Overview Purpose This analysis is made to determine whether it is practical to make a bike-share program similar to NYC in Des Moines. This is done by making sure the data is properly formatted using pandas in jupyter notebook, then creating visualizations that showcase the data in a way that provides a clear understanding. Overview Purpose This analysis is made to determine whether it is practical to make a bike-share program similar to NYC in Des Moines.
This is done by making sure the data is properly formatted using pandas in jupyter notebook, then creating visualizations that showcase the data in a way that provides a clear understanding.
Results The link to the Tableau story and all visualizations on Tableau is below.
dashboards
Visualizations There are descriptions provided below each visualization for clarification purposes. ** Visualization 1** visualization1
This first visualization shows that most rides are for a duration of around 5 minutes. Visualization 2 visualization2
The second visualization shows that male riders have the most trips. 5 minutes seems to be the duration that recurs the most regardless of gender. Visualization 3 visualization3
The third visualization shows that trips are usually made around 8am as well as 5-6pm on weekdays(excluding wednesday 5-6). On the weekends, trips seem to be made throughout the afternoon. Visualization 4 visualization4
The fourth visualization shows that a majority of the trips are made by male users at peak times. When looking at the usual ride times, all genders seem to have the same pattern. Visualization 5 visualization5
The fifth visualization shows that most of the trips are made by subscribers, primarily the male subscribers. The male subscribers had the most trips on Thursdays. Visualization 6 visualization6
The sixth visualization shows the popularity of the starting stations. The southwest area of NYC seems to contain some of the most popular starting stations(could be due to tourists). Visualization 7 visualization7
The seventh visualization shows the popularity of the ending stations. The stations seem to be just as popular starting stations as ending stations. The popularity of the stations seems nearly identical in both this and the previous visualization. Summary The majority of rides seem to be male subscribers making their weekday commutes. If a bike-share program is to be created in Des Moines it should be made in a business district, as this would cater to a similar population.
Some other visualizations that can be made would be to find the most common routes and how many people use them(could be filtered by time for further detail) as well as finding the most used bikes so they could be checked for repairs/maintenance.