Ford GoBike System Data Exploration and explanatory

Conducted an end-to-end exploratory data analysis project on Ford GoBike trip data using Python, Pandas, Matplotlib, and Seaborn. The work involved data cleaning, feature engineering, outlier handling, and analyzing trip duration patterns by user type, age, hour, and day of the week. The findings were then transformed into a clear presentation that highlighted key behavioral differences between Subscribers and Customers, showing commuter versus casual riding patterns through well-designed visualizations and data-driven insights.