---
license: cc-by-4.0
language:
- en
task_categories:
- tabular-regression
- time-series-forecasting
multilinguality: multilingual
size_categories:
- n<1K
tags:
- tabular
- africa
- open-data
- official-statistics
- mauritius
- mdpa
- energy
- environment-and-natural-resources
- consumption
- electricity
- generated
- renewable-energy
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-00000-of-00001.parquet
pretty_name: "Main Energy indicators, Republic of Mauritius, 2018-2024 - Percentage of renewables from total final energy consumption | Africa (MDPA)"
---

# Main Energy indicators, Republic of Mauritius, 2018-2024 - Percentage of renewables from total final energy consumption | Africa (MDPA)

**7 rows** - **1 Africa country/area** - **2018-2024** - **1 indicator** - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*

![rows](https://img.shields.io/badge/rows-7-blue)
![countries](https://img.shields.io/badge/countries-1-green)
![period](https://img.shields.io/badge/period-2018--2024-orange)
![indicators](https://img.shields.io/badge/indicators-1-purple)
![license](https://img.shields.io/badge/license-cc--by--4.0-lightgrey)

## TL;DR

This dataset contains **7 rows** from **MDPA**, covering **Main Energy indicators, Republic of Mauritius, 2018-2024 - Percentage of renewables from total final energy consumption**. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

## What This Dataset Measures

Energy datasets help analysts study supply, demand, prices, generation, access, and the infrastructure behind economic activity.

Source-provided context: Dataset shows the main Energy indicators, Republic of Mauritius, 2018 to 2024

## How To Read This Dataset

- **One row means:** one indicator observation for one geography, time period, and optional source dimensions.
- **Primary geography column:** `country_iso3`.
- **Best time column:** `year`.
- **Time coverage basis:** year.
- **Recommended join keys:** `country_iso3`, `year`, `indicator_id`.

## Coverage

| Dimension | Value |
|---|---:|
| Rows | 7 |
| Countries/areas | 1 |
| First period | 2018 |
| Last period | 2024 |
| Indicators | 1 |
| Columns | 15 |
| Source format | CSV |

## Geographic Coverage

Top areas shown below, sorted by row count when available:

| Area | Rows | First year | Last year | Name |
|------|-----:|-----------:|----------:|------|
| `MUS` | 7 | 2018 | 2024 | `Mauritius` |

## Indicators, Variables, Or Resource Contents

- `main-energy-indicators-republic-of-mauritius-2018-2024-percentage-of-ren-c0e01021` - Main Energy indicators, Republic of Mauritius, 2018-2024 - Percentage of renewables from total final energy consumption(source_units_unspecified)

## Schema

| Column | Type | Description | Example |
|--------|------|-------------|---------|
| `indicator_id` | `string` | Stable source or Electric Sheep Africa indicator identifier. | `main-energy-indicators-republic-of-mauritius-2018-2024-percentage-of-...` |
| `indicator_name` | `string` | Human-readable indicator name. | `Main Energy indicators, Republic of Mauritius, 2018-2024 - Percentage...` |
| `country_iso3` | `string` | ISO3 country or area code. | `MUS` |
| `country_name` | `string` | Country or area name. | `Mauritius` |
| `year` | `int64` | Observation year. | `2018` |
| `value` | `double` | Numeric observation value. | `2.5` |
| `unit` | `string` | Measurement unit, when supplied by the source. | `source_units_unspecified` |
| `source_provider` | `string` | Publishing organization. | `MDPA` |
| `source_dataset` | `string` | Source dataset or package title. | `Main Energy indicators, Republic of Mauritius, 2018-2024` |
| `source_resource` | `string` | Source resource title, table name, or file name. | `main_energy_indicators-republic-of-mauritius-2018-2024v.csv` |
| `source_package_id` | `string` | Source package identifier. | `e398d0b3-75e4-424c-89cb-cb2caa281e94` |
| `source_resource_id` | `string` | Source resource identifier. | `0f445a42-d734-4293-a8ff-724efff02c29` |
| `source_url` | `string` | Original source URL or download URL. | `https://data.govmu.org/dataset/e398d0b3-75e4-424c-89cb-cb2caa281e94/r...` |
| `license_id` | `string` | Source license identifier. | `cc-by` |
| `retrieved_at` | `string` | UTC source retrieval timestamp from the Electric Sheep Africa pipeline. | `2026-07-16T18:12:36Z` |

