electricsheepafrica/africa-eth-views-conflict-forecasts

--- annotations_creators: - no-annotation language_creators: - found language: - en license: cc-by-sa-4.0 multilinguality: - monolingual size_categories: - n<1K source_datasets: - original task_categories: - tabular-classification - tabular-regression task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - conflict-violence - fatalities - forecasting - hxl - eth pretty_name: "Ethiopia - VIEWS conflict forecasts" dataset_info: splits: - name: train num_examples: 28 - name: test num_examples: 7 --- # Ethiopia - VIEWS conflict forecasts **Publisher:** Violence & Impacts Early-Warning System · **Source:** [HDX](https://data.humdata.org/dataset/eth-views-conflict-forecasts) · **License:** `cc-by-sa` · **Updated:** 2026-04-01 --- ## Abstract The Violence & Impacts Early-Warning System (VIEWS) is an award-winning conflict prediction system that generates monthly forecasts for violent conflicts across the world up to three years in advance. It is supported by the iterative research and development activities undertaken by the VIEWS consortium. Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-04-01. Geographic scope: **ETH**. *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)** | 36 | | **Columns** | 12 (8 numeric, 4 categorical, 0 datetime) | | **Train split** | 28 rows | | **Test split** | 7 rows | | **Geographic scope** | ETH | | **Publisher** | Violence & Impacts Early-Warning System | | **HDX last updated** | 2026-04-01 | --- ## Variables **Geographic** — `country_id` (range 57.0–57.0), `isoab` (ETH), `year` (range 2026.0–2029.0). **Temporal** — `month_id` (range 555.0–590.0), `month` (range 1.0–12.0). **Identifier / Metadata** — `name` (Ethiopia), `gwcode` (range 530.0–530.0), `esa_source` (HDX), `esa_processed` (2026-04-06). **Other** — `main_mean_ln` (range 4.2885–5.3638), `main_mean` (range 71.8546–212.5314), `main_dich` (range 0.9999–1.0). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-eth-views-conflict-forecasts") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() ``` --- ## Schema | Column | Type | Null % | Range / Sample Values | |---|---|---|---| | `country_id` | int64 | 0.0% | 57.0 – 57.0 (mean 57.0) | | `month_id` | int64 | 0.0% | 555.0 – 590.0 (mean 572.5) | | `name` | object | 0.0% | Ethiopia | | `gwcode` | int64 | 0.0% | 530.0 – 530.0 (mean 530.0) | | `isoab` | object | 0.0% | ETH | | `year` | int64 | 0.0% | 2026.0 – 2029.0 (mean 2027.1667) | | `month` | int64 | 0.0% | 1.0 – 12.0 (mean 6.5) | | `main_mean_ln` | float64 | 0.0% | 4.2885 – 5.3638 (mean 4.7643) | | `main_mean` | float64 | 0.0% | 71.8546 – 212.5314 (mean 122.8956) | | `main_dich` | float64 | 0.0% | 0.9999 – 1.0 (mean 1.0) | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-06 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `country_id` | 57.0 | 57.0 | 57.0 | 57.0 | | `month_id` | 555.0 | 590.0 | 572.5 | 572.5 | | `gwcode` | 530.0 | 530.0 | 530.0 | 530.0 | | `year` | 2026.0 | 2029.0 | 2027.1667 | 2027.0 | | `month` | 1.0 | 12.0 | 6.5 | 6.5 | | `main_mean_ln` | 4.2885 | 5.3638 | 4.7643 | 4.6075 | | `main_mean` | 71.8546 | 212.5314 | 122.8956 | 99.2433 | | `main_dich` | 0.9999 | 1.0 | 1.0 | 1.0 | --- ## 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 Violence & Impacts Early-Warning System 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/eth-views-conflict-forecasts) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_eth_views_conflict_forecasts, title = {Ethiopia - VIEWS