electricsheepafrica/africa-dza-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
- dza
pretty_name: "Algeria - VIEWS conflict forecasts"
dataset_info:
splits:
- name: train
num_examples: 28
- name: test
num_examples: 7
---

# Algeria - VIEWS conflict forecasts

**Publisher:** Violence & Impacts Early-Warning System · **Source:** [HDX](https://data.humdata.org/dataset/dza-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: **DZA**.

*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** | DZA |
| **Publisher** | Violence & Impacts Early-Warning System |
| **HDX last updated** | 2026-04-01 |

---

## Variables

**Geographic** — `country_id` (range 67.0–67.0), `isoab` (DZA), `year` (range 2026.0–2029.0).

**Temporal** — `month_id` (range 555.0–590.0), `month` (range 1.0–12.0).

**Identifier / Metadata** — `name` (Algeria), `gwcode` (range 615.0–615.0), `esa_source` (HDX), `esa_processed` (2026-04-06).

**Other** — `main_mean_ln` (range 0.0642–0.2581), `main_mean` (range 0.0663–0.2945), `main_dich` (range 0.0–0.0).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-dza-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% | 67.0 – 67.0 (mean 67.0) |
| `month_id` | int64 | 0.0% | 555.0 – 590.0 (mean 572.5) |
| `name` | object | 0.0% | Algeria |
| `gwcode` | int64 | 0.0% | 615.0 – 615.0 (mean 615.0) |
| `isoab` | object | 0.0% | DZA |
| `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% | 0.0642 – 0.2581 (mean 0.1246) |
| `main_mean` | float64 | 0.0% | 0.0663 – 0.2945 (mean 0.134) |
| `main_dich` | float64 | 0.0% | 0.0 – 0.0 (mean 0.0) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-06 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `country_id` | 67.0 | 67.0 | 67.0 | 67.0 |
| `month_id` | 555.0 | 590.0 | 572.5 | 572.5 |
| `gwcode` | 615.0 | 615.0 | 615.0 | 615.0 |
| `year` | 2026.0 | 2029.0 | 2027.1667 | 2027.0 |
| `month` | 1.0 | 12.0 | 6.5 | 6.5 |
| `main_mean_ln` | 0.0642 | 0.2581 | 0.1246 | 0.1079 |
| `main_mean` | 0.0663 | 0.2945 | 0.134 | 0.1139 |
| `main_dich` | 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 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/dza-views-conflict-forecasts) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_dza_views_conflict_forecasts,
title = {Algeria - VIEWS conflict forecasts},
author = {Violence & Impacts Early-Warning System},
year = {2026},
url = {https://data.humdata.org/dataset/dza-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.*

标注创建者:
- 无标注
语言生成方式:
- 采集所得
语言:
- 英语
许可证: cc-by-sa-4.0
多语言类型:
- 单语言
样本规模类别:
- 样本数少于1000
源数据集:
- 原创数据集
任务类别:
- 表格分类
- 表格回归
任务子类别: []
标签:
- 非洲
- 人道主义
- HDX
- Electric Sheep Africa
- 冲突暴力
- 伤亡
- 预测
- HXL
- DZA
展示名称: "阿尔及利亚——VIEWS冲突预测数据集"
数据集信息:
划分:
- 名称: train
样本数: 28
- 名称: test
样本数: 7

# 阿尔及利亚——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**: [人道主义数据交换（HDX）](https://data.humdata.org/dataset/dza-views-conflict-forecasts) · **许可证**: `cc-by-sa` · **最后更新时间**: 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，可提前三个月生成全球范围内暴力冲突的月度预测结果。该系统的研发得到了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。数据最后于2026-04-01在HDX平台更新。地理覆盖范围: **DZA**。

*本数据集由[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

| | |
|---|---|
| **所属领域** | 冲突与安全 |
| **观测单元** | 国家级聚合数据 |
| **总样本行数** | 36 |
| **特征列数** | 12 (8个数值型、4个分类型、0个日期时间型) |
| **训练集划分** | 28条样本 |
| **测试集划分** | 7条样本 |
| **地理覆盖范围** | DZA |
| **发布方** | 暴力与影响早期预警系统 |
| **HDX平台最后更新时间** | 2026-04-01 |

---

## 变量

**地理类变量** — `country_id` (取值范围67.0–67.0), `isoab` (DZA), `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` (阿尔及利亚), `gwcode` (取值范围615.0–615.0), `esa_source` (HDX), `esa_processed` (2026-04-06)。

**其他变量** — `main_mean_ln` (取值范围0.0642–0.2581), `main_mean` (取值范围0.0663–0.2945), `main_dich` (取值范围0.0–0.0)。

---

## 快速入门

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-dza-views-conflict-forecasts")
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 | 缺失率 | 取值范围/样本值 |
|---|---|---|---|
| `country_id` | int64 | 0.0% | 67.0 – 67.0 (均值67.0) |
| `month_id` | int64 | 0.0% | 555.0 – 590.0 (均值572.5) |
| `name` | object | 0.0% | 阿尔及利亚 |
| `gwcode` | int64 | 0.0% | 615.0 – 615.0 (均值615.0) |
| `isoab` | object | 0.0% | DZA |
| `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% | 0.0642 – 0.2581 (均值0.1246) |
| `main_mean` | float64 | 0.0% | 0.0663 – 0.2945 (均值0.134) |
| `main_dich` | float64 | 0.0% | 0.0 – 0.0 (均值0.0) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 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 |
|---|---|---|---|---|
| `country_id` | 67.0 | 67.0 | 67.0 | 67.0 |
| `month_id` | 555.0 | 590.0 | 572.5 | 572.5 |
| `gwcode` | 615.0 | 615.0 | 615.0 | 615.0 |
| `year` | 2026.0 | 2029.0 | 2027.1667 | 2027.0 |
| `month` | 1.0 | 12.0 | 6.5 | 6.5 |
| `main_mean_ln` | 0.0642 | 0.2581 | 0.1246 | 0.1079 |
| `main_mean` | 0.0663 | 0.2945 | 0.134 | 0.1139 |
| `main_dich` | 0.0 | 0.0 | 0.0 | 0.0 |

---

## 数据整理

原始数据通过CKAN应用程序编程接口从HDX平台下载并转换为Parquet格式。列名被统一转换为小写并标准化为蛇形命名法（snake_case）。常见的缺失值标记（`N/A`, `null`, `none`, `-`, `unknown`, `no data`, `#N/A`）被统一替换为`NaN`。本数据集使用固定随机种子（42）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

- 本数据集的数据源自暴力与影响早期预警系统，尚未由Electric Sheep Africa（ESA）进行独立验证。
- 自动化数据清洗无法修正原始数据收集中的错报值、定义不一致或采样偏差问题。
- 请参阅[HDX平台原始数据集页面](https://data.humdata.org/dataset/dza-views-conflict-forecasts)以获取发布方提供的方法说明与免责声明。

---

## 引用格式

bibtex
@dataset{hdx_africa_dza_views_conflict_forecasts,
title = {阿尔及利亚——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/dza-views-conflict-forecasts},
note = {由Electric Sheep Africa针对机器学习需求重新封装 (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。*