Exploring Patterns and Growth in Motor Vehicle Registrations Through Data Visualization

Session

Computer Science and Communication Engineering

Description

This research examines the patterns and trends of motor vehicle registrations in North Macedonia's municipalities between 2012 and 2023. The analysis, which breaks down vehicle types by year, includes motorcycles, passenger cars, buses, and freight vehicles. Every year, the data is arranged into blocks of nine columns, each of which includes comprehensive information for each town. Finding significant insights, such as growth patterns, changes in the popularity of particular vehicle types, and geographical variations, is the aim of this investigation. The project provides a thorough understanding of the evolution of automobile registrations in the nation over time by processing and visualizing data using Python and Jupyter Notebook.

Keywords:

data mining, time series analysis, clustering, vehicle registration, transportation statistics, North Macedonia, Python, Jupyter Notebook

Proceedings Editor

Edmond Hajrizi

ISBN

978-9951-982-41-2

Location

UBT Lipjan, Kosovo

Start Date

25-10-2025 9:00 AM

End Date

26-10-2025 6:00 PM

DOI

10.33107/ubt-ic.2025.106

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Oct 25th, 9:00 AM Oct 26th, 6:00 PM

Exploring Patterns and Growth in Motor Vehicle Registrations Through Data Visualization

UBT Lipjan, Kosovo

This research examines the patterns and trends of motor vehicle registrations in North Macedonia's municipalities between 2012 and 2023. The analysis, which breaks down vehicle types by year, includes motorcycles, passenger cars, buses, and freight vehicles. Every year, the data is arranged into blocks of nine columns, each of which includes comprehensive information for each town. Finding significant insights, such as growth patterns, changes in the popularity of particular vehicle types, and geographical variations, is the aim of this investigation. The project provides a thorough understanding of the evolution of automobile registrations in the nation over time by processing and visualizing data using Python and Jupyter Notebook.