conflict forecasts}, author = {Violence & Impacts Early-Warning System}, year = {2026}, url = {https://data.humdata.org/dataset/eth-views-conflict-forecasts}, 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: 爬取获取 language: 英语 license: CC BY-SA 4.0 multilinguality: 单语言 size_categories: 数据规模小于1000条 source_datasets: 原始数据集 task_categories: 表格分类、表格回归 task_ids: 无任务子类别 tags: 非洲、人道主义、HDX（Humanitarian Data Exchange）、Electric Sheep Africa、冲突暴力、伤亡、预测、HXL、ETH pretty_name: "埃塞俄比亚——VIEWS冲突预测数据集" # 埃塞俄比亚——VIEWS冲突预测数据集 **发布方：暴力与影响早期预警系统（Violence & Impacts Early-Warning System，VIEWS）** · **来源：[HDX（Humanitarian Data Exchange）](https://data.humdata.org/dataset/eth-views-conflict-forecasts) · **许可协议：`cc-by-sa` · **更新时间：2026-04-01 --- ## 摘要 暴力与影响早期预警系统（Violence & Impacts Early-Warning System，VIEWS）是一款屡获殊荣的冲突预测系统，可提前长达三年生成全球范围内暴力冲突的月度预测报告，其研发得到了VIEWS联盟开展的迭代研究与开发活动的支持。 本数据集的每一行均代表国家级聚合数据。数据最近一次在HDX平台更新的时间为2026-04-01。地理覆盖范围：**ETH（埃塞俄比亚）**。 *本数据集由[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 | | | |---|---| | **领域** | 冲突与安全 | | **观测单元** | 国家级聚合数据 | | **总数据行数** | 36 | | **列数** | 12（8个数值型、4个分类型、0个日期时间型） | | **训练集划分** | 28行 | | **测试集划分** | 7行 | | **地理覆盖范围** | ETH | | **发布方** | 暴力与影响早期预警系统 | | **HDX最后更新时间** | 2026-04-01 --- ## 变量 **地理类变量** — `country_id`（取值范围57.0–57.0）、`isoab`（ETH）、`year`（取值范围2026.0–2029.0）。 **时间类变量** — `month_id`（取值范围555.0–590.0）、`month`（取值范围1.0–12.0）。 **标识符/元数据变量** — `name`（埃塞俄比亚）、`gwcode`（取值范围530.0–530.0）、`esa_source`（HDX）、`esa_processed`（2026-04-06）。 **其他变量** — `main_mean_ln`（取值范围4.2885–5.3638）、`main_mean`（取值范围71.8546–212.5314）、`main_dich`（取值范围0.9999–1.0）。 --- ## 快速上手 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-eth-views-conflict-forecasts") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() --- ## 数据结构 | 列名 | 数据类型 | 空值占比 | 取值范围/示例值 | |---|---|---|---| | `country_id` | int64 | 0.0% | 57.0 – 57.0（均值57.0） | | `month_id` | int64 | 0.0% | 555.0 – 590.0（均值572.5） | | `name` | object | 0.0% | 埃塞俄比亚 | | `gwcode` | int64 | 0.0% | 530.0 – 530.0（均值530.0） | | `isoab` | object | 0.0% | ETH | | `year` | int64 | 0.0% | 2026.0 – 2029.0（均值2027.1667） | | `month` | int64 | 0.0% | 1.0 – 12.0（均值6.5） | | `main_mean_ln` | float64 | 0.0% | 4.2885 – 5.3638（均值4.7643） | | `main_mean` | float64 | 0.0% | 71.8546 – 212.5314（均值122.8956） | | `main_dich` | float64 | 0.0% | 0.9999 – 1.0（均值1.0） | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-06 | --- ## 数值统计摘要 | 列名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---|---| | `country_id` | 57.0 | 57.0 | 57.0 | 57.0 | | `month_id` | 555.0 | 590.0 | 572.5 | 572.5 | | `gwcode` | 530.0 | 530.0 | 530.0 | 530.0 | | `year` | 2026.0 | 2029.0 | 2027.1667 | 2027.0 | | `month` | 1.0 | 12.0 | 6.5 | 6.5 | | `main_mean_ln` | 4.2885 | 5.3638 | 4.7643 | 4.6075 | | `main_mean` | 71.8546 | 212.5314 | 122.8956 | 99.2433 | | `main_dich` | 0.9999 | 1.0 | 1.0 | 1.0 | --- ## 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压缩格式保存为Parquet文件。 --- ## 数据集局限性 - 数据源自暴力与影响早期预警系统，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值、定义不一致或抽样偏差问题。 - 请参阅[原始HDX数据集页面](https://data.humdata.org/dataset/eth-views-conflict-forecasts)查看发布方提供的方法论说明与注意事项。 --- ## 引用格式 bibtex @dataset{hdx_africa_eth_views_conflict_forecasts, title = {埃塞俄比亚——VIEWS冲突预测数据集}, author = {暴力与影响早期预警系统}, year = {2026}, url = {https://data.humdata.org/dataset/eth-views-conflict-forecasts}, note = {由Electric Sheep Africa重新打包以适配机器学习场景（https://huggingface.co/electricsheepafrica)} } --- *[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — 非洲的机器学习数据集基础设施。尼日利亚拉各斯。*