This project analyzes 12 months of Cyclistic bike-share data to understand differences between annual members and casual riders. Using data cleaning, transformation, and visualization techniques in R, the analysis identifies key patterns in ride frequency, duration, and seasonal trends. Insights from this study inform targeted marketing strategies aimed at converting casual riders into annual members.

© 2026 Ayomide Hannah Igbaroola. All rights reserved. This R script accompanies the research article “Socioeconomic and environmental factors influencing agricultural virtual water trade in Germany” and may be used for learning only.

Nadhif Muhammad Firaas_5003251160_D_Tugas Komstat