Bikeshare Stats Insights (Practice)

In this project, I explore US bikeshare data for Chicago, New York City, and Washington. Using Python, Pandas, and NumPy, I load and filter data based on user input for city, month, and day. I calculate and display various statistics including the most frequent travel times, most popular stations, trip durations, and user demographics. The project also involves creating a user interface to view raw data and restarting the analysis as needed. This project was the final step to obtain the FWD professional data analyst certificate.