---
license: odbl
language:
- en
task_categories:
- tabular-regression
- time-series-forecasting
multilinguality: monolingual
size_categories:
- n<1K
tags:
- tabular
- xlsx
- africa
- morocco
- official-statistics
- open-data
pretty_name: "Principaux Indicateurs des Rentes des Accidents de la Circulation | Africa (Morocco official open data)"
---

# Principaux Indicateurs des Rentes des Accidents de la Circulation | Africa (Morocco official open data)

10 rows - 1 Africa country - 2020-2024 - Repackaged by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

![rows](https://img.shields.io/badge/rows-10-blue)
![countries](https://img.shields.io/badge/countries-1-green)
![years](https://img.shields.io/badge/years-2020-2024-orange)
![indicators](https://img.shields.io/badge/indicators-0-purple)
![license](https://img.shields.io/badge/license-odbl-lightgrey)

## TL;DR

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

## About the source

- **Source:** [Principaux Indicateurs des Rentes des Accidents de la Circulation](https://data.gov.ma/data/dataset/principaux-indicateurs-des-rentes-des-accidents-de-la-circulation)
- **Publisher:** Caisse Nationale de Retraites et d’Assurances
- **Resource:** [Principaux Indicateurs des Rentes des Accidents de la Circulation.xlsx](https://data.gov.ma/data/fr/dataset/a4069fd1-ee3d-41d3-a928-8a55299c0e37/resource/6a58473c-aeb3-4207-a73d-7ca0b1631054/download/principaux-indicateurs-des-rentes-des-accidents-de-la-circulation.xlsx)
- **Format:** `XLSX`
- **License:** [Open Data Commons Open Database License](https://opendatacommons.org/licenses/odbl/)
- **Packaging mode:** `indicator_long`

## Geographic coverage

1 Africa country:

| Country | Rows | First year | Last year | Name |
|---------|-----:|-----------:|----------:|------|
| `MAR` | 10 | 2020 | 2024 | `Morocco` |

## Indicators or Resource Contents

- `<NA>` - <NA>

## Schema

| Column | Type | Description | Example |
|--------|------|-------------|---------|
| `indicator_id` | `string` | Stable indicator identifier. | `` |
| `indicator_name` | `string` | Human-readable indicator name. | `` |
| `country_iso3` | `string` | ISO3 country code. | `` |
| `source_sheet` | `string` | Workbook sheet name, when the source is a spreadsheet. | `CNRA - RENTES AC` |
| `country_name` | `string` | Country name. | `` |
| `year` | `Int64` | Observation year. | `2020` |
| `value` | `float64` | Numeric observation value. | `97.54` |
| `unit` | `string` | Measurement unit, when available. | `source_units_unspecified` |
| `dimension_rentes_ac` | `string` | Source dimension. | `Indemnités Reçues (en MDH)` |
| `source_provider` | `string` | Publishing organization. | `Caisse Nationale de Retraites et d’Assurances` |
| `source_dataset` | `string` | Source package title. | `Principaux Indicateurs des Rentes des Accidents de la Circulation` |
| `source_resource` | `string` | Source resource title. | `Principaux Indicateurs des Rentes des Accidents de la Circulation.xlsx` |
| `source_package_id` | `string` | CKAN package UUID. | `a4069fd1-ee3d-41d3-a928-8a55299c0e37` |
| `source_resource_id` | `string` | CKAN resource UUID. | `6a58473c-aeb3-4207-a73d-7ca0b1631054` |
| `source_url` | `string` | Original source resource URL. | `https://data.gov.ma/data/fr/dataset/a4069fd1-ee3d-41d3-a928-8a55299c0e37` |
| `license_id` | `string` | Source license identifier. | `odc-odbl` |
| `retrieved_at` | `string` | UTC retrieval timestamp. | `2026-07-16T21:31:48Z` |

## Usage

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-morocco-principaux-indicateurs-des-rentes-des-accidents-de-la-circ-8c16703a")
df = ds["train"].to_pandas()
print(df.head())
```

### Filter to one country

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

### 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_morocco_principaux_indicateurs_des_rentes_des_accidents_de_la_circ_8c1670_2024,
  title        = {Principaux Indicateurs des Rentes des Accidents de la Circulation | Africa (Morocco official open data)},
  author       = {Caisse Nationale de Retraites et d’Assurances},
  year         = {2024},
  url          = {https://data.gov.ma/data/dataset/principaux-indicateurs-des-rentes-des-accidents-de-la-circulation},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-morocco-principaux-indicateurs-des-rentes-des-accidents-de-la-circ-8c16703a}}
}
```

## License

Released under [Open Data Commons Open Database License](https://opendatacommons.org/licenses/odbl/).

Original data (c) Caisse Nationale de Retraites et d’Assurances. 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.gov.ma/data/fr/dataset/a4069fd1-ee3d-41d3-a928-8a55299c0e37/resource/6a58473c-aeb3-4207-a73d-7ca0b1631054/download/principaux-indicateurs-des-rentes-des-accidents-de-la-circulation.xlsx