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electricsheepafrica
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africa-mozambique-inquerito-anual-as-empresas-2011-10a607a3

Tasks:
Tabular Classification
Tabular Regression
Modalities:
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Text
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Formats:
parquet
Languages:
English
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< 1K
Tags:
tabular
africa
open-data
official-statistics
mozambique
instituto-nacional-de-estatistica
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metadata 
license: other
language:
  - en
task_categories:
  - tabular-classification
  - tabular-regression
multilinguality: multilingual
size_categories:
  - n<1K
tags:
  - tabular
  - africa
  - open-data
  - official-statistics
  - mozambique
  - instituto-nacional-de-estatistica
  - transport
  - inquerito-anual-as-empresas
  - questionario-2019-xlsx
  - '2011'
  - survey
  - document
  - questionnaire-doc
  - qst
  - questionarios
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-00000-of-00001.parquet
pretty_name: Inquerito Anual As Empresas 2011 | Africa (INSTITUTO NACIONAL DE ESTATISTICA)

Inquerito Anual As Empresas 2011 | Africa (INSTITUTO NACIONAL DE ESTATISTICA)

345 rows - 1 Africa country/area - 2019 - source table - Engineered by Electric Sheep Africa

rows countries period indicators license

TL;DR

This dataset contains 345 rows from INSTITUTO NACIONAL DE ESTATISTICA, covering Inquerito Anual As Empresas 2011. 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 345
Countries/areas 1
First period 2019
Last period 2019
Indicators 0
Columns 23
Source format XLSX

Geographic Coverage

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

Area Rows First year Last year Name
MOZ 345 2019 2019 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-39-181:2019:0
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 int64 Source column from the original resource. 2019
year int64 Observation year. 2019
nome_do_estabelecimento string Source column from the original resource. ``
no_de_pessoal_ao_servico string Source column from the original resource. Homens
column_3 string Source column from the original resource. Mulheres
nome_da_provincia string Source column from the original resource. ``
column_5 string Source column from the original resource. ``
nome_do_grupo string Source column from the original resource. Se dentro do País
column string Source column from the original resource. ``
source_period_start_year int64 Start year inferred from source metadata. 2019
source_period_end_year int64 End year inferred from source metadata. 2019
source_period_label dictionary<values=string, indices=int8, ordered=0> Source column from the original resource. 2019
source_provider dictionary<values=string, indices=int8, ordered=0> Publishing organization. INSTITUTO NACIONAL DE ESTATISTICA
source_dataset dictionary<values=string, indices=int8, ordered=0> Source dataset or package title. Inquérito Anual As Empresas 2011
source_resource dictionary<values=string, indices=int8, ordered=0> Source resource title, table name, or file name. Inquerito Anual as Empresas
source_package_id dictionary<values=string, indices=int8, ordered=0> Source package identifier. MOZ-IAE2011.V1
source_resource_id dictionary<values=string, indices=int8, ordered=0> Source resource identifier. moz-ine-nada-39-181
source_url dictionary<values=string, indices=int8, ordered=0> Original source URL or download URL. https://mozdata.ine.gov.mz/index.php/catalog/39/download/181
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

Usage 

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-mozambique-inquerito-anual-as-empresas-2011-10a607a3")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns 

print(df.info())
print(df.head())

Filter By Geography 

if "country_iso3" in df.columns:
    sample = df[df["country_iso3"] == "MOZ"]

Time-Series Pattern 

if "value" in df.columns and "year" in df.columns:
    trend = df.sort_values("year")

Pivot For Analysis 

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

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 

@misc{electric_sheep_africa_africa_mozambique_inquerito_anual_as_empresas_2011_10a607a3_2019,
  title        = {Inquerito Anual As Empresas 2011 | Africa (INSTITUTO NACIONAL DE ESTATISTICA)},
  author       = {INSTITUTO NACIONAL DE ESTATISTICA},
  year         = {2019},
  url          = {https://mozdata.ine.gov.mz/index.php/catalog/39/related-materials},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mozambique-inquerito-anual-as-empresas-2011-10a607a3}}
}

License

Released under other-open.

Original data is published by INSTITUTO NACIONAL DE ESTATISTICA. 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/39/related-materials