README.md

---
license: cc-by-sa-4.0
language:
- en
task_categories:
- tabular-regression
- time-series-forecasting
multilinguality: monolingual
size_categories:
- n<1K
tags:
- tabular
- csv
- africa
- mauritius
- official-statistics
- open-data
- economics
pretty_name: "Employment by sex in the EOE sector | Africa (Mauritius official open data)"
---

# Employment by sex in the EOE sector | Africa (Mauritius official open data)

34 rows - 1 Africa country - 2007-2023 - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

![rows](https://img.shields.io/badge/rows-34-blue)
![countries](https://img.shields.io/badge/countries-1-green)
![years](https://img.shields.io/badge/years-2007-2023-orange)
![indicators](https://img.shields.io/badge/indicators-2-purple)
![license](https://img.shields.io/badge/license-cc-by-sa-4.0-lightgrey)

## TL;DR

This dataset packages one official CSV resource from **Mauritius** as
ML-ready Parquet. The CSV is the provenance boundary; all usable indicators or
tabular columns from the source file stay together in this repo.

## About the source

- **Source:** [Employment by sex in the EOE sector](https://data.govmu.org/dataset/employment-sex-eoe-sector)
- **Publisher:** MDPA
- **Resource:** [Employment-by-sex-in-the-EOE-sector.csv](https://data.govmu.org/dataset/e90a9db9-0893-4f23-8c9e-2ea5088561bc/resource/0de43d2c-cd97-404a-8961-038c575be180/download/employment-by-sex-in-the-eoe-sector.csv)
- **License:** [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)
- **Packaging mode:** `indicator_long`

## Geographic coverage

1 Africa country:

| Country | Rows | First year | Last year | Name |
|---------|-----:|-----------:|----------:|------|
| `MUS` | 34 | 2007 | 2023 | `Mauritius` |

## Indicators or Resource Contents

- `employment-by-sex-in-the-eoe-sector-male-4e82d347` - Employment by sex in the EOE sector - male
- `employment-by-sex-in-the-eoe-sector-female-9c693fce` - Employment by sex in the EOE sector - female

## Schema

| Column | Type | Description | Example |
|--------|------|-------------|---------|
| `indicator_id` | `object` | Stable indicator identifier. | `employment-by-sex-in-the-eoe-sector-male-4e82d347` |
| `indicator_name` | `object` | Human-readable indicator name. | `Employment by sex in the EOE sector - male` |
| `country_iso3` | `object` | ISO3 country code. | `MUS` |
| `country_name` | `object` | Country name. | `Mauritius` |
| `year` | `Int64` | Observation year. | `2007` |
| `value` | `float64` | Numeric observation value. | `25640.0` |
| `unit` | `object` | Measurement unit, when available. | `source_units_unspecified` |
| `source_provider` | `object` | Publishing organization. | `MDPA` |
| `source_dataset` | `object` | Source package title. | `Employment by sex in the EOE sector` |
| `source_resource` | `object` | Source resource title. | `Employment-by-sex-in-the-EOE-sector.csv` |
| `source_package_id` | `object` | CKAN package UUID. | `e90a9db9-0893-4f23-8c9e-2ea5088561bc` |
| `source_resource_id` | `object` | CKAN resource UUID. | `0de43d2c-cd97-404a-8961-038c575be180` |
| `source_url` | `object` | Original CSV URL. | `https://data.govmu.org/dataset/e90a9db9-0893-4f23-8c9e-2ea5088561bc/reso` |
| `license_id` | `object` | Source license identifier. | `CC-BY-SA-4.0` |
| `retrieved_at` | `object` | UTC retrieval timestamp. | `2026-07-16T19:23:24Z` |

## Usage

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-employment-by-sex-in-the-eoe-sector-528317f6")
df = ds["train"].to_pandas()
print(df.head())
```

### Filter to one country

```python
sample_country = df[df["country_iso3"] == "MUS"]
```

### Work with indicators

```python
if "indicator_id" in df.columns:
    print(df["indicator_id"].value_counts().head())
    sample = df.sort_values([c for c in ["indicator_id", "year"] if c in df.columns])
```

## Citation

```bibtex
@misc{electric_sheep_africa_africa_mauritius_employment_by_sex_in_the_eoe_sector_528317f6_2023,
  title        = {Employment by sex in the EOE sector | Africa (Mauritius official open data)},
  author       = {MDPA},
  year         = {2023},
  url          = {https://data.govmu.org/dataset/employment-sex-eoe-sector},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-employment-by-sex-in-the-eoe-sector-528317f6}}
}
```

## License

Released under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/).

Original data (c) MDPA. When using this dataset, please cite both the
original source above and the Electric Sheep Africa repackaging.

## About Electric Sheep

Electric Sheep Africa is part of the Electric Sheep mission: a unified,
ML-ready data layer for Africa on Hugging Face. We pull data from authoritative
open sources, normalize the schemas, package as Parquet, and publish with
consistent dataset cards so researchers and developers can use `load_dataset()`
to start working in seconds.

Browse the full collection: [huggingface.co/electricsheepafrica](https://huggingface.co/electricsheepafrica)

---

Provenance: ingested 2026-07-16 via the Electric Sheep pipeline. Source URL:
https://data.govmu.org/dataset/e90a9db9-0893-4f23-8c9e-2ea5088561bc/resource/0de43d2c-cd97-404a-8961-038c575be180/download/employment-by-sex-in-the-eoe-sector.csv