electricsheepafrica/africa-idmc-idp-data-zmb

--- annotations_creators: - no-annotation language_creators: - found language: - en license: cc-by-4.0 multilinguality: - monolingual size_categories: - n<1K source_datasets: - original task_categories: - tabular-classification task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - conflict-violence - displacement - internally-displaced-persons-idp - natural-disasters - zmb pretty_name: "Zambia - Internal Displacements (New Displacements) – IDPs" dataset_info: splits: - name: train num_examples: 0 - name: test num_examples: 0 --- # Zambia - Internal Displacements (New Displacements) – IDPs **Publisher:** Internal Displacement Monitoring Centre (IDMC) · **Source:** [HDX](https://data.humdata.org/dataset/idmc-idp-data-zmb) · **License:** `cc-by-igo` · **Updated:** 2026-03-18 --- ## Abstract The [Global Internal Displacement Database (GIDD)](http://www.internal-displacement.org/database/displacement-data), maintained by the [Internal Displacement Monitoring Centre (IDMC)](https://www.internal-displacement.org/), provides comprehensive, validated annual estimates of internal displacement worldwide. It defines internally displaced persons (IDPs) in line with the [1998 Guiding Principles](https://www.internal-displacement.org/internal-displacement/guiding-principles-on-internal-displacement/), as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border. The GIDD tracks two primary metrics: "People Displaced" or population "Stock" figures, which represent the total number of people living in displacement at year-end, and "New Displacement," which counts new displacement incidents (population Flows) rather than individual people, accounting for potential multiple displacements by the same person. This dataset serves as a crucial resource for understanding long-term trends and validated displacement figures globally. For further detailed information and complete API specifications, users are encouraged to consult the official documentation at https://www.internal-displacement.org/database/api-documentation/. "Internally displaced persons - IDPs" refers to the number of people living in displacement as of the end of each year. "Internal displacements (New Displacements)" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once. Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-03-18. Geographic scope: **ZMB**. *Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).* --- ## Dataset Characteristics | | | |---|---| | **Domain** | Conflict and security | | **Unit of observation** | Country-level aggregates | | **Rows (total)** | 1 | | **Columns** | 9 (5 numeric, 4 categorical, 0 datetime) | | **Train split** | 0 rows | | **Test split** | 0 rows | | **Geographic scope** | ZMB | | **Publisher** | Internal Displacement Monitoring Centre (IDMC) | | **HDX last updated** | 2026-03-18 | --- ## Variables **Geographic** — `iso3` (ZMB), `country_name` (Zambia), `year` (range 2024.0–2024.0), `new_displacement` (range 513.0–513.0), `new_displacement_rounded` (range 510.0–510.0) and 2 others. **Identifier / Metadata** — `esa_source` (HDX), `esa_processed` (2026-04-07). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-idmc-idp-data-zmb") 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% | ZMB | | `country_name` | object | 0.0% | Zambia | | `year` | int64 | 0.0% | 2024.0 – 2024.0 (mean 2024.0) | | `new_displacement` | int64 | 0.0% | 513.0 – 513.0 (mean 513.0) | | `new_displacement_rounded` | int64 | 0.0% | 510.0 – 510.0 (mean 510.0) | | `total_displacement` | int64 | 0.0% | 186.0 – 186.0 (mean 186.0) | | `total_displacement_rounded` | int64 | 0.0% | 190.0 – 190.0 (mean 190.0) | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-07 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `year` | 2024.0 | 2024.0 | 2024.0 | 2024.0 | | `new_displacement` | 513.0 | 513.0 | 513.0 | 513.0 | | `new_displacement_rounded` | 510.0 | 510.0 | 510.0 | 510.0 | | `total_displacement` | 186.0 | 186.0 | 186.0 | 186.0 | | `total_displacement_rounded` | 190.0 | 190.0 | 190.0 | 190.0 | --- ## 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 Internal Displacement