File size: 9,901 Bytes
2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd 2549f40 8d34cdd | 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 | ---
license: other
language:
- en
task_categories:
- tabular-classification
- tabular-regression
multilinguality: multilingual
size_categories:
- n<1K
tags:
- "tabular"
- "africa"
- "open-data"
- "official-statistics"
- "mozambique"
- "demovis"
- "transport"
- "verbete-inquerito-mensal-aos-tribunais"
- "novo-verbete-tribunais12052021-xlsx"
- "2020"
- "survey"
- "document"
- "questionnaire-doc"
- "qst"
- "questionarios"
configs:
- config_name: default
data_files:
- split: train
path: data/train-00000-of-00001.parquet
pretty_name: "Inquerito Crime E Justica 2020 | Africa (DEMOVIS)"
---
# Inquerito Crime E Justica 2020 | Africa (DEMOVIS)
**459 rows** - **1 Africa country/area** - **2020** - **source table** - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*





## TL;DR
This dataset contains **459 rows** from **DEMOVIS**, covering **Inquerito Crime E Justica 2020**. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.
## What This Dataset Measures
Transport datasets help analysts examine mobility, infrastructure, passenger movement, logistics, and access to services.
Source-provided context: Document, Questionnaire [doc/qst]
## 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:** `year`.
- **Time coverage basis:** year.
- **Recommended join keys:** `country_iso3` where available plus source-specific keys.
## Coverage
| Dimension | Value |
|---|---:|
| Rows | 459 |
| Countries/areas | 1 |
| First period | 2020 |
| Last period | 2020 |
| Indicators | 0 |
| Columns | 40 |
| Source format | XLSX |
## Geographic Coverage
Top areas shown below, sorted by row count when available:
| Area | Rows | First year | Last year | Name |
|------|-----:|-----------:|----------:|------|
| `MOZ` | 459 | 2020 | 2020 | `Mozambique` |
## 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. | `moz-ine-nada-60-338:tribunais:0` |
| `country_iso3` | `dictionary<values=string, indices=int8, ordered=0>` | ISO3 country or area code. | `MOZ` |
| `country_name` | `dictionary<values=string, indices=int8, ordered=0>` | Country or area name. | `Mozambique` |
| `source_sheet` | `string` | Source column from the original resource. | `Tribunais` |
| `year` | `int64` | Observation year. | `2020` |
| `column_1` | `string` | Source column from the original resource. | `Querela` |
| `reus_presos` | `string` | Source column from the original resource. | `` |
| `column_3` | `string` | Source column from the original resource. | `` |
| `reus_nao_presos` | `string` | Source column from the original resource. | `` |
| `column_5` | `string` | Source column from the original resource. | `` |
| `reus_presos_2` | `string` | Source column from the original resource. | `` |
| `column_7` | `string` | Source column from the original resource. | `` |
| `reus_nao_presos_2` | `string` | Source column from the original resource. | `` |
| `column_9` | `string` | Source column from the original resource. | `` |
| `reus_presos_3` | `string` | Source column from the original resource. | `` |
| `column_11` | `string` | Source column from the original resource. | `` |
| `reus_nao_presos_3` | `string` | Source column from the original resource. | `` |
| `column_13` | `string` | Source column from the original resource. | `` |
| `reus_presos_4` | `string` | Source column from the original resource. | `` |
| `column_15` | `string` | Source column from the original resource. | `` |
| `reus_nao_presos_4` | `string` | Source column from the original resource. | `` |
| `column_17` | `string` | Source column from the original resource. | `` |
| `reus_presos_5` | `string` | Source column from the original resource. | `0` |
| `column_19` | `string` | Source column from the original resource. | `` |
| `column_20` | `string` | Source column from the original resource. | `` |
| `reus_nao_presos_5` | `string` | Source column from the original resource. | `0` |
| `source_period_start_year` | `int64` | Start year inferred from source metadata. | `2020` |
| `source_period_end_year` | `int64` | End year inferred from source metadata. | `2020` |
| `source_period_label` | `dictionary<values=string, indices=int8, ordered=0>` | Source column from the original resource. | `2020` |
| `source_provider` | `dictionary<values=string, indices=int8, ordered=0>` | Publishing organization. | `DEMOVIS` |
| `source_dataset` | `dictionary<values=string, indices=int8, ordered=0>` | Source dataset or package title. | `Inquerito Crime e Justica 2020` |
| `source_resource` | `dictionary<values=string, indices=int8, ordered=0>` | Source resource title, table name, or file name. | `Verbete - Inquérito Mensal aos Tribunais` |
| `source_package_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source package identifier. | `MZ-JC-2020` |
| `source_resource_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source resource identifier. | `moz-ine-nada-60-338` |
| `source_url` | `dictionary<values=string, indices=int8, ordered=0>` | Original source URL or download URL. | `https://mozdata.ine.gov.mz/index.php/catalog/60/download/338` |
| `license_id` | `dictionary<values=string, indices=int8, ordered=0>` | Source license identifier. | `other-open` |
| `retrieved_at` | `dictionary<values=string, indices=int8, ordered=0>` | UTC source retrieval timestamp from the Electric Sheep Africa pipeline. | `2026-08-07T22:10:37Z` |
| `caracteristicas` | `string` | Source column from the original resource. | `` |
| `verbete_vigente` | `string` | Source column from the original resource. | `` |
| `verbete_actualizado` | `string` | Source column from the original resource. | `` |
## Usage
```python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-mozambique-inquerito-crime-e-justica-2020-7acd4028")
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"] == "MOZ"]
```
### 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:** [DEMOVIS](https://mozdata.ine.gov.mz/index.php/catalog/60/related-materials)
- **Publisher:** DEMOVIS
- **Portal:** [https://mozdata.ine.gov.mz](https://mozdata.ine.gov.mz)
- **Resource:** [Verbete - Inquérito Mensal aos Tribunais](https://mozdata.ine.gov.mz/index.php/catalog/60/download/338)
- **License:** other-open
- **Retrieved/generated:** `2026-08-07T22:11:07Z`
- **Hugging Face repo:** [electricsheepafrica/africa-mozambique-inquerito-crime-e-justica-2020-7acd4028](https://huggingface.co/datasets/electricsheepafrica/africa-mozambique-inquerito-crime-e-justica-2020-7acd4028)
## 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 mobility over time
- Compare routes or geographies
- Join with economic and population data
- Build time-series views and period-over-period comparisons
- Check missingness before modeling
- Use `country_iso3` as the safest geography join key when present
## Citation
```bibtex
@misc{electric_sheep_africa_africa_mozambique_inquerito_crime_e_justica_2020_7acd4028_2020,
title = {Inquerito Crime E Justica 2020 | Africa (DEMOVIS)},
author = {DEMOVIS},
year = {2020},
url = {https://mozdata.ine.gov.mz/index.php/catalog/60/related-materials},
publisher = {Hugging Face Datasets, engineered by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mozambique-inquerito-crime-e-justica-2020-7acd4028}}
}
```
## License
Released under other-open.
Original data is published by DEMOVIS. 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://mozdata.ine.gov.mz/index.php/catalog/60/related-materials
|