This project analyzes a year of public ride-share data from a fictional company, Cyclistics, to identify key behavioral differences between casual and annual members. The goal was to provide actionable recommendations to help the company convert more casual users into loyal members.
- Casual riders preferred weekends and shorter trips.
- Members used the service more consistently during weekdays.
- High-activity stations in downtown areas showed higher conversion potential.
- Excel: Data cleaning and organization
- R (tidyverse): Data exploration and analysis
- Tableau: Dashboard creation and visual storytelling
Cyclistics_Cleaned.xlsx: The cleaned dataset used for analysis.Cyclistics_Report.pdf: Final report with findings and recommendations.dashboard_tableau.png: Screenshot of the dashboard built in Tableau.
Joshua Valdez
LinkedIn