--- license: cc-by-4.0 language: - en task_categories: - tabular-regression - time-series-forecasting multilinguality: monolingual size_categories: - n<1K tags: - tabular - csv - africa - niger - official-statistics - open-data - ict configs: - config_name: default data_files: - split: train path: data/train-00000-of-00001.parquet pretty_name: "Niger - Aid Worker Security Database | Africa (Niger official open data)" --- # Niger - Aid Worker Security Database | Africa (Niger official open data) 725 rows - 1 Africa country - 2010-2025 - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica) ![rows](https://img.shields.io/badge/rows-725-blue) ![countries](https://img.shields.io/badge/countries-1-green) ![years](https://img.shields.io/badge/years-2010-2025-orange) ![indicators](https://img.shields.io/badge/indicators-29-purple) ![license](https://img.shields.io/badge/license-cc-by-4.0-lightgrey) ## TL;DR This dataset packages one official `CSV` resource from **Niger** as ML-ready Parquet. The source file is the provenance boundary; all usable indicators or tabular columns from the resource stay together in this repo. ## About the source - **Source:** [Niger - Aid Worker Security Database](https://data.humdata.org/dataset/aid-worker-security-database-ner) - **Publisher:** Humanitarian Outcomes - **Resource:** [AWSD_NE_security_incidents.csv](https://data.humdata.org/dataset/1bf753c4-8bd7-40f3-9d79-987a4e8ffbe6/resource/f66e7152-4b05-4ca4-a6d9-6d1c9efca69f/download/awsd_ne_security_incidents.csv) - **Format:** `CSV` - **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) - **Packaging mode:** `indicator_long` ## Geographic coverage 1 Africa country: | Country | Rows | First year | Last year | Name | |---------|-----:|-----------:|----------:|------| | `NER` | 725 | 2010 | 2025 | `Niger` | ## Indicators or Resource Contents - `niger-aid-worker-security-database-incident-id-e7197724` - Niger - Aid Worker Security Database - incident id - `niger-aid-worker-security-database-month-d749a4ff` - Niger - Aid Worker Security Database - month - `niger-aid-worker-security-database-day-eb34192b` - Niger - Aid Worker Security Database - day - `niger-aid-worker-security-database-un-598815c0` - Niger - Aid Worker Security Database - un - `niger-aid-worker-security-database-ingo-e69d1da3` - Niger - Aid Worker Security Database - ingo - `niger-aid-worker-security-database-icrc-5b68380e` - Niger - Aid Worker Security Database - icrc - `niger-aid-worker-security-database-nrcs-and-ifrc-57fd7431` - Niger - Aid Worker Security Database - nrcs and ifrc - `niger-aid-worker-security-database-nngo-226a0c40` - Niger - Aid Worker Security Database - nngo - `niger-aid-worker-security-database-other-718d2e34` - Niger - Aid Worker Security Database - other - `niger-aid-worker-security-database-nationals-killed-00bf3689` - Niger - Aid Worker Security Database - nationals killed - `niger-aid-worker-security-database-nationals-wounded-960bf73e` - Niger - Aid Worker Security Database - nationals wounded - `niger-aid-worker-security-database-nationals-kidnapped-38e77b2b` - Niger - Aid Worker Security Database - nationals kidnapped - `niger-aid-worker-security-database-nationals-detained-c92c2f6b` - Niger - Aid Worker Security Database - nationals detained - `niger-aid-worker-security-database-total-nationals-9e8a578e` - Niger - Aid Worker Security Database - total nationals - `niger-aid-worker-security-database-internationals-killed-cd774102` - Niger - Aid Worker Security Database - internationals killed - `niger-aid-worker-security-database-internationals-wounded-68375bf2` - Niger - Aid Worker Security Database - internationals wounded - `niger-aid-worker-security-database-internationals-kidnapped-2433ee57` - Niger - Aid Worker Security Database - internationals kidnapped - `niger-aid-worker-security-database-internationals-detained-447c2ca5` - Niger - Aid Worker Security Database - internationals detained - `niger-aid-worker-security-database-total-internationals-a38f8191` - Niger - Aid Worker Security Database - total internationals - `niger-aid-worker-security-database-total-killed-19e55b75` - Niger - Aid Worker Security Database - total killed ## Schema | Column | Type | Description | Example | |--------|------|-------------|---------| | `indicator_id` | `string` | Stable