--- 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)* ![rows](https://img.shields.io/badge/rows-459-blue) ![countries](https://img.shields.io/badge/countries-1-green) ![period](https://img.shields.io/badge/period-2020-orange) ![indicators](https://img.shields.io/badge/indicators-0-purple) ![license](https://img.shields.io/badge/license-other-lightgrey) ## 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` | ISO3 country or area code. | `MOZ` | | `country_name` | `dictionary` | 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` | Source column from the original resource. | `2020` | | `source_provider` | `dictionary` | Publishing organization. | `DEMOVIS` | | `source_dataset` | `dictionary` | Source dataset or package title. | `Inquerito Crime e Justica 2020` | | `source_resource` | `dictionary` | Source resource title, table name, or file name. | `Verbete - Inquérito Mensal aos Tribunais` | | `source_package_id` | `dictionary` | Source package identifier. | `MZ-JC-2020` | | `source_resource_id` | `dictionary` | Source resource identifier. | `moz-ine-nada-60-338` | | `source_url` | `dictionary` | Original source URL or download URL. | `https://mozdata.ine.gov.mz/index.php/catalog/60/download/338` | | `license_id` | `dictionary` | Source license identifier. | `other-open` | | `retrieved_at` | `dictionary` | 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