electricsheepafrica/africa-unhcr-population-data-for-sle

--- 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: - tabular-classification - tabular-regression task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - asylum-seekers - internally-displaced-persons-idp - population - refugees - stateless-persons - sle pretty_name: "Sierra Leone - Data on forcibly displaced populations and stateless persons" dataset_info: splits: - name: train num_examples: 1411 - name: test num_examples: 352 --- # Sierra Leone - Data on forcibly displaced populations and stateless persons **Publisher:** UNHCR - The UN Refugee Agency · **Source:** [HDX](https://data.humdata.org/dataset/unhcr-population-data-for-sle) · **License:** `cc-by-igo` · **Updated:** 2026-02-25 --- ## Abstract Data collated by UNHCR, containing information about forcibly displaced populations and stateless persons, spanning across more than 70 years of statistical activities. The data includes the countries / territories of asylum and origin. Specific resources are available for end-year population totals, demographics, asylum applications, decisions, and solutions availed by refugees and IDPs (resettlement, naturalisation or returns). Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-02-25. Geographic scope: **SLE**. *Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).* --- ## Dataset Characteristics | | | |---|---| | **Domain** | Demographics and population | | **Unit of observation** | First-level administrative unit observations | | **Rows (total)** | 1,764 | | **Columns** | 14 (8 numeric, 6 categorical, 0 datetime) | | **Train split** | 1,411 rows | | **Test split** | 352 rows | | **Geographic scope** | SLE | | **Publisher** | UNHCR - The UN Refugee Agency | | **HDX last updated** | 2026-02-25 | --- ## Variables **Geographic** — `year` (range 1988.0–2025.0), `country_of_origin_code` (SLE), `country_of_asylum_code` (GBR, GIN, NLD), `country_of_origin_name` (Sierra Leone), `country_of_asylum_name` (United Kingdom of Great Britain and Northern Ireland, Guinea, Netherlands (Kingdom of the)) and 4 others. **Identifier / Metadata** — `refugees` (range 0.0–370631.0), `esa_source` (HDX), `esa_processed` (2026-04-04). **Other** — `other_people_in_need_of_international_protection` (range 0.0–0.0), `others_of_concern_to_unhcr` (range 0.0–2500.0). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-unhcr-population-data-for-sle") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() ``` --- ## Schema | Column | Type | Null % | Range / Sample Values | |---|---|---|---| | `year` | int64 | 0.0% | 1988.0 – 2025.0 (mean 2010.3985) | | `country_of_origin_code` | object | 0.0% | SLE | | `country_of_asylum_code` | object | 0.0% | GBR, GIN, NLD | | `country_of_origin_name` | object | 0.0% | Sierra Leone | | `country_of_asylum_name` | object | 0.0% | United Kingdom of Great Britain and Northern Ireland, Guinea, Netherlands (Kingdom of the) | | `refugees` | int64 | 0.0% | 0.0 – 370631.0 (mean 2304.3452) | | `asylum_seekers` | int64 | 0.0% | 0.0 – 3440.0 (mean 82.8333) | | `other_people_in_need_of_international_protection` | int64 | 0.0% | 0.0 – 0.0 (mean 0.0) | | `internally_displaced_persons` | int64 | 0.0% | 0.0 – 782000.0 (mean 2700.2268) | | `stateless_persons` | int64 | 0.0% | 0.0 – 0.0 (mean 0.0) | | `others_of_concern_to_unhcr` | int64 | 0.0% | 0.0 – 2500.0 (mean 9.2857) | | `host_community` | int64 | 0.0% | 0.0 – 0.0 (mean 0.0) | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-04 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `year` | 1988.0 | 2025.0 | 2010.3985 | 2010.0 | | `refugees` | 0.0 | 370631.0 | 2304.3452 | 15.5 | | `asylum_seekers` | 0.0 | 3440.0 | 82.8333 | 5.0 | | `other_people_in_need_of_international_protection` | 0.0 | 0.0 | 0.0 | 0.0 | | `internally_displaced_persons` | 0.0 | 782000.0 | 2700.2268 | 0.0 | | `stateless_persons` | 0.0 | 0.0 | 0.0 | 0.0 | | `others_of_concern_to_unhcr` | 0.0 | 2500.0 | 9.2857 | 0.0 | | `host_community` | 0.0 | 0.0 | 0.0 | 0.0 | --- ## 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`. 