electricsheepafrica/africa-egypt-capmas-pre-university-education-5f38c44e

Pre-University Education | Africa (CAPMAS Egypt Open Data)

38,298 rows - 1 Africa country/area - 2010-2023 - 492 indicators - Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)

TL;DR

This dataset contains 38,298 rows from CAPMAS Egypt Open Data, covering Pre-University Education. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Education datasets help analysts study access, participation, learning systems, infrastructure, and outcomes across places and periods.

This dataset covers Pre-University Education 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

• —2449 - Percentage of public expenditure on pre-university education to GDP(Percentage)
• —2450 - Total Cost of a Student in Pre-University Education According to Educational Stages(Egyptian Pounds)
• —2452 - Expenditure on Pre-University Education(Million)
• —2454 - Net Enrollment Rate Across Educational Stages(Rate)
• —2453 - Gross Domestic Product (GDP) Value(Million)
• —2455 - Total Enrollment Rate Across Educational Stages(Rate)
• —2458 - Number of students in the agricultural secondary education stage by governorate(Number)
• —2459 - Number of teachers for the agricultural secondary education stage by governorate(Number)
• —2461 - The relative distribution of enrolled students in industrial secondary education according to specialization branches.(Percentage)
• —2460 - Relative distribution of enrolled students in secondary commercial education (General - Hotel) according to specialization branches.(Percentage)
• —2462 - Relative distribution of graduates from industrial secondary education according to specialization fields.(Percentage)
• —2466 - The relative distribution of enrolled students in agricultural secondary education according to specialization branches.(Percentage)
• —2463 - Number of Pre-Primary Al-Azhar Institutes by Governorate(Number)
• —2468 - Number of Agricultural Secondary Schools by Gender(Number)
• —2464 - Number of teachers for pre-primary Al-Azhar stage by governorate(Number)
• —2470 - The relative distribution of enrolled students in technical education according to educational groups.(Percentage)
• —2476 - The relative distribution of students in technical schools in the fields of social sciences, business, and law according to areas of study.(Percentage)
• —2483 - Public expenditure on pre-university education according to the state budget(EGP Thousand)
• —2479 - Relative distribution of enrolled students in secondary commercial education (General - Hotel)(Percentage)
• —2472 - Number of classrooms for pre-primary Al-Azhar education by governorate(Number)
• —... 472 more indicators

Schema

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-egypt-capmas-pre-university-education-5f38c44e")
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: Pre-University Education
• —License: Source-specific or other license
• —Retrieved/generated: 2026-08-08T13:12:43Z
• —Hugging Face repo: electricsheepafrica/africa-egypt-capmas-pre-university-education-5f38c44e

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

• —Compare education indicators by geography
• —Track participation or completion trends
• —Join with population and poverty indicators
• —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_pre_university_education_5f38c44e_2023,
  title        = {Pre-University Education | Africa (CAPMAS Egypt Open Data)},
  author       = {Central Agency for Public Mobilisation and Statistics (CAPMAS), Egypt},
  year         = {2023},
  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-pre-university-education-5f38c44e}}
}

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