my data set describe the details of every trip including duration, trip start time and end time, start station detaails such as id, name, latitude, longitude, with the same for the end station also bike id is provided along with user type if it is subscriber = member or customer = guest and then a detailed information about the user its gender and birth.
after visualizing we observe that number of subscribers are way more than that of the customers in other way the time spent by customers more than subscribers. i observed that the duration is in its most in the 8th of february with a duration about 50 mins for subscribers wheras its peak on 11th and 19th of the month for customers with 180 mins and 150 mins.yes user type strengthens the customer side.
wherever the number of subscribers are more than customers but customers are leading with respect to duration and days of the months. I did some data wrangling and converted the duration to minutes and hours to investegate the data more clear and extracted the day from the data in a single column to explore its data. in the duratuion graph there was a very large outlier so i excluded the data greater than 3 hours to make sure to study the graph in a clearer way.