electricsheepafrica/africa-equal-acces-to-power-2021

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- tabular-classification
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- political-pluralism
- representation-of-marginalized-social-groups
- benin
- botswana
- cape-verde
- ethiopia
- kenya
pretty_name: "Equal Access to Power, 2021"
dataset_info:
splits:
- name: train
num_examples: 1180
- name: test
num_examples: 295
---

# Equal Access to Power, 2021

**Publisher:** V-Dem Institute · **Source:** [OpenAfrica](https://open.africa/dataset/equal-acces-to-power-2021) · **License:** `cc-by` · **Updated:** 2023-01-23

---

## Abstract

Based on expert assessments, it combines information on the extent to which all social groups can influence and participate in policy-making. It ranges from 0 to 1 (most equal).

Each row in this dataset represents tabular records. Data was last updated on OpenAfrica on 2023-01-23. Geographic scope: **BENIN, BOTSWANA, CAPE-VERDE, ETHIOPIA, KENYA, NIGERIA, SENEGAL, SOUTH-AFRICA, and 4 others**.

*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Humanitarian and development data |
| **Unit of observation** | Tabular records |
| **Rows (total)** | 1,476 |
| **Columns** | 7 (4 numeric, 3 categorical, 0 datetime) |
| **Train split** | 1,180 rows |
| **Test split** | 295 rows |
| **Geographic scope** | BENIN, BOTSWANA, CAPE-VERDE, ETHIOPIA, KENYA, NIGERIA, SENEGAL, SOUTH-AFRICA, and 4 others |
| **Publisher** | V-Dem Institute |
| **OpenAfrica last updated** | 2023-01-23 |

---

## Variables

**Identifier / Metadata** — `unnamed_1` (range 1789.0–2021.0), `unnamed_2` (range 0.017–0.925), `unnamed_3` (range 0.003–0.806), `unnamed_4` (range 0.062–0.973), `esa_source` (HDX) and 1 others.

**Other** — `equal_access_to_power_1900_2021` (Ethiopia, Sudan, Benin).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-equal-acces-to-power-2021")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

print(train.shape)
train.head()
```

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `equal_access_to_power_1900_2021` | object | 0.1% | Ethiopia, Sudan, Benin |
| `unnamed_1` | float64 | 0.1% | 1789.0 – 2021.0 (mean 1948.6377) |
| `unnamed_2` | float64 | 0.1% | 0.017 – 0.925 (mean 0.3288) |
| `unnamed_3` | float64 | 0.1% | 0.003 – 0.806 (mean 0.2116) |
| `unnamed_4` | float64 | 0.1% | 0.062 – 0.973 (mean 0.4706) |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-28 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `unnamed_1` | 1789.0 | 2021.0 | 1948.6377 | 1954.5 |
| `unnamed_2` | 0.017 | 0.925 | 0.3288 | 0.175 |
| `unnamed_3` | 0.003 | 0.806 | 0.2116 | 0.076 |
| `unnamed_4` | 0.062 | 0.973 | 0.4706 | 0.365 |

---

## Curation

Raw data was downloaded from OpenAfrica 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) 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 V-Dem Institute and has not been independently validated by ESA.
- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
- This dataset spans 12 countries; geographic and methodological inconsistencies across national boundaries may affect cross-country comparability.
- Refer to the [original HDX dataset page](https://open.africa/dataset/equal-acces-to-power-2021) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{openafrica_africa_equal_acces_to_power_2021,
title = {Equal Access to Power, 2021},
author = {V-Dem Institute},
year = {2023},
url = {https://open.africa/dataset/equal-acces-to-power-2021},
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.*