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Standardize Electric Sheep Africa dataset card
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---
license: cc-by-4.0
language:
- en
task_categories:
- tabular-classification
- tabular-regression
multilinguality: monolingual
size_categories:
- 10K<n<100K
tags:
- "africa"
- "electric-sheep-africa"
- "open-data"
- "metadata-backed"
- "climate-environment"
- "csv"
- "tabular"
- "text"
- "climate"
- "environment"
- "synthetic-data"
- "sub-saharan-africa"
- "climate-vulnerability"
- "climate-adaptation"
- "climate-risk"
- "synthetic"
pretty_name: "Africa Synth Climate Climate Vulnerability Exposure Niger | Africa (Electric Sheep Africa metadata inventory)"
---
# Africa Synth Climate Climate Vulnerability Exposure Niger | Africa (Electric Sheep Africa metadata inventory)
**Size category:** `10K<n<100K` - **Formats:** `csv` - **Sector:** climate_environment - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*
![size](https://img.shields.io/badge/size-10K%3Cn%3C100K-blue)
![sector](https://img.shields.io/badge/sector-climate_environment-green)
![downloads](https://img.shields.io/badge/HF_downloads-40-orange)
![license](https://img.shields.io/badge/license-cc--by--4.0-lightgrey)
## TL;DR
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.
## What This Dataset Covers
Public datasets help analysts inspect structured evidence, build reproducible workflows, and compare patterns across domains.
Dataset context from the existing Hugging Face card: ⚠️ Synthetic dataset — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference. Climate Vulnerability and Exposure - Africa A comprehensive synthetic dataset assessing climate vulnerability, exposure indices, and adaptive capacity across Sub-Saharan African countries. Dataset Description This dataset provides detailed records of climate vulnerability assessments across 15 Sub-Saharan African countries.… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-climate-climate-vulnerability-exposure-niger.
## Dataset Profile
| Field | Value |
|---|---|
| Hugging Face repo | [`electricsheepafrica/africa-synth-climate-climate-vulnerability-exposure-niger`](https://huggingface.co/datasets/electricsheepafrica/africa-synth-climate-climate-vulnerability-exposure-niger) |
| Sector | climate_environment |
| Topic tags | climate, environment, synthetic-data, sub-saharan-africa, climate-vulnerability, climate-adaptation, climate-risk, synthetic |
| Modalities | `tabular`, `text` |
| Formats | `csv` |
| Size category | `10K<n<100K` |
| Countries | Niger |
| ISO3 coverage | `NER` |
| Last modified on HF | `2026-04-14 22:52:45+00:00` |
| Inventory snapshot | `2026-07-16T16:00:34Z` |
## How To Read This Dataset
- Start from the repository files and the dataset viewer when available.
- Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
- Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
- Preserve missing values until you have a defensible imputation rule.
## Usage
```python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-synth-climate-climate-vulnerability-exposure-niger")
print(ds)
split_name = next(iter(ds))
table = ds[split_name]
print(table.features)
print(table[:3])
```
### Convert To Pandas When Tabular
```python
from datasets import Dataset
first_split = ds[next(iter(ds))]
if isinstance(first_split, Dataset):
df = first_split.to_pandas()
print(df.head())
```
## Data Quality Notes
- This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
- Exact schema, row counts, and source files should be inspected in the repository data files.
- Metadata gaps from the inventory: upstream_publisher.
- Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.
## Source And Provenance
- **Source context:** Electric Sheep Africa metadata inventory
- **Publisher/source attribution:** Public dataset metadata
- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
- **Hugging Face URL:** [https://huggingface.co/datasets/electricsheepafrica/africa-synth-climate-climate-vulnerability-exposure-niger](https://huggingface.co/datasets/electricsheepafrica/africa-synth-climate-climate-vulnerability-exposure-niger)
- **Inventory retrieved at:** `2026-07-16T16:00:34Z`
## Suggested Analyses
- Inspect schema and missingness before modeling.
- Profile variables by geography, time, and subgroup columns where present.
- Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
- Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.
## Citation
```bibtex
@misc{electric_sheep_africa_africa_synth_climate_climate_vulnerability_exposure_niger_2026,
title = {Africa Synth Climate Climate Vulnerability Exposure Niger | Africa (Electric Sheep Africa metadata inventory)},
author = {Public dataset metadata},
year = {2026},
url = {https://huggingface.co/datasets/electricsheepafrica/africa-synth-climate-climate-vulnerability-exposure-niger},
publisher = {Hugging Face Datasets, engineered by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-synth-climate-climate-vulnerability-exposure-niger}}
}
```
## License
Released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
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.
## About Electric Sheep Africa
Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.
---
Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: `catalog/esa_metadata_inventory/master_metadata.jsonl`.