electricsheepafrica/africa-ucdp-data-for-guinea
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--- 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 - other task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - conflict-violence - hxl - gin pretty_name: "Guinea - Data on Conflict Events" dataset_info: splits: - name: train num_examples: 66 - name: test num_examples: 16 --- # Guinea - Data on Conflict Events **Publisher:** HDX · **Source:** [HDX](https://data.humdata.org/dataset/ucdp-data-for-guinea) · **License:** `cc-by-igo` · **Updated:** 2026-04-03 --- ## Abstract This dataset is UCDP's most disaggregated dataset, covering individual events of organized violence (phenomena of lethal violence occurring at a given time and place). These events are sufficiently fine-grained to be geo-coded down to the level of individual villages, with temporal durations disaggregated to single, individual days. Sundberg, Ralph, and Erik Melander, 2013, “Introducing the UCDP Georeferenced Event Dataset”, Journal of Peace Research, vol.50, no.4, 523-532 Högbladh Stina, 2019, “UCDP GED Codebook version 19.1”, Department of Peace and Conflict Research, Uppsala University Each row in this dataset represents first-level administrative unit observations. Temporal coverage is indicated by the `date_start`, `date_end` column(s). Geographic scope: **GIN**. *Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).* --- ## Dataset Characteristics | | | |---|---| | **Domain** | Conflict and security | | **Unit of observation** | First-level administrative unit observations | | **Rows (total)** | 83 | | **Columns** | 48 (27 numeric, 18 categorical, 2 datetime) | | **Train split** | 66 rows | | **Test split** | 16 rows | | **Geographic scope** | GIN | | **Publisher** | HDX | | **HDX last updated** | 2026-04-03 | --- ## Variables **Geographic** — `year` (range 1994.0–2021.0), `active_year`, `type_of_violence` (range 1.0–3.0), `dyad_dset_id` (range 77.0–16493.0), `dyad_new_id` (range 654.0–16493.0) and 9 others. **Temporal** — `date_prec` (range 1.0–4.0), `date_start`, `date_end`. **Outcome / Measurement** — `number_of_sources` (range -1.0–3.0), `deaths_a` (range 0.0–5.0), `deaths_b`, `deaths_civilians`, `deaths_unknown`. **Identifier / Metadata** — `id` (range 11856.0–393367.0), `relid` (GUI-2000-1-57-2, SIE-1998-3-1384-41, GUI-2015-3-438-0), `code_status` (Clear), `conflict_dset_id` (range 77.0–16493.0), `conflict_new_id` (range 307.0–15103.0) and 12 others. **Other** — `where_prec` (range 1.0–6.0), `where_description` (Conakry city, Conakry prefecture, Conakry region, Gueckedou town, Gueckedou prefecture, Nzrkor region, Macenta prefecture ((Macarbou vilalge in), Nzrkor region)), `adm_1`, `adm_2`, `geom_wkt` and 4 others. --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-ucdp-data-for-guinea") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() ``` --- ## Schema | Column | Type | Null % | Range / Sample Values | |---|---|---|---| | `id` | int64 | 0.0% | 11856.0 – 393367.0 (mean 42753.0241) | | `relid` | object | 0.0% | GUI-2000-1-57-2, SIE-1998-3-1384-41, GUI-2015-3-438-0 | | `year` | int64 | 0.0% | 1994.0 – 2021.0 (mean 2005.1084) | | `active_year` | bool | 0.0% | | | `code_status` | object | 0.0% | Clear | | `type_of_violence` | int64 | 0.0% | 1.0 – 3.0 (mean 2.3133) | | `conflict_dset_id` | int64 | 0.0% | 77.0 – 16493.0 (mean 1107.1807) | | `conflict_new_id` | int64 | 0.0% | 307.0 – 