Hugging Face's logo

Datasets:
electricsheepafrica
/
africa-morocco-activite-detaillee-des-cours-d-appel-en-2022-b656113c

Tasks:
Tabular Regression
Time Series Forecasting
Modalities:
Tabular
Text
Formats:
parquet
Languages:
English
Size:
< 1K
Tags:
tabular
africa
open-data
official-statistics
morocco
mj
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
xet
 Community
africa-morocco-activite-detaillee-des-cours-d-appel-en-2022-b656113c
File size: 21,013 Bytes
c778113
 
 
 
 
 
 
d0add8d
c778113
 
 
d0add8d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c778113
 
d0add8d
c778113
d0add8d
c778113
 
 
d0add8d
 
c778113
 
 
 
d0add8d
c778113
d0add8d
c778113
d0add8d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c778113
d0add8d
c778113
d0add8d
c778113
d0add8d
 
 
c778113
d0add8d
c778113
d0add8d
c778113
 
 
 
 
d0add8d
c778113
d0add8d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c778113
 
 
 
 
 
 
 
 
 
 
d0add8d
c778113
 
d0add8d
 
c778113
 
d0add8d
c778113
 
d0add8d
 
c778113
 
d0add8d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c778113
 
 
 
d0add8d
c778113
 
 
d0add8d
c778113
 
 
 
 
 
 
 
d0add8d
 
 
c778113
d0add8d
c778113
d0add8d
c778113
 
 
d0add8d
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
---
license: odbl
language:
- en
task_categories:
- tabular-regression
- time-series-forecasting
multilinguality: multilingual
size_categories:
- n<1K
tags:
- "tabular"
- "africa"
- "open-data"
- "official-statistics"
- "morocco"
- "mj"
- "morocco-open-data"
- "justice"
- "cours-appel"
- "tribunaux"
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-00000-of-00001.parquet
pretty_name: "Activite Detaillee Des Cours D Appel En 2022 | Africa (Morocco Open Data)"
---

# Activite Detaillee Des Cours D Appel En 2022 | Africa (Morocco Open Data)

**88 rows** - **1 Africa country/area** - **1946-1990** - **1 indicator** - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*

![rows](https://img.shields.io/badge/rows-88-blue)
![countries](https://img.shields.io/badge/countries-1-green)
![period](https://img.shields.io/badge/period-1946--1990-orange)
![indicators](https://img.shields.io/badge/indicators-1-purple)
![license](https://img.shields.io/badge/license-odbl-lightgrey)

## TL;DR

This dataset contains **88 rows** from **Morocco Open Data**, covering **Activite Detaillee Des Cours D Appel En 2022**. 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 en 2022

## 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 | 88 |
| Countries/areas | 1 |
| First period | 1946 |
| Last period | 1990 |
| Indicators | 1 |
| Columns | 147 |
| Source format | XLSX |

## Geographic Coverage

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

| Area | Rows | First year | Last year | Name |
|------|-----:|-----------:|----------:|------|
| `<NA>` | 88 | 1946 | 1990 | `Morocco` |

## Indicators, Variables, Or Resource Contents

- `source-indicator` - Activite Detaillee Des Cours D Appel En 2022(source_units_unspecified)

