---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- tabular-classification
- tabular-regression
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- democratic-culture
- benin
- botswana
- cape-verde
- ethiopia
- kenya
pretty_name: "Global Freedom; Freedom in the world 2022"
dataset_info:
  splits:
    - name: train
      num_examples: 90
    - name: test
      num_examples: 22
---

# Global Freedom; Freedom in the world 2022

**Publisher:** Freedom House · **Source:** [OpenAfrica](https://open.africa/dataset/global-freedom-freedom-in-the-world-2022) · **License:** `cc-by` · **Updated:** 2023-01-24

---

## Abstract

Individual freedoms—ranging from the right to vote to freedom of expression and equality before the law—can be affected by state or nonstate actors. Scores are based on a scale of 0 (Not Free) to 100 (Free)

Each row in this dataset represents tabular records. Data was last updated on OpenAfrica on 2023-01-24. 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)** | 113 |
| **Columns** | 8 (4 numeric, 4 categorical, 0 datetime) |
| **Train split** | 90 rows |
| **Test split** | 22 rows |
| **Geographic scope** | BENIN, BOTSWANA, CAPE-VERDE, ETHIOPIA, KENYA, NIGERIA, SENEGAL, SOUTH-AFRICA, and 4 others |
| **Publisher** | Freedom House |
| **OpenAfrica last updated** | 2023-01-24 |

---

## Variables

**Outcome / Measurement** — `freedom_scores_2013_2022` (Benin, Botswana, Cabo Verde).

**Identifier / Metadata** — `unnamed_1` (range 2013.0–2022.0), `unnamed_2` (range 0.0–38.0), `unnamed_3` (range 4.0–54.0), `unnamed_4` (range 6.0–92.0), `unnamed_5` (Partly Free, Free, Not Free) and 2 others.

---

## Quick Start

```python
from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-global-freedom-freedom-in-the-world-2022")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `freedom_scores_2013_2022` | object | 0.9% | Benin, Botswana, Cabo Verde |
| `unnamed_1` | float64 | 2.7% | 2013.0 – 2022.0 (mean 2017.5) |
| `unnamed_2` | float64 | 2.7% | 0.0 – 38.0 (mean 23.1818) |
| `unnamed_3` | float64 | 2.7% | 4.0 – 54.0 (mean 33.5818) |
| `unnamed_4` | float64 | 2.7% | 6.0 – 92.0 (mean 56.7636) |
| `unnamed_5` | object | 1.8% | Partly Free, Free, Not Free |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-28 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
| `unnamed_1` | 2013.0 | 2022.0 | 2017.5 | 2017.5 |
| `unnamed_2` | 0.0 | 38.0 | 23.1818 | 25.0 |
| `unnamed_3` | 4.0 | 54.0 | 33.5818 | 34.0 |
| `unnamed_4` | 6.0 | 92.0 | 56.7636 | 60.0 |

---

## 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 Freedom House 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/global-freedom-freedom-in-the-world-2022) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{openafrica_africa_global_freedom_freedom_in_the_world_2022,
  title     = {Global Freedom; Freedom in the world 2022},
  author    = {Freedom House},
  year      = {2023},
  url       = {https://open.africa/dataset/global-freedom-freedom-in-the-world-2022},
  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.*