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

--- 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 - mli pretty_name: "Mali - Data on forcibly displaced populations and stateless persons" dataset_info: splits: - name: train num_examples: 895 - name: test num_examples: 223 --- # Mali - 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-mli) · **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: **MLI**. *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)** | 1,119 | | **Columns** | 14 (8 numeric, 6 categorical, 0 datetime) | | **Train split** | 895 rows | | **Test split** | 223 rows | | **Geographic scope** | MLI | | **Publisher** | UNHCR - The UN Refugee Agency | | **HDX last updated** | 2026-02-25 | --- ## Variables **Geographic** — `year` (range 1991.0–2025.0), `country_of_origin_code` (MLI), `country_of_asylum_code` (NLD, BFA, SWE), `country_of_origin_name` (Mali), `country_of_asylum_name` (Netherlands (Kingdom of the), Burkina Faso, Sweden) and 4 others. **Identifier / Metadata** — `refugees` (range 0.0–169355.0), `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 0.0–3500.0). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-unhcr-population-data-for-mli") 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% | 1991.0 – 2025.0 (mean 2014.4021) | | `country_of_origin_code` | object | 0.0% | MLI | | `country_of_asylum_code` | object | 0.0% | NLD, BFA, SWE | | `country_of_origin_name` | object | 0.0% | Mali | | `country_of_asylum_name` | object | 0.0% | Netherlands (Kingdom of the), Burkina Faso, Sweden | | `refugees` | int64 | 0.0% | 0.0 – 169355.0 (mean 2959.2672) | | `asylum_seekers` | int64 | 0.0% | 0.0 – 10722.0 (mean 161.8186) | | `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 – 402167.0 (mean 2887.3056) | | `stateless_persons` | int64 | 0.0% | 0.0 – 0.0 (mean 0.0) | | `others_of_concern_to_unhcr` | int64 | 0.0% | 0.0 – 3500.0 (mean 28.6184) | | `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` | 1991.0 | 2025.0 | 2014.4021 | 2016.0 | | `refugees` | 0.0 | 169355.0 | 2959.2672 | 7.0 | | `asylum_seekers` | 0.0 | 10722.0 | 161.8186 | 6.0 | | `other_people_in_need_of_international_protection` | 0.0 | 0.0 | 0.0 | 0.0 | | `internally_displaced_persons` | 0.0 | 402167.0 | 2887.3056 | 0.0 | | `stateless_persons` | 0.0 | 0.0 | 0.0 | 0.0 | | `others_of_concern_to_unhcr` | 0.0 | 3500.0 | 28.6184 | 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-mli) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_unhcr_population_data_for_mli, title = {Mali - 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-mli}, 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: - 已获取（found，指从现有公开资源中获取而非人工生成） language: - 英语（en） license: 知识共享署名4.0国际许可协议（cc-by-4.0） multilinguality: - 单语言（monolingual） size_categories: - 1000 < 样本数 < 10000 source_datasets: - 原始数据集 task_categories: - 表格分类（tabular-classification） - 表格回归（tabular-regression） task_ids: - 无 tags: - 非洲（africa） - 人道主义（humanitarian） - HDX（人类数据交换平台，Humanitarian Data Exchange） - 非洲电羊团队（electric-sheep-africa） - 寻求庇护者（asylum-seekers） - 国内流离失所者（internally-displaced-persons-idp） - 人口（population） - 难民（refugees） - 无国籍人士（stateless-persons） - 马里国家代码（mli） pretty_name: "马里——被迫流离失所人口与无国籍人士数据" dataset_info: splits: - name: train num_examples: 895 - name: test num_examples: 223 # 马里——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） · **数据来源**：[HDX（人类数据交换平台，Humanitarian Data Exchange）](https://data.humdata.org/dataset/unhcr-population-data-for-mli) · **许可协议**：`cc-by-igo` · **最后更新时间**：2026-02-25 --- ## 摘要 本数据集由联合国难民署（UNHCR - The UN Refugee Agency）整理汇编，涵盖70余年统计活动中有关被迫流离失所人口与无国籍人士的完整信息。