electricsheepafrica/africa-judicial-constraints-on-the-executive-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-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- independent-judiciary
- rule-of-law
- benin
- botswana
- cape-verde
- ethiopia
- kenya
pretty_name: "Judicial Constraints on the Executive, 2021"
dataset_info:
splits:
- name: train
num_examples: 1180
- name: test
num_examples: 295
---

# Judicial Constraints on the Executive, 2021

**Publisher:** V-Dem Institute · **Source:** [OpenAfrica](https://open.africa/dataset/judicial-constraints-on-the-executive-2021) · **License:** `cc-by` · **Updated:** 2023-01-23

---

## Abstract

Based on the expert assessments and index, it combines information on the extent to which the executive respects the constitution and complies with the rulings of independent courts. It ranges from 0 to 1 (most constrained).

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 0.021–0.937), `unnamed_3` (range 0.006–0.866), `unnamed_4` (range 0.055–0.971), `esa_source` (HDX) and 1 others.

**Other** — `judicial_constraint_1900_2021` (Ethiopia, Sudan, Benin).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-judicial-constraints-on-the-executive-2021")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `judicial_constraint_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% | 0.021 – 0.937 (mean 0.4363) |
| `unnamed_3` | float64 | 0.1% | 0.006 – 0.866 (mean 0.3228) |
| `unnamed_4` | float64 | 0.1% | 0.055 – 0.971 (mean 0.5591) |
| `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` | 0.021 | 0.937 | 0.4363 | 0.365 |
| `unnamed_3` | 0.006 | 0.866 | 0.3228 | 0.232 |
| `unnamed_4` | 0.055 | 0.971 | 0.5591 | 0.531 |

---

## 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/judicial-constraints-on-the-executive-2021) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{openafrica_africa_judicial_constraints_on_the_executive_2021,
title = {Judicial Constraints on the Executive, 2021},
author = {V-Dem Institute},
year = {2023},
url = {https://open.africa/dataset/judicial-constraints-on-the-executive-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.*