This analysis explores a daily bike rental dataset using R, focusing on understanding usage patterns over time. The report includes data cleaning, summary statistics, visualizations of total, casual, and registered user counts, and application of smoothing techniques like rolling averages to highlight trends. The workflow provides a foundation for further time series modeling and forecasting.