electricsheepafrica/africa-egypt-capmas-licensed-vehicles-25bbb787

Licensed Vehicles | Africa (CAPMAS Egypt Open Data)

5,975 rows - 1 Africa country/area - 2010-2023 - 79 indicators - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 5,975 rows from CAPMAS Egypt Open Data, covering Licensed Vehicles. 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.

This dataset covers Licensed Vehicles 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

Dimension	Value
Rows	5,975
Countries/areas	1
First period	2010
Last period	2023
Indicators	79
Columns	12
Source format	PARQUET

Geographic Coverage

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

Area	Rows	First year	Last year	Name
EGY	5,975	2010	2023	Egypt

Indicators, Variables, Or Resource Contents

• 9191 - Percentage of Vehicles by Type of License(Percentage)
• 9193 - Number of vehicles by governorates(Number)
• 9195 - Percentage of Vehicles by Regions(Percentage)
• 9196 - Number of Vehicles by Regions(Number)
• 9194 - Number of vehicles according to the type of license(Number)
• 9200 - Number of vehicles according to the type of license(Number)
• 9197 - Percentage of vehicles according to the type of license(Percentage)
• 9202 - Number of vehicles by regions(Number)
• 9201 - Percentage of Vehicles by Regions(Percentage)
• 9204 - Percentage of Buses by Governorates(Percentage)
• 9207 - Percentage of Buses by Regions(Percentage)
• 9208 - Number of Buses by Regions(Number)
• 9206 - Number of Buses by Type of License(Number)
• 9192 - Percentage of Vehicles by Governorates(Percentage)
• 9209 - Percentage of Transport Vehicles and Trailers by Type of License(Percentage)
• 9212 - Number of transport vehicles and trailers by regions(Number)
• 9213 - Percentage of Transport Vehicles and Trailers by Regions(Percentage)
• 9210 - Percentage of Transport Vehicles and Trailers by Governorates(Percentage)
• 9198 - Percentage of Vehicles by Governorates(Percentage)
• 9199 - Number of vehicles by governorates(Number)
• ... 59 more indicators

Schema

Column	Type	Description	Example
filter_id	string	Source column from the original resource.	1077
filter_ar	string	Source column from the original resource.	خاص
filter_en	string	Source column from the original resource.	Private
value	double	Numeric observation value.	50.1
year	int64	Observation year.	2013
quarter	null	Source column from the original resource.	``
month	null	Source column from the original resource.	``
indicator_id	string	Stable source or Electric Sheep Africa indicator identifier.	9191
indicator_name	string	Human-readable indicator name.	Percentage of Vehicles by Type of License
indicator_name_ar	string	Source column from the original resource.	نسبة المركبات طبقا لنوع الترخيص
unit	string	Measurement unit, when supplied by the source.	Percentage
periodicity	string	Source column from the original resource.	Annually

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-egypt-capmas-licensed-vehicles-25bbb787")
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: Licensed Vehicles
• License: Source-specific or other license
• Retrieved/generated: 2026-08-08T13:11:17Z
• Hugging Face repo: electricsheepafrica/africa-egypt-capmas-licensed-vehicles-25bbb787

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
• 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_licensed_vehicles_25bbb787_2023,
  title        = {Licensed Vehicles | 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-licensed-vehicles-25bbb787}}
}

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.

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Provenance: README standardized 2026-08-11 by the Electric Sheep Africa README system. Source URL: https://www.capmas.gov.eg