I have used data visualization libraries with Python to explore and understand the dataset of Fordgobike system.
The main area of interest was the factors influencing the bike ride time.
This dataset holds 5054 bikes with 1,863,721 rows and 14 features after combining 12 months datasets into a annual one. After data wrangling, there are 8 columns left with dropping unecessary features.
In the data exploration, I find majority of bike trips last just under 10 minutes, even though there are trip duration up to 300 minutes and more. I also find there was consistent minimum of bike trips throughout the year. Moreover, June and July had the longest ride timeNovember, and December had shortest ride time. When adding the user type variable I find most Customers choose short ride through the year, but subscribers prefer to have a middle and long trip through the year.