15103.0 (mean 1224.6627) | | `conflict_name` | object | 0.0% | Government of Guinea - Civilians, Guinea: Government, RUF - Civilians | | `dyad_dset_id` | int64 | 0.0% | 77.0 – 16493.0 (mean 1207.5181) | | `dyad_new_id` | int64 | 0.0% | 654.0 – 16493.0 (mean 1682.1205) | | `dyad_name` | object | 0.0% | Government of Guinea - Civilians, Government of Guinea - RFDG, RUF - Civilians | | `side_a_dset_id` | int64 | 0.0% | 77.0 – 1713.0 (mean 285.3253) | | `side_a_new_id` | int64 | 0.0% | 77.0 – 1713.0 (mean 285.3253) | | `side_a` | object | 0.0% | Government of Guinea, RUF, Torma | | `side_b_dset_id` | int64 | 0.0% | 463.0 – 9999.0 (mean 6358.9398) | | `side_b_new_id` | int64 | 0.0% | 1.0 – 7813.0 (mean 336.0482) | | `side_b` | object | 0.0% | Civilians, RFDG, Torma Manian | | `number_of_sources` | int64 | 0.0% | -1.0 – 3.0 (mean -0.5904) | | `source_article` | object | 0.0% | Amnesty InternationalOctober 2001, "Guinea and Sierra Leone: No place of refuge", 18, HRW Report, "Dying for Change", April 2007, Vol.18, No.5(A), Amnesty Report, AFR 29/003/2007 | | `source_original` | object | 13.3% | witnesses, military sources, government | | `where_prec` | int64 | 0.0% | 1.0 – 6.0 (mean 1.6988) | | `where_coordinates` | object | 0.0% | Conakry city, Macenta town, Macenta prefecture | | `where_description` | object | 0.0% | Conakry city, Conakry prefecture, Conakry region, Gueckedou town, Gueckedou prefecture, Nzrkor region, Macenta prefecture ((Macarbou vilalge in), Nzrkor region) | | `adm_1` | object | 3.6% | | | `adm_2` | object | 12.0% | | | `latitude` | float64 | 0.0% | 7.3499 – 11.4167 (mean 9.1949) | | `longitude` | float64 | 0.0% | -14.6167 – -8.5333 (mean -11.3618) | | `geom_wkt` | object | 0.0% | | | `priogrid_gid` | int64 | 0.0% | 140022.0 – 145782.0 (mean 142967.1446) | | `country` | object | 0.0% | | | `iso3` | object | 0.0% | | | `country_id` | int64 | 0.0% | 438.0 – 438.0 (mean 438.0) | | `region` | object | 0.0% | | | `event_clarity` | int64 | 0.0% | 1.0 – 2.0 (mean 1.0361) | | `date_prec` | int64 | 0.0% | 1.0 – 4.0 (mean 1.3494) | | `date_start` | datetime64[ns] | 0.0% | | | `date_end` | datetime64[ns] | 0.0% | | | `deaths_a` | int64 | 0.0% | 0.0 – 5.0 (mean 0.1687) | | `deaths_b` | int64 | 0.0% | | | `deaths_civilians` | int64 | 0.0% | | | `deaths_unknown` | int64 | 0.0% | | | `best` | int64 | 0.0% | | | `high` | int64 | 0.0% | | | `low` | int64 | 0.0% | | | `gwnoa` | float64 | 25.3% | | | `esa_source` | object | 0.0% | | | `esa_processed` | object | 0.0% | | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| | `id` | 11856.0 | 393367.0 | 42753.0241 | 12770.0 | | `year` | 1994.0 | 2021.0 | 2005.1084 | 2006.0 | | `type_of_violence` | 1.0 | 3.0 | 2.3133 | 3.0 | | `conflict_dset_id` | 77.0 | 16493.0 | 1107.1807 | 307.0 | | `conflict_new_id` | 307.0 | 15103.0 | 1224.6627 | 458.0 | | `dyad_dset_id` | 77.0 | 16493.0 | 1207.5181 | 532.0 | | `dyad_new_id` | 654.0 | 16493.0 | 1682.1205 | 925.0 | | `side_a_dset_id` | 77.0 | 1713.0 | 285.3253 | 77.0 | | `side_a_new_id` | 77.0 | 1713.0 | 285.3253 | 77.0 | | `side_b_dset_id` | 463.0 | 9999.0 | 6358.9398 | 9999.0 | | `side_b_new_id` | 1.0 | 7813.0 | 336.0482 | 1.0 | | `number_of_sources` | -1.0 | 3.0 | -0.5904 | -1.0 | | `where_prec` | 1.0 | 6.0 | 1.6988 | 1.0 | | `latitude` | 7.3499 | 11.4167 | 9.1949 | 9.3667 | | `longitude` | -14.6167 | -8.5333 | -11.3618 | -10.7333 | --- ## 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`. 