Monitoring Centre (IDMC) 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/idmc-idp-data-zmb) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_idmc_idp_data_zmb, title = {Zambia - Internal Displacements (New Displacements) – IDPs}, author = {Internal Displacement Monitoring Centre (IDMC)}, year = {2026}, url = {https://data.humdata.org/dataset/idmc-idp-data-zmb}, 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: - 公开获取 language: - 英语 license: CC-BY-4.0 multilinguality: - 单语言 size_categories: - 样本数少于1000 source_datasets: - 原始数据集 task_categories: - 表格分类 task_ids: [] tags: - 非洲 - 人道主义 - HDX - Electric Sheep Africa - 冲突与暴力 - 流离失所 - 国内流离失所者（IDPs） - 自然灾害 - ZMB pretty_name: "赞比亚——国内流离失所（新增流离失所情况）——国内流离失所者（IDPs）" dataset_info: splits: - name: train num_examples: 0 - name: test num_examples: 0 --- # 赞比亚——国内流离失所（新增流离失所情况）——国内流离失所者（IDPs） **发布方**：国内流离失所监测中心（Internal Displacement Monitoring Centre, IDMC） · **数据源**：[HDX](https://data.humdata.org/dataset/idmc-idp-data-zmb) · **许可证**：`CC-BY-IGO` · **更新时间**：2026-03-18 --- ## 摘要 由[全球国内流离失所数据库（GIDD）](http://www.internal-displacement.org/database/displacement-data)（由[国内流离失所监测中心（IDMC）](https://www.internal-displacement.org/)维护）提供覆盖全球的、经过验证的年度国内流离失所情况估算数据。该数据库依据《1998年国内流离失所指导原则》（[1998 Guiding Principles](https://www.internal-displacement.org/internal-displacement/guiding-principles-on-internal-displacement/)）对国内流离失所者（IDPs）作出定义：因武装冲突、规避武装冲突影响、大规模暴力事件、人权侵犯行为、自然灾害或人为灾害，被迫或不得不逃离家园或惯常居所，且未跨越国际边境的个人或群体。 GIDD 主要追踪两项核心指标：一是“流离失所人口”或年末流离失所人口存量（Stock），即年末处于流离失所状态的总人口数；二是“新增流离失所情况”，统计的是新增流离失所事件（人口流动量）而非个体人数，以此涵盖同一人多次流离失所的情况。本数据集是理解全球国内流离失所长期趋势与经验证的流离失所数据的重要资源。如需获取详细信息与完整API规范，建议用户查阅官方文档：https://www.internal-displacement.org/database/api-documentation/。 “国内流离失所者（IDPs）”指截至每年年末处于流离失所状态的人口总数。 “国内流离失所（新增流离失所情况）”指记录的新增流离失所事件数，而非流离失所者人数，这是考虑到个人可能多次经历流离失所。 本数据集的每一行均为国家级汇总数据。数据最后于2026-03-18在HDX平台更新。地理覆盖范围：**ZMB（赞比亚）**。 *本数据集经[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 | | | |---|---| | **研究领域** | 冲突与安全 | | **观测单元** | 国家级汇总数据 | | **总行数** | 1 | | **总列数** | 9（5个数值型列、4个分类型列、0个日期时间型列） | | **训练集拆分** | 0行 | | **测试集拆分** | 0行 | | **地理覆盖范围** | ZMB（赞比亚） | | **发布方** | 国内流离失所监测中心（IDMC） | | **HDX平台最后更新时间** | 2026-03-18 | --- ## 变量说明 ### 地理类变量 `iso3`（国家ISO3代码，取值为ZMB）、`country_name`（国家名称，赞比亚）、`year`（取值范围：2024.0–2024.0）、`new_displacement`（取值范围：513.0–513.0）、`new_displacement_rounded`（取值范围：510.0–510.0）及另外2个变量。 ### 标识符与元数据类变量 `esa_source`（数据来源：HDX）、`esa_processed`（数据处理时间：2026-04-07）。 --- ## 快速上手 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-idmc-idp-data-zmb") 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` | 字符串型（object） | 0.0% | ZMB | | `country_name` | 字符串型（object） | 0.0% | 赞比亚 | | `year` | 64位整数型（int64） | 0.0% | 2024.0 – 2024.0（均值：2024.0） | | `new_displacement` | 64位整数型（int64） | 0.0% | 513.0 – 513.0（均值：513.0） | | `new_displacement_rounded` | 64位整数型（int64） | 0.0% | 510.0 – 510.0（均值：510.0） | | `total_displacement` | 64位整数型（int64） | 0.0% | 186.0 – 186.0（均值：186.0） | | `total_displacement_rounded` | 64位整数型（int64） | 0.0% | 190.0 – 190.0（均值：190.0） | | `esa_source` | 字符串型（object） | 0.0% | HDX | | `esa_processed` | 字符串型（object） | 0.0% | 2026-04-07 | --- ## 数值统计摘要 | 列名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---|---| | `year` | 2024.0 | 2024.0 | 2024.0 | 2024.0 | | `new_displacement` | 513.0 | 513.0 | 513.0 | 513.0 | | `new_displacement_rounded` | 510.0 | 510.0 | 510.0 | 510.0 | | `total_displacement` | 186.0 | 186.0 | 186.0 | 186.0 | | `total_displacement_rounded` | 190.0 | 190.0 | 190.0 | 190.0 | --- ## 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采用蛇形命名法（snake_case）进行标准化。常见的缺失值标记（`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 1. 本数据集数据源自国内流离失所监测中心（IDMC），Electric Sheep Africa未对其进行独立验证。 2. 自动化数据清洗无法修正原始数据集中的错报值、定义不一致或采样偏差问题。 3. 如需了解发布方提供的方法说明与注意事项，请查阅[HDX原始数据集页面](https://data.humdata.org/dataset/idmc-idp-data-zmb)。 --- ## 引用格式 bibtex @dataset{hdx_africa_idmc_idp_data_zmb, title = {Zambia - Internal Displacements (New Displacements) – IDPs}, author = {Internal Displacement Monitoring Centre (IDMC)}, year = {2026}, url = {https://data.humdata.org/dataset/idmc-idp-data-zmb}, 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平台，尼日利亚拉各斯。*