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Bikesharing

Overview of the analysis

The purpose of this project is to show investors how the bike-sharing model works in NYC in order to demonstrate that running this model in Des Moines is a strong business proposal.

Results

Checkout times for users

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The majority of users check out between the first twenty minutes. This information tell us that the system would need to invest in high quantity if bikes to cover the demand. On the other hand, it could result in less repairs as trips are short.

Checkout times by Gender

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The difference between males and females is in terms of the number of users, as the trend keeps being very similar to the general one. Males tend to take slightly longer trips.

Trips by Weekday per hour

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During the weekdays, the trend shows us that people use the service to commute to and from work; however after work is when they used it more. Saturday is also the stronger day for bike users during the weekend.

Trips by Gender

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Males are clearly the majority of the system users, having the commute from work as the strongest time. For example, females represent 34% of the males' usage during the busier day, Thursday at 5 PM.

User trips by Gender by Weekday

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Males seem to rely on the system for their transportation as most are subscribers. Most users of the system are subscribers, using it weekdays. Non-subscribers use it more during the weekend.

Gender Breakdown

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Males represent 65,27%, which can mean that although the majority, the usage could be equal not in total users but the percentage of users of each gender using the service.

Average Trip Duration

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The graph is showing us that people born between 1990 and 1995 and upwards are the ones making the longest trips.

link to dashboard

About

Used Tableau to analyze and discover valued information in the bike-sharing system data in NYC.

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