4 column(s) with >80% missing values were removed: `source_office`, `source_date`, `source_headline`, `gwnob`. 2 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). 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 HDX 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: `gwnoa`. - Refer to the [original HDX dataset page](https://data.humdata.org/dataset/ucdp-data-for-guinea) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_ucdp_data_for_guinea, title = {Guinea - Data on Conflict Events}, author = {HDX}, year = {2026}, url = {https://data.humdata.org/dataset/ucdp-data-for-guinea}, 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: - 现有公开资源获取 language: - en license: cc-by-4.0 multilinguality: - 单语言 size_categories: - n<1K source_datasets: - 原始数据集 task_categories: - 表格分类 - 其他 task_ids: [] tags: - 非洲 - 人道主义 - HDX - Electric Sheep Africa - 冲突暴力 - HXL - GIN pretty_name: "几内亚——冲突事件数据集" dataset_info: splits: - name: train num_examples: 66 - name: test num_examples: 16 --- # 几内亚——冲突事件数据集 **发布方**：HDX · **来源**：[HDX](https://data.humdata.org/dataset/ucdp-data-for-guinea) · **许可证**：`cc-by-igo` · **更新时间**：2026-04-03 --- ## 摘要 本数据集为乌普萨拉冲突数据项目（UCDP）粒度最精细的数据集，涵盖有组织暴力的单个事件（即特定时间与地点发生的致命暴力事件）。这些事件的地理编码精度可细化至单个村庄级别，时间粒度可精确至单日。 Sundberg, Ralph 与 Erik Melander, 2013, 《UCDP地理参考事件数据集介绍》, 《和平研究期刊》, 第50卷第4期, 第523-532页 Högbladh Stina, 2019, 《UCDP GED代码手册19.1版》, 乌普萨拉大学和平与冲突研究系 本数据集的每一行均代表一级行政单元的观测数据。时间范围由`date_start`与`date_end`列标注。地理覆盖范围：**几内亚（GIN）**。 *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。* --- ## 数据集特征 | | | |---|---| | **领域** | 冲突与安全 | | **观测单元** | 一级行政单元 | | **总条数** | 83 | | **列数** | 48（27个数值列、18个分类列、2个日期时间列） | | **训练集条数** | 66 | | **测试集条数** | 16 | | **地理覆盖范围** | GIN（几内亚） | | **发布方** | HDX | | **HDX最后更新时间** | 2026-04-03 | --- ## 变量说明 **地理类变量** — `year`（取值范围1994.0–2021.0）、`active_year`、`type_of_violence`（取值范围1.0–3.0）、`dyad_dset_id`（取值范围77.0–16493.0）、`dyad_new_id`（取值范围654.0–16493.0）及另外9个变量。 **时间类变量** — `date_prec`（取值范围1.0–4.0）、`date_start`、`date_end`。 **结果/测量类变量** — `number_of_sources`（取值范围-1.0–3.0）、`deaths_a`（取值范围0.0–5.0）、`deaths_b`、`deaths_civilians`（平民死亡人数）、`deaths_unknown`（未知身份死亡人数）。 **标识符/元数据类变量** — `id`（取值范围11856.0–393367.0）、`relid`（示例值：GUI-2000-1-57-2、SIE-1998-3-1384-41、GUI-2015-3-438-0）、`code_status`（取值为Clear）、`conflict_dset_id`（取值范围77.0–16493.0）、`conflict_new_id`（取值范围307.0–15103.0）及另外12个变量。 **其他类变量** — `where_prec`（取值范围1.0–6.0）、`where_description`（示例值：科纳克里市、科纳克里省、科纳克里大区、盖凯杜镇、盖凯杜省、恩泽雷科雷大区、马森塔省（含Macarbou村））、`adm_1`、`adm_2`、`geom_wkt`及另外4个变量。 --- ## 快速上手 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-ucdp-data-for-guinea") 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 | |---|---|---|---| | `id` | int64 | 0.0% | 11856.0 – 393367.0（均值42753.0241） | | `relid` | object | 0.0% | GUI-2000-1-57-2, SIE-1998-3-1384-41, GUI-2015-3-438-0 | | `year` | int64 | 0.0% | 1994.0 – 2021.0（均值2005.1084） | | `active_year` | bool | 0.0% | | | `code_status` | object | 0.0% | Clear | | `type_of_violence` | int64 | 0.0% | 1.0 – 3.0（均值2.3133） | | `conflict_dset_id` | int64 | 0.0% | 77.0 – 16493.0（均值1107.1807） | | `conflict_new_id` | int64 | 0.0% | 307.0 – 15103.0（均值1224.6627） | | `conflict_name` | object | 0.0% | 几内亚政府-平民、几内亚：政府、联阵-平民 | | `dyad_dset_id` | int64 | 0.0% | 77.0 – 16493.0（均值1207.5181） | | `dyad_new_id` | int64 | 0.0% | 654.0 – 16493.0（均值1682.1205） | | `dyad_name` | object | 0.0% | 几内亚政府-平民、几内亚政府-RFDG、联阵-平民 | | `side_a_dset_id` | int64 | 0.0% | 77.0 – 