This project is part of the Google Data Analytics Professional Certificate.
To analyze the Cyclistic bike-share dataset and provide actionable insights to help convert casual riders into annual members.
- R & RStudio for data cleaning, wrangling, and analysis
- R Markdown for documentation and reporting
- Tableau Public for interactive data visualization
cyclistic_case_study.Rmd— R Markdown analysis scriptcyclistic_case_study.html— Rendered report from R Markdown
🔗 Click here to view the full HTML report
🔗 View the interactive dashboard on Tableau Public
- Casual riders consistently took longer rides than annual members, even during the winter months of January through March. This suggests many casual riders may be using the service for leisure or tourism rather than commuting.
- The top end stations for casual riders were heavily concentrated near Chicago's lakeshore, indicating popular recreational areas.
- In contrast, annual members primarily ended their rides within the Loop, aligning with patterns typical of local commuters.
- These trends support the idea that casual riders are more likely tourists or recreational users, while annual members are typically local, routine commuters.
- To support the business goal of converting casual riders into annual members, it's recommended to:
- Conduct further analysis on Q2 data (warmer months) to better identify local casual riders who may be open to membership.
- Target marketing efforts:including print and social media, near high-traffic lakeshore stations to attract potential converts among recreational riders.
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