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This analysis portrays a variety of visualizations that summarize the NYC Citibike data in August of 2019. The goal was to create a business proposal for the Des Moines area.

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Bike_Sharing

The objective of this analysis is to analyze the Citibike NYC data throughout August 2019 and put together a business proposal for the Des Moines, Iowa area. The question is: Should Des Moines adopt a city bike program?

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Resources:

Overview:

I created an analysis using Tableau to help investors visualize the potential for a bike-sharing program in Des Moines. My bike trip analysis provides the following:

  • The length of time that bikes are checked out for all riders and genders.
  • The number of bike trips for all riders and genders for each hour of each day of the week.
  • The number of bike trips for each type of user and gender for each day of the week.

I also included a dashboard that contains the basic information necessary to understand these visualizations. Those visualizations include:

  • Number of trips.
  • Customer type.
  • August peak hours and a suggestion for bike repair times.
  • Gender breakdown.
  • Top starting ride locations (filtered by popularity)

Screen Shot 2022-08-09 at 5 36 46 PM

Findings:

The visualization below describes the length of time that bikes are checked out for all users.

As you can see from both visualizations, most users checked bikes out for 20 minutes and males held the majority compared to females and unknown.

Screen Shot 2022-08-09 at 5 38 07 PM

The visualization below describes the length of time that bikes are checked out by gender.

Screen Shot 2022-08-09 at 5 38 43 PM

The visualization below describes the number of bike trips for each type of user and gender for each day of the week.

As you can see, the most popular users are male subscribers.

Screen Shot 2022-08-09 at 5 42 47 PM

The visualization below describes the number of bike trips for each gender by hour.

As you can see, the most active gender is males during the time frame of 8AM (Monday-Friday) as well as 5PM-6PM (Monday-Friday).

Screen Shot 2022-08-09 at 5 50 50 PM

Summary:

City bike programs are popular, especially in dense urban areas such as NYC. Male subscribers dominate the user variety; more research should be done to better understand why. It would be smart to target more female users through advertising, doing so would help increase profits and popularity through new customer support. More analyses can be found through my Tableau link. I include all parts of the data file using a variety of different visualizations.

Des Moines: Additional research

After analyzing the NYC Citibike data, I think it would be beneficial for the city to adopt a city bike program. Another visualization that could be beneficial to include in the business proposal could be to analyze the amount of vehicle traffic and try to determine the pros for users if they were to switch to a city bike alternative. Also, it would be interesting to try and visualize the positive environmental impacts that city bikes have on a specific city. If people were interested in a city bike program and chose to bike as an alternative to vehicles, the impact could positively affect the area.

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This analysis portrays a variety of visualizations that summarize the NYC Citibike data in August of 2019. The goal was to create a business proposal for the Des Moines area.

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