1713.0（均值285.3253） | | `side_a_new_id` | int64 | 0.0% | 77.0 – 1713.0（均值285.3253） | | `side_a` | object | 0.0% | 几内亚政府、联阵、托尔马 | | `side_b_dset_id` | int64 | 0.0% | 463.0 – 9999.0（均值6358.9398） | | `side_b_new_id` | int64 | 0.0% | 1.0 – 7813.0（均值336.0482） | | `side_b` | object | 0.0% | 平民、RFDG、托尔马·马利安 | | `number_of_sources` | int64 | 0.0% | -1.0 – 3.0（均值-0.5904） | | `source_article` | object | 0.0% | 大赦国际2001年10月报告《几内亚与塞拉利昂：无处可逃》、HRW报告《为变革而死》2007年4月、第18卷第5(A)期、大赦国际报告AFR 29/003/2007 | | `source_original` | object | 13.3% | 目击者、军方消息来源、政府 | | `where_prec` | int64 | 0.0% | 1.0 – 6.0（均值1.6988） | | `where_coordinates` | object | 0.0% | 科纳克里市、马森塔镇、马森塔省 | | `where_description` | object | 0.0% | 科纳克里市、科纳克里省、科纳克里大区、盖凯杜镇、盖凯杜省、恩泽雷科雷大区、马森塔省（含Macarbou村） | | `adm_1` | object | 3.6% | | | `adm_2` | object | 12.0% | | | `latitude` | float64 | 0.0% | 7.3499 – 11.4167（均值9.1949） | | `longitude` | float64 | 0.0% | -14.6167 – -8.5333（均值-11.3618） | | `geom_wkt` | object | 0.0% | | | `priogrid_gid` | int64 | 0.0% | 140022.0 – 145782.0（均值142967.1446） | | `country` | object | 0.0% | | | `iso3` | object | 0.0% | | | `country_id` | int64 | 0.0% | 438.0 – 438.0（均值438.0） | | `region` | object | 0.0% | | | `event_clarity` | int64 | 0.0% | 1.0 – 2.0（均值1.0361） | | `date_prec` | int64 | 0.0% | 1.0 – 4.0（均值1.3494） | | `date_start` | datetime64[ns] | 0.0% | | | `date_end` | datetime64[ns] | 0.0% | | | `deaths_a` | int64 | 0.0% | 0.0 – 5.0（均值0.1687） | | `deaths_b` | int64 | 0.0% | | | `deaths_civilians` | int64 | 0.0% | | | `deaths_unknown` | int64 | 0.0% | | | `best` | int64 | 0.0% | | | `high` | int64 | 0.0% | | | `low` | int64 | 0.0% | | | `gwnoa` | float64 | 25.3% | | | `esa_source` | object | 0.0% | | | `esa_processed` | object | 0.0% | | --- ## 数值统计摘要 | 列名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---|---| | `id` | 11856.0 | 393367.0 | 42753.0241 | 12770.0 | | `year` | 1994.0 | 2021.0 | 2005.1084 | 2006.0 | | `type_of_violence` | 1.0 | 3.0 | 2.3133 | 3.0 | | `conflict_dset_id` | 77.0 | 16493.0 | 1107.1807 | 307.0 | | `conflict_new_id` | 307.0 | 15103.0 | 1224.6627 | 458.0 | | `dyad_dset_id` | 77.0 | 16493.0 | 1207.5181 | 532.0 | | `dyad_new_id` | 654.0 | 16493.0 | 1682.1205 | 925.0 | | `side_a_dset_id` | 77.0 | 1713.0 | 285.3253 | 77.0 | | `side_a_new_id` | 77.0 | 1713.0 | 285.3253 | 77.0 | | `side_b_dset_id` | 463.0 | 9999.0 | 6358.9398 | 9999.0 | | `side_b_new_id` | 1.0 | 7813.0 | 336.0482 | 1.0 | | `number_of_sources` | -1.0 | 3.0 | -0.5904 | -1.0 | | `where_prec` | 1.0 | 6.0 | 1.6988 | 1.0 | | `latitude` | 7.3499 | 11.4167 | 9.1949 | 9.3667 | | `longitude` | -14.6167 | -8.5333 | -11.3618 | -10.7333 | --- ## 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并采用蛇形命名法（snake_case）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`。移除了4个缺失值占比超过80%的列：`source_office`、`source_date`、`source_headline`、`gwnob`。根据解析成功率（阈值>85%），将2列从字符串类型转换为数值或日期时间类型。本数据集以80/20的比例划分为训练集与测试集，采用固定随机种子（42）进行划分，并以Snappy压缩的Parquet格式保存。 --- ## 局限性说明 - 本数据集源自HDX，尚未由Electric Sheep Africa（ESA）进行独立验证。 - 自动化清洗流程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。 - 以下列的缺失值占比超过20%，在建模时需谨慎使用：`gwnoa`。 - 如需了解发布方的方法论说明与注意事项，请参阅[HDX原始数据集页面](https://data.humdata.org/dataset/ucdp-data-for-guinea)。 --- ## 引用格式 bibtex @dataset{hdx_africa_ucdp_data_for_guinea, title = {Guinea - Data on Conflict Events}, author = {HDX}, year = {2026}, url = {https://data.humdata.org/dataset/ucdp-data-for-guinea}, 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。尼日利亚拉各斯。*