数据包含庇护国与来源国/地区的相关字段，可获取的统计项包括年末人口总数、人口结构特征、庇护申请情况、审批结果，以及为难民和国内流离失所者（internally-displaced-persons-idp）提供的各类安置方案（重新安置、入籍或自愿返国）。 数据集中每一行代表一个一级行政单位的观测记录，最后一次在HDX平台更新的时间为2026-02-25，地理覆盖范围仅限马里（MLI）。 *本数据集由[非洲电羊团队（Electric Sheep Africa）](https://huggingface.co/electricsheepafrica)整理为适用于机器学习的Parquet格式。* --- ## 数据集特征 | 类别 | 详情 | |---|---| | **研究领域** | 人口学与人口统计 | | **观测单位** | 一级行政单位观测记录 | | **总样本行数** | 1119 | | **字段数量** | 14个（8个数值型字段、6个分类型字段、0个日期时间型字段） | | **训练集样本数** | 895条 | | **测试集样本数** | 223条 | | **地理覆盖范围** | 马里（MLI） | | **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 | --- ## 字段说明 ### 地理类字段 `year`（年份，取值范围1991.0–2025.0）、`country_of_origin_code`（来源国代码，固定为MLI）、`country_of_asylum_code`（庇护国代码，包括NLD、BFA、SWE）、`country_of_origin_name`（来源国名称，固定为马里）、`country_of_asylum_name`（庇护国名称，包括荷兰王国、布基纳法索、瑞典）等共6个字段，另有4个补充地理类字段。 ### 标识符与元数据类字段 `refugees`（难民数量，取值范围0.0–169355.0）、`esa_source`（数据来源，固定为HDX）、`esa_processed`（数据集处理日期，2026-04-04）。 ### 其他类字段 `other_people_in_need_of_international_protection`（需国际保护的其他人群数量，取值范围0.0–0.0）、`others_of_concern_to_unhcr`（联合国难民署关注的其他人群数量，取值范围0.0–3500.0）。 --- ## 快速入门 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-unhcr-population-data-for-mli") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() --- ## 数据架构 | 字段名 | 数据类型 | 空值占比 | 范围/示例值 | |---|---|---|---| | `year` | int64 | 0.0% | 1991.0 – 2025.0（均值2014.4021） | | `country_of_origin_code` | object | 0.0% | 固定为MLI | | `country_of_asylum_code` | object | 0.0% | 可选值：NLD、BFA、SWE | | `country_of_origin_name` | object | 0.0% | 固定为马里 | | `country_of_asylum_name` | object | 0.0% | 可选值：荷兰王国、布基纳法索、瑞典 | | `refugees` | int64 | 0.0% | 0.0 – 169355.0（均值2959.2672） | | `asylum_seekers` | int64 | 0.0% | 0.0 – 10722.0（均值161.8186） | | `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 – 402167.0（均值2887.3056） | | `stateless_persons` | int64 | 0.0% | 0.0 – 0.0（均值0.0） | | `others_of_concern_to_unhcr` | int64 | 0.0% | 0.0 – 3500.0（均值28.6184） | | `host_community` | int64 | 0.0% | 0.0 – 0.0（均值0.0） | | `esa_source` | object | 0.0% | 固定为HDX | | `esa_processed` | object | 0.0% | 2026-04-04 | --- ## 数值型统计摘要 | 字段名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---|---| | `year` | 1991.0 | 2025.0 | 2014.4021 | 2016.0 | | `refugees` | 0.0 | 169355.0 | 2959.2672 | 7.0 | | `asylum_seekers` | 0.0 | 10722.0 | 161.8186 | 6.0 | | `other_people_in_need_of_international_protection` | 0.0 | 0.0 | 0.0 | 0.0 | | `internally_displaced_persons` | 0.0 | 402167.0 | 2887.3056 | 0.0 | | `stateless_persons` | 0.0 | 0.0 | 0.0 | 0.0 | | `others_of_concern_to_unhcr` | 0.0 | 3500.0 | 28.6184 | 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；所有字段名统一转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`。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，并保存为Snappy压缩的Parquet格式文件。 --- ## 局限性说明 1. 本数据集数据来源于联合国难民署，未由非洲电羊团队进行独立验证； 2. 自动化清洗流程无法修正原始数据采集阶段存在的错报值、定义不一致或抽样偏差问题； 3. 如需了解发布方的方法论说明与相关注意事项，请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/unhcr-population-data-for-mli)。 --- ## 引用格式 bibtex @dataset{hdx_africa_unhcr_population_data_for_mli, title = {Mali - 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-mli}, note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)} } --- *[非洲电羊团队（Electric Sheep Africa）](https://huggingface.co/electricsheepafrica)——非洲机器学习数据集基础设施提供商，总部位于尼日利亚拉各斯。*