electricsheepafrica/africa-3w-operational-presence-may-2016

--- 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: - other task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - education - who-is-doing-what-and-where-3w-4w-5w - eth pretty_name: "Ethiopia - 3W Operational Presence May 2016" dataset_info: splits: - name: train num_examples: 1640 - name: test num_examples: 410 --- # Ethiopia - 3W Operational Presence May 2016 **Publisher:** OCHA Ethiopia · **Source:** [HDX](https://data.humdata.org/dataset/3w-operational-presence-may-2016) · **License:** `cc-by` · **Updated:** 2023-03-03 --- ## Abstract The Who Does What Where is a core humanitarian dataset for coordination. This data contains operational presence of humanitarian partners in Ethiopia at admin3 level by cluster in CSV format. Each row in this dataset represents subnational administrative unit observations. Data was last updated on HDX on 2023-03-03. Geographic scope: **ETH**. *Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).* --- ## Dataset Characteristics | | | |---|---| | **Domain** | Education | | **Unit of observation** | Subnational administrative unit observations | | **Rows (total)** | 2,050 | | **Columns** | 14 (1 numeric, 13 categorical, 0 datetime) | | **Train split** | 1,640 rows | | **Test split** | 410 rows | | **Geographic scope** | ETH | | **Publisher** | OCHA Ethiopia | | **HDX last updated** | 2023-03-03 | --- ## Variables **Geographic** — `organization_type` (International NGO, Government, United Nations), `region` (Amhara, Oromia, SNNPR), `zone` (North Wollo, Wag Himra, East Harerge), `woreda` (Sekota, Guba Lafto, Kobo), `woreda_code` (range 10101.0–508061.0) and 1 others. **Identifier / Metadata** — `esa_source`, `esa_processed`. **Other** — `organization` (NDRMC, SCI, CRS), `sector` (WASH, Food, Agriculture), `subsector` (General food distribution, Crop, Water), `activities` (Food Distributions, CMAM, Construction of motorized borehole), `project_status` (Ongoing) and 1 others. --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-3w-operational-presence-may-2016") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() ``` --- ## Schema | Column | Type | Null % | Range / Sample Values | |---|---|---|---| | `organization` | object | 0.0% | NDRMC, SCI, CRS | | `organization_type` | object | 0.0% | International NGO, Government, United Nations | | `region` | object | 0.0% | Amhara, Oromia, SNNPR | | `zone` | object | 0.0% | North Wollo, Wag Himra, East Harerge | | `woreda` | object | 0.0% | Sekota, Guba Lafto, Kobo | | `woreda_code` | float64 | 0.0% | 10101.0 – 508061.0 (mean 41637.286) | | `project_type` | object | 0.0% | Emergency Response | | `sector` | object | 0.0% | WASH, Food, Agriculture | | `subsector` | object | 13.8% | General food distribution, Crop, Water | | `activities` | object | 6.7% | Food Distributions, CMAM, Construction of motorized borehole | | `project_status` | object | 0.0% | Ongoing | | `implementing_partner_s` | object | 0.0% | | | `esa_source` | object | 0.0% | | | `esa_processed` | object | 0.0% | | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `woreda_code` | 10101.0 | 508061.0 | 41637.286 | 40503.0 | --- ## 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`. 1,887 exact duplicate rows were removed. 