electricsheepafrica/africa-egypt-capmas-storage-for-the-benefit-of-others-in-public-public-business-and-2b1097a0

Storage for the Benefit of Others in Public, Public Business, and Private Sector Establishments | Africa (CAPMAS Egypt Open Data)

7,959 rows - 1 Africa country/area - 2010-2022 - 81 indicators - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

TL;DR

This dataset contains 7,959 rows from CAPMAS Egypt Open Data, covering Storage for the Benefit of Others in Public, Public Business, and Private Sector Establishments. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Demographic datasets help analysts understand population structure, household conditions, migration, gender, age, and settlement patterns.

This dataset covers Storage for the Benefit of Others in Public, Public Business, and Private Sector Establishments 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

Geographic Coverage

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

Indicators, Variables, Or Resource Contents

• —2443 - Total Value of Service Expenses in Warehouses and Storage Facilities(thousand pound)
• —2532 - Total Value of Service Expenses in Refrigerators(thousand pound)
• —7048 - Total Value of Service Expenses in Silos(thousand pound)
• —2487 - Total number of permanent and temporary employees in cold storage facilities(Number)
• —2432 - Total number of permanent and temporary employees in storage facilities and warehouses(Number)
• —2605 - Total number of permanent and temporary employees in silos(Number)
• —2441 - Total value of consumed commodity supplies in stores and warehouses - Other commodity supplies(thousand pound)
• —2447 - Total value of inventory movement of goods owned by establishments in stores and warehouses - beginning of the year(thousand pound)
• —2448 - Total value of inventory movement of goods owned by establishments in stores and warehouses - end of year(thousand pound)
• —2522 - Total value of goods consumed in refrigerators - Other goods supplies(thousand pound)
• —2565 - Total value of inventory movement of goods owned by establishments in refrigerators - end of year(thousand pound)
• —2562 - Total value of inventory movement of goods owned by establishments in refrigerators - beginning of the year(thousand pound)
• —7046 - Total Value of Goods Consumed in Silos - Other Goods Supplies(thousand pound)
• —7055 - Total Value of Inventory Movement of Goods Owned by Facilities in Silos - End of Year(thousand pound)
• —7054 - Total Value of Inventory Movement of Goods Owned by Facilities in Silos - Beginning of the Year(thousand pound)
• —2549 - Total Value of Other Expenses in Refrigerators(thousand pound)
• —2434 - Total number of permanent and temporary workers in storage facilities and warehouses by governorates(Number)
• —2445 - Total Value of Other Expenses in Warehouses and Storage Facilities(thousand pound)
• —7050 - Total Value of Other Expenses in Silos(thousand pound)
• —2438 - Total value of goods consumed in stores and warehouses - electricity(thousand pound)
• —... 61 more indicators

Schema

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-egypt-capmas-storage-for-the-benefit-of-others-in-public-public-business-and-2b1097a0")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

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

Filter By Geography

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

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

• —Source: CAPMAS Egypt Open Data
• —Publisher: Central Agency for Public Mobilisation and Statistics (CAPMAS), Egypt
• —Portal: https://www.capmas.gov.eg
• —Resource: Storage for the Benefit of Others in Public, Public Business, and Private Sector Establishments
• —License: Source-specific or other license
• —Retrieved/generated: 2026-08-08T13:11:55Z
• —Hugging Face repo: electricsheepafrica/africa-egypt-capmas-storage-for-the-benefit-of-others-in-public-public-business-and-2b1097a0

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

• —Build demographic profiles
• —Normalize indicators per capita
• —Join with service-delivery 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

@misc{electric_sheep_africa_africa_egypt_capmas_storage_for_the_benefit_of_others_in_public_public_business_2022,
  title        = {Storage for the Benefit of Others in Public, Public Business, and Private Sector Establishments | 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-storage-for-the-benefit-of-others-in-public-public-business-and-2b1097a0}}
}

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