The purpose of this analysis was to provide a group of shareholders an analysis of New York City ridesharing data so that they can provide a thorough proposal to investors for a bike sharing program in Des Moines, Iowa. Tableau was used to create several visualizations of a very large dataset of bike share data that includes trip location, trip duration, and rider type and gender. A story was created in Tableau that includes each of the visualizations. The story can be viewed by clicking the following link.
Also, the visualizations can be seen in the images in the Results section below.
Please see the visualizations and their explanations below.
This visualization shows that the vast majority of bikes were checked out for relatively short periods of time, less than 10 minutes, with the peak around 6 mins.
This visualization shows the same but that the vast majority of bikes checked out were by males.
This pie chart confirms that the vast majority of bike share users are male.
This heat map shows that the majority of trips are taken during peak commute hours, to and from work, 6-9 am and 4-7 pm.
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This heat map confirms this trend, but also by gender, reiterating that males are responsible for most trips and that they occur at peak commute times.
This heat map shows similar information but by weekday and includes whether the bike share riders are customers or subscribers. Subscribers are responsible for most of the trips and they occur Monday/Tuesday and Thursday/Friday.
This bubble chart shows the end locations of each of the bike share trips. This is important if one also knows the land use, zoning, and demographics of the people living and working in this area of New York City. Similar analyses can be performed for Des Moines.
It is evident in the visualizations above that bike sharing is very much linked to work commutes, especially short commutes and for males. Assuming Des Moines has a bustling downtown area that includes sufficient employment opportunities and residential areas near such employment, the city could definitely benefit from a bike sharing program. Additional analyses that should be completed involve Des Moines specifically. An analysis of the land use and zoning of Des Moines and an analysis of the demographics of the city of Des Moines would be beneficial. The program would benefit from knowing where employment opportunities are and where people are living. It would also help to see a gender breakdown of this data. This same analysis would allow shareholders and investors to understand not only the feasibility of such a program but also aid in its implementation.