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Bikeshare Challenge

Overview

Bikeshare data from CitiBike's program in New York City was analyzed to help inform decisions on a potential program in Des Moines, Iowa. The data analyzed was from August 2019, during the busy summer months. A number of different variables were analyzed including trip duration, pickup and dropoff locations and times, as well as customer data like customer type, gender and age.

Results

Starting Locations

Bike pickup locations were plotted by number of bikes. While pickup spots are across the boroughs, the most popular spots are in Midtown and Lower Manhattan.

Starting Locations

Ending Locations

Dropoff locations are also spread across the city with the most popular again being in Midtown and Lower Manhattan.

Ending Locations

Trip Duration

Trip durations were graphed by frequency with shorter rides being most prevalent.

Trip Duration

Trip Duration by Gender

Looking at trip duration by Gender reveals the majority of riders identify as male with the majority of riders taking short trips regardless of Gender.

Trip Duration by Gender

Trips by Hour by Weekday and Hour

Looking at a heat map of bike pickup times by hour and day of the week a couple of trends emerge:

  • The busiest pickup times during the week are during the morning commute (6-9am) and evening commute (5-6pm).
  • The weekends were also busy with the highest volume during the daylight hours (8am-7pm) and Saturday being slightly busier than Sunday.

Trips by Weekday

Trips by Hour/Weekday/Gender

Similar trends are apparent when looking at the heat map broken out by Gender.

Trips by Hour and Gender

Trips by Weekday and Gender

Number of trips broken out by weekday and customer type indicate that Male Subscribers are the most frequent users with Thursday having the most riders. Non-subscriber ridership is fairly consistent without a lot of fluctuations between day of the week.

Trips by Weekday and Gender

Summary

General

Looking at the historical NYC rideshare data from August 2009 gives insight into the business model and the feasibility of creating a similar program in Des Moines. High volume pickup locations, times of day, and days of the week were identified. Customer behavior trends by type and gender help to further understand the ridership in NYC.

Additional Questions

Des Moines, Iowas and New York City are very different markets and the following questions should be asked:

  • How does the potential ridership pool differ between New York City and Des Moines?
  • How many tourists does Des Moines have compared to NYC?
  • Population density of NYC vs. Des Moines?

Recommended additional analysis of NYC data

Further analysis of the Citibike data is recommended:

  • Ridership data over an entire year concentrating on how ridership fluctuates by month.
  • Compare ridership volume with NYC weather conditions to gauge the effect of weather on ridership levels.

This analysis was built using Tableau Public.

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NYC Bikeshare data analysis and visualization utilizing Tableau and Python

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