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
Recommended Citation
Krasniqi, Ensar; Osmani, Shkurte Luma; Idrizi, Florim; and Memeti, Ermira, "Exploring Patterns and Growth in Motor Vehicle Registrations Through Data Visualization" (2025). UBT International Conference. 38.
https://knowledgecenter.ubt-uni.net/conference/2025UBTIC/CS/38
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.
