---
license: odbl
language:
- en
task_categories:
- tabular-classification
- tabular-regression
multilinguality: multilingual
size_categories:
- n<1K
tags:
- "tabular"
- "africa"
- "open-data"
- "official-statistics"
- "morocco"
- "mj"
- "morocco-open-data"
- "justice"
- "cours-appel"
- "section-civile"
- "section-criminelle"
- "activite"
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-00000-of-00001.parquet
pretty_name: "Activite Detaillee Des Cours D Appel | Africa (Morocco Open Data)"
---

# Activite Detaillee Des Cours D Appel | Africa (Morocco Open Data)

**4 rows** - **1 Africa country/area** - **time not specified** - **source table** - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*

![rows](https://img.shields.io/badge/rows-4-blue)
![countries](https://img.shields.io/badge/countries-1-green)
![period](https://img.shields.io/badge/period-time%20not%20specified-orange)
![indicators](https://img.shields.io/badge/indicators-0-purple)
![license](https://img.shields.io/badge/license-odbl-lightgrey)

## TL;DR

This dataset contains **4 rows** from **Morocco Open Data**, covering **Activite Detaillee Des Cours D Appel**. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

## What This Dataset Measures

Official statistics datasets help analysts inspect public data as published by governments, national statistical systems, and regional data portals.

Source-provided context: Ce fichier présente l'activité détaillée des Cours d'appel (section civile et criminelle)

## How To Read This Dataset

- **One row means:** one source record from the original tabular resource, with Electric Sheep Africa provenance columns added where available.
- **Primary geography column:** `country_iso3`.
- **Best time column:** `not detected`.
- **Time coverage basis:** not detected.
- **Recommended join keys:** `country_iso3` where available plus source-specific keys.

## Coverage

| Dimension | Value |
|---|---:|
| Rows | 4 |
| Countries/areas | 1 |
| First period | n/a |
| Last period | n/a |
| Indicators | 0 |
| Columns | 27 |
| Source format | XLSX |

## Geographic Coverage

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

| Area | Rows | First year | Last year | Name |
|------|-----:|-----------:|----------:|------|
| `MAR` | 4 | n/a | n/a | `Morocco` |

## Indicators, Variables, Or Resource Contents

- This repo preserves one source tabular resource with its usable columns kept together.

## Schema

| Column | Type | Description | Example |
|--------|------|-------------|---------|
| `source_record_id` | `string` | Stable row identifier assigned during Electric Sheep Africa engineering. | `fbc329b4-f597-473d-a3da-a49a81a90562:dataset:0` |
| `country_iso3` | `string` | ISO3 country or area code. | `MAR` |
| `country_name` | `string` | Country or area name. | `Morocco` |
| `source_sheet` | `string` | Source column from the original resource. | `استئناف` |
| `column_1` | `double` | Source column from the original resource. | `` |
| `column` | `string` | Source column from the original resource. | `النسبة من المسجل` |
| `d_2511` | `double` | Source column from the original resource. | `0.0084397971222006` |
| `d_13310` | `double` | Source column from the original resource. | `0.0447366386684547` |
| `d_2515` | `double` | Source column from the original resource. | `0.0084532416417102` |
| `d_2356` | `double` | Source column from the original resource. | `0.0079188219912005` |
| `d_18224` | `double` | Source column from the original resource. | `0.0612532308860946` |
| `d_20695` | `double` | Source column from the original resource. | `0.0695585828131984` |
| `d_180` | `double` | Source column from the original resource. | `0.0006050033779355` |
| `d_233` | `double` | Source column from the original resource. | `0.0007831432614387` |
| `d_155672` | `double` | Source column from the original resource. | `0.5232338102776629` |
| `d_3694` | `double` | Source column from the original resource. | `0.0124160137671879` |
| `d_56353` | `double` | Source column from the original resource. | `0.1894097519822263` |
| `d_21776` | `double` | Source column from the original resource. | `0.073191964210689` |
| `d_297519` | `int64` | Source column from the original resource. | `1` |
| `source_provider` | `string` | Publishing organization. | `MJ` |
| `source_dataset` | `string` | Source dataset or package title. | `Activité détaillée des Cours d'appel` |
| `source_resource` | `string` | Source resource title, table name, or file name. | `النشاط العام لمحاكم الاستئناف مدني-زجري سنة 2023.xlsx` |
| `source_package_id` | `string` | Source package identifier. | `733fb4a9-af59-45ae-8a8e-c9370645fb07` |
| `source_resource_id` | `string` | Source resource identifier. | `fbc329b4-f597-473d-a3da-a49a81a90562` |
| `source_url` | `string` | Original source URL or download URL. | `https://data.gov.ma/data/ar/dataset/733fb4a9-af59-45ae-8a8e-c9370645f...` |
| `license_id` | `string` | Source license identifier. | `odc-odbl` |
| `retrieved_at` | `string` | UTC source retrieval timestamp from the Electric Sheep Africa pipeline. | `2026-07-16T21:31:48Z` |

## Usage

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-morocco-activite-detaillee-des-cours-d-appel-9150ef0f")
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"] == "MAR"]
```

### 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

- No canonical year/date column was detected in the packaged table; use source metadata and domain context for temporal interpretation.
- 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:** [Morocco Open Data](https://data.gov.ma/data/dataset/activite-detaillee-des-cours-d-appel-en-2023)
- **Publisher:** MJ
- **Portal:** [https://data.gov.ma/data](https://data.gov.ma/data)
- **Resource:** [النشاط العام لمحاكم الاستئناف مدني-زجري سنة 2023.xlsx](https://data.gov.ma/data/ar/dataset/733fb4a9-af59-45ae-8a8e-c9370645fb07/resource/fbc329b4-f597-473d-a3da-a49a81a90562/download/-2023.xlsx)
- **License:** [Open Data Commons Open Database License](https://opendatacommons.org/licenses/odbl/)
- **Retrieved/generated:** `2026-07-16T21:33:11Z`
- **Hugging Face repo:** [electricsheepafrica/africa-morocco-activite-detaillee-des-cours-d-appel-9150ef0f](https://huggingface.co/datasets/electricsheepafrica/africa-morocco-activite-detaillee-des-cours-d-appel-9150ef0f)

## 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

- Profile the distribution of values
- Compare categories or geographies
- Join with complementary public datasets
- Check missingness before modeling
- Use `country_iso3` as the safest geography join key when present

## Citation

```bibtex
@misc{electric_sheep_africa_africa_morocco_activite_detaillee_des_cours_d_appel_9150ef0f_2026,
  title        = {Activite Detaillee Des Cours D Appel | Africa (Morocco Open Data)},
  author       = {MJ},
  year         = {2026},
  url          = {https://data.gov.ma/data/dataset/activite-detaillee-des-cours-d-appel-en-2023},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-morocco-activite-detaillee-des-cours-d-appel-9150ef0f}}
}
```

## License

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

Original data is published by MJ. 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.gov.ma/data/dataset/activite-detaillee-des-cours-d-appel-en-2023