## Schema

| Column | Type | Description | Example |
|--------|------|-------------|---------|
| `indicator_id` | `string` | Stable source or Electric Sheep Africa indicator identifier. | `` |
| `indicator_name` | `string` | Human-readable indicator name. | `` |
| `country_iso3` | `string` | ISO3 country or area code. | `` |
| `source_sheet` | `string` | Source column from the original resource. | `الاستئناف بتفصيل2022` |
| `country_name` | `string` | Country or area name. | `` |
| `year` | `int64` | Observation year. | `1952` |
| `value` | `double` | Numeric observation value. | `316.0` |
| `unit` | `string` | Measurement unit, when supplied by the source. | `source_units_unspecified` |
| `dimension_column` | `string` | Source dimension retained during long-form normalization. | `محكمة الاستئناف بالرباط` |
| `dimension_d_349` | `string` | Source dimension retained during long-form normalization. | `302` |
| `dimension_d_2125` | `string` | Source dimension retained during long-form normalization. | `3147` |
| `dimension_d_342` | `string` | Source dimension retained during long-form normalization. | `314` |
| `dimension_d_373` | `string` | Source dimension retained during long-form normalization. | `1136` |
| `dimension_d_429` | `string` | Source dimension retained during long-form normalization. | `278` |
| `dimension_d_3` | `string` | Source dimension retained during long-form normalization. | `55` |
| `dimension_d_980` | `string` | Source dimension retained during long-form normalization. | `2441` |
| `dimension_d_1448` | `string` | Source dimension retained during long-form normalization. | `882` |
| `dimension_d_64` | `string` | Source dimension retained during long-form normalization. | `2` |
| `dimension_d_838` | `string` | Source dimension retained during long-form normalization. | `2682` |
| `dimension_d_0` | `string` | Source dimension retained during long-form normalization. | `0` |
| `dimension_d_6951` | `string` | Source dimension retained during long-form normalization. | `11239` |
| `dimension_column_2` | `string` | Source dimension retained during long-form normalization. | `محكمة الاستئناف بالرباط` |
| `dimension_d_2220` | `string` | Source dimension retained during long-form normalization. | `972` |
| `dimension_d_7536` | `string` | Source dimension retained during long-form normalization. | `2227` |
| `dimension_d_500` | `string` | Source dimension retained during long-form normalization. | `181` |
| `dimension_d_567` | `string` | Source dimension retained during long-form normalization. | `743` |
| `dimension_d_2050` | `string` | Source dimension retained during long-form normalization. | `259` |
| `dimension_d_145` | `string` | Source dimension retained during long-form normalization. | `193` |
| `dimension_d_2596` | `string` | Source dimension retained during long-form normalization. | `1405` |
| `dimension_d_9873` | `string` | Source dimension retained during long-form normalization. | `1543` |
| `dimension_d_198` | `string` | Source dimension retained during long-form normalization. | `0` |
| `dimension_d_2884` | `string` | Source dimension retained during long-form normalization. | `1782` |
| `dimension_d_0_2` | `string` | Source dimension retained during long-form normalization. | `0` |
| `dimension_d_28569` | `string` | Source dimension retained during long-form normalization. | `9305` |
| `dimension_column_3` | `string` | Source dimension retained during long-form normalization. | `محكمة الاستئناف بالرباط` |
| `dimension_d_2569` | `string` | Source dimension retained during long-form normalization. | `1274` |
| `dimension_d_9661` | `string` | Source dimension retained during long-form normalization. | `5374` |
| `dimension_d_842` | `string` | Source dimension retained during long-form normalization. | `495` |
| `dimension_d_940` | `string` | Source dimension retained during long-form normalization. | `1879` |
| `dimension_d_2479` | `string` | Source dimension retained during long-form normalization. | `537` |
| `dimension_d_148` | `string` | Source dimension retained during long-form normalization. | `248` |
| `dimension_d_3576` | `string` | Source dimension retained during long-form normalization. | `3846` |
| `dimension_d_11321` | `string` | Source dimension retained during long-form normalization. | `2425` |
| `dimension_d_262` | `string` | Source dimension retained during long-form normalization. | `2` |
| `dimension_d_3722` | `string` | Source dimension retained during long-form normalization. | `4464` |
| `dimension_d_0_3` | `string` | Source dimension retained during long-form normalization. | `0` |
| `dimension_d_35520` | `string` | Source dimension retained during long-form normalization. | `20544` |
| `dimension_column_4` | `string` | Source dimension retained during long-form normalization. | `محكمة الاستئناف بالرباط` |
| `dimension_d_2410` | `string` | Source dimension retained during long-form normalization. | `996` |
| `dimension_d_6997` | `string` | Source dimension retained during long-form normalization. | `3081` |
| `dimension_d_494` | `string` | Source dimension retained during long-form normalization. | `297` |
| `dimension_d_460` | `string` | Source dimension retained during long-form normalization. | `1154` |
| `dimension_d_145_2` | `string` | Source dimension retained during long-form normalization. | `243` |
| `dimension_d_2743` | `string` | Source dimension retained during long-form normalization. | `2344` |
| `dimension_d_7925` | `string` | Source dimension retained during long-form normalization. | `1805` |
| `dimension_d_193` | `string` | Source dimension retained during long-form normalization. | `1` |
| `dimension_d_2666` | `string` | Source dimension retained during long-form normalization. | `2880` |
| `dimension_d_0_4` | `string` | Source dimension retained during long-form normalization. | `0` |
| `dimension_d_25985` | `string` | Source dimension retained during long-form normalization. | `13117` |
| `dimension_column_5` | `string` | Source dimension retained during long-form normalization. | `محكمة الاستئناف بالرباط` |
| `dimension_d_159` | `string` | Source dimension retained during long-form normalization. | `278` |
| `dimension_d_2664` | `string` | Source dimension retained during long-form normalization. | `2293` |
| `dimension_d_348` | `string` | Source dimension retained during long-form normalization. | `198` |
| `dimension_d_480` | `string` | Source dimension retained during long-form normalization. | `725` |
| `dimension_d_527` | `string` | Source dimension retained during long-form normalization. | `221` |
| `dimension_d_3_2` | `string` | Source dimension retained during long-form normalization. | `5` |
| `dimension_d_833` | `string` | Source dimension retained during long-form normalization. | `1502` |
| `dimension_d_3396` | `string` | Source dimension retained during long-form normalization. | `620` |
| `dimension_d_69` | `string` | Source dimension retained during long-form normalization. | `1` |
| `dimension_d_1056` | `string` | Source dimension retained during long-form normalization. | `1584` |
| `dimension_d_0_5` | `string` | Source dimension retained during long-form normalization. | `0` |
| `dimension_d_9535` | `string` | Source dimension retained during long-form normalization. | `7427` |
| `dimension_column_6` | `string` | Source dimension retained during long-form normalization. | `محكمة الاستئناف بالرباط` |
| `dimension_d_77` | `string` | Source dimension retained during long-form normalization. | `277` |
| `dimension_d_134` | `string` | Source dimension retained during long-form normalization. | `1916` |
| `dimension_d_82` | `string` | Source dimension retained during long-form normalization. | `177` |
| `dimension_d_129` | `string` | Source dimension retained during long-form normalization. | `48` |
| `dimension_d_956` | `string` | Source dimension retained during long-form normalization. | `1850` |
| `dimension_d_99` | `string` | Source dimension retained during long-form normalization. | `1020` |
| `dimension_d_16` | `string` | Source dimension retained during long-form normalization. | `73` |
| `dimension_d_23` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_1739` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_30` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_88` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_100` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_3473` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_column_7` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_460_2` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_410` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_237` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_3766` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_2467` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_30_2` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_39` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_14901` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_451` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_574` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_2787` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_28068` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_column_8` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_537` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_2080` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_492` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_366` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_4722` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_2566` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_46` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_62` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_16640` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_481` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_662` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_2887` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_31541` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_column_9` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_457` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_253` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_284` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_2732` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_2094` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_22` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_28` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_14265` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_424` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_610` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_2738` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_25862` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_column_10` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_80` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_125` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_239` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_82_2` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_472` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_24` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_34` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_2375` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_57` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_52` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_149` | `string` | Source dimension retained during long-form normalization. | `` |
| `dimension_d_5679` | `string` | Source dimension retained during long-form normalization. | `` |
| `source_provider` | `string` | Publishing organization. | `` |
| `source_dataset` | `string` | Source dataset or package title. | `` |
| `source_resource` | `string` | Source resource title, table name, or file name. | `` |
| `source_package_id` | `string` | Source package identifier. | `` |
| `source_resource_id` | `string` | Source resource identifier. | `` |
| `source_url` | `string` | Original source URL or download URL. | `` |
| `license_id` | `string` | Source license identifier. | `` |
| `retrieved_at` | `string` | UTC source retrieval timestamp from the Electric Sheep Africa pipeline. | `` |

