electricsheepafrica/africa-idmc-idp-data-gha

--- 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 - gha pretty_name: "Ghana - Internal Displacements (New Displacements) – IDPs" dataset_info: splits: - name: train num_examples: 3 - name: test num_examples: 0 --- # Ghana - Internal Displacements (New Displacements) – IDPs **Publisher:** Internal Displacement Monitoring Centre (IDMC) · **Source:** [HDX](https://data.humdata.org/dataset/idmc-idp-data-gha) · **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: **GHA**. *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)** | 4 | | **Columns** | 9 (5 numeric, 4 categorical, 0 datetime) | | **Train split** | 3 rows | | **Test split** | 0 rows | | **Geographic scope** | GHA | | **Publisher** | Internal Displacement Monitoring Centre (IDMC) | | **HDX last updated** | 2026-03-18 | --- ## Variables **Geographic** — `iso3` (GHA), `country_name` (Ghana), `year` (range 2018.0–2024.0), `new_displacement` (range 679.0–5000.0), `new_displacement_rounded` (range 680.0–5000.0) and 2 others. **Identifier / Metadata** — `esa_source` (HDX), `esa_processed` (2026-04-06). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-idmc-idp-data-gha") 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% | GHA | | `country_name` | object | 0.0% | Ghana | | `year` | int64 | 0.0% | 2018.0 – 2024.0 (mean 2021.0) | | `new_displacement` | float64 | 25.0% | 679.0 – 5000.0 (mean 2571.3333) | | `new_displacement_rounded` | float64 | 25.0% | 680.0 – 5000.0 (mean 2560.0) | | `total_displacement` | float64 | 25.0% | 3158.0 – 5000.0 (mean 3998.3333) | | `total_displacement_rounded` | float64 | 25.0% | 3200.0 – 5000.0 (mean 4000.0) | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-06 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `year` | 2018.0 | 2024.0 | 2021.0 | 2021.0 | | `new_displacement` | 679.0 | 5000.0 | 2571.3333 | 2035.0 | | `new_displacement_rounded` | 680.0 | 5000.0 | 2560.0 | 2000.0 | | `total_displacement` | 3158.0 | 5000.0 | 3998.3333 | 3837.0 | | `total_displacement_rounded` | 3200.0 | 5000.0 | 4000.0 | 3800.0 | --- ## 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. - The following columns have >20% missing values and should be treated with caution in modelling: `new_displacement`, `new_displacement_rounded`, `total_displacement`, `total_displacement_rounded`. - Refer to the [original HDX dataset page](https://data.humdata.org/dataset/idmc-idp-data-gha) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_idmc_idp_data_gha, title = {Ghana - Internal Displacements (New Displacements) – IDPs}, author = {Internal Displacement Monitoring Centre (IDMC)}, year = {2026}, url = {https://data.humdata.org/dataset/idmc-idp-data-gha}, 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: - 公开采集 language: - 英语 license: cc-by-4.0 multilinguality: - 单语言 size_categories: - n<1K source_datasets: - 原创数据集 task_categories: - 表格分类（tabular-classification） task_ids: [] tags: - africa - humanitarian - HDX - electric-sheep-africa - conflict-violence - displacement - internally-displaced-persons-idp - natural-disasters - gha pretty_name: "加纳——国内流离失所情况（新增流离事件）——内部流离失所者（IDPs）" dataset_info: splits: - name: train num_examples: 3 - name: test num_examples: 0 # 加纳——国内流离失所情况（新增流离事件）——内部流离失所者（IDPs） **发布方**: 国内流离失所监测中心（Internal Displacement Monitoring Centre, IDMC） · **数据来源**: [人道主义数据交换（Humanitarian Data Exchange, HDX）](https://data.humdata.org/dataset/idmc-idp-data-gha) · **许可证**: `cc-by-igo` · **更新时间**: 2026-03-18 --- ## 摘要 由国内流离失所监测中心（IDMC）维护的[全球国内流离失所数据库（Global Internal Displacement Database, GIDD）](http://www.internal-displacement.org/database/displacement-data)，提供了全球范围内经过验证的全面年度国内流离失所人口估算数据。