigh`. 1 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). 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 The DHS Program and has not been independently validated by ESA. - Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection. - The following columns have >20% missing values and should be treated with caution in modelling: `byvariablelabel`, `surveyyearlabel`, `denominatorweighted`, `denominatorunweighted`, `levelrank`. - Refer to the [original HDX dataset page](https://data.humdata.org/dataset/dhs-subnational-data-for-benin) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_demographics_benin, title = {Benin - Subnational Demographic and Health Data}, author = {The DHS Program}, year = {2026}, url = {https://data.humdata.org/dataset/dhs-subnational-data-for-benin}, 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: - 无标注 language_creators: - 采集自现有资源 language: - 英语 license: - 其他 multilinguality: - 单语言 size_categories: - 1000<样本数<10000 source_datasets: - 原创数据集 task_categories: - 表格分类 - 其他 task_ids: [] tags: - 非洲 - 人道主义 - HDX - Electric Sheep Africa - 人口统计 - 卫生 - 贝宁 pretty_name: "贝宁——次国家人口与健康数据集" dataset_info: splits: - name: 训练集 num_examples: 1302 - name: 测试集 num_examples: 325 --- # 贝宁——次国家人口与健康数据集 **发布方：人口与健康调查项目（DHS Program）** · **来源：[HDX](https://data.humdata.org/dataset/dhs-subnational-data-for-benin)** · **许可协议：`hdx-other`** · **更新时间：2026-02-24** --- ## 摘要 本数据集包含来自[DHS数据门户](https://api.dhsprogram.com/)的数据。HDX平台上另有一份[贝宁——国家人口与健康数据](https://data.humdata.org/dataset/dhs-data-for-benin)数据集。 人口与健康调查项目应用程序编程接口（DHS Program API）可为软件开发人员提供人口与健康调查项目（DHS Program）的聚合指标数据。该API可用于开发各类应用，以辅助分析、可视化、探索并传播来自全球90余个国家的人口、健康、艾滋病病毒（HIV）及营养相关数据。 本数据集的每一行均代表一级行政单元的观测记录。该数据集最近一次在HDX平台的更新时间为2026-02-24。地理覆盖范围：**BEN（贝宁）**。 本数据集由[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** | 一级行政单元观测记录 | | **总行数** | 1628 | | **列数** | 30（14个数值型列，16个分类型列，0个日期时间型列） | | **训练集划分** | 1302行 | | **测试集划分** | 325行 | | **地理覆盖范围** | BEN | | **发布方** | 人口与健康调查项目 | | **HDX平台最后更新时间** | 2026-02-24 | --- ## 变量分类 ### 地理类字段 `iso3`（BEN）、`location`（阿塔科拉/当加、博尔古/阿里巴里、莫诺/库福）、`dhs_countrycode`（BJ）、`countryname`（贝宁）、`surveyyear`（取值范围1996.0–2017.0）及另外8个字段。 ### 结果/测量类字段 `value`（取值范围0.0–203.0）、`istotal`（取值范围0.0–0.0）。 ### 标识符/元数据类字段 `dataid`（取值范围29760.0–7978800.0）、`indicatorid`（RH_DELP_C_DHF、CH_DIAT_C_ORT、CM_ECMR_C_U5M）、`characteristicid`（取值范围387001.0–387018.0）、`characteristiclabel`（阿塔科拉/当加、博尔古/阿里巴里、莫诺/库福）、`ispreferred`（取值范围0.0–1.0）及另外3个字段。 ### 其他类字段 `indicator`（分娩地点：卫生机构、腹泻治疗：口服补液盐或快速健康检测、5岁以下儿童死亡率）、`precision`（取值范围0.0–1.0）、`indicatororder`（取值范围11763080.0–260321010.0）、`characteristicorder`（取值范围1387001.0–1387018.0）、`denominatorweighted`（取值范围19.0–4854.0）及另外2个字段。 --- ## 快速上手 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-demographics-benin") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() --- ## 数据模式 | 列名 | 数据类型 | 空值占比 | 取值范围/示例值 | |---|---|---|---| | `iso3` | 字符串（object） | 0.0% | 示例值：BEN | | `location` | 字符串（object） | 0.0% | 示例值：阿塔科拉/当加、博尔古/阿里巴里、莫诺/库福 | | `dataid` | 64位整型（int64） | 0.0% | 取值范围29760.0 – 7978800.0（均值3804204.4472） | | `indicator` | 字符串（object） | 0.0% | 示例值：分娩地点：卫生机构、腹泻治疗：口服补液盐或快速健康检测、5岁以下儿童死亡率 | | `value` | 64位浮点型（float64） | 0.0% | 取值范围0.0 – 203.0（均值35.355） | | `precision` | 64位整型（int64） | 0.0% | 取值范围0.0 – 1.0（均值0.9165） | | `dhs_countrycode` | 字符串（object） | 0.0% | 示例值：BJ | | `countryname` | 字符串（object） | 0.0% | 