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electricsheepafrica/africa-egypt-capmas-industrial-commodities-production-of-the-public-and-public-busin-941913d9

Industrial Commodities Production of the Public and Public Business Sectors | Africa (CAPMAS Egypt Open Data) 333 rows - 1 Africa country/area - 2010-2022 - 2 indicators - Engineered by Electric Sheep Africa TL;DR This dataset contains 333 rows from CAPMAS Egypt Open Data, covering Industrial Commodities Production of the Public and Public Business Sectors. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-egypt-capmas-industrial-commodities-production-of-the-public-and-public-busin-941913d9.

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Dataset Card

Industrial Commodities Production of the Public and Public Business Sectors | Africa (CAPMAS Egypt Open Data)

333 rows - 1 Africa country/area - 2010-2022 - 2 indicators - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

rows countries period indicators license

TL;DR

This dataset contains 333 rows from CAPMAS Egypt Open Data, covering Industrial Commodities Production of the Public and Public Business Sectors. 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.

This dataset covers Industrial Commodities Production of the Public and Public Business Sectors from CAPMAS Egypt Open Data. Use the source and schema sections below to confirm definitions, units, and collection methodology before sensitive analytical use.

How To Read This Dataset

  • —One row means: one indicator observation for one geography, time period, and optional source dimensions.
  • —Primary geography column: source metadata (EGY).
  • —Best time column: year.
  • —Time coverage basis: year.
  • —Recommended join keys: year, indicator_id, plus source-specific dimension columns.

Coverage

DimensionValue
Rows333
Countries/areas1
First period2010
Last period2022
Indicators2
Columns12
Source formatPARQUET

Geographic Coverage

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

AreaRowsFirst yearLast yearName
EGY33320102022Egypt

Indicators, Variables, Or Resource Contents

  • —1983 - Relative distribution of commodities that contribute to the value of industrial production of commodities to the public /public business sector(Percentage)
  • —1954 - Value of Industrial Production of Commodities for Public /Public Business Sector(EGP Thousand)

Schema

ColumnTypeDescriptionExample
filter_idstringSource column from the original resource.3750
filter_arstringSource column from the original resource.ركازات ومعادن
filter_enstringSource column from the original resource.Ores and minerals
valuedoubleNumeric observation value.4.18
yearint64Observation year.2020
quarternullSource column from the original resource.``
monthnullSource column from the original resource.``
indicator_idstringStable source or Electric Sheep Africa indicator identifier.1983
indicator_namestringHuman-readable indicator name.Relative distribution of commodities that contribute to the value of ...
indicator_name_arstringSource column from the original resource.التوزيع النسبي للسلع المساهمة في قيمة الانتاج الصناعي السلعي للقطاع ا...
unitstringMeasurement unit, when supplied by the source.Percentage
periodicitystringSource column from the original resource.Annually

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-egypt-capmas-industrial-commodities-production-of-the-public-and-public-busin-941913d9")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

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

Filter By Geography

python
# This dataset is scoped to Egypt in source metadata.
sample = df.copy()

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

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 indicator x period matrices
  • —Check missingness before modeling
  • —Use source or repo metadata for country scope when a geography column is not present

Citation

bibtex
@misc{electric_sheep_africa_africa_egypt_capmas_industrial_commodities_production_of_the_public_and_public_b_2022,
  title        = {Industrial Commodities Production of the Public and Public Business Sectors | Africa (CAPMAS Egypt Open Data)},
  author       = {Central Agency for Public Mobilisation and Statistics (CAPMAS), Egypt},
  year         = {2022},
  url          = {https://www.capmas.gov.eg},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-egypt-capmas-industrial-commodities-production-of-the-public-and-public-busin-941913d9}}
}

License

Released under Source-specific or other license.

Original data is published by Central Agency for Public Mobilisation and Statistics (CAPMAS), Egypt. 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://www.capmas.gov.eg