Standardize Electric Sheep Africa dataset card
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README.md
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task_categories:
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- tabular-classification
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- tabular-regression
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- time-series-forecasting
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multilinguality: monolingual
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size_categories:
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- 1K<n<10K
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tags:
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- africa
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---
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# Deaths From Terrorism By Target | Africa (Our World in Data)
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*
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## TL;DR
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This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
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## What This Dataset Covers
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Public datasets help analysts inspect structured evidence, build reproducible workflows, and compare patterns across domains.
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Dataset context from the existing Hugging Face card: Deaths From Terrorism By Target | Africa (Our World in Data) 🌍 2,578 observations · 51 Africa countries · 1970–2021 · Repackaged by Electric Sheep Africa TL;DR This dataset contains 2,578 observations of Deaths From Terrorism By Target data across 51 Africa countries, spanning 1970–2021. About the source Source: Our World in Data Publisher: Our World in Data License: cc-by-4.0 Topic: Deaths From Terrorism By Target Geographic… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-owid-deaths-from-terrorism-by-target.
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## Dataset Profile
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| Field | Value |
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|---|---|
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| Hugging Face repo | [`electricsheepafrica/africa-owid-deaths-from-terrorism-by-target`](https://huggingface.co/datasets/electricsheepafrica/africa-owid-deaths-from-terrorism-by-target) |
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| Sector | governance_security |
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| Topic tags | tabular, our-world-in-data, deaths-from-terrorism-by-target, owid, long-run-series, time-series |
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| Modalities | `tabular`, `text` |
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| Formats | `parquet` |
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| Size category | `1K<n<10K` |
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| Countries | Africa-wide or source-defined African coverage |
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| ISO3 coverage | `not declared` |
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| Last modified on HF | `2026-06-05 02:03:54+00:00` |
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| Inventory snapshot | `2026-07-16T16:00:34Z` |
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## How To Read This Dataset
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- Start from the repository files and the dataset viewer when available.
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- Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
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- Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
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- Preserve missing values until you have a defensible imputation rule.
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## Usage
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from datasets import load_dataset
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ds = load_dataset("electricsheepafrica/africa-owid-deaths-from-terrorism-by-target")
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print(ds)
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split_name = next(iter(ds))
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table = ds[split_name]
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print(table.features)
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print(table[:3])
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```
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### Convert To Pandas When Tabular
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```python
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from datasets import Dataset
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first_split = ds[next(iter(ds))]
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if isinstance(first_split, Dataset):
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df = first_split.to_pandas()
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print(df.head())
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```
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## Data Quality Notes
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- This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
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- Exact schema, row counts, and source files should be inspected in the repository data files.
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- Metadata gaps from the inventory: country, upstream_publisher.
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- Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.
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## Source And Provenance
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- **Source context:** Electric Sheep Africa metadata inventory
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- **Publisher/source attribution:** Public dataset metadata
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- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
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- **Hugging Face URL:** [https://huggingface.co/datasets/electricsheepafrica/africa-owid-deaths-from-terrorism-by-target](https://huggingface.co/datasets/electricsheepafrica/africa-owid-deaths-from-terrorism-by-target)
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- **Inventory retrieved at:** `2026-07-16T16:00:34Z`
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## Suggested Analyses
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- Inspect schema and missingness before modeling.
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- Profile variables by geography, time, and subgroup columns where present.
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- Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
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- Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.
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## Citation
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```bibtex
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@misc{electric_sheep_africa_africa_owid_deaths_from_terrorism_by_target_2026,
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title = {Deaths From Terrorism By Target | Africa (Our World in Data) | Africa (Electric Sheep Africa metadata inventory)},
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author = {Public dataset metadata},
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year = {2026},
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url = {https://huggingface.co/datasets/electricsheepafrica/africa-owid-deaths-from-terrorism-by-target},
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publisher = {Hugging Face Datasets, engineered by Electric Sheep Africa},
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howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-owid-deaths-from-terrorism-by-target}}
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}
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```
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## License
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Released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
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Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.
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## About Electric Sheep Africa
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Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.
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---
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Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: `catalog/esa_metadata_inventory/master_metadata.jsonl`.
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