示例值：贝宁 | | `surveyyear` | 64位整型（int64） | 0.0% | 取值范围1996.0 – 2017.0（均值2009.4152） | | `surveyid` | 字符串（object） | 0.0% | 示例值：BJ2017DHS、BJ2006DHS、BJ2012DHS | | `indicatorid` | 字符串（object） | 0.0% | 示例值：RH_DELP_C_DHF、CH_DIAT_C_ORT、CM_ECMR_C_U5M | | `indicatororder` | 64位整型（int64） | 0.0% | 取值范围11763080.0 – 260321010.0（均值97976826.3391） | | `indicatortype` | 字符串（object） | 0.0% | 示例值：I | | `characteristicid` | 64位整型（int64） | 0.0% | 取值范围387001.0 – 387018.0（均值387009.2254） | | `characteristicorder` | 64位整型（int64） | 0.0% | 取值范围1387001.0 – 1387018.0（均值1387009.2254） | | `characteristiccategory` | 字符串（object） | 0.0% | 示例值：Region | | `characteristiclabel` | 字符串（object） | 0.0% | 示例值：阿塔科拉/当加、博尔古/阿里巴里、莫诺/库福 | | `byvariableid` | 64位整型（int64） | 0.0% | 取值范围0.0 – 631001.0（均值10950.0522） | | `byvariablelabel` | 字符串（object） | 70.5% | 无有效取值 | | `istotal` | 64位整型（int64） | 0.0% | 取值范围0.0 – 0.0（均值0.0） | | `ispreferred` | 64位整型（int64） | 0.0% | 取值范围0.0 – 1.0（均值0.8679） | | `sdrid` | 字符串（object） | 0.0% | 无有效取值 | | `regionid` | 字符串（object） | 0.0% | 无有效取值 | | `surveyyearlabel` | 64位浮点型（float64） | 54.1% | 取值范围1996.0 – 2006.0（均值2003.246） | | `surveytype` | 字符串（object） | 0.0% | 无有效取值 | | `denominatorweighted` | 64位浮点型（float64） | 25.1% | 取值范围19.0 – 4854.0（均值1040.3525） | | `denominatorunweighted` | 64位浮点型（float64） | 25.1% | 取值范围25.0 – 4080.0（均值1045.7582） | | `levelrank` | 64位浮点型（float64） | 30.1% | 取值范围1.0 – 1.0（均值1.0） | | `esa_source` | 字符串（object） | 0.0% | 无有效取值 | | `esa_processed` | 字符串（object） | 0.0% | 无有效取值 | --- ## 数值型统计摘要 | 列名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---|---| | `dataid` | 29760.0 | 7978800.0 | 3804204.4472 | 4045764.5 | | `value` | 0.0 | 203.0 | 35.355 | 23.1 | | `precision` | 0.0 | 1.0 | 0.9165 | 1.0 | | `surveyyear` | 1996.0 | 2017.0 | 2009.4152 | 2012.0 | | `indicatororder` | 11763080.0 | 260321010.0 | 97976826.3391 | 93906230.0 | | `characteristicid` | 387001.0 | 387018.0 | 387009.2254 | 387009.0 | | `characteristicorder` | 1387001.0 | 1387018.0 | 1387009.2254 | 1387009.0 | | `byvariableid` | 0.0 | 631001.0 | 10950.0522 | 0.0 | | `istotal` | 0.0 | 0.0 | 0.0 | 0.0 | | `ispreferred` | 0.0 | 1.0 | 0.8679 | 1.0 | | `surveyyearlabel` | 1996.0 | 2006.0 | 2003.246 | 2006.0 | | `denominatorweighted` | 19.0 | 4854.0 | 1040.3525 | 853.0 | | `denominatorunweighted` | 25.0 | 4080.0 | 1045.7582 | 871.5 | | `levelrank` | 1.0 | 1.0 | 1.0 | 1.0 | --- ## 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。对列名进行小写转换并统一为蛇形命名法。将常见的缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。删除了2个缺失值占比超过80%的列：`cilow`与`cihigh`。根据解析成功率（阈值85%）将1个列从字符串类型转换为数值或日期时间类型。采用固定随机种子（42）将数据集按80/20的比例划分为训练集与测试集，并以Snappy压缩的Parquet格式存储。 --- ## 局限性说明 - 数据源自人口与健康调查项目，未由Electric Sheep Africa（ESA）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。 - 以下列的缺失值占比超过20%，在建模时需谨慎使用：`byvariablelabel`、`surveyyearlabel`、`denominatorweighted`、`denominatorunweighted`、`levelrank`。 - 请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/dhs-subnational-data-for-benin)查看发布方提供的方法学说明与注意事项。 --- ## 引用格式 bibtex @dataset{hdx_africa_demographics_benin, title = {Benin - Subnational Demographic and Health Data}, author = {The DHS Program}, year = {2026}, url = {https://data.humdata.org/dataset/dhs-subnational-data-for-benin}, note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)} } --- *[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — 非洲机器学习数据集基础设施。尼日利亚拉各斯。*
