The dataset used for this project includes information about individual rides made in a bike-sharing system covering the greater San Francisco Bay area. The dataset can be downloaded here with more details available here here

In the exploration, i discovered that there isn't any strong correlation between trip duration and other variables in the dataset. I found a rather surprising result with more female members in total compared to me after i computed and plot the frequency of the gender and the average trip duration among them. It is wothy of note that there does not exists a bike share for all trip option for customerss with all values being no. The subscriber on the other hand sees a higher number of male and female bike share for all trip.

For the analysis, i focused mainly on the features that have a huge influence on the duration of trips. Afterwards, i plotted the distribution of the duration and proceeded to plot a log scalled version of the same distribution.

Subsequently, I examined the frequency of the main features under investigation including birth year, gender, type, etc. I incorporated different charts (violin, boxplots, scatter, grouped bar, scatter) to try and explore the data and present its findings.