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 OCHA Ethiopia 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/3w-operational-presence-may-2016) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_3w_operational_presence_may_2016, title = {Ethiopia - 3W Operational Presence May 2016}, author = {OCHA Ethiopia}, year = {2023}, url = {https://data.humdata.org/dataset/3w-operational-presence-may-2016}, 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: - 公开获取 language: - en license: cc-by-4.0 multilinguality: - 单语言 size_categories: - 1000<n<10000 source_datasets: - 原创数据集 task_categories: - 其他 task_ids: [] tags: - 非洲 - 人道主义 - HDX（Humanitarian Data Exchange） - electric-sheep-africa - 教育 - who-is-doing-what-and-where-3w-4w-5w - ETH（埃塞俄比亚国家代码） pretty_name: "埃塞俄比亚——2016年5月3W运营存在情况" dataset_info: splits: - name: 训练集 num_examples: 1640 - name: 测试集 num_examples: 410 # 埃塞俄比亚——2016年5月3W运营存在情况 **发布方：埃塞俄比亚联合国人道主义事务协调厅（Office for the Coordination of Humanitarian Affairs, Ethiopia，简称OCHA）** · **数据来源：[HDX（Humanitarian Data Exchange）](https://data.humdata.org/dataset/3w-operational-presence-may-2016)** · **授权协议：`cc-by`** · **最后更新：2023-03-03** --- ## 摘要 "谁在何地做何事"（Who Does What Where，简称3W）是用于人道主义协调工作的核心数据集。本数据集以CSV格式存储了埃塞俄比亚三级行政区（admin3）层面、按集群分类的人道主义合作伙伴运营存在情况。数据集中每一行对应一条次国家级行政单元的观测记录。本数据集最后于2023年3月3日在HDX平台更新，地理覆盖范围为**ETH（埃塞俄比亚）**。本数据集已由[电动绵羊非洲团队（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 | 类别 | 详情 | |---|---| | **领域** | 教育 | | **观测单元** | 次国家级行政单元 | | **总数据行数** | 2050 | | **列数** | 14列（1列为数值型，13列为分类型，无日期时间列） | | **训练集行数** | 1640 | | **测试集行数** | 410 | | **地理覆盖范围** | ETH（埃塞俄比亚） | | **发布方** | 埃塞俄比亚联合国人道主义事务协调厅 | | **HDX平台最后更新时间** | 2023年3月3日 | --- ## 变量说明 ### 地理类变量 `organization_type`（机构类型：国际非政府组织、政府、联合国）、`region`（地区：阿姆哈拉、奥罗米亚、SNNPR）、`zone`（分区：北沃洛、瓦格希姆拉、东哈勒盖）、`woreda`（埃塞俄比亚次区级行政单位，示例：塞科塔、古巴拉夫托、科博）、`woreda_code`（woreda代码，取值范围10101.0–508061.0）及其他1个变量。 ### 标识/元数据类变量 `esa_source`（数据来源标识）、`esa_processed`（数据处理标识）。 ### 其他变量 `organization`（执行机构：NDRMC、SCI、CRS）、`sector`（行业领域：WASH（水、卫生与个人卫生）、粮食、农业）、`subsector`（细分领域：一般粮食分配、作物种植、供水）、`activities`（活动内容：粮食分配、CMAM（社区急性营养不良管理）、机动钻井建设）、`project_status`（项目状态：进行中）及其他1个变量。 --- ## 快速上手 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-3w-operational-presence-may-2016") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() --- ## 数据Schema | 列名 | 数据类型 | 缺失率 | 取值范围/示例值 | |---|---|---|---| | `organization` | 字符型 | 0.0% | NDRMC、SCI、CRS | | `organization_type` | 字符型 | 0.0% | 国际非政府组织、政府、联合国 | | `region` | 字符型 | 0.0% | 阿姆哈拉、奥罗米亚、SNNPR | | `zone` | 字符型 | 0.0% | 北沃洛、瓦格希姆拉、东哈勒盖 | | `woreda` | 字符型 | 0.0% | 塞科塔、古巴拉夫托、科博 | | `woreda_code` | 浮点型 | 0.0% | 10101.0 – 508061.0（均值为41637.286） | | `project_type` | 字符型 | 0.0% | 应急响应 | | `sector` | 字符型 | 0.0% | WASH（水、卫生与个人卫生）、粮食、农业 | | `subsector` | 字符型 | 13.8% | 一般粮食分配、作物种植、供水 | | `activities` | 字符型 | 6.7% | 粮食分配、CMAM（社区急性营养不良管理）、机动钻井建设 | | `project_status` | 字符型 | 0.0% | 进行中 | | `implementing_partner_s` | 字符型 | 0.0% | 无 | | `esa_source` | 字符型 | 0.0% | 无 | | `esa_processed` | 字符型 | 0.0% | 无 | --- ## 数值型变量统计摘要 | 列名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---|---| | `woreda_code` | 10101.0 | 508061.0 | 41637.286 | 40503.0 | --- ## 数据整理流程 原始数据通过CKAN应用程序编程接口从HDX平台下载，并转换为Parquet格式。列名统一转换为小写并标准化为蛇形命名法（snake_case）。将常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。移除了1887条完全重复的行。使用固定随机种子（42）将数据集按80/20的比例划分为训练集与测试集，并以Snappy压缩格式的Parquet文件存储。 --- ## 数据集局限性 - 本数据集源自埃塞俄比亚联合国人道主义事务协调厅，未经过电动绵羊非洲团队的独立验证。 - 自动化数据清洗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说明与注意事项，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/3w-operational-presence-may-2016)。 --- ## 引用格式 bibtex @dataset{hdx_africa_3w_operational_presence_may_2016, title = {Ethiopia - 3W Operational Presence May 2016}, author = {OCHA Ethiopia}, year = {2023}, url = {https://data.humdata.org/dataset/3w-operational-presence-may-2016}, note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)} } --- *[电动绵羊非洲团队（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。*