indicator identifier. | `niger-aid-worker-security-database-incident-id-e7197724` | | `indicator_name` | `string` | Human-readable indicator name. | `Niger - Aid Worker Security Database - incident id` | | `country_iso3` | `string` | ISO3 country code. | `NER` | | `country_name` | `string` | Country name. | `Niger` | | `year` | `Int64` | Observation year. | `2010` | | `value` | `float64` | Numeric observation value. | `968.0` | | `unit` | `string` | Measurement unit, when available. | `source_units_unspecified` | | `dimension_country_code` | `string` | Source dimension. | `NE` | | `dimension_country` | `string` | Source dimension. | `Niger` | | `dimension_region` | `string` | Source dimension. | `` | | `dimension_district` | `string` | Source dimension. | `` | | `dimension_city` | `string` | Source dimension. | `` | | `dimension_means_of_attack` | `string` | Source dimension. | `Kidnap-killing` | | `dimension_attack_context` | `string` | Source dimension. | `Unknown` | | `dimension_location` | `string` | Source dimension. | `Unknown` | | `dimension_motive` | `string` | Source dimension. | `Political` | | `dimension_actor_type` | `string` | Source dimension. | `Non-state armed group: Regional` | | `dimension_actor_name` | `string` | Source dimension. | `Al-Qaeda (affiliated)` | | `dimension_details` | `string` | Source dimension. | `1 NGO international (French) staff kidnapped by Al-Qaeda in the Islamic ` | | `dimension_verified` | `string` | Source dimension. | `Archived` | | `dimension_source` | `string` | Source dimension. | `Media` | | `source_period_start_year` | `Int64` | First year inferred from source resource metadata. | `` | | `source_period_end_year` | `Int64` | Last year inferred from source resource metadata. | `` | | `source_period_label` | `string` | Human-readable period inferred from source resource metadata. | `` | | `source_provider` | `category` | Publishing organization. | `Humanitarian Outcomes` | | `source_dataset` | `category` | Source package title. | `Niger - Aid Worker Security Database` | | `source_resource` | `category` | Source resource title. | `AWSD_NE_security_incidents.csv` | | `source_package_id` | `category` | CKAN package UUID. | `1bf753c4-8bd7-40f3-9d79-987a4e8ffbe6` | | `source_resource_id` | `category` | CKAN resource UUID. | `f66e7152-4b05-4ca4-a6d9-6d1c9efca69f` | | `source_url` | `category` | Original source resource URL. | `https://data.humdata.org/dataset/1bf753c4-8bd7-40f3-9d79-987a4e8ffbe6/re` | | `license_id` | `category` | Source license identifier. | `cc-by` | | `retrieved_at` | `category` | UTC retrieval timestamp. | `2026-08-14T00:35:21Z` | ## Usage ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-niger-niger-aid-worker-security-database-5b8e057c") df = ds["train"].to_pandas() print(df.head()) ``` ### Filter to one country ```python sample_country = df[df["country_iso3"] == "NER"] ``` ### Work with indicators ```python if "indicator_id" in df.columns: print(df["indicator_id"].value_counts().head()) sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns]) ``` ## Citation ```bibtex @misc{electric_sheep_africa_africa_niger_niger_aid_worker_security_database_5b8e057c_2025, title = {Niger - Aid Worker Security Database | Africa (Niger official open data)}, author = {Humanitarian Outcomes}, year = {2025}, url = {https://data.humdata.org/dataset/aid-worker-security-database-ner}, publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa}, howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-niger-niger-aid-worker-security-database-5b8e057c}} } ``` ## License Released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). Original data (c) Humanitarian Outcomes. When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging. ## About Electric Sheep Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on Hugging Face. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use `load_dataset()` to start working in seconds. Browse the full collection: [huggingface.co/electricsheepafrica](https://huggingface.co/electricsheepafrica) --- Provenance: ingested 2026-08-14 via the Electric Sheep pipeline. Source URL: https://data.humdata.org/dataset/1bf753c4-8bd7-40f3-9d79-987a4e8ffbe6/resource/f66e7152-4b05-4ca4-a6d9-6d1c9efca69f/download/awsd_ne_security_incidents.csv