The dataset consists of information of about 183412 individual rides made in the ford go bike that covers the greater San Francisco Bay area for the month of February of the year 2019. The data was downloaded from the site
During my exploration several findings was observed. I found that most the long trip in terms of duration was taken on Thursday and that Saturday and Sunday had the less travel time because of fatigue due to commuting and working during the week days. I also found out that Male prefer to cycle as means of exercise and commuting than female. The average customer take longer rides than subscribers, subscribers are more likely to use the ford bike for commuting on a daily basis than customers that could be employing the bike for tour purpose only.
My main interest for the presentation was the influence of duration in hours on age, gender of users, the type of users of the go bike and the duration of use. I started by introducing the dataset, then started by plotting on a bar chart the number of trips taken for each day of the week, I use a bar chart because I was only trying to determine the number of rides taken each day and this provided me with the most accurate depiction of the categorical variables, start_day and end_day. I further plotted on an histogram the distribution of genders of users of the ford bike. I used colors to differentiate the various genders on the plot to make distinction between number of users and duration clearer. Lastly, I plotted on a violinplot the distribution of user type and duration covered under 1 hour, this sample size was plotted to get rid of the outlier and to give me a perspective of the general shape and distribution of the data for the different type of users.