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 UNHCR - The UN Refugee Agency 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/unhcr-population-data-for-sle) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_unhcr_population_data_for_sle, title = {Sierra Leone - Data on forcibly displaced populations and stateless persons}, author = {UNHCR - The UN Refugee Agency}, year = {2026}, url = {https://data.humdata.org/dataset/unhcr-population-data-for-sle}, 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: - 现有采集数据 language: - en license: cc-by-4.0 multilinguality: - 单语 size_categories: - 1000 < 样本数 < 10000 source_datasets: - 原创数据集 task_categories: - 表格分类 - 表格回归 task_ids: [] tags: - 非洲 - 人道主义 - HDX - Electric Sheep Africa - 寻求庇护者 - 境内流离失所者（internally-displaced-persons, IDP） - 人口 - 难民 - 无国籍人士 - SLE pretty_name: "塞拉利昂——被迫流离失所人口与无国籍人士数据" dataset_info: splits: - name: train num_examples: 1411 - name: test num_examples: 352 # 塞拉利昂——被迫流离失所人口与无国籍人士数据 **发布方**：联合国难民署（UNHCR - The UN Refugee Agency）· **来源**：[HDX（人道主义数据交换平台）](https://data.humdata.org/dataset/unhcr-population-data-for-sle) · **许可证**：`cc-by-igo` · **更新时间**：2026-02-25 --- ## 摘要 本数据集由联合国难民署整理，收录了跨越70余年统计工作的被迫流离失所人口与无国籍人士相关信息，涵盖庇护国与来源国/地区的数据。数据集包含年末人口总数、人口结构、庇护申请、审批结果以及为难民和境内流离失所者（internally-displaced-persons, IDP）提供的解决方案（重新安置、归化或自愿遣返）等专项资源。 本数据集的每一行代表一级行政单元的观测数据。数据最后一次在HDX平台更新的时间为2026-02-25，地理覆盖范围：**塞拉利昂（SLE）**。 *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** | 人口与人口统计学 | | **观测单元** | 一级行政单元观测数据 | | **总数据行数** | 1764 | | **列数** | 14（8个数值型，6个分类型，0个日期型） | | **训练集拆分** | 1411行 | | **测试集拆分** | 352行 | | **地理覆盖范围** | SLE（塞拉利昂） | | **发布方** | 联合国难民署（UNHCR - The UN Refugee Agency） | | **HDX平台最后更新时间** | 2026-02-25 | --- ## 变量 ### 地理类 `year`（取值范围1988.0–2025.0）、`country_of_origin_code`（SLE）、`country_of_asylum_code`（GBR、GIN、NLD）、`country_of_origin_name`（塞拉利昂）、`country_of_asylum_name`（大不列颠及北爱尔兰联合王国、几内亚、荷兰王国）及另外4个字段。 ### 标识符与元数据类 `refugees`（取值范围0.0–370631.0）、`esa_source`（HDX）、`esa_processed`（2026-04-04）。 ### 其他类 `other_people_in_need_of_international_protection`（取值范围0.0–0.0）、`others_of_concern_to_unhcr`（取值范围0.0–2500.0）。 --- ## 快速上手 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-unhcr-population-data-for-sle") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() --- ## 数据模式（Schema） | 列名 | 数据类型 | 空值占比 | 取值范围/示例值 | |---|---|---|---| | `year` | int64 | 0.0% | 1988.0 – 2025.0（均值2010.3985） | | `country_of_origin_code` | object | 0.0% | SLE | | `country_of_asylum_code` | object | 0.0% | GBR、GIN、NLD | | `country_of_origin_name` | object | 0.0% | 塞拉利昂 | | `country_of_asylum_name` | object | 0.0% | 大不列颠及北爱尔兰联合王国、几内亚、荷兰王国 | | `refugees` | int64 | 0.0% | 0.0 – 370631.0（均值2304.3452） | | `asylum_seekers` | int64 | 0.0% | 0.0 – 3440.0（均值82.8333） | | `other_people_in_need_of_international_protection` | int64 | 0.0% | 0.0 – 0.0（均值0.0） | | `internally_displaced_persons` | int64 | 0.0% | 0.0 – 782000.0（均值2700.2268） | | `stateless_persons` | int64 | 0.0% | 0.0 – 0.0（均值0.0） | | `others_of_concern_to_unhcr` | int64 | 0.0% | 0.0 – 2500.0（均值9.2857） | | `host_community` | int64 | 0.0% | 0.0 – 0.0（均值0.0） | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-04 | --- ## 数值型字段统计摘要 | 列名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---|---| | `year` | 1988.0 | 2025.0 | 2010.3985 | 2010.0 | | `refugees` | 0.0 | 370631.0 | 2304.3452 | 15.5 | | `asylum_seekers` | 0.0 | 3440.0 | 82.8333 | 5.0 | | `other_people_in_need_of_international_protection` | 0.0 | 0.0 | 0.0 | 0.0 | | `internally_displaced_persons` | 0.0 | 782000.0 | 2700.2268 | 0.0 | | `stateless_persons` | 0.0 | 0.0 | 0.0 | 0.0 | | `others_of_concern_to_unhcr` | 0.0 | 2500.0 | 9.2857 | 0.0 | | `host_community` | 0.0 | 0.0 | 0.0 | 0.0 | --- ## 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。列名统一转换为小写并标准化为蛇形命名法。常见缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）被统一替换为`NaN`。本数据集使用固定随机种子（42）按照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 - 数据源自联合国难民署，未经过Electric Sheep Africa的独立验证。 - 自动化清洗流程无法修正原始数据收集中的错报、定义不一致或抽样偏差问题。 - 如需查看发布方的方法论说明与免责声明，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/unhcr-population-data-for-sle)。 --- ## 引用格式 bibtex @dataset{hdx_africa_unhcr_population_data_for_sle, title = {Sierra Leone - Data on forcibly displaced populations and stateless persons}, author = {UNHCR - The UN Refugee Agency}, year = {2026}, url = {https://data.humdata.org/dataset/unhcr-population-data-for-sle}, note = {由Electric Sheep Africa整理为机器学习可用格式 (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。*