electricsheepafrica/africa-west-and-central-africa-administrative-boundaries-levels

--- 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 - central-africa - geodata - populated-places-settlements - west-africa - ben - bfa - cpv - cmr - caf pretty_name: "West and Central Africa - Administrative boundaries levels 0 - 2 and Settlements" dataset_info: splits: - name: train num_examples: 1884 - name: test num_examples: 471 --- # West and Central Africa - Administrative boundaries levels 0 - 2 and Settlements **Publisher:** OCHA West and Central Africa (ROWCA) · **Source:** [HDX](https://data.humdata.org/dataset/west-and-central-africa-administrative-boundaries-levels) · **License:** `cc-by` · **Updated:** 2025-05-05 --- ## Abstract West and Central Africa Administrative boundaries, administrative level 0 to 2. Notice: The boundaries and names shown and the designations used on these shapefiles do not imply official endorsement or acceptance by the United Nations. West and Central Africa settlements with administrative capitals Each row in this dataset represents subnational administrative unit observations. Temporal coverage is indicated by the `last_modif`, `date` column(s). Geographic scope: **BEN, BFA, CPV, CMR, CAF, TCD, COG, CIV, and 16 others**. *Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).* --- ## Dataset Characteristics | | | |---|---| | **Domain** | Humanitarian and development data | | **Unit of observation** | Subnational administrative unit observations | | **Rows (total)** | 2,355 | | **Columns** | 14 (3 numeric, 9 categorical, 2 datetime) | | **Train split** | 1,884 rows | | **Test split** | 471 rows | | **Geographic scope** | BEN, BFA, CPV, CMR, CAF, TCD, COG, CIV, and 16 others | | **Publisher** | OCHA West and Central Africa (ROWCA) | | **HDX last updated** | 2025-05-05 | --- ## Variables **Geographic** — `admin0name` (Nigeria, Ghana, Democratic Republic of Congo), `admin0pcod` (NG, GH, CD), `admin1name` (Kano, Ashanti, Eastern), `admin2name` (Sao Joao Baptista, Nossa Senhora Da Luz, Dagana), `admin1pcod` (NG20, GH02, NG21) and 1 others. **Temporal** — `date`. **Identifier / Metadata** — `objectid_1` (range 1.0–2356.0), `source` (OCHAfrom ctrylayers), `esa_source` (HDX), `esa_processed` (2026-04-08). **Other** — `last_modif`, `shape_leng` (range 0.0462–26.1063), `shape_area` (range 0.0001–28.8161). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-west-and-central-africa-administrative-boundaries-levels") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() ``` --- ## Schema | Column | Type | Null % | Range / Sample Values | |---|---|---|---| | `objectid_1` | int64 | 0.0% | 1.0 – 2356.0 (mean 1178.6025) | | `admin0name` | object | 0.0% | Nigeria, Ghana, Democratic Republic of Congo | | `admin0pcod` | object | 0.0% | NG, GH, CD | | `admin1name` | object | 0.0% | Kano, Ashanti, Eastern | | `admin2name` | object | 0.0% | Sao Joao Baptista, Nossa Senhora Da Luz, Dagana | | `admin1pcod` | object | 0.0% | NG20, GH02, NG21 | | `admin2pcod` | object | 0.0% | CD10, CI0903, LR0402 | | `last_modif` | datetime64[ns] | 0.0% | | | `source` | object | 0.0% | OCHAfrom ctrylayers | | `date` | datetime64[ns] | 0.0% | | | `shape_leng` | float64 | 0.0% | 0.0462 – 26.1063 (mean 2.5904) | | `shape_area` | float64 | 0.0% | 0.0001 – 28.8161 (mean 0.4021) | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-08 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `objectid_1` | 1.0 | 2356.0 | 1178.6025 | 1179.0 | | `shape_leng` | 0.0462 | 26.1063 | 2.5904 | 1.777 | | `shape_area` | 0.0001 | 28.8161 | 0.4021 | 0.1037 | --- ## 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 OCHA West and Central Africa (ROWCA) and has not been independently validated by ESA. - Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection. - This dataset spans 24 countries; geographic and methodological inconsistencies across national boundaries may affect cross-country comparability. - Refer to the [original HDX dataset page](https://data.humdata.org/dataset/west-and-central-africa-administrative-boundaries-levels) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_west_and_central_africa_administrative_boundaries_levels, title = {West and Central Africa - Administrative boundaries levels 0 - 2 and Settlements}, author = {OCHA West and Central Africa (ROWCA)}, year = {2025}, url = {https://data.humdata.org/dataset/west-and-central-africa-administrative-boundaries-levels}, 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: - 现有资源抓取 language: - 英语 license: 知识共享署名4.0（cc-by-4.0） multilinguality: - 单语言 size_categories: - 1000 < 样本量 < 10000 source_datasets: - 原创数据集 task_categories: - 其他 task_ids: [] tags: - 非洲 - 人道主义 - 人道主义数据交换（Humanitarian Data Exchange, HDX） - Electric Sheep Africa - 中非 - 地理数据 - 居民点与定居点 - 西非 - BEN - BFA - CPV - CMR - CAF pretty_name: "西非与中非——0至2级行政边界与居民点" dataset_info: splits: - name: train num_examples: 1884 - name: test num_examples: 471 # 西非与中非——0至2级行政边界与居民点 **发布方**：联合国人道主义事务协调厅（Office for the Coordination of Humanitarian Affairs, OCHA）西非与中非办事处（ROWCA）· **来源**：[人道主义数据交换（Humanitarian Data Exchange, HDX）](https://data.humdata.org/dataset/west-and-central-africa-administrative-boundaries-levels) · **许可协议**：`cc-by` · **更新时间**：2025-05-05 --- ## 摘要 本数据集包含西非与中非地区0至2级行政边界数据。注意：本数据集附带的边界、名称及相关标识并不代表联合国的官方认可或接受。 本数据集同时涵盖西非与中非地区带有行政首府的居民点数据。 数据集中每一行代表一条次国家级行政单元的观测记录。时间覆盖范围由`last_modif`、`date`字段体现。地理覆盖范围：**BEN、BFA、CPV、CMR、CAF、TCD、COG、CIV及另外16个国家**。 本数据集由[Electric Sheep Africa](https://huggingface.co/electricsheepafrica)整理为机器学习可用的Parquet格式。 --- ## 数据集特征 | | | |---|---| | **领域** | 人道主义与发展数据 | | **观测单元** | 次国家级行政单元观测记录 | | **总行数** | 2355 | | **字段数** | 14（3个数值型、9个分类型、2个日期时间型） | | **训练集划分** | 1884行 | | **测试集划分** | 471行 | | **地理覆盖范围** | BEN、BFA、CPV、CMR、CAF、TCD、COG、CIV及另外16个国家 | | **发布方** | 联合国人道主义事务协调厅西非与中非办事处（ROWCA） | | **HDX最后更新时间** | 2025-05-05 | --- ## 字段说明 ### 地理类字段 `admin0name`（示例值：尼日利亚、加纳、刚果民主共和国）、`admin0pcod`（示例值：NG、GH、CD）、`admin1name`（示例值：卡诺、阿散蒂、东部省）、`admin2name`（示例值：圣若昂巴普蒂斯塔、圣卢西亚、达加纳）、`admin1pcod`（示例值：NG20、GH02、NG21）及1个其他字段。 ### 时间类字段 `date`。 ### 标识符与元数据字段 `objectid_1`（取值范围1.0–2356.0）、`source`（OCHAfrom ctrylayers）、`esa_source`（HDX）、`esa_processed`（2026-04-08）。 ### 其他字段 `last_modif`、`shape_leng`（取值范围0.0462–26.1063）、`shape_area`（取值范围0.0001–28.8161）。 --- ## 快速上手 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-west-and-central-africa-administrative-boundaries-levels") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() --- ## 字段结构 | 字段名 | 数据类型 | 空值占比 | 取值范围/示例值 | |---|---|---|---| | `objectid_1` | int64 | 0.0% | 1.0 – 2356.0（均值1178.6025） | | `admin0name` | object | 0.0% | 尼日利亚、加纳、刚果民主共和国 | | `admin0pcod` | object | 0.0% | NG、GH、CD | | `admin1name` | object | 0.0% | 卡诺、阿散蒂、东部省 | | `admin2name` | object | 0.0% | 圣若昂巴普蒂斯塔、圣卢西亚、达加纳 | | `admin1pcod` | object | 0.0% | NG20、GH02、NG21 | | `admin2pcod` | object | 0.0% | CD10、CI0903、LR0402 | | `last_modif` | datetime64[ns] | 0.0% | 无 | | `source` | object | 0.0% | OCHAfrom ctrylayers | | `date` | datetime64[ns] | 0.0% | 无 | | `shape_leng` | float64 | 0.0% | 0.0462 – 26.1063（均值2.5904） | | `shape_area` | float64 | 0.0% | 0.0001 – 28.8161（均值0.4021） | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-08 | --- ## 数值型字段统计摘要 | 字段名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---|---| | `objectid_1` | 1.0 | 2356.0 | 1178.6025 | 1179.0 | | `shape_leng` | 0.0462 | 26.1063 | 2.5904 | 1.777 | | `shape_area` | 0.0001 | 28.8161 | 0.4021 | 0.1037 | --- ## 数据整理流程 原始数据通过CKAN API从HDX下载，并转换为Parquet格式。字段名统一转换为小写蛇形命名法。常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）被统一替换为`NaN`。本数据集以固定随机种子（42）按80/20比例划分为训练集与测试集，并保存为Snappy压缩的Parquet格式。 --- ## 数据集局限性 - 数据源自联合国人道主义事务协调厅西非与中非办事处（ROWCA），并未经Electric Sheep Africa独立验证。 - 自动化清洗无法修正原始数据收集中的错报值、定义不一致或采样偏差问题。 - 本数据集覆盖24个国家，各国边界的地理与方法学差异可能影响跨国可比性。 - 如需查看发布方的方法说明与免责声明，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/west-and-central-africa-administrative-boundaries-levels)。 --- ## 引用格式 bibtex @dataset{hdx_africa_west_and_central_africa_administrative_boundaries_levels, title = {West and Central Africa - Administrative boundaries levels 0 - 2 and Settlements}, author = {OCHA West and Central Africa (ROWCA)}, year = {2025}, url = {https://data.humdata.org/dataset/west-and-central-africa-administrative-boundaries-levels}, 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提供商。尼日利亚拉各斯。*