## Usage

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mauritius-main-energy-indicators-republic-of-mauritius-2018-2024-percentag-c0e01021")
df = ds["train"].to_pandas()
print(df.head())
```

### Inspect Columns

```python
print(df.info())
print(df.head())
```

### Filter By Geography

```python
if "country_iso3" in df.columns:
    sample = df[df["country_iso3"] == "MUS"]
```

### Time-Series Pattern

```python
if "value" in df.columns and "year" in df.columns:
    trend = df.sort_values("year")
```

### Pivot For Analysis

```python
if {"indicator_id", "year", "value"}.issubset(df.columns):
    matrix = df.pivot_table(index="year", columns="indicator_id", values="value")
    print(matrix.tail())
```

## Data Quality Notes

- Canonical time field: `year`.
- Missing values are preserved rather than silently imputed.
- Column names are standardized for machine use; source meanings are preserved where known.
- Always confirm source methodology, units, and collection definitions before policy, production, or redistribution-sensitive use.

## Source And Provenance

- **Source:** [MDPA](https://data.govmu.org/dataset/main-energy-indicators-republic-of-mauritius-2018-2024)
- **Publisher:** MDPA
- **Portal:** [https://data.govmu.org](https://data.govmu.org)
- **Resource:** [main_energy_indicators-republic-of-mauritius-2018-2024v.csv](https://data.govmu.org/dataset/e398d0b3-75e4-424c-89cb-cb2caa281e94/resource/0f445a42-d734-4293-a8ff-724efff02c29/download/main_energy_indicators-republic-of-mauritius-2018-2024v.csv)
- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
- **Retrieved/generated:** `2026-07-16T18:12:45Z`
- **Hugging Face repo:** [electricsheepafrica/africa-mauritius-main-energy-indicators-republic-of-mauritius-2018-2024-percentag-c0e01021](https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-main-energy-indicators-republic-of-mauritius-2018-2024-percentag-c0e01021)

## Transformations Applied

- Converted the source table to Parquet for efficient analytics and ML workflows.
- Added or preserved source provenance columns where available.
- Standardized README metadata, dataset loading configuration, schema documentation, and citation format.
- Preserved source-reported values without analytical imputation.

## Suggested Analyses

- Track supply or price trends
- Compare energy sources
- Join with population, industry, or emissions data
- Build time-series views and period-over-period comparisons
- Pivot to geography x period or indicator x period matrices
- Check missingness before modeling
- Use `country_iso3` as the safest geography join key when present

## Citation

```bibtex
@misc{electric_sheep_africa_africa_mauritius_main_energy_indicators_republic_of_mauritius_2018_2024_percenta_2024,
  title        = {Main Energy indicators, Republic of Mauritius, 2018-2024 - Percentage of renewables from total final energy consumption | Africa (MDPA)},
  author       = {MDPA},
  year         = {2024},
  url          = {https://data.govmu.org/dataset/main-energy-indicators-republic-of-mauritius-2018-2024},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mauritius-main-energy-indicators-republic-of-mauritius-2018-2024-percentag-c0e01021}}
}
```

## License

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

Original data is published by MDPA. Electric Sheep Africa
engineering standardizes the data for discovery, loading, and analysis on
Hugging Face. Cite both the original source and this ML-ready dataset when used.

## About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.

---

Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://data.govmu.org/dataset/main-energy-indicators-republic-of-mauritius-2018-2024