This data contains information about ford gobike system data convering Sans Francisco Bay area. There are 183, 412 rides with columns such as duration_sec, bike_id, user_type, member_birth_year, member_gender, bike sharing for all trip et cetera. The data can be found here https://video.udacity-data.com/topher/2020/October/5f91cf38_201902-fordgobike-tripdata/201902-fordgobike-tripdata.csv
There are about 183,412 data sets which includes some Nan values. Data that are Nan are dropped before analysis The youngest rider is 18 years and the oldest rider is 141 years There are more subscribers compared to customers Most riders are in their 20's and 30's Males are the most common riders Only subscribers were involved in bike sharing Customers had the highest duration Males are higher in all user type, there are more males in customer type as well as subscribers type
For the presentation, I focus on just the distribution of ride frequency by gender, relationship between user type and duration and relationship between user type and gender and A clustered bar chart of member age, duration sec and user type. The plots were conducted using the plot, seaborn and barplot function.