## Usage

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-morocco-activite-detaillee-des-cours-d-appel-en-2022-b656113c")
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

- 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:** [Morocco Open Data](https://data.gov.ma/data/dataset/activite-detaillee-des-cours-d-appel-en-2022)
- **Publisher:** MJ
- **Portal:** [https://data.gov.ma/data](https://data.gov.ma/data)
- **Resource:** [النشاط المفصل لمحاكم الاستئناف.xlsx](https://data.gov.ma/data/ar/dataset/a71932ce-435a-490a-b3e2-ccaaff028118/resource/f38c1707-26cb-451f-aa2d-163a5ecf4574/download/-.xlsx)
- **License:** [Open Data Commons Open Database License](https://opendatacommons.org/licenses/odbl/)
- **Retrieved/generated:** `2026-07-16T22:10:19Z`
- **Hugging Face repo:** [electricsheepafrica/africa-morocco-activite-detaillee-des-cours-d-appel-en-2022-b656113c](https://huggingface.co/datasets/electricsheepafrica/africa-morocco-activite-detaillee-des-cours-d-appel-en-2022-b656113c)

## 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
- 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_morocco_activite_detaillee_des_cours_d_appel_en_2022_b656113c_1990,
  title        = {Activite Detaillee Des Cours D Appel En 2022 | Africa (Morocco Open Data)},
  author       = {MJ},
  year         = {1990},
  url          = {https://data.gov.ma/data/dataset/activite-detaillee-des-cours-d-appel-en-2022},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-morocco-activite-detaillee-des-cours-d-appel-en-2022-b656113c}}
}
```

## 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-2022