该数据库依据[1998年指导原则](https://www.internal-displacement.org/internal-displacement/guiding-principles-on-internal-displacement/)，将内部流离失所者（Internally Displaced Persons, IDPs）定义为：因武装冲突、规避武装冲突影响、普遍性暴力事件、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住地，且未跨越国际边境的个人或群体。 GIDD追踪两项核心指标：一是“流离失所人口”或称年末存量（Stock）数据，即年末处于流离失所状态的总人口数；二是“新增流离事件”，统计的是新增流离事件（人口流动量）而非个体流离人数，以此覆盖同一人多次流离的情况。本数据集是了解全球长期流离失所趋势与经验证的流离数据的重要资源。如需获取详细信息与完整API规范，请参阅官方文档：https://www.internal-displacement.org/database/api-documentation/。 “内部流离失所者——IDPs”指年末处于流离失所状态的人口总数。 “国内流离失所情况（新增流离事件）”指记录的新增流离事件或案例数量，而非流离人口总数，这是因为部分人员可能多次经历流离。 本数据集的每一行均代表国家级汇总数据。数据最近一次在HDX上的更新时间为2026-03-18。地理覆盖范围：**GHA（加纳）**。 *本数据集经[Electric Sheep Africa](https://huggingface.co/electricsheepafrica)整理为适合机器学习的Parquet格式。* --- ## 数据集特征 | | | |---|---| | **领域** | 冲突与安全 | | **观测单元** | 国家级汇总数据 | | **总行数** | 4 | | **列数** | 9（5列数值型，4列分类型，0列日期时间型） | | **训练集划分** | 3行 | | **测试集划分** | 0行 | | **地理覆盖范围** | GHA | | **发布方** | 国内流离失所监测中心（IDMC） | | **HDX最后更新时间** | 2026-03-18 | --- ## 变量 **地理相关变量** — `iso3`（GHA）、`country_name`（加纳）、`year`（取值范围2018.0–2024.0）、`new_displacement`（取值范围679.0–5000.0）、`new_displacement_rounded`（取值范围680.0–5000.0）及另外2列。 **标识符与元数据变量** — `esa_source`（HDX）、`esa_processed`（2026-04-06）。 --- ## 快速入门 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-idmc-idp-data-gha") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() --- ## 数据架构 | 列名 | 数据类型 | 缺失率 | 取值范围/示例值 | |---|---|---|---| | `iso3` | 字符串型 | 0.0% | GHA | | `country_name` | 字符串型 | 0.0% | 加纳 | | `year` | 64位整型 | 0.0% | 2018.0 – 2024.0（均值2021.0） | | `new_displacement` | 64位浮点型 | 25.0% | 679.0 – 5000.0（均值2571.3333） | | `new_displacement_rounded` | 64位浮点型 | 25.0% | 680.0 – 5000.0（均值2560.0） | | `total_displacement` | 64位浮点型 | 25.0% | 3158.0 – 5000.0（均值3998.3333） | | `total_displacement_rounded` | 64位浮点型 | 25.0% | 3200.0 – 5000.0（均值4000.0） | | `esa_source` | 字符串型 | 0.0% | HDX | | `esa_processed` | 字符串型 | 0.0% | 2026-04-06 | --- ## 数值型变量统计摘要 | 列名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---|---| | `year` | 2018.0 | 2024.0 | 2021.0 | 2021.0 | | `new_displacement` | 679.0 | 5000.0 | 2571.3333 | 2035.0 | | `new_displacement_rounded` | 680.0 | 5000.0 | 2560.0 | 2000.0 | | `total_displacement` | 3158.0 | 5000.0 | 3998.3333 | 3837.0 | | `total_displacement_rounded` | 3200.0 | 5000.0 | 4000.0 | 3800.0 | --- ## 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。列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）按照80/20的比例划分为训练集与测试集，并以Snappy压缩格式保存为Parquet文件。 --- ## 局限性说明 - 数据源自国内流离失所监测中心（IDMC），并未经Electric Sheep Africa独立验证。 - 自动化清洗流程无法修正原始数据收集阶段的错报值、定义不一致或抽样偏差问题。 - 以下列的缺失率超过20%，在建模时需谨慎使用：`new_displacement`、`new_displacement_rounded`、`total_displacement`、`total_displacement_rounded`。 - 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/idmc-idp-data-gha)。 --- ## 引用格式 bibtex @dataset{hdx_africa_idmc_idp_data_gha, title = {加纳——国内流离失所情况（新增流离事件）——内部流离失所者（IDPs)}, author = {国内流离失所监测中心（IDMC)}, year = {2026}, url = {https://data.humdata.org/dataset/idmc-idp-data-gha}, note = {由Electric Sheep Africa重新打包